# Appendix D Emissions Preparation and Results

# Appendix D.1 Emissions Inventory Quality Assurance Project Plan

# FUTURE YEAR EMISSION INVENTORY DEVELOPMENT TO SUPPORT ATMOSPHERIC MODELING OF FINE PARTICULATE MATTER AND OZONE IN THE SOUTHEASTERN US



# DRAFT QUALITY ASSURANCE PROJECT PLAN

Effective Date: March 2006

# ASSOCIATION FOR SOUTHEASTERN INTEGRATED PLANNING

ASIP

FUTURE YEAR EMISSION INVENTORY DEVELOPMENT TO SUPPORT ATMOSPHERIC MODELING OF FINE

PARTICULATE MATTER AND OZONE IN THE SOUTHEASTERN US
QUALITY ASSURANCE PROJECT PLAN

Effective Date: March 2006

APPROVED BY

(ASIP Technical Director) (ASIP Emission Inventory Tech. Advisor)

(MACTEC Program Manager (MACTEC Quality Assurance Coordinator)

(MACTEC Task Manager) (MACTEC Task Manager)

# Table of Contents

FUTURE YEAR EMISSION INVENT ORY DEVELOPMENT TO SUPPORT ATMOSPHERIC MODELING OF FINE PARTICULATE MATTER AND OZONE IN THE SOUTHEASTERN US QA PROJECT PLAN

1.0 PROJECT MANAGEMENT ......................................................................................... 1
1.1 Problem Definition/Background................................................................................. 1 1.2 Project/Task Description ............................................................................................. 2 1.3 Project Organization.................................................................................................... 3 1.4 Quality Objectives and Criteria.................................................................................. 6 1.5 Special Training/Certification..................................................................................... 6 1.6 Documents and Records .............................................................................................. 6
2.0 DATA ACQUISITION ................................................................................................... 1
2.1 Point Source Procedures.............................................................................................. 1 2.2 Area Source Procedures .............................................................................................. 1
3.0 ASSESSMENT AND OVERSIGHT.............................................................................. 1
3.1 Assessments and Response Actions ............................................................................ 1 3.2 Reports to Management............................................................................................... 1
4.0 DATA VALIDATION AND USABILITY .................................................................... 1
4.1 Accuracy Assessment ................................................................................................... 1 4.2 Completeness Assessment............................................................................................ 1 4.3 Comparability Assessment .......................................................................................... 1 4.4 Representativeness Assessment................................................................................... 1

TABLES AND FIGURES Page
Figure 1. Project Organization Chart.................................................. 1-5 Figure 2. Audit Check Form ............................................................... 3-2
Table 1. Data Quality Objectives, Procedures, and Indicators ........... 1-8

Distribution List: Pat Brewer, ASIP (Technical Director) Greg Stella, Alpine Geophysics, Inc. (ASIP Emission Inventory Technical Advisor) Douglas Toothman, MACTEC (Q uality Assurance Coordinator) William Barnard, MACTEC (Program Manager, Area and Nonroad Source Task Leader) Edward Sabo, MACTEC (Point Source Task Leader) Dan Meszler, MESZLER Engineering Services, Inc. (Mobile Source Task Leader)

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# 1.0 PROJECT MANAGEMENT
1.1 Problem Definition/Background
The Southeastern States Air Resource Managers (SESARM) has been designated by the United States Environmental Protection Agency (EPA) as the entity responsible for coordinating and implementing regional planning for the eight SE SARM states (Alabama, Florida, Kentucky, Georgia, Mississippi, North Carolina, South Ca rolina and Tennessee) plus Virginia, West Virginia, and Tribes. Through a memorandum of understanding, these parties are collaborating in the organization Visibility Improvement State and Tribal Association of the Southeast (VISTAS) on the technical analysis and planning activities that support state implementation plans for regional haze. The participating agencies have concluded that a collaborative regional process is also the most efficient approach for the states to develop the technical analyses supporting attainment demonstrations for the fine particulate matter (PM2.5) and eight-hour ozone standards. Along with the local air regulatory agencies for Jefferson County, AL, Jefferson County, KY, Mecklenberg County, NC, Forsythe County, NC, Knox County, TN, and Shelby County, TN, these agencies have become signatory parties to the collaborative effort called the Association for Southeastern Integrat ed Planning (ASIP). SESARM will coordinate among participating agencies and oversee the performance of the ASIP inventory and modeling tasks in parallel with the VISTAS regional haze project tasks. Emissions inventory efforts include the development of emissions inventories and forecasts to be utilized in ASIP modeling efforts. At least one area in seven states (Alabama, Georgia, North Carolina, Kentucky, Tennessee, Virginia, and West Virginia) has been designated as nonattainment for the PM 2.5 

# . In addition, South Carolina has one three-county area that was designated as unclassifiable. The PM 2.5 

# compliance date is April 2010 unless a state demonstrates that more time is necessary in which case up to five additional years may be granted. State implementation plans (SIPs) will be due in April 2008 and the modeling year for the PM 2.5 

# attainment demonstration will be 2009.
The States of Alabama, Georgia, Kentucky, North Carolina, South Carolina, Tennessee, Virginia, and West Virginia have one or more nonattainment areas for the eight hour ozone standard. Basic nonattainment areas are required to attain the 8-hour ozone standard by June 15, 2009, while moderate nonattainment areas are required to attain by June 15, 2010. This will require states with basic 8-hour ozone nonattainment areas to demonstrate attainment for the year 2008 and moderate areas will require 2009 as the modeling year

The objective of this project is to compile future year emission inventories to support fine particulate matter and ozone modeling efforts in the ASIP region for all source categories. This project has the following overall design specifications:

• 

# Pollutant Coverage - primary and precursor annual and seasonal emissions necessary to accurately model fine particulate matter and ozone, including primary PM2.5 and

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# PM10, ammonia (NH3), oxides of sulfur (SOx), volatile organic compounds (VOCs), oxides of nitrogen (NOx) and carbon monoxide (CO)

• 

# Source Coverage – all source categories except biogenic.

• 

# Geographic Areas – the ASIP states (A labama, Florida, Georgia, Kentucky, Mississippi, North Carolina, South Carolina, Tennessee, Virginia, West Virginia) The inventories created under this contract will be used in creating future year modeling inventories (modeled under other ASIP work tasks) to support chemical transport modeling of fine particulate matter and ozone in the southeastern U.S. and to evaluate potential control strategies for the National Ambient Air Qua lity Standards (NAAQS) for fine particulate and ozone. Two future year inventories will be prepared along with evaluations of various controls for those inventories. In addition, updates of the 2002 base year inventory will be performed under this contract as necessary to develop the projection years. The purpose of this Quality Assurance Project Plan (QAPP) is to outline and guide the process for quality assuring the inventory development to ensure the development of complete, accurate, and consistent emission inventories. The QAPP is consistent with the recommendations in the EPA quality assurance requirements 1 

# and the Emission Inventory Improvement Program’s QA guidance 2 

# . The QAPP includes tasks associated with obtaining State data, merging and augmenting State submittals with available EPA databases, improving the activity data and emission factors for important source categories, obtaining and developing growth and control factors, obtaining State and stakeholder revi ew of the emission inventory, and providing documentation of the maintenance (revisions, updates, corrections) of the inventory.
1.2 Project/Task Description

EPA 3 

# has specified that calendar year 2002 be used as the base year for emission inventories to support planning efforts under the 8-hour ozone, PM2.5, and Regional Haze programs. ASIP has planned an iterative process to use and enhan ce the 2002 base inventory prepared by MATEC for the Visibility Improvement State and Tribal Association of the Southeast (VISTAS) as part of regional haze planning, that incorporates improved information as it becomes available. In addition, work on the PM2.5 and ozone NAAQS calls for continued measures of progress. As a consequence, emissions inventories for 2008 and 2009 will be required to assess such progress.

• 

# A revised 2009 Base G future year inve ntory based off of the 2009 projections developed previously for VISTAS (Base G due May 2006). This inventory will be developed using the final version of th e 2002 VISTAS base year. The revised 2009 inventory is designed to support modeling runs for fine particulate and ozone. It will be created using readily available growth and control information from the Clean Air Interstate Rule (CAIR), the Heavy Duty Diesel Rule (HDD Rule), the DOE’s Annual Energy Outlook 2006, and other EPA rules. In addition, control programs under these rules as well as State Implementation Plans (SIP) will be incorporated. The growth and control factors will be those developed for the VISTAS 2009 regional haze and PM2.5 inventory development effort augmented by updated information from other regional inventory developmen t work and modifications based on State

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# comments. Typical year emissions for electric generating units (EGUs), wildfire and prescribed burning sources will be revised as necessary to incorporate new data. Control programs that are “on-the-books” and “on-the-way” will be incorporated into the estimates. Three control strategy inventories will also be developed for 2009.

• 

# A 2008 Inventory Base G (available Spring/ Summer 2006). This inventory will be created using information developed for th e 2009 inventory with revised growth and control factors to account for a 2008 projection rather than a 2009 projection. The inventory will still include “on-the-books” and “on-the-way” control programs as well as any SIP or other State specific controls. This QAPP focuses on the tasks associated with developing these inventories.
Projection Inventory Activities. The effort includes the following area source activities: 1. Assemble data needed to update the 2009 VISTAS inventory to account for Base G changes to the base year 2002 inventory and any changes to growth or control factors for 2009 based on State/workgroup review. 2. Prepare the 2009 inventory using data received as part of step 1. 3. Assemble data needed to develop the 2008 ASIP inventory. This includes development of growth and control factors for 2008 which are not currently available. 4. Prepare the 2008 ASIP projection inventory using data developed in step 3. 5. Recommend methods for control strategies for 2009. 6. Prepare 2009 control strategy inventories. 7. Revise the 2002 “typical year” inventory for electric generating units (EGUs) with any updated data. 8. Revise the “typical year” inventory for wild and prescribed fires with any updated data. Other Activities. In addition to the above tasks related to projecting emissions, a report detailing the methods used to develop the projections will be prepared.

1.3 Project Organization
Figure 1 and Table 1 identify the individuals and or ganizations participating in the project. Their specific roles and responsibilities include:

• 

# Ms. Pat Brewer, Technical Coordinator, will plan, conduct, and supervise technical and managerial aspects of the project. She will facilitate communications among State/local agencies, MACTEC, and the SESARM Executive Director.

• 

# Mr. Greg Stella, Emission Inventory Technical Advisor, will work with the Technical Coordinator to define the emission inventory development activities needed to support PM2.5 and ozone modeling and planning activities.

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• 

# State/local Agency Coordinators will compile and submit data to MACTEC, participate in QA/QC reviews, and help revise, update, and correct the inventory.

• 

# William Barnard, MACTEC Program Manager, will direct and monitor technical and financial performance throughout the project and will serve as a senior primary contact with ASIP on contract and project management issues. Mr. Barnard will also direct aspects of the projection inventory development related to area and mobile sources. He will plan and conduct the technical aspects of the development of the area and mobile source inventories, supervise daily activities, identify effective QC procedures and make recommendations on needed QC procedures.

• 

# Edward Sabo, MACTEC Point Source Task Leader, will plan and manage all point source activities. He will plan and conduct the technical aspects of the development of the point source inventory, supervise daily activities, identify effective QC procedures and make recommendations on needed QC procedures.

• 

# Dan Meszler, MACTEC Mobile Source Task Leader, will plan and manage all mobile source activities. He will plan and conduct the technical aspects of the development of input files for the MOBILE and NONROAD models and for nonroad sources not covered by the NONROAD model. He will help identify effective QC procedures and make recommendations on needed QC procedures.

• 

# Douglas Toothman, MACTEC QA Coordinator, will help ensure that adequate QA/QC procedures are incorporated into the inventory development process. He will work independent of the inventory development Task Leaders to assist in the conduct of project QA/QC assessments.

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# FIGURE 1 – PROJECT ORGANIZATION CHART ASIP Technical Coordinator Pat Brewer ASIP Emission Inventory Technical Advisor Greg Stella

MACTEC Program Manager

William Barnard MACTEC QA Coordinator Doug Toothman

MACTEC Point Source Manager Edward Sabo MACTEC Area/Mobile Source Manager William Barnard ASIP State/local Coordinators

MACTEC Technical Support Engineers, Scientists, Programmers, Graphic Artists, Editors

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# 1.4 Quality Objectives and Criteria
The goal of the inventory process is to provide the best possible inventory under given resource constraints. Data Quality Objectives (DQO) are statements about the level of acceptable uncertainty or error. Their purpose is to ensure that the final data will be sufficient for the intended use of the inventory. A well-developed and implemented quality assurance program fosters confidence in the inventory and any resu lting regulatory program. It also gives the end user important information about the limitations of the emission estimates in order to avoid misuse of data.
Table 1 summarizes the Data Quality Objectives for the ASIP inventories that will be compiled for this contract. The first column of Table 1 defines four data quality objectives: accuracy, completeness, comparability and representativeness. The second column identifies the procedures that will be used to achieve each objective. The third column identifies Data Quality Indicators (DQI), which are qualitative and quantitative descriptors used in interpreting the degree of acceptability or utility of data.
1.5 Special Training/Certification
All staff performing data review and analysis are air quality professionals and have sufficient education/experience to perform emission estimation calculations and work with emission inventory databases. Most staff have recei ved specific emission inventory training through conferences, workshops, self-study programs, and on-the-job work experiences. There are no specifically mandated training requirements for work performed on this project.

1.6 Documents and Records
QAPP Control. Any changes to this QAPP will be initiated either by the Program Manager, the Task Leaders, or the QA coordinator. Each change will be given a revision number and date in the document control block in the upper corner of th e affected pages. It will be the responsibility of the initiating person to distribute copies of the changed pages to all the persons on the Distribution List and to the appropriate project team members.

Data Collection Records. Clear documentation of the data collected from the State/local agencies, EPA, and other agencies is integral to the quality analysis review. Records will be maintained containing a description of the data received, the name of the person and agency submitting the data, the date of the submission, and other relevant information about the data submission. The following types of data will be collected during this project:

• 

# EPA’s 1999 National Emission Inventory (Version 2 Final)

• 

# State CERR submittals

• 

# State/local agency data submittals in NIF 3.0 format

• 

# Growth factors assembled by EPA

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• 

# EPA’s Final Summary Emission Reports for 2002 with CEM information for electric utilities regulated by the Acid Rain Program

• 

# EPA’s Toxic Release Inventory for 1999/2000 with ammonia emissions data

• 

# Point source surveys for target facilities to obtain missing information

• 

# State/local agency submittals of updated activity data related to fugitive dust sources, primarily paved and unpaved roads, livestock activities and agricultural activity (tilling).

• 

# State agency submittals of information necessary to calculate fire emissions and geographically locate where these fires occurred in 2002.

• 

# State agency submittals of updated activity data for animal operations for use with the Carnegie Mellon University ammonia model.

• 

# State/local agency revisions, updates, corrections in response to various QA/QC checks. These may be provided in a variety of formats depending on the nature of the response.

• 

# Department of Energy fuel efficiency data

• 

# EGAS growth factors

• 

# VMT data

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# TABLE 1 DATA QUALITY OBJECTIVES, PROCEDURES, AND INDICATORS

Data Quality Objective Pro cedures Example Indicators Accuracy - reduce uncertainty in emission estimates where possible, validate that data elements needed for modeling are within accepted parameters, and verify that emission estimates agree with accepted reference values. 1. Identify weaknesses in existing inventories, identify new methods/data to reduce uncertainty, and obtain new activity/emission factor data where available.2. Use EPA’s NIF QA tool and adhoc reports to perform computerized checks of valid codes/data ranges and to identify outliers. 3. Conduct senior technical review

of pollutant totals by facility, source category, state, and region. 4. Compare to other published data. 1. Qualitative assessment of the inventory’s strengths and weaknesses. 2. 100% of stack data and temporal

factors in valid ranges for > 100 tpy sources. 3. 100% of sources have valid

geographic coordinates. 4. 100% correction of significant

outliers. 5. Agreement of ASIP emissions and

EPA CEM data and EPA TRI data. 6. Compare projection emissions to

base year emissions to ensure that values are within expected ranges. Completeness – include all major point sources, include emission estimates for PM2.5 and ammonia, verify that all important areas source categories are included for all counties and all mobile source categories are accounted for. 1. Compare ASIP utility data to EPA CEM data. 2. Compare ASIP point source

ammonia data to EPA TRI data. 3. State/local agencies compare

facility list to their Title V permit lists. 4. Compare small point source

emissions to area source emissions. 5. Compare PM10 and PM2.5

emissions. 6. Plot area source spatial

distributions by source category and county. 1. 100% of all u tilities accounted for in database. 2. 100% of large ammonia sources

in TRI accounted for in database. 3. 100% of Title V sources

accounted for in database 4. Small point sources included as

either small point sources or as

area sources. 5. PM2.5 and ammonia emissions

included in inventory 6. Area source emissions for

important source categories for all counties in region. 7. All mobile sources accounted for. 8. Explanation of any missing data

or sources. Comparability – verify that emission estimates are similar to other peer-reviewed inventories and that any major deviations are explained. 1. Compare emission totals by source category, pollutant, geographic region, and year with previous emission inventories. 1. Explanation for large discrepancies in emissions

Representativeness – use emission estimation methods that reflect local conditions and the time period of interest. 1. Identify where national defaults used instead of local activity data. 2. Identify where emissions were

grown for base year 2002 data were not available. 3. Identify growth factors for

projection years. 1. Explanation for use of national defaults. 2. Determination of representative

values for “typical years” for some sources for projections (i.e., fires, utility emissions).

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# Data Handling Records. Another key element of the QA program is maintaining written documentation of calculations, assumptions, and all other activities associated with incorporating the State/local agency submittals and other data with the projection and base year inventories. Nearly all data being developed and/or compiled will use computerized databases or other electronic files. For many of these databases, we will use blank fields in the database tables to keep track of the source of the data. We will also maintain a log of activities to document how the data described above were incorporated to create the ASIP inventories. The log will include complete descriptions of the data sources used, the procedures used to incorporate the data, the approach used to determine the completeness, and any contacts made with data submitters to resolve questions. A file will be maintained to ensure that the data handling records are retained and easily located.
QA/QC Records. We will perform a variety of quality control reviews of the inventory. For example, we will check stack parameters, source classification codes, and geographic coordinates for point sources that emit at least 100 tons of any pollutant per year. Reports containing the results of these checks will be transmitted to the State/local agencies for investigation and correction. Documentation of each finding will include a description of the action or data reviewed that led to the quality concern and will provide recommendations for corrective actions.

Corrective Action Records. Records of corrective and follow-up actions identified during the quality review process will be maintained. Both the corrective action identified and the results of the actions taken in response will be documented for inclusion in the final report. If no corrective action can be made, we will document the implications on the overall quality of the inventory.

Data Reporting Package. The final data reporting package will contain four elements:

• 

# An emission summary report that describes the emissions inventory by pollutant and source category, summarizes the methods and data used to compile the inventory, assesses the limitations and appropriate uses of the inventory data, and contains any other information pertinent to the inventory;

• 

# A quality assurance summary report that describes the quality assurance efforts completed, summarizes the corrective actions taken, and provides suggestions for further inventory improvement based on the results of the quality assurance process;

• 

# Electronic data files containing the ASIP inventories in NIF 3.0 format; and

• 

# Electronic and paper files containing all original data submittals and all backup documentation will be stored on file at MACTEC for a period of no less than three years.

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# 2.0 DATA ACQUISITION
The projection year ASIP inventories will rely primarily on air emission information from existing databases. The data collection, handling, and management process is described below, along with the associated quality control procedures and methods. The QC system is designed to:

• 

# Provide routine and consistent checks and documentation points in the inventory development process to verify data integrity, correctness, and completeness;

• 

# Identify and reduce errors and omissions;

• 

# Maximize consistency within the inventory preparation and documentation process;

• 

# Facilitate internal and external inventory review processes. The data acquisition process should be viewed as an iterative process. As decisions are made, new questions will surface that require solutions, until the iterations are complete.
2.1 Projection Year Inventory Procedures
For the projection inventories, the following procedures will be used to compile and quality assure the inventory: 1. Use the final version (Base G) of the 2002 VISTAS Base/Typical Year inventory as a starting point. a. Back calculate uncontrolled emissions for 2002 Base/Typical Year inventory to use as starting point for sources that will be grown for the projection inventory. (unclear) 2. Prepare/Obtain Growth and Control files a. Obtain growth factor files from EGAS for use with categories that will be grown with EGAS growth factors; incorporate Annual Energy Outlook 2006 information into EGAS to replace the AEO 2004 data currently embedded in EGAS. b. Obtain control factors for “on-the-book” and “on-the-way” controls as well as any controls for control strategy evaluations. Controls will be obtained from recent EPA rulemakings, proposed rules (e.g., Clean Air Interstate Rule [CAIR]), andState SIPs. For EGUs, control information will be obtained from VISTASsponsored IPM runs, supplemented with state-supplied adjustments as to where future controls will be installed. c. Determine/obtain growth factors for non-EGAS sources (e.g., agricultural crops, fertilizers, etc.). Growth factors for these sources will be calculated from existing projection inventories prepared by EPA (e.g., EPA Ammonia Inventory). Growth factors will be calculated using linear interpolation of projected emissions if the actual year is not available. 3. Project sources using growth and control factors

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# a. For sources to be grown using EGAS gr owth factors, apply growth and control factors. b. For sources not using EGAS growth f actors, apply non-EGAS growth factors. c. Identify and resolve any errors/discrepancies from the use of EGAS growth factors or other growth factor data d. Track comments/concerns received and corrective actions taken 4. Determine emissions for sources requiring “typical” year emission updates. a. These sources include EGUs and fires b. For fires make any modifications needed including incorporating the long-term effects of prescribed burning programs. Update and revise the typical emissions based on changes submitted by State air and forestry personnel and to include future year projections of prescribed burning. c. Update the typical year emission data from EGU sources based on State comments and any revised CEM or IPM data. 5. Develop mobile source emission inventories a. Prepare projected VMT for review by States/stakeholders for onroad mobile

sources. b. Prepare SMOKE ready MOBILE input file s for review by States/stakeholders. MOBILE input files will contain required control programs either “on-the-books” or “on-the-way”. (my understanding is this subtask is not MACTEC’s responsibility) c. Prepare NONROAD model input files for review by States/stakeholders.NONROAD input files will contain required control programs either “on-thebooks” or “on-the-way”. d. Run the NONROAD 2005 model, develop emission summaries and provide to States/Stakeholders for review/comment. e. Develop growth factors and projected emissions for nonroad sources not in the NONROAD model. Growth factors will be based on existing estimates from EPA rulemaking projections (e.g., Heavy Duty Diesel and other rules). Provide growth factors for review by States/Stakeholders. f. Prepare non-NONROAD model emission estimates. Provide for States/Stakeholder review/comment. 6. Conduct QA/QC to identify errors and inconsistencies a. Prepare ad-hoc reports to identify gaps and logical inconsistencies. b. Ask States/local agencies to provide feedback on large scale inconsistencies and on missing sources. c. Update database with State/local supplied revisions. d. Track comments/concerns received and corrective actions taken 7. Provide inventory for review by stakeholders

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# a. Prepare an emission summary report that describes the emissions inventory by pollutant and source category, summarizes the methods and data used to compile the inventory, assesses the limitations and appropriate uses of the inventory data, and contains any other information pertinent to the inventory b. Prepare a quality assurance summary report that describes the quality assurance efforts completed, summarizes the corrective actions taken, and provides suggestions for further inventory improvement based on the results of the quality assurance process c. Provide electronic data files containing the ASIP inventories in NIF 3.0 format d. Track comments/concerns received and corrective actions taken 8. Incorporate feedback from stakeholders a nd prepare final reports and electronic files

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# 3.0 ASSESSMENT AND OVERSIGHT
The subsections in this group address the activities for assessing the effectiveness of project implementation and associated QA and QC activities. The purpose of the assessment is to ensure that the QA Project Plan is implemented as prescribed. The assessment consists of external activities that include a planned system of review and audit procedures by personnel not actively involved in the inventory development process. The key concept of this component is independent objective review by a third party to access the effectiveness of the internal Quality Control program and the quality of the inventory, and to reduce or eliminate any inherent bias in the inventory process.
3.1 Assessments and Response Actions
The MACTEC Quality Assurance Coordinator w ill conduct technical systems audits throughout the project. Audits are managerial tools used to evaluate how effectively the emission inventory team complies with predetermined specifications for developing an accurate and complete inventory. The MACTEC QAC will conduct audits at the initiation of each project to review the Work Plan and QAPP, at the 50% complete and 75% complete levels to review the technical aspects of each project and at the 95% completion level to review the data submittal package. This provides assessment of the project during the planning stage, the data collection stage, the emissions calculations stage, and the report preparation stage. An example audit checklist for point sources is presented in Figure 2.
3.2 Reports to Management
Audit reports will be distributed within two w eeks of the conduct of each audit to the persons interviewed and the MACTEC Task Leaders. A summary of the types of quality concerns found will be periodically forwarded to the MACTEC Pr ogram Manager to keep him informed of the quality issues found and actions being taken to resolve them. Audit reports will be retained in a file and used to conduct subsequent audits and plan follow-up activities. When an audit team finds items that require immediate action, they will inform the MACTEC Program Manager of the necessary corrective actions.

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# AUDIT CHECKLIST

Auditor:

______________________________________ Date:

_________________________________________ Data/Procedure Reviewed:

_____________________________________________________________

___________________________________________________________________________________ Project Personnel Involved in Work:

_____________________________________________________

____________________________________________________________________________________ Instructions: Select a facility or source category with high emissions and evaluate the quality of the data and adequacy of the data handling procedures. R ecord the findings and recommendations for corrective actions, if any, on this checklist and comment sheet. If recommendations for corrective actions are made, discuss them with the Project Manager immediatel y following the audit. Conduct follow-up activities to determine if the actions taken in response to th e recommendations appropriately resolved the quality issues identified.

I. DATA
A. Identify the source category eval uated: _____________________________________________ B. Describe the data included in the master file for the facility or source category.

_____________________________________________________________________________

_____________________________________________________________________________ C. Are the data documented in a manner that will not have the potential to be misinterpreted? Y/N Were the instructions for docu menting the data followed? ................................................. Y/N D. Are there missing data fields? ............................................................................................ ........ Y/N What procedures are taken by the Task Leaders to ascertain missing?

___________________________________________________________________________

___________________________________________________________________________ At what point in the inventory process are requests for missing data made?

___________________________________________________________________________

___________________________________________________________________________ How is the receipt of the missing data handled?

___________________________________________________________________________

___________________________________________________________________________ Is the procedure followed to ascertain mi ssing data efficient and adequate? ............................ Y/N E. How do emissions compare to other inventories? 1999 NEI Versi on 2 Final ________________________________________________________ 2000 TRI _____________________________________________________________________ 2002 ETS/CEM ________________________________________________________________ Are differences in emissions unders tandable and explainable? ................................................. Y/N If any of the values are incorrect, explain how the emissions data were corrected.

___________________________________________________________________________ Figure 2 Audit Check Form

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## II. EMISSIONS DATABASE
A. Who provided the data for inco rporation into th e datab ase? __________________________

_______________________________________________________________________ B. Was there evidence that the data were reviewed for accuracy and completeness prior to incorporation in the database? ............................................................................................ ... Y/N C. Were data logs maintained to descr ibe how the data was incorporated? ................................... Y/N D. Ask the data incorporation personnel to e xplain the QC procedures followed to ensure data quality. Do they agree with th e procedures described in the QAPP? ................................ Y/N E. Does the computer system appear to be adequate for its intended use? (Ask the data processing personnel about the problems they have experienced with the system.) .......... Y/N F. Is the data entry progressing as expected and are the procedures followed adequate to ensure data quality? ...................................................................................................... ......... Y/N

III. RECOMMENDATIONS FOR CORRECTIVE ACTIONS

_________________________________________________________________ ____________________

_________________________________________________________________ ____________________

_________________________________________________________________ ____________________

_________________________________________________________________ ____________________

_________________________________________________________________ ____________________

IV. COMMENTS

_________________________________________________________________ ____________________

_________________________________________________________________ ____________________

_________________________________________________________________ ____________________

_________________________________________________________________ ____________________

_________________________________________________________________ ____________________



# V. SIGNATURES

______________________________ ____________________________ (QA Auditor) (QA Coordinator)

______________________________ ____________________________ (Program Manager) (Task Manager)

______________________________ ____________________________ (Project Participant) (Project Participant)

Figure 2 Audit Check Form (Concluded)

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# 4.0 DATA VALIDATION AND USABILITY
Section 4 addresses the QA activities that occur after the data collection phase of the project is completed. Implementation of these subsections determines whether or not the data conform to the specified criteria, thus satisfying the project objectives.
4.1 Accuracy Assessment
A qualitative discussion of accuracy will include an assessment of the extent to which the initially identified weaknesses in the inventory have been remedied through the use of improved activity data, emission factors, or other sources of information. Remaining weaknesses will be assessed.
The accuracy assessment will include a summary of whether any data identified as outside of its valid range remained outside of the valid range in the final inventory. If any data remained outside of its valid range, an explanation will be given. The qualitative discussion will also include a summary of errors or discrepancies identified in the QA/QC process.
A final semi-quantitative discussion of accuracy will consist of pollutant summaries for individual facilities, industry types, source categorie s, and statewide totals. The ASIP inventory will be compared to other peer-reviewed inventories, and where major discrepancies exist, we will provide an assessment of the reasons for the differences in emission estimates.
4.2 Completeness Assessment
A statement will be prepared assessing whether all required facilities, source categories, pollutants, and data elements were included in the inventory. If any facilities or source categories were not included, an explanation of the omission will be provided. If any individual data elements were not provided, we will discuss the elements, frequency of omissions, and overall impact on the quality of the inventory.
4.3 Comparability Assessment
Several summations of emissions data will be made to address comparability. Overall percentage differences for individual facilities (current year to prior year), industry types, processes, and statewide inventory will be calculated. Explanations of any large differences will be made.
4.4 Representativeness Assessment
A statement will be prepared describing where national defaults have been used instead of local activity data.

## Project: ASIP 2002 Inventory Section: 5 Revision No. 0 Revision Date: 3/17/2006 Page 1 of 1



# 5.0 REFERENCES
1. U.S. Environmental Protection Agency. March 2001. EPA Requirements for Quality Assurance Project Plans (EPA/240/B-01/003). http://www.epa.gov/quality/qs-docs/r5- final.pdf 2. Emission Inventory Improvement Program (EIIP) Document Series - Volume VI Quality Assurance Procedures and DARS Software. EPA | TTN CHIEF | EIIP | Technical Reports | Volume VI Quality Assurance Procedures 3. U.S. Environmental Protection Agency. November 18, 2002. 2002 Base Year Emission Inventory SIP Planning: 8-hr Ozone, PM2.5 and Regional Haze Programs. http://www.4cleanair.org/members/committee/criteria/EPA200211181.pdf

# Appendix D.2 Emissions Inventory Documentation

# Appendix D.2a
Point Source Emissions Inventory Documentation

## Emissions Preparations & Results Appendix D.2a - 1 Regional Haze SIP for NC Class I Areas December 17, 2007

## Emissions Preparations & Results Appendix D.2a - 2 Regional Haze SIP for NC Class I Areas December 17, 2007 

# TABLE OF CONTENTS

1. INTRODUCTION ................................................................................................................ ...... 4

2. 2002 POINT SOURCE INVENTORY DEVELOPMENT ........................................................ 4 2.1 Development of 2002 Actual Point Source Inventory.................................................... 5 2.1.1 Consolidated Emissions Reporting Rule .................................................................... 5 2.1.2 Initial Data Evaluation ................................................................................................ 6 2.1.3 PM Augmentation....................................................................................................... 7 2.1.4 EGU Analysis ............................................................................................................. 9 2.1.5 Emission Inventory QA Review ............................................................................... 11 2.1.6 Summary of the 2002 Actual Inventory.................................................................... 11 2.2 Development of Typical Year EGU Inventory............................................................. 12

3. 2018 POINT SOURCE EMISSIONS INVENTORY DEVELOPMENT................................ 14 3.1 EGU Emission Projections ........................................................................................... 14 3.1.1 Chronology of the Development of EGU Projections .............................................. 15 3.1.2 VISTAS/MRPO IPM runs for EGU sources ............................................................ 16 3.1.3 Post-Processing of IPM Parsed Files ........................................................................ 17 3.1.4 Eliminating Double Counting of EGU Units............................................................ 19 3.1.5 Quality Assurance steps............................................................................................ 20 3.1.6 S/L Adjustments to IPM Modeling Results.............................................................. 21 3.2 Non-EGU Emission Projections ................................................................................... 22 3.2.1 Growth assumptions for non-EGU sources .............................................................. 23 3.2.2 Control Programs applied to non-EGU sources........................................................ 25 3.2.3 Quality Assurance steps............................................................................................ 27
4. Emission Inventory Summaries ................................................................................................ 28 4.1 Summary of EGU Point Source Inventories................................................................. 28 4.2 Summary of non-EGU Point Source Inventories.......................................................... 32

## Emissions Preparations & Results Appendix D.2a - 3 Regional Haze SIP for NC Class I Areas December 17, 2007 

# LIST OF TABLES Table 2.1.3-1. Comparison of North Carolina PM Emissions: CERR versus the 2002 VISTAS Point Source Inventory ......................................................................................................... .. 9 Table 2.1.6-1 2002 Actual Point Source Inventory for North Carolina....................................... 12 Table 2.2-1 NO x 

# Emissions Comparison for EGUs..................................................................... 13 Table 3.1.6-1 NCDAQ Adjustments to IPM Resu lts for the 2009 and 2018 EGU Inventories .. 22 Table 4.1-1 EGU Point Source SO 2 

# Emission Comparison ........................................................ 29 Table 41.7-2 EGU Point Source NO x 

# Emission Comparison...................................................... 29 Table 4.1-3 EGU Point Source VOC Emission Comparison ...................................................... 30 Table 4.1-4 EGU Point Source CO Emission Comparison ......................................................... 30 Table 4.1-5 EGU Point Source PM 10 

# -PRI Emission Comparison............................................... 31 Table 4.1-6 EGU Point Source PM 2.5 

# -PRI Emission Comparison ............................................. 31 Table 4.1-7 EGU Point Source NH 3 

# Emission Comparison........................................................ 32 Table 4.2-1 Non-EGU Point Source SO 2 

# Emission Comparison ................................................ 32 Table 4.2-2 Non-EGU Point Source NO x 

# Emission Comparison................................................ 33 Table 4.2-3 Non-EGU Point Sour ce VOC Emission Comparison .............................................. 33 Table 4.2-4 Non-EGU Point Sour ce CO Emission Comparison ................................................. 34 Table 4.2-5 Non-EGU Point Source PM 10 

# -PRI Emission Comparison....................................... 34 Table 4.2-6 Non-EGU Point Source PM25-PRI Emission Comparison ..................................... 35 Table 4.2-7 Non-EGU Point Source NH 3 

# Emission Comparison................................................ 35

## Emissions Preparations & Results Appendix D.2a - 4 Regional Haze SIP for NC Class I Areas December 17, 2007 

# 1. INTRODUCTION

The regional haze modeling was performed by the Southeast Regional Planning Organization, Visibility Improvement State and Tribal Associa tion of the Southeast (VISTAS) and is run by the ten Southeast states (Alabama, Florida, Georgia, Kentucky, Mississippi, North Carolina, South Carolina, Tennessee, Virginia and West Virginia) and the local programs and tribal agencies located within these states. The regional haze modeling uses annual simulations and includes an intermediate year. VISTAS developed emission estimates for all pollutants of concern for regional haze.



# 2. 2002 POINT SOURCE INVENTORY DEVELOPMENT

This section details the development of the 2002 base year inventory for point sources. There were two major components to the development of the point source sector of the inventory. The first component was the incorporation of data submitted by State and Local (S/L) agencies to the United States Environmental Protection Agency (U SEPA) as part of the Consolidated Emissions Reporting Rule (CERR) requirements. Work on incorporating the CERR data into the revised base year involved: 1) obtaining the data from the USEPA or the S/L agencies, 2) evaluating the emissions and pollutants reported in the CERR submittals, 3) augmenting CERR data with annual emission estimates for primary coarse particulate matter (PM 10 

# -PRI) and primary fine particulate matter (PM 2.5 

# -PRI); 4) evaluating the emissions from electric generating units, 5) completing quality assurance reviews for each component of the point source inventory, and 6) updating the database with corrections or new information from S/L agencies based on their review of the 2002 inventory. The processe s used to perform the emission inventory development are described in the first portion of this section.

The second component was the development of a “t ypical” year inventory for electric generating units (EGUs). The VISTAS states determined th at a typical year EGU inventory was necessary to smooth out any anomalies in emissions from the EGU sector due to meteorology, economic, and outage factors in 2002. The typical year EGU i nventory is intended to represent the five-year (2000-2004) period that will be used to determine the regional baseline and to determine the regional haze reasonable progress goals. The second part of this section discusses the development of the typical year EGU inventory.

## Emissions Preparations & Results Appendix D.2a - 5 Regional Haze SIP for NC Class I Areas December 17, 2007 

# 2.1 Development of 2002 Actual Point Source Inventory

VISTAS/ASIP contracted with MACTEC to de velop the 2002 emission inventory. The North Carolina Division of Air Quality (NCDAQ) submitted the most updated statewide emission inventory to the contractor with the exception of the emissions from the three local programs. For the three local programs, Forsyth, Mecklenburg, and Buncombe Counties, the CERR submittal from the USEPA was used. Once all of the files were obtained, MACTEC ran the files through the USEPA’s National Emissions Inventory (NEI) Input Format (NIF) Basic Format and Content checking tool to ensure that the files were submitted in standard NIF format and that there were no referential integrity issues with the files.

The primary task in preparing the 2002 base year point source inventory was the incorporation of corrections and new information as submitted by the S/L agencies based on their review of the previous draft versions of the inventory. The following subsections document the data sources for the inventory, the checks made on the CERR submittals, the evaluation of EGU emissions, and other quality assurance/quality control (QA/QC) checks. The final subsection summarizes the 2002 point source inventory by sector (EGU and non-EGU).

Throughout the development of the point sour ce emissions inventory, the NCDAQ completed detailed reviews of the inventories prepared by the VISTAS contractor and provided comments and data corrections when needed.

2.1.1 Consolidated Emissions Reporting Rule The CERR was published in the Federal Register on June 10, 2002 (67 Federal Register 39602). This brief summary is provided as a quick introduction to the CERR and covers the major items in the rule.

The purpose of the CERR is to simplify reporting, offer options for data collection and exchange, and unify reporting dates for various categories of criteria pollutant emission inventories. The rule applies to S/L agencies. Previous reporting requirements have, at times, forced reporting agencies into inefficient collecting and reporting activities. This rule consolidates the emission inventory reporting requirements found in va rious parts of the Clean Air Act (CAA). Consolidation of reporting requirements will enable S/L agencies to better explain to program managers and the public the necessity for a consistent inventory program, increases the efficiency of the emission inventory program, a nd provide more consistent and uniform data.

## Emissions Preparations & Results Appendix D.2a - 6 Regional Haze SIP for NC Class I Areas December 17, 2007 

# States are required to prepare a comprehensive statewide inventory every three years. The first inventory was for the year 2002 and was due J une 1, 2004. This CERR inventory was used for the VISTAS 2002 base year.

2.1.2 Initial Data Evaluation MACTEC conducted an initial review of the 2002 point source CERR data. The following evaluations were completed to identify potential data quality issues associated with the CERR data:

• 

# Compared the number of sites in the CERR submittal to the number of sites in the VISTAS draft 2002 inventory; the number of sites in the CERR submittal was less than in the VISTAS draft 2002 inventory, since the CERR data was limited to major sources, while the VISTAS draft 2002 inventory contained data for both major and minor sources; verified with S/L contacts that minor s ources not included in the CERR point source inventory were included in the CERR area source inventory.

• 

# Checked for correct pollutant codes and corrected to make them NIF-compliant.

• 

# Checked for types of particulate matter (PM) codes reported (i.e., PM-FIL, PM-CON, PM-PRI, PM10-PRI, PM10-FIL, PM25-PRI, PM25-FIL); corrected codes with obvious errors (i.e., changed PMPRI to PM-PRI). The PM augmentation process for filling in missing PM pollutants is discussed later in Section 2.1.3.

• 

# Converted all emission values that were not in tons to tons to allow for preparation of emission summaries using consistent units.

• 

# Checked start and end dates in the NIF files to confirm consistency with the 2002 base
year.

• 

# Compared annual and daily emissions when daily emissions were reported; in some cases, the daily value was non-zero (but very small) but the annual value was zero. This was generally the result of rounding in an S/L agency’s submittal.

• 

# Compared ammonia (NH 3 

# ) emissions as reported in the CERR submittals and the 2002 Toxics Release Inventory; worked with S/L agencies to resolve any outstanding discrepancies.

## Emissions Preparations & Results Appendix D.2a - 7 Regional Haze SIP for NC Class I Areas December 17, 2007 • 

# Compared sulfur dioxide (SO 2 

# ) and nitrogen oxides (NOx) emissions for EGUs to the USEPA’s Clean Air Markets Division (CAM D) continuous emission monitoring (CEM) database to identify any outstanding discrepancies. A full discussion of the EGU emissions analysis is discussed later in Section 2.1.4.

• 

# Prepared State-level emission summaries by pollutant for both the EGU and non-EGU sectors to allow S/L agencies to compare emissions as reported in the 1999 NEI Version 2, the VISTAS draft 2002 inventory, and the CERR submittals.

• 

# Prepared facility-level emission summaries by pollutant to allow S/L agencies to review facility level emissions for reasonableness and accuracy.

MACTEC communicated the results of these analyses through email/telephone exchanges with the S/L point source contacts as well as through Excel summary spreadsheets. The VISTAS S/L agencies submitted corrections and updates as necessary to resolve any QA/QC issues from these checks.

2.1.3 PM Augmentation Particulate matter emissions can be reported in many different forms, as follows:

PM Category Description

PM-PRI Primary PM (includes filterable and condensable)

PM-CON Primary PM, condensable portion only (all less than 1 micron)

PM-FIL Primary PM, filterable portion only

PM 10 

# -PRI Primary PM 10 

# (includes filterable and condensable)

PM 10 

# -FIL Primary PM 10 

# , filterable portion only

PM 2.5 

# -PRI Primary PM 2.5 

# (includes filterable and condensable)

PM 2.5 

# -FIL Primary PM 2.5 

# , filterable portion only

North Carolina reports PM-PRI, PM 10 

# -PRI

, 

# and PM 2.5 

# –PRI in the CERR. From any one of these pollutants, the USEPA has developed augmentation procedures to estimate PM10-PRI,

## Emissions Preparations & Results Appendix D.2a - 8 Regional Haze SIP for NC Class I Areas December 17, 2007 

# PM 10 

# -FIL, PM 2.5 

# -PRI, PM 2.5 

# -FIL, and PM-CON. If not included in a S/L inventory, PM 10 

# -PRI and PM 2.5 

# -PRI were calculated by adding PM 10 

# -FIL and PM-CON or PM 2.5 

# -FIL and PM-CON, respectively.

The procedures for augmenting point source PM emissions are documented in detail in the USEPA’s document Documentation for the Final 1999 National Emissions Inventory {Version 3} for Criteria Air Pollutants and Ammonia – Point Sources , January 31, 2004. (http://www.epa.gov/ttn/chief/net/1999inventory.html). Briefly, the PM data augmentation procedure includes the following five steps:

• 

# Step 1: Prepare S/L/Tribal PM and PM 10 

# Emissions for Input to the PM Calculator

• 

# Step 2: Develop and Apply S ource-Specific Conversion Factors

• 

# Step 3: Prepare Factors from PM Calculator

• 

# Step 4: Develop and Apply Algorithms to Es timate Emissions from S/L/Tribal Inventory Data

• 

# Step 5: Review Results and Update the NEI with Emission Estimates and Control Information.

Please refer to the USEPA documentation for a complete description of the PM augmentation procedures.

Table 2.1.3-1compares the original PM emission estimates from the North Carolina CERR submittals and the revised 2002 VISTAS emissions estimates calculated using the above methodology. This table is intended to show th at MACTEC took whatever State/Local provided in the way of PM and filled in gaps to add in PM-CON where emissions were missing in order to calculate PM 10 

# -PRI and PM 2.5 

# -PRI for all processes to get a complete set of particulate data. MACTEC did not compare any other pollutants besides PM, since for other pollutants CERR emissions equal VISTAS emissions

## Emissions Preparations & Results Appendix D.2a - 9 Regional Haze SIP for NC Class I Areas December 17, 2007 

# Table 2.1.3-1. Comparison of North Caro lina PM Emissions: CERR versus the 2002 VISTAS Point Source Inventory

Database PM-PRI PM-FIL PM-CON PM10-PRI PM10-FIL PM2.5-PRI PM2.5-FIL

CERR 48,110 0 0 36,222 0 24,159 0 VISTAS 48,114 41,407 6,708 36,992 30,284 27,512 21,113 Note 1: CERR refers to data as submitted by S/L agencies; VISTAS refers to data calculated by MACTEC using the PM augmentation methodologies described in this document.
Note 2: The emission values in the VISTAS emission rows above differ slightly from the final values in the inventory. This is due to several corrections and updates to the 2002 inventory submitted by S/L agencies after the PM augmentation was performed as discussed in Section 2.1.3.



# After the PM augmentation process was perfor med, MACTEC executed a series of checks to identify potential inconsistencies in the PM inventory. These checks included:

• PM-PRI less than PM 10 

# -PRI, PM 2.5 

# -PRI, PM 10 

# -FIL, PM 2.5 

# -FIL, or PM-CON;

• PM-FIL less than PM 10 

# -FIL or PM 2.5 

# -FIL;

• PM 10 

# -PRI less than PM 2.5 

# -PRI, PM 10 

# -FIL, PM 2.5 

# -FIL or PM-CON;

• PM 10 

# -FIL less than PM 2.5 

# -FIL;

• PM25-PRI less than PM 2.5 

# -FIL or PM-CON;

• The sum of PM 10 

# -FIL and PM-CON not equal to PM 10 

# -PRI; and

• The sum of PM 2.5 

# -FIL and PM-CON not equal to PM 2.5 

# -PRI.

MACTEC asked S/L agencies to review this information and provide corrections where the inconsistencies were significant.

Note that for the inventory, only the PM 10 

# -PRI and PM 2.5 

# -PRI emission estimates were retained since they are the only two PM species that are included in the air quality modeling. Other PM species were removed from the inventory to facilitate emissions modeling.

2.1.4 EGU Analysis MACTEC made a comparison of the annual SO 2 

# and NO x 

# emissions for EGUs as reported in the S/L agencies CERR submittals and the data from the USEPA’s CAMD CEM database to identify any outstanding discrepancies. Facilities report hour ly CEM data to the USEPA for units that are subject to CEM reporting requirements of the NO x 

# SIP Call rule and Title IV of the CAA. The

## Emissions Preparations & Results Appendix D.2a - 10 Regional Haze SIP for NC Class I Areas December 17, 2007 

# USEPA sums the hourly CEM emissions to the annual level, and MACTEC compared these annual CEM emissions to those in the S/L i nventories. The 2002 CEM inventory containing NOx and SO2 emissions and heat input data we re downloaded from the USEPA CAMD web site ( www.epa.gov/airmarkets ). The data were provided by quarter and emission unit.

The first step in the EGU analysis involved preparing a crosswalk file to match facilities and units in the CAMD inventory to facilities and units in the S/L inventories. In the CAMD inventory, the Office of Regulatory Informati on Systems (ORIS) identification (ID) code identifies unique facilities and the unit ID identifies unique boilers and internal combustion engines (i.e., turbines and reciprocating engines) . In the North Carolina point source emissions inventories, the state and county code (FIPS code ) and State facility ID together identify unique facilities and the emission unit ID identifies unique boilers or internal combustion engines. In most cases, there is a one-to-one correspondence between the CAMD identifiers and the S/L identifiers. However, in some of the S/L inventories, the emissions for multiple emission units are summed and reported under one emission unit ID. MACTEC created an Excel spreadsheet that contained an initial crosswalk with the ORIS ID and unit ID in the CEM inventory matched to the State and county FIPS, State facility ID, and emission unit ID in the emissions inventories. The initial crosswalk contained both the annual emissions summed from the CAMD database, as well as, the S/L emission estimate. The matching at the facility level was nearly complete. In some cases, however, S/L agencies or stakeholders’ assistance was needed to match some of the CEM units to emission units in the S/L inventories.

The second step in the EGU analysis was to prepare an Excel spreadsheet that compared the annual emissions from the hourly CAMD inventory to the annual emissions reported in the S/L inventory. The facility-level comparison of CEM to emission inventory NO x 

# and SO 2 

# emissions found that for most facilities, the annual emissions from the S/L inventory equaled the CAMD CEM emissions. Minor differences could be expl ained because the facility in the S/L inventory contained additional small or emergency units that were not included in the CAMD database.

The final step in the EGU analysis was to compare the SO 2 

# and NO x 

# emissions for select Southern Company units in the VISTAS region. Southern Company is a super-regional company that owns EGUs in four VISTAS Stat es (Alabama, Florida, Georgia, and Mississippi) and participates in VISTAS as an industry st akeholder. Southern Company independently provided emission estimates for 2002 as part of the development of the preliminary VISTAS 2002 inventory. Emission estimates were reviewed by the States and incorporated into the States CERR submittal. There were no major inconsistencies between the Southern Company data, the CAMD data, and the S/L CERR data.

## Emissions Preparations & Results Appendix D.2a - 11 Regional Haze SIP for NC Class I Areas December 17, 2007 

# The minor inconsistencies found included small differences in emission estimates (<2 percent difference), exclusion/inclusion of small gas-fire d units in the different databases, and grouping of emission units in S/L CERR submittals where CAMD listed each unit individually. MACTEC compared SO 2 

# and NO x 

# emissions on a unit-by-unit basis and did not find any major inconsistencies.

2.1.5 Emission Inventory QA Review Throughout the inventory development process, QA steps were performed to ensure that no double counting of emissions occurred, and to ensure that a full and complete inventory was developed for VISTAS. QA was an important co mponent to the inventory development process and MACTEC performed the following QA steps on the point source component of the VISTAS revised 2002 base year inventory:

1. Facility level emission summaries were prepared and evaluated to ensure that emissions were consistent and that there were no missing sources.

2. State-level EGU and non-EGU comparisons (by pollutant) were developed between the 2002 base year inventory, the draft VISTAS 2002 inventory, and the 1999 NEI Version 2 inventory.

3. Data product summaries and raw NIF 3.0 data files were provided to the VISTAS Emission Inventory Technical Advisor and to the Point Source, EGU, and non-EGU Special Interest Work Group representatives for review and comment. Changes based on these comments were reviewed and approved by the S/L point source contact prior to implementing the changes in the files.

Version numbering was used for all inventory files developed. The version numbering process used a decimal system to track major and minor changes.

2.1.6 Summary of the 2002 Actual Inventory Tables 2.1.6-1 summarize the final 2002 actual base year inventory for North Carolina. All values are in tons per year. The EGU emissions include the emissions from all processes with a Source Classification Code (SCC) of either 1- 01-xxx-xx (External Combustion Boilers – Electric Generation) or 2-01-xxx-xx (Internal Combustion Engines – Electric Generation). Emissions for all other SCCs are included in the non-EGU column.

## Emissions Preparations & Results Appendix D.2a - 12 Regional Haze SIP for NC Class I Areas December 17, 2007 

# Table 2.1.6-1 2002 Actual Point Source Inventory for North Carolina

Pollutant All Point Sources EGUs Non-EGUs
SO 2 

# 522,113 477,990 44,123
NO x 

# 196,782 151,854 44,928
VOC 62,170 988 61,182

CO 64,461 13,885 50,576
PM 10 

# -PRI 36,592 22,754 13,838
PM 2.5 

# -PRI 26,998 16,498 10,500
NH 3 

# 1,234 54 1,180 VOC = Volatile Organic Compounds CO = Carbon Monoxide

2.2 Development of Typical Year EGU Inventory
VISTAS developed a typical year 2002 emission inventory for EGUs to avoid anomalies in emissions due to variability in meteorology, economic, and outage factors in 2002. The typical year inventory represents the five year (2000-2004) period, which are the years used to calculate the regional haze baseline.

Data from the USEPA’s CAMD were used to develop normalization factors for producing a 2002 typical year inventory for EGUs. The VIST AS contractor used the ratio of the 2000-2004 average heat input and the 2002 actual heat input to normalize the 2002 actual emissions. MACTEC obtained data from the USEPA CAMD for utilities regulated by the Acid Rain program. Annual data for the period 2000 to 2004 were obtained from the CAMD web site. The parameters available were the SO2 and NOx emission rates, heat input, and operating hours.

MACTEC used the actual 2002 heat input and the av erage heat input for the 5-year period from 2000-2004 as the normalization factor, as follows:

Normalization Factor: 2000-2004 average heat input 2002 actual heat input

If the unit did not operate for all five years, then the 2000-2004 average heat input was calculated for the one or two years in which the unit did operate. The annual actual emissions were multiplied by the normalization factor to determine the typical emissions for 2002, as follows:

## Emissions Preparations & Results Appendix D.2a - 13 Regional Haze SIP for NC Class I Areas December 17, 2007 

# Typical Emissions = 2002 actual emissions x Normalization Factor

After applying the normalization factor, some adjustments were needed for special circumstances. For example, a unit may not have operated in 2002 and thus have zero emissions. If the unit had been permanently retired prio r to 2002, then MACTEC used zero emissions for the typical year. If the unit had not been permanently retired and would normally operate in a typical year, then MACTEC used the 2001 (or 2000) heat input and emission rate to calculate the typical year emissions.

The final step was to replace the 2002 actual emissions with the 2002 typical year data described above. MACTEC provided the raw data and results of the typical year calculations in a spreadsheet for S/L agency to review and comment. Any comments made were incorporated into the typical 2002 inventory.

Table 2.2-1 summarizes emissions by State and po llutant for the actual 2002 EGU inventory and the typical year EGU inventory. For the entir e VISTAS region, actual 2002 NOx emissions were about 0.1 percent lower than the typical year emissions. North Carolina’s actual 2002 NOx emissions were 2.0 percent higher than the typical year emissions.

Table 2.2-1 NO x 

# Emissions Comparison for EGUs
NO x 

# Emissions (tons/year) State Actual 2002 Typical 2002 Percentage Difference AL 161,038 154,704 3.9 FL 257,677 282,507 -9.6 GA 147,517 148,126 -0.4 KY 198,817 201,928 -1.6 MS 43,135 40,433 6.3 NC 151,854 148,812 2.0 SC 88,241 88,528 -0.3 TN 157,307 152,137 3.3 VA 86,886 85,081 2.1 WV 230,977 222,437 3.7

## Emissions Preparations & Results Appendix D.2a - 14 Regional Haze SIP for NC Class I Areas December 17, 2007 

# 3. 2018 POINT SOURCE EMISSIONS INVENTORY DEVELOPMENT

Different approaches were used for different sectors of the point source inventory. For the EGUs, VISTAS relied primarily on the Integrated Planning Model ® 

# (IPM), version 2.1.9, to project future generation, as well as, to calculate the impact of future emission control programs. The IPM results were adjusted based on S/L agency knowledge of planned emission controls at specific EGUs. For non-EGUs, VISTAS used recently updated growth and control data consistent with the data used in the USEPA’s Clean Air Interstate Rule (CAIR) analyses, and supplemented these data with available S/L agency input and updated fuel use forecast data for the United States Department of Energy.

For both sectors, VISTAS generated 2018 inventory with control scenarios that account for post2002 emission reductions from promulgated and propos ed Federal, State, Local, and site-specific control programs as of July 1, 2004. Secti on 3.1 discusses the EGU projection inventory development, while Section 3.2 discusses the non-EGU projection inventory development.

3.1 EGU Emission Projections
The following subsections discuss the aspects of the development of the EGU projections.

• A chronology of the EGU development process used by MACTEC and discuss key decisions in selecting the final methods for performing the emissions projections.

• The development of the final set of IPM runs that are included in the VISTAS 2018 inventory.

• The process of transforming the IPM parsed files into NIF format.

• The process for ensuring that units accounted for in IPM were not double-counted in the non-EGU inventory.

• The QA/QC checks that were made to ensure that the IPM results were properly incorporated into the VISTAS inventory.

• The changes to the IPM results that S/L agencies requested to be included in the VISTAS inventory based on new information that was not accounted for in the IPM

runs.

• Summary of 2002 and 2018 EGU emissions by state

## Emissions Preparations & Results Appendix D.2a - 15 Regional Haze SIP for NC Class I Areas December 17, 2007 

# 3.1.1 Chronology of the Development of EGU Projections Initially, VISTAS considered three options for developing the 2009 and 2018 projection inventories for EGUs:

• 

# Option 1 – Use the results of IPM modeling conducted in support of the proposed CAIR base and control case analyses as the starting point and refine the projections with readily available inputs from stakeholders; these IPM runs were conducted for 2010 and 2015, which VISTAS would use to represent projected emissions in 2009 and 2018 respectively.

• 

# Option 2 – Use the VISTAS 2002 typical year as the starting point, apply growth factors from the Energy Information Administration, and refine future emission rates with stakeholder input regarding utilization rates, capacity, retirements, and new unit information.

• 

# Option 3 – Use the results of a new round of IPM modeling sponsored by VISTAS and the Midwest Regional Planning Organization (MRPO). These runs incorporated VISTAS specific unit and regulation modified parameters, and generate results for 2018 explicitly.

An additional consideration for each of the three options was the inclusion of emission projections developed by the Southern Company specifically for their units. Southern Company used their energy budget forecast to project net generation and heat input for every existing and future Southern Company EGU for the year 2018.

Each of these three options and the Southern Company projections were discussed in a series of conference calls with the VISTAS EGU Special Interest Work Group (SIWG) during the fall of 2004. During a conference call on December 6, 2004, the VISTAS EGU SIWG approved the use of the latest VISTAS/MRPO sponsored IPM runs (Option 3) to represent 2018 EGU forecasts of emissions the future year cases.

The Option 3 IPM modeling resulted from a joint agreement by VISTAS and MRPO to work together to develop future year utility emissions based on IPM modeling. The decision to use IPM modeling was based in part on a study of utility forecast methods by E.H. Pechan and Associates, Inc. (Pechan) for MRPO, which recommended IPM as a viable methodology. Although the USEPA used IPM recently to support their rulemaking for the CAIR, VISTAS stakeholders felt that certain model inputs needed to be improved. Thus, VISTAS and MRPO decided to hire contractors to conduct new IPM modeling and to post-process the IPM results.

## Emissions Preparations & Results Appendix D.2a - 16 Regional Haze SIP for NC Class I Areas December 17, 2007 

# For 2018, Southern Company projections were generally less than IPM because of assumptions made by Southern Company on which units would be economical to control and incorrect data in the NEEDS database which feeds IPM.

In August 2004, VISTAS contracted with ICF to run IPM to provide utility forecasts for 2018 under two future scenarios – Base Case and CAIR Case. The Base Case represents the current operation of the power system under currently known laws and regulations, including those that come into force in the study horizon. The CAIR Case is the Base Case with the proposed CAIR rule superimposed. The run results were parsed at the unit level for 2018. The IPM output files were delivered by ICF in November, and the post-processed data files were delivered by Pechan in December 2004.

On March 10, 2005, the USEPA issued the final CAIR. VISTAS and MRPO, in conjunction with other regional planning organizations (R POs), conducted another round of IPM modeling, which reflected changes to control assumptions based on the final CAIR as well as additional changes to model inputs based on S/L agency and stakeholder comments. Several conference calls were conducted in the spring/summer of 2005 to discuss and provide comments on IPM assumptions related to six main topics: power system operation, generating resources, emission control technologies, set-up parameters and rule, financial assumptions, and fuel assumptions.

For the summer 2006 set of IPM runs, ICF generate d two different parsed files. One file includes all fuel burning units (fossil, biomass, landfill gas), as well as, non-fuel burning units (hydro, wind, etc.). The second file contains ju st the fossil-fuel burning units (e.g., emissions from biomass and landfill gas are omitted). The RPOs decided to use the fossil-only file for modeling to be consistent with the USEPA, since the USEPA used the fossil only results for CAIR analyses. For the 10 VISTAS states, non-fossil fuels accounted for only 0.13 percent of the NOx emissions and 0.04 percent of the SO2 emissions in the 2018 IPM runs

VISTAS asked S/L agencies to review the results of the summer 2006 set of IPM runs, which were incorporated into the VISTAS inventor y. The NCDAQ primarily reviewed and commented on the IPM results with respect to IPM decisions on NOx post-combustion controls and SO2 scrubbers. The NCDAQ decided to let the IPM solve the 2018 emissions.

3.1.2 VISTAS/MRPO IPM runs for EGU sources The following summary of the VISTAS/MRPO IPM ® 

# modeling is based on ICF’s documentation Future Year Electricity Generating Sector Emission Inventory Development Using the IPM ® 

# in Support of Fine Particulate Mass and Visibility Modeling in the VISTAS and

## Emissions Preparations & Results Appendix D.2a - 17 Regional Haze SIP for NC Class I Areas December 17, 2007 

# Midwest RPO Regions , April 2005. The ICF documentation is to be used as an extension to the USEPA's proposed CAIR modeling runs documented in Documentation Supplement for EPA Modeling Applications (V.2.1.6) Using the IPM , EPA 430/R-03-007, July 2003.

IPM provides “forecasts of least-cost capacity expansion, electricity dispatch, and emission control strategies for meeting energy demand a nd environmental, transmission, dispatch, and reliability constraints.” The underlying database in this modeling is the USEPA’s National Electric Energy Data System (NEEDS) released with the CAIR Notice of Data Availability (NODA). The NEEDS database contains the existing and planned/committed unit data in the USEPA modeling applications of IPM. N EEDS includes basic geographic, operating, air emissions, and other data on these generating units . VISTAS States and stakeholders provided changes for:

• NO x 

# post-combustion control on existing units

• SO 2 

# scrubbers on existing units

• SO 2 

# emission limitations

• PM controls on existing units

• Summer net dependable capacity

• Heat rate for existing units

• SO 2 

# and NO x 

# control plans based on State rules or enforcement settlements

The years 2009 and 2018 were explicitly modeled in this set of runs. Again, the NCDAQ decided to let the IPM model solve the 2018 emissions.

3.1.3 Post-Processing of IPM Parsed Files The following summary of the VISTAS/MRPO IPM modeling is based on Pechan’s documentation LADCO IPM Model Parsed File Post-Processing Methodology and File Preparation , February 8, 2005. The essence of the IPM model post-processing methodology is to take an initial IPM model output file and tran sform it into air quality model input files. ICF via VISTAS/MRPO provided an initial spreadsheet file containing unit-level records of both (1) “existing” units and (2) committed or new generic aggregates.

All records have unit and fuel type data; existing, retrofit (for SO 2 

# and NO x 

# ), and separate NO x 

# control information; annual SO 2 

# and NO x 

# emissions and heat input; summer season (MaySeptember) NO x 

# and heat input; July day NO x 

# and heat input; coal heat input by coal type;

## Emissions Preparations & Results Appendix D.2a - 18 Regional Haze SIP for NC Class I Areas December 17, 2007 

# nameplate capacity (mega-watts), and State FIPS code. Existing units also have county FIPS code, a unique plant identifier (ORISPL) and unit ID (also called boiler ID) (BLRID); generic units do not have these data. The processing includes estimating various types of emissions and adding in control efficiencies, stack paramete rs, latitude-longitude coordinates, and State identifiers (plant ID, point ID, stack ID, process ID). Additionally, the generic units are sited in a county and given appropriate IDs. This processing is described in more detail below.

The data are prepared by transforming the generic aggregates into units similar to the existing units in terms of the available data. The generic aggregates are split into smaller generic units based on their unit types and capacity, are provided a dummy ORIS unique plant and boiler ID, and are given a county FIPS code based on an algorithm that sites each generic by assigning a sister plant that is in a county based on its attainment/nonattainment status. Within a State, plants (in county then ORIS plant code order) in attainment counties are used first as sister sites to generic units, followed by plants in PM2.5 nonattainment counties, followed by plants in 8-hour ozone nonattainment counties. Note that no LADCO or VISTAS States provided blackout counties that would not be considered when siting generics, so this process is identical to the one used for the USEPA IPM post-processing.

SCCs were assigned for all units; unit/fuel/firing/bottom type data were used for existing units’assignments, while only unit and fuel type were used for generic units’ assignments. Latitudelongitude coordinates were assigned, first using the USEPA-provided data files, secondly using the September 17, 2004 Pechan in-house latitude-longitude file, and lastly using county centroids. These data were only used when the data were not provided in the 2002 NIF files. Stack parameters were attached, first using th e USEPA-provided data files, secondly using a March 9, 2004 Pechan in-house stack parameter file based on previous Energy Information Adminitration form 767 (EIA-767) data, and lastly using an the USEPA June 2003 SCC-based default stack parameter file. These data were only used when the data were not provided in the 2002 NIF files.

Additional data were required for estimating VOC, CO, filterable primary PM 10 

# and PM2.5, PM condensable, and NH 3 

# emissions for all units. Thus, ash and sulfur contents were assigned by first using 2002 EIA-767 values for existing units or SCC-based defaults; filterable PM10 and PM2.5 efficiencies were obtained from th e 2002 EGU NEI that were based on 2002 EIA-767 control data and the PM Calculator program (a default of 99.2 percent is used for coal units if necessary); fuel use was back calculated from th e given heat input and a default SCC-based heat content; and emission factors were obtained fr om an USEPA-approved October 7, 2004 Pechan emission factor file based on the USEPA’s AP-42 emi ssion factors. Note that this updated file is not the one used for estimating emissions for previous USEPA post-processed IPM files.

## Emissions Preparations & Results Appendix D.2a - 19 Regional Haze SIP for NC Class I Areas December 17, 2007 

# Emissions for 28 temporal-pollutant combinations were estimated since there are seven pollutants (VOC, CO, primary PM 10 

# and PM 2.5 

# , NH 3 

# , SO 2 

# and NO x 

# ) and four temporal periods (annual, summer season, winter season, July day).

The next step was to match the IPM unit IDs with the identifiers in VISTAS 2002 inventory. A crosswalk file was used to obtain FIPS State a nd county, plant ID (within State and county), and point ID. If the FIPS State and county, plant ID and point ID are in the 2002 VISTAS NIF tables, then the process ID and stack ID are obtai ned from the NIF; otherwise, defaults, described above, were used.

Pechan provided the post-processed files in NIF 3.0 format. Two sets of tables were developed: “NIF files” for IPM units that have a crosswalk match and are in the 2002 VISTAS inventory, and “NoNIF files” for IPM units that are not in the 2002 VISTAS inventory (which includes existing units with or without a crosswalk match as well as generic units).

3.1.4 Eliminating Double Counting of EGU Units The following procedures were used to avoid double counting of EGU emissions in the 2018 point source inventory. The 2002 VISTAS point s ource emission inventory contains both EGUs and non-EGUs. Since this file contains bot h EGUs and non-EGU point sources, and EGU emissions are projected using the IPM, it was necessary to split the 2002 point source file into two components. The first component contains those emission units accounted for in the IPM forecasts. The second component contains all other point sources not accounted for in IPM.

As described in the previous section, Pechan developed 2018 NIF files for EGUs from the IPM parsed files. All IPM matched units were initially removed from the 2018 point source inventory to create the non-EGU inventory (which was pr ojected to 2018 using the non-EGU growth and control factors described in Section 3.2.1). This was done on a unit-by-unit basis based on a cross-reference table that matches IPM emission unit identifiers (ORISPL plant code and BLRID emission unit code) to VISTAS NIF emission un it identifiers (FIPSST state code, FIPSCNTY county code, State Plant ID, State Point ID). When there was a match between the IPM ORISPL/BLRID and the VISTAS emission unit ID, the unit was assigned to the EGU inventory; all other emission units were assigned to the non-EGU inventory.

If an emission unit was contained in the NIF files created by Pechan from the IPM output, the corresponding unit was removed from the initial 2018 point source inventory. The NIF 2018 EGU files from the IPM parsed files were then merged with the non-EGU 2018 files to create the 2018 point source files.

## Emissions Preparations & Results Appendix D.2a - 20 Regional Haze SIP for NC Class I Areas December 17, 2007 

# Next, MACTEC prepared several ad-hoc QA/QC queries to verify that there was no doublecounting of emissions in the EGU and non-EGU inventories:

• MACTEC reviewed the IPM parsed files to identify EGUs accounted for in IPM. MACTEC compared this list of emission units to the non-EGU inventory derived from the VISTAS cross-reference table to verify that units accounted for in IPM were not double-counted in the non-EGU inventory. As a result of this comparison, MACTEC made a few adjustments in the cross-reference table to add emission units for four plants to ensure these units accounted for in IPM were moved to the EGU inventory.

• MACTEC reviewed the non-EGU inventory to identify remaining emission units with a Standard Industrial Classification (SIC) code of “4911 Electrical Services” or SCC of “1- 01-xxx-xx External Combustion Boiler, Electric Generation”.

• MACTEC compared the list of sources meeting these selection criteria to the IPM parsed file to ensure that these units were not double-counted.

MACTEC asked S/L agencies to review the 2018 poi nt source inventory to verify whether there was any double counting of EGU emissions.

3.1.5 Quality Assurance steps Quality assurance was an important component to the inventory development process and MACTEC performed the following QA steps on the EGU component of the VISTAS revised 2009 and 2018 EGU inventories:

1. Provided parsed files (i.e., Excel spreadsheets that provide unit-level results derived from the model plant projections obtained by the IPM) to the VISTAS EGU SIWG for review and comment.

2. Provided facility level emission summaries for 2018 for both the base case and CAIR case to the VISTAS EGU SIWG to ensure that emissions were consistent and that there were no missing sources.

3. Compared State-level emissions from the IPM parsed files with the post-processed NIF files to verify that the post-processed NIF files were consistent with the IPM parsed file results.

## Emissions Preparations & Results Appendix D.2a - 21 Regional Haze SIP for NC Class I Areas December 17, 2007 

# VISTAS requested S/L review of these files – the changes specified by North Carolina as a result of this review are documented in the following subsection.

3.1.6 S/L Adjustments to IPM Modeling Results After the S/L agency review of the final set of IPM runs, S/L agencies specified a number of changes to the IPM results to better reflect current information on when and where future controls would occur. These changes to the IPM results primarily involved S/L agency addition or subtraction of future emission controls base d on the best available data from state rules, enforcement agreements, compliance plans, permits, and discussions/commitments from individual companies.

For example, Duke Energy and Progress Energy have updated their plans for complying with North Carolina’s Clean Smokestack Act. These plans vary substantially from the IPM results both in terms current and future controls and timing of these controls. As a result, NCDAQ replaced the IPM emission projections for 2009 w ith projections from the Duke Energy and Progress Energy compliance plan. The NCDAQ elected to use the IPM results for 2018.

Some S/L agencies specified changes to the controls assigned by IPM to reflect their best estimates of emission controls. The VISTAS cont ractors used a scrubber control efficiency of 90 percent when adding or removing SO 2 

# scrubber controls, used a control efficiency of 90 percent when adding or removing NO x 

# SCR controls at coal-fired plants, 80 percent when adding or removing NO x 

# SCR controls at gas-fired plants, a nd 35 percent when adding or removing NO x 

# SNCR controls. The specific changes from the NCDAQ to the IPM results are also summarized in Table 3.1.6-1.

S/L agencies provided information and/or comment on changes in stack parameters from the 2002 inventory for the 2009 and 2018 inventories. Changes to stack parameters were also made in cases where new controls are scheduled to be installed. In cases where an emission unit projected to have a SO 2 

# scrubber in either 2009 or 2018, some states were able to provide revised stack parameters for some units based on design features for the new control system. Other units projected to install scrubbers by 2009 or 2018 are not far enough along in the design process to have specific design details. For those units, the VISTAS EGU SIWG made the following assumptions: 1) the scrubber is a wet scrubber; 2) keep the current stack height the same; 3) keep the current flow rate the same, and 4) change the stack exit temperature to 169 °F (this is the virtual temperature derived from a wet temperature of 130 °F). VISTAS determined that exit temperature (wet) of 130 °F +/- 5 °F is representative of different size units and wet scrubber technology. A final table of the 2009 and 2018 NO x 

# and SO 2 

# controls that will be or are assumed

## Emissions Preparations & Results Appendix D.2a - 22 Regional Haze SIP for NC Class I Areas December 17, 2007 

# to be applied to specific EGU emission units throughout the VISTAS states is presented in Appendix H.7.

Table 3.1.6-1 NCDAQ Adjustments to IPM Re sults for the 2009 and 2018 EGU Inventories

Plant Name and ID Unit Nature of Update/Correction
G G Allen (2718) Belews Creek (8042)1 Buck (2720) Cliffside (2721) Dan River (2723) Marshall (2727) Riverbend (2732) All Replaced all IPM 2009 results with emission projections from Duke Power’s NC Clean Smokestacks Act Compliance Plan for 2006. Used IPM results for 2018.

Asheville (2706) Cape Fear (2708) Lee (2709) Mayo (6250) Roxboro (2712) Sutton (2713) Weatherspoon (2716) All Replaced all IPM 2009 results with emission projections from Progress Energy’s NC Clean Smokestacks Act Compliance Plan for 2006. Used IPM results for 2018.

Dwayne Collier Battle Cogeneration Facility ORISID=10384 GEN1

GEN2 Dwayne Collier Battle is a duplicate entry. This is Cogentrixof Rocky Mount (37-065-3706500146, stacks G-26 and G27). Duplicate entries were removed from the 2009 and 2018 inventory.

Kannapolis Energy Partners ORISID=10626 GEN2

GEN3 Kannapolis Energy emissions are being used as credits for another facility. IPM emissions from this facility (37-025- ORIS10626) were removed from the EGU inventory for 2009 and 2018. Emissions from Kannapolis Energy (37-025- 3702500113) were carried forward in the 2009/2018 inventory.



# 3.2 Non-EGU Emission Projections
The general approach for assembling future year data was to use recently updated growth and control data consistent with the data used in the USEPA’s CAIR analyses, supplement these data with available stakeholder input, and provide the results for stakeholder review to ensure credibility. The VISTAS contractor used the 2002 VISTAS base year inventory, based on the 2002 CERR submittals as the starting point fo r the non-EGU projection inventory. The 2002 VISTAS/ASIP point source emission inventory c ontains both EGUs and non-EGUs. Since this file contains both EGUs and non-EGU point sour ces, and EGU emissions are projected using the

## Emissions Preparations & Results Appendix D.2a - 23 Regional Haze SIP for NC Class I Areas December 17, 2007 

# IPM, it was necessary to split the 2002 point source file into two components. The first component contains those emission units accounted for in the IPM forecasts. The secondcomponent contains all other point sources not accounted for in IPM and constitutes the nonEGU emissions inventory.

MACTEC performed the following activities to apply growth and control factors to the 2002 non-EGU emissions inventory to generate the 2009 and 2018 projection inventories:

• 

# Obtained, reviewed, and applied the most current growth factors developed by the USEPA, based on forecasts from an updated Regional Economic Models, Inc. (REMI) model (version 5.5) and the latest Annual Energy Outlook published by the Department of Energy (DOE);

• 

# Obtained, reviewed, and applied any State-sp ecific or sector-specific growth factors submitted by stakeholders;

• 

# Obtained and incorporated information regarding sources that have shut down after 2002 and set the emissions to zero in the projection inventories;

• 

# Obtained, reviewed, and applied control assumptions;

• 

# Provided data files in NIF3.0 format and emission summaries in EXCEL format for review and comment; and

• 

# Updated the database with corrections or new information from S/L agencies based on their review of the 2009 and 2018 inventories.

The following sections discuss each of these steps.

3.2.1 Growth assumptions for non-EGU sources The growth factor data used in developing th e emission inventory were consistent with the USEPA’s analyses for the CAIR rulemaking. Thes e growth factors are fully documented in the USEPA’s reports entitled Development of Growth Factors for Future Year Modeling Inventories (dated April 30, 2004) and CAIR Emission Inventory Overview (dated July 23, 2004). Three sources of data were used in developing the growth factors for the 2009 and 2018 emissions inventories:

## Emissions Preparations & Results Appendix D.2a - 24 Regional Haze SIP for NC Class I Areas December 17, 2007 • 

# State-specific growth rates from the Regional Economic Model, Inc. (REMI) Policy Insight ® 

# model, version 5.5 (being used in the development of the EGAS Version 5.0). The REMI socioeconomic data (output by i ndustry sector, population, farm sector value added, and gasoline and oil expenditures) are available by 4-digit SIC code at the State level.

• 

# Energy consumption data from the Department of Energy, Energy Information Administration’s (EIA) Annual Energy Outlook 2004, with Projections through 2025 for use in generating growth factors for non-EGU fuel combustion sources. These data include regional or national fuel-use forecast data that were mapped to specific SCCs for the non-EGU fuel use sectors (e.g., commercial coal, industrial natural gas). Growth factors for the residential natural gas combustion category, for example, are based on residential natural gas consumption forecasts that are reported at the Census division level. These Census divisions represent a group of States (e.g., the South Atlantic division includes eight southeastern States a nd the District of Columbia). Although one would expect different growth rates in each of these States due to unique demographic and socioeconomic trends, all States within each division received the same growth rate.

• 

# Specific changes for sectors (e.g., plastics, synthetic rubber, carbon black, cement manufacturing, primary metals, fabricated metals, motor vehicles and equipment) where the REMI-based rates were unrealistic or highly uncertain. Growth projections for these sectors were based on industry group forecasts, Bureau of Labor Statistics (BLS) projections and Bureau of Economic Analys is (BEA) historical growth from 1987-2002.

In addition to the growth data described above, VISTAS received two sets of growth projections from stakeholders. The American Forest a nd Paper Association (AF&PA) supplied growth projections for the pulp and paper sector, which were applied to SIC 26xx Paper and Allied Products, for growth from 2002 to 2009 and 2002 to 2018. The AF&PA projection factors (1.067 and 1.169, respectively) are for the United States industry and apply to all States equally. The number come from the 15-year forecast for world pulp and recovered paper prepared by Resource Information Systems Inc. (RISI). The VISTAS contractor used the above AF&PA growth factors by SIC instead of the factors obt ained from the USEPA’s CAIR analysis for the 2009 and 2018 emission inventories.

The NCDAQ considered recent projections for three key sectors in North Carolina where declining production was anticipated – SIC 22xx Textile Mill Products, 23xx Apparel and Other Fabrics, and 25xx Furniture and Fixtures. For 2009 and 2018 inventories, the NCDAQ decided to use a growth factor of 1.0 for these SIC codes. Although the NCDAQ has data that shows a

## Emissions Preparations & Results Appendix D.2a - 25 Regional Haze SIP for NC Class I Areas December 17, 2007 

# steady decline in these industries in North Carolina, the NCDAQ wanted to maintain the emission levels at 2002 levels so the future emission reduction credits were available in the event that they are needed for nonattainment areas.

For the 2009 and 2018 inventories, the VISTAS/ASIP contractor made one additional change to the growth factors. The Annual Energy Outlook (AEO) 2004 data was replaced with the more recent AEO2006 forecasts (released in February 2006) to reflect changes in the energy market and to improve the emissions growth factors produced. The VISTAS contractor obtained the corresponding AEO2006 projection tables from DOE. VISTAS developed tables comparing the growth factors based on AEO2004 and AEO2006 and these comparison tables were reviewed by the S/L agencies. Based on this review, the VISTAS states decided to use the AEO2006 growth factors for fuel burning SCCs.

VISTAS used the USEPA’s EGAS model and updated the corresponding AEO2006 projection tables to create growth factors by SCC. VI STAS applied the updated growth factors to 2002 actual emissions and replaced the 2009 and 2018 emissions in NIF EM tables for the affected SCCs.

3.2.2 Control Programs applied to non-EGU sources The VISTAS’s contractor developed a control s cenario to address the CAA requirements. The control scenario accounts for post-2002 emission reductions from promulgated Federal, State, Local, and site-specific control programs and are listed below.

• Atlanta / Northern Kentucky / Birmingham 1-hour ozone SIPs

• Industrial Boiler/Process Heater/RICE MACT

• NO x 

## RACT in 1-hour NAA SIPs

• NO x 

## SIP Call (Phase I)

• NO x 

## SIP Call (Phase II)

• RFP 3 percent Plans where in place for one hour plans

• VOC 2-, 4-, 7-, and 10-year MACT Standards

• Combustion Turbine MACT



# The methodologies used to account for the emission reductions associated with these emission control programs are discussed in the following sections.

## Emissions Preparations & Results Appendix D.2a - 26 Regional Haze SIP for NC Class I Areas December 17, 2007 

# NO x 

# SIP Call (Phase I)
Phase I of the NO x 

# SIP call applies to certain large non-EGUs, including large industrial boilers and turbines, and cement kilns. States in the VISTAS region affected by the NO x 

# SIP call have developed rules for the control of NOx emissions that have been approved by the USEPA. VISTAS reviewed the available State rules and guidance documents to determine the affected sources and ozone season allowances. VISTAS also obtained and reviewed information in the USEPA’s CAMD NOx Allowance Tracking System – Allowances Held Report. Since these controls are to be in effect by the year 2007, VISTAS capped the emissions for NO x 

# SIP call affected sources at 2007 levels and carried forward the capped levels for the 2009 and 2018 future year inventories.

NO x 

# SIP Call (Phase II)
The final Phase II NO x 

# SIP call rule was finalized on April 21, 2004. States had until April 21, 2005, to submit SIPs meeting the Phase II NO x 

# budget requirements. The Phase II rule applies to large IC engines, which are primarily used in pipeline transmission service at compressor stations. VISTAS identified affected units using the same methodology as was used by the USEPA in the proposed Phase II rule (i.e., a large IC engine is one that emitted, on average, more than 1 ton per day during 2002). The final rule reflects a control level of 82 percent for natural gas-fired IC engines and 90 per cent for diesel or dual fuel categories. North Carolina provided more specific information on the anticipated controls at the compressor stations. This information was used in the 2009 and 2018 inventories instead of the default approach used by the USEPA in the proposed Phase II rule.

Industrial Boiler/Process Heater MACT The USEPA anticipates reductions in PM and SO 2 

# as a result of the Industrial Boiler/Process Heater MACT standard. The methods used to account for these reductions are the same as those used for the CAIR analysis. Reductions were included for existing units firing solid fuel (coal, wood, waste, biomass), which had a design capacity greater than 10 mmBtu/hr. The USEPA prepared a list of SCCs for solid fuel industrial, commercial/ institutional boilers and process heaters. The VISTAS contractor identified boilers greater than 10 mmBtu/hr using either the boiler capacity from the VISTAS 2002 inventory, or if the boiler capacity was missing, a default capacity based on a methodology developed by the USEPA for assigning default capacities based on SCC code. The applied MACT control efficiencies were 4 percent for SO 2 

# and 40 for percent for PM 10 

# and PM 2.5 

# .

## Emissions Preparations & Results Appendix D.2a - 27 Regional Haze SIP for NC Class I Areas December 17, 2007 

# 2, 4, 7, and 10-year MACT Standards Maximum achievable control technology (MACT) requirements were also applied, as documented in the USEPA’s report entitled Control Packet Development and Data Sources, dated July 14, 2004. The point source MACTs and associated emission reductions were designed from Federal Register notices and di scussions with the USEPA’s Emission Standards Division staff. VISTAS did not apply reductions for MACT standards with an initial compliance date of 2001 or earlier, assuming that the effects of these controls are already accounted for in the 2002 inventories supplied by the States. Em ission reductions were applied only for MACT standards with an initial compliance date of 2002 or greater.

Combustion Turbine MACT The projection inventory does not include the NO x 

# co-benefit effects of the MACT regulations for Gas Turbines or stationary Reciprocating Internal Combustion Engines, which the USEPA estimates to be small compared to the overall inventory.

Clean Air Interstate Rule CAIR does not require or assume additional emission reductions from non-EGU boilers and turbines.

3.2.3 Quality Assurance steps Final QA checks were run on the revised projection inventory data set to ensure that all corrections provided by the S/L agencies and stakeholders were correctly incorporated into the S/L inventories and that there were no remaini ng QA issues that could be addressed during the duration of the project. After exporting the inve ntory to ASCII text files in NIF 3.0, the USEPA QA program was run on the ASCII files and the QA output was reviewed to verify that all QA issues that could be addressed were resolved.

Throughout the inventory development process, quality assurance steps were performed to ensure that no double counting of emissions occurred, and to ensure that a full and complete inventory was developed for North Carolina. Quality assurance was an important component to the inventory development process and MACTEC performed the following QA steps on the point source component of the VISTAS inventory:

1. Facility level emission summaries were prepared and evaluated to ensure that emissions were consistent and reasonable. The summaries included base year 2002

## Emissions Preparations & Results Appendix D.2a - 28 Regional Haze SIP for NC Class I Areas December 17, 2007 

# emissions, 2009/2018 projected emissions accounting only for growth, 2009/2018 projected emissions accounting for both gr owth and emission reductions from CAA controls.

2. State-level non-EGU comparisons (by pollutant) were developed for the base year 2002 emissions, 2009/2018 projected emissions accounting only for growth, 2009/2018 projected emissions accounting for both growth and emission reductions from CAA controls.

3. Data product summaries and raw NIF 3.0 data files were provided to the VISTAS Emission Inventory Technical Advisor and to the Point Source, EGU, and non-EGU Special Interest Work Group representatives for review and comment. Changes based on these comments were reviewed and approved by North Carolina point source contact prior to implementing the changes in the files.

4. Version numbering was used for all inventory files developed. The version numbering process used a decimal system to track major and minor changes.



# 4. Emission Inventory Summaries

The following sections include the emissions inve ntory summaries for the point source for all of the states within the VISTAS region. The first section provides the 2002, 2009 and 2018 emissions for the EGU sources and the second section provides the emissions for the non-EGU

sources.

4.1 Summary of EGU Point Source Inventories
Tables 4.1-1 through 4.1-7 summarize the 2002 base year inventory and 2009 and 2018 projection inventories for the EGU source sect or. The 2009 and 2018 inventories include the adjustments to the IPM results specified by the S/L agencies in the previous section.

## Emissions Preparations & Results Appendix D.2a - 29 Regional Haze SIP for NC Class I Areas December 17, 2007 

# Table 4.1-1 EGU Point Source SO 2 

# Emission Comparison

State 2002 VISTAS 2009 IPM Based with S/L Adjustments 2018 IPM Based with S/L Adjustments AL 447,828 378,052 305,262
FL 453,631 186,055 132,177
GA 514,952 417,449 230,856
KY 484,057 290,193 226,062
MS 67,429 76,579 15,146
NC 477,990 242,286 108,492
SC 206,399 124,608 93,274
TN 334,151 255,410 112,672
VA 241,204 225,653 140,233
WV 516,084 277,489 115,324 Total 3,743,725 2,473,774 1,479,498



# Table 4.1-2 EGU Point Source NO x 

# Emission Comparison

State 2002 VISTAS 2009 IPM Based with S/L Adjustments 2018 IPM Based with S/L Adjustments AL 161,038 82,305 64,358
FL 257,677 86,165 73,125
GA 147,517 98,497 75,717
KY 198,817 92,021 64,378
MS 43,135 36,011 10,271
NC 151,854 66,522 62,353
SC 88,241 46,915 51,456
TN 157,307 66,405 31,715
VA 86,886 66,219 75,594
WV 230,977 86,328 51,241 Total 1,523,449 727,388 560,208

## Emissions Preparations & Results Appendix D.2a - 30 Regional Haze SIP for NC Class I Areas December 17, 2007 

# Table 4.1-3 EGU Point Source VOC Emission Comparison

State 2002 VISTAS 2009 IPM Based with S/L Adjustments 2018IPM Based with S/L Adjustments
AL 2,295 2,473 2,952
FL 2,524 1,910 2,376
GA 1,244 2,314 2,841
KY 1,487 1,369 1,426
MS 648 404 1,114
NC 988 954 1,345
SC 470 660 906
TN 926 932 976
VA 754 778 996
WV 1,180 1,361 1,387 Total 12,516 13,155 16,319



# Table 4.1-4 EGU Point Source CO Emission Comparison

State 2002 VISTAS 2009 IPM Based with S/L Adjustments 2018 IPM Based with S/L Adjustments
AL 11,279 14,986 24,342
FL 57,113 35,928 53,772
GA 9,712 23,721 44,476
KY 12,619 15,812 17,144
MS 5,303 5,051 15,282
NC 13,885 14,942 20,223
SC 6,990 11,135 14,786
TN 7,084 7,213 7,723
VA 6,892 12,509 15,420
WV 10,341 11,493 11,961 Total 141,218 152,790 225,129

## Emissions Preparations & Results Appendix D.2a - 31 Regional Haze SIP for NC Class I Areas December 17, 2007 

# Table 4.1-5 EGU Point Source PM 10 

# -PRI Emission Comparison

State 2002 VISTAS 2009 IPM Based with S/L Adjustments 2018 IPM Based with S/L Adjustments
AL 7,646 6,969 7,822
FL 21,387 9,007 9,953
GA 11,224 17,891 20,909
KY 4,701 6,463 6,694
MS 1,633 4,957 7,187
NC 22,754 22,152 37,376
SC 21,400 19,395 28,826
TN 14,640 15,608 15,941
VA 3,960 5,508 13,775
WV 4,573 5,657 6,349 Total 113,918 113,607 154,832



# Table 4.1-6 EGU Point Source PM 2.5 

# -PRI Emission Comparison

State 2002 VISTAS 2009 IPM Based with S/L Adjustments 2018 IPM Based with S/L Adjustments
AL 4,113 3,921 4,768
FL 15,643 5,910 6,843
GA 4,939 10,907 13,983
KY 2,802 4,279 4,434
MS 1,138 4,777 7,033
NC 16,498 15,949 29,792
SC 17,154 16,042 25,032
TN 12,166 13,092 13,387
VA 2,606 4,067 11,976
WV 2,210 2,940 3,648 Total 79,269 81,884 120,896

## Emissions Preparations & Results Appendix D.2a - 32 Regional Haze SIP for NC Class I Areas December 17, 2007 

# Table 4.1-7 EGU Point Source NH 3 

# Emission Comparison

State 2002 VISTAS 2009 IPM Based with S/L Adjustments 2018 IPM Based with S/L Adjustments
AL 317 359 1,072
FL 234 1,631 2,976
GA 83 686 1,677
KY 326 400 476
MS 190 333 827
NC 54 445 663
SC 142 343 617
TN 204 227 241
VA 127 694 622
WV 121 330 180 Total 1,798 5,448 9,351 

# Note: Emission summaries above are based on SCC’s 1-01-xxx-xx and 2-01-xxx-xx

4.2 Summary of non-EGU Point Source Inventories
Tables 4.2-1 through 4.2-7 summarize the 2002 base year inventory and the 2009 and 2018 projection inventory for the non-EGU point source sector.

Table 4.2-1 Non-EGU Point Source SO 2 

# Emission Comparison
State 2002 2009 2018
AL 96,481 101,246 113,224
FL 65,090 65,511 75,047
GA 53,778 53,987 59,349
KY 34,029 36,418 40,682
MS 35,960 25,564 39,221
NC 44,123 42,536 46,314
SC 53,518 48,324 53,577
TN 79,604 70,678 77,247
VA 63,903 62,560 68,909
WV 54,070 55,973 62,193 Total 580,556 562,797 635,763

## Emissions Preparations & Results Appendix D.2a - 33 Regional Haze SIP for NC Class I Areas December 17, 2007 

# Table 4.2-2 Non-EGU Point Source NO x 

# Emission Comparison
State 2002 2009 2018
AL 83,310 69,409 78,318
FL 45,156 46,020 51,902
GA 49,251 50,353 55,824
KY 38,392 37,758 41,034
MS 61,526 56,397 61,533
NC 44,928 34,767 37,801
SC 42,153 40,019 44,021
TN 64,344 57,883 63,453
VA 60,415 51,046 55,945
WV 46,612 38,031 43,359 Total 536,087 481,683 533,190



# Table 4.2-3 Non-EGU Point Source VOC Emission Comparison
State 2002 2009 2018

AL 47,037 46,644 54,291
FL 38,471 36,880 42,811
GA 33,709 34,116 40,282
KY 44,834 47,785 55,861
MS 43,204 37,747 45,338
NC 61,182 61,925 70,875
SC 38,458 35,665 43,656
TN 84,328 74,089 93,266
VA 43,152 43,726 53,186
WV 14,595 13,810 16,565 Total 448,970 432,387 516,131

## Emissions Preparations & Results Appendix D.2a - 34 Regional Haze SIP for NC Class I Areas December 17, 2007 

# Table 4.2-4 Non-EGU Point Source CO Emission Comparison
State 2002 2009 2018

AL 174,271 180,369 201,794
FL 81,933 87,037 96,819
GA 130,850 147,427 167,904
KY 109,936 122,024 139,437
MS 54,568 57,748 66,858
NC 50,576 53,744 62,197
SC 56,315 60,473 68,988
TN 115,264 119,665 140,942
VA 63,796 68,346 76,998
WV 89,879 100,045 119,332 Total 927,388 996,878 1,141,269



# Table 4.2-5 Non-EGU Point Source PM 10 

# -PRI Emission Comparison
State 2002 2009 2018
AL 25,240 25,421 29,924
FL 35,857 39,872 46,456
GA 21,610 23,103 27,273
KY 16,626 17,174 20,153
MS 19,472 19,245 22,859
NC 13,838 13,910 15,737
SC 14,142 13,370 15,139
TN 35,174 34,833 42,280
VA 13,252 13,048 15,112
WV 17,503 17,090 21,735 Total 212,714 217,066 256,668

## Emissions Preparations & Results Appendix D.2a - 35 Regional Haze SIP for NC Class I Areas December 17, 2007 

# Table 4.2-6 Non-EGU Point Source PM25-PRI Emission Comparison
State 2002 2009 2018
AL 19,178 19,230 22,598
FL 30,504 33,946 39,430
GA 17,462 18,982 22,416
KY 11,372 11,686 13,739
MS 9,906 9,199 10,739
NC 10,500 10,458 11,825
SC 10,245 9,390 11,086
TN 27,807 27,577 33,532
VA 10,165 9,988 11,594
WV 13,313 12,769 16,516 Total 160,452 163,225 193,475



# Table 4.2-7 Non-EGU Point Source NH 3 

# Emission Comparison
State 2002 2009 2018
AL 1,883 2,132 2,464
FL 1,423 1,544 1,829
GA 3,613 3,963 4,797
KY 674 760 901
MS 1,169 668 764
NC 1,180 1,285 1,466
SC 1,411 1,578 1,779
TN 1,613 1,841 2,214
VA 3,104 3,049 3,604
WV 332 341 413 Total 16,402 17,161 20,231

# Appendix D.2b

Area and Nonroad Mobile Source Emissions Inventory Documentation

## Emissions Preparations & Results Appendix D.2b -1 Regional Haze SIP for NC Class I Areas December 17, 2007

## Emissions Preparations & Results Appendix D.2b -2 Regional Haze SIP for NC Class I Areas December 17, 2007 

# TABLE OF CONTENTS

1. OVERALL METHODOLOGY.................................................................................................. 7 1.1 SOURCE CATEGORY IDENTIFICATION...................................................................... 7 1.2 AREA SOURCE EMISSION ESTIMATION APPROACH .............................................. 7 1.3 NONROAD MOBILE SOURCE EMI SSION ESTIMATION APPROACH................... 10 1.4 EMISSION TABLES ........................................................................................................ 10

2. DISCUSSION OF AREA SOURCE CATEGORIES .............................................................. 11 2.1 2002 NORTH CAROLINA-DEVELOPED AREA SOURCE INVENTORY ................. 11 2.1.1 GASOLINE DISTRIBUTION................................................................................... 11 2.1.1.1 Gasoline Dispensing Facilities............................................................................. 11 2.1.1.2 Aircraft Refueling ................................................................................................ 14 2.1.2 STATIONARY SOURCE SO LVENT EVAPORATION.......................................... 14 2.1.2.1 Dry Cleaning........................................................................................................ 15 2.1.2.2 Graphic Arts/Printing........................................................................................... 15 2.1.2.3 Solvent Cleaning and Degreasing........................................................................ 16 2.1.2.4 Auto Body Refinishing ........................................................................................ 17 2.1.2.5 Architectural Coatings ......................................................................................... 18 2.1.2.6 Traffic Markings .................................................................................................. 19 2.1.2.7 Industrial Surface Coating ................................................................................... 20 2.1.2.8 Asphalt Paving..................................................................................................... 21 2.1.2.9 Roofing Operations.............................................................................................. 23 2.1.2.10 Pesticide Application ......................................................................................... 24 2.1.2.11 Commercial/Consumer Solvent Use.................................................................. 30 2.1.3 BIOPROCESS EMI SSION SOURCES ..................................................................... 31 2.1.3.1 Bakeries.............................................................................................................. .. 31 2.1.4 OTHER MAN MADE AREA SOURCES ................................................................. 31 2.1.4.1 Structure Fires...................................................................................................... 3 1 2.1.4.2 Charbroiling ......................................................................................................... 3 2 2.1.4.3 Open Burning – Municipal Solid Waste and Yard Trimmings ........................... 33 2.1.4.4 Small Stationary Source Fossil Fuel Use............................................................. 34 2.1.4.5 Vehicle Fires ........................................................................................................ 4 3 2.1.4.6 Agricultural Burning............................................................................................ 44 2.1.4.7 On Site Incineration ............................................................................................. 45 2.2 2002 VISTAS-DEVELOPED AREA SOURCE INVENTORY...................................... 46 2.2.1 Ammonia from Agricultural Sources.......................................................................... 47 2.2.2 Paved and Unpaved Road Emissions.......................................................................... 47 2.2.3 Stage II emissions ...................................................................................................... . 47 2.2.4 Portable Fuel Containers............................................................................................. 48

## Emissions Preparations & Results Appendix D.2b -3 Regional Haze SIP for NC Class I Areas December 17, 2007 

# 2.2.5 Forest Fires............................................................................................................ ...... 48

3. 2002 VISTAS-DEVELOPED NONROAD MOBILE SOURCE INVENTORY .................... 52 3.1 NONROAD Model Sources .............................................................................................. 52 3.2 Aircraft Engines.......................................................................................................... ....... 53 3.3 Railroad Locomotives...................................................................................................... .. 54 3.4 Commercial Marine Vessel (CMV)................................................................................... 55

4. QUALITY ASSURANCE OF 2002 EMISSIONS INVENTORY .......................................... 59

5. 2009 AND 2018 AREA SOURCE EMISSI ON INVENTORY DEVELOPMENT ................ 60 5.1 Projection of Stationary Area Sources................................................................................ 60 5.2 Projection of Agricultural Area Sources............................................................................ 61 5.3 Projection of Forest Fires Area Sources ............................................................................ 62

6. 2009 AND 2018 NONROAD SOURCE EMI SSION INVENTORY DEVELOPMENT ....... 63 6.1 Projection of NONROAD Model Sources.......................................................................... 64 6.2 Projection of Non-N ONROAD Model Sources ................................................................. 64

7. QUALITY ASSURANCE OF 2009 AND 2018 EMISSIONS INVENTORY........................ 69

8. ADDITIONAL DATA............................................................................................................. . 71 8.1 SIC TO NAICS CROSSWALK ........................................................................................ 71 8.2 FRACTION OF NAICS CODE EMPLOYMENT USED TO CREATE SIC EMPLOYMENT..................................................................................................................... 119

## Emissions Preparations & Results Appendix D.2b -4 Regional Haze SIP for NC Class I Areas December 17, 2007 

# LIST OF TABLES

Table 2.1.1.1-1 Factors Used For Calculating Emission Factor.................................................. 12 Table 2.1.1.1-2 Emission Factors For Gasoline Dispensing......................................................... 13 Table 2.1.2.3-1 Emission Factors Cleaning & Degreasing.......................................................... 17 Table 2.1.2.7-1 Per Capita Emission F actors For Industrial Surface Coating............................. 20 Table 2.1.2.7-2 Per Employee Emission Fact ors for Industrial Surface Coating........................ 20 Table 2.1.2.10-1 Agriculture Pesticides Application Rates......................................................... 27 Table 2.1.2.10-2 Emission Factors by Crop Type ....................................................................... 29
Table 2.1.2.11-1 Misc. Non-Industrial Cons umer-Commercial Emission Factors ..................... 30
Table 2.1.4.4-1 Fuel Use in North Carolina 2002........................................................................ 34
Table 2.1.4.4-2 Combustion Emission Factors............................................................................ 35
Table 2.1.4.4-3 Emission Factors fo r Liquefied Petroleum Gas.................................................. 41
Table 2.1.4.7-1 Yield of Pollutant Values for Uncontrolled Refuse Combustors ....................... 45
Table 2.2.5-1 2002 North Carolina Actual and Typical Fire Emissions ..................................... 51 Table 3.3-1 2002 National Rail Transportation En ergy Use by Fuel Type (Trillion BTU) ........ 55 Table 6.2-1 Locally Generated Growth Factors for North Carolina ........................................ 67
Table 6.2-2 Estimated Emission Reducti on Impacts based on T-4 Rule ................................. 68 Table 6.2-3 Estimated Emission Reduction Impacts Relative to VISTAS 2002 Base Year Values.................................................................................................................... ....... 68

## Emissions Preparations & Results Appendix D.2b -5 Regional Haze SIP for NC Class I Areas December 17, 2007 

# List of Acronyms Acronym Definition ATADS Air Traffic Activity Data System BTS Bureau of Transportation Statistics BTU British Thermal Units CAIR Clean Air Interstate Rule CARB California Air Resource Board CMV Commercial Marine Vessel CNG Compressed Natural Gas EDMS Emissions and Dispersion Modeling System EIA Energy Information Administration EIIP Emissions Inventory Improvement Program E-GAS 5.0 Economic Growth Analysis System version 5.0 FAA Federal Aviation Administration GF Growth Factor IAQTR Interstate Air Quality Transport Rule LPG Liquid Petroleum Gas LTO Landing and Takeoff MSW Municipal Solid Waste NAAQS National Ambient Air Quality Standards NAICS North American Indus try Classification System NCDAQ North Carolina Division of Air Quality NCDFR North Carolina Division of Forest Resources NCDOT North Carolina Department of Transportation NCSU North Carolina State University NEI National Emission Inventory NG Natural Gas NOx Nitrogen Oxides OTAQ Office of Transportation and Air Quality PFC Portable Fuel Container PM Particulate Matter QA Quality Assurance RDU Raleigh/Durham International Airport RIA Regulatory Impact Analysis SCC Source Classification Code SI Spark-Ignition SIC Standard Industrial Classification SIP State Implementation Plan SIWG Special Interest Workgroup

## Emissions Preparations & Results Appendix D.2b -6 Regional Haze SIP for NC Class I Areas December 17, 2007 

# T4 Tier 4 USACE U.S. Army Corps of Engineers USEPA U.S. Environmental Protection Agency USFA U.S. Fire Administration VISTAS Visibility Improvement State & Tribal Association of the Southeast VMT Vehicle Miles Traveled VOC Volatile Organic Compounds

## Emissions Preparations & Results Appendix D.2b -7 Regional Haze SIP for NC Class I Areas December 17, 2007 

# 1. OVERALL METHODOLOGY

1.1 SOURCE CATEGORY IDENTIFICATION
The area source categories were identified from U. S. Environmental Protection Agency’s (USEPA’s) guidance document EPA-450/4-91-016, Procedures for the Preparation of Emission Inventories of Carbon Monoxide and Precursors of Ozone, Vol. 1 , from this point on this document will be referred to as the Procedures document; the Emissions Inventory Improvement Program (EIIP) Technical Reports, Volume 3, Area Sources as of December 2002 (the most current version at the time of the inventory development), from this point on this document will be referred to as EIIP Tech Report ; and a report entitled, Documentation of the Base G 2002 Base Year, 2009 and 2018, Emission Inventories for VISTAS and written by the VISTAS contractor company, MACTEC, Inc.

Nonroad mobile sources were identified from the USEPA’s guidance document the Procedures document. Nonroad mobile source emissions are estimated by the methodologies suggested in the USEPA document, EPA-454/R-05-001, Emissions Inventory Guidance for Implementation of Ozone and Particulate Matter National Ambien t Air Quality Standards (NAAQS) and Regional Haze Regulations ; EPA-450/4-81-026d (Revised) Procedures for Emission Inventory Preparation, Volume IV; Mobile Sources (Mobile Source Procedures); and from the USEPA’s nonroad mobile model NONROAD2005c released March 21, 2006.

1.2 AREA SOURCE EMISSION ESTIMATION APPROACH
Area source emissions are estimated by multiplying an emission factor by some known indicator of collective activity for each source category within the inventory area. An indicator is any parameter associated with the activity level of a source that can be correlated with the air pollutant emissions from that source, such as production, number of employees, or population.

In general, one of the following emissions estimation approaches is used to calculate the area source emissions: per capita emission factors, employment-related emission factors, commodity consumption-related emission factors, and level of activity based emission factors. The emission factors used were obtained from the EIIP Tech Reports , the Procedures document or the USEPA’s AP

- 

# 42 Compilation of Air Pollutant Emission Factors, Fifth Edition , referred to as AP-42

.

## Emissions Preparations & Results Appendix D.2b -8 Regional Haze SIP for NC Class I Areas December 17, 2007 

# There are several methods for estimating the activity level for a specific area source category. These are: treating area sources as point sources, surveying local activity levels, apportioning national or statewide activity totals to local inventory areas, using population or employment data. All of these methods were used to estimate area source emissions

Certain emission categories were adjusted for such things as season or rule effectiveness and rule penetration. These are discussed in the particular source categories descriptions.

For certain categories, there can be overlap between the point source emissions and the area source emissions calculated with emission factors. The 2002 point source emissions in these categories were identified so that they could be subtracted where appropriate.

There are a number of categories where emissions were calculated with emission factors based on employment. These emission factors were developed by the USEPA when employment reports were organized by Standard Industr ial Classification (SIC) code. Since 1997, employment statistics are organized by the Nort h American Industry Classification System (NAICS). For the solvent cleaning industries, the SIC codes do not directly correspond to single NAICS code. Sometimes several partial NAICS employment values will relate to a SIC code. A crosswalk was used to determine what percentage of a NAICS employment value would correspond to the SIC codes. The tables from the US Census showing the NAICS-SIC crosswalk are reproduced in Section 8 – Additional Data. It should be noted that the crosswalk is based on national totals and is not specific to any particul ar state. In Section 8.2, the employment fraction of the NAICS codes used to create the SIC code employment data is tabulated.

The employment numbers were obtained from the on-line 2002 County Business Patterns for the various NAICS codes at the county level for North Carolina. In addition to having employment values (or employment ranges due to confidentiality rules) by NAICS, the County Business Patterns breaks down the number of facilities by employment categories. The employment categories are 1 – 4, 5 – 9, 10 – 19, 20 – 49, 50 – 99, 100 – 249, 250 – 499, 500 – 999, >1000 employees. To account for point sources, it was assumed that facilities with 100 employees or greater were point sources and were not considered in the calculations.

When a NAICS category gave a number of employees and there were no establishments with 100 employees or greater, then the value was used. However, in most cases the County Business Patterns gave a range of total employees in the county instead of the actual number. When this occurred, facility sizes were considered and the mid-range of employees was assumed, in accordance with the EIIP Tech. Report . For example, a NAICS category for a county had a range of employment of 100-249 with two establis hments with 1 – 4 employees, one with 20-49

## Emissions Preparations & Results Appendix D.2b -9 Regional Haze SIP for NC Class I Areas December 17, 2007 

# employees, and one with 100-249 employees. Assuming 3 to be the mid-range of 1 –4 and 35 to be the mid-range of 20-49, the employment used for the area source calculation was estimated

as:

(2 x 3) + (1 x 35) = 41 employees

The larger establishment was assumed to be a point source and not taken into consideration for the area source calculation.

If a total number of employees was provided and there were establishments with 100 employees or greater, then the mid-range of the smaller facilities were used as described above. The estimated employment was compared to the value given to ensure that remainder would account for the large establishment. In cases where the remainder would not be enough employment to account for the larger establishment, the area source employment was adjusted down. For example, a NAICS category had 250 employees with one establishment with 20 – 49 employees (mid-range 35), two establishments with 50 – 99 employees (mid-range 75), and one establishment with 100 – 249 employees. The employment estimated for the area source and the remainder employment was estimated as:

(1 x 35) + (2 x 75) = 185 employees 250 – 185 = 65 employees

The remainder of 65 employees is not enough to account for an establishment of 100 – 249 employees. Therefore, the area source employment was adjusted down by 35 so that there were 100 employees remaining to account for the large establishment.

Subsections 2.1 through 2.2 address the area source emissions inventories that were developed by both the North Carolina Division of Air Quality (NCDAQ) and the southeast regional haze planning organization, Visibility Improvement St ate & Tribal Association of the Southeast (VISTAS). VISTAS is a collaborative effort of state governments, tribal governments, and various federal agencies established to initiate and coordinate activities associated with the management of regional haze, visibility and other air quality issues in the Southeastern United States. VISTAS is comprised of the following ten southeastern states: Alabama, Florida, Georgia, Kentucky, Mississippi, North Carolina, S outh Carolina, Tennessee, Virginia, and West Virginia. MACTEC, Inc., a contractor compa ny to VISTAS, developed the VISTAS portion of the area source emissions inventory.

## Emissions Preparations & Results Appendix D.2b -10 Regional Haze SIP for NC Class I Areas December 17, 2007 

# There are four major area source categories comprising of a number of individual area source types. Sections 2.1.1 through 2.1.4 address each of these categories and include a number of subsections that corresponds to the contributory area sources. The objective of each subsection is to describe each source category and the emission estimation and/or projection procedures.

1.3 NONROAD MOBILE SOURCE EMISSI ON ESTIMATION APPROACH
Non-highway mobile sources, sometimes referred to as off-road mobile, are those sources that can move but do not use the highway system. Off-road mobile sources are further divided into nonroad mobile, railroad locomotives, aircraft engines, and commercial marine vessels (CMV). The estimation of emissions from mobile sources, like area sources, involves multiplying an activity level by an emission factor.

The majority of the off-road mobile emissions were estimated by using the USEPA’s off-road mobile model NONROAD2005c. Direct emissions are generated with this model. For aircraft engine emissions, the Federal Aviation Admi nistration (FAA) Emissions and Dispersion Modeling System (EDMS) model was used. Aircraft operations were inputted into the model and the model predicts the engine emissions based on average landing and take-off practices for the aircraft type. For railroad locomotive emi ssions, emission factors were obtained from the Mobile Source Procedures document and the activity level was obtained from the various railroad companies.

1.4 EMISSION TABLES
Tables showing summaries of emissions at the county level for North Carolina as well as at the state level for all VISTAS states may be found in Appendix D.3. These are grouped for the point, non-road, area, and mobile categories. It should be noted that the area source emissions are reported at the “as inventoried” levels rather than the “as modeled” levels. For several dust categories (paved and unpaved roads plus others) a transport adjustment factor is applied for modeling because studies have shown that for these source categories significant dust settles back to ground within a few hundred meters of the point of emission.

## Emissions Preparations & Results Appendix D.2b -11 Regional Haze SIP for NC Class I Areas December 17, 2007 

# 2. DISCUSSION OF AREA SOURCE CATEGORIES

2.1 2002 NORTH CAROLINA-DEVELO PED AREA SOURCE INVENTORY
Area sources represent a collection of many small, unidentified points of air pollution emissions within a specified geographical area, emitting less than the minimum level prescribed for point sources. Because these sources are too small and/or too numerous to be surveyed and characterized individually, all area source activities are collectively estimated. The county is usually the geographic area for which emissions from area sources are compiled, primarily because counties are the smallest areas for which data used for estimating emissions is readily available. Emissions are calculated on an annual basis in tons per year.

2.1.1 GASOLINE DISTRIBUTION The area source emissions attributed to this category are associated with various operations related to gasoline and aircraft fuel handling a nd distribution. Since tank farms and bulk plants are specifically addressed in the point source inventory, the area source category is limited to fuel handling, storage, and distribution operations a ssociated with the service stations and in the refueling of aircrafts.

2.1.1.1 Gasoline Dispensing Facilities Since service stations are so numerous, they are collectively considered as an area source. The area source emissions that are derived for this subsection involve determining the estimated emissions that occur at each of the following operations: 1) losses during storage tank filling, 2) storage tank breathing and working losses, 3) spillage and 4) truck transit losses. The emissions from vehicle refueling are captured in the mobile source inventory in the emission factors produced by the USEPA MOBILE6.2 model and therefore are not estimated as part of the area source inventory.

As part of the air toxics program, Stage I controls for gasoline dispensing facilities was adopted by the State, effective May 1990 with final compliance by January 1, 1994. Stage I is the vapor recovery technology on the underground storage tanks and reduces the emissions during the tank filling operations at service stations.

The North Carolina Department of Agriculture, Standards Division is responsible for going to all gasoline dispensing facilities and testing the fuels to ensure that they meet the quality standards of the State. The NCDAQ has worked out an agreement with the Standards Division to also check for Stage I controls. A notice is sent to the NCDAQ for every facility checked by the

## Emissions Preparations & Results Appendix D.2b -12 Regional Haze SIP for NC Class I Areas December 17, 2007 

# Standards Division verifying if a facility has properly maintained control equipment. If a facility is not found to be properly maintaining the control equipment, then the NCDAQ sends a notice of violation informing the facility that the controls are required and gives the facility time to correct the violation before fines are assessed. From this information the rule effectiveness and rule penetration can be estimated. The rule effectiveness is the percentage of facilities with proper equipment maintenance and use and represents the actual degree of source compliance. Rule penetration is the percentage of facilities covered by the rule and thus require Stage I equipment. Control efficiency is the expected percent reduction from proper application of this control technology.

The volatile organic compounds (VOCs) emissi on factor for underground storage tank filling was calculated by using an equation from AP-42 , in Section 5.2, Transportation And Marketing Of Petroleum Liquids on page 5.2-4 (equation).

EF = 12.46 [SPM ] x [1-(RE x CE x RP)] [ T ]

where EF = emission factor in pounds of VOC per 1000 gallons S = Saturation factor P = True vapor pressure (in pounds per square inch area) M = Molecular weight of vapors (lb/lb-mole) T = Temperature of bulk liquid ( o 

# Rankin) RE = Rule Effectiveness CE = Control Efficiency RP = Rule Penetration

The saturation factor was obtained from AP-42 , Table 5.2-1 and the true vapor pressure and molecular weight of vapors were obtained from AP-42 , Table 7.1-2. For the temperature an average of the June, July and August average monthly temperature for 2002 was used. A worst case temperature estimate was used year round in calculating annual emissions. These temperatures were obtained from the North Ca rolina Climatological Data, a publication of the National Oceanic and Atmospheric Administration. All of the factors used to calculate the emission factor for Stage I, i.e. balanced submerged filling, are listed in Table 2.1.1.1-1.

Table 2.1.1.1-1 Factors Used For Calculating Emission Factor S P M T

1 6.49 67 537.6 o 

# R (77.6 o 

# F)

## Emissions Preparations & Results Appendix D.2b -13 Regional Haze SIP for NC Class I Areas December 17, 2007 

# EF = 12.46 ⎡ 1 x 6.49 x 67 ⎤ x [1 – ( .97 x .95 x .99)] ⎣ 537.6 ⎦ = 0.884 lb VOC/1000 gal. Gasoline

The emission factors for tank truck transit, breathing losses and spillage were obtained from the EIIP Tech Report , Chapter 11 Gasoline Marketing, Table 11.3-1 and are listed below in Table 2.1.1.1-2. The tank truck transit emission factor includes the emission rate for an empty tank plus a full tank and was adjusted by a factor of 1.25 as recommended by the EIIP Tech Report, pg. 11.5-3.

Table 2.1.1.1-2 Emission Factors For Gasoline Dispensing Underground Storage Tank Filling Tank Truck Transit Breathing Spillage

0.884 lb/1000gal 0.000075 lb/gal 0.001 lb/gal 0.00068 lb/gal

The activity data needed to calculate the emissions is number of gallons of fuel sold in each county per year. This was obtained from a repor t from the North Carolina Petroleum Marketers Association. A weighting factor was devi sed by producing the sum of county population (1000’s), county registered vehicles (1000’s), a nd county motor fuel outlets. The factors were summed for the 100 counties and a fractional part of the whole found for each county. This fraction was multiplied by the state total gallons of gasoline and diesel sold in 2002 to get an estimate of gallons of fuel per county.

Note that diesel fuel used is combined with gasoline for the sake of simplification. This will result in some overestimation of VOC emissions because the volatility of gasoline is higher than diesel fuel.

Annual VOC emissions for underground storage tank filling, tank truck transit, breathing losses and spillage were calculated. Underground storage tank annual VOC emissions for each county were calculated using the following equation.

EM = FC x (1/1000) x EF x (1 ton/2000 lbs.)
where EM = annual county VOC emissions in tons per year FC = county fuel consumption of gasoline and diesel in gallons/year EF = emission factor in pounds of VOC per 1000 gallons

## Emissions Preparations & Results Appendix D.2b -14 Regional Haze SIP for NC Class I Areas December 17, 2007 

# Tank truck transit, breathing losses, and spillage annual VOC emissions for each county were calculated individually, using the following equation.

EM = FC x EF x (1 ton/2000 lbs.)
where EM = annual county VOC emissions in tons per year for tank truck transit, breathing losses, or spillage FC = county fuel consumption of gasoline and diesel in gallons/year EF = emission factor in pounds of VOC per gallon for tank truck transit, breathing losses, or spillage
2.1.1.2 Aircraft Refueling Like vehicle refueling, aircraft refueling resu lts in VOC emissions from displacement of the vapor laden air in the aircraft’s fuel tank. This source category is generally estimated only for large commercial airports. There are a few small commuter airports in the State; however, the amount of the emissions from these are typically negligible.

The emissions from aircraft refueling were dete rmined by using the number of gallons of fuel supplied to the airports and multiplying it by the appropriate emission factor. The businesses that supply the fuel to the airports were contacted to determine the amount and type of fuel supplied to each airport during 2002. The information obtained was for the two fuel types supplied, Jet A Kerosene and Aviation Gasoline.

The emission factors used are 11.38 lb VOC/1000 gallons of aviation gasoline and 0.065 lb VOC/1000 gallons of Jet A kerosene.

The annual emissions for the base year were calculated using equation 2.1.1.2-1.

EM i 

# = Gallons/year x EF i 

# ___ (2000 lbs/ton) 2.1.1.2-1

where EM i 

# = emissions for source category (i) EF i 

# = emission factor for source category (i)

2.1.2 STATIONARY SOURCE SOLVENT EVAPORATION There are eleven subcategories that involve stationary source solvent evaporative emissions. They include: dry cleaning, graphic arts, solven t cleaning, automotive refinishing, architectural

## Emissions Preparations & Results Appendix D.2b -15 Regional Haze SIP for NC Class I Areas December 17, 2007 

# coatings, traffic markings, industrial surf ace coating, asphalt paving, roofing operations, pesticide application, and consumer/commercial solvent use. The methodology used to calculate the emissions from these sources are described in detail in each subsection.

2.1.2.1 Dry Cleaning The VOC emissions from dry cleaning vary with the type of process and the solvent used. For the most part, dry cleaners (coin-operated and conventional commercial) are small business entities. As a result of their size, dry cleaning emissions are typically not captured as point sources. However, dry cleaning operations can be a significant emission source for VOC emissions, when taken collectively.

The emissions from dry cleaners are estimated by multiplying the number of employees at dry cleaners by a national per-employee emission factor, 1800 lbs. of VOC/employee/year, found in the EIIP Tech. Report . The guidance also stated that the number of employees can be found in the County Business Patterns for SIC code 7215 (coin-operated) and 7216 (commercial). In 1997, the SIC code system was replaced with the NAICS. Thus, the number of employees was obtained for NAICS codes 812310 (coin-opera ted) and 812320 (commercial). The NAICS employment numbers were previously processed to exclude any facilities with 100 or more employees, which were deemed to be point sources. According to the SIC to NAICS crosswalk, 80% of employment for NAICS 812320 represents the number of employees for commercial dry cleaners (SIC 7216).

The emissions for 2002 were calculated using equation 2.1.2.1-1.

EM = Employees/Year x EF (2000 lb/tons) 2.1.2.1-1

where EM = emissions for source category tons/day EF = emission factor for source category, 1800 lbs VOC/employee/yr

2.1.2.2 Graphic Arts/Printing Graphic arts include operations that are involve d in printing of newspapers, magazines, books, and other printed materials, which can be divided into several subsets based upon printing technology. Over the last decade ink-jet and offset lithography have emerged as the dominant technologies. The use of oils as ink solvents and the reduction of alcohols in the fountain solution and in the cleanup solutions have resulted in notable reductions in emissions for offset lithography. Ink-jet printing results in essentially no VOC emissions.

## Emissions Preparations & Results Appendix D.2b -16 Regional Haze SIP for NC Class I Areas December 17, 2007 

# A number of establishments that generate emissions in this source category are in-house graphic arts operations at plants that are in non-printing industries. Therefore, an employee per SIC code emission factor is not very reliable. The per- capita emission factor of 1.3 lbs VOC/person/year provided by the EIIP Tech. Report was used to calculate the VOC emissions. This emission factor estimates the emissions from facilities less than 100 tons VOC/year. It assumes that facilities greater than 100 tons VOC/year will be in the point source inventory. The population used to calculate the base year emissions was obtained from the North Carolina Office of State Budget and Management (OSBM).

The annual emissions for the base year were calculated using equation 2.1.2.2-1.

EM a 

# = ((EF)*(Population 2002 

# )*(1 ton/2000 lb)) 2.1.2.2-1

where EM = emissions for source category for county (a) ton/yr EF = emission factor for source category, 1.3 lbs VOC/person/yr

2.1.2.3 Solvent Cleaning and Degreasing Solvent cleaning operations are integral to many businesses and industries, and are conducted for the purpose of removing grease, oils, waxes, carbon deposits, etc. from metals, plastic, or glass surfaces. Solvent cleaning is usually performed prior to painting, plating, inspection, repair, assembly, etc. The solvents used in the cleaning operations can be either in a liquid or vapor phase. Generally, these solvents have high vapor pressures and therefore emit VOC emissions.

There are two basic types of solvent cleaning techniques, cold cleaning and vapor cleaning. Cold cleaning machines use solvents in the liquid phase to clean and remove foreign material such as oils and grease from the surface of materials. These machines are batch loaded, and cleaning operations include spraying/flushing solv ent or parts agitation, wipe cleaning, brushing, and immersion.

The vapor cleaning technique can be further divided into open top degreasing and in-line cleaning. The open top degreasing machines are tanks designed to generate and contain solvent vapor. The tank is equipped with a heating system that boils the liquid solvent. As the solvent boils, dense solvent vapors rise and displace the air in the tank. Coolant is circulated in condensing coils on the top of the tank to create a controlled vapor zone within the tank. Condensing solvent vapors dissolve the contaminants on the surface of the workload and flush both the dissolved and undissolved contaminants from the workload.

## Emissions Preparations & Results Appendix D.2b -17 Regional Haze SIP for NC Class I Areas December 17, 2007 

# In-line cleaning machines employ automated loading on a continuous basis. These machines are often custom made for large-scale operations. A continuous or multiple-batch loading systemgreatly reduces or even eliminates the manual parts handling associated with batch cleaning. Inline cleaning machines are enclosed to prevent solvent losses; however, entry and exit openings cannot be sealed.

The VOC emissions for this category are estimated by using the per employee factors (from the EIIP Tech. Report , Chapter 6, Table 6.5-2) listed in Table 2.1.2.3-1 below:

Table 2.1.2.3-1 Emission Factors Cleaning & Degreasing Source Category lb VOC/employee/yr Electronic and Other Elec: Open Top Degreasing 29 Miscellaneous Manufacturing: Open Top Degreasing 9.8 Miscellaneous Manufacturing: Cold Cleaning 24 Auto Repair Services: Cold Cleaning 270

Employment data was derived from the 2002 County Business Patterns provided by the U. S. Census Bureau. For each of these categories, employment in a number of SIC groups is needed. These employment numbers were generated from the NAICS employment numbers for each county and summed as needed. See SIC Codes from NAICS Codes for Employment Based Categories in Section 9.1 for the full listing of NAICS and SIC for each source category. Fractional employee numbers are a result of the NAICS to SIC conversion process.

The annual emissions for the base year were calculated using equation 2.1.2.3-1.

EM = (Employees) x EF (2000 lb/tons) 2.1.2.3-1

where EM = emissions for source category, tons per year EF = emission factor for source category

2.1.2.4 Auto Body Refinishing Auto body refinishing operations consist of: vehi cle preparation, primer application, topcoat application, and spray equipment cleaning. These operations result in significant VOC

## Emissions Preparations & Results Appendix D.2b -18 Regional Haze SIP for NC Class I Areas December 17, 2007 

# emissions. The solvent is typically 100% volatile and can constitute up to 6.5 pounds of VOC per gallon of cleaner or paint.

The EIIP methodology for estimating emissions from this source category recommends apportioning a national VOC emission estimate to the county level by the number of employees reported for NAISC code 811121. The national estimate of 79,429.59 tons of VOC per year was based on 1997 data. In order to estimate the emissions for 2002, the national VOC estimate provided by the EIIP Tech. Report was divided by the 1997 national employment data to create a per employee emission factor.

This emission factor was used with the 2002 employment data to estimate emissions from auto body refinishing. The employment data was obtai ned from the 2002 County Business Patterns.

The emissions for 2002 were calculated using equation 2.1.2.4-1.

EM = Employees x EF 2.1.2.4-1

where EM = emissions for source category EF = emission factor for source category, 0.387 tons VOC/employee/yr

2.1.2.5 Architectural Coatings This category includes the application of paint, primer, varnish or lacquer to architectural surfaces, and the use of solvents as thinners and for cleanup.

The VOC emissions for this source category were estimated by multiplying county population data by a usage factor for either water or solvent based coatings, and an emissions factor for either water or solvent based coatings. This method entails gathering national architectural paint usage from the County Business industrial report MA325F and generating per capita usage factors. It is important to be able to differentiate between the water based usage from the solvent based usage since the emission factor for solvent based paints is over 5 times higher than the factor for water based paints.

Emissions Factor: Water based = 0.74 lb VOC/gallon; Solvent Based= 3.87 lb VOC/gallon

VOC ai 

# = (POP ai 

# *UF b 

# *EF b 

# )/*(2000lbs/ton) -- ton/year

## Emissions Preparations & Results Appendix D.2b -19 Regional Haze SIP for NC Class I Areas December 17, 2007 

# Where: VOC a 

# = VOC emissions for county (a) POP a 

# = Population for county (a) EF b 

# = emission factor for paint type (b) UF b 

# = Usage factor for paint type (b)

The usage factor is found by dividing the national total architectural surface coating quantities for either solvent or water-based coatings by the U.S. population for that year. For 2002, the usage factor for each paint type is estimated below:

UF solvent: (127,703,000 gal/yr of solvent based) / (287,973,924) = 0.443 gal/person/yr UF water: (589,527,000 gal/yr of water based) / (287,973,924) = 2.047 gal/person/yr

2.1.2.6 Traffic Markings The paint used in traffic markings operations (the painting of center lines, shoulders, etc.) emits VOC emissions during the drying process. The exte nt of emissions is largely a function of the paint being solvent or water based. The North Carolina Department of Transportation (NCDOT) utilizes three general types of paint, which can be classified as water based paint, epoxy paint containing organic solvents, and thermoplastic paint. The use of thermoplastic paint results in negligible VOC emissions and therefore is not included in the emissions inventory.

Although the NCDOT utilizes both water and solvent based paints, there is uncertainty with respect to what percentage of the paint used is organic solvent based. To avoid under estimating the emissions from this source category, it is assumed that all paint, excluding thermoplastic, is organic solvent based.

The NCDOT reported that 854,215 gallons of paint were used statewide in 2002. The gallons of paint by county were apportioned by number of lane miles in the county divided by the state total (equation 2.1.2.6-1) and the estimated gallons use d. The emission factors were obtained from the EIIP Tech. Report , Table-14.4-1 and Table-14.5-2, which ga ve emission factors as a function of gallons of paint (3.64 lb VOC/gal.).

Gallons Paint County 

# = (Gallons Paint State 

# /yr) x (# Lane Miles) County 

# 2.1.2.6-1 (# Lane Miles) State



# The emissions for 2002 were calculated using equation 2.1.2.6-2.

EM = Gallons/year Paint x EF 2.1.2.6-2

## Emissions Preparations & Results Appendix D.2b -20 Regional Haze SIP for NC Class I Areas December 17, 2007 

# (2000 lb/ton)

where EM = emissions for source category EF = emission factor for source category 2.1.2.7 Industrial Surface Coating Surface coating operations involve applying a thin layer of coating (e.g. paint, lacquer, enamel, varnish, etc.) to the surface of an object for decorative or protective purposes. The coating products, which are solvent based, emit VOC emissions as the result of solvent evaporation during the drying or curing process.

Ideally, the VOC emissions from industrial surface coating activities should be captured as point sources. From a practical standpoint, this is not always accomplished. For example, three of the industrial surface coating subcategories, namely other product coatings, high-performance maintenance, and other special purpose coatings, only utilized per capita emission factors and have no NAICS associated with them. The emission factors, obtained from the EIIP Tech. Report , Table 8.5-2, for these surface coating subcategories are listed in the Table 2.1.2.7-1 below.

Table 2.1.2.7-1 Per Capita Emission Factors For Industrial Surface Coating Subcategory Per Capita Factor (lb/yr/person) Other product coatings High-performance maintenance. Other special purpose coatings 0.6 0.8 0.8

The emissions for the remaining industrial surface coating subcategories were estimated using per employee emission factors. These emission factors were obtained from the EIIP Tech. Report , Table 8.5-1 and are listed below in Table 2.1.2.7-2.

Table 2.1.2.7-2 Per Employee Emission Factors for Industrial Surface Coating Subcategory Per Employee Factor (lb VOC/employee/yr) Furniture & Fixtures 944 Metal Containers 6,029 Automobile (new) 794 Machinery & Equipment 77 Appliances 463 Other Transportation Equipment 35

## Emissions Preparations & Results Appendix D.2b -21 Regional Haze SIP for NC Class I Areas December 17, 2007 

# Sheet, strip & Coil 2,877 Factory Finished Wood 131 Electrical Insulation 290 Marine Coatings 308 The EIIP Tech. Report also listed SIC codes for these industrial surface coating subcategories. As stated earlier, the SIC codes were replaced in 1997 with NAICS. The employment data was estimated using the method outlined in Section 2.1.2.1.

The annual emissions for population and employment based emission factors were calculated using equations 2.1.2.7-1 and 2.1.2.7-2, respectively.

EM = Population x EF 2.1.2.7-1 (2000 lb/ton)

EM = Employees x EF 2.1.2.7-2 (2000 lb/ton)

where EM = emissions for source category EF = emission factor for source category

2.1.2.8 Asphalt Paving Two types of asphalt paving are used for road paving and repair; emulsified asphalt and cutback asphalt. Emulsified asphalt is a type of liquefied road surfacing material made from a blend of water with an emulsifier. Cutback asphalt is a type of liquefied road surface that is prepared by blending or "cutting back" asphalt cement with various kinds of petroleum distillates. VOC emissions occur as the asphalt cures.

Hot-mix is composed of high molecular weight organics with minimal vapor pressures; consequently, VOC emissions are negligible. The use of emulsified asphalt does result in VOC emissions; but the emissions are significantly less th an cutback. New formulations of emulsified asphalt, such as cationic, continue to result in reduced emissions. The use of emulsified asphalt is primarily for tack coating, which is a surface preparation for the hot-mix layer. The tonnage of hot-mix asphalt is accounted for by the NCDOT di stricts and not on a county basis. District tonnage was allocated on a county basis by apportioning county paved mileage as reported in the NCDOT 2000 Highway Summary Report. However, the amount of emulsified asphalt used is

## Emissions Preparations & Results Appendix D.2b -22 Regional Haze SIP for NC Class I Areas December 17, 2007 

# not tracked by the NCDOT in any useable way. As a consequence, the NCDOT provided the following methodology to predict emulsified usage:

## Emissions Preparations & Results Appendix D.2b -23 Regional Haze SIP for NC Class I Areas December 17, 2007 

# Square Yd. of hot-mix = (Tons of Hot-mix) x (2000 lbs./Ton) 2.1.2.8-1 (220 lbs/ Square Yd. of Hot-mix)

Gallons of Emulsified asphalt = (Sq. Yd. of hot-mix) x (0.08 gal./Sq. Yd. of hot-mix) 

# 2.1.2.8-2

The VOC emissions were calculated using the em issions factor for emulsified asphalt (9.2 lb VOC/barrel) and the number of gallons of emulsified asphalt per barrel (42 gal./barrel) from Table 17.5-2 of the EIIP Tech. Report

.
The emissions for the base year were calculated using equation 2.1.2.8-3.

EM = (gallons/year Emulsified Asphalt) x EF (42 gal/barrel) x (2000 lb/tons) 2.1.2.8-3

where EM = emissions for source category EF = emission factor for source category

Cutback asphalt emissions are included in the aspha lt paving category. Since the assembly of the latest VISTAS 2002 inventory, it was found that the NCDOT specification for asphalt in 2002 was hot mix and emulsified asphalt with hot mix but not cutback asphalt. Surrounding states have precluded the use of cut back by statutory provisions; which has driven asphalt manufactures to discontinue cutback production throughout the region. The absence of the use of cutback has resulted in substantial reductions in emissions from asphalt paving operations in North Carolina. Although cutback asphalt emissions are included in the VISTAS 2002 inventory, the 93.04 tons of VOC per year represents a relatively small amount and does not significantly affect the accuracy of the inventory.

2.1.2.9 Roofing Operations This category covers the installation and repair of asphalt roofs on commercial and industrial buildings. This category includes only hot-applie d asphalt roofing, for which the only significant emissions source is the kettle used to heat the asphalt. The amount of asphalt roofing activity is estimated by summing the number of felt, cap, and flashing squares used in North Carolina during the year 2000. This information was ascertained from the Asphalt Roofing Manufacturing Association. The amount of asphalt used is given by the equation 2.1.2.9-1, which uses the default value of 20 lbs. of asphalt / square found in the EIIP Tech. Report . The emissions by county, shown in equation 2.1.2.9-2, were apportioned by roofing establishments in the county divided by the state total, using the number of establishments from NAISC code

## Emissions Preparations & Results Appendix D.2b -24 Regional Haze SIP for NC Class I Areas December 17, 2007 

# 23561 from the 2000 County Business Patterns. The 2000 County Business Patterns was the latest available data at the time of the inventory development.

Asphalt (Ton/yr) = (# squares) x (20 lbs. of asphalt/square) 2.1.2.9-1 (2000 lbs./ton)

Asphalt County 

# = (Tons/yr Asphalt State 

# ) x (# Roofing Establishments) County 

# 2.1.2.9-2 (# Roofing Establishments) State



# The EIIP Tech. Report reported the emissions factor as 6.2 lbs. VOC/ton asphalt for roofing operations.

The emissions for the base year inventory were calculated using equation 2.1.2.9-3.

EM = (tons/yr Asphalt) x EF (2000 lb/tons) 2.1.2.9-3

where EM = emissions for source category EF = emission factor for source category

2.1.2.10 Pesticide Application Pesticides broadly include any substance used to kill or retard the growth of insects, rodents, fungi, weeds, or microorganisms. Formulations of organic pesticides are commonly made by combining synthetic materials with various petr oleum products. The petroleum products, or inert ingredients, act as a carrier of the active component and usually evaporate into the atmosphere.

Agricultural Pesticides Agricultural pesticides are applied in various manners, which directly affect the possible emissions associated with the application, regard less of the amount of solvent contained in the pesticide. There are basically three types of pesticide/herbicide application methods. One is the "incorporated" type, in which the product is applied and immediately incorporated into the soil. It is expected that little if any evaporation of solv ent occur in this type of application. The next type, "pre-emergence", is where the product is put on the ground immediately after the crop is planted. This provides a protective layer. Some evaporation of solvent would be expected with this type of application. The largest emissions would occur from "over the top" application of pesticides. These pesticides are sprayed directly on the foliage to kill weeds or insects. This application would provide an opportunity for a great deal of solvent to evaporate.

## Emissions Preparations & Results Appendix D.2b -25 Regional Haze SIP for NC Class I Areas December 17, 2007 

# The overall pesticide usage associated with agricultural crop production continues to slowly decrease in North Carolina driven by conservative pest management practices and the cost of pesticides as reported by the North Carolina Cooperative Extension office. The large majority of pesticide usage is confined to the production of tobacco and cotton crops. Because of the small crop size and high cash value, significant tobacco acreage is found in North Carolina.

The planted crop acreage from the North Carolina Department of Agriculture, Agricultural Statistic Division and crop profile reports prep ared by the North Carolina Cooperative Extension office, and other university extension services, for the US Department of Agriculture Pest Management Center were used to estimate agricultural pesticide usage. Crop acreage from the North Carolina Agricultural Statistic Division wa s obtained from http://www.ncagr.com/stats/. Crop profile reports conducted by NCSU are based on surveys; where participation is reported to be as high as 90 percent for the more important cash crops. Crop profile reports for grains and soybeans do not exist for North Carolina; therefore, data for these crops were obtained from other state profiles and from discussions with representatives of the North Carolina Cooperative Extension office.

The individual crop profiles outline the current agricultural pesticide practices, i.e. the pesticide agents (insecticides, herbicides, fungicides), the percentage of acres treated, and the pounds of active ingredient pesticide applied per acre. The crop profiles often reports the application of the active ingredient (pounds of active ingredient per acre) as a range of values. For the worst-case scenario, the highest reported value was used. The number of applications of a single pesticide was usually one per year for all pesticides. The few exceptions to one application are more than accounted for by the conservative practice of using the highest value of application rate.

The pounds of active ingredients for each crop were calculated by using equation 2.1.2.10-1 and an example calculation for soybeans follows. Table 2.1.2.10-1 presents the pesticides associated with a particular crop, the % of treated acres, and the lbs. of active pesticide ingredient per year.

(lbs. AI/acre) CROP 

# = ∑ (% acres treated) x (lb AI/acre) PESTICIDE 

# 2.1.2.10-1

where AI = active ingredient.

## Emissions Preparations & Results Appendix D.2b -26 Regional Haze SIP for NC Class I Areas December 17, 2007 

# For soybeans, the pounds of active ingredients for the crop is:

Pesticide % Acres Treated Lb AI/acre/yr Paraquat 20 0.47 Glyphosate 10 4 Sulfusate 5 4 Carbaryl 10 1.5

(lbs. AI/acre) SOYBEAN 

# =(0.20 x 0.47) + (0.10 x 4) + (0.05 x 4) + (0.10 x 1.5) =0.844 lbs. AI/acre/yr for soybeans

## Emissions Preparations & Results Appendix D.2b -27 Regional Haze SIP for NC Class I Areas December 17, 2007 

# Table 2.1.2.10-1 Agriculture Pesticides Application Rates
Crop/Agent % Acres Treated Lbs. active ingredient/Acre 

## Crop/Agent % Acres Treated Lbs. active ingredient/Acre 

## Soybeans Corn Silage Paraquat 20 0.47 Terbufos 35 1 Glyphosate 10 4 Chloropyrifus 10 1 Sulfusate 5 4 Phorate 10 1 Carbaryl 10 1.5 Ethoprop 5 1 Cotton Carbofuran 5 1 Tribufos 100 0.75 M Parathion 50 0.75 Aldicarb 91 0.75 Thiocarb 90 0.6 Prourgite 0.45 0.73 Methomyl 50 0.45 Dicofol 0.55 1.6 Corn Grain Dicrotophos 0.45 0.2 Terbufos 35 1 Acephate 2.1 0.5 Chloropyrifus 10 1 M-Parathion 1 0.5 Phorate 10 1 L-cyhalothrin 99 0.145 Ethoprop 5 1 Thiocarb 40 0.75 Carbofuran 5 1 Aldicarb 50 0.725 M Parathion 50 0.75 Tobacco Thiocarb 90 0.6 Acephate 70 1.5 Methomyl 50 0.45 Spinosad 13 0.05 Oats Methomyl 11 0.45 M Parathion 5 0.5 Endosulfan 7 1 Wheat Imidacoloprid 62 0.03 M Parathion 5 0.5 Chloropicrin 41 79.8 Sweet Potatoes Dichloropropene 35 89.5 Napropamide 50 1.5 Clomazone 75 1 Clomazone 25 0.87 Metalaxyl 49 0.76 Fluazifop 20 0.17 Barley Carbaryl 25 0.67 M Parathion 0.8 0.5 Peanuts Irish Potatoes Chlorpyrifus 60 1 Phorate 3 40 1.20 Disulfoton 90 0.75 Glyphosate 6 5 Esfenvalerate 25 0.03 Metolachor 8 2 Folicur 1 51 0.51 Metribuzin 55 0.5 Vernolate 45 2.5 Sorghum Dichloropropene 0.16 80 MethyParathion 1 0.75 Chlorpyrifus 1 1 Carbaryl 1 2

## Emissions Preparations & Results Appendix D.2b -28 Regional Haze SIP for NC Class I Areas December 17, 2007 

# The emission factors for each crop were calculated utilizing information from the EIIP Tech. Report , p 9.5-4, which relates active ingredients to VOC emissions. According to the EIIP Tech. Report , for every pound of active ingredient there are 2.45 pounds of VOC, of this 90% is evaporated. The emission factors for each crop were calculated using Equation 4.2.10-2, with an example calculation for soybean following.

EF CROP 

# = (lb AI CROP 

# /acre/yr) x (2.45 lb. VOC/l b. of AI) x (0.90) 2.1.2.10-2

Where EF CROP 

# = Emission factor in lbs. VOC/active ingredient for each crop/year AI CROP 

# = Active ingredient for each crop

For soybeans the emission factor is: Lbs. AI/acre for soybean = 0.844 lbs. AI/acre/year

EF SOYBEAN 

# = (0.844 lb active ingredient/acre/yr) x (2.45 lb VOC/active ingredient) x (0.90) = 1.861 lbs. VOC/acre/year

An exception to the above calculation was for the usage of the pesticides: chloropicrin and 1,3 dichloropropene. These fumigants are widely us ed for treating tobacco beds for nematodes and constitute a major portion of the pesticide inventory. They have a moderate vapor pressure of 18.3 and 34 millimeters of mercury (at 77 ° F), respectively, and their formulation is approximately 96% to 98% of the active ingredient. In light of these properties, the VOC emissions are assumed to be equal to the application per acre, which are 79 pounds/acre/year for chloropicrin and 89.5 pounds/acre/year for 1,3 dichloropropene. Table 2.1.2.10-2 list the pounds of active ingredients per acre and the calculated emission factor for each crop.

## Emissions Preparations & Results Appendix D.2b -29 Regional Haze SIP for NC Class I Areas December 17, 2007 

# Table 2.1.2.10-2 Emission Factors by Crop Type
Crop Lbs. Active Ingredients/acre/year Lbs. VOC/Acre/year Soybeans 0.844 1.861 Cotton 2.267 4.999 Barley 0.004 0.009 Corn – Silage 1.79 3.947 Corn – Grain 1.79 3.947 Wheat 0.025 0.055 Oats 0.025 0.055 Sweet Potato 1.169 2.578 Tobacco - Non-fumigant 2.317 5.109 - Fumigant 64.043 64.043 Total Tobacco 69.152 Peanuts - Non-fumigant 2.9175 6.433 - Fumigant 0.128 0.282 Total Peanuts 6.715 Irish Potatoes 1.9350 4.267 Sorghum 0.0375 0.083

The emissions for 2002 were calculated using equation 2.1.2.10-3.

EM a 

# = ( ∑ (CROP) a 

# x EF CROP 

# ) (2000 lb/tons) 2.1.2.10-3

where EM a 

# = emissions for source category in county (a) CROP = acres of specific crop in county (a) EF CROP 

# = emission factor for specific crop

Nonagricultural Pesticide Nonagricultural pesticide applications are consid ered as part of the commercial/consumer solvent use emission factor and no longer a separate subcategory. Please refer to the next section.

## Emissions Preparations & Results Appendix D.2b -30 Regional Haze SIP for NC Class I Areas December 17, 2007 

# 2.1.2.11 Commercial/Consumer Solvent Use This category includes only non-industrial solvents that are used in commercial or consumer applications. The solvent containing products consist of a diverse grouping, e.g. personal care products, household products, automotive aftermarket products, adhesives and sealants, pesticides, some coatings, and other commercial and consumer products that may emit VOC and ammonia (NH 3 

# ) emissions.

There are seven categories. They are named and their emission factors listed in Table 2.1.2.11-1 below.

Table 2.1.2.11-1 Misc. Non-Industrial Co nsumer-Commercial Emission Factors Subcategory lb VOC/yr/person. lb NH 3 

# /yr/person. All Coatings and Related Products 0.95 - All FIFRA Related Products 1.78 - Miscellaneous Products (Not Otherwise Covered) 0.07 -

Personal Care Products 2.32 - Household Products 0.079 0.031 Automotive Aftermarket Products 1.36 - Adhesives and Sealants 0.57 -

VOC emissions for this category is estimated by using nationally based per capita emissions factors. The county population values are used to estimate the emissions from this source category.

The emissions for the base year inventory were calculated using equation 2.1.2.11-1.

EM = (Population 2002 

# ) x EF (2000 lb/tons) 2.1.2.11-1

where EM = emissions for source category, tons per year EF = emission factor for source category

## Emissions Preparations & Results Appendix D.2b -31 Regional Haze SIP for NC Class I Areas December 17, 2007 

# 2.1.3 BIOPROCESS EMISSION SOURCES Bioprocess emission sources include those sour ces whose emissions result from biological processes (e.g., fermentations). Source categories include bakeries, breweries, wineries and distilleries.

2.1.3.1 Bakeries Ethanol, a VOC, is a by-product of fermentation of bread dough. The ethanol emissions from large commercial bakeries are accounted for as point sources; however, ethanol emissions occur from grocery store bakery departments and small business bakeries not accounted for under the point source inventory.

The EIIP Tech. Report prescribes accounting for these emissions by the use of a per capita consumption factor of 70 pounds of bread per pe rson per year and an emission factor of 0.5 pounds of VOC per 1000 pounds of baked bread. The county populations obtained from the North Carolina Office of State Budget and Management were used to estimate the emissions from this source category.

The emissions for the base year inventory were calculated using equation 2.1.3.1-1.

EM = (Population) b 

# x CF x EF (2000 lb/tons) 2.1.3.1-1

where EM = emissions for source category Population b 

# = Population in base year CF = Consumption factor, 70 lb bread/person/year EF = emission factor for source category, 0.5 lb VOC/1000 lb bread baked

2.1.4 OTHER MAN MADE AREA SOURCES Other man made area sources agricultural burning, structure fires, and orchard heaters. The methodology used to calculate the emissions from these sources are described in detail in each subsection.

2.1.4.1 Structure Fires Burning fires can produce short term emissions of organic compounds and nitrogen oxides (NOx). The U.S. Fire Administration (USFA) of the Department of Homeland Security maintains statistics on the number of fires per county. The number of fires per county for 2002 was derived from 2001 and 2002 population statistics and 2001 USFA fire statistics. The USFA

## Emissions Preparations & Results Appendix D.2b -32 Regional Haze SIP for NC Class I Areas December 17, 2007 

# fire statistics were obtained from the USFA we bsite at http://www.usfa.fema.gov/safety/. As 2002 fire statistics were not available, a fires per person factor for 2001 was calculated and found to be equal to 0.00184 fires/person/year. The 2001 county population values were obtained from the North Carolina State Demographics website at http://demog.state.nc.us/. The 2001 population values were the latest data available. The 0.00184 fires per person per year was applied to the 2002 population for each county to determine the number of fires in each county for 2002.

The emission factors and fuel loading factor s were obtained from the EIIP Tech. Report , Table 18.4-1 and Table 18.4-2, respectively. The emission factors are 11 pounds of VOC per ton burned, 1.4 pounds of NOx per ton burned and 60 pounds of CO per ton burned. The loading factor is 1.15 tons of material burned per structural fire.

The emissions for the base year 2002 invent ory were calculated using Equation 2.1.4.2-1.

EM P 

# = (2002 County population) x (FPP) x (CF) x (EF P 

# ) (2000 lb/tons) 2.1.4.2-1

where EM P 

# = emissions for structure fires for pollutant (P) FPP = fires per person in 2001, 0.00184 fires/person/year CF = Conversion factor, 1.15 tons burned/structure fire EF P 

# = emission factor for pollutant (P)

2.1.4.2 Charbroiling The commercial charbroiling of ground beef emits VOC emissions. According to the methodology in the EIIP Tech. Report , county Health Departments should be able to provide the number of restaurants in a county as well as the percentage of those restaurants that charbroil meat. The NCDAQ was able to ascertain the number of restaurants in each county in 2002 from the North Carolina Division of Environmental Services, Inspection, Statistics, and Fee Branch. To determine the percentage of charbroiling restaurants, the county Health Departments of several counties were surveyed.

According to the EIIP Tech. Report , the average throughput of meat per restaurant with a charbroiler is 1160 pounds per week and the emissions factor is 3.94 pounds of VOC per 1000 pounds of meat.

The emissions for the base year inventory were calculated using Equations 2.1.4.3-1.

## Emissions Preparations & Results Appendix D.2b -33 Regional Haze SIP for NC Class I Areas December 17, 2007 

# EM a 

# = (# Restaurants) x (% Charbroiling) x (CF) x (EF) (2000 lb/tons) x (1 yr/52 wks) 2.1.4.3-1

where EM a 

# = emissions for source category in county (a) ton/yr CF = conversion factor, 1160 lb meat charbroiled/week EF = emission factor, 3.94 lb VOC/1000 lb meat charbroiled

2.1.4.3 Open Burning – Municipal Solid Waste and Yard Trimmings This Subsection describes the combined emission inventory methodology for source classification code (SCC) 2610030000 Residentia l Open Burning – Household and SCC 2610000100 Open Burning – Yard Trimmings. Open burning is treated as a means of waste disposal in rural areas. Materials burned generally include agricultural refuse, landscaping refuse, or scrap wood. Local authorities could not provide assistance with estimating the tons of refuse burned or the amount burned. According to local authorities, burning permits are issued year round without requiring a notation for the amount burned.

It was assumed that all municipal solid waste (MSW) and yard trimmings, were burned in the open for solid waste generated outside the municipal corporate limits. According to the EIIP Tech. Report , Table 16.5-1, it is estimated that 3.77 pounds of MSW is generated per person per day and 0.64 pounds of yard trimmings are generated per person per day. Since it is illegal to burn within the corporate limits, the rural populati on was estimated by using the same percentage of rural population in each county as what was reported in the 2000 census. The 2000 total and rural populations for each county was obtained from the North Carolina Office of State Budget and Management, State Data Center. The 2000 total and rural populations was the latest data available.

VOC, NOx, carbon monoxide (CO), sulfur dioxide (SO 2 

# ), and NH 3 

# emission factors for open burning of MSW were obtained from EIIP Tech. Report , Table 16.4-1, Open Burning of Municipal Refuse. The emission factors are 6.676 pounds VOC per ton MSW burned, 6 pounds NOx per ton MSW burned, 85 pounds CO per ton MSW burned, 1 pounds SO 2 

# per ton MSW burned, and 6.0 E-07 pounds NH 3 

# per ton MSW burned. The rural percent of the populations for the statewide counties were obtained from the 2000 census data. Since burning permits are issued year round, the activity days per year was 365. These values were used to calculate the tons per year emissions for the base year. The emissions from the burning of MSW for the base year 2002 inventory were calculated using e quation 2.1.4.4-1. The emissions from the burning of yard trimmings for the base year 2002 i nventory were calculated using equation 2.1.4.4-2.

## Emissions Preparations & Results Appendix D.2b -34 Regional Haze SIP for NC Class I Areas December 17, 2007 

# EM P,MSW 

# = (Rural Population in 2002) x (CF MSW 

# ) x (EF P 

# ) x (365 days/yr) (2000 lb/tons) 2.1.4.4-1

EM P,YT 

# = (Rural Population in 2002) x (CF YT 

# ) x (EF P 

# ) x (365 days/yr) (2000 lb/tons) 2.1.4.4-2

where EM P,MSW 

# = emissions from burning MSW for pollutant (P) EM P,YT 

# = emissions from burning yard trimmings for pollutant (P) CF MSW 

# = conversion factor, 3.77 lb MSW/person/day = 0.001885 ton MSW/person/day CF YT 

# = conversion factor, 0.64 lb yard trimmings/person/day = 0.00032 ton yard trimmings/person/day EF P 

# = emission factor for pollutant (P)

2.1.4.4 Small Stationary Source Fossil Fuel Use In general, fossil fuels are burned for space and hot water heating. This source category covers VOC, NOx and CO emissions from natural gas (NG) and liquid petroleum gas (LPG), oil, coal, and wood combustion in the residential, commercial/institutional (called commercial), and industrial sectors.

The “demand for energy” for these fuel types is known as fuel usage. Fuel usage data for North Carolina was taken from NC Energy Outlook 2003 by Global Insight, Inc for the base year 2002. The following table shows the data used.

Table 2.1.4.4-1 Fuel Use in North Carolina 2002 Fuel Units Residential Commercial Industrial NG 10 6 

# ft 3 

# 64,014 40,580 95,718 LPG gallons 282,775,596 47,960,199 198,606,965 Oil gallons 215,804,019 113,088,933 343,414,390 Coal tons 46,872 85,735 0 Wood tons 1,625,111 164,327 8,583,778

Emission factors used are shown in Table 2.1.4.4-2 below.

## Emissions Preparations & Results Appendix D.2b -35 Regional Haze SIP for NC Class I Areas December 17, 2007 

# Table 2.1.4.4-2 Combustion Emission FactorsNH32000.00121.80.4900.0080.030.0863.200.0080.030.086PM2.57.60.009060.0014013.807.60.0009750.0027624.759885.477.60.001250.0039694.759885.47PM107.60.0090606.234.67.60.009060.0044912.95756.487.60.0011250.00576312.95756.48SO20.60.0000540.0042631.620.40.60.00005130.00461638.760.375480.60.00005130.004627538.760.37548CO400.0020.005275252.6840.0020.0057.337.243.250.00340.0050.57.2NOx940.0140.0189.12.6167.50.01450.03715.83.304224163.330.020.03914.93.304224VOC5.50.00030.0007130.07229.05.50.000350.0007350.070.2553264.960.000350.000240.070.255326Unitslb/106ft3Lb/galLb/galLb/tonLb/tonlb/106ft3Lb/galLb/galLb/tonLb/tonlb/106ft3Lb/galLb/galLb/tonLb/tonFuelNGLPGOilCoalWoodNGLPGOilCoalWoodNGLPGOilCoalWoodSectorResidentialResidentialResidentialResidentialResidentialCommercialCommercialCommercialCommercialCommercialIndustrialIndustrialIndustrialIndustrialIndustrial

## Emissions Preparations & Results Appendix D.2b -36 Regional Haze SIP for NC Class I Areas December 17, 2007 

# Fuel Oil Combustion Fuel oil consumption covers the use of kerosene, distillate oil and residual oil. Distillate oil includes fuel oil grades 1, 2, and 4; residual oil includes fuel grades 5 and 6. In most areas, residual oil is not used by residential sources. Kerosene and distillate oils are primarily used for space heating in domestic and small commercial buildings, while residual oils are used primarily for industrial and large commercial applications. It was assumed that residential fuel oils are normally used only for heating and therefore, no residential fuel oil emissions were calculated for summer months.

The base year statewide annual fuel oil demand for energy, obtained from the NC Energy Outlook 2003 , was converted British Thermal Units (BTUs) to gallons of fuel used for each heating classification (i.e., residential, commercia l, and industrial). The conversion factors used were obtained from the NC Energy Outlook 2003 and are 135,000 BTU per gallon of kerosene, 138,690 BTU per gallon of distillate oil, and 149,690 BTU per gallon of residual oil.

Once converted to gallons of fuel, the statewide fuel use was then apportioned to the county level. This was accomplished by multiplying the number of gallons of fuel used in the state by the fraction of housing units heated by fuel oils in the county compared to that of the whole state (see the equation below).

# gal/yr fuel for County X = (# gal/yr fuel oil for State) x (# housing units heated by fuel oil in County X) (# housing units heated by fuel oil in State)



# The fraction of housing units was used to distribute the fuel on a county level for the residential heating classifications. The number of housing units heated by fuel oils was obtained from the 2000 Census.

Commercial and industrial fuel usage was apportioned according to the number of business establishments in the State and counties. The numbers were taken from 1997 (last year of SIC based statistics) County Business Patterns. Establishments with SICs from 50 xx through 99 xx were summed. Industrial sources were calculated in a manner similar to commercial sources burning oil or coal.

Emission factors were obtained from AP-42, Tabl e 1.3-1 and from AP-42, Table 1.3-3. Fuel oil combustion emission factors are listed in Table 2.1.4.4-2, as shown above.

Point source emissions with SCC 1-03-004-xx and 1-03-005-xx identified commercial residual oil and distillate oil emissions, respectively; while source emissions with SCC 1-02-004-xx and

## Emissions Preparations & Results Appendix D.2b -37 Regional Haze SIP for NC Class I Areas December 17, 2007 

# 1-02-005-xx identified industrial residual and distillate oil emissions, respectively. The point source emissions were subtracted from the area source emissions.

Coal Combustion There are three types of coal used for space heating: anthracite, bituminous and lignite. According to AP-42, anthracite, or hard coal, is mined almost exclusively in Pennsylvania and is consumed in Pennsylvania and in states that are within easy shipping distance. In addition, lignite coal is mined in North Dakota and Texas and is consumed near where it mined. Since the incidence of anthracite and lignite coal burning is low in North Carolina, the emissions from coal combustion were calculated utilizing only the emission factors for bituminous coal.

It was assumed that residential coal is normally used only for heating and therefore, no residential coal emissions were calculated for summer months.

The base year statewide annual coal demand for energy, obtained from the NC Energy Outlook 2003 , was converted from BTU to tons of coal used for each heating classification (i.e., residential, commercial, and industrial). The conversion factor used was 21,100,000 BTU per ton of coal.

Once converted to tons of coal, the statewide coal use was then apportioned to the county level. This was calculated by multiplying the number of tons of coal used in the state by the fraction of housing units heated by coal in the county, compared to that of the whole state (see the equation below).

# ton/yr of coal for County X = (# ton/yr of coal for State) x (# housing units heated by coal in County X) (# housing units heated by coal in State)



# The fraction of housing units was used to distribute the coal on a county level for both heating classifications. The number of housing units h eated by coal was obtained from the Federal Bureau of the Census and the 2003 NC State Energy Plan (http://www.doa.state.nc.us/doa/energy).

There were several emission factors for bituminous coal combustion listed in AP-42, Table 1.1-3. For the purpose of estimating the emissions from coal combustion, the equipment listed in AP-42, Table 1.1-3 were grouped into industrial, commercial/institutional and residential type equipment. The emission factors were averaged for each type and the averaged emission factors were used to calculate the emissions. Table 2.1.4.4-2 shown above lists the averaged emission factors used in the calculati ons. It should be noted that fluidized bed

## Emissions Preparations & Results Appendix D.2b -38 Regional Haze SIP for NC Class I Areas December 17, 2007 

# combustors (FBC) were not included in the averaged emission factors because FBC does not constitute a significant percentage of the total boiler population, according to AP-42, Section 1.1. Point source emissions with SCC 1-03-002-xx, identified commercial coal combustion emissions. The point source annual emissions in t ons per year were subtracted from the area source emissions.

Residential Coal Combustion Emissions:

Pollutant emitted by = (# tons/year Coal) x EF 

# coal combustion (2000 pounds/ton)

Commercial Coal Combustion Emissions:

Pollutant emitted by = (# tons/year Coal) x EF 

# coal combustion (2000 pounds/ton)

Industrial Coal Combustion Emissions:

There is no industrial coal combustion in the area source inventory because it is included in the point source emissions inventory.

Natural Gas Combustion Currently in the United States, natural gas is one of the major types of fuels used for heating. It is mainly used for industrial process stream and heat production, commercial and residential space heating and for electric power generation. Although natural gas is a relatively clean burning fuel, some emissions can result from its combustion.

The base year statewide annual demand for natural gas energy, obtained from the NC Energy Outlook 2003 , were converted from BTU to 10 6 

# cubic feet of natural gas used for each heating classification (i.e., residential, commercial, a nd industrial). The conversion factor used was 1,000 BTU per cubic foot of natural gas.

Once converted to cubic feet of natural gas, the statewide natural gas use was then apportioned to the county level. This was calculated by multiplyi ng the number of cubic feet of natural gas used in the state by the fraction of housing units heated by natural gas in the county, in comparison to the state (see the equation below).

## Emissions Preparations & Results Appendix D.2b -39 Regional Haze SIP for NC Class I Areas December 17, 2007 

## # ft 3 

## /yr nat gas for County X = (# ft 3/ 

## yr nat gas for State)x (# housing units heated by nat gas in County X) (# housing units heated by nat gas in State)



# The fraction of housing units was used to distribute the natural gas usage on a county level for each heating classification. The number of housing units heated by natural gas was obtained from the 2000 Census.

The North Carolina Utilities Commission provided data from the U.S. Department of Energy, Energy Information Administration giving monthly usage of natural gas by residential and commercial customers in North Carolina for 2002.

There were several emission factors listed for industrial and commercial natural gas boilers in AP-42, Table 1.4-1. For the purpose of estimating the emissions from natural gas combustion, an average of the emission factors were used. Table 2.1.4.4-2 shown above lists the averaged emission factors used in the calculations. According to the Procedures document, Table 5.8-1, the activity days per week is 7 for residential heating and 6 for commercial and industrial heating. These values were used to calculate the annual emissions in tons per year for the base
year.

Point source emissions with SCC 1-03-006-xxx and 1-02-006-xxx, identified commercial and industrial natural gas combustion emissions, respectively. Where point source emissions were indicated, these were deducted from the 2002 annual emission estimates.

Residential Natural Gas Combustion Emissions :

Pollutant emitted by = (# ft 3 

# /year natural gas) x EF Nat. gas combustion (2000 pounds/ton)



# Commercial Natural Gas Combustion Emissions:

Pollutant emitted by = (# ft 3 

## /year natural gas) x EF 

# Nat. gas combustion (2000 pounds/ton)

Industrial Natural Gas Combustion Emissions:

Pollutant emitted by = (# ft 3 

## /year natural gas) x EF Nat. gas combustion (2000 pounds/ton)

## Emissions Preparations & Results Appendix D.2b -40 Regional Haze SIP for NC Class I Areas December 17, 2007 

# Liquified Petroleum Gas Combustion Liquefied petroleum gas (LPG) consists of pr opane, propylene, butane, and butylenes. The largest market for LPG is the domestic/commercial market, followed by the chemical industry and agricultural markets. LPG is also used as a stand-by fuel for facilities that have natural gas service contracts that can be interrupted. The form of LPG used primarily for domestic heating is propane. Liquefied petroleum gas is considered a clean fuel because it does not produce visible emissions.

The base year statewide annual LPG demand fo r energy, obtained from the NC Energy Outlook 2003 , was converted from BTU to 10 3 

# gallons of LPG used for each heating classification (i.e., residential, commercial, and industrial). The conversion factor was 95,475 BTU per gallon of LPG.

Once converted to gallons of LPG, the statewide LPG use was then apportioned to the county level. This was accomplished by multiplying the number of gallons of LPG used in the state by the fraction of housing units heated by LPG in the county compared to that of the whole state (see the equation below).

# gal/yr LPG for County X = (# gal/yr LPG for State) x (# housing units heated by LPG in County X) (# housing units heated by LPG in State)



# The fraction of housing units was used to distribute the LPG usage on a county level for each heating classification. The number of housing units heated by LPG was obtained from the 2000 Census.

The North Carolina Utilities Commission provided data from the U.S. Department of Energy, Energy Information Administration giving monthly usage of LPG by residential and commercial customers in North Carolina for 2002.

The emission factors listed in AP-42, Table 1.5-1 were averaged for industrial and commercial sources. There is no residential LPG emission factor listed in AP-42. Since the form of LPG used primarily for domestic heating is propane, the commercial propane emission factor was used for residential LPG combustion. The emission factors listed in AP-42, as well as the average emission factors used for estimating the emissions from LPG combustion are listed in Table 2.1.4.4-3. Point source emissions with SCC 1-03-010-xxx and 1-02-010-xxx, identified commercial and industrial LPG combustion emissions, respectively. Where point source emissions were indicated, these were deducted from the 2002 annual emission estimate.

## Emissions Preparations & Results Appendix D.2b -41 Regional Haze SIP for NC Class I Areas December 17, 2007 

# Residential LPG Emissions:
CO emitted by = (# gal/year LPG) x EF 

# LPG combustion (2000 pounds/ton)

Commercial LPG Combustion Emissions:
CO emitted by = (# gal/year LPG) x EF LPG combustion (2000 pounds/ton)



# Industrial LPG Combustion Emissions:
CO emitted by = (# gal/year LPG) x EF LPG combustion (2000 pounds/ton)



# Table 2.1.4.4-3 Emission Factors for Liquefied Petroleum Gas Application/Fuel Type Emission Factors (lb /gallon)
Industrial Commercial Residential
Butane 0.0036 0.0021 - Propane 0.0032 0.0019 0.0019 Averaged CO Emission Factor 0.0034 0.002 0.002 Butane 0.021 0.015 0.015 Propane 0.019 0.014 0.014 Averaged NOx Emission Factor 0.02 0.0145 0.014 Butane 0.0004 0.0004 0.0004 Propane 0.0003 0.0003 0.0003 Averaged VOC Emission Factor 0.00035 0.00035 0.0003 Butane - - - Propane - - - Averaged SO 2 

# Emission Factor 0.0000513 0.0000513 0.000054 Butane - - - Propane - - - Averaged PM 10 

# Emission Factor 0.001125 0.00906 0.00906 Butane - - - Propane - - - Averaged PM 2.5 

# Emission Factor 0.001125 0.00906 0.00906

Wood Combustion

The use of wood as a source of heat occurs in the residential and industrial sectors. It was assumed that residential wood is normally used only for heating and therefore, no residential wood emissions were calculated for summer months. The burning of wood waste in boilers is mostly confined to those industries where the wood is available as a byproduct. Most often this

## Emissions Preparations & Results Appendix D.2b -42 Regional Haze SIP for NC Class I Areas December 17, 2007 

# is in the lumber, furniture and plywood industries. These types of industries are included in the point source inventory, therefore, no area source emissions will be calculated for industrial wood combustion. Wood stoves, commonly used in residences as space heaters, are used both as the primary source of heat and as a supplement to conventional heating systems.

The base year statewide annual wood demand for energy, obtained from the NC Energy Outlook 2003 , was converted from BTU to tons of wood used for residential heating. The conversion factor was 4,500 BTU per pound of wood, which is the mid-point of the range (4,000 to 5,000 BTU per pound of wood) given in AP-42, Section 1.6.

Once converted to tons of wood, the statewide wood use was then apportioned to the county level. This was accomplished by multiplying the number of tons of wood use in the state by the fraction of housing units heated by wood in the county compared to that of the whole state (see the equation below).

# tons/yr Wood in County X = (# ton/yr Wood in State) x (# housing units heated by Wood in County X) (# housing units heated by Wood in State)



# The fraction of housing units was used to distribute the wood usage on a county level. The number of housing units heated by wood was obtained from the 2000 Census.

The CO emission factor was obtained from the Procedures document, in Table 2.4-1. The residential wood combustion emission factors shown above in Table 2.1.4.4-2 were obtained from the Table 2.4-1 of the EIIP Tech. Report , Volume III, Chapter II. According to the Procedures document, Table 5.8-1, the activity days per week is 7 for residential heating.

Residential Wood Emissions: CO emitted by = (# ton/year Wood) x EF Wood combustion (2000 pounds/ton)

Small Electric Utility Boilers This source subcategory has been treated as a point source since the information was available for each facility. Refer to the point source cat egory discussion in Appendix D.2a for further details.

## Emissions Preparations & Results Appendix D.2b -43 Regional Haze SIP for NC Class I Areas December 17, 2007 

# 2.1.4.5 Vehicle Fires Vehicle fire emissions within the State are estimated by considering the estimated number vehicles burned in the State, the amount of materi al burned (the fuel loading) in a vehicle fire, and the emission factors for the open burning of automobile components. The assumptions for amount of material burned and the emission factors were based on the USEPA’s AP-42 , Section 2.5 Open Burning, 1996.

The estimated number of vehicle fires was determined by apportioning a national fire statistic to a county level. The USFA of the Department of Homeland Security maintains national-level fire statistics. The number of fires nationwide in 2002 was 1,734,500 and was available from the USFA website at http://www.usfa.fema.gov/statistics/ national/. The percentage of vehicle fires was applied to the national-level total number of fires. The number of national-level vehicle fires was then apportioned to a state-level. The ratio of North Carolina vehicle miles traveled (VMT) to U.S. VMT (92,894,000,000 VMT / 2,855,756,000,000 VMT) was applied to the number of national-level vehicle fires to obtain the number of North Carolina vehicle fires. The VMT statistics were obtained from the U.S. De partment of Transportation, Federal Highway Administration website at http://www.fhwa.dot .gov/policy/ohim/hs02/vm2.htm. The number of state-level vehicle fires was then apportioned to a county level based on paved mile per county in 2002. Paved mile per county data was obtained from the NCDOT. Using the above method, 2002 vehicle fire emissions were calculated.

The amount of vehicle material burned (the fuel loading) in a vehicle fire was estimated by assuming that an average vehicle has 500 pounds of components (.25 tons) that can burn in a fire, based on a 3,700 pounds average vehicle weight (CARB, 1995).

The emission factors were obtained from Tabl e 2.5-1, Emission Factors for Open Burning of Municipal Refuse, of the USEPA’s AP-42 , Section 2.5 Open Burning, 1996. The emission factors are 32 pounds of VOC per ton burned and 4 pounds of NOx per ton burned.

The emissions for the base inventory were calculated using equations 2.1.4.5-1.

EM P 

# = (# of Vehicle Fires per year) x (CF) x (EF P 

# ) (2000 lb/tons) 2.1.4.5-1

PJ a 

# EM = EM P 

# x GF a 

# 2.1.4.5-2

where EM P 

# = emissions for structure fires for pollutant (P) CF = Conversion factor, 0.25 tons burned/vehicle fire

## Emissions Preparations & Results Appendix D.2b -44 Regional Haze SIP for NC Class I Areas December 17, 2007 

# EF P 

# = emission factor for pollutant (P)

2.1.4.6 Agricultural Burning This source subcategory covers burning practices us ed to clear and/or prepare land for planting. These operations include stubble burning, burning of agricultural crop residues, and the burning of stand field crops as part of harvesting (e.g., sugar cane). According to the North Carolina Department of Agriculture, when soybeans are double cropped with wheat, the wheat stubble is usually burned back after harvest about one fourth of the time. According to Dr. J. Dunphy, a soybean specialist at North Carolina State University, the acres of soybean double cropped with wheat in North Carolina is approximately equal to the acres of wheat planted. Therefore, one fourth of the acreage of wheat planted in 2002 was used to calculate the emissions from agricultural burning practices in North Carolina.

The fuel loading factor and the yield of pollu tant for burning wheat stubble was obtained from AP-42 , Table 2.5.5. The fuel loading factor is 1.9 tons of fuel consumed per acre burned. The yield of pollutant was dependent upon whether the field was head-fire burned or back-fire burned. The percentage of each burning type used was not available, therefore, the assumption was made that each type was used 50 percent of the time. The yield of pollutant used, 11 pounds of VOC per ton of fuel consumed, is on average of the two types of burning. To calculate the emission factors, the fuel loading factor is multiplied by the yield of the specific pollutant.

EF VOC 

# = (1.9 tons/acre) (11 lb VOC/ton burned) = 20.9 lb VOC/acre burned

EF CO 

# = (1.9 tons/acre) (118 lb CO/ton burned) = 224.2 lb CO/acre burned

The annual emissions were calculated using the number of acres burned and the per acre emission factor. According to the North Caro lina Department of Agriculture, field burning occurs only during June and July.

The number of acres of wheat planted was obtained from the North Carolina Department of Agriculture, Agriculture Statistics Division. The emissions for the 2002 base year inventory were calculated using equation 2.1.4.8-1.

EM = (1⁄4 x (wheat acreage/year)) x EF (2000 lb/ton) 2.1.4.6-1

## Emissions Preparations & Results Appendix D.2b -45 Regional Haze SIP for NC Class I Areas December 17, 2007 

# where EM = emissions for source category EF = emission factor

2.1.4.7 On Site Incineration On-site incineration is the confined burning of waste leaves, landscape refuse and other refuse or rubbish. In North Carolina, commercial/institutional and industrial incinerators are required to have an Air Quality Permit in order to operate. Therefore, all industrial incinerators are identified in the point source inventory. There may be small commercial/institutional incinerators that have not been identified in the point source inventory and as a result emissions were calculated for commercial on-site incinerators.

No data was available to determine the amount of waste burned in on-site incinerators. Therefore, the amount of solid waste burned was es timated with the fuel loading factor (L) given in Table 4.6-1 of the Procedures document. The commercial fuel loading factor is 23 tons of refuse/1,000 population/year. The yield for comme rcial incineration was obtained from several sources. The yield of NOx, CO, SO 2 

# , PM 10 

# , PM 2.5 

# (P) was obtained from AP-42 , Table 2.1-12 and are listed in Table 2.1.4.7-1. The yield value used of NOx, CO, SO 2 

# , PM 10 

# , and PM 2.5 

# was the average of the yield values listed in AP-42 . The yield of VOC is 8.556 lb/ton of refuse and was obtained from EIIP Technical Report , Open Burning, Table 16.4-1. The yield of NH 3 

# is 1.19 lb/ton of refuse and was obtained from E IIP Area Source Methods Document, “Estimating Emissions from Anthropogenic Nonagricultural Sources”.

Table 2.1.4.7-1 Yield of Pollutant Values for Uncontrolled Refuse Combustors

Pollutant Multiple Chamber Combustor Yield Value (lb Pollutant/ton refuse burned) 

# Single Chamber Combustor Yield Value (lb Pollutant/ton refuse burned) 

# Average Yield Value (lb Pollutant/ton refuse burned)



# NOx 3 2 2.5

CO 10 20 15

SO 2 

# 2.5 2.5 2.5

PM 10 

# 7 15 11

PM 2.5 

# 7 15 11

To calculate the per capita pollutant emission factor (EF) for on-site commercial incinerators, the fuel loading factor was multiplied by the yield of the pollutant, as shown in the following equation.

## Emissions Preparations & Results Appendix D.2b -46 Regional Haze SIP for NC Class I Areas December 17, 2007 

## EF P 

## = L COMMERCIAL 

## x P INCINERATION



# = (23 tons of refuse/1000 population/year) x (15 lb CO/ton of refuse burned)

= 345 lb CO/1000 population/year



# The emissions from industrial and commercial on-site incineration for the base year 2002 inventory were calculated using equation 2.1.4.7-1. For the consideration of air quality modeling, all PM 10 

# emissions are assumed to be PM 2.5 

# emissions.

EM P 

# = (Rural Population in 2002) x (EF P 

# ) (2000 lb/tons) 2.1.4.7-1

where EM P 

# = emissions from on-site incineration for pollutant (P) in tons/year EF P 

# = emission factor for pollutant (P)

The population was obtained from the 2000 census data. Point sources were identified in the statewide counties. Point source emissions w ith source classification codes (SCC) 5-xx-xxx-xx identified waste incineration emissions. The point source emissions in tons per year were subtracted from the area source emissions.

2.2 2002 VISTAS-DEVELOPED AREA SOURCE INVENTORY
Section 2.2 details the portion of the 2002 base year area source inventory, which was developed for VISTAS by the VISTAS contractor, MACTEC, In c. This information was obtained from the report entitled Documentation of the Base G 2002 Base Year, 2009, and 2018, Emission Inventories for VISTAS prepared for VISTAS by MACTEC, Inc. This report is included in Appendix D.5.

Several major components of the area source sector of the inventory, which were developed by VISTAS, are discussed in Sections 2.2.1 through 2.2.5. Ammonia emissions from livestock and fertilizer sources are discussed in Section 2.2.1. PM 2.5 

# and PM 10 

# emissions from paved and unpaved roads are discussed in Section 2.2.2. Stage II emissions are discussed in Section 2.2.3 and were removed from the area source inventory and included in the mobile sector of the inventory. Also, emissions from portable fuel containers were added and are discussed in Section 2.2.4. Section 2.2.5 describes the developm ent of the fires emissions inventory and distinguishes the difference between an actual vers us typical inventory with regards to fires.

## Emissions Preparations & Results Appendix D.2b -47 Regional Haze SIP for NC Class I Areas December 17, 2007 

# The following Sections are based on excerpts, with some editing, taken from a document entitled, Documentation of the Base G 2002 Base Year, 2009 and 2018 Emission Inventories for VISTAS and prepared by MACTEC, Inc.

2.2.1 Ammonia from Agricultural Sources VISTAS used version 3.6 of the Carnegie Mellon University (CMU) NH 3 

# model ( http://www.cmu.edu/ammonia/ ) to calculate NH 3 

# emission estimates for livestock and fertilizers. Results from this model were used for all VISTAS States. The CMU model version 3.6 was used in large part because it had been just recently been updated to include the latest (2002) Census of Agriculture animal population statistics.

For the ammonia inventory, VISTAS removed all wildlife and human perspiration emissions. Thus all emissions from these two categories were deleted in the 2002 inventory.

2.2.2 Paved and Unpaved Road Emissions VISTAS used the most recent PM emission estimates developed by the USEPA as part of the NEI development effort (Roy Huntley, USEPA, email communication, 8/30/2004). The USEPA had developed and used an improved methodology for estimating paved road emissions for 2002. MACTEC obtained those emissions in March 2004 in NIF format from the USEPA FTP site.

PM 2.5 

# emissions from several fugitive dust sources were also updated for 2002 inventory. The Western Regional Air Partnership (WRAP) and the USEPA had been investigating overestimation of the PM 2.5 

# / PM 10 

# ratio in several fugitive dust. Based on data received from the USEPA, VISTAS decided to revise the PM 2.5 

# emissions from construction, paved roads and unpaved road sources. PM 2.5 

# emissions in the emission inventory, which was developed by the USEPA were multiplied by 0.67, 0.6, and 0.67 for construction, paved roads and unpaved roads, respectively, to produce the values found in 2002 inventory. No changes were made to PM 10 

# , only to PM 2.5 

# emissions.

2.2.3 Stage II emissions For the 2002 inventory, the VISTAS States all agreed to remove the Stage II refueling emissions from the area source inventory and include them in the non-road and on-road sectors.

## Emissions Preparations & Results Appendix D.2b -48 Regional Haze SIP for NC Class I Areas December 17, 2007 

# 2.2.4 Portable Fuel Containers Portable fuel containers (PFCs), Sour ce Classification Code (SCC) 2501060300, covers emissions from residential and commercial sector portable gasoline containers. This category typically accounts for permeation, diurnal, transport, spillage, and vapor displacement emissions. Spillage from refueling operations and vapor disp lacement emissions were not included to avoid double counting refueling in the non-road sector.

MACTEC found that the USEPA had prepared a national inventory of emissions by State for portable fuel containers. Data on emissions fr om this source prepared by the USEPA were presented in the report, Estimating Emissions Associated with Portable Fuel Containers (PFCs), Draft Report , Office of Transportation and Air Qu ality, USEPA, Report # EPA420-D-06-003, February 2006”.

The 2002 county-level emission estimates were obtained through an allocation method based on fuel usage. Initially, 2005 emission estimates, except those from vapor displacement and spillage from refueling operations, were obtained from the USEPA’s report and assumed to be equal to 2002 values. Permeation, diurnal, and transport emission estimates were summed and allocated to the county-level, based on the fuel usage information obtained from the NONROAD2005 model. The SCCs that use containe rs for refueling were acquired from the spillage file of the NONROAD model. Then the fuel usages by county from the NONROAD 2005 runs prepared for VISTAS were summed fo r those SCCs by county. The county level fuel use was then divided by the State total fuel use for the same SCCs to determine the fraction of total State fuel usage and that fraction was used to allocate the State-level emissions to the county.

2.2.5 Forest Fires The fires source category includes wildfire, pres cribed burning, and land clearing fires. These fires can be intermittent in nature, but many of these can produce large quantities of air pollutant emissions. Wildfires in certain rural areas can produce large, short-term organic emissions. Prescribed burning is used a as a forest management practice to establish favorable seedbeds, remove competing underbrush, accelerate nutrient cycling, control tree pests and contribute other ecological benefits. Agricultural burning covers agricultural burning practices used to clear and/or prepare land for planting. In land cleari ng fires, waste from logging operations is often burned under controlled conditions to reduce the potential fire hazards in forests and to remove brush that can serve as a host for destructive insects.

## Emissions Preparations & Results Appendix D.2b -49 Regional Haze SIP for NC Class I Areas December 17, 2007 

# The total wildfire acreage burned was obtained from the North Carolina Division of Forest Resources (NCDFR) for each county in the State. These numbers however are replaced with the 2002 “typical” year for the purpose of modeling. Fire emissions are not easily grown or projected. Thus, the replacement was done so that the fires represented in the area source inventory are considered typical and do not reflect an abnormally low or high year as far as fires. The typical year forest fire inventories were developed by MACTEC, Inc. with input from state and federal forest resource staff. The typi cal year covered wildfire, prescribed burning, agricultural fires and land clearing fires. The development of the typical year inventory is described below.

State level ratios of acres over a longer-term record (three or more years) developed for each fire type relative to 2002. The 2002 acreage was then scaled up or down based on these ratios to develop a typical year inventory. VISTAS Fire Special Interest Work Group based the ratio on county-level data for States that supplied long-te rm fire-by-fire acreage data rather than Statelevel ratios. Where States did not supply long-te rm fire-by-fire acreage data, MACTEC reverted to using State-level ratios. With one broad exception (wildfires) this method was implemented for all fires. MACTEC solicited long term fire -by-fire acreage data by fire type from each VISTAS State. A minimum of three or more years of data were used to develop the ratios. Those data were then used to develop a ratio for each county based on the number of acres burned in each county for each fire type relative to 2002.

If VISTAS had long term county prescribed fi re data from a State, a county acreage ratio, described below, was developed.

acreage Rx level county actual 2002 acres Rx level county average term Long

= Ratio

This ratio was then multiplied times the actual 2002 acreage to get a typical value (basically the long term average county level acres). Wherever possible this calculation was performed on a fire-by-fire basis. The acreage calculated using the ratio was then used with the fuel loading and emission factor values to calculate emissions. Below are three exceptions to this method.

Exception 1: Use of State Ratios for Wildfires
Wildfires estimates were developed using State ratios rather than county ratios because some counties were showing unrealistic ratios, which were created by very short term data records or missing data. In addition, exceptionally large and small fires were removed from the database. VISTAS also removed all fires less than 0.1 acres from the dataset.

## Emissions Preparations & Results Appendix D.2b -50 Regional Haze SIP for NC Class I Areas December 17, 2007 

# Exception 2: Correction for Blackened Acres on Forest Service Lands
Acres, submitted by the U.S. Forest Service (USFS) for wildfires and prescribed fires on USFS lands, represented perimeter acres rather than “blackened” acres. Therefore, for prescribed fires greater than 100 acres in size, the acreage was adjusted to be 80 percent of the initial reported value. For prescribed fires of 100 acres or less, the acreage values were maintained as reported. All reported acreage values for wildfires were adjusted to be 66 percent of their values, as initially reported.

Exception 3: Missing/Non-reported data

When VISTAS did not receive data from a VISTAS State for a particular fire type, a composite average for the entire VISTAS region was used to determine the typical value for that type fire. This technique was applied to all fire types when data was missing.

For wildfires and prescribed burning, ratios were also developed for “northern” and “southern” tier States within the VISTAS region and those ratios were applied to each State with missing data depending upon whether they were considered a “northern” or “southern” tier State. Development of “southern” and “northern” tier data was an attempt to account for a change from a predominantly pine/evergreen ecosystem (southern) to a pine/deciduous ecosystem (northern).

Table 2.2.5-1 below presents a comparison in tons per year of the 2002 actual fire emissions and the 2002 typical fire emissions for wildfires, prescribed burning, agricultural fires and land clearing fires in North Carolina.

## Emissions Preparations & Results Appendix D.2b -51 Regional Haze SIP for NC Class I Areas December 17, 2007 

# Table 2.2.5-1 2002 North Carolina Actual and Typical Fire EmissionsNH395.1448.00157.69155.21PM2.51825.841035.003002.502927.07PM102126.611210.003504.443413SO2124.8967.00206.78204.15CO22045.4812446.0036210.8435123.29VOC1005.04619.191609.221777.61NOx458.18282.28733.62810.38Actual Fire Emissions (TPY)Fire TypeWildfiresPrescribedBurningTypical Fire Emissions (TPY)WildfiresPrescribedBurning

## Emissions Preparations & Results Appendix D.2b -52 Regional Haze SIP for NC Class I Areas December 17, 2007 

# 3. 2002 VISTAS-DEVELOPED NONROAD MOBILE SOURCE INVENTORY

Development of emission estimates for nonroad mobile sources is documented in the MACTEC, Inc. document titled Documentation of the Base G 2002 Base Year, 2009 and 2018, Emission Inventories for VISTAS

.
Nonroad mobile sources are those sources that can move but do not use the highway system. Examples include lawn mowers, agricultural equipment, construction equipment, aircraft engines, railroad locomotives, powerboats, and commercial marine (ships). All but the aircraft engine, railroad locomotive emissions and commercial marine activity were estimated using the USEPA’s off-road mobile model NONROAD2005c, which was released March 21, 2006. Direct emissions are generated with this model. This version incorporates all the USEPA final nonroad mobile engine emission standards, incl uding the recreational and large spark-ignition engines rules that were published in the Federal Register in November 2002. Although this model is considered to be a final model, an updated version is planned that may incorporate revised inputs for the small spark-ignition (SI) (<19 kW) and recreational marine SI categories in conjunction with additional promulgated nonroad mobile engine standards.

Nonroad mobile sources calculated through the NONROAD model are discussed in Section 6.1 Aircraft, railroad and commercial marine emissions are discussed in Sections 3.2 through 3.4.

3.1 NONROAD Model Sources
The nonroad mobile source category includes a diverse collection of equipment such as lawn mowers, chain saws, tractors, all terrain vehicles, fork lifts and construction equipment. The USEPA NONROAD2005c model generates emissions directly and includes more than 80 different types of equipment. To facilitate analysis and reporting, the USEPA grouped the equipment types into ten equipment categories. These include:

Agricultural equipment Lawn and garden equipment Airport ground support equipment Logging equipment Commercial equipment Railroad maintenance equipment Construction equipment Recreational marine equipment Industrial equipment Recreational equipment

## Emissions Preparations & Results Appendix D.2b -53 Regional Haze SIP for NC Class I Areas December 17, 2007 

# Additionally, the emissions are broken out by five different engine types. These include: 2-stroke and 4-stroke spark engines, diesel e ngines, liquid petroleum gas (LPG) and compressed natural gas (CNG) fueled engines.

One of the default input files was edited to reflect North Carolina specific information. In the“SEASON.DAT” file, the region representative of North Carolina was changed from MidAtlantic to Southeast. This was done after an evaluation of the meteorological data in the two files and comparing it to that of Charlotte. Default data was used for the remaining input files used in the NONROAD model.

3.2 Aircraft Engines
Aircraft engines, like other engines, emit pollutants whenever the engines are in operation. However, the only emissions that are of concern for this inventory are the portion of the operation that occurs below the mixing layer. This is because the emissions tend to disperse whenever the aircraft is above the mixing layer and therefore has little or no effect on ground level ozone.

The aircraft operations of interest are termed the landing and takeoff (LTO) cycle. The cycle begins when the aircraft approaches the airport, descending below the mixing layer, lands and taxis to the gate. It continues as the aircraft idles at the gate and then taxis back out to the runway for the subsequent takeoff and climbout as it heads back to cruising altitudes, above the mixing layer.

Aircraft can be categorized by use into four classifications: commercial, air taxis, general aviation and military. Commercial aircraft include those used for scheduled service transporting passengers and/or freight. Air taxis, or commute r aircraft, also fly scheduled service carrying passengers and/or freight but usually are smaller aircraft and operate on a more limited basis than commercial carriers. General aviation include all other non-military aircraft used for recreational flying, personal transportation, and various other activities. Military aircraft cover a wide range of sizes, uses and operating missions. The military aircraft are treated as a separate classification since the LTO operations reported at the airports group all military aircraft together.

Emission factors are available for the many aircraft and engine combinations that exist. Factors for each aircraft exist for four operating modes in the LTO cycle. Emissions are calculated by obtaining data for the number of LTO cycles of th e various aircraft at each airport in question, multiplying by the appropriate factors, and summing the results for the year under consideration.

## Emissions Preparations & Results Appendix D.2b -54 Regional Haze SIP for NC Class I Areas December 17, 2007 

# Development of the 2002 aircraft emissions are described in the MACTEC document titled Documentation of the Base G 2002 Base Year, 2009 and 2018 Emission Inventories for VISTAS

. This document refers back to a document titled “Development of the VISTAS Draft 2002 Mobile Source Emission Inventory (February 2004 Version)” prepared by E.H. Pechan & Associates, Inc. Both of these documents are included in Appendix D.5.

The starting point for development of aircraft emissions estimates is the 1999 National Emission Inventory (1999 NEI) prepared by the USEPA. Th ese emissions were grown to appropriate values for 2002 and 2009 using growth factors developed by the USEPA for the CAIR. Along the way there was input by the various States including North Carolina to arrive at more accurate emission estimates.

3.3 Railroad Locomotives
Railroads are categorized by size (Class I, Class 2) and passenger service (Amtrak and North Carolina Department of Transportation (NCDOT) Ra il Division). Class I railroads are long haul operations, consisting of Norfolk Southern Corpora tion and CSX Corporation in North Carolina. Class II and Class III railroads are short lines, serving localized markets. Passenger service is provided by Amtrak and the NCDOT Rail Division in North Carolina. These entities lease trackage from Class I railroads.

Development of railroad emissions is described in the MACTEC document titled Documentation of the Base G 2002 Base Year, 2009 and 2018 Emission Inventories for VISTAS . The VISTAS/ASIP railroad emission estimates starte d with 1999 emission estimates developed for the USEPA’s 1999 NEI Version 2 as base year estimates for the VISTAS region. Additional information is provided in “Development of the VISTAS Draft 2002 Mobile Source Emission Inventory (February 2004 Version)” prepared by E.H. Pechan & Associates, Inc.

Projected emissions for 2002 were developed in two steps as described below. For 1999 to 2001, State-level rail fuel consumption was obtai ned from the Department of Energy, Energy Information Administration’s (EIA’s) Fuel Oil and Kerosene Sales.

For 2001 to 2002, VISTAS applied national growth factors developed from fuel consumption projections in EIA’s Annual Energy Outlook. A growth factor of 1.4 was used for locomotives and applied to 1999 emissions to first develop 2001 emissions. Table 3.3-1 lists the growth factors used to generate 2002 emissions.

## Emissions Preparations & Results Appendix D.2b -55 Regional Haze SIP for NC Class I Areas December 17, 2007



# Table 3.3-1 2002 National Rail Transportation Energy Use by Fuel Type (Trillion BTU) 2001 2002 Growth Factor (GF) Intercity Rail (Electric) 10.17 10.40 1.0226
Intercity Rail (Diesel) 16.60 16.88 1.0169 Transit Rail (Electric) 46.36 47.40 1.0224 Intercity/Transit Rail Average (SCC 2285002008) 1.0206

Commuter Rail (Electric) 16.13 16.49 1.0223
Commuter Rail (Diesel) 26.31 26.76 1.0171 Commuter Rail Average (SCC 2285002009) 1.0197

Freight Rail (Distillate) (SCCs 2285002000, 2285002005, 2285002006, 2285002007, 2285002010) 512.81 492.32 0.9600

Source: Department of Energy, Energy Information Administration, Annual Energy Outlook 2003: Table 34. Transportation Sector Energy Use by Fuel Type Within a Mode



# 3.4 Commercial Marine Vessel (CMV)
The following description of development of commercial marine emission estimates is based on excerpts, with some editing, taken from the MACTEC document titled Documentation of the Base G 2002 Base Year, 2009 and 2018 Emission Inventories for VISTAS and a document titled “Development of the VISTAS Draft 2002 Mobile Source Emission Inventory (February 2004 Version)” prepared by E.H. Pechan & Associates, Inc

An initial 2002 base year emissions inventory for commercial marine vessels (CMV) was prepared for VISTAS in early 2004. The methods and data used to develop the inventory are presented in a February 9, 2004 report “ Development of the VISTAS Draft 2002 Mobile Source Emission Inventory (February 2004 Version) ” prepared by E.H. Pechan & Associates, Inc. Revisions to the initial 2002 emissions inventory (prepared by Pechan) were implemented to ensure that the latest State and local data were incorporated. For CMV, North Carolina provided no revised data.

For 2002 commercial marine vessels (CMVs), Pechan used 1999 emission estimates developed

## Emissions Preparations & Results Appendix D.2b -56 Regional Haze SIP for NC Class I Areas December 17, 2007 

# for the USEPA’s 1999 NEI Version 2 as base year estimates for the VISTAS region. Pechan then improved the spatial distribution of CMV emission estimates for the VISTAS region.

Ideally, CMV emission estimates would be developed using local activity data that account for vessel type, engine type and mode of operati on (cruise, maneuvering, and hotelling). Creating this type of “bottom-up” emission inventory require s a large amount of effort. Therefore, Pechan utilized port-specific emission estimates develope d for the 1999 NEI, distributed using a revised allocation methodology, which incorporates information on the number of port facilities in each county.

The 2002 VISTAS commercial marine inventory is based on the USEPA’s 1999 NEI Version 2.0, projected to 2002 using appropriate growth f actors. The 1999 NEI estimated emissions for these categories according to the following SCCs:

SCC Descriptor 1 Descriptor 3 Descriptor 6 Descriptor 8 2280002100 Mobile Sources Marine Vessels, Commercial Diesel Port emissions 2280002200 Mobile Sources Marine Vessels, Commercial Diesel Underway emissions 2280003100 Mobile Sources Marine Vessels, Commercial Residual Port emissions 2280003200 Mobile Sources Marine Vessels, Commercial Residual Underway emissions



# For the 1999 NEI, commercial marine diesel emissions were developed by obtaining 2000 emission estimates for all pollutants except SO 2 

# from the USEPA’s Office of Transportation and Air Quality (OTAQ) marine diesel regulatory background documentation ( Draft Regulatory Impact Analysis - Control of Emissions from Compression-Ignition Marine Engines ). To estimate emissions for 1999, 2000 estimates were backcast using growth factors obtained from the draft Regulatory Impact Analysis (RIA) cited above. Steam-powered residual CMV emission estimates were developed by obtaining fu el usage data from OTAQ and applying fuelbased emission factors. A similar method was used for diesel SO 2 

# emissions. National diesel usage was estimated assuming a sulfur content of 0.25 percent and the USEPA emission factors.

In apportioning, distillate and residual fuels are considered separately. National diesel emissions were disaggregated into port and underway emissions estimates based on the assumption that 75 percent of distillate fuel is consumed within the port, while the remaining fuel is consumed while underway, consistent with the USEPA guidance. National residual emissions were disaggregated into port and underway emissions estimates based on the assumption that 25 percent of residual fuel is consumed within the port, while the remaining fuel is consumed while underway.

## Emissions Preparations & Results Appendix D.2b -57 Regional Haze SIP for NC Class I Areas December 17, 2007 

# To allocate to counties, port emissions were assigned to the 150 largest U.S. ports based on activity obtained from the U.S. Army Corps of Engineers (USACE). The percentage of total traffic for each port was calculated by dividing th e port-level traffic by the total traffic. Emissions for each port were then assigned to a single county.

Underway emissions are assigned to counties ba sed on a county’s shipping lane traffic. The Bureau of Transportation Statistics’ (BTS) National Transportation Atlas Databases-1999 contains data on the thousand tons per mile traveled for each shipping lane link in the United States (BTS-CD26). Where navigable rivers fo rm a county or State boundary, the shipping lane traffic is proportioned to individual counties based on the length of shoreline that is shared. For example, if two counties share a navigable river, and both counties have the same length of shoreline, the shipping traffic is split evenly between the two counties. Shipping lanes that are not within counties, for example in the ocean, are associated to States based on BTS assignments. These waterway weights are then evenly distributed among the counties within these States that have navigable waterways. All shipping activity is summed at the county-level and compared with national shipping activity to determine what portion of activity can be attributed to individual counties. These proportions were used in disaggregating the national CMV emission estimates to the county level.

States that share borders with non-VISTAS Stat es along the Mississippi and Ohio Rivers have expressed concern about the representativeness of port emission estimates at a county-level. Revising the county-level emissions estimates would allow more accurate modeling of emissions in the VISTAS states.

For underway emissions, Pechan believes that the allocation procedure results in a reasonable distribution of county-level emissions. Howe ver, the methodology to allocate port emissions results in all the emissions being assigned to a single county.

Port areas encompass multiple States and counties and in some cases, multiple waterways. Therefore, the emissions allocation process must incorporate all counties in the vicinity of the port where activity is occurring. This is especially true for inland rivers where activity takes place on both riverbanks and for ten river miles or more outside the port city. The revised methodology allocates port emissions based on a surrogate for port-related activity in each county, rather than using a single county to define the port.

The report, Waterborne Commerce of the United States, Calendar Year 1999, hereafter referred to as Waterborne Commerce, presents the cargo tonnage and number of vessel trips in major waterways of the United States. The report defines port areas, which USACE uses to develop

## Emissions Preparations & Results Appendix D.2b -58 Regional Haze SIP for NC Class I Areas December 17, 2007 

# the Top 150 Ports in the United States by amount of cargo tonnage. As discussed previously, the 1999 NEI allocates all the port emissions to these 150 ports based on the cargo tonnage handled by the port. Pechan uses this allocation of emissions to each port area as the starting point of its revised allocation process. Morehead City Harbor and the Port of Wilmington are the two main ports in North Carolina.

The next step was to develop a list of counties that make up the port area. Port area definitions were obtained from Waterborne Commerce . The port area definition for Morehead City Harbor port was “Morehead City Harbor, NC”. The port area definition for Wilmington City port was “Both banks of the Cape Fear River extending fr om a point about 18 miles below the foot of Castle St. in Wilmington to a point about 2 mile s above the Railroad Bridge at Navassa, and both banks of Northeast (Cape Fear) River from its mouth to a point about 1.67 miles above the Hilton Railroad Bridge”. Using the port definitions by river mile, Pechan established which counties are included in each port area. The Port of Wilmington is included in the counties of Hanover and New Brunswick. The Morehead City Harbor is included in Carteret county.

The next step in allocating emissions is to develop a surrogate for the amount of CMV activity in each county of the port area. Pechan assumed that the activity of vessels in each county is related to the number of port facilities operating in a given county. Port facilities include terminals, piers, wharves, and docks that are involved in all types of commercial activity and support services. Pechan obtained the number of port facilities in each county from USACE reports, The Port Series Reports. The USACE periodically surveys the commercial marine industry to obtain information on port facilities and publishes it in The Port Series Reports. The reports give the name, location, operations, and describe the physical and inter-modal characteristics of the facilities. The data includes the location of the facility by river mile, State, and county.

For each port area, Pechan calculated the ratio between the number of port facilities in each county to the total number of facilities in all counties that make up the port area. This ratio was used to allocate emissions for each port area to the county-level. The ratio for Morehead City Harbor was 1.0 in Carteret county and the ratio s for the Port of Wilmington were 0.8974 in New Hanover county and 0.1026 in Brunswick county. Pechan was directed to perform the reallocation for all VISTAS ports.

## Emissions Preparations & Results Appendix D.2b -59 Regional Haze SIP for NC Class I Areas December 17, 2007 

# 4. QUALITY ASSURANCE OF 2002 EMISSIONS INVENTORY

Many emission estimation methods are based on AP-42 factors located on the USEPA website at http://www.epa.gov/ttn/chief/ap42/, factors given in the Procedures document, and factors given in the documents of the Emission Inventory Improvement Program website located at http://www.epa.gov/ttn/chief/eiip/ . Sources of error would primarily be associated with multiplier values, data entry errors, and the accuracy of formulas.

For the portion of the 2002 inventory developed by North Carolina, specific quality assurance (QA) procedures were followed. Under the direction of the Quality Assurance Coordinator, emission sources whose contribution were either at the high or low end of the range of estimates were scrutinized more closely to ensure that the emission estimates were estimated correctly. In addition, the raw data used in the calculations were verified to make sure transference to the spreadsheets was accomplished accurately. Furthermore, the formulas used to calculate the daily emissions were reviewed and checked for correctness. Random independent checks of the calculations were also performed to ensure the accuracy of the inventory.

For the portion of the 2002 inventory deve loped by VISTAS and MACTEC, specific QA procedures were followed. These procedures are outlined in the document titled Documentation of the Base G 2002 Base Year, 2009, and 2018, Emission Inventories for VISTAS prepared for VISTAS by MACTEC, Inc. Throughout the inventory development process, quality assurance steps were performed to ensure that no double counting of emissions occurred, and to ensure that a full and complete inventory was developed for VISTAS. Quality assurance was an important component to the inventory development process and MACTEC performed the following QA steps on the area source component of the 2002 inventory:

1. All CERR and NIF format State supplied data submittals were run through the USEPA’s Format and Content checking software.

2. SCC level emission summaries were prepared and evaluated to ensure that emissions were consistent and that there were no missing sources.

3. Fields were either added or used within each NIF data table to track the sources of data for each emission record.

4. Data product summaries were provided to both the VISTAS Emission Inventory Technical Advisor and to Area Source and Fires SIWG representatives for review and comment. Changes based on these comments were implemented in the files.

## Emissions Preparations & Results Appendix D.2b -60 Regional Haze SIP for NC Class I Areas December 17, 2007 

# 5. Version numbering was used for all inventory files developed. The version numbering process used a decimal system to track major and minor changes. For example, a major change would result in a version going from 1.0 to 2.0. A minor change would cause a version number to go from 1.0 to 1.1. Minor changes resulting from largely editorial changes would result in a change from 1.00 to 1.01.

6. All final NIF files were checked using the USEPA Format and Content checking software and summary information by State and pollutant were prepared comparing the previous versions of the inventory to the latest.
For the fires inventory, data related to fuel loading and fuel consumption was reviewed and approved by the VISTAS Fire SIWG to ensure that values used for each type of fire and each individual fire were appropriate. Members of th e VISTAS Fire SIWG included representatives from most State Divisions of Forestry (or equiva lent) as well as U.S. Forest Service and National Park Service personnel.

In addition, for the nonroad portion of the invent ory prepared by VISTAS, tier comparisons (by pollutant) were developed between the revised 2002 base year inventory and the initial base year inventory.



# 5. 2009 AND 2018 AREA SOURCE EMISSION INVENTORY DEVELOPMENT

This subsection describes the methodology used to develop the 2009 and 2018 area source inventories. Separate methods for projecting emissions were used for non-agricultural (stationary area), agricultural area sources and forest fire area sources. The agricultural area sources method are for ammonia emissions and important for regional haze and fine particulate matter.

The following Sections are based on excerpts, with some editing, taken from a document entitled, Documentation of the Base G 2002 Base Year, 2009 and 2018 Emission Inventories for VISTAS and prepared by MACTEC, Inc.

5.1 Projection of Stationary Area Sources
VISTAS 2002 base year inventory emissions were used as a starting point for calculating 2009 and 2018 emissions. MACTEC, Inc. first back calculated uncontrolled emissions from the 2002

## Emissions Preparations & Results Appendix D.2b -61 Regional Haze SIP for NC Class I Areas December 17, 2007 

# base year inventory. Growth and control factors were then applied based on controls initially identified for the Clean Air Interstate Rule (CAIR) and growth factors identified for the CAIR projections. In some cases, Economic Growth Analysis System version 5.0 (EGAS 5.0) growth factors were used if no growth factor was av ailable from the CAIR growth factor files.

The 2009 and 2018 growth factors were obtained from the USEPA growth factors and indirectly from 2010 and 2015 CAIR growth factors. Usi ng a 2001 base year, interpolation of 2010 and 2015 CAIR growth factors yielded 2009 and 2018 gr owth factors. MACTEC used the TREND function of Microsoft Excel for interpolation. Inte rpolated growth factors were calculated at the State and SCC level.

In a few cases, additional growth factors had to be added for sources that had not initially been included in a draft 2002 inventory. These growth factors were obtained from EGAS 5.0. Finally updates to growth factors from EGAS 5.0 were made for fuel fired emission sources. The updated growth factors reflected the most recent data from the Department of Energy’s Annual Energy Outlook (AEO). These data were used to reflect changes in energy efficiency resulting from new or updated fuel firing technologies.

North Carolina provided 2009 and 2018 updated emission files used to update the emissions for each year for several source categories. However not all sources in the inventory were included in these North Carolina updates. As a consequence, the final 2009 inventory for North Carolina included emissions updated using the North Carolina supplied files and emissions developed using growth and control factors as outlined above.

5.2 Projection of Agricultural Area Sources

MACTEC used the version 3.1 2002 base year inventory data (which was based on the CMU ammonia model version 3.6). MACTEC obtained Stat e specific growth, if available. Otherwise, growth factors were used, which were developed from the USEPA Interstate Air Quality Transport Rule (IAQTR)/Ammonia inventory. Growth factors for several agricultural livestock categories were developed by the USEPA, as part of the NEI.

In addition, ammonia growth factors for a few categories (mainly feedlots) were assigned to be the same as growth factors for PM emissions from the NEI projections. This assignment was made because the CMU model showed emissions from these categories but the NEI projections did not show ammonia emissions but did show PM emissions. No growth factors were found for horse and pony emissions. These emissions were held constant at 2002 levels.

## Emissions Preparations & Results Appendix D.2b -62 Regional Haze SIP for NC Class I Areas December 17, 2007 

# No controls were identified by North Carolina; thus, all projected emissions for agricultural area sources represent simple growth with no controls.

Wild animal and human perspiration emissions were removed from the 2009 and 2018 inventories. All swine emissions for North Carolina were maintained at 2002 levels for each 2009 and 2018 to capture a moratorium on swine production in that State.

5.3 Projection of Forest Fires Area Sources
Several Federal agencies indicated that they had plans for increased prescribed fire burning in future years and that the “typical” fire invent ory would likely not adequately capture those increases. Thus, MACTEC acquired the data necessary to provide 2009 specific projections for the prescribed fire component of the fire inventory.

The U.S. Fish and Wildlife Service (USFWS) submitted annual acreage data by National Wildlife Refuge (NWR) and by county with estimates of acres burned per day for each NWR. USFS provided fire-by-fire acreage estimates based on mapping projected burning acreage to current 2002 modeling days. However, USFWS did not submit data for VISTAS original base year preparation process, thus there was no known USFWS data in the 2002 actual or typical inventories. MACTEC therefore developed a method that could use the county-level data submitted by USFWS.

Several VISTAS States run a prescribed fi re-permitting program. To avoid double counting, only State data and not USFWS or USFS data wa s used in those States for the 2002 actual inventory.

The method used by MACTEC to include the USFS data applied a county level data approach for USFS data where a State had a prescribed fire permitting program and a fire-by-fire replacement for USFS data in States without permit programs. MACTEC used a county level approach for all of the USFWS data. The approach used for each data set is discussed below.

For USFWS data, 2002 annual county acres burned was subtracted from the USFWS projected acreage. A 0.8 factor was applied to the difference to account for blackened acres instead of the total perimeter acres that were reported. The revised total additional USFWS acreage was then added to the total county “typical” acreage to determine future acreage burned for 2009 and 2018.

## Emissions Preparations & Results Appendix D.2b -63 Regional Haze SIP for NC Class I Areas December 17, 2007 

# MACTEC then allocated the increased acreage to current modeling days. The average daily acres burned data provided by USFWS per NWR/county was used to allocate the acreage to the correct number of days required to burn all of the acres. Guidance supplied by USFWS indicated that up to three times the average daily acres burned could potentially be allocated to any one day.

For the USFS fire-by-fire acreage estimates, MACTEC summed the USFS data at a county-level for States that had permit programs, then added the sum to the typical acreage and allocated the acres to current modeling days. For States that do not have a State prescribed fire permit program, MACTEC simply replaced the current fire- by-fire records in the database with fire-byfire records from the USFS and recalculated em issions based on fuel model and fuel loading. VISTAS also applied the same 0.8 correction for blackened acres applied to all USFS supplied acreage as the supplied values represented perimeter acres.

An additional problem with developing year-speci fic prescribed fire projections was how to adequately capture the temporal profile for those fires. In the 2002 actual fire inventory, fires occur on same days as state/FLM records. In the 2002 “typical” year inventory, fire acreage increased or decreased from acreage on the same fire days as were in the 2002 actual inventory, since the acres were simply increased for each day based on a multiplier used to convert from actual to typical.

When prescribed fires acreage was added to a future year, MACTEC added acreage to individual fire days proportional to the annual increase (if acreage on a day is 10 percent of annual, add 10 percent of projected increase to that same day).



# 6. 2009 AND 2018 NONROAD SOURCE EMISSION INVENTORY DEVELOPMENT

The subsections that follow describe the projection process used to develop 2009 and 2018 nonroad projection estimates for sources found in the NONROAD model and those sources estimated outside of the model (locomotives, airplanes and commercial marine vessels).

## Emissions Preparations & Results Appendix D.2b -64 Regional Haze SIP for NC Class I Areas December 17, 2007 

# 6.1 Projection of NONROAD Model Sources
NONROAD model input files were prepared based on the 2002 base year inventory input files with appropriate updates for the projection years. Other specific updates for the projection years for NONROAD model sources consist of:

1. Revise the emission inventory year in the model (as well as various output file naming commands) to be reflective of the projection year.

2. Revise the fuel sulfur content for gasoline and diesel powered equipment.

3. Implement a limited number of local control program changes (national control program changes are handled internally within the NONROAD model, so explicit input file changes are not required).

All equipment population growth and fleet turnover impacts are handled internally within the NONROAD model, so that explicit input file changes are not required.

The final NONROAD2005c that was used for inventory development is capable of handling separate diesel fuel sulfur inputs for land-based and marine-based nonroad mobile source equipment in a single model execution. The following diesel fuel sulfur values were used: Diesel S (ppm) 2002 2009 2018 Land-Based 2500 348 11 Marine-Based 2638 408 56

6.2 Projection of Non-NONROAD Model Sources
Using the 2002 base year emissions inventory fo r aircraft, locomotives, and CMV prepared as described earlier in this document, corresponding emission projections for 2009 and 2018 were developed. The following description is largely taken from the MACTEC document titled Documentation of the Base G 2002 Base Year, 2009 and 2018 Emission Inventories for VISTAS

. Briefly, the methodology relies on growth and control factors developed from inventories used in support of recent USEPA rulemakings, and consists of the following steps:

(a) Begin with the 2002 base year emission estimates for aircraft, locomotive, and CMV.

(b) Detailed inventory data (both before and after controls) for these same emission sources for 1996, 2010, 2015, and 2020 were obtained from the USEPA's CAIR Technical

## Emissions Preparations & Results Appendix D.2b -65 Regional Haze SIP for NC Class I Areas December 17, 2007 

# Support Document. Using these data, combined growth and control factors for the period 2002-2009 and 2002-2018 were estimated using straight line interpolation between 1996 and 2010 (for 2009) and 2015 and 2020 (for 2018). This is done at the State-county-SCC-pollutant level of detail.

(c) The USEPA growth and control data are matched against the 2002 VISTAS base year data using State-county-SCC-pollutant as the match key. Ideally, there would be a one-to-one match and the process would end at this point. Unfortunately, actual match results were not always ideal, so additional matching criteria were required. For subsequent reference, this initial (highest resolution) matching criterion is denoted as the “CAIR-Primary” criterion.

(d) A second matching criterion is applied that utilizes a similar, but higher-level SCC (lower resolution) matching approach. For example, SCC 2275020000 (commercial aircraft) in the 2002 base year inventory data would be matched with SCC 2275000000 (all aircraft) in the CAIR data. This criterion is applied to records in the 2002 base year emissions file that are not matched using the “CAIR-Primary” criterion, and is also performed at the State-county-SCC-pollutant level of detail. For subsequent reference, this is denoted as the “CAIR-Secondary” criterion. At the end of this process, a number of unmatched records continued to remain, so a third level matching criterion was required.

(e) In the third matching step, the most frequently used SCC in the USEPA CAIR files for each of the aircraft, locomotive, and commercial marine sectors is averaged at the State level to produce a “default” State and pollutant-specific growth and control factor for the sector. The resulting factor is used as a “default” growth factor for all unmatched county-SCC-pollutant level data in each State. In effect, State-specific growth data are applied to county level data for which an explicit match between the VISTAS 2002 base year data and the USEPA CAIR data could not be developed. The default growth and control SCCs are 2275020000 (commercial aircraft) for the aircraft sector, 2280002000 (commercial marine diesel total) for the CMV sector, and 2285002000 (railroad equipment diesel total) for the locomotive sector. Matches made using this criterion are denoted as “CAIR-Tertiary” matches.

(f) According to USEPA documentation, the CA IR baseline emissions include the impacts of the (then proposed) Tier 4 (T4) nonroad mobile diesel rulemaking, which implements a low sulfur fuel requirement that affects both future CMV and locomotive emissions. However, the impacts of this rule were originally intended to be excluded from the initial VISTAS 2018 forecast, which was to include only “on-the-books” controls. (The T4 rule

## Emissions Preparations & Results Appendix D.2b -66 Regional Haze SIP for NC Class I Areas December 17, 2007 

# was finalized subsequent to the development of the preliminary 2018 inventory in March of 2004.) Given its final status, T4 impacts have now been moved into the “on the books” inventory for nonroad mobile source equipment. In addition, since there are no other proposed rules affecting the nonroad mobile source sector between 2002 and 2018, there is no difference between the 2018 “on the books” and 2018 “on the way” inventories for the sector; so that only a single forecast inventory (for each evaluation year) was developed. Nevertheless, since the algorithms developed to produce the VISTAS forecasts were developed when there was a distinction between the “on the books” and “on the way” inventories, the distinct algorithms used to produce the two inventories have been maintained even though the conceptual distinctions have been lost. This approach was taken for two reasons. First, it allowed the previously developed algorithms to be utilized without change. Second, it allowed for separate treatment of the T4 emissions impact, which was important as those impacts have changed between the proposed and final T4 rules. Thus, previous USEPA inventories that include the proposed T4 impacts would not be accurate. Therefore, the procedural discussion continues to reflect the distinctions between non-T4 and T4 emissions, as these distinctions continue to be intrinsically important to the forecasting process. Therefore, a second set of USEPA CAIR files that excluded the Tier 4 diesel impacts was obtained and the same matching exercise described above in steps (b) through (e) was performed using these “No T4” files. It is important to note that the matching exercise described in steps (b) through (e) cannot simply be replaced because the “No T4” files obtained from the USEPA include only those SCCs specifically affected by the T4 rule (i.e., diesel CMV and locomotives). So in effect, the matching exercise was augmented (rather than replaced) with an additional three criteria analogous to those described in steps (c) through (e), and these are denoted as the “No T4-Primary,” “No T4-Secondary,” and “No T4-Tertiary” criteria. Because they exclude the impacts of the proposed T4 rule, matches using the “No T4” criteria supersede matches made using the basic CAIR criteria (as described in steps (c) through (e) above).

The CAIR matching criteria were overridden for any record for which States provided local growth data. Only North Carolina provided these forecasts, as North Carolina has provided specific growth factors for airport emissions in four counties. Because the provided data were based on forecasted changes in landings and takeoffs at major North Carolina airports, the factors were applied only to commercial (SCC 2275020000) and air taxi (SCC 2275060000) emissions. Emissions forecasts for military and general aviation aircraft operations, as well as all aircraft operations in counties other than the four identified in the North Carolina growth factor submission, continued to utilize the growth

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# factors developed according to steps (b) through (f) above. Table 6.2-1 presents the locally generated growth factors applied in North Carolina.

Table 6.2-1 Locally Generated Growth Factors for North Carolina

FIP 2009 Factor 2018 Factor
37067 0.71 0.84
37081 0.97 0.89
37119 1.15 1.01
37183 0.88 0.81

Note:
Growth factor = Year Emissions/2002 Emissions. Under CAIR approach, 2009 = 1.16 to 1.17 for all 4 counties. Under CAIR approach, 2018 = 1.36 to 1.37 for all 4 counties.



# (h) Using this approach, each State-county-SCC-pollutant was assigned a combined growth and control factor using the USEPA CAIR forecast or locally provided data. The 22,838 data records for aircraft, locomotives, and CM V in the 2002 base year emissions file were assigned growth factors in accordance with the following breakdown:

48 records matched State-provided growth factors, 4,179 records matched using the CAIR-Primary criterion, 240 records matched using the CAIR-Secondary criterion, 7,463 records matched using the CAIR-Tertiary criterion, 720 records matched using the No T4-Primary criterion, 3,858 records matched using the No T4-Secondary criterion, and 6,330 records matched using the No T4-Tertiary criterion.

(i) Finally, the impacts of the T4 rule as adopted were applied to the grown “non T4” emission estimates. The actual T4 emission standards do not affect aircraft, locomotive, or CMV directly, but associated diesel fuel sulfur requirements do affect locomotives and CMV. Lower fuel sulfur content affects both SO 2 

# and PM emissions. Expected fuel sulfur contents were obtained for 2009 and 2018 from the USEPA technical support document for the final T4 rule ( Final Regulatory Analysis: Control of Emissions from Nonroad Diesel Engines , EPA420-R-04-007, May 2004). According to that document, the average diesel fuel sulfur content for locomotives and CMV is expected to be 408 parts per million by weight (ppmW) in 2009 and 56 ppmW in 2018. These compare to expected non-T4 fuel sulfur levels of 2599 ppmW in 2009 and 2336 ppmW in 2018.

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# Table 6.2-2 uses calculated emissions estimates for base and T4 control scenarios to estimate emission reduction impacts.

Table 6.2-2 Estimated Emission Reduc tion Impacts based on T-4 Rule

2009 2018 CMV SO 2 

## = Non-T4 SO 2 

## × 0.1569 0.0241 Locomotive SO 2 

## = Non-T4 SO 2 

## × 0.1569 0.0241 CMV PM = Non-T4 PM × 0.8962 0.8762 Locomotive PM = Non-T4 PM × 0.8117 0.7734



# However, since the diesel fuel sulfur content assumed for the 2002 VISTAS base year inventory, upon which the 2009 and 2018 inventories were based, is 2500 ppmW, a small adjustment to the emission reduction multiplier calculated from the T4 rule is appropriate since they are measured relative to modestly different sulfur contents (2599 ppmW for 2009 and 2336 ppmW for 2018). Correcting for these modest differences produces the emission reduction impact estimates relative to forecasts based on the VISTAS 2002 inventory shown in Table 6.2-3.

Table 6.2-3 Estimated Emission Reduction Impacts Relative to VISTAS 2002 Base Year Values

2009 2018 CMV SO 2 

## = Non-T4 SO 2 

## × 0.1632 0.0225 Locomotive SO 2 

## = Non-T4 SO 2 

## × 0.1632 0.0225 CMV PM = Non-T4 PM × 0.9004 0.8685 Locomotive PM = Non-T4 PM × 0.8187 0.7610



# These factors were applied directly to the non-T4 emission forecasts to produce the final VISTAS 2009 and 2018 emissions inventories for aircraft, locomotive, and CMV.

During the development of the preliminary 2018 VISTAS inventory in March 2004, this process yielded reasonable results and exhibited no particular systematic concerns. However, when the initial 2009 inventory was developed, significant concerns related to SO 2 

# and PM were encountered. Essentially, what was revealed by the initial 2009 forecast was a series of apparent inconsistencies in the CAIR 2010 and 2015 emission inventories (as compared to the 1996 and 2020 CAIR inventories) that were masked during the construction of the “longer-term” 2018 inventory.

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# For the most part, the issue seems to be centered on SO 2 

# and PM records, which are those records primarily affected by the T4 rule. But, as noted above, there does not seem to be any pattern of consistency that would indicate that eith er inclusion or exclusion of T4 rule impacts is the underlying cause. Moreover, where they occur, the observed growth extremes generally affect both SO 2 

# and PM equally, while one would expect PM effects to be buffered if the T4 rule was the underlying cause, since changes in diesel fu el sulfur content will only affect a fraction of PM (i.e., sulfate), while directly reducing SO 2 

# .
While forecast inventories for aircraft, locomotives, and CMV were developed for 2009 and 2018 using both growth methods, it was ultimately decided to utilize the 1996-2020 growth basis since it provided more reasonable growth rates for 2009.



# 7. QUALITY ASSURANCE OF 2009 AND 2018 EMISSIONS INVENTORY

For the portion of the 2009 and 2018 inventories developed by North Carolina, specific QA procedures were followed. Under the direction of the Quality Assurance Coordinator, emission sources whose contribution were either at the high or low end of the range of estimates were scrutinized more closely to ensure that the emission estimates were estimated correctly. In addition, the raw data used in the calculations were verified to make sure transference to the spreadsheets was accomplished accurately. Furthermore, the formulas used to calculate the daily emissions were reviewed and checked for correctness. Random independent checks of the calculations were also performed to ensure the accuracy of the inventory.

For the portion of the 2009 and 2018 inventories developed by VISTAS and MACTEC, Inc., specific QA procedures were followed. These procedures are outlined in the document titled Documentation of the Base G 2002 Base Year, 2009, and 2018, Emission Inventories for VISTAS prepared for VISTAS by MACTEC, Inc. Throughout the inventory development process, quality assurance steps were performed to ensure that no double counting of emissions occurred, to ensure that a full and complete inventory was developed for VISTAS, and to make sure that projection calculations were working correctly. Quality assurance was an important component to the inventory development process and MACTEC performed the following QA steps on the stationary and agricultural area source, and the nonroad mobile source components of the 2009 and 2018 emission inventories:

1. All final files were run through EPA’s Format and Content checking software.

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# 2. SCC level emission summaries were prepared and evaluated to ensure that emissions were consistent and that there were no missing sources.

3. Tier comparisons (by pollutant) were developed between the 2002 base year inventory and the 2009 and 2018 projection i nventories. In addition, total VISTAS pollutant summaries were prepared to compare total emissions by pollutant between earlier and later versions of the inventory.

4. Data product summaries were provided to both the VISTAS Emission Inventory Technical Advisor and to the SIWG representatives for review and comment. Changes based on these comments were implemented in the files.

5. Version numbering was used for all inventory files developed. The version numbering process used a decimal system to track major and minor changes. For example, a major change would result in a version going from 1.0 to 2.0. A minor change would cause a version number to go from 1.0 to 1.1. Minor changes resulting from largely editorial changes would result in a change from 1.00 to 1.01.

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# 8. ADDITIONAL DATA

8.1 SIC TO NAICS CROSSWALK

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# 8.2 FRACTION OF NAICS CODE EMPLOYMENT USED TO CREATE SIC EMPLOYMENT

SIC NAICS SIC Employees 1997 NAICS Employees ‘1997 Employee Fraction NAICS description

Factory Finished Wood Surface Coating



# 2426 321918 10521 38100 0.276 Other millwork (including flooring) 

# 2426 337215 6310 75382 0.084 Showcase, partition, shelving, & locker mfg 

# 2426 321912 17109 39763 0.430 Cut stock, resawing lumber, & planing 

# 2429 321113 304 119760 0.003 Sawmills 

# 2429 321920 684 51134 0.013 Wood container & pallet mfg 

# 2429 321999 355 43839 0.008 All other miscellaneous wood product mfg 

# 2431 321911 64771 64771 1.000 Wood window & door mfg 

# 2431 321918 27488 38100 0.721 Other millwork (including flooring) 

# 2434 337110 79579 99257 0.802 Wood kitchen cabinet & counter top mfg 

# 2435 321211 22151 22151 1.000 Hardwood veneer & plywood mfg 

# 2436 321212 28843 28843 1.000 Softwood veneer & plywood mfg 

# 2439 321912 0 39763 0.000 Cut stock, resawing lumber, & planing 

# 2439 321214 32522 32522 1.000 Truss mfg 

# 2439 321113 0 119760 0.000 Sawmills 

# 2439 321213 5372 5372 1.000 Engineered wood member (except truss) mfg 

# 2441 321920 4885 51134 0.096 Wood container & pallet mfg 

# 2448 321920 38994 51134 0.763 Wood container & pallet mfg 

# 2449 321920 5701 51134 0.111 Wood container & pallet mfg 

# 2451 321991 68269 68269 1.000 Manufactured home (mobile home) mfg 

# 2452 321992 22965 22965 1.000 Prefabricated wood building mfg 

# 2493 321219 25269 25269 1.000 Reconstituted wood product mfg 

# 2499 339999 13740 74137 0.185 All other miscellaneous mfg 

# 2499 332321 0 74944 0.000 Metal window & door mfg 

# 2499 321920 870 51134 0.017 Wood container & pallet mfg 

# 2499 321912 549 39763 0.014 Cut stock, resawing lumber, & planing 

# 2499 321999 41844 43839 0.954 All other miscellaneous wood product mfg Furniture & Fixtures Surface Coating and Part of Miscellaneous Degreasing



# 2511 337122 123368 128248 0.962 Nonupholstered wood household furniture mfg 

# 2512 337121 85258 90009 0.947 Upholstered household furniture mfg 

# 2514 337124 22835 22835 1.000 Metal household furniture mfg 

# 2515 337121 1601 90009 0.018 Upholstered household furniture mfg 

# 2515 337910 23072 23072 1.000 Mattress mfg

## Emissions Preparations & Results Appendix D.2b -120 Regional Haze SIP for NC Class I Areas December 17, 2007 

# SIC NAICS SIC Employees 1997 NAICS Employees ‘1997 Employee Fraction NAICS description



# 2517 337129 4273 4273 1.000 Wood television, radio, & sewing machine cabinet mfg 

# 2519 337125 4708 4708 1.000 Household furniture (except wood & metal) mfg 

# 2521 337211 30641 30641 1.000 Wood office furniture mfg 

# 2522 337214 44222 44222 1.000 Office furniture (except wood) mfg 

# 2531 336360 20784 45600 0.456 Motor vehicle seating & interior trim mfg 

# 2531 337127 15254 38218 0.399 Institutional furniture mfg 

# 2531 339942 941 7990 0.118 Lead pencil & art good mfg 

# 2541 337110 9785 99257 0.099 Wood kitchen cabinet & counter top mfg 

# 2541 337212 24363 24363 1.000 Custom architectural woodwork & millwork mfg 

# 2541 337215 23305 75382 0.309 Showcase, partition, shelving, & locker mfg 

# 2542 337215 44472 75382 0.590 Showcase, partition, shelving, & locker mfg 

# 2591 337920 19617 19617 1.000 Blind & shade mfg 

# 2599 337127 22448 38218 0.587 Institutional furniture mfg 

# 2599 339113 2925 85315 0.034 Surgical appliance & supplies mfg Part of Misc. Degreasing



# 3312 324199 1731 3671 0.472 All other petroleum & coal products mfg 

# 3312 331111 144074 146514 0.983 Iron & steel mills 

# 3313 331112 3724 3724 1.000 Electrometallurgical ferroalloy product mfg 

# 3313 331492 311 11610 0.027 Other nonferrous metal secondary smelting, refining, & alloying 

# 3315 331222 23489 23489 1.000 Steel wire drawing 

# 3315 332618 2265 46174 0.049 Other fabricated wire product mfg 

# 3316 331221 14362 14362 1.000 Cold-rolled steel shape mfg 

# 3317 331210 27723 27723 1.000 Iron & steel pipes & tubes mfg from purchased steel 

# 3321 331511 83570 86198 0.970 Iron foundries 

# 3322 331511 2628 86198 0.030 Iron foundries 

# 3324 331512 22673 22673 1.000 Steel investment foundries 

# 3325 331513 23982 23982 1.000 Steel foundries (except investment) 

# 3331 331411 7360 7360 1.000 Primary smelting & refining of copper 

# 3334 331312 15763 15763 1.000 Primary aluminum production 

# 3339 331419 10132 10132 1.000 Other nonferrous metal primary smelting & refining 

# 3341 331423 1768 2333 0.758 Secondary smelting, refining, & alloying of copper

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# SIC NAICS SIC Employees 1997 NAICS Employees ‘1997 Employee Fraction NAICS description



# 3341 331492 5485 11610 0.472 Other nonferrous metal secondary smelting, refining, & alloying 

# 3341 331314 6226 6714 0.927 Secondary smelting & alloying of aluminum 

# 3351 331421 21150 21150 1.000 Copper rolling, drawing, & extruding 

# 3353 331315 25111 25111 1.000 Aluminum sheet, plate, & foil mfg 

# 3353 332996 0 29364 0.000 Fabricated pipe & pipe fitting mfg 

# 3354 331316 30357 30357 1.000 Aluminum extruded product mfg 

# 3355 331319 2657 4306 0.617 Other aluminum rolling & drawing 

# 3356 331491 17237 25872 0.666 Other nonferrous metal rolling, drawing, & extruding Part of Misc. Degreasing and Part of Electrical Insulation Surface Coating



# 3357 331319 1649 4306 0.383 Other aluminum rolling & drawing 

# 3357 331422 4692 4692 1.000 Copper wire (except mechanical) drawing 

# 3357 331491 8635 25872 0.334 Other nonferrous metal rolling, drawing, & extruding 

# 3357 335921 8589 8589 1.000 Fiber optic cable mfg 

# 3357 335929 46267 46267 1.000 Other communication & energy wire mfg Part of Misc. Degreasing



# 3363 331521 27717 27717 1.000 Aluminum die-casting foundries 

# 3364 331522 17243 17243 1.000 Nonferrous (except aluminum) die-casting foundries 

# 3365 331524 34098 34098 1.000 Aluminum foundries (except die-casting) 

# 3366 331525 8909 8909 1.000 Copper foundries (except die-casting) 

# 3369 331528 6529 6529 1.000 Other nonferrous foundries (except diecasting) 

# 3398 332811 22674 22674 1.000 Metal heat treating 

# 3399 331111 2440 146514 0.017 Iron & steel mills 

# 3399 331314 488 6714 0.073 Secondary smelting & alloying of aluminum 

# 3399 331423 565 2333 0.242 Secondary smelting, refining, & alloying of copper 

# 3399 331492 5814 11610 0.501 Other nonferrous metal secondary smelting, refining, & alloying 

# 3399 332618 2088 46174 0.045 Other fabricated wire product mfg Part of Misc. Degreasing and Metal Containers Surface Coating



# 3411 332431 27316 27316 1.000 Metal can mfg 

# 3412 332439 6318 14922 0.423 Other metal container mfg Part of Misc. Degreasing



# 3421 332211 11129 11230 0.991 Cutlery & flatware (except precious) mfg 

# 3423 332212 42947 50388 0.852 Hand & edge tool mfg

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# SIC NAICS SIC Employees 1997 NAICS Employees ‘1997 Employee Fraction NAICS description



# 3425 332213 9149 9149 1.000 Saw blade & handsaw mfg 

# 3429 332439 4135 14922 0.277 Other metal container mfg 

# 3429 332510 70884 74285 0.954 Hardware mfg 

# 3429 332919 750 18739 0.040 Other metal valve & pipe fitting mfg 

# 3431 332998 9994 9994 1.000 Enameled iron & metal sanitary ware mfg 

# 3432 332913 16202 16202 1.000 Plumbing fixture fitting & trim mfg 

# 3432 332999 474 79070 0.006 All other miscellaneous fabricated metal product mfg 

# 3433 333414 22495 24666 0.912 Heating equipment (except warm air furnaces) mfg 

# 3441 332312 84704 93433 0.907 Fabricated structural metal mfg 

# 3442 332321 72970 74944 0.974 Metal window & door mfg 

# 3443 333415 339 119795 0.003 AC & warm air heating & commercial/industrial refrig equip mfg 

# 3443 332420 33704 33704 1.000 Metal tank (heavy gauge) mfg 

# 3443 332313 25453 25453 1.000 Plate work mfg 

# 3443 332410 27542 27542 1.000 Power boiler & heat exchanger mfg 

# 3444 332322 129826 129826 1.000 Sheet metal work mfg 

# 3444 332439 2074 14922 0.139 Other metal container mfg 

# 3446 332323 30960 34391 0.900 Ornamental & architectural metal work mfg 

# 3448 332311 25946 25946 1.000 Prefabricated metal building & component mfg 

# 3449 332114 15219 15219 1.000 Custom roll forming 

# 3449 332312 8729 93433 0.093 Fabricated structural metal mfg 

# 3449 332321 1974 74944 0.026 Metal window & door mfg 

# 3449 332323 349 34391 0.010 Ornamental & architectural metal work mfg 

# 3451 332721 80404 80404 1.000 Precision turned product mfg 

# 3452 332722 52995 52995 1.000 Bolt, nut, screw, rivet, & washer mfg 

# 3462 332111 26432 26432 1.000 Iron & steel forging 

# 3463 332112 9129 9129 1.000 Nonferrous forging 

# 3465 336370 126905 126905 1.000 Motor vehicle metal stamping 

# 3466 332115 4682 4682 1.000 Crown & closure mfg 

# 3469 332116 93086 93086 1.000 Metal stamping 

# 3469 332214 7724 7724 1.000 Kitchen utensil, pot, & pan mfg 

# 3471 332813 74640 74640 1.000 Electroplating, plating, polishing, anodizing, & coloring

## Emissions Preparations & Results Appendix D.2b -123 Regional Haze SIP for NC Class I Areas December 17, 2007 

# SIC NAICS SIC Employees 1997 NAICS Employees ‘1997 Employee Fraction NAICS description

Part of Misc. Degreasing and Sheet, Strip & Coil Surface Coating



# 3479 332812 55904 55904 1.000 Metal coating/engraving (exc jewelry/silverware)/allied services 

# 3479 339911 79 34773 0.002 Jewelry (except costume) mfg 

# 3479 339912 103 6459 0.016 Silverware & plated ware mfg 

# 3479 339914 29 14573 0.002 Costume jewelry & novelty mfg Part of Misc. Degreasing



# 3482 332992 6863 6863 1.000 Small arms ammunition mfg 

# 3483 332993 9427 9427 1.000 Ammunition (except small arms) mfg 

# 3484 332994 9907 9907 1.000 Small arms mfg 

# 3489 332995 12285 12285 1.000 Other ordnance & accessories mfg 

# 3491 332911 53459 53459 1.000 Industrial valve mfg 

# 3492 332912 37132 37132 1.000 Fluid power valve & hose fitting mfg 

# 3493 332611 5381 5381 1.000 Spring (heavy gauge) mfg 

# 3494 332919 17652 18739 0.942 Other metal valve & pipe fitting mfg 

# 3494 332999 564 79070 0.007 All other miscellaneous fabricated metal product mfg 

# 3495 332612 18798 18798 1.000 Spring (light gauge) mfg 

# 3495 334518 175 6333 0.028 Watch, clock, & part mfg 

# 3496 332618 41821 46174 0.906 Other fabricated wire product mfg 

# 3497 332999 5648 79070 0.071 All other miscellaneous fabricated metal product mfg 

# 3497 322225 4967 4967 1.000 Laminated aluminum foil mfg for flexible packaging uses 

# 3498 332996 29364 29364 1.000 Fabricated pipe & pipe fitting mfg 

# 3499 332439 2331 14922 0.156 Other metal container mfg 

# 3499 332510 3401 74285 0.046 Hardware mfg 

# 3499 332919 375 18739 0.020 Other metal valve & pipe fitting mfg 

# 3499 332999 63736 79070 0.806 All other miscellaneous fabricated metal product mfg 

# 3499 337215 1295 75382 0.017 Showcase, partition, shelving, & locker mfg 

# 3499 339914 568 14573 0.039 Costume jewelry & novelty mfg 

# 3499 332117 10760 10760 1.000 Powder metallurgy part mfg Part of Misc. Degreasing and Machinery & Equipment Surface Coating



# 3511 333611 19529 19529 1.000 Turbine & turbine generator set unit mfg 

# 3519 333618 56338 56348 1.000 Other engine equipment mfg 

# 3519 336399 896 174465 0.005 All other motor vehicle parts mfg 

# 3523 332212 60 50388 0.001 Hand & edge tool mfg

## Emissions Preparations & Results Appendix D.2b -124 Regional Haze SIP for NC Class I Areas December 17, 2007 

# SIC NAICS SIC Employees 1997 NAICS Employees ‘1997 Employee Fraction NAICS description



# 3523 333922 320 39599 0.008 Conveyor & conveying equipment mfg 

# 3523 333111 66370 66370 1.000 Farm machinery & equipment mfg 

# 3523 332323 3082 34391 0.090 Ornamental & architectural metal work mfg 

# 3524 332212 60 50388 0.001 Hand & edge tool mfg 

# 3524 333112 28617 28617 1.000 Lawn & garden tractor & home lawn & garden equipment mfg 

# 3531 333120 74965 74965 1.000 Construction machinery mfg 

# 3531 333923 10263 18014 0.570 Overhead traveling crane, hoist, & monorail system mfg 

# 3531 336510 2379 34012 0.070 Railroad rolling stock mfg 

# 3532 333131 13547 13547 1.000 Mining machinery & equipment mfg 

# 3533 333132 29451 29451 1.000 Oil & gas field machinery & equipment mfg 

# 3534 333921 9442 9442 1.000 Elevator & moving stairway mfg 

# 3535 333922 39279 39599 0.992 Conveyor & conveying equipment mfg 

# 3536 333923 7751 18014 0.430 Overhead traveling crane, hoist, & monorail system mfg 

# 3537 333924 25953 25953 1.000 Industrial truck, tractor, trailer, & stacker machinery mfg 

# 3537 332439 64 14922 0.004 Other metal container mfg 

# 3537 332999 240 79070 0.003 All other miscellaneous fabricated metal product mfg 

# 3541 333512 28849 29371 0.982 Machine tool (metal cutting types) mfg 

# 3542 333513 14185 14185 1.000 Machine tool (metal forming types) mfg 

# 3543 332997 7959 7959 1.000 Industrial pattern mfg 

# 3544 333511 48657 48657 1.000 Industrial mold mfg 

# 3544 333514 80113 80113 1.000 Special die & tool, die set, jig, & fixture mfg 

# 3545 332212 6379 50388 0.127 Hand & edge tool mfg 

# 3545 333515 47925 47925 1.000 Cutting tool & machine tool accessory mfg 

# 3546 333991 16816 16816 1.000 Power-driven handtool mfg 

# 3547 333516 4149 4149 1.000 Rolling mill machinery & equipment mfg 

# 3548 335311 0 26638 0.000 Power, distribution, & specialty transformer mfg 

# 3548 333992 22434 22505 0.997 Welding & soldering equipment mfg 

# 3549 333518 19023 19023 1.000 Other metalworking machinery mfg 

# 3552 333292 13600 13600 1.000 Textile machinery mfg 

# 3553 333210 9117 9117 1.000 Sawmill & woodworking machinery mfg 

# 3554 333291 18594 18594 1.000 Paper industry machinery mfg 

# 3555 333293 17500 21000 0.833 Printing machinery & equipment mfg

## Emissions Preparations & Results Appendix D.2b -125 Regional Haze SIP for NC Class I Areas December 17, 2007 

# SIC NAICS SIC Employees 1997 NAICS Employees ‘1997 Employee Fraction NAICS description



# 3556 333294 19026 19026 1.000 Food product machinery mfg 

# 3559 333319 2890 56910 0.051 Other commercial & service industry machinery mfg 

# 3559 333220 18574 18574 1.000 Plastics & rubber industry machinery mfg 

# 3559 333295 40087 40087 1.000 Semiconductor machinery mfg 

# 3559 333298 53046 53106 0.999 All other industrial machinery mfg 

# 3561 333911 36552 36552 1.000 Pump & pumping equipment mfg 

# 3562 332991 36991 36991 1.000 Ball & roller bearing mfg 

# 3563 333912 24821 24821 1.000 Air & gas compressor mfg 

# 3564 333411 16183 16183 1.000 Air purification equipment mfg 

# 3564 333412 13723 13723 1.000 Industrial & commercial fan & blower mfg 

# 3565 333993 31581 31581 1.000 Packaging machinery mfg 

# 3566 333612 16231 16231 1.000 Speed changer, industrial high-speed drive, & gear mfg 

# 3567 333994 17585 17585 1.000 Industrial process furnace & oven mfg 

# 3568 333613 21604 21604 1.000 Mechanical power transmission equipment mfg 

# 3569 333999 50088 61151 0.819 All other miscellaneous general-purpose machinery mfg 

# 3571 334111 100115 100115 1.000 Electronic computer mfg 

# 3572 334112 42364 42364 1.000 Computer storage device mfg 

# 3575 334113 5764 5764 1.000 Computer terminal mfg 

# 3577 334119 87253 93970 0.929 Other computer peripheral equipment mfg 

# 3578 333313 966 14831 0.065 Office machinery mfg 

# 3578 334119 6717 93970 0.071 Other computer peripheral equipment mfg 

# 3579 333313 13865 14831 0.935 Office machinery mfg 

# 3579 334518 750 6333 0.118 Watch, clock, & part mfg 

# 3579 339942 1234 7990 0.154 Lead pencil & art good mfg 

# 3581 333311 8178 8178 1.000 Automatic vending machine mfg 

# 3582 333312 4523 4523 1.000 Commercial laundry, drycleaning, & pressing machine mfg 

# 3585 333415 119456 119795 0.997 AC & warm air heating & commercial/industrial refrig equip mfg 

# 3585 336391 21522 21522 1.000 Motor vehicle air-conditioning mfg 

# 3586 333913 6824 6824 1.000 Measuring & dispensing pump mfg 

# 3589 333319 44172 56910 0.776 Other commercial & service industry machinery mfg 

# 3592 336311 17518 17518 1.000 Carburetor, piston, piston ring, & valve mfg 

# 3593 333995 23062 23062 1.000 Fluid power cylinder & actuator mfg

## Emissions Preparations & Results Appendix D.2b -126 Regional Haze SIP for NC Class I Areas December 17, 2007 

# SIC NAICS SIC Employees 1997 NAICS Employees ‘1997 Employee Fraction NAICS description



# 3594 333996 15482 15482 1.000 Fluid power pump & motor mfg 

# 3596 333997 4871 4871 1.000 Scale & balance (except laboratory) mfg 

# 3599 332710 290951 290951 1.000 Machine shops 

# 3599 332999 4199 79070 0.053 All other miscellaneous fabricated metal product mfg 

# 3599 333319 1335 56910 0.023 Other commercial & service industry machinery mfg 

# 3599 333999 11063 61151 0.181 All other miscellaneous general-purpose machinery mfg Part of Misc. & Electronic Degreasing and Part of Electrical Insulation Surface Coating



# 3612 335311 26638 26638 1.000 Power, distribution, & specialty transformer mfg Part of Misc. & Electronic Degreasing



# 3613 335313 41291 41291 1.000 Switchgear & switchboard apparatus mfg 

# 3621 335312 71112 74666 0.952 Motor & generator mfg 

# 3624 335991 10887 10887 1.000 Carbon & graphite product mfg 

# 3625 335314 68365 68365 1.000 Relay & industrial control mfg 

# 3629 335999 18682 44754 0.417 All other miscellaneous electrical equipment & component mfg Part of Misc. & Electronic Degreasing and Appliance Surface Coating



# 3631 335221 17543 17543 1.000 Household cooking appliance mfg 

# 3632 335222 24597 24597 1.000 Household refrigerator & home freezer mfg 

# 3633 335224 14801 14801 1.000 Household laundry equipment mfg 

# 3634 333414 2171 24666 0.088 Heating equipment (except warm air furnaces) mfg 

# 3634 335211 17058 17058 1.000 Electric housewares & household fan mfg 

# 3635 335212 10537 10537 1.000 Household vacuum cleaner mfg 

# 3639 333298 60 53106 0.001 All other industrial machinery mfg 

# 3639 335212 0 10537 0.000 Household vacuum cleaner mfg 

# 3639 335228 13309 13309 1.000 Other major household appliance mfg Part of Misc. & Electronic Degreasing



# 3641 335110 15903 15903 1.000 Electric lamp bulb & part mfg 

# 3643 335931 44907 44907 1.000 Current-carrying wiring device mfg 

# 3644 335932 23540 23540 1.000 Noncurrent-carrying wiring device mfg 

# 3645 335121 16395 17685 0.927 Residential electric lighting fixture mfg 

# 3646 335122 23090 23090 1.000 Commercial/industrial/institutional electric lighting fixture mfg 

# 3647 336321 16506 16506 1.000 Vehicular lighting equipment mfg 

# 3648 335129 18274 18282 1.000 Other lighting equipment mfg

## Emissions Preparations & Results Appendix D.2b -127 Regional Haze SIP for NC Class I Areas December 17, 2007 

# SIC NAICS SIC Employees 1997 NAICS Employees ‘1997 Employee Fraction NAICS description



# 3651 334310 31727 31727 1.000 Audio & video equipment mfg 

# 3652 334612 16598 25554 0.650 Prerecorded CD (except software), tape, & record reproducing 

# 3661 334210 104262 104262 1.000 Telephone apparatus mfg 

# 3661 334416 63 19431 0.003 Electronic coil, transformer, & other inductor mfg 

# 3661 334418 6083 111054 0.055 Printed circuit assembly (electronic assembly) mfg 

# 3663 334220 148156 164461 0.901 Radio & TV broadcasting & wireless communications equipment mfg 

# 3669 334290 25187 25187 1.000 Other communications equipment mfg 

# 3671 334411 21976 21976 1.000 Electron tube mfg 

# 3672 334412 76702 76702 1.000 Bare printed circuit board mfg 

# 3674 334413 199497 199497 1.000 Semiconductor & related device mfg 

# 3675 334414 18882 18882 1.000 Electronic capacitor mfg 

# 3676 334415 11964 11964 1.000 Electronic resistor mfg 

# 3677 334416 19178 19431 0.987 Electronic coil, transformer, & other inductor mfg 

# 3678 334417 37232 37232 1.000 Electronic connector mfg 

# 3679 336322 12786 95491 0.134 Other motor vehicle electrical & electronic equipment mfg 

# 3679 334220 16305 164461 0.099 Radio & TV broadcasting & wireless communications equipment mfg 

# 3679 334418 104971 111054 0.945 Printed circuit assembly (electronic assembly) mfg 

# 3679 334419 92200 92200 1.000 Other electronic component mfg 

# 3691 335911 23288 23288 1.000 Storage battery mfg 

# 3692 335912 8917 8917 1.000 Primary battery mfg 

# 3694 336322 52216 95491 0.547 Other motor vehicle electrical & electronic equipment mfg 

# 3695 334613 21345 21345 1.000 Magnetic & optical recording media mfg 

# 3699 333992 71 22505 0.003 Welding & soldering equipment mfg 

# 3699 335999 26072 44754 0.583 All other miscellaneous electrical equipment & component mfg 

# 3699 335129 8 18282 0.000 Other lighting equipment mfg 

# 3699 334519 29 33933 0.001 Other measuring & controlling device mfg 

# 3699 334516 159 38359 0.004 Analytical laboratory instrument mfg 

# 3699 334119 0 93970 0.000 Other computer peripheral equipment mfg 

# 3699 334510 542 54385 0.010 Electromedical & electrotherapeutic apparatus mfg

## Emissions Preparations & Results Appendix D.2b -128 Regional Haze SIP for NC Class I Areas December 17, 2007 

# SIC NAICS SIC Employees 1997 NAICS Employees ‘1997 Employee Fraction NAICS description



# 3699 339114 0 18072 0.000 Dental equipment & supplies mfg 

# 3699 333512 522 29371 0.018 Machine tool (metal cutting types) mfg 

# 3699 333319 8513 56910 0.150 Other commercial & service industry machinery mfg 

# 3699 333315 0 24707 0.000 Photographic & photocopying equipment mfg 

# 3699 333314 56 20857 0.003 Optical instrument & lens mfg 

# 3699 333293 175 21000 0.008 Printing machinery & equipment mfg 

# 3699 333292 0 13600 0.000 Textile machinery mfg 

# 3699 332212 424 50388 0.008 Hand & edge tool mfg 

# 3699 334511 604 188161 0.003 Search, detection, navigation, & guidance instrument mfg 

# 3699 333618 10 56348 0.000 Other engine equipment mfg Part of Misc. Degreasing and New Automobile Surface Coating



# 3711 336992 375 5788 0.065 Military armored vehicle, tank, & tank component mfg 

# 3711 336111 114060 114060 1.000 Automobile mfg 

# 3711 336112 94033 94033 1.000 Light truck & utility vehicle mfg 

# 3711 336120 28214 28214 1.000 Heavy duty truck mfg 

# 3711 336211 404 43384 0.009 Motor vehicle body mfg Part of Misc. Degreasing and Part of Othe r Transportation Equipment Surface Coating



# 3713 336211 41779 43384 0.963 Motor vehicle body mfg 

# 3714 336312 81368 81368 1.000 Gasoline engine & engine parts mfg 

# 3714 336322 30489 95491 0.319 Other motor vehicle electrical & electronic equipment mfg 

# 3714 336330 48944 48944 1.000 Motor vehicle steering & suspension component (except spring) mfg 

# 3714 336340 43132 43132 1.000 Motor vehicle brake system mfg 

# 3714 336350 111954 111954 1.000 Motor vehicle transmission & power train parts mfg 

# 3714 336399 173569 174465 0.995 All other motor vehicle parts mfg 

# 3714 336211 1201 43384 0.028 Motor vehicle body mfg 

# 3715 336212 30678 30678 1.000 Truck trailer mfg 

# 3716 336213 18086 18086 1.000 Motor home mfg 

# 3721 336411 200961 200961 1.000 Aircraft mfg 

# 3724 336412 82557 82557 1.000 Aircraft engine & engine parts mfg 

# 3728 332912 0 37132 0.000 Fluid power valve & hose fitting mfg 

# 3728 336413 127729 127729 1.000 Other aircraft part & auxiliary equipment mfg 

# 3728 333995 0 23062 0.000 Fluid power cylinder & actuator mfg

## Emissions Preparations & Results Appendix D.2b -129 Regional Haze SIP for NC Class I Areas December 17, 2007 

# SIC NAICS SIC Employees 1997 NAICS Employees ‘1997 Employee Fraction NAICS description



# 3728 333996 0 15482 0.000 Fluid power pump & motor mfg Part of Misc. Degreasing and Marine Surface Coating



# 3731 336611 97385 97385 1.000 Ship building & repairing 

# 3732 336612 41422 41422 1.000 Boat building 

# 3732 811490 9454 65213 0.145 Other personal & household goods repair & maintenance Part of Misc. Degreasing and Part of Othe r Transportation Equipment Surface Coating



# 3743 333911 0 36552 0.000 Pump & pumping equipment mfg 

# 3743 336510 31633 34012 0.930 Railroad rolling stock mfg 

# 3751 336991 17158 17218 0.997 Motorcycle, bicycle, & parts mfg 

# 3761 336414 52158 52158 1.000 Guided missile & space vehicle mfg 

# 3764 336415 18540 18540 1.000 Guided missile & space vehicle propulsion unit & parts mfg 

# 3769 336419 6110 6110 1.000 Other guided missile & space vehicle parts & auxiliary equip mfg 

# 3792 336214 20112 33352 0.603 Travel trailer & camper mfg 

# 3795 336992 5415 5788 0.936 Military armored vehicle, tank, & tank component mfg 

# 3799 336214 13240 33352 0.397 Travel trailer & camper mfg 

# 3799 336999 19466 19466 1.000 All other transportation equipment mfg 

# 3799 332212 60 50388 0.001 Hand & edge tool mfg Part of Misc. Degreasing



# 3812 334511 187557 188161 0.997 Search, detection, navigation, & guidance instrument mfg 

# 3821 339111 18253 18253 1.000 Laboratory apparatus & furniture mfg 

# 3822 334512 21450 21450 1.000 Automatic environmental control mfg 

# 3823 334513 49196 49196 1.000 Industrial process control instrument mfg 

# 3824 334514 17390 17390 1.000 Totalizing fluid meter & counting device mfg 

# 3825 334416 190 19431 0.010 Electronic coil, transformer, & other inductor mfg 

# 3825 334515 63332 63332 1.000 Electricity measuring & testing instrument mfg 

# 3826 334516 38200 38359 0.996 Analytical laboratory instrument mfg 

# 3827 333314 20801 20857 0.997 Optical instrument & lens mfg 

# 3829 339112 521 107819 0.005 Surgical & medical instrument mfg 

# 3829 334519 33904 33933 0.999 Other measuring & controlling device mfg 

# 3841 339112 107298 107819 0.995 Surgical & medical instrument mfg 

# 3842 322121 375 120176 0.003 Paper (except newsprint) mills 

# 3842 322291 2236 21791 0.103 Sanitary paper product mfg

## Emissions Preparations & Results Appendix D.2b -130 Regional Haze SIP for NC Class I Areas December 17, 2007 

# SIC NAICS SIC Employees 1997 NAICS Employees ‘1997 Employee Fraction NAICS description



# 3842 334510 6722 54385 0.124 Electromedical & electrotherapeutic apparatus mfg 

# 3842 339113 82390 85315 0.966 Surgical appliance & supplies mfg 

# 3843 339114 18072 18072 1.000 Dental equipment & supplies mfg 

# 3844 334517 14276 14276 1.000 Irradiation apparatus mfg 

# 3845 334510 47121 54385 0.866 Electromedical & electrotherapeutic apparatus mfg 

# 3851 339115 26366 26366 1.000 Ophthalmic goods mfg 

# 3861 325992 38935 38935 1.000 Photographic film, paper, plate, & chemical mfg 

# 3861 333315 24707 24707 1.000 Photographic & photocopying equipment mfg 

# 3873 334518 5646 6333 0.892 Watch, clock, & part mfg 

# 3911 339911 34694 34773 0.998 Jewelry (except costume) mfg 

# 3914 332211 101 11230 0.009 Cutlery & flatware (except precious) mfg 

# 3914 339912 6356 6459 0.984 Silverware & plated ware mfg 

# 3915 339913 5396 5396 1.000 Jewelers' material & lapidary work mfg 

# 3931 339992 13411 13411 1.000 Musical instrument mfg 

# 3942 339931 3393 3393 1.000 Doll & stuffed toy mfg 

# 3944 336991 60 17218 0.003 Motorcycle, bicycle, & parts mfg 

# 3944 339932 29622 29622 1.000 Game, toy, & children's vehicle mfg 

# 3949 339920 69664 69664 1.000 Sporting & athletic goods mfg 

# 3951 339941 8394 8394 1.000 Pen & mechanical pencil mfg 

# 3952 339942 5815 7990 0.728 Lead pencil & art good mfg 

# 3952 337127 187 38218 0.005 Institutional furniture mfg 

# 3952 325998 0 35915 0.000 All other miscellaneous chemical product & preparation mfg 

# 3953 339943 7831 7831 1.000 Marking device mfg 

# 3955 339944 5923 5923 1.000 Carbon paper & inked ribbon mfg 

# 3961 339914 13976 14573 0.959 Costume jewelry & novelty mfg 

# 3965 339993 7500 7842 0.956 Fastener, button, needle, & pin mfg 

# 3991 339994 13882 16826 0.825 Broom, brush, & mop mfg 

# 3993 339950 82956 82956 1.000 Sign mfg 

# 3995 339995 6962 6962 1.000 Burial casket mfg 

# 3996 326192 5614 6070 0.925 Resilient floor covering mfg 

# 3999 323119 0 33016 0.000 Other commercial printing 

# 3999 337127 329 38218 0.009 Institutional furniture mfg 

# 3999 335121 1216 17685 0.069 Residential electric lighting fixture mfg

## Emissions Preparations & Results Appendix D.2b -131 Regional Haze SIP for NC Class I Areas December 17, 2007 

# SIC NAICS SIC Employees 1997 NAICS Employees ‘1997 Employee Fraction NAICS description



# 3999 332999 3231 79070 0.041 All other miscellaneous fabricated metal product mfg 

# 3999 332212 750 50388 0.015 Hand & edge tool mfg 

# 3999 326199 3141 526382 0.006 All other plastics product mfg 

# 3999 325998 572 35915 0.016 All other miscellaneous chemical product & preparation mfg 

# 3999 314999 2167 64480 0.034 All other miscellaneous textile product mills 

# 3999 323113 0 72221 0.000 Commercial screen printing 

# 3999 339999 60397 74137 0.815 All other miscellaneous mfg 

# 3999 316110 329 15317 0.021 Leather & hide tanning & finishing 

# 3999 321999 0 43839 0.000 All other miscellaneous wood product mfg 

# 3999 322299 0 24302 0.000 All other converted paper product mfg 

# 3999 323110 0 415117 0.000 Commercial lithographic printing 

# 3999 323111 0 23260 0.000 Commercial gravure printing 

# 3999 323112 0 30588 0.000 Commercial flexographic printing Part of Misc. Open Top Degreasing & Auto Repair Cold Cleaning



# 4173 488490 220 7480 0.029 Other support activities for road transportation 

# 4231 488490 120 7480 0.016 Other support activities for road transportation 

# 5511 441110 1046243 1046243 1.000 New car dealers 

# 5521 441120 92752 92752 1.000 Used car dealers 

# 5541 447190 69640 308105 0.226 Other gasoline stations 

# 5541 447110 432935 613957 0.705 Gasoline stations with convenience stores 

# 5541 447190 238465 308105 0.774 Other gasoline stations 

# 5551 441222 35134 35134 1.000 Boat dealers 

# 5561 441210 29463 29463 1.000 Recreational vehicle dealers 

# 7532 811121 192853 205172 0.940 Automotive body, paint, & interior repair & maintenance 

# 7532 811121 6507 205172 0.032 Automotive body, paint, & interior repair & maintenance 

# 7532 811121 5812 205172 0.028 Automotive body, paint, & interior repair & maintenance 

# 7533 811112 23015 23015 1.000 Automotive exhaust system repair 

# 7534 811198 2991 14780 0.202 All other automotive repair & maintenance 

# 7534 326212 7939 7939 1.000 Tire retreading 

# 7536 811122 29187 29187 1.000 Automotive glass replacement shops 

# 7537 811113 29442 29442 1.000 Automotive transmission repair 

# 7538 811111 290634 290634 1.000 General automotive repair

## Emissions Preparations & Results Appendix D.2b -132 Regional Haze SIP for NC Class I Areas December 17, 2007 

# SIC NAICS SIC Employees 1997 NAICS Employees ‘1997 Employee Fraction NAICS description



# 7539 811118 3954 42234 0.094 Other automotive mechanical & electrical repair & maintenance 

# 7539 811118 4802 42234 0.114 Other automotive mechanical & electrical repair & maintenance 

# 7539 811118 18216 42234 0.431 Other automotive mechanical & electrical repair & maintenance 

# 7539 811118 6890 42234 0.163 Other automotive mechanical & electrical repair & maintenance 

# 7539 811118 8372 42234 0.198 Other automotive mechanical & electrical repair & maintenance Dry Cleaning



# 7215 812310 53023 53023 1.000 Dry cleaning, coin operated 

# 7216 812320 166208 203777 0.816 Dry cleaning, commercial

# Appendix D.2c

On-Road Mobile Source Emissions Inventory Documentation

## Emissions Preparations & Results Appendix D.2c - 1 Regional Haze SIP for NC Class I Areas December 17, 2007

## Emissions Preparations & Results Appendix D.2c - 2 Regional Haze SIP for NC Class I Areas December 17, 2007 

# TABLE OF CONTENTS

1. INTRODUCTION AND SCOPE ...................................................................................................3

2. OVERALL METHODOLOGY......................................................................................................3
2.1 SOURCE CATEGORY......................................................................................................3
2.2 EMISSION ESTIMATION APPROACH..........................................................................3
3. QUALITY ASSURANCE MEASURES........................................................................................4

4. DISCUSSION OF MOBILE SOURCE CATEGORIES................................................................5 4.1 MOBILE6.2 Input Assumptions.........................................................................................5 4.1.1 Speed Assumptions........................................................................................................ .5 4.1.2 Vehicle Age Distribution ................................................................................................7 4.1.3 Vehicle Mix Assumptions...............................................................................................8 4.1.4 Temperature, Relative Humidity and Barometric Pressure Assumptions ....................15 4.1.5 Vehicle Inspection and Mainte nance Program Assumptions .......................................15 4.1.6 Reid Vapor Pressure Assumptions................................................................................15 4.2 VMT Assumptions............................................................................................................ 16

LIST OF TABLES

Table 4.1-1. Speeds used for NC’s 2002 On-road Mobile Emissions Iventory ................................6 Table 4.1-2. Speeds used for NC’s 2018 On-road Mobile Emissions Iventory ................................7 Table 4.1-3. Percentage of Ve hicles Per Vehicle Type by F unctional Road Class in NC ................9 Table 4.1-4. Calculation of New 2000 Statewide Rural In terstate Vehicle Mix .............................12 Table 4.1-5. Calculation of 2002 NC Statewide Rural Inte rstate Vehicle Mix ................................14 Table 4.2-1. North Carolina 2002 Daily Vehicle Miles Traveled by County..................................16 Table 4.2-2. North Carolina 2018 Daily Vehicle Miles Traveled by County..................................19

## Emissions Preparations & Results Appendix D.2c - 3 Regional Haze SIP for NC Class I Areas December 17, 2007 

# 1. INTRODUCTION AND SCOPE
The regional haze modeling was performed by the Southeast Regional Planning Organization, Visibility Improvement State and Tribal Associa tion of the Southeast (VISTAS), which is run by the ten Southeast states (Alabama, Florida, Georgia, Kentucky, Mississippi, North Carolina, South Carolina, Tennessee, Virginia and West Virginia) and the local programs and tribal agencies located within these states. The regional haze modeling uses an annual simulation, therefore the emission estimates for all pollutants of concern for regional haze were developed for an annual modeling run.

On-road mobile source emissions are very small contributors to visibility degradation in Class I areas in the VISTAS region. Despite playing a small role in visibility impairment, on-road mobile emissions were generated following the same guidelines and methods as those applied to support ozone and fine particulate attainment demonstrations.



# 2. OVERALL METHODOLOGY

2.1 SOURCE CATEGORY
On-road mobile sources were estimated using the U. S. Environmental Protection Agency (USEPA) highway mobile model MOBILE6.2.

2.2 EMISSION ESTIMATION APPROACH
Mobile source emissions are estimated by the methodologies suggested in the USEPA’s document Emissions Inventory Guidance for Implementation of Ozone and Particulate Matter National Ambient Air Quality Standards (NAAQS) and Regional Haze Regulations . The estimation of emissions from on-road mobile sources, like area sources, involves multiplying an activity level (e.g. vehicle miles traveled (VMT) by vehicle type and road type) by an emission factor (grams/mile for a given vehicle type and road type).

The MOBILE6 module of SMOKE was used to develop the on-road mobile source emissions estimates for carbon monoxide (CO), nitrogen oxide s (NOx), ammonia (NH3), fine particulate matter (PM2.5), sulfur dioxide (SO2), and vola tile organic compounds (VOCs) emissions. The MOBILE6 parameters, vehicle fleet descriptions, and VMT estimates were combined with gridded, episode-specific temperature data to calculate the gridded, temporalized emission estimates. Of note, whereas the on-network emissions estimates are spatially allocated based on link location and subsequently summed to the grid cell level, the off-network emissions estimates are spatially allocated based on a combination of the FHWA Version 2.0 highway networks and population. For the VISTAS 36/12 km modeling, no link based data was used. The MOBILE6

## Emissions Preparations & Results Appendix D.2c - 4 Regional Haze SIP for NC Class I Areas December 17, 2007 

# emissions factors are based on episode-specific temperatures predicted by the meteorological model (MM5). Further, the MOBILE6 emissions factors model accounts for the following:

• Hourly and daily minimum/maximum temperatures, relative humidity and barometric pressure;

• Facility speeds;

• Locale-specific inspection/maintenance (I/M) control programs, if any;

• Adjustments for running losses;

• Splitting of evaporative and exhaust emissions into separate source categories;

• VMT, fleet turnover, and changes in fuel composition and Reid vapor pressure (RVP).



# 3. QUALITY ASSURANCE MEASURES
The Quality Assurance (QA) of the data is one of the most important steps in performing an air quality modeling study. Because emissions inventory development is tedious, time consuming and involves complex manipulation of many different types of large data sets, errors are frequently made and, if rigorous QA measures are not in place, these errors may remain undetected. For the on-road mobile source category, QA can be broken into two components: 1) input files/data, and 2) SMOKE outputs/summa ries. On-road mobile input data QA is summarized below. SMOKE output QA is summarized in Appendix D.4a of this document for all source categories.

On-road mobile input data was collected from the North Carolina Department of Transportation (NCDOT) and specific Metropolitan Planning Organi zations (MPOs) throughout North Carolina. The North Carolina Division of Air Quality (NCDAQ) checked the speed information for reasonableness against previous sets of speeds for that specific area. Additionally, the following data elements are checked for accuracy in the input files prior to use in the modeling: pollutants, fuel RVP, inspection and maintenance program settings, anti-tampering program settings, calendar year, evaluation month. All input files are printed and checked by hand against a “key” with the original source of the information. This QA step is always performed by a person other than the one who generated the files. If any di screpancies are found, they are marked on the hard copy and supplied by to the person who generated the input files for correction. Vehicle age distribution is another input referenced in the act ual MOBILE6.2 input file. This file is checked

## Emissions Preparations & Results Appendix D.2c - 5 Regional Haze SIP for NC Class I Areas December 17, 2007 

# against the original spreadsheet from which it is generated. Again, if any discrepancies are found, they are noted and returned to the person responsible for generating those files. VMT and vehicle mix (also referred to as VMT mix) are additional data elements that are checked after they are formatted for SMOKE. This file is checked against the original source of the VMT and VMT mix data.



# 4. DISCUSSION OF MOBILE SOURCE CATEGORIES
On-road mobile sources are considered those vehicles that travel on the roadways. Motor vehicles emit CO, NH3, NOx, PM2.5, SO2, and VOCs and the emissions from motor vehicles occur throughout the day while the vehicle is in motion, at idle, parked, and during refueling. All of these emissions processes need to be estimated in order to properly reflect the total emissions from this source category. In its simplest terms, emissions from highway mobile sources are calculated by multiplying an activity level, in this case VMT as provided by the NCDOT and MPOs, by an emission factor.

The USEPA developed the MOBILE model to estimate emission factors based on information on the way vehicles are driven in a particular area. The newest version of the MOBILE model (MOBILE6.2) was used. This model was released by the USEPA in draft form in 2002 and in final form in 2003. Key inputs for MOBILE6.2 include information on the age of vehicles on the roads, the average speed of those vehicles, what types of roads those vehicles are traveling on, any control technologies in place in an area to reduce emissions for motor vehicles (e.g., emissions inspection programs), and ambient temperature.

A very important component of the on-road mobile emission estimation process is interagency consultation. The primary transporation partners involved in the regional haze modelingincluded: USEPA, NCDOT, Federal Highway Administration, Capital Area MPO, DurhamChapel Hill-Carrboro MPO, Gaston Urban Ar ea MPO, Mecklenburg Union MPO, Cabarrus Rowan MPO, Greensboro Urban Area MPO, and th e Burlington-Graham MPO. Specifically the NCDOT and MPOs were consulted for input data such as speeds and VMT for the rural counties where travel demand model data sets were not available.

4.1 MOBILE6.2 Input Assumptions
4.1.1 Speed Assumptions Emissions from motor vehicles vary with the manner in which the vehicle is operated. Vehicles traveling at 65 miles per hour (mph) emit a very different mix of pollutants than the car that is

## Emissions Preparations & Results Appendix D.2c - 6 Regional Haze SIP for NC Class I Areas December 17, 2007 

# idling at a stoplight. In order to estimate emi ssions from vehicles for a typical day, NCDOT and the MPOs provided speeds for their respective counties.

The speeds for several urban counties covered by the MPOs were generated from their latest travel demand models and are differenciated into the morning rush hours (AM), the evening rush hours (PM) and off-peak (OP) speeds. The NCDOT recommended using Wake County off-peak speeds for all remaining counties in North Carolina.

Table 4.1-1 and 4.1-2 provide a summary of the 2002 and 2018 speeds, respectively. The column headings in these tables represent the road types used in the modeling.

Table 4.1-1. Speeds used for NC’s 2002 On-road Mobile Emissions Iventory

rural interstate other principal arterial rural minor arterial major collector minor collector rural local urban Interstate urban freeway other principal arterial minor arterial collector urban local Wake County 110 130 150 170 190 210 230 250 270 290 310 330 AM 64 56 45 44 43 43 52 55 36 37 35 36 PM 62 56 45 44 43 43 53 57 36 37 35 37 OP 66 57 50 46 44 44 60 60 42 42 37 38 Durham County AM 66 55 50 48 50 41 48 50 35 33 38 34 PM 65 54 51 48 50 42 49 48 36 34 38 34 OP 66 55 52 49 50 43 63 57 42 37 39 34 Chatham County AM - 52 43 48 44 46 - - - - - - PM - 51 42 48 44 46 - - - - - - OP - 53 43 48 43 46 - - - - - - Franklin County AM - 54 55 43 48 44 - - - - - - PM - 53 54 42 48 44 - - - - - - OP - 55 55 43 48 44 - - - - - - Johnston County AM 64 43 43 43 42 42 62 - 28 31 31 29 PM 64 43 43 43 42 42 62 - 28 31 31 29 OP 64 43 43 43 42 42 62 - 28 31 31 29 Orange County AM 64 - 50 43 42 44 63 21 34 32 27 24 PM 64 - 50 43 42 44 63 25 36 32 28 25 OP 64 - 51 44 42 45 65 40 38 33 29 26 Iredell County 62 68 29 37 34 30 62 - 30 32 30 30 Mecklenburg County - 33 28 51 37 30 43 43 26 26 25 30

Cabarrus County - 43 46 42 38 30 44 - 30 31 33 30 Gaston County 30 72 41 44 44 30 49 65 28 32 27 30 Lincoln County - 65 37 52 48 30 - - 44 22 24 30 Rowan County - 42 53 53 52 30 58 - 40 40 35 30 Union County - 45 49 46 46 30 - 35 34 35 38 30 Guilford County 55 53 42 44 44 31 45 50 28 31 32 23 Forsyth County 55 55 44 41 40 33 55 51 32 21 27 21 Davidson County 62 52 40 43 43 37 60 55 30 32 34 22

Davie County 66 53 43 38 41 44 - - - - - - Rest of NC Counties 66 57 50 46 44 44 60 60 42 42 37 38

## Emissions Preparations & Results Appendix D.2c - 7 Regional Haze SIP for NC Class I Areas December 17, 2007 

# Table 4.1-2. Speeds used for NC’s 2018 On-road Mobile Emissions Iventory

4.1.2 Vehicle Age Distribution The vehicle age distribution comes from annual registration data for North Carolina from the NCDOT. For this analysis the age distribution was generated based on 2004 data, the latest available count data. The NCDOT provided the data based on the number of vehicle types per year from 1974 through 2004. Vehicles greater than 25 years old were combined and included as the 25 th 

# model year. The vehicle count information is provided for nine vehicle types; light duty gas vehicles (LDGV), light duty diesel vehi cles (LDDV), light duty gas trucks 1 (LDGT1), light duty gas trucks 2 (LDGT2), light duty diesel trucks 1 (LDDT1), light duty diesel trucks 2 (LDDT2), heavy duty gas vehicles (HDGV), heavy duty diesel vehicles (HDDV) and motorcycles (MC). LDDT1 and LDDT2 are combined and labeled as light duty diesel trucks (LDDT).

This vehicle distribution corresponds to the old MOBILE5 format and does not correlate to the USEPA MOBILE6.2 model vehicle types. In orde r to convert the data provided by the NCDOT into the MOBILE6.2 model format, the NCDAQ used a utility developed by the USEPA that disaggregates the 8 MOBILE5 model vehicle t ypes into the 16 MOBILE6.2 vehicle types. rural interstate other principal arterial rural minor arterial major collector minor collector rural local urban Interstate urban freeway other principal arterial minor arterial collector urban local Wake Count y 110 130 150 170 190 210 230 250 270 290 310 330 AM 60 55 44 44 41 43 50 55 34 38 34 36 PM 56 55 44 43 40 43 50 56 35 38 34 36 OP 66 59 49 45 44 44 61 62 41 42 37 38 Durham County AM 64 55 46 46 45 41 52 48 32 34 36 33 PM 62 54 48 47 46 41 52 48 35 35 37 34 OP 66 55 52 47 45 43 64 58 42 38 39 35 Chatham County AM - 53 43 47 45 46 - - - - - 30 PM - 52 43 48 45 46 - - - - - 30 OP - 53 43 48 44 46 - - - - - 30 Franklin County AM - 52 52 43 48 43 - - - - - - PM - 50 52 41 48 42 - - - - - - OP - 55 55 42 48 43 - - - - - - Johnston County AM 65 43 43 43 42 42 62 - 28 31 31 30 PM 65 43 43 43 42 42 62 - 28 31 31 30 OP 65 43 43 43 42 42 62 - 28 31 31 30 Orange County AM 63 - 50 43 42 44 60 22 33 32 26 24 PM 63 - 50 43 42 44 61 29 35 33 27 25 OP 65 - 51 44 42 45 66 40 37 35 29 26 Mecklenburg Count y - 22 18 32 26 30 41 49 25 26 24 30

Cabarrus Count y - 46 41 38 34 30 35 - 28 29 30 30 Gaston Count y 42 66 36 43 41 30 44 66 26 29 26 30 Lincoln Count y - 59 37 51 45 30 0 - 41 23 22 30 Rowan Count y - 45 49 50 50 30 57 - 38 39 36 30 Union Count y - 46 43 45 44 30 - 36 33 32 36 30 Stanly Count y - 39 39 45 47 15 - - 31 31 30 15 Cleveland Count y 45 33 34 42 41 15 30 31 22 29 23 15

Iredell Count y 57 66 26 32 30 30 60 0 27 26 28 30 Guilford Count y 55 53 41 43 45 44 52 53 29 32 33 33 Forsyth Count y 55 55 44 41 40 39 55 52 30 31 31 26 Davidson Count y 62 51 39 43 42 38 60 55 29 31 34 22

Davie Count y 66 53 43 38 41 44 - - - - - - Rest of NC 66 59 49 45 44 44 61 62 41 42 37 38

## Emissions Preparations & Results Appendix D.2c - 8 Regional Haze SIP for NC Class I Areas December 17, 2007 

# The count data provided by the NCDOT is conve rted to fractions by dividing each count per vehicle type per year by the total number of vehicles in that classification for all years. For example, the number of 2004 light duty vehicles divided by the total number of light duty vehicles for all years. The fractions are arranged into MOBILE5 format for conversion to the 16 vehicle types required by the MOBILE6.2 model using the USEPA conversion utility.

4.1.3 Vehicle Mix Assumptions The vehicle mix refers to the percentage of different vehicle types on each of the 12 FHWA road types. It is critical for estimating mobile emissions in an area to use data that accurately reflects the vehicles types traveling on each of these different road types.

Historically, the North Carolina statewide vehicl e mix was created using spreadsheets that were developed in the mid-1990s. In August 2004, the USEPA released the guidance document EPA420-R-04-013
, Technical Guidance on the Use of MOBILE6.2 for Emission Inventory Preparation

. The NCDAQ created a new statewide mix based on this methodology. Outlined below is the methodology used to convert the 13 Highway Performance Monitoring System (HPMS) vehicle types count data reported to FH WA and generate a state specific vehicle mix.

The North Carolina HPMS data that was used to generate the new statewide vehicle mix was based on 1999 through 2001 data counts. This was the latest available statewide count information at the time of the emissions modeling. Table 4.1-3 shows the percent of vehicles per vehicle type for each of the 12 road classes.

## Emissions Preparations & Results Appendix D.2c - 9 Regional Haze SIP for NC Class I Areas December 17, 2007Table 4.1-3. Percentage of Vehicles Per Vehicle Type by Functional Road Class in NC

## Emissions Preparations & Results Appendix D.2c - 10 Regional Haze SIP for NC Class I Areas December 17, 2007 

# Disaggregating State Specific Information Section 4.1.5 of Technical Guidance on the Use of MOBILE6.2 for Emission Inventory Preparation , illustrates how to map the HPMS statewide vehicle data to general vehicle categories. This mapping is outlined below:

HPMS Category General Category Motorcycle Motorcycle (MC) Passenger Car Passenger Car (LDV) Other 2-Axel, 4-Tire Vehicles Light Truck (LDT) Busses Bus (HDB)
All Other Trucks: Single unit, 2-axel, 6-tire Single unit, 3-axel Single unit, 4 or more axel Single trailer, 4 or fewer axel Single trailer, 5-axel Single trailer, 6 or more axel Multi-trailer, 5 or fewer axel Multi-trailer, 6-axel Multi-trailer, 7 or more axel Heavy Duty Truck (HDV)



# The HPMS data in Table 4.1-3 was grouped into these five general categories for each road type. In order to expand the five general categories to the 16 vehicle types used in MOBILE6.2, the national average VMT fractions by each vehicle cl ass were used. The 2000 fractions were used since the state specific data is from 1999 through 2001. The national average data was obtained from Table 4.1.2 in Technical Guidance on the Use of MOBILE6.2 for Emission Inventory Preparation . An example for rural interstates is illustrated below:

From Table 4.1-3 above: Passenger Cars = 56.93% 5 axel Trailer = 19.23% Pickup Trucks = 10.80% 6 axel Trailer = 0.48% Bus = 1.06% 5 axel Multi Trailer = 0.73% 2 axel Trucks = 2.50% 6 axel Multi Trailer = 0.24% 3 axel Trucks = 1.56% 7 axel Multi Trailer = 0.11% 4 axel Trucks = 1.09% Motorcycles = 0.49% 4 axel Trailer = 4.79%

## Emissions Preparations & Results Appendix D.2c - 11 Regional Haze SIP for NC Class I Areas December 17, 2007 

# Therefore, the five general categories are: Motorcycles = 0.49% Light Duty Vehicles = 56.93% Light Duty Trucks = 10.80% Heavy Duty Buses = 1.06% Heavy Duty Vehicles = 30.73%

From Table 4.1.2 in Technical Guidance on the Use of MOBILE6.2 for Emission Inventory Preparation , the 2000 national average vehicle mix for light duty trucks, buses and heavy duty trucks are:

Light Duty Trucks Heavy Duty Trucks

LDT1 = 0.0655 LDT2 = 0.2179 LDT3 = 0.0672 LDT4 = 0.0309 Total = 0.3815

Buses

Using the methodology described in Section 4.1.5 in Technical Guidance on the Use of MOBILE6.2 for Emission Inventory Preparation the new 2000 North Carolina statewide mix was developed. The basic formula for developing the mix is shown below,

Vehicle Type = (2000 M6.2 fraction for vehicle) X (99-01 State total for group)

. (2000 M6.2 total for subcategory)



# Table 4.1-4 displays the calculation for each vehicle type for the 2000 rural interstate vehicle mix. HDV2B = 0.0380 HDV3 = 0.0038 HDV4 = 0.0029 HDV5 = 0.0022 HDV6 = 0.0082 HDV7 = 0.0098 HDV8A = 0.0108 HDV8B = 0.0386 Total = 0.1143 HDBS = 0.0019 HDBT = 0.0009 Total = 0.0028

## Emissions Preparations & Results Appendix D.2c - 12 Regional Haze SIP for NC Class I Areas December 17, 2007 

# Table 4.1-4. Calculation of New 2000 Stat ewide Rural Interstate Vehicle Mix Vehicle

Type Calculation New 2000 Mix
Light Duty Vehicles LDV = LDV = 0.5693 MC = MC = 0.0049
Light Duty Trucks LDT1 = 0.0655 x (0.1080/0.3815) = 0.0185 LDT2 = 0.2179 x (0.1080/0.3815) = 0.0617 LDT3 = 0.0672 x (0.1080/0.3815) = 0.0190 LDT4 = 0.0309 x (0.1080/0.3815) = 0.0087 Total Light Duty Vehicles 0.6822

Heavy Duty Vehicles HDV2B = 0.0380 x (0.3073/0.1143) = 0.1022 HDV3 = 0.0038 x (0.3073/0.1143) = 0.0102 HDV4 = 0.0029 x (0.3073/0.1143) = 0.0078 HDV5 = 0.0022 x (0.3073/0.1143) = 0.0059 HDV6 = 0.0082 x (0.3073/0.1143) = 0.0220 HDV7 = 0.0098 x (0.3073/0.1143) = 0.0263 HDV8A = 0.0108 x (0.3073/0.1143) = 0.0290 HDV8B = 0.0386 x (0.3073/0.1143) = 0.1038

Buses HDBS = 0.0019 x (0.0106/0.0028) = 0.0072 HDBT = 0.0009 x (0.0106/0.0028) = 0.0034 Total Heavy Duty Vehicles 0.3178

2002 NC Statewide Vehicle Mix Once the 2000 vehicle mix was generated, the other years were created using the methodology described in Section 4.1.4 in Technical Guidance on the Use of MOBILE6.2 for Emission Inventory Preparation . This method grouped light duty vehicles, light duty trucks and motorcycles together and heavy duty buses, heavy duty trucks and heavy duty vehicles together. The combined percentages for these groupings are listed below.

Light Duty Vehicles = 68.22% Heavy Duty Vehicles = 31.78%

## Emissions Preparations & Results Appendix D.2c - 13 Regional Haze SIP for NC Class I Areas December 17, 2007 

# The MOBILE6.2 vehicle mix fractions for the year being developed were obtained from Table 4.1.2 in Technical Guidance on the Use of MOBILE6.2 for Emission Inventory Preparation . The MOBILE6.2 vehicle fractions for 2002 are listed below.

Light Duty Vehicles Heavy Duty Vehicles

The North Carolina 2002 vehicle mix was normalized to the MOBILE6.2 fractions using the following formula:

Vehicle Type = (2002 M6 fraction for vehicle) X (2000 State total for group) (2002 M6 total for group)



# Table 4.1-5 below displays the calculations used to generate the 2002 North Carolina vehicle mix for rural interstate. HDV2B = 0.0382 HDV3 = 0.0038 HDV4 = 0.0030 HDV5 = 0.0022 HDV6 = 0.0084 HDV7 = 0.0100 HDV8A = 0.0109 HDV8B = 0.0390 HDBS = 0.0019 HDBT = 0.0009 Total = 0.1183 LDV = 0.4646 LDT1 = 0.0706 LDT2 = 0.2349 LDT3 = 0.0724 LDT4 = 0.0333 MC = 0.006 Total = 0.8818

## Emissions Preparations & Results Appendix D.2c - 14 Regional Haze SIP for NC Class I Areas December 17, 2007 

# Table 4.1-5. Calculation of 2002 NC Statew ide Rural Interstate Vehicle Mix Vehicle

Type Calculation 2002 State Mix

Light Duty Vehicles LDV = 0.4646 x (0.6822/0.8818) = 0.3594 LDT1 = 0.0706 x (0.6822/0.8818) = 0.0546 LDT2 = 0.2349 x (0.6822/0.8818) = 0.1817 LDT3 = 0.0724 x (0.6822/0.8818) = 0.0560 LDT4 = 0.0333 x (0.6822/0.8818) = 0.0258 MC = 0.006 x (0.6822/0.8818) 0.0046

Heavy Duty Vehicles HDV2B = 0.0382 x (0.3178/0.1183) = 0.1026 HDV3 = 0.0038 x (0.3178/0.1183) = 0.0102 HDV4 = 0.0030 x (0.3178/0.1183) = 0.0081 HDV5 = 0.0022 x (0.3178/0.1183) = 0.0059 HDV6 = 0.0084 x (0.3178/0.1183) = 0.0226 HDV7 = 0.0100 x (0.3178/0.1183) = 0.0269 HDV8A = 0.0109 x (0.3178/0.1183) = 0.0293 HDV8B = 0.0390 x (0.3178/0.1183) = 0.1048 HDBS = 0.0019 x (0.3178/0.1183) = 0.0051 HDBT = 0.0009 x (0.3178/0.1183) = 0.0024

The North Carolina transportation partners recommended the use of the statewide vehicle mix for all counties in North Carolina with the exception of the North Carolina counties within the Charlotte-Gastonia-Rock Hill, North Carolina-South Carolina 8-hour ozone nonattainment area. For these counties, local vehicle count data was used to develop the vehicle mix using the method explained above. Since there was not adequate local vehicle count data for the interstates and freeways, the statewide mix was used for these road types.

The 2018 vehicle mix was developed in a similar manner as the 2002. Again, the statewidevehicle mix was used for all areas except the North Carolina counties within the CharlotteGastonia-Rock Hill 8-hour ozone nonattainment area, where local data was available.

## Emissions Preparations & Results Appendix D.2c - 15 Regional Haze SIP for NC Class I Areas December 17, 2007 

# 4.1.4 Temperature, Relative Humidity and Barometric Pressure Assumptions MOBILE6.2 emission factors used by the emissions preprocessor model SMOKE are significantly influenced by temperature and to a lesser extent, humidity. The most desirable approach from an accuracy standpoint is to model on-road mobile emissions using gridded, temporalized data from the meterological model. The VISTAS on-road mobile inventories were developed using this approach.

4.1.5 Vehicle Inspection and Maintenance Program Assumptions In the early 1990’s, North Carolina adopted emissions inspection requirements for vehicles in 9 urban counties. This program tested emissions at idle for 1975 and newer gasoline powered light duty vehicles. This “idle test” was assumed to have a compliance rate of 95 percent and covered Cabarrus, Durham, Forsyth, Gaston, Guilford, Mecklenburg, Orange, Union and Wake Counties. In addtion, the inspection stations are required to administer an anti-tampering check to ensure that emissions control equipment on any vehicle 35 years old and newer has not been altered.

In 2002, North Carolina implemented a new vehicle emissions inspection program referred to as onboard diagnostics (OBDII). This program covers all light duty gasoline powered vehicles that are model year 1996 and newer. The program was initially implemented in the 9 counties that originally had the “idle test” and was expanded to include a total of 48 counties between July 2002 and January 2006. The idle test requirement remained in place in the original 9 counties until the final phase-in in January 2006, at which time the idle test requirements were dropped and only the OBDII test was required for model year 1996 and newer.

Since the OBDII program did not begin until midway through 2002, the 2002 annual on-road mobile inventory to support regional haze modeling was developed with an “idle test” in the 9 counties listed above plus the anti-tampering in all counties. The 2018 annual on-road mobileinventory was developed with the OBDII program in 48 counties in North Carolina plus the antitampering in all counties.

4.1.6 Reid Vapor Pressure Assumptions RVP is a measure of gasoline’s volatility. The following reflects the RVP settings used in the development of the North Carolina annual on-road mobile inventory to support regional haze modeling. An RVP of 7.8 pounds per square inch (psi) is required during May through September in Davidson, Durham, Forsyth, Gaston, Guilford, Mecklenburg, and Wake Counties, Dutchville Township in Granville County and pa rt of Davie Conty bounded by the Yadkin River, Dutchmans Creek, NC Highway 801, Fulton Creek and back to the Yadkin River. The remainder of North Carolina must have an RVP of 9.0 psi during May through September.

## Emissions Preparations & Results Appendix D.2c - 16 Regional Haze SIP for NC Class I Areas December 17, 2007 

# During the remainder of the year, statewide RVPs are 13.5 psi in October, November, February, March and April, and 15 psi in December and January. The RVP data is provided by the North Carolina Department of Agriculture who is responsible for testing fuels in North Carolina.

4.2 VMT Assumptions
In order to calculate emissions from on-road mobile sources, emission factors are developed as discussed throughout this document. The emission factors are then multiplied by an activity level, which for on-road mobile sources is VMT.

For most counties in North Carolina, 2002 VMT was derived from the 2002 HPMS data provided by NCDOT. Where this travel demand model data was available, it was the recommendation of the North Carolina transportation partners to use it instead of the HPMS data. Therefore, as with the speed data, VMT from several urban counties’ travel demand models were used instead of HPMS VMT.

For most counties in North Carolina, the 2018 VMT was grown based on a linear interpolation of the most recent 10 years (1995-2004) of HPMS data provided by NCDOT. Similar to the 2002 VMT, where there is travel demand model data available, it was used instead of the grown HPMS data.

In situations where certain North Carolina counties are partially covered by a travel demand model, and the North Carolina transportation partners anticipate future versions of the travel models to cover the entire county, an adjusted HPMS VMT number was used. This upward adjustment (30%) of the countywide HPMS VMT data is based on an analysis by the NCDAQ that shows that travel demand model VMT can be as much as 30% higher than the HPMS VMT. Table 4.2-1 and 4.2-2 below summarizes the 2002 and 2018 VMT, respectively, used in the development of the on-road mobile inventory to support regional haze modeling.

Table 4.2-1. North Carolina 2002 Daily Vehicle Miles Traveled by County County Name FIPS 2002 VMT Notes ALAMANCE 37001 4,638,621 HPMS * 1.3 

## ALEXANDER 37003 642,180 HPMS 

## ALLEGHANY 37005 244,990 HPMS 

## ANSON 37007 854,800 HPMS 

## ASHE 37009 674,530 HPMS 

## AVERY 37011 540,780 HPMS 

## BEAUFORT 37013 1,130,680 HPMS 

## BERTIE 37015 746,030 HPMS 

## BLADEN 37017 1,130,220 HPMS 

## BRUNSWICK 37019 2,822,450 HPMS

## Emissions Preparations & Results Appendix D.2c - 17 Regional Haze SIP for NC Class I Areas December 17, 2007 

# Table 4.2-1. North Carolina 2002 Daily Vehicle Miles Traveled by County County Name FIPS 2002 VMT Notes BUNCOMBE 37021 5,966,490 HPMS 

## BURKE 37023 3,396,042 HPMS * 1.3 

## CABARRUS 37025 5,315,528 Provided by Charlotte Department of Transportation on 6/6/05 

## CALDWELL 37027 2,368,938 HPMS * 1.3 

## CAMDEN 37029 300,640 HPMS 

## CARTERET 37031 1,735,210 HPMS 

## CASWELL 37033 603,780 HPMS 

## CATAWBA 37035 5,777,564 HPMS * 1.3 

## CHATHAM 37037 2,202,928 HPMS * 1.3 

## CHEROKEE 37039 715,940 HPMS 

## CHOWAN 37041 319,640 HPMS 

## CLAY 37043 250,380 HPMS 

## CLEVELAND 37045 2,693,410 HPMS 

## COLUMBUS 37047 1,745,100 HPMS 

## CRAVEN 37049 2,799,090 HPMS 

## CUMBERLAND 37051 9,901,749 HPMS * 1.3 

## CURRITUCK 37053 902,070 HPMS 

## DARE 37055 1,501,580 HPMS 

## DAVIDSON 37057 4,952,266 Interpolated from 2000 and 2004 data used in NC's 1-hr ozone maintenance plan updates 

## DAVIE 37059 1,364,370 HPMS 

## DUPLIN 37061 1,818,440 HPMS 

## DURHAM 37063 7,658,827 2002 VMT from information provided by NCDOT on 7/30/04 

## EDGECOMBE 37065 2,012,543 HPMS * 1.3 

## FORSYTH 37067 10,040,729 Interpolated from 2000 and 2014 data provided by NCDOT on 7/28/04 

## FRANKLIN 37069 1,663,415 HPMS * 1.3 

## GASTON 37071 6,710,377 Provided by Charlotte Department of Transportation on 6/6/05 

## GATES 37073 324,350 HPMS 

## GRAHAM 37075 168,610 HPMS 

## GRANVILLE 37077 2,319,707 HPMS * 1.3 

## GREENE 37079 583,580 HPMS 

## GUILFORD 37081 14,973,172 Interpolated from 2000 and 2004 data used in NC's 1-hr ozone maintenance plan updates 

## HALIFAX 37083 1,841,180 HPMS 

## HARNETT 37085 2,264,790 HPMS 

## HAYWOOD 37087 2,270,040 HPMS 

## HENDERSON 37089 2,243,200 HPMS 

## HERTFORD 37091 557,140 HPMS 

## HOKE 37093 773,290 HPMS 

## HYDE 37095 157,850 HPMS 

## IREDELL 37097 6,324,006 HPMS * 1.3 

## JACKSON 37099 1,325,000 HPMS 

## JOHNSTON 37101 6,376,981 HPMS * 1.3 

## JONES 37103 518,830 HPMS 

## LEE 37105 1,532,080 HPMS 

## LENOIR 37107 1,680,360 HPMS

## Emissions Preparations & Results Appendix D.2c - 18 Regional Haze SIP for NC Class I Areas December 17, 2007 

# Table 4.2-1. North Carolina 2002 Daily Vehicle Miles Traveled by County County Name FIPS 2002 VMT Notes LINCOLN 37109 2,145,479 Provided by Charlotte Department of Transportation on 6/6/05 

## MACON 37113 924,310 HPMS 

## MADISON 37115 518,620 HPMS 

## MARTIN 37117 900,970 HPMS 

## MCDOWELL 37111 1,648,160 HPMS 

## MECKLENBURG 37119 25,660,666 Provided by Charlotte Department of Transportation on 6/6/05 

## MITCHELL 37121 369,310 HPMS 

## MONTGOMERY 37123 1,023,200 HPMS 

## MOORE 37125 2,042,430 HPMS 

## NASH 37127 4,532,138 HPMS * 1.3 

## NEW HANOVER 37129 3,317,520 HPMS 

## NORTHAMPTON 37131 885,960 HPMS 

## ONSLOW 37133 3,222,940 HPMS 

## ORANGE 37135 4,745,208 HPMS * 1.3 

## PAMLICO 37137 315,590 HPMS 

## PASQUOTANK 37139 692,670 HPMS 

## PENDER 37141 1,726,180 HPMS 

## PERQUIMANS 37143 369,440 HPMS 

## PERSON 37145 798,930 HPMS 

## PITT 37147 3,005,670 HPMS 

## POLK 37149 765,570 HPMS 

## RANDOLPH 37151 4,861,324 HPMS * 1.3 

## RICHMOND 37153 1,501,470 HPMS 

## ROBESON 37155 4,256,650 HPMS 

## ROCKINGHAM 37157 2,558,820 HPMS 

## ROWAN 37159 4,870,192 Provided by Charlotte Department of Transportation on 6/6/05 

## RUTHERFORD 37161 1,649,000 HPMS 

## SAMPSON 37163 1,980,230 HPMS 

## SCOTLAND 37165 1,119,800 HPMS 

## STANLY 37167 1,480,430 HPMS 

## STOKES 37169 995,800 HPMS 

## SURRY 37171 2,562,850 HPMS 

## SWAIN 37173 553,040 HPMS 

## TRANSYLVANIA 37175 789,620 HPMS 

## TYRRELL 37177 148,260 HPMS 

## UNION 37179 3,974,587 Provided by Charlotte Department of Transportation on 6/6/05 

## VANCE 37181 1,376,990 HPMS 

## WAKE 37183 21,001,106 2002 VMT from information provided by NCDOT on 7/30/04 

## WARREN 37185 628,780 HPMS 

## WASHINGTON 37187 418,360 HPMS 

## WATAUGA 37189 1,073,710 HPMS 

## WAYNE 37191 2,835,910 HPMS 

## WILKES 37193 1,858,010 HPMS 

## WILSON 37195 2,502,030 HPMS

## Emissions Preparations & Results Appendix D.2c - 19 Regional Haze SIP for NC Class I Areas December 17, 2007 

# Table 4.2-1. North Carolina 2002 Daily Vehicle Miles Traveled by County County Name FIPS 2002 VMT Notes YADKIN 37197 1,400,420 HPMS 

## YANCEY 37199 413,670 HPMS 

## NC TOTAL 270,798,512



# Table 4.2-2. North Carolina 2018 Daily Vehicle Miles Traveled by County County Name FIPS 2018 VMT Notes ALAMANCE 37001 6,205,451 HPMS * 1.3 

## ALEXANDER 37003 845,834 HPMS 

## ALLEGHANY 37005 284,619 HPMS 

## ANSON 37007 1,047,225 HPMS 

## ASHE 37009 935,462 HPMS 

## AVERY 37011 587,741 HPMS 

## BEAUFORT 37013 1,198,250 HPMS 

## BERTIE 37015 871,700 HPMS 

## BLADEN 37017 1,375,754 HPMS 

## BRUNSWICK 37019 4,743,177 HPMS 

## BUNCOMBE 37021 7,857,944 HPMS 

## BURKE 37023 4,167,597 HPMS * 1.3 

## CABARRUS 37025 8,606,995 Grown from 2002 and 2009 VMT provided by CDOT on 2/18/05 

## CALDWELL 37027 2,861,140 HPMS * 1.3 

## CAMDEN 37029 385,176 HPMS 

## CARTERET 37031 1,944,452 HPMS 

## CASWELL 37033 775,464 HPMS 

## CATAWBA 37035 8,115,935 HPMS * 1.3 

## CHATHAM 37037 3,608,669 HPMS * 1.3 

## CHEROKEE 37039 986,411 HPMS 

## CHOWAN 37041 404,771 HPMS 

## CLAY 37043 367,492 HPMS 

## CLEVELAND 37045 4,660,835 HPMS * 1.3 

## COLUMBUS 37047 2,646,141 HPMS 

## CRAVEN 37049 4,634,527 HPMS 

## CUMBERLAND 37051 12,679,082 HPMS * 1.3 

## CURRITUCK 37053 1,954,709 HPMS 

## DARE 37055 1,957,352 HPMS 

## DAVIDSON 37057 7,099,694 Grown from 2012 and 2015 data used in NC's 1-hr ozone maintenance plan updates 

## DAVIE 37059 1,753,768 HPMS 

## DUPLIN 37061 2,542,655 HPMS 

## DURHAM 37063 11,209,276 Interpolated from the 2010 and 2020 VMT used in the 2005 8-hr ozone conformity exercise 

## EDGECOMBE 37065 2,645,708 HPMS * 1.3 

## FORSYTH 37067 13,677,739 Interpolated from 2014 and 2020 data provided by NCDOT on 2/23/05 

## FRANKLIN 37069 2,853,518 HPMS * 1.5 

## GASTON 37071 9,801,026 Interpolated from the 2010 and 2020 VMT used in the 2005 8-hr ozone conformity exercise 

## GATES 37073 365,022 HPMS

## Emissions Preparations & Results Appendix D.2c - 20 Regional Haze SIP for NC Class I Areas December 17, 2007 

# Table 4.2-2. North Carolina 2018 Daily Vehicle Miles Traveled by County County Name FIPS 2018 VMT Notes GRAHAM 37075 191,247 HPMS 

## GRANVILLE 37077 2,941,985 HPMS * 1.3 

## GREENE 37079 765,269 HPMS 

## GUILFORD 37081 18,610,442 interpolated from the 2010 and 2020 VMT used in the 2005 PM2.5 conformity exercise 

## HALIFAX 37083 2,020,613 HPMS 

## HARNETT 37085 2,897,788 HPMS 

## HAYWOOD 37087 2,961,335 HPMS 

## HENDERSON 37089 3,243,634 HPMS 

## HERTFORD 37091 568,660 HPMS 

## HOKE 37093 1,167,266 HPMS 

## HYDE 37095 337,721 HPMS 

## IREDELL 37097 9,050,427 HPMS * 1.4 

## JACKSON 37099 1,905,768 HPMS 

## JOHNSTON 37101 10,135,804 HPMS * 1.4 

## JONES 37103 620,169 HPMS 

## LEE 37105 2,204,636 HPMS 

## LENOIR 37107 1,987,991 HPMS 

## LINCOLN 37109 3,318,465 Grown from 2002 and 2009 VMT provided by CDOT on 2/18/05 

## MACON 37113 1,281,167 HPMS 

## MADISON 37115 737,680 HPMS 

## MARTIN 37117 1,152,060 HPMS 

## MCDOWELL 37111 2,121,414 HPMS 

## MECKLENBURG 37119 39,238,484 Interpolated from the 2010 and 2020 VMT used in the 2005 8-hr ozone conformity exercise 

## MITCHELL 37121 457,934 HPMS 

## MONTGOMERY 37123 1,362,345 HPMS 

## MOORE 37125 2,758,880 HPMS 

## NASH 37127 5,588,571 HPMS * 1.3 

## NEW HANOVER 37129 4,851,069 HPMS 

## NORTHAMPTON 37131 1,077,413 HPMS 

## ONSLOW 37133 4,946,726 HPMS 

## ORANGE 37135 6,813,307 HPMS * 1.3 

## PAMLICO 37137 411,288 HPMS 

## PASQUOTANK 37139 961,905 HPMS 

## PENDER 37141 2,372,701 HPMS 

## PERQUIMANS 37143 555,188 HPMS 

## PERSON 37145 1,037,013 HPMS 

## PITT 37147 3,877,084 HPMS 

## POLK 37149 1,114,156 HPMS 

## RANDOLPH 37151 6,545,913 HPMS * 1.3 

## RICHMOND 37153 1,937,394 HPMS 

## ROBESON 37155 5,135,468 HPMS 

## ROCKINGHAM 37157 2,824,077 HPMS 

## ROWAN 37159 6,835,566 Grown from 2002 and 2009 VMT provided by CDOT on 2/18/05 

## RUTHERFORD 37161 2,060,298 HPMS 

## SAMPSON 37163 2,483,742 HPMS 

## SCOTLAND 37165 1,354,813 HPMS 

## STANLY 37167 1,814,968 HPMS

## Emissions Preparations & Results Appendix D.2c - 21 Regional Haze SIP for NC Class I Areas December 17, 2007 

# Table 4.2-2. North Carolina 2018 Daily Vehicle Miles Traveled by County County Name FIPS 2018 VMT Notes STOKES 37169 1,302,316 HPMS 

## SURRY 37171 2,969,519 HPMS 

## SWAIN 37173 615,707 HPMS 

## TRANSYLVANIA 37175 1,042,179 HPMS 

## TYRRELL 37177 250,223 HPMS 

## UNION 37179 5,961,762 Grown from 2002 and 2009 VMT provided by CDOT on 2/18/05 

## VANCE 37181 1,857,697 HPMS 

## WAKE 37183 34,936,724 Interpolated from the 2010 and 2020 VMT used in the 2005 8-hr ozone conformity exercise 

## WARREN 37185 861,911 HPMS 

## WASHINGTON 37187 483,359 HPMS 

## WATAUGA 37189 1,160,296 HPMS 

## WAYNE 37191 4,024,978 HPMS 

## WILKES 37193 2,286,565 HPMS 

## WILSON 37195 3,093,448 HPMS 

## YADKIN 37197 1,776,643 HPMS 

## YANCEY 37199 450,324 HPMS 

## NC TOTAL 380,369,806

# Appendix D.3 Emissions Inventory SummariesTable 1. Typical 2002 BaseG2 Annual Emission Summary for North Carolina Counties (tons)PointNon-roadAreaMobileCountyVOC NOx SO2 PM-10 PM-2.5 NH3 VOC NOx SO2 PM-10 PM-2.5 NH3 VOC NOx SO2 PM-10 PM-2.5 NH3 VOC NOx SO2 PM-10 PM-2.5 NH3Alamance Co 327.2 154.5 23.9 70.0 51.3 6.9 1017.5 1038.1 77.2 76.8 73.1 0.9 3516.5 612.6 75.6 3358.9 898.3 537.2 4687.2 6080.4 210.8 116.4 82.6 165.0Alexander Co 348.1 6.0 4.0 40.6 26.2 0.0 287.2 234.5 17.4 20.1 19.2 0.2 1761.9 173.1 23.5 1454.9 429.4 1772.5 671.5 657.1 28.2 15.0 10.523.2Alleghany Co 5.3 0.1 0.3 0.6 0.2 0.0 71.4 88.0 8.8 8.8 8.5 0.1 889.0 90.1 13.0 970.6 319.7 337.1 261.2 247.6 10.7 5.7 3.9 8.9Anson Co 60.2 72.2 172.1 46.7 38.3 0.6 147.0 526.9 36.8 22.0 20.5 0.1 912.2 110.4 20.3 1216.8 355.2 2475.2 878.9 1024.8 39.4 21.9 15.6 30.5Ashe Co 5.1 13.0 22.0 14.4 9.3 0.0 170.6 165.8 16.8 17.3 16.6 0.2 1990.9 203.6 31.1 1729.5 655.3 216.5 721.7 666.0 29.2 15.3 10.6 24.5Avery Co 27.5 5.1 12.2 1.3 0.8 0.0 295.2 143.3 15.7 19.7 18.7 0.2 1061.6 159.4 43.7 963.6 340.0 83.5 551.2 602.9 24.3 13.2 9.3 19.4Beaufort Co 99.9 625.8 4813.7 667.7 406.5 536.7 1675.6 959.3 84.7 89.9 85.1 0.7 1951.9 263.2 29.2 2892.8 809.2 1183.4 1186.1 1133.1 48.5 25.4 17.5 41.0Bertie Co 216.2 86.6 268.4 28.9 19.5 6.8 449.1 270.3 28.5 31.3 30.0 0.3 1529.6 125.5 22.6 1952.3 559.6 1680.3 769.9 832.2 33.6 18.3 12.926.7Bladen Co 190.4 276.3 1079.9 62.9 40.2 0.4 348.9 477.4 37.1 33.4 31.8 0.3 1641.1 212.0 41.2 2937.7 910.4 8799.5 1177.5 1136.4 49.3 26.1 18.1 40.9Brunswick Co 1288.1 2391.5 5609.9 195.6 113.1 2.3 1196.9 1166.1 133.8 98.3 93.3 0.8 2164.0 397.3 51.6 2461.4 814.3 1074.3 2901.1 3240.2 126.9 69.2 48.7 101.2Buncombe Co 403.5 5329.3 17031.5 528.7 263.0 2.8 1703.0 1643.2 137.5 138.4 131.9 1.3 7090.2 1324.7 235.0 6391.7 2059.8 318.4 5879.0 8438.3 278.4 157.2 112.7 210.6Burke Co 737.6 117.3 242.3 192.4 174.8 1.1 427.7 594.3 36.9 32.2 30.7 0.5 3159.8 393.9 70.5 2752.0 881.5 373.1 3423.5 5156.2 166.6 97.5 71.2118.4Cabarrus Co 782.9 915.8 2081.4 79.2 50.5 10.1 864.3 1550.6 126.9 102.9 97.9 0.9 3243.1 546.0 57.0 3953.4 1030.9 520.1 7353.7 5681.1 233.2 123.8 85.9 190.4Caldwell Co 4105.7 410.3 37.8 220.9 156.0 0.0 510.1 551.5 34.3 35.5 34.0 0.6 3340.7 385.3 56.9 2772.3 998.1 326.1 2537.0 2382.8 101.5 53.0 36.5 85.8Camden Co 0.0 0.0 0.0 0.0 0.0 0.0 610.8 201.0 22.3 27.4 26.1 0.2 306.8 45.0 7.3 1680.8 400.1 192.2 302.4 337.4 13.5 7.4 5.2 10.8Carteret Co 97.8 38.9 182.3 38.6 6.8 0.0 5692.3 2618.0 346.0 216.5 201.2 1.7 1982.2 541.5 99.0 3071.0 1368.8 182.1 1738.0 1908.7 77.1 41.6 29.2 62.3Caswell Co 0.0 0.0 0.0 0.0 0.0 0.0 94.0 217.1 17.4 12.4 11.7 0.1 1536.8 132.0 18.9 1550.7 486.3 174.8 625.7 669.0 27.1 14.7 10.4 21.7Catawba Co 4083.7 19269.6 82371.7 5011.3 4238.9 5.0 1107.3 1619.7 99.7 90.4 86.5 1.4 5053.2 770.4 91.5 4516.2 1191.5 477.5 6040.4 7049.9 259.8 142.0 100.1 206.4Chatham Co 726.7 3305.0 11871.7 1246.4 677.0 0.4 519.2 580.7 55.2 50.9 48.9 0.5 2426.0 273.1 42.3 2603.3 883.2 2450.6 2291.4 2417.9 99.9 54.9 38.8 78.8Cherokee Co 0.0 0.0 0.0 0.0 0.0 0.0 301.2 144.9 14.6 17.4 16.6 0.2 1820.6 205.4 32.4 1384.2 577.0 146.9 724.8 825.9 32.5 17.8 12.6 25.6Chowan Co 94.5 33.0 168.7 48.0 16.8 0.1 583.9 172.7 17.3 22.6 21.5 0.2 556.8 76.3 10.9 1015.4 250.2 610.4 330.6 333.0 13.7 7.1 4.9 11.6Clay Co 0.0 0.0 0.0 0.5 0.1 0.0 203.9 67.2 7.2 10.4 9.9 0.1 505.9 68.7 8.1 620.3 193.8 29.2 254.8 261.5 11.1 6.0 4.2 9.0Cleveland Co 670.3 291.0 172.4 275.5 241.1 0.2 471.2 745.2 54.6 46.4 44.3 0.6 2916.7 465.6 88.9 3237.1 829.7 1029.6 3026.5 2832.4 119.8 64.445.0 96.3Columbus Co 2670.0 2608.5 2829.3 1590.5 1372.8 128.2 566.3 548.1 48.7 48.9 46.6 0.4 2323.8 339.5 55.3 2749.8 804.2 3063.6 1794.6 1882.7 77.041.3 28.8 62.8Craven Co 2533.1 1693.6 1477.9 721.9 521.4 65.8 973.8 569.2 54.2 56.2 53.6 0.5 2298.1 376.5 46.8 2805.2 756.9 1257.5 2995.1 2884.6 119.7 62.543.0 101.4Cumberland Co 1219.6 736.9 1545.2 280.2 132.0 0.4 1319.6 1703.6 140.5 122.6 116.6 1.2 5258.6 790.5 107.9 5913.6 1419.4 1517.4 10473.5 12143.9446.2 244.4 172.5 353.4Currituck Co 0.0 0.0 0.0 6.0 2.5 0.0 2005.2 537.0 60.2 74.6 70.5 0.7 713.7 115.8 16.5 1412.9 362.9 219.6 876.5 971.6 40.6 22.2 15.7 32.3Dare Co 2.3 75.4 7.6 2.6 1.6 0.0 8509.7 1062.0 105.2 193.3 180.2 2.1 871.8 273.1 36.0 1732.9 433.8 16.6 1521.7 1592.9 66.5 35.8 25.0 54.1Davidson Co 2791.3 3240.7 408.0 457.5 391.7 6.5 809.1 1545.1 101.7 77.3 73.2 0.9 4806.8 656.7 97.5 4468.8 1221.9 559.0 5072.0 6456.2 229.9 128.9 92.2 175.5Davie Co 258.1 35.1 16.0 68.1 58.1 1.2 398.0 280.3 24.3 28.9 27.6 0.3 1714.0 179.8 24.7 1681.5 500.1 445.7 1270.5 2569.9 75.4 47.7 36.2 45.9Duplin Co 17.3 299.2 599.1 150.0 106.8 0.0 186.5 412.0 41.3 42.0 40.6 0.3 1882.0 251.2 33.9 4565.2 1041.3 23702.1 1835.7 2676.8 89.8 52.7 38.6 63.5Durham Co 236.0 352.2 593.3 22.9 17.4 0.5 1517.5 2328.2 215.6 189.6 182.4 2.0 4047.7 1053.9 117.3 4624.6 1179.7 133.2 5434.5 8250.5 337.8 160.5 108.6 279.3Edgecombe Co 281.4 2108.9 331.7 79.6 49.0 0.0 284.2 874.6 61.4 47.1 44.8 0.4 2091.4 271.1 49.4 3460.0 854.9 1913.2 2078.8 2117.5 87.1 45.931.8 72.8Forsyth Co 2296.4 1529.5 3784.3 346.8 200.1 19.4 1579.5 1844.4 157.6 145.9 139.8 1.7 6077.5 1541.5 244.0 7141.2 1746.2 286.4 8787.1 11599.3 455.3 224.0 154.0 360.5Table 1. Typical 2002 BaseG2 Annual Emission Summary for North Carolina Counties (tons)PointNon-roadAreaMobileCountyVOC NOx SO2 PM-10 PM-2.5 NH3 VOC NOx SO2 PM-10 PM-2.5 NH3 VOC NOx SO2 PM-10 PM-2.5 NH3 VOC NOx SO2 PM-10 PM-2.5 NH3Franklin Co 444.8 26.9 6.7 10.0 6.3 0.0 266.6 282.6 26.2 26.4 25.3 0.3 2066.3 262.1 33.2 2266.1 669.0 577.1 1653.2 1798.3 74.3 40.3 28.3 59.8Gaston Co 907.1 14609.5 54597.3 3101.0 2669.8 12.3 944.0 1448.7 106.2 87.7 83.4 1.0 4587.4 775.6 90.8 4044.7 1011.0 291.1 5217.5 6611.5 296.1 134.9 89.8 243.5Gates Co 0.0 0.0 0.0 0.5 0.2 0.0 98.3 127.9 14.7 14.8 14.3 0.1 650.7 64.2 10.3 1138.5 316.5 589.4 324.8 381.3 14.8 8.2 5.8 11.6Graham Co 504.5 25.0 25.8 19.8 13.9 0.0 120.3 44.1 3.5 4.5 4.2 0.1 546.4 59.8 8.8 585.7 207.3 19.3 178.8 167.5 7.3 3.8 2.6 6.1Granville Co 621.6 23.6 1.5 49.0 45.9 29.0 346.4 527.2 49.6 44.8 43.1 0.5 2603.4 254.4 33.6 2476.4 809.2 179.6 1608.8 3519.8 117.6 61.0 43.881.5Greene Co 0.0 1.9 9.1 0.6 0.2 0.0 85.9 219.8 23.6 21.8 21.0 0.1 1079.9 94.2 12.1 1688.8 391.3 4505.9 603.6 605.8 25.7 13.7 9.6 21.1Guilford Co 3931.8 218.7 282.2 221.6 135.0 10.6 3394.1 4408.0 376.3 358.9 344.1 3.7 9393.6 2296.0 231.8 9006.4 2332.4 585.3 12727.2 16815.5 675.2 331.4 227.2 538.1Halifax Co 484.5 4039.7 2426.6 361.7 264.7 5.3 383.5 748.6 59.5 49.8 47.3 0.3 2606.1 268.6 35.6 3387.5 905.3 1122.7 1837.0 3018.9 93.9 56.441.8 63.5Harnett Co 0.0 3.4 0.0 13.4 11.2 0.0 520.8 938.9 72.4 55.3 52.1 0.4 2705.5 449.8 62.1 3671.3 972.3 2263.8 2272.1 3008.4 107.0 60.8 43.8 80.0Haywood Co 1506.9 5599.9 8731.4 898.8 877.8 77.6 619.6 329.1 32.4 39.8 37.8 0.3 2972.8 374.3 69.2 2565.5 952.3 333.4 2136.0 4069.2 120.8 74.756.0 77.3Henderson Co 781.3 75.8 1.7 34.8 27.9 0.5 1349.5 655.4 58.2 78.0 73.9 0.7 3396.2 496.9 62.2 3416.1 1081.5 261.6 2251.6 3073.1 105.4 59.7 43.0 79.2Hertford Co 181.5 176.7 148.7 152.4 134.0 0.0 223.8 187.5 18.9 21.3 20.4 0.2 894.5 139.8 37.6 1426.2 347.8 933.6 584.8 575.2 24.5 13.0 9.1 20.1Hoke Co 181.0 62.2 127.3 21.4 21.4 0.0 164.6 204.2 20.4 20.9 20.1 0.2 1062.5 186.4 34.6 1786.8 631.7 934.8 830.6 847.9 34.7 18.8 13.2 27.8Hyde Co 0.3 16.5 1.4 4.2 1.6 0.0 6489.8 675.9 64.1 132.2 122.9 1.5 470.8 46.1 6.4 2044.3 479.3 145.8 166.4 161.1 6.9 3.7 2.6 5.7Iredell Co 774.3 3967.1 539.6 121.5 105.1 19.9 839.8 1148.7 102.4 92.8 89.2 1.0 3999.3 579.8 108.2 4751.7 1310.4 1904.2 6425.0 10172.6 323.6194.5 143.9 217.1Jackson Co 37.7 76.7 13.0 41.1 31.8 0.0 365.6 275.4 31.0 31.7 30.3 0.3 2177.4 268.2 33.6 1725.6 722.8 46.4 1272.2 1600.5 61.6 34.5 24.7 47.1Johnston Co 179.7 48.3 28.9 10.0 9.7 1.7 841.6 1705.9 138.6 113.0 107.4 0.9 3810.7 626.3 75.1 5519.6 1369.5 2855.4 6225.8 10847.5 335.0 205.4 153.4 218.1Jones Co 0.0 0.0 0.0 10.1 3.2 0.0 69.7 136.3 15.2 14.5 13.9 0.1 534.1 54.3 8.3 1042.1 247.0 2480.8 509.8 611.6 23.7 13.1 9.3 18.5Lee Co 286.1 96.3 90.7 171.5 155.2 0.0 306.5 564.3 45.3 38.5 37.0 0.5 1427.3 278.1 31.1 1495.6 415.2 484.5 1575.4 1571.1 64.8 33.5 22.9 55.6Lenoir Co 353.2 755.2 1122.2 75.9 46.9 17.5 335.5 411.0 35.4 36.7 35.2 0.3 1852.3 246.4 31.4 3501.7 753.2 3666.7 1767.4 1569.9 69.7 35.4 23.9 61.3Lincoln Co 767.5 119.0 17.8 72.3 64.8 0.3 409.9 553.6 42.5 37.4 35.6 0.4 2229.4 306.7 68.5 2606.3 730.5 345.1 2535.5 2051.6 90.4 46.1 31.277.8Mc Dowell Co 730.8 244.9 50.7 242.9 182.6 0.0 417.1 883.9 55.5 37.1 34.6 0.4 2014.4 223.8 43.6 1759.5 603.8 240.7 1543.0 2988.2 88.9 55.4 41.7 56.0Macon Co 4.9 0.0 0.0 0.8 0.2 0.0 489.9 210.4 21.8 28.6 27.1 0.3 2065.9 264.8 32.2 1670.3 695.4 72.8 927.5 1059.7 42.0 23.1 16.3 33.1Madison Co 0.0 0.0 0.0 0.0 0.0 0.0 159.3 327.2 23.5 16.1 15.1 0.1 1602.6 142.7 30.7 1250.6 469.2 117.6 516.3 591.8 23.5 12.9 9.1 18.5Martin Co 1085.1 4606.2 3426.0 640.2 523.0 102.6 251.6 242.6 23.9 26.1 25.0 0.2 1431.8 160.9 22.2 1935.0 484.7 620.5 939.6 979.7 39.8 21.314.9 32.4Mecklenburg Co 2082.4 765.4 867.7 528.0 390.5 72.2 7653.1 8351.7 836.8 929.4 894.8 7.6 11422.2 3424.8 356.5 13585.6 2167.0 414.0 26067.1 25981.4 1122.0 506.7 335.3 933.9Mitchell Co 467.8 75.8 23.6 54.8 48.9 0.0 262.3 667.2 42.9 25.7 23.6 0.1 1045.7 122.1 21.1 844.7 297.8 35.8 385.3 391.2 16.2 8.6 6.0 13.3Montgomery Co 544.3 117.7 54.2 195.4 144.2 0.1 264.0 241.1 18.8 18.1 17.3 0.2 1467.9 166.8 31.8 1366.9 478.6 1446.1 1058.5 1201.0 46.8 25.918.4 36.5Moore Co 8.0 12.2 14.7 4.1 2.8 0.0 535.5 503.7 48.9 46.3 44.2 0.5 2578.1 464.7 54.3 2317.9 786.3 2275.2 2191.5 2051.3 87.1 45.2 31.1 74.1Nash Co 378.9 172.8 95.7 19.2 14.1 0.8 406.2 715.7 61.4 53.0 50.6 0.4 3275.7 520.7 65.7 3900.1 1059.9 1925.4 4356.3 6824.2 223.6 131.5 96.2 158.0New Hanover Co 2275.1 10332.3 27675.4 1154.3 609.2 5.5 1586.2 3633.9 478.4 233.4 220.1 1.6 2723.5 632.8 72.2 2614.5 689.3 126.0 3470.9 3305.8140.1 72.4 49.5 120.3Northampton Co 162.7 23.1 8.6 65.3 20.2 1.3 230.9 582.5 47.0 35.7 33.8 0.2 1160.4 140.9 25.3 3215.3 793.6 1706.1 871.1 1413.0 45.4 27.3 20.2 30.6Onslow Co 64.3 23.1 32.1 3.5 3.1 0.0 1247.2 566.2 60.9 69.3 66.0 0.6 3107.9 509.6 75.9 3079.1 940.6 2547.2 3586.5 3239.0 138.1 72.1 49.6 116.8Orange Co 70.9 527.5 148.6 24.0 16.1 0.0 893.8 903.6 96.0 91.6 87.6 0.7 3257.0 606.4 122.9 3344.7 977.8 401.1 3187.4 7610.2 247.7 130.6 94.6165.2Table 1. Typical 2002 BaseG2 Annual Emission Summary for North Carolina Counties (tons)PointNon-roadAreaMobileCountyVOC NOx SO2 PM-10 PM-2.5 NH3 VOC NOx SO2 PM-10 PM-2.5 NH3 VOC NOx SO2 PM-10 PM-2.5 NH3 VOC NOx SO2 PM-10 PM-2.5 NH3Pamlico Co 0.0 0.0 0.0 0.0 0.0 0.0 0.0 758.6 89.0 88.2 84.5 0.7 498.6 72.3 10.0 980.2 248.3 107.8 343.0 297.7 13.3 6.9 4.7 11.5Pasquotank Co 3.0 8.3 4.3 7.3 18.1 5.7 0.0 379.7 41.1 52.4 50.2 0.4 891.7 188.7 25.2 3137.8 699.5 149.0 723.5 667.8 28.9 14.7 10.0 25.2Pender Co 0.0 0.0 0.0 0.6 0.1 0.0 397.4 288.3 32.4 31.1 29.8 0.3 1637.9 302.7 53.1 2034.2 780.6 3259.7 1668.6 2753.1 88.2 53.0 39.2 59.7Perquimans Co 0.0 230.1 20.2 358.2 304.8 4.7 772.8 246.7 26.7 34.5 32.9 0.3 621.6 69.0 10.0 2112.6 505.2 548.0 384.1 441.2 17.0 9.4 6.7 13.2Person Co 381.1 33688.0 126780.3 4165.9 1802.2 29.4 290.3 267.4 23.2 23.4 22.3 0.2 1872.3 195.0 40.8 1538.4 535.0 220.7 836.6 766.8 33.8 17.4 11.9 29.0Pitt Co 616.1 256.4 62.8 57.4 44.9 3.9 662.4 1181.0 108.0 97.5 93.7 0.8 3629.4 568.2 66.5 4014.4 1005.1 2271.8 3111.2 2973.0 128.0 66.6 45.7109.1Polk Co 0.2 2.0 1.2 0.5 0.3 0.0 166.5 123.5 11.1 11.7 11.1 0.1 932.7 130.5 28.2 869.7 292.3 55.5 720.8 1417.3 41.7 26.1 19.7 25.9Randolph Co 2532.9 19.3 3.0 188.1 173.0 0.0 735.2 971.6 66.4 62.6 59.8 0.9 5669.1 664.6 88.1 4411.3 1357.0 3555.5 4904.2 5954.3 218.2 119.1 83.9 173.8Richmond Co 20.7 289.7 64.8 60.1 35.7 7.2 302.5 632.7 47.4 33.5 31.6 0.3 1333.0 231.9 37.9 1439.5 445.6 1797.8 1562.8 1624.4 65.5 34.8 24.254.1Robeson Co 220.7 3092.6 7762.4 219.5 98.0 0.9 458.0 1239.1 100.3 83.7 79.9 0.6 4500.6 606.4 100.4 8866.4 2429.5 5390.3 4230.6 6445.4 209.7 123.1 90.0 148.4Rockingham Co 766.1 7858.9 5290.8 539.9 358.4 4.0 496.9 805.8 56.4 45.2 42.8 0.5 3757.7 456.1 66.6 3250.9 1017.4 312.4 2633.6 2610.3 109.3 57.0 39.2 92.8Rowan Co 2297.3 3924.1 10600.6 835.7 674.6 9.7 749.3 1280.5 86.6 69.3 65.4 0.7 3504.5 508.3 116.1 3997.6 1020.1 524.5 5342.4 6703.6 229.0 129.1 92.5 171.4Rutherford Co 761.3 5118.1 29902.4 2252.0 1795.1 0.5 434.9 640.3 45.0 36.5 34.4 0.4 2448.0 320.3 47.3 2475.3 752.2 377.6 1809.9 1703.9 71.838.0 26.3 59.6Sampson Co 24.4 27.0 18.3 74.0 22.1 0.0 227.5 477.8 48.5 50.0 48.3 0.4 2293.8 314.7 47.7 7801.4 1731.5 21430.0 2026.4 2556.3 92.8 52.4 37.670.1Scotland Co 818.9 1597.8 252.1 426.8 410.0 2.6 150.4 484.6 31.9 22.1 20.9 0.2 1113.0 225.9 46.1 1899.9 712.6 632.4 1176.2 1147.2 48.0 25.1 17.3 40.5Stanly Co 357.9 521.1 1654.0 233.5 166.4 0.0 524.6 500.5 39.2 40.9 38.9 0.4 1927.7 289.4 40.9 2389.0 663.3 1442.2 2662.0 2001.1 92.0 46.5 31.4 79.8Stokes Co 199.7 35861.1 83483.9 4688.5 4060.3 7.1 265.0 293.2 24.7 22.9 21.7 0.2 2565.3 227.0 45.8 2087.6 712.3 333.3 1067.4 1051.9 43.9 23.4 16.4 35.9Surry Co 1531.3 257.1 320.5 199.8 125.7 0.0 560.3 467.1 36.2 41.5 39.6 0.5 2976.6 406.9 55.2 2903.4 814.6 1817.3 2588.9 3735.0 125.5 73.2 53.5 89.6Swain Co 0.0 0.0 0.0 0.0 0.0 0.0 755.4 112.2 12.3 29.4 27.4 0.2 1162.0 121.1 16.5 824.0 345.4 204.8 580.1 610.1 24.8 13.5 9.5 19.8Transylvania Co 148.6 890.4 1545.5 62.0 58.8 0.6 947.3 221.4 21.8 42.6 40.0 0.3 1428.5 174.2 20.1 1326.6 462.0 96.9 800.5 773.1 33.8 17.7 12.2 28.6Tyrrell Co 0.0 0.0 0.0 0.0 0.0 0.0 1845.2 287.9 30.0 47.7 44.7 0.5 345.3 31.0 4.9 3043.9 693.2 277.4 152.8 178.1 6.8 3.8 2.7 5.3Union Co 375.3 74.5 169.1 116.2 37.3 0.0 1460.2 1994.5 187.0 174.2 166.8 1.6 3616.0 611.1 62.5 5238.4 1452.5 5909.7 4546.0 3778.1 170.7 88.6 60.7 143.6Vance Co 212.2 824.6 267.1 147.3 134.8 0.1 458.0 245.9 22.3 26.5 25.2 0.3 1671.7 237.3 33.5 1717.3 523.3 88.9 1347.4 1998.6 66.1 38.0 27.648.3Wake Co 1060.4 204.6 76.4 244.9 68.2 2.2 5741.6 6299.5 657.4 725.1 698.4 5.7 12700.5 3472.9 346.1 15940.0 4165.6 455.7 14782.2 24086.6 961.5468.7 322.6 759.2Warren Co 0.7 2.1 0.2 2.6 1.7 0.0 198.7 136.4 15.1 14.2 13.6 0.1 1213.5 127.3 20.4 1199.3 412.4 651.5 627.6 1075.1 33.1 20.2 15.1 21.5Washington Co 0.0 0.0 0.0 8.9 3.6 0.0 732.4 338.6 32.6 38.9 37.1 0.3 739.4 109.4 13.8 1569.1 500.0 523.4 425.4 458.0 18.6 10.0 7.0 15.1Watauga Co 26.7 46.2 40.1 17.3 13.4 0.0 680.8 411.3 46.3 52.8 50.4 0.4 2063.8 353.7 85.0 1863.6 665.6 253.9 1128.4 1173.1 47.6 25.6 17.9 38.6Wayne Co 1104.8 5324.0 14731.4 722.6 459.0 0.0 508.6 708.3 65.2 63.7 61.4 0.6 2843.6 549.9 69.1 5738.2 1324.3 8197.4 3061.5 2803.1 119.3 61.341.7 103.2Wilkes Co 1212.3 310.1 95.1 139.1 110.0 2.8 397.7 331.6 26.6 29.6 28.3 0.4 3031.8 357.4 83.8 2811.2 900.5 4606.8 1926.3 2013.3 82.6 44.6 31.2 66.9Wilson Co 1049.4 443.8 1122.2 228.8 191.4 5.4 531.0 1091.2 82.7 66.1 62.7 0.6 2294.5 319.7 37.5 3172.8 727.7 574.2 2537.4 3009.0 112.7 61.6 43.5 89.3Yadkin Co 38.1 1.2 7.0 3.5 2.5 0.0 182.4 224.6 21.3 22.2 21.4 0.2 1691.5 199.2 28.2 2058.8 545.1 1488.7 1362.2 2260.3 72.0 43.5 32.2 48.3Yancey Co 12.6 2.8 5.3 0.1 0.1 0.0 283.6 400.6 26.6 19.9 18.3 0.1 1405.5 141.0 29.5 1051.0 417.5 67.9 417.7 487.1 18.9 10.4 7.4 14.8Table 2. 2009 BaseG2 Annual Emission Summary for North Carolina Counties (tons)Point Non-road Area MobileCountyVOC NOx SO2 PM-10 PM-2.5 NH3 VOC NOx SO2 PM-10 PM-2.5 NH3VOC NOx SO2 PM-10 PM-2.5 NH3VOC NOx SO2 PM-10 PM-2.5 NH3Alamance Co 344.3 162.4 25.4 49.8 37.5 6.9 644.7 809.8 13.0 63.1 59.9 1.0 2808.9 670.1 80.6 3544.4 983.0 581.0 3011.9 3789.4 25.0 96.0 61.1196.3Alexander Co 366.3 6.5 4.2 40.6 26.1 0.0 228.1 173.1 2.9 17.1 16.2 0.3 1297.3 188.2 25.6 1494.5 424.4 1994.2 453.7 435.7 3.3 12.4 7.7 27.3Alleghany Co 5.0 0.1 0.3 0.5 0.2 0.0 50.4 70.0 1.4 6.5 6.2 0.1 603.2 97.2 13.9 982.8 300.0 337.1 170.5 158.0 1.2 4.5 2.8 10.1Anson Co 62.4 72.6 156.4 45.0 38.4 0.6 105.9 453.2 6.0 16.4 15.3 0.1 707.1 119.6 21.6 1273.0 370.3 2734.2 574.1 651.0 4.4 17.0 10.8 34.6Ashe Co 3.4 14.2 25.8 17.5 11.3 0.0 163.7 132.7 2.7 14.2 13.5 0.2 1344.7 219.2 33.4 1735.1 608.5 226.6 485.6 439.2 3.4 12.6 7.8 28.5Avery Co 29.6 5.8 13.3 1.5 1.0 0.0 281.0 120.8 2.6 18.1 17.1 0.2 763.4 176.0 46.3 1013.7 345.0 91.9 336.8 361.1 2.6 9.7 6.1 20.5Beaufort Co 99.1 699.8 5390.7 748.3 455.7 602.2 1376.9 848.7 15.6 69.5 65.6 0.8 1626.3 287.8 31.8 2941.1 832.8 1195.7 729.8 709.2 5.3 19.612.2 43.9Bertie Co 223.9 74.3 213.6 27.4 18.4 7.3 328.8 231.3 5.7 21.6 20.6 0.3 1143.4 138.1 24.2 1950.1 534.1 1834.8 493.5 527.9 3.7 14.2 9.0 30.0Bladen Co 235.5 801.7 2489.2 60.8 38.3 0.6 329.6 391.1 6.5 26.6 25.2 0.3 1345.0 227.1 43.3 2950.0 918.2 8922.2 770.0 727.8 5.6 20.8 12.9 46.6Brunswick Co 1508.4 2807.2 7016.0 347.7 262.0 6.7 1021.7 1035.4 51.5 81.9 77.4 0.9 1838.9 428.8 55.6 2623.4 900.4 1088.4 2057.1 2310.6 17.0 64.7 40.9 136.5Buncombe Co 432.1 1051.4 1750.0 629.4 312.3 1.3 1700.6 1342.6 25.4 125.3 118.8 1.5 5257.8 1419.6 243.0 6582.5 2076.4 331.7 3719.0 5094.5 32.2 125.5 80.7 247.2Burke Co 798.5 126.5 275.0 238.2 220.1 1.3 288.8 447.9 6.3 25.6 24.3 0.5 2281.5 426.3 75.4 2856.6 885.3 419.9 2029.8 3072.9 18.6 75.2 49.8132.9Cabarrus Co 729.1 854.5 2023.5 80.4 51.4 9.6 568.1 1294.7 21.2 81.0 76.9 1.0 2679.0 594.8 61.9 4234.0 1192.8 553.4 4336.9 3599.4 30.7 113.069.4 257.1Caldwell Co 4102.7 429.9 38.2 221.0 154.8 0.0 422.6 384.0 5.9 30.5 29.1 0.6 2366.9 415.6 61.0 2856.0 986.1 345.0 1488.1 1467.3 11.5 43.0 26.7 95.1Camden Co 0.0 0.0 0.0 0.0 0.0 0.0 447.9 189.6 4.7 19.0 18.0 0.2 266.0 48.1 7.8 1681.5 406.5 193.4 202.1 214.6 1.5 5.8 3.6 12.5Carteret Co 94.5 37.3 177.2 46.0 7.4 0.0 4618.5 2594.3 237.0 183.3 170.1 1.6 1950.5 646.4 123.2 3557.8 1747.3 202.8 991.7 1128.3 8.4 32.0 20.2 67.3Caswell Co 0.0 0.00.00.0 0.0 0.0 66.9 187.2 2.8 9.2 8.7 0.1 1114.1 144.8 20.8 1566.6 463.6 188.6 418.5 437.9 3.1 11.9 7.5 25.2Catawba Co 3501.0 13094.5 10797.5 3755.1 3246.6 8.9 819.0 1178.4 17.2 73.5 70.2 1.5 3964.3 830.0 96.0 4783.8 1333.5 512.6 3984.9 4445.7 31.4 119.2 75.2 251.3Chatham Co 628.3 1976.5 14221.6 949.7 530.6 30.1 355.9 464.3 9.1 38.7 37.1 0.5 1787.2 298.6 45.7 2663.0 872.8 2736.6 1644.3 1727.5 13.3 51.1 32.5 105.4Cherokee Co 0.0 0.0 0.0 0.0 0.0 0.0 300.1 119.6 2.4 15.6 14.7 0.2 1270.5 238.9 39.1 1458.3 589.0 164.0 502.9 559.8 3.9 14.8 9.4 30.9Chowan Co 65.9 32.8 168.7 50.2 17.5 0.1 428.4 159.8 3.9 15.8 15.0 0.2 455.4 83.3 11.6 1044.7 260.5 640.7 220.2 222.2 1.6 5.9 3.7 13.5Clay Co 0.0 0.0 0.0 0.6 0.1 0.0 227.5 57.6 1.2 10.3 9.7 0.1 374.9 74.5 8.9 652.9 195.9 30.1 179.6 179.4 1.3 5.1 3.2 11.0Cleveland Co 734.3 324.0 192.4 300.1 261.1 0.2 367.3 583.8 9.2 36.8 35.1 0.6 2248.3 507.0 92.7 3385.3 884.5 1119.7 2468.0 2190.6 18.2 68.242.6 147.2Columbus Co 2559.3 2758.0 3013.1 1659.2 1419.2 136.4 519.7 450.7 9.0 39.5 37.4 0.4 1989.8 368.5 59.9 2849.5 857.5 3093.9 1306.3 1415.6 10.0 37.9 23.9 80.4Craven Co 2702.5 1968.7 1556.9 775.0 560.4 70.2 741.0 480.1 10.6 43.1 40.9 0.6 2168.9 508.5 76.9 3382.6 1213.7 1287.2 2092.0 2027.2 15.8 58.6 36.3 131.3Cumberland Co 1289.2 579.7 1306.6 229.1 125.2 3.5 990.4 1336.5 22.2 98.7 93.6 1.3 4576.9 866.0 114.2 6287.9 1665.4 1582.2 6521.8 7313.1 51.4 195.8 123.7 410.5Currituck Co 0.0 0.0 0.0 6.7 2.8 0.0 1584.7 512.4 12.3 57.7 54.5 0.8 628.1 145.1 23.1 1544.4 460.1 230.2 814.5 857.8 6.4 24.3 15.3 52.0Dare Co 2.0 72.1 8.3 2.8 1.7 0.0 6679.3 1163.7 19.8 148.3 138.2 2.2 939.9 361.3 56.3 2188.7 798.2 32.7 1019.5 1038.0 7.7 29.0 18.1 63.1Davidson Co 2840.9 1434.3 442.0 455.3 389.1 7.3 599.9 1243.3 17.2 61.1 57.7 0.9 3651.1 712.5 104.5 4693.6 1299.5 606.1 3378.3 4185.6 28.5 110.7 71.0 220.4Davie Co 259.4 35.1 16.0 68.5 58.2 1.2 391.9 224.3 4.1 26.0 24.6 0.3 1339.8 195.2 27.0 1734.3 502.4 467.8 827.9 1520.7 8.2 34.6 23.7 52.1Duplin Co 20.0 523.2 2319.7 200.4 157.4 1.1 132.6 340.1 6.7 29.3 28.3 0.3 1643.8 275.6 36.8 4589.2 1085.0 24403.1 1285.7 1811.8 10.8 43.6 28.8 77.6Durham Co 293.7 368.3 581.6 26.2 20.0 0.5 1084.8 1821.2 36.1 149.4 143.3 2.2 3524.7 1134.8 122.3 5062.5 1439.8 145.8 3622.4 5118.3 44.1 150.2 89.9 356.5Edgecombe Co 357.5 1978.8 651.8 227.3 213.9 5.5 194.2 712.5 10.3 34.6 32.9 0.5 1729.5 295.0 51.6 3496.3 880.0 1955.8 1309.7 1343.4 10.4 38.724.0 85.9Forsyth Co 2384.2 1507.2 3817.3 345.3 188.7 22.1 1056.5 1456.3 26.6 116.5 111.4 1.9 5120.5 1648.0 250.7 7717.6 2114.6 307.9 5898.4 6540.3 53.9188.4 114.4 432.7Table 2. 2009 BaseG2 Annual Emission Summary for North Carolina Counties (tons)Point Non-road Area MobileCountyVOC NOx SO2 PM-10 PM-2.5 NH3 VOC NOx SO2 PM-10 PM-2.5 NH3VOC NOx SO2 PM-10 PM-2.5 NH3VOC NOx SO2 PM-10 PM-2.5 NH3Franklin Co 501.3 28.3 7.6 11.1 6.8 0.0 175.4 224.2 4.3 20.3 19.4 0.3 1607.9 285.2 36.4 2357.2 694.4 603.9 1304.3 1370.3 10.7 40.5 25.5 86.4Gaston Co 1072.2 7920.1 49092.5 3627.2 3126.6 104.9 687.9 1162.7 17.9 70.2 66.6 1.1 3878.7 848.6 97.1 4342.5 1149.4 317.2 3453.5 3918.0 38.8 129.0 76.2 312.5Gates Co 0.0 0.0 0.0 0.5 0.2 0.0 68.4 108.4 3.4 10.4 10.0 0.1 481.6 69.9 11.1 1152.5 308.4 627.5 204.8 233.8 1.6 6.1 3.9 12.6Graham Co 504.5 25.0 25.8 19.8 13.9 0.0 85.8 34.8 0.6 3.4 3.2 0.1 410.0 79.1 13.4 675.1 255.5 23.4 114.8 106.0 0.8 3.0 1.8 6.9Granville Co 693.0 25.1 1.7 58.0 54.4 29.1 224.2 408.8 8.2 34.4 33.0 0.5 1934.7 277.6 36.7 2502.5 781.5 186.0 878.1 1901.9 13.1 47.0 30.089.9Greene Co 0.1 2.1 9.5 0.7 0.2 0.0 59.0 185.5 4.9 15.4 14.8 0.1 905.5 102.9 13.3 1725.1 408.0 4599.4 404.1 397.2 3.0 11.1 6.9 24.5Guilford Co 4204.3 222.2 251.8 219.0 143.8 10.8 2297.0 3568.5 73.3 297.9 285.3 4.0 7819.4 2488.4 246.7 9654.9 2717.5 620.6 8508.9 9759.0 81.0 284.9 173.8 645.0Halifax Co 509.9 3736.3 2946.8 573.1 466.6 15.7 305.0 639.2 9.8 38.2 36.1 0.4 1963.9 297.8 38.6 3396.5 876.9 1168.8 1118.2 1893.6 10.2 42.729.0 68.1Harnett Co 0.0 3.2 0.0 15.5 12.9 0.0 347.1 809.1 12.0 43.0 40.5 0.4 2314.7 485.6 66.6 3830.3 1073.0 2469.4 1424.0 1837.6 12.4 48.5 31.4 93.5Haywood Co 1591.7 2945.0 9263.9 930.6 908.2 82.8 681.3 270.4 5.4 38.3 36.1 0.4 2048.4 398.6 71.4 2564.4 871.3 335.9 1320.6 2539.2 13.9 58.740.2 90.2Henderson Co 717.5 82.0 1.8 34.7 27.2 0.6 1562.5 528.5 9.7 79.0 74.2 0.9 2548.0 537.8 66.7 3544.9 1110.5 269.6 1480.3 2055.4 13.2 52.2 34.0 98.2Hertford Co 202.3 151.6 130.3 136.6 117.9 0.0 200.3 152.2 3.0 16.5 15.8 0.2 743.4 151.2 38.8 1463.7 362.4 986.9 353.2 339.7 2.5 9.5 6.021.1Hoke Co 213.0 62.7 127.3 21.4 21.4 0.0 155.8 163.2 3.4 16.4 15.7 0.2 903.9 196.4 36.2 1849.3 662.9 951.5 593.4 607.5 4.3 16.4 10.4 34.9Hyde Co 0.2 15.6 1.6 4.8 1.8 0.0 4797.8 785.3 12.8 88.6 82.4 1.5 370.5 50.4 6.8 2022.5 469.9 148.2 159.6 151.5 1.2 4.3 2.7 9.7Iredell Co 669.4 1380.8 550.4 127.5 109.9 22.2 671.5 909.6 17.1 72.5 69.5 1.1 3068.2 625.9 113.9 4987.6 1408.4 2070.6 4303.5 6814.8 40.8 169.4 114.7 270.2Jackson Co 40.5 82.1 13.6 43.2 33.7 0.0 11574.3 3735.1 63.7 376.3 355.7 5.8 1506.2 297.4 38.4 1765.4 698.7 53.1 902.1 1102.4 7.5 29.0 18.658.0Johnston Co 234.4 48.8 30.3 10.7 10.4 1.7 651.5 1446.3 23.0 88.4 83.7 0.9 3238.0 675.5 81.2 5785.3 1527.8 2987.5 4540.9 7532.6 44.0 183.3 124.1 293.6Jones Co 0.0 0.0 0.0 11.0 3.4 0.0 47.9 116.3 3.5 10.2 9.8 0.1 613.8 126.1 27.4 1377.7 520.8 2512.9 328.8 385.5 2.6 10.1 6.4 20.7Lee Co 301.7 102.5 96.4 119.3 101.1 0.0 201.2 426.5 7.6 29.6 28.4 0.5 1152.3 301.1 33.4 1587.9 452.9 531.5 1054.5 1061.7 8.2 30.4 18.8 69.1Lenoir Co 405.5 813.8 1215.2 83.9 51.4 18.4 272.2 329.6 7.0 28.4 27.2 0.4 1607.5 272.9 34.0 3561.4 805.7 3815.7 1055.0 953.3 7.9 29.0 17.7 67.9Lincoln Co 852.0 40.6 4.3 72.6 65.3 0.3 323.1 451.0 7.1 30.0 28.5 0.4 1698.2 332.3 79.8 2737.1 774.8 372.1 1653.9 1515.2 12.1 44.7 27.6 100.0Mc Dowell Co 681.5 258.8 50.8 231.2 167.1 0.0 365.6 733.9 9.3 31.6 29.4 0.4 1414.9 241.6 46.0 1806.2 581.3 268.1 1024.6 1870.2 10.0 42.0 28.7 64.6Macon Co 5.6 0.0 0.0 0.9 0.2 0.0 506.3 175.1 3.6 27.5 25.9 0.3 1445.3 297.4 37.8 1731.0 692.2 79.8 637.4 707.6 4.9 18.9 12.0 39.4Madison Co 0.0 0.0 0.0 0.0 0.0 0.0 157.5 284.1 3.9 13.5 12.6 0.1 1098.3 154.3 32.3 1244.7 419.3 118.6 356.6 533.7 3.1 12.8 8.5 22.2Martin Co 1188.4 4400.0 3616.5 682.9 426.7 109.5 206.2 202.5 4.9 20.8 19.8 0.2 1156.1 177.9 24.3 1954.5 482.6 655.1 623.7 666.7 4.7 17.711.2 37.6Mecklenburg Co 1942.3 766.6 788.1 566.2 412.0 81.2 5333.8 7177.9 214.5 825.9 794.7 7.9 10215.2 3734.6 373.8 14973.1 3139.8 452.2 13604.0 14027.2 143.6 471.8 274.6 1193.1Mitchell Co 474.1 76.4 25.0 56.1 50.1 0.0 314.4 583.7 7.2 23.4 21.5 0.1 735.0 131.6 22.4 865.1 277.2 37.8 250.9 252.0 1.8 6.9 4.3 15.1Montgomery Co 601.5 127.8 55.6 189.5 142.8 0.1 226.0 180.2 3.1 14.9 14.1 0.2 1162.4 221.6 45.0 1600.8 638.0 1619.0 713.0 806.7 5.5 21.213.5 42.9Moore Co 8.1 12.4 14.7 4.2 2.9 0.0 357.2 412.4 8.0 36.6 34.8 0.5 2038.4 499.1 58.2 2431.8 822.7 2527.9 1418.4 1304.3 10.5 38.9 24.0 88.8Nash Co 292.3 183.3 101.7 21.4 15.9 0.8 281.2 601.6 10.1 39.8 38.0 0.5 2625.0 564.8 69.9 3999.1 1101.3 2089.5 2713.2 4078.6 25.2 101.5 66.9182.3New Hanover Co 2358.5 7088.0 30044.9 1603.2 789.0 19.1 1183.6 3318.5 307.1 202.5 190.4 1.5 2394.7 691.5 75.3 2835.8 819.9 132.3 2276.1 2134.417.4 63.8 38.9 149.1Northampton Co 188.6 24.9 9.7 67.5 22.2 1.5 168.0 508.5 7.7 25.4 24.0 0.2 898.1 151.7 26.7 3198.9 783.3 1768.1 565.5 880.8 5.1 20.7 13.9 35.0Onslow Co 46.7 24.0 36.2 4.1 3.6 0.0 1148.8 495.7 11.1 59.2 56.0 0.7 2678.9 538.9 79.8 3247.7 1031.0 2664.2 2358.0 2154.5 17.4 64.1 39.4 146.5Orange Co 81.4 530.1 148.4 20.8 14.1 0.0 863.8 768.1 15.9 77.7 73.8 0.8 2572.9 658.3 127.1 3531.7 1045.5 415.6 1625.6 3648.1 23.9 86.8 56.1157.4Table 2. 2009 BaseG2 Annual Emission Summary for North Carolina Counties (tons)Point Non-road Area MobileCountyVOC NOx SO2 PM-10 PM-2.5 NH3 VOC NOx SO2 PM-10 PM-2.5 NH3VOC NOx SO2 PM-10 PM-2.5 NH3VOC NOx SO2 PM-10 PM-2.5 NH3Pamlico Co 0.0 0.0 0.0 0.0 0.0 0.0 1813.8 317.6 6.5 43.3 40.4 0.6 429.9 78.7 10.8 1013.2 261.6 109.7 237.9 206.9 1.6 6.0 3.6 14.1Pasquotank Co 3.7 10.4 9.1 22.1 6.9 0.0 600.6 340.6 8.3 40.3 38.6 0.4 766.0 202.8 26.6 3157.1 733.0 152.0 504.6 493.0 3.6 13.4 8.2 30.5Pender Co 0.0 0.0 0.0 0.2 0.1 0.0 273.1 243.1 7.3 24.0 22.8 0.3 1373.5 320.7 55.7 2127.5 818.9 3322.6 1143.7 1727.7 10.1 41.1 27.3 71.4Perquimans Co 0.0 0.0 0.0 0.6 0.1 0.0 568.1 234.1 5.4 23.6 22.4 0.3 487.0 75.2 10.8 2103.1 501.1 594.7 274.3 318.9 2.1 8.2 5.3 16.8Person Co 348.6 9148.9 26525.6 4332.8 2080.4 35.4 195.7 210.9 3.8 17.9 17.1 0.3 1398.5 212.7 43.1 1565.9 513.7 226.3 559.2 518.4 4.0 14.7 9.0 33.7Pitt Co 652.1 263.8 58.5 60.5 47.3 3.8 456.0 975.2 21.5 75.4 72.4 0.9 3195.1 617.5 71.5 4185.0 1118.4 2310.0 1952.1 1828.7 15.0 55.3 33.9 127.4Polk Co 0.3 2.5 1.5 0.6 0.4 0.0 104.3 102.1 1.8 9.7 9.2 0.1 663.6 141.5 29.5 902.5 283.2 57.8 514.2 951.9 5.0 21.2 14.5 32.2Randolph Co 2771.5 20.7 3.5 189.0 173.0 0.0 527.9 725.3 11.2 50.4 48.0 0.9 4219.3 723.1 95.0 4544.5 1360.5 3962.6 3150.5 3834.4 26.2 100.8 64.2 206.1Richmond Co 11.3 91.7 56.2 28.9 17.4 0.0 203.7 533.7 7.9 26.1 24.6 0.3 1075.8 250.1 40.0 1522.7 476.7 1978.6 1013.3 1071.0 7.5 28.3 17.861.1Robeson Co 155.6 3460.0 8307.0 350.0 153.4 32.4 318.4 1038.9 15.9 60.0 57.2 0.7 3696.5 652.9 106.8 8916.6 2484.5 5570.1 2558.2 3770.5 23.2 93.6 61.9 166.5Rockingham Co 802.7 4000.3 10371.5 665.1 497.3 49.6 431.1 654.9 9.4 37.2 35.1 0.5 2779.0 500.4 71.6 3327.7 1001.8 324.9 1499.3 1515.1 11.844.1 27.4 98.5Rowan Co 2416.6 3019.7 12321.7 857.6 692.1 107.2 651.6 1048.1 14.5 56.4 53.1 0.7 2741.2 551.2 121.1 4216.3 1111.1 543.5 3397.7 3767.8 26.4 98.9 61.6 215.6Rutherford Co 773.8 2923.6 38083.5 2635.5 2101.9 32.1 378.2 518.1 7.5 30.9 29.1 0.4 1777.3 347.3 50.9 2546.6 751.7 395.6 1079.2 1047.5 8.230.8 19.2 67.4Sampson Co 23.7 28.8 19.9 78.4 22.3 0.0 161.1 391.9 7.9 34.8 33.6 0.4 1969.0 340.8 51.1 7721.9 1748.8 22001.7 1328.1 1675.3 10.7 42.0 27.380.1Scotland Co 906.9 1789.1 281.4 473.7 455.3 3.1 104.9 392.8 5.3 16.4 15.5 0.2 957.0 236.5 47.7 1969.5 746.7 688.5 759.8 766.5 5.5 20.7 12.9 45.7Stanly Co 377.8 547.9 1773.0 257.2 183.4 0.0 484.3 405.5 6.6 34.6 32.8 0.4 1518.5 311.3 43.6 2497.4 708.0 1598.5 1457.0 1171.5 10.1 36.7 22.3 85.8Stokes Co 151.3 4299.8 10511.0 3009.0 2602.3 4.5 272.4 248.3 4.1 19.5 18.4 0.2 1833.3 247.5 48.8 2110.5 669.8 346.4 654.4 646.1 5.1 19.011.9 41.6Surry Co 1388.2 264.6 330.6 205.9 130.5 0.0 401.8 351.1 6.1 34.5 32.8 0.6 2250.3 439.1 58.8 2987.0 817.4 2000.0 1465.9 2274.5 13.8 56.1 37.4 96.4Swain Co 0.0 0.0 0.0 0.0 0.0 0.0 992.6 102.8 2.0 35.5 33.0 0.3 811.9 132.2 17.8 822.1 303.2 215.6 354.6 362.1 2.6 9.9 6.2 21.0Transylvania Co 131.4 945.4 1567.8 54.2 51.2 0.7 1245.5 188.2 3.6 49.8 46.4 0.4 1073.9 191.2 21.8 1363.2 451.9 107.9 541.3 531.0 4.1 15.1 9.4 33.8Tyrrell Co 0.0 0.0 0.0 0.0 0.0 0.0 1365.6 307.2 7.3 32.1 30.1 0.5 280.1 33.5 5.3 2979.7 677.5 280.2 117.6 139.4 0.9 3.6 2.3 7.2Union Co 389.4 78.4 171.1 88.7 39.9 0.0 968.9 1641.2 31.1 137.6 131.4 1.7 2999.8 663.1 68.4 5487.8 1609.5 6671.2 3171.3 2363.4 20.8 73.9 44.0183.4Vance Co 248.9 929.9 301.3 163.8 150.5 0.1 395.9 197.2 3.7 23.0 21.7 0.3 1293.2 257.2 35.7 1773.1 528.9 91.6 898.7 1319.0 7.7 31.0 20.556.2Wake Co 1135.2 216.6 77.4 263.7 74.8 3.0 3863.0 5420.7 165.3 636.6 612.9 5.9 11257.2 3733.4 358.4 17383.2 5096.3 493.8 10141.6 13813.8 122.3 414.7 246.9 997.6Warren Co 0.7 2.1 0.2 2.6 1.7 0.0 142.6 105.2 2.3 10.2 9.8 0.1 887.3 138.1 22.0 1221.4 395.8 680.2 428.6 702.0 3.9 16.0 10.8 25.8Washington Co 0.0 0.0 0.0 10.8 4.3 0.0 535.7 300.2 6.4 27.0 25.7 0.3 682.9 152.8 24.7 1759.7 653.6 572.3 272.2 288.3 2.1 7.8 4.9 16.8Watauga Co 27.5 46.5 42.2 18.0 13.8 0.0 716.4 345.0 7.6 48.5 45.9 0.5 1508.6 376.0 86.9 1911.2 652.0 259.1 680.4 710.5 5.0 18.9 11.9 40.3Wayne Co 856.8 3524.7 15683.2 766.8 469.8 27.6 397.3 566.0 10.7 48.2 46.2 0.7 2517.3 591.5 73.3 5909.1 1474.6 8632.2 2022.1 1802.5 14.7 53.532.6 126.2Wilkes Co 1243.0 327.9 77.4 145.2 115.4 3.2 307.5 249.4 4.4 24.5 23.3 0.4 2160.2 387.3 87.8 2865.6 873.9 5219.3 1150.2 1194.4 9.2 34.8 21.8 75.0Wilson Co 753.1 364.5 881.1 203.1 167.4 5.2 398.6 907.4 13.8 51.5 48.8 0.6 1971.6 354.6 40.3 3271.7 791.1 584.6 1525.4 1980.9 13.2 51.6 33.499.9Yadkin Co 38.6 1.2 7.0 3.5 2.5 0.0 123.2 179.7 3.5 16.4 15.8 0.2 1276.6 215.8 30.6 2104.6 545.5 1635.1 897.5 1359.4 7.9 32.1 21.4 55.0Yancey Co 15.6 3.0 5.3 0.2 0.1 0.0 274.7 351.0 4.4 18.4 17.0 0.1 964.3 151.7 31.0 1054.7 376.1 70.6 256.4 294.0 2.0 7.7 4.9 15.8Table 3. 2018 BaseG2 Annual Emission Summary for North Carolina Counties (tons)Point Non-road Area MobileCountyVOC NOx SO2 PM-10 PM-2.5 NH3 VOC NOx SO2 PM-10 PM-2.5 NH3 VOC NOx SO2 PM-10 PM-2.5 NH3 VOC NOx SO2 PM-10 PM-2.5 NH3Alamance Co 430.2 176.1 30.0 56.6 42.7 6.9 615.2 498.3 1.5 47.5 44.7 1.2 2878.4 740.1 87.4 3925.0 1023.6 632.5 1732.9 1633.1 24.0 72.4 35.4229.4Alexander Co 394.6 7.2 4.4 42.1 27.0 0.0 186.7 90.4 0.3 11.7 11.0 0.3 1332.4 203.2 27.2 1605.5 422.6 2282.6 299.0 236.6 3.2 9.7 4.7 31.7Alleghany Co 6.2 0.2 0.3 0.7 0.2 0.0 47.5 39.9 0.1 4.0 3.8 0.1 531.2 102.8 14.4 1044.6 294.0 338.9 102.2 78.8 1.1 3.2 1.5 10.7Anson Co 78.1 161.7 160.5 76.4 68.9 28.0 93.0 354.2 0.7 11.8 10.9 0.1 692.7 127.8 22.7 1378.2 378.8 3069.7 366.6 322.3 4.1 12.3 6.0 38.8Ashe Co 4.2 16.8 30.9 22.0 14.2 0.0 132.7 74.1 0.2 8.5 8.1 0.2 1157.4 229.9 34.2 1841.8 587.4 235.0 339.6 256.9 3.6 10.6 5.1 35.3Avery Co 35.8 6.8 14.9 1.9 1.2 0.0 229.9 75.5 0.2 12.6 11.8 0.2 693.0 187.9 46.7 1107.0 345.8 98.8 203.8 173.7 2.3 6.8 3.3 21.9Beaufort Co 116.5 815.6 6294.1 874.6 532.5 704.7 1053.2 650.1 3.8 44.5 41.7 0.9 1581.7 314.8 34.2 3009.7 832.9 1204.0 423.6 338.1 4.6 13.66.6 45.1Bertie Co 245.7 77.6 219.8 29.6 19.9 7.8 254.9 157.0 1.8 12.3 11.7 0.3 1021.8 148.4 25.3 1971.2 514.7 2030.9 303.2 257.8 3.4 10.1 4.9 32.5Bladen Co 307.0 895.9 2507.7 92.9 69.5 28.1 246.6 267.5 1.2 16.6 15.6 0.3 1308.2 241.8 45.3 2960.6 905.8 9078.4 483.8 380.4 5.3 15.7 7.651.8Brunswick Co 1923.9 2899.3 6248.9 438.8 332.4 61.4 828.1 771.7 38.5 56.2 52.7 1.0 1897.4 460.6 59.6 2898.8 937.5 1099.5 1317.8 1127.3 18.4 55.1 26.8 176.9Buncombe Co 511.5 1105.8 1074.9 679.6 358.2 31.9 1352.4 862.6 5.5 85.7 80.9 1.7 5054.0 1525.2 248.6 7128.0 2065.4 336.6 2146.8 2149.7 30.6 92.8 45.6 288.5Burke Co 902.9 139.8 325.1 308.0 289.1 1.6 250.4 266.1 0.8 17.8 16.8 0.6 2176.5 455.5 78.5 3128.7 888.8 474.0 1137.6 1240.3 16.6 51.2 25.6 150.0Cabarrus Co 880.6 887.5 2036.3 89.1 57.0 11.5 544.5 882.3 1.9 56.0 52.7 1.2 2852.1 646.3 66.5 4719.2 1260.8 592.3 2637.5 1786.6 33.2 97.1 46.8 323.1Caldwell Co 4217.1 453.6 38.5 228.4 159.3 0.1 331.1 175.9 0.7 19.6 18.5 0.7 2233.6 443.8 63.5 3110.4 992.2 362.8 826.3 636.6 11.0 32.7 15.8107.4Camden Co 0.0 0.0 0.0 0.0 0.0 0.0 341.6 148.9 1.7 11.3 10.7 0.3 264.3 51.5 8.3 1655.6 399.3 193.8 132.2 112.6 1.5 4.4 2.1 14.4Carteret Co 126.4 143.0 312.7 138.3 89.1 32.2 3487.2 2469.4 230.4 143.4 132.8 1.7 2060.0 699.8 131.5 3856.8 1859.2 209.6 527.4 457.6 7.5 22.5 11.0 72.4Caswell Co 0.0 0.0 0.0 0.0 0.0 0.0 56.9 38.4 0.1 4.1 3.9 0.1 982.2 156.2 22.4 1642.2 451.2 203.9 272.3 227.6 3.0 9.0 4.3 29.0Catawba Co 3793.3 12475.9 5442.8 3708.2 3133.3 9.1 661.7 726.6 2.3 49.4 46.7 1.8 4392.9 905.7 102.6 5282.9 1393.9 551.6 2346.1 2011.1 31.4 94.0 45.8 301.6Chatham Co 703.1 1916.1 606.9 923.7 530.6 0.9 299.2 267.4 0.7 24.1 22.9 0.6 1689.3 321.6 48.7 2838.1 867.5 3105.8 1025.7 838.5 14.0 42.2 20.6 134.1Cherokee Co 0.0 0.0 0.0 0.0 0.0 0.0 227.5 71.1 0.2 9.6 9.0 0.2 1145.0 270.5 44.9 1622.2 628.1 180.6 339.0 296.9 3.8 11.5 5.6 36.7Chowan Co 87.4 133.2 279.1 132.8 98.6 32.2 329.8 127.4 1.7 9.8 9.2 0.2 455.9 89.9 12.3 1088.7 264.9 674.5 140.8 116.0 1.5 4.5 2.2 15.2Clay Co 0.0 0.0 0.0 0.7 0.1 0.0 165.9 36.1 0.1 6.4 6.0 0.1 368.6 87.0 11.4 754.4 227.5 31.5 126.8 103.7 1.4 4.2 2.0 13.8Cleveland Co 898.3 1218.2 1246.5 2082.9 1953.7 18.2 308.1 358.7 1.0 23.5 22.2 0.7 2262.6 551.1 96.4 3678.5 901.3 1231.3 1409.9 997.8 18.1 53.6 26.0 173.5Columbus Co 2849.3 2955.5 3299.0 1860.0 1587.6 150.0 406.9 302.6 2.2 25.2 23.7 0.5 1949.7 397.6 65.0 3007.5 873.2 3123.6 910.0 783.7 10.2 30.6 14.9 98.7Craven Co 3028.7 2198.6 1691.7 854.3 618.6 77.1 598.1 324.2 3.0 27.6 26.1 0.7 2276.3 562.0 85.8 3682.0 1316.2 1295.7 1364.7 1034.3 17.8 52.725.4 174.2Cumberland Co 1534.1 626.7 1353.3 261.4 142.5 4.0 906.9 983.5 2.3 70.4 66.1 1.5 5023.0 939.8 121.2 6878.0 1762.1 1661.7 3657.5 3168.8 49.1 147.4 71.8 470.1Currituck Co 0.0 0.0 0.0 8.1 3.3 0.0 1202.8 389.7 1.0 35.3 33.2 0.8 627.6 156.6 24.6 1612.8 465.9 236.8 647.5 555.4 7.6 22.6 11.0 73.1Dare Co 74.5 1778.6 2054.1 3458.6 3291.2 36.1 5018.4 1176.8 9.9 96.7 90.0 2.3 1113.3 438.9 72.3 2631.4 1034.4 44.3 671.4 557.3 7.5 22.5 10.9 73.4Davidson Co 3013.9 1576.0 496.7 491.4 422.6 8.5 505.3 844.6 2.1 41.7 39.1 1.1 3710.1 770.9 109.7 5171.3 1331.8 660.9 1973.7 1858.1 27.7 83.841.1 261.3Davie Co 261.2 35.1 16.0 69.4 58.8 1.2 304.2 135.3 0.4 17.1 16.1 0.4 1324.3 210.1 28.8 1869.2 503.2 494.1 550.8 712.5 7.2 22.9 11.7 61.0Duplin Co 59.2 1375.8 3356.6 1945.6 1818.0 19.1 118.1 208.9 0.4 16.5 15.8 0.4 1632.4 301.4 39.9 4560.7 1069.4 25311.5 863.2 890.8 10.1 31.315.6 91.8Durham Co 373.6 409.0 610.4 31.9 24.8 0.6 932.1 971.8 2.5 91.4 87.1 2.6 3874.3 1242.0 130.5 5790.9 1563.7 157.8 2093.9 1827.4 43.3 125.3 59.1 416.1Edgecombe Co 455.2 1988.8 332.3 238.1 223.4 5.5 164.9 490.2 1.1 22.3 21.0 0.5 1691.4 321.6 53.8 3535.3 870.2 2005.1 743.6 594.1 10.1 30.2 14.6 99.4Forsyth Co 2671.3 1463.7 3347.9 350.8 187.8 25.1 1006.6 854.9 2.6 79.2 75.1 2.2 5538.0 1787.6 258.8 8714.9 2273.4 328.4 3389.5 2647.4 53.0 154.2 73.1 506.9Table 3. 2018 BaseG2 Annual Emission Summary for North Carolina Counties (tons)Point Non-road Area MobileCountyVOC NOx SO2 PM-10 PM-2.5 NH3 VOC NOx SO2 PM-10 PM-2.5 NH3 VOC NOx SO2 PM-10 PM-2.5 NH3 VOC NOx SO2 PM-10 PM-2.5 NH3Franklin Co 605.8 32.3 8.5 13.3 8.1 0.0 165.2 132.0 0.3 13.6 12.9 0.3 1523.1 310.2 39.6 2545.7 704.2 634.3 789.9 651.4 11.0 33.0 16.1 106.6Gaston Co 1301.5 5574.2 14732.2 3898.5 3374.5 101.3 612.1 754.1 1.9 47.6 44.8 1.2 4191.1 932.8 102.7 4888.5 1218.1 345.2 2017.7 1431.9 38.1108.1 50.5 364.3Gates Co 0.0 0.0 0.0 0.5 0.2 0.0 58.6 70.4 1.5 6.2 5.9 0.1 434.2 75.1 11.8 1184.3 303.4 674.3 124.6 111.0 1.4 4.2 2.1 13.5Graham Co 504.5 25.0 25.8 19.8 13.9 0.0 70.1 21.6 0.1 2.4 2.2 0.1 422.7 109.4 21.1 862.1 362.5 29.2 68.3 52.7 0.7 2.1 1.0 7.2Granville Co 792.1 26.7 2.0 70.5 66.0 29.1 195.5 214.6 0.6 21.2 20.2 0.6 1763.1 301.2 39.8 2621.7 762.6 189.0 512.3 621.4 11.9 35.3 17.1 104.5Greene Co 0.1 2.4 10.4 0.7 0.2 0.0 54.6 121.6 1.6 9.0 8.6 0.2 840.4 112.5 14.6 1774.7 408.6 4718.7 268.2 216.1 2.9 8.7 4.2 28.7Guilford Co 4996.0 242.8 265.3 256.3 167.3 12.2 2183.2 2236.6 19.4 218.6 208.2 4.8 8496.6 2736.9 260.7 10821.7 2884.8 654.6 4497.7 3512.6 71.9208.8 98.9 691.8Halifax Co 628.8 5453.5 4753.6 4056.4 3777.1 50.7 262.1 472.9 1.1 26.0 24.4 0.4 1818.6 322.5 41.1 3450.3 845.4 1220.9 665.1 788.1 8.2 25.813.0 71.1Harnett Co 0.0 3.9 0.0 18.8 15.6 0.0 332.5 614.0 1.3 31.9 29.7 0.5 2362.9 529.4 72.2 4073.4 1103.0 2733.3 798.0 765.5 11.4 34.6 17.1 106.2Haywood Co 1743.9 3034.0 10149.5 1019.6 995.0 90.7 520.3 163.1 0.5 24.8 23.3 0.5 1819.1 428.5 74.2 2765.0 871.1 336.3 759.1 1020.2 12.1 38.419.5 103.5Henderson Co 761.2 89.7 1.9 41.5 32.5 0.6 1158.1 317.2 1.1 51.0 47.7 1.0 2440.8 581.9 71.2 3858.4 1116.3 273.7 882.4 899.0 12.8 39.1 19.3118.1Hertford Co 240.9 163.1 151.4 161.1 139.3 0.0 158.0 92.6 0.2 9.9 9.4 0.2 735.6 163.4 39.0 1516.9 365.5 1053.7 202.4 160.0 2.2 6.5 3.1 21.4Hoke Co 273.5 63.1 127.3 21.5 21.5 0.0 119.8 90.6 0.2 9.4 9.0 0.2 905.1 208.0 38.0 1948.9 675.4 971.1 420.4 343.3 4.5 13.5 6.6 43.6Hyde Co 0.2 19.1 2.0 5.8 2.1 0.0 3609.2 850.5 5.6 56.2 52.3 1.5 335.5 54.9 7.3 1960.8 452.0 149.0 118.1 93.3 1.3 3.8 1.8 12.7Iredell Co 780.9 1474.8 580.2 141.9 121.9 25.6 548.5 516.5 1.3 43.0 41.0 1.3 3054.4 682.1 119.8 5458.5 1444.4 2289.9 2497.8 2863.5 37.0 115.6 58.5 317.9Jackson Co 44.6 90.0 14.9 47.4 36.9 0.0 276.0 135.0 0.3 17.4 16.4 0.4 1366.4 342.6 47.4 1990.5 769.3 59.4 623.0 588.3 7.4 22.5 11.0 70.4Johnston Co 324.1 54.5 33.4 12.4 12.0 1.7 567.7 1022.2 2.1 58.9 55.3 1.1 3280.9 737.3 88.5 6204.5 1580.7 3153.1 2737.6 3260.4 41.2 129.3 65.4 357.7Jones Co 0.0 0.0 0.0 12.9 4.0 0.0 43.5 77.9 1.5 6.1 5.8 0.1 626.5 147.4 32.5 1488.0 588.1 2538.6 207.2 189.4 2.4 7.2 3.5 23.0Lee Co 337.7 122.3 115.3 142.1 121.4 0.0 172.9 226.3 0.6 18.1 17.3 0.6 1167.1 330.0 36.0 1755.6 471.5 590.4 620.5 495.5 8.4 24.9 12.0 83.0Lenoir Co 480.1 840.4 1250.1 98.1 59.7 21.5 229.3 204.6 1.9 18.0 17.2 0.4 1621.6 298.7 36.5 3613.5 806.9 4003.5 570.1 413.8 7.6 22.3 10.775.2Lincoln Co 991.9 43.1 5.1 80.4 71.8 0.4 270.5 297.5 0.7 19.8 18.6 0.5 1668.6 360.9 94.3 2997.3 795.2 405.2 1001.7 749.8 12.9 38.0 18.4 124.2Mc Dowell Co 697.3 275.9 51.0 270.9 193.4 0.0 288.5 545.6 1.3 23.3 21.5 0.4 1284.2 254.7 46.8 1963.7 572.1 299.4 669.7 847.4 8.7 27.5 14.074.2Macon Co 7.0 0.0 0.0 1.1 0.3 0.0 398.6 107.1 0.4 18.6 17.4 0.4 1295.0 327.8 42.4 1884.4 707.1 82.5 437.9 383.4 5.0 14.9 7.3 47.7Madison Co 0.0 0.0 0.0 0.0 0.0 0.0 126.1 221.8 0.5 9.5 8.8 0.1 934.8 162.0 32.9 1311.2 398.0 116.3 241.9 262.6 2.9 9.1 4.6 26.5Martin Co 1343.0 4726.2 3955.9 747.8 467.4 120.0 178.0 136.6 1.7 14.2 13.4 0.3 1077.3 194.3 26.3 1991.4 473.2 694.3 404.2 342.6 4.4 13.3 6.5 43.0Mecklenburg Co 2332.0 831.7 830.0 655.3 475.3 95.0 5192.2 4885.0 112.4 684.0 656.8 9.4 11735.2 4152.9 390.8 17224.5 3584.1 488.3 8377.3 5600.5 151.3 426.2 198.1 1470.4Mitchell Co 509.2 77.6 28.2 59.9 53.8 0.0 230.6 474.0 1.0 17.1 15.7 0.2 667.2 138.9 22.9 944.0 271.6 37.8 161.7 131.7 1.8 5.2 2.5 17.2Montgomery Co 726.6 139.8 57.7 216.8 162.7 0.1 175.3 98.1 0.3 9.2 8.7 0.3 1130.2 233.6 46.0 1721.0 638.1 1829.4 475.9 419.0 5.3 16.0 7.850.4Moore Co 9.6 13.2 15.0 4.7 3.3 0.0 342.6 258.8 0.7 25.5 24.0 0.6 2034.4 541.5 62.3 2667.3 838.5 2852.3 811.3 599.9 10.6 31.2 15.0 104.1Nash Co 342.6 218.6 122.0 25.3 18.8 0.8 267.7 415.0 0.9 26.2 24.8 0.6 2571.1 618.4 75.2 4186.7 1106.7 2297.0 1487.4 1625.7 22.2 68.5 34.1 201.8New Hanover Co 2737.2 3543.1 12784.0 1503.5 756.6 19.2 1073.3 2761.3 290.4 166.1 155.0 1.8 2671.2 750.4 78.6 3191.5 883.9 138.0 1368.3 1027.618.4 54.4 26.1 183.1Northampton Co 225.0 29.2 11.3 78.0 24.9 1.8 141.2 390.2 0.8 16.4 15.3 0.2 825.7 162.4 27.8 3146.5 755.5 1845.2 352.8 394.2 4.3 13.5 6.838.5Onslow Co 55.4 28.2 43.1 5.0 4.4 0.0 890.3 338.5 2.3 37.1 34.9 0.8 2840.2 581.8 84.8 3526.3 1068.7 2813.4 1473.3 1066.6 18.9 55.9 26.9 186.6Orange Co 96.1 549.2 153.2 23.6 16.1 0.0 693.7 480.4 1.1 48.7 46.0 1.0 2594.5 719.9 130.4 3908.3 1077.9 430.6 1218.9 1459.6 27.6 82.3 39.8240.9Table 3. 2018 BaseG2 Annual Emission Summary for North Carolina Counties (tons)Point Non-road Area MobileCountyVOC NOx SO2 PM-10 PM-2.5 NH3 VOC NOx SO2 PM-10 PM-2.5 NH3 VOC NOx SO2 PM-10 PM-2.5 NH3 VOC NOx SO2 PM-10 PM-2.5 NH3Pamlico Co 0.0 0.0 0.0 0.0 0.0 0.0 1344.8 309.1 2.9 26.8 25.0 0.6 429.9 86.4 11.7 1063.1 267.7 110.2 148.9 110.4 1.6 4.6 2.2 15.6Pasquotank Co 4.7 13.4 11.7 28.3 8.8 0.0 506.3 246.3 2.7 28.8 27.6 0.5 798.9 221.4 28.5 3143.4 725.1 153.2 339.4 272.4 3.7 10.8 5.2 36.2Pender Co 0.0 0.0 0.0 0.3 0.1 0.0 250.1 160.7 3.1 16.5 15.6 0.4 1382.3 342.3 58.7 2291.4 835.4 3402.2 775.6 848.9 9.5 29.5 14.7 85.2Perquimans Co 0.0 0.0 0.0 0.6 0.1 0.0 433.7 187.6 1.8 13.9 13.2 0.3 453.2 81.5 11.6 2065.4 485.2 652.1 191.2 171.8 2.2 6.5 3.2 20.6Person Co 376.2 6581.8 11842.0 4367.4 2128.5 30.3 170.5 124.9 0.3 11.8 11.2 0.3 1277.9 231.4 44.9 1669.1 504.8 229.8 367.0 284.8 3.9 11.75.6 39.1Pitt Co 791.3 288.9 61.5 68.3 52.8 4.8 423.4 627.0 6.0 50.6 48.3 1.1 3294.0 676.7 76.8 4428.3 1153.9 2353.8 1096.9 819.3 14.8 43.7 21.0 146.4Polk Co 0.3 3.2 1.9 0.7 0.5 0.0 104.2 69.4 0.2 7.7 7.2 0.1 606.7 152.7 30.3 992.7 282.9 58.5 353.0 450.7 4.6 14.5 7.4 38.9Randolph Co 3121.7 23.6 4.1 197.6 178.2 0.0 455.8 404.9 1.3 33.7 31.8 1.1 4342.5 785.6 102.3 4918.7 1355.4 4487.9 1823.3 1681.2 25.4 76.6 37.5 242.3Richmond Co 12.0 80.0 58.7 28.4 17.2 0.0 187.3 391.2 0.9 18.8 17.5 0.3 1095.9 271.3 41.5 1677.3 494.0 2211.7 681.2 573.5 7.5 22.2 10.8 72.4Robeson Co 165.8 2479.9 6782.1 261.9 115.9 23.0 286.5 765.7 1.3 37.7 35.6 0.8 3595.6 708.0 113.2 8940.0 2443.3 5790.9 1407.2 1504.6 20.5 63.1 31.5 185.2Rockingham Co 872.6 3741.8 7469.5 533.9 381.4 35.6 348.7 451.2 1.1 25.2 23.6 0.6 2587.0 544.3 75.4 3565.0 986.6 332.7 792.8 626.6 10.8 32.215.5 106.1Rowan Co 3112.0 3232.7 11106.8 905.5 728.1 109.0 520.6 730.2 1.7 37.5 35.1 0.9 2785.2 600.7 124.9 4636.4 1145.8 563.8 1963.7 1690.3 26.5 78.4 38.1 254.4Rutherford Co 886.3 3924.2 5923.5 6389.0 5038.4 0.9 308.3 355.5 0.9 21.5 20.1 0.5 1683.9 375.2 53.4 2736.3 746.8 414.3 608.5 460.8 7.9 23.6 11.4 77.3Sampson Co 25.2 30.9 21.3 87.2 24.6 0.0 142.1 235.0 0.4 19.3 18.6 0.5 1952.9 373.2 55.2 7459.3 1680.8 22740.9 853.6 813.5 9.8 29.8 14.7 90.8Scotland Co 1156.9 2080.2 325.0 546.9 525.9 4.2 87.6 273.9 0.6 10.8 10.1 0.3 978.0 250.3 49.3 2078.5 760.2 758.9 477.8 390.6 5.2 15.4 7.550.8Stanly Co 407.3 632.0 2000.1 295.2 210.6 0.0 378.0 263.8 0.7 22.5 21.2 0.5 1528.1 335.8 45.9 2697.8 733.3 1796.9 552.9 369.4 7.0 20.3 9.768.5Stokes Co 200.1 5234.9 5758.4 3987.0 3447.6 6.0 209.5 173.8 0.4 12.3 11.5 0.2 1622.6 264.8 50.7 2250.4 648.4 358.3 378.0 291.1 5.0 14.9 7.2 48.9Surry Co 1442.4 274.2 341.2 215.6 137.9 0.0 359.7 193.4 0.7 24.8 23.4 0.6 2121.5 471.7 60.7 3197.6 813.8 2231.9 803.1 898.2 11.9 36.9 18.5106.3Swain Co 0.0 0.0 0.0 0.0 0.0 0.0 687.1 71.3 0.4 21.8 20.3 0.3 704.7 142.4 18.9 881.7 288.2 226.4 219.6 179.7 2.4 7.1 3.4 23.0Transylvania Co 150.5 1035.5 1716.1 59.4 56.0 0.8 874.7 118.8 0.5 31.3 29.1 0.5 1007.5 205.2 23.0 1475.7 448.3 118.9 354.4 288.7 4.0 11.85.7 39.2Tyrrell Co 0.0 0.0 0.0 0.0 0.0 0.0 1027.8 298.8 3.9 19.7 18.5 0.5 256.8 36.1 5.6 2821.0 642.2 281.1 86.4 78.5 1.0 2.9 1.4 9.2Union Co 473.2 88.0 181.0 105.9 48.0 0.0 906.5 1018.3 2.4 92.4 87.4 2.0 3125.6 722.1 74.6 5908.9 1663.3 7654.1 1900.6 1195.6 22.8 66.0 31.5226.4Vance Co 300.6 1087.8 352.5 188.1 173.8 0.1 314.4 120.1 0.4 15.5 14.5 0.3 1231.8 279.6 38.1 1900.2 532.1 91.5 610.2 654.1 7.3 22.6 11.3 67.1Wake Co 1386.0 254.1 85.5 309.5 88.0 3.9 3808.8 3638.3 84.0 523.3 502.6 7.0 12372.6 4089.4 383.1 19721.3 5504.9 530.6 6638.6 5546.5 134.7 389.0 183.2 1302.9Warren Co 0.7 2.1 0.2 2.6 1.7 0.0 119.4 58.8 0.1 6.2 5.9 0.1 802.6 148.0 23.3 1297.6 389.9 715.6 288.0 331.8 3.5 11.0 5.5 30.4Washington Co 0.0 0.0 0.0 13.7 5.4 0.0 407.7 221.8 1.9 16.1 15.3 0.4 701.6 184.7 32.2 1906.0 749.2 628.2 166.4 141.4 1.9 5.6 2.7 18.1Watauga Co 29.5 51.7 47.4 19.4 14.7 0.0 557.5 201.7 0.6 31.2 29.4 0.6 1399.3 400.4 86.6 2068.1 645.5 261.6 414.5 343.8 4.5 13.4 6.5 43.3Wayne Co 970.7 2553.0 12288.3 911.3 548.7 27.9 342.8 333.0 0.8 28.9 27.5 0.8 2620.4 646.5 79.3 6113.0 1505.8 9191.6 1193.6 851.3 15.3 45.121.6 152.4Wilkes Co 1473.6 356.9 79.8 156.7 125.4 4.1 266.7 136.2 0.5 16.8 15.9 0.4 2007.0 413.2 89.3 3062.0 856.9 6011.3 646.2 519.5 8.8 26.4 12.885.6Wilson Co 927.8 373.1 901.4 220.7 181.4 6.4 345.7 636.1 1.4 34.7 32.6 0.7 2014.3 388.0 43.3 3406.7 803.6 593.0 852.5 823.4 12.1 36.9 18.2 113.3Yadkin Co 40.0 1.2 7.0 3.5 2.5 0.0 113.7 105.3 0.2 10.2 9.8 0.3 1196.5 232.3 32.4 2219.8 541.4 1824.0 590.3 643.3 7.1 22.1 11.1 63.6Yancey Co 20.1 3.4 5.3 0.2 0.1 0.0 223.0 287.1 0.7 14.7 13.5 0.2 828.2 158.4 31.3 1130.1 360.2 70.7 154.0 137.6 1.7 5.2 2.6 16.7Table 4. Typical 2002 BaseG2 Annual Emission Summary for VISTAS States (tons)Point Non-road Area MobileStateVOC NOx SO2 PM10 PM2.5 NH3 VOC NOxSO2 PM10 PM2.5 NH3 VOC NOx SO2 PM10 PM2.5 NH3 VOC NOx SO2 PM10 PM2.5 NH3AL 49332 244348 544309 32886 23291 2200 60487 65366 7584 4787 4787 33 209200 34900 54812 444259 101442 60275 127295 158212 6900 3903 2799 5588FL 40995 302833 518721 57244 46147 1657 272072 180627 20614 18281 18281 134 455828 48664 44619 541816 147633 40603 527209 465640 20915 11275 7868 18114GA 34401 196731 568726 32740 22333 3696 85965 97961 9005 8618 8618 60 333045 49987 60370 757656 159438 83066 283421 307732 12184 7246 516810546KY 46321 237209 518086 21327 14174 1000 44805 104571 14043 6425 6425 31 98713 40966 41941 240226 51763 51246 103503 156417 6308 3723 2697 5055MS 43852 104661 103389 21105 11044 1359 41081 88787 11315 5010 5010 23 145433 7528 871 358070 64080 58899 87672 111914 4614 2859 2112 3585NC 61484 196731 522093 36539 26953 1233 94480 84284 7693 7348 7348 65 250044 41517 5815 300838 83520 162183 263766 327329 12420 6579 4623 9702SC 38928 130394 259917 35542 27399 1553 55016 50249 4866 4152 4152 33 175665 24602 14087 287161 63802 29074 116163 140489 5972 3452 2501 4694TN 78230 221638 413735 49174 39511 1746 66450 96827 10441 6819 6819 43 151436 20063 29956 220789 50833 34368 179807 238577 9226 5371 3949 6625VA 43906 147301 305107 17212 12771 3231 74866 63219 8663 8728 8728 48 173901 52396 105989 255738 61350 44064 159790 222374 8294 4549 3102 7852WV 15775 277589 570154 22076 15523 453 18566 33239 2112 1850 1850 9 62627 13631 11683 118622 24289 9975 42174 58999 2464 1381 995 1908Table 5. 2009 BaseG2 Annual Emission Summary for VISTAS States (tons)Point Non-road Area MobileStateVOC NOx SO2 PM10 PM2.5 NH3 VOC NOxSO2 PM10 PM2.5 NH3 VOC NOx SO2 PM10 PM2.5 NH3 VOC NOx SO2 PM10 PM2.5 NH3AL 49117 151714 479298 32390 23151 2491 50249 56862 3471 4027 3776 36 170956 35831 50910 465666 105211 66318 76990 101831 810 3171 2032 6364FL 38790 132185 251566 48879 39856 3175 209543 163794 8967 15613 14866 148 471699 47979 40827 601700 153344 41773 340947 315840 2612 9911 617321781GA 35758 148809 471432 40888 29813 4649 67686 85733 2725 7521 7175 68 306337 51925 60604 840245 169011 91439 195125 209349 1585 6072 384012687KY 49155 129779 326611 23637 15965 1160 38558 94752 9180 5544 5203 34 97379 43548 43222 248844 52553 53115 73942 101182 759 2976 1920 5796MS 38151 92409 102143 24202 13976 1002 36197 80567 7191 4270 3985 25 139636 8048 982 373154 67173 63985 52107 70743 537 2275 1508 4035NC 62161 101236 284802 36007 26360 1730 74056 70997 1892 6055 5760 72 200873 45382 6281 315004 90729 170734 168676 201609 1503 5572 349311825SC 36325 86934 172933 32765 25432 1921 43061 43235 1701 3471 3294 36 162152 25259 14411 307452 67567 31595 72603 92499 721 2862 1855 5523TN 67470 124274 326067 49753 40171 1991 55358 86641 5651 5877 5557 48 151980 20717 30614 234285 52357 35222 115181 151912 1076 4206 27517782VA 44504 117265 288213 18556 14055 3743 57009 54993 1707 7510 7136 53 146587 53596 106083 270648 61875 46798 96770 134232 1079 3747 22419086WV 15171 124359 333462 22747 15709 671 18069 30133 359 1640 1528 11 57472 14384 12300 118365 23903 10637 24843 35635 279 1068 684 2148Table 6. 2018 BaseG2 Annual Emission Summary for VISTAS States (tons)Point Non-road Area MobileStateVOC NOx SO2 PM10 PM2.5 NH3 VOC NOxSO2 PM10 PM2.5 NH3 VOC NOx SO2 PM10 PM2.5 NH3 VOC NOx SO2 PM10 PM2.5 NH3AL 55911 141178 249006 37309 26978 3497 40407 43799 2818 3041 2835 42 181116 36945 52950 497924 108892 73969 49175 47298 720 2410 1192 7298FL 44715 110243 214247 55811 45761 4494 183452 127885 7536 12497 11868 171 541502 50499 42445 676986 161210 43590 222303 150180 2533 8268 403826163GA 41290 125083 134394 45360 33642 6473 56761 64579 1709 6015 5730 79 353224 55518 62636 944009 180697 102112 109763 102179 1457 4844 2380 14873KY 57205 100774 251907 26347 17806 1337 30920 79392 8592 4556 4256 40 106827 45806 44322 262719 53955 55321 47066 52263 763 2580 1272 7811MS 46393 71988 54364 29866 17592 1309 28842 68252 6638 3452 3203 29 154882 8322 986 392507 68891 70194 31616 30619 440 1624 819 4566NC 71247 94276 148972 48354 37789 2073 61327 49046 905 4298 4069 83 203132 49514 6674 338872 93406 181333 101099 87791 1481 4392 2123 14065SC 44516 94089 140779 43249 35540 2357 36131 31758 1198 2617 2474 41 177272 26491 14817 333404 70274 34536 46301 43490 643 2184 1087 6473TN 84459 93443 189572 57258 46214 2356 45084 70226 5207 4672 4403 55 177683 21810 31993 254244 54784 36239 67324 69385 948 3092 1544 9021VA 54107 116560 178300 28617 23351 4157 49052 40393 507 6208 5891 61 150174 57137 109479 293512 64058 50335 61964 63342 1043 3212 1543 10624WV 17947 94536 168125 28079 20159 590 14086 25710 56 1292 1198 13 62931 15773 12865 124825 24729 11516 16121 17247 253 819 405 2497Annual NOx Emissions by Source Sector0200,000400,000600,000800,0001,000,0001,200,000 A L F L G A K Y M S N C S C T N V A W V

Tons per yearFIRESAREANONROADONROADNONEGUEGU2002 Actual EGU and Fires2002 Typical EGU and Fires20092018Annual VOC Emissions by Source Sector0200,000400,000600,000800,0001,000,0001,200,0001,400,000 A L F L G A K Y M S N C S C T N V A W V

Tons per yearFIRESAREANONROADONROADNONEGUEGU2002 Actual EGU and Fires2002 Typical EGU and Fires20092018Annual SO2Emissions by Source Sector0100,000200,000300,000400,000500,000600,000700,000 A L F L G A K Y M S N C S C T N V A W V

Tons per yearFIRESAREANONROADONROADNONEGUEGU2002 Actual EGU and Fires2002 Typical EGU and Fires20092018Annual PM10Emissions by Source Sector0200,000400,000600,000800,0001,000,0001,200,000 A L F L G A K Y M S N C S C T N V A W V

Tons per yearFIRESAREANONROADONROADNONEGUEGU2002 Actual EGU and Fires2002 Typical EGU and Fires20092018Annual PM2.5Emissions by Source Sector050,000100,000150,000200,000250,000 A L F L G A K Y M S N C S C T N V A W V

Tons per yearFIRESAREANONROADONROADNONEGUEGU2002 Actual EGU and Fires2002 Typical EGU and Fires20092018Annual NH3Emissions by Source Sector050,000100,000150,000200,000250,000 A L F L G A K Y M S N C S C T N V A W V

Tons per yearFIRESAREANONROADONROADNONEGUEGU2002 Actual EGU and Fires2002 Typical EGU and Fires20092018

# Appendix D.4 Emissions Modeling Documentation

# Appendix D.4a Emissions Modeling Documentation

# Background
The Sparse Matrix Operator Kernel Emissions (SMOKE) modeling system is an emissions modeling system that generates hourly gridded speciated emission inputs of mobile, nonroad mobile, area, point, fire and biogenic emission sources for photochemical grid models. SMOKE is the fastest emissions processing tool currently available to the air quality modeling community. The sparse matrix approach utilized throughout SMOKE permits both rapid and flexible processing of emissions data. The processing is rapid because SMOKE utilizes a series of matrix calculations instead of less efficient algorithms used in previous systems. The processing is flexible because the processing steps of temporal projection, controls, chemical speciation, temporal allocation, and spatial allocation have been separated into independent operations wherever possible. The results from these steps are merged together at a final stage of processing. Each of these emissions processing steps are detailed below. 

# Temporal Allocation
VISTAS 2002, 2009 and 2018 annual emissions modeling was configured to generate point, area, nonroad mobile, on-road mobile, and biogenic source emissions. In addition, certain subcategories, such as fires and EGUs were maintained in separate source category files in order to allow maximum flexibility in producing alternate strategies. With the exception of biogenic and on-road mobile source emissions that are generated using the BEIS and MOBILE6 modules in SMOKE, pre-computed annual emissions were processed using the month, day, and hour specific temporal profiles of the SMOKE model. Point and biogenic sources were modeled for each day of the annual period while area and nonroad sources were modeled as a block of Thursday, Friday, Saturday, Sunday, Monday, one per month (total of 60 days modeled).
VISTAS based its temporal profiles and source category cross-reference files on the USEPA CAIR/CAMR/CAVR modeling platform with files located on USEPA’s CAIR file transfer website ( ftp://www.airmodelingftp.com/ ). Modifications were made to reflect State specific profiles or updated state of knowledge application of these profiles. Some of these changes included the reallocation of North Carolina NONROAD generated emission categories to a regional set of temporal profiles more consistent with the operation of these source types in the State. Additionally, EGU CEM-based temporal profiles and onroad emissions modeling were prepared in manners deviating from USEPA’s original CAIR platform.
New temporal profiles used by VISTAS during modeling of the 2002, 2009 and 2018 EGU emissions took the place of USEPA provi ded default temporal profiles that are generally accepted as not accurately depicting temporal distribution of emissions from EGUs in the U.S. (see Attachment 1 by Stella et. al.). VISTAS EGU temporal profiles were developed using hourly CEM data as reported to USEPA’s Clean Air Market’s Division (CAMD) for the Acid Rain Program.

# The work conducted in this process had the main objective of developing temporal profiles for VISTAS EGUs necessary to apply in the generation of SMOKE PTHOUR formatted emissions. Additionally, State-level monthly, day-of-week, and diurnal profiles were developed for application to non-CEM matched units in the VISTAS emissions inventory. These temporal distri butions represent a significant improvement over the USEPA defaults.
On-road mobile modeling in SMOKE was done for selected weeks (seven days) of each month - using these days as a “representative week” of the entire month. This selection allows for the representation of day-of-the-w eek variability in the on-road motor vehicles, and models a representation of the meteorological variability in each month. The modeled weeks were selected from mid-month, avoiding inclusion of major holidays. Holidays were modeled as the Sunday of the representative week, while the day after a holiday was modeled as a Monday. VISTAS executed sensitivity tests to examine this “representative week” methodology versus an everyday on-road mobile modeling method. VISTAS determined that the use of representative week on-road mobile emissions produced ozone and particulate matter concentrations (and thus regional haze) that were nearly indistinguishable from the “everyday” mobile method. VISTAS determined that the difference in the modeled air quality - resulting from the on-road mobile modeling methods - was insignificant. For more information on this study see Attachment 2 by Abraczinskas et. al.
On-road mobile emissions are represented by the following weeks per month: January 15-21 February 12-18 March 12-18 April16-22 May 14-20 June 11-17 July 16-22 August 13-19 September 17-23 October 15-21 November 12-18 December 17-23


# Speciation
Speciation is the process of disaggregating i nventory pollutants into individual chemical species components or groups of species. The need for speciation is determined by the inventory purpose. Inventory applications that require detailed speciation include photochemical modeling, air toxics inventories, chemical mass balance modeling, and visibility modeling.
Depending on the purpose of a particular emi ssions inventory, the inventory may include TOG, NOx, sulfur oxides (SOx), CO, total suspended particulate matter (TSP),

# particulate matter less than 10 micrometers in aerodynamic diameter (PM10), or ammonia (NH3). However, modeling inventories may require these emissions to be expressed in terms of other pollutants. Additionally, for some models, NOx emissions may need to be specified as NO and NO2. Also, PM may need to be separated into various fractions, such as PM10 and PM less than 2.5 micrometers in aerodynamic diameter (PM2.5).
SMOKE was configured to speciate the emissions estimates according to the requirements of the Carbon Bond Mechanism version four (CBM-IV, CB-IV or CB4). The SMOKE model reformats the emissions estimates for use in CMAQ modeling based on source category code (SCC) and speciation profile cross-reference files. The speciation profiles and source category cross-references use in VISTAS modeling are based on USEPA’s CAIR/CAVR/CAMR modeling platform with files located on USEPA’s CAIR file transfer website ( ftp://www.airmodelingftp.com/ ). Minor modifications were made to reflect State specific profiles or updated state of knowledge application of these profiles. One major change made in the VISTAS modeling was the modification of coal combustion cross-refe rence from speciation profile “NCOAL” to profile “22001.”


# Spatial Allocation
Because air quality modeling strives to replicate the actual physical and chemical processes that occur in an inventory domain, it is important that the physical location of emissions be determined as accurately as possible. In an ideal situation, the physical location of all emissions would be known exactly. In reality, however, the spatial allocation of emissions in a modeling inventory only approximates the actual location of emissions.
Gridding surrogates are used to spatially allocate emission sources from a coarse geographic area to finer grid cells used for modeling. There can be hundreds of unique source categories in an emissions inventory, which is typically developed for counties, states, or other areas. The exact location of most major emission sources is known and their geographic coordinates are usually contained in the inventory. These usually are referred to as major point sources and include electric utilities and major industrial facilities. However, other emission sources are estimated for the entire county or other area as an aggregate since the exact locations of each source are not included in the modeling inventory. Surrogates are human activities or land use information that are used to represent a more precise location of emission source category groups. A gridded surrogate ratio is the ratio of the amount of a surrogate in a modeling grid cell to the total amount of that surrogate in a county. Grid cell emissions are calculated by multiplying the cell’s gridded surrogate ratio by the county emissions.
These surrogates and their associated SCC cross-references were originally developed by USEPA ( http://www.epa.gov/ttn/chief/emch/spatial/newsurrogate.html ) and converted to the gridded domain definitions of the VISTAS model requirements.

# Development of Gridded Surrogate Files

The general process for creating the SMOKE-ready gridded surrogate files from the ArcGIS shape files is as follows:
1. Overlay the grid on the surrogates. Generate the grid polygons (36/12km) with the specifications of the VISTAS domain and spatially overlay (intersect) the grid onto the surrogate area polygons or points. The resulting geodatabase contains, for each surrogate, the county FIPS code, the grid column and row number, and the amount (area, miles or count) of the county’s portion of the surrogate in that cell.
2. Extract and convert each geodatabase table to a useful dataset. Each table contains the gridded area, miles or count in each county for a specific surrogate. The variables include FIPS code, column number, row number and area, miles or count.
3. Calculate surrogate ratios. Surrogate ratios are calculated for each surrogate using a series of program files. The programs sum the surrogates for each county and calculate each the ratio by dividing the county cell surrogate value by the total county surrogate value. Combination surrogates where both are of the same type (i.e., Heavy and High Tech Industrial are both area) were summed prior to calculating the ratio. Combination surrogates with unlike data (i.e., 3/4 Roadway Miles plus 1/4 Population are line and areadata) were summed after calculating the ratios and then normalized. The surrogate crossreference code was also assigned here.
4. Gap-fill surrogates for counties missing data. There will be many instances where inventory emissions exist for a particular c ounty but there is no data, for that county, for the surrogate assigned. For example, a count y with class 1 locomotive emissions may not have data for the class 1 railroad surrogate. In this case we have selected to incorporate, within the assigned surrogate, a different source of data (a different surrogate) for that particular county. We incorporate secondary surrogates even if there is no emission source that requires it for that particular county. We denote this process as “gap-filling.” All surrogates resulting from the gap-filling process have ratios for all counties.
For each surrogate, we assign a secondary or tertiary surrogate where needed for gap filling. For the class 1 railroad surrogate example mentioned above, we chose total railroads as the secondary surrogate. The secondary or tertiary surrogate chosen would be the same across all counties and apply to all SCCs that use the particular primary surrogate. We pull in and substitute the secondary surrogate for counties where the primary surrogate is missing. Tertiary surrogates will then be assigned to those counties that are still without surrogates.
For identified counties having no values for each surrogate, we assign the data based on the appropriate secondary or tertiary surrogate to these counties. A check to see that surrogate ratios for each county sum to approximately 1.00 is also performed in our surrogate development. Ratios will not always sum exactly to 1.00 due to rounding. However, SMOKE will normalize surrogates greater than 1.00.

# 5. Create SMOKE-formatted spatial surrogate files. The resulting data from the previous steps is then reconfigured into SMOKE-ready format and used in the spatial allocation process. 

# Treatment of Large Fire Plume Rise
Wildfire, agricultural, and prescribed burn emissions were handled separately from the standard area source input files. We used day specific or monthly estimates of fire emissions from VISTAS, which include burn acreage and biomass loading information for the VISTAS states. Depending on the completeness and quality of the data received, VISTAS-specific calculations were made to calculate spatial and temporal distributions of the fire emissions, rather than relying on st andard distribution profiles. We calculated vertical distribution of the fire emissions , based on fire size and biomass involvement. SMOKE v2.1 can model fire plume rise when provided with the following variables:
PTOP – Top of the fire plume profile (meters above ground level) PBOT – Bottom of the fire plume profile (meters above ground level) Lay1 – The percent of the emissions entrained in the first modeling layer
For those fires as having the necessary data elements to site these files with distinct time and space coordinates, these variables were prepared and included in the modeling files used to process this emission source type.
The WRAP Fire Emissions Joint Forum Emissions Inventory Report (see http://www.wrapair.org/forums/fejf/documents/WRAP_2002_PhII_EI_Report_20050722 .pdf) has documented an approach for calculating these plume descriptors. In this method, the fires are assigned to one of 5 size categories, based on the total burn acreage, and the biomass fuel loading. These categories are then used to calculate representative hourly plume profiles. These profiles are then used by SMOKE 2.1 to distribute the vertical emissions for the fires. To successfully model fires as elevated point sources, the data included both the day or days on which the fire occurs, and a spatial identifier of the fire location.


# Quality Assurance
The Quality Assurance (QA) is one of the most important steps in performing an air quality modeling study. Because emissions inventory development is tedious, time consuming and involves complex manipulation of many different types of large data sets, errors are frequently made and, if rigorous QA measures are not in place, these errors may remain undetected.
A number of QA files were prepared and used to check for gross errors in the emissions inputs. Importing the model-ready emissions into PAVE and looking at both the spatial and temporal distribution of the emission provides insight into the quality and accuracy

# of the emissions inputs. Some of the additional steps for checking the emissions are summarized in the bulleted list below.

• Visualizing the model-ready emissions with the scale of the plots set to a very low value, we can determine whether there are areas omitted from the raw inventory or if emissions sources are erroneously located in water cells.

• Spot-check the holiday emissions files to confirm that they are temporally allocated like Sundays.

• Producing pie charts emission summaries th at highlight the contribution of each emissions source component (e.g. nonroad mobile).

• Normalizing the emissions by population for each state will illustrate where the inventories may be deficient and provide a reality check of the inventories.

• Spot check vertical allocation of point sources using PAVE.
State inventory summaries prepared prior to the emissions processing were compared against SMOKE output report totals generated after each major step of the emissions generation process.
For speciation, a comparison of the inventory state totals versus the same state totals with the speciation matrix applied was completed.
For checking the vertical allocation of the emissions, reports by source, hour, and layer for randomly selected states in the domain were created. These reports were created for a representative weekday in each of the episodes for each of these selected states.
The quantitative QA analyses often reveal significant deficiencies in the input data or the model setup. It may become necessary to tailor these procedures to track down the source of each major problem. As such, we will only outline the basic quantitative QA steps that were performed in an attempt to reveal the underlying problems with the inventories or processing.
Following are some of the reports that were generated to review the processed emissions:

• State and county totals from inventory for each source category

o (example provided in Table 1 below for Area sources)

• State and county totals after spatial allocation for each source category

• State and county totals by day after temporal allocation for each source category for representative days

• State and county totals by model species after chemical speciation for each source category

• State and county model-ready totals (after spatial allocation, temporal allocation, and chemical speciation) for each source category and for all source categories combined

• If elevated source selection is chosen by user, the report indicating which sources have been selected as elevated and plume-in-grid will be included.

# • Totals by source category code (SCC) from the inventory for area, mobile, and point sources

• Totals by state and SCC from the inventory for area, mobile, and point sources

• Totals by county and SCC from the inventory for area, mobile, and point sources

• Totals by SCC and spatial surrogates code for area and mobile sources

• Totals by speciation profile code for area, mobile, and point sources

• Totals by speciation profile code and SCC for area, mobile, and point sources

• Totals by monthly temporal profile code for area, mobile, and point sources

• Totals by monthly temporal profile code and SCC for area, mobile, and point

sources
• Totals by weekly temporal profile code for area, mobile, and point sources

• Totals by weekly temporal profile code and SCC for area, mobile, and point

sources
• Totals by diurnal temporal profile code for area, mobile, and point sources

• Totals by diurnal temporal profile code and SCC for area, mobile, and point

sources

• 

# PAVE plots of gridded inventory pollutants for all pollutants for area, mobile, and point sources

# Table 1. Example of a State totals report for Area Sources

Stationary area Processed as Area sources Base inventory year 2018 No gridding matrix applied No speciation matrix applied Temporal factors applied for episode from Thursday July 18, 2002 at 000000 to Thursday July 18, 2002 at 230000 Annual total data basis in report Date Region State CO NOX VOC NH3 SO2 PM10 PM2_5 PMC [tons/day] [tons/day] [tons/day] [tons/day] [tons/day] [tons/day] [tons/day] [tons/day]

------------------------------------------------------------------------------------------------------------------------------------------------------------------ 07/18/200 2 1000 Alabama 5.21E+01 2.19E+01 3.88E+02 2.16E+02 9.34E+01 3.66E+01 2.52E+01 1.14E+01 07/18/200 2 4000 Arizona 4.34E+02 1.94E+02 3.55E+02 1.22E+02 1.01E+01 5.17E+01 4.84E+01 3.24E+00 07/18/200 2 5000 Arkansas 4.48E+02 6.06E+01 2.14E+02 4.51E+02 7.90E+01 7.08E+01 6.25E+01 8.30E+00 07/18/200 2 6000 California 8.67E+02 3.73E+02 1.48E+03 9.55E+02 2.65E+01 2.71E+02 2.18E+02 5.26E+01 07/18/200 2 8000 Colorado 9.01E+00 1.01E+01 1.83E+02 2.16E+02 2.80E+00 2.39E+00 2.30E+00 9.67E-02 07/18/200 2 9000 Connectic u 6.37E+00 1.05E+01 1.18E+02 1.99E+01 5.39E-01 3.81E+00 3.54E+00 2.69E-01 07/18/200 2 10000 Delaware 6.56E+00 4.74E+00 2.36E+01 6.12E+01 1.48E+00 7.90E+00 2.75E+00 5.15E+00 07/18/200 2 11000 District of C 1.74E+00 1.99E+00 1.33E+01 2.68E-02 2.32E+00 9.36E-01 8.92E-01 4.37E-02 07/18/200 2 12000 Florida 1.14E+02 8.36E+01 1.35E+03 1.08E+02 1.36E+02 3.07E+01 2.56E+01 5.03E+00 07/18/200 2 13000 Georgia 1.63E+02 8.88E+01 8.71E+02 3.11E+02 1.68E+02 6.60E+01 5.05E+01 1.55E+01 07/18/200 2 16000 Idaho 1.06E+02 1.32E+02 7.85E+02 2.00E+02 2.93E+00 9.50E+01 6.70E+01 2.81E+01 07/18/200 2 17000 Illinois 8.25E+01 6.82E+01 5.73E+02 2.14E+02 1.50E+01 2.69E+01 2.40E+01 4.38E+00 07/18/200 2 18000 Indiana 1.27E+02 6.27E+01 5.45E+02 2.69E+02 1.58E+02 1.56E+02 8.07E+01 7.51E+01 07/18/200 2 19000 Iowa 4.81E+01 6.41E+00 3.07E+02 7.24E+02 2.23E+00 1.86E+01 1.65E+01 2.19E+00 07/18/200 2 20000 Kansas 2.26E+03 1.09E+02 3.71E+02 2.32E+02 3.86E+01 2.86E+02 2.19E+02 6.72E+01 07/18/200 2 21000 Kentucky 8.95E+01 1.21E+02 2.70E+02 1.24E+02 1.02E+02 3.00E+01 2.55E+01 4.50E+00 07/18/200 2 22000 Louisiana 1.66E+03 3.31E+02 3.21E+02 2.24E+02 2.51E+02 1.93E+02 1.65E+02 2.81E+01 07/18/200 2 23000 Maine 2.74E+01 7.23E+00 1.21E+02 3.06E+01 1.53E+01 1.19E+01 1.09E+01 1.04E+00 07/18/200 2 24000 Maryland 2.49E+02 2.66E+01 2.06E+02 9.56E+01 2.21E+01 3.43E+01 3.31E+01 1.14E+00 07/18/200 2 25000 Massachu s 9.95E+01 6.14E+01 2.80E+02 3.87E+01 3.46E+01 5.01E+01 4.36E+01 6.46E+00 07/18/200 2 26000 Michigan 4.64E+01 5.89E+01 5.22E+02 1.39E+02 1.06E+02 1.98E+01 8.99E+00 1.08E+01 07/18/200 2 27000 Minnesota 1.80E+02 1.41E+02 4.52E+02 3.66E+02 3.55E+01 4.87E+01 4.19E+01 6.78E+00 07/18/200 2 28000 Mississippi 4.91E+00 3.25E+00 3.41E+02 1.76E+02 7.73E-01 5.19E+00 1.50E+00 3.69E+00 07/18/200 2 29000 Missouri 2.32E+02 7.43E+01 4.40E+02 3.90E+02 1.24E+02 6.70E+01 5.39E+01 1.31E+01 07/18/200 2 30000 Montana 4.60E+01 3.25E+01 1.02E+02 9.16E+01 2.63E+00 8.46E+00 7.97E+00 4.88E-01 07/18/200 2 31000 Nebraska 1.38E+02 4.25E+01 2.07E+02 3.43E+02 2.68E+01 2.20E+01 1.80E+01 4.06E+00 07/18/200 2 32000 Nevada 1.44E+02 1.95E+01 1.35E+02 2.41E+01 8.17E+00 1.77E+01 1.71E+01 6.02E-01 07/18/200 2 33000 New Ham p 3.82E+01 2.61E+01 8.11E+01 7.21E+00 7.62E+00 2.30E+01 2.06E+01 2.40E+00 07/18/200 2 34000 New Jerse y 1.45E+01 2.24E+01 2.70E+02 5.55E+01 8.55E+00 1.94E+01 9.83E+00 9.72E+00 07/18/200 2 35000 New Mexi c 8.55E+01 7.68E+01 1.48E+02 1.37E+02 1.78E+01 1.52E+01 1.37E+01 1.55E+00 07/18/200 2 36000 New York 7.14E+01 1.15E+02 7.02E+02 2.64E+02 2.28E+02 9.92E+01 4.78E+01 5.14E+01 07/18/200 2 37000 North Car o 1.08E+03 1.12E+02 4.50E+02 5.32E+02 1.63E+01 1.97E+01 1.53E+01 4.51E+00 07/18/200 2 38000 North Dak o 1.80E+01 5.18E+01 1.28E+02 1.25E+02 1.43E+02 7.04E+00 3.74E+00 3.30E+00 07/18/200 2 39000 Ohio 4.02E+01 5.19E+01 6.51E+02 2.81E+02 3.48E+01 5.26E+00 4.70E+00 5.61E-01 07/18/200 2 40000 Oklahoma 1.00E+03 3.38E+02 5.98E+02 3.30E+02 3.23E+01 1.48E+02 1.18E+02 2.97E+01 07/18/200 2 41000 Oregon 1.77E+02 5.42E+01 5.19E+02 9.80E+01 5.96E+01 7.30E+01 6.81E+01 4.93E+00 07/18/200 2 42000 Pennsylva n 3.47E+02 5.72E+01 5.80E+02 3.18E+02 7.39E+01 7.30E+01 5.08E+01 2.22E+01 07/18/200 2 44000 Rhode Isla 1.11E+01 5.57E+00 1.29E+02 2.85E+00 5.43E+00 2.17E+00 2.00E+00 1.65E-01 07/18/200 2 45000 South Car o 1.23E+02 5.25E+01 3.95E+02 9.36E+01 3.12E+01 2.27E+01 1.95E+01 3.20E+00 07/18/200 2 46000 South Dak o 1.73E+01 1.43E+01 8.98E+01 2.69E+02 5.49E+01 5.92E+00 4.44E+00 1.48E+00 07/18/200 2 47000 Tennesse e 8.91E+01 3.53E+01 4.42E+02 8.82E+01 7.95E+01 3.51E+01 2.80E+01 7.16E+00 07/18/200 2 48000 Texas 1.71E+03 2.24E+02 1.18E+03 8.96E+02 1.87E+01 1.96E+02 1.65E+02 3.32E+01 07/18/200 2 49000 Utah 1.99E+02 5.54E+01 1.62E+02 9.43E+01 2.39E+01 2.68E+01 2.54E+01 1.41E+00 07/18/200 2 50000 Vermont 3.95E+01 4.55E+00 3.79E+01 4.14E+01 1.05E+01 6.09E+00 5.48E+00 6.09E-01 07/18/200 2 51000 Virginia 1.98E+02 1.26E+02 3.34E+02 1.40E+02 2.87E+01 5.71E+01 2.31E+01 3.40E+01 07/18/200 2 53000 Washingto 3.64E+02 4.41E+01 3.26E+02 1.21E+02 4.90E+00 6.00E+01 5.81E+01 1.92E+00 07/18/200 2 54000 West Virgi n 3.84E+01 3.07E+01 1.57E+02 3.65E+01 3.15E+01 1.56E+01 1.36E+01 2.03E+00 07/18/200 2 55000 Wisconsin 8.57E+01 3.00E+01 4.35E+02 3.56E+02 9.08E+00 1.62E+01 1.49E+01 1.30E+00 07/18/200 2 56000 Wyoming 5.24E+01 2.14E+02 4.57E+01 6.93E+01 3.83E+01 7.36E+00 6.09E+00 1.27E+00

# Additional State QA Procedures
Once the on-road mobile SMOKE outputs were acquired by NCDAQ, a number of metrics were generated to further QA and summarize the emissions. Those included:

• County emissions totals, bar charts to visually examine whether the counties with the highest emissions are consistent with what was expected from county VMT distribution. (example provided in Figure 1)

• County emissions by SCC code (vehicle and facility) were examined with pie charts to ensure distribution of emissions by vehicle type fits the conceptual model.

• PAVE plots were generated to check to ensure emissions where showing up in all counties in NC. Scale was lowered to make sure no emissions were omitted.

• PAVE plots were animated over a 24-hr period to ensure diurnal changes in emissions were as they should be.

• PAVE plots were visually inspected to make sure emissions were highest/lowest in logical places.
The following QA checks were performed both together and separate for EGU and nonEGU point sources:

• Data product summaries and raw NIF 3.0 data files were examined.

• County emissions totals were examined to assure the counties with the highest emissions were consistent with what was expected.

• PAVE plots were generated to check to ensure emissions where showing up in all counties in NC. Scale was lowered to make sure no emissions were omitted.

• PAVE plots were animated over a 24-hr period to ensure diurnal changes in emissions were as they should be.

• PAVE plots were visually inspected to make sure emissions were highest/lowest in logical places.

• Errors detected in earlier model runs were rechecked with each successive model run to assure their correction was carried forward in subsequent runs.

• NIF files were examined to identify problems with latitude and longitude, as well as, stack parameters.

• Parsed files were examined (i.e., Excel spreadsheets that provide unit-level results derived from the model plant projections obtained by the IPM) for accuracy.

• Facility level emission summaries for 2018 were examined for both the base case and CAIR case to ensure that emissions were consistent and that there were no missing sources.

• Emissions and controls for Duke Energy and Progress Energy were compared to their latest updated plans for complying with North Carolina’s Clean Smokestack Act. (These plans varied substantially from the IPM results both in terms of current and future controls and timing of these controls. As a result, NCDAQ replaced the IPM emission projections for 2009 with projections from the Duke Energy and Progress Energy compliance plans. NCDAQ elected to use the IPM

# results for 2018, with the exception of Duke Lee 3, for which IPM imposed a scrubber that will not exist. This scrubber was removed from the final run.)

• Ensured that stack parameters were modified appropriately and where necessary at facilities where new controls are scheduled to be installed.

• Input files were examined to assure there were no double counted facilities (example would be if a facility was known by two different names and counted under each).
Typical fire emissions SMOKE output in the VISTAS states were acquired by NCDAQ from Alpine Geophysics. The plots and summary reports for these area source fire emissions were spot-checked for QA and included:

• County emissions totals and County emissions by SCC code, were visually examine whether the counties with the highest emissions are consistent with what was expected.

• PAVE plots were generated to check to ensure emissions where showing up in all counties in NC. Scale was lowered to make sure no emissions were omitted.

• PAVE plots were animated over a 24-hr period to ensure diurnal changes in emissions were as they should be.

• PAVE plots were visually inspected to make sure emissions were highest/lowest in logical places.

# Figure 1. Example of a bar chart showing county total NOx emissions.

NC NOx Emissions by County

0.0 5.0 10.0 15.0 20.0 25.0 30.0 35.0 40.0 45.0

Alam an ce Co An

so n C

o

B eauf

o rt Co Brunswick C o Cab

arr

u s Co Carteret Co

Ch

at ham Co

C lay Co Craven Co D

ar e C

o Du

p lin C

o Forsyth C o Gates Co

G

reen

e Co Harnett Co

Hertf o rd Co
Ir ed

ell C

o Jo

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L incoln Co

Mad

ison

Co Mit

ch

ell Co

N ash

Co
O

n slo

w Co Pasquota n k Co Per

s on

C o Ran

d olp

h Co Rockingham Co

S

ampso n Co St

o kes C o Transylvania Co Vance Co

W

as hin

g to

n Co Wilkes Co

Yancey Cotons/day NOx

# Appendix D.4b Temporal Profile Development for Electric Generating Units

### Atmospheric Scien ces Group

387 Pollard Mine Road, Burnsville, NC 28714 828.675.9045 

# Development of Temporal Profiles for Electric Generating Units

(EGUs) In the VISTAS States : Final Technical Memorandum

Prepared for:

Pat Brewer VISTAS Technical Coordinator 2090 US Highway 70 Swannanoa, NC 28778

Prepared by:
Gregory Stella Alpine Geophysics, LLC 387 Pollard Mine Road Burnsville, NC 28714

27 February 2006

## Atmospheric Sciences Group

## Atmospheric Scien ces Group


# TABLE OF CONTENTS

1.0 Introduction

................................................................................................ ....................................................................... 1 2.0 Data Obtained

................................................................................................ .................................................................... 1 2.1. Source of Information

................................................................................................ ................................................ 1 2.2. File Contents

................................................................................................ ................................................................ 2 2.3. Quality Control / Quality Assurance

........................................................................................................................ 2 3.0 Inventory Matching

................................................................................................ .......................................................... 2 4.0 Assumptions and Calculations

................................................................................................ ....................................... 3 4.1. Profile Calculations

................................................................................................ ..................................................... 3 4.1.1. Actual 2002 Profiles

................................................................................................ .............................................. 4 4.1.2. Typical EGU Profil es

................................................................................................ .......................................... 10 5.0 Application of Factors

................................................................................................ ................................................... 14

Appendix A Actual 2002 State Level Monthly Profiles [Tabular] Appendix B Actual 2002 State Level Monthly Profiles [Graphic al] Appendix C Actual 2002 State Level Monthly

- Day of Week Profiles [Tabular] Appendix D Actual 2002 State Level Monthly

- Diurnal Profiles [Tabular] Appendix E Average 2000

- 2004 State Level Monthly Profiles [Tabular] Appendix F Average 2000

- 2004 State Level Monthly Profiles [Graphical] Appendix G Average 2000

- 2004 State Level Monthly

- Day of Week Profiles [Tabular] Appendix H Average 2000

- 2004 State Level Monthly

- Diurnal Profiles [Tabular]

### Atmospheric Sciences Group

1



# 1.0 Introduction The objective of this analysis was to develop temporal profiles for EGUs in the VISTAS states (AL, GA, FL, KY, MS, NC, SC, TN, VA, and WV). These temporal profiles will be used by the VISTAS Emissions and Air Quality Modeling Team during modeling of the VISTAS 2002 and 2018 EGU emissions, in place of SMOKE de fault temporal profiles that are accepted to not accurately depict temporal distribution of emissions from EGUs in the U.S. VISTAS EGU temporal profiles were developed using hourly CEM data as reported to EPA’s Clean Air Market’s Division (CAMD) for the A cid Rain Program.
This technical memorandum describes the work conducted by Alpine Geophysics (Alpine) in order to assist VISTAS in this task with the main objective of developing temporal profiles for VISTAS EGUs necessary to apply in the generation of S MOKE PTHOUR formatted emissions. Additionally, State

- level monthly, day

- of

- week, and diurnal profiles were developed for application to non

- CEM matched units in the VISTAS emissions inventory. These temporal distributions represent a significant improveme nt over the SMOKE defaults, and will be used for both actual 2002 and “typical” 2002 and 2018 modeling.
Two sets of monthly profiles were developed by Alpine:

1. Profiles based solely on actual 2002 CEM

- based data at the state level. The 2002

- only profile s are intended to be used by VISTAS in developing model performance evaluation metrics necessary for configuring air quality models in attainment demonstration analyses.

2. Profiles based on historical averages of 2000 through 2004 CEM

- based data. These hist orical 2000

- 2004 average profiles were developed and are recommended to be used to represent consistent “typical” operating conditions at EGUs in the VISTAS domain for the base year and future year emission estimates.
Analyses conducted by Alpine Geophysi cs indicate an added benefit to the modeling results with the application of CEM

- based day

- of

- week and diurnal profiles, in addition to the monthly profiles for each state. As part of this analysis, specific day

- of

- week (Monday, Tuesday, Wednesday, etc.) a nd diurnal profiles were developed for each month and State to better represent operating conditions at units within each State. The day of week and diurnal profiles were developed from averages of CEM

- based emissions and heat input activity occurring on that day

- of

week or during that hour

- of

- day. These profiles are intended to be applied to units were CEM matches cannot be made to VISTAS emission inventories. 

# 2.0 Data Obtained

2.1. Source of Information Five years (2000 through 2004) of hourly CEM information fro m EPA = s CAMD website were obtained for each unit in the VISTAS states 1 

### . The “ Prepackaged Data” option allows the download of files containing emissions data for a specific state, quarter or month, and year. Each prepackaged data file is in .csv (comma del imited) format and contains the following fields: State, Facility Name, Facility ID (ORISPL), Unit ID, Date, Hour, SO 2 

### Emissions (lbs), CO 2 

### Emissions (tons), NO x 

### Emissions Rate (lb/mmBtu), NO x 

### Emissions (lbs), Heat Input (mmBtu), Operating Time (hours), Gr oss Load (MW), and Steam Load (1000 lb/hr). For this analysis, we obtained the prepackaged monthly unit

- level hourly emissions data by state and year. Using these data, we reformatted the files and quality assured for applicability to this analysis.

1 

### http://cfpub.epa.gov/gdm/index.cfm?fuseaction=prepackaged.select

### Atmospheric Sciences Group

2



# 2.2. File Contents The reformatted files were prepared as identified in Table 1.

Table 1. CEM data file format.

Column Description State State in which the facility is located. Facility Name The name given by the owners and operators to a facility. Facility ID (ORISPL) The unique six

- 

### digit facility identification number, also called an ORISPL, assigned by the Energy Information Administration, a component of the Department of Energy.

Unit ID Each unit at a facility has a unique identification number. It is alp 

### hanumeric and may be from one to six characters in length. For utility units and other units that generate energy for sale, the unit ID used for Part 75 reporting is the same unit ID that appears in the National Allowance Database (NADB) (for Acid Rain Pro gram units) or in the State's allowance allocation list. Day Day on which a unit was operating.
Hour Hour on which a unit was operating. Operating Hours Percent of hour in which a unit was operating. Gross Load (MW) Gross load is the output of the unit as measured in megawatts. Steam Load (1000 lb/hr) Steam load is the output of the unit as measured in 1000 lb/hr of steam. SO 2 

### Mass (lbs) SO 2 

### released for the hour in pounds. SO 2 

### Mass Measurement Flag Indicates whether the value for SO 2 

### mass was measur ed or derived due to missing data. SO 2 

### Rate (lbs/mmBtu) SO 2 

### emissions rate in pounds per million British thermal units (lbs/mmBtu). SO 2 

### Rate Measurement Flag Indicates whether the value for SO 2 

### rate was measured or derived due to missing data. NO x 

### Rate (lb/mmBtu) NOx emissions rate in pounds per million British thermal units (lbs/mmBtu). NO x 

### Rate Measurement Flag Indicates whether the value for NO x 

### rate was measured or derived due to missing data. NO x 

### Mass (lbs) NO x 

### released for the hour in pounds. NO x 

### Mass Measurement Flag Indicates whether the value for NO x 

### mass was measured or derived due to missing data. CO 2 

### Mass (lbs) CO 2 

### released for the hour in pounds. CO 2 

### Mass Measurement Flag Indicates whether the value for CO 2 

### mass was measured or derived d ue to missing data. CO 2 

### Rate (lbs/mmBtu) CO 2 

### emissions rate in pounds per million British thermal units (lbs/mmBtu). CO 2 

### Rate Measurement Flag Indicates whether the value for CO 2 

### rate was measured or derived due to missing data. Heat Input (mmBtu) Heat per hour as calculated by multiplying the quantity of fuel by the fuel's heat content.


# 2.3. Quality Control / Quality Assurance Each file was reviewed to determine if NOx, SO2 and heat input values were represented for each hour of every day for each unit in t he obtained data. Zero values were considered to be valid if operating time identifiers indicated no operation during that hour (e.g., data value of zero but operating hours greater than zero).
Using the measurement flags and field values in the reformatt ed files, numerous spot checks were made of anomalous or missing variable data to ensure that data corruption was not impacting the statistical analyses. Additionally, each year’s hourly total of NOx, SO2, and heat input (per state) were summed and compare d to EPA annual summaries of the same data elements.

When there were f

acilities or units with no emissions data or unit characteristics, we verified that these sources are not required to report emissions data or had not yet reported emissions data to EPA . In some cases, certain months or quarters of the year were blank for individual units or facilities and using EPA data caveat reports, we verified these units were not in operation during those times. 

# 3.0 Inventory Matching
Prior to the development of the un it

- specific SO2, NOx, and heat input ratios for each hour, the step of matching CEM units to the VISTAS 2002 modeling inventory started. Because naming convention and facility or unit

### Atmospheric Sciences Group

3

numbering can be unique at the Federal, State, local, or facility level, the step of matching existing units from an emissions inventory to the CEM data base proved to be more complicated than anticipated.
The VISTAS EGU emission inventory accounted for approximately 3.7 million tons of SO2 and 1.5 million tons of NOx in cale ndar year 2002. There were 861 units reporting to the CEM database in 2002 for the ten VISTAS States. The primary objective of the inventory matching steps was to account for as many units and tons as possible allowing for the unit

- specific application of hourly temporal distribution profiles.
Under the direction of VISTAS, staff at MACTEC Engineering and Consulting, Inc. prepared comparisons of the VISTAS 2002 emission inventory of EGU sources to that of CEM

- based emissions, heat input, and operating char acteristics. For each unit identified as an EGU source in the VISTAS inventory, an attempt was made to match it to a CEM unit and associated data.
Automated facility (ORIS) and unit identification was made for a majority of units who maintained the same numbering and nomenclature between the two data sets. This first computerized step captured the majority of emissions by matching some of the largest units in the VISTAS domain. The remaining steps were followed in order to match the outstanding facilities and emissions as reported by VISTAS States in the 2002 emission inventory.
MACTEC developed county

- level reports of the remaining unmatched facilities and units from the VISTAS inventory and made comparisons of annual emissions of SO2 and NOx to the CEM

- based SO2 and NOx for sources also identified within the same county. This step of the matching process allowed an incremental amount of emissions and units to be accounted for and assigned unit

- specific profiles for model performance evaluation.
Finally, remaining VISTAS inventory and CEM sources were manually compared to each other in an effort to determine if reporting errors in State or county codes or facility or unit identification codes accounted for this reminder of unmatched sources. These manual matches were confirmed or revised with VISTAS State and stakeholder participation and input. With this step, a few sources were identified to have facility identification changes or misreported county codes preventing automated matching from occurring and corrected for the final application of factors.
Once all methods of comparison were exhausted, the remaining unmatched VISTAS emission inventory of EGU sources was excluded from the unit

- specific profile assignment steps and was allocated more generalized facility or State temporal profiles as described in the following section.
This inventory comparison process allowed for the match of over 650 of the 861 CEM identified units (76%) to the VISTAS EGU emission inventory for 2002. More importantly, however, was the match of 99.95 percent of the SO2 emissions and over 99.4 percent of the NOx emissions from these sources in the VISTAS domain. 

# 4.0 Assumptions and Calculations

4.1. Profile Calculations Two sets of profile types have been developed for modeling EGU emissi ons within the VISTAS domain. The first set are to be applied to individual units able to be matched to CEM data, the second are to be applied to EGU sources within the VISTAS domain where CEM

- based matches could not be identified.
The first set of tempor

al profiles have been developed for specific hour

- of

- date periods based on historical actual 2002 or average NOx, SO2, and heat input data for sources reporting under EPA’s CEM program between 2000 and 2004. These profiles are based on the actual or statis tical average of the CEM data variables (NOx, SO2, and heat input) for each hour

- of

- date (e.g., Hour 12 of March 3) during the year. In the typical profile calculation, variables are calculated for each hour when the operating time of the CEM is greater th an 0 (e.g., the unit is in operation during that hour). In the case of 2002

- only calculations, all reported NOx, SO2, and heat input data were used in the averaging, including those identified as non

- operating hours. This allowed for the best representatio n of actual 2002 conditions for the expected use of these profiles for model validation studies.

### Atmospheric Sciences Group

4

In the second set of profiles, NOx, SO2, and heat input values were averaged over each unit to allow for the calculation of State level monthly, day

- of

- week, and diurnal profiles for VISTAS States.

For the 2000

- 2004 averaging period, representation of typical operating conditions was desired, so in the averaging calculation only valid operating hour NOx, SO2, and heat input values were used. This prevented th e introduction of equipment shutdown because of power outages, control installation, or planned maintenance into the temporal profile calculation.


## 4.1.1. Actual 2002 Profiles

Through the EPA’s Clean Air Market’s Data and Maps website, quarterly unit

- level hourl y emissions data by State and calendar year 2002 were obtained for purposes of developing temporal allocation factors applicable to EGU sources within the VISTAS domain. Key elements in these data sets include the State where the unit is located, facility name, facility identification (ORISPL) code (assigned by the Department of Energy at the Energy Information Administration), unit identification code, date of record, hour of record, SO2, CO2, and NOx mass (in lbs per hour), heat input (million British the rmal units [MMBtu]), and NOx emission rate (lbs/MMBtu).
SO2 and NOx mass and heat input values were summed for each unit to an annual level to allow for the calculation of an hour of date

- to

- annual ratio estimation. Equation 1 provides this calculation fo r heat input. Table 1 provides an example result of the ratio calculation.

Equation (1) 

# ∑ = 1

31 , ,, 

## / Jan

Dec date hr date hr ratio 

## hi

hi hi

where hi = heat input (MMBtu)

Table 1. Application of Calculated Ratios for Actual 2002 by Unit

Actual Reported Values [2002] C alculated Ratios

ORISPL UnitID Date Hour SO2 Mass NOx Mass Heat Input SO2 NOx Heat Input

3 2 01

- 01

- 2002 0 15.563 10.294 13.3 1.417E

- 06 1.915E

-

06 1.372E

-

06

3 2 01

- 01

- 2002 1 14.977 8.338 12.5 1.364E

- 06 1.551E

-

06 1.289E

-

06
3 2 01

- 01

- 2002 2 14.93 9.286 12. 6 1.360E

- 06 1.728E

-

06 1.300E

-

06

3 2 01

- 01

- 2002 3 14.774 9.677 12.8 1.346E

- 06 1.800E

-

06 1.320E

-

06

... ... ... ... ... ... ... ... ... ... 3 2 07

- 01

- 2002 0 1084.017 717.467 995.1 9.873E

- 05 1.335E

-

04 1.026E

-

04

3 2 07

- 01

- 2002 1 1102.47 750.04 1012.2 1.004E

- 04 1.395E

-

04 1.044E

-

04

3 2 07

- 01

- 2002 2 1109.41 768.55 1016.6 1.010E

- 04 1.430E

-

04 1.049E

-

04
3 2 07

- 01

- 2002 3 1102.598 772.614 1012.6 1.004E

- 04 1.437E

-

04 1.044E

-

04

3 2 07

- 01

- 2002 4 1087.909 736.967 998.6 9.909E

- 05 1.371E

-

04 1.030E

-

04

3 2 07

- 01

- 2002 5 1099.375 731.888 1009 .5 1.001E

- 04 1.362E

-

04 1.041E

-

04
3 2 07

- 01

- 2002 6 1127.007 693.779 1026.3 1.026E

- 04 1.291E

-

04 1.059E

-

04

3 2 07

- 01

- 2002 7 1203.814 644.008 1114.2 1.096E

- 04 1.198E

-

04 1.149E

-

04

... ... ... ... ... ... ... ... ... ... 3 2 12

- 31

- 2002 21 712.26 503.505 835 6.487E

- 05 9.367E

-

05 8.612E

-

05

3 2 12

- 31

- 2002 22 716.983 587.419 850.1 6.530E

- 05 1.093E

-

04 8.768E

-

05

3 2 12

- 31

- 2002 23 521.311 430.787 647.8 4.748E

- 05 8.014E

-

05 6.681E

-

05

3954 3 Annual Sum 10979533.36 5375215.80 9695608.12 1.000 1.000 1.000

### Atmospheric Sciences Group

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Since it was assume d that all sources in the VISTAS EGU inventory would not be matched to individual CEM

based units, the same calculations were performed for each State so that a hierarchical application of ratios (unit first, State second) could be assigned as necessary. T able 2 shows example ratios calculated for each month by State. Table 3 reflects an example of the State

- month

- day of week ratio calculation and Table 4 shows a State

- month

diurnal ratio calculation example. Each of these ratios were calculated for each St ate in the VISTAS domain and used in instances where CEM unit matches could not be made to the VISTAS base year emissions inventory.
Three parameter values (SO2 mass, NOx mass, heat input) were calculated at each aggregation as NOx and SO2 emissions vary due to fuel blend, sulfur content, or seasonal control and are not necessarily representative of the other variables’ seasonal, daily, or even hourly variation. As seen in Figure 1, when viewed on a VISTAS

- domain total, the monthly variation in relative di stribution of SO2, NOx, and heat input differs enough to justify calculating each parameter value set of temporal profiles with CEM data.

Table 2. Application of Calculated Ratios for Actual 2002 by Example State and Month

Actual Reported Values [2002] Calculated Ratios State Month SO2 Mass NOx Mass Heat Input SO2 NOx Heat Input FL Jan 67,755,539 42,004,513 113,531,981 0.0726 0.0813 0.0733
FL Feb 56,516,278 34,145,451 91,969,840 0.0605 0.0661 0.0594
FL Mar 69,997,283 39,244,669 107,685,763 0.0750 0. 0759 0.0695
FL Apr 73,678,638 40,824,242 118,170,997 0.0789 0.0790 0.0763
FL May 88,889,603 48,974,695 142,351,045 0.0952 0.0948 0.0919
FL Jun 79,736,153 44,027,147 138,648,667 0.0854 0.0852 0.0895
FL Jul 94,401,559 50,007,339 157,075,598 0.1011 0.0968 0.1014
FL Aug 93,041,423 50,077,048 160,601,359 0.0996 0.0969 0.1037
FL Sep 93,349,234 49,183,990 155,433,110 0.1000 0.0952 0.1003
FL Oct 84,214,449 46,837,495 146,347,289 0.0902 0.0906 0.0945
FL Nov 60,374,969 33,098,684 105,854,682 0.0647 0.0641 0.0 683
FL Dec 71,853,245 38,331,463 111,702,695 0.0769 0.0742 0.0721

FL Total 933,808,373 516,756,735 1,549,373,024 1.0000 1.0000 1.0000



### Table 3. Application of Calculated Ratios for Actual 2002 by Example State and Month and Day of Week

Act ual Reported Values [2002] Calculated Ratios State Month Day of Week SO2 Mass NOx Mass Heat Input SO2 NOx Heat Input
GA Mar Sun 13,057,959 4,005,097 10,089,522 

### 0.1467 0.1437 0.1458
GA Mar Mon 11,937,355 3,841,172 9,564,295 

### 0.1341 0.1378 0.1382
GA Mar T ue 11,860,749 3,766,317 9,351,652 

### 0.1332 0.1351 0.1352
GA Mar Wed 12,020,458 3,764,653 9,232,574 

### 0.1350 0.1351 0.1334
GA Mar Thu 11,560,778 3,677,100 9,056,011 

### 0.1299 0.1319 0.1309
GA Mar Fri 14,572,757 4,616,042 11,368,579 

### 0.1637 0.1656 0.1643
GA Mar Sat 14,005,730 4,197,929 10,522,180 

### 0.1573 0.1506 0.1521

GA Mar Total 89,015,786 27,868,311 69,184,812 

### 1.0000 1.0000 1.0000

### Atmospheric Sciences Group

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Table 4. Application of Calculated Ratios for Actual 2002 by Example State and Month and Hour of Day

Actual Repor ted Values [2002] Calculated Ratios State Month Hour SO2 Mass NOx Mass Heat Input SO2 NOx Heat Input SC Dec 0 1,356,270 556,321 1,309,476 0.0399 0.0399 0.0398
SC Dec 1 1,332,499 540,268 1,279,485 0.0392 0.0387 0.0389
SC Dec 2 1,324,618 536,330 1,275,73 2 0.0389 0.0384 0.0388 SC Dec 3 1,330,924 538,908 1,284,514 0.0391 0.0386 0.0391
SC Dec 4 1,335,158 545,819 1,296,880 0.0392 0.0391 0.0394
SC Dec 5 1,385,906 565,695 1,340,759 0.0407 0.0405 0.0408 SC Dec 6 1,436,829 586,536 1,387,329 0.0422 0.0420 0.04 22
SC Dec 7 1,488,961 611,648 1,440,753 0.0438 0.0438 0.0438
SC Dec 8 1,491,509 613,176 1,444,956 0.0438 0.0440 0.0440 SC Dec 9 1,501,425 618,516 1,447,916 0.0441 0.0443 0.0440
SC Dec 10 1,484,685 610,879 1,431,441 0.0436 0.0438 0.0435
SC Dec 11 1,459 ,697 593,638 1,395,938 0.0429 0.0426 0.0425 SC Dec 12 1,423,246 578,669 1,365,957 0.0418 0.0415 0.0415
SC Dec 13 1,391,851 570,939 1,345,091 0.0409 0.0409 0.0409
SC Dec 14 1,352,161 557,078 1,319,068 0.0397 0.0399 0.0401 SC Dec 15 1,344,643 551,497 1,3 12,670 0.0395 0.0395 0.0399
SC Dec 16 1,369,024 559,569 1,333,589 0.0402 0.0401 0.0406
SC Dec 17 1,449,587 595,765 1,398,917 0.0426 0.0427 0.0426 SC Dec 18 1,493,742 621,423 1,438,833 0.0439 0.0445 0.0438
SC Dec 19 1,473,502 611,050 1,427,712 0.0433 0. 0438 0.0434
SC Dec 20 1,479,504 608,223 1,424,664 0.0435 0.0436 0.0433 SC Dec 21 1,475,680 608,049 1,421,202 0.0434 0.0436 0.0432
SC Dec 22 1,450,119 597,906 1,401,208 0.0426 0.0429 0.0426
SC Dec 23 1,391,087 573,310 1,351,539 0.0409 0.0411 0.0411

SC Dec Daily 34,022,628 13,951,210 32,875,627 1.0000 1.0000 1.0000

### Atmospheric Sciences Group

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Figure 1. Monthly variation in 2002 of CEM reported heat input, NOx mass, and SO2 mass for VISTAS domain.

0.060 0.065 0.070 0.075 0.080 0.085 0.090 0.095 0.100 0.105 0.110

Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov DecRelative Distribution Heat Input NOx SO2



### When viewed on a State by State basis, the differences in monthly va riation are even more pronounced as individual facilities within each State may be affected during any calendar year by extreme temperature variation, shutdowns, or regular maintenance or installation of equipment. As an example, Figure 2 represents CEM da ta from the State of Mississippi during calendar year 2002 and reveals that SO2 emissions increase throughout the year, NOx emissions stay relatively high during the summer months, and heat input peaks during the month of July. Although Figures 1 and 2 are roughly comparable in shape and monthly distribution, the relative distribution of these values is quite different. In Mississippi’s case, close to thirteen percent of the State’s CEM

- based heat input occurs in July. This compares to the VISTAS average of just over ten percent of CEM

- based heat input in July.
Finally, when these data are reviewed at a unit level, the differences become incrementally more distinct due to the unique nature of individual facilities, their operating schedules, pollution regul ation, fuel characteristics, and applied technologies. For example, a facility that is complying with summertime NOx regulation may have selective catalytic reduction (SCR) installed on its boiler(s) which in practice may only be run during ozone season mo nths. During this period of time, heat input and SO2 emissions may remain consistent with State or regional monthly profiles, but the NOx emissions may drop significantly relative to the rest of the year.
Figure 3 represents an extreme unit

- specific case for monthly differences from State or regional temporal allocation. The unit presented is a Mississippi baseload coal

- fired boiler which in 2002 emitted over 4,000 tons of NOx and over 11,000 tons of SO2. This unit would typically run at consistent levels during the entire period, but due to a planned maintenance outage was not in operation in late January through the middle of April in 2002. Given the unique operation of this boiler during this year, the use of a regional or even State

- level monthly tempor al distribution would introduce significant inaccuracy to air quality modeling in the immediate or downwind area associated with this facility. While this may not be significant at great distance downwind of the source or for annual concentration estimates , more locally, and especially over shorter time scales (daily or weekly), such simplifications would have a noticeable effect on air quality model predictions.

### Atmospheric Sciences Group

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Figure 2. Monthly variation in 2002 of CEM reported heat input, NOx mass, and SO2 mass for Mis sissippi.

0.020 0.040 0.060 0.080 0.100 0.120 0.140

Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov DecRelative Distribution Heat Input NOx SO2



### Figure 3. Monthly variation in 2002 of CEM reported heat input, NOx mass, and SO2 mass for specific baseload coal

- fired unit in Mississippi with planned outage in late January through mid April.

0.000 0.020 0.040 0.060 0.080 0.100 0.120 0.140

Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov DecRelative Distribution Heat Input NOx SO2

### Atmospheric Sciences Group

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Thus, while improving the representativenes s of unit

- specific monthly temporal profiles is desirable, providing day and hour

- specific values are clearly better. For this reason, during the model performance evaluation process in the VISTAS Phase II modeling, hour

- specific temporal ratios were devel oped for every CEM reporting unit in the VISTAS domain. These ratios allowed for the hour

- by

- hour accounting of emissions released at each unit at each facility within the VISTAS domain that reported output under the CEM guidelines.
Figure 4 represents th e actual daily distribution of SO2 and NOx emissions and heat input from the Mississippi baseload unit from the above example. As can been seen in this figure, not only is the planned January through April outage represented correctly, there are significan t peaks and valleys throughout the calendar year which could not be accurately represented with the application of average monthly, day

- of

- week, or hourly distribution factors. In reality, only the actual operating characteristics of this unit could captur e the differences from hour to hour which are potentially quite important in terms of correctly modeling the impact of the source on downwind oxidant and fine particulate concentrations 2



### . Figure 4. Actual daily unit

- specific 2002 SO2 (tons), NOx, (tons), and heat input (MMBtu) distribution from CEM data.

0

10 20 30 40 50 60 70

01-Jan-02 01-Feb-02 01-Mar-02 01-Apr-02 01-May-02 01-Jun-02 01-Jul-02 01-Aug-02 01-Sep-02 01-Oct-02 01-Nov-02 01-Dec-02 31-Dec-02Emissions (Tons)

0 20,000 40,000 60,000 80,000 100,000 120,000 140,000Heat Input (MMBtu) SO2 NOx Heat Input

2 

### Stella, G.M., “Development of Hourly Inventories Utilizing CEM

- Based Data,” presented at the International Emission Inventory Conference, Las Vegas, NV, April, 2005.

### Atmospheric Sciences Group

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## 4.1.2. Typical EGU Profiles

Hour of day of month specific temporal profiles were developed by calculating the arithmetic mean of each unit’s NOx, SO2, and heat input by specific hour of day per month (e.g., Hour 21 of Wednesdays in July) from the data obtained from 2000 through 2004. In order to accomplish this calculation, each record of CEM data was first assigned a day of week. This assignment was based on the actual CEM’s date of record and day of week o f that record. An example of this assignment is shown in Table 5.

Table 5. Example Day

- of

- Week per Month Assignment

Date Day of Week 08/01/02 Thu 08/02/02 Fri 08/03/02 Sat 08/04/02 Sun 08/05/02 Mon 08/06/02 Tue 08/07/02 Wed


### Once days of week wer

e assigned to each record in the CEM data base, the arithmetic mean of each unit’s NOx, SO2, and heat input were calculated for the ORISPL

- UNITID

- MONTH

- DAY OF WEEK

- HOUR combination. Only records where the CEMs were operating for more than half the recorded hour (OPTIME > 0.5) were used in the averaging calculation. An example of the averaged results can be seen in Table 6.

Table 6. Arithmetic Mean of CEM

- based Variables for Temporal Profile Calculation

Calculated Average Values [2000

– 2004] State Facility ORISPL UnitID Month Day of Week Hour SO2 Mass NOx Mass Heat Input WV Mount Storm Power Station 3954 3 1 Tue 0 406.0526 3384.074 5196.11
WV Mount Storm Power Station 3954 3 1 Tue 1 389.6474 3287.845 5103.06 WV Mount Storm Power Station 3954 3 1 Tue 2 395.2737 3342.848 5175.95

... ... ... ... ... ... ... ... ... ... WV Mount Storm Power Station 3954 3 7 Mon 4 524.7864 2505.9391 4654.34 WV Mount Storm Power Station 3954 3 7 Mon 5 690.5636 2602.9887 4795.64
WV Mount Storm Power Station 3954 3 7 Mon 6 912.4227 2572 .0275 4727.08
WV Mount Storm Power Station 3954 3 7 Mon 7 1060.3 2664.8686 4914.25 WV Mount Storm Power Station 3954 3 7 Mon 8 850.2364 2678.231 5029.58
WV Mount Storm Power Station 3954 3 7 Mon 9 415.3455 2716.8 5042.55
WV Mount Storm Power Station 39 54 3 7 Mon 10 408.8591 2876.5008 5123.71 WV Mount Storm Power Station 3954 3 7 Mon 11 371.9909 2776.0361 5147.85
WV Mount Storm Power Station 3954 3 7 Mon 12 327.2045 2785.5325 5129.66
WV Mount Storm Power Station 3954 3 7 Mon 13 316.0364 2826.901 5172. 29 WV Mount Storm Power Station 3954 3 7 Mon 14 317.1136 2816.1328 5146.07
WV Mount Storm Power Station 3954 3 7 Mon 15 329.6455 2789.0962 5121.75
WV Mount Storm Power Station 3954 3 7 Mon 16 332.7773 2818.5379 5147.05

... ... ... ... ... ... ... ... ... ... WV Mount Sto rm Power Station 3954 3 12 Tue 21 806.7 3432.001 5375.49
WV Mount Storm Power Station 3954 3 12 Tue 22 806.5778 3447.709 5377.68 WV Mount Storm Power Station 3954 3 12 Tue 23 795.4667 3419.069 5359.43

### Atmospheric Sciences Group

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These values were then applied to each unit and ho ur based on the 2002 calendar to match the meteorological data used in the emissions processing. An example of this application can be seen in Table 7. The date specific hourly averages were then summed to a unit summer (May

– Sept) and winter months total and ratios were developed based on each daily hour’s average value divided by the average sum total depending on the season of the day. This permitted the appropriate allocation of summertime NOx (as forecasted by IPM) when summer control only was predict ed. Using the annual average ratios instead of the seasonal distributions would produce summertime emissions different than what was output from the model.

Table 7. Application of Calculated Ratios to Day of Year by Unit

Calculated Average Values [2 000

– 2004] Calculated Ratios

ORISPL UnitID Date Day of Week Hour SO2 Mass NOx Mass Heat Input SO2 NOx Heat Input

3797 4 09/30/02 Mon 19 2591.95 381.78 1527.26 2.899E

- 04 2.396E

-

04 2.863E

-

04

3797 4 09/30/02 Mon 20 2596.81 379.88 1525.60 2.904E

- 04 2.385E

-

04 2.860E

-

04

3797 4 09/30/02 Mon 21 2569.03 370.50 1506.74 2.873E

- 04 2.326E

-

04 2.824E

-

04
3797 4 09/30/02 Mon 22 2547.62 367.24 1498.66 2.849E

- 04 2.305E

-

04 2.809E

-

04

3797 4 09/30/02 Mon 23 2483.88 360.66 1465.68 2.778E

- 04 2.264E

-

04 2.747E

-

04

3797 4 10/ 01/02 Tue 0 1968.94 478.47 1170.76 1.587E

- 04 1.517E

-

04 1.604E

-

04
3797 4 10/01/02 Tue 1 1942.47 480.28 1160.68 1.565E

- 04 1.522E

-

04 1.590E

-

04

3797 4 10/01/02 Tue 2 1858.54 462.44 1122.29 1.498E

- 04 1.466E

-

04 1.537E

-

04

3797 4 10/01/02 Tue 3 1988.43 486.07 1 187.56 1.602E

- 04 1.541E

-

04 1.627E

-

04
3797 4 10/01/02 Tue 4 2125.96 528.59 1263.00 1.713E

- 04 1.676E

-

04 1.730E

-

04

3797 4 10/01/02 Tue 5 2255.22 562.18 1325.40 1.818E

- 04 1.782E

-

04 1.815E

-

04

3797 4 10/01/02 Tue 6 2267.27 558.77 1337.81 1.827E

- 04 1.771E

-

04 1 .832E

-

04
3797 4 10/01/02 Tue 7 2313.00 579.94 1370.73 1.864E

- 04 1.838E

-

04 1.878E

-

04

3797 4 Summer 8941480.78 1593123.80 5334723.17

3797 4 Winter 12408352.17 3154758.40 7300596.69
3797 4 Annual Sum 21349832.95 4747882.21 12635319.86


### Equation 2 reflects this calculation for heat input for a summer hour. Ratios were calculated for NOx, SO2, and heat input values. These ratios were then applied to each unit’s seasonal (summer or winter) emission value for NOx, SO2, and all other pollutants, respectively.

Equation (2) 

# ∑ = 1

30 , , , ,, 

## / May

Sep sum date hr sum date hr ratio 

## hi

hi hi

where hi = heat input (MMBtu)

The actual hour

- of

- day

- of

- month averages calculated from the CEM data were not used directly as emissions for that ho ur, but were used only in the calculation of the ratios to be applied to a pre

- calculated seasonal (summer or winter) emission value. This allowed for the retention of emission estimates calculated using means other than CEM data, if a State or local agenc y found them to be more appropriate or if it were derived by other means (e.g., IPM) but an improved distribution of emissions using CEM

- based ratios.
As in the actual 2002 profiles calculations, these same calculations were additionally performed for eac h State so that a hierarchical application of ratios (unit first, State second) could be assigned as necessary. Instead of having variables at the unit level, however, State level values were used. These State value calculations were based on the sum of th e unit

- level variable averages to the level of aggregation required by the calculation (e.g., State

- month. State

- month

- day

- of

- week, or State

- month

- hour). Table 8 shows example ratios calculated for each month by State. Table 9 reflects an example of the St ate

- month

- day of week ratio calculation and Table 10 shows a State

- month

### Atmospheric Sciences Group

12

diurnal ratio calculation example. Each of these ratios were calculated for each State in the VISTAS domain and used in instances where CEM unit matches could not be made to the VISTA S base year emissions inventory.
Again, three parameter values (SO2 mass, NOx mass, heat input) were calculated at each aggregation as NOx and SO2 emissions vary due to fuel blend, sulfur content, or seasonal control and are not necessarily representative of the other variables’ seasonal, daily, or even hourly variation.

Table 8. Application of Calculated Ratios for Typical Operation by Example State and Month

Calculated Average Values [2000

– 2004] Calculated Ratios State Month SO2 Mass NOx Mass Hea t Input SO2 NOx Heat Input FL Jan 116,011,253 62,989,958 198,751,048 0.0858 0.0875 0.0831
FL Feb 93,958,786 50,831,818 164,949,702 0.0695 0.0706 0.0690
FL Mar 111,505,553 60,285,972 196,705,697 0.0824 0.0838 0.0822
FL Apr 107,015,438 59,071,792 195,338 ,204 0.0791 0.0821 0.0817
FL May 118,589,361 61,811,604 207,803,996 0.0877 0.0859 0.0869
FL Jun 116,068,987 59,801,640 202,716,214 0.0858 0.0831 0.0848
FL Jul 123,868,749 62,500,169 212,478,437 0.0916 0.0868 0.0888
FL Aug 125,384,940 64,572,843 214,637 ,218 0.0927 0.0897 0.0897
FL Sep 113,080,789 59,913,723 206,712,956 0.0836 0.0832 0.0864
FL Oct 109,960,828 61,551,310 206,924,170 0.0813 0.0855 0.0865
FL Nov 101,781,383 55,861,718 186,984,665 0.0752 0.0776 0.0782
FL Dec 115,588,740 60,566,444 197,592 ,133 0.0854 0.0841 0.0826

FL Total 1,352,814,807 719,758,990 2,391,594,439 1.0000 1.0000 1.0000



### Table 9. Application of Calculated Ratios for Typical Operation by Example State and Month and Day of Week

Calculated Average Values [2000

– 20 04] Calculated Ratios State Month Day of Week SO2 Mass NOx Mass Heat Input SO2 NOx Heat Input GA Mar Sun 15,495,089 4,641,883 12,167,666 0.1455 0.1403 0.1319
GA Mar Mon 14,334,901 4,513,847 13,362,335 0.1346 0.1365 0.1449
GA Mar Tue 14,420,895 4,532,75 0 13,463,600 0.1354 0.1370 0.1460
GA Mar Wed 14,170,345 4,489,531 13,057,182 0.1331 0.1357 0.1416
GA Mar Thu 14,004,649 4,446,853 12,249,119 0.1315 0.1344 0.1328
GA Mar Fri 17,177,952 5,357,920 14,842,639 0.1613 0.1620 0.1609
GA Mar Sat 16,881,455 5,09 6,281 13,100,433 0.1585 0.1541 0.1420

GA Mar Total 106,485,284 33,079,065 92,242,973 1.0000 1.0000 1.0000

### Atmospheric Sciences Group

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Table 10. Application of Calculated Ratios for Typical Operation by Example State and Month and Hour of Day

Calculated Average Valu es [2000

– 2004] Calculated Ratios State Month Hour SO2 Mass NOx Mass Heat Input SO2 NOx Heat Input SC Dec 0 1,790,705 674,127 1,908,284 0.0401 0.0395 0.0375
SC Dec 1 1,760,847 659,279 1,877,399 0.0395 0.0386 0.0369
SC Dec 2 1,766,498 660,719 1,890,957 0.0396 0.0387 0.0372 SC Dec 3 1,766,455 664,407 1,922,535 0.0396 0.0389 0.0378
SC Dec 4 1,788,023 677,882 2,005,041 0.0401 0.0397 0.0394
SC Dec 5 1,839,136 708,796 2,193,779 0.0412 0.0415 0.0431 SC Dec 6 1,903,431 736,781 2,379,535 0.0427 0.0432 0.046 8
SC Dec 7 1,957,422 760,608 2,504,498 0.0439 0.0446 0.0492
SC Dec 8 1,958,923 768,669 2,515,860 0.0439 0.0450 0.0494 SC Dec 9 1,974,624 767,392 2,419,052 0.0443 0.0450 0.0475
SC Dec 10 1,944,825 751,207 2,264,252 0.0436 0.0440 0.0445
SC Dec 11 1,888, 552 723,857 2,140,166 0.0423 0.0424 0.0421 SC Dec 12 1,833,408 694,261 2,022,036 0.0411 0.0407 0.0397
SC Dec 13 1,781,162 673,316 1,936,841 0.0399 0.0395 0.0381
SC Dec 14 1,755,403 663,791 1,911,001 0.0393 0.0389 0.0376 SC Dec 15 1,743,443 660,042 1,89 7,088 0.0391 0.0387 0.0373
SC Dec 16 1,775,717 669,264 1,937,000 0.0398 0.0392 0.0381
SC Dec 17 1,877,548 713,920 2,099,275 0.0421 0.0418 0.0413 SC Dec 18 1,948,165 753,627 2,255,923 0.0437 0.0442 0.0443
SC Dec 19 1,940,185 753,123 2,258,417 0.0435 0.0 441 0.0444
SC Dec 20 1,941,859 750,942 2,221,568 0.0435 0.0440 0.0437 SC Dec 21 1,930,605 743,880 2,182,689 0.0433 0.0436 0.0429
SC Dec 22 1,909,077 732,480 2,140,416 0.0428 0.0429 0.0421
SC Dec 23 1,841,457 702,464 2,003,560 0.0413 0.0412 0.0394

SC Dec Daily 44,617,469 17,064,833 50,887,170 1.0000 1.0000 1.0000

### Atmospheric Sciences Group

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# 5.0 Application of Factors

VISTAS chose to prepare its air quality modeling inventories with Version 2.1 of the Sparse Matrix Operating Kernel Emissions (SMOKE) model. For this reason , all emissions were required to be converted to SMOKE’s data formats. In particular, because hour specific temporal profiles for each day of a year are not accepted directly by the model, it was necessary to develop a set of hourly emissions inputs to cir cumvent this limitation. These were generated in the EMS PTHOUR format as described in SMOKE input file documentation 3



### .
The CEM format for individual hour

- specific data files as available in SMOKE was not utilized for VISTAS emissions processing as the em issions allowable by hour would have been limited to NOx, SO2, and CO2. If this file format and optional run configuration were exercised, the NOx, SO2, and CO2 emissions processed by the model would have been accurate for CEM reported emissions, but the r emaining pollutants coupled with each CEM unit would have received the monthly, daily, and diurnal temporal profiles associated with the source category codes from the unit. This could lead to potentially displaced emissions if a unit were operating at dif ferent times than the default profiles indicated. Additionally, in cases where States may not have reported annual emission estimates directly based on CEMs, these emissions would be slightly different that the original annual inventory.

In VISTAS Phase II modeling, for those EGU sources where CEM data were utilized, NOx, SO2, and heat input

based hour

- specific profiles were developed and applied to annual NOx, SO2, and all other emissions, respectively, for both the actual and typical 2002 modeling. Heat input was chosen as a surrogate for non

- CEM reported pollutants as the majority of remaining compounds are not as significantly impacted by controls or fuel content, yet the distribution of these emissions would occur during the same times CEM reported po llutants were emitted.
The application of hourly ratios to annual emissions ensured that the annual values provided by States under the CERR were maintained, but distributed using actual hourly to annual profiles. Additionally, for stakeholder sources pro viding hour

- specific data approved by the State in which they operated, data were substituted for State provided emissions and CEM

- based distributions.
To temporally allocate the remaining EGU point sources, the NOx, SO2, and heat input data were collecte d from the 2002 or 2000

- 2004 CEM datasets, and used to develop State

- level temporal distributions. These month

- specific hour and day of week temporal profiles were used in conjunction with the emissions inventory to calculate hourly EGU emissions by unit.
Although not as accurate a distribution as the unit

- specific factors, the State

- based temporal distribution provided improved results to the default profiles provided with the emissions model. Figure 10 represents the monthly distribution comparisons of VISTAS State heat input to the default monthly distribution from Version 2.0 of SMOKE for source category code (SCC) 10100201, representing External Combustion Boilers; Electric Generation; Bituminous/Subbituminous Coal; Pulverized Coal: Wet Bottom (Bitumi nous Coal), a relatively common boiler type and fuel configuration in the VISTAS domain. This example is for the actual 2002 modeling exercise.
Much like the distinction in month to month variation of the profiles, day of week and diurnal patterns based o n CEM data vary from unit to unit. Again, if one were to assign the same day of week or diurnal profile to every unit in the inventory, emissions from these sources would inappropriately be distributed during the episode of interest. In addition to the uni

que distribution provided by the unit

- specific factors based on CEM data, aggregate State level daily and diurnal temporal distribution factors were developed and applied during this process. Figure 11 shows the variance in diurnal distribution from Tennes see’s average CEM

- based NOx emissions data for each of the twelve months of calendar year 2002 as would have been applied to units unmatched to CEM sources.

3 

### University of North Carolina at Chapel Hill, Sparse Matrix Operator Kernel Emissions (SMOKE) Modeling System , ht tp://cf.unc.edu/cep/empd/products/smoke/index.cfm

.

### Atmospheric Sciences Group

15

Figure 10. Relative distribution of actual 2002 monthly VISTAS State CEM

- based heat input.

0.040 0.050 0.060 0.070 0.080 0.090 0.100 0.110 0.120 0.130

Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov DecRelative Distribution

AL FL GA KY MS NC SC TN VA WV SMOKE



### Figu re 11. Relative distribution of diurnal actual 2002 CEM

- based NOx emissions for Tennessee.

0.0370 0.0380 0.0390 0.0400 0.0410 0.0420 0.0430 0.0440

hr1 hr2 hr3 hr4 hr5 hr6 hr7 hr8 hr9 hr10 hr11 hr12 hr13 hr14 hr15 hr16 hr17 hr18 hr19 hr20 hr21 hr22 hr23 hr24Relative Distribution

Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec

## Atmospheric Sciences Group



# Development of Temporal Profiles for Electric Generating Units

(EGUs) In the VISTAS States :

Appendices

### Atmospheric Sciences Group 

## Appendix A Actual 2002 State Level Monthly Profiles CEM-Based Distribution Alpine Geophysics



### SO2 Mass NOx Mass Heat Input State Month [lbs] [lbs] [MMBtu] SO2 Ratio NOx Ratio Heat Input AL 01 71,985,561 26,094,534 70,343,696 0.080297 0.080758 0.078053 AL 02 57,903,388 22,121,272 59,816,548 0.064589 0.068462 0.066372 AL 03 59,481,424 22,711,853 58,082,148 0.066349 0.070289 0.064447 AL 04 60,498,479 22,601,336 61,617,037 0.067483 0.069947 0.068370 AL 05 67,141,301 24,842,210 69,022,034 0.074893 0.076883 0.076586 AL 06 81,679,140 28,448,320 85,011,304 0.091109 0.088043 0.094328 AL 07 89,737,924 30,849,625 95,110,736 0.100099 0.095475 0.105534 AL 08 88,893,542 30,600,954 93,950,509 0.099157 0.094705 0.104246 AL 09 82,237,240 28,090,654 84,414,970 0.091732 0.086936 0.093666 AL 10 80,712,208 29,703,883 78,387,675 0.090031 0.091929 0.086978 AL 11 74,242,553 28,277,348 72,760,471 0.082814 0.087514 0.080734 AL 12 81,983,321 28,776,840 72,718,335 0.091449 0.089060 0.080687 FL 01 67,755,539 42,004,513 113,531,981 0.072558 0.081285 0.073276 FL 02 56,516,278 34,145,451 91,969,840 0.060522 0.066076 0.059359 FL 03 69,997,283 39,244,669 107,685,763 0.074959 0.075944 0.069503 FL 04 73,678,638 40,824,242 118,170,997 0.078901 0.079001 0.076270 FL 05 88,889,603 48,974,695 142,351,045 0.095190 0.094773 0.091877 FL 06 79,736,153 44,027,147 138,648,667 0.085388 0.085199 0.089487 FL 07 94,401,559 50,007,339 157,075,598 0.101093 0.096772 0.101380 FL 08 93,041,423 50,077,048 160,601,359 0.099637 0.096906 0.103656 FL 09 93,349,234 49,183,990 155,433,110 0.099966 0.095178 0.100320 FL 10 84,214,449 46,837,495 146,347,289 0.090184 0.090637 0.094456 FL 11 60,374,969 33,098,684 105,854,682 0.064655 0.064051 0.068321 FL 12 71,853,245 38,331,463 111,702,695 0.076946 0.074177 0.072095 GA 01 81,756,601 27,799,209 63,415,895 0.079739 0.094906 0.075141 GA 02 68,133,493 22,814,914 52,566,583 0.066452 0.077890 0.062285 GA 03 89,015,786 27,868,311 69,184,812 0.086819 0.095142 0.081976 GA 04 80,522,787 25,019,836 66,614,357 0.078535 0.085417 0.078930 GA 05 84,874,780 21,939,581 69,424,347 0.082780 0.074901 0.082260 GA 06 91,768,073 23,452,819 78,443,585 0.089503 0.080068 0.092947 GA 07 101,133,038 25,987,636 90,892,421 0.098637 0.088721 0.107697 GA 08 100,105,847 25,722,660 89,736,768 0.097635 0.087817 0.106328 GA 09 90,266,321 23,228,209 76,918,862 0.088038 0.079301 0.091140 GA 10 86,793,068 25,058,379 72,028,619 0.084651 0.085549 0.085346 GA 11 65,803,396 19,848,168 51,567,258 0.064179 0.067761 0.061101 GA 12 85,135,314 24,172,877 63,170,593 0.083034 0.082526 0.074850 KY 01 88,386,777 39,297,968 83,186,021 0.091572 0.098968 0.086426 KY 02 73,148,461 34,435,644 72,214,276 0.075785 0.086723 0.075027 KY 03 82,734,302 41,124,378 82,802,323 0.085716 0.103568 0.086027 KY 04 72,547,026 33,467,755 74,544,260 0.075162 0.084285 0.077447 KY 05 76,980,636 27,980,223 77,097,793 0.079755 0.070466 0.080100 KY 06 85,293,823 30,542,925 85,578,097 0.088368 0.076919 0.088911 KY 07 92,870,696 35,215,707 95,716,558 0.096218 0.088687 0.099444 KY 08 96,501,913 33,121,796 94,222,283 0.099980 0.083414 0.097892 KY 09 82,195,196 27,877,611 80,643,890 0.085157 0.070207 0.083785 KY 10 62,185,552 27,638,495 68,747,591 0.064427 0.069605 0.071425 KY 11 63,939,037 28,358,494 66,295,502 0.066243 0.071418 0.068877 KY 12 88,431,377 38,015,871 81,464,864 0.091618 0.095739 0.084638 MS 01 8,031,682 4,498,565 18,693,278 0.061085 0.050717 0.060192 MS 02 5,223,761 4,352,472 16,918,379 0.039730 0.049070 0.054477 MS 03 8,904,502 5,053,631 19,528,557 0.067724 0.056975 0.062882



### Actual Reported Values [2002] Calculated Ratios

A-1

### Atmospheric Sciences Group 

## Appendix A Actual 2002 State Level Monthly Profiles CEM-Based Distribution Alpine Geophysics



### SO2 Mass NOx Mass Heat Input State Month [lbs] [lbs] [MMBtu] SO2 Ratio NOx Ratio Heat Input

Actual Reported Values [2002] Calculated Ratios

MS 04 8,490,345 6,990,633 21,539,003 0.064574 0.078813 0.069355 MS 05 11,716,102 8,877,359 26,494,505 0.089107 0.100084 0.085312 MS 06 11,720,087 9,160,148 32,351,189 0.089138 0.103272 0.104171 MS 07 10,698,661 9,678,640 39,353,163 0.081369 0.109118 0.126717 MS 08 12,248,376 9,455,323 35,788,550 0.093156 0.106600 0.115239 MS 09 13,318,131 9,033,521 32,264,075 0.101292 0.101845 0.103890 MS 10 15,606,833 7,970,595 24,320,790 0.118699 0.089861 0.078313 MS 11 12,055,561 6,231,694 20,456,689 0.091689 0.070257 0.065870 MS 12 13,468,929 7,396,477 22,851,683 0.102439 0.083388 0.073582 NC 01 75,136,353 24,858,345 55,899,678 0.081142 0.085303 0.077304 NC 02 62,625,577 21,049,420 48,060,753 0.067631 0.072233 0.066464 NC 03 76,510,384 25,871,214 58,529,352 0.082626 0.088779 0.080941 NC 04 64,544,010 20,896,091 51,248,689 0.069703 0.071706 0.070873 NC 05 66,362,875 19,060,689 50,405,626 0.071667 0.065408 0.069707 NC 06 84,872,317 24,704,467 66,064,806 0.091656 0.084775 0.091362 NC 07 97,274,800 27,668,346 78,086,028 0.105050 0.094946 0.107986 NC 08 91,520,225 25,673,272 73,521,724 0.098835 0.088100 0.101674 NC 09 85,254,440 25,011,683 66,746,058 0.092069 0.085829 0.092304 NC 10 75,964,852 25,715,410 60,880,736 0.082037 0.088244 0.084193 NC 11 70,335,464 24,469,355 55,259,007 0.075957 0.083968 0.076418 NC 12 75,584,957 26,433,121 58,408,497 0.081626 0.090707 0.080774 SC 01 31,082,047 12,447,442 32,071,078 0.078049 0.075075 0.076619 SC 02 27,616,162 12,022,360 29,372,326 0.069346 0.072511 0.070172 SC 03 30,786,036 13,748,694 31,919,340 0.077306 0.082923 0.076257 SC 04 30,808,574 13,051,703 31,881,213 0.077363 0.078719 0.076166 SC 05 33,379,734 14,540,834 38,224,387 0.083819 0.087701 0.091320 SC 06 36,455,084 15,294,979 40,844,336 0.091541 0.092249 0.097579 SC 07 40,837,836 17,082,250 45,488,310 0.102547 0.103029 0.108674 SC 08 38,676,732 15,591,844 42,790,308 0.097120 0.094040 0.102228 SC 09 35,679,673 14,131,599 36,057,937 0.089594 0.085233 0.086144 SC 10 30,213,689 12,200,904 29,683,343 0.075869 0.073588 0.070915 SC 11 28,677,840 11,736,758 27,369,314 0.072012 0.070788 0.065386 SC 12 34,022,628 13,951,210 32,875,627 0.085433 0.084145 0.078541 TN 01 55,962,590 26,490,714 50,517,218 0.083032 0.083381 0.078240 TN 02 49,772,972 25,111,225 48,268,869 0.073848 0.079039 0.074758 TN 03 53,888,451 27,786,281 53,773,402 0.079954 0.087459 0.083283 TN 04 53,635,523 26,944,116 53,669,004 0.079579 0.084808 0.083121 TN 05 53,793,041 26,211,598 55,397,434 0.079813 0.082503 0.085798 TN 06 58,083,892 28,960,784 60,205,128 0.086179 0.091156 0.093244 TN 07 62,716,273 29,685,685 65,260,117 0.093052 0.093438 0.101073 TN 08 64,732,592 30,656,307 65,844,216 0.096044 0.096493 0.101978 TN 09 55,363,943 25,203,715 54,267,287 0.082144 0.079330 0.084048 TN 10 54,815,971 22,361,942 45,237,221 0.081331 0.070386 0.070062 TN 11 52,473,786 22,941,078 44,704,253 0.077856 0.072209 0.069237 TN 12 58,750,090 25,351,968 48,528,016 0.087168 0.079797 0.075159 VA 01 38,475,114 13,884,068 35,726,965 0.083335 0.088021 0.089043 VA 02 36,246,280 12,707,978 31,318,850 0.078508 0.080565 0.078057 VA 03 34,493,035 12,014,135 28,445,130 0.074710 0.076167 0.070894 VA 04 33,658,381 11,725,743 27,639,417 0.072902 0.074338 0.068886 VA 05 30,058,763 11,157,143 27,241,039 0.065106 0.070733 0.067893 VA 06 40,434,224 13,273,415 36,207,957 0.087578 0.084150 0.090242

A-2

### Atmospheric Sciences Group 

## Appendix A Actual 2002 State Level Monthly Profiles CEM-Based Distribution Alpine Geophysics



### SO2 Mass NOx Mass Heat Input State Month [lbs] [lbs] [MMBtu] SO2 Ratio NOx Ratio Heat Input

Actual Reported Values [2002] Calculated Ratios

VA 07 46,742,629 15,010,587 43,450,363 0.101242 0.095163 0.108292 VA 08 48,824,486 15,473,443 43,802,591 0.105751 0.098098 0.109170 VA 09 38,575,335 12,737,625 32,393,260 0.083552 0.080753 0.080734 VA 10 33,870,666 11,850,176 28,537,080 0.073362 0.075127 0.071124 VA 11 35,473,124 12,423,503 29,886,473 0.076833 0.078762 0.074487 VA 12 44,839,404 15,477,229 36,583,137 0.097120 0.098122 0.091177 WV 01 96,944,793 42,044,442 79,092,849 0.095586 0.093087 0.087747 WV 02 82,119,857 40,236,394 75,363,295 0.080968 0.089084 0.083610 WV 03 80,265,558 39,449,563 74,655,220 0.079140 0.087342 0.082824 WV 04 73,771,312 36,354,805 65,768,483 0.072737 0.080490 0.072965 WV 05 77,750,748 29,700,855 71,390,537 0.076661 0.065758 0.079202 WV 06 81,443,429 33,281,430 76,494,657 0.080302 0.073686 0.084865 WV 07 92,721,546 37,174,696 85,322,770 0.091422 0.082305 0.094659 WV 08 90,767,443 34,927,795 80,025,146 0.089495 0.077331 0.088782 WV 09 75,981,801 31,220,707 67,184,933 0.074916 0.069123 0.074536 WV 10 84,776,265 40,999,243 73,853,919 0.083588 0.090773 0.081935 WV 11 85,826,466 41,795,648 73,025,375 0.084623 0.092536 0.081016 WV 12 91,850,814 44,482,447 79,194,247 0.090563 0.098485 0.087860

A-3

### Atmonspheric Sciences Group 

## Appendix B Actual 2002 Alabama Monthly Profiles CEM-Based Distribution Alpine Geophysics

0.000 0.020 0.040 0.060 0.080 0.100 0.120

Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec
MonthNormailzed Distribution Ratio



### SO2 Ratio NOx Ratio Heat Input

### Atmonspheric Sciences Group 

## Appendix B Actual 2002 Florida Monthly Profiles CEM-Based Distribution Alpine Geophysics

0.000 0.020 0.040 0.060 0.080 0.100 0.120

Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec
MonthNormailzed Distribution Ratio



### SO2 Ratio NOx Ratio Heat Input

### Atmonspheric Sciences Group 

## Appendix B Actual 2002 Georgia Monthly Profiles CEM-Based Distribution Alpine Geophysics

0.000 0.020 0.040 0.060 0.080 0.100 0.120

Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec
MonthNormailzed Distribution Ratio



### SO2 Ratio NOx Ratio Heat Input

### Atmonspheric Sciences Group 

## Appendix B Actual 2002 Kentucky Monthly Profiles CEM-Based Distribution Alpine Geophysics

0.000 0.020 0.040 0.060 0.080 0.100 0.120

Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec
MonthNormailzed Distribution Ratio



### SO2 Ratio NOx Ratio Heat Input

### Atmonspheric Sciences Group 

## Appendix B Actual 2002 Mississippi Monthly Profiles CEM-Based Distribution Alpine Geophysics

0.000 0.020 0.040 0.060 0.080 0.100 0.120 0.140

Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec
MonthNormailzed Distribution Ratio



### SO2 Ratio NOx Ratio Heat Input

### Atmonspheric Sciences Group 

## Appendix B Actual 2002 North Carolina Monthly Profiles

CEM-Based Distribution Alpine Geophysics

0.000 0.020 0.040 0.060 0.080 0.100 0.120

Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec
MonthNormailzed Distribution Ratio



### SO2 Ratio NOx Ratio Heat Input

### Atmonspheric Sciences Group 

## Appendix B Actual 2002 South Carolina Monthly Profiles

CEM-Based Distribution Alpine Geophysics

0.000 0.020 0.040 0.060 0.080 0.100 0.120

Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec
MonthNormailzed Distribution Ratio



### SO2 Ratio NOx Ratio Heat Input

### Atmonspheric Sciences Group 

## Appendix B Actual 2002 Tennessee Monthly Profiles CEM-Based Distribution Alpine Geophysics

0.000 0.020 0.040 0.060 0.080 0.100 0.120

Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec
MonthNormailzed Distribution Ratio



### SO2 Ratio NOx Ratio Heat Input

### Atmonspheric Sciences Group 

## Appendix B Actual 2002 Virginia Monthly Profiles CEM-Based Distribution Alpine Geophysics

0.000 0.020 0.040 0.060 0.080 0.100 0.120

Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec
MonthNormailzed Distribution Ratio



### SO2 Ratio NOx Ratio Heat Input

### Atmonspheric Sciences Group 

## Appendix B Actual 2002 West Virginia Monthly Profiles

CEM-Based Distribution Alpine Geophysics

0.000 0.020 0.040 0.060 0.080 0.100 0.120

Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec
MonthNormailzed Distribution Ratio



### SO2 Ratio NOx Ratio Heat InputAtmospheric Sciences Group 

### Appendix C Actual 2002 State Level Monthly-Day of Week Profiles

CEM-Based Distribution Alpine Geophysics

SO2 Mass NOx Mass Heat Input State Month Day of Week [lbs] [lbs] [MMBtu] SO2 Ratio NOx Ratio Heat Input AL Jan Sun 9,078,807 3,231,646 8,611,813 0.1261 0.1238 0.1224 AL Jan Mon 9,587,489 3,364,368 8,983,683 0.1332 0.1289 0.1277 AL Jan Tue 11,871,297 4,316,474 11,635,467 0.1649 0.1654 0.1654 AL Jan Wed 11,552,004 4,141,961 11,476,100 0.1605 0.1587 0.1631 AL Jan Thu 11,404,376 4,160,093 11,262,809 0.1584 0.1594 0.1601 AL Jan Fri 9,219,511 3,479,116 9,299,661 0.1281 0.1333 0.1322 AL Jan Sat 9,272,077 3,400,877 9,074,163 0.1288 0.1303 0.1290 AL Feb Sun 7,678,659 2,884,011 7,851,550 0.1326 0.1304 0.1313 AL Feb Mon 8,259,941 3,146,902 8,605,518 0.1427 0.1423 0.1439 AL Feb Tue 8,577,231 3,342,049 8,942,171 0.1481 0.1511 0.1495 AL Feb Wed 8,906,514 3,447,121 9,212,008 0.1538 0.1558 0.1540 AL Feb Thu 8,898,663 3,439,817 9,113,886 0.1537 0.1555 0.1524 AL Feb Fri 7,896,813 2,939,154 8,119,378 0.1364 0.1329 0.1357 AL Feb Sat 7,685,567 2,922,218 7,972,038 0.1327 0.1321 0.1333 AL Mar Sun 9,169,116 3,442,468 8,988,048 0.1542 0.1516 0.1547 AL Mar Mon 7,985,823 3,055,344 7,932,040 0.1343 0.1345 0.1366 AL Mar Tue 7,961,605 3,080,761 7,836,035 0.1339 0.1356 0.1349 AL Mar Wed 8,057,393 3,064,834 7,756,403 0.1355 0.1349 0.1335 AL Mar Thu 7,646,534 2,976,099 7,493,543 0.1286 0.1310 0.1290 AL Mar Fri 9,624,602 3,716,488 9,419,901 0.1618 0.1636 0.1622 AL Mar Sat 9,036,351 3,375,859 8,656,178 0.1519 0.1486 0.1490 AL Apr Sun 7,620,840 2,872,729 7,843,393 0.1260 0.1271 0.1273 AL Apr Mon 10,150,271 3,847,452 10,442,420 0.1678 0.1702 0.1695 AL Apr Tue 10,493,280 3,823,328 10,456,244 0.1734 0.1692 0.1697 AL Apr Wed 8,320,056 3,020,201 8,435,022 0.1375 0.1336 0.1369 AL Apr Thu 7,965,139 3,041,039 8,333,366 0.1317 0.1346 0.1352 AL Apr Fri 8,062,984 3,022,769 8,122,807 0.1333 0.1337 0.1318 AL Apr Sat 7,885,908 2,973,818 7,983,785 0.1303 0.1316 0.1296 AL May Sun 8,107,156 2,976,706 8,104,159 0.1207 0.1198 0.1174 AL May Mon 8,344,498 3,122,652 8,602,771 0.1243 0.1257 0.1246 AL May Tue 8,661,029 3,272,698 9,166,876 0.1290 0.1317 0.1328 AL May Wed 11,060,209 4,019,235 11,271,411 0.1647 0.1618 0.1633 AL May Thu 11,105,548 4,148,329 11,677,777 0.1654 0.1670 0.1692 AL May Fri 11,312,659 4,217,537 11,782,733 0.1685 0.1698 0.1707 AL May Sat 8,550,201 3,085,052 8,416,307 0.1273 0.1242 0.1219 AL Jun Sun 12,587,947 4,402,497 12,982,636 0.1541 0.1548 0.1527 AL Jun Mon 11,311,870 3,948,700 11,605,638 0.1385 0.1388 0.1365 AL Jun Tue 11,236,776 3,984,947 11,798,088 0.1376 0.1401 0.1388 AL Jun Wed 11,369,518 3,928,254 12,018,504 0.1392 0.1381 0.1414 AL Jun Thu 11,706,257 3,940,713 12,092,484 0.1433 0.1385 0.1422 AL Jun Fri 10,946,286 3,800,514 11,469,300 0.1340 0.1336 0.1349 AL Jun Sat 12,520,487 4,442,695 13,044,653 0.1533 0.1562 0.1534 AL Jul Sun 11,366,228 3,975,824 12,027,702 0.1267 0.1289 0.1265 AL Jul Mon 14,589,504 5,091,302 15,716,753 0.1626 0.1650 0.1652 AL Jul Tue 14,544,109 5,000,409 15,611,007 0.1621 0.1621 0.1641 AL Jul Wed 14,205,305 4,936,355 15,547,284 0.1583 0.1600 0.1635 AL Jul Thu 11,905,134 3,883,382 12,075,394 0.1327 0.1259 0.1270 AL Jul Fri 11,644,249 3,998,238 12,084,420 0.1298 0.1296 0.1271 AL Jul Sat 11,483,394 3,964,115 12,048,177 0.1280 0.1285 0.1267 AL Aug Sun 10,825,551 3,821,512 11,515,637 0.1218 0.1249 0.1226 AL Aug Mon 11,445,364 4,000,822 12,190,122 0.1288 0.1307 0.1298 AL Aug Tue 12,007,879 4,045,329 12,492,605 0.1351 0.1322 0.1330 AL Aug Wed 11,922,474 4,052,097 12,481,993 0.1341 0.1324 0.1329 AL Aug Thu 14,078,738 4,923,253 15,268,914 0.1584 0.1609 0.1625 AL Aug Fri 14,553,733 4,962,397 15,356,359 0.1637 0.1622 0.1635 AL Aug Sat 14,059,804 4,795,544 14,644,879 0.1582 0.1567 0.1559 AL Sep Sun 13,072,758 4,471,264 13,196,855 0.1590 0.1592 0.1563 Actual Reported Values [2002] Calculated Ratios

C-1Atmospheric Sciences Group 

### Appendix C Actual 2002 State Level Monthly-Day of Week Profiles

CEM-Based Distribution Alpine Geophysics

SO2 Mass NOx Mass Heat Input State Month Day of Week [lbs] [lbs] [MMBtu] SO2 Ratio NOx Ratio Heat Input Actual Reported Values [2002] Calculated Ratios

AL Sep Mon 13,294,919 4,721,035 14,078,907 0.1617 0.1681 0.1668 AL Sep Tue 11,047,145 3,741,275 11,630,507 0.1343 0.1332 0.1378 AL Sep Wed 11,238,257 3,759,477 11,648,841 0.1367 0.1338 0.1380 AL Sep Thu 11,442,771 3,799,645 11,604,738 0.1391 0.1353 0.1375 AL Sep Fri 11,202,342 3,873,202 11,416,026 0.1362 0.1379 0.1352 AL Sep Sat 10,939,047 3,724,756 10,839,095 0.1330 0.1326 0.1284 AL Oct Sun 10,266,327 3,811,745 9,910,846 0.1272 0.1283 0.1264 AL Oct Mon 10,511,864 3,893,598 10,251,681 0.1302 0.1311 0.1308 AL Oct Tue 13,228,690 4,772,703 12,828,813 0.1639 0.1607 0.1637 AL Oct Wed 12,878,703 4,736,208 12,615,330 0.1596 0.1594 0.1609 AL Oct Thu 12,833,772 4,840,532 12,710,749 0.1590 0.1630 0.1622 AL Oct Fri 10,462,972 3,882,324 10,152,030 0.1296 0.1307 0.1295 AL Oct Sat 10,529,880 3,766,773 9,918,226 0.1305 0.1268 0.1265 AL Nov Sun 9,435,823 3,618,731 9,252,124 0.1271 0.1280 0.1272 AL Nov Mon 9,815,895 3,866,691 9,985,632 0.1322 0.1367 0.1372 AL Nov Tue 9,908,528 3,758,532 9,858,206 0.1335 0.1329 0.1355 AL Nov Wed 10,263,466 3,844,651 9,895,694 0.1382 0.1360 0.1360 AL Nov Thu 10,032,649 3,798,189 9,806,574 0.1351 0.1343 0.1348 AL Nov Fri 12,478,956 4,733,218 12,183,571 0.1681 0.1674 0.1674 AL Nov Sat 12,307,237 4,657,337 11,778,669 0.1658 0.1647 0.1619 AL Dec Sun 13,039,568 4,497,908 11,373,273 0.1591 0.1563 0.1564 AL Dec Mon 13,332,284 4,684,608 11,658,842 0.1626 0.1628 0.1603 AL Dec Tue 12,586,572 4,509,227 11,390,750 0.1535 0.1567 0.1566 AL Dec Wed 10,401,903 3,640,431 9,394,390 0.1269 0.1265 0.1292 AL Dec Thu 10,699,833 3,718,555 9,589,043 0.1305 0.1292 0.1319 AL Dec Fri 11,098,568 3,886,991 9,771,669 0.1354 0.1351 0.1344 AL Dec Sat 10,824,595 3,839,120 9,540,370 0.1320 0.1334 0.1312 FL Jan Sun 6,460,018 4,145,458 12,075,614 0.0953 0.0987 0.1064 FL Jan Mon 8,223,824 5,249,656 14,295,053 0.1214 0.1250 0.1259 FL Jan Tue 11,267,068 6,878,180 18,626,699 0.1663 0.1637 0.1641 FL Jan Wed 12,006,882 7,370,189 19,424,661 0.1772 0.1755 0.1711 FL Jan Thu 11,580,132 7,146,149 19,145,131 0.1709 0.1701 0.1686 FL Jan Fri 9,933,130 6,055,862 15,781,937 0.1466 0.1442 0.1390 FL Jan Sat 8,284,487 5,159,019 14,182,886 0.1223 0.1228 0.1249 FL Feb Sun 6,580,888 4,153,211 11,712,808 0.1164 0.1216 0.1274 FL Feb Mon 7,821,429 4,772,468 12,898,655 0.1384 0.1398 0.1402 FL Feb Tue 8,529,572 5,203,703 13,717,324 0.1509 0.1524 0.1492 FL Feb Wed 8,869,381 5,320,865 13,997,444 0.1569 0.1558 0.1522 FL Feb Thu 9,547,499 5,584,277 14,448,682 0.1689 0.1635 0.1571 FL Feb Fri 8,171,784 4,783,682 13,156,243 0.1446 0.1401 0.1430 FL Feb Sat 6,995,726 4,327,246 12,038,684 0.1238 0.1267 0.1309 FL Mar Sun 10,436,073 5,703,152 16,073,032 0.1491 0.1453 0.1493 FL Mar Mon 10,042,536 5,525,518 14,872,599 0.1435 0.1408 0.1381 FL Mar Tue 10,504,478 5,792,477 15,448,467 0.1501 0.1476 0.1435 FL Mar Wed 9,340,619 5,216,743 14,425,208 0.1334 0.1329 0.1340 FL Mar Thu 8,492,454 4,795,916 13,518,581 0.1213 0.1222 0.1255 FL Mar Fri 11,164,084 6,463,221 17,344,633 0.1595 0.1647 0.1611 FL Mar Sat 10,017,039 5,747,641 16,003,244 0.1431 0.1465 0.1486 FL Apr Sun 8,585,377 4,964,930 14,931,077 0.1165 0.1216 0.1264 FL Apr Mon 12,745,138 6,974,440 20,136,929 0.1730 0.1708 0.1704 FL Apr Tue 13,343,375 7,153,016 20,555,830 0.1811 0.1752 0.1739 FL Apr Wed 10,008,186 5,591,661 15,816,344 0.1358 0.1370 0.1338 FL Apr Thu 10,282,959 5,571,398 16,008,555 0.1396 0.1365 0.1355 FL Apr Fri 9,897,428 5,469,872 15,727,299 0.1343 0.1340 0.1331 FL Apr Sat 8,816,175 5,098,925 14,994,963 0.1197 0.1249 0.1269 FL May Sun 10,872,937 5,917,228 17,154,454 0.1223 0.1208 0.1205 FL May Mon 11,087,315 6,389,920 18,204,704 0.1247 0.1305 0.1279

C-2Atmospheric Sciences Group 

### Appendix C Actual 2002 State Level Monthly-Day of Week Profiles

CEM-Based Distribution Alpine Geophysics

SO2 Mass NOx Mass Heat Input State Month Day of Week [lbs] [lbs] [MMBtu] SO2 Ratio NOx Ratio Heat Input Actual Reported Values [2002] Calculated Ratios

FL May Tue 11,144,651 6,436,362 18,386,978 0.1254 0.1314 0.1292 FL May Wed 14,157,439 7,871,861 23,067,275 0.1593 0.1607 0.1620 FL May Thu 14,810,343 8,012,280 23,271,348 0.1666 0.1636 0.1635 FL May Fri 15,308,300 8,088,722 23,788,784 0.1722 0.1652 0.1671 FL May Sat 11,508,619 6,258,321 18,477,502 0.1295 0.1278 0.1298 FL Jun Sun 12,367,759 6,882,537 21,942,803 0.1551 0.1563 0.1583 FL Jun Mon 11,089,956 6,219,462 19,326,803 0.1391 0.1413 0.1394 FL Jun Tue 10,971,633 6,121,052 18,888,412 0.1376 0.1390 0.1362 FL Jun Wed 11,459,795 6,206,384 19,340,130 0.1437 0.1410 0.1395 FL Jun Thu 11,212,701 6,178,620 19,271,553 0.1406 0.1403 0.1390 FL Jun Fri 10,572,042 5,742,576 18,179,541 0.1326 0.1304 0.1311 FL Jun Sat 12,062,267 6,676,517 21,699,426 0.1513 0.1516 0.1565 FL Jul Sun 11,389,822 6,203,670 19,727,509 0.1207 0.1241 0.1256 FL Jul Mon 15,576,693 8,073,373 25,570,026 0.1650 0.1614 0.1628 FL Jul Tue 15,745,575 8,312,180 25,816,928 0.1668 0.1662 0.1644 FL Jul Wed 16,455,780 8,585,816 26,347,891 0.1743 0.1717 0.1677 FL Jul Thu 12,386,180 6,441,152 20,216,893 0.1312 0.1288 0.1287 FL Jul Fri 11,671,181 6,307,316 19,905,505 0.1236 0.1261 0.1267 FL Jul Sat 11,176,329 6,083,834 19,490,845 0.1184 0.1217 0.1241 FL Aug Sun 11,119,169 6,052,295 20,141,414 0.1195 0.1209 0.1254 FL Aug Mon 12,439,096 6,729,392 21,508,484 0.1337 0.1344 0.1339 FL Aug Tue 12,028,439 6,501,920 20,980,955 0.1293 0.1298 0.1306 FL Aug Wed 11,903,888 6,410,214 20,537,494 0.1279 0.1280 0.1279 FL Aug Thu 15,997,665 8,468,246 26,490,393 0.1719 0.1691 0.1649 FL Aug Fri 15,513,519 8,145,000 25,857,372 0.1667 0.1626 0.1610 FL Aug Sat 14,039,647 7,769,981 25,085,246 0.1509 0.1552 0.1562 FL Sep Sun 14,248,272 7,881,518 25,139,667 0.1526 0.1602 0.1617 FL Sep Mon 15,481,285 8,321,569 26,523,726 0.1658 0.1692 0.1706 FL Sep Tue 13,875,523 6,610,166 21,058,066 0.1486 0.1344 0.1355 FL Sep Wed 12,827,853 6,510,169 20,695,394 0.1374 0.1324 0.1331 FL Sep Thu 12,381,697 6,587,855 20,702,534 0.1326 0.1339 0.1332 FL Sep Fri 12,599,112 6,705,049 20,791,900 0.1350 0.1363 0.1338 FL Sep Sat 11,935,491 6,567,663 20,521,823 0.1279 0.1335 0.1320 FL Oct Sun 10,201,802 5,635,841 18,079,248 0.1211 0.1203 0.1235 FL Oct Mon 10,950,396 6,102,400 19,331,362 0.1300 0.1303 0.1321 FL Oct Tue 14,462,004 7,914,664 24,697,888 0.1717 0.1690 0.1688 FL Oct Wed 13,960,820 7,814,557 24,127,857 0.1658 0.1668 0.1649 FL Oct Thu 13,145,418 7,478,321 23,145,375 0.1561 0.1597 0.1582 FL Oct Fri 10,799,123 6,073,134 18,679,147 0.1282 0.1297 0.1276 FL Oct Sat 10,694,885 5,818,576 18,286,411 0.1270 0.1242 0.1250 FL Nov Sun 7,657,765 4,160,806 13,477,795 0.1268 0.1257 0.1273 FL Nov Mon 8,709,070 4,831,448 15,459,908 0.1442 0.1460 0.1460 FL Nov Tue 8,565,162 4,743,499 15,536,089 0.1419 0.1433 0.1468 FL Nov Wed 7,928,875 4,569,865 14,424,685 0.1313 0.1381 0.1363 FL Nov Thu 7,349,917 4,039,745 13,034,212 0.1217 0.1221 0.1231 FL Nov Fri 10,189,470 5,494,954 17,273,306 0.1688 0.1660 0.1632 FL Nov Sat 9,974,710 5,258,366 16,648,687 0.1652 0.1589 0.1573 FL Dec Sun 10,845,001 5,969,341 17,326,559 0.1509 0.1557 0.1551 FL Dec Mon 12,472,114 6,696,988 18,977,359 0.1736 0.1747 0.1699 FL Dec Tue 11,633,954 6,196,791 18,110,973 0.1619 0.1617 0.1621 FL Dec Wed 8,614,557 4,632,533 13,804,951 0.1199 0.1209 0.1236 FL Dec Thu 9,417,556 4,917,346 14,754,058 0.1311 0.1283 0.1321 FL Dec Fri 9,766,113 4,987,111 14,570,949 0.1359 0.1301 0.1304 FL Dec Sat 9,103,950 4,931,354 14,157,847 0.1267 0.1287 0.1267 GA Jan Sun 9,232,479 3,069,863 7,033,231 0.1129 0.1104 0.1109 GA Jan Mon 10,338,614 3,448,548 7,991,068 0.1265 0.1241 0.1260 GA Jan Tue 13,705,744 4,638,953 10,633,396 0.1676 0.1669 0.1677

C-3Atmospheric Sciences Group 

### Appendix C Actual 2002 State Level Monthly-Day of Week Profiles

CEM-Based Distribution Alpine Geophysics

SO2 Mass NOx Mass Heat Input State Month Day of Week [lbs] [lbs] [MMBtu] SO2 Ratio NOx Ratio Heat Input Actual Reported Values [2002] Calculated Ratios

GA Jan Wed 13,582,481 4,709,185 10,869,230 0.1661 0.1694 0.1714 GA Jan Thu 13,486,891 4,777,788 10,715,734 0.1650 0.1719 0.1690 GA Jan Fri 11,438,830 3,805,041 8,528,349 0.1399 0.1369 0.1345 GA Jan Sat 9,971,562 3,349,832 7,644,887 0.1220 0.1205 0.1206 GA Feb Sun 8,517,612 2,781,030 6,474,213 0.1250 0.1219 0.1232 GA Feb Mon 10,022,044 3,306,596 7,599,264 0.1471 0.1449 0.1446 GA Feb Tue 10,492,127 3,510,987 8,053,143 0.1540 0.1539 0.1532 GA Feb Wed 10,239,133 3,550,856 8,250,818 0.1503 0.1556 0.1570 GA Feb Thu 10,364,380 3,560,605 8,216,068 0.1521 0.1561 0.1563 GA Feb Fri 9,479,298 3,170,924 7,167,972 0.1391 0.1390 0.1364 GA Feb Sat 9,018,899 2,933,916 6,805,104 0.1324 0.1286 0.1295 GA Mar Sun 13,057,959 4,005,097 10,089,522 0.1467 0.1437 0.1458 GA Mar Mon 11,937,355 3,841,172 9,564,295 0.1341 0.1378 0.1382 GA Mar Tue 11,860,749 3,766,317 9,351,652 0.1332 0.1351 0.1352 GA Mar Wed 12,020,458 3,764,653 9,232,574 0.1350 0.1351 0.1334 GA Mar Thu 11,560,778 3,677,100 9,056,011 0.1299 0.1319 0.1309 GA Mar Fri 14,572,757 4,616,042 11,368,579 0.1637 0.1656 0.1643 GA Mar Sat 14,005,730 4,197,929 10,522,180 0.1573 0.1506 0.1521 GA Apr Sun 10,010,321 3,054,871 8,130,063 0.1243 0.1221 0.1220 GA Apr Mon 13,726,614 4,219,606 11,234,934 0.1705 0.1687 0.1687 GA Apr Tue 13,642,243 4,159,996 11,257,306 0.1694 0.1663 0.1690 GA Apr Wed 11,119,160 3,557,859 9,454,040 0.1381 0.1422 0.1419 GA Apr Thu 11,121,181 3,547,214 9,402,072 0.1381 0.1418 0.1411 GA Apr Fri 10,992,958 3,469,508 9,154,244 0.1365 0.1387 0.1374 GA Apr Sat 9,910,312 3,010,782 7,981,698 0.1231 0.1203 0.1198 GA May Sun 9,954,317 2,489,279 7,718,318 0.1173 0.1135 0.1112 GA May Mon 11,083,543 2,846,449 8,849,737 0.1306 0.1297 0.1275 GA May Tue 10,860,158 2,817,251 8,937,307 0.1280 0.1284 0.1287 GA May Wed 14,055,700 3,723,984 11,705,218 0.1656 0.1697 0.1686 GA May Thu 14,190,755 3,795,027 12,132,195 0.1672 0.1730 0.1748 GA May Fri 14,364,190 3,677,935 11,892,964 0.1692 0.1676 0.1713 GA May Sat 10,366,117 2,589,657 8,188,607 0.1221 0.1180 0.1180 GA Jun Sun 14,272,108 3,565,552 11,872,006 0.1555 0.1520 0.1513 GA Jun Mon 12,565,097 3,230,084 10,796,899 0.1369 0.1377 0.1376 GA Jun Tue 12,662,512 3,342,327 11,036,638 0.1380 0.1425 0.1407 GA Jun Wed 12,559,472 3,370,089 11,213,296 0.1369 0.1437 0.1429 GA Jun Thu 12,721,557 3,228,578 11,169,416 0.1386 0.1377 0.1424 GA Jun Fri 12,401,462 3,087,958 10,360,176 0.1351 0.1317 0.1321 GA Jun Sat 14,585,864 3,628,231 11,995,154 0.1589 0.1547 0.1529 GA Jul Sun 13,058,471 3,295,789 10,898,881 0.1291 0.1268 0.1199 GA Jul Mon 17,056,043 4,331,902 15,504,540 0.1686 0.1667 0.1706 GA Jul Tue 16,718,544 4,271,189 15,356,784 0.1653 0.1644 0.1690 GA Jul Wed 16,380,787 4,258,436 15,192,772 0.1620 0.1639 0.1672 GA Jul Thu 12,544,497 3,284,625 11,428,407 0.1240 0.1264 0.1257 GA Jul Fri 12,723,398 3,311,110 11,501,703 0.1258 0.1274 0.1265 GA Jul Sat 12,651,296 3,234,586 11,009,335 0.1251 0.1245 0.1211 GA Aug Sun 12,591,882 3,173,151 11,054,009 0.1258 0.1234 0.1232 GA Aug Mon 12,689,424 3,377,612 12,101,546 0.1268 0.1313 0.1349 GA Aug Tue 12,811,575 3,370,696 11,902,603 0.1280 0.1310 0.1326 GA Aug Wed 13,615,740 3,466,528 11,742,465 0.1360 0.1348 0.1309 GA Aug Thu 16,548,070 4,256,601 14,871,154 0.1653 0.1655 0.1657 GA Aug Fri 16,223,157 4,132,201 14,523,344 0.1621 0.1606 0.1618 GA Aug Sat 15,625,999 3,945,870 13,541,647 0.1561 0.1534 0.1509 GA Sep Sun 14,076,695 3,552,007 11,239,335 0.1559 0.1529 0.1461 GA Sep Mon 15,118,284 3,952,189 12,971,319 0.1675 0.1701 0.1686 GA Sep Tue 12,290,870 3,222,102 10,846,543 0.1362 0.1387 0.1410 GA Sep Wed 12,207,239 3,171,924 10,870,491 0.1352 0.1366 0.1413

C-4Atmospheric Sciences Group 

### Appendix C Actual 2002 State Level Monthly-Day of Week Profiles

CEM-Based Distribution Alpine Geophysics

SO2 Mass NOx Mass Heat Input State Month Day of Week [lbs] [lbs] [MMBtu] SO2 Ratio NOx Ratio Heat Input Actual Reported Values [2002] Calculated Ratios

GA Sep Thu 12,591,996 3,238,385 10,829,315 0.1395 0.1394 0.1408 GA Sep Fri 12,421,915 3,205,151 10,688,743 0.1376 0.1380 0.1390 GA Sep Sat 11,559,321 2,886,451 9,473,115 0.1281 0.1243 0.1232 GA Oct Sun 10,397,107 2,974,956 8,483,587 0.1198 0.1187 0.1178 GA Oct Mon 11,403,595 3,298,001 9,526,894 0.1314 0.1316 0.1323 GA Oct Tue 14,439,466 4,101,982 11,815,930 0.1664 0.1637 0.1640 GA Oct Wed 14,214,276 4,088,386 11,998,314 0.1638 0.1632 0.1666 GA Oct Thu 13,694,824 4,055,175 11,641,902 0.1578 0.1618 0.1616 GA Oct Fri 12,031,671 3,451,730 9,692,488 0.1386 0.1377 0.1346 GA Oct Sat 10,612,129 3,088,149 8,869,504 0.1223 0.1232 0.1231 GA Nov Sun 7,942,685 2,407,347 6,217,734 0.1207 0.1213 0.1206 GA Nov Mon 8,844,920 2,615,409 7,084,667 0.1344 0.1318 0.1374 GA Nov Tue 9,227,463 2,767,059 7,247,112 0.1402 0.1394 0.1405 GA Nov Wed 9,082,791 2,734,529 7,082,431 0.1380 0.1378 0.1373 GA Nov Thu 8,610,960 2,620,947 6,807,102 0.1309 0.1320 0.1320 GA Nov Fri 11,542,238 3,520,543 9,025,713 0.1754 0.1774 0.1750 GA Nov Sat 10,552,339 3,182,333 8,102,499 0.1604 0.1603 0.1571 GA Dec Sun 13,004,566 3,746,897 9,702,453 0.1528 0.1550 0.1536 GA Dec Mon 13,858,316 3,958,234 10,421,734 0.1628 0.1637 0.1650 GA Dec Tue 13,256,445 3,711,914 9,632,877 0.1557 0.1536 0.1525 GA Dec Wed 11,138,682 3,116,085 8,141,135 0.1308 0.1289 0.1289 GA Dec Thu 11,563,462 3,248,852 8,623,577 0.1358 0.1344 0.1365 GA Dec Fri 11,123,706 3,221,012 8,415,659 0.1307 0.1332 0.1332 GA Dec Sat 11,190,137 3,169,883 8,233,157 0.1314 0.1311 0.1303 KY Jan Sun 10,270,235 4,703,579 9,758,647 0.1162 0.1197 0.1173 KY Jan Mon 11,539,709 5,046,171 10,626,099 0.1306 0.1284 0.1277 KY Jan Tue 15,061,302 6,731,703 14,077,147 0.1704 0.1713 0.1692 KY Jan Wed 14,510,265 6,483,005 13,921,770 0.1642 0.1650 0.1674 KY Jan Thu 14,358,226 6,395,736 13,698,769 0.1624 0.1627 0.1647 KY Jan Fri 11,886,600 5,269,506 11,149,264 0.1345 0.1341 0.1340 KY Jan Sat 10,760,440 4,668,269 9,954,325 0.1217 0.1188 0.1197 KY Feb Sun 9,273,118 4,493,769 9,287,609 0.1268 0.1305 0.1286 KY Feb Mon 10,698,695 5,006,598 10,493,992 0.1463 0.1454 0.1453 KY Feb Tue 11,049,604 5,019,573 10,675,037 0.1511 0.1458 0.1478 KY Feb Wed 10,988,215 5,204,070 10,974,160 0.1502 0.1511 0.1520 KY Feb Thu 10,907,690 5,180,909 10,864,856 0.1491 0.1505 0.1505 KY Feb Fri 10,657,807 4,893,188 10,379,093 0.1457 0.1421 0.1437 KY Feb Sat 9,573,332 4,637,537 9,539,529 0.1309 0.1347 0.1321 KY Mar Sun 12,449,952 6,209,245 12,535,877 0.1505 0.1510 0.1514 KY Mar Mon 10,769,505 5,314,571 11,106,869 0.1302 0.1292 0.1341 KY Mar Tue 10,934,200 5,430,959 11,060,798 0.1322 0.1321 0.1336 KY Mar Wed 10,792,115 5,419,872 10,805,019 0.1304 0.1318 0.1305 KY Mar Thu 11,387,697 5,600,168 10,998,489 0.1376 0.1362 0.1328 KY Mar Fri 13,969,862 6,871,102 13,744,840 0.1689 0.1671 0.1660 KY Mar Sat 12,430,971 6,278,461 12,550,430 0.1503 0.1527 0.1516 KY Apr Sun 9,440,462 4,040,042 9,003,071 0.1301 0.1207 0.1208 KY Apr Mon 12,029,772 5,556,708 12,233,952 0.1658 0.1660 0.1641 KY Apr Tue 12,169,395 5,716,910 12,665,327 0.1677 0.1708 0.1699 KY Apr Wed 9,755,391 4,714,274 10,387,544 0.1345 0.1409 0.1393 KY Apr Thu 9,918,828 4,690,559 10,520,996 0.1367 0.1402 0.1411 KY Apr Fri 10,189,074 4,497,976 10,237,877 0.1404 0.1344 0.1373 KY Apr Sat 9,044,103 4,251,285 9,495,495 0.1247 0.1270 0.1274 KY May Sun 8,721,837 3,096,807 8,845,557 0.1133 0.1107 0.1147 KY May Mon 9,805,389 3,493,285 9,768,175 0.1274 0.1248 0.1267 KY May Tue 10,172,511 3,691,499 10,248,717 0.1321 0.1319 0.1329 KY May Wed 12,873,917 4,704,825 13,036,482 0.1672 0.1681 0.1691 KY May Thu 13,075,505 4,867,081 13,146,483 0.1699 0.1739 0.1705

C-5Atmospheric Sciences Group 

### Appendix C Actual 2002 State Level Monthly-Day of Week Profiles

CEM-Based Distribution Alpine Geophysics

SO2 Mass NOx Mass Heat Input State Month Day of Week [lbs] [lbs] [MMBtu] SO2 Ratio NOx Ratio Heat Input Actual Reported Values [2002] Calculated Ratios

KY May Fri 13,102,085 4,803,200 12,929,328 0.1702 0.1717 0.1677 KY May Sat 9,229,392 3,323,525 9,123,052 0.1199 0.1188 0.1183 KY Jun Sun 13,097,530 4,814,592 13,368,251 0.1536 0.1576 0.1562 KY Jun Mon 11,562,934 4,122,623 11,797,191 0.1356 0.1350 0.1379 KY Jun Tue 11,825,018 4,125,795 11,986,840 0.1386 0.1351 0.1401 KY Jun Wed 11,913,603 4,146,870 11,814,114 0.1397 0.1358 0.1381 KY Jun Thu 11,761,537 4,223,220 11,682,495 0.1379 0.1383 0.1365 KY Jun Fri 11,657,871 4,138,851 11,416,531 0.1367 0.1355 0.1334 KY Jun Sat 13,475,330 4,970,974 13,512,676 0.1580 0.1628 0.1579 KY Jul Sun 11,000,103 4,228,753 11,474,666 0.1184 0.1201 0.1199 KY Jul Mon 15,221,903 5,799,467 16,236,060 0.1639 0.1647 0.1696 KY Jul Tue 15,586,161 5,892,652 16,250,857 0.1678 0.1673 0.1698 KY Jul Wed 15,848,885 5,960,625 16,059,029 0.1707 0.1693 0.1678 KY Jul Thu 12,087,649 4,641,082 12,271,901 0.1302 0.1318 0.1282 KY Jul Fri 11,938,622 4,480,461 12,055,761 0.1286 0.1272 0.1260 KY Jul Sat 11,187,371 4,212,667 11,368,284 0.1205 0.1196 0.1188 KY Aug Sun 11,464,975 3,968,809 11,390,677 0.1188 0.1198 0.1209 KY Aug Mon 12,722,876 4,364,195 12,550,331 0.1318 0.1318 0.1332 KY Aug Tue 12,838,881 4,348,497 12,127,449 0.1330 0.1313 0.1287 KY Aug Wed 12,425,590 4,305,000 11,887,785 0.1288 0.1300 0.1262 KY Aug Thu 16,393,313 5,629,334 16,016,227 0.1699 0.1700 0.1700 KY Aug Fri 15,928,210 5,441,996 15,728,517 0.1651 0.1643 0.1669 KY Aug Sat 14,728,068 5,063,965 14,521,296 0.1526 0.1529 0.1541 KY Sep Sun 12,334,892 4,393,170 12,436,610 0.1501 0.1576 0.1542 KY Sep Mon 13,086,486 4,521,776 13,321,536 0.1592 0.1622 0.1652 KY Sep Tue 11,454,621 3,771,255 11,237,734 0.1394 0.1353 0.1394 KY Sep Wed 11,907,326 3,898,335 11,356,949 0.1449 0.1398 0.1408 KY Sep Thu 12,209,265 3,979,824 11,420,214 0.1485 0.1428 0.1416 KY Sep Fri 11,475,114 3,934,062 11,034,323 0.1396 0.1411 0.1368 KY Sep Sat 9,727,491 3,379,189 9,836,525 0.1183 0.1212 0.1220 KY Oct Sun 7,030,398 3,265,328 8,040,664 0.1131 0.1181 0.1170 KY Oct Mon 7,922,852 3,562,669 8,966,781 0.1274 0.1289 0.1304 KY Oct Tue 10,269,313 4,485,604 11,437,533 0.1651 0.1623 0.1664 KY Oct Wed 10,417,054 4,606,075 11,429,565 0.1675 0.1667 0.1663 KY Oct Thu 10,272,497 4,614,147 11,437,553 0.1652 0.1669 0.1664 KY Oct Fri 8,629,280 3,726,376 9,200,723 0.1388 0.1348 0.1338 KY Oct Sat 7,644,159 3,378,296 8,234,771 0.1229 0.1222 0.1198 KY Nov Sun 8,150,962 3,587,210 8,195,700 0.1275 0.1265 0.1236 KY Nov Mon 8,513,454 3,754,778 8,830,831 0.1331 0.1324 0.1332 KY Nov Tue 8,956,056 3,849,691 9,157,593 0.1401 0.1358 0.1381 KY Nov Wed 9,009,202 3,930,605 9,392,895 0.1409 0.1386 0.1417 KY Nov Thu 8,785,090 3,867,535 9,137,339 0.1374 0.1364 0.1378 KY Nov Fri 10,638,305 4,839,143 11,154,899 0.1664 0.1706 0.1683 KY Nov Sat 9,885,969 4,529,531 10,426,245 0.1546 0.1597 0.1573 KY Dec Sun 13,751,086 5,791,894 12,574,986 0.1555 0.1524 0.1544 KY Dec Mon 14,708,462 6,185,093 13,319,447 0.1663 0.1627 0.1635 KY Dec Tue 13,646,586 5,957,038 12,733,986 0.1543 0.1567 0.1563 KY Dec Wed 11,490,561 4,982,102 10,673,162 0.1299 0.1311 0.1310 KY Dec Thu 11,581,339 4,966,695 10,704,120 0.1310 0.1306 0.1314 KY Dec Fri 11,670,703 5,125,253 10,866,627 0.1320 0.1348 0.1334 KY Dec Sat 11,582,639 5,007,797 10,592,536 0.1310 0.1317 0.1300 MS Jan Sun 904,897 540,780 2,229,272 0.1127 0.1202 0.1193 MS Jan Mon 884,693 538,688 2,419,669 0.1102 0.1197 0.1294 MS Jan Tue 1,272,678 763,344 3,176,764 0.1585 0.1697 0.1699 MS Jan Wed 1,256,638 725,387 3,015,192 0.1565 0.1612 0.1613 MS Jan Thu 1,435,210 724,606 2,987,585 0.1787 0.1611 0.1598 MS Jan Fri 1,279,731 647,676 2,591,505 0.1593 0.1440 0.1386

C-6Atmospheric Sciences Group 

### Appendix C Actual 2002 State Level Monthly-Day of Week Profiles

CEM-Based Distribution Alpine Geophysics

SO2 Mass NOx Mass Heat Input State Month Day of Week [lbs] [lbs] [MMBtu] SO2 Ratio NOx Ratio Heat Input Actual Reported Values [2002] Calculated Ratios

MS Jan Sat 997,835 558,084 2,273,291 0.1242 0.1241 0.1216 MS Feb Sun 704,878 502,518 1,954,626 0.1349 0.1155 0.1155 MS Feb Mon 750,012 600,918 2,445,498 0.1436 0.1381 0.1445 MS Feb Tue 769,346 683,480 2,604,310 0.1473 0.1570 0.1539 MS Feb Wed 745,941 672,171 2,688,374 0.1428 0.1544 0.1589 MS Feb Thu 734,368 695,394 2,753,744 0.1406 0.1598 0.1628 MS Feb Fri 729,864 613,779 2,339,840 0.1397 0.1410 0.1383 MS Feb Sat 789,351 584,212 2,131,987 0.1511 0.1342 0.1260 MS Mar Sun 1,313,576 763,531 2,842,229 0.1475 0.1511 0.1455 MS Mar Mon 1,305,394 744,917 2,942,525 0.1466 0.1474 0.1507 MS Mar Tue 1,240,604 737,401 2,723,527 0.1393 0.1459 0.1395 MS Mar Wed 1,014,880 591,810 2,447,882 0.1140 0.1171 0.1253 MS Mar Thu 1,203,282 568,338 2,433,636 0.1351 0.1125 0.1246 MS Mar Fri 1,411,498 839,796 3,277,887 0.1585 0.1662 0.1679 MS Mar Sat 1,415,268 807,839 2,860,871 0.1589 0.1599 0.1465 MS Apr Sun 1,031,720 896,711 2,547,692 0.1215 0.1283 0.1183 MS Apr Mon 1,418,557 1,119,333 3,749,101 0.1671 0.1601 0.1741 MS Apr Tue 1,448,693 1,151,001 3,823,746 0.1706 0.1646 0.1775 MS Apr Wed 1,181,200 1,025,202 2,989,515 0.1391 0.1467 0.1388 MS Apr Thu 1,158,271 974,419 2,974,759 0.1364 0.1394 0.1381 MS Apr Fri 1,257,424 960,388 2,979,508 0.1481 0.1374 0.1383 MS Apr Sat 994,479 863,580 2,474,681 0.1171 0.1235 0.1149 MS May Sun 1,422,694 1,064,533 3,121,756 0.1214 0.1199 0.1178 MS May Mon 1,468,064 1,154,670 3,426,385 0.1253 0.1301 0.1293 MS May Tue 1,486,600 1,157,161 3,569,177 0.1269 0.1303 0.1347 MS May Wed 1,996,595 1,534,145 4,559,048 0.1704 0.1728 0.1721 MS May Thu 2,011,508 1,429,857 4,350,367 0.1717 0.1611 0.1642 MS May Fri 1,882,909 1,419,566 4,303,561 0.1607 0.1599 0.1624 MS May Sat 1,447,731 1,117,427 3,164,211 0.1236 0.1259 0.1194 MS Jun Sun 1,832,954 1,451,407 4,926,211 0.1564 0.1584 0.1523 MS Jun Mon 1,661,528 1,310,917 4,491,165 0.1418 0.1431 0.1388 MS Jun Tue 1,653,189 1,337,291 4,696,628 0.1411 0.1460 0.1452 MS Jun Wed 1,612,479 1,245,751 4,617,148 0.1376 0.1360 0.1427 MS Jun Thu 1,570,037 1,184,933 4,493,868 0.1340 0.1294 0.1389 MS Jun Fri 1,513,745 1,142,742 4,270,744 0.1292 0.1248 0.1320 MS Jun Sat 1,876,156 1,487,107 4,855,426 0.1601 0.1623 0.1501 MS Jul Sun 1,358,639 1,254,953 4,798,594 0.1270 0.1297 0.1219 MS Jul Mon 1,689,165 1,629,981 6,863,935 0.1579 0.1684 0.1744 MS Jul Tue 1,675,253 1,569,842 6,583,694 0.1566 0.1622 0.1673 MS Jul Wed 1,735,708 1,530,321 6,472,288 0.1622 0.1581 0.1645 MS Jul Thu 1,396,555 1,176,693 4,815,474 0.1305 0.1216 0.1224 MS Jul Fri 1,459,492 1,229,244 4,975,617 0.1364 0.1270 0.1264 MS Jul Sat 1,383,849 1,287,607 4,843,560 0.1293 0.1330 0.1231 MS Aug Sun 1,497,659 1,159,011 4,262,061 0.1223 0.1226 0.1191 MS Aug Mon 1,589,252 1,245,350 4,802,292 0.1298 0.1317 0.1342 MS Aug Tue 1,554,535 1,269,499 4,718,796 0.1269 0.1343 0.1319 MS Aug Wed 1,655,644 1,263,557 4,645,132 0.1352 0.1336 0.1298 MS Aug Thu 2,050,836 1,530,464 6,097,728 0.1674 0.1619 0.1704 MS Aug Fri 1,970,009 1,506,798 5,957,979 0.1608 0.1594 0.1665 MS Aug Sat 1,930,441 1,480,644 5,304,563 0.1576 0.1566 0.1482 MS Sep Sun 2,075,570 1,344,183 4,728,914 0.1558 0.1488 0.1466 MS Sep Mon 2,226,209 1,541,736 5,542,349 0.1672 0.1707 0.1718 MS Sep Tue 1,801,422 1,218,091 4,585,278 0.1353 0.1348 0.1421 MS Sep Wed 1,798,606 1,224,911 4,480,227 0.1350 0.1356 0.1389 MS Sep Thu 1,806,354 1,224,706 4,390,807 0.1356 0.1356 0.1361 MS Sep Fri 1,857,849 1,274,918 4,472,483 0.1395 0.1411 0.1386 MS Sep Sat 1,752,121 1,204,977 4,064,017 0.1316 0.1334 0.1260

C-7Atmospheric Sciences Group 

### Appendix C Actual 2002 State Level Monthly-Day of Week Profiles

CEM-Based Distribution Alpine Geophysics

SO2 Mass NOx Mass Heat Input State Month Day of Week [lbs] [lbs] [MMBtu] SO2 Ratio NOx Ratio Heat Input Actual Reported Values [2002] Calculated Ratios

MS Oct Sun 2,220,003 962,280 2,894,748 0.1422 0.1207 0.1190 MS Oct Mon 1,981,879 996,422 3,021,027 0.1270 0.1250 0.1242 MS Oct Tue 2,322,184 1,327,051 4,117,422 0.1488 0.1665 0.1693 MS Oct Wed 2,340,334 1,273,244 4,160,206 0.1500 0.1597 0.1711 MS Oct Thu 2,607,752 1,260,699 3,968,751 0.1671 0.1582 0.1632 MS Oct Fri 2,152,085 1,122,427 3,209,223 0.1379 0.1408 0.1320 MS Oct Sat 1,982,595 1,028,473 2,949,412 0.1270 0.1290 0.1213 MS Nov Sun 1,640,681 807,360 2,569,335 0.1361 0.1296 0.1256 MS Nov Mon 1,693,415 914,715 2,966,915 0.1405 0.1468 0.1450 MS Nov Tue 1,601,550 832,892 2,793,803 0.1328 0.1337 0.1366 MS Nov Wed 1,576,741 831,228 2,755,602 0.1308 0.1334 0.1347 MS Nov Thu 1,596,917 832,323 2,785,168 0.1325 0.1336 0.1361 MS Nov Fri 1,996,460 1,047,089 3,453,120 0.1656 0.1680 0.1688 MS Nov Sat 1,949,796 966,088 3,132,747 0.1617 0.1550 0.1531 MS Dec Sun 1,996,486 1,008,277 3,334,370 0.1482 0.1363 0.1459 MS Dec Mon 2,203,790 1,145,523 3,649,094 0.1636 0.1549 0.1597 MS Dec Tue 2,106,378 1,140,221 3,585,275 0.1564 0.1542 0.1569 MS Dec Wed 1,716,941 1,026,918 3,164,414 0.1275 0.1388 0.1385 MS Dec Thu 1,928,610 1,106,585 3,198,528 0.1432 0.1496 0.1400 MS Dec Fri 1,821,097 1,029,176 3,056,645 0.1352 0.1391 0.1338 MS Dec Sat 1,695,628 939,777 2,863,358 0.1259 0.1271 0.1253 NC Jan Sun 8,446,366 2,681,807 6,134,314 0.1124 0.1079 0.1097 NC Jan Mon 10,171,604 3,345,762 7,371,709 0.1354 0.1346 0.1319 NC Jan Tue 12,566,630 4,153,575 9,290,616 0.1673 0.1671 0.1662 NC Jan Wed 13,221,695 4,348,717 9,904,866 0.1760 0.1749 0.1772 NC Jan Thu 11,787,737 3,925,957 8,899,677 0.1569 0.1579 0.1592 NC Jan Fri 9,197,100 3,117,223 6,972,591 0.1224 0.1254 0.1247 NC Jan Sat 9,745,220 3,285,303 7,325,904 0.1297 0.1322 0.1311 NC Feb Sun 7,304,746 2,355,707 5,555,402 0.1166 0.1119 0.1156 NC Feb Mon 10,056,545 3,418,509 7,593,637 0.1606 0.1624 0.1580 NC Feb Tue 10,385,306 3,595,088 7,978,509 0.1658 0.1708 0.1660 NC Feb Wed 9,981,814 3,455,989 7,768,728 0.1594 0.1642 0.1616 NC Feb Thu 9,831,231 3,369,143 7,670,776 0.1570 0.1601 0.1596 NC Feb Fri 8,018,270 2,576,448 6,077,023 0.1280 0.1224 0.1264 NC Feb Sat 7,047,666 2,278,536 5,416,679 0.1125 0.1082 0.1127 NC Mar Sun 9,739,481 3,163,701 7,352,756 0.1273 0.1223 0.1256 NC Mar Mon 10,962,526 3,746,649 8,610,209 0.1433 0.1448 0.1471 NC Mar Tue 11,050,595 3,808,634 8,676,652 0.1444 0.1472 0.1482 NC Mar Wed 11,143,002 3,781,070 8,419,884 0.1456 0.1461 0.1439 NC Mar Thu 10,503,277 3,560,977 7,894,508 0.1373 0.1376 0.1349 NC Mar Fri 12,350,667 4,207,136 9,412,951 0.1614 0.1626 0.1608 NC Mar Sat 10,760,836 3,603,048 8,162,391 0.1406 0.1393 0.1395 NC Apr Sun 7,418,351 2,442,417 5,924,501 0.1149 0.1169 0.1156 NC Apr Mon 11,101,684 3,538,012 8,670,601 0.1720 0.1693 0.1692 NC Apr Tue 11,123,979 3,624,636 8,873,339 0.1723 0.1735 0.1731 NC Apr Wed 9,040,206 2,943,073 7,348,177 0.1401 0.1408 0.1434 NC Apr Thu 9,109,135 2,973,631 7,390,821 0.1411 0.1423 0.1442 NC Apr Fri 9,127,925 2,905,104 7,047,939 0.1414 0.1390 0.1375 NC Apr Sat 7,622,729 2,469,220 5,993,311 0.1181 0.1182 0.1169 NC May Sun 6,302,423 1,845,303 4,899,811 0.0950 0.0968 0.0972 NC May Mon 8,011,934 2,375,964 6,157,806 0.1207 0.1247 0.1222 NC May Tue 8,543,861 2,433,460 6,537,302 0.1287 0.1277 0.1297 NC May Wed 11,761,292 3,325,775 8,839,985 0.1772 0.1745 0.1754 NC May Thu 12,618,376 3,596,311 9,346,529 0.1901 0.1887 0.1854 NC May Fri 12,025,175 3,450,325 9,189,881 0.1812 0.1810 0.1823 NC May Sat 7,099,814 2,033,551 5,434,312 0.1070 0.1067 0.1078 NC Jun Sun 11,994,684 3,486,676 9,165,389 0.1413 0.1411 0.1387

C-8Atmospheric Sciences Group 

### Appendix C Actual 2002 State Level Monthly-Day of Week Profiles

CEM-Based Distribution Alpine Geophysics

SO2 Mass NOx Mass Heat Input State Month Day of Week [lbs] [lbs] [MMBtu] SO2 Ratio NOx Ratio Heat Input Actual Reported Values [2002] Calculated Ratios

NC Jun Mon 11,802,811 3,608,397 9,302,131 0.1391 0.1461 0.1408 NC Jun Tue 12,049,906 3,592,704 9,704,591 0.1420 0.1454 0.1469 NC Jun Wed 12,231,769 3,538,150 9,829,867 0.1441 0.1432 0.1488 NC Jun Thu 12,381,596 3,536,034 9,714,573 0.1459 0.1431 0.1470 NC Jun Fri 11,684,595 3,366,516 8,745,531 0.1377 0.1363 0.1324 NC Jun Sat 12,726,957 3,575,990 9,602,725 0.1500 0.1448 0.1454 NC Jul Sun 11,448,700 3,228,094 8,995,898 0.1177 0.1167 0.1152 NC Jul Mon 16,133,073 4,702,944 13,537,615 0.1659 0.1700 0.1734 NC Jul Tue 16,479,766 4,824,393 13,766,597 0.1694 0.1744 0.1763 NC Jul Wed 16,984,370 4,745,921 13,527,744 0.1746 0.1715 0.1732 NC Jul Thu 12,260,436 3,411,582 9,549,979 0.1260 0.1233 0.1223 NC Jul Fri 12,122,655 3,431,079 9,595,200 0.1246 0.1240 0.1229 NC Jul Sat 11,845,801 3,324,333 9,112,995 0.1218 0.1201 0.1167 NC Aug Sun 11,072,635 2,963,784 8,703,011 0.1210 0.1154 0.1184 NC Aug Mon 12,661,063 3,599,089 10,326,051 0.1383 0.1402 0.1404 NC Aug Tue 12,513,775 3,590,375 10,109,127 0.1367 0.1398 0.1375 NC Aug Wed 11,559,338 3,181,655 9,187,608 0.1263 0.1239 0.1250 NC Aug Thu 15,351,044 4,399,396 12,387,874 0.1677 0.1714 0.1685 NC Aug Fri 15,014,139 4,273,209 12,191,345 0.1641 0.1664 0.1658 NC Aug Sat 13,348,231 3,665,764 10,616,707 0.1459 0.1428 0.1444 NC Sep Sun 12,011,365 3,358,571 9,205,904 0.1409 0.1343 0.1379 NC Sep Mon 14,043,987 4,198,925 11,017,684 0.1647 0.1679 0.1651 NC Sep Tue 11,751,511 3,495,842 9,439,256 0.1378 0.1398 0.1414 NC Sep Wed 12,138,403 3,552,624 9,630,051 0.1424 0.1420 0.1443 NC Sep Thu 11,993,148 3,573,649 9,308,881 0.1407 0.1429 0.1395 NC Sep Fri 12,027,878 3,610,121 9,457,121 0.1411 0.1443 0.1417 NC Sep Sat 11,288,147 3,221,952 8,687,161 0.1324 0.1288 0.1302 NC Oct Sun 8,155,718 2,677,025 6,437,025 0.1074 0.1041 0.1057 NC Oct Mon 9,680,927 3,251,014 7,687,946 0.1274 0.1264 0.1263 NC Oct Tue 13,212,603 4,454,524 10,414,004 0.1739 0.1732 0.1711 NC Oct Wed 13,209,662 4,369,215 10,439,442 0.1739 0.1699 0.1715 NC Oct Thu 12,906,984 4,463,457 10,491,107 0.1699 0.1736 0.1723 NC Oct Fri 9,780,095 3,482,496 8,158,376 0.1287 0.1354 0.1340 NC Oct Sat 9,018,864 3,017,679 7,252,836 0.1187 0.1173 0.1191 NC Nov Sun 7,482,715 2,561,724 5,927,852 0.1064 0.1047 0.1073 NC Nov Mon 9,596,784 3,288,922 7,495,268 0.1364 0.1344 0.1356 NC Nov Tue 10,365,457 3,623,153 8,194,564 0.1474 0.1481 0.1483 NC Nov Wed 10,225,631 3,596,784 8,059,773 0.1454 0.1470 0.1459 NC Nov Thu 9,964,891 3,504,538 7,895,958 0.1417 0.1432 0.1429 NC Nov Fri 12,363,616 4,334,489 9,634,353 0.1758 0.1771 0.1743 NC Nov Sat 10,336,370 3,559,744 8,051,239 0.1470 0.1455 0.1457 NC Dec Sun 10,688,597 3,665,976 8,147,974 0.1414 0.1387 0.1395 NC Dec Mon 11,982,304 4,325,079 9,419,769 0.1585 0.1636 0.1613 NC Dec Tue 12,467,509 4,340,982 9,585,056 0.1649 0.1642 0.1641 NC Dec Wed 11,024,801 3,814,348 8,498,463 0.1459 0.1443 0.1455 NC Dec Thu 10,051,949 3,533,212 7,913,104 0.1330 0.1337 0.1355 NC Dec Fri 9,810,173 3,482,215 7,703,877 0.1298 0.1317 0.1319 NC Dec Sat 9,559,625 3,271,310 7,140,253 0.1265 0.1238 0.1222 SC Jan Sun 3,636,970 1,476,366 3,944,497 0.1170 0.1186 0.1230 SC Jan Mon 3,942,696 1,560,978 4,121,987 0.1268 0.1254 0.1285 SC Jan Tue 5,151,041 2,079,859 5,256,067 0.1657 0.1671 0.1639 SC Jan Wed 5,259,530 2,160,283 5,399,384 0.1692 0.1736 0.1684 SC Jan Thu 4,997,169 1,988,044 5,097,835 0.1608 0.1597 0.1590 SC Jan Fri 4,044,225 1,554,409 4,086,561 0.1301 0.1249 0.1274 SC Jan Sat 4,050,417 1,627,503 4,164,747 0.1303 0.1307 0.1299 SC Feb Sun 3,505,008 1,568,059 3,903,760 0.1269 0.1304 0.1329 SC Feb Mon 4,069,438 1,751,384 4,190,347 0.1474 0.1457 0.1427

C-9Atmospheric Sciences Group 

### Appendix C Actual 2002 State Level Monthly-Day of Week Profiles

CEM-Based Distribution Alpine Geophysics

SO2 Mass NOx Mass Heat Input State Month Day of Week [lbs] [lbs] [MMBtu] SO2 Ratio NOx Ratio Heat Input Actual Reported Values [2002] Calculated Ratios

SC Feb Tue 4,430,044 1,863,072 4,448,544 0.1604 0.1550 0.1515 SC Feb Wed 4,318,396 1,855,284 4,505,578 0.1564 0.1543 0.1534 SC Feb Thu 4,205,690 1,845,750 4,471,557 0.1523 0.1535 0.1522 SC Feb Fri 3,624,500 1,603,802 3,987,755 0.1312 0.1334 0.1358 SC Feb Sat 3,463,086 1,535,008 3,864,784 0.1254 0.1277 0.1316 SC Mar Sun 4,336,524 1,973,802 4,537,629 0.1409 0.1436 0.1422 SC Mar Mon 4,183,356 1,816,900 4,262,600 0.1359 0.1322 0.1335 SC Mar Tue 4,240,162 1,866,062 4,468,803 0.1377 0.1357 0.1400 SC Mar Wed 4,254,321 1,846,213 4,300,152 0.1382 0.1343 0.1347 SC Mar Thu 4,145,005 1,864,218 4,245,007 0.1346 0.1356 0.1330 SC Mar Fri 5,182,524 2,287,889 5,306,269 0.1683 0.1664 0.1662 SC Mar Sat 4,444,143 2,093,609 4,798,881 0.1444 0.1523 0.1503 SC Apr Sun 4,017,490 1,649,192 4,084,689 0.1304 0.1264 0.1281 SC Apr Mon 5,125,101 2,150,863 5,324,631 0.1664 0.1648 0.1670 SC Apr Tue 4,979,358 2,126,442 5,184,660 0.1616 0.1629 0.1626 SC Apr Wed 4,233,850 1,773,496 4,320,385 0.1374 0.1359 0.1355 SC Apr Thu 4,229,100 1,837,077 4,399,336 0.1373 0.1408 0.1380 SC Apr Fri 4,300,860 1,827,319 4,422,361 0.1396 0.1400 0.1387 SC Apr Sat 3,922,816 1,687,315 4,145,150 0.1273 0.1293 0.1300 SC May Sun 4,058,982 1,768,790 4,629,139 0.1216 0.1216 0.1211 SC May Mon 4,369,970 1,898,496 4,968,000 0.1309 0.1306 0.1300 SC May Tue 4,205,508 1,822,100 4,774,535 0.1260 0.1253 0.1249 SC May Wed 5,327,689 2,312,421 6,085,422 0.1596 0.1590 0.1592 SC May Thu 5,552,853 2,407,456 6,467,533 0.1664 0.1656 0.1692 SC May Fri 5,710,821 2,482,088 6,611,345 0.1711 0.1707 0.1730 SC May Sat 4,153,912 1,849,484 4,688,413 0.1244 0.1272 0.1227 SC Jun Sun 5,422,310 2,325,012 5,940,742 0.1487 0.1520 0.1454 SC Jun Mon 4,950,283 2,099,485 5,639,270 0.1358 0.1373 0.1381 SC Jun Tue 5,193,496 2,170,648 5,935,461 0.1425 0.1419 0.1453 SC Jun Wed 5,212,633 2,181,658 6,016,294 0.1430 0.1426 0.1473 SC Jun Thu 5,085,180 2,111,423 5,811,622 0.1395 0.1380 0.1423 SC Jun Fri 4,963,259 2,031,580 5,346,414 0.1361 0.1328 0.1309 SC Jun Sat 5,627,924 2,375,174 6,154,533 0.1544 0.1553 0.1507 SC Jul Sun 4,952,032 2,105,431 5,426,837 0.1213 0.1233 0.1193 SC Jul Mon 6,752,415 2,802,511 7,673,334 0.1653 0.1641 0.1687 SC Jul Tue 6,809,749 2,824,594 7,748,669 0.1668 0.1654 0.1703 SC Jul Wed 6,874,946 2,798,981 7,695,441 0.1683 0.1639 0.1692 SC Jul Thu 5,251,525 2,201,617 5,760,574 0.1286 0.1289 0.1266 SC Jul Fri 5,212,751 2,210,808 5,700,322 0.1276 0.1294 0.1253 SC Jul Sat 4,984,418 2,138,308 5,483,132 0.1221 0.1252 0.1205 SC Aug Sun 4,857,872 1,938,847 5,355,760 0.1256 0.1244 0.1252 SC Aug Mon 5,119,566 2,068,536 5,777,624 0.1324 0.1327 0.1350 SC Aug Tue 5,066,437 2,036,102 5,681,494 0.1310 0.1306 0.1328 SC Aug Wed 5,172,581 2,034,297 5,579,938 0.1337 0.1305 0.1304 SC Aug Thu 6,236,009 2,453,044 6,793,190 0.1612 0.1573 0.1588 SC Aug Fri 6,262,985 2,595,706 6,994,996 0.1619 0.1665 0.1635 SC Aug Sat 5,961,282 2,465,312 6,607,305 0.1541 0.1581 0.1544 SC Sep Sun 5,498,826 2,178,099 5,470,366 0.1541 0.1541 0.1517 SC Sep Mon 5,960,568 2,369,286 5,977,253 0.1671 0.1677 0.1658 SC Sep Tue 4,801,579 1,876,836 4,973,585 0.1346 0.1328 0.1379 SC Sep Wed 4,883,651 1,904,108 5,127,470 0.1369 0.1347 0.1422 SC Sep Thu 4,971,406 1,973,186 5,012,399 0.1393 0.1396 0.1390 SC Sep Fri 4,849,982 1,939,577 4,839,884 0.1359 0.1373 0.1342 SC Sep Sat 4,713,661 1,890,509 4,656,981 0.1321 0.1338 0.1292 SC Oct Sun 3,474,565 1,447,631 3,546,049 0.1150 0.1186 0.1195 SC Oct Mon 3,731,594 1,539,738 3,703,080 0.1235 0.1262 0.1248 SC Oct Tue 5,047,781 1,994,340 4,807,363 0.1671 0.1635 0.1620

C-10Atmospheric Sciences Group 

### Appendix C Actual 2002 State Level Monthly-Day of Week Profiles

CEM-Based Distribution Alpine Geophysics

SO2 Mass NOx Mass Heat Input State Month Day of Week [lbs] [lbs] [MMBtu] SO2 Ratio NOx Ratio Heat Input Actual Reported Values [2002] Calculated Ratios

SC Oct Wed 5,129,931 2,032,331 4,942,086 0.1698 0.1666 0.1665 SC Oct Thu 5,248,856 2,061,315 4,976,570 0.1737 0.1689 0.1677 SC Oct Fri 3,999,885 1,628,467 4,041,772 0.1324 0.1335 0.1362 SC Oct Sat 3,581,077 1,497,082 3,666,423 0.1185 0.1227 0.1235 SC Nov Sun 3,600,924 1,476,229 3,448,462 0.1256 0.1258 0.1260 SC Nov Mon 3,687,208 1,524,774 3,579,756 0.1286 0.1299 0.1308 SC Nov Tue 3,880,976 1,573,954 3,696,134 0.1353 0.1341 0.1350 SC Nov Wed 3,868,341 1,582,952 3,670,084 0.1349 0.1349 0.1341 SC Nov Thu 3,956,142 1,625,215 3,755,471 0.1380 0.1385 0.1372 SC Nov Fri 4,948,051 2,026,053 4,752,479 0.1725 0.1726 0.1736 SC Nov Sat 4,736,198 1,927,582 4,466,927 0.1652 0.1642 0.1632 SC Dec Sun 5,391,234 2,143,010 5,049,728 0.1585 0.1536 0.1536 SC Dec Mon 5,548,299 2,290,764 5,366,100 0.1631 0.1642 0.1632 SC Dec Tue 5,480,807 2,216,128 5,356,259 0.1611 0.1588 0.1629 SC Dec Wed 4,622,930 1,853,300 4,391,836 0.1359 0.1328 0.1336 SC Dec Thu 4,440,114 1,871,504 4,393,124 0.1305 0.1341 0.1336 SC Dec Fri 4,181,951 1,765,482 4,128,271 0.1229 0.1265 0.1256 SC Dec Sat 4,357,292 1,811,023 4,190,308 0.1281 0.1298 0.1275 TN Jan Sun 7,151,423 3,277,424 6,179,940 0.1278 0.1237 0.1223 TN Jan Mon 7,106,220 3,226,742 6,301,100 0.1270 0.1218 0.1247 TN Jan Tue 8,852,906 4,256,829 8,158,335 0.1582 0.1607 0.1615 TN Jan Wed 8,794,062 4,368,528 8,265,550 0.1571 0.1649 0.1636 TN Jan Thu 8,948,768 4,340,296 8,335,659 0.1599 0.1638 0.1650 TN Jan Fri 7,598,313 3,605,119 6,880,280 0.1358 0.1361 0.1362 TN Jan Sat 7,510,899 3,415,776 6,396,355 0.1342 0.1289 0.1266 TN Feb Sun 6,639,711 3,313,368 6,378,482 0.1334 0.1319 0.1321 TN Feb Mon 7,275,325 3,618,611 6,948,514 0.1462 0.1441 0.1440 TN Feb Tue 7,277,165 3,684,542 7,067,758 0.1462 0.1467 0.1464 TN Feb Wed 7,251,055 3,660,125 7,093,264 0.1457 0.1458 0.1470 TN Feb Thu 7,367,583 3,746,576 7,227,135 0.1480 0.1492 0.1497 TN Feb Fri 7,029,233 3,684,932 6,981,685 0.1412 0.1467 0.1446 TN Feb Sat 6,932,900 3,403,070 6,572,031 0.1393 0.1355 0.1362 TN Mar Sun 8,164,525 4,299,233 8,212,236 0.1515 0.1547 0.1527 TN Mar Mon 7,166,283 3,645,887 7,289,591 0.1330 0.1312 0.1356 TN Mar Tue 7,154,085 3,699,328 7,142,489 0.1328 0.1331 0.1328 TN Mar Wed 7,162,657 3,629,929 7,104,015 0.1329 0.1306 0.1321 TN Mar Thu 7,191,347 3,577,816 6,909,033 0.1334 0.1288 0.1285 TN Mar Fri 8,858,548 4,552,595 8,820,839 0.1644 0.1638 0.1640 TN Mar Sat 8,191,006 4,381,492 8,295,199 0.1520 0.1577 0.1543 TN Apr Sun 6,738,807 3,413,870 6,820,527 0.1256 0.1267 0.1271 TN Apr Mon 8,702,386 4,493,505 8,874,848 0.1623 0.1668 0.1654 TN Apr Tue 9,096,288 4,547,297 9,064,902 0.1696 0.1688 0.1689 TN Apr Wed 7,240,318 3,711,499 7,315,348 0.1350 0.1377 0.1363 TN Apr Thu 7,480,487 3,660,029 7,384,760 0.1395 0.1358 0.1376 TN Apr Fri 7,415,532 3,611,558 7,183,531 0.1383 0.1340 0.1338 TN Apr Sat 6,961,705 3,506,357 7,025,087 0.1298 0.1301 0.1309 TN May Sun 6,310,558 3,129,930 6,706,450 0.1173 0.1194 0.1211 TN May Mon 6,708,857 3,342,190 7,078,696 0.1247 0.1275 0.1278 TN May Tue 7,132,449 3,470,921 7,312,958 0.1326 0.1324 0.1320 TN May Wed 9,272,405 4,464,382 9,471,156 0.1724 0.1703 0.1710 TN May Thu 9,008,800 4,305,927 9,106,279 0.1675 0.1643 0.1644 TN May Fri 8,685,462 4,265,685 8,918,043 0.1615 0.1627 0.1610 TN May Sat 6,674,510 3,232,563 6,803,853 0.1241 0.1233 0.1228 TN Jun Sun 9,319,933 4,709,925 9,500,878 0.1605 0.1626 0.1578 TN Jun Mon 7,841,052 3,833,472 8,260,443 0.1350 0.1324 0.1372 TN Jun Tue 8,046,824 3,892,653 8,267,340 0.1385 0.1344 0.1373 TN Jun Wed 8,115,635 3,924,083 8,181,840 0.1397 0.1355 0.1359

C-11Atmospheric Sciences Group 

### Appendix C Actual 2002 State Level Monthly-Day of Week Profiles

CEM-Based Distribution Alpine Geophysics

SO2 Mass NOx Mass Heat Input State Month Day of Week [lbs] [lbs] [MMBtu] SO2 Ratio NOx Ratio Heat Input Actual Reported Values [2002] Calculated Ratios

TN Jun Thu 7,908,747 3,897,867 8,264,116 0.1362 0.1346 0.1373 TN Jun Fri 7,440,089 3,934,565 8,020,227 0.1281 0.1359 0.1332 TN Jun Sat 9,411,612 4,768,219 9,710,283 0.1620 0.1646 0.1613 TN Jul Sun 7,774,543 3,623,011 7,974,059 0.1240 0.1220 0.1222 TN Jul Mon 10,307,744 4,999,148 11,264,465 0.1644 0.1684 0.1726 TN Jul Tue 10,464,081 5,093,362 11,321,319 0.1668 0.1716 0.1735 TN Jul Wed 10,596,757 5,070,165 11,084,819 0.1690 0.1708 0.1699 TN Jul Thu 8,064,229 3,736,165 8,023,553 0.1286 0.1259 0.1229 TN Jul Fri 7,890,085 3,649,213 7,881,373 0.1258 0.1229 0.1208 TN Jul Sat 7,618,834 3,514,621 7,710,530 0.1215 0.1184 0.1182 TN Aug Sun 8,174,467 3,845,977 8,115,355 0.1263 0.1255 0.1233 TN Aug Mon 8,399,769 3,946,405 8,671,939 0.1298 0.1287 0.1317 TN Aug Tue 8,539,977 4,068,471 8,665,993 0.1319 0.1327 0.1316 TN Aug Wed 8,532,687 4,082,232 8,596,692 0.1318 0.1332 0.1306 TN Aug Thu 10,531,971 4,969,209 10,880,135 0.1627 0.1621 0.1652 TN Aug Fri 10,402,230 4,923,961 10,609,855 0.1607 0.1606 0.1611 TN Aug Sat 10,151,492 4,820,052 10,304,247 0.1568 0.1572 0.1565 TN Sep Sun 9,116,699 4,077,524 8,671,313 0.1647 0.1618 0.1598 TN Sep Mon 9,469,339 4,198,698 9,160,298 0.1710 0.1666 0.1688 TN Sep Tue 7,829,458 3,581,195 7,726,770 0.1414 0.1421 0.1424 TN Sep Wed 7,343,362 3,488,344 7,362,144 0.1326 0.1384 0.1357 TN Sep Thu 7,301,205 3,426,916 7,270,427 0.1319 0.1360 0.1340 TN Sep Fri 7,193,620 3,320,429 7,187,551 0.1299 0.1317 0.1324 TN Sep Sat 7,110,260 3,110,608 6,888,784 0.1284 0.1234 0.1269 TN Oct Sun 6,708,010 2,833,598 5,647,137 0.1224 0.1267 0.1248 TN Oct Mon 7,342,244 3,079,627 6,044,894 0.1339 0.1377 0.1336 TN Oct Tue 8,702,014 3,502,606 7,163,112 0.1587 0.1566 0.1583 TN Oct Wed 8,873,754 3,587,670 7,418,539 0.1619 0.1604 0.1640 TN Oct Thu 8,965,902 3,612,495 7,272,597 0.1636 0.1615 0.1608 TN Oct Fri 7,181,995 2,835,539 5,852,668 0.1310 0.1268 0.1294 TN Oct Sat 7,042,051 2,910,409 5,838,274 0.1285 0.1302 0.1291 TN Nov Sun 6,634,653 2,977,876 5,712,119 0.1264 0.1298 0.1278 TN Nov Mon 6,868,040 2,986,966 5,856,205 0.1309 0.1302 0.1310 TN Nov Tue 6,912,082 3,014,858 5,895,146 0.1317 0.1314 0.1319 TN Nov Wed 7,386,472 3,138,730 6,180,765 0.1408 0.1368 0.1383 TN Nov Thu 7,266,754 3,137,786 6,131,963 0.1385 0.1368 0.1372 TN Nov Fri 8,736,435 3,862,733 7,534,521 0.1665 0.1684 0.1685 TN Nov Sat 8,669,349 3,822,128 7,393,534 0.1652 0.1666 0.1654 TN Dec Sun 9,120,079 3,928,257 7,327,683 0.1552 0.1549 0.1510 TN Dec Mon 9,492,230 3,968,058 7,741,356 0.1616 0.1565 0.1595 TN Dec Tue 9,136,375 3,894,752 7,595,049 0.1555 0.1536 0.1565 TN Dec Wed 7,742,072 3,388,273 6,504,259 0.1318 0.1336 0.1340 TN Dec Thu 7,732,612 3,400,001 6,571,263 0.1316 0.1341 0.1354 TN Dec Fri 7,885,726 3,475,255 6,579,511 0.1342 0.1371 0.1356 TN Dec Sat 7,640,994 3,297,372 6,208,895 0.1301 0.1301 0.1279 VA Jan Sun 4,671,075 1,627,775 4,289,396 0.1214 0.1172 0.1201 VA Jan Mon 5,127,288 1,888,213 4,792,953 0.1333 0.1360 0.1342 VA Jan Tue 6,288,913 2,330,010 5,917,567 0.1635 0.1678 0.1656 VA Jan Wed 6,426,139 2,349,164 5,998,072 0.1670 0.1692 0.1679 VA Jan Thu 6,087,252 2,199,341 5,596,030 0.1582 0.1584 0.1566 VA Jan Fri 4,942,574 1,758,916 4,611,180 0.1285 0.1267 0.1291 VA Jan Sat 4,931,872 1,730,649 4,521,767 0.1282 0.1246 0.1266 VA Feb Sun 4,661,072 1,603,715 3,882,421 0.1286 0.1262 0.1240 VA Feb Mon 5,294,467 1,854,921 4,541,253 0.1461 0.1460 0.1450 VA Feb Tue 5,544,956 1,997,045 4,953,922 0.1530 0.1571 0.1582 VA Feb Wed 5,493,596 1,936,049 4,814,990 0.1516 0.1523 0.1537 VA Feb Thu 5,623,211 1,961,653 4,981,039 0.1551 0.1544 0.1590

C-12Atmospheric Sciences Group 

### Appendix C Actual 2002 State Level Monthly-Day of Week Profiles

CEM-Based Distribution Alpine Geophysics

SO2 Mass NOx Mass Heat Input State Month Day of Week [lbs] [lbs] [MMBtu] SO2 Ratio NOx Ratio Heat Input Actual Reported Values [2002] Calculated Ratios

VA Feb Fri 5,164,652 1,819,180 4,435,077 0.1425 0.1432 0.1416 VA Feb Sat 4,464,327 1,535,416 3,710,148 0.1232 0.1208 0.1185 VA Mar Sun 4,771,702 1,689,644 4,031,521 0.1383 0.1406 0.1417 VA Mar Mon 4,673,869 1,659,957 3,933,598 0.1355 0.1382 0.1383 VA Mar Tue 4,912,351 1,712,399 4,076,583 0.1424 0.1425 0.1433 VA Mar Wed 4,539,833 1,611,426 3,835,600 0.1316 0.1341 0.1348 VA Mar Thu 4,608,329 1,571,027 3,657,444 0.1336 0.1308 0.1286 VA Mar Fri 5,913,571 2,012,689 4,756,675 0.1714 0.1675 0.1672 VA Mar Sat 5,073,380 1,756,992 4,153,709 0.1471 0.1462 0.1460 VA Apr Sun 3,934,246 1,285,481 3,053,611 0.1169 0.1096 0.1105 VA Apr Mon 5,487,481 1,952,750 4,544,203 0.1630 0.1665 0.1644 VA Apr Tue 5,689,972 2,001,568 4,733,486 0.1691 0.1707 0.1713 VA Apr Wed 4,875,005 1,730,770 4,111,619 0.1448 0.1476 0.1488 VA Apr Thu 4,882,307 1,719,776 4,095,300 0.1451 0.1467 0.1482 VA Apr Fri 4,773,451 1,670,964 3,904,637 0.1418 0.1425 0.1413 VA Apr Sat 4,015,919 1,364,434 3,196,561 0.1193 0.1164 0.1157 VA May Sun 3,218,291 1,163,169 2,909,963 0.1071 0.1043 0.1068 VA May Mon 3,852,292 1,404,101 3,460,786 0.1282 0.1258 0.1270 VA May Tue 4,028,549 1,542,377 3,718,889 0.1340 0.1382 0.1365 VA May Wed 5,065,619 1,882,276 4,450,655 0.1685 0.1687 0.1634 VA May Thu 5,218,813 1,929,634 4,651,484 0.1736 0.1730 0.1708 VA May Fri 5,113,973 1,935,832 4,824,797 0.1701 0.1735 0.1771 VA May Sat 3,561,226 1,299,755 3,224,466 0.1185 0.1165 0.1184 VA Jun Sun 5,918,371 1,954,176 5,228,149 0.1464 0.1472 0.1444 VA Jun Mon 5,380,536 1,858,027 5,033,669 0.1331 0.1400 0.1390 VA Jun Tue 5,741,465 1,910,216 5,231,137 0.1420 0.1439 0.1445 VA Jun Wed 5,844,449 1,938,523 5,480,711 0.1445 0.1460 0.1514 VA Jun Thu 5,888,810 1,926,866 5,360,703 0.1456 0.1452 0.1481 VA Jun Fri 5,444,340 1,697,644 4,586,981 0.1346 0.1279 0.1267 VA Jun Sat 6,216,252 1,987,961 5,286,607 0.1537 0.1498 0.1460 VA Jul Sun 5,618,750 1,698,805 4,978,472 0.1202 0.1132 0.1146 VA Jul Mon 7,735,624 2,576,732 7,511,844 0.1655 0.1717 0.1729 VA Jul Tue 7,964,202 2,674,568 7,864,148 0.1704 0.1782 0.1810 VA Jul Wed 8,008,050 2,551,626 7,541,354 0.1713 0.1700 0.1736 VA Jul Thu 6,087,237 1,963,497 5,580,009 0.1302 0.1308 0.1284 VA Jul Fri 5,780,446 1,875,879 5,270,813 0.1237 0.1250 0.1213 VA Jul Sat 5,548,321 1,669,481 4,703,724 0.1187 0.1112 0.1083 VA Aug Sun 5,942,163 1,945,966 5,528,807 0.1217 0.1258 0.1262 VA Aug Mon 6,544,591 2,183,768 6,273,049 0.1340 0.1411 0.1432 VA Aug Tue 6,430,299 2,089,827 5,843,290 0.1317 0.1351 0.1334 VA Aug Wed 6,337,564 1,935,351 5,454,543 0.1298 0.1251 0.1245 VA Aug Thu 7,906,645 2,450,182 6,995,583 0.1619 0.1583 0.1597 VA Aug Fri 8,036,876 2,519,734 7,102,004 0.1646 0.1628 0.1621 VA Aug Sat 7,626,348 2,348,614 6,605,314 0.1562 0.1518 0.1508 VA Sep Sun 6,151,617 1,978,118 4,929,060 0.1595 0.1553 0.1522 VA Sep Mon 6,566,603 2,133,784 5,391,407 0.1702 0.1675 0.1664 VA Sep Tue 5,365,799 1,794,621 4,651,991 0.1391 0.1409 0.1436 VA Sep Wed 5,465,825 1,804,007 4,743,694 0.1417 0.1416 0.1464 VA Sep Thu 5,045,993 1,717,372 4,362,899 0.1308 0.1348 0.1347 VA Sep Fri 5,033,204 1,678,732 4,222,150 0.1305 0.1318 0.1303 VA Sep Sat 4,946,295 1,630,991 4,092,060 0.1282 0.1280 0.1263 VA Oct Sun 3,692,119 1,251,585 3,100,156 0.1090 0.1056 0.1086 VA Oct Mon 4,206,900 1,484,768 3,550,480 0.1242 0.1253 0.1244 VA Oct Tue 5,577,237 1,958,392 4,648,356 0.1647 0.1653 0.1629 VA Oct Wed 5,640,810 1,985,068 4,767,390 0.1665 0.1675 0.1671 VA Oct Thu 5,918,145 2,042,093 4,932,204 0.1747 0.1723 0.1728 VA Oct Fri 4,677,931 1,668,985 3,951,402 0.1381 0.1408 0.1385

C-13Atmospheric Sciences Group 

### Appendix C Actual 2002 State Level Monthly-Day of Week Profiles

CEM-Based Distribution Alpine Geophysics

SO2 Mass NOx Mass Heat Input State Month Day of Week [lbs] [lbs] [MMBtu] SO2 Ratio NOx Ratio Heat Input Actual Reported Values [2002] Calculated Ratios

VA Oct Sat 4,157,525 1,459,285 3,587,092 0.1227 0.1231 0.1257 VA Nov Sun 4,220,213 1,431,590 3,617,607 0.1190 0.1152 0.1210 VA Nov Mon 4,891,550 1,737,603 4,153,022 0.1379 0.1399 0.1390 VA Nov Tue 5,029,654 1,788,688 4,263,728 0.1418 0.1440 0.1427 VA Nov Wed 4,952,524 1,733,240 4,099,073 0.1396 0.1395 0.1372 VA Nov Thu 4,840,374 1,663,470 3,976,369 0.1365 0.1339 0.1330 VA Nov Fri 5,923,766 2,111,331 5,016,854 0.1670 0.1699 0.1679 VA Nov Sat 5,615,042 1,957,581 4,759,820 0.1583 0.1576 0.1593 VA Dec Sun 6,746,456 2,206,423 5,350,646 0.1505 0.1426 0.1463 VA Dec Mon 7,125,574 2,493,055 5,902,703 0.1589 0.1611 0.1614 VA Dec Tue 7,232,167 2,512,962 5,984,967 0.1613 0.1624 0.1636 VA Dec Wed 6,074,987 2,139,652 5,051,424 0.1355 0.1382 0.1381 VA Dec Thu 5,954,834 2,128,843 4,939,470 0.1328 0.1375 0.1350 VA Dec Fri 5,915,700 2,055,015 4,810,763 0.1319 0.1328 0.1315 VA Dec Sat 5,789,687 1,941,279 4,543,164 0.1291 0.1254 0.1242 WV Jan Sun 11,362,417 4,706,298 9,184,827 0.1172 0.1119 0.1161 WV Jan Mon 12,746,157 5,609,443 10,329,318 0.1315 0.1334 0.1306 WV Jan Tue 16,025,452 6,936,712 12,928,984 0.1653 0.1650 0.1635 WV Jan Wed 16,587,904 7,210,448 13,412,571 0.1711 0.1715 0.1696 WV Jan Thu 15,888,932 7,111,818 13,366,382 0.1639 0.1692 0.1690 WV Jan Fri 12,499,459 5,419,092 10,203,801 0.1289 0.1289 0.1290 WV Jan Sat 11,834,473 5,050,631 9,666,967 0.1221 0.1201 0.1222 WV Feb Sun 9,761,299 4,892,152 9,703,703 0.1189 0.1216 0.1288 WV Feb Mon 12,044,491 6,038,110 11,178,623 0.1467 0.1501 0.1483 WV Feb Tue 12,832,974 6,116,505 11,350,011 0.1563 0.1520 0.1506 WV Feb Wed 12,896,606 6,141,238 11,321,181 0.1570 0.1526 0.1502 WV Feb Thu 12,943,440 6,145,521 11,332,231 0.1576 0.1527 0.1504 WV Feb Fri 11,297,042 5,729,243 10,551,962 0.1376 0.1424 0.1400 WV Feb Sat 10,344,006 5,173,626 9,925,582 0.1260 0.1286 0.1317 WV Mar Sun 11,411,568 5,522,778 10,810,556 0.1422 0.1400 0.1448 WV Mar Mon 11,185,040 5,704,666 10,255,251 0.1394 0.1446 0.1374 WV Mar Tue 10,875,143 5,424,842 10,034,164 0.1355 0.1375 0.1344 WV Mar Wed 11,063,397 5,350,789 10,059,659 0.1378 0.1356 0.1347 WV Mar Thu 10,804,359 5,341,667 10,059,216 0.1346 0.1354 0.1347 WV Mar Fri 12,999,519 6,389,171 12,235,557 0.1620 0.1620 0.1639 WV Mar Sat 11,926,532 5,715,649 11,200,817 0.1486 0.1449 0.1500 WV Apr Sun 8,230,926 4,008,590 7,520,679 0.1116 0.1103 0.1144 WV Apr Mon 13,019,560 6,516,027 11,564,401 0.1765 0.1792 0.1758 WV Apr Tue 13,421,803 6,624,951 11,914,166 0.1819 0.1822 0.1812 WV Apr Wed 10,288,018 5,090,179 9,209,586 0.1395 0.1400 0.1400 WV Apr Thu 10,413,172 5,023,528 9,062,366 0.1412 0.1382 0.1378 WV Apr Fri 9,902,694 4,928,496 8,726,917 0.1342 0.1356 0.1327 WV Apr Sat 8,495,137 4,163,034 7,770,368 0.1152 0.1145 0.1181 WV May Sun 8,306,339 2,944,167 7,996,162 0.1068 0.0991 0.1120 WV May Mon 10,130,014 3,834,464 9,355,254 0.1303 0.1291 0.1310 WV May Tue 10,407,395 4,128,373 9,758,847 0.1339 0.1390 0.1367 WV May Wed 13,266,098 5,204,946 11,969,899 0.1706 0.1752 0.1677 WV May Thu 13,398,522 5,207,201 12,053,920 0.1723 0.1753 0.1688 WV May Fri 13,674,556 5,093,689 12,138,618 0.1759 0.1715 0.1700 WV May Sat 8,567,825 3,288,016 8,117,837 0.1102 0.1107 0.1137 WV Jun Sun 12,605,642 5,081,170 11,780,562 0.1548 0.1527 0.1540 WV Jun Mon 11,290,645 4,540,816 10,591,380 0.1386 0.1364 0.1385 WV Jun Tue 11,610,911 4,595,418 10,739,527 0.1426 0.1381 0.1404 WV Jun Wed 11,368,121 4,657,261 10,615,897 0.1396 0.1399 0.1388 WV Jun Thu 11,062,252 4,695,347 10,545,153 0.1358 0.1411 0.1379 WV Jun Fri 10,791,181 4,515,861 10,203,905 0.1325 0.1357 0.1334 WV Jun Sat 12,714,677 5,195,557 12,018,233 0.1561 0.1561 0.1571

C-14Atmospheric Sciences Group 

### Appendix C Actual 2002 State Level Monthly-Day of Week Profiles

CEM-Based Distribution Alpine Geophysics

SO2 Mass NOx Mass Heat Input State Month Day of Week [lbs] [lbs] [MMBtu] SO2 Ratio NOx Ratio Heat Input Actual Reported Values [2002] Calculated Ratios

WV Jul Sun 10,897,546 4,532,340 10,352,667 0.1175 0.1219 0.1213 WV Jul Mon 15,472,405 6,114,793 14,028,539 0.1669 0.1645 0.1644 WV Jul Tue 15,799,247 6,415,584 14,425,103 0.1704 0.1726 0.1691 WV Jul Wed 15,507,068 6,193,792 14,322,772 0.1672 0.1666 0.1679 WV Jul Thu 12,372,989 4,863,245 11,133,926 0.1334 0.1308 0.1305 WV Jul Fri 12,071,926 4,767,363 10,919,490 0.1302 0.1282 0.1280 WV Jul Sat 10,600,364 4,287,577 10,140,273 0.1143 0.1153 0.1188 WV Aug Sun 11,656,231 4,162,352 9,827,247 0.1284 0.1192 0.1228 WV Aug Mon 12,809,925 4,830,501 10,895,778 0.1411 0.1383 0.1362 WV Aug Tue 11,776,614 4,749,439 10,679,474 0.1297 0.1360 0.1335 WV Aug Wed 11,329,372 4,587,980 10,316,041 0.1248 0.1314 0.1289 WV Aug Thu 14,736,121 5,897,056 13,280,919 0.1624 0.1688 0.1660 WV Aug Fri 14,529,434 5,615,164 13,019,969 0.1601 0.1608 0.1627 WV Aug Sat 13,929,746 5,085,303 12,005,717 0.1535 0.1456 0.1500 WV Sep Sun 11,612,005 4,708,389 10,262,147 0.1528 0.1508 0.1527 WV Sep Mon 12,788,760 5,326,795 11,523,815 0.1683 0.1706 0.1715 WV Sep Tue 9,976,375 4,316,273 9,123,357 0.1313 0.1383 0.1358 WV Sep Wed 10,491,744 4,220,061 9,039,473 0.1381 0.1352 0.1345 WV Sep Thu 10,601,754 4,245,287 9,084,482 0.1395 0.1360 0.1352 WV Sep Fri 10,657,825 4,361,606 9,347,806 0.1403 0.1397 0.1391 WV Sep Sat 9,853,339 4,042,295 8,803,854 0.1297 0.1295 0.1310 WV Oct Sun 9,141,960 4,267,809 8,053,453 0.1078 0.1041 0.1090 WV Oct Mon 10,673,339 5,381,381 9,467,208 0.1259 0.1313 0.1282 WV Oct Tue 14,435,264 6,771,443 12,431,127 0.1703 0.1652 0.1683 WV Oct Wed 14,553,965 7,066,114 12,720,143 0.1717 0.1723 0.1722 WV Oct Thu 14,417,207 7,121,049 12,715,645 0.1701 0.1737 0.1722 WV Oct Fri 11,616,706 5,706,283 9,914,309 0.1370 0.1392 0.1342 WV Oct Sat 9,937,824 4,685,164 8,552,034 0.1172 0.1143 0.1158 WV Nov Sun 9,830,355 4,646,371 8,666,821 0.1145 0.1112 0.1187 WV Nov Mon 12,283,095 5,937,267 10,150,235 0.1431 0.1421 0.1390 WV Nov Tue 12,392,447 5,929,688 10,141,362 0.1444 0.1419 0.1389 WV Nov Wed 12,176,489 6,016,380 10,080,562 0.1419 0.1439 0.1380 WV Nov Thu 11,901,060 5,578,593 9,845,417 0.1387 0.1335 0.1348 WV Nov Fri 14,642,524 7,429,822 12,695,913 0.1706 0.1778 0.1739 WV Nov Sat 12,600,494 6,257,527 11,445,065 0.1468 0.1497 0.1567 WV Dec Sun 12,753,680 6,146,041 11,504,752 0.1389 0.1382 0.1453 WV Dec Mon 14,784,590 7,460,520 13,164,425 0.1610 0.1677 0.1662 WV Dec Tue 15,188,434 7,493,324 13,307,758 0.1654 0.1685 0.1680 WV Dec Wed 12,822,904 6,234,917 10,932,624 0.1396 0.1402 0.1380 WV Dec Thu 12,945,118 6,180,002 10,710,641 0.1409 0.1389 0.1352 WV Dec Fri 12,381,927 5,734,914 10,125,916 0.1348 0.1289 0.1279 WV Dec Sat 10,974,161 5,232,730 9,448,131 0.1195 0.1176 0.1193

C-15Atmospheric Sciences Group 

### Appendix D Actual 2002 State Level Monthly-Diurnal Profiles

CEM-Based Distribution Alpine Geophysics

SO2 Mass NOx Mass Heat Input State Month Hour [lbs] [lbs] [MMBtu] SO2 Ratio NOx Ratio Heat Input AL Jan 0 2,741,987 1,004,315 2,690,807 0.0381 0.0385 0.0383 AL Jan 1 2,717,405 994,117 2,656,333 0.0377 0.0381 0.0378 AL Jan 2 2,732,495 993,417 2,670,658 0.0380 0.0381 0.0380 AL Jan 3 2,787,197 1,006,543 2,711,547 0.0387 0.0386 0.0385 AL Jan 4 2,892,370 1,044,668 2,813,871 0.0402 0.0400 0.0400 AL Jan 5 3,043,742 1,095,960 2,973,281 0.0423 0.0420 0.0423 AL Jan 6 3,165,246 1,139,346 3,102,993 0.0440 0.0437 0.0441 AL Jan 7 3,153,129 1,138,326 3,101,803 0.0438 0.0436 0.0441 AL Jan 8 3,140,327 1,131,614 3,097,499 0.0436 0.0434 0.0440 AL Jan 9 3,203,467 1,153,016 3,087,739 0.0445 0.0442 0.0439 AL Jan 10 3,143,675 1,132,663 3,039,305 0.0437 0.0434 0.0432 AL Jan 11 3,102,170 1,119,903 2,983,100 0.0431 0.0429 0.0424 AL Jan 12 3,066,551 1,107,992 2,969,232 0.0426 0.0425 0.0422 AL Jan 13 3,013,840 1,088,445 2,924,398 0.0419 0.0417 0.0416 AL Jan 14 2,940,305 1,072,596 2,886,458 0.0408 0.0411 0.0410 AL Jan 15 2,936,570 1,074,049 2,879,720 0.0408 0.0412 0.0409 AL Jan 16 2,986,108 1,094,245 2,934,536 0.0415 0.0419 0.0417 AL Jan 17 3,128,407 1,131,955 3,060,818 0.0435 0.0434 0.0435 AL Jan 18 3,165,955 1,140,293 3,094,074 0.0440 0.0437 0.0440 AL Jan 19 3,119,814 1,124,019 3,053,305 0.0433 0.0431 0.0434 AL Jan 20 3,079,102 1,118,468 3,026,147 0.0428 0.0429 0.0430 AL Jan 21 3,025,517 1,100,925 2,976,770 0.0420 0.0422 0.0423 AL Jan 22 2,923,913 1,069,313 2,876,314 0.0406 0.0410 0.0409 AL Jan 23 2,776,269 1,018,348 2,732,989 0.0386 0.0390 0.0389 AL Feb 0 2,253,373 868,185 2,357,008 0.0389 0.0392 0.0394 AL Feb 1 2,224,059 859,658 2,318,041 0.0384 0.0389 0.0388 AL Feb 2 2,229,268 866,148 2,328,309 0.0385 0.0392 0.0389 AL Feb 3 2,261,953 879,145 2,365,382 0.0391 0.0397 0.0395 AL Feb 4 2,338,927 903,372 2,441,093 0.0404 0.0408 0.0408 AL Feb 5 2,436,805 933,109 2,532,481 0.0421 0.0422 0.0423 AL Feb 6 2,515,424 963,393 2,611,818 0.0434 0.0436 0.0437 AL Feb 7 2,538,948 968,548 2,610,717 0.0438 0.0438 0.0436 AL Feb 8 2,515,296 955,200 2,583,556 0.0434 0.0432 0.0432 AL Feb 9 2,540,711 958,276 2,552,241 0.0439 0.0433 0.0427 AL Feb 10 2,492,642 937,659 2,545,359 0.0430 0.0424 0.0426 AL Feb 11 2,470,000 931,823 2,519,838 0.0427 0.0421 0.0421 AL Feb 12 2,425,186 917,544 2,500,106 0.0419 0.0415 0.0418 AL Feb 13 2,383,050 900,232 2,447,506 0.0412 0.0407 0.0409 AL Feb 14 2,352,497 894,740 2,423,254 0.0406 0.0404 0.0405 AL Feb 15 2,337,173 891,481 2,410,974 0.0404 0.0403 0.0403 AL Feb 16 2,353,899 898,603 2,435,772 0.0407 0.0406 0.0407 AL Feb 17 2,420,477 924,045 2,509,107 0.0418 0.0418 0.0419 AL Feb 18 2,501,328 953,661 2,588,924 0.0432 0.0431 0.0433 AL Feb 19 2,491,231 950,950 2,576,810 0.0430 0.0430 0.0431 AL Feb 20 2,502,966 955,068 2,583,883 0.0432 0.0432 0.0432 AL Feb 21 2,495,709 954,918 2,577,873 0.0431 0.0432 0.0431 AL Feb 22 2,459,759 942,871 2,539,927 0.0425 0.0426 0.0425 AL Feb 23 2,362,705 912,645 2,456,568 0.0408 0.0413 0.0411 AL Mar 0 2,344,204 896,246 2,291,650 0.0394 0.0395 0.0395 AL Mar 1 2,290,492 878,336 2,235,146 0.0385 0.0387 0.0385 AL Mar 2 2,268,031 871,699 2,220,460 0.0381 0.0384 0.0382 AL Mar 3 2,270,932 876,499 2,233,320 0.0382 0.0386 0.0385 AL Mar 4 2,328,738 894,751 2,285,963 0.0392 0.0394 0.0394 Actual Reported Values [2002] Calculated Ratios

D-1Atmospheric Sciences Group 

### Appendix D Actual 2002 State Level Monthly-Diurnal Profiles

CEM-Based Distribution Alpine Geophysics

SO2 Mass NOx Mass Heat Input State Month Hour [lbs] [lbs] [MMBtu] SO2 Ratio NOx Ratio Heat Input Actual Reported Values [2002] Calculated Ratios

AL Mar 5 2,428,390 925,936 2,383,519 0.0408 0.0408 0.0410 AL Mar 6 2,508,590 953,226 2,464,397 0.0422 0.0420 0.0424 AL Mar 7 2,530,656 959,550 2,462,077 0.0425 0.0422 0.0424 AL Mar 8 2,561,924 977,286 2,477,056 0.0431 0.0430 0.0426 AL Mar 9 2,579,385 986,553 2,474,954 0.0434 0.0434 0.0426 AL Mar 10 2,557,475 978,823 2,477,934 0.0430 0.0431 0.0427 AL Mar 11 2,548,567 973,844 2,475,127 0.0428 0.0429 0.0426 AL Mar 12 2,542,765 970,831 2,484,634 0.0427 0.0427 0.0428 AL Mar 13 2,520,064 957,301 2,456,497 0.0424 0.0421 0.0423 AL Mar 14 2,505,486 955,765 2,446,978 0.0421 0.0421 0.0421 AL Mar 15 2,503,392 956,547 2,449,363 0.0421 0.0421 0.0422 AL Mar 16 2,524,971 964,459 2,460,914 0.0424 0.0425 0.0424 AL Mar 17 2,540,478 967,101 2,478,745 0.0427 0.0426 0.0427 AL Mar 18 2,591,567 986,968 2,543,551 0.0436 0.0435 0.0438 AL Mar 19 2,589,398 988,472 2,548,349 0.0435 0.0435 0.0439 AL Mar 20 2,568,710 979,980 2,519,139 0.0432 0.0431 0.0434 AL Mar 21 2,532,064 962,803 2,471,543 0.0426 0.0424 0.0426 AL Mar 22 2,474,817 941,870 2,414,411 0.0416 0.0415 0.0416 AL Mar 23 2,370,330 907,008 2,326,421 0.0398 0.0399 0.0401 AL Apr 0 2,228,515 836,202 2,285,448 0.0368 0.0370 0.0371 AL Apr 1 2,173,032 822,140 2,247,199 0.0359 0.0364 0.0365 AL Apr 2 2,153,881 818,757 2,234,410 0.0356 0.0362 0.0363 AL Apr 3 2,232,176 844,256 2,286,631 0.0369 0.0374 0.0371 AL Apr 4 2,389,439 897,207 2,408,707 0.0395 0.0397 0.0391 AL Apr 5 2,493,826 933,813 2,505,623 0.0412 0.0413 0.0407 AL Apr 6 2,554,599 952,174 2,560,375 0.0422 0.0421 0.0416 AL Apr 7 2,582,156 963,601 2,591,138 0.0427 0.0426 0.0421 AL Apr 8 2,639,813 979,628 2,624,462 0.0436 0.0433 0.0426 AL Apr 9 2,643,446 980,260 2,662,754 0.0437 0.0434 0.0432 AL Apr 10 2,653,155 984,214 2,694,000 0.0439 0.0435 0.0437 AL Apr 11 2,645,360 984,831 2,711,517 0.0437 0.0436 0.0440 AL Apr 12 2,624,188 978,349 2,708,341 0.0434 0.0433 0.0440 AL Apr 13 2,632,266 979,546 2,719,694 0.0435 0.0433 0.0441 AL Apr 14 2,652,217 987,702 2,721,904 0.0438 0.0437 0.0442 AL Apr 15 2,648,834 990,953 2,705,156 0.0438 0.0438 0.0439 AL Apr 16 2,621,452 984,228 2,687,882 0.0433 0.0435 0.0436 AL Apr 17 2,614,784 979,617 2,682,079 0.0432 0.0433 0.0435 AL Apr 18 2,628,751 978,975 2,699,451 0.0435 0.0433 0.0438 AL Apr 19 2,653,626 987,709 2,716,044 0.0439 0.0437 0.0441 AL Apr 20 2,631,521 977,459 2,680,736 0.0435 0.0432 0.0435 AL Apr 21 2,567,425 952,799 2,603,716 0.0424 0.0422 0.0423 AL Apr 22 2,464,894 919,642 2,483,958 0.0407 0.0407 0.0403 AL Apr 23 2,369,125 887,276 2,395,812 0.0392 0.0393 0.0389 AL May 0 2,465,552 908,349 2,524,318 0.0367 0.0366 0.0366 AL May 1 2,420,701 890,183 2,472,941 0.0361 0.0358 0.0358 AL May 2 2,406,368 883,322 2,446,821 0.0358 0.0356 0.0354 AL May 3 2,479,383 904,473 2,501,796 0.0369 0.0364 0.0362 AL May 4 2,602,268 957,753 2,624,949 0.0388 0.0386 0.0380 AL May 5 2,677,066 993,418 2,712,234 0.0399 0.0400 0.0393 AL May 6 2,779,517 1,027,989 2,806,238 0.0414 0.0414 0.0407 AL May 7 2,848,345 1,045,051 2,875,058 0.0424 0.0421 0.0417 AL May 8 2,931,694 1,063,579 2,953,366 0.0437 0.0428 0.0428 AL May 9 2,924,381 1,075,077 2,989,107 0.0436 0.0433 0.0433

D-2Atmospheric Sciences Group 

### Appendix D Actual 2002 State Level Monthly-Diurnal Profiles

CEM-Based Distribution Alpine Geophysics

SO2 Mass NOx Mass Heat Input State Month Hour [lbs] [lbs] [MMBtu] SO2 Ratio NOx Ratio Heat Input Actual Reported Values [2002] Calculated Ratios

AL May 10 2,938,699 1,091,747 3,041,252 0.0438 0.0439 0.0441 AL May 11 2,947,674 1,099,596 3,077,771 0.0439 0.0443 0.0446 AL May 12 2,936,754 1,089,078 3,069,164 0.0437 0.0438 0.0445 AL May 13 2,945,390 1,097,482 3,103,684 0.0439 0.0442 0.0450 AL May 14 2,939,698 1,112,440 3,106,993 0.0438 0.0448 0.0450 AL May 15 2,956,416 1,106,665 3,113,515 0.0440 0.0445 0.0451 AL May 16 2,955,262 1,103,806 3,100,165 0.0440 0.0444 0.0449 AL May 17 2,952,378 1,102,965 3,079,650 0.0440 0.0444 0.0446 AL May 18 2,938,574 1,092,977 3,038,781 0.0438 0.0440 0.0440 AL May 19 2,977,607 1,102,186 3,069,979 0.0443 0.0444 0.0445 AL May 20 2,937,077 1,085,710 3,009,359 0.0437 0.0437 0.0436 AL May 21 2,844,515 1,047,367 2,889,529 0.0424 0.0422 0.0419 AL May 22 2,722,348 1,000,434 2,758,208 0.0405 0.0403 0.0400 AL May 23 2,613,635 960,563 2,657,155 0.0389 0.0387 0.0385 AL Jun 0 2,968,696 1,028,663 3,076,335 0.0363 0.0362 0.0362 AL Jun 1 2,832,644 987,788 2,984,774 0.0347 0.0347 0.0351 AL Jun 2 2,738,909 957,899 2,906,863 0.0335 0.0337 0.0342 AL Jun 3 2,793,854 970,712 2,944,737 0.0342 0.0341 0.0346 AL Jun 4 2,930,010 1,012,097 3,057,162 0.0359 0.0356 0.0360 AL Jun 5 3,078,245 1,058,356 3,187,128 0.0377 0.0372 0.0375 AL Jun 6 3,296,494 1,139,625 3,346,605 0.0404 0.0401 0.0394 AL Jun 7 3,446,820 1,200,750 3,495,633 0.0422 0.0422 0.0411 AL Jun 8 3,612,260 1,245,866 3,641,676 0.0442 0.0438 0.0428 AL Jun 9 3,661,396 1,262,673 3,742,119 0.0448 0.0444 0.0440 AL Jun 10 3,677,963 1,274,079 3,805,701 0.0450 0.0448 0.0448 AL Jun 11 3,698,926 1,293,955 3,868,213 0.0453 0.0455 0.0455 AL Jun 12 3,656,461 1,279,429 3,883,824 0.0448 0.0450 0.0457 AL Jun 13 3,671,689 1,294,921 3,919,363 0.0450 0.0455 0.0461 AL Jun 14 3,671,228 1,285,782 3,902,063 0.0449 0.0452 0.0459 AL Jun 15 3,680,401 1,290,857 3,892,849 0.0451 0.0454 0.0458 AL Jun 16 3,674,613 1,292,845 3,881,062 0.0450 0.0454 0.0457 AL Jun 17 3,664,720 1,285,717 3,864,300 0.0449 0.0452 0.0455 AL Jun 18 3,642,194 1,271,867 3,811,846 0.0446 0.0447 0.0448 AL Jun 19 3,676,208 1,284,584 3,825,728 0.0450 0.0452 0.0450 AL Jun 20 3,642,893 1,269,302 3,753,943 0.0446 0.0446 0.0442 AL Jun 21 3,519,611 1,223,561 3,591,565 0.0431 0.0430 0.0422 AL Jun 22 3,310,525 1,150,005 3,391,162 0.0405 0.0404 0.0399 AL Jun 23 3,132,379 1,086,983 3,236,656 0.0383 0.0382 0.0381 AL Jul 0 3,351,891 1,159,796 3,519,285 0.0374 0.0376 0.0370 AL Jul 1 3,209,694 1,111,818 3,419,808 0.0358 0.0360 0.0360 AL Jul 2 3,133,780 1,087,810 3,361,520 0.0349 0.0353 0.0353 AL Jul 3 3,149,495 1,096,513 3,374,098 0.0351 0.0355 0.0355 AL Jul 4 3,264,237 1,136,963 3,477,228 0.0364 0.0369 0.0366 AL Jul 5 3,354,945 1,164,931 3,584,943 0.0374 0.0378 0.0377 AL Jul 6 3,552,275 1,231,220 3,722,799 0.0396 0.0399 0.0391 AL Jul 7 3,762,714 1,273,158 3,855,300 0.0419 0.0413 0.0405 AL Jul 8 3,898,906 1,328,282 4,027,155 0.0434 0.0431 0.0423 AL Jul 9 4,004,317 1,358,026 4,162,034 0.0446 0.0440 0.0438 AL Jul 10 4,052,600 1,369,903 4,248,781 0.0452 0.0444 0.0447 AL Jul 11 4,042,434 1,373,838 4,301,796 0.0450 0.0445 0.0452 AL Jul 12 3,998,643 1,371,727 4,328,386 0.0446 0.0445 0.0455 AL Jul 13 4,005,257 1,379,736 4,338,694 0.0446 0.0447 0.0456 AL Jul 14 4,021,426 1,382,915 4,351,967 0.0448 0.0448 0.0458

D-3Atmospheric Sciences Group 

### Appendix D Actual 2002 State Level Monthly-Diurnal Profiles

CEM-Based Distribution Alpine Geophysics

SO2 Mass NOx Mass Heat Input State Month Hour [lbs] [lbs] [MMBtu] SO2 Ratio NOx Ratio Heat Input Actual Reported Values [2002] Calculated Ratios

AL Jul 15 4,011,322 1,377,002 4,328,342 0.0447 0.0446 0.0455 AL Jul 16 3,971,531 1,374,932 4,297,663 0.0443 0.0446 0.0452 AL Jul 17 3,970,177 1,371,961 4,279,469 0.0442 0.0445 0.0450 AL Jul 18 3,954,613 1,361,364 4,219,046 0.0441 0.0441 0.0444 AL Jul 19 3,971,366 1,363,853 4,222,712 0.0443 0.0442 0.0444 AL Jul 20 3,954,276 1,354,338 4,162,522 0.0441 0.0439 0.0438 AL Jul 21 3,868,801 1,324,102 4,014,526 0.0431 0.0429 0.0422 AL Jul 22 3,688,548 1,270,811 3,827,832 0.0411 0.0412 0.0402 AL Jul 23 3,544,676 1,224,624 3,684,831 0.0395 0.0397 0.0387 AL Aug 0 3,315,508 1,145,136 3,467,179 0.0373 0.0374 0.0369 AL Aug 1 3,191,575 1,096,332 3,357,297 0.0359 0.0358 0.0357 AL Aug 2 3,131,686 1,066,341 3,295,620 0.0352 0.0348 0.0351 AL Aug 3 3,189,797 1,076,150 3,316,610 0.0359 0.0352 0.0353 AL Aug 4 3,345,349 1,131,553 3,442,497 0.0376 0.0370 0.0366 AL Aug 5 3,467,950 1,178,821 3,586,753 0.0390 0.0385 0.0382 AL Aug 6 3,557,705 1,212,665 3,669,843 0.0400 0.0396 0.0391 AL Aug 7 3,691,415 1,251,997 3,792,486 0.0415 0.0409 0.0404 AL Aug 8 3,908,307 1,308,189 3,947,840 0.0440 0.0427 0.0420 AL Aug 9 3,903,178 1,333,735 4,068,709 0.0439 0.0436 0.0433 AL Aug 10 3,934,441 1,349,001 4,168,401 0.0443 0.0441 0.0444 AL Aug 11 3,966,574 1,365,544 4,245,039 0.0446 0.0446 0.0452 AL Aug 12 3,955,846 1,368,079 4,265,544 0.0445 0.0447 0.0454 AL Aug 13 3,956,345 1,373,515 4,303,852 0.0445 0.0449 0.0458 AL Aug 14 3,983,111 1,378,187 4,308,814 0.0448 0.0450 0.0459 AL Aug 15 3,973,821 1,380,620 4,309,578 0.0447 0.0451 0.0459 AL Aug 16 3,951,313 1,378,479 4,282,645 0.0444 0.0450 0.0456 AL Aug 17 3,942,194 1,377,544 4,257,902 0.0443 0.0450 0.0453 AL Aug 18 3,922,582 1,366,680 4,225,247 0.0441 0.0447 0.0450 AL Aug 19 3,921,040 1,364,494 4,214,527 0.0441 0.0446 0.0449 AL Aug 20 3,850,720 1,347,245 4,126,683 0.0433 0.0440 0.0439 AL Aug 21 3,747,671 1,301,451 3,947,717 0.0422 0.0425 0.0420 AL Aug 22 3,597,935 1,245,039 3,741,936 0.0405 0.0407 0.0398 AL Aug 23 3,487,479 1,204,159 3,607,788 0.0392 0.0394 0.0384 AL Sep 0 3,172,931 1,062,515 3,165,623 0.0386 0.0378 0.0375 AL Sep 1 3,095,788 1,041,210 3,108,778 0.0376 0.0371 0.0368 AL Sep 2 3,047,740 1,023,435 3,062,886 0.0371 0.0364 0.0363 AL Sep 3 3,072,181 1,031,217 3,082,703 0.0374 0.0367 0.0365 AL Sep 4 3,194,890 1,073,982 3,203,935 0.0388 0.0382 0.0380 AL Sep 5 3,281,892 1,105,758 3,315,138 0.0399 0.0394 0.0393 AL Sep 6 3,311,581 1,124,098 3,345,868 0.0403 0.0400 0.0396 AL Sep 7 3,413,675 1,137,808 3,402,796 0.0415 0.0405 0.0403 AL Sep 8 3,486,832 1,172,114 3,507,791 0.0424 0.0417 0.0416 AL Sep 9 3,535,599 1,195,133 3,590,521 0.0430 0.0425 0.0425 AL Sep 10 3,565,956 1,216,228 3,668,282 0.0434 0.0433 0.0435 AL Sep 11 3,545,009 1,223,250 3,704,548 0.0431 0.0435 0.0439 AL Sep 12 3,551,028 1,225,644 3,731,097 0.0432 0.0436 0.0442 AL Sep 13 3,573,196 1,241,350 3,768,609 0.0434 0.0442 0.0446 AL Sep 14 3,597,339 1,252,545 3,808,605 0.0437 0.0446 0.0451 AL Sep 15 3,614,664 1,261,701 3,827,550 0.0440 0.0449 0.0453 AL Sep 16 3,617,021 1,261,578 3,819,086 0.0440 0.0449 0.0452 AL Sep 17 3,619,580 1,257,109 3,813,056 0.0440 0.0448 0.0452 AL Sep 18 3,627,053 1,260,241 3,819,723 0.0441 0.0449 0.0452 AL Sep 19 3,623,409 1,261,463 3,790,437 0.0441 0.0449 0.0449

D-4Atmospheric Sciences Group 

### Appendix D Actual 2002 State Level Monthly-Diurnal Profiles

CEM-Based Distribution Alpine Geophysics

SO2 Mass NOx Mass Heat Input State Month Hour [lbs] [lbs] [MMBtu] SO2 Ratio NOx Ratio Heat Input Actual Reported Values [2002] Calculated Ratios

AL Sep 20 3,577,183 1,236,416 3,705,718 0.0435 0.0440 0.0439 AL Sep 21 3,487,786 1,192,909 3,538,876 0.0424 0.0425 0.0419 AL Sep 22 3,359,963 1,136,427 3,376,674 0.0409 0.0405 0.0400 AL Sep 23 3,264,945 1,096,522 3,256,671 0.0397 0.0390 0.0386 AL Oct 0 3,110,672 1,130,772 2,995,713 0.0385 0.0381 0.0382 AL Oct 1 3,075,088 1,117,841 2,961,641 0.0381 0.0376 0.0378 AL Oct 2 3,065,688 1,114,839 2,951,087 0.0380 0.0375 0.0376 AL Oct 3 3,104,259 1,130,696 2,975,923 0.0385 0.0381 0.0380 AL Oct 4 3,196,004 1,158,663 3,059,006 0.0396 0.0390 0.0390 AL Oct 5 3,315,156 1,198,160 3,168,032 0.0411 0.0403 0.0404 AL Oct 6 3,364,686 1,323,201 3,197,922 0.0417 0.0445 0.0408 AL Oct 7 3,422,774 1,235,158 3,245,934 0.0424 0.0416 0.0414 AL Oct 8 3,489,941 1,264,016 3,330,052 0.0432 0.0426 0.0425 AL Oct 9 3,501,328 1,284,386 3,360,289 0.0434 0.0432 0.0429 AL Oct 10 3,500,981 1,287,602 3,397,817 0.0434 0.0433 0.0433 AL Oct 11 3,501,855 1,285,763 3,431,617 0.0434 0.0433 0.0438 AL Oct 12 3,484,004 1,282,104 3,416,445 0.0432 0.0432 0.0436 AL Oct 13 3,474,043 1,280,710 3,419,364 0.0430 0.0431 0.0436 AL Oct 14 3,479,549 1,285,734 3,426,303 0.0431 0.0433 0.0437 AL Oct 15 3,488,225 1,289,705 3,429,926 0.0432 0.0434 0.0438 AL Oct 16 3,484,827 1,287,241 3,425,513 0.0432 0.0433 0.0437 AL Oct 17 3,492,875 1,294,313 3,450,441 0.0433 0.0436 0.0440 AL Oct 18 3,487,520 1,296,565 3,450,107 0.0432 0.0436 0.0440 AL Oct 19 3,470,708 1,291,892 3,423,988 0.0430 0.0435 0.0437 AL Oct 20 3,448,538 1,278,748 3,382,095 0.0427 0.0430 0.0431 AL Oct 21 3,358,028 1,244,928 3,277,885 0.0416 0.0419 0.0418 AL Oct 22 3,232,770 1,188,205 3,147,611 0.0401 0.0400 0.0402 AL Oct 23 3,162,688 1,152,640 3,062,964 0.0392 0.0388 0.0391 AL Nov 0 2,874,503 1,104,123 2,854,064 0.0387 0.0390 0.0392 AL Nov 1 2,824,556 1,075,192 2,803,283 0.0380 0.0380 0.0385 AL Nov 2 2,803,979 1,066,604 2,785,904 0.0378 0.0377 0.0383 AL Nov 3 2,835,080 1,074,985 2,809,520 0.0382 0.0380 0.0386 AL Nov 4 2,931,408 1,112,758 2,879,968 0.0395 0.0394 0.0396 AL Nov 5 3,064,807 1,168,346 3,003,774 0.0413 0.0413 0.0413 AL Nov 6 3,161,339 1,208,664 3,112,630 0.0426 0.0427 0.0428 AL Nov 7 3,177,846 1,205,865 3,112,150 0.0428 0.0426 0.0428 AL Nov 8 3,177,364 1,213,164 3,104,175 0.0428 0.0429 0.0427 AL Nov 9 3,223,552 1,221,702 3,125,561 0.0434 0.0432 0.0430 AL Nov 10 3,199,469 1,210,652 3,111,519 0.0431 0.0428 0.0428 AL Nov 11 3,162,935 1,200,713 3,087,776 0.0426 0.0425 0.0424 AL Nov 12 3,139,935 1,192,359 3,070,345 0.0423 0.0422 0.0422 AL Nov 13 3,111,729 1,180,161 3,045,946 0.0419 0.0417 0.0419 AL Nov 14 3,093,392 1,177,945 3,039,804 0.0417 0.0417 0.0418 AL Nov 15 3,107,507 1,183,590 3,050,221 0.0419 0.0419 0.0419 AL Nov 16 3,158,072 1,200,446 3,085,113 0.0425 0.0425 0.0424 AL Nov 17 3,232,524 1,226,969 3,161,025 0.0435 0.0434 0.0434 AL Nov 18 3,242,583 1,233,932 3,174,638 0.0437 0.0436 0.0436 AL Nov 19 3,223,480 1,228,574 3,146,189 0.0434 0.0434 0.0432 AL Nov 20 3,221,533 1,230,598 3,134,188 0.0434 0.0435 0.0431 AL Nov 21 3,189,452 1,222,540 3,104,203 0.0430 0.0432 0.0427 AL Nov 22 3,093,471 1,190,949 3,024,037 0.0417 0.0421 0.0416 AL Nov 23 2,992,038 1,146,518 2,934,438 0.0403 0.0405 0.0403 AL Dec 0 3,205,831 1,118,722 2,838,057 0.0391 0.0389 0.0390

D-5Atmospheric Sciences Group 

### Appendix D Actual 2002 State Level Monthly-Diurnal Profiles

CEM-Based Distribution Alpine Geophysics

SO2 Mass NOx Mass Heat Input State Month Hour [lbs] [lbs] [MMBtu] SO2 Ratio NOx Ratio Heat Input Actual Reported Values [2002] Calculated Ratios

AL Dec 1 3,167,538 1,104,087 2,799,640 0.0386 0.0384 0.0385 AL Dec 2 3,164,469 1,107,980 2,806,818 0.0386 0.0385 0.0386 AL Dec 3 3,208,038 1,121,620 2,831,324 0.0391 0.0390 0.0389 AL Dec 4 3,281,914 1,146,890 2,893,251 0.0400 0.0399 0.0398 AL Dec 5 3,375,405 1,177,736 2,976,587 0.0412 0.0409 0.0409 AL Dec 6 3,488,636 1,217,589 3,099,293 0.0426 0.0423 0.0426 AL Dec 7 3,537,289 1,235,510 3,119,173 0.0431 0.0429 0.0429 AL Dec 8 3,552,158 1,245,669 3,132,449 0.0433 0.0433 0.0431 AL Dec 9 3,557,325 1,246,315 3,125,154 0.0434 0.0433 0.0430 AL Dec 10 3,526,064 1,227,192 3,100,960 0.0430 0.0426 0.0426 AL Dec 11 3,483,264 1,214,331 3,082,794 0.0425 0.0422 0.0424 AL Dec 12 3,434,044 1,241,858 3,048,547 0.0419 0.0432 0.0419 AL Dec 13 3,374,003 1,174,327 2,992,974 0.0412 0.0408 0.0412 AL Dec 14 3,345,612 1,170,860 2,976,566 0.0408 0.0407 0.0409 AL Dec 15 3,362,456 1,180,238 2,991,073 0.0410 0.0410 0.0411 AL Dec 16 3,459,775 1,207,176 3,083,525 0.0422 0.0419 0.0424 AL Dec 17 3,581,738 1,253,741 3,194,905 0.0437 0.0436 0.0439 AL Dec 18 3,594,082 1,267,370 3,214,573 0.0438 0.0440 0.0442 AL Dec 19 3,561,608 1,260,092 3,184,828 0.0434 0.0438 0.0438 AL Dec 20 3,553,749 1,262,191 3,182,503 0.0433 0.0439 0.0438 AL Dec 21 3,531,360 1,250,529 3,142,266 0.0431 0.0435 0.0432 AL Dec 22 3,391,080 1,202,136 3,015,338 0.0414 0.0418 0.0415 AL Dec 23 3,245,883 1,142,679 2,885,737 0.0396 0.0397 0.0397 FL Jan 0 2,299,429 1,317,982 3,802,850 0.0339 0.0314 0.0335 FL Jan 1 2,205,527 1,257,798 3,697,919 0.0326 0.0299 0.0326 FL Jan 2 2,203,963 1,246,266 3,666,185 0.0325 0.0297 0.0323 FL Jan 3 2,224,477 1,250,434 3,680,320 0.0328 0.0298 0.0324 FL Jan 4 2,284,250 1,290,657 3,781,954 0.0337 0.0307 0.0333 FL Jan 5 2,459,505 1,414,683 4,091,805 0.0363 0.0337 0.0360 FL Jan 6 2,811,845 1,692,344 4,638,345 0.0415 0.0403 0.0409 FL Jan 7 3,064,938 1,880,467 5,019,589 0.0452 0.0448 0.0442 FL Jan 8 3,170,024 1,940,985 5,162,357 0.0468 0.0462 0.0455 FL Jan 9 3,170,704 1,963,743 5,230,019 0.0468 0.0468 0.0461 FL Jan 10 3,124,703 1,969,530 5,213,708 0.0461 0.0469 0.0459 FL Jan 11 3,017,949 1,946,980 5,117,836 0.0445 0.0464 0.0451 FL Jan 12 2,945,721 1,910,654 5,051,668 0.0435 0.0455 0.0445 FL Jan 13 2,865,363 1,885,266 4,973,371 0.0423 0.0449 0.0438 FL Jan 14 2,787,986 1,852,388 4,892,552 0.0411 0.0441 0.0431 FL Jan 15 2,763,289 1,845,891 4,887,769 0.0408 0.0439 0.0431 FL Jan 16 2,818,523 1,852,995 4,954,466 0.0416 0.0441 0.0436 FL Jan 17 2,988,376 1,932,657 5,171,039 0.0441 0.0460 0.0455 FL Jan 18 3,403,106 2,208,330 5,663,489 0.0502 0.0526 0.0499 FL Jan 19 3,437,839 2,218,481 5,659,902 0.0507 0.0528 0.0499 FL Jan 20 3,262,336 2,059,050 5,394,295 0.0481 0.0490 0.0475 FL Jan 21 3,069,958 1,894,485 5,044,943 0.0453 0.0451 0.0444 FL Jan 22 2,845,762 1,696,995 4,601,522 0.0420 0.0404 0.0405 FL Jan 23 2,529,965 1,475,452 4,134,079 0.0373 0.0351 0.0364 FL Feb 0 1,739,031 1,000,902 2,955,834 0.0308 0.0293 0.0321 FL Feb 1 1,639,945 950,067 2,863,918 0.0290 0.0278 0.0311 FL Feb 2 1,614,541 940,528 2,835,025 0.0286 0.0275 0.0308 FL Feb 3 1,628,970 945,847 2,850,111 0.0288 0.0277 0.0310 FL Feb 4 1,703,212 985,965 2,959,196 0.0301 0.0289 0.0322 FL Feb 5 1,883,746 1,113,555 3,227,540 0.0333 0.0326 0.0351

D-6Atmospheric Sciences Group 

### Appendix D Actual 2002 State Level Monthly-Diurnal Profiles

CEM-Based Distribution Alpine Geophysics

SO2 Mass NOx Mass Heat Input State Month Hour [lbs] [lbs] [MMBtu] SO2 Ratio NOx Ratio Heat Input Actual Reported Values [2002] Calculated Ratios

FL Feb 6 2,231,263 1,369,389 3,744,256 0.0395 0.0401 0.0407 FL Feb 7 2,549,195 1,574,901 4,140,555 0.0451 0.0461 0.0450 FL Feb 8 2,630,878 1,622,353 4,229,664 0.0466 0.0475 0.0460 FL Feb 9 2,663,642 1,636,975 4,275,492 0.0471 0.0479 0.0465 FL Feb 10 2,676,062 1,647,364 4,281,343 0.0474 0.0482 0.0466 FL Feb 11 2,589,032 1,594,755 4,186,358 0.0458 0.0467 0.0455 FL Feb 12 2,572,962 1,574,694 4,160,030 0.0455 0.0461 0.0452 FL Feb 13 2,533,366 1,542,525 4,100,874 0.0448 0.0452 0.0446 FL Feb 14 2,468,675 1,505,675 4,040,322 0.0437 0.0441 0.0439 FL Feb 15 2,437,319 1,489,801 4,018,065 0.0431 0.0436 0.0437 FL Feb 16 2,485,234 1,511,169 4,053,660 0.0440 0.0443 0.0441 FL Feb 17 2,622,007 1,570,652 4,176,316 0.0464 0.0460 0.0454 FL Feb 18 2,909,760 1,767,552 4,517,601 0.0515 0.0518 0.0491 FL Feb 19 3,042,293 1,880,881 4,673,318 0.0538 0.0551 0.0508 FL Feb 20 2,864,365 1,746,495 4,466,848 0.0507 0.0511 0.0486 FL Feb 21 2,616,249 1,578,955 4,147,251 0.0463 0.0462 0.0451 FL Feb 22 2,372,582 1,405,912 3,744,772 0.0420 0.0412 0.0407 FL Feb 23 2,041,951 1,188,540 3,321,492 0.0361 0.0348 0.0361 FL Mar 0 2,065,747 1,118,271 3,326,436 0.0295 0.0285 0.0309 FL Mar 1 1,892,868 1,021,148 3,150,206 0.0270 0.0260 0.0293 FL Mar 2 1,812,928 972,919 3,049,145 0.0259 0.0248 0.0283 FL Mar 3 1,780,953 952,037 3,015,716 0.0254 0.0243 0.0280 FL Mar 4 1,794,312 964,647 3,063,493 0.0256 0.0246 0.0284 FL Mar 5 1,909,055 1,036,145 3,261,928 0.0273 0.0264 0.0303 FL Mar 6 2,197,426 1,257,075 3,709,903 0.0314 0.0320 0.0345 FL Mar 7 2,503,340 1,433,445 4,059,937 0.0358 0.0365 0.0377 FL Mar 8 2,796,992 1,591,721 4,400,782 0.0400 0.0406 0.0409 FL Mar 9 3,082,333 1,761,870 4,705,991 0.0440 0.0449 0.0437 FL Mar 10 3,304,592 1,893,779 4,950,066 0.0472 0.0483 0.0460 FL Mar 11 3,406,777 1,952,537 5,100,355 0.0487 0.0498 0.0474 FL Mar 12 3,531,215 2,002,825 5,258,910 0.0504 0.0510 0.0488 FL Mar 13 3,603,289 2,037,519 5,371,325 0.0515 0.0519 0.0499 FL Mar 14 3,621,294 2,053,895 5,419,103 0.0517 0.0523 0.0503 FL Mar 15 3,636,365 2,071,947 5,469,103 0.0520 0.0528 0.0508 FL Mar 16 3,658,356 2,077,598 5,508,128 0.0523 0.0529 0.0512 FL Mar 17 3,649,044 2,063,222 5,486,935 0.0521 0.0526 0.0510 FL Mar 18 3,665,857 2,064,820 5,509,632 0.0524 0.0526 0.0512 FL Mar 19 3,797,955 2,163,173 5,651,331 0.0543 0.0551 0.0525 FL Mar 20 3,647,981 2,045,159 5,355,404 0.0521 0.0521 0.0497 FL Mar 21 3,305,681 1,824,702 4,851,991 0.0472 0.0465 0.0451 FL Mar 22 2,894,733 1,577,278 4,272,169 0.0414 0.0402 0.0397 FL Mar 23 2,438,191 1,306,940 3,737,774 0.0348 0.0333 0.0347 FL Apr 0 2,122,556 1,128,625 3,490,862 0.0288 0.0276 0.0295 FL Apr 1 1,955,149 1,040,978 3,289,089 0.0265 0.0255 0.0278 FL Apr 2 1,855,862 981,468 3,170,624 0.0252 0.0240 0.0268 FL Apr 3 1,800,327 958,514 3,132,493 0.0244 0.0235 0.0265 FL Apr 4 1,863,832 997,119 3,259,524 0.0253 0.0244 0.0276 FL Apr 5 2,120,117 1,141,959 3,624,431 0.0288 0.0280 0.0307 FL Apr 6 2,331,975 1,283,729 3,880,292 0.0317 0.0314 0.0328 FL Apr 7 2,593,181 1,413,140 4,196,646 0.0352 0.0346 0.0355 FL Apr 8 2,975,070 1,642,288 4,675,402 0.0404 0.0402 0.0396 FL Apr 9 3,343,630 1,872,994 5,163,994 0.0454 0.0459 0.0437 FL Apr 10 3,504,661 1,982,715 5,463,767 0.0476 0.0486 0.0462

D-7Atmospheric Sciences Group 

### Appendix D Actual 2002 State Level Monthly-Diurnal Profiles

CEM-Based Distribution Alpine Geophysics

SO2 Mass NOx Mass Heat Input State Month Hour [lbs] [lbs] [MMBtu] SO2 Ratio NOx Ratio Heat Input Actual Reported Values [2002] Calculated Ratios

FL Apr 11 3,649,330 2,073,756 5,789,773 0.0495 0.0508 0.0490 FL Apr 12 3,781,688 2,159,615 6,046,237 0.0513 0.0529 0.0512 FL Apr 13 3,893,061 2,220,023 6,221,809 0.0528 0.0544 0.0527 FL Apr 14 3,953,203 2,259,477 6,332,557 0.0537 0.0553 0.0536 FL Apr 15 3,998,628 2,280,871 6,378,876 0.0543 0.0559 0.0540 FL Apr 16 3,990,290 2,262,393 6,361,091 0.0542 0.0554 0.0538 FL Apr 17 3,908,528 2,184,250 6,242,845 0.0530 0.0535 0.0528 FL Apr 18 3,791,245 2,074,985 6,058,031 0.0515 0.0508 0.0513 FL Apr 19 3,820,024 2,129,698 6,089,124 0.0518 0.0522 0.0515 FL Apr 20 3,646,766 2,031,072 5,761,902 0.0495 0.0498 0.0488 FL Apr 21 3,324,598 1,811,729 5,154,381 0.0451 0.0444 0.0436 FL Apr 22 2,970,775 1,575,175 4,510,460 0.0403 0.0386 0.0382 FL Apr 23 2,484,141 1,317,669 3,876,789 0.0337 0.0323 0.0328 FL May 0 2,689,862 1,391,174 4,381,615 0.0303 0.0284 0.0308 FL May 1 2,468,891 1,278,539 4,145,946 0.0278 0.0261 0.0291 FL May 2 2,325,003 1,204,227 3,980,709 0.0262 0.0246 0.0280 FL May 3 2,263,462 1,166,204 3,915,140 0.0255 0.0238 0.0275 FL May 4 2,325,504 1,208,506 4,009,619 0.0262 0.0247 0.0282 FL May 5 2,493,137 1,339,156 4,332,215 0.0280 0.0273 0.0304 FL May 6 2,667,714 1,485,846 4,601,428 0.0300 0.0303 0.0323 FL May 7 3,067,426 1,686,661 5,044,905 0.0345 0.0344 0.0354 FL May 8 3,530,119 1,979,806 5,639,262 0.0397 0.0404 0.0396 FL May 9 3,943,577 2,225,986 6,170,132 0.0444 0.0455 0.0433 FL May 10 4,229,022 2,370,428 6,568,070 0.0476 0.0484 0.0461 FL May 11 4,442,858 2,502,439 6,970,468 0.0500 0.0511 0.0490 FL May 12 4,600,077 2,610,520 7,266,157 0.0518 0.0533 0.0510 FL May 13 4,735,876 2,671,933 7,475,686 0.0533 0.0546 0.0525 FL May 14 4,772,662 2,713,834 7,601,247 0.0537 0.0554 0.0534 FL May 15 4,826,640 2,741,605 7,677,735 0.0543 0.0560 0.0539 FL May 16 4,790,138 2,732,148 7,651,794 0.0539 0.0558 0.0538 FL May 17 4,712,657 2,661,594 7,508,591 0.0530 0.0543 0.0527 FL May 18 4,578,167 2,542,934 7,229,033 0.0515 0.0519 0.0508 FL May 19 4,537,772 2,516,298 7,101,309 0.0510 0.0514 0.0499 FL May 20 4,395,449 2,403,361 6,791,659 0.0494 0.0491 0.0477 FL May 21 3,973,920 2,134,501 6,149,474 0.0447 0.0436 0.0432 FL May 22 3,509,330 1,847,059 5,393,998 0.0395 0.0377 0.0379 FL May 23 3,010,341 1,559,934 4,744,853 0.0339 0.0319 0.0333 FL Jun 0 2,327,977 1,218,145 4,260,414 0.0292 0.0277 0.0307 FL Jun 1 2,170,264 1,120,203 4,058,007 0.0272 0.0254 0.0293 FL Jun 2 2,087,072 1,061,400 3,928,415 0.0262 0.0241 0.0283 FL Jun 3 2,049,322 1,027,751 3,878,517 0.0257 0.0233 0.0280 FL Jun 4 2,110,924 1,074,696 3,972,435 0.0265 0.0244 0.0287 FL Jun 5 2,262,760 1,191,967 4,205,780 0.0284 0.0271 0.0303 FL Jun 6 2,413,993 1,314,488 4,465,226 0.0303 0.0299 0.0322 FL Jun 7 2,773,342 1,503,293 4,951,556 0.0348 0.0341 0.0357 FL Jun 8 3,209,213 1,786,352 5,594,830 0.0402 0.0406 0.0404 FL Jun 9 3,631,593 2,050,735 6,222,743 0.0455 0.0466 0.0449 FL Jun 10 3,909,068 2,236,325 6,667,647 0.0490 0.0508 0.0481 FL Jun 11 4,142,700 2,366,376 7,050,242 0.0520 0.0537 0.0508 FL Jun 12 4,280,226 2,453,926 7,283,016 0.0537 0.0557 0.0525 FL Jun 13 4,329,363 2,497,502 7,406,475 0.0543 0.0567 0.0534 FL Jun 14 4,342,046 2,501,575 7,447,835 0.0545 0.0568 0.0537 FL Jun 15 4,373,068 2,492,079 7,424,718 0.0548 0.0566 0.0536

D-8Atmospheric Sciences Group 

### Appendix D Actual 2002 State Level Monthly-Diurnal Profiles

CEM-Based Distribution Alpine Geophysics

SO2 Mass NOx Mass Heat Input State Month Hour [lbs] [lbs] [MMBtu] SO2 Ratio NOx Ratio Heat Input Actual Reported Values [2002] Calculated Ratios

FL Jun 16 4,297,804 2,451,182 7,307,677 0.0539 0.0557 0.0527 FL Jun 17 4,185,382 2,363,754 7,110,051 0.0525 0.0537 0.0513 FL Jun 18 4,004,746 2,239,952 6,807,106 0.0502 0.0509 0.0491 FL Jun 19 3,955,616 2,197,245 6,650,925 0.0496 0.0499 0.0480 FL Jun 20 3,848,942 2,108,853 6,425,375 0.0483 0.0479 0.0463 FL Jun 21 3,473,837 1,852,184 5,819,896 0.0436 0.0421 0.0420 FL Jun 22 2,994,965 1,572,011 5,141,817 0.0376 0.0357 0.0371 FL Jun 23 2,561,929 1,345,153 4,567,964 0.0321 0.0306 0.0329 FL Jul 0 2,764,634 1,386,971 4,816,291 0.0293 0.0277 0.0307 FL Jul 1 2,545,942 1,280,746 4,581,235 0.0270 0.0256 0.0292 FL Jul 2 2,436,428 1,224,798 4,438,465 0.0258 0.0245 0.0283 FL Jul 3 2,377,262 1,199,963 4,383,175 0.0252 0.0240 0.0279 FL Jul 4 2,429,436 1,233,367 4,456,088 0.0257 0.0247 0.0284 FL Jul 5 2,639,313 1,348,365 4,696,660 0.0280 0.0270 0.0299 FL Jul 6 2,834,109 1,491,803 4,967,819 0.0300 0.0298 0.0316 FL Jul 7 3,267,863 1,700,966 5,528,838 0.0346 0.0340 0.0352 FL Jul 8 3,821,763 2,022,891 6,248,963 0.0405 0.0405 0.0398 FL Jul 9 4,365,148 2,340,596 6,971,523 0.0462 0.0468 0.0444 FL Jul 10 4,659,769 2,540,243 7,541,648 0.0494 0.0508 0.0480 FL Jul 11 4,938,917 2,677,430 7,996,631 0.0523 0.0535 0.0509 FL Jul 12 5,043,492 2,757,728 8,295,607 0.0534 0.0551 0.0528 FL Jul 13 5,104,851 2,795,003 8,439,245 0.0541 0.0559 0.0537 FL Jul 14 5,115,175 2,792,514 8,465,961 0.0542 0.0558 0.0539 FL Jul 15 5,105,309 2,772,194 8,441,744 0.0541 0.0554 0.0537 FL Jul 16 5,058,076 2,740,193 8,339,669 0.0536 0.0548 0.0531 FL Jul 17 4,909,169 2,648,749 8,102,609 0.0520 0.0530 0.0516 FL Jul 18 4,706,304 2,524,426 7,752,706 0.0499 0.0505 0.0494 FL Jul 19 4,682,476 2,493,147 7,516,717 0.0496 0.0499 0.0479 FL Jul 20 4,574,717 2,417,075 7,252,137 0.0485 0.0483 0.0462 FL Jul 21 4,180,311 2,159,689 6,642,740 0.0443 0.0432 0.0423 FL Jul 22 3,690,444 1,863,713 5,927,220 0.0391 0.0373 0.0377 FL Jul 23 3,150,654 1,594,768 5,271,908 0.0334 0.0319 0.0336 FL Aug 0 2,608,883 1,386,882 4,979,830 0.0280 0.0277 0.0310 FL Aug 1 2,437,417 1,276,225 4,755,731 0.0262 0.0255 0.0296 FL Aug 2 2,354,421 1,214,270 4,627,584 0.0253 0.0242 0.0288 FL Aug 3 2,313,626 1,192,577 4,574,524 0.0249 0.0238 0.0285 FL Aug 4 2,395,781 1,248,024 4,668,581 0.0257 0.0249 0.0291 FL Aug 5 2,688,209 1,412,342 4,977,943 0.0289 0.0282 0.0310 FL Aug 6 2,880,070 1,555,155 5,209,770 0.0310 0.0311 0.0324 FL Aug 7 3,164,114 1,702,356 5,623,819 0.0340 0.0340 0.0350 FL Aug 8 3,626,746 1,991,233 6,319,345 0.0390 0.0398 0.0393 FL Aug 9 4,226,563 2,323,985 7,000,308 0.0454 0.0464 0.0436 FL Aug 10 4,636,871 2,548,869 7,564,068 0.0498 0.0509 0.0471 FL Aug 11 4,957,215 2,688,031 8,078,386 0.0533 0.0537 0.0503 FL Aug 12 5,111,701 2,758,274 8,439,913 0.0549 0.0551 0.0526 FL Aug 13 5,173,346 2,779,967 8,610,449 0.0556 0.0555 0.0536 FL Aug 14 5,162,257 2,796,689 8,674,792 0.0555 0.0558 0.0540 FL Aug 15 5,164,485 2,800,364 8,660,851 0.0555 0.0559 0.0539 FL Aug 16 5,109,262 2,768,931 8,561,034 0.0549 0.0553 0.0533 FL Aug 17 4,943,811 2,672,121 8,286,667 0.0531 0.0534 0.0516 FL Aug 18 4,738,381 2,558,304 7,938,631 0.0509 0.0511 0.0494 FL Aug 19 4,694,499 2,563,794 7,774,096 0.0505 0.0512 0.0484 FL Aug 20 4,439,949 2,401,878 7,361,739 0.0477 0.0480 0.0458

D-9Atmospheric Sciences Group 

### Appendix D Actual 2002 State Level Monthly-Diurnal Profiles

CEM-Based Distribution Alpine Geophysics

SO2 Mass NOx Mass Heat Input State Month Hour [lbs] [lbs] [MMBtu] SO2 Ratio NOx Ratio Heat Input Actual Reported Values [2002] Calculated Ratios

FL Aug 21 3,921,356 2,096,770 6,659,633 0.0421 0.0419 0.0415 FL Aug 22 3,382,248 1,799,085 5,939,495 0.0364 0.0359 0.0370 FL Aug 23 2,910,211 1,540,920 5,314,172 0.0313 0.0308 0.0331 FL Sep 0 2,708,611 1,387,186 4,784,932 0.0290 0.0282 0.0308 FL Sep 1 2,514,397 1,279,494 4,573,301 0.0269 0.0260 0.0294 FL Sep 2 2,398,720 1,225,302 4,424,367 0.0257 0.0249 0.0285 FL Sep 3 2,422,626 1,203,096 4,388,493 0.0260 0.0245 0.0282 FL Sep 4 2,506,904 1,261,239 4,510,807 0.0269 0.0256 0.0290 FL Sep 5 2,794,786 1,444,834 4,896,159 0.0299 0.0294 0.0315 FL Sep 6 3,005,639 1,592,511 5,171,211 0.0322 0.0324 0.0333 FL Sep 7 3,270,983 1,716,554 5,497,234 0.0350 0.0349 0.0354 FL Sep 8 3,786,093 2,002,631 6,124,390 0.0406 0.0407 0.0394 FL Sep 9 4,229,653 2,275,995 6,778,310 0.0453 0.0463 0.0436 FL Sep 10 4,554,202 2,445,027 7,319,218 0.0488 0.0497 0.0471 FL Sep 11 4,740,934 2,544,115 7,752,600 0.0508 0.0517 0.0499 FL Sep 12 4,839,713 2,614,613 8,047,634 0.0518 0.0532 0.0518 FL Sep 13 4,933,152 2,649,517 8,199,271 0.0528 0.0539 0.0528 FL Sep 14 4,958,121 2,667,247 8,261,451 0.0531 0.0542 0.0532 FL Sep 15 5,021,128 2,695,063 8,304,722 0.0538 0.0548 0.0534 FL Sep 16 5,024,782 2,673,650 8,237,181 0.0538 0.0544 0.0530 FL Sep 17 4,878,090 2,594,131 8,034,281 0.0523 0.0527 0.0517 FL Sep 18 4,805,646 2,553,110 7,856,441 0.0515 0.0519 0.0505 FL Sep 19 4,768,398 2,545,932 7,693,340 0.0511 0.0518 0.0495 FL Sep 20 4,493,000 2,355,915 7,183,854 0.0481 0.0479 0.0462 FL Sep 21 4,052,049 2,090,276 6,459,353 0.0434 0.0425 0.0416 FL Sep 22 3,578,820 1,811,223 5,782,777 0.0383 0.0368 0.0372 FL Sep 23 3,062,785 1,555,331 5,151,784 0.0328 0.0316 0.0331 FL Oct 0 2,422,224 1,290,455 4,446,933 0.0288 0.0276 0.0304 FL Oct 1 2,221,106 1,205,028 4,239,433 0.0264 0.0257 0.0290 FL Oct 2 2,105,140 1,161,576 4,097,228 0.0250 0.0248 0.0280 FL Oct 3 2,092,128 1,169,293 4,070,536 0.0248 0.0250 0.0278 FL Oct 4 2,160,334 1,221,328 4,181,679 0.0257 0.0261 0.0286 FL Oct 5 2,463,876 1,392,473 4,598,178 0.0293 0.0297 0.0314 FL Oct 6 2,719,176 1,558,485 4,924,325 0.0323 0.0333 0.0336 FL Oct 7 2,956,227 1,659,338 5,200,175 0.0351 0.0354 0.0355 FL Oct 8 3,400,452 1,939,313 5,776,142 0.0404 0.0414 0.0395 FL Oct 9 3,818,689 2,193,478 6,389,625 0.0453 0.0468 0.0437 FL Oct 10 4,066,601 2,304,802 6,845,470 0.0483 0.0492 0.0468 FL Oct 11 4,228,972 2,388,141 7,234,608 0.0502 0.0510 0.0494 FL Oct 12 4,352,260 2,458,552 7,565,589 0.0517 0.0525 0.0517 FL Oct 13 4,459,482 2,509,089 7,723,420 0.0530 0.0536 0.0528 FL Oct 14 4,537,436 2,534,034 7,803,083 0.0539 0.0541 0.0533 FL Oct 15 4,558,251 2,547,198 7,842,287 0.0541 0.0544 0.0536 FL Oct 16 4,519,088 2,517,130 7,772,732 0.0537 0.0537 0.0531 FL Oct 17 4,448,813 2,462,966 7,617,209 0.0528 0.0526 0.0520 FL Oct 18 4,427,654 2,477,421 7,609,288 0.0526 0.0529 0.0520 FL Oct 19 4,329,673 2,406,661 7,377,367 0.0514 0.0514 0.0504 FL Oct 20 4,076,034 2,232,148 6,770,143 0.0484 0.0477 0.0463 FL Oct 21 3,741,614 2,013,886 6,066,147 0.0444 0.0430 0.0415 FL Oct 22 3,308,374 1,739,951 5,422,231 0.0393 0.0371 0.0371 FL Oct 23 2,800,845 1,454,747 4,773,460 0.0333 0.0311 0.0326 FL Nov 0 1,905,132 1,003,990 3,433,701 0.0316 0.0303 0.0324 FL Nov 1 1,776,295 942,635 3,297,448 0.0294 0.0285 0.0312

D-10Atmospheric Sciences Group 

### Appendix D Actual 2002 State Level Monthly-Diurnal Profiles

CEM-Based Distribution Alpine Geophysics

SO2 Mass NOx Mass Heat Input State Month Hour [lbs] [lbs] [MMBtu] SO2 Ratio NOx Ratio Heat Input Actual Reported Values [2002] Calculated Ratios

FL Nov 2 1,720,649 915,919 3,241,600 0.0285 0.0277 0.0306 FL Nov 3 1,716,201 912,836 3,232,048 0.0284 0.0276 0.0305 FL Nov 4 1,752,891 941,352 3,301,467 0.0290 0.0284 0.0312 FL Nov 5 1,923,578 1,034,631 3,553,069 0.0319 0.0313 0.0336 FL Nov 6 2,206,824 1,219,971 4,004,690 0.0366 0.0369 0.0378 FL Nov 7 2,429,823 1,354,748 4,353,493 0.0402 0.0409 0.0411 FL Nov 8 2,539,198 1,427,671 4,577,180 0.0421 0.0431 0.0432 FL Nov 9 2,699,341 1,513,974 4,772,232 0.0447 0.0457 0.0451 FL Nov 10 2,792,366 1,563,604 4,873,110 0.0463 0.0472 0.0460 FL Nov 11 2,831,979 1,586,315 4,913,748 0.0469 0.0479 0.0464 FL Nov 12 2,859,948 1,597,981 4,974,149 0.0474 0.0483 0.0470 FL Nov 13 2,882,171 1,613,453 4,999,215 0.0477 0.0487 0.0472 FL Nov 14 2,859,560 1,605,351 4,994,232 0.0474 0.0485 0.0472 FL Nov 15 2,861,307 1,590,790 4,986,532 0.0474 0.0481 0.0471 FL Nov 16 2,884,918 1,583,826 4,972,123 0.0478 0.0479 0.0470 FL Nov 17 3,033,337 1,663,972 5,145,039 0.0502 0.0503 0.0486 FL Nov 18 3,307,458 1,829,838 5,449,317 0.0548 0.0553 0.0515 FL Nov 19 3,160,750 1,739,759 5,286,470 0.0524 0.0526 0.0499 FL Nov 20 2,947,565 1,597,543 4,995,779 0.0488 0.0483 0.0472 FL Nov 21 2,689,128 1,442,497 4,604,876 0.0445 0.0436 0.0435 FL Nov 22 2,447,020 1,285,405 4,154,027 0.0405 0.0388 0.0392 FL Nov 23 2,147,528 1,130,622 3,739,137 0.0356 0.0342 0.0353 FL Dec 0 2,372,123 1,264,648 3,881,404 0.0330 0.0330 0.0347 FL Dec 1 2,245,185 1,183,650 3,717,536 0.0312 0.0309 0.0333 FL Dec 2 2,206,899 1,157,339 3,654,568 0.0307 0.0302 0.0327 FL Dec 3 2,236,869 1,165,095 3,679,289 0.0311 0.0304 0.0329 FL Dec 4 2,322,902 1,210,969 3,801,230 0.0323 0.0316 0.0340 FL Dec 5 2,510,538 1,322,618 4,098,961 0.0349 0.0345 0.0367 FL Dec 6 2,874,429 1,544,008 4,618,700 0.0400 0.0403 0.0413 FL Dec 7 3,213,825 1,716,219 5,019,009 0.0447 0.0448 0.0449 FL Dec 8 3,356,460 1,784,855 5,171,955 0.0467 0.0466 0.0463 FL Dec 9 3,393,441 1,801,923 5,174,899 0.0472 0.0470 0.0463 FL Dec 10 3,356,634 1,791,702 5,082,097 0.0467 0.0467 0.0455 FL Dec 11 3,222,421 1,737,039 4,907,740 0.0448 0.0453 0.0439 FL Dec 12 3,123,973 1,689,904 4,791,163 0.0435 0.0441 0.0429 FL Dec 13 3,025,463 1,634,947 4,687,544 0.0421 0.0427 0.0420 FL Dec 14 2,925,363 1,568,048 4,596,479 0.0407 0.0409 0.0411 FL Dec 15 2,897,980 1,556,949 4,581,226 0.0403 0.0406 0.0410 FL Dec 16 2,996,515 1,599,374 4,667,701 0.0417 0.0417 0.0418 FL Dec 17 3,357,392 1,784,690 5,030,380 0.0467 0.0466 0.0450 FL Dec 18 3,804,081 2,038,224 5,585,788 0.0529 0.0532 0.0500 FL Dec 19 3,740,986 2,008,136 5,549,078 0.0521 0.0524 0.0497 FL Dec 20 3,612,719 1,923,594 5,383,213 0.0503 0.0502 0.0482 FL Dec 21 3,353,392 1,793,466 5,093,614 0.0467 0.0468 0.0456 FL Dec 22 3,034,792 1,622,585 4,679,589 0.0422 0.0423 0.0419 FL Dec 23 2,668,864 1,431,479 4,249,530 0.0371 0.0373 0.0380 GA Jan 0 3,081,484 1,016,202 2,340,253 0.0377 0.0366 0.0369 GA Jan 1 2,949,286 964,517 2,195,318 0.0361 0.0347 0.0346 GA Jan 2 2,865,505 936,415 2,126,012 0.0350 0.0337 0.0335 GA Jan 3 2,900,519 943,348 2,150,704 0.0355 0.0339 0.0339 GA Jan 4 2,957,851 966,570 2,217,577 0.0362 0.0348 0.0350 GA Jan 5 3,145,168 1,038,599 2,403,042 0.0385 0.0374 0.0379 GA Jan 6 3,435,901 1,159,035 2,660,473 0.0420 0.0417 0.0420

D-11Atmospheric Sciences Group 

### Appendix D Actual 2002 State Level Monthly-Diurnal Profiles

CEM-Based Distribution Alpine Geophysics

SO2 Mass NOx Mass Heat Input State Month Hour [lbs] [lbs] [MMBtu] SO2 Ratio NOx Ratio Heat Input Actual Reported Values [2002] Calculated Ratios

GA Jan 7 3,604,884 1,224,737 2,834,892 0.0441 0.0441 0.0447 GA Jan 8 3,628,562 1,254,786 2,879,729 0.0444 0.0451 0.0454 GA Jan 9 3,688,435 1,273,855 2,917,373 0.0451 0.0458 0.0460 GA Jan 10 3,677,299 1,270,527 2,895,397 0.0450 0.0457 0.0457 GA Jan 11 3,615,236 1,245,228 2,829,872 0.0442 0.0448 0.0446 GA Jan 12 3,539,550 1,221,446 2,764,815 0.0433 0.0439 0.0436 GA Jan 13 3,470,848 1,199,782 2,719,272 0.0425 0.0432 0.0429 GA Jan 14 3,378,883 1,167,399 2,656,164 0.0413 0.0420 0.0419 GA Jan 15 3,380,835 1,159,983 2,647,659 0.0414 0.0417 0.0418 GA Jan 16 3,387,504 1,158,424 2,648,109 0.0414 0.0417 0.0418 GA Jan 17 3,476,139 1,193,922 2,719,762 0.0425 0.0429 0.0429 GA Jan 18 3,714,008 1,288,852 2,925,435 0.0454 0.0464 0.0461 GA Jan 19 3,729,879 1,296,346 2,945,555 0.0456 0.0466 0.0464 GA Jan 20 3,677,547 1,272,235 2,884,245 0.0450 0.0458 0.0455 GA Jan 21 3,662,914 1,258,425 2,847,536 0.0448 0.0453 0.0449 GA Jan 22 3,513,472 1,196,251 2,711,276 0.0430 0.0430 0.0428 GA Jan 23 3,274,893 1,092,325 2,495,423 0.0401 0.0393 0.0394 GA Feb 0 2,595,393 840,335 1,964,091 0.0381 0.0368 0.0374 GA Feb 1 2,438,479 773,016 1,806,224 0.0358 0.0339 0.0344 GA Feb 2 2,402,466 761,473 1,772,263 0.0353 0.0334 0.0337 GA Feb 3 2,430,819 771,214 1,797,003 0.0357 0.0338 0.0342 GA Feb 4 2,502,545 797,704 1,868,587 0.0367 0.0350 0.0355 GA Feb 5 2,676,776 872,805 2,052,106 0.0393 0.0383 0.0390 GA Feb 6 2,954,890 990,105 2,337,884 0.0434 0.0434 0.0445 GA Feb 7 3,001,646 1,020,225 2,409,980 0.0441 0.0447 0.0458 GA Feb 8 3,010,620 1,033,092 2,419,402 0.0442 0.0453 0.0460 GA Feb 9 3,028,005 1,040,937 2,411,898 0.0444 0.0456 0.0459 GA Feb 10 3,025,164 1,042,323 2,373,556 0.0444 0.0457 0.0452 GA Feb 11 3,005,101 1,037,541 2,338,672 0.0441 0.0455 0.0445 GA Feb 12 2,937,709 1,010,754 2,278,298 0.0431 0.0443 0.0433 GA Feb 13 2,873,477 985,976 2,232,689 0.0422 0.0432 0.0425 GA Feb 14 2,840,695 969,492 2,199,902 0.0417 0.0425 0.0418 GA Feb 15 2,823,748 958,191 2,175,080 0.0414 0.0420 0.0414 GA Feb 16 2,814,802 942,200 2,162,280 0.0413 0.0413 0.0411 GA Feb 17 2,843,641 945,750 2,176,934 0.0417 0.0415 0.0414 GA Feb 18 2,993,582 999,573 2,296,217 0.0439 0.0438 0.0437 GA Feb 19 3,065,711 1,037,202 2,367,065 0.0450 0.0455 0.0450 GA Feb 20 3,045,727 1,029,512 2,353,794 0.0447 0.0451 0.0448 GA Feb 21 3,033,325 1,024,219 2,339,301 0.0445 0.0449 0.0445 GA Feb 22 2,964,313 997,382 2,275,595 0.0435 0.0437 0.0433 GA Feb 23 2,824,858 933,895 2,157,763 0.0415 0.0409 0.0410 GA Mar 0 3,417,026 1,057,909 2,624,626 0.0384 0.0380 0.0379 GA Mar 1 3,223,285 986,736 2,424,761 0.0362 0.0354 0.0350 GA Mar 2 3,100,577 950,982 2,331,005 0.0348 0.0341 0.0337 GA Mar 3 3,099,235 951,567 2,335,602 0.0348 0.0341 0.0338 GA Mar 4 3,160,512 966,120 2,403,292 0.0355 0.0347 0.0347 GA Mar 5 3,379,124 1,038,161 2,612,688 0.0380 0.0373 0.0378 GA Mar 6 3,677,933 1,137,574 2,897,527 0.0413 0.0408 0.0419 GA Mar 7 3,802,103 1,180,891 3,009,686 0.0427 0.0424 0.0435 GA Mar 8 3,829,788 1,198,884 3,035,573 0.0430 0.0430 0.0439 GA Mar 9 3,911,099 1,219,591 3,081,701 0.0439 0.0438 0.0445 GA Mar 10 3,971,013 1,241,090 3,111,307 0.0446 0.0445 0.0450 GA Mar 11 3,982,510 1,251,231 3,115,945 0.0447 0.0449 0.0450

D-12Atmospheric Sciences Group 

### Appendix D Actual 2002 State Level Monthly-Diurnal Profiles

CEM-Based Distribution Alpine Geophysics

SO2 Mass NOx Mass Heat Input State Month Hour [lbs] [lbs] [MMBtu] SO2 Ratio NOx Ratio Heat Input Actual Reported Values [2002] Calculated Ratios

GA Mar 12 3,977,999 1,247,441 3,090,907 0.0447 0.0448 0.0447 GA Mar 13 3,935,417 1,239,080 3,057,292 0.0442 0.0445 0.0442 GA Mar 14 3,896,650 1,231,954 3,037,551 0.0438 0.0442 0.0439 GA Mar 15 3,864,947 1,227,906 3,026,695 0.0434 0.0441 0.0437 GA Mar 16 3,854,437 1,226,266 3,012,634 0.0433 0.0440 0.0435 GA Mar 17 3,833,826 1,211,299 2,968,105 0.0431 0.0435 0.0429 GA Mar 18 3,864,032 1,216,869 2,988,038 0.0434 0.0437 0.0432 GA Mar 19 4,003,952 1,271,071 3,125,736 0.0450 0.0456 0.0452 GA Mar 20 3,964,763 1,260,303 3,107,123 0.0445 0.0452 0.0449 GA Mar 21 3,910,822 1,245,091 3,063,826 0.0439 0.0447 0.0443 GA Mar 22 3,771,398 1,190,601 2,943,504 0.0424 0.0427 0.0425 GA Mar 23 3,583,337 1,119,695 2,779,688 0.0403 0.0402 0.0402 GA Apr 0 2,789,663 843,201 2,174,794 0.0346 0.0337 0.0326 GA Apr 1 2,548,208 762,521 1,983,443 0.0316 0.0305 0.0298 GA Apr 2 2,435,657 726,336 1,897,465 0.0302 0.0290 0.0285 GA Apr 3 2,453,167 728,709 1,906,139 0.0305 0.0291 0.0286 GA Apr 4 2,618,393 776,135 2,032,694 0.0325 0.0310 0.0305 GA Apr 5 3,028,015 914,585 2,359,985 0.0376 0.0366 0.0354 GA Apr 6 3,248,036 998,019 2,550,297 0.0403 0.0399 0.0383 GA Apr 7 3,387,864 1,048,569 2,678,347 0.0421 0.0419 0.0402 GA Apr 8 3,516,925 1,096,858 2,792,179 0.0437 0.0438 0.0419 GA Apr 9 3,601,256 1,129,425 2,901,164 0.0447 0.0451 0.0436 GA Apr 10 3,660,869 1,154,007 3,010,283 0.0455 0.0461 0.0452 GA Apr 11 3,685,891 1,165,890 3,083,589 0.0458 0.0466 0.0463 GA Apr 12 3,690,720 1,170,578 3,143,491 0.0458 0.0468 0.0472 GA Apr 13 3,712,291 1,177,805 3,220,634 0.0461 0.0471 0.0483 GA Apr 14 3,730,433 1,186,350 3,265,617 0.0463 0.0474 0.0490 GA Apr 15 3,754,238 1,194,345 3,303,224 0.0466 0.0477 0.0496 GA Apr 16 3,738,027 1,186,158 3,287,172 0.0464 0.0474 0.0493 GA Apr 17 3,679,438 1,161,133 3,232,864 0.0457 0.0464 0.0485 GA Apr 18 3,578,838 1,122,980 3,121,158 0.0444 0.0449 0.0469 GA Apr 19 3,725,133 1,172,544 3,227,991 0.0463 0.0469 0.0485 GA Apr 20 3,791,970 1,189,274 3,240,056 0.0471 0.0475 0.0486 GA Apr 21 3,651,034 1,132,938 3,033,113 0.0453 0.0453 0.0455 GA Apr 22 3,386,986 1,039,348 2,724,809 0.0421 0.0415 0.0409 GA Apr 23 3,109,735 942,129 2,443,848 0.0386 0.0377 0.0367 GA May 0 2,862,510 703,226 2,229,240 0.0337 0.0321 0.0321 GA May 1 2,690,290 653,170 2,096,545 0.0317 0.0298 0.0302 GA May 2 2,628,393 632,035 2,047,433 0.0310 0.0288 0.0295 GA May 3 2,627,406 630,748 2,046,614 0.0310 0.0287 0.0295 GA May 4 2,771,990 676,333 2,168,902 0.0327 0.0308 0.0312 GA May 5 3,111,208 786,240 2,454,397 0.0367 0.0358 0.0354 GA May 6 3,255,210 828,469 2,571,194 0.0384 0.0378 0.0370 GA May 7 3,381,486 877,460 2,709,196 0.0398 0.0400 0.0390 GA May 8 3,592,044 927,355 2,876,947 0.0423 0.0423 0.0414 GA May 9 3,760,249 983,699 3,017,186 0.0443 0.0448 0.0435 GA May 10 3,894,932 1,024,621 3,145,229 0.0459 0.0467 0.0453 GA May 11 3,966,104 1,042,102 3,241,704 0.0467 0.0475 0.0467 GA May 12 3,984,238 1,053,209 3,316,947 0.0469 0.0480 0.0478 GA May 13 3,988,683 1,056,839 3,395,215 0.0470 0.0482 0.0489 GA May 14 4,018,010 1,064,121 3,459,352 0.0473 0.0485 0.0498 GA May 15 4,048,235 1,069,427 3,488,917 0.0477 0.0487 0.0503 GA May 16 4,020,133 1,063,467 3,458,272 0.0474 0.0485 0.0498

D-13Atmospheric Sciences Group 

### Appendix D Actual 2002 State Level Monthly-Diurnal Profiles

CEM-Based Distribution Alpine Geophysics

SO2 Mass NOx Mass Heat Input State Month Hour [lbs] [lbs] [MMBtu] SO2 Ratio NOx Ratio Heat Input Actual Reported Values [2002] Calculated Ratios

GA May 17 3,995,337 1,051,934 3,396,551 0.0471 0.0479 0.0489 GA May 18 3,890,290 1,024,500 3,288,080 0.0458 0.0467 0.0474 GA May 19 3,894,083 1,029,554 3,276,798 0.0459 0.0469 0.0472 GA May 20 4,009,084 1,068,147 3,347,594 0.0472 0.0487 0.0482 GA May 21 3,828,790 1,002,938 3,119,169 0.0451 0.0457 0.0449 GA May 22 3,489,841 890,368 2,777,349 0.0411 0.0406 0.0400 GA May 23 3,166,236 799,617 2,495,515 0.0373 0.0364 0.0359 GA Jun 0 3,008,914 739,466 2,442,026 0.0328 0.0315 0.0311 GA Jun 1 2,806,664 689,690 2,290,927 0.0306 0.0294 0.0292 GA Jun 2 2,707,968 661,059 2,214,208 0.0295 0.0282 0.0282 GA Jun 3 2,658,218 646,893 2,177,901 0.0290 0.0276 0.0278 GA Jun 4 2,727,775 665,830 2,244,559 0.0297 0.0284 0.0286 GA Jun 5 2,979,157 728,225 2,453,292 0.0325 0.0311 0.0313 GA Jun 6 3,220,038 787,563 2,634,034 0.0351 0.0336 0.0336 GA Jun 7 3,554,723 876,796 2,912,390 0.0387 0.0374 0.0371 GA Jun 8 3,897,756 960,357 3,200,488 0.0425 0.0409 0.0408 GA Jun 9 4,211,665 1,074,809 3,481,640 0.0459 0.0458 0.0444 GA Jun 10 4,401,278 1,155,721 3,684,921 0.0480 0.0493 0.0470 GA Jun 11 4,499,677 1,182,059 3,814,987 0.0490 0.0504 0.0486 GA Jun 12 4,474,133 1,191,431 3,917,905 0.0488 0.0508 0.0499 GA Jun 13 4,468,729 1,191,448 4,024,775 0.0487 0.0508 0.0513 GA Jun 14 4,444,476 1,167,277 4,045,510 0.0484 0.0498 0.0516 GA Jun 15 4,453,900 1,174,999 4,081,582 0.0485 0.0501 0.0520 GA Jun 16 4,435,292 1,170,664 4,040,416 0.0483 0.0499 0.0515 GA Jun 17 4,420,522 1,162,399 3,983,193 0.0482 0.0496 0.0508 GA Jun 18 4,323,560 1,125,121 3,854,256 0.0471 0.0480 0.0491 GA Jun 19 4,300,376 1,114,807 3,762,531 0.0469 0.0475 0.0480 GA Jun 20 4,400,072 1,149,139 3,788,244 0.0479 0.0490 0.0483 GA Jun 21 4,232,409 1,079,052 3,558,073 0.0461 0.0460 0.0454 GA Jun 22 3,771,866 932,998 3,101,363 0.0411 0.0398 0.0395 GA Jun 23 3,368,903 825,016 2,734,365 0.0367 0.0352 0.0349 GA Jul 0 3,546,728 850,270 2,801,407 0.0351 0.0327 0.0308 GA Jul 1 3,286,519 788,821 2,603,679 0.0325 0.0304 0.0286 GA Jul 2 3,151,827 752,881 2,507,999 0.0312 0.0290 0.0276 GA Jul 3 3,047,078 727,991 2,439,217 0.0301 0.0280 0.0268 GA Jul 4 3,076,871 739,541 2,496,442 0.0304 0.0285 0.0275 GA Jul 5 3,327,006 801,637 2,731,612 0.0329 0.0308 0.0301 GA Jul 6 3,545,378 862,171 2,936,247 0.0351 0.0332 0.0323 GA Jul 7 3,886,676 963,246 3,218,154 0.0384 0.0371 0.0354 GA Jul 8 4,279,139 1,069,723 3,555,188 0.0423 0.0412 0.0391 GA Jul 9 4,592,856 1,180,153 3,875,590 0.0454 0.0454 0.0426 GA Jul 10 4,760,474 1,256,275 4,168,707 0.0471 0.0483 0.0459 GA Jul 11 4,823,385 1,288,919 4,437,842 0.0477 0.0496 0.0488 GA Jul 12 4,817,667 1,299,954 4,649,944 0.0476 0.0500 0.0512 GA Jul 13 4,795,180 1,292,611 4,777,930 0.0474 0.0497 0.0526 GA Jul 14 4,811,790 1,290,783 4,865,630 0.0476 0.0497 0.0535 GA Jul 15 4,808,412 1,288,459 4,884,975 0.0475 0.0496 0.0537 GA Jul 16 4,766,908 1,274,466 4,819,432 0.0471 0.0490 0.0530 GA Jul 17 4,754,857 1,266,101 4,742,004 0.0470 0.0487 0.0522 GA Jul 18 4,712,471 1,255,183 4,621,128 0.0466 0.0483 0.0508 GA Jul 19 4,689,089 1,240,539 4,472,248 0.0464 0.0477 0.0492 GA Jul 20 4,762,284 1,261,497 4,395,554 0.0471 0.0485 0.0484 GA Jul 21 4,605,730 1,193,090 4,102,357 0.0455 0.0459 0.0451

D-14Atmospheric Sciences Group 

### Appendix D Actual 2002 State Level Monthly-Diurnal Profiles

CEM-Based Distribution Alpine Geophysics

SO2 Mass NOx Mass Heat Input State Month Hour [lbs] [lbs] [MMBtu] SO2 Ratio NOx Ratio Heat Input Actual Reported Values [2002] Calculated Ratios

GA Jul 22 4,342,713 1,084,216 3,622,986 0.0429 0.0417 0.0399 GA Jul 23 3,942,001 959,108 3,166,148 0.0390 0.0369 0.0348 GA Aug 0 3,347,635 808,884 2,691,013 0.0334 0.0314 0.0300 GA Aug 1 3,108,946 752,274 2,511,485 0.0311 0.0292 0.0280 GA Aug 2 2,960,090 714,038 2,394,293 0.0296 0.0278 0.0267 GA Aug 3 2,891,878 698,505 2,353,093 0.0289 0.0272 0.0262 GA Aug 4 2,991,531 730,269 2,454,200 0.0299 0.0284 0.0273 GA Aug 5 3,402,119 839,676 2,803,938 0.0340 0.0326 0.0312 GA Aug 6 3,610,005 886,341 2,982,179 0.0361 0.0345 0.0332 GA Aug 7 3,846,318 958,340 3,193,482 0.0384 0.0373 0.0356 GA Aug 8 4,186,561 1,047,722 3,491,777 0.0418 0.0407 0.0389 GA Aug 9 4,492,241 1,154,701 3,812,415 0.0449 0.0449 0.0425 GA Aug 10 4,713,264 1,235,548 4,124,383 0.0471 0.0480 0.0460 GA Aug 11 4,808,173 1,270,462 4,407,168 0.0480 0.0494 0.0491 GA Aug 12 4,806,515 1,293,425 4,614,453 0.0480 0.0503 0.0514 GA Aug 13 4,773,293 1,290,448 4,724,098 0.0477 0.0502 0.0526 GA Aug 14 4,821,465 1,301,317 4,810,453 0.0482 0.0506 0.0536 GA Aug 15 4,837,464 1,305,484 4,853,821 0.0483 0.0508 0.0541 GA Aug 16 4,832,156 1,291,100 4,827,250 0.0483 0.0502 0.0538 GA Aug 17 4,814,712 1,275,253 4,755,263 0.0481 0.0496 0.0530 GA Aug 18 4,754,811 1,251,543 4,614,937 0.0475 0.0487 0.0514 GA Aug 19 4,826,464 1,272,706 4,530,597 0.0482 0.0495 0.0505 GA Aug 20 4,876,143 1,275,387 4,379,870 0.0487 0.0496 0.0488 GA Aug 21 4,573,014 1,151,787 3,954,395 0.0457 0.0448 0.0441 GA Aug 22 4,147,761 1,020,685 3,456,135 0.0414 0.0397 0.0385 GA Aug 23 3,683,286 896,764 2,996,067 0.0368 0.0349 0.0334 GA Sep 0 3,009,475 732,602 2,389,452 0.0333 0.0315 0.0311 GA Sep 1 2,798,361 679,069 2,226,087 0.0310 0.0292 0.0289 GA Sep 2 2,730,489 658,755 2,169,827 0.0302 0.0284 0.0282 GA Sep 3 2,694,962 650,082 2,146,182 0.0299 0.0280 0.0279 GA Sep 4 2,844,595 690,083 2,286,997 0.0315 0.0297 0.0297 GA Sep 5 3,271,242 804,912 2,648,378 0.0362 0.0347 0.0344 GA Sep 6 3,475,122 873,271 2,813,105 0.0385 0.0376 0.0366 GA Sep 7 3,575,292 911,489 2,905,325 0.0396 0.0392 0.0378 GA Sep 8 3,818,349 976,568 3,110,425 0.0423 0.0420 0.0404 GA Sep 9 4,063,853 1,059,168 3,313,946 0.0450 0.0456 0.0431 GA Sep 10 4,195,567 1,099,444 3,453,831 0.0465 0.0473 0.0449 GA Sep 11 4,258,319 1,122,130 3,626,506 0.0472 0.0483 0.0471 GA Sep 12 4,247,401 1,130,052 3,763,897 0.0471 0.0486 0.0489 GA Sep 13 4,216,303 1,120,233 3,851,069 0.0467 0.0482 0.0501 GA Sep 14 4,286,977 1,145,800 3,947,648 0.0475 0.0493 0.0513 GA Sep 15 4,298,266 1,143,880 3,969,173 0.0476 0.0492 0.0516 GA Sep 16 4,300,760 1,143,304 3,959,467 0.0476 0.0492 0.0515 GA Sep 17 4,286,809 1,132,268 3,923,210 0.0475 0.0487 0.0510 GA Sep 18 4,251,737 1,123,463 3,856,901 0.0471 0.0484 0.0501 GA Sep 19 4,338,120 1,158,585 3,854,147 0.0481 0.0499 0.0501 GA Sep 20 4,312,678 1,136,506 3,701,142 0.0478 0.0489 0.0481 GA Sep 21 4,033,318 1,020,758 3,369,190 0.0447 0.0439 0.0438 GA Sep 22 3,628,268 896,583 2,958,396 0.0402 0.0386 0.0385 GA Sep 23 3,330,058 819,207 2,674,563 0.0369 0.0353 0.0348 GA Oct 0 3,024,341 843,008 2,383,057 0.0348 0.0336 0.0331 GA Oct 1 2,835,764 790,684 2,225,640 0.0327 0.0316 0.0309 GA Oct 2 2,752,610 762,589 2,164,809 0.0317 0.0304 0.0301

D-15Atmospheric Sciences Group 

### Appendix D Actual 2002 State Level Monthly-Diurnal Profiles

CEM-Based Distribution Alpine Geophysics

SO2 Mass NOx Mass Heat Input State Month Hour [lbs] [lbs] [MMBtu] SO2 Ratio NOx Ratio Heat Input Actual Reported Values [2002] Calculated Ratios

GA Oct 3 2,749,874 759,496 2,172,202 0.0317 0.0303 0.0302 GA Oct 4 2,925,267 814,974 2,339,237 0.0337 0.0325 0.0325 GA Oct 5 3,390,126 957,805 2,735,597 0.0391 0.0382 0.0380 GA Oct 6 3,644,766 1,053,423 2,957,529 0.0420 0.0420 0.0411 GA Oct 7 3,660,429 1,059,395 2,981,953 0.0422 0.0423 0.0414 GA Oct 8 3,834,979 1,104,456 3,135,991 0.0442 0.0441 0.0435 GA Oct 9 3,978,480 1,172,051 3,273,242 0.0458 0.0468 0.0454 GA Oct 10 4,041,725 1,196,557 3,340,349 0.0466 0.0478 0.0464 GA Oct 11 4,032,502 1,190,421 3,367,673 0.0465 0.0475 0.0468 GA Oct 12 3,991,285 1,180,209 3,400,795 0.0460 0.0471 0.0472 GA Oct 13 3,956,405 1,169,035 3,416,843 0.0456 0.0467 0.0474 GA Oct 14 3,980,852 1,165,158 3,442,999 0.0459 0.0465 0.0478 GA Oct 15 3,909,246 1,138,307 3,384,935 0.0450 0.0454 0.0470 GA Oct 16 3,835,247 1,114,350 3,316,197 0.0442 0.0445 0.0460 GA Oct 17 3,770,204 1,083,946 3,244,010 0.0434 0.0433 0.0450 GA Oct 18 3,991,327 1,166,302 3,396,098 0.0460 0.0465 0.0471 GA Oct 19 3,985,946 1,167,536 3,396,720 0.0459 0.0466 0.0472 GA Oct 20 3,922,570 1,139,658 3,307,415 0.0452 0.0455 0.0459 GA Oct 21 3,769,072 1,081,326 3,114,572 0.0434 0.0432 0.0432 GA Oct 22 3,537,128 1,016,710 2,881,077 0.0408 0.0406 0.0400 GA Oct 23 3,272,925 930,983 2,649,678 0.0377 0.0372 0.0368 GA Nov 0 2,391,540 713,386 1,844,139 0.0363 0.0359 0.0358 GA Nov 1 2,191,833 658,568 1,701,295 0.0333 0.0332 0.0330 GA Nov 2 2,170,324 652,284 1,686,387 0.0330 0.0329 0.0327 GA Nov 3 2,192,867 661,412 1,703,475 0.0333 0.0333 0.0330 GA Nov 4 2,265,811 681,905 1,761,688 0.0344 0.0344 0.0342 GA Nov 5 2,471,430 744,993 1,921,015 0.0376 0.0375 0.0373 GA Nov 6 2,798,410 840,649 2,193,449 0.0425 0.0424 0.0425 GA Nov 7 2,928,754 876,343 2,324,481 0.0445 0.0442 0.0451 GA Nov 8 2,932,187 883,546 2,332,659 0.0446 0.0445 0.0452 GA Nov 9 2,970,055 906,636 2,360,401 0.0451 0.0457 0.0458 GA Nov 10 2,977,862 907,208 2,361,423 0.0453 0.0457 0.0458 GA Nov 11 2,950,498 894,889 2,328,479 0.0448 0.0451 0.0452 GA Nov 12 2,879,839 866,218 2,260,493 0.0438 0.0436 0.0438 GA Nov 13 2,817,301 850,405 2,217,301 0.0428 0.0428 0.0430 GA Nov 14 2,783,968 836,638 2,184,224 0.0423 0.0422 0.0424 GA Nov 15 2,747,955 823,644 2,150,294 0.0418 0.0415 0.0417 GA Nov 16 2,747,342 824,060 2,154,890 0.0418 0.0415 0.0418 GA Nov 17 2,907,624 874,351 2,282,999 0.0442 0.0441 0.0443 GA Nov 18 3,128,326 954,355 2,461,924 0.0475 0.0481 0.0477 GA Nov 19 3,033,620 921,971 2,385,076 0.0461 0.0465 0.0463 GA Nov 20 3,004,830 909,942 2,359,263 0.0457 0.0458 0.0458 GA Nov 21 2,997,472 905,166 2,334,964 0.0456 0.0456 0.0453 GA Nov 22 2,891,353 874,720 2,239,642 0.0439 0.0441 0.0434 GA Nov 23 2,622,194 784,878 2,017,294 0.0398 0.0395 0.0391 GA Dec 0 3,184,757 911,373 2,349,473 0.0374 0.0377 0.0372 GA Dec 1 3,044,448 869,162 2,236,648 0.0358 0.0360 0.0354 GA Dec 2 3,001,849 858,234 2,204,723 0.0353 0.0355 0.0349 GA Dec 3 3,042,393 871,163 2,238,095 0.0357 0.0360 0.0354 GA Dec 4 3,115,407 893,785 2,299,144 0.0366 0.0370 0.0364 GA Dec 5 3,356,710 963,853 2,484,849 0.0394 0.0399 0.0393 GA Dec 6 3,601,980 1,025,340 2,675,314 0.0423 0.0424 0.0424 GA Dec 7 3,774,865 1,075,306 2,813,304 0.0443 0.0445 0.0445

D-16Atmospheric Sciences Group 

### Appendix D Actual 2002 State Level Monthly-Diurnal Profiles

CEM-Based Distribution Alpine Geophysics

SO2 Mass NOx Mass Heat Input State Month Hour [lbs] [lbs] [MMBtu] SO2 Ratio NOx Ratio Heat Input Actual Reported Values [2002] Calculated Ratios

GA Dec 8 3,846,502 1,092,262 2,872,706 0.0452 0.0452 0.0455 GA Dec 9 3,964,116 1,120,959 2,954,298 0.0466 0.0464 0.0468 GA Dec 10 3,941,586 1,110,828 2,922,525 0.0463 0.0460 0.0463 GA Dec 11 3,833,348 1,080,541 2,832,270 0.0450 0.0447 0.0448 GA Dec 12 3,655,005 1,022,879 2,690,751 0.0429 0.0423 0.0426 GA Dec 13 3,486,128 974,802 2,572,520 0.0409 0.0403 0.0407 GA Dec 14 3,379,358 946,052 2,491,664 0.0397 0.0391 0.0394 GA Dec 15 3,341,646 939,716 2,470,131 0.0393 0.0389 0.0391 GA Dec 16 3,381,507 951,842 2,500,962 0.0397 0.0394 0.0396 GA Dec 17 3,641,599 1,033,032 2,713,281 0.0428 0.0427 0.0430 GA Dec 18 3,905,537 1,111,357 2,920,685 0.0459 0.0460 0.0462 GA Dec 19 3,847,743 1,093,998 2,882,576 0.0452 0.0453 0.0456 GA Dec 20 3,836,009 1,097,050 2,878,995 0.0451 0.0454 0.0456 GA Dec 21 3,842,983 1,102,271 2,880,206 0.0451 0.0456 0.0456 GA Dec 22 3,711,113 1,058,039 2,766,944 0.0436 0.0438 0.0438 GA Dec 23 3,398,724 969,035 2,518,529 0.0399 0.0401 0.0399 KY Jan 0 3,403,668 1,530,327 3,227,175 0.0385 0.0389 0.0388 KY Jan 1 3,356,459 1,515,572 3,189,213 0.0380 0.0386 0.0383 KY Jan 2 3,351,496 1,510,032 3,178,874 0.0379 0.0384 0.0382 KY Jan 3 3,325,442 1,511,114 3,172,865 0.0376 0.0385 0.0381 KY Jan 4 3,383,306 1,536,046 3,221,053 0.0383 0.0391 0.0387 KY Jan 5 3,481,136 1,581,741 3,309,261 0.0394 0.0402 0.0398 KY Jan 6 3,716,104 1,654,464 3,492,098 0.0420 0.0421 0.0420 KY Jan 7 3,877,206 1,705,939 3,595,334 0.0439 0.0434 0.0432 KY Jan 8 3,840,350 1,712,259 3,617,341 0.0434 0.0436 0.0435 KY Jan 9 3,876,148 1,712,579 3,623,036 0.0439 0.0436 0.0436 KY Jan 10 3,875,302 1,709,885 3,616,547 0.0438 0.0435 0.0435 KY Jan 11 3,812,307 1,688,952 3,570,206 0.0431 0.0430 0.0429 KY Jan 12 3,758,419 1,676,231 3,541,721 0.0425 0.0427 0.0426 KY Jan 13 3,737,421 1,657,035 3,523,255 0.0423 0.0422 0.0424 KY Jan 14 3,687,918 1,635,905 3,475,817 0.0417 0.0416 0.0418 KY Jan 15 3,686,011 1,635,068 3,458,763 0.0417 0.0416 0.0416 KY Jan 16 3,673,933 1,630,127 3,465,012 0.0416 0.0415 0.0417 KY Jan 17 3,800,622 1,680,994 3,563,265 0.0430 0.0428 0.0428 KY Jan 18 3,927,434 1,728,430 3,662,176 0.0444 0.0440 0.0440 KY Jan 19 3,915,752 1,715,930 3,660,602 0.0443 0.0437 0.0440 KY Jan 20 3,901,330 1,713,194 3,647,940 0.0441 0.0436 0.0439 KY Jan 21 3,826,253 1,677,239 3,588,814 0.0433 0.0427 0.0431 KY Jan 22 3,685,571 1,626,726 3,471,996 0.0417 0.0414 0.0417 KY Jan 23 3,487,190 1,552,179 3,313,659 0.0395 0.0395 0.0398 KY Feb 0 2,829,863 1,334,316 2,804,656 0.0387 0.0387 0.0388 KY Feb 1 2,783,432 1,319,681 2,762,629 0.0381 0.0383 0.0383 KY Feb 2 2,780,312 1,327,383 2,758,522 0.0380 0.0385 0.0382 KY Feb 3 2,783,437 1,334,391 2,765,908 0.0381 0.0388 0.0383 KY Feb 4 2,808,633 1,347,084 2,794,191 0.0384 0.0391 0.0387 KY Feb 5 2,893,613 1,392,134 2,876,104 0.0396 0.0404 0.0398 KY Feb 6 3,124,498 1,466,306 3,062,707 0.0427 0.0426 0.0424 KY Feb 7 3,220,300 1,510,175 3,174,431 0.0440 0.0439 0.0440 KY Feb 8 3,220,342 1,519,438 3,190,584 0.0440 0.0441 0.0442 KY Feb 9 3,234,938 1,509,214 3,179,580 0.0442 0.0438 0.0440 KY Feb 10 3,219,423 1,487,640 3,151,346 0.0440 0.0432 0.0436 KY Feb 11 3,171,385 1,464,205 3,102,736 0.0434 0.0425 0.0430 KY Feb 12 3,118,981 1,450,126 3,075,598 0.0426 0.0421 0.0426

D-17Atmospheric Sciences Group 

### Appendix D Actual 2002 State Level Monthly-Diurnal Profiles

CEM-Based Distribution Alpine Geophysics

SO2 Mass NOx Mass Heat Input State Month Hour [lbs] [lbs] [MMBtu] SO2 Ratio NOx Ratio Heat Input Actual Reported Values [2002] Calculated Ratios

KY Feb 13 3,087,740 1,438,494 3,039,064 0.0422 0.0418 0.0421 KY Feb 14 3,041,776 1,425,843 3,006,107 0.0416 0.0414 0.0416 KY Feb 15 2,962,587 1,405,630 2,960,468 0.0405 0.0408 0.0410 KY Feb 16 2,969,604 1,420,115 2,969,838 0.0406 0.0412 0.0411 KY Feb 17 3,025,983 1,444,163 3,011,747 0.0414 0.0419 0.0417 KY Feb 18 3,175,924 1,502,240 3,122,661 0.0434 0.0436 0.0432 KY Feb 19 3,239,455 1,525,694 3,182,281 0.0443 0.0443 0.0441 KY Feb 20 3,241,346 1,515,277 3,170,633 0.0443 0.0440 0.0439 KY Feb 21 3,203,555 1,497,237 3,139,781 0.0438 0.0435 0.0435 KY Feb 22 3,087,236 1,431,626 3,020,520 0.0422 0.0416 0.0418 KY Feb 23 2,924,098 1,367,233 2,892,185 0.0400 0.0397 0.0401 KY Mar 0 3,185,786 1,597,308 3,209,200 0.0385 0.0388 0.0388 KY Mar 1 3,145,216 1,580,585 3,162,086 0.0380 0.0384 0.0382 KY Mar 2 3,127,009 1,566,619 3,138,402 0.0378 0.0381 0.0379 KY Mar 3 3,132,252 1,561,969 3,135,774 0.0379 0.0380 0.0379 KY Mar 4 3,173,696 1,582,742 3,172,277 0.0384 0.0385 0.0383 KY Mar 5 3,232,720 1,637,221 3,260,566 0.0391 0.0398 0.0394 KY Mar 6 3,393,169 1,699,015 3,430,167 0.0410 0.0413 0.0414 KY Mar 7 3,458,281 1,723,061 3,534,234 0.0418 0.0419 0.0427 KY Mar 8 3,509,975 1,758,137 3,589,716 0.0424 0.0428 0.0434 KY Mar 9 3,597,920 1,785,203 3,617,826 0.0435 0.0434 0.0437 KY Mar 10 3,613,242 1,790,499 3,613,791 0.0437 0.0435 0.0436 KY Mar 11 3,584,905 1,768,236 3,576,422 0.0433 0.0430 0.0432 KY Mar 12 3,544,290 1,749,911 3,544,251 0.0428 0.0426 0.0428 KY Mar 13 3,655,282 1,819,021 3,611,132 0.0442 0.0442 0.0436 KY Mar 14 3,535,794 1,757,290 3,530,484 0.0427 0.0427 0.0426 KY Mar 15 3,546,558 1,753,426 3,525,239 0.0429 0.0426 0.0426 KY Mar 16 3,520,012 1,740,871 3,508,906 0.0425 0.0423 0.0424 KY Mar 17 3,555,166 1,752,176 3,520,024 0.0430 0.0426 0.0425 KY Mar 18 3,597,891 1,773,745 3,559,003 0.0435 0.0431 0.0430 KY Mar 19 3,662,983 1,805,934 3,622,700 0.0443 0.0439 0.0438 KY Mar 20 3,642,846 1,799,363 3,611,867 0.0440 0.0438 0.0436 KY Mar 21 3,573,836 1,771,991 3,563,435 0.0432 0.0431 0.0430 KY Mar 22 3,447,860 1,712,142 3,455,996 0.0417 0.0416 0.0417 KY Mar 23 3,297,612 1,637,915 3,308,824 0.0399 0.0398 0.0400 KY Apr 0 2,652,782 1,256,983 2,775,278 0.0366 0.0376 0.0372 KY Apr 1 2,578,533 1,240,530 2,714,866 0.0355 0.0371 0.0364 KY Apr 2 2,539,099 1,232,367 2,680,329 0.0350 0.0368 0.0360 KY Apr 3 2,563,228 1,243,106 2,702,289 0.0353 0.0371 0.0363 KY Apr 4 2,669,459 1,277,918 2,797,385 0.0368 0.0382 0.0375 KY Apr 5 2,868,256 1,356,584 2,960,670 0.0395 0.0405 0.0397 KY Apr 6 3,043,737 1,395,220 3,089,577 0.0420 0.0417 0.0414 KY Apr 7 3,081,560 1,412,219 3,135,179 0.0425 0.0422 0.0421 KY Apr 8 3,152,613 1,434,867 3,196,901 0.0435 0.0429 0.0429 KY Apr 9 3,213,817 1,454,516 3,250,449 0.0443 0.0435 0.0436 KY Apr 10 3,201,104 1,460,987 3,265,708 0.0441 0.0437 0.0438 KY Apr 11 3,227,748 1,462,574 3,283,978 0.0445 0.0437 0.0441 KY Apr 12 3,244,155 1,469,970 3,296,417 0.0447 0.0439 0.0442 KY Apr 13 3,294,530 1,512,286 3,349,575 0.0454 0.0452 0.0449 KY Apr 14 3,225,863 1,467,375 3,300,463 0.0445 0.0438 0.0443 KY Apr 15 3,246,863 1,474,433 3,297,745 0.0448 0.0441 0.0442 KY Apr 16 3,181,718 1,445,314 3,259,483 0.0439 0.0432 0.0437 KY Apr 17 3,142,674 1,442,521 3,241,339 0.0433 0.0431 0.0435

D-18Atmospheric Sciences Group 

### Appendix D Actual 2002 State Level Monthly-Diurnal Profiles

CEM-Based Distribution Alpine Geophysics

SO2 Mass NOx Mass Heat Input State Month Hour [lbs] [lbs] [MMBtu] SO2 Ratio NOx Ratio Heat Input Actual Reported Values [2002] Calculated Ratios

KY Apr 18 3,126,256 1,431,467 3,235,488 0.0431 0.0428 0.0434 KY Apr 19 3,223,590 1,471,310 3,303,417 0.0444 0.0440 0.0443 KY Apr 20 3,246,443 1,484,013 3,316,619 0.0447 0.0443 0.0445 KY Apr 21 3,119,964 1,426,202 3,195,581 0.0430 0.0426 0.0429 KY Apr 22 2,927,566 1,333,595 3,018,570 0.0404 0.0398 0.0405 KY Apr 23 2,775,468 1,281,398 2,876,956 0.0383 0.0383 0.0386 KY May 0 2,753,698 1,001,149 2,871,635 0.0358 0.0358 0.0372 KY May 1 2,690,840 975,009 2,799,305 0.0350 0.0348 0.0363 KY May 2 2,641,386 961,985 2,759,918 0.0343 0.0344 0.0358 KY May 3 2,653,648 968,606 2,776,235 0.0345 0.0346 0.0360 KY May 4 2,758,274 1,006,456 2,854,851 0.0358 0.0360 0.0370 KY May 5 2,962,969 1,077,012 3,006,024 0.0385 0.0385 0.0390 KY May 6 3,108,173 1,131,439 3,108,291 0.0404 0.0404 0.0403 KY May 7 3,246,123 1,175,456 3,201,514 0.0422 0.0420 0.0415 KY May 8 3,362,209 1,211,559 3,282,879 0.0437 0.0433 0.0426 KY May 9 3,412,737 1,231,691 3,338,533 0.0443 0.0440 0.0433 KY May 10 3,427,604 1,243,925 3,367,381 0.0445 0.0445 0.0437 KY May 11 3,445,882 1,259,701 3,388,882 0.0448 0.0450 0.0440 KY May 12 3,464,924 1,274,611 3,423,353 0.0450 0.0456 0.0444 KY May 13 3,475,586 1,272,090 3,438,235 0.0451 0.0455 0.0446 KY May 14 3,473,027 1,265,149 3,444,229 0.0451 0.0452 0.0447 KY May 15 3,500,580 1,270,320 3,469,372 0.0455 0.0454 0.0450 KY May 16 3,485,066 1,268,396 3,459,248 0.0453 0.0453 0.0449 KY May 17 3,468,876 1,263,917 3,440,084 0.0451 0.0452 0.0446 KY May 18 3,415,836 1,236,715 3,384,093 0.0444 0.0442 0.0439 KY May 19 3,432,299 1,242,014 3,387,275 0.0446 0.0444 0.0439 KY May 20 3,473,176 1,256,092 3,432,270 0.0451 0.0449 0.0445 KY May 21 3,319,166 1,202,820 3,321,394 0.0431 0.0430 0.0431 KY May 22 3,091,184 1,121,825 3,142,247 0.0402 0.0401 0.0408 KY May 23 2,917,373 1,062,287 3,000,545 0.0379 0.0380 0.0389 KY Jun 0 3,087,977 1,098,570 3,176,102 0.0362 0.0360 0.0371 KY Jun 1 2,953,012 1,055,620 3,065,944 0.0346 0.0346 0.0358 KY Jun 2 2,865,983 1,026,659 2,979,935 0.0336 0.0336 0.0348 KY Jun 3 2,843,390 1,017,902 2,959,134 0.0333 0.0333 0.0346 KY Jun 4 2,906,264 1,041,091 3,002,535 0.0341 0.0341 0.0351 KY Jun 5 3,059,048 1,099,966 3,110,267 0.0359 0.0360 0.0363 KY Jun 6 3,204,088 1,146,437 3,221,607 0.0376 0.0375 0.0376 KY Jun 7 3,421,248 1,229,315 3,394,164 0.0401 0.0402 0.0397 KY Jun 8 3,621,947 1,293,765 3,549,992 0.0425 0.0424 0.0415 KY Jun 9 3,760,733 1,348,936 3,668,349 0.0441 0.0442 0.0429 KY Jun 10 3,834,572 1,383,306 3,737,507 0.0450 0.0453 0.0437 KY Jun 11 3,901,548 1,400,903 3,812,157 0.0457 0.0459 0.0445 KY Jun 12 3,932,342 1,414,479 3,876,596 0.0461 0.0463 0.0453 KY Jun 13 3,949,981 1,415,226 3,927,136 0.0463 0.0463 0.0459 KY Jun 14 3,967,478 1,427,059 3,976,104 0.0465 0.0467 0.0465 KY Jun 15 3,987,835 1,442,622 4,004,468 0.0468 0.0472 0.0468 KY Jun 16 3,986,667 1,438,679 4,016,540 0.0467 0.0471 0.0469 KY Jun 17 3,947,074 1,417,526 3,972,265 0.0463 0.0464 0.0464 KY Jun 18 3,898,341 1,390,335 3,897,748 0.0457 0.0455 0.0455 KY Jun 19 3,863,192 1,374,134 3,842,399 0.0453 0.0450 0.0449 KY Jun 20 3,830,039 1,369,835 3,822,773 0.0449 0.0448 0.0447 KY Jun 21 3,697,446 1,320,277 3,717,975 0.0433 0.0432 0.0434 KY Jun 22 3,490,495 1,234,849 3,519,303 0.0409 0.0404 0.0411

D-19Atmospheric Sciences Group 

### Appendix D Actual 2002 State Level Monthly-Diurnal Profiles

CEM-Based Distribution Alpine Geophysics

SO2 Mass NOx Mass Heat Input State Month Hour [lbs] [lbs] [MMBtu] SO2 Ratio NOx Ratio Heat Input Actual Reported Values [2002] Calculated Ratios

KY Jun 23 3,283,126 1,155,437 3,327,095 0.0385 0.0378 0.0389 KY Jul 0 3,525,121 1,331,886 3,534,514 0.0380 0.0378 0.0369 KY Jul 1 3,355,237 1,278,905 3,408,333 0.0361 0.0363 0.0356 KY Jul 2 3,215,415 1,229,615 3,298,801 0.0346 0.0349 0.0345 KY Jul 3 3,168,227 1,212,003 3,261,769 0.0341 0.0344 0.0341 KY Jul 4 3,215,166 1,224,381 3,286,885 0.0346 0.0348 0.0343 KY Jul 5 3,321,384 1,263,814 3,351,338 0.0358 0.0359 0.0350 KY Jul 6 3,465,319 1,306,343 3,461,501 0.0373 0.0371 0.0362 KY Jul 7 3,664,746 1,400,810 3,650,990 0.0395 0.0398 0.0381 KY Jul 8 3,915,678 1,481,616 3,827,253 0.0422 0.0421 0.0400 KY Jul 9 4,100,617 1,552,676 4,009,935 0.0442 0.0441 0.0419 KY Jul 10 4,141,842 1,573,982 4,151,119 0.0446 0.0447 0.0434 KY Jul 11 4,190,991 1,589,808 4,298,228 0.0451 0.0451 0.0449 KY Jul 12 4,219,096 1,595,652 4,395,777 0.0454 0.0453 0.0459 KY Jul 13 4,213,583 1,604,227 4,467,887 0.0454 0.0456 0.0467 KY Jul 14 4,224,360 1,604,273 4,523,244 0.0455 0.0456 0.0473 KY Jul 15 4,234,207 1,608,449 4,560,024 0.0456 0.0457 0.0476 KY Jul 16 4,210,072 1,604,432 4,559,755 0.0453 0.0456 0.0476 KY Jul 17 4,197,444 1,597,634 4,535,354 0.0452 0.0454 0.0474 KY Jul 18 4,139,296 1,572,406 4,460,260 0.0446 0.0447 0.0466 KY Jul 19 4,140,343 1,564,292 4,380,970 0.0446 0.0444 0.0458 KY Jul 20 4,179,115 1,575,403 4,341,558 0.0450 0.0447 0.0454 KY Jul 21 4,131,951 1,553,267 4,232,940 0.0445 0.0441 0.0442 KY Jul 22 3,957,477 1,482,271 3,988,890 0.0426 0.0421 0.0417 KY Jul 23 3,744,010 1,407,561 3,729,233 0.0403 0.0400 0.0390 KY Aug 0 3,544,915 1,202,709 3,469,105 0.0367 0.0363 0.0368 KY Aug 1 3,422,524 1,164,603 3,357,856 0.0355 0.0352 0.0356 KY Aug 2 3,338,501 1,132,562 3,267,414 0.0346 0.0342 0.0347 KY Aug 3 3,293,103 1,128,706 3,236,508 0.0341 0.0341 0.0343 KY Aug 4 3,335,828 1,148,595 3,300,443 0.0346 0.0347 0.0350 KY Aug 5 3,491,034 1,206,789 3,412,044 0.0362 0.0364 0.0362 KY Aug 6 3,642,600 1,243,553 3,522,178 0.0377 0.0375 0.0374 KY Aug 7 3,835,140 1,323,473 3,678,395 0.0397 0.0400 0.0390 KY Aug 8 4,073,626 1,399,971 3,843,845 0.0422 0.0423 0.0408 KY Aug 9 4,251,294 1,455,968 4,003,870 0.0441 0.0440 0.0425 KY Aug 10 4,347,259 1,489,535 4,136,920 0.0450 0.0450 0.0439 KY Aug 11 4,378,717 1,508,733 4,256,480 0.0454 0.0456 0.0452 KY Aug 12 4,393,903 1,524,118 4,329,887 0.0455 0.0460 0.0460 KY Aug 13 4,422,976 1,539,768 4,406,800 0.0458 0.0465 0.0468 KY Aug 14 4,437,716 1,547,653 4,443,495 0.0460 0.0467 0.0472 KY Aug 15 4,440,542 1,551,651 4,459,320 0.0460 0.0468 0.0473 KY Aug 16 4,425,588 1,545,263 4,454,603 0.0459 0.0467 0.0473 KY Aug 17 4,413,783 1,524,853 4,409,269 0.0457 0.0460 0.0468 KY Aug 18 4,380,936 1,494,913 4,303,740 0.0454 0.0451 0.0457 KY Aug 19 4,392,024 1,496,749 4,251,095 0.0455 0.0452 0.0451 KY Aug 20 4,379,610 1,485,377 4,217,501 0.0454 0.0448 0.0448 KY Aug 21 4,210,888 1,417,089 4,044,108 0.0436 0.0428 0.0429 KY Aug 22 3,941,472 1,332,682 3,817,994 0.0408 0.0402 0.0405 KY Aug 23 3,707,933 1,256,482 3,599,411 0.0384 0.0379 0.0382 KY Sep 0 2,964,289 996,485 2,919,930 0.0361 0.0357 0.0362 KY Sep 1 2,870,382 964,072 2,840,432 0.0349 0.0346 0.0352 KY Sep 2 2,787,976 943,915 2,779,477 0.0339 0.0339 0.0345 KY Sep 3 2,804,532 948,776 2,769,609 0.0341 0.0340 0.0343

D-20Atmospheric Sciences Group 

### Appendix D Actual 2002 State Level Monthly-Diurnal Profiles

CEM-Based Distribution Alpine Geophysics

SO2 Mass NOx Mass Heat Input State Month Hour [lbs] [lbs] [MMBtu] SO2 Ratio NOx Ratio Heat Input Actual Reported Values [2002] Calculated Ratios

KY Sep 4 2,898,744 989,718 2,857,648 0.0353 0.0355 0.0354 KY Sep 5 3,081,772 1,060,568 2,995,084 0.0375 0.0380 0.0371 KY Sep 6 3,215,608 1,097,097 3,121,585 0.0391 0.0394 0.0387 KY Sep 7 3,304,284 1,130,784 3,199,454 0.0402 0.0406 0.0397 KY Sep 8 3,434,411 1,171,758 3,315,509 0.0418 0.0420 0.0411 KY Sep 9 3,570,839 1,209,673 3,424,910 0.0434 0.0434 0.0425 KY Sep 10 3,678,814 1,241,639 3,519,188 0.0448 0.0445 0.0436 KY Sep 11 3,750,708 1,270,557 3,614,918 0.0456 0.0456 0.0448 KY Sep 12 3,773,180 1,277,130 3,679,481 0.0459 0.0458 0.0456 KY Sep 13 3,801,227 1,289,703 3,743,219 0.0462 0.0463 0.0464 KY Sep 14 3,800,140 1,297,044 3,787,747 0.0462 0.0465 0.0470 KY Sep 15 3,795,994 1,302,319 3,801,880 0.0462 0.0467 0.0471 KY Sep 16 3,783,543 1,300,148 3,796,428 0.0460 0.0466 0.0471 KY Sep 17 3,771,127 1,286,477 3,763,923 0.0459 0.0461 0.0467 KY Sep 18 3,765,419 1,275,206 3,722,780 0.0458 0.0457 0.0462 KY Sep 19 3,791,830 1,277,823 3,716,984 0.0461 0.0458 0.0461 KY Sep 20 3,740,714 1,250,721 3,633,445 0.0455 0.0449 0.0451 KY Sep 21 3,500,976 1,175,689 3,423,771 0.0426 0.0422 0.0425 KY Sep 22 3,242,851 1,088,648 3,194,804 0.0395 0.0391 0.0396 KY Sep 23 3,065,835 1,031,663 3,021,684 0.0373 0.0370 0.0375 KY Oct 0 2,278,896 1,039,501 2,586,750 0.0366 0.0376 0.0376 KY Oct 1 2,227,233 1,020,526 2,543,419 0.0358 0.0369 0.0370 KY Oct 2 2,198,399 1,012,344 2,512,024 0.0354 0.0366 0.0365 KY Oct 3 2,212,904 1,021,216 2,525,691 0.0356 0.0369 0.0367 KY Oct 4 2,311,335 1,052,998 2,608,913 0.0372 0.0381 0.0379 KY Oct 5 2,469,785 1,101,259 2,726,671 0.0397 0.0398 0.0397 KY Oct 6 2,637,419 1,158,074 2,862,691 0.0424 0.0419 0.0416 KY Oct 7 2,693,406 1,176,028 2,913,310 0.0433 0.0426 0.0424 KY Oct 8 2,729,754 1,188,281 2,952,105 0.0439 0.0430 0.0429 KY Oct 9 2,757,119 1,192,403 2,993,360 0.0443 0.0431 0.0435 KY Oct 10 2,723,051 1,187,873 2,995,231 0.0438 0.0430 0.0436 KY Oct 11 2,720,381 1,189,661 3,007,614 0.0437 0.0430 0.0437 KY Oct 12 2,714,978 1,194,446 3,011,627 0.0437 0.0432 0.0438 KY Oct 13 2,707,186 1,199,090 3,009,588 0.0435 0.0434 0.0438 KY Oct 14 2,706,257 1,197,544 2,994,231 0.0435 0.0433 0.0436 KY Oct 15 2,711,523 1,203,563 2,996,320 0.0436 0.0435 0.0436 KY Oct 16 2,723,684 1,210,665 3,000,402 0.0438 0.0438 0.0436 KY Oct 17 2,750,183 1,226,818 3,027,326 0.0442 0.0444 0.0440 KY Oct 18 2,804,990 1,246,471 3,066,898 0.0451 0.0451 0.0446 KY Oct 19 2,833,249 1,242,487 3,066,753 0.0456 0.0450 0.0446 KY Oct 20 2,759,348 1,216,889 3,006,234 0.0444 0.0440 0.0437 KY Oct 21 2,652,098 1,169,920 2,906,404 0.0426 0.0423 0.0423 KY Oct 22 2,494,473 1,115,242 2,771,093 0.0401 0.0404 0.0403 KY Oct 23 2,367,902 1,075,197 2,662,935 0.0381 0.0389 0.0387 KY Nov 0 2,422,536 1,118,975 2,591,748 0.0379 0.0395 0.0391 KY Nov 1 2,356,323 1,095,090 2,537,410 0.0369 0.0386 0.0383 KY Nov 2 2,367,494 1,086,653 2,516,480 0.0370 0.0383 0.0380 KY Nov 3 2,386,839 1,089,267 2,519,274 0.0373 0.0384 0.0380 KY Nov 4 2,415,740 1,106,413 2,558,320 0.0378 0.0390 0.0386 KY Nov 5 2,468,416 1,129,838 2,607,883 0.0386 0.0398 0.0393 KY Nov 6 2,632,729 1,175,377 2,735,869 0.0412 0.0414 0.0413 KY Nov 7 2,714,530 1,195,414 2,795,275 0.0425 0.0422 0.0422 KY Nov 8 2,754,488 1,204,179 2,825,323 0.0431 0.0425 0.0426

D-21Atmospheric Sciences Group 

### Appendix D Actual 2002 State Level Monthly-Diurnal Profiles

CEM-Based Distribution Alpine Geophysics

SO2 Mass NOx Mass Heat Input State Month Hour [lbs] [lbs] [MMBtu] SO2 Ratio NOx Ratio Heat Input Actual Reported Values [2002] Calculated Ratios

KY Nov 9 2,824,461 1,226,327 2,890,106 0.0442 0.0432 0.0436 KY Nov 10 2,813,806 1,227,058 2,907,006 0.0440 0.0433 0.0438 KY Nov 11 2,777,561 1,212,096 2,868,910 0.0434 0.0427 0.0433 KY Nov 12 2,750,079 1,202,290 2,850,666 0.0430 0.0424 0.0430 KY Nov 13 2,757,965 1,197,718 2,832,599 0.0431 0.0422 0.0427 KY Nov 14 2,728,342 1,183,900 2,811,323 0.0427 0.0417 0.0424 KY Nov 15 2,703,926 1,182,019 2,797,686 0.0423 0.0417 0.0422 KY Nov 16 2,711,087 1,192,712 2,800,355 0.0424 0.0421 0.0422 KY Nov 17 2,831,053 1,228,197 2,871,391 0.0443 0.0433 0.0433 KY Nov 18 2,874,376 1,248,720 2,908,424 0.0450 0.0440 0.0439 KY Nov 19 2,830,424 1,242,309 2,889,743 0.0443 0.0438 0.0436 KY Nov 20 2,809,414 1,236,011 2,877,825 0.0439 0.0436 0.0434 KY Nov 21 2,810,067 1,224,376 2,845,340 0.0439 0.0432 0.0429 KY Nov 22 2,655,656 1,192,816 2,771,150 0.0415 0.0421 0.0418 KY Nov 23 2,541,726 1,160,739 2,685,393 0.0398 0.0409 0.0405 KY Dec 0 3,397,203 1,497,727 3,221,155 0.0384 0.0394 0.0395 KY Dec 1 3,341,898 1,480,833 3,177,042 0.0378 0.0390 0.0390 KY Dec 2 3,304,945 1,464,534 3,147,297 0.0374 0.0385 0.0386 KY Dec 3 3,314,704 1,461,086 3,144,311 0.0375 0.0384 0.0386 KY Dec 4 3,357,070 1,475,238 3,171,851 0.0380 0.0388 0.0389 KY Dec 5 3,503,380 1,532,005 3,271,587 0.0396 0.0403 0.0402 KY Dec 6 3,707,600 1,592,737 3,395,494 0.0419 0.0419 0.0417 KY Dec 7 3,807,538 1,614,496 3,455,002 0.0431 0.0425 0.0424 KY Dec 8 3,860,987 1,642,801 3,506,340 0.0437 0.0432 0.0430 KY Dec 9 3,911,254 1,658,278 3,544,522 0.0442 0.0436 0.0435 KY Dec 10 3,910,089 1,644,946 3,525,036 0.0442 0.0433 0.0433 KY Dec 11 3,825,710 1,621,156 3,475,841 0.0433 0.0426 0.0427 KY Dec 12 3,783,955 1,608,546 3,449,877 0.0428 0.0423 0.0423 KY Dec 13 3,740,261 1,597,853 3,420,474 0.0423 0.0420 0.0420 KY Dec 14 3,678,324 1,579,253 3,380,910 0.0416 0.0415 0.0415 KY Dec 15 3,679,275 1,562,779 3,359,655 0.0416 0.0411 0.0412 KY Dec 16 3,723,602 1,588,964 3,403,955 0.0421 0.0418 0.0418 KY Dec 17 3,867,731 1,646,054 3,514,154 0.0437 0.0433 0.0431 KY Dec 18 3,908,982 1,662,935 3,561,609 0.0442 0.0437 0.0437 KY Dec 19 3,860,887 1,644,759 3,539,105 0.0437 0.0433 0.0434 KY Dec 20 3,867,744 1,651,301 3,543,614 0.0437 0.0434 0.0435 KY Dec 21 3,819,045 1,638,890 3,509,569 0.0432 0.0431 0.0431 KY Dec 22 3,723,350 1,603,663 3,432,871 0.0421 0.0422 0.0421 KY Dec 23 3,535,845 1,545,039 3,313,593 0.0400 0.0406 0.0407 MS Jan 0 300,037 157,706 681,031 0.0374 0.0351 0.0364 MS Jan 1 289,290 151,459 665,738 0.0360 0.0337 0.0356 MS Jan 2 287,751 148,804 660,967 0.0358 0.0331 0.0354 MS Jan 3 291,148 148,222 668,501 0.0362 0.0329 0.0358 MS Jan 4 302,852 156,414 695,674 0.0377 0.0348 0.0372 MS Jan 5 323,353 178,713 755,028 0.0403 0.0397 0.0404 MS Jan 6 348,706 198,881 818,333 0.0434 0.0442 0.0438 MS Jan 7 355,063 209,218 838,316 0.0442 0.0465 0.0448 MS Jan 8 357,451 206,704 838,060 0.0445 0.0459 0.0448 MS Jan 9 358,623 208,957 842,247 0.0447 0.0464 0.0451 MS Jan 10 356,907 204,931 839,569 0.0444 0.0456 0.0449 MS Jan 11 346,623 195,627 818,876 0.0432 0.0435 0.0438 MS Jan 12 340,586 185,527 797,895 0.0424 0.0412 0.0427 MS Jan 13 331,359 183,143 776,008 0.0413 0.0407 0.0415

D-22Atmospheric Sciences Group 

### Appendix D Actual 2002 State Level Monthly-Diurnal Profiles

CEM-Based Distribution Alpine Geophysics

SO2 Mass NOx Mass Heat Input State Month Hour [lbs] [lbs] [MMBtu] SO2 Ratio NOx Ratio Heat Input Actual Reported Values [2002] Calculated Ratios

MS Jan 14 324,003 176,230 757,019 0.0403 0.0392 0.0405 MS Jan 15 323,645 173,168 752,708 0.0403 0.0385 0.0403 MS Jan 16 333,852 181,977 777,833 0.0416 0.0405 0.0416 MS Jan 17 359,449 203,235 835,302 0.0448 0.0452 0.0447 MS Jan 18 372,202 229,266 879,363 0.0463 0.0510 0.0470 MS Jan 19 371,048 225,168 872,934 0.0462 0.0501 0.0467 MS Jan 20 367,302 220,656 855,161 0.0457 0.0491 0.0457 MS Jan 21 354,555 206,831 821,109 0.0441 0.0460 0.0439 MS Jan 22 331,412 185,461 751,395 0.0413 0.0412 0.0402 MS Jan 23 304,465 162,266 694,209 0.0379 0.0361 0.0371 MS Feb 0 181,787 144,680 592,680 0.0348 0.0332 0.0350 MS Feb 1 176,523 142,763 588,813 0.0338 0.0328 0.0348 MS Feb 2 177,588 142,598 591,129 0.0340 0.0328 0.0349 MS Feb 3 182,268 145,277 599,182 0.0349 0.0334 0.0354 MS Feb 4 200,147 159,233 639,307 0.0383 0.0366 0.0378 MS Feb 5 226,102 186,280 713,386 0.0433 0.0428 0.0422 MS Feb 6 245,608 224,842 804,213 0.0470 0.0517 0.0475 MS Feb 7 246,999 236,630 821,878 0.0473 0.0544 0.0486 MS Feb 8 242,749 223,482 799,264 0.0465 0.0513 0.0472 MS Feb 9 239,154 211,830 778,398 0.0458 0.0487 0.0460 MS Feb 10 239,008 195,473 748,970 0.0458 0.0449 0.0443 MS Feb 11 226,841 180,839 724,298 0.0434 0.0415 0.0428 MS Feb 12 216,102 168,902 699,967 0.0414 0.0388 0.0414 MS Feb 13 208,962 158,781 678,787 0.0400 0.0365 0.0401 MS Feb 14 201,923 150,653 662,724 0.0387 0.0346 0.0392 MS Feb 15 198,164 149,084 656,827 0.0379 0.0343 0.0388 MS Feb 16 204,955 155,311 668,145 0.0392 0.0357 0.0395 MS Feb 17 217,497 176,733 707,004 0.0416 0.0406 0.0418 MS Feb 18 243,658 218,277 777,572 0.0466 0.0502 0.0460 MS Feb 19 244,724 219,127 785,091 0.0468 0.0503 0.0464 MS Feb 20 242,419 214,983 781,038 0.0464 0.0494 0.0462 MS Feb 21 236,058 202,851 767,413 0.0452 0.0466 0.0454 MS Feb 22 223,683 182,973 694,935 0.0428 0.0420 0.0411 MS Feb 23 200,839 160,870 637,359 0.0384 0.0370 0.0377 MS Mar 0 337,599 176,903 671,396 0.0379 0.0350 0.0344 MS Mar 1 311,836 168,021 658,557 0.0350 0.0332 0.0337 MS Mar 2 298,832 162,591 652,653 0.0336 0.0322 0.0334 MS Mar 3 299,837 164,420 659,372 0.0337 0.0325 0.0338 MS Mar 4 321,524 174,209 688,550 0.0361 0.0345 0.0353 MS Mar 5 356,989 209,620 774,745 0.0401 0.0415 0.0397 MS Mar 6 373,584 225,222 850,416 0.0420 0.0446 0.0435 MS Mar 7 379,808 226,647 863,398 0.0427 0.0448 0.0442 MS Mar 8 388,936 228,973 869,283 0.0437 0.0453 0.0445 MS Mar 9 392,827 226,272 874,879 0.0441 0.0448 0.0448 MS Mar 10 393,128 224,267 885,425 0.0441 0.0444 0.0453 MS Mar 11 396,026 223,489 878,915 0.0445 0.0442 0.0450 MS Mar 12 393,023 217,458 865,563 0.0441 0.0430 0.0443 MS Mar 13 388,540 214,283 854,086 0.0436 0.0424 0.0437 MS Mar 14 381,636 209,095 841,469 0.0429 0.0414 0.0431 MS Mar 15 378,494 207,557 832,329 0.0425 0.0411 0.0426 MS Mar 16 386,426 211,259 834,927 0.0434 0.0418 0.0428 MS Mar 17 392,149 216,518 846,550 0.0440 0.0428 0.0433 MS Mar 18 397,547 236,378 907,903 0.0446 0.0468 0.0465

D-23Atmospheric Sciences Group 

### Appendix D Actual 2002 State Level Monthly-Diurnal Profiles

CEM-Based Distribution Alpine Geophysics

SO2 Mass NOx Mass Heat Input State Month Hour [lbs] [lbs] [MMBtu] SO2 Ratio NOx Ratio Heat Input Actual Reported Values [2002] Calculated Ratios

MS Mar 19 398,376 246,894 933,628 0.0447 0.0489 0.0478 MS Mar 20 392,734 240,412 918,228 0.0441 0.0476 0.0470 MS Mar 21 388,730 229,585 887,976 0.0437 0.0454 0.0455 MS Mar 22 391,128 220,615 777,514 0.0439 0.0437 0.0398 MS Mar 23 364,793 192,944 700,796 0.0410 0.0382 0.0359 MS Apr 0 289,274 210,302 674,456 0.0341 0.0301 0.0313 MS Apr 1 272,781 194,279 658,179 0.0321 0.0278 0.0306 MS Apr 2 255,674 182,964 645,036 0.0301 0.0262 0.0299 MS Apr 3 258,132 199,983 667,783 0.0304 0.0286 0.0310 MS Apr 4 294,364 213,211 739,553 0.0347 0.0305 0.0343 MS Apr 5 326,760 248,505 808,818 0.0385 0.0355 0.0376 MS Apr 6 349,825 267,606 870,840 0.0412 0.0383 0.0404 MS Apr 7 366,360 286,256 903,990 0.0432 0.0409 0.0420 MS Apr 8 379,890 301,972 930,848 0.0447 0.0432 0.0432 MS Apr 9 375,915 307,857 955,252 0.0443 0.0440 0.0443 MS Apr 10 371,886 312,687 967,176 0.0438 0.0447 0.0449 MS Apr 11 376,643 332,849 1,000,566 0.0444 0.0476 0.0465 MS Apr 12 385,311 340,996 1,025,779 0.0454 0.0488 0.0476 MS Apr 13 385,970 343,187 1,030,671 0.0455 0.0491 0.0479 MS Apr 14 386,736 347,908 1,032,186 0.0456 0.0498 0.0479 MS Apr 15 393,806 353,322 1,044,825 0.0464 0.0505 0.0485 MS Apr 16 394,838 351,503 1,035,746 0.0465 0.0503 0.0481 MS Apr 17 390,569 341,431 1,018,817 0.0460 0.0488 0.0473 MS Apr 18 392,006 336,261 1,017,146 0.0462 0.0481 0.0472 MS Apr 19 398,154 351,627 1,047,902 0.0469 0.0503 0.0487 MS Apr 20 396,961 340,313 1,018,343 0.0468 0.0487 0.0473 MS Apr 21 380,259 311,166 925,539 0.0448 0.0445 0.0430 MS Apr 22 350,316 272,826 794,988 0.0413 0.0390 0.0369 MS Apr 23 317,916 241,623 724,562 0.0374 0.0346 0.0336 MS May 0 357,994 258,998 847,936 0.0306 0.0292 0.0320 MS May 1 334,112 244,300 819,285 0.0285 0.0275 0.0309 MS May 2 327,824 241,345 814,911 0.0280 0.0272 0.0308 MS May 3 332,654 265,833 838,645 0.0284 0.0299 0.0317 MS May 4 372,890 271,971 912,516 0.0318 0.0306 0.0344 MS May 5 417,989 301,039 981,611 0.0357 0.0339 0.0370 MS May 6 462,291 329,864 1,039,932 0.0395 0.0372 0.0393 MS May 7 519,425 362,519 1,094,522 0.0443 0.0408 0.0413 MS May 8 538,400 388,483 1,159,752 0.0460 0.0438 0.0438 MS May 9 557,538 411,089 1,195,918 0.0476 0.0463 0.0451 MS May 10 559,292 415,930 1,218,226 0.0477 0.0469 0.0460 MS May 11 561,832 421,646 1,239,118 0.0480 0.0475 0.0468 MS May 12 561,123 434,561 1,258,714 0.0479 0.0490 0.0475 MS May 13 551,740 439,634 1,267,729 0.0471 0.0495 0.0478 MS May 14 556,478 448,826 1,275,851 0.0475 0.0506 0.0482 MS May 15 559,115 458,503 1,286,808 0.0477 0.0516 0.0486 MS May 16 555,371 449,044 1,269,685 0.0474 0.0506 0.0479 MS May 17 546,069 433,700 1,241,680 0.0466 0.0489 0.0469 MS May 18 547,005 425,738 1,228,655 0.0467 0.0480 0.0464 MS May 19 555,484 429,915 1,252,377 0.0474 0.0484 0.0473 MS May 20 549,539 418,655 1,219,580 0.0469 0.0472 0.0460 MS May 21 523,192 395,984 1,133,626 0.0447 0.0446 0.0428 MS May 22 465,486 339,347 996,424 0.0397 0.0382 0.0376 MS May 23 403,263 290,433 901,005 0.0344 0.0327 0.0340

D-24Atmospheric Sciences Group 

### Appendix D Actual 2002 State Level Monthly-Diurnal Profiles

CEM-Based Distribution Alpine Geophysics

SO2 Mass NOx Mass Heat Input State Month Hour [lbs] [lbs] [MMBtu] SO2 Ratio NOx Ratio Heat Input Actual Reported Values [2002] Calculated Ratios

MS Jun 0 341,454 235,254 927,740 0.0291 0.0257 0.0287 MS Jun 1 313,065 218,714 893,033 0.0267 0.0239 0.0276 MS Jun 2 301,332 210,169 881,348 0.0257 0.0229 0.0272 MS Jun 3 299,823 226,308 893,898 0.0256 0.0247 0.0276 MS Jun 4 316,990 218,625 935,610 0.0270 0.0239 0.0289 MS Jun 5 348,643 235,736 1,008,613 0.0297 0.0257 0.0312 MS Jun 6 418,960 280,818 1,124,291 0.0357 0.0307 0.0348 MS Jun 7 501,141 340,706 1,246,624 0.0428 0.0372 0.0385 MS Jun 8 556,441 400,331 1,381,849 0.0475 0.0437 0.0427 MS Jun 9 582,672 435,660 1,481,015 0.0497 0.0476 0.0458 MS Jun 10 587,392 462,309 1,561,519 0.0501 0.0505 0.0483 MS Jun 11 587,946 480,422 1,620,330 0.0502 0.0524 0.0501 MS Jun 12 579,770 492,880 1,669,654 0.0495 0.0538 0.0516 MS Jun 13 582,636 506,140 1,711,224 0.0497 0.0553 0.0529 MS Jun 14 576,726 511,502 1,728,760 0.0492 0.0558 0.0534 MS Jun 15 574,684 511,288 1,709,965 0.0490 0.0558 0.0529 MS Jun 16 576,196 502,375 1,679,497 0.0492 0.0548 0.0519 MS Jun 17 574,724 487,944 1,643,867 0.0490 0.0533 0.0508 MS Jun 18 563,424 466,631 1,592,798 0.0481 0.0509 0.0492 MS Jun 19 569,402 461,103 1,579,160 0.0486 0.0503 0.0488 MS Jun 20 564,833 449,387 1,524,446 0.0482 0.0491 0.0471 MS Jun 21 536,034 409,384 1,371,958 0.0457 0.0447 0.0424 MS Jun 22 468,975 342,086 1,163,023 0.0400 0.0373 0.0359 MS Jun 23 396,823 274,378 1,020,968 0.0339 0.0300 0.0316 MS Jul 0 335,908 249,121 1,125,103 0.0314 0.0257 0.0286 MS Jul 1 313,481 235,121 1,078,662 0.0293 0.0243 0.0274 MS Jul 2 304,077 227,325 1,063,423 0.0284 0.0235 0.0270 MS Jul 3 306,472 256,296 1,077,182 0.0286 0.0265 0.0274 MS Jul 4 310,640 229,379 1,112,128 0.0290 0.0237 0.0283 MS Jul 5 323,746 238,455 1,199,792 0.0303 0.0246 0.0305 MS Jul 6 356,823 256,224 1,297,782 0.0334 0.0265 0.0330 MS Jul 7 432,199 310,499 1,428,708 0.0404 0.0321 0.0363 MS Jul 8 482,603 385,501 1,618,928 0.0451 0.0398 0.0411 MS Jul 9 522,690 465,594 1,822,567 0.0489 0.0481 0.0463 MS Jul 10 526,584 511,772 1,970,217 0.0492 0.0529 0.0501 MS Jul 11 522,227 534,097 2,063,143 0.0488 0.0552 0.0524 MS Jul 12 517,438 549,768 2,104,001 0.0484 0.0568 0.0535 MS Jul 13 517,959 559,794 2,130,414 0.0484 0.0578 0.0541 MS Jul 14 521,343 566,802 2,145,659 0.0487 0.0586 0.0545 MS Jul 15 522,356 559,386 2,133,553 0.0488 0.0578 0.0542 MS Jul 16 520,649 541,060 2,077,357 0.0487 0.0559 0.0528 MS Jul 17 518,672 521,602 2,022,392 0.0485 0.0539 0.0514 MS Jul 18 515,755 494,005 1,941,461 0.0482 0.0510 0.0493 MS Jul 19 520,684 489,970 1,914,389 0.0487 0.0506 0.0486 MS Jul 20 515,789 468,363 1,823,823 0.0482 0.0484 0.0463 MS Jul 21 485,998 412,354 1,609,793 0.0454 0.0426 0.0409 MS Jul 22 429,361 336,937 1,377,414 0.0401 0.0348 0.0350 MS Jul 23 375,205 279,215 1,215,274 0.0351 0.0288 0.0309 MS Aug 0 398,879 261,206 1,049,987 0.0326 0.0276 0.0293 MS Aug 1 369,182 234,851 1,000,838 0.0301 0.0248 0.0280 MS Aug 2 349,692 222,480 972,515 0.0286 0.0235 0.0272 MS Aug 3 339,796 254,166 978,245 0.0277 0.0269 0.0273 MS Aug 4 372,731 231,950 1,043,736 0.0304 0.0245 0.0292

D-25Atmospheric Sciences Group 

### Appendix D Actual 2002 State Level Monthly-Diurnal Profiles

CEM-Based Distribution Alpine Geophysics

SO2 Mass NOx Mass Heat Input State Month Hour [lbs] [lbs] [MMBtu] SO2 Ratio NOx Ratio Heat Input Actual Reported Values [2002] Calculated Ratios

MS Aug 5 413,169 265,592 1,152,662 0.0337 0.0281 0.0322 MS Aug 6 432,852 276,313 1,217,001 0.0353 0.0292 0.0340 MS Aug 7 501,186 312,383 1,301,644 0.0409 0.0330 0.0364 MS Aug 8 554,195 382,784 1,469,266 0.0452 0.0405 0.0411 MS Aug 9 585,918 443,572 1,637,685 0.0478 0.0469 0.0458 MS Aug 10 591,357 476,018 1,755,828 0.0483 0.0503 0.0491 MS Aug 11 600,847 506,589 1,835,440 0.0491 0.0536 0.0513 MS Aug 12 603,122 532,009 1,889,629 0.0492 0.0563 0.0528 MS Aug 13 586,026 538,137 1,902,462 0.0478 0.0569 0.0532 MS Aug 14 583,473 536,550 1,917,367 0.0476 0.0567 0.0536 MS Aug 15 584,740 529,567 1,908,645 0.0477 0.0560 0.0533 MS Aug 16 589,342 518,409 1,878,059 0.0481 0.0548 0.0525 MS Aug 17 590,667 496,486 1,832,408 0.0482 0.0525 0.0512 MS Aug 18 582,754 478,822 1,776,197 0.0476 0.0506 0.0496 MS Aug 19 588,827 484,336 1,780,993 0.0481 0.0512 0.0498 MS Aug 20 574,252 449,220 1,655,777 0.0469 0.0475 0.0463 MS Aug 21 538,304 391,064 1,445,807 0.0439 0.0414 0.0404 MS Aug 22 479,992 337,585 1,257,748 0.0392 0.0357 0.0351 MS Aug 23 437,072 295,235 1,128,610 0.0357 0.0312 0.0315 MS Sep 0 482,689 281,966 1,043,624 0.0362 0.0312 0.0323 MS Sep 1 445,736 256,382 993,578 0.0335 0.0284 0.0308 MS Sep 2 428,348 244,301 975,792 0.0322 0.0270 0.0302 MS Sep 3 435,162 283,234 986,914 0.0327 0.0314 0.0306 MS Sep 4 504,198 272,583 1,064,745 0.0379 0.0302 0.0330 MS Sep 5 515,957 309,119 1,170,081 0.0387 0.0342 0.0363 MS Sep 6 530,668 316,791 1,201,358 0.0398 0.0351 0.0372 MS Sep 7 575,287 340,452 1,254,581 0.0432 0.0377 0.0389 MS Sep 8 585,787 366,390 1,327,534 0.0440 0.0406 0.0411 MS Sep 9 607,119 390,951 1,399,564 0.0456 0.0433 0.0434 MS Sep 10 603,621 419,081 1,480,585 0.0453 0.0464 0.0459 MS Sep 11 585,894 438,565 1,538,719 0.0440 0.0485 0.0477 MS Sep 12 597,948 456,406 1,579,728 0.0449 0.0505 0.0490 MS Sep 13 592,172 468,633 1,611,365 0.0445 0.0519 0.0499 MS Sep 14 594,184 474,728 1,632,628 0.0446 0.0526 0.0506 MS Sep 15 596,279 477,153 1,626,359 0.0448 0.0528 0.0504 MS Sep 16 595,741 463,914 1,596,336 0.0447 0.0514 0.0495 MS Sep 17 587,489 443,603 1,549,374 0.0441 0.0491 0.0480 MS Sep 18 592,914 438,949 1,552,705 0.0445 0.0486 0.0481 MS Sep 19 594,008 430,245 1,533,455 0.0446 0.0476 0.0475 MS Sep 20 599,159 404,017 1,457,581 0.0450 0.0447 0.0452 MS Sep 21 578,140 382,545 1,348,572 0.0434 0.0423 0.0418 MS Sep 22 560,123 352,725 1,216,799 0.0421 0.0390 0.0377 MS Sep 23 529,509 320,788 1,122,099 0.0398 0.0355 0.0348 MS Oct 0 565,288 243,633 834,105 0.0362 0.0306 0.0343 MS Oct 1 535,302 229,086 803,940 0.0343 0.0287 0.0331 MS Oct 2 522,671 218,960 788,851 0.0335 0.0275 0.0324 MS Oct 3 529,653 229,990 800,166 0.0339 0.0289 0.0329 MS Oct 4 583,011 260,379 860,499 0.0374 0.0327 0.0354 MS Oct 5 629,052 304,118 939,223 0.0403 0.0382 0.0386 MS Oct 6 652,760 323,868 977,237 0.0418 0.0406 0.0402 MS Oct 7 679,279 339,666 1,006,683 0.0435 0.0426 0.0414 MS Oct 8 681,417 352,752 1,033,371 0.0437 0.0443 0.0425 MS Oct 9 683,547 362,346 1,059,491 0.0438 0.0455 0.0436

D-26Atmospheric Sciences Group 

### Appendix D Actual 2002 State Level Monthly-Diurnal Profiles

CEM-Based Distribution Alpine Geophysics

SO2 Mass NOx Mass Heat Input State Month Hour [lbs] [lbs] [MMBtu] SO2 Ratio NOx Ratio Heat Input Actual Reported Values [2002] Calculated Ratios

MS Oct 10 682,487 374,889 1,096,290 0.0437 0.0470 0.0451 MS Oct 11 687,037 377,064 1,111,744 0.0440 0.0473 0.0457 MS Oct 12 679,613 380,131 1,122,029 0.0435 0.0477 0.0461 MS Oct 13 676,460 381,240 1,126,078 0.0433 0.0478 0.0463 MS Oct 14 682,114 387,409 1,139,635 0.0437 0.0486 0.0469 MS Oct 15 687,412 386,942 1,142,886 0.0440 0.0485 0.0470 MS Oct 16 698,644 381,009 1,136,132 0.0448 0.0478 0.0467 MS Oct 17 702,784 385,270 1,141,571 0.0450 0.0483 0.0469 MS Oct 18 711,740 393,016 1,148,316 0.0456 0.0493 0.0472 MS Oct 19 700,116 379,092 1,114,584 0.0449 0.0476 0.0458 MS Oct 20 700,266 360,465 1,078,800 0.0449 0.0452 0.0444 MS Oct 21 686,503 341,372 1,029,868 0.0440 0.0428 0.0423 MS Oct 22 648,327 307,205 949,460 0.0415 0.0385 0.0390 MS Oct 23 601,351 270,693 879,834 0.0385 0.0340 0.0362 MS Nov 0 400,696 193,241 734,380 0.0332 0.0310 0.0359 MS Nov 1 373,946 176,574 705,147 0.0310 0.0283 0.0345 MS Nov 2 367,834 173,773 699,903 0.0305 0.0279 0.0342 MS Nov 3 369,863 176,852 701,041 0.0307 0.0284 0.0343 MS Nov 4 414,161 187,139 725,637 0.0344 0.0300 0.0355 MS Nov 5 454,879 224,615 806,127 0.0377 0.0360 0.0394 MS Nov 6 508,757 269,805 881,643 0.0422 0.0433 0.0431 MS Nov 7 538,661 295,334 911,553 0.0447 0.0474 0.0446 MS Nov 8 558,581 294,868 918,995 0.0463 0.0473 0.0449 MS Nov 9 554,742 293,716 913,857 0.0460 0.0471 0.0447 MS Nov 10 551,136 286,727 905,875 0.0457 0.0460 0.0443 MS Nov 11 557,048 277,518 888,002 0.0462 0.0445 0.0434 MS Nov 12 532,534 273,491 880,710 0.0442 0.0439 0.0431 MS Nov 13 518,395 267,818 867,677 0.0430 0.0430 0.0424 MS Nov 14 510,686 264,270 858,778 0.0424 0.0424 0.0420 MS Nov 15 505,459 262,016 853,820 0.0419 0.0420 0.0417 MS Nov 16 519,638 273,591 877,629 0.0431 0.0439 0.0429 MS Nov 17 560,499 309,237 934,759 0.0465 0.0496 0.0457 MS Nov 18 568,506 320,622 946,437 0.0472 0.0515 0.0463 MS Nov 19 569,521 310,905 933,636 0.0472 0.0499 0.0456 MS Nov 20 571,807 306,361 930,840 0.0474 0.0492 0.0455 MS Nov 21 563,862 296,086 912,102 0.0468 0.0475 0.0446 MS Nov 22 525,369 271,591 870,135 0.0436 0.0436 0.0425 MS Nov 23 458,981 225,544 798,006 0.0381 0.0362 0.0390 MS Dec 0 476,147 237,179 822,181 0.0354 0.0321 0.0360 MS Dec 1 451,792 218,043 793,981 0.0335 0.0295 0.0347 MS Dec 2 445,967 214,157 791,509 0.0331 0.0290 0.0346 MS Dec 3 456,261 236,967 804,468 0.0339 0.0320 0.0352 MS Dec 4 504,954 240,382 845,365 0.0375 0.0325 0.0370 MS Dec 5 529,892 277,311 922,914 0.0393 0.0375 0.0404 MS Dec 6 582,038 324,463 1,007,153 0.0432 0.0439 0.0441 MS Dec 7 614,010 354,025 1,038,332 0.0456 0.0479 0.0454 MS Dec 8 619,411 360,044 1,044,873 0.0460 0.0487 0.0457 MS Dec 9 623,495 352,069 1,031,891 0.0463 0.0476 0.0452 MS Dec 10 620,949 341,455 1,015,725 0.0461 0.0462 0.0444 MS Dec 11 608,450 329,084 994,310 0.0452 0.0445 0.0435 MS Dec 12 570,890 309,824 962,797 0.0424 0.0419 0.0421 MS Dec 13 540,947 288,800 928,195 0.0402 0.0390 0.0406 MS Dec 14 527,041 278,854 906,371 0.0391 0.0377 0.0397

D-27Atmospheric Sciences Group 

### Appendix D Actual 2002 State Level Monthly-Diurnal Profiles

CEM-Based Distribution Alpine Geophysics

SO2 Mass NOx Mass Heat Input State Month Hour [lbs] [lbs] [MMBtu] SO2 Ratio NOx Ratio Heat Input Actual Reported Values [2002] Calculated Ratios

MS Dec 15 521,029 275,687 903,094 0.0387 0.0373 0.0395 MS Dec 16 553,791 298,249 946,805 0.0411 0.0403 0.0414 MS Dec 17 610,161 359,840 1,045,532 0.0453 0.0487 0.0458 MS Dec 18 628,087 388,120 1,072,393 0.0466 0.0525 0.0469 MS Dec 19 624,442 380,566 1,059,697 0.0464 0.0515 0.0464 MS Dec 20 627,989 375,875 1,055,467 0.0466 0.0508 0.0462 MS Dec 21 626,583 363,339 1,034,920 0.0465 0.0491 0.0453 MS Dec 22 587,229 322,351 954,040 0.0436 0.0436 0.0417 MS Dec 23 517,373 269,794 869,671 0.0384 0.0365 0.0381 NC Jan 0 2,630,975 859,723 1,955,963 0.0350 0.0346 0.0350 NC Jan 1 2,562,449 831,570 1,905,915 0.0341 0.0335 0.0341 NC Jan 2 2,564,877 838,395 1,907,095 0.0341 0.0337 0.0341 NC Jan 3 2,616,016 859,202 1,941,224 0.0348 0.0346 0.0347 NC Jan 4 2,720,291 898,273 2,018,727 0.0362 0.0361 0.0361 NC Jan 5 2,919,313 970,045 2,180,723 0.0389 0.0390 0.0390 NC Jan 6 3,294,821 1,102,686 2,471,242 0.0439 0.0444 0.0442 NC Jan 7 3,590,076 1,211,876 2,696,514 0.0478 0.0488 0.0482 NC Jan 8 3,627,979 1,217,893 2,715,407 0.0483 0.0490 0.0486 NC Jan 9 3,624,291 1,207,443 2,703,260 0.0482 0.0486 0.0484 NC Jan 10 3,518,422 1,166,785 2,612,241 0.0468 0.0469 0.0467 NC Jan 11 3,362,694 1,108,944 2,491,667 0.0448 0.0446 0.0446 NC Jan 12 3,193,991 1,047,245 2,365,831 0.0425 0.0421 0.0423 NC Jan 13 3,074,947 1,005,676 2,285,065 0.0409 0.0405 0.0409 NC Jan 14 2,925,281 952,644 2,179,694 0.0389 0.0383 0.0390 NC Jan 15 2,853,359 931,251 2,125,468 0.0380 0.0375 0.0380 NC Jan 16 2,922,144 956,239 2,161,760 0.0389 0.0385 0.0387 NC Jan 17 3,193,499 1,056,706 2,368,659 0.0425 0.0425 0.0424 NC Jan 18 3,551,508 1,191,636 2,634,748 0.0473 0.0479 0.0471 NC Jan 19 3,567,174 1,191,243 2,650,007 0.0475 0.0479 0.0474 NC Jan 20 3,512,057 1,169,749 2,609,983 0.0467 0.0471 0.0467 NC Jan 21 3,374,034 1,121,922 2,506,410 0.0449 0.0451 0.0448 NC Jan 22 3,130,889 1,037,328 2,323,144 0.0417 0.0417 0.0416 NC Jan 23 2,805,267 923,873 2,088,930 0.0373 0.0372 0.0374 NC Feb 0 2,243,689 737,358 1,705,321 0.0358 0.0350 0.0355 NC Feb 1 2,188,134 720,208 1,666,712 0.0349 0.0342 0.0347 NC Feb 2 2,194,916 723,781 1,671,053 0.0350 0.0344 0.0348 NC Feb 3 2,227,515 734,823 1,695,737 0.0356 0.0349 0.0353 NC Feb 4 2,323,093 770,376 1,775,542 0.0371 0.0366 0.0369 NC Feb 5 2,510,043 843,255 1,935,605 0.0401 0.0401 0.0403 NC Feb 6 2,829,576 969,740 2,208,607 0.0452 0.0461 0.0460 NC Feb 7 3,019,976 1,040,026 2,363,842 0.0482 0.0494 0.0492 NC Feb 8 3,019,940 1,035,102 2,354,654 0.0482 0.0492 0.0490 NC Feb 9 3,002,148 1,022,495 2,317,789 0.0479 0.0486 0.0482 NC Feb 10 2,937,533 991,673 2,247,044 0.0469 0.0471 0.0468 NC Feb 11 2,754,524 916,134 2,097,798 0.0440 0.0435 0.0436 NC Feb 12 2,597,462 858,523 1,971,450 0.0415 0.0408 0.0410 NC Feb 13 2,491,984 829,814 1,899,637 0.0398 0.0394 0.0395 NC Feb 14 2,370,849 785,262 1,813,470 0.0379 0.0373 0.0377 NC Feb 15 2,301,743 760,176 1,767,680 0.0368 0.0361 0.0368 NC Feb 16 2,320,623 768,492 1,784,228 0.0371 0.0365 0.0371 NC Feb 17 2,456,740 822,213 1,887,638 0.0392 0.0391 0.0393 NC Feb 18 2,828,704 963,052 2,172,877 0.0452 0.0458 0.0452 NC Feb 19 2,975,097 1,020,124 2,286,492 0.0475 0.0485 0.0476

D-28Atmospheric Sciences Group 

### Appendix D Actual 2002 State Level Monthly-Diurnal Profiles

CEM-Based Distribution Alpine Geophysics

SO2 Mass NOx Mass Heat Input State Month Hour [lbs] [lbs] [MMBtu] SO2 Ratio NOx Ratio Heat Input Actual Reported Values [2002] Calculated Ratios

NC Feb 20 2,968,979 1,012,751 2,277,715 0.0474 0.0481 0.0474 NC Feb 21 2,883,352 983,654 2,208,226 0.0460 0.0467 0.0459 NC Feb 22 2,705,714 915,621 2,066,252 0.0432 0.0435 0.0430 NC Feb 23 2,473,241 824,767 1,885,384 0.0395 0.0392 0.0392 NC Mar 0 2,725,806 904,880 2,064,139 0.0356 0.0350 0.0353 NC Mar 1 2,634,486 876,776 1,996,882 0.0344 0.0339 0.0341 NC Mar 2 2,589,581 869,204 1,967,840 0.0338 0.0336 0.0336 NC Mar 3 2,589,626 876,922 1,979,959 0.0338 0.0339 0.0338 NC Mar 4 2,665,398 906,525 2,048,489 0.0348 0.0350 0.0350 NC Mar 5 2,859,675 980,235 2,219,850 0.0374 0.0379 0.0379 NC Mar 6 3,158,503 1,091,413 2,474,309 0.0413 0.0422 0.0423 NC Mar 7 3,353,397 1,149,547 2,637,616 0.0438 0.0444 0.0451 NC Mar 8 3,452,820 1,174,830 2,726,724 0.0451 0.0454 0.0466 NC Mar 9 3,515,809 1,198,162 2,756,759 0.0460 0.0463 0.0471 NC Mar 10 3,489,088 1,187,487 2,696,651 0.0456 0.0459 0.0461 NC Mar 11 3,432,315 1,163,359 2,616,274 0.0449 0.0450 0.0447 NC Mar 12 3,372,629 1,139,592 2,556,665 0.0441 0.0440 0.0437 NC Mar 13 3,334,536 1,127,854 2,521,645 0.0436 0.0436 0.0431 NC Mar 14 3,277,864 1,107,537 2,475,694 0.0428 0.0428 0.0423 NC Mar 15 3,234,822 1,090,435 2,435,233 0.0423 0.0421 0.0416 NC Mar 16 3,229,493 1,087,890 2,428,141 0.0422 0.0421 0.0415 NC Mar 17 3,282,167 1,110,123 2,468,275 0.0429 0.0429 0.0422 NC Mar 18 3,447,637 1,165,469 2,610,195 0.0451 0.0450 0.0446 NC Mar 19 3,625,821 1,225,601 2,763,594 0.0474 0.0474 0.0472 NC Mar 20 3,581,085 1,210,100 2,745,960 0.0468 0.0468 0.0469 NC Mar 21 3,481,781 1,171,116 2,648,182 0.0455 0.0453 0.0452 NC Mar 22 3,259,210 1,087,920 2,473,492 0.0426 0.0421 0.0423 NC Mar 23 2,916,834 968,238 2,216,783 0.0381 0.0374 0.0379 NC Apr 0 2,100,618 675,853 1,639,262 0.0325 0.0323 0.0320 NC Apr 1 1,975,823 636,031 1,548,301 0.0306 0.0304 0.0302 NC Apr 2 1,914,434 623,313 1,506,496 0.0297 0.0298 0.0294 NC Apr 3 1,925,010 626,285 1,515,239 0.0298 0.0300 0.0296 NC Apr 4 2,093,958 681,925 1,648,485 0.0324 0.0326 0.0322 NC Apr 5 2,429,882 785,950 1,904,016 0.0376 0.0376 0.0372 NC Apr 6 2,661,185 857,123 2,076,864 0.0412 0.0410 0.0405 NC Apr 7 2,812,670 899,495 2,187,267 0.0436 0.0430 0.0427 NC Apr 8 2,908,089 926,797 2,258,984 0.0451 0.0444 0.0441 NC Apr 9 2,939,854 945,176 2,299,896 0.0455 0.0452 0.0449 NC Apr 10 2,981,835 965,708 2,356,874 0.0462 0.0462 0.0460 NC Apr 11 2,991,441 972,217 2,389,992 0.0463 0.0465 0.0466 NC Apr 12 3,011,115 982,571 2,428,632 0.0467 0.0470 0.0474 NC Apr 13 3,001,891 978,498 2,441,745 0.0465 0.0468 0.0476 NC Apr 14 2,996,159 978,737 2,439,053 0.0464 0.0468 0.0476 NC Apr 15 2,996,410 982,248 2,440,123 0.0464 0.0470 0.0476 NC Apr 16 2,975,435 974,714 2,421,676 0.0461 0.0466 0.0473 NC Apr 17 2,952,541 966,745 2,397,870 0.0457 0.0463 0.0468 NC Apr 18 2,936,462 951,709 2,373,795 0.0455 0.0455 0.0463 NC Apr 19 3,059,548 994,109 2,451,840 0.0474 0.0476 0.0478 NC Apr 20 3,057,268 987,583 2,425,891 0.0474 0.0473 0.0473 NC Apr 21 2,900,727 931,579 2,274,873 0.0449 0.0446 0.0444 NC Apr 22 2,599,540 833,083 2,021,591 0.0403 0.0399 0.0394 NC Apr 23 2,322,114 738,642 1,799,924 0.0360 0.0353 0.0351 NC May 0 2,065,925 562,250 1,529,727 0.0311 0.0295 0.0303

D-29Atmospheric Sciences Group 

### Appendix D Actual 2002 State Level Monthly-Diurnal Profiles

CEM-Based Distribution Alpine Geophysics

SO2 Mass NOx Mass Heat Input State Month Hour [lbs] [lbs] [MMBtu] SO2 Ratio NOx Ratio Heat Input Actual Reported Values [2002] Calculated Ratios

NC May 1 1,942,880 529,629 1,440,259 0.0293 0.0278 0.0286 NC May 2 1,874,541 512,022 1,394,864 0.0282 0.0269 0.0277 NC May 3 1,876,529 516,720 1,403,648 0.0283 0.0271 0.0278 NC May 4 2,033,834 569,058 1,526,099 0.0306 0.0299 0.0303 NC May 5 2,331,128 665,142 1,746,123 0.0351 0.0349 0.0346 NC May 6 2,601,795 743,433 1,943,820 0.0392 0.0390 0.0386 NC May 7 2,723,097 780,487 2,035,283 0.0410 0.0409 0.0404 NC May 8 2,890,108 833,200 2,168,760 0.0436 0.0437 0.0430 NC May 9 3,015,858 873,553 2,275,028 0.0454 0.0458 0.0451 NC May 10 3,099,776 903,719 2,352,058 0.0467 0.0474 0.0467 NC May 11 3,155,782 929,798 2,414,664 0.0476 0.0488 0.0479 NC May 12 3,220,459 954,022 2,489,769 0.0485 0.0501 0.0494 NC May 13 3,225,509 957,339 2,512,222 0.0486 0.0502 0.0498 NC May 14 3,227,364 958,813 2,522,483 0.0486 0.0503 0.0500 NC May 15 3,255,755 963,573 2,536,475 0.0491 0.0506 0.0503 NC May 16 3,262,086 956,245 2,534,920 0.0492 0.0502 0.0503 NC May 17 3,223,841 933,698 2,496,255 0.0486 0.0490 0.0495 NC May 18 3,135,372 900,144 2,415,281 0.0472 0.0472 0.0479 NC May 19 3,151,605 908,334 2,416,369 0.0475 0.0477 0.0479 NC May 20 3,186,474 913,399 2,408,969 0.0480 0.0479 0.0478 NC May 21 2,981,839 846,832 2,219,083 0.0449 0.0444 0.0440 NC May 22 2,577,084 718,668 1,912,726 0.0388 0.0377 0.0379 NC May 23 2,304,233 630,612 1,710,740 0.0347 0.0331 0.0339 NC Jun 0 2,698,752 744,271 2,043,707 0.0318 0.0301 0.0309 NC Jun 1 2,479,228 667,633 1,881,847 0.0292 0.0270 0.0285 NC Jun 2 2,323,403 617,724 1,770,006 0.0274 0.0250 0.0268 NC Jun 3 2,277,608 607,874 1,737,010 0.0268 0.0246 0.0263 NC Jun 4 2,387,746 643,693 1,813,473 0.0281 0.0261 0.0274 NC Jun 5 2,573,317 709,718 1,948,011 0.0303 0.0287 0.0295 NC Jun 6 2,838,747 793,658 2,134,912 0.0334 0.0321 0.0323 NC Jun 7 3,166,072 892,709 2,373,823 0.0373 0.0361 0.0359 NC Jun 8 3,524,626 1,007,912 2,641,944 0.0415 0.0408 0.0400 NC Jun 9 3,843,069 1,123,200 2,904,535 0.0453 0.0455 0.0440 NC Jun 10 4,043,416 1,198,420 3,104,571 0.0476 0.0485 0.0470 NC Jun 11 4,192,670 1,256,435 3,262,160 0.0494 0.0509 0.0494 NC Jun 12 4,258,502 1,278,050 3,373,191 0.0502 0.0517 0.0511 NC Jun 13 4,289,051 1,290,971 3,453,047 0.0505 0.0523 0.0523 NC Jun 14 4,321,317 1,305,932 3,504,898 0.0509 0.0529 0.0531 NC Jun 15 4,349,451 1,313,942 3,524,878 0.0512 0.0532 0.0534 NC Jun 16 4,341,649 1,311,642 3,510,840 0.0512 0.0531 0.0531 NC Jun 17 4,304,106 1,291,874 3,467,981 0.0507 0.0523 0.0525 NC Jun 18 4,175,661 1,237,434 3,336,184 0.0492 0.0501 0.0505 NC Jun 19 4,056,076 1,198,189 3,201,002 0.0478 0.0485 0.0485 NC Jun 20 4,064,283 1,205,448 3,172,571 0.0479 0.0488 0.0480 NC Jun 21 3,832,571 1,129,651 2,951,417 0.0452 0.0457 0.0447 NC Jun 22 3,463,424 1,007,586 2,635,046 0.0408 0.0408 0.0399 NC Jun 23 3,067,572 870,502 2,317,749 0.0361 0.0352 0.0351 NC Jul 0 3,354,173 921,685 2,530,425 0.0345 0.0333 0.0324 NC Jul 1 3,102,787 854,676 2,351,750 0.0319 0.0309 0.0301 NC Jul 2 2,911,773 802,741 2,215,003 0.0299 0.0290 0.0284 NC Jul 3 2,825,326 780,292 2,152,351 0.0290 0.0282 0.0276 NC Jul 4 2,907,343 814,431 2,214,240 0.0299 0.0294 0.0284 NC Jul 5 3,128,868 880,781 2,379,883 0.0322 0.0318 0.0305

D-30Atmospheric Sciences Group 

### Appendix D Actual 2002 State Level Monthly-Diurnal Profiles

CEM-Based Distribution Alpine Geophysics

SO2 Mass NOx Mass Heat Input State Month Hour [lbs] [lbs] [MMBtu] SO2 Ratio NOx Ratio Heat Input Actual Reported Values [2002] Calculated Ratios

NC Jul 6 3,364,298 932,557 2,556,208 0.0346 0.0337 0.0327 NC Jul 7 3,727,524 1,033,747 2,842,468 0.0383 0.0374 0.0364 NC Jul 8 4,083,493 1,137,915 3,140,889 0.0420 0.0411 0.0402 NC Jul 9 4,380,317 1,234,238 3,405,321 0.0450 0.0446 0.0436 NC Jul 10 4,570,924 1,300,164 3,598,940 0.0470 0.0470 0.0461 NC Jul 11 4,666,649 1,338,728 3,767,945 0.0480 0.0484 0.0483 NC Jul 12 4,717,837 1,369,012 3,906,870 0.0485 0.0495 0.0500 NC Jul 13 4,730,905 1,384,309 4,007,760 0.0486 0.0500 0.0513 NC Jul 14 4,739,704 1,389,410 4,057,834 0.0487 0.0502 0.0520 NC Jul 15 4,742,237 1,396,672 4,071,903 0.0488 0.0505 0.0521 NC Jul 16 4,731,546 1,388,003 4,056,107 0.0486 0.0502 0.0519 NC Jul 17 4,705,403 1,376,275 4,011,432 0.0484 0.0497 0.0514 NC Jul 18 4,599,800 1,327,134 3,874,506 0.0473 0.0480 0.0496 NC Jul 19 4,539,753 1,297,041 3,759,845 0.0467 0.0469 0.0482 NC Jul 20 4,506,297 1,291,594 3,683,093 0.0463 0.0467 0.0472 NC Jul 21 4,373,391 1,238,584 3,488,460 0.0450 0.0448 0.0447 NC Jul 22 4,124,519 1,150,002 3,189,787 0.0424 0.0416 0.0408 NC Jul 23 3,739,934 1,028,356 2,823,010 0.0384 0.0372 0.0362 NC Aug 0 3,147,274 820,311 2,369,555 0.0344 0.0320 0.0322 NC Aug 1 2,939,408 758,945 2,222,246 0.0321 0.0296 0.0302 NC Aug 2 2,778,657 716,182 2,106,431 0.0304 0.0279 0.0287 NC Aug 3 2,714,267 702,973 2,062,647 0.0297 0.0274 0.0281 NC Aug 4 2,809,982 738,251 2,138,949 0.0307 0.0288 0.0291 NC Aug 5 3,106,915 821,031 2,364,730 0.0339 0.0320 0.0322 NC Aug 6 3,271,595 868,994 2,488,143 0.0357 0.0338 0.0338 NC Aug 7 3,520,512 951,753 2,682,675 0.0385 0.0371 0.0365 NC Aug 8 3,832,243 1,058,899 2,947,079 0.0419 0.0412 0.0401 NC Aug 9 4,044,942 1,136,586 3,170,537 0.0442 0.0443 0.0431 NC Aug 10 4,236,026 1,210,737 3,383,136 0.0463 0.0472 0.0460 NC Aug 11 4,374,045 1,265,673 3,583,654 0.0478 0.0493 0.0487 NC Aug 12 4,448,054 1,306,663 3,732,151 0.0486 0.0509 0.0508 NC Aug 13 4,463,954 1,316,993 3,801,307 0.0488 0.0513 0.0517 NC Aug 14 4,466,890 1,324,169 3,826,912 0.0488 0.0516 0.0521 NC Aug 15 4,474,224 1,330,615 3,838,517 0.0489 0.0518 0.0522 NC Aug 16 4,480,697 1,330,857 3,833,061 0.0490 0.0518 0.0521 NC Aug 17 4,464,415 1,317,485 3,798,214 0.0488 0.0513 0.0517 NC Aug 18 4,368,273 1,262,744 3,657,788 0.0477 0.0492 0.0498 NC Aug 19 4,299,971 1,233,117 3,569,848 0.0470 0.0480 0.0486 NC Aug 20 4,242,454 1,203,933 3,464,344 0.0464 0.0469 0.0471 NC Aug 21 4,010,663 1,115,907 3,162,517 0.0438 0.0435 0.0430 NC Aug 22 3,678,946 996,483 2,804,548 0.0402 0.0388 0.0381 NC Aug 23 3,345,819 883,969 2,512,733 0.0366 0.0344 0.0342 NC Sep 0 2,594,163 751,815 2,013,200 0.0304 0.0301 0.0302 NC Sep 1 2,425,818 708,706 1,894,572 0.0285 0.0283 0.0284 NC Sep 2 2,320,656 677,824 1,816,379 0.0272 0.0271 0.0272 NC Sep 3 2,292,901 670,975 1,796,988 0.0269 0.0268 0.0269 NC Sep 4 2,464,312 720,190 1,924,097 0.0289 0.0288 0.0288 NC Sep 5 2,876,553 852,274 2,226,771 0.0337 0.0341 0.0334 NC Sep 6 3,213,128 941,390 2,470,322 0.0377 0.0376 0.0370 NC Sep 7 3,400,320 993,645 2,607,715 0.0399 0.0397 0.0391 NC Sep 8 3,637,976 1,062,104 2,793,098 0.0427 0.0425 0.0418 NC Sep 9 3,861,830 1,127,816 2,971,071 0.0453 0.0451 0.0445 NC Sep 10 4,036,881 1,186,609 3,135,700 0.0474 0.0474 0.0470

D-31Atmospheric Sciences Group 

### Appendix D Actual 2002 State Level Monthly-Diurnal Profiles

CEM-Based Distribution Alpine Geophysics

SO2 Mass NOx Mass Heat Input State Month Hour [lbs] [lbs] [MMBtu] SO2 Ratio NOx Ratio Heat Input Actual Reported Values [2002] Calculated Ratios

NC Sep 11 4,130,342 1,220,631 3,234,052 0.0484 0.0488 0.0485 NC Sep 12 4,199,576 1,251,593 3,323,592 0.0493 0.0500 0.0498 NC Sep 13 4,224,482 1,261,381 3,372,396 0.0496 0.0504 0.0505 NC Sep 14 4,231,071 1,259,360 3,385,954 0.0496 0.0504 0.0507 NC Sep 15 4,242,472 1,264,312 3,402,050 0.0498 0.0505 0.0510 NC Sep 16 4,244,232 1,264,242 3,391,946 0.0498 0.0505 0.0508 NC Sep 17 4,226,775 1,248,945 3,359,088 0.0496 0.0499 0.0503 NC Sep 18 4,208,856 1,232,865 3,330,576 0.0494 0.0493 0.0499 NC Sep 19 4,225,962 1,238,465 3,338,028 0.0496 0.0495 0.0500 NC Sep 20 4,094,679 1,183,723 3,191,573 0.0480 0.0473 0.0478 NC Sep 21 3,815,098 1,090,161 2,934,209 0.0447 0.0436 0.0440 NC Sep 22 3,343,293 951,941 2,565,452 0.0392 0.0381 0.0384 NC Sep 23 2,943,063 850,713 2,267,230 0.0345 0.0340 0.0340 NC Oct 0 2,424,400 812,600 1,926,201 0.0319 0.0316 0.0316 NC Oct 1 2,285,677 772,232 1,823,035 0.0301 0.0300 0.0299 NC Oct 2 2,220,651 756,793 1,776,132 0.0292 0.0294 0.0292 NC Oct 3 2,243,688 767,340 1,795,867 0.0295 0.0298 0.0295 NC Oct 4 2,450,879 845,015 1,956,573 0.0323 0.0329 0.0321 NC Oct 5 2,859,392 977,580 2,263,350 0.0376 0.0380 0.0372 NC Oct 6 3,217,818 1,085,582 2,540,167 0.0424 0.0422 0.0417 NC Oct 7 3,307,214 1,105,589 2,607,134 0.0435 0.0430 0.0428 NC Oct 8 3,428,397 1,152,865 2,706,103 0.0451 0.0448 0.0444 NC Oct 9 3,491,653 1,178,585 2,770,212 0.0460 0.0458 0.0455 NC Oct 10 3,517,217 1,192,605 2,811,151 0.0463 0.0464 0.0462 NC Oct 11 3,538,950 1,204,998 2,843,030 0.0466 0.0469 0.0467 NC Oct 12 3,529,712 1,200,971 2,855,779 0.0465 0.0467 0.0469 NC Oct 13 3,527,575 1,200,801 2,875,571 0.0464 0.0467 0.0472 NC Oct 14 3,525,571 1,199,032 2,881,917 0.0464 0.0466 0.0473 NC Oct 15 3,538,115 1,202,132 2,881,056 0.0466 0.0467 0.0473 NC Oct 16 3,553,556 1,212,512 2,890,076 0.0468 0.0472 0.0475 NC Oct 17 3,586,460 1,224,221 2,909,629 0.0472 0.0476 0.0478 NC Oct 18 3,663,611 1,253,981 2,972,033 0.0482 0.0488 0.0488 NC Oct 19 3,614,898 1,228,106 2,918,644 0.0476 0.0478 0.0479 NC Oct 20 3,513,638 1,183,174 2,811,865 0.0463 0.0460 0.0462 NC Oct 21 3,333,450 1,108,298 2,637,286 0.0439 0.0431 0.0433 NC Oct 22 2,956,146 975,213 2,338,054 0.0389 0.0379 0.0384 NC Oct 23 2,636,184 875,188 2,089,871 0.0347 0.0340 0.0343 NC Nov 0 2,547,217 879,719 2,011,827 0.0362 0.0360 0.0364 NC Nov 1 2,459,319 846,721 1,942,672 0.0350 0.0346 0.0352 NC Nov 2 2,433,618 843,768 1,921,253 0.0346 0.0345 0.0348 NC Nov 3 2,450,746 855,500 1,934,662 0.0348 0.0350 0.0350 NC Nov 4 2,567,117 900,472 2,028,517 0.0365 0.0368 0.0367 NC Nov 5 2,792,642 987,481 2,215,227 0.0397 0.0404 0.0401 NC Nov 6 3,069,432 1,077,264 2,433,311 0.0436 0.0440 0.0440 NC Nov 7 3,211,209 1,120,156 2,539,068 0.0457 0.0458 0.0459 NC Nov 8 3,243,790 1,116,948 2,541,021 0.0461 0.0456 0.0460 NC Nov 9 3,234,097 1,116,443 2,523,217 0.0460 0.0456 0.0457 NC Nov 10 3,188,140 1,105,415 2,484,544 0.0453 0.0452 0.0450 NC Nov 11 3,080,695 1,065,180 2,401,616 0.0438 0.0435 0.0435 NC Nov 12 2,949,281 1,023,692 2,302,453 0.0419 0.0418 0.0417 NC Nov 13 2,858,735 997,869 2,238,957 0.0406 0.0408 0.0405 NC Nov 14 2,788,593 969,690 2,185,558 0.0396 0.0396 0.0396 NC Nov 15 2,756,208 961,551 2,162,884 0.0392 0.0393 0.0391

D-32Atmospheric Sciences Group 

### Appendix D Actual 2002 State Level Monthly-Diurnal Profiles

CEM-Based Distribution Alpine Geophysics

SO2 Mass NOx Mass Heat Input State Month Hour [lbs] [lbs] [MMBtu] SO2 Ratio NOx Ratio Heat Input Actual Reported Values [2002] Calculated Ratios

NC Nov 16 2,842,698 986,636 2,233,334 0.0404 0.0403 0.0404 NC Nov 17 3,113,777 1,094,330 2,440,223 0.0443 0.0447 0.0442 NC Nov 18 3,299,571 1,163,945 2,585,335 0.0469 0.0476 0.0468 NC Nov 19 3,281,261 1,143,162 2,573,396 0.0467 0.0467 0.0466 NC Nov 20 3,266,244 1,130,250 2,562,040 0.0464 0.0462 0.0464 NC Nov 21 3,181,852 1,105,473 2,499,861 0.0452 0.0452 0.0452 NC Nov 22 2,999,763 1,039,345 2,358,610 0.0426 0.0425 0.0427 NC Nov 23 2,719,459 938,347 2,139,422 0.0387 0.0383 0.0387 NC Dec 0 2,786,311 952,086 2,137,402 0.0369 0.0360 0.0366 NC Dec 1 2,688,299 918,583 2,066,058 0.0356 0.0348 0.0354 NC Dec 2 2,652,627 910,901 2,041,385 0.0351 0.0345 0.0350 NC Dec 3 2,681,579 924,596 2,064,035 0.0355 0.0350 0.0353 NC Dec 4 2,793,097 973,712 2,151,528 0.0370 0.0368 0.0368 NC Dec 5 2,978,587 1,039,056 2,299,246 0.0394 0.0393 0.0394 NC Dec 6 3,255,765 1,138,815 2,527,471 0.0431 0.0431 0.0433 NC Dec 7 3,468,637 1,222,783 2,697,743 0.0459 0.0463 0.0462 NC Dec 8 3,528,746 1,244,532 2,735,466 0.0467 0.0471 0.0468 NC Dec 9 3,499,852 1,231,070 2,705,546 0.0463 0.0466 0.0463 NC Dec 10 3,402,765 1,194,282 2,627,210 0.0450 0.0452 0.0450 NC Dec 11 3,273,673 1,144,185 2,526,301 0.0433 0.0433 0.0433 NC Dec 12 3,116,777 1,085,434 2,401,454 0.0412 0.0411 0.0411 NC Dec 13 2,996,242 1,044,492 2,311,719 0.0396 0.0395 0.0396 NC Dec 14 2,905,118 1,018,633 2,243,181 0.0384 0.0385 0.0384 NC Dec 15 2,862,458 1,005,003 2,213,736 0.0379 0.0380 0.0379 NC Dec 16 2,998,333 1,041,875 2,319,069 0.0397 0.0394 0.0397 NC Dec 17 3,345,572 1,177,991 2,596,998 0.0443 0.0446 0.0445 NC Dec 18 3,540,109 1,274,586 2,749,103 0.0468 0.0482 0.0471 NC Dec 19 3,530,539 1,245,967 2,739,450 0.0467 0.0471 0.0469 NC Dec 20 3,508,778 1,235,613 2,725,026 0.0464 0.0467 0.0467 NC Dec 21 3,456,701 1,218,913 2,673,450 0.0457 0.0461 0.0458 NC Dec 22 3,313,726 1,158,670 2,550,455 0.0438 0.0438 0.0437 NC Dec 23 3,000,663 1,031,342 2,305,464 0.0397 0.0390 0.0395 SC Jan 0 1,194,843 480,648 1,247,487 0.0384 0.0386 0.0389 SC Jan 1 1,181,062 468,835 1,223,955 0.0380 0.0377 0.0382 SC Jan 2 1,178,324 465,076 1,215,074 0.0379 0.0374 0.0379 SC Jan 3 1,185,185 465,533 1,218,379 0.0381 0.0374 0.0380 SC Jan 4 1,203,617 473,274 1,235,149 0.0387 0.0380 0.0385 SC Jan 5 1,244,456 491,415 1,270,561 0.0400 0.0395 0.0396 SC Jan 6 1,345,325 534,230 1,358,260 0.0433 0.0429 0.0424 SC Jan 7 1,417,318 570,794 1,441,179 0.0456 0.0459 0.0449 SC Jan 8 1,416,853 576,272 1,455,985 0.0456 0.0463 0.0454 SC Jan 9 1,415,176 572,561 1,446,396 0.0455 0.0460 0.0451 SC Jan 10 1,397,177 570,131 1,436,696 0.0450 0.0458 0.0448 SC Jan 11 1,360,857 555,144 1,405,593 0.0438 0.0446 0.0438 SC Jan 12 1,301,336 525,161 1,352,206 0.0419 0.0422 0.0422 SC Jan 13 1,250,536 498,742 1,308,808 0.0402 0.0401 0.0408 SC Jan 14 1,223,591 483,833 1,281,905 0.0394 0.0389 0.0400 SC Jan 15 1,207,238 471,171 1,257,847 0.0388 0.0379 0.0392 SC Jan 16 1,219,228 474,017 1,265,489 0.0392 0.0381 0.0395 SC Jan 17 1,277,592 499,120 1,316,601 0.0411 0.0401 0.0411 SC Jan 18 1,386,046 555,815 1,414,662 0.0446 0.0447 0.0441 SC Jan 19 1,395,284 566,893 1,429,707 0.0449 0.0455 0.0446 SC Jan 20 1,388,573 564,996 1,426,484 0.0447 0.0454 0.0445

D-33Atmospheric Sciences Group 

### Appendix D Actual 2002 State Level Monthly-Diurnal Profiles

CEM-Based Distribution Alpine Geophysics

SO2 Mass NOx Mass Heat Input State Month Hour [lbs] [lbs] [MMBtu] SO2 Ratio NOx Ratio Heat Input Actual Reported Values [2002] Calculated Ratios

SC Jan 21 1,353,844 553,482 1,405,199 0.0436 0.0445 0.0438 SC Jan 22 1,301,954 530,961 1,362,865 0.0419 0.0427 0.0425 SC Jan 23 1,236,633 499,336 1,294,592 0.0398 0.0401 0.0404 SC Feb 0 1,041,655 453,992 1,137,929 0.0377 0.0378 0.0387 SC Feb 1 1,023,879 441,068 1,114,670 0.0371 0.0367 0.0379 SC Feb 2 1,025,675 442,264 1,115,322 0.0371 0.0368 0.0380 SC Feb 3 1,041,433 448,073 1,123,781 0.0377 0.0373 0.0383 SC Feb 4 1,064,963 460,399 1,142,344 0.0386 0.0383 0.0389 SC Feb 5 1,113,818 481,647 1,189,091 0.0403 0.0401 0.0405 SC Feb 6 1,204,046 520,862 1,267,530 0.0436 0.0433 0.0432 SC Feb 7 1,269,465 556,447 1,338,662 0.0460 0.0463 0.0456 SC Feb 8 1,271,254 558,690 1,347,296 0.0460 0.0465 0.0459 SC Feb 9 1,261,215 551,623 1,325,078 0.0457 0.0459 0.0451 SC Feb 10 1,258,014 548,546 1,307,257 0.0456 0.0456 0.0445 SC Feb 11 1,213,058 533,420 1,273,502 0.0439 0.0444 0.0434 SC Feb 12 1,157,145 509,539 1,232,702 0.0419 0.0424 0.0420 SC Feb 13 1,115,616 489,378 1,196,676 0.0404 0.0407 0.0407 SC Feb 14 1,083,985 473,997 1,174,255 0.0393 0.0394 0.0400 SC Feb 15 1,069,355 465,111 1,159,918 0.0387 0.0387 0.0395 SC Feb 16 1,083,211 467,600 1,165,528 0.0392 0.0389 0.0397 SC Feb 17 1,113,435 482,842 1,193,396 0.0403 0.0402 0.0406 SC Feb 18 1,195,180 515,881 1,256,756 0.0433 0.0429 0.0428 SC Feb 19 1,237,637 538,211 1,291,252 0.0448 0.0448 0.0440 SC Feb 20 1,228,729 535,559 1,283,159 0.0445 0.0445 0.0437 SC Feb 21 1,220,471 532,359 1,276,459 0.0442 0.0443 0.0435 SC Feb 22 1,194,620 523,226 1,257,240 0.0433 0.0435 0.0428 SC Feb 23 1,128,305 491,626 1,202,526 0.0409 0.0409 0.0409 SC Mar 0 1,147,569 507,527 1,208,175 0.0373 0.0369 0.0379 SC Mar 1 1,110,411 488,536 1,170,163 0.0361 0.0355 0.0367 SC Mar 2 1,106,133 482,100 1,160,443 0.0359 0.0351 0.0364 SC Mar 3 1,117,730 484,035 1,164,246 0.0363 0.0352 0.0365 SC Mar 4 1,134,897 488,530 1,175,239 0.0369 0.0355 0.0368 SC Mar 5 1,177,436 506,209 1,223,198 0.0382 0.0368 0.0383 SC Mar 6 1,259,703 551,851 1,318,478 0.0409 0.0401 0.0413 SC Mar 7 1,331,476 588,096 1,389,787 0.0432 0.0428 0.0435 SC Mar 8 1,346,676 607,086 1,416,752 0.0437 0.0442 0.0444 SC Mar 9 1,363,068 610,741 1,424,503 0.0443 0.0444 0.0446 SC Mar 10 1,362,102 613,492 1,412,867 0.0442 0.0446 0.0443 SC Mar 11 1,348,072 608,769 1,397,146 0.0438 0.0443 0.0438 SC Mar 12 1,331,944 603,304 1,378,584 0.0433 0.0439 0.0432 SC Mar 13 1,324,281 598,146 1,363,276 0.0430 0.0435 0.0427 SC Mar 14 1,308,840 587,857 1,346,240 0.0425 0.0428 0.0422 SC Mar 15 1,299,894 581,352 1,334,578 0.0422 0.0423 0.0418 SC Mar 16 1,311,716 586,865 1,342,143 0.0426 0.0427 0.0420 SC Mar 17 1,327,170 594,508 1,355,504 0.0431 0.0432 0.0425 SC Mar 18 1,360,944 609,339 1,389,484 0.0442 0.0443 0.0435 SC Mar 19 1,403,774 632,070 1,434,512 0.0456 0.0460 0.0449 SC Mar 20 1,404,116 635,255 1,438,786 0.0456 0.0462 0.0451 SC Mar 21 1,378,675 627,017 1,419,091 0.0448 0.0456 0.0445 SC Mar 22 1,327,543 607,815 1,381,745 0.0431 0.0442 0.0433 SC Mar 23 1,201,867 548,195 1,274,399 0.0390 0.0399 0.0399 SC Apr 0 1,133,885 466,873 1,159,489 0.0368 0.0358 0.0364 SC Apr 1 1,098,489 445,533 1,126,493 0.0357 0.0341 0.0353

D-34Atmospheric Sciences Group 

### Appendix D Actual 2002 State Level Monthly-Diurnal Profiles

CEM-Based Distribution Alpine Geophysics

SO2 Mass NOx Mass Heat Input State Month Hour [lbs] [lbs] [MMBtu] SO2 Ratio NOx Ratio Heat Input Actual Reported Values [2002] Calculated Ratios

SC Apr 2 1,074,450 434,469 1,105,970 0.0349 0.0333 0.0347 SC Apr 3 1,067,571 432,836 1,101,070 0.0347 0.0332 0.0345 SC Apr 4 1,094,306 440,836 1,117,672 0.0355 0.0338 0.0351 SC Apr 5 1,171,162 473,005 1,179,856 0.0380 0.0362 0.0370 SC Apr 6 1,258,502 523,651 1,267,925 0.0408 0.0401 0.0398 SC Apr 7 1,294,607 547,925 1,302,811 0.0420 0.0420 0.0409 SC Apr 8 1,328,850 566,276 1,332,824 0.0431 0.0434 0.0418 SC Apr 9 1,359,580 580,188 1,362,251 0.0441 0.0445 0.0427 SC Apr 10 1,371,543 583,066 1,386,790 0.0445 0.0447 0.0435 SC Apr 11 1,368,109 583,729 1,407,762 0.0444 0.0447 0.0442 SC Apr 12 1,374,089 588,721 1,424,583 0.0446 0.0451 0.0447 SC Apr 13 1,361,595 583,547 1,420,912 0.0442 0.0447 0.0446 SC Apr 14 1,367,002 588,115 1,443,671 0.0444 0.0451 0.0453 SC Apr 15 1,369,994 591,700 1,455,560 0.0445 0.0453 0.0457 SC Apr 16 1,379,249 593,261 1,463,247 0.0448 0.0455 0.0459 SC Apr 17 1,375,841 592,628 1,462,644 0.0447 0.0454 0.0459 SC Apr 18 1,362,699 588,327 1,449,990 0.0442 0.0451 0.0455 SC Apr 19 1,380,346 594,549 1,460,011 0.0448 0.0456 0.0458 SC Apr 20 1,384,434 598,346 1,458,963 0.0449 0.0458 0.0458 SC Apr 21 1,358,113 591,722 1,423,692 0.0441 0.0453 0.0447 SC Apr 22 1,282,401 557,662 1,334,871 0.0416 0.0427 0.0419 SC Apr 23 1,191,759 504,735 1,232,157 0.0387 0.0387 0.0386 SC May 0 1,228,688 516,553 1,383,850 0.0368 0.0355 0.0362 SC May 1 1,201,855 500,262 1,352,550 0.0360 0.0344 0.0354 SC May 2 1,185,694 491,051 1,336,057 0.0355 0.0338 0.0350 SC May 3 1,169,177 487,170 1,324,226 0.0350 0.0335 0.0346 SC May 4 1,189,532 495,280 1,341,690 0.0356 0.0341 0.0351 SC May 5 1,259,593 523,755 1,406,545 0.0377 0.0360 0.0368 SC May 6 1,333,625 569,197 1,491,985 0.0400 0.0391 0.0390 SC May 7 1,359,691 589,010 1,529,045 0.0407 0.0405 0.0400 SC May 8 1,406,248 612,485 1,576,795 0.0421 0.0421 0.0413 SC May 9 1,444,207 638,558 1,625,268 0.0433 0.0439 0.0425 SC May 10 1,462,974 653,634 1,672,791 0.0438 0.0450 0.0438 SC May 11 1,477,568 659,991 1,710,819 0.0443 0.0454 0.0448 SC May 12 1,490,383 665,928 1,737,149 0.0446 0.0458 0.0454 SC May 13 1,497,507 669,215 1,752,602 0.0449 0.0460 0.0459 SC May 14 1,503,844 671,032 1,763,879 0.0451 0.0461 0.0461 SC May 15 1,516,709 673,616 1,774,779 0.0454 0.0463 0.0464 SC May 16 1,523,324 674,286 1,778,700 0.0456 0.0464 0.0465 SC May 17 1,515,986 671,958 1,772,017 0.0454 0.0462 0.0464 SC May 18 1,493,820 660,267 1,748,196 0.0448 0.0454 0.0457 SC May 19 1,484,653 652,972 1,733,108 0.0445 0.0449 0.0453 SC May 20 1,503,697 661,029 1,732,271 0.0450 0.0455 0.0453 SC May 21 1,471,313 651,703 1,672,660 0.0441 0.0448 0.0438 SC May 22 1,373,862 602,536 1,553,626 0.0412 0.0414 0.0406 SC May 23 1,285,784 549,346 1,453,778 0.0385 0.0378 0.0380 SC Jun 0 1,317,160 534,747 1,418,600 0.0361 0.0350 0.0347 SC Jun 1 1,254,115 504,239 1,360,666 0.0344 0.0330 0.0333 SC Jun 2 1,218,081 490,965 1,327,523 0.0334 0.0321 0.0325 SC Jun 3 1,196,077 481,911 1,308,651 0.0328 0.0315 0.0320 SC Jun 4 1,201,291 483,865 1,307,341 0.0330 0.0316 0.0320 SC Jun 5 1,244,751 500,138 1,339,899 0.0341 0.0327 0.0328 SC Jun 6 1,313,605 529,260 1,394,558 0.0360 0.0346 0.0341

D-35Atmospheric Sciences Group 

### Appendix D Actual 2002 State Level Monthly-Diurnal Profiles

CEM-Based Distribution Alpine Geophysics

SO2 Mass NOx Mass Heat Input State Month Hour [lbs] [lbs] [MMBtu] SO2 Ratio NOx Ratio Heat Input Actual Reported Values [2002] Calculated Ratios

SC Jun 7 1,388,136 570,681 1,480,296 0.0381 0.0373 0.0362 SC Jun 8 1,513,695 627,740 1,604,495 0.0415 0.0410 0.0393 SC Jun 9 1,594,676 669,173 1,708,432 0.0437 0.0438 0.0418 SC Jun 10 1,650,250 702,690 1,831,365 0.0453 0.0459 0.0448 SC Jun 11 1,688,649 720,117 1,930,073 0.0463 0.0471 0.0473 SC Jun 12 1,715,234 734,256 1,998,193 0.0471 0.0480 0.0489 SC Jun 13 1,728,158 739,791 2,029,002 0.0474 0.0484 0.0497 SC Jun 14 1,733,573 740,392 2,036,326 0.0476 0.0484 0.0499 SC Jun 15 1,731,234 738,786 2,032,064 0.0475 0.0483 0.0498 SC Jun 16 1,727,326 737,522 2,027,165 0.0474 0.0482 0.0496 SC Jun 17 1,714,522 733,951 2,011,417 0.0470 0.0480 0.0492 SC Jun 18 1,694,167 725,702 1,990,211 0.0465 0.0474 0.0487 SC Jun 19 1,658,889 709,176 1,932,339 0.0455 0.0464 0.0473 SC Jun 20 1,663,468 706,596 1,888,845 0.0456 0.0462 0.0462 SC Jun 21 1,612,342 690,122 1,779,653 0.0442 0.0451 0.0436 SC Jun 22 1,505,012 643,357 1,614,139 0.0413 0.0421 0.0395 SC Jun 23 1,390,672 579,803 1,493,083 0.0381 0.0379 0.0366 SC Jul 0 1,550,861 647,375 1,621,672 0.0380 0.0379 0.0357 SC Jul 1 1,485,649 606,974 1,557,981 0.0364 0.0355 0.0343 SC Jul 2 1,435,894 577,435 1,512,180 0.0352 0.0338 0.0332 SC Jul 3 1,406,613 563,617 1,489,064 0.0344 0.0330 0.0327 SC Jul 4 1,393,604 552,854 1,472,430 0.0341 0.0324 0.0324 SC Jul 5 1,427,729 562,174 1,495,141 0.0350 0.0329 0.0329 SC Jul 6 1,483,276 581,958 1,528,722 0.0363 0.0341 0.0336 SC Jul 7 1,553,204 624,180 1,617,557 0.0380 0.0365 0.0356 SC Jul 8 1,669,386 685,118 1,746,634 0.0409 0.0401 0.0384 SC Jul 9 1,780,560 744,007 1,914,618 0.0436 0.0436 0.0421 SC Jul 10 1,841,166 780,080 2,059,147 0.0451 0.0457 0.0453 SC Jul 11 1,871,650 797,506 2,160,641 0.0458 0.0467 0.0475 SC Jul 12 1,885,097 804,057 2,215,621 0.0462 0.0471 0.0487 SC Jul 13 1,893,481 804,660 2,247,460 0.0464 0.0471 0.0494 SC Jul 14 1,880,848 802,907 2,250,524 0.0461 0.0470 0.0495 SC Jul 15 1,871,265 802,725 2,253,254 0.0458 0.0470 0.0495 SC Jul 16 1,874,544 803,356 2,251,591 0.0459 0.0470 0.0495 SC Jul 17 1,864,347 800,267 2,238,259 0.0457 0.0468 0.0492 SC Jul 18 1,841,150 793,304 2,202,195 0.0451 0.0464 0.0484 SC Jul 19 1,817,323 777,456 2,137,212 0.0445 0.0455 0.0470 SC Jul 20 1,825,395 776,122 2,056,405 0.0447 0.0454 0.0452 SC Jul 21 1,806,089 766,607 1,942,184 0.0442 0.0449 0.0427 SC Jul 22 1,745,295 737,081 1,813,537 0.0427 0.0431 0.0399 SC Jul 23 1,633,411 690,428 1,704,282 0.0400 0.0404 0.0375 SC Aug 0 1,438,903 564,220 1,495,896 0.0372 0.0362 0.0350 SC Aug 1 1,371,260 533,223 1,434,370 0.0355 0.0342 0.0335 SC Aug 2 1,314,516 510,277 1,387,397 0.0340 0.0327 0.0324 SC Aug 3 1,292,699 501,939 1,371,174 0.0334 0.0322 0.0320 SC Aug 4 1,315,716 507,934 1,381,607 0.0340 0.0326 0.0323 SC Aug 5 1,409,065 544,067 1,448,169 0.0364 0.0349 0.0338 SC Aug 6 1,484,951 578,736 1,510,958 0.0384 0.0371 0.0353 SC Aug 7 1,510,405 596,475 1,565,906 0.0391 0.0383 0.0366 SC Aug 8 1,583,021 630,367 1,655,106 0.0409 0.0404 0.0387 SC Aug 9 1,667,201 673,589 1,798,684 0.0431 0.0432 0.0420 SC Aug 10 1,721,623 702,425 1,936,111 0.0445 0.0451 0.0452 SC Aug 11 1,762,679 721,381 2,040,296 0.0456 0.0463 0.0477

D-36Atmospheric Sciences Group 

### Appendix D Actual 2002 State Level Monthly-Diurnal Profiles

CEM-Based Distribution Alpine Geophysics

SO2 Mass NOx Mass Heat Input State Month Hour [lbs] [lbs] [MMBtu] SO2 Ratio NOx Ratio Heat Input Actual Reported Values [2002] Calculated Ratios

SC Aug 12 1,787,421 735,211 2,090,912 0.0462 0.0472 0.0489 SC Aug 13 1,793,621 740,812 2,115,282 0.0464 0.0475 0.0494 SC Aug 14 1,793,187 740,506 2,117,739 0.0464 0.0475 0.0495 SC Aug 15 1,805,171 745,541 2,123,103 0.0467 0.0478 0.0496 SC Aug 16 1,807,683 746,813 2,121,240 0.0467 0.0479 0.0496 SC Aug 17 1,797,020 739,242 2,103,452 0.0465 0.0474 0.0492 SC Aug 18 1,772,300 727,860 2,068,105 0.0458 0.0467 0.0483 SC Aug 19 1,755,499 718,248 2,025,562 0.0454 0.0461 0.0473 SC Aug 20 1,748,648 715,426 1,965,235 0.0452 0.0459 0.0459 SC Aug 21 1,689,776 690,266 1,822,903 0.0437 0.0443 0.0426 SC Aug 22 1,578,938 640,743 1,664,935 0.0408 0.0411 0.0389 SC Aug 23 1,475,430 586,544 1,546,164 0.0381 0.0376 0.0361 SC Sep 0 1,267,171 489,865 1,287,184 0.0355 0.0347 0.0357 SC Sep 1 1,214,880 466,986 1,245,487 0.0340 0.0330 0.0345 SC Sep 2 1,179,221 452,666 1,218,077 0.0331 0.0320 0.0338 SC Sep 3 1,166,196 446,962 1,205,510 0.0327 0.0316 0.0334 SC Sep 4 1,193,111 456,933 1,221,705 0.0334 0.0323 0.0339 SC Sep 5 1,298,674 501,016 1,299,352 0.0364 0.0355 0.0360 SC Sep 6 1,395,952 546,074 1,378,585 0.0391 0.0386 0.0382 SC Sep 7 1,399,227 551,691 1,397,508 0.0392 0.0390 0.0388 SC Sep 8 1,484,456 586,479 1,473,117 0.0416 0.0415 0.0409 SC Sep 9 1,551,745 619,554 1,550,128 0.0435 0.0438 0.0430 SC Sep 10 1,607,397 642,136 1,608,375 0.0451 0.0454 0.0446 SC Sep 11 1,641,868 654,374 1,654,612 0.0460 0.0463 0.0459 SC Sep 12 1,656,163 663,988 1,683,369 0.0464 0.0470 0.0467 SC Sep 13 1,664,480 668,709 1,698,407 0.0467 0.0473 0.0471 SC Sep 14 1,667,461 671,110 1,704,850 0.0467 0.0475 0.0473 SC Sep 15 1,665,656 670,852 1,701,846 0.0467 0.0475 0.0472 SC Sep 16 1,671,289 672,480 1,697,383 0.0468 0.0476 0.0471 SC Sep 17 1,663,662 668,885 1,691,010 0.0466 0.0473 0.0469 SC Sep 18 1,656,238 662,424 1,678,966 0.0464 0.0469 0.0466 SC Sep 19 1,665,481 663,287 1,673,145 0.0467 0.0469 0.0464 SC Sep 20 1,639,488 655,455 1,639,684 0.0460 0.0464 0.0455 SC Sep 21 1,561,295 625,954 1,561,141 0.0438 0.0443 0.0433 SC Sep 22 1,439,682 571,244 1,443,309 0.0404 0.0404 0.0400 SC Sep 23 1,328,878 522,474 1,345,189 0.0372 0.0370 0.0373 SC Oct 0 1,083,438 432,962 1,077,489 0.0359 0.0355 0.0363 SC Oct 1 1,045,716 411,972 1,041,266 0.0346 0.0338 0.0351 SC Oct 2 1,036,821 405,198 1,029,069 0.0343 0.0332 0.0347 SC Oct 3 1,041,711 404,777 1,026,238 0.0345 0.0332 0.0346 SC Oct 4 1,087,634 424,511 1,063,636 0.0360 0.0348 0.0358 SC Oct 5 1,188,034 464,658 1,138,266 0.0393 0.0381 0.0383 SC Oct 6 1,264,169 506,142 1,202,115 0.0418 0.0415 0.0405 SC Oct 7 1,281,158 514,592 1,225,918 0.0424 0.0422 0.0413 SC Oct 8 1,327,321 532,210 1,264,589 0.0439 0.0436 0.0426 SC Oct 9 1,352,740 543,750 1,289,224 0.0448 0.0446 0.0434 SC Oct 10 1,362,337 555,102 1,312,226 0.0451 0.0455 0.0442 SC Oct 11 1,356,707 556,753 1,327,909 0.0449 0.0456 0.0447 SC Oct 12 1,354,978 556,010 1,344,829 0.0448 0.0456 0.0453 SC Oct 13 1,350,576 555,834 1,350,789 0.0447 0.0456 0.0455 SC Oct 14 1,347,416 554,676 1,351,650 0.0446 0.0455 0.0455 SC Oct 15 1,342,470 552,929 1,352,179 0.0444 0.0453 0.0456 SC Oct 16 1,346,603 553,976 1,354,292 0.0446 0.0454 0.0456

D-37Atmospheric Sciences Group 

### Appendix D Actual 2002 State Level Monthly-Diurnal Profiles

CEM-Based Distribution Alpine Geophysics

SO2 Mass NOx Mass Heat Input State Month Hour [lbs] [lbs] [MMBtu] SO2 Ratio NOx Ratio Heat Input Actual Reported Values [2002] Calculated Ratios

SC Oct 17 1,349,409 551,984 1,350,493 0.0447 0.0452 0.0455 SC Oct 18 1,351,247 548,130 1,346,388 0.0447 0.0449 0.0454 SC Oct 19 1,350,041 549,817 1,335,542 0.0447 0.0451 0.0450 SC Oct 20 1,339,271 544,543 1,310,248 0.0443 0.0446 0.0441 SC Oct 21 1,312,079 532,082 1,273,823 0.0434 0.0436 0.0429 SC Oct 22 1,215,755 494,039 1,195,535 0.0402 0.0405 0.0403 SC Oct 23 1,126,056 454,256 1,119,629 0.0373 0.0372 0.0377 SC Nov 0 1,142,879 465,804 1,092,879 0.0399 0.0397 0.0399 SC Nov 1 1,121,516 454,090 1,069,293 0.0391 0.0387 0.0391 SC Nov 2 1,107,818 445,707 1,056,930 0.0386 0.0380 0.0386 SC Nov 3 1,112,215 448,817 1,060,109 0.0388 0.0382 0.0387 SC Nov 4 1,117,929 452,879 1,068,293 0.0390 0.0386 0.0390 SC Nov 5 1,155,180 470,750 1,105,723 0.0403 0.0401 0.0404 SC Nov 6 1,214,771 493,858 1,148,648 0.0424 0.0421 0.0420 SC Nov 7 1,238,138 509,024 1,183,112 0.0432 0.0434 0.0432 SC Nov 8 1,229,883 505,155 1,180,162 0.0429 0.0430 0.0431 SC Nov 9 1,239,623 505,179 1,179,357 0.0432 0.0430 0.0431 SC Nov 10 1,229,433 501,538 1,163,431 0.0429 0.0427 0.0425 SC Nov 11 1,218,899 498,788 1,159,807 0.0425 0.0425 0.0424 SC Nov 12 1,205,021 493,462 1,152,594 0.0420 0.0420 0.0421 SC Nov 13 1,190,767 485,270 1,136,787 0.0415 0.0413 0.0415 SC Nov 14 1,173,108 478,959 1,124,147 0.0409 0.0408 0.0411 SC Nov 15 1,168,764 477,481 1,121,535 0.0408 0.0407 0.0410 SC Nov 16 1,166,053 478,332 1,126,451 0.0407 0.0408 0.0412 SC Nov 17 1,217,287 499,460 1,166,260 0.0424 0.0426 0.0426 SC Nov 18 1,260,433 520,571 1,201,570 0.0440 0.0444 0.0439 SC Nov 19 1,261,010 520,195 1,196,676 0.0440 0.0443 0.0437 SC Nov 20 1,256,921 518,826 1,192,076 0.0438 0.0442 0.0436 SC Nov 21 1,247,080 517,189 1,187,202 0.0435 0.0441 0.0434 SC Nov 22 1,227,629 508,506 1,169,284 0.0428 0.0433 0.0427 SC Nov 23 1,175,485 486,920 1,126,987 0.0410 0.0415 0.0412 SC Dec 0 1,356,270 556,321 1,309,476 0.0399 0.0399 0.0398 SC Dec 1 1,332,499 540,268 1,279,485 0.0392 0.0387 0.0389 SC Dec 2 1,324,618 536,330 1,275,732 0.0389 0.0384 0.0388 SC Dec 3 1,330,924 538,908 1,284,514 0.0391 0.0386 0.0391 SC Dec 4 1,335,158 545,819 1,296,880 0.0392 0.0391 0.0394 SC Dec 5 1,385,906 565,695 1,340,759 0.0407 0.0405 0.0408 SC Dec 6 1,436,829 586,536 1,387,329 0.0422 0.0420 0.0422 SC Dec 7 1,488,961 611,648 1,440,753 0.0438 0.0438 0.0438 SC Dec 8 1,491,509 613,176 1,444,956 0.0438 0.0440 0.0440 SC Dec 9 1,501,425 618,516 1,447,916 0.0441 0.0443 0.0440 SC Dec 10 1,484,685 610,879 1,431,441 0.0436 0.0438 0.0435 SC Dec 11 1,459,697 593,638 1,395,938 0.0429 0.0426 0.0425 SC Dec 12 1,423,246 578,669 1,365,957 0.0418 0.0415 0.0415 SC Dec 13 1,391,851 570,939 1,345,091 0.0409 0.0409 0.0409 SC Dec 14 1,352,161 557,078 1,319,068 0.0397 0.0399 0.0401 SC Dec 15 1,344,643 551,497 1,312,670 0.0395 0.0395 0.0399 SC Dec 16 1,369,024 559,569 1,333,589 0.0402 0.0401 0.0406 SC Dec 17 1,449,587 595,765 1,398,917 0.0426 0.0427 0.0426 SC Dec 18 1,493,742 621,423 1,438,833 0.0439 0.0445 0.0438 SC Dec 19 1,473,502 611,050 1,427,712 0.0433 0.0438 0.0434 SC Dec 20 1,479,504 608,223 1,424,664 0.0435 0.0436 0.0433 SC Dec 21 1,475,680 608,049 1,421,202 0.0434 0.0436 0.0432

D-38Atmospheric Sciences Group 

### Appendix D Actual 2002 State Level Monthly-Diurnal Profiles

CEM-Based Distribution Alpine Geophysics

SO2 Mass NOx Mass Heat Input State Month Hour [lbs] [lbs] [MMBtu] SO2 Ratio NOx Ratio Heat Input Actual Reported Values [2002] Calculated Ratios

SC Dec 22 1,450,119 597,906 1,401,208 0.0426 0.0429 0.0426 SC Dec 23 1,391,087 573,310 1,351,539 0.0409 0.0411 0.0411 TN Jan 0 2,280,657 1,090,246 2,060,661 0.0408 0.0412 0.0408 TN Jan 1 2,276,680 1,086,084 2,055,798 0.0407 0.0410 0.0407 TN Jan 2 2,272,794 1,084,755 2,049,805 0.0406 0.0409 0.0406 TN Jan 3 2,283,587 1,086,794 2,055,875 0.0408 0.0410 0.0407 TN Jan 4 2,315,278 1,097,078 2,085,158 0.0414 0.0414 0.0413 TN Jan 5 2,354,985 1,117,772 2,125,268 0.0421 0.0422 0.0421 TN Jan 6 2,377,419 1,130,729 2,160,310 0.0425 0.0427 0.0428 TN Jan 7 2,379,741 1,134,700 2,158,578 0.0425 0.0428 0.0427 TN Jan 8 2,385,006 1,131,469 2,152,929 0.0426 0.0427 0.0426 TN Jan 9 2,382,917 1,123,629 2,142,415 0.0426 0.0424 0.0424 TN Jan 10 2,365,473 1,117,013 2,124,072 0.0423 0.0422 0.0420 TN Jan 11 2,327,368 1,103,862 2,103,953 0.0416 0.0417 0.0416 TN Jan 12 2,316,863 1,091,178 2,093,020 0.0414 0.0412 0.0414 TN Jan 13 2,309,096 1,078,383 2,078,746 0.0413 0.0407 0.0411 TN Jan 14 2,299,661 1,075,824 2,074,755 0.0411 0.0406 0.0411 TN Jan 15 2,321,027 1,088,345 2,097,187 0.0415 0.0411 0.0415 TN Jan 16 2,343,037 1,095,908 2,109,557 0.0419 0.0414 0.0418 TN Jan 17 2,367,599 1,107,163 2,131,849 0.0423 0.0418 0.0422 TN Jan 18 2,380,012 1,121,715 2,145,891 0.0425 0.0423 0.0425 TN Jan 19 2,370,033 1,119,519 2,140,261 0.0424 0.0423 0.0424 TN Jan 20 2,365,048 1,117,332 2,136,469 0.0423 0.0422 0.0423 TN Jan 21 2,342,389 1,110,766 2,116,629 0.0419 0.0419 0.0419 TN Jan 22 2,292,432 1,097,607 2,075,794 0.0410 0.0414 0.0411 TN Jan 23 2,253,488 1,082,843 2,042,235 0.0403 0.0409 0.0404 TN Feb 0 2,045,561 1,036,193 1,974,208 0.0411 0.0413 0.0409 TN Feb 1 2,037,112 1,028,755 1,964,950 0.0409 0.0410 0.0407 TN Feb 2 2,036,584 1,027,141 1,965,731 0.0409 0.0409 0.0407 TN Feb 3 2,051,386 1,033,416 1,976,667 0.0412 0.0412 0.0410 TN Feb 4 2,081,945 1,043,732 2,001,259 0.0418 0.0416 0.0415 TN Feb 5 2,119,150 1,058,631 2,035,996 0.0426 0.0422 0.0422 TN Feb 6 2,129,069 1,067,771 2,052,247 0.0428 0.0425 0.0425 TN Feb 7 2,110,861 1,062,664 2,046,802 0.0424 0.0423 0.0424 TN Feb 8 2,121,686 1,063,805 2,048,373 0.0426 0.0424 0.0424 TN Feb 9 2,098,143 1,055,196 2,045,894 0.0422 0.0420 0.0424 TN Feb 10 2,075,935 1,049,309 2,035,769 0.0417 0.0418 0.0422 TN Feb 11 2,068,315 1,047,712 2,029,719 0.0416 0.0417 0.0421 TN Feb 12 2,054,168 1,044,777 2,018,542 0.0413 0.0416 0.0418 TN Feb 13 2,034,932 1,038,578 2,002,914 0.0409 0.0414 0.0415 TN Feb 14 2,011,399 1,030,459 1,985,070 0.0404 0.0410 0.0411 TN Feb 15 2,002,182 1,029,651 1,978,422 0.0402 0.0410 0.0410 TN Feb 16 2,025,350 1,034,663 1,991,100 0.0407 0.0412 0.0413 TN Feb 17 2,061,721 1,046,012 2,017,429 0.0414 0.0417 0.0418 TN Feb 18 2,100,734 1,054,346 2,024,956 0.0422 0.0420 0.0420 TN Feb 19 2,107,282 1,051,903 2,019,594 0.0423 0.0419 0.0418 TN Feb 20 2,118,880 1,052,061 2,023,781 0.0426 0.0419 0.0419 TN Feb 21 2,113,523 1,053,535 2,023,349 0.0425 0.0420 0.0419 TN Feb 22 2,087,880 1,052,103 2,006,920 0.0419 0.0419 0.0416 TN Feb 23 2,079,170 1,048,811 1,999,179 0.0418 0.0418 0.0414 TN Mar 0 2,180,326 1,137,957 2,190,242 0.0405 0.0410 0.0407 TN Mar 1 2,156,648 1,130,759 2,174,875 0.0400 0.0407 0.0404 TN Mar 2 2,137,773 1,126,441 2,164,468 0.0397 0.0405 0.0403

D-39Atmospheric Sciences Group 

### Appendix D Actual 2002 State Level Monthly-Diurnal Profiles

CEM-Based Distribution Alpine Geophysics

SO2 Mass NOx Mass Heat Input State Month Hour [lbs] [lbs] [MMBtu] SO2 Ratio NOx Ratio Heat Input Actual Reported Values [2002] Calculated Ratios

TN Mar 3 2,142,861 1,124,783 2,171,287 0.0398 0.0405 0.0404 TN Mar 4 2,165,441 1,134,289 2,194,430 0.0402 0.0408 0.0408 TN Mar 5 2,210,240 1,150,811 2,235,294 0.0410 0.0414 0.0416 TN Mar 6 2,247,318 1,174,062 2,289,372 0.0417 0.0423 0.0426 TN Mar 7 2,237,563 1,174,836 2,285,107 0.0415 0.0423 0.0425 TN Mar 8 2,250,433 1,170,688 2,270,641 0.0418 0.0421 0.0422 TN Mar 9 2,278,430 1,175,946 2,286,604 0.0423 0.0423 0.0425 TN Mar 10 2,288,113 1,178,902 2,294,721 0.0425 0.0424 0.0427 TN Mar 11 2,291,351 1,179,668 2,283,107 0.0425 0.0425 0.0425 TN Mar 12 2,290,673 1,174,183 2,272,685 0.0425 0.0423 0.0423 TN Mar 13 2,286,454 1,166,158 2,256,742 0.0424 0.0420 0.0420 TN Mar 14 2,280,776 1,163,689 2,246,497 0.0423 0.0419 0.0418 TN Mar 15 2,284,314 1,161,581 2,249,873 0.0424 0.0418 0.0418 TN Mar 16 2,285,313 1,160,340 2,250,387 0.0424 0.0418 0.0418 TN Mar 17 2,287,641 1,162,243 2,248,851 0.0425 0.0418 0.0418 TN Mar 18 2,312,247 1,170,061 2,262,283 0.0429 0.0421 0.0421 TN Mar 19 2,314,670 1,170,576 2,259,844 0.0430 0.0421 0.0420 TN Mar 20 2,302,073 1,165,324 2,253,878 0.0427 0.0419 0.0419 TN Mar 21 2,274,016 1,161,954 2,248,913 0.0422 0.0418 0.0418 TN Mar 22 2,209,224 1,140,592 2,203,141 0.0410 0.0410 0.0410 TN Mar 23 2,174,554 1,130,438 2,180,161 0.0404 0.0407 0.0405 TN Apr 0 2,044,749 1,061,543 2,070,830 0.0381 0.0394 0.0386 TN Apr 1 2,005,156 1,046,422 2,036,645 0.0374 0.0388 0.0379 TN Apr 2 2,004,324 1,041,500 2,026,268 0.0374 0.0387 0.0378 TN Apr 3 2,045,372 1,055,392 2,058,094 0.0381 0.0392 0.0383 TN Apr 4 2,141,951 1,088,750 2,135,048 0.0399 0.0404 0.0398 TN Apr 5 2,226,460 1,118,523 2,198,103 0.0415 0.0415 0.0410 TN Apr 6 2,233,453 1,121,488 2,209,347 0.0416 0.0416 0.0412 TN Apr 7 2,264,203 1,131,645 2,229,844 0.0422 0.0420 0.0415 TN Apr 8 2,284,079 1,138,038 2,249,554 0.0426 0.0422 0.0419 TN Apr 9 2,297,398 1,139,610 2,272,535 0.0428 0.0423 0.0423 TN Apr 10 2,312,291 1,140,698 2,298,553 0.0431 0.0423 0.0428 TN Apr 11 2,309,811 1,138,665 2,307,521 0.0431 0.0423 0.0430 TN Apr 12 2,310,818 1,140,028 2,311,347 0.0431 0.0423 0.0431 TN Apr 13 2,310,720 1,146,265 2,329,188 0.0431 0.0425 0.0434 TN Apr 14 2,309,927 1,147,491 2,336,905 0.0431 0.0426 0.0435 TN Apr 15 2,310,604 1,149,649 2,341,989 0.0431 0.0427 0.0436 TN Apr 16 2,311,508 1,155,848 2,347,038 0.0431 0.0429 0.0437 TN Apr 17 2,311,177 1,158,728 2,342,439 0.0431 0.0430 0.0436 TN Apr 18 2,333,502 1,167,531 2,352,881 0.0435 0.0433 0.0438 TN Apr 19 2,346,118 1,165,574 2,352,994 0.0437 0.0433 0.0438 TN Apr 20 2,337,132 1,158,848 2,321,872 0.0436 0.0430 0.0433 TN Apr 21 2,274,011 1,136,940 2,237,857 0.0424 0.0422 0.0417 TN Apr 22 2,188,145 1,109,353 2,174,202 0.0408 0.0412 0.0405 TN Apr 23 2,122,615 1,085,586 2,127,949 0.0396 0.0403 0.0396 TN May 0 2,097,390 1,044,045 2,183,067 0.0390 0.0398 0.0394 TN May 1 2,059,125 1,025,383 2,145,941 0.0383 0.0391 0.0387 TN May 2 2,044,200 1,012,178 2,124,933 0.0380 0.0386 0.0384 TN May 3 2,062,636 1,018,551 2,141,667 0.0383 0.0389 0.0387 TN May 4 2,107,827 1,041,643 2,184,093 0.0392 0.0397 0.0394 TN May 5 2,168,969 1,065,468 2,238,029 0.0403 0.0406 0.0404 TN May 6 2,178,130 1,073,329 2,252,855 0.0405 0.0409 0.0407 TN May 7 2,223,555 1,085,827 2,276,424 0.0413 0.0414 0.0411

D-40Atmospheric Sciences Group 

### Appendix D Actual 2002 State Level Monthly-Diurnal Profiles

CEM-Based Distribution Alpine Geophysics

SO2 Mass NOx Mass Heat Input State Month Hour [lbs] [lbs] [MMBtu] SO2 Ratio NOx Ratio Heat Input Actual Reported Values [2002] Calculated Ratios

TN May 8 2,291,831 1,109,084 2,334,809 0.0426 0.0423 0.0421 TN May 9 2,304,353 1,112,287 2,352,677 0.0428 0.0424 0.0425 TN May 10 2,316,864 1,119,631 2,371,950 0.0431 0.0427 0.0428 TN May 11 2,330,777 1,130,585 2,396,929 0.0433 0.0431 0.0433 TN May 12 2,332,930 1,125,359 2,400,531 0.0434 0.0429 0.0433 TN May 13 2,349,411 1,137,190 2,423,689 0.0437 0.0434 0.0438 TN May 14 2,344,893 1,131,685 2,422,228 0.0436 0.0432 0.0437 TN May 15 2,333,830 1,124,888 2,407,856 0.0434 0.0429 0.0435 TN May 16 2,337,173 1,127,827 2,408,655 0.0434 0.0430 0.0435 TN May 17 2,324,409 1,124,076 2,389,619 0.0432 0.0429 0.0431 TN May 18 2,328,213 1,121,883 2,381,990 0.0433 0.0428 0.0430 TN May 19 2,350,543 1,121,297 2,389,039 0.0437 0.0428 0.0431 TN May 20 2,332,491 1,118,215 2,372,526 0.0434 0.0427 0.0428 TN May 21 2,250,042 1,094,437 2,304,079 0.0418 0.0418 0.0416 TN May 22 2,181,192 1,080,175 2,264,001 0.0405 0.0412 0.0409 TN May 23 2,142,259 1,066,553 2,229,848 0.0398 0.0407 0.0403 TN Jun 0 2,246,844 1,163,244 2,348,629 0.0387 0.0402 0.0390 TN Jun 1 2,157,024 1,116,780 2,254,251 0.0371 0.0386 0.0374 TN Jun 2 2,114,606 1,091,410 2,206,758 0.0364 0.0377 0.0367 TN Jun 3 2,122,681 1,090,934 2,209,308 0.0365 0.0377 0.0367 TN Jun 4 2,166,926 1,110,534 2,256,363 0.0373 0.0383 0.0375 TN Jun 5 2,197,182 1,121,043 2,280,986 0.0378 0.0387 0.0379 TN Jun 6 2,245,908 1,133,255 2,321,132 0.0387 0.0391 0.0386 TN Jun 7 2,380,289 1,182,770 2,422,629 0.0410 0.0408 0.0402 TN Jun 8 2,475,740 1,222,110 2,519,902 0.0426 0.0422 0.0419 TN Jun 9 2,521,948 1,243,308 2,580,303 0.0434 0.0429 0.0429 TN Jun 10 2,540,649 1,252,511 2,616,466 0.0437 0.0432 0.0435 TN Jun 11 2,556,532 1,258,730 2,639,054 0.0440 0.0435 0.0438 TN Jun 12 2,551,271 1,259,623 2,658,926 0.0439 0.0435 0.0442 TN Jun 13 2,556,432 1,260,605 2,690,570 0.0440 0.0435 0.0447 TN Jun 14 2,568,395 1,257,352 2,701,819 0.0442 0.0434 0.0449 TN Jun 15 2,571,738 1,261,886 2,709,178 0.0443 0.0436 0.0450 TN Jun 16 2,571,247 1,259,730 2,695,121 0.0443 0.0435 0.0448 TN Jun 17 2,567,684 1,258,082 2,681,601 0.0442 0.0434 0.0445 TN Jun 18 2,563,903 1,254,680 2,663,559 0.0441 0.0433 0.0442 TN Jun 19 2,570,639 1,256,567 2,651,315 0.0443 0.0434 0.0440 TN Jun 20 2,557,808 1,252,991 2,621,719 0.0440 0.0433 0.0435 TN Jun 21 2,502,736 1,237,210 2,547,606 0.0431 0.0427 0.0423 TN Jun 22 2,415,922 1,215,513 2,484,921 0.0416 0.0420 0.0413 TN Jun 23 2,359,788 1,199,917 2,443,012 0.0406 0.0414 0.0406 TN Jul 0 2,483,790 1,202,492 2,513,570 0.0396 0.0405 0.0385 TN Jul 1 2,399,485 1,184,193 2,454,175 0.0383 0.0399 0.0376 TN Jul 2 2,342,566 1,162,167 2,402,688 0.0374 0.0391 0.0368 TN Jul 3 2,351,902 1,159,517 2,402,184 0.0375 0.0391 0.0368 TN Jul 4 2,394,141 1,167,605 2,428,316 0.0382 0.0393 0.0372 TN Jul 5 2,405,527 1,170,775 2,445,342 0.0384 0.0394 0.0375 TN Jul 6 2,475,120 1,185,236 2,494,763 0.0395 0.0399 0.0382 TN Jul 7 2,594,352 1,225,183 2,593,504 0.0414 0.0413 0.0397 TN Jul 8 2,665,212 1,241,348 2,664,052 0.0425 0.0418 0.0408 TN Jul 9 2,717,800 1,258,136 2,754,759 0.0433 0.0424 0.0422 TN Jul 10 2,735,468 1,268,759 2,858,838 0.0436 0.0427 0.0438 TN Jul 11 2,736,509 1,272,416 2,925,505 0.0436 0.0429 0.0448 TN Jul 12 2,733,200 1,278,347 2,972,783 0.0436 0.0431 0.0456

D-41Atmospheric Sciences Group 

### Appendix D Actual 2002 State Level Monthly-Diurnal Profiles

CEM-Based Distribution Alpine Geophysics

SO2 Mass NOx Mass Heat Input State Month Hour [lbs] [lbs] [MMBtu] SO2 Ratio NOx Ratio Heat Input Actual Reported Values [2002] Calculated Ratios

TN Jul 13 2,721,767 1,271,801 2,979,932 0.0434 0.0428 0.0457 TN Jul 14 2,725,109 1,273,232 2,983,227 0.0435 0.0429 0.0457 TN Jul 15 2,727,026 1,274,190 2,979,882 0.0435 0.0429 0.0457 TN Jul 16 2,728,768 1,277,405 2,969,560 0.0435 0.0430 0.0455 TN Jul 17 2,730,777 1,275,804 2,938,302 0.0435 0.0430 0.0450 TN Jul 18 2,730,727 1,275,132 2,908,965 0.0435 0.0430 0.0446 TN Jul 19 2,734,862 1,273,353 2,885,817 0.0436 0.0429 0.0442 TN Jul 20 2,724,414 1,269,790 2,824,939 0.0434 0.0428 0.0433 TN Jul 21 2,682,158 1,261,150 2,709,560 0.0428 0.0425 0.0415 TN Jul 22 2,609,134 1,237,889 2,605,099 0.0416 0.0417 0.0399 TN Jul 23 2,566,458 1,219,764 2,564,354 0.0409 0.0411 0.0393 TN Aug 0 2,589,072 1,244,659 2,571,778 0.0400 0.0406 0.0391 TN Aug 1 2,482,005 1,213,802 2,491,469 0.0383 0.0396 0.0378 TN Aug 2 2,412,655 1,190,281 2,433,679 0.0373 0.0388 0.0370 TN Aug 3 2,415,732 1,186,501 2,431,309 0.0373 0.0387 0.0369 TN Aug 4 2,517,052 1,216,870 2,509,643 0.0389 0.0397 0.0381 TN Aug 5 2,560,068 1,236,898 2,557,754 0.0395 0.0403 0.0388 TN Aug 6 2,573,052 1,239,009 2,559,716 0.0397 0.0404 0.0389 TN Aug 7 2,687,855 1,273,323 2,636,910 0.0415 0.0415 0.0400 TN Aug 8 2,751,791 1,288,132 2,706,827 0.0425 0.0420 0.0411 TN Aug 9 2,785,826 1,297,919 2,766,035 0.0430 0.0423 0.0420 TN Aug 10 2,794,196 1,305,843 2,842,356 0.0432 0.0426 0.0432 TN Aug 11 2,796,816 1,311,987 2,907,571 0.0432 0.0428 0.0442 TN Aug 12 2,807,974 1,318,004 2,952,191 0.0434 0.0430 0.0448 TN Aug 13 2,808,826 1,320,679 2,973,811 0.0434 0.0431 0.0452 TN Aug 14 2,811,072 1,322,692 2,980,643 0.0434 0.0431 0.0453 TN Aug 15 2,811,713 1,323,530 2,985,965 0.0434 0.0432 0.0453 TN Aug 16 2,814,605 1,319,242 2,961,149 0.0435 0.0430 0.0450 TN Aug 17 2,809,050 1,314,222 2,946,849 0.0434 0.0429 0.0448 TN Aug 18 2,811,343 1,310,855 2,921,085 0.0434 0.0428 0.0444 TN Aug 19 2,822,940 1,309,436 2,898,504 0.0436 0.0427 0.0440 TN Aug 20 2,791,507 1,300,921 2,825,941 0.0431 0.0424 0.0429 TN Aug 21 2,746,217 1,286,560 2,726,683 0.0424 0.0420 0.0414 TN Aug 22 2,687,580 1,269,256 2,648,952 0.0415 0.0414 0.0402 TN Aug 23 2,643,644 1,255,684 2,607,394 0.0408 0.0410 0.0396 TN Sep 0 2,100,256 994,602 2,062,966 0.0379 0.0395 0.0380 TN Sep 1 2,047,482 972,290 2,009,555 0.0370 0.0386 0.0370 TN Sep 2 2,011,459 948,849 1,968,782 0.0363 0.0376 0.0363 TN Sep 3 2,022,730 952,560 1,976,847 0.0365 0.0378 0.0364 TN Sep 4 2,110,465 985,460 2,053,490 0.0381 0.0391 0.0378 TN Sep 5 2,217,288 1,025,173 2,144,343 0.0400 0.0407 0.0395 TN Sep 6 2,208,307 1,025,125 2,148,584 0.0399 0.0407 0.0396 TN Sep 7 2,272,117 1,042,945 2,204,052 0.0410 0.0414 0.0406 TN Sep 8 2,353,309 1,065,925 2,273,730 0.0425 0.0423 0.0419 TN Sep 9 2,390,600 1,078,517 2,315,077 0.0432 0.0428 0.0427 TN Sep 10 2,415,712 1,082,908 2,333,874 0.0436 0.0430 0.0430 TN Sep 11 2,422,511 1,085,326 2,366,086 0.0438 0.0431 0.0436 TN Sep 12 2,432,854 1,088,395 2,393,500 0.0439 0.0432 0.0441 TN Sep 13 2,438,961 1,094,403 2,426,071 0.0441 0.0434 0.0447 TN Sep 14 2,442,999 1,091,969 2,454,300 0.0441 0.0433 0.0452 TN Sep 15 2,449,388 1,092,741 2,462,484 0.0442 0.0434 0.0454 TN Sep 16 2,450,695 1,096,504 2,469,534 0.0443 0.0435 0.0455 TN Sep 17 2,452,366 1,099,411 2,453,851 0.0443 0.0436 0.0452

D-42Atmospheric Sciences Group 

### Appendix D Actual 2002 State Level Monthly-Diurnal Profiles

CEM-Based Distribution Alpine Geophysics

SO2 Mass NOx Mass Heat Input State Month Hour [lbs] [lbs] [MMBtu] SO2 Ratio NOx Ratio Heat Input Actual Reported Values [2002] Calculated Ratios

TN Sep 18 2,479,684 1,100,837 2,448,194 0.0448 0.0437 0.0451 TN Sep 19 2,479,355 1,098,149 2,427,647 0.0448 0.0436 0.0447 TN Sep 20 2,436,004 1,083,302 2,338,680 0.0440 0.0430 0.0431 TN Sep 21 2,329,020 1,057,042 2,243,274 0.0421 0.0419 0.0413 TN Sep 22 2,234,964 1,032,337 2,174,590 0.0404 0.0410 0.0401 TN Sep 23 2,165,417 1,008,946 2,117,775 0.0391 0.0400 0.0390 TN Oct 0 2,139,772 882,922 1,778,041 0.0390 0.0395 0.0393 TN Oct 1 2,091,048 864,540 1,731,779 0.0381 0.0387 0.0383 TN Oct 2 2,071,604 853,095 1,712,494 0.0378 0.0381 0.0379 TN Oct 3 2,110,192 863,463 1,734,343 0.0385 0.0386 0.0383 TN Oct 4 2,186,854 888,082 1,786,906 0.0399 0.0397 0.0395 TN Oct 5 2,268,051 920,636 1,849,494 0.0414 0.0412 0.0409 TN Oct 6 2,246,949 918,115 1,842,517 0.0410 0.0411 0.0407 TN Oct 7 2,305,963 935,475 1,879,680 0.0421 0.0418 0.0416 TN Oct 8 2,334,590 941,996 1,900,013 0.0426 0.0421 0.0420 TN Oct 9 2,348,131 947,167 1,918,210 0.0428 0.0424 0.0424 TN Oct 10 2,352,830 948,748 1,926,088 0.0429 0.0424 0.0426 TN Oct 11 2,360,530 954,116 1,943,405 0.0431 0.0427 0.0430 TN Oct 12 2,359,928 953,643 1,946,378 0.0431 0.0426 0.0430 TN Oct 13 2,355,481 954,978 1,952,041 0.0430 0.0427 0.0432 TN Oct 14 2,352,945 958,397 1,962,268 0.0429 0.0429 0.0434 TN Oct 15 2,367,845 963,646 1,970,641 0.0432 0.0431 0.0436 TN Oct 16 2,372,944 965,803 1,972,460 0.0433 0.0432 0.0436 TN Oct 17 2,384,097 969,314 1,980,106 0.0435 0.0433 0.0438 TN Oct 18 2,383,452 969,581 1,980,602 0.0435 0.0434 0.0438 TN Oct 19 2,371,349 964,505 1,964,370 0.0433 0.0431 0.0434 TN Oct 20 2,343,180 959,852 1,926,794 0.0427 0.0429 0.0426 TN Oct 21 2,303,770 951,687 1,902,263 0.0420 0.0426 0.0421 TN Oct 22 2,227,075 926,290 1,857,672 0.0406 0.0414 0.0411 TN Oct 23 2,177,392 905,891 1,818,658 0.0397 0.0405 0.0402 TN Nov 0 2,122,166 939,253 1,824,730 0.0404 0.0409 0.0408 TN Nov 1 2,103,234 928,523 1,808,506 0.0401 0.0405 0.0405 TN Nov 2 2,081,677 922,513 1,796,588 0.0397 0.0402 0.0402 TN Nov 3 2,091,184 924,630 1,801,275 0.0399 0.0403 0.0403 TN Nov 4 2,140,977 939,754 1,834,880 0.0408 0.0410 0.0410 TN Nov 5 2,185,224 954,192 1,874,290 0.0416 0.0416 0.0419 TN Nov 6 2,215,954 968,937 1,904,312 0.0422 0.0422 0.0426 TN Nov 7 2,199,361 966,143 1,890,767 0.0419 0.0421 0.0423 TN Nov 8 2,240,555 976,082 1,906,513 0.0427 0.0425 0.0426 TN Nov 9 2,235,377 969,674 1,896,398 0.0426 0.0423 0.0424 TN Nov 10 2,228,033 963,362 1,886,306 0.0425 0.0420 0.0422 TN Nov 11 2,201,933 954,595 1,868,083 0.0420 0.0416 0.0418 TN Nov 12 2,186,268 952,154 1,856,347 0.0417 0.0415 0.0415 TN Nov 13 2,173,193 948,302 1,846,796 0.0414 0.0413 0.0413 TN Nov 14 2,169,805 946,823 1,845,494 0.0414 0.0413 0.0413 TN Nov 15 2,173,733 947,154 1,849,851 0.0414 0.0413 0.0414 TN Nov 16 2,214,871 958,831 1,871,799 0.0422 0.0418 0.0419 TN Nov 17 2,276,241 979,171 1,907,962 0.0434 0.0427 0.0427 TN Nov 18 2,264,239 983,901 1,905,184 0.0431 0.0429 0.0426 TN Nov 19 2,252,067 981,371 1,900,588 0.0429 0.0428 0.0425 TN Nov 20 2,236,975 974,822 1,890,883 0.0426 0.0425 0.0423 TN Nov 21 2,206,086 967,213 1,874,494 0.0420 0.0422 0.0419 TN Nov 22 2,150,907 951,900 1,840,745 0.0410 0.0415 0.0412

D-43Atmospheric Sciences Group 

### Appendix D Actual 2002 State Level Monthly-Diurnal Profiles

CEM-Based Distribution Alpine Geophysics

SO2 Mass NOx Mass Heat Input State Month Hour [lbs] [lbs] [MMBtu] SO2 Ratio NOx Ratio Heat Input Actual Reported Values [2002] Calculated Ratios

TN Nov 23 2,123,724 941,780 1,821,462 0.0405 0.0411 0.0407 TN Dec 0 2,375,447 1,040,346 1,966,374 0.0404 0.0410 0.0405 TN Dec 1 2,368,124 1,038,608 1,961,291 0.0403 0.0410 0.0404 TN Dec 2 2,365,244 1,040,760 1,962,485 0.0403 0.0411 0.0404 TN Dec 3 2,374,892 1,039,526 1,967,265 0.0404 0.0410 0.0405 TN Dec 4 2,400,829 1,049,395 1,987,220 0.0409 0.0414 0.0409 TN Dec 5 2,444,720 1,061,600 2,019,991 0.0416 0.0419 0.0416 TN Dec 6 2,479,036 1,073,879 2,059,962 0.0422 0.0424 0.0424 TN Dec 7 2,454,089 1,064,469 2,052,942 0.0418 0.0420 0.0423 TN Dec 8 2,506,996 1,084,025 2,073,253 0.0427 0.0428 0.0427 TN Dec 9 2,493,623 1,074,369 2,057,139 0.0424 0.0424 0.0424 TN Dec 10 2,468,993 1,059,911 2,031,806 0.0420 0.0418 0.0419 TN Dec 11 2,443,688 1,052,604 2,013,783 0.0416 0.0415 0.0415 TN Dec 12 2,432,161 1,043,185 2,000,237 0.0414 0.0411 0.0412 TN Dec 13 2,412,745 1,034,056 1,982,778 0.0411 0.0408 0.0409 TN Dec 14 2,387,833 1,027,022 1,967,780 0.0406 0.0405 0.0405 TN Dec 15 2,410,985 1,029,460 1,979,718 0.0410 0.0406 0.0408 TN Dec 16 2,485,741 1,047,783 2,034,725 0.0423 0.0413 0.0419 TN Dec 17 2,530,101 1,068,450 2,087,328 0.0431 0.0421 0.0430 TN Dec 18 2,524,339 1,079,512 2,098,589 0.0430 0.0426 0.0432 TN Dec 19 2,513,226 1,082,453 2,092,628 0.0428 0.0427 0.0431 TN Dec 20 2,511,044 1,079,600 2,081,736 0.0427 0.0426 0.0429 TN Dec 21 2,499,871 1,073,275 2,053,754 0.0426 0.0423 0.0423 TN Dec 22 2,456,046 1,060,522 2,012,941 0.0418 0.0418 0.0415 TN Dec 23 2,410,321 1,047,159 1,982,293 0.0410 0.0413 0.0408 VA Jan 0 1,469,978 510,941 1,363,411 0.0382 0.0368 0.0382 VA Jan 1 1,413,972 489,263 1,318,879 0.0368 0.0352 0.0369 VA Jan 2 1,394,261 477,993 1,299,882 0.0362 0.0344 0.0364 VA Jan 3 1,397,937 478,827 1,303,996 0.0363 0.0345 0.0365 VA Jan 4 1,416,371 486,582 1,324,620 0.0368 0.0350 0.0371 VA Jan 5 1,487,816 517,463 1,389,246 0.0387 0.0373 0.0389 VA Jan 6 1,623,644 579,686 1,510,446 0.0422 0.0418 0.0423 VA Jan 7 1,715,251 625,847 1,590,037 0.0446 0.0451 0.0445 VA Jan 8 1,722,037 632,495 1,599,147 0.0448 0.0456 0.0448 VA Jan 9 1,720,004 632,290 1,597,612 0.0447 0.0455 0.0447 VA Jan 10 1,706,659 626,351 1,584,494 0.0444 0.0451 0.0444 VA Jan 11 1,689,686 619,991 1,567,420 0.0439 0.0447 0.0439 VA Jan 12 1,658,244 607,065 1,538,644 0.0431 0.0437 0.0431 VA Jan 13 1,625,083 594,625 1,510,414 0.0422 0.0428 0.0423 VA Jan 14 1,569,117 572,708 1,464,270 0.0408 0.0412 0.0410 VA Jan 15 1,555,639 568,031 1,453,720 0.0404 0.0409 0.0407 VA Jan 16 1,587,985 579,215 1,480,877 0.0413 0.0417 0.0414 VA Jan 17 1,695,410 621,520 1,572,071 0.0441 0.0448 0.0440 VA Jan 18 1,738,629 643,076 1,610,889 0.0452 0.0463 0.0451 VA Jan 19 1,730,939 638,860 1,599,981 0.0450 0.0460 0.0448 VA Jan 20 1,708,932 629,991 1,578,255 0.0444 0.0454 0.0442 VA Jan 21 1,687,903 621,447 1,553,653 0.0439 0.0448 0.0435 VA Jan 22 1,616,851 584,859 1,491,201 0.0420 0.0421 0.0417 VA Jan 23 1,542,767 544,940 1,423,800 0.0401 0.0392 0.0399 VA Feb 0 1,368,690 469,483 1,181,951 0.0378 0.0369 0.0377 VA Feb 1 1,336,875 456,681 1,154,602 0.0369 0.0359 0.0369 VA Feb 2 1,322,779 451,116 1,147,582 0.0365 0.0355 0.0366 VA Feb 3 1,333,836 458,129 1,164,392 0.0368 0.0361 0.0372

D-44Atmospheric Sciences Group 

### Appendix D Actual 2002 State Level Monthly-Diurnal Profiles

CEM-Based Distribution Alpine Geophysics

SO2 Mass NOx Mass Heat Input State Month Hour [lbs] [lbs] [MMBtu] SO2 Ratio NOx Ratio Heat Input Actual Reported Values [2002] Calculated Ratios

VA Feb 4 1,361,878 471,759 1,192,234 0.0376 0.0371 0.0381 VA Feb 5 1,421,122 494,336 1,243,585 0.0392 0.0389 0.0397 VA Feb 6 1,530,749 542,251 1,336,999 0.0422 0.0427 0.0427 VA Feb 7 1,602,705 572,795 1,400,421 0.0442 0.0451 0.0447 VA Feb 8 1,613,145 574,906 1,405,919 0.0445 0.0452 0.0449 VA Feb 9 1,615,977 574,927 1,401,863 0.0446 0.0452 0.0448 VA Feb 10 1,607,668 568,840 1,386,028 0.0444 0.0448 0.0443 VA Feb 11 1,584,820 559,052 1,360,943 0.0437 0.0440 0.0435 VA Feb 12 1,549,939 544,312 1,333,674 0.0428 0.0428 0.0426 VA Feb 13 1,525,397 535,758 1,314,055 0.0421 0.0422 0.0420 VA Feb 14 1,499,947 524,061 1,291,568 0.0414 0.0412 0.0412 VA Feb 15 1,484,587 518,692 1,278,640 0.0410 0.0408 0.0408 VA Feb 16 1,491,150 520,331 1,284,022 0.0411 0.0409 0.0410 VA Feb 17 1,545,105 540,830 1,325,078 0.0426 0.0426 0.0423 VA Feb 18 1,617,388 572,189 1,387,502 0.0446 0.0450 0.0443 VA Feb 19 1,624,248 576,665 1,395,102 0.0448 0.0454 0.0445 VA Feb 20 1,615,343 571,246 1,385,202 0.0446 0.0450 0.0442 VA Feb 21 1,594,985 563,656 1,368,972 0.0440 0.0444 0.0437 VA Feb 22 1,536,741 541,001 1,321,964 0.0424 0.0426 0.0422 VA Feb 23 1,461,207 504,963 1,256,551 0.0403 0.0397 0.0401 VA Mar 0 1,279,376 439,049 1,063,062 0.0371 0.0365 0.0374 VA Mar 1 1,233,249 418,530 1,024,957 0.0358 0.0348 0.0360 VA Mar 2 1,207,911 410,251 1,007,598 0.0350 0.0341 0.0354 VA Mar 3 1,216,260 412,516 1,018,161 0.0353 0.0343 0.0358 VA Mar 4 1,240,030 421,138 1,037,719 0.0360 0.0351 0.0365 VA Mar 5 1,327,489 457,104 1,111,007 0.0385 0.0380 0.0391 VA Mar 6 1,444,267 501,981 1,200,290 0.0419 0.0418 0.0422 VA Mar 7 1,498,835 523,135 1,248,898 0.0435 0.0435 0.0439 VA Mar 8 1,518,411 534,023 1,265,340 0.0440 0.0444 0.0445 VA Mar 9 1,530,914 537,909 1,269,390 0.0444 0.0448 0.0446 VA Mar 10 1,534,346 538,245 1,265,708 0.0445 0.0448 0.0445 VA Mar 11 1,541,252 542,417 1,260,104 0.0447 0.0451 0.0443 VA Mar 12 1,534,861 536,853 1,247,994 0.0445 0.0447 0.0439 VA Mar 13 1,521,261 531,616 1,236,573 0.0441 0.0442 0.0435 VA Mar 14 1,481,449 518,802 1,207,868 0.0429 0.0432 0.0425 VA Mar 15 1,464,895 510,978 1,198,302 0.0425 0.0425 0.0421 VA Mar 16 1,464,553 510,115 1,204,163 0.0425 0.0425 0.0423 VA Mar 17 1,482,592 517,774 1,220,188 0.0430 0.0431 0.0429 VA Mar 18 1,532,009 537,788 1,260,929 0.0444 0.0448 0.0443 VA Mar 19 1,561,784 551,019 1,280,662 0.0453 0.0459 0.0450 VA Mar 20 1,544,567 544,288 1,264,308 0.0448 0.0453 0.0444 VA Mar 21 1,518,580 536,290 1,240,768 0.0440 0.0446 0.0436 VA Mar 22 1,446,590 507,931 1,186,577 0.0419 0.0423 0.0417 VA Mar 23 1,367,554 474,384 1,124,567 0.0396 0.0395 0.0395 VA Apr 0 1,240,716 406,440 987,895 0.0369 0.0347 0.0357 VA Apr 1 1,213,794 397,410 965,908 0.0361 0.0339 0.0349 VA Apr 2 1,200,095 393,264 957,266 0.0357 0.0335 0.0346 VA Apr 3 1,203,851 394,822 962,158 0.0358 0.0337 0.0348 VA Apr 4 1,244,120 413,841 998,655 0.0370 0.0353 0.0361 VA Apr 5 1,339,178 457,128 1,077,834 0.0398 0.0390 0.0390 VA Apr 6 1,395,573 483,859 1,128,950 0.0415 0.0413 0.0408 VA Apr 7 1,426,154 497,975 1,159,394 0.0424 0.0425 0.0419 VA Apr 8 1,444,940 506,658 1,176,576 0.0429 0.0432 0.0426

D-45Atmospheric Sciences Group 

### Appendix D Actual 2002 State Level Monthly-Diurnal Profiles

CEM-Based Distribution Alpine Geophysics

SO2 Mass NOx Mass Heat Input State Month Hour [lbs] [lbs] [MMBtu] SO2 Ratio NOx Ratio Heat Input Actual Reported Values [2002] Calculated Ratios

VA Apr 9 1,476,162 522,122 1,206,938 0.0439 0.0445 0.0437 VA Apr 10 1,486,502 529,550 1,234,909 0.0442 0.0452 0.0447 VA Apr 11 1,493,336 533,666 1,254,458 0.0444 0.0455 0.0454 VA Apr 12 1,492,266 533,296 1,259,077 0.0443 0.0455 0.0456 VA Apr 13 1,485,756 533,147 1,258,882 0.0441 0.0455 0.0455 VA Apr 14 1,473,870 527,614 1,248,261 0.0438 0.0450 0.0452 VA Apr 15 1,476,587 528,575 1,241,334 0.0439 0.0451 0.0449 VA Apr 16 1,470,082 525,736 1,230,503 0.0437 0.0448 0.0445 VA Apr 17 1,466,249 523,085 1,219,327 0.0436 0.0446 0.0441 VA Apr 18 1,462,774 521,639 1,217,577 0.0435 0.0445 0.0441 VA Apr 19 1,509,568 541,326 1,258,536 0.0448 0.0462 0.0455 VA Apr 20 1,501,750 536,426 1,250,026 0.0446 0.0457 0.0452 VA Apr 21 1,463,454 514,150 1,200,114 0.0435 0.0438 0.0434 VA Apr 22 1,381,127 468,961 1,102,738 0.0410 0.0400 0.0399 VA Apr 23 1,310,475 435,052 1,042,101 0.0389 0.0371 0.0377 VA May 0 1,034,088 374,835 945,590 0.0344 0.0336 0.0347 VA May 1 960,760 346,845 890,073 0.0320 0.0311 0.0327 VA May 2 932,997 334,289 866,886 0.0310 0.0300 0.0318 VA May 3 950,186 340,260 881,082 0.0316 0.0305 0.0323 VA May 4 1,027,900 371,481 942,158 0.0342 0.0333 0.0346 VA May 5 1,162,255 425,470 1,047,649 0.0387 0.0381 0.0385 VA May 6 1,245,261 458,944 1,111,770 0.0414 0.0411 0.0408 VA May 7 1,285,665 479,791 1,152,941 0.0428 0.0430 0.0423 VA May 8 1,333,772 496,349 1,194,430 0.0444 0.0445 0.0438 VA May 9 1,361,141 508,109 1,221,558 0.0453 0.0455 0.0448 VA May 10 1,365,884 510,428 1,226,515 0.0454 0.0457 0.0450 VA May 11 1,371,925 511,465 1,227,741 0.0456 0.0458 0.0451 VA May 12 1,371,310 512,607 1,233,486 0.0456 0.0459 0.0453 VA May 13 1,370,472 514,400 1,242,210 0.0456 0.0461 0.0456 VA May 14 1,364,316 509,992 1,242,288 0.0454 0.0457 0.0456 VA May 15 1,369,912 514,563 1,250,824 0.0456 0.0461 0.0459 VA May 16 1,370,996 514,114 1,249,905 0.0456 0.0461 0.0459 VA May 17 1,378,307 514,779 1,251,148 0.0459 0.0461 0.0459 VA May 18 1,366,028 510,451 1,232,663 0.0454 0.0458 0.0453 VA May 19 1,378,988 517,473 1,242,266 0.0459 0.0464 0.0456 VA May 20 1,380,676 521,775 1,245,211 0.0459 0.0468 0.0457 VA May 21 1,309,293 493,845 1,183,239 0.0436 0.0443 0.0434 VA May 22 1,218,862 452,909 1,110,801 0.0405 0.0406 0.0408 VA May 23 1,147,769 421,967 1,048,606 0.0382 0.0378 0.0385 VA Jun 0 1,397,495 443,092 1,235,263 0.0346 0.0334 0.0341 VA Jun 1 1,327,255 410,390 1,162,803 0.0328 0.0309 0.0321 VA Jun 2 1,278,550 386,745 1,114,453 0.0316 0.0291 0.0308 VA Jun 3 1,271,890 382,365 1,108,061 0.0315 0.0288 0.0306 VA Jun 4 1,310,627 397,290 1,146,548 0.0324 0.0299 0.0317 VA Jun 5 1,398,242 435,155 1,228,045 0.0346 0.0328 0.0339 VA Jun 6 1,495,866 471,389 1,306,937 0.0370 0.0355 0.0361 VA Jun 7 1,600,863 513,334 1,404,233 0.0396 0.0387 0.0388 VA Jun 8 1,700,518 554,536 1,496,298 0.0421 0.0418 0.0413 VA Jun 9 1,790,807 591,290 1,586,098 0.0443 0.0445 0.0438 VA Jun 10 1,848,522 614,171 1,656,220 0.0457 0.0463 0.0457 VA Jun 11 1,887,068 631,219 1,710,038 0.0467 0.0476 0.0472 VA Jun 12 1,906,968 641,883 1,749,832 0.0472 0.0484 0.0483 VA Jun 13 1,923,519 648,826 1,770,567 0.0476 0.0489 0.0489

D-46Atmospheric Sciences Group 

### Appendix D Actual 2002 State Level Monthly-Diurnal Profiles

CEM-Based Distribution Alpine Geophysics

SO2 Mass NOx Mass Heat Input State Month Hour [lbs] [lbs] [MMBtu] SO2 Ratio NOx Ratio Heat Input Actual Reported Values [2002] Calculated Ratios

VA Jun 14 1,927,468 651,916 1,778,766 0.0477 0.0491 0.0491 VA Jun 15 1,931,654 656,225 1,783,908 0.0478 0.0494 0.0493 VA Jun 16 1,925,274 656,042 1,781,177 0.0476 0.0494 0.0492 VA Jun 17 1,910,579 651,675 1,754,851 0.0473 0.0491 0.0485 VA Jun 18 1,880,003 639,257 1,708,902 0.0465 0.0482 0.0472 VA Jun 19 1,867,546 629,573 1,676,621 0.0462 0.0474 0.0463 VA Jun 20 1,853,464 625,447 1,654,206 0.0458 0.0471 0.0457 VA Jun 21 1,784,928 596,774 1,570,992 0.0441 0.0450 0.0434 VA Jun 22 1,674,345 547,840 1,465,449 0.0414 0.0413 0.0405 VA Jun 23 1,540,774 496,982 1,357,686 0.0381 0.0374 0.0375 VA Jul 0 1,738,779 538,400 1,560,424 0.0372 0.0359 0.0359 VA Jul 1 1,625,367 498,365 1,459,915 0.0348 0.0332 0.0336 VA Jul 2 1,551,236 468,148 1,386,096 0.0332 0.0312 0.0319 VA Jul 3 1,538,408 459,996 1,372,485 0.0329 0.0306 0.0316 VA Jul 4 1,576,187 474,633 1,412,899 0.0337 0.0316 0.0325 VA Jul 5 1,639,540 503,238 1,481,939 0.0351 0.0335 0.0341 VA Jul 6 1,693,447 523,681 1,528,950 0.0362 0.0349 0.0352 VA Jul 7 1,804,205 564,995 1,625,548 0.0386 0.0376 0.0374 VA Jul 8 1,921,147 614,906 1,740,732 0.0411 0.0410 0.0401 VA Jul 9 2,047,059 662,993 1,870,471 0.0438 0.0442 0.0430 VA Jul 10 2,113,607 692,843 1,969,526 0.0452 0.0462 0.0453 VA Jul 11 2,156,850 710,646 2,034,113 0.0461 0.0473 0.0468 VA Jul 12 2,169,969 717,075 2,085,421 0.0464 0.0478 0.0480 VA Jul 13 2,184,131 727,002 2,112,606 0.0467 0.0484 0.0486 VA Jul 14 2,175,525 725,200 2,114,597 0.0465 0.0483 0.0487 VA Jul 15 2,174,896 722,663 2,118,194 0.0465 0.0481 0.0487 VA Jul 16 2,166,576 721,456 2,117,406 0.0464 0.0481 0.0487 VA Jul 17 2,153,812 713,979 2,093,281 0.0461 0.0476 0.0482 VA Jul 18 2,127,855 699,628 2,034,501 0.0455 0.0466 0.0468 VA Jul 19 2,118,827 691,020 2,000,297 0.0453 0.0460 0.0460 VA Jul 20 2,119,353 690,686 1,973,226 0.0453 0.0460 0.0454 VA Jul 21 2,068,277 667,743 1,883,303 0.0442 0.0445 0.0433 VA Jul 22 1,985,229 629,328 1,783,692 0.0425 0.0419 0.0411 VA Jul 23 1,892,348 591,962 1,690,742 0.0405 0.0394 0.0389 VA Aug 0 1,869,122 566,252 1,611,217 0.0383 0.0366 0.0368 VA Aug 1 1,770,023 530,040 1,525,329 0.0363 0.0343 0.0348 VA Aug 2 1,691,266 500,687 1,455,173 0.0346 0.0324 0.0332 VA Aug 3 1,675,446 495,600 1,440,022 0.0343 0.0320 0.0329 VA Aug 4 1,709,086 504,668 1,474,981 0.0350 0.0326 0.0337 VA Aug 5 1,811,968 548,687 1,565,972 0.0371 0.0355 0.0358 VA Aug 6 1,864,223 570,743 1,610,359 0.0382 0.0369 0.0368 VA Aug 7 1,927,147 597,885 1,667,208 0.0395 0.0386 0.0381 VA Aug 8 2,026,347 640,451 1,762,032 0.0415 0.0414 0.0402 VA Aug 9 2,132,365 683,465 1,882,225 0.0437 0.0442 0.0430 VA Aug 10 2,189,968 708,981 1,970,167 0.0449 0.0458 0.0450 VA Aug 11 2,214,024 722,887 2,038,314 0.0453 0.0467 0.0465 VA Aug 12 2,228,353 729,285 2,087,813 0.0456 0.0471 0.0477 VA Aug 13 2,239,713 735,915 2,114,598 0.0459 0.0476 0.0483 VA Aug 14 2,233,013 735,928 2,118,959 0.0457 0.0476 0.0484 VA Aug 15 2,240,896 741,005 2,127,267 0.0459 0.0479 0.0486 VA Aug 16 2,232,515 735,891 2,112,344 0.0457 0.0476 0.0482 VA Aug 17 2,219,245 728,152 2,083,159 0.0455 0.0471 0.0476 VA Aug 18 2,179,915 709,548 2,013,656 0.0446 0.0459 0.0460

D-47Atmospheric Sciences Group 

### Appendix D Actual 2002 State Level Monthly-Diurnal Profiles

CEM-Based Distribution Alpine Geophysics

SO2 Mass NOx Mass Heat Input State Month Hour [lbs] [lbs] [MMBtu] SO2 Ratio NOx Ratio Heat Input Actual Reported Values [2002] Calculated Ratios

VA Aug 19 2,176,270 705,356 1,980,929 0.0446 0.0456 0.0452 VA Aug 20 2,149,798 695,186 1,924,909 0.0440 0.0449 0.0439 VA Aug 21 2,089,053 663,648 1,820,277 0.0428 0.0429 0.0416 VA Aug 22 2,009,321 625,344 1,739,811 0.0412 0.0404 0.0397 VA Aug 23 1,945,406 597,840 1,675,872 0.0398 0.0386 0.0383 VA Sep 0 1,441,293 453,438 1,191,408 0.0374 0.0356 0.0368 VA Sep 1 1,373,736 430,714 1,140,404 0.0356 0.0338 0.0352 VA Sep 2 1,331,167 413,971 1,102,235 0.0345 0.0325 0.0340 VA Sep 3 1,333,267 413,374 1,102,619 0.0346 0.0325 0.0340 VA Sep 4 1,389,343 431,321 1,145,949 0.0360 0.0339 0.0354 VA Sep 5 1,494,999 480,393 1,237,255 0.0388 0.0377 0.0382 VA Sep 6 1,529,036 498,769 1,269,575 0.0396 0.0392 0.0392 VA Sep 7 1,560,168 514,607 1,301,916 0.0404 0.0404 0.0402 VA Sep 8 1,611,696 533,108 1,347,058 0.0418 0.0419 0.0416 VA Sep 9 1,674,599 559,003 1,401,255 0.0434 0.0439 0.0433 VA Sep 10 1,701,371 572,026 1,432,931 0.0441 0.0449 0.0442 VA Sep 11 1,724,516 582,023 1,456,658 0.0447 0.0457 0.0450 VA Sep 12 1,734,545 588,564 1,475,368 0.0450 0.0462 0.0455 VA Sep 13 1,746,074 596,034 1,493,022 0.0453 0.0468 0.0461 VA Sep 14 1,745,378 595,458 1,499,485 0.0452 0.0467 0.0463 VA Sep 15 1,760,129 600,202 1,512,952 0.0456 0.0471 0.0467 VA Sep 16 1,750,973 597,119 1,505,446 0.0454 0.0469 0.0465 VA Sep 17 1,739,990 590,786 1,485,986 0.0451 0.0464 0.0459 VA Sep 18 1,733,578 585,300 1,466,840 0.0449 0.0460 0.0453 VA Sep 19 1,748,668 592,387 1,472,470 0.0453 0.0465 0.0455 VA Sep 20 1,715,018 577,989 1,438,203 0.0445 0.0454 0.0444 VA Sep 21 1,645,660 547,575 1,369,655 0.0427 0.0430 0.0423 VA Sep 22 1,581,120 508,940 1,303,840 0.0410 0.0400 0.0403 VA Sep 23 1,509,011 474,525 1,240,731 0.0391 0.0373 0.0383 VA Oct 0 1,221,781 405,730 1,026,446 0.0361 0.0342 0.0360 VA Oct 1 1,166,433 387,319 990,460 0.0344 0.0327 0.0347 VA Oct 2 1,140,794 378,566 972,622 0.0337 0.0319 0.0341 VA Oct 3 1,160,122 384,134 985,395 0.0343 0.0324 0.0345 VA Oct 4 1,242,765 415,598 1,043,253 0.0367 0.0351 0.0366 VA Oct 5 1,356,444 468,870 1,134,250 0.0400 0.0396 0.0397 VA Oct 6 1,415,398 497,074 1,180,074 0.0418 0.0419 0.0414 VA Oct 7 1,442,788 511,947 1,202,382 0.0426 0.0432 0.0421 VA Oct 8 1,464,098 519,804 1,221,570 0.0432 0.0439 0.0428 VA Oct 9 1,484,481 527,100 1,236,826 0.0438 0.0445 0.0433 VA Oct 10 1,493,670 529,323 1,257,436 0.0441 0.0447 0.0441 VA Oct 11 1,500,217 533,391 1,272,612 0.0443 0.0450 0.0446 VA Oct 12 1,506,866 535,891 1,283,639 0.0445 0.0452 0.0450 VA Oct 13 1,503,493 534,275 1,278,132 0.0444 0.0451 0.0448 VA Oct 14 1,489,453 530,463 1,269,255 0.0440 0.0448 0.0445 VA Oct 15 1,504,898 533,922 1,276,238 0.0444 0.0451 0.0447 VA Oct 16 1,505,924 534,017 1,280,487 0.0445 0.0451 0.0449 VA Oct 17 1,534,643 545,454 1,297,310 0.0453 0.0460 0.0455 VA Oct 18 1,547,227 551,891 1,307,433 0.0457 0.0466 0.0458 VA Oct 19 1,544,313 551,759 1,300,798 0.0456 0.0466 0.0456 VA Oct 20 1,517,573 541,240 1,270,167 0.0448 0.0457 0.0445 VA Oct 21 1,456,750 517,452 1,214,843 0.0430 0.0437 0.0426 VA Oct 22 1,371,855 474,149 1,145,336 0.0405 0.0400 0.0401 VA Oct 23 1,298,679 440,807 1,090,117 0.0383 0.0372 0.0382

D-48Atmospheric Sciences Group 

### Appendix D Actual 2002 State Level Monthly-Diurnal Profiles

CEM-Based Distribution Alpine Geophysics

SO2 Mass NOx Mass Heat Input State Month Hour [lbs] [lbs] [MMBtu] SO2 Ratio NOx Ratio Heat Input Actual Reported Values [2002] Calculated Ratios

VA Nov 0 1,346,748 459,200 1,150,618 0.0380 0.0370 0.0385 VA Nov 1 1,284,143 434,306 1,101,450 0.0362 0.0350 0.0369 VA Nov 2 1,265,761 425,988 1,084,782 0.0357 0.0343 0.0363 VA Nov 3 1,288,920 432,073 1,100,391 0.0363 0.0348 0.0368 VA Nov 4 1,316,994 441,875 1,119,993 0.0371 0.0356 0.0375 VA Nov 5 1,403,047 481,014 1,188,526 0.0396 0.0387 0.0398 VA Nov 6 1,488,053 522,859 1,254,477 0.0419 0.0421 0.0420 VA Nov 7 1,532,338 546,440 1,289,619 0.0432 0.0440 0.0432 VA Nov 8 1,545,741 552,814 1,299,845 0.0436 0.0445 0.0435 VA Nov 9 1,564,025 557,509 1,310,789 0.0441 0.0449 0.0439 VA Nov 10 1,561,776 553,622 1,308,086 0.0440 0.0446 0.0438 VA Nov 11 1,547,040 546,267 1,289,361 0.0436 0.0440 0.0431 VA Nov 12 1,529,504 537,425 1,273,837 0.0431 0.0433 0.0426 VA Nov 13 1,504,168 525,938 1,258,230 0.0424 0.0423 0.0421 VA Nov 14 1,475,387 513,798 1,237,805 0.0416 0.0414 0.0414 VA Nov 15 1,470,236 510,335 1,232,782 0.0414 0.0411 0.0412 VA Nov 16 1,502,506 527,752 1,259,292 0.0424 0.0425 0.0421 VA Nov 17 1,579,638 563,577 1,327,338 0.0445 0.0454 0.0444 VA Nov 18 1,608,098 580,411 1,350,672 0.0453 0.0467 0.0452 VA Nov 19 1,605,564 576,425 1,346,058 0.0453 0.0464 0.0450 VA Nov 20 1,585,664 565,149 1,330,345 0.0447 0.0455 0.0445 VA Nov 21 1,553,960 551,946 1,304,971 0.0438 0.0444 0.0437 VA Nov 22 1,486,684 523,280 1,255,853 0.0419 0.0421 0.0420 VA Nov 23 1,427,128 493,496 1,211,354 0.0402 0.0397 0.0405 VA Dec 0 1,752,992 596,011 1,430,870 0.0391 0.0385 0.0391 VA Dec 1 1,660,775 560,462 1,364,181 0.0370 0.0362 0.0373 VA Dec 2 1,630,683 546,098 1,343,121 0.0364 0.0353 0.0367 VA Dec 3 1,634,996 547,799 1,345,334 0.0365 0.0354 0.0368 VA Dec 4 1,672,277 561,026 1,369,551 0.0373 0.0362 0.0374 VA Dec 5 1,772,406 599,408 1,442,270 0.0395 0.0387 0.0394 VA Dec 6 1,879,874 642,755 1,527,259 0.0419 0.0415 0.0417 VA Dec 7 1,939,570 673,122 1,587,201 0.0433 0.0435 0.0434 VA Dec 8 1,959,012 686,691 1,608,093 0.0437 0.0444 0.0440 VA Dec 9 1,959,083 686,457 1,601,157 0.0437 0.0444 0.0438 VA Dec 10 1,944,859 677,174 1,588,688 0.0434 0.0438 0.0434 VA Dec 11 1,923,095 666,093 1,560,100 0.0429 0.0430 0.0426 VA Dec 12 1,894,389 652,835 1,534,593 0.0422 0.0422 0.0419 VA Dec 13 1,877,733 644,574 1,516,367 0.0419 0.0416 0.0414 VA Dec 14 1,854,241 632,723 1,496,169 0.0414 0.0409 0.0409 VA Dec 15 1,838,390 628,026 1,488,006 0.0410 0.0406 0.0407 VA Dec 16 1,884,334 647,311 1,531,248 0.0420 0.0418 0.0419 VA Dec 17 1,995,799 703,152 1,639,545 0.0445 0.0454 0.0448 VA Dec 18 2,008,396 712,884 1,651,185 0.0448 0.0461 0.0451 VA Dec 19 2,013,772 712,139 1,648,060 0.0449 0.0460 0.0450 VA Dec 20 2,005,900 709,037 1,637,546 0.0447 0.0458 0.0448 VA Dec 21 1,986,146 698,568 1,620,807 0.0443 0.0451 0.0443 VA Dec 22 1,912,307 663,003 1,556,698 0.0426 0.0428 0.0426 VA Dec 23 1,838,374 629,883 1,495,088 0.0410 0.0407 0.0409 WV Jan 0 3,586,286 1,489,559 2,975,721 0.0370 0.0354 0.0376 WV Jan 1 3,506,867 1,439,034 2,901,910 0.0362 0.0342 0.0367 WV Jan 2 3,468,517 1,422,624 2,875,801 0.0358 0.0338 0.0364 WV Jan 3 3,456,105 1,415,775 2,856,734 0.0357 0.0337 0.0361 WV Jan 4 3,502,022 1,434,796 2,891,945 0.0361 0.0341 0.0366

D-49Atmospheric Sciences Group 

### Appendix D Actual 2002 State Level Monthly-Diurnal Profiles

CEM-Based Distribution Alpine Geophysics

SO2 Mass NOx Mass Heat Input State Month Hour [lbs] [lbs] [MMBtu] SO2 Ratio NOx Ratio Heat Input Actual Reported Values [2002] Calculated Ratios

WV Jan 5 3,645,809 1,500,327 2,992,132 0.0376 0.0357 0.0378 WV Jan 6 3,977,151 1,680,028 3,228,492 0.0410 0.0400 0.0408 WV Jan 7 4,251,989 1,855,463 3,430,492 0.0439 0.0441 0.0434 WV Jan 8 4,343,136 1,912,455 3,491,370 0.0448 0.0455 0.0441 WV Jan 9 4,389,086 1,921,035 3,505,236 0.0453 0.0457 0.0443 WV Jan 10 4,387,288 1,926,571 3,506,307 0.0453 0.0458 0.0443 WV Jan 11 4,320,628 1,903,047 3,476,671 0.0446 0.0453 0.0440 WV Jan 12 4,272,325 1,877,152 3,446,545 0.0441 0.0446 0.0436 WV Jan 13 4,221,505 1,850,243 3,412,924 0.0435 0.0440 0.0432 WV Jan 14 4,148,881 1,813,653 3,372,611 0.0428 0.0431 0.0426 WV Jan 15 4,095,634 1,785,330 3,341,710 0.0422 0.0425 0.0423 WV Jan 16 4,105,341 1,806,571 3,373,654 0.0423 0.0430 0.0427 WV Jan 17 4,229,481 1,883,758 3,468,947 0.0436 0.0448 0.0439 WV Jan 18 4,370,183 1,989,261 3,580,114 0.0451 0.0473 0.0453 WV Jan 19 4,362,026 1,974,348 3,566,426 0.0450 0.0470 0.0451 WV Jan 20 4,346,352 1,956,219 3,543,898 0.0448 0.0465 0.0448 WV Jan 21 4,244,400 1,891,439 3,463,041 0.0438 0.0450 0.0438 WV Jan 22 3,991,991 1,741,388 3,298,390 0.0412 0.0414 0.0417 WV Jan 23 3,721,790 1,574,365 3,091,779 0.0384 0.0374 0.0391 WV Feb 0 3,083,613 1,471,681 2,904,706 0.0376 0.0366 0.0385 WV Feb 1 2,996,658 1,415,433 2,826,998 0.0365 0.0352 0.0375 WV Feb 2 2,971,783 1,396,334 2,800,408 0.0362 0.0347 0.0372 WV Feb 3 2,969,671 1,393,637 2,789,493 0.0362 0.0346 0.0370 WV Feb 4 3,011,920 1,416,134 2,824,109 0.0367 0.0352 0.0375 WV Feb 5 3,169,650 1,499,630 2,941,708 0.0386 0.0373 0.0390 WV Feb 6 3,437,383 1,658,982 3,134,188 0.0419 0.0412 0.0416 WV Feb 7 3,590,158 1,781,802 3,264,536 0.0437 0.0443 0.0433 WV Feb 8 3,638,972 1,819,065 3,304,548 0.0443 0.0452 0.0438 WV Feb 9 3,662,841 1,826,984 3,305,017 0.0446 0.0454 0.0439 WV Feb 10 3,666,484 1,830,416 3,314,530 0.0446 0.0455 0.0440 WV Feb 11 3,614,578 1,797,916 3,279,293 0.0440 0.0447 0.0435 WV Feb 12 3,551,743 1,769,981 3,245,013 0.0433 0.0440 0.0431 WV Feb 13 3,512,984 1,741,132 3,209,913 0.0428 0.0433 0.0426 WV Feb 14 3,463,896 1,701,745 3,168,050 0.0422 0.0423 0.0420 WV Feb 15 3,405,978 1,672,774 3,134,443 0.0415 0.0416 0.0416 WV Feb 16 3,424,571 1,683,824 3,153,904 0.0417 0.0418 0.0418 WV Feb 17 3,504,989 1,720,579 3,208,870 0.0427 0.0428 0.0426 WV Feb 18 3,641,381 1,821,793 3,323,895 0.0443 0.0453 0.0441 WV Feb 19 3,697,271 1,853,339 3,351,977 0.0450 0.0461 0.0445 WV Feb 20 3,691,280 1,845,789 3,343,727 0.0449 0.0459 0.0444 WV Feb 21 3,637,796 1,810,063 3,298,193 0.0443 0.0450 0.0438 WV Feb 22 3,507,924 1,724,596 3,199,695 0.0427 0.0429 0.0425 WV Feb 23 3,266,332 1,582,764 3,036,081 0.0398 0.0393 0.0403 WV Mar 0 2,956,020 1,403,742 2,803,600 0.0368 0.0356 0.0376 WV Mar 1 2,849,280 1,343,894 2,709,083 0.0355 0.0341 0.0363 WV Mar 2 2,796,725 1,326,060 2,681,699 0.0348 0.0336 0.0359 WV Mar 3 2,788,370 1,318,662 2,669,770 0.0347 0.0334 0.0358 WV Mar 4 2,845,587 1,343,066 2,714,269 0.0355 0.0340 0.0364 WV Mar 5 3,023,839 1,436,532 2,855,425 0.0377 0.0364 0.0382 WV Mar 6 3,303,618 1,588,719 3,066,327 0.0412 0.0403 0.0411 WV Mar 7 3,469,616 1,694,879 3,201,030 0.0432 0.0430 0.0429 WV Mar 8 3,550,028 1,755,713 3,274,699 0.0442 0.0445 0.0439 WV Mar 9 3,613,065 1,799,740 3,322,001 0.0450 0.0456 0.0445

D-50Atmospheric Sciences Group 

### Appendix D Actual 2002 State Level Monthly-Diurnal Profiles

CEM-Based Distribution Alpine Geophysics

SO2 Mass NOx Mass Heat Input State Month Hour [lbs] [lbs] [MMBtu] SO2 Ratio NOx Ratio Heat Input Actual Reported Values [2002] Calculated Ratios

WV Mar 10 3,645,075 1,823,212 3,347,426 0.0454 0.0462 0.0448 WV Mar 11 3,638,241 1,826,686 3,338,051 0.0453 0.0463 0.0447 WV Mar 12 3,597,759 1,798,797 3,303,456 0.0448 0.0456 0.0442 WV Mar 13 3,537,428 1,759,681 3,263,295 0.0441 0.0446 0.0437 WV Mar 14 3,467,033 1,718,721 3,211,202 0.0432 0.0436 0.0430 WV Mar 15 3,401,963 1,684,003 3,167,015 0.0424 0.0427 0.0424 WV Mar 16 3,412,637 1,694,361 3,168,540 0.0425 0.0430 0.0424 WV Mar 17 3,455,603 1,720,419 3,204,943 0.0431 0.0436 0.0429 WV Mar 18 3,581,695 1,787,495 3,295,887 0.0446 0.0453 0.0441 WV Mar 19 3,690,924 1,873,467 3,387,225 0.0460 0.0475 0.0454 WV Mar 20 3,663,641 1,851,403 3,357,474 0.0456 0.0469 0.0450 WV Mar 21 3,566,306 1,788,110 3,284,756 0.0444 0.0453 0.0440 WV Mar 22 3,338,283 1,639,235 3,118,799 0.0416 0.0416 0.0418 WV Mar 23 3,072,820 1,472,966 2,909,247 0.0383 0.0373 0.0390 WV Apr 0 2,516,974 1,212,084 2,347,023 0.0341 0.0333 0.0357 WV Apr 1 2,431,013 1,171,024 2,278,118 0.0330 0.0322 0.0346 WV Apr 2 2,409,717 1,163,540 2,265,763 0.0327 0.0320 0.0345 WV Apr 3 2,428,017 1,162,503 2,268,626 0.0329 0.0320 0.0345 WV Apr 4 2,527,131 1,198,798 2,337,792 0.0343 0.0330 0.0355 WV Apr 5 2,799,484 1,334,513 2,534,850 0.0379 0.0367 0.0385 WV Apr 6 3,057,971 1,486,151 2,713,532 0.0415 0.0409 0.0413 WV Apr 7 3,205,894 1,584,380 2,827,670 0.0435 0.0436 0.0430 WV Apr 8 3,300,511 1,645,098 2,910,730 0.0447 0.0453 0.0443 WV Apr 9 3,371,940 1,689,883 2,966,807 0.0457 0.0465 0.0451 WV Apr 10 3,407,597 1,711,419 2,989,164 0.0462 0.0471 0.0454 WV Apr 11 3,391,609 1,708,707 2,984,424 0.0460 0.0470 0.0454 WV Apr 12 3,393,566 1,707,990 2,980,706 0.0460 0.0470 0.0453 WV Apr 13 3,381,808 1,705,171 2,966,171 0.0458 0.0469 0.0451 WV Apr 14 3,346,414 1,681,908 2,943,156 0.0454 0.0463 0.0448 WV Apr 15 3,320,437 1,669,943 2,930,846 0.0450 0.0459 0.0446 WV Apr 16 3,275,077 1,634,232 2,894,929 0.0444 0.0450 0.0440 WV Apr 17 3,259,107 1,612,599 2,877,690 0.0442 0.0444 0.0438 WV Apr 18 3,283,364 1,626,920 2,896,021 0.0445 0.0448 0.0440 WV Apr 19 3,374,748 1,679,820 2,960,309 0.0457 0.0462 0.0450 WV Apr 20 3,395,888 1,686,318 2,971,513 0.0460 0.0464 0.0452 WV Apr 21 3,223,879 1,569,046 2,830,404 0.0437 0.0432 0.0430 WV Apr 22 2,950,082 1,417,057 2,626,803 0.0400 0.0390 0.0399 WV Apr 23 2,719,084 1,295,703 2,465,436 0.0369 0.0356 0.0375 WV May 0 2,707,290 1,020,566 2,559,576 0.0348 0.0344 0.0359 WV May 1 2,628,441 981,055 2,496,649 0.0338 0.0330 0.0350 WV May 2 2,587,332 968,612 2,461,722 0.0333 0.0326 0.0345 WV May 3 2,617,594 974,162 2,480,275 0.0337 0.0328 0.0347 WV May 4 2,750,964 1,031,270 2,582,779 0.0354 0.0347 0.0362 WV May 5 2,988,524 1,130,152 2,756,540 0.0384 0.0381 0.0386 WV May 6 3,208,377 1,224,083 2,921,207 0.0413 0.0412 0.0409 WV May 7 3,338,313 1,294,564 3,033,967 0.0429 0.0436 0.0425 WV May 8 3,457,856 1,335,852 3,123,813 0.0445 0.0450 0.0438 WV May 9 3,536,570 1,355,206 3,186,053 0.0455 0.0456 0.0446 WV May 10 3,554,063 1,368,494 3,217,968 0.0457 0.0461 0.0451 WV May 11 3,535,694 1,366,110 3,211,219 0.0455 0.0460 0.0450 WV May 12 3,524,564 1,368,190 3,212,666 0.0453 0.0461 0.0450 WV May 13 3,498,012 1,345,225 3,177,331 0.0450 0.0453 0.0445 WV May 14 3,510,508 1,343,687 3,182,755 0.0452 0.0452 0.0446

D-51Atmospheric Sciences Group 

### Appendix D Actual 2002 State Level Monthly-Diurnal Profiles

CEM-Based Distribution Alpine Geophysics

SO2 Mass NOx Mass Heat Input State Month Hour [lbs] [lbs] [MMBtu] SO2 Ratio NOx Ratio Heat Input Actual Reported Values [2002] Calculated Ratios

WV May 15 3,525,475 1,352,447 3,194,660 0.0453 0.0455 0.0447 WV May 16 3,513,171 1,347,149 3,192,495 0.0452 0.0454 0.0447 WV May 17 3,479,267 1,337,554 3,171,058 0.0447 0.0450 0.0444 WV May 18 3,454,200 1,327,411 3,155,351 0.0444 0.0447 0.0442 WV May 19 3,484,602 1,333,989 3,175,696 0.0448 0.0449 0.0445 WV May 20 3,520,461 1,351,418 3,203,979 0.0453 0.0455 0.0449 WV May 21 3,372,448 1,282,601 3,095,328 0.0434 0.0432 0.0434 WV May 22 3,102,337 1,176,136 2,894,819 0.0399 0.0396 0.0405 WV May 23 2,854,686 1,084,922 2,702,630 0.0367 0.0365 0.0379 WV Jun 0 2,843,469 1,152,973 2,753,778 0.0349 0.0346 0.0360 WV Jun 1 2,726,373 1,097,574 2,644,370 0.0335 0.0330 0.0346 WV Jun 2 2,618,664 1,060,356 2,559,837 0.0322 0.0319 0.0335 WV Jun 3 2,597,860 1,051,368 2,533,191 0.0319 0.0316 0.0331 WV Jun 4 2,650,707 1,077,889 2,586,631 0.0325 0.0324 0.0338 WV Jun 5 2,771,076 1,132,722 2,701,065 0.0340 0.0340 0.0353 WV Jun 6 2,984,091 1,222,075 2,883,981 0.0366 0.0367 0.0377 WV Jun 7 3,229,224 1,322,822 3,084,170 0.0396 0.0397 0.0403 WV Jun 8 3,444,511 1,409,967 3,236,957 0.0423 0.0424 0.0423 WV Jun 9 3,595,116 1,481,520 3,356,516 0.0441 0.0445 0.0439 WV Jun 10 3,701,838 1,522,116 3,437,688 0.0455 0.0457 0.0449 WV Jun 11 3,781,442 1,559,595 3,509,835 0.0464 0.0469 0.0459 WV Jun 12 3,814,628 1,572,730 3,544,776 0.0468 0.0473 0.0463 WV Jun 13 3,809,153 1,569,311 3,547,716 0.0468 0.0472 0.0464 WV Jun 14 3,830,303 1,577,459 3,555,127 0.0470 0.0474 0.0465 WV Jun 15 3,815,668 1,575,585 3,551,631 0.0469 0.0473 0.0464 WV Jun 16 3,837,647 1,579,964 3,551,755 0.0471 0.0475 0.0464 WV Jun 17 3,827,331 1,575,908 3,531,529 0.0470 0.0474 0.0462 WV Jun 18 3,824,669 1,565,305 3,516,672 0.0470 0.0470 0.0460 WV Jun 19 3,801,976 1,544,178 3,485,066 0.0467 0.0464 0.0456 WV Jun 20 3,822,383 1,539,705 3,488,072 0.0469 0.0463 0.0456 WV Jun 21 3,664,460 1,482,015 3,378,299 0.0450 0.0445 0.0442 WV Jun 22 3,386,760 1,371,539 3,154,797 0.0416 0.0412 0.0412 WV Jun 23 3,064,083 1,236,755 2,901,197 0.0376 0.0372 0.0379 WV Jul 0 3,397,815 1,351,534 3,196,171 0.0366 0.0364 0.0375 WV Jul 1 3,252,067 1,299,799 3,091,026 0.0351 0.0350 0.0362 WV Jul 2 3,152,459 1,262,576 3,015,795 0.0340 0.0340 0.0353 WV Jul 3 3,119,567 1,235,049 2,974,803 0.0336 0.0332 0.0349 WV Jul 4 3,158,978 1,252,745 3,002,539 0.0341 0.0337 0.0352 WV Jul 5 3,265,984 1,287,349 3,083,114 0.0352 0.0346 0.0361 WV Jul 6 3,412,627 1,355,566 3,185,911 0.0368 0.0365 0.0373 WV Jul 7 3,645,945 1,461,311 3,383,432 0.0393 0.0393 0.0397 WV Jul 8 3,886,415 1,556,538 3,554,072 0.0419 0.0419 0.0417 WV Jul 9 4,070,545 1,628,778 3,697,547 0.0439 0.0438 0.0433 WV Jul 10 4,174,422 1,678,715 3,794,163 0.0450 0.0452 0.0445 WV Jul 11 4,216,840 1,699,266 3,824,864 0.0455 0.0457 0.0448 WV Jul 12 4,232,083 1,703,997 3,847,949 0.0456 0.0458 0.0451 WV Jul 13 4,263,637 1,717,091 3,878,062 0.0460 0.0462 0.0455 WV Jul 14 4,284,548 1,730,452 3,898,551 0.0462 0.0465 0.0457 WV Jul 15 4,266,411 1,726,522 3,886,680 0.0460 0.0464 0.0456 WV Jul 16 4,310,280 1,737,883 3,907,327 0.0465 0.0467 0.0458 WV Jul 17 4,298,259 1,735,019 3,893,392 0.0464 0.0467 0.0456 WV Jul 18 4,270,704 1,721,917 3,863,670 0.0461 0.0463 0.0453 WV Jul 19 4,206,882 1,698,798 3,807,381 0.0454 0.0457 0.0446

D-52Atmospheric Sciences Group 

### Appendix D Actual 2002 State Level Monthly-Diurnal Profiles

CEM-Based Distribution Alpine Geophysics

SO2 Mass NOx Mass Heat Input State Month Hour [lbs] [lbs] [MMBtu] SO2 Ratio NOx Ratio Heat Input Actual Reported Values [2002] Calculated Ratios

WV Jul 20 4,216,411 1,688,204 3,813,857 0.0455 0.0454 0.0447 WV Jul 21 4,109,330 1,642,771 3,750,329 0.0443 0.0442 0.0440 WV Jul 22 3,903,083 1,561,544 3,595,662 0.0421 0.0420 0.0421 WV Jul 23 3,606,254 1,441,272 3,376,472 0.0389 0.0388 0.0396 WV Aug 0 3,321,408 1,267,632 2,979,735 0.0366 0.0363 0.0372 WV Aug 1 3,224,037 1,227,882 2,906,303 0.0355 0.0352 0.0363 WV Aug 2 3,103,798 1,189,181 2,830,579 0.0342 0.0340 0.0354 WV Aug 3 3,051,056 1,172,137 2,796,757 0.0336 0.0336 0.0349 WV Aug 4 3,109,025 1,198,934 2,839,560 0.0343 0.0343 0.0355 WV Aug 5 3,234,711 1,244,919 2,938,801 0.0356 0.0356 0.0367 WV Aug 6 3,386,692 1,300,705 3,035,359 0.0373 0.0372 0.0379 WV Aug 7 3,619,032 1,373,365 3,196,950 0.0399 0.0393 0.0399 WV Aug 8 3,824,375 1,440,371 3,341,468 0.0421 0.0412 0.0418 WV Aug 9 3,964,546 1,502,325 3,460,676 0.0437 0.0430 0.0432 WV Aug 10 4,066,747 1,556,919 3,560,168 0.0448 0.0446 0.0445 WV Aug 11 4,133,222 1,603,039 3,636,996 0.0455 0.0459 0.0454 WV Aug 12 4,179,451 1,629,659 3,682,605 0.0460 0.0467 0.0460 WV Aug 13 4,172,028 1,631,044 3,676,060 0.0460 0.0467 0.0459 WV Aug 14 4,196,846 1,633,652 3,676,364 0.0462 0.0468 0.0459 WV Aug 15 4,220,257 1,640,023 3,673,741 0.0465 0.0470 0.0459 WV Aug 16 4,232,450 1,645,270 3,673,424 0.0466 0.0471 0.0459 WV Aug 17 4,197,859 1,626,913 3,644,753 0.0462 0.0466 0.0455 WV Aug 18 4,141,932 1,602,043 3,596,560 0.0456 0.0459 0.0449 WV Aug 19 4,134,746 1,594,540 3,571,720 0.0456 0.0457 0.0446 WV Aug 20 4,130,351 1,592,291 3,563,911 0.0455 0.0456 0.0445 WV Aug 21 3,947,237 1,514,010 3,435,941 0.0435 0.0433 0.0429 WV Aug 22 3,726,104 1,424,841 3,255,475 0.0411 0.0408 0.0407 WV Aug 23 3,449,532 1,316,101 3,051,240 0.0380 0.0377 0.0381 WV Sep 0 2,641,922 1,070,453 2,419,773 0.0348 0.0343 0.0360 WV Sep 1 2,558,375 1,038,903 2,359,312 0.0337 0.0333 0.0351 WV Sep 2 2,525,429 1,021,458 2,318,669 0.0332 0.0327 0.0345 WV Sep 3 2,494,438 1,014,077 2,312,561 0.0328 0.0325 0.0344 WV Sep 4 2,593,714 1,052,523 2,391,523 0.0341 0.0337 0.0356 WV Sep 5 2,844,069 1,151,502 2,555,935 0.0374 0.0369 0.0380 WV Sep 6 3,000,826 1,220,351 2,652,239 0.0395 0.0391 0.0395 WV Sep 7 3,099,292 1,263,999 2,726,877 0.0408 0.0405 0.0406 WV Sep 8 3,231,758 1,305,316 2,807,726 0.0425 0.0418 0.0418 WV Sep 9 3,326,189 1,353,136 2,888,422 0.0438 0.0433 0.0430 WV Sep 10 3,395,390 1,396,807 2,948,903 0.0447 0.0447 0.0439 WV Sep 11 3,461,605 1,424,919 3,005,414 0.0456 0.0456 0.0447 WV Sep 12 3,479,595 1,446,803 3,034,151 0.0458 0.0463 0.0452 WV Sep 13 3,511,704 1,462,581 3,063,096 0.0462 0.0468 0.0456 WV Sep 14 3,506,242 1,468,555 3,073,539 0.0461 0.0470 0.0457 WV Sep 15 3,500,360 1,476,395 3,080,994 0.0461 0.0473 0.0459 WV Sep 16 3,524,947 1,488,834 3,098,448 0.0464 0.0477 0.0461 WV Sep 17 3,498,796 1,464,378 3,071,309 0.0460 0.0469 0.0457 WV Sep 18 3,502,274 1,446,004 3,054,264 0.0461 0.0463 0.0455 WV Sep 19 3,532,304 1,451,761 3,067,918 0.0465 0.0465 0.0457 WV Sep 20 3,487,174 1,426,238 3,027,826 0.0459 0.0457 0.0451 WV Sep 21 3,315,771 1,350,538 2,900,224 0.0436 0.0433 0.0432 WV Sep 22 3,104,899 1,265,740 2,753,717 0.0409 0.0405 0.0410 WV Sep 23 2,844,727 1,159,438 2,572,096 0.0374 0.0371 0.0383 WV Oct 0 3,026,493 1,406,807 2,717,153 0.0357 0.0343 0.0368

D-53Atmospheric Sciences Group 

### Appendix D Actual 2002 State Level Monthly-Diurnal Profiles

CEM-Based Distribution Alpine Geophysics

SO2 Mass NOx Mass Heat Input State Month Hour [lbs] [lbs] [MMBtu] SO2 Ratio NOx Ratio Heat Input Actual Reported Values [2002] Calculated Ratios

WV Oct 1 2,928,313 1,362,009 2,645,418 0.0345 0.0332 0.0358 WV Oct 2 2,887,608 1,346,647 2,616,803 0.0341 0.0328 0.0354 WV Oct 3 2,899,205 1,346,799 2,623,332 0.0342 0.0328 0.0355 WV Oct 4 3,028,647 1,402,439 2,719,299 0.0357 0.0342 0.0368 WV Oct 5 3,313,783 1,552,023 2,912,582 0.0391 0.0379 0.0394 WV Oct 6 3,542,744 1,690,580 3,076,942 0.0418 0.0412 0.0417 WV Oct 7 3,665,917 1,759,230 3,168,877 0.0432 0.0429 0.0429 WV Oct 8 3,751,272 1,825,970 3,226,123 0.0442 0.0445 0.0437 WV Oct 9 3,805,809 1,846,873 3,244,787 0.0449 0.0450 0.0439 WV Oct 10 3,813,050 1,856,289 3,258,150 0.0450 0.0453 0.0441 WV Oct 11 3,839,575 1,862,838 3,272,732 0.0453 0.0454 0.0443 WV Oct 12 3,823,911 1,866,040 3,275,905 0.0451 0.0455 0.0444 WV Oct 13 3,780,486 1,857,643 3,259,377 0.0446 0.0453 0.0441 WV Oct 14 3,746,790 1,831,179 3,231,209 0.0442 0.0447 0.0438 WV Oct 15 3,727,943 1,828,023 3,227,163 0.0440 0.0446 0.0437 WV Oct 16 3,714,988 1,836,090 3,224,183 0.0438 0.0448 0.0437 WV Oct 17 3,766,728 1,869,558 3,258,145 0.0444 0.0456 0.0441 WV Oct 18 3,868,885 1,944,068 3,329,026 0.0456 0.0474 0.0451 WV Oct 19 3,861,941 1,933,684 3,323,673 0.0456 0.0472 0.0450 WV Oct 20 3,823,490 1,885,927 3,284,109 0.0451 0.0460 0.0445 WV Oct 21 3,631,118 1,768,538 3,154,327 0.0428 0.0431 0.0427 WV Oct 22 3,378,765 1,625,898 2,983,326 0.0399 0.0397 0.0404 WV Oct 23 3,148,807 1,494,091 2,821,278 0.0371 0.0364 0.0382 WV Nov 0 3,117,338 1,470,760 2,731,864 0.0363 0.0352 0.0374 WV Nov 1 3,016,171 1,412,455 2,657,397 0.0351 0.0338 0.0364 WV Nov 2 2,979,990 1,392,134 2,626,885 0.0347 0.0333 0.0360 WV Nov 3 2,989,420 1,396,337 2,632,487 0.0348 0.0334 0.0360 WV Nov 4 3,019,868 1,411,782 2,655,631 0.0352 0.0338 0.0364 WV Nov 5 3,177,773 1,493,500 2,774,932 0.0370 0.0357 0.0380 WV Nov 6 3,495,104 1,683,124 2,987,267 0.0407 0.0403 0.0409 WV Nov 7 3,726,505 1,833,926 3,148,278 0.0434 0.0439 0.0431 WV Nov 8 3,834,074 1,904,575 3,220,382 0.0447 0.0456 0.0441 WV Nov 9 3,865,251 1,914,186 3,236,778 0.0450 0.0458 0.0443 WV Nov 10 3,883,450 1,921,247 3,236,826 0.0452 0.0460 0.0443 WV Nov 11 3,839,198 1,891,371 3,204,364 0.0447 0.0453 0.0439 WV Nov 12 3,778,574 1,843,919 3,161,839 0.0440 0.0441 0.0433 WV Nov 13 3,710,360 1,814,446 3,123,297 0.0432 0.0434 0.0428 WV Nov 14 3,656,231 1,784,789 3,092,715 0.0426 0.0427 0.0424 WV Nov 15 3,629,587 1,773,938 3,084,549 0.0423 0.0424 0.0422 WV Nov 16 3,660,121 1,791,718 3,109,393 0.0426 0.0429 0.0426 WV Nov 17 3,836,771 1,897,202 3,228,241 0.0447 0.0454 0.0442 WV Nov 18 3,952,885 1,979,057 3,314,698 0.0461 0.0474 0.0454 WV Nov 19 3,924,541 1,964,754 3,300,521 0.0457 0.0470 0.0452 WV Nov 20 3,909,736 1,952,816 3,283,265 0.0456 0.0467 0.0450 WV Nov 21 3,832,696 1,902,314 3,230,112 0.0447 0.0455 0.0442 WV Nov 22 3,601,756 1,754,154 3,069,819 0.0420 0.0420 0.0420 WV Nov 23 3,389,068 1,611,143 2,913,834 0.0395 0.0385 0.0399 WV Dec 0 3,404,522 1,601,479 3,011,458 0.0371 0.0360 0.0380 WV Dec 1 3,286,612 1,533,057 2,921,867 0.0358 0.0345 0.0369 WV Dec 2 3,232,262 1,508,155 2,877,148 0.0352 0.0339 0.0363 WV Dec 3 3,210,231 1,505,642 2,868,508 0.0350 0.0338 0.0362 WV Dec 4 3,264,787 1,533,576 2,908,406 0.0355 0.0345 0.0367 WV Dec 5 3,420,375 1,609,406 3,007,631 0.0372 0.0362 0.0380

D-54Atmospheric Sciences Group 

### Appendix D Actual 2002 State Level Monthly-Diurnal Profiles

CEM-Based Distribution Alpine Geophysics

SO2 Mass NOx Mass Heat Input State Month Hour [lbs] [lbs] [MMBtu] SO2 Ratio NOx Ratio Heat Input Actual Reported Values [2002] Calculated Ratios

WV Dec 6 3,697,969 1,783,014 3,198,789 0.0403 0.0401 0.0404 WV Dec 7 3,924,210 1,918,829 3,358,948 0.0427 0.0431 0.0424 WV Dec 8 4,042,205 1,994,642 3,450,461 0.0440 0.0448 0.0436 WV Dec 9 4,111,049 2,035,320 3,500,334 0.0448 0.0458 0.0442 WV Dec 10 4,110,585 2,027,310 3,489,849 0.0448 0.0456 0.0441 WV Dec 11 4,076,404 1,993,840 3,471,311 0.0444 0.0448 0.0438 WV Dec 12 4,046,861 1,954,975 3,438,541 0.0441 0.0439 0.0434 WV Dec 13 4,004,867 1,922,444 3,406,151 0.0436 0.0432 0.0430 WV Dec 14 3,921,172 1,869,324 3,345,903 0.0427 0.0420 0.0422 WV Dec 15 3,855,417 1,834,963 3,315,226 0.0420 0.0413 0.0419 WV Dec 16 3,888,660 1,878,029 3,354,174 0.0423 0.0422 0.0424 WV Dec 17 4,109,097 2,037,631 3,503,434 0.0447 0.0458 0.0442 WV Dec 18 4,209,514 2,117,544 3,578,429 0.0458 0.0476 0.0452 WV Dec 19 4,199,396 2,097,840 3,575,421 0.0457 0.0472 0.0451 WV Dec 20 4,161,050 2,067,815 3,544,693 0.0453 0.0465 0.0448 WV Dec 21 4,115,588 2,029,959 3,509,552 0.0448 0.0456 0.0443 WV Dec 22 3,928,733 1,904,833 3,383,567 0.0428 0.0428 0.0427 WV Dec 23 3,629,250 1,722,821 3,174,446 0.0395 0.0387 0.0401

D-55

### Atmospheric Sciences Group 

## Appendix E Average 2000-2004 State Level Monthly Profiles

CEM-Based Distribution Alpine Geophysics

SO2 Mass NOx Mass Heat Input State Month [lbs] [lbs] [MMBtu] SO2 Ratio NOx Ratio Heat Input AL 01 96,930,269 35,587,650 106,607,722 0.0891 0.0906 0.0841 AL 02 89,299,276 31,712,573 92,320,799 0.0821 0.0807 0.0728 AL 03 97,977,033 34,625,029 99,742,940 0.0901 0.0881 0.0787 AL 04 88,243,177 32,334,269 100,129,509 0.0811 0.0823 0.0790 AL 05 89,962,666 32,627,766 112,967,968 0.0827 0.0830 0.0891 AL 06 87,102,237 31,193,299 111,088,721 0.0801 0.0794 0.0876 AL 07 91,587,444 32,073,978 120,110,609 0.0842 0.0816 0.0947 AL 08 90,517,064 32,282,799 119,715,397 0.0832 0.0822 0.0944 AL 09 86,093,933 30,205,186 108,873,196 0.0792 0.0769 0.0859 AL 10 94,862,824 34,337,900 104,619,520 0.0872 0.0874 0.0825 AL 11 85,540,251 32,415,917 91,045,088 0.0787 0.0825 0.0718 AL 12 89,344,392 33,549,632 100,769,555 0.0822 0.0854 0.0795 FL 01 116,011,253 62,989,958 198,751,048 0.0858 0.0875 0.0831 FL 02 93,958,786 50,831,818 164,949,702 0.0695 0.0706 0.0690 FL 03 111,505,553 60,285,972 196,705,697 0.0824 0.0838 0.0822 FL 04 107,015,438 59,071,792 195,338,204 0.0791 0.0821 0.0817 FL 05 118,589,361 61,811,604 207,803,996 0.0877 0.0859 0.0869 FL 06 116,068,987 59,801,640 202,716,214 0.0858 0.0831 0.0848 FL 07 123,868,749 62,500,169 212,478,437 0.0916 0.0868 0.0888 FL 08 125,384,940 64,572,843 214,637,218 0.0927 0.0897 0.0897 FL 09 113,080,789 59,913,723 206,712,956 0.0836 0.0832 0.0864 FL 10 109,960,828 61,551,310 206,924,170 0.0813 0.0855 0.0865 FL 11 101,781,383 55,861,718 186,984,665 0.0752 0.0776 0.0782 FL 12 115,588,740 60,566,444 197,592,133 0.0854 0.0841 0.0826 GA 01 111,381,833 35,300,170 101,578,866 0.0899 0.1020 0.0843 GA 02 98,896,327 30,678,660 86,718,335 0.0798 0.0887 0.0720 GA 03 106,485,284 33,079,065 92,242,973 0.0859 0.0956 0.0765 GA 04 102,974,144 30,008,861 103,324,610 0.0831 0.0867 0.0857 GA 05 105,293,816 25,969,027 106,952,596 0.0850 0.0751 0.0888 GA 06 102,271,647 24,738,987 106,006,251 0.0825 0.0715 0.0880 GA 07 108,957,317 26,952,614 120,877,914 0.0879 0.0779 0.1003 GA 08 108,752,336 26,639,752 120,190,489 0.0878 0.0770 0.0997 GA 09 97,918,725 23,487,485 104,072,746 0.0790 0.0679 0.0864 GA 10 101,536,528 30,369,446 96,452,757 0.0819 0.0878 0.0800 GA 11 93,759,865 28,223,403 78,439,851 0.0757 0.0816 0.0651 GA 12 101,006,607 30,570,535 88,223,873 0.0815 0.0883 0.0732 KY 01 114,451,110 50,961,629 103,156,727 0.0911 0.1020 0.0862 KY 02 99,582,190 45,260,425 92,691,929 0.0793 0.0906 0.0774 KY 03 106,411,998 49,574,474 102,526,546 0.0847 0.0993 0.0857 KY 04 101,118,302 45,106,138 100,653,753 0.0805 0.0903 0.0841 KY 05 104,021,647 37,580,055 99,546,365 0.0828 0.0752 0.0832 KY 06 105,872,032 34,128,995 97,828,149 0.0843 0.0683 0.0817 KY 07 108,881,756 35,056,185 107,192,042 0.0867 0.0702 0.0896 KY 08 104,798,920 34,486,336 105,469,064 0.0835 0.0690 0.0881 KY 09 100,167,234 31,953,387 96,012,045 0.0798 0.0640 0.0802 KY 10 103,383,830 43,615,561 97,660,979 0.0823 0.0873 0.0816 KY 11 101,028,279 44,613,743 94,343,813 0.0804 0.0893 0.0788 KY 12 106,076,566 47,126,961 99,865,268 0.0845 0.0944 0.0834 MS 01 26,002,429 14,959,002 50,082,518 0.0941 0.0940 0.0871 MS 02 21,206,233 11,880,358 40,471,183 0.0768 0.0747 0.0704 MS 03 25,528,343 13,158,285 47,129,522 0.0924 0.0827 0.0819

Average Values [2000-2004] Calculated Ratios

E-1

### Atmospheric Sciences Group 

## Appendix E Average 2000-2004 State Level Monthly Profiles

CEM-Based Distribution Alpine Geophysics

SO2 Mass NOx Mass Heat Input State Month [lbs] [lbs] [MMBtu] SO2 Ratio NOx Ratio Heat Input

Average Values [2000-2004] Calculated Ratios

MS 04 21,273,756 12,214,212 46,195,711 0.0770 0.0768 0.0803 MS 05 22,125,071 11,792,392 50,436,986 0.0801 0.0741 0.0877 MS 06 20,491,237 12,047,012 48,840,874 0.0742 0.0757 0.0849 MS 07 21,656,323 13,520,807 58,072,028 0.0784 0.0850 0.1010 MS 08 23,098,376 13,834,360 56,814,327 0.0836 0.0870 0.0988 MS 09 20,523,293 12,077,193 46,707,196 0.0743 0.0759 0.0812 MS 10 24,275,175 13,614,844 43,907,379 0.0879 0.0856 0.0763 MS 11 24,222,077 14,399,213 41,359,918 0.0877 0.0905 0.0719 MS 12 25,787,873 15,593,701 45,087,695 0.0934 0.0980 0.0784 NC 01 97,331,884 37,053,636 92,254,907 0.0866 0.0983 0.0883 NC 02 87,137,443 31,305,996 77,220,069 0.0775 0.0831 0.0739 NC 03 97,833,212 33,620,839 82,323,264 0.0871 0.0892 0.0788 NC 04 92,583,583 31,510,173 82,114,199 0.0824 0.0836 0.0786 NC 05 93,010,611 30,993,014 92,701,935 0.0828 0.0822 0.0887 NC 06 89,783,619 27,981,850 86,656,380 0.0799 0.0742 0.0829 NC 07 96,373,472 29,656,314 95,664,904 0.0858 0.0787 0.0915 NC 08 98,109,730 30,628,115 98,103,529 0.0873 0.0813 0.0939 NC 09 90,309,848 27,225,566 84,456,086 0.0804 0.0722 0.0808 NC 10 93,077,269 31,140,223 83,355,612 0.0828 0.0826 0.0798 NC 11 89,955,025 29,977,442 72,940,892 0.0800 0.0795 0.0698 NC 12 98,265,370 35,793,481 97,185,382 0.0874 0.0950 0.0930 SC 01 43,721,987 18,432,548 49,580,491 0.0868 0.0916 0.0808 SC 02 38,541,035 16,084,499 43,227,327 0.0765 0.0800 0.0705 SC 03 41,798,931 16,863,740 48,271,000 0.0830 0.0838 0.0787 SC 04 39,311,540 16,302,473 46,550,374 0.0780 0.0810 0.0759 SC 05 41,348,611 18,341,342 57,954,394 0.0821 0.0912 0.0945 SC 06 40,997,908 16,485,083 55,608,346 0.0814 0.0820 0.0907 SC 07 43,867,411 17,240,809 58,741,824 0.0871 0.0857 0.0958 SC 08 44,651,381 17,110,102 58,644,588 0.0886 0.0851 0.0956 SC 09 40,323,039 15,481,066 50,978,159 0.0800 0.0770 0.0831 SC 10 42,560,796 16,101,822 48,087,082 0.0845 0.0800 0.0784 SC 11 42,129,900 15,649,579 44,762,435 0.0836 0.0778 0.0730 SC 12 44,617,469 17,064,833 50,887,170 0.0885 0.0848 0.0830 TN 01 71,608,169 32,463,649 70,543,984 0.0891 0.0918 0.0878 TN 02 63,447,099 28,516,971 57,807,903 0.0790 0.0806 0.0719 TN 03 70,285,032 30,789,323 62,978,124 0.0875 0.0870 0.0784 TN 04 67,115,103 29,544,149 62,263,948 0.0836 0.0835 0.0775 TN 05 67,604,846 30,239,993 73,924,640 0.0842 0.0855 0.0920 TN 06 64,995,186 27,570,520 69,983,255 0.0809 0.0779 0.0871 TN 07 69,115,263 28,472,467 75,627,607 0.0860 0.0805 0.0941 TN 08 68,203,771 27,938,018 75,482,963 0.0849 0.0790 0.0939 TN 09 64,028,005 26,223,217 66,657,640 0.0797 0.0741 0.0830 TN 10 67,207,741 30,302,087 63,600,104 0.0837 0.0857 0.0792 TN 11 64,351,135 30,025,154 60,930,714 0.0801 0.0849 0.0758 TN 12 65,304,428 31,613,217 63,691,363 0.0813 0.0894 0.0793 VA 01 48,819,916 19,354,669 61,201,527 0.0903 0.0899 0.0845 VA 02 42,459,207 16,120,688 50,059,887 0.0786 0.0749 0.0692 VA 03 46,445,863 17,609,976 52,456,475 0.0860 0.0818 0.0725 VA 04 45,434,640 16,978,258 55,638,983 0.0841 0.0789 0.0769 VA 05 44,510,048 20,277,218 70,273,499 0.0824 0.0942 0.0971 VA 06 44,336,821 18,643,880 65,152,697 0.0820 0.0866 0.0900

E-2

### Atmospheric Sciences Group 

## Appendix E Average 2000-2004 State Level Monthly Profiles

CEM-Based Distribution Alpine Geophysics

SO2 Mass NOx Mass Heat Input State Month [lbs] [lbs] [MMBtu] SO2 Ratio NOx Ratio Heat Input

Average Values [2000-2004] Calculated Ratios

VA 07 47,115,998 18,686,032 71,852,733 0.0872 0.0868 0.0993 VA 08 47,071,668 19,614,203 74,982,624 0.0871 0.0911 0.1036 VA 09 41,488,618 16,595,117 60,690,737 0.0768 0.0771 0.0838 VA 10 41,835,028 16,195,498 49,286,979 0.0774 0.0752 0.0681 VA 11 43,194,175 16,478,500 52,422,881 0.0799 0.0766 0.0724 VA 12 47,668,957 18,685,461 59,876,938 0.0882 0.0868 0.0827 WV 01 111,875,900 52,042,851 92,757,729 0.0894 0.0974 0.0850 WV 02 101,345,095 47,532,002 84,725,694 0.0810 0.0889 0.0776 WV 03 110,021,992 50,082,217 92,337,571 0.0879 0.0937 0.0846 WV 04 104,297,369 47,902,177 89,453,424 0.0833 0.0896 0.0820 WV 05 104,359,859 41,624,694 92,539,479 0.0834 0.0779 0.0848 WV 06 99,762,595 36,857,627 88,460,783 0.0797 0.0690 0.0810 WV 07 103,652,169 39,048,341 94,718,439 0.0828 0.0731 0.0868 WV 08 105,240,948 37,751,302 96,769,225 0.0841 0.0706 0.0887 WV 09 100,547,899 36,230,294 91,003,310 0.0803 0.0678 0.0834 WV 10 104,134,189 47,928,604 90,978,471 0.0832 0.0897 0.0834 WV 11 101,789,220 48,091,022 87,501,683 0.0813 0.0900 0.0802 WV 12 104,764,255 49,305,966 90,235,248 0.0837 0.0923 0.0827

E-3

### Atmonspheric Sciences Group 

## Appendix F Average 2000-2004 Alabama Monthly Profiles

CEM-Based Distribution Alpine Geophysics

F-1 0.000 0.010 0.020 0.030 0.040 0.050 0.060 0.070 0.080 0.090 0.100

Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec
MonthNormailzed Distribution Ratio



### SO2 Ratio NOx Ratio Heat Input

### Atmonspheric Sciences Group 

## Appendix F Average 2000-2004 Florida Monthly Profiles

CEM-Based Distribution Alpine Geophysics

F-2 0.000 0.010 0.020 0.030 0.040 0.050 0.060 0.070 0.080 0.090 0.100

Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec
MonthNormailzed Distribution Ratio



### SO2 Ratio NOx Ratio Heat Input

### Atmonspheric Sciences Group 

## Appendix F Average 2000-2004 Georgia Monthly Profiles

CEM-Based Distribution Alpine Geophysics

F-3 0.000 0.020 0.040 0.060 0.080 0.100 0.120

Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec
MonthNormailzed Distribution Ratio



### SO2 Ratio NOx Ratio Heat Input

### Atmonspheric Sciences Group 

## Appendix F Average 2000-2004 Kentucky Monthly Profiles

CEM-Based Distribution Alpine Geophysics

F-4 0.000 0.020 0.040 0.060 0.080 0.100 0.120

Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec
MonthNormailzed Distribution Ratio



### SO2 Ratio NOx Ratio Heat Input

### Atmonspheric Sciences Group 

## Appendix F Average 2000-2004 Mississippi Monthly Profiles

CEM-Based Distribution Alpine Geophysics

F-5 0.000 0.020 0.040 0.060 0.080 0.100 0.120

Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec
MonthNormailzed Distribution Ratio



### SO2 Ratio NOx Ratio Heat Input

### Atmonspheric Sciences Group 

## Appendix F Average 2000-2004 North Carolina Monthly Profiles

CEM-Based Distribution Alpine Geophysics

F-6 0.000 0.020 0.040 0.060 0.080 0.100 0.120

Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec
MonthNormailzed Distribution Ratio



### SO2 Ratio NOx Ratio Heat Input

### Atmonspheric Sciences Group 

## Appendix F Average 2000-2004 South Carolina Monthly Profiles

CEM-Based Distribution Alpine Geophysics

F-7 0.000 0.020 0.040 0.060 0.080 0.100 0.120

Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec
MonthNormailzed Distribution Ratio



### SO2 Ratio NOx Ratio Heat Input

### Atmonspheric Sciences Group 

## Appendix F Average 2000-2004 Tennessee Monthly Profiles

CEM-Based Distribution Alpine Geophysics

F-8 0.000 0.010 0.020 0.030 0.040 0.050 0.060 0.070 0.080 0.090 0.100

Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec
MonthNormailzed Distribution Ratio



### SO2 Ratio NOx Ratio Heat Input

### Atmonspheric Sciences Group 

## Appendix F Average 2000-2004 Virginia Monthly Profiles

CEM-Based Distribution Alpine Geophysics

F-9 0.000 0.020 0.040 0.060 0.080 0.100 0.120

Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec
MonthNormailzed Distribution Ratio



### SO2 Ratio NOx Ratio Heat Input

### Atmonspheric Sciences Group 

## Appendix F Average 2000-2004 West Virginia Monthly Profiles

CEM-Based Distribution Alpine Geophysics

F-10 0.000 0.020 0.040 0.060 0.080 0.100 0.120

Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec
MonthNormailzed Distribution Ratio



### SO2 Ratio NOx Ratio Heat InputAtmospheric Sciences Group 

### Appendix G Average 2000-2004 State Level Monthly-Day of Week Profiles

CEM-Based Distribution Alpine Geophysics

SO2 Mass NOx Mass Heat Input State Month Day of Week [lbs] [lbs] [MMBtu] SO2 Ratio NOx Ratio Heat Input AL Jan Sun 11,973,393 4,292,483 12,150,601 0.1235 0.1206 0.1140 AL Jan Mon 12,374,833 4,518,105 13,660,275 0.1277 0.1270 0.1281 AL Jan Tue 15,759,152 5,811,809 17,855,568 0.1626 0.1633 0.1675 AL Jan Wed 15,817,025 5,904,760 18,056,233 0.1632 0.1659 0.1694 AL Jan Thu 15,848,565 5,912,905 17,883,602 0.1635 0.1662 0.1678 AL Jan Fri 12,652,920 4,622,646 14,110,073 0.1305 0.1299 0.1324 AL Jan Sat 12,504,382 4,524,941 12,891,370 0.1290 0.1271 0.1209 AL Feb Sun 12,465,714 4,378,603 11,982,100 0.1396 0.1381 0.1298 AL Feb Mon 12,648,797 4,566,922 13,683,022 0.1416 0.1440 0.1482 AL Feb Tue 13,055,528 4,650,784 13,916,803 0.1462 0.1467 0.1507 AL Feb Wed 12,952,638 4,624,268 13,892,291 0.1450 0.1458 0.1505 AL Feb Thu 13,064,253 4,654,235 13,656,975 0.1463 0.1468 0.1479 AL Feb Fri 12,605,617 4,453,161 13,144,836 0.1412 0.1404 0.1424 AL Feb Sat 12,506,729 4,384,600 12,044,772 0.1401 0.1383 0.1305 AL Mar Sun 15,136,907 5,425,946 15,180,521 0.1545 0.1567 0.1522 AL Mar Mon 12,807,193 4,585,951 14,006,813 0.1307 0.1324 0.1404 AL Mar Tue 12,944,714 4,570,137 13,805,523 0.1321 0.1320 0.1384 AL Mar Wed 12,999,541 4,537,373 13,259,394 0.1327 0.1310 0.1329 AL Mar Thu 12,873,383 4,506,075 12,778,477 0.1314 0.1301 0.1281 AL Mar Fri 15,661,836 5,503,590 15,357,680 0.1599 0.1589 0.1540 AL Mar Sat 15,553,458 5,495,957 15,354,531 0.1587 0.1587 0.1539 AL Apr Sun 11,332,686 4,123,907 12,698,306 0.1284 0.1275 0.1268 AL Apr Mon 14,709,426 5,394,905 16,813,048 0.1667 0.1668 0.1679 AL Apr Tue 14,964,648 5,500,081 17,133,697 0.1696 0.1701 0.1711 AL Apr Wed 11,974,199 4,381,431 13,657,561 0.1357 0.1355 0.1364 AL Apr Thu 11,841,341 4,392,824 13,582,578 0.1342 0.1359 0.1357 AL Apr Fri 11,589,435 4,252,648 13,155,951 0.1313 0.1315 0.1314 AL Apr Sat 11,831,443 4,288,474 13,088,368 0.1341 0.1326 0.1307 AL May Sun 11,290,254 3,924,702 13,059,831 0.1255 0.1203 0.1156 AL May Mon 11,516,514 4,115,730 14,403,677 0.1280 0.1261 0.1275 AL May Tue 11,730,957 4,236,978 14,784,483 0.1304 0.1299 0.1309 AL May Wed 14,812,058 5,491,479 18,961,819 0.1646 0.1683 0.1679 AL May Thu 14,475,031 5,429,397 18,685,109 0.1609 0.1664 0.1654 AL May Fri 14,613,756 5,349,841 19,086,178 0.1624 0.1640 0.1690 AL May Sat 11,524,096 4,079,639 13,986,871 0.1281 0.1250 0.1238 AL Jun Sun 13,957,660 4,981,619 17,448,833 0.1602 0.1597 0.1571 AL Jun Mon 11,633,110 4,294,059 14,994,420 0.1336 0.1377 0.1350 AL Jun Tue 11,576,426 4,230,898 15,073,323 0.1329 0.1356 0.1357 AL Jun Wed 11,663,562 4,201,231 15,347,162 0.1339 0.1347 0.1382 AL Jun Thu 12,000,645 4,240,320 15,246,768 0.1378 0.1359 0.1372 AL Jun Fri 11,905,820 4,190,850 15,112,838 0.1367 0.1344 0.1360 AL Jun Sat 14,365,013 5,054,322 17,865,378 0.1649 0.1620 0.1608 AL Jul Sun 11,478,359 4,030,395 14,872,793 0.1253 0.1257 0.1238 AL Jul Mon 14,896,744 5,353,452 19,661,377 0.1627 0.1669 0.1637 AL Jul Tue 14,892,334 5,240,213 19,673,860 0.1626 0.1634 0.1638 AL Jul Wed 14,865,558 5,188,296 19,695,559 0.1623 0.1618 0.1640 AL Jul Thu 12,025,777 4,112,950 15,522,479 0.1313 0.1282 0.1292 AL Jul Fri 11,771,513 4,111,362 15,390,421 0.1285 0.1282 0.1281 AL Jul Sat 11,657,160 4,037,311 15,294,119 0.1273 0.1259 0.1273 AL Aug Sun 11,088,782 3,913,833 14,625,355 0.1225 0.1212 0.1222 AL Aug Mon 11,442,122 4,181,420 15,548,602 0.1264 0.1295 0.1299 AL Aug Tue 11,752,571 4,201,299 15,748,722 0.1298 0.1301 0.1316 AL Aug Wed 11,940,710 4,288,501 15,898,971 0.1319 0.1328 0.1328 AL Aug Thu 15,014,026 5,347,097 19,862,773 0.1659 0.1656 0.1659 AL Aug Fri 14,892,207 5,266,987 19,530,653 0.1645 0.1632 0.1631 AL Aug Sat 14,386,647 5,083,661 18,500,321 0.1589 0.1575 0.1545 AL Sep Sun 13,885,652 4,820,670 16,659,869 0.1613 0.1596 0.1530 Average Values [2000-2004] Calculated Ratios

G-1Atmospheric Sciences Group 

### Appendix G Average 2000-2004 State Level Monthly-Day of Week Profiles

CEM-Based Distribution Alpine Geophysics

SO2 Mass NOx Mass Heat Input State Month Day of Week [lbs] [lbs] [MMBtu] SO2 Ratio NOx Ratio Heat Input Average Values [2000-2004] Calculated Ratios

AL Sep Mon 14,141,995 5,038,855 18,062,372 0.1643 0.1668 0.1659 AL Sep Tue 11,484,404 4,082,649 14,962,763 0.1334 0.1352 0.1374 AL Sep Wed 11,524,522 4,022,576 15,083,427 0.1339 0.1332 0.1385 AL Sep Thu 11,685,702 4,046,346 15,167,290 0.1357 0.1340 0.1393 AL Sep Fri 11,811,386 4,173,863 15,058,953 0.1372 0.1382 0.1383 AL Sep Sat 11,560,273 4,020,226 13,878,522 0.1343 0.1331 0.1275 AL Oct Sun 11,811,377 4,289,943 12,293,195 0.1245 0.1249 0.1175 AL Oct Mon 12,332,346 4,513,994 13,800,627 0.1300 0.1315 0.1319 AL Oct Tue 15,474,221 5,650,161 18,121,815 0.1631 0.1645 0.1732 AL Oct Wed 15,551,242 5,595,423 17,461,781 0.1639 0.1630 0.1669 AL Oct Thu 15,534,833 5,592,238 17,160,242 0.1638 0.1629 0.1640 AL Oct Fri 12,155,982 4,367,495 13,056,737 0.1281 0.1272 0.1248 AL Oct Sat 12,002,823 4,328,644 12,725,123 0.1265 0.1261 0.1216 AL Nov Sun 10,950,379 4,115,386 11,183,830 0.1280 0.1270 0.1228 AL Nov Mon 11,507,720 4,411,521 12,990,319 0.1345 0.1361 0.1427 AL Nov Tue 11,720,227 4,422,309 12,908,336 0.1370 0.1364 0.1418 AL Nov Wed 11,739,397 4,445,575 12,902,505 0.1372 0.1371 0.1417 AL Nov Thu 11,403,389 4,330,306 12,158,977 0.1333 0.1336 0.1335 AL Nov Fri 14,207,798 5,352,146 14,393,969 0.1661 0.1651 0.1581 AL Nov Sat 14,011,340 5,338,674 14,507,152 0.1638 0.1647 0.1593 AL Dec Sun 14,259,735 5,291,444 15,673,882 0.1596 0.1577 0.1555 AL Dec Mon 14,521,256 5,449,977 16,243,296 0.1625 0.1624 0.1612 AL Dec Tue 14,337,889 5,387,676 16,636,483 0.1605 0.1606 0.1651 AL Dec Wed 11,519,363 4,344,609 13,758,100 0.1289 0.1295 0.1365 AL Dec Thu 11,537,461 4,339,002 13,205,960 0.1291 0.1293 0.1311 AL Dec Fri 11,518,162 4,387,499 12,641,479 0.1289 0.1308 0.1254 AL Dec Sat 11,650,526 4,349,426 12,610,355 0.1304 0.1296 0.1251 FL Jan Sun 13,052,230 7,160,414 23,398,263 0.1125 0.1137 0.1177 FL Jan Mon 14,866,982 7,996,928 25,194,145 0.1282 0.1270 0.1268 FL Jan Tue 18,966,078 10,294,960 31,932,987 0.1635 0.1634 0.1607 FL Jan Wed 20,016,132 10,819,976 32,850,433 0.1725 0.1718 0.1653 FL Jan Thu 19,295,311 10,472,703 32,116,708 0.1663 0.1663 0.1616 FL Jan Fri 15,354,992 8,522,403 27,688,357 0.1324 0.1353 0.1393 FL Jan Sat 14,459,528 7,722,574 25,570,155 0.1246 0.1226 0.1287 FL Feb Sun 12,328,843 6,678,620 22,095,068 0.1312 0.1314 0.1340 FL Feb Mon 13,274,623 7,208,897 22,824,084 0.1413 0.1418 0.1384 FL Feb Tue 13,693,951 7,472,016 23,752,507 0.1457 0.1470 0.1440 FL Feb Wed 13,836,434 7,526,378 24,260,947 0.1473 0.1481 0.1471 FL Feb Thu 14,626,146 7,756,851 24,978,352 0.1557 0.1526 0.1514 FL Feb Fri 13,387,771 7,250,124 24,015,119 0.1425 0.1426 0.1456 FL Feb Sat 12,811,018 6,938,932 23,023,625 0.1363 0.1365 0.1396 FL Mar Sun 16,314,717 8,834,739 28,930,182 0.1463 0.1465 0.1471 FL Mar Mon 14,145,402 7,894,516 25,499,466 0.1269 0.1310 0.1296 FL Mar Tue 15,509,617 8,218,394 26,796,918 0.1391 0.1363 0.1362 FL Mar Wed 14,681,727 7,998,106 26,192,929 0.1317 0.1327 0.1332 FL Mar Thu 15,079,501 8,032,083 26,337,928 0.1352 0.1332 0.1339 FL Mar Fri 18,299,777 9,808,680 32,297,624 0.1641 0.1627 0.1642 FL Mar Sat 17,474,812 9,499,456 30,650,650 0.1567 0.1576 0.1558 FL Apr Sun 13,180,026 7,253,618 24,850,878 0.1232 0.1228 0.1272 FL Apr Mon 18,541,655 10,196,466 33,323,177 0.1733 0.1726 0.1706 FL Apr Tue 18,213,655 10,190,833 33,629,986 0.1702 0.1725 0.1722 FL Apr Wed 14,605,188 7,968,116 26,091,761 0.1365 0.1349 0.1336 FL Apr Thu 14,526,273 7,984,231 25,923,235 0.1357 0.1352 0.1327 FL Apr Fri 14,280,951 7,906,375 26,138,199 0.1334 0.1338 0.1338 FL Apr Sat 13,667,690 7,572,152 25,380,968 0.1277 0.1282 0.1299 FL May Sun 14,357,464 7,485,459 25,863,896 0.1211 0.1211 0.1245 FL May Mon 15,154,083 7,956,981 26,787,554 0.1278 0.1287 0.1289

G-2Atmospheric Sciences Group 

### Appendix G Average 2000-2004 State Level Monthly-Day of Week Profiles

CEM-Based Distribution Alpine Geophysics

SO2 Mass NOx Mass Heat Input State Month Day of Week [lbs] [lbs] [MMBtu] SO2 Ratio NOx Ratio Heat Input Average Values [2000-2004] Calculated Ratios

FL May Tue 15,455,197 8,087,887 26,870,989 0.1303 0.1308 0.1293 FL May Wed 19,503,288 10,111,972 33,711,442 0.1645 0.1636 0.1622 FL May Thu 19,515,243 10,161,786 34,071,726 0.1646 0.1644 0.1640 FL May Fri 19,586,389 10,147,265 33,901,927 0.1652 0.1642 0.1631 FL May Sat 15,017,697 7,860,254 26,596,461 0.1266 0.1272 0.1280 FL Jun Sun 18,310,691 9,452,183 32,537,086 0.1578 0.1581 0.1605 FL Jun Mon 15,781,319 8,161,348 27,330,779 0.1360 0.1365 0.1348 FL Jun Tue 15,960,643 8,221,474 27,459,697 0.1375 0.1375 0.1355 FL Jun Wed 16,100,778 8,299,845 27,869,080 0.1387 0.1388 0.1375 FL Jun Thu 15,570,508 8,114,098 27,364,774 0.1341 0.1357 0.1350 FL Jun Fri 15,525,917 7,973,482 27,062,460 0.1338 0.1333 0.1335 FL Jun Sat 18,819,132 9,579,210 33,092,339 0.1621 0.1602 0.1632 FL Jul Sun 14,708,203 7,575,148 26,405,051 0.1187 0.1212 0.1243 FL Jul Mon 20,178,197 10,115,348 34,663,034 0.1629 0.1618 0.1631 FL Jul Tue 20,451,635 10,271,409 34,820,771 0.1651 0.1643 0.1639 FL Jul Wed 20,493,877 10,275,526 34,553,648 0.1654 0.1644 0.1626 FL Jul Thu 16,472,099 8,264,690 27,655,517 0.1330 0.1322 0.1302 FL Jul Fri 16,330,885 8,240,365 27,757,755 0.1318 0.1318 0.1306 FL Jul Sat 15,233,852 7,757,683 26,622,660 0.1230 0.1241 0.1253 FL Aug Sun 14,832,430 7,770,298 26,355,005 0.1183 0.1203 0.1228 FL Aug Mon 16,289,567 8,415,375 27,921,417 0.1299 0.1303 0.1301 FL Aug Tue 16,409,009 8,464,979 27,982,337 0.1309 0.1311 0.1304 FL Aug Wed 16,599,763 8,412,726 27,839,040 0.1324 0.1303 0.1297 FL Aug Thu 21,190,840 10,674,830 35,352,991 0.1690 0.1653 0.1647 FL Aug Fri 20,753,135 10,663,040 35,280,658 0.1655 0.1651 0.1644 FL Aug Sat 19,310,195 10,171,594 33,905,771 0.1540 0.1575 0.1580 FL Sep Sun 17,407,168 9,327,229 33,090,745 0.1539 0.1557 0.1601 FL Sep Mon 18,951,071 10,063,106 34,697,245 0.1676 0.1680 0.1679 FL Sep Tue 15,814,547 8,275,493 28,027,452 0.1399 0.1381 0.1356 FL Sep Wed 15,592,813 8,221,478 28,140,157 0.1379 0.1372 0.1361 FL Sep Thu 15,256,995 8,137,970 28,067,153 0.1349 0.1358 0.1358 FL Sep Fri 15,323,186 8,044,147 27,681,511 0.1355 0.1343 0.1339 FL Sep Sat 14,735,009 7,844,300 27,008,693 0.1303 0.1309 0.1307 FL Oct Sun 13,398,285 7,549,892 25,661,085 0.1218 0.1227 0.1240 FL Oct Mon 14,202,904 7,990,788 27,002,819 0.1292 0.1298 0.1305 FL Oct Tue 18,096,168 9,983,295 34,056,575 0.1646 0.1622 0.1646 FL Oct Wed 17,946,866 10,125,375 33,672,517 0.1632 0.1645 0.1627 FL Oct Thu 18,294,441 10,176,870 33,532,221 0.1664 0.1653 0.1621 FL Oct Fri 14,378,959 8,087,989 26,782,353 0.1308 0.1314 0.1294 FL Oct Sat 13,643,205 7,637,100 26,216,601 0.1241 0.1241 0.1267 FL Nov Sun 12,425,949 6,985,756 23,514,454 0.1221 0.1251 0.1258 FL Nov Mon 13,791,110 7,588,195 25,610,183 0.1355 0.1358 0.1370 FL Nov Tue 14,159,503 7,809,700 26,113,365 0.1391 0.1398 0.1397 FL Nov Wed 14,370,209 7,842,655 25,876,805 0.1412 0.1404 0.1384 FL Nov Thu 13,592,948 7,519,473 24,826,599 0.1336 0.1346 0.1328 FL Nov Fri 16,684,484 9,125,303 30,670,840 0.1639 0.1634 0.1640 FL Nov Sat 16,757,179 8,990,636 30,372,419 0.1646 0.1609 0.1624 FL Dec Sun 18,192,578 9,580,007 31,795,817 0.1574 0.1582 0.1609 FL Dec Mon 18,247,650 9,703,301 31,978,285 0.1579 0.1602 0.1618 FL Dec Tue 18,262,323 9,595,586 31,915,018 0.1580 0.1584 0.1615 FL Dec Wed 14,947,606 7,892,737 25,962,148 0.1293 0.1303 0.1314 FL Dec Thu 15,731,535 8,249,796 26,206,079 0.1361 0.1362 0.1326 FL Dec Fri 15,220,061 7,809,988 25,012,084 0.1317 0.1289 0.1266 FL Dec Sat 14,986,986 7,735,028 24,722,702 0.1297 0.1277 0.1251 GA Jan Sun 13,124,248 4,020,218 11,305,425 0.1178 0.1139 0.1113 GA Jan Mon 14,360,931 4,512,619 12,504,023 0.1289 0.1278 0.1231 GA Jan Tue 18,524,178 5,840,250 16,704,047 0.1663 0.1654 0.1644

G-3Atmospheric Sciences Group 

### Appendix G Average 2000-2004 State Level Monthly-Day of Week Profiles

CEM-Based Distribution Alpine Geophysics

SO2 Mass NOx Mass Heat Input State Month Day of Week [lbs] [lbs] [MMBtu] SO2 Ratio NOx Ratio Heat Input Average Values [2000-2004] Calculated Ratios

GA Jan Wed 18,483,995 5,950,256 17,283,608 0.1660 0.1686 0.1701 GA Jan Thu 17,872,716 5,819,388 16,862,298 0.1605 0.1649 0.1660 GA Jan Fri 14,637,093 4,697,899 14,218,196 0.1314 0.1331 0.1400 GA Jan Sat 14,378,672 4,459,541 12,701,268 0.1291 0.1263 0.1250 GA Feb Sun 13,382,988 3,957,671 10,524,683 0.1353 0.1290 0.1214 GA Feb Mon 14,770,265 4,523,997 12,942,006 0.1494 0.1475 0.1492 GA Feb Tue 14,508,558 4,595,940 13,154,535 0.1467 0.1498 0.1517 GA Feb Wed 14,470,656 4,563,033 13,554,721 0.1463 0.1487 0.1563 GA Feb Thu 14,407,456 4,600,185 13,771,393 0.1457 0.1499 0.1588 GA Feb Fri 13,742,723 4,340,244 11,899,583 0.1390 0.1415 0.1372 GA Feb Sat 13,613,681 4,097,591 10,871,415 0.1377 0.1336 0.1254 GA Mar Sun 15,495,089 4,641,883 12,167,666 0.1455 0.1403 0.1319 GA Mar Mon 14,334,901 4,513,847 13,362,335 0.1346 0.1365 0.1449 GA Mar Tue 14,420,895 4,532,750 13,463,600 0.1354 0.1370 0.1460 GA Mar Wed 14,170,345 4,489,531 13,057,182 0.1331 0.1357 0.1416 GA Mar Thu 14,004,649 4,446,853 12,249,119 0.1315 0.1344 0.1328 GA Mar Fri 17,177,952 5,357,920 14,842,639 0.1613 0.1620 0.1609 GA Mar Sat 16,881,455 5,096,281 13,100,433 0.1585 0.1541 0.1420 GA Apr Sun 12,693,095 3,672,253 11,719,631 0.1233 0.1224 0.1134 GA Apr Mon 17,251,251 5,137,684 18,011,935 0.1675 0.1712 0.1743 GA Apr Tue 17,584,479 5,057,585 18,208,078 0.1708 0.1685 0.1762 GA Apr Wed 13,945,269 4,029,330 14,482,773 0.1354 0.1343 0.1402 GA Apr Thu 14,088,286 4,141,433 14,549,349 0.1368 0.1380 0.1408 GA Apr Fri 13,898,987 4,014,958 13,810,855 0.1350 0.1338 0.1337 GA Apr Sat 13,512,776 3,955,619 12,541,990 0.1312 0.1318 0.1214 GA May Sun 12,906,496 2,943,453 11,988,411 0.1226 0.1133 0.1121 GA May Mon 13,439,964 3,255,041 13,325,027 0.1276 0.1253 0.1246 GA May Tue 13,342,706 3,443,206 13,496,507 0.1267 0.1326 0.1262 GA May Wed 16,859,064 4,405,016 17,702,345 0.1601 0.1696 0.1655 GA May Thu 17,404,134 4,394,630 18,689,800 0.1653 0.1692 0.1747 GA May Fri 17,637,771 4,321,631 18,223,384 0.1675 0.1664 0.1704 GA May Sat 13,703,682 3,206,049 13,527,121 0.1301 0.1235 0.1265 GA Jun Sun 16,235,802 3,781,890 16,311,536 0.1588 0.1529 0.1539 GA Jun Mon 13,881,743 3,266,998 14,225,348 0.1357 0.1321 0.1342 GA Jun Tue 13,809,085 3,372,791 14,673,939 0.1350 0.1363 0.1384 GA Jun Wed 13,979,459 3,424,713 15,005,533 0.1367 0.1384 0.1416 GA Jun Thu 14,048,031 3,487,248 14,772,625 0.1374 0.1410 0.1394 GA Jun Fri 13,653,375 3,370,860 14,100,835 0.1335 0.1363 0.1330 GA Jun Sat 16,664,151 4,034,487 16,916,436 0.1629 0.1631 0.1596 GA Jul Sun 13,493,095 3,379,960 14,451,977 0.1238 0.1254 0.1196 GA Jul Mon 17,801,210 4,556,344 19,924,880 0.1634 0.1691 0.1648 GA Jul Tue 17,736,601 4,396,225 19,892,108 0.1628 0.1631 0.1646 GA Jul Wed 17,688,477 4,396,005 20,106,026 0.1623 0.1631 0.1663 GA Jul Thu 14,116,591 3,450,943 16,084,166 0.1296 0.1280 0.1331 GA Jul Fri 14,202,897 3,403,815 15,676,086 0.1304 0.1263 0.1297 GA Jul Sat 13,918,446 3,369,321 14,742,670 0.1277 0.1250 0.1220 GA Aug Sun 13,460,815 3,033,642 13,996,540 0.1238 0.1139 0.1165 GA Aug Mon 14,006,159 3,327,578 15,676,687 0.1288 0.1249 0.1304 GA Aug Tue 13,931,609 3,456,530 16,030,001 0.1281 0.1298 0.1334 GA Aug Wed 14,283,637 3,631,066 15,723,552 0.1313 0.1363 0.1308 GA Aug Thu 17,975,152 4,576,805 19,839,720 0.1653 0.1718 0.1651 GA Aug Fri 17,749,354 4,363,885 20,001,135 0.1632 0.1638 0.1664 GA Aug Sat 17,345,611 4,250,247 18,922,855 0.1595 0.1595 0.1574 GA Sep Sun 15,448,171 3,602,062 15,157,438 0.1578 0.1534 0.1456 GA Sep Mon 16,414,338 3,876,193 17,459,170 0.1676 0.1650 0.1678 GA Sep Tue 13,131,984 3,099,912 14,117,735 0.1341 0.1320 0.1357 GA Sep Wed 13,320,417 3,165,578 14,440,389 0.1360 0.1348 0.1388

G-4Atmospheric Sciences Group 

### Appendix G Average 2000-2004 State Level Monthly-Day of Week Profiles

CEM-Based Distribution Alpine Geophysics

SO2 Mass NOx Mass Heat Input State Month Day of Week [lbs] [lbs] [MMBtu] SO2 Ratio NOx Ratio Heat Input Average Values [2000-2004] Calculated Ratios

GA Sep Thu 13,516,677 3,288,041 14,927,333 0.1380 0.1400 0.1434 GA Sep Fri 13,444,163 3,378,753 15,048,148 0.1373 0.1439 0.1446 GA Sep Sat 12,642,974 3,076,945 12,922,533 0.1291 0.1310 0.1242 GA Oct Sun 12,221,190 3,547,451 10,953,557 0.1204 0.1168 0.1136 GA Oct Mon 13,361,673 4,095,621 12,885,298 0.1316 0.1349 0.1336 GA Oct Tue 16,938,579 5,190,094 16,406,795 0.1668 0.1709 0.1701 GA Oct Wed 16,923,596 5,106,862 16,895,152 0.1667 0.1682 0.1752 GA Oct Thu 16,501,991 4,995,042 16,151,355 0.1625 0.1645 0.1675 GA Oct Fri 13,305,028 3,870,352 12,036,350 0.1310 0.1274 0.1248 GA Oct Sat 12,284,472 3,564,025 11,124,250 0.1210 0.1174 0.1153 GA Nov Sun 11,646,313 3,389,419 8,962,157 0.1242 0.1201 0.1143 GA Nov Mon 13,073,222 3,945,534 11,430,721 0.1394 0.1398 0.1457 GA Nov Tue 13,191,844 3,986,329 11,603,064 0.1407 0.1412 0.1479 GA Nov Wed 12,998,499 4,054,567 11,677,317 0.1386 0.1437 0.1489 GA Nov Thu 12,454,620 3,848,249 10,562,184 0.1328 0.1363 0.1347 GA Nov Fri 15,290,213 4,579,302 12,324,022 0.1631 0.1623 0.1571 GA Nov Sat 15,105,153 4,420,003 11,880,385 0.1611 0.1566 0.1515 GA Dec Sun 15,270,476 4,619,508 12,878,140 0.1512 0.1511 0.1460 GA Dec Mon 16,620,084 5,058,485 14,687,554 0.1645 0.1655 0.1665 GA Dec Tue 16,351,400 4,949,393 14,751,688 0.1619 0.1619 0.1672 GA Dec Wed 13,562,340 4,109,788 12,508,459 0.1343 0.1344 0.1418 GA Dec Thu 13,153,577 4,029,058 11,982,882 0.1302 0.1318 0.1358 GA Dec Fri 13,076,436 3,969,867 11,132,791 0.1295 0.1299 0.1262 GA Dec Sat 12,972,294 3,834,436 10,282,360 0.1284 0.1254 0.1165 KY Jan Sun 13,951,350 6,324,291 12,340,439 0.1219 0.1241 0.1196 KY Jan Mon 14,648,386 6,568,474 13,191,315 0.1280 0.1289 0.1279 KY Jan Tue 18,754,926 8,319,015 16,806,905 0.1639 0.1632 0.1629 KY Jan Wed 18,737,070 8,302,139 16,702,204 0.1637 0.1629 0.1619 KY Jan Thu 18,617,927 8,274,249 17,253,825 0.1627 0.1624 0.1673 KY Jan Fri 14,989,539 6,674,316 13,836,584 0.1310 0.1310 0.1341 KY Jan Sat 14,751,911 6,499,145 13,025,455 0.1289 0.1275 0.1263 KY Feb Sun 13,614,024 6,109,118 12,294,809 0.1367 0.1350 0.1326 KY Feb Mon 14,397,395 6,582,725 13,387,654 0.1446 0.1454 0.1444 KY Feb Tue 14,555,978 6,610,627 13,801,950 0.1462 0.1461 0.1489 KY Feb Wed 14,329,132 6,724,437 14,007,595 0.1439 0.1486 0.1511 KY Feb Thu 14,616,707 6,568,675 13,427,712 0.1468 0.1451 0.1449 KY Feb Fri 14,205,033 6,385,449 12,975,468 0.1426 0.1411 0.1400 KY Feb Sat 13,863,920 6,279,393 12,796,740 0.1392 0.1387 0.1381 KY Mar Sun 16,154,103 7,633,026 15,634,188 0.1518 0.1540 0.1525 KY Mar Mon 13,697,223 6,340,694 13,810,745 0.1287 0.1279 0.1347 KY Mar Tue 14,077,465 6,505,076 13,891,463 0.1323 0.1312 0.1355 KY Mar Wed 14,152,624 6,445,515 13,294,931 0.1330 0.1300 0.1297 KY Mar Thu 14,228,900 6,555,563 13,351,220 0.1337 0.1322 0.1302 KY Mar Fri 17,604,219 8,283,732 16,713,671 0.1654 0.1671 0.1630 KY Mar Sat 16,497,463 7,810,869 15,830,328 0.1550 0.1576 0.1544 KY Apr Sun 12,664,919 5,692,491 12,300,015 0.1252 0.1262 0.1222 KY Apr Mon 16,959,493 7,671,569 17,098,033 0.1677 0.1701 0.1699 KY Apr Tue 17,071,625 7,772,987 17,448,992 0.1688 0.1723 0.1734 KY Apr Wed 13,857,201 6,101,485 13,777,709 0.1370 0.1353 0.1369 KY Apr Thu 13,903,554 6,065,542 13,876,852 0.1375 0.1345 0.1379 KY Apr Fri 13,716,257 5,951,503 13,472,483 0.1356 0.1319 0.1338 KY Apr Sat 12,945,254 5,850,563 12,679,669 0.1280 0.1297 0.1260 KY May Sun 12,456,298 4,367,716 11,712,119 0.1197 0.1162 0.1177 KY May Mon 13,110,103 4,772,353 12,765,025 0.1260 0.1270 0.1282 KY May Tue 13,515,816 5,059,816 13,131,188 0.1299 0.1346 0.1319 KY May Wed 17,039,088 6,330,032 16,401,532 0.1638 0.1684 0.1648 KY May Thu 17,180,451 6,257,493 16,428,566 0.1652 0.1665 0.1650

G-5Atmospheric Sciences Group 

### Appendix G Average 2000-2004 State Level Monthly-Day of Week Profiles

CEM-Based Distribution Alpine Geophysics

SO2 Mass NOx Mass Heat Input State Month Day of Week [lbs] [lbs] [MMBtu] SO2 Ratio NOx Ratio Heat Input Average Values [2000-2004] Calculated Ratios

KY May Fri 17,730,036 6,198,671 16,780,192 0.1704 0.1649 0.1686 KY May Sat 12,989,855 4,593,973 12,327,744 0.1249 0.1222 0.1238 KY Jun Sun 16,427,192 5,214,046 14,825,059 0.1552 0.1528 0.1515 KY Jun Mon 14,418,433 4,609,315 13,524,297 0.1362 0.1351 0.1382 KY Jun Tue 14,716,957 4,703,306 13,812,994 0.1390 0.1378 0.1412 KY Jun Wed 14,946,201 4,688,060 13,762,886 0.1412 0.1374 0.1407 KY Jun Thu 14,520,946 4,780,070 13,478,982 0.1372 0.1401 0.1378 KY Jun Fri 14,372,136 4,691,043 13,090,249 0.1358 0.1375 0.1338 KY Jun Sat 16,470,166 5,443,154 15,333,682 0.1556 0.1595 0.1567 KY Jul Sun 13,244,569 4,448,178 13,049,965 0.1216 0.1269 0.1217 KY Jul Mon 17,797,803 5,939,637 17,936,410 0.1635 0.1694 0.1673 KY Jul Tue 18,024,388 5,840,628 17,786,205 0.1655 0.1666 0.1659 KY Jul Wed 18,006,476 5,728,943 17,730,534 0.1654 0.1634 0.1654 KY Jul Thu 14,180,922 4,403,898 13,941,707 0.1302 0.1256 0.1301 KY Jul Fri 14,046,649 4,359,457 13,625,059 0.1290 0.1244 0.1271 KY Jul Sat 13,580,950 4,335,445 13,122,163 0.1247 0.1237 0.1224 KY Aug Sun 12,657,699 3,968,906 12,321,196 0.1208 0.1151 0.1168 KY Aug Mon 13,431,315 4,290,811 13,998,056 0.1282 0.1244 0.1327 KY Aug Tue 13,951,503 4,490,599 13,738,219 0.1331 0.1302 0.1303 KY Aug Wed 14,027,682 4,722,032 13,908,301 0.1339 0.1369 0.1319 KY Aug Thu 17,490,094 5,971,600 17,868,881 0.1669 0.1732 0.1694 KY Aug Fri 17,069,499 5,736,578 17,711,338 0.1629 0.1663 0.1679 KY Aug Sat 16,171,129 5,305,811 15,923,072 0.1543 0.1539 0.1510 KY Sep Sun 15,560,753 5,159,716 14,794,644 0.1553 0.1615 0.1541 KY Sep Mon 16,691,163 5,314,459 16,076,578 0.1666 0.1663 0.1674 KY Sep Tue 13,588,051 4,280,822 13,252,975 0.1357 0.1340 0.1380 KY Sep Wed 13,648,570 4,327,920 13,280,817 0.1363 0.1354 0.1383 KY Sep Thu 13,835,926 4,291,753 13,183,716 0.1381 0.1343 0.1373 KY Sep Fri 13,884,049 4,410,151 13,162,399 0.1386 0.1380 0.1371 KY Sep Sat 12,958,721 4,168,565 12,260,916 0.1294 0.1305 0.1277 KY Oct Sun 12,141,431 5,354,039 11,492,581 0.1174 0.1228 0.1177 KY Oct Mon 13,299,820 5,652,234 12,677,771 0.1286 0.1296 0.1298 KY Oct Tue 17,100,418 7,229,922 16,388,261 0.1654 0.1658 0.1678 KY Oct Wed 17,118,965 7,190,218 16,425,518 0.1656 0.1649 0.1682 KY Oct Thu 17,274,935 7,151,119 16,036,970 0.1671 0.1640 0.1642 KY Oct Fri 13,765,153 5,621,152 12,698,452 0.1331 0.1289 0.1300 KY Oct Sat 12,683,108 5,416,877 11,941,426 0.1227 0.1242 0.1223 KY Nov Sun 12,888,034 5,689,531 11,479,068 0.1276 0.1275 0.1217 KY Nov Mon 13,827,750 6,033,281 12,998,049 0.1369 0.1352 0.1378 KY Nov Tue 14,027,391 6,156,558 13,280,129 0.1388 0.1380 0.1408 KY Nov Wed 13,817,947 6,111,620 13,092,157 0.1368 0.1370 0.1388 KY Nov Thu 13,433,079 6,044,717 12,858,995 0.1330 0.1355 0.1363 KY Nov Fri 16,819,649 7,428,344 15,553,025 0.1665 0.1665 0.1649 KY Nov Sat 16,214,428 7,149,693 15,082,390 0.1605 0.1603 0.1599 KY Dec Sun 16,266,536 7,260,701 15,042,094 0.1533 0.1541 0.1506 KY Dec Mon 17,099,626 7,535,136 16,334,542 0.1612 0.1599 0.1636 KY Dec Tue 17,351,671 7,571,480 16,257,812 0.1636 0.1607 0.1628 KY Dec Wed 14,124,157 6,354,861 13,497,177 0.1332 0.1348 0.1352 KY Dec Thu 13,901,436 6,145,481 13,098,858 0.1311 0.1304 0.1312 KY Dec Fri 13,867,147 6,193,877 13,039,149 0.1307 0.1314 0.1306 KY Dec Sat 13,465,992 6,065,424 12,595,635 0.1269 0.1287 0.1261 MS Jan Sun 2,934,027 1,547,031 5,070,324 0.1128 0.1034 0.1012 MS Jan Mon 3,211,301 1,796,701 6,005,754 0.1235 0.1201 0.1199 MS Jan Tue 4,376,210 2,575,555 8,503,271 0.1683 0.1722 0.1698 MS Jan Wed 4,447,777 2,510,206 8,647,532 0.1711 0.1678 0.1727 MS Jan Thu 4,254,311 2,482,838 8,660,945 0.1636 0.1660 0.1729 MS Jan Fri 3,387,442 2,084,011 7,203,543 0.1303 0.1393 0.1438

G-6Atmospheric Sciences Group 

### Appendix G Average 2000-2004 State Level Monthly-Day of Week Profiles

CEM-Based Distribution Alpine Geophysics

SO2 Mass NOx Mass Heat Input State Month Day of Week [lbs] [lbs] [MMBtu] SO2 Ratio NOx Ratio Heat Input Average Values [2000-2004] Calculated Ratios

MS Jan Sat 3,391,361 1,962,660 5,991,150 0.1304 0.1312 0.1196 MS Feb Sun 2,865,707 1,539,649 4,982,124 0.1351 0.1296 0.1231 MS Feb Mon 3,045,835 1,706,390 5,818,853 0.1436 0.1436 0.1438 MS Feb Tue 2,946,366 1,680,065 6,058,331 0.1389 0.1414 0.1497 MS Feb Wed 3,050,683 1,748,835 6,271,216 0.1439 0.1472 0.1550 MS Feb Thu 3,152,909 1,772,814 6,454,138 0.1487 0.1492 0.1595 MS Feb Fri 3,183,084 1,721,498 5,634,487 0.1501 0.1449 0.1392 MS Feb Sat 2,961,648 1,711,108 5,252,034 0.1397 0.1440 0.1298 MS Mar Sun 3,536,374 1,770,341 6,574,596 0.1385 0.1345 0.1395 MS Mar Mon 3,354,673 1,837,396 6,523,294 0.1314 0.1396 0.1384 MS Mar Tue 3,739,452 1,994,948 6,723,534 0.1465 0.1516 0.1427 MS Mar Wed 3,656,975 1,879,896 6,472,039 0.1433 0.1429 0.1373 MS Mar Thu 3,519,508 1,781,031 6,253,976 0.1379 0.1354 0.1327 MS Mar Fri 3,858,765 1,999,341 7,488,276 0.1512 0.1519 0.1589 MS Mar Sat 3,862,595 1,895,332 7,093,809 0.1513 0.1440 0.1505 MS Apr Sun 2,802,706 1,550,523 5,068,596 0.1317 0.1269 0.1097 MS Apr Mon 3,522,340 2,054,745 7,897,071 0.1656 0.1682 0.1709 MS Apr Tue 3,368,315 2,015,573 8,579,047 0.1583 0.1650 0.1857 MS Apr Wed 2,960,970 1,712,096 6,675,080 0.1392 0.1402 0.1445 MS Apr Thu 2,955,704 1,732,620 6,321,601 0.1389 0.1419 0.1368 MS Apr Fri 2,856,821 1,592,191 6,260,019 0.1343 0.1304 0.1355 MS Apr Sat 2,806,900 1,556,465 5,394,296 0.1319 0.1274 0.1168 MS May Sun 2,590,337 1,347,670 5,761,467 0.1171 0.1143 0.1142 MS May Mon 2,821,631 1,516,133 6,688,091 0.1275 0.1286 0.1326 MS May Tue 2,953,516 1,581,490 6,734,189 0.1335 0.1341 0.1335 MS May Wed 3,823,573 1,935,958 8,214,151 0.1728 0.1642 0.1629 MS May Thu 3,670,372 1,965,880 8,388,543 0.1659 0.1667 0.1663 MS May Fri 3,371,461 1,934,087 8,483,172 0.1524 0.1640 0.1682 MS May Sat 2,894,182 1,511,175 6,167,372 0.1308 0.1281 0.1223 MS Jun Sun 3,218,591 1,902,886 7,575,004 0.1571 0.1580 0.1551 MS Jun Mon 2,697,806 1,679,401 6,841,996 0.1317 0.1394 0.1401 MS Jun Tue 2,719,988 1,611,625 6,613,821 0.1327 0.1338 0.1354 MS Jun Wed 2,755,870 1,631,480 6,712,697 0.1345 0.1354 0.1374 MS Jun Thu 2,845,794 1,626,021 6,661,510 0.1389 0.1350 0.1364 MS Jun Fri 2,829,302 1,593,911 6,637,388 0.1381 0.1323 0.1359 MS Jun Sat 3,423,886 2,001,689 7,798,457 0.1671 0.1662 0.1597 MS Jul Sun 2,788,663 1,638,489 6,251,771 0.1288 0.1212 0.1077 MS Jul Mon 3,405,599 2,237,694 10,224,933 0.1573 0.1655 0.1761 MS Jul Tue 3,448,674 2,189,589 10,177,932 0.1592 0.1619 0.1753 MS Jul Wed 3,388,723 2,140,674 9,734,319 0.1565 0.1583 0.1676 MS Jul Thu 2,919,688 1,811,222 7,636,333 0.1348 0.1340 0.1315 MS Jul Fri 2,896,864 1,779,411 7,423,708 0.1338 0.1316 0.1278 MS Jul Sat 2,808,112 1,723,730 6,623,033 0.1297 0.1275 0.1140 MS Aug Sun 2,895,411 1,656,512 6,714,526 0.1254 0.1197 0.1182 MS Aug Mon 3,074,029 1,814,139 7,573,903 0.1331 0.1311 0.1333 MS Aug Tue 3,086,467 1,808,880 7,702,160 0.1336 0.1308 0.1356 MS Aug Wed 3,109,788 1,837,416 7,519,726 0.1346 0.1328 0.1324 MS Aug Thu 3,776,028 2,353,215 9,748,609 0.1635 0.1701 0.1716 MS Aug Fri 3,614,761 2,215,018 9,221,906 0.1565 0.1601 0.1623 MS Aug Sat 3,541,892 2,149,180 8,333,496 0.1533 0.1554 0.1467 MS Sep Sun 3,076,179 1,765,446 6,702,748 0.1499 0.1462 0.1435 MS Sep Mon 3,399,174 2,143,898 8,513,746 0.1656 0.1775 0.1823 MS Sep Tue 2,799,490 1,690,307 6,329,646 0.1364 0.1400 0.1355 MS Sep Wed 2,884,057 1,655,046 6,522,357 0.1405 0.1370 0.1396 MS Sep Thu 2,754,512 1,559,383 6,174,835 0.1342 0.1291 0.1322 MS Sep Fri 2,827,643 1,681,841 6,652,181 0.1378 0.1393 0.1424 MS Sep Sat 2,782,238 1,581,271 5,811,684 0.1356 0.1309 0.1244

G-7Atmospheric Sciences Group 

### Appendix G Average 2000-2004 State Level Monthly-Day of Week Profiles

CEM-Based Distribution Alpine Geophysics

SO2 Mass NOx Mass Heat Input State Month Day of Week [lbs] [lbs] [MMBtu] SO2 Ratio NOx Ratio Heat Input Average Values [2000-2004] Calculated Ratios

MS Oct Sun 3,278,945 1,583,575 5,127,382 0.1351 0.1163 0.1168 MS Oct Mon 3,248,925 1,854,673 5,569,888 0.1338 0.1362 0.1269 MS Oct Tue 3,990,653 2,290,719 7,468,788 0.1644 0.1683 0.1701 MS Oct Wed 3,843,403 2,259,117 7,721,640 0.1583 0.1659 0.1759 MS Oct Thu 3,738,950 2,254,009 6,989,380 0.1540 0.1656 0.1592 MS Oct Fri 3,057,451 1,786,361 5,631,502 0.1259 0.1312 0.1283 MS Oct Sat 3,116,847 1,586,390 5,398,799 0.1284 0.1165 0.1230 MS Nov Sun 2,968,150 1,518,472 4,817,704 0.1225 0.1055 0.1165 MS Nov Mon 3,277,374 2,027,572 6,000,382 0.1353 0.1408 0.1451 MS Nov Tue 3,430,763 2,101,835 6,096,504 0.1416 0.1460 0.1474 MS Nov Wed 3,723,161 2,303,904 6,077,856 0.1537 0.1600 0.1470 MS Nov Thu 3,320,974 1,859,539 5,420,987 0.1371 0.1291 0.1311 MS Nov Fri 3,670,295 2,220,336 6,568,420 0.1515 0.1542 0.1588 MS Nov Sat 3,831,361 2,367,555 6,378,066 0.1582 0.1644 0.1542 MS Dec Sun 4,165,179 2,346,770 6,260,737 0.1615 0.1505 0.1389 MS Dec Mon 3,980,279 2,569,066 8,105,561 0.1543 0.1648 0.1798 MS Dec Tue 3,854,472 2,566,199 7,311,023 0.1495 0.1646 0.1622 MS Dec Wed 3,359,960 2,132,483 6,471,988 0.1303 0.1368 0.1435 MS Dec Thu 3,395,266 2,018,285 5,948,199 0.1317 0.1294 0.1319 MS Dec Fri 3,506,671 2,023,650 5,728,721 0.1360 0.1298 0.1271 MS Dec Sat 3,526,047 1,937,249 5,261,466 0.1367 0.1242 0.1167 NC Jan Sun 11,560,761 4,249,277 9,886,708 0.1188 0.1147 0.1072 NC Jan Mon 12,574,135 4,827,083 11,673,165 0.1292 0.1303 0.1265 NC Jan Tue 15,914,366 5,976,859 14,437,971 0.1635 0.1613 0.1565 NC Jan Wed 16,265,175 6,180,766 16,052,916 0.1671 0.1668 0.1740 NC Jan Thu 15,906,990 6,067,725 15,819,307 0.1634 0.1638 0.1715 NC Jan Fri 12,722,270 5,026,049 13,149,759 0.1307 0.1356 0.1425 NC Jan Sat 12,388,186 4,725,877 11,235,081 0.1273 0.1275 0.1218 NC Feb Sun 11,253,673 3,991,235 9,863,838 0.1291 0.1275 0.1277 NC Feb Mon 13,019,558 4,745,266 12,077,127 0.1494 0.1516 0.1564 NC Feb Tue 13,131,342 4,727,808 11,411,117 0.1507 0.1510 0.1478 NC Feb Wed 12,697,796 4,649,147 11,442,703 0.1457 0.1485 0.1482 NC Feb Thu 12,755,297 4,761,010 12,182,443 0.1464 0.1521 0.1578 NC Feb Fri 12,543,945 4,351,743 10,497,224 0.1440 0.1390 0.1359 NC Feb Sat 11,735,833 4,079,787 9,745,618 0.1347 0.1303 0.1262 NC Mar Sun 13,215,914 4,396,336 10,507,879 0.1351 0.1308 0.1276 NC Mar Mon 13,109,591 4,680,045 12,123,509 0.1340 0.1392 0.1473 NC Mar Tue 13,489,418 4,803,912 12,457,110 0.1379 0.1429 0.1513 NC Mar Wed 13,251,851 4,629,968 11,247,320 0.1355 0.1377 0.1366 NC Mar Thu 13,003,971 4,452,547 10,611,013 0.1329 0.1324 0.1289 NC Mar Fri 16,099,512 5,471,485 13,239,143 0.1646 0.1627 0.1608 NC Mar Sat 15,662,956 5,186,547 12,137,290 0.1601 0.1543 0.1474 NC Apr Sun 10,365,527 3,419,497 8,537,340 0.1120 0.1085 0.1040 NC Apr Mon 15,778,590 5,363,049 14,204,953 0.1704 0.1702 0.1730 NC Apr Tue 16,016,035 5,633,374 15,421,565 0.1730 0.1788 0.1878 NC Apr Wed 12,837,940 4,348,243 11,661,251 0.1387 0.1380 0.1420 NC Apr Thu 13,058,838 4,448,763 11,453,508 0.1410 0.1412 0.1395 NC Apr Fri 12,672,336 4,394,180 11,092,891 0.1369 0.1395 0.1351 NC Apr Sat 11,854,316 3,903,067 9,742,692 0.1280 0.1239 0.1186 NC May Sun 10,567,915 3,460,975 10,014,907 0.1136 0.1117 0.1080 NC May Mon 11,380,064 3,829,182 11,589,806 0.1224 0.1235 0.1250 NC May Tue 11,927,341 4,012,583 12,246,904 0.1282 0.1295 0.1321 NC May Wed 15,656,917 5,171,053 15,443,752 0.1683 0.1668 0.1666 NC May Thu 15,919,175 5,248,882 15,559,076 0.1712 0.1694 0.1678 NC May Fri 15,768,764 5,307,036 15,945,613 0.1695 0.1712 0.1720 NC May Sat 11,790,435 3,963,302 11,901,876 0.1268 0.1279 0.1284 NC Jun Sun 13,367,053 4,138,287 12,252,759 0.1489 0.1479 0.1414

G-8Atmospheric Sciences Group 

### Appendix G Average 2000-2004 State Level Monthly-Day of Week Profiles

CEM-Based Distribution Alpine Geophysics

SO2 Mass NOx Mass Heat Input State Month Day of Week [lbs] [lbs] [MMBtu] SO2 Ratio NOx Ratio Heat Input Average Values [2000-2004] Calculated Ratios

NC Jun Mon 11,979,927 3,818,428 11,743,113 0.1334 0.1365 0.1355 NC Jun Tue 12,240,369 3,803,148 12,035,557 0.1363 0.1359 0.1389 NC Jun Wed 12,709,046 3,888,576 12,455,794 0.1416 0.1390 0.1437 NC Jun Thu 12,725,711 4,055,491 12,717,286 0.1417 0.1449 0.1468 NC Jun Fri 12,229,854 3,828,431 12,054,275 0.1362 0.1368 0.1391 NC Jun Sat 14,531,658 4,449,489 13,397,596 0.1619 0.1590 0.1546 NC Jul Sun 11,246,431 3,418,516 10,641,975 0.1167 0.1153 0.1112 NC Jul Mon 15,651,357 4,989,285 16,150,177 0.1624 0.1682 0.1688 NC Jul Tue 16,108,173 5,103,743 16,759,522 0.1671 0.1721 0.1752 NC Jul Wed 16,579,960 5,132,330 16,715,137 0.1720 0.1731 0.1747 NC Jul Thu 12,670,597 3,862,163 12,537,462 0.1315 0.1302 0.1311 NC Jul Fri 12,278,284 3,696,064 12,009,448 0.1274 0.1246 0.1255 NC Jul Sat 11,838,669 3,454,214 10,851,183 0.1228 0.1165 0.1134 NC Aug Sun 11,479,244 3,358,626 10,736,719 0.1170 0.1097 0.1094 NC Aug Mon 12,629,747 3,877,004 12,763,508 0.1287 0.1266 0.1301 NC Aug Tue 12,812,427 4,063,792 13,237,499 0.1306 0.1327 0.1349 NC Aug Wed 13,012,606 4,137,501 13,383,854 0.1326 0.1351 0.1364 NC Aug Thu 16,525,562 5,294,573 17,020,078 0.1684 0.1729 0.1735 NC Aug Fri 16,384,752 5,213,137 16,625,089 0.1670 0.1702 0.1695 NC Aug Sat 15,265,391 4,683,482 14,336,782 0.1556 0.1529 0.1461 NC Sep Sun 13,712,599 4,074,212 12,514,877 0.1518 0.1496 0.1482 NC Sep Mon 15,128,207 4,601,799 14,184,006 0.1675 0.1690 0.1679 NC Sep Tue 12,446,519 3,728,527 11,630,920 0.1378 0.1369 0.1377 NC Sep Wed 12,427,864 3,750,678 12,093,798 0.1376 0.1378 0.1432 NC Sep Thu 12,665,249 3,791,337 12,075,466 0.1402 0.1393 0.1430 NC Sep Fri 12,425,087 3,827,947 11,780,541 0.1376 0.1406 0.1395 NC Sep Sat 11,504,324 3,451,066 10,176,479 0.1274 0.1268 0.1205 NC Oct Sun 9,926,001 3,347,481 9,219,235 0.1066 0.1075 0.1106 NC Oct Mon 12,000,192 4,004,111 10,100,002 0.1289 0.1286 0.1212 NC Oct Tue 15,724,365 5,416,992 14,901,932 0.1689 0.1740 0.1788 NC Oct Wed 15,819,491 5,289,407 14,324,894 0.1700 0.1699 0.1719 NC Oct Thu 15,750,876 5,302,371 13,678,768 0.1692 0.1703 0.1641 NC Oct Fri 12,372,634 4,029,992 10,848,320 0.1329 0.1294 0.1301 NC Oct Sat 11,483,709 3,749,869 10,282,460 0.1234 0.1204 0.1234 NC Nov Sun 10,023,278 3,222,274 7,792,129 0.1114 0.1075 0.1068 NC Nov Mon 12,447,300 4,137,529 9,964,986 0.1384 0.1380 0.1366 NC Nov Tue 12,881,077 4,292,782 10,453,683 0.1432 0.1432 0.1433 NC Nov Wed 12,916,994 4,383,358 10,645,915 0.1436 0.1462 0.1460 NC Nov Thu 12,385,728 4,224,955 10,610,434 0.1377 0.1409 0.1455 NC Nov Fri 15,167,077 5,089,774 12,499,202 0.1686 0.1698 0.1714 NC Nov Sat 14,133,571 4,626,771 10,974,544 0.1571 0.1543 0.1505 NC Dec Sun 14,791,350 5,258,122 13,326,998 0.1505 0.1469 0.1371 NC Dec Mon 16,237,678 5,826,236 15,406,573 0.1652 0.1628 0.1585 NC Dec Tue 16,315,997 5,957,529 16,703,694 0.1660 0.1664 0.1719 NC Dec Wed 12,963,222 4,805,957 13,540,009 0.1319 0.1343 0.1393 NC Dec Thu 12,777,627 4,841,250 14,031,890 0.1300 0.1353 0.1444 NC Dec Fri 12,568,143 4,666,300 12,869,912 0.1279 0.1304 0.1324 NC Dec Sat 12,611,354 4,438,087 11,306,307 0.1283 0.1240 0.1163 SC Jan Sun 5,286,611 2,299,193 5,931,799 0.1209 0.1247 0.1196 SC Jan Mon 5,518,504 2,268,103 6,449,806 0.1262 0.1230 0.1301 SC Jan Tue 7,105,148 2,913,672 8,059,401 0.1625 0.1581 0.1626 SC Jan Wed 7,212,795 2,960,524 7,936,264 0.1650 0.1606 0.1601 SC Jan Thu 7,225,322 3,082,517 8,272,676 0.1653 0.1672 0.1669 SC Jan Fri 5,801,117 2,484,678 6,705,029 0.1327 0.1348 0.1352 SC Jan Sat 5,572,491 2,423,861 6,225,516 0.1275 0.1315 0.1256 SC Feb Sun 5,294,051 2,161,161 5,744,847 0.1374 0.1344 0.1329 SC Feb Mon 5,615,000 2,312,931 6,373,437 0.1457 0.1438 0.1474

G-9Atmospheric Sciences Group 

### Appendix G Average 2000-2004 State Level Monthly-Day of Week Profiles

CEM-Based Distribution Alpine Geophysics

SO2 Mass NOx Mass Heat Input State Month Day of Week [lbs] [lbs] [MMBtu] SO2 Ratio NOx Ratio Heat Input Average Values [2000-2004] Calculated Ratios

SC Feb Tue 5,605,890 2,374,050 6,441,940 0.1455 0.1476 0.1490 SC Feb Wed 5,521,102 2,343,140 6,387,296 0.1433 0.1457 0.1478 SC Feb Thu 5,670,915 2,389,128 6,494,850 0.1471 0.1485 0.1502 SC Feb Fri 5,519,594 2,264,999 6,018,260 0.1432 0.1408 0.1392 SC Feb Sat 5,314,483 2,239,090 5,766,696 0.1379 0.1392 0.1334 SC Mar Sun 6,243,777 2,481,381 6,574,279 0.1494 0.1471 0.1362 SC Mar Mon 5,571,915 2,290,581 6,793,033 0.1333 0.1358 0.1407 SC Mar Tue 5,614,590 2,298,253 7,164,458 0.1343 0.1363 0.1484 SC Mar Wed 5,581,053 2,241,721 6,668,461 0.1335 0.1329 0.1381 SC Mar Thu 5,493,948 2,242,960 6,140,967 0.1314 0.1330 0.1272 SC Mar Fri 6,744,831 2,705,745 7,629,740 0.1614 0.1604 0.1581 SC Mar Sat 6,548,817 2,603,100 7,300,062 0.1567 0.1544 0.1512 SC Apr Sun 4,866,897 2,025,673 5,514,502 0.1238 0.1243 0.1185 SC Apr Mon 6,582,528 2,761,303 7,892,285 0.1674 0.1694 0.1695 SC Apr Tue 6,553,751 2,764,562 7,577,646 0.1667 0.1696 0.1628 SC Apr Wed 5,420,705 2,235,667 6,541,198 0.1379 0.1371 0.1405 SC Apr Thu 5,434,929 2,229,200 6,735,259 0.1383 0.1367 0.1447 SC Apr Fri 5,360,997 2,172,034 6,328,859 0.1364 0.1332 0.1360 SC Apr Sat 5,091,734 2,114,032 5,960,624 0.1295 0.1297 0.1280 SC May Sun 4,956,438 2,200,048 6,729,759 0.1199 0.1200 0.1161 SC May Mon 5,224,306 2,306,267 7,328,601 0.1263 0.1257 0.1265 SC May Tue 5,372,448 2,355,685 7,528,493 0.1299 0.1284 0.1299 SC May Wed 6,740,001 2,976,890 9,452,710 0.1630 0.1623 0.1631 SC May Thu 6,940,903 3,066,999 9,693,933 0.1679 0.1672 0.1673 SC May Fri 6,854,306 3,105,902 9,864,722 0.1658 0.1693 0.1702 SC May Sat 5,260,209 2,329,552 7,356,176 0.1272 0.1270 0.1269 SC Jun Sun 6,383,589 2,577,662 8,188,890 0.1557 0.1564 0.1473 SC Jun Mon 5,372,449 2,221,814 7,396,371 0.1310 0.1348 0.1330 SC Jun Tue 5,536,697 2,198,447 7,589,704 0.1350 0.1334 0.1365 SC Jun Wed 5,581,008 2,243,382 7,845,895 0.1361 0.1361 0.1411 SC Jun Thu 5,597,302 2,280,841 7,803,034 0.1365 0.1384 0.1403 SC Jun Fri 5,633,901 2,247,249 7,688,499 0.1374 0.1363 0.1383 SC Jun Sat 6,892,963 2,715,688 9,095,953 0.1681 0.1647 0.1636 SC Jul Sun 5,413,887 2,117,128 7,170,967 0.1234 0.1228 0.1221 SC Jul Mon 7,085,887 2,816,784 9,552,726 0.1615 0.1634 0.1626 SC Jul Tue 7,204,088 2,859,286 9,856,055 0.1642 0.1658 0.1678 SC Jul Wed 7,243,156 2,903,936 9,808,396 0.1651 0.1684 0.1670 SC Jul Thu 5,771,911 2,239,458 7,676,462 0.1316 0.1299 0.1307 SC Jul Fri 5,688,169 2,228,514 7,570,468 0.1297 0.1293 0.1289 SC Jul Sat 5,460,312 2,075,704 7,106,750 0.1245 0.1204 0.1210 SC Aug Sun 5,482,755 2,037,311 7,317,015 0.1228 0.1191 0.1248 SC Aug Mon 5,756,711 2,192,128 7,666,671 0.1289 0.1281 0.1307 SC Aug Tue 5,812,452 2,179,431 7,552,200 0.1302 0.1274 0.1288 SC Aug Wed 5,847,602 2,245,012 7,592,610 0.1310 0.1312 0.1295 SC Aug Thu 7,349,689 2,913,385 9,792,236 0.1646 0.1703 0.1670 SC Aug Fri 7,338,728 2,861,283 9,655,335 0.1644 0.1672 0.1646 SC Aug Sat 7,063,443 2,681,552 9,068,522 0.1582 0.1567 0.1546 SC Sep Sun 6,339,672 2,424,941 7,471,183 0.1572 0.1566 0.1466 SC Sep Mon 6,787,257 2,657,781 8,685,323 0.1683 0.1717 0.1704 SC Sep Tue 5,388,827 2,077,370 7,061,264 0.1336 0.1342 0.1385 SC Sep Wed 5,472,142 2,087,907 7,133,322 0.1357 0.1349 0.1399 SC Sep Thu 5,569,864 2,100,333 7,160,117 0.1381 0.1357 0.1405 SC Sep Fri 5,483,049 2,110,868 7,101,504 0.1360 0.1364 0.1393 SC Sep Sat 5,282,229 2,021,866 6,365,447 0.1310 0.1306 0.1249 SC Oct Sun 5,151,806 1,929,694 5,751,902 0.1210 0.1198 0.1196 SC Oct Mon 5,549,253 2,115,276 6,066,443 0.1304 0.1314 0.1262 SC Oct Tue 6,997,266 2,674,898 7,877,912 0.1644 0.1661 0.1638

G-10Atmospheric Sciences Group 

### Appendix G Average 2000-2004 State Level Monthly-Day of Week Profiles

CEM-Based Distribution Alpine Geophysics

SO2 Mass NOx Mass Heat Input State Month Day of Week [lbs] [lbs] [MMBtu] SO2 Ratio NOx Ratio Heat Input Average Values [2000-2004] Calculated Ratios

SC Oct Wed 6,894,938 2,655,754 8,340,717 0.1620 0.1649 0.1735 SC Oct Thu 6,986,528 2,639,916 7,522,795 0.1642 0.1640 0.1564 SC Oct Fri 5,491,463 2,044,827 6,110,234 0.1290 0.1270 0.1271 SC Oct Sat 5,489,541 2,041,458 6,417,078 0.1290 0.1268 0.1334 SC Nov Sun 5,303,068 1,987,453 5,023,639 0.1259 0.1270 0.1122 SC Nov Mon 5,595,362 2,093,756 6,380,031 0.1328 0.1338 0.1425 SC Nov Tue 5,920,911 2,160,967 6,713,867 0.1405 0.1381 0.1500 SC Nov Wed 5,810,872 2,172,297 6,727,295 0.1379 0.1388 0.1503 SC Nov Thu 5,716,637 2,122,812 6,301,654 0.1357 0.1356 0.1408 SC Nov Fri 6,991,739 2,559,269 7,160,715 0.1660 0.1635 0.1600 SC Nov Sat 6,791,311 2,553,023 6,455,234 0.1612 0.1631 0.1442 SC Dec Sun 7,036,662 2,681,721 7,352,493 0.1577 0.1571 0.1445 SC Dec Mon 7,256,042 2,832,586 9,388,765 0.1626 0.1660 0.1845 SC Dec Tue 7,256,788 2,771,868 8,759,465 0.1626 0.1624 0.1721 SC Dec Wed 5,797,730 2,196,236 6,716,005 0.1299 0.1287 0.1320 SC Dec Thu 5,798,886 2,203,624 6,558,441 0.1300 0.1291 0.1289 SC Dec Fri 5,699,841 2,175,738 6,092,912 0.1277 0.1275 0.1197 SC Dec Sat 5,771,520 2,203,060 6,019,090 0.1294 0.1291 0.1183 TN Jan Sun 9,099,686 4,091,623 7,860,007 0.1271 0.1260 0.1114 TN Jan Mon 9,350,839 4,087,116 8,986,290 0.1306 0.1259 0.1274 TN Jan Tue 11,592,830 5,207,451 11,639,003 0.1619 0.1604 0.1650 TN Jan Wed 11,485,493 5,331,473 11,741,383 0.1604 0.1642 0.1664 TN Jan Thu 11,505,996 5,297,978 12,272,227 0.1607 0.1632 0.1740 TN Jan Fri 9,376,798 4,287,250 9,623,665 0.1309 0.1321 0.1364 TN Jan Sat 9,196,527 4,160,758 8,421,408 0.1284 0.1282 0.1194 TN Feb Sun 8,800,773 3,967,147 7,600,561 0.1387 0.1391 0.1315 TN Feb Mon 9,159,306 4,100,701 8,568,313 0.1444 0.1438 0.1482 TN Feb Tue 9,247,034 4,127,780 8,596,687 0.1457 0.1447 0.1487 TN Feb Wed 9,117,262 4,204,190 8,935,096 0.1437 0.1474 0.1546 TN Feb Thu 9,052,507 4,072,547 8,333,834 0.1427 0.1428 0.1442 TN Feb Fri 9,083,992 4,056,706 7,977,179 0.1432 0.1423 0.1380 TN Feb Sat 8,986,225 3,987,899 7,796,234 0.1416 0.1398 0.1349 TN Mar Sun 10,966,197 4,760,105 9,351,965 0.1560 0.1546 0.1485 TN Mar Mon 9,143,307 3,993,837 8,990,902 0.1301 0.1297 0.1428 TN Mar Tue 9,182,937 4,060,570 8,406,031 0.1307 0.1319 0.1335 TN Mar Wed 9,185,207 4,030,563 8,357,946 0.1307 0.1309 0.1327 TN Mar Thu 9,231,709 4,035,004 8,255,316 0.1313 0.1311 0.1311 TN Mar Fri 11,389,629 5,003,488 10,084,990 0.1620 0.1625 0.1601 TN Mar Sat 11,186,046 4,905,757 9,530,974 0.1592 0.1593 0.1513 TN Apr Sun 8,560,160 3,801,188 7,498,187 0.1275 0.1287 0.1204 TN Apr Mon 11,203,790 4,969,527 10,454,039 0.1669 0.1682 0.1679 TN Apr Tue 11,446,890 5,015,504 10,762,527 0.1706 0.1698 0.1729 TN Apr Wed 8,997,027 3,972,060 8,745,116 0.1341 0.1344 0.1405 TN Apr Thu 9,067,307 3,974,330 8,751,285 0.1351 0.1345 0.1406 TN Apr Fri 8,946,817 3,889,910 8,149,838 0.1333 0.1317 0.1309 TN Apr Sat 8,893,112 3,921,629 7,902,956 0.1325 0.1327 0.1269 TN May Sun 8,403,065 3,567,755 8,320,215 0.1243 0.1180 0.1125 TN May Mon 8,539,591 3,716,083 9,348,867 0.1263 0.1229 0.1265 TN May Tue 8,817,207 3,898,796 9,335,224 0.1304 0.1289 0.1263 TN May Wed 11,087,808 4,969,226 12,093,631 0.1640 0.1643 0.1636 TN May Thu 10,990,628 5,056,791 12,579,593 0.1626 0.1672 0.1702 TN May Fri 11,052,801 5,165,825 12,864,637 0.1635 0.1708 0.1740 TN May Sat 8,713,746 3,865,517 9,382,473 0.1289 0.1278 0.1269 TN Jun Sun 10,393,098 4,533,967 11,156,081 0.1599 0.1644 0.1594 TN Jun Mon 8,711,697 3,725,581 9,783,408 0.1340 0.1351 0.1398 TN Jun Tue 8,741,729 3,627,897 9,459,498 0.1345 0.1316 0.1352 TN Jun Wed 8,766,721 3,631,756 9,539,806 0.1349 0.1317 0.1363

G-11Atmospheric Sciences Group 

### Appendix G Average 2000-2004 State Level Monthly-Day of Week Profiles

CEM-Based Distribution Alpine Geophysics

SO2 Mass NOx Mass Heat Input State Month Day of Week [lbs] [lbs] [MMBtu] SO2 Ratio NOx Ratio Heat Input Average Values [2000-2004] Calculated Ratios

TN Jun Thu 8,848,458 3,742,830 9,620,040 0.1361 0.1358 0.1375 TN Jun Fri 8,762,875 3,790,104 9,262,557 0.1348 0.1375 0.1324 TN Jun Sat 10,770,608 4,518,386 11,161,866 0.1657 0.1639 0.1595 TN Jul Sun 8,894,036 3,579,627 9,352,175 0.1287 0.1257 0.1237 TN Jul Mon 11,252,738 4,697,567 12,710,610 0.1628 0.1650 0.1681 TN Jul Tue 11,137,713 4,767,180 12,778,672 0.1611 0.1674 0.1690 TN Jul Wed 11,200,250 4,781,047 12,540,421 0.1621 0.1679 0.1658 TN Jul Thu 8,854,548 3,652,058 9,565,743 0.1281 0.1283 0.1265 TN Jul Fri 8,854,281 3,501,416 9,340,928 0.1281 0.1230 0.1235 TN Jul Sat 8,921,698 3,493,570 9,339,060 0.1291 0.1227 0.1235 TN Aug Sun 8,473,075 3,359,083 8,744,330 0.1242 0.1202 0.1158 TN Aug Mon 8,749,130 3,521,647 9,755,649 0.1283 0.1261 0.1292 TN Aug Tue 8,913,755 3,615,783 9,963,585 0.1307 0.1294 0.1320 TN Aug Wed 8,964,350 3,725,019 9,943,413 0.1314 0.1333 0.1317 TN Aug Thu 11,193,413 4,717,520 12,762,471 0.1641 0.1689 0.1691 TN Aug Fri 10,997,095 4,615,603 12,369,001 0.1612 0.1652 0.1639 TN Aug Sat 10,912,952 4,383,365 11,944,515 0.1600 0.1569 0.1582 TN Sep Sun 10,404,619 4,343,533 10,196,585 0.1625 0.1656 0.1530 TN Sep Mon 10,676,388 4,428,210 11,176,536 0.1667 0.1689 0.1677 TN Sep Tue 8,551,785 3,567,888 9,085,899 0.1336 0.1361 0.1363 TN Sep Wed 8,498,673 3,440,180 9,105,219 0.1327 0.1312 0.1366 TN Sep Thu 8,615,031 3,408,390 9,133,138 0.1346 0.1300 0.1370 TN Sep Fri 8,756,376 3,556,133 9,246,219 0.1368 0.1356 0.1387 TN Sep Sat 8,525,133 3,478,882 8,714,045 0.1331 0.1327 0.1307 TN Oct Sun 8,531,840 3,835,755 7,772,483 0.1269 0.1266 0.1222 TN Oct Mon 8,892,684 3,950,484 8,309,721 0.1323 0.1304 0.1307 TN Oct Tue 10,917,649 4,858,337 10,314,372 0.1624 0.1603 0.1622 TN Oct Wed 10,773,156 4,936,690 10,827,798 0.1603 0.1629 0.1702 TN Oct Thu 10,901,265 4,951,409 10,418,961 0.1622 0.1634 0.1638 TN Oct Fri 8,672,179 3,928,690 8,161,391 0.1290 0.1297 0.1283 TN Oct Sat 8,518,967 3,840,721 7,795,377 0.1268 0.1267 0.1226 TN Nov Sun 8,241,119 3,919,519 7,683,311 0.1281 0.1305 0.1261 TN Nov Mon 8,660,832 4,016,217 8,330,173 0.1346 0.1338 0.1367 TN Nov Tue 8,692,746 4,018,035 8,354,128 0.1351 0.1338 0.1371 TN Nov Wed 8,831,053 4,072,301 8,375,377 0.1372 0.1356 0.1375 TN Nov Thu 8,819,830 4,107,426 8,125,227 0.1371 0.1368 0.1334 TN Nov Fri 10,672,438 4,930,921 10,247,631 0.1658 0.1642 0.1682 TN Nov Sat 10,433,116 4,960,736 9,814,868 0.1621 0.1652 0.1611 TN Dec Sun 10,493,511 5,080,387 9,970,039 0.1607 0.1607 0.1565 TN Dec Mon 10,472,176 5,047,077 10,091,372 0.1604 0.1597 0.1584 TN Dec Tue 10,364,186 5,053,370 10,218,924 0.1587 0.1598 0.1604 TN Dec Wed 8,430,160 4,133,341 8,447,439 0.1291 0.1307 0.1326 TN Dec Thu 8,400,272 4,064,361 8,215,987 0.1286 0.1286 0.1290 TN Dec Fri 8,538,944 4,171,606 8,609,539 0.1308 0.1320 0.1352 TN Dec Sat 8,605,180 4,063,075 8,138,063 0.1318 0.1285 0.1278 VA Jan Sun 5,811,765 2,316,017 7,616,300 0.1190 0.1197 0.1244 VA Jan Mon 6,211,403 2,485,527 7,917,891 0.1272 0.1284 0.1294 VA Jan Tue 7,940,198 3,138,739 9,712,340 0.1626 0.1622 0.1587 VA Jan Wed 8,024,931 3,204,521 10,072,675 0.1644 0.1656 0.1646 VA Jan Thu 8,113,493 3,186,724 9,926,427 0.1662 0.1646 0.1622 VA Jan Fri 6,460,028 2,592,834 8,413,562 0.1323 0.1340 0.1375 VA Jan Sat 6,258,098 2,430,307 7,542,331 0.1282 0.1256 0.1232 VA Feb Sun 5,807,914 2,167,826 6,825,013 0.1368 0.1345 0.1363 VA Feb Mon 6,350,995 2,452,208 7,696,337 0.1496 0.1521 0.1537 VA Feb Tue 6,219,530 2,418,822 7,435,721 0.1465 0.1500 0.1485 VA Feb Wed 6,140,607 2,358,956 7,187,303 0.1446 0.1463 0.1436 VA Feb Thu 6,247,503 2,395,843 7,595,661 0.1471 0.1486 0.1517

G-12Atmospheric Sciences Group 

### Appendix G Average 2000-2004 State Level Monthly-Day of Week Profiles

CEM-Based Distribution Alpine Geophysics

SO2 Mass NOx Mass Heat Input State Month Day of Week [lbs] [lbs] [MMBtu] SO2 Ratio NOx Ratio Heat Input Average Values [2000-2004] Calculated Ratios

VA Feb Fri 5,958,249 2,218,883 6,858,750 0.1403 0.1376 0.1370 VA Feb Sat 5,734,408 2,108,150 6,461,103 0.1351 0.1308 0.1291 VA Mar Sun 6,546,714 2,460,961 7,210,271 0.1410 0.1397 0.1375 VA Mar Mon 6,199,479 2,422,357 7,382,697 0.1335 0.1376 0.1407 VA Mar Tue 6,467,668 2,472,571 7,695,216 0.1393 0.1404 0.1467 VA Mar Wed 6,285,724 2,391,185 7,319,783 0.1353 0.1358 0.1395 VA Mar Thu 6,219,394 2,338,411 6,727,654 0.1339 0.1328 0.1283 VA Mar Fri 7,586,557 2,841,834 8,251,167 0.1633 0.1614 0.1573 VA Mar Sat 7,140,328 2,682,658 7,869,685 0.1537 0.1523 0.1500 VA Apr Sun 5,372,630 1,885,933 5,689,911 0.1182 0.1111 0.1023 VA Apr Mon 7,705,227 2,927,979 9,715,459 0.1696 0.1725 0.1746 VA Apr Tue 7,721,008 3,004,679 10,378,295 0.1699 0.1770 0.1865 VA Apr Wed 6,305,442 2,407,495 8,290,264 0.1388 0.1418 0.1490 VA Apr Thu 6,439,621 2,426,647 8,198,125 0.1417 0.1429 0.1473 VA Apr Fri 6,095,372 2,276,176 7,413,038 0.1342 0.1341 0.1332 VA Apr Sat 5,795,340 2,049,349 5,953,890 0.1276 0.1207 0.1070 VA May Sun 5,016,098 2,303,849 8,186,499 0.1127 0.1136 0.1165 VA May Mon 5,618,443 2,483,055 9,338,456 0.1262 0.1225 0.1329 VA May Tue 5,887,808 2,662,709 9,429,232 0.1323 0.1313 0.1342 VA May Wed 7,492,377 3,701,360 11,942,285 0.1683 0.1825 0.1699 VA May Thu 7,331,220 3,231,990 10,860,283 0.1647 0.1594 0.1545 VA May Fri 7,617,544 3,513,772 11,906,835 0.1711 0.1733 0.1694 VA May Sat 5,546,558 2,380,483 8,609,908 0.1246 0.1174 0.1225 VA Jun Sun 6,513,553 2,944,360 8,979,026 0.1469 0.1579 0.1378 VA Jun Mon 5,944,473 2,397,677 8,636,259 0.1341 0.1286 0.1326 VA Jun Tue 6,003,344 2,404,199 9,085,917 0.1354 0.1290 0.1395 VA Jun Wed 6,290,346 2,771,395 9,628,014 0.1419 0.1486 0.1478 VA Jun Thu 6,247,335 2,822,810 9,834,003 0.1409 0.1514 0.1509 VA Jun Fri 6,138,069 2,382,480 8,912,624 0.1384 0.1278 0.1368 VA Jun Sat 7,199,701 2,920,958 10,076,854 0.1624 0.1567 0.1547 VA Jul Sun 5,503,862 2,224,650 8,312,789 0.1168 0.1191 0.1157 VA Jul Mon 7,633,800 3,278,534 12,325,491 0.1620 0.1755 0.1715 VA Jul Tue 7,823,761 3,126,318 12,341,767 0.1661 0.1673 0.1718 VA Jul Wed 7,952,170 3,092,320 12,102,055 0.1688 0.1655 0.1684 VA Jul Thu 6,287,319 2,419,804 9,400,829 0.1334 0.1295 0.1308 VA Jul Fri 6,140,261 2,380,424 9,079,155 0.1303 0.1274 0.1264 VA Jul Sat 5,774,825 2,163,984 8,290,648 0.1226 0.1158 0.1154 VA Aug Sun 5,448,930 2,097,174 8,196,327 0.1158 0.1069 0.1093 VA Aug Mon 6,139,944 2,465,314 9,840,814 0.1304 0.1257 0.1312 VA Aug Tue 6,193,758 2,612,080 10,136,460 0.1316 0.1332 0.1352 VA Aug Wed 6,186,308 2,620,372 9,968,553 0.1314 0.1336 0.1329 VA Aug Thu 7,809,322 3,289,728 12,666,064 0.1659 0.1677 0.1689 VA Aug Fri 7,865,395 3,581,866 13,016,442 0.1671 0.1826 0.1736 VA Aug Sat 7,428,011 2,947,669 11,157,963 0.1578 0.1503 0.1488 VA Sep Sun 6,177,672 2,488,478 8,731,469 0.1489 0.1500 0.1439 VA Sep Mon 7,109,030 2,890,060 10,904,947 0.1713 0.1742 0.1797 VA Sep Tue 5,928,175 2,381,555 8,626,984 0.1429 0.1435 0.1421 VA Sep Wed 5,932,703 2,271,312 8,613,889 0.1430 0.1369 0.1419 VA Sep Thu 5,889,653 2,273,535 8,570,257 0.1420 0.1370 0.1412 VA Sep Fri 5,437,800 2,220,372 7,955,577 0.1311 0.1338 0.1311 VA Sep Sat 5,013,585 2,069,804 7,287,614 0.1208 0.1247 0.1201 VA Oct Sun 4,771,469 1,784,307 5,367,161 0.1141 0.1102 0.1089 VA Oct Mon 5,414,776 2,165,936 6,569,238 0.1294 0.1337 0.1333 VA Oct Tue 7,072,886 2,772,936 8,419,584 0.1691 0.1712 0.1708 VA Oct Wed 7,030,678 2,680,581 8,274,150 0.1681 0.1655 0.1679 VA Oct Thu 6,960,514 2,691,664 8,339,010 0.1664 0.1662 0.1692 VA Oct Fri 5,531,903 2,160,818 6,476,213 0.1322 0.1334 0.1314

G-13Atmospheric Sciences Group 

### Appendix G Average 2000-2004 State Level Monthly-Day of Week Profiles

CEM-Based Distribution Alpine Geophysics

SO2 Mass NOx Mass Heat Input State Month Day of Week [lbs] [lbs] [MMBtu] SO2 Ratio NOx Ratio Heat Input Average Values [2000-2004] Calculated Ratios

VA Oct Sat 5,052,803 1,939,255 5,841,623 0.1208 0.1197 0.1185 VA Nov Sun 4,951,164 1,817,900 5,508,618 0.1146 0.1103 0.1051 VA Nov Mon 5,894,107 2,288,508 7,448,643 0.1365 0.1389 0.1421 VA Nov Tue 6,154,674 2,395,715 8,186,811 0.1425 0.1454 0.1562 VA Nov Wed 6,258,978 2,403,829 7,844,902 0.1449 0.1459 0.1496 VA Nov Thu 5,847,652 2,232,942 7,199,537 0.1354 0.1355 0.1373 VA Nov Fri 7,594,341 2,888,008 8,967,164 0.1758 0.1753 0.1711 VA Nov Sat 6,493,259 2,451,598 7,267,207 0.1503 0.1488 0.1386 VA Dec Sun 7,487,546 2,806,711 8,422,661 0.1571 0.1502 0.1407 VA Dec Mon 7,706,240 3,188,365 11,274,103 0.1617 0.1706 0.1883 VA Dec Tue 7,650,735 2,999,800 9,868,823 0.1605 0.1605 0.1648 VA Dec Wed 6,147,705 2,394,021 7,657,538 0.1290 0.1281 0.1279 VA Dec Thu 6,246,331 2,471,379 7,814,089 0.1310 0.1323 0.1305 VA Dec Fri 6,214,437 2,470,674 7,691,748 0.1304 0.1322 0.1285 VA Dec Sat 6,215,963 2,354,510 7,147,977 0.1304 0.1260 0.1194 WV Jan Sun 13,100,315 5,799,646 10,867,329 0.1171 0.1114 0.1172 WV Jan Mon 14,362,750 6,742,714 12,003,777 0.1284 0.1296 0.1294 WV Jan Tue 18,380,394 8,731,334 15,294,185 0.1643 0.1678 0.1649 WV Jan Wed 18,649,891 8,753,658 15,342,028 0.1667 0.1682 0.1654 WV Jan Thu 18,460,881 8,670,949 15,363,013 0.1650 0.1666 0.1656 WV Jan Fri 14,751,419 6,880,007 12,181,754 0.1319 0.1322 0.1313 WV Jan Sat 14,170,249 6,464,543 11,705,645 0.1267 0.1242 0.1262 WV Feb Sun 13,515,091 6,243,479 11,396,913 0.1334 0.1314 0.1345 WV Feb Mon 14,644,850 6,934,137 12,277,541 0.1445 0.1459 0.1449 WV Feb Tue 14,828,460 6,946,924 12,430,932 0.1463 0.1462 0.1467 WV Feb Wed 14,759,293 6,959,149 12,305,147 0.1456 0.1464 0.1452 WV Feb Thu 14,609,084 6,915,589 12,214,470 0.1442 0.1455 0.1442 WV Feb Fri 14,583,419 6,820,286 12,151,113 0.1439 0.1435 0.1434 WV Feb Sat 14,404,898 6,712,438 11,949,578 0.1421 0.1412 0.1410 WV Mar Sun 16,122,515 7,236,109 13,753,265 0.1465 0.1445 0.1489 WV Mar Mon 14,519,230 6,825,535 12,576,681 0.1320 0.1363 0.1362 WV Mar Tue 14,710,069 6,798,174 12,342,614 0.1337 0.1357 0.1337 WV Mar Wed 14,856,321 6,663,871 12,085,672 0.1350 0.1331 0.1309 WV Mar Thu 14,806,603 6,772,985 12,285,137 0.1346 0.1352 0.1330 WV Mar Fri 17,926,131 8,136,390 14,944,895 0.1629 0.1625 0.1619 WV Mar Sat 17,081,123 7,649,154 14,349,306 0.1553 0.1527 0.1554 WV Apr Sun 12,659,911 5,616,755 10,711,173 0.1214 0.1173 0.1197 WV Apr Mon 17,613,006 8,128,426 15,122,209 0.1689 0.1697 0.1691 WV Apr Tue 17,929,618 8,331,690 15,445,939 0.1719 0.1739 0.1727 WV Apr Wed 14,445,569 6,673,004 12,480,197 0.1385 0.1393 0.1395 WV Apr Thu 14,237,092 6,681,897 12,404,167 0.1365 0.1395 0.1387 WV Apr Fri 13,967,495 6,422,716 11,926,943 0.1339 0.1341 0.1333 WV Apr Sat 13,444,678 6,047,689 11,362,797 0.1289 0.1263 0.1270 WV May Sun 11,759,655 4,646,889 10,863,241 0.1127 0.1116 0.1174 WV May Mon 13,257,241 5,319,864 11,860,681 0.1270 0.1278 0.1282 WV May Tue 14,019,375 5,696,886 12,212,949 0.1343 0.1369 0.1320 WV May Wed 17,425,095 7,041,737 15,343,080 0.1670 0.1692 0.1658 WV May Thu 17,510,110 7,006,274 15,483,728 0.1678 0.1683 0.1673 WV May Fri 17,612,584 6,869,355 15,321,354 0.1688 0.1650 0.1656 WV May Sat 12,775,798 5,043,687 11,454,445 0.1224 0.1212 0.1238 WV Jun Sun 14,957,872 5,513,227 13,450,208 0.1499 0.1496 0.1520 WV Jun Mon 13,487,078 4,966,344 12,093,706 0.1352 0.1347 0.1367 WV Jun Tue 13,810,046 4,924,808 12,328,120 0.1384 0.1336 0.1394 WV Jun Wed 14,035,209 5,019,365 12,246,507 0.1407 0.1362 0.1384 WV Jun Thu 13,971,661 5,248,525 12,289,497 0.1400 0.1424 0.1389 WV Jun Fri 13,647,530 5,202,625 11,944,391 0.1368 0.1412 0.1350 WV Jun Sat 15,853,200 5,982,734 14,108,354 0.1589 0.1623 0.1595

G-14Atmospheric Sciences Group 

### Appendix G Average 2000-2004 State Level Monthly-Day of Week Profiles

CEM-Based Distribution Alpine Geophysics

SO2 Mass NOx Mass Heat Input State Month Day of Week [lbs] [lbs] [MMBtu] SO2 Ratio NOx Ratio Heat Input Average Values [2000-2004] Calculated Ratios

WV Jul Sun 12,579,090 4,859,371 11,483,663 0.1214 0.1244 0.1212 WV Jul Mon 16,922,966 6,628,216 15,654,385 0.1633 0.1697 0.1653 WV Jul Tue 16,829,969 6,510,534 15,642,798 0.1624 0.1667 0.1652 WV Jul Wed 16,922,109 6,356,022 15,616,084 0.1633 0.1628 0.1649 WV Jul Thu 13,767,564 4,995,695 12,445,189 0.1328 0.1279 0.1314 WV Jul Fri 13,765,831 4,996,420 12,282,163 0.1328 0.1280 0.1297 WV Jul Sat 12,864,639 4,702,083 11,594,157 0.1241 0.1204 0.1224 WV Aug Sun 12,420,738 4,243,325 11,548,441 0.1180 0.1124 0.1193 WV Aug Mon 13,711,685 4,876,761 12,698,726 0.1303 0.1292 0.1312 WV Aug Tue 13,802,245 4,932,803 12,778,560 0.1311 0.1307 0.1321 WV Aug Wed 13,982,519 5,203,299 12,734,042 0.1329 0.1378 0.1316 WV Aug Thu 17,526,678 6,525,344 16,118,431 0.1665 0.1729 0.1666 WV Aug Fri 17,375,999 6,269,445 16,109,397 0.1651 0.1661 0.1665 WV Aug Sat 16,421,084 5,700,325 14,781,627 0.1560 0.1510 0.1528 WV Sep Sun 15,387,791 5,583,374 14,178,712 0.1530 0.1541 0.1558 WV Sep Mon 16,479,807 5,987,538 15,060,884 0.1639 0.1653 0.1655 WV Sep Tue 13,653,144 4,977,030 12,477,507 0.1358 0.1374 0.1371 WV Sep Wed 13,978,860 4,854,370 12,357,544 0.1390 0.1340 0.1358 WV Sep Thu 13,844,610 4,851,874 12,422,717 0.1377 0.1339 0.1365 WV Sep Fri 13,973,475 5,127,295 12,521,330 0.1390 0.1415 0.1376 WV Sep Sat 13,230,214 4,848,814 11,984,616 0.1316 0.1338 0.1317 WV Oct Sun 11,795,713 5,328,806 10,519,418 0.1133 0.1112 0.1156 WV Oct Mon 13,506,437 6,360,933 11,820,770 0.1297 0.1327 0.1299 WV Oct Tue 17,397,758 8,030,289 15,157,209 0.1671 0.1675 0.1666 WV Oct Wed 17,332,497 7,975,342 15,086,415 0.1664 0.1664 0.1658 WV Oct Thu 17,546,866 8,115,257 15,238,555 0.1685 0.1693 0.1675 WV Oct Fri 14,025,759 6,395,999 11,980,650 0.1347 0.1334 0.1317 WV Oct Sat 12,529,159 5,721,977 11,175,454 0.1203 0.1194 0.1228 WV Nov Sun 12,129,792 5,619,696 10,631,285 0.1192 0.1169 0.1215 WV Nov Mon 13,864,511 6,604,163 11,913,288 0.1362 0.1373 0.1361 WV Nov Tue 14,354,084 6,781,122 12,170,429 0.1410 0.1410 0.1391 WV Nov Wed 14,405,997 6,847,447 12,275,110 0.1415 0.1424 0.1403 WV Nov Thu 13,730,088 6,400,457 11,689,312 0.1349 0.1331 0.1336 WV Nov Fri 17,117,867 8,198,832 14,796,047 0.1682 0.1705 0.1691 WV Nov Sat 16,186,882 7,639,304 14,026,213 0.1590 0.1589 0.1603 WV Dec Sun 15,617,799 7,200,553 13,529,804 0.1491 0.1460 0.1499 WV Dec Mon 16,601,004 7,918,361 14,743,758 0.1585 0.1606 0.1634 WV Dec Tue 17,036,342 8,066,876 14,717,030 0.1626 0.1636 0.1631 WV Dec Wed 13,898,570 6,561,202 11,840,873 0.1327 0.1331 0.1312 WV Dec Thu 14,069,657 6,626,904 11,884,163 0.1343 0.1344 0.1317 WV Dec Fri 14,040,201 6,649,697 12,003,729 0.1340 0.1349 0.1330 WV Dec Sat 13,500,681 6,282,373 11,515,891 0.1289 0.1274 0.1276

G-15Atmospheric Sciences Group 

### Appendix H Average 2000-2004 State Level Monthly-Diurnal Profiles

CEM-Based Distribution Alpine Geophysics

SO2 Mass NOx Mass Heat Input State Month Hour [lbs] [lbs] [MMBtu] SO2 Ratio NOx Ratio Heat Input AL Jan 0 3,832,622 1,392,784 4,120,769 0.0395 0.0391 0.0387 AL Jan 1 3,809,746 1,388,794 4,104,496 0.0393 0.0390 0.0385 AL Jan 2 3,837,326 1,409,897 4,181,432 0.0396 0.0396 0.0392 AL Jan 3 3,872,244 1,416,932 4,244,428 0.0399 0.0398 0.0398 AL Jan 4 3,954,578 1,442,167 4,360,856 0.0408 0.0405 0.0409 AL Jan 5 4,058,942 1,485,648 4,575,472 0.0419 0.0417 0.0429 AL Jan 6 4,146,714 1,523,527 4,732,549 0.0428 0.0428 0.0444 AL Jan 7 4,144,066 1,535,797 4,686,268 0.0428 0.0432 0.0440 AL Jan 8 4,154,152 1,527,650 4,662,311 0.0429 0.0429 0.0437 AL Jan 9 4,197,324 1,541,262 4,646,238 0.0433 0.0433 0.0436 AL Jan 10 4,144,211 1,536,368 4,568,193 0.0428 0.0432 0.0429 AL Jan 11 4,106,061 1,520,068 4,516,912 0.0424 0.0427 0.0424 AL Jan 12 4,072,688 1,502,952 4,430,110 0.0420 0.0422 0.0416 AL Jan 13 4,004,292 1,471,843 4,338,987 0.0413 0.0414 0.0407 AL Jan 14 3,946,062 1,451,861 4,298,092 0.0407 0.0408 0.0403 AL Jan 15 3,949,273 1,448,804 4,285,043 0.0407 0.0407 0.0402 AL Jan 16 4,004,065 1,472,030 4,367,663 0.0413 0.0414 0.0410 AL Jan 17 4,121,578 1,522,913 4,569,818 0.0425 0.0428 0.0429 AL Jan 18 4,163,180 1,529,167 4,629,152 0.0430 0.0430 0.0434 AL Jan 19 4,136,097 1,515,161 4,571,459 0.0427 0.0426 0.0429 AL Jan 20 4,145,700 1,519,543 4,577,690 0.0428 0.0427 0.0429 AL Jan 21 4,125,600 1,511,622 4,521,593 0.0426 0.0425 0.0424 AL Jan 22 4,060,942 1,489,296 4,386,027 0.0419 0.0418 0.0411 AL Jan 23 3,942,804 1,431,564 4,232,162 0.0407 0.0402 0.0397 AL Feb 0 3,533,625 1,253,887 3,594,975 0.0396 0.0395 0.0389 AL Feb 1 3,487,513 1,236,149 3,548,210 0.0391 0.0390 0.0384 AL Feb 2 3,483,693 1,239,510 3,560,034 0.0390 0.0391 0.0386 AL Feb 3 3,539,241 1,250,195 3,664,698 0.0396 0.0394 0.0397 AL Feb 4 3,650,176 1,285,888 3,808,325 0.0409 0.0405 0.0413 AL Feb 5 3,760,946 1,330,454 3,964,089 0.0421 0.0420 0.0429 AL Feb 6 3,838,201 1,371,166 4,116,946 0.0430 0.0432 0.0446 AL Feb 7 3,850,449 1,374,094 4,099,473 0.0431 0.0433 0.0444 AL Feb 8 3,807,644 1,369,131 4,026,312 0.0426 0.0432 0.0436 AL Feb 9 3,827,781 1,366,508 3,973,960 0.0429 0.0431 0.0430 AL Feb 10 3,820,790 1,350,468 3,939,317 0.0428 0.0426 0.0427 AL Feb 11 3,818,017 1,344,208 3,929,298 0.0428 0.0424 0.0426 AL Feb 12 3,763,616 1,323,974 3,862,170 0.0421 0.0417 0.0418 AL Feb 13 3,716,580 1,308,905 3,794,748 0.0416 0.0413 0.0411 AL Feb 14 3,707,376 1,308,841 3,783,297 0.0415 0.0413 0.0410 AL Feb 15 3,713,519 1,309,785 3,785,935 0.0416 0.0413 0.0410 AL Feb 16 3,731,767 1,322,800 3,814,771 0.0418 0.0417 0.0413 AL Feb 17 3,785,828 1,346,395 3,931,720 0.0424 0.0425 0.0426 AL Feb 18 3,834,263 1,369,480 4,038,456 0.0429 0.0432 0.0437 AL Feb 19 3,809,317 1,368,459 4,006,765 0.0427 0.0432 0.0434 AL Feb 20 3,786,113 1,353,892 3,910,013 0.0424 0.0427 0.0424 AL Feb 21 3,751,734 1,341,345 3,839,564 0.0420 0.0423 0.0416 AL Feb 22 3,693,699 1,314,805 3,718,028 0.0414 0.0415 0.0403 AL Feb 23 3,587,387 1,272,233 3,609,697 0.0402 0.0401 0.0391 AL Mar 0 3,884,884 1,355,573 3,822,870 0.0397 0.0392 0.0383 AL Mar 1 3,827,542 1,337,086 3,777,070 0.0391 0.0386 0.0379 AL Mar 2 3,820,846 1,339,596 3,789,362 0.0390 0.0387 0.0380 AL Mar 3 3,841,024 1,348,644 3,826,479 0.0392 0.0389 0.0384 AL Mar 4 3,914,521 1,377,239 3,929,343 0.0400 0.0398 0.0394 Average Values [2000-2004] Calculated Ratios

H-1Atmospheric Sciences Group 

### Appendix H Average 2000-2004 State Level Monthly-Diurnal Profiles

CEM-Based Distribution Alpine Geophysics

SO2 Mass NOx Mass Heat Input State Month Hour [lbs] [lbs] [MMBtu] SO2 Ratio NOx Ratio Heat Input Average Values [2000-2004] Calculated Ratios

AL Mar 5 4,054,316 1,429,153 4,139,114 0.0414 0.0413 0.0415 AL Mar 6 4,127,528 1,459,314 4,262,823 0.0421 0.0421 0.0427 AL Mar 7 4,154,653 1,464,376 4,233,137 0.0424 0.0423 0.0424 AL Mar 8 4,166,633 1,472,592 4,261,932 0.0425 0.0425 0.0427 AL Mar 9 4,189,848 1,479,971 4,271,323 0.0428 0.0427 0.0428 AL Mar 10 4,174,285 1,483,811 4,268,181 0.0426 0.0429 0.0428 AL Mar 11 4,156,507 1,476,068 4,254,967 0.0424 0.0426 0.0427 AL Mar 12 4,131,520 1,474,033 4,274,598 0.0422 0.0426 0.0429 AL Mar 13 4,108,706 1,462,540 4,246,704 0.0419 0.0422 0.0426 AL Mar 14 4,119,333 1,465,494 4,271,940 0.0420 0.0423 0.0428 AL Mar 15 4,126,074 1,464,845 4,267,467 0.0421 0.0423 0.0428 AL Mar 16 4,137,700 1,475,522 4,249,552 0.0422 0.0426 0.0426 AL Mar 17 4,147,480 1,475,701 4,253,733 0.0423 0.0426 0.0426 AL Mar 18 4,223,743 1,507,052 4,402,908 0.0431 0.0435 0.0441 AL Mar 19 4,226,663 1,498,418 4,412,192 0.0431 0.0433 0.0442 AL Mar 20 4,196,460 1,486,812 4,339,197 0.0428 0.0429 0.0435 AL Mar 21 4,162,035 1,464,285 4,182,939 0.0425 0.0423 0.0419 AL Mar 22 4,112,232 1,437,662 4,070,175 0.0420 0.0415 0.0408 AL Mar 23 3,972,501 1,389,240 3,934,933 0.0405 0.0401 0.0395 AL Apr 0 3,363,198 1,217,532 3,698,549 0.0381 0.0377 0.0369 AL Apr 1 3,318,487 1,226,840 3,676,330 0.0376 0.0379 0.0367 AL Apr 2 3,313,384 1,224,253 3,669,911 0.0375 0.0379 0.0367 AL Apr 3 3,402,206 1,231,546 3,742,732 0.0386 0.0381 0.0374 AL Apr 4 3,575,530 1,295,380 3,944,154 0.0405 0.0401 0.0394 AL Apr 5 3,685,748 1,349,191 4,131,717 0.0418 0.0417 0.0413 AL Apr 6 3,715,609 1,373,011 4,187,547 0.0421 0.0425 0.0418 AL Apr 7 3,740,649 1,360,712 4,144,855 0.0424 0.0421 0.0414 AL Apr 8 3,782,629 1,381,548 4,157,764 0.0429 0.0427 0.0415 AL Apr 9 3,818,629 1,386,461 4,271,958 0.0433 0.0429 0.0427 AL Apr 10 3,809,084 1,397,435 4,356,611 0.0432 0.0432 0.0435 AL Apr 11 3,802,578 1,393,134 4,406,377 0.0431 0.0431 0.0440 AL Apr 12 3,771,988 1,384,184 4,419,719 0.0427 0.0428 0.0441 AL Apr 13 3,779,174 1,386,794 4,441,381 0.0428 0.0429 0.0444 AL Apr 14 3,782,737 1,396,661 4,457,323 0.0429 0.0432 0.0445 AL Apr 15 3,775,005 1,406,020 4,451,082 0.0428 0.0435 0.0445 AL Apr 16 3,781,714 1,398,764 4,427,061 0.0429 0.0433 0.0442 AL Apr 17 3,791,836 1,397,385 4,412,649 0.0430 0.0432 0.0441 AL Apr 18 3,815,899 1,409,963 4,458,379 0.0432 0.0436 0.0445 AL Apr 19 3,827,202 1,415,440 4,450,921 0.0434 0.0438 0.0445 AL Apr 20 3,781,426 1,386,890 4,338,012 0.0429 0.0429 0.0433 AL Apr 21 3,714,250 1,353,685 4,167,295 0.0421 0.0419 0.0416 AL Apr 22 3,598,737 1,302,914 3,919,037 0.0408 0.0403 0.0391 AL Apr 23 3,495,479 1,258,528 3,798,145 0.0396 0.0389 0.0379 AL May 0 3,336,544 1,204,200 3,957,971 0.0371 0.0369 0.0350 AL May 1 3,235,207 1,167,840 3,853,580 0.0360 0.0358 0.0341 AL May 2 3,187,798 1,149,355 3,800,179 0.0354 0.0352 0.0336 AL May 3 3,278,716 1,172,350 3,874,610 0.0364 0.0359 0.0343 AL May 4 3,481,698 1,252,805 4,061,025 0.0387 0.0384 0.0359 AL May 5 3,618,028 1,304,064 4,242,931 0.0402 0.0400 0.0376 AL May 6 3,711,280 1,326,707 4,405,290 0.0413 0.0407 0.0390 AL May 7 3,807,688 1,357,099 4,593,502 0.0423 0.0416 0.0407 AL May 8 3,910,037 1,415,728 4,809,122 0.0435 0.0434 0.0426 AL May 9 3,945,371 1,432,231 4,937,386 0.0439 0.0439 0.0437

H-2Atmospheric Sciences Group 

### Appendix H Average 2000-2004 State Level Monthly-Diurnal Profiles

CEM-Based Distribution Alpine Geophysics

SO2 Mass NOx Mass Heat Input State Month Hour [lbs] [lbs] [MMBtu] SO2 Ratio NOx Ratio Heat Input Average Values [2000-2004] Calculated Ratios

AL May 10 3,959,804 1,444,770 5,078,134 0.0440 0.0443 0.0450 AL May 11 3,984,853 1,463,785 5,187,569 0.0443 0.0449 0.0459 AL May 12 3,967,316 1,463,002 5,269,665 0.0441 0.0448 0.0466 AL May 13 3,969,347 1,469,503 5,321,405 0.0441 0.0450 0.0471 AL May 14 3,973,176 1,470,089 5,352,352 0.0442 0.0451 0.0474 AL May 15 3,983,688 1,477,372 5,362,174 0.0443 0.0453 0.0475 AL May 16 3,969,189 1,447,344 5,261,688 0.0441 0.0444 0.0466 AL May 17 3,947,675 1,438,262 5,195,482 0.0439 0.0441 0.0460 AL May 18 3,917,508 1,433,101 5,143,555 0.0435 0.0439 0.0455 AL May 19 3,942,531 1,451,739 5,163,763 0.0438 0.0445 0.0457 AL May 20 3,882,556 1,399,938 4,962,672 0.0432 0.0429 0.0439 AL May 21 3,786,170 1,355,129 4,694,712 0.0421 0.0415 0.0416 AL May 22 3,658,659 1,283,668 4,334,298 0.0407 0.0393 0.0384 AL May 23 3,507,827 1,247,687 4,104,904 0.0390 0.0382 0.0363 AL Jun 0 3,249,457 1,135,350 3,889,416 0.0373 0.0364 0.0350 AL Jun 1 3,118,010 1,100,797 3,794,112 0.0358 0.0353 0.0342 AL Jun 2 3,046,926 1,081,031 3,725,689 0.0350 0.0347 0.0335 AL Jun 3 3,089,289 1,101,845 3,763,688 0.0355 0.0353 0.0339 AL Jun 4 3,204,111 1,144,934 3,887,662 0.0368 0.0367 0.0350 AL Jun 5 3,301,357 1,176,830 4,024,403 0.0379 0.0377 0.0362 AL Jun 6 3,481,535 1,232,393 4,204,486 0.0400 0.0395 0.0378 AL Jun 7 3,640,010 1,283,636 4,365,599 0.0418 0.0412 0.0393 AL Jun 8 3,786,169 1,336,261 4,591,409 0.0435 0.0428 0.0413 AL Jun 9 3,849,169 1,379,354 4,872,063 0.0442 0.0442 0.0439 AL Jun 10 3,886,151 1,407,767 5,049,662 0.0446 0.0451 0.0455 AL Jun 11 3,899,135 1,415,593 5,234,525 0.0448 0.0454 0.0471 AL Jun 12 3,882,514 1,420,588 5,337,089 0.0446 0.0455 0.0480 AL Jun 13 3,883,981 1,422,434 5,350,779 0.0446 0.0456 0.0482 AL Jun 14 3,891,077 1,426,441 5,325,650 0.0447 0.0457 0.0479 AL Jun 15 3,904,160 1,429,269 5,326,230 0.0448 0.0458 0.0479 AL Jun 16 3,890,967 1,416,563 5,294,467 0.0447 0.0454 0.0477 AL Jun 17 3,874,046 1,403,488 5,238,057 0.0445 0.0450 0.0472 AL Jun 18 3,836,617 1,382,313 5,100,573 0.0440 0.0443 0.0459 AL Jun 19 3,862,525 1,391,041 5,060,286 0.0443 0.0446 0.0456 AL Jun 20 3,825,675 1,372,354 4,862,221 0.0439 0.0440 0.0438 AL Jun 21 3,727,151 1,307,044 4,537,952 0.0428 0.0419 0.0408 AL Jun 22 3,561,423 1,241,753 4,216,643 0.0409 0.0398 0.0380 AL Jun 23 3,410,779 1,184,219 4,036,059 0.0392 0.0380 0.0363 AL Jul 0 3,439,331 1,179,646 4,241,206 0.0376 0.0368 0.0353 AL Jul 1 3,292,043 1,133,656 4,108,549 0.0359 0.0353 0.0342 AL Jul 2 3,221,553 1,112,403 4,048,567 0.0352 0.0347 0.0337 AL Jul 3 3,230,938 1,117,015 4,055,211 0.0353 0.0348 0.0338 AL Jul 4 3,344,145 1,162,812 4,150,241 0.0365 0.0363 0.0346 AL Jul 5 3,442,485 1,205,619 4,325,308 0.0376 0.0376 0.0360 AL Jul 6 3,597,919 1,249,932 4,517,342 0.0393 0.0390 0.0376 AL Jul 7 3,770,680 1,304,482 4,741,948 0.0412 0.0407 0.0395 AL Jul 8 3,936,064 1,383,541 5,014,602 0.0430 0.0431 0.0417 AL Jul 9 4,035,072 1,412,474 5,258,624 0.0441 0.0440 0.0438 AL Jul 10 4,098,677 1,460,627 5,438,453 0.0448 0.0455 0.0453 AL Jul 11 4,121,751 1,454,293 5,604,370 0.0450 0.0453 0.0467 AL Jul 12 4,101,025 1,452,552 5,705,407 0.0448 0.0453 0.0475 AL Jul 13 4,091,145 1,450,657 5,736,411 0.0447 0.0452 0.0478 AL Jul 14 4,102,687 1,458,381 5,760,754 0.0448 0.0455 0.0480

H-3Atmospheric Sciences Group 

### Appendix H Average 2000-2004 State Level Monthly-Diurnal Profiles

CEM-Based Distribution Alpine Geophysics

SO2 Mass NOx Mass Heat Input State Month Hour [lbs] [lbs] [MMBtu] SO2 Ratio NOx Ratio Heat Input Average Values [2000-2004] Calculated Ratios

AL Jul 15 4,105,831 1,456,744 5,744,619 0.0448 0.0454 0.0478 AL Jul 16 4,088,730 1,450,875 5,678,442 0.0446 0.0452 0.0473 AL Jul 17 4,074,377 1,441,938 5,602,017 0.0445 0.0450 0.0466 AL Jul 18 4,046,811 1,425,856 5,503,034 0.0442 0.0445 0.0458 AL Jul 19 4,057,207 1,423,649 5,489,189 0.0443 0.0444 0.0457 AL Jul 20 4,028,869 1,408,944 5,276,923 0.0440 0.0439 0.0439 AL Jul 21 3,939,185 1,370,873 4,966,147 0.0430 0.0427 0.0413 AL Jul 22 3,785,688 1,311,615 4,694,013 0.0413 0.0409 0.0391 AL Jul 23 3,635,231 1,245,395 4,449,233 0.0397 0.0388 0.0370 AL Aug 0 3,431,253 1,193,699 4,186,623 0.0379 0.0370 0.0350 AL Aug 1 3,307,883 1,150,053 4,077,525 0.0365 0.0356 0.0341 AL Aug 2 3,256,822 1,131,091 4,013,306 0.0360 0.0350 0.0335 AL Aug 3 3,292,935 1,152,962 4,042,147 0.0364 0.0357 0.0338 AL Aug 4 3,449,798 1,209,426 4,215,379 0.0381 0.0375 0.0352 AL Aug 5 3,566,895 1,267,176 4,383,240 0.0394 0.0393 0.0366 AL Aug 6 3,626,514 1,287,197 4,519,263 0.0401 0.0399 0.0378 AL Aug 7 3,741,028 1,342,638 4,671,194 0.0413 0.0416 0.0390 AL Aug 8 3,880,563 1,370,276 4,978,193 0.0429 0.0424 0.0416 AL Aug 9 3,941,442 1,414,788 5,234,978 0.0435 0.0438 0.0437 AL Aug 10 3,984,075 1,443,741 5,472,107 0.0440 0.0447 0.0457 AL Aug 11 4,011,170 1,441,002 5,610,521 0.0443 0.0446 0.0469 AL Aug 12 4,004,862 1,446,340 5,680,752 0.0442 0.0448 0.0475 AL Aug 13 4,006,916 1,450,309 5,728,806 0.0443 0.0449 0.0479 AL Aug 14 4,021,532 1,463,125 5,750,748 0.0444 0.0453 0.0480 AL Aug 15 4,022,793 1,463,121 5,756,612 0.0444 0.0453 0.0481 AL Aug 16 4,011,804 1,453,868 5,709,595 0.0443 0.0450 0.0477 AL Aug 17 3,999,859 1,440,569 5,615,593 0.0442 0.0446 0.0469 AL Aug 18 3,976,679 1,429,307 5,552,926 0.0439 0.0443 0.0464 AL Aug 19 3,970,599 1,424,331 5,462,287 0.0439 0.0441 0.0456 AL Aug 20 3,924,918 1,403,283 5,238,962 0.0434 0.0435 0.0438 AL Aug 21 3,834,050 1,360,582 4,909,036 0.0424 0.0421 0.0410 AL Aug 22 3,681,304 1,297,182 4,559,770 0.0407 0.0402 0.0381 AL Aug 23 3,571,373 1,246,733 4,345,837 0.0395 0.0386 0.0363 AL Sep 0 3,173,133 1,087,802 3,726,533 0.0369 0.0360 0.0342 AL Sep 1 3,085,837 1,064,028 3,661,167 0.0358 0.0352 0.0336 AL Sep 2 3,044,225 1,051,232 3,623,321 0.0354 0.0348 0.0333 AL Sep 3 3,087,917 1,065,342 3,658,420 0.0359 0.0353 0.0336 AL Sep 4 3,281,892 1,134,947 3,853,372 0.0381 0.0376 0.0354 AL Sep 5 3,449,316 1,197,293 4,077,599 0.0401 0.0396 0.0375 AL Sep 6 3,491,093 1,228,696 4,209,757 0.0405 0.0407 0.0387 AL Sep 7 3,589,499 1,273,314 4,339,749 0.0417 0.0422 0.0399 AL Sep 8 3,693,656 1,295,401 4,516,642 0.0429 0.0429 0.0415 AL Sep 9 3,753,630 1,326,750 4,705,712 0.0436 0.0439 0.0432 AL Sep 10 3,793,897 1,344,080 4,868,926 0.0441 0.0445 0.0447 AL Sep 11 3,814,789 1,353,910 5,047,015 0.0443 0.0448 0.0464 AL Sep 12 3,810,937 1,364,922 5,157,180 0.0443 0.0452 0.0474 AL Sep 13 3,824,476 1,365,307 5,211,391 0.0444 0.0452 0.0479 AL Sep 14 3,842,311 1,367,787 5,278,551 0.0446 0.0453 0.0485 AL Sep 15 3,855,155 1,369,353 5,279,121 0.0448 0.0453 0.0485 AL Sep 16 3,842,896 1,364,140 5,244,513 0.0446 0.0452 0.0482 AL Sep 17 3,840,388 1,358,817 5,199,308 0.0446 0.0450 0.0478 AL Sep 18 3,852,451 1,366,889 5,177,795 0.0447 0.0453 0.0476 AL Sep 19 3,838,056 1,349,035 5,040,981 0.0446 0.0447 0.0463

H-4Atmospheric Sciences Group 

### Appendix H Average 2000-2004 State Level Monthly-Diurnal Profiles

CEM-Based Distribution Alpine Geophysics

SO2 Mass NOx Mass Heat Input State Month Hour [lbs] [lbs] [MMBtu] SO2 Ratio NOx Ratio Heat Input Average Values [2000-2004] Calculated Ratios

AL Sep 20 3,766,174 1,308,138 4,762,991 0.0437 0.0433 0.0437 AL Sep 21 3,627,576 1,252,788 4,357,940 0.0421 0.0415 0.0400 AL Sep 22 3,439,979 1,184,709 4,038,063 0.0400 0.0392 0.0371 AL Sep 23 3,294,649 1,130,504 3,837,152 0.0383 0.0374 0.0352 AL Oct 0 3,632,590 1,292,415 3,716,299 0.0383 0.0376 0.0355 AL Oct 1 3,566,773 1,275,337 3,658,994 0.0376 0.0371 0.0350 AL Oct 2 3,550,154 1,272,032 3,645,593 0.0374 0.0370 0.0348 AL Oct 3 3,622,818 1,298,930 3,715,279 0.0382 0.0378 0.0355 AL Oct 4 3,816,443 1,361,689 3,908,601 0.0402 0.0397 0.0374 AL Oct 5 3,964,777 1,422,147 4,179,281 0.0418 0.0414 0.0399 AL Oct 6 3,982,938 1,464,711 4,302,262 0.0420 0.0427 0.0411 AL Oct 7 4,034,829 1,454,472 4,405,035 0.0425 0.0424 0.0421 AL Oct 8 4,084,350 1,473,771 4,493,838 0.0431 0.0429 0.0430 AL Oct 9 4,092,334 1,486,378 4,588,066 0.0431 0.0433 0.0439 AL Oct 10 4,100,833 1,486,998 4,657,813 0.0432 0.0433 0.0445 AL Oct 11 4,103,409 1,494,434 4,731,151 0.0433 0.0435 0.0452 AL Oct 12 4,077,261 1,489,692 4,761,539 0.0430 0.0434 0.0455 AL Oct 13 4,076,784 1,493,384 4,753,105 0.0430 0.0435 0.0454 AL Oct 14 4,084,027 1,496,244 4,759,557 0.0431 0.0436 0.0455 AL Oct 15 4,091,111 1,496,627 4,745,431 0.0431 0.0436 0.0454 AL Oct 16 4,091,084 1,497,434 4,756,253 0.0431 0.0436 0.0455 AL Oct 17 4,105,544 1,502,049 4,805,118 0.0433 0.0437 0.0459 AL Oct 18 4,104,966 1,503,458 4,764,255 0.0433 0.0438 0.0455 AL Oct 19 4,083,456 1,487,218 4,657,595 0.0430 0.0433 0.0445 AL Oct 20 4,048,426 1,465,206 4,506,250 0.0427 0.0427 0.0431 AL Oct 21 3,970,419 1,423,742 4,241,227 0.0419 0.0415 0.0405 AL Oct 22 3,842,465 1,371,164 4,022,655 0.0405 0.0399 0.0385 AL Oct 23 3,735,034 1,328,366 3,844,323 0.0394 0.0387 0.0367 AL Nov 0 3,267,264 1,247,402 3,299,233 0.0382 0.0385 0.0362 AL Nov 1 3,204,439 1,212,764 3,235,759 0.0375 0.0374 0.0355 AL Nov 2 3,181,765 1,213,704 3,237,355 0.0372 0.0374 0.0356 AL Nov 3 3,208,275 1,219,805 3,277,901 0.0375 0.0376 0.0360 AL Nov 4 3,317,965 1,255,332 3,402,159 0.0388 0.0387 0.0374 AL Nov 5 3,500,997 1,321,240 3,633,182 0.0409 0.0408 0.0399 AL Nov 6 3,617,744 1,374,822 3,878,759 0.0423 0.0424 0.0426 AL Nov 7 3,651,716 1,383,616 3,949,207 0.0427 0.0427 0.0434 AL Nov 8 3,686,742 1,392,750 3,957,532 0.0431 0.0430 0.0435 AL Nov 9 3,724,441 1,400,877 3,976,990 0.0435 0.0432 0.0437 AL Nov 10 3,704,353 1,400,083 4,019,889 0.0433 0.0432 0.0442 AL Nov 11 3,692,782 1,403,186 4,057,061 0.0432 0.0433 0.0446 AL Nov 12 3,676,420 1,393,003 4,030,364 0.0430 0.0430 0.0443 AL Nov 13 3,651,783 1,382,082 3,955,983 0.0427 0.0426 0.0435 AL Nov 14 3,639,470 1,380,674 3,934,235 0.0425 0.0426 0.0432 AL Nov 15 3,642,229 1,376,339 3,903,518 0.0426 0.0425 0.0429 AL Nov 16 3,692,761 1,394,692 4,019,062 0.0432 0.0430 0.0441 AL Nov 17 3,760,549 1,423,722 4,162,605 0.0440 0.0439 0.0457 AL Nov 18 3,753,211 1,429,019 4,186,038 0.0439 0.0441 0.0460 AL Nov 19 3,721,778 1,413,776 4,135,212 0.0435 0.0436 0.0454 AL Nov 20 3,695,216 1,400,293 4,002,565 0.0432 0.0432 0.0440 AL Nov 21 3,641,056 1,376,237 3,826,538 0.0426 0.0425 0.0420 AL Nov 22 3,521,606 1,332,335 3,575,679 0.0412 0.0411 0.0393 AL Nov 23 3,385,691 1,288,165 3,388,264 0.0396 0.0397 0.0372 AL Dec 0 3,528,822 1,323,984 3,877,301 0.0395 0.0395 0.0385

H-5Atmospheric Sciences Group 

### Appendix H Average 2000-2004 State Level Monthly-Diurnal Profiles

CEM-Based Distribution Alpine Geophysics

SO2 Mass NOx Mass Heat Input State Month Hour [lbs] [lbs] [MMBtu] SO2 Ratio NOx Ratio Heat Input Average Values [2000-2004] Calculated Ratios

AL Dec 1 3,455,700 1,299,710 3,812,929 0.0387 0.0387 0.0378 AL Dec 2 3,450,663 1,302,222 3,812,469 0.0386 0.0388 0.0378 AL Dec 3 3,486,042 1,312,140 3,842,898 0.0390 0.0391 0.0381 AL Dec 4 3,561,526 1,351,413 4,009,684 0.0399 0.0403 0.0398 AL Dec 5 3,691,291 1,392,356 4,216,662 0.0413 0.0415 0.0418 AL Dec 6 3,808,679 1,436,242 4,391,288 0.0426 0.0428 0.0436 AL Dec 7 3,849,370 1,442,553 4,426,423 0.0431 0.0430 0.0439 AL Dec 8 3,867,228 1,445,250 4,389,009 0.0433 0.0431 0.0436 AL Dec 9 3,873,293 1,445,929 4,341,531 0.0434 0.0431 0.0431 AL Dec 10 3,843,700 1,432,897 4,312,111 0.0430 0.0427 0.0428 AL Dec 11 3,800,122 1,418,517 4,254,327 0.0425 0.0423 0.0422 AL Dec 12 3,736,547 1,406,341 4,191,604 0.0418 0.0419 0.0416 AL Dec 13 3,659,619 1,369,323 4,092,232 0.0410 0.0408 0.0406 AL Dec 14 3,606,430 1,356,548 4,069,143 0.0404 0.0404 0.0404 AL Dec 15 3,631,611 1,368,864 4,116,419 0.0406 0.0408 0.0408 AL Dec 16 3,728,053 1,404,849 4,283,856 0.0417 0.0419 0.0425 AL Dec 17 3,878,777 1,456,685 4,475,306 0.0434 0.0434 0.0444 AL Dec 18 3,906,726 1,466,262 4,507,942 0.0437 0.0437 0.0447 AL Dec 19 3,875,131 1,458,101 4,452,005 0.0434 0.0435 0.0442 AL Dec 20 3,876,365 1,452,244 4,397,504 0.0434 0.0433 0.0436 AL Dec 21 3,858,933 1,444,312 4,325,152 0.0432 0.0431 0.0429 AL Dec 22 3,755,148 1,402,934 4,153,973 0.0420 0.0418 0.0412 AL Dec 23 3,614,616 1,359,957 4,017,788 0.0405 0.0405 0.0399 FL Jan 0 4,092,917 2,105,649 6,987,856 0.0353 0.0334 0.0352 FL Jan 1 3,987,160 2,035,874 6,898,903 0.0344 0.0323 0.0347 FL Jan 2 3,969,797 2,031,934 6,906,056 0.0342 0.0323 0.0347 FL Jan 3 4,002,571 2,069,592 7,035,278 0.0345 0.0329 0.0354 FL Jan 4 4,117,388 2,174,218 7,449,461 0.0355 0.0345 0.0375 FL Jan 5 4,479,652 2,396,830 8,148,718 0.0386 0.0381 0.0410 FL Jan 6 5,174,782 2,828,553 9,183,615 0.0446 0.0449 0.0462 FL Jan 7 5,717,909 3,155,634 9,845,442 0.0493 0.0501 0.0495 FL Jan 8 5,760,945 3,192,267 9,911,845 0.0497 0.0507 0.0499 FL Jan 9 5,596,442 3,102,531 9,574,243 0.0482 0.0493 0.0482 FL Jan 10 5,355,908 2,964,195 9,053,718 0.0462 0.0471 0.0456 FL Jan 11 5,051,096 2,824,581 8,500,073 0.0435 0.0448 0.0428 FL Jan 12 4,807,243 2,611,433 8,065,116 0.0414 0.0415 0.0406 FL Jan 13 4,557,208 2,478,633 7,746,587 0.0393 0.0393 0.0390 FL Jan 14 4,348,649 2,364,071 7,449,604 0.0375 0.0375 0.0375 FL Jan 15 4,286,664 2,327,446 7,356,274 0.0370 0.0369 0.0370 FL Jan 16 4,385,028 2,374,163 7,524,846 0.0378 0.0377 0.0379 FL Jan 17 4,858,385 2,645,810 8,268,667 0.0419 0.0420 0.0416 FL Jan 18 5,704,399 3,160,866 9,468,763 0.0492 0.0502 0.0476 FL Jan 19 5,743,463 3,241,746 9,613,610 0.0495 0.0515 0.0484 FL Jan 20 5,498,856 3,078,322 9,308,547 0.0474 0.0489 0.0468 FL Jan 21 5,177,963 2,871,307 8,801,908 0.0446 0.0456 0.0443 FL Jan 22 4,908,336 2,630,830 8,167,507 0.0423 0.0418 0.0411 FL Jan 23 4,428,492 2,323,474 7,484,412 0.0382 0.0369 0.0377 FL Feb 0 2,843,907 1,468,930 5,312,973 0.0303 0.0289 0.0322 FL Feb 1 2,672,347 1,391,877 5,132,938 0.0284 0.0274 0.0311 FL Feb 2 2,564,226 1,347,543 5,007,986 0.0273 0.0265 0.0304 FL Feb 3 2,550,645 1,347,706 5,022,651 0.0271 0.0265 0.0304 FL Feb 4 2,603,632 1,390,611 5,195,066 0.0277 0.0274 0.0315 FL Feb 5 2,897,018 1,552,695 5,719,031 0.0308 0.0305 0.0347

H-6Atmospheric Sciences Group 

### Appendix H Average 2000-2004 State Level Monthly-Diurnal Profiles

CEM-Based Distribution Alpine Geophysics

SO2 Mass NOx Mass Heat Input State Month Hour [lbs] [lbs] [MMBtu] SO2 Ratio NOx Ratio Heat Input Average Values [2000-2004] Calculated Ratios

FL Feb 6 3,602,560 1,982,073 6,872,933 0.0383 0.0390 0.0417 FL Feb 7 4,201,272 2,325,930 7,680,764 0.0447 0.0458 0.0466 FL Feb 8 4,367,138 2,395,477 7,781,623 0.0465 0.0471 0.0472 FL Feb 9 4,422,900 2,420,472 7,732,427 0.0471 0.0476 0.0469 FL Feb 10 4,458,881 2,438,577 7,562,420 0.0475 0.0480 0.0458 FL Feb 11 4,389,493 2,382,402 7,340,385 0.0467 0.0469 0.0445 FL Feb 12 4,330,015 2,364,939 7,272,402 0.0461 0.0465 0.0441 FL Feb 13 4,300,811 2,352,445 7,230,408 0.0458 0.0463 0.0438 FL Feb 14 4,221,312 2,306,854 7,170,989 0.0449 0.0454 0.0435 FL Feb 15 4,241,059 2,317,603 7,204,323 0.0451 0.0456 0.0437 FL Feb 16 4,321,957 2,348,475 7,310,653 0.0460 0.0462 0.0443 FL Feb 17 4,502,792 2,432,169 7,559,804 0.0479 0.0478 0.0458 FL Feb 18 5,064,768 2,734,325 8,339,846 0.0539 0.0538 0.0506 FL Feb 19 5,226,395 2,858,688 8,591,004 0.0556 0.0562 0.0521 FL Feb 20 4,798,063 2,604,697 8,044,823 0.0511 0.0512 0.0488 FL Feb 21 4,284,859 2,310,862 7,344,108 0.0456 0.0455 0.0445 FL Feb 22 3,831,661 2,044,379 6,628,589 0.0408 0.0402 0.0402 FL Feb 23 3,261,076 1,712,086 5,891,556 0.0347 0.0337 0.0357 FL Mar 0 3,393,482 1,746,949 6,158,635 0.0304 0.0290 0.0313 FL Mar 1 3,131,030 1,597,082 5,893,284 0.0281 0.0265 0.0300 FL Mar 2 2,986,263 1,516,235 5,703,128 0.0268 0.0252 0.0290 FL Mar 3 2,920,560 1,485,480 5,624,453 0.0262 0.0246 0.0286 FL Mar 4 2,941,877 1,503,977 5,664,936 0.0264 0.0249 0.0288 FL Mar 5 3,156,463 1,628,630 6,037,441 0.0283 0.0270 0.0307 FL Mar 6 3,688,413 1,962,560 6,934,659 0.0331 0.0326 0.0353 FL Mar 7 4,174,443 2,233,007 7,530,457 0.0374 0.0370 0.0383 FL Mar 8 4,565,073 2,460,491 7,929,663 0.0409 0.0408 0.0403 FL Mar 9 4,955,768 2,720,368 8,407,702 0.0444 0.0451 0.0427 FL Mar 10 5,238,317 2,887,913 8,870,979 0.0470 0.0479 0.0451 FL Mar 11 5,370,699 2,987,753 9,202,544 0.0482 0.0496 0.0468 FL Mar 12 5,518,223 3,054,007 9,575,664 0.0495 0.0507 0.0487 FL Mar 13 5,592,032 3,102,973 9,797,330 0.0502 0.0515 0.0498 FL Mar 14 5,614,340 3,120,407 9,897,194 0.0504 0.0518 0.0503 FL Mar 15 5,691,689 3,156,307 9,993,214 0.0510 0.0524 0.0508 FL Mar 16 5,707,207 3,157,176 10,043,000 0.0512 0.0524 0.0511 FL Mar 17 5,690,130 3,132,464 9,975,039 0.0510 0.0520 0.0507 FL Mar 18 5,807,055 3,182,134 10,094,726 0.0521 0.0528 0.0513 FL Mar 19 6,060,481 3,342,494 10,376,991 0.0544 0.0554 0.0528 FL Mar 20 5,685,976 3,099,357 9,729,690 0.0510 0.0514 0.0495 FL Mar 21 5,106,809 2,729,404 8,718,323 0.0458 0.0453 0.0443 FL Mar 22 4,546,936 2,410,497 7,700,628 0.0408 0.0400 0.0391 FL Mar 23 3,962,286 2,068,307 6,846,020 0.0355 0.0343 0.0348 FL Apr 0 3,073,473 1,596,832 5,818,515 0.0287 0.0270 0.0298 FL Apr 1 2,830,568 1,464,614 5,507,523 0.0265 0.0248 0.0282 FL Apr 2 2,712,866 1,401,941 5,353,106 0.0254 0.0237 0.0274 FL Apr 3 2,687,715 1,398,112 5,341,580 0.0251 0.0237 0.0273 FL Apr 4 2,884,533 1,512,851 5,606,259 0.0270 0.0256 0.0287 FL Apr 5 3,377,502 1,808,189 6,324,646 0.0316 0.0306 0.0324 FL Apr 6 3,701,542 2,024,027 6,883,043 0.0346 0.0343 0.0352 FL Apr 7 4,029,897 2,189,545 7,308,193 0.0377 0.0371 0.0374 FL Apr 8 4,435,204 2,429,739 7,846,588 0.0414 0.0411 0.0402 FL Apr 9 4,800,755 2,669,166 8,433,318 0.0449 0.0452 0.0432 FL Apr 10 5,003,384 2,806,647 8,951,308 0.0468 0.0475 0.0458

H-7Atmospheric Sciences Group 

### Appendix H Average 2000-2004 State Level Monthly-Diurnal Profiles

CEM-Based Distribution Alpine Geophysics

SO2 Mass NOx Mass Heat Input State Month Hour [lbs] [lbs] [MMBtu] SO2 Ratio NOx Ratio Heat Input Average Values [2000-2004] Calculated Ratios

FL Apr 11 5,202,417 2,944,645 9,493,938 0.0486 0.0498 0.0486 FL Apr 12 5,375,267 3,054,496 9,838,364 0.0502 0.0517 0.0504 FL Apr 13 5,540,550 3,155,947 10,110,799 0.0518 0.0534 0.0518 FL Apr 14 5,669,250 3,235,350 10,270,190 0.0530 0.0548 0.0526 FL Apr 15 5,758,423 3,296,338 10,401,429 0.0538 0.0558 0.0532 FL Apr 16 5,747,345 3,273,691 10,406,169 0.0537 0.0554 0.0533 FL Apr 17 5,636,021 3,182,448 10,224,599 0.0527 0.0539 0.0523 FL Apr 18 5,499,025 3,076,297 9,966,284 0.0514 0.0521 0.0510 FL Apr 19 5,565,173 3,123,280 10,085,034 0.0520 0.0529 0.0516 FL Apr 20 5,249,717 2,916,414 9,379,352 0.0491 0.0494 0.0480 FL Apr 21 4,676,711 2,548,574 8,349,346 0.0437 0.0431 0.0427 FL Apr 22 4,085,358 2,156,831 7,180,264 0.0382 0.0365 0.0368 FL Apr 23 3,472,742 1,805,817 6,258,356 0.0325 0.0306 0.0320 FL May 0 3,326,795 1,616,442 6,064,855 0.0281 0.0262 0.0292 FL May 1 3,039,934 1,466,219 5,722,859 0.0256 0.0237 0.0275 FL May 2 2,875,087 1,383,514 5,511,885 0.0242 0.0224 0.0265 FL May 3 2,805,215 1,349,812 5,436,296 0.0237 0.0218 0.0262 FL May 4 2,925,111 1,419,558 5,587,227 0.0247 0.0230 0.0269 FL May 5 3,310,211 1,647,323 6,084,579 0.0279 0.0267 0.0293 FL May 6 3,613,515 1,829,481 6,474,592 0.0305 0.0296 0.0312 FL May 7 4,112,896 2,091,150 7,118,987 0.0347 0.0338 0.0343 FL May 8 4,723,020 2,464,573 8,082,604 0.0398 0.0399 0.0389 FL May 9 5,299,044 2,811,031 9,070,995 0.0447 0.0455 0.0437 FL May 10 5,706,734 3,039,074 9,862,622 0.0481 0.0492 0.0475 FL May 11 6,030,558 3,227,787 10,499,703 0.0509 0.0522 0.0505 FL May 12 6,263,770 3,385,820 10,897,017 0.0528 0.0548 0.0524 FL May 13 6,446,397 3,492,920 11,144,147 0.0544 0.0565 0.0536 FL May 14 6,543,458 3,558,781 11,309,808 0.0552 0.0576 0.0544 FL May 15 6,614,706 3,583,476 11,374,785 0.0558 0.0580 0.0547 FL May 16 6,562,714 3,553,849 11,330,486 0.0553 0.0575 0.0545 FL May 17 6,427,404 3,442,964 11,098,178 0.0542 0.0557 0.0534 FL May 18 6,181,112 3,276,351 10,751,974 0.0521 0.0530 0.0517 FL May 19 6,139,862 3,238,277 10,691,352 0.0518 0.0524 0.0514 FL May 20 5,893,410 3,067,363 10,097,821 0.0497 0.0496 0.0486 FL May 21 5,287,670 2,690,286 9,149,571 0.0446 0.0435 0.0440 FL May 22 4,599,556 2,287,025 7,794,463 0.0388 0.0370 0.0375 FL May 23 3,861,183 1,888,530 6,647,187 0.0326 0.0306 0.0320 FL Jun 0 3,334,119 1,623,321 6,030,237 0.0287 0.0271 0.0297 FL Jun 1 3,042,173 1,477,781 5,675,625 0.0262 0.0247 0.0280 FL Jun 2 2,871,886 1,395,072 5,469,455 0.0247 0.0233 0.0270 FL Jun 3 2,808,510 1,364,334 5,407,215 0.0242 0.0228 0.0267 FL Jun 4 2,878,822 1,415,032 5,509,409 0.0248 0.0237 0.0272 FL Jun 5 3,119,955 1,566,763 5,839,325 0.0269 0.0262 0.0288 FL Jun 6 3,404,220 1,735,684 6,254,804 0.0293 0.0290 0.0309 FL Jun 7 4,032,166 2,035,794 7,016,218 0.0347 0.0340 0.0346 FL Jun 8 4,776,825 2,462,038 8,031,552 0.0412 0.0412 0.0396 FL Jun 9 5,423,465 2,825,843 9,043,192 0.0467 0.0473 0.0446 FL Jun 10 5,815,644 3,070,394 9,883,174 0.0501 0.0513 0.0488 FL Jun 11 6,093,639 3,216,302 10,461,280 0.0525 0.0538 0.0516 FL Jun 12 6,247,754 3,312,468 10,811,077 0.0538 0.0554 0.0533 FL Jun 13 6,320,569 3,356,495 10,962,083 0.0545 0.0561 0.0541 FL Jun 14 6,341,297 3,367,293 10,985,575 0.0546 0.0563 0.0542 FL Jun 15 6,344,416 3,369,723 10,982,417 0.0547 0.0563 0.0542

H-8Atmospheric Sciences Group 

### Appendix H Average 2000-2004 State Level Monthly-Diurnal Profiles

CEM-Based Distribution Alpine Geophysics

SO2 Mass NOx Mass Heat Input State Month Hour [lbs] [lbs] [MMBtu] SO2 Ratio NOx Ratio Heat Input Average Values [2000-2004] Calculated Ratios

FL Jun 16 6,269,294 3,320,859 10,860,559 0.0540 0.0555 0.0536 FL Jun 17 6,120,897 3,218,578 10,637,320 0.0527 0.0538 0.0525 FL Jun 18 5,922,533 3,097,039 10,290,936 0.0510 0.0518 0.0508 FL Jun 19 5,845,292 3,040,879 10,168,724 0.0504 0.0508 0.0502 FL Jun 20 5,689,872 2,925,963 9,695,671 0.0490 0.0489 0.0478 FL Jun 21 5,131,651 2,575,186 8,588,464 0.0442 0.0431 0.0424 FL Jun 22 4,444,503 2,187,491 7,527,536 0.0383 0.0366 0.0371 FL Jun 23 3,789,487 1,841,308 6,584,364 0.0326 0.0308 0.0325 FL Jul 0 3,575,775 1,727,375 6,473,654 0.0289 0.0276 0.0305 FL Jul 1 3,231,898 1,562,357 6,065,421 0.0261 0.0250 0.0285 FL Jul 2 3,057,902 1,477,501 5,858,455 0.0247 0.0236 0.0276 FL Jul 3 2,974,058 1,438,242 5,770,235 0.0240 0.0230 0.0272 FL Jul 4 3,053,015 1,480,314 5,869,580 0.0246 0.0237 0.0276 FL Jul 5 3,325,632 1,634,831 6,179,486 0.0268 0.0262 0.0291 FL Jul 6 3,613,376 1,799,944 6,528,285 0.0292 0.0288 0.0307 FL Jul 7 4,246,867 2,096,989 7,276,877 0.0343 0.0336 0.0342 FL Jul 8 5,069,730 2,544,519 8,299,636 0.0409 0.0407 0.0391 FL Jul 9 5,740,767 2,923,651 9,388,410 0.0463 0.0468 0.0442 FL Jul 10 6,186,872 3,176,179 10,346,853 0.0499 0.0508 0.0487 FL Jul 11 6,503,084 3,330,370 10,857,354 0.0525 0.0533 0.0511 FL Jul 12 6,647,623 3,431,257 11,223,802 0.0537 0.0549 0.0528 FL Jul 13 6,737,151 3,484,978 11,394,602 0.0544 0.0558 0.0536 FL Jul 14 6,778,167 3,495,377 11,454,929 0.0547 0.0559 0.0539 FL Jul 15 6,758,177 3,484,708 11,429,250 0.0546 0.0558 0.0538 FL Jul 16 6,679,320 3,434,352 11,299,820 0.0539 0.0549 0.0532 FL Jul 17 6,539,832 3,347,206 11,082,596 0.0528 0.0536 0.0522 FL Jul 18 6,335,429 3,246,664 10,752,871 0.0511 0.0519 0.0506 FL Jul 19 6,236,519 3,181,356 10,486,444 0.0503 0.0509 0.0494 FL Jul 20 6,045,983 3,064,615 10,047,487 0.0488 0.0490 0.0473 FL Jul 21 5,518,680 2,743,333 9,067,924 0.0446 0.0439 0.0427 FL Jul 22 4,869,850 2,380,279 8,127,752 0.0393 0.0381 0.0383 FL Jul 23 4,143,043 2,013,772 7,196,712 0.0334 0.0322 0.0339 FL Aug 0 3,564,393 1,781,146 6,534,802 0.0284 0.0276 0.0304 FL Aug 1 3,276,121 1,613,514 6,181,075 0.0261 0.0250 0.0288 FL Aug 2 3,100,454 1,529,078 5,969,374 0.0247 0.0237 0.0278 FL Aug 3 3,052,193 1,498,961 5,901,660 0.0243 0.0232 0.0275 FL Aug 4 3,179,466 1,572,152 6,057,681 0.0254 0.0243 0.0282 FL Aug 5 3,552,813 1,774,970 6,500,915 0.0283 0.0275 0.0303 FL Aug 6 3,836,397 1,946,107 6,840,145 0.0306 0.0301 0.0319 FL Aug 7 4,360,651 2,201,808 7,491,447 0.0348 0.0341 0.0349 FL Aug 8 5,147,287 2,615,712 8,415,064 0.0411 0.0405 0.0392 FL Aug 9 5,851,181 3,045,606 9,440,418 0.0467 0.0472 0.0440 FL Aug 10 6,280,147 3,278,659 10,326,913 0.0501 0.0508 0.0481 FL Aug 11 6,574,423 3,434,963 10,940,166 0.0524 0.0532 0.0510 FL Aug 12 6,728,198 3,523,530 11,253,235 0.0537 0.0546 0.0524 FL Aug 13 6,802,676 3,570,035 11,389,350 0.0543 0.0553 0.0531 FL Aug 14 6,811,688 3,579,043 11,441,662 0.0543 0.0554 0.0533 FL Aug 15 6,807,926 3,589,688 11,446,440 0.0543 0.0556 0.0533 FL Aug 16 6,728,261 3,547,074 11,342,046 0.0537 0.0549 0.0528 FL Aug 17 6,590,840 3,459,057 11,113,844 0.0526 0.0536 0.0518 FL Aug 18 6,406,482 3,356,251 10,830,083 0.0511 0.0520 0.0505 FL Aug 19 6,374,766 3,331,776 10,715,705 0.0508 0.0516 0.0499 FL Aug 20 6,083,356 3,144,413 10,114,289 0.0485 0.0487 0.0471

H-9Atmospheric Sciences Group 

### Appendix H Average 2000-2004 State Level Monthly-Diurnal Profiles

CEM-Based Distribution Alpine Geophysics

SO2 Mass NOx Mass Heat Input State Month Hour [lbs] [lbs] [MMBtu] SO2 Ratio NOx Ratio Heat Input Average Values [2000-2004] Calculated Ratios

FL Aug 21 5,460,832 2,778,636 9,148,809 0.0436 0.0430 0.0426 FL Aug 22 4,740,533 2,377,352 8,125,071 0.0378 0.0368 0.0379 FL Aug 23 4,073,852 2,023,312 7,117,022 0.0325 0.0313 0.0332 FL Sep 0 3,295,486 1,683,032 6,357,252 0.0291 0.0281 0.0308 FL Sep 1 3,054,328 1,544,844 6,027,816 0.0270 0.0258 0.0292 FL Sep 2 2,909,071 1,470,927 5,840,466 0.0257 0.0246 0.0283 FL Sep 3 2,848,662 1,439,026 5,769,383 0.0252 0.0240 0.0279 FL Sep 4 2,985,098 1,516,893 5,976,600 0.0264 0.0253 0.0289 FL Sep 5 3,413,573 1,762,053 6,558,840 0.0302 0.0294 0.0317 FL Sep 6 3,693,072 1,927,679 6,928,814 0.0327 0.0322 0.0335 FL Sep 7 4,056,408 2,104,073 7,379,883 0.0359 0.0351 0.0357 FL Sep 8 4,636,127 2,448,223 8,179,183 0.0410 0.0409 0.0396 FL Sep 9 5,147,884 2,756,871 9,025,355 0.0455 0.0460 0.0437 FL Sep 10 5,478,304 2,958,241 9,788,328 0.0484 0.0494 0.0474 FL Sep 11 5,747,325 3,097,586 10,302,132 0.0508 0.0517 0.0498 FL Sep 12 5,907,674 3,199,328 10,642,966 0.0522 0.0534 0.0515 FL Sep 13 6,019,188 3,261,256 10,812,176 0.0532 0.0544 0.0523 FL Sep 14 6,059,976 3,280,405 10,903,981 0.0536 0.0548 0.0527 FL Sep 15 6,064,459 3,290,948 10,906,861 0.0536 0.0549 0.0528 FL Sep 16 6,006,647 3,254,683 10,822,329 0.0531 0.0543 0.0524 FL Sep 17 5,876,036 3,171,578 10,598,132 0.0520 0.0529 0.0513 FL Sep 18 5,822,108 3,118,206 10,463,069 0.0515 0.0520 0.0506 FL Sep 19 5,797,575 3,093,577 10,346,960 0.0513 0.0516 0.0501 FL Sep 20 5,414,502 2,869,423 9,652,916 0.0479 0.0479 0.0467 FL Sep 21 4,853,029 2,546,396 8,714,372 0.0429 0.0425 0.0422 FL Sep 22 4,293,776 2,222,527 7,824,944 0.0380 0.0371 0.0379 FL Sep 23 3,700,481 1,895,950 6,890,195 0.0327 0.0316 0.0333 FL Oct 0 3,104,734 1,651,439 6,268,709 0.0282 0.0268 0.0303 FL Oct 1 2,862,531 1,530,723 5,950,210 0.0260 0.0249 0.0288 FL Oct 2 2,742,880 1,464,239 5,745,508 0.0249 0.0238 0.0278 FL Oct 3 2,709,592 1,446,897 5,673,751 0.0246 0.0235 0.0274 FL Oct 4 2,849,720 1,533,459 5,866,761 0.0259 0.0249 0.0284 FL Oct 5 3,313,322 1,844,985 6,602,870 0.0301 0.0300 0.0319 FL Oct 6 3,695,928 2,074,978 7,203,247 0.0336 0.0337 0.0348 FL Oct 7 3,974,216 2,235,297 7,565,209 0.0361 0.0363 0.0366 FL Oct 8 4,429,740 2,515,143 8,198,854 0.0403 0.0409 0.0396 FL Oct 9 4,882,509 2,807,084 8,993,535 0.0444 0.0456 0.0435 FL Oct 10 5,202,215 2,991,865 9,637,381 0.0473 0.0486 0.0466 FL Oct 11 5,474,511 3,162,491 10,194,001 0.0498 0.0514 0.0493 FL Oct 12 5,678,861 3,277,154 10,535,313 0.0516 0.0532 0.0509 FL Oct 13 5,837,087 3,344,772 10,753,557 0.0531 0.0543 0.0520 FL Oct 14 5,945,864 3,397,996 10,895,397 0.0541 0.0552 0.0527 FL Oct 15 5,991,411 3,424,548 10,944,894 0.0545 0.0556 0.0529 FL Oct 16 5,949,385 3,372,697 10,837,382 0.0541 0.0548 0.0524 FL Oct 17 5,848,989 3,309,247 10,653,810 0.0532 0.0538 0.0515 FL Oct 18 5,901,087 3,332,412 10,819,210 0.0537 0.0541 0.0523 FL Oct 19 5,694,397 3,193,654 10,459,446 0.0518 0.0519 0.0505 FL Oct 20 5,260,538 2,914,173 9,707,974 0.0478 0.0473 0.0469 FL Oct 21 4,791,615 2,599,563 8,698,668 0.0436 0.0422 0.0420 FL Oct 22 4,225,071 2,247,514 7,851,632 0.0384 0.0365 0.0379 FL Oct 23 3,594,624 1,878,981 6,866,853 0.0327 0.0305 0.0332 FL Nov 0 3,044,968 1,618,401 5,819,531 0.0299 0.0290 0.0311 FL Nov 1 2,777,594 1,468,989 5,512,673 0.0273 0.0263 0.0295

H-10Atmospheric Sciences Group 

### Appendix H Average 2000-2004 State Level Monthly-Diurnal Profiles

CEM-Based Distribution Alpine Geophysics

SO2 Mass NOx Mass Heat Input State Month Hour [lbs] [lbs] [MMBtu] SO2 Ratio NOx Ratio Heat Input Average Values [2000-2004] Calculated Ratios

FL Nov 2 2,653,691 1,395,551 5,353,049 0.0261 0.0250 0.0286 FL Nov 3 2,586,368 1,355,820 5,261,410 0.0254 0.0243 0.0281 FL Nov 4 2,598,990 1,378,455 5,353,885 0.0255 0.0247 0.0286 FL Nov 5 2,819,377 1,506,116 5,782,260 0.0277 0.0270 0.0309 FL Nov 6 3,302,710 1,792,289 6,614,270 0.0324 0.0321 0.0354 FL Nov 7 3,734,201 2,034,922 7,193,222 0.0367 0.0364 0.0385 FL Nov 8 4,072,530 2,217,271 7,562,409 0.0400 0.0397 0.0404 FL Nov 9 4,497,804 2,477,548 7,992,516 0.0442 0.0444 0.0427 FL Nov 10 4,816,543 2,669,967 8,478,717 0.0473 0.0478 0.0453 FL Nov 11 4,973,313 2,782,983 8,868,292 0.0489 0.0498 0.0474 FL Nov 12 5,118,667 2,866,930 9,226,948 0.0503 0.0513 0.0493 FL Nov 13 5,187,656 2,908,628 9,435,498 0.0510 0.0521 0.0505 FL Nov 14 5,207,361 2,925,067 9,516,005 0.0512 0.0524 0.0509 FL Nov 15 5,186,047 2,916,563 9,510,674 0.0510 0.0522 0.0509 FL Nov 16 5,165,234 2,887,608 9,415,200 0.0507 0.0517 0.0504 FL Nov 17 5,372,940 2,950,688 9,536,043 0.0528 0.0528 0.0510 FL Nov 18 5,786,071 3,242,415 10,104,293 0.0568 0.0580 0.0540 FL Nov 19 5,502,445 3,071,543 9,685,622 0.0541 0.0550 0.0518 FL Nov 20 5,083,579 2,787,902 8,950,110 0.0499 0.0499 0.0479 FL Nov 21 4,606,891 2,501,085 8,062,198 0.0453 0.0448 0.0431 FL Nov 22 4,121,388 2,198,178 7,242,891 0.0405 0.0394 0.0387 FL Nov 23 3,565,017 1,906,796 6,506,948 0.0350 0.0341 0.0348 FL Dec 0 3,867,036 1,958,903 6,697,383 0.0335 0.0323 0.0339 FL Dec 1 3,646,266 1,827,185 6,449,122 0.0315 0.0302 0.0326 FL Dec 2 3,531,691 1,771,459 6,333,062 0.0306 0.0292 0.0321 FL Dec 3 3,530,144 1,784,984 6,386,244 0.0305 0.0295 0.0323 FL Dec 4 3,591,211 1,829,544 6,604,823 0.0311 0.0302 0.0334 FL Dec 5 3,878,589 2,007,700 7,188,348 0.0336 0.0331 0.0364 FL Dec 6 4,514,013 2,346,050 8,223,759 0.0391 0.0387 0.0416 FL Dec 7 5,015,086 2,616,065 8,843,233 0.0434 0.0432 0.0448 FL Dec 8 5,230,443 2,748,219 9,012,759 0.0453 0.0454 0.0456 FL Dec 9 5,364,090 2,830,596 9,011,280 0.0464 0.0467 0.0456 FL Dec 10 5,394,263 2,883,931 8,907,500 0.0467 0.0476 0.0451 FL Dec 11 5,246,008 2,804,416 8,686,481 0.0454 0.0463 0.0440 FL Dec 12 5,131,615 2,728,167 8,552,591 0.0444 0.0450 0.0433 FL Dec 13 5,010,970 2,670,246 8,458,189 0.0434 0.0441 0.0428 FL Dec 14 4,860,948 2,552,274 8,308,360 0.0421 0.0421 0.0420 FL Dec 15 4,796,664 2,524,132 8,249,553 0.0415 0.0417 0.0418 FL Dec 16 4,920,343 2,580,134 8,347,312 0.0426 0.0426 0.0422 FL Dec 17 5,445,792 2,859,955 9,027,178 0.0471 0.0472 0.0457 FL Dec 18 6,101,562 3,267,980 10,037,688 0.0528 0.0540 0.0508 FL Dec 19 5,991,902 3,205,477 9,967,374 0.0518 0.0529 0.0504 FL Dec 20 5,759,969 3,055,643 9,593,120 0.0498 0.0505 0.0486 FL Dec 21 5,416,896 2,849,012 9,004,299 0.0469 0.0470 0.0456 FL Dec 22 4,967,136 2,594,369 8,264,178 0.0430 0.0428 0.0418 FL Dec 23 4,376,102 2,270,002 7,438,294 0.0379 0.0375 0.0376 GA Jan 0 4,233,689 1,304,214 3,602,490 0.0380 0.0369 0.0355 GA Jan 1 4,069,755 1,242,993 3,360,124 0.0365 0.0352 0.0331 GA Jan 2 4,036,727 1,236,644 3,363,390 0.0362 0.0350 0.0331 GA Jan 3 4,084,970 1,261,863 3,490,189 0.0367 0.0357 0.0344 GA Jan 4 4,187,679 1,305,573 3,674,953 0.0376 0.0370 0.0362 GA Jan 5 4,413,590 1,397,250 4,080,038 0.0396 0.0396 0.0402 GA Jan 6 4,762,719 1,532,193 4,632,863 0.0428 0.0434 0.0456

H-11Atmospheric Sciences Group 

### Appendix H Average 2000-2004 State Level Monthly-Diurnal Profiles

CEM-Based Distribution Alpine Geophysics

SO2 Mass NOx Mass Heat Input State Month Hour [lbs] [lbs] [MMBtu] SO2 Ratio NOx Ratio Heat Input Average Values [2000-2004] Calculated Ratios

GA Jan 7 4,959,825 1,614,529 5,048,216 0.0445 0.0457 0.0497 GA Jan 8 4,980,466 1,638,500 5,145,586 0.0447 0.0464 0.0507 GA Jan 9 5,038,432 1,636,170 5,034,586 0.0452 0.0464 0.0496 GA Jan 10 5,027,956 1,623,096 4,814,350 0.0451 0.0460 0.0474 GA Jan 11 4,917,419 1,577,624 4,517,124 0.0441 0.0447 0.0445 GA Jan 12 4,785,959 1,518,170 4,183,606 0.0430 0.0430 0.0412 GA Jan 13 4,654,797 1,472,083 4,005,913 0.0418 0.0417 0.0394 GA Jan 14 4,502,347 1,414,721 3,869,244 0.0404 0.0401 0.0381 GA Jan 15 4,421,647 1,382,037 3,798,692 0.0397 0.0392 0.0374 GA Jan 16 4,411,331 1,378,984 3,815,287 0.0396 0.0391 0.0376 GA Jan 17 4,600,671 1,441,859 4,086,980 0.0413 0.0408 0.0402 GA Jan 18 5,002,493 1,594,476 4,576,213 0.0449 0.0452 0.0451 GA Jan 19 5,009,244 1,604,307 4,711,802 0.0450 0.0454 0.0464 GA Jan 20 4,965,073 1,590,262 4,702,389 0.0446 0.0450 0.0463 GA Jan 21 4,963,539 1,581,832 4,629,572 0.0446 0.0448 0.0456 GA Jan 22 4,817,725 1,531,220 4,449,776 0.0433 0.0434 0.0438 GA Jan 23 4,533,780 1,419,571 3,985,482 0.0407 0.0402 0.0392 GA Feb 0 3,774,340 1,130,138 2,958,453 0.0382 0.0368 0.0341 GA Feb 1 3,574,504 1,067,150 2,758,105 0.0361 0.0348 0.0318 GA Feb 2 3,492,743 1,051,378 2,710,799 0.0353 0.0343 0.0313 GA Feb 3 3,526,641 1,070,488 2,777,636 0.0357 0.0349 0.0320 GA Feb 4 3,588,548 1,096,820 2,928,871 0.0363 0.0358 0.0338 GA Feb 5 3,775,058 1,177,114 3,298,174 0.0382 0.0384 0.0380 GA Feb 6 4,167,738 1,314,960 3,899,627 0.0421 0.0429 0.0450 GA Feb 7 4,340,787 1,386,477 4,218,243 0.0439 0.0452 0.0486 GA Feb 8 4,371,863 1,400,001 4,243,185 0.0442 0.0456 0.0489 GA Feb 9 4,433,066 1,403,554 4,174,920 0.0448 0.0458 0.0481 GA Feb 10 4,443,237 1,396,970 4,068,977 0.0449 0.0455 0.0469 GA Feb 11 4,425,360 1,378,942 3,983,664 0.0447 0.0449 0.0459 GA Feb 12 4,357,426 1,352,110 3,864,261 0.0441 0.0441 0.0446 GA Feb 13 4,280,320 1,327,913 3,729,155 0.0433 0.0433 0.0430 GA Feb 14 4,184,175 1,305,094 3,640,022 0.0423 0.0425 0.0420 GA Feb 15 4,114,094 1,273,613 3,589,221 0.0416 0.0415 0.0414 GA Feb 16 4,070,973 1,262,909 3,578,142 0.0412 0.0412 0.0413 GA Feb 17 4,106,193 1,266,073 3,628,022 0.0415 0.0413 0.0418 GA Feb 18 4,346,078 1,348,178 3,895,020 0.0439 0.0439 0.0449 GA Feb 19 4,492,274 1,404,199 4,038,269 0.0454 0.0458 0.0466 GA Feb 20 4,424,737 1,379,514 3,981,189 0.0447 0.0450 0.0459 GA Feb 21 4,374,151 1,361,595 3,873,017 0.0442 0.0444 0.0447 GA Feb 22 4,233,273 1,307,169 3,626,230 0.0428 0.0426 0.0418 GA Feb 23 3,998,749 1,216,302 3,255,135 0.0404 0.0396 0.0375 GA Mar 0 3,997,495 1,189,785 3,154,773 0.0375 0.0360 0.0342 GA Mar 1 3,738,974 1,109,156 2,891,616 0.0351 0.0335 0.0313 GA Mar 2 3,585,477 1,068,313 2,786,741 0.0337 0.0323 0.0302 GA Mar 3 3,558,898 1,065,843 2,798,856 0.0334 0.0322 0.0303 GA Mar 4 3,615,956 1,100,086 2,984,181 0.0340 0.0333 0.0324 GA Mar 5 3,893,344 1,195,768 3,355,232 0.0366 0.0361 0.0364 GA Mar 6 4,365,454 1,374,678 3,958,846 0.0410 0.0416 0.0429 GA Mar 7 4,537,585 1,441,590 4,213,546 0.0426 0.0436 0.0457 GA Mar 8 4,623,927 1,467,417 4,258,813 0.0434 0.0444 0.0462 GA Mar 9 4,776,001 1,511,176 4,314,932 0.0449 0.0457 0.0468 GA Mar 10 4,832,769 1,529,287 4,307,109 0.0454 0.0462 0.0467 GA Mar 11 4,820,067 1,525,683 4,301,294 0.0453 0.0461 0.0466

H-12Atmospheric Sciences Group 

### Appendix H Average 2000-2004 State Level Monthly-Diurnal Profiles

CEM-Based Distribution Alpine Geophysics

SO2 Mass NOx Mass Heat Input State Month Hour [lbs] [lbs] [MMBtu] SO2 Ratio NOx Ratio Heat Input Average Values [2000-2004] Calculated Ratios

GA Mar 12 4,809,839 1,512,714 4,247,577 0.0452 0.0457 0.0460 GA Mar 13 4,757,300 1,489,644 4,136,289 0.0447 0.0450 0.0448 GA Mar 14 4,717,782 1,477,282 4,099,208 0.0443 0.0447 0.0444 GA Mar 15 4,713,095 1,473,379 4,102,564 0.0443 0.0445 0.0445 GA Mar 16 4,686,402 1,463,323 4,082,266 0.0440 0.0442 0.0443 GA Mar 17 4,618,436 1,432,837 4,026,578 0.0434 0.0433 0.0437 GA Mar 18 4,641,666 1,440,117 4,064,085 0.0436 0.0435 0.0441 GA Mar 19 4,892,867 1,544,277 4,351,853 0.0459 0.0467 0.0472 GA Mar 20 4,811,260 1,515,075 4,312,097 0.0452 0.0458 0.0467 GA Mar 21 4,690,833 1,461,199 4,130,124 0.0441 0.0442 0.0448 GA Mar 22 4,519,180 1,390,013 3,859,115 0.0424 0.0420 0.0418 GA Mar 23 4,280,676 1,300,423 3,505,280 0.0402 0.0393 0.0380 GA Apr 0 3,564,230 971,430 2,917,929 0.0346 0.0324 0.0282 GA Apr 1 3,339,119 905,329 2,732,239 0.0324 0.0302 0.0264 GA Apr 2 3,241,743 877,514 2,678,089 0.0315 0.0292 0.0259 GA Apr 3 3,255,517 885,104 2,714,157 0.0316 0.0295 0.0263 GA Apr 4 3,457,823 952,887 2,963,657 0.0336 0.0318 0.0287 GA Apr 5 3,961,985 1,135,362 3,481,924 0.0385 0.0378 0.0337 GA Apr 6 4,241,795 1,229,424 3,813,166 0.0412 0.0410 0.0369 GA Apr 7 4,401,604 1,275,710 3,966,276 0.0427 0.0425 0.0384 GA Apr 8 4,554,260 1,326,462 4,085,351 0.0442 0.0442 0.0395 GA Apr 9 4,655,368 1,359,978 4,229,157 0.0452 0.0453 0.0409 GA Apr 10 4,708,373 1,401,019 4,580,473 0.0457 0.0467 0.0443 GA Apr 11 4,703,864 1,410,975 4,870,975 0.0457 0.0470 0.0471 GA Apr 12 4,706,411 1,424,680 5,117,829 0.0457 0.0475 0.0495 GA Apr 13 4,716,791 1,439,289 5,394,576 0.0458 0.0480 0.0522 GA Apr 14 4,720,339 1,442,419 5,451,060 0.0458 0.0481 0.0528 GA Apr 15 4,735,104 1,448,755 5,561,599 0.0460 0.0483 0.0538 GA Apr 16 4,703,517 1,431,275 5,545,151 0.0457 0.0477 0.0537 GA Apr 17 4,610,615 1,381,529 5,419,379 0.0448 0.0460 0.0525 GA Apr 18 4,491,048 1,325,156 5,255,384 0.0436 0.0442 0.0509 GA Apr 19 4,686,475 1,395,209 5,312,978 0.0455 0.0465 0.0514 GA Apr 20 4,775,348 1,416,077 5,255,071 0.0464 0.0472 0.0509 GA Apr 21 4,585,231 1,323,660 4,778,860 0.0445 0.0441 0.0463 GA Apr 22 4,269,437 1,191,494 3,936,623 0.0415 0.0397 0.0381 GA Apr 23 3,888,147 1,058,123 3,262,708 0.0378 0.0353 0.0316 GA May 0 3,651,805 808,018 2,983,275 0.0347 0.0311 0.0279 GA May 1 3,436,095 746,479 2,781,290 0.0326 0.0287 0.0260 GA May 2 3,348,132 717,894 2,702,478 0.0318 0.0276 0.0253 GA May 3 3,334,788 713,170 2,703,132 0.0317 0.0275 0.0253 GA May 4 3,446,730 753,127 2,848,337 0.0327 0.0290 0.0266 GA May 5 3,779,436 863,032 3,208,566 0.0359 0.0332 0.0300 GA May 6 3,987,086 944,548 3,517,897 0.0379 0.0364 0.0329 GA May 7 4,163,886 1,018,931 3,905,273 0.0395 0.0392 0.0365 GA May 8 4,424,183 1,094,434 4,219,525 0.0420 0.0421 0.0395 GA May 9 4,670,900 1,173,432 4,529,682 0.0444 0.0452 0.0424 GA May 10 4,843,085 1,236,541 4,850,410 0.0460 0.0476 0.0454 GA May 11 4,924,055 1,267,461 5,178,330 0.0468 0.0488 0.0484 GA May 12 4,964,755 1,294,195 5,474,421 0.0472 0.0498 0.0512 GA May 13 4,991,458 1,317,943 5,747,084 0.0474 0.0508 0.0537 GA May 14 5,029,247 1,331,694 5,932,574 0.0478 0.0513 0.0555 GA May 15 5,034,896 1,332,001 6,003,879 0.0478 0.0513 0.0561 GA May 16 5,003,154 1,314,935 5,970,214 0.0475 0.0506 0.0558

H-13Atmospheric Sciences Group 

### Appendix H Average 2000-2004 State Level Monthly-Diurnal Profiles

CEM-Based Distribution Alpine Geophysics

SO2 Mass NOx Mass Heat Input State Month Hour [lbs] [lbs] [MMBtu] SO2 Ratio NOx Ratio Heat Input Average Values [2000-2004] Calculated Ratios

GA May 17 4,914,107 1,273,901 5,778,889 0.0467 0.0491 0.0540 GA May 18 4,762,392 1,216,180 5,526,261 0.0452 0.0468 0.0517 GA May 19 4,735,841 1,205,339 5,405,658 0.0450 0.0464 0.0505 GA May 20 4,900,591 1,254,824 5,403,299 0.0465 0.0483 0.0505 GA May 21 4,668,636 1,164,526 4,883,439 0.0443 0.0448 0.0457 GA May 22 4,315,373 1,023,301 4,023,238 0.0410 0.0394 0.0376 GA May 23 3,963,186 903,119 3,375,443 0.0376 0.0348 0.0316 GA Jun 0 3,539,056 783,143 2,898,646 0.0346 0.0317 0.0273 GA Jun 1 3,342,924 724,888 2,707,026 0.0327 0.0293 0.0255 GA Jun 2 3,238,457 691,664 2,613,966 0.0317 0.0280 0.0247 GA Jun 3 3,198,469 679,105 2,581,471 0.0313 0.0275 0.0244 GA Jun 4 3,277,062 705,914 2,687,844 0.0320 0.0285 0.0254 GA Jun 5 3,467,538 758,652 2,875,700 0.0339 0.0307 0.0271 GA Jun 6 3,611,886 809,678 3,072,767 0.0353 0.0327 0.0290 GA Jun 7 3,857,779 897,104 3,406,586 0.0377 0.0363 0.0321 GA Jun 8 4,163,525 988,231 3,773,158 0.0407 0.0399 0.0356 GA Jun 9 4,513,208 1,097,174 4,254,964 0.0441 0.0443 0.0401 GA Jun 10 4,782,141 1,192,779 4,820,628 0.0468 0.0482 0.0455 GA Jun 11 4,920,265 1,247,510 5,332,737 0.0481 0.0504 0.0503 GA Jun 12 4,957,509 1,278,881 5,769,697 0.0485 0.0517 0.0544 GA Jun 13 4,981,459 1,297,463 6,002,578 0.0487 0.0524 0.0566 GA Jun 14 4,986,980 1,294,551 6,099,520 0.0488 0.0523 0.0575 GA Jun 15 4,989,560 1,292,507 6,153,735 0.0488 0.0522 0.0581 GA Jun 16 4,952,392 1,274,892 6,091,568 0.0484 0.0515 0.0575 GA Jun 17 4,836,568 1,235,405 5,954,563 0.0473 0.0499 0.0562 GA Jun 18 4,705,878 1,189,573 5,785,139 0.0460 0.0481 0.0546 GA Jun 19 4,618,851 1,158,250 5,588,600 0.0452 0.0468 0.0527 GA Jun 20 4,756,115 1,183,186 5,416,940 0.0465 0.0478 0.0511 GA Jun 21 4,552,378 1,108,365 4,893,067 0.0445 0.0448 0.0462 GA Jun 22 4,199,228 988,296 3,994,790 0.0411 0.0399 0.0377 GA Jun 23 3,822,417 861,775 3,230,562 0.0374 0.0348 0.0305 GA Jul 0 3,916,819 877,213 3,541,583 0.0359 0.0325 0.0293 GA Jul 1 3,650,716 805,041 3,167,031 0.0335 0.0299 0.0262 GA Jul 2 3,514,882 765,635 3,014,404 0.0323 0.0284 0.0249 GA Jul 3 3,452,895 747,095 2,961,853 0.0317 0.0277 0.0245 GA Jul 4 3,511,223 767,987 3,045,310 0.0322 0.0285 0.0252 GA Jul 5 3,704,041 826,229 3,250,414 0.0340 0.0307 0.0269 GA Jul 6 3,829,278 867,426 3,468,228 0.0351 0.0322 0.0287 GA Jul 7 4,091,703 953,981 3,809,941 0.0376 0.0354 0.0315 GA Jul 8 4,457,430 1,077,515 4,336,979 0.0409 0.0400 0.0359 GA Jul 9 4,806,955 1,207,677 4,964,175 0.0441 0.0448 0.0411 GA Jul 10 5,036,079 1,300,925 5,666,292 0.0462 0.0483 0.0469 GA Jul 11 5,155,520 1,349,260 6,155,695 0.0473 0.0501 0.0509 GA Jul 12 5,177,825 1,371,464 6,492,532 0.0475 0.0509 0.0537 GA Jul 13 5,175,246 1,379,488 6,643,936 0.0475 0.0512 0.0550 GA Jul 14 5,194,096 1,376,909 6,701,037 0.0477 0.0511 0.0554 GA Jul 15 5,193,852 1,371,416 6,710,450 0.0477 0.0509 0.0555 GA Jul 16 5,171,250 1,361,059 6,684,938 0.0475 0.0505 0.0553 GA Jul 17 5,116,520 1,335,488 6,577,580 0.0470 0.0495 0.0544 GA Jul 18 5,034,524 1,301,262 6,433,627 0.0462 0.0483 0.0532 GA Jul 19 4,973,180 1,280,116 6,269,343 0.0456 0.0475 0.0519 GA Jul 20 5,062,736 1,303,367 6,155,679 0.0465 0.0484 0.0509 GA Jul 21 4,866,836 1,225,906 5,752,022 0.0447 0.0455 0.0476

H-14Atmospheric Sciences Group 

### Appendix H Average 2000-2004 State Level Monthly-Diurnal Profiles

CEM-Based Distribution Alpine Geophysics

SO2 Mass NOx Mass Heat Input State Month Hour [lbs] [lbs] [MMBtu] SO2 Ratio NOx Ratio Heat Input Average Values [2000-2004] Calculated Ratios

GA Jul 22 4,604,811 1,113,275 4,995,747 0.0423 0.0413 0.0413 GA Jul 23 4,258,902 986,882 4,079,119 0.0391 0.0366 0.0337 GA Aug 0 3,899,937 855,590 3,426,179 0.0359 0.0321 0.0285 GA Aug 1 3,645,352 794,616 3,103,869 0.0335 0.0298 0.0258 GA Aug 2 3,506,094 756,285 2,972,926 0.0322 0.0284 0.0247 GA Aug 3 3,440,903 742,445 2,933,373 0.0316 0.0279 0.0244 GA Aug 4 3,532,488 773,278 3,076,898 0.0325 0.0290 0.0256 GA Aug 5 3,841,756 865,886 3,377,050 0.0353 0.0325 0.0281 GA Aug 6 3,988,737 913,918 3,599,891 0.0367 0.0343 0.0300 GA Aug 7 4,115,834 961,077 3,859,834 0.0378 0.0361 0.0321 GA Aug 8 4,410,849 1,055,034 4,285,284 0.0406 0.0396 0.0357 GA Aug 9 4,741,335 1,174,399 4,876,520 0.0436 0.0441 0.0406 GA Aug 10 4,972,801 1,268,303 5,513,837 0.0457 0.0476 0.0459 GA Aug 11 5,072,919 1,309,543 6,015,051 0.0466 0.0492 0.0500 GA Aug 12 5,114,743 1,343,072 6,406,516 0.0470 0.0504 0.0533 GA Aug 13 5,141,330 1,358,804 6,585,912 0.0473 0.0510 0.0548 GA Aug 14 5,194,964 1,370,203 6,668,961 0.0478 0.0514 0.0555 GA Aug 15 5,222,165 1,375,254 6,718,781 0.0480 0.0516 0.0559 GA Aug 16 5,185,128 1,355,869 6,691,244 0.0477 0.0509 0.0557 GA Aug 17 5,103,254 1,324,349 6,589,148 0.0469 0.0497 0.0548 GA Aug 18 5,003,743 1,282,766 6,434,687 0.0460 0.0482 0.0535 GA Aug 19 5,063,989 1,295,580 6,373,416 0.0466 0.0486 0.0530 GA Aug 20 5,089,131 1,292,450 6,247,038 0.0468 0.0485 0.0520 GA Aug 21 4,795,709 1,169,200 5,654,475 0.0441 0.0439 0.0470 GA Aug 22 4,486,241 1,051,342 4,812,187 0.0413 0.0395 0.0400 GA Aug 23 4,182,935 950,486 3,967,411 0.0385 0.0357 0.0330 GA Sep 0 3,374,537 727,276 2,859,911 0.0345 0.0310 0.0275 GA Sep 1 3,210,218 685,875 2,683,783 0.0328 0.0292 0.0258 GA Sep 2 3,153,568 669,187 2,627,830 0.0322 0.0285 0.0252 GA Sep 3 3,131,174 663,527 2,613,517 0.0320 0.0283 0.0251 GA Sep 4 3,244,687 699,243 2,761,757 0.0331 0.0298 0.0265 GA Sep 5 3,548,272 789,280 3,064,049 0.0362 0.0336 0.0294 GA Sep 6 3,745,576 852,643 3,280,593 0.0383 0.0363 0.0315 GA Sep 7 3,794,073 881,809 3,444,831 0.0387 0.0375 0.0331 GA Sep 8 4,002,588 949,104 3,767,079 0.0409 0.0404 0.0362 GA Sep 9 4,256,241 1,033,429 4,083,764 0.0435 0.0440 0.0392 GA Sep 10 4,451,006 1,107,189 4,569,307 0.0455 0.0471 0.0439 GA Sep 11 4,564,647 1,152,980 5,152,056 0.0466 0.0491 0.0495 GA Sep 12 4,608,962 1,177,435 5,560,161 0.0471 0.0501 0.0534 GA Sep 13 4,627,153 1,190,764 5,783,572 0.0473 0.0507 0.0556 GA Sep 14 4,681,501 1,200,116 5,879,271 0.0478 0.0511 0.0565 GA Sep 15 4,695,492 1,198,842 5,967,405 0.0480 0.0510 0.0573 GA Sep 16 4,669,153 1,187,923 5,976,244 0.0477 0.0506 0.0574 GA Sep 17 4,567,468 1,149,742 5,805,500 0.0466 0.0490 0.0558 GA Sep 18 4,539,377 1,132,314 5,675,597 0.0464 0.0482 0.0545 GA Sep 19 4,694,527 1,184,088 5,733,354 0.0479 0.0504 0.0551 GA Sep 20 4,599,510 1,143,616 5,342,792 0.0470 0.0487 0.0513 GA Sep 21 4,262,360 1,017,576 4,559,609 0.0435 0.0433 0.0438 GA Sep 22 3,883,605 889,294 3,697,881 0.0397 0.0379 0.0355 GA Sep 23 3,613,029 804,234 3,182,885 0.0369 0.0342 0.0306 GA Oct 0 3,424,077 966,476 2,726,697 0.0337 0.0318 0.0283 GA Oct 1 3,252,068 915,461 2,577,881 0.0320 0.0301 0.0267 GA Oct 2 3,176,936 892,948 2,520,048 0.0313 0.0294 0.0261

H-15Atmospheric Sciences Group 

### Appendix H Average 2000-2004 State Level Monthly-Diurnal Profiles

CEM-Based Distribution Alpine Geophysics

SO2 Mass NOx Mass Heat Input State Month Hour [lbs] [lbs] [MMBtu] SO2 Ratio NOx Ratio Heat Input Average Values [2000-2004] Calculated Ratios

GA Oct 3 3,175,461 897,825 2,557,847 0.0313 0.0296 0.0265 GA Oct 4 3,348,361 956,620 2,744,659 0.0330 0.0315 0.0285 GA Oct 5 3,820,292 1,114,324 3,199,393 0.0376 0.0367 0.0332 GA Oct 6 4,202,916 1,250,409 3,611,767 0.0414 0.0412 0.0374 GA Oct 7 4,204,944 1,270,721 3,743,463 0.0414 0.0418 0.0388 GA Oct 8 4,409,792 1,330,379 3,923,733 0.0434 0.0438 0.0407 GA Oct 9 4,595,307 1,397,727 4,201,872 0.0453 0.0460 0.0436 GA Oct 10 4,711,321 1,433,500 4,428,597 0.0464 0.0472 0.0459 GA Oct 11 4,738,024 1,443,424 4,583,088 0.0467 0.0475 0.0475 GA Oct 12 4,760,172 1,455,292 4,826,392 0.0469 0.0479 0.0500 GA Oct 13 4,758,664 1,464,295 5,010,417 0.0469 0.0482 0.0519 GA Oct 14 4,763,471 1,465,501 5,158,158 0.0469 0.0483 0.0535 GA Oct 15 4,717,659 1,449,246 5,136,118 0.0465 0.0477 0.0533 GA Oct 16 4,611,236 1,407,859 5,035,569 0.0454 0.0464 0.0522 GA Oct 17 4,512,979 1,370,102 4,912,889 0.0444 0.0451 0.0509 GA Oct 18 4,768,229 1,449,458 5,048,325 0.0470 0.0477 0.0523 GA Oct 19 4,762,668 1,452,551 5,052,950 0.0469 0.0478 0.0524 GA Oct 20 4,639,316 1,405,279 4,762,206 0.0457 0.0463 0.0494 GA Oct 21 4,410,969 1,314,796 4,141,260 0.0434 0.0433 0.0429 GA Oct 22 4,061,281 1,194,468 3,501,240 0.0400 0.0393 0.0363 GA Oct 23 3,710,386 1,070,787 3,048,189 0.0365 0.0353 0.0316 GA Nov 0 3,339,248 974,946 2,619,608 0.0356 0.0345 0.0334 GA Nov 1 3,104,177 907,681 2,423,547 0.0331 0.0322 0.0309 GA Nov 2 3,020,999 886,724 2,355,047 0.0322 0.0314 0.0300 GA Nov 3 3,013,150 886,579 2,353,815 0.0321 0.0314 0.0300 GA Nov 4 3,066,621 906,274 2,421,072 0.0327 0.0321 0.0309 GA Nov 5 3,294,479 981,968 2,662,847 0.0351 0.0348 0.0339 GA Nov 6 3,768,468 1,133,368 3,123,551 0.0402 0.0402 0.0398 GA Nov 7 4,045,097 1,235,041 3,506,006 0.0431 0.0438 0.0447 GA Nov 8 4,161,953 1,273,471 3,644,833 0.0444 0.0451 0.0465 GA Nov 9 4,287,329 1,310,591 3,701,404 0.0457 0.0464 0.0472 GA Nov 10 4,331,493 1,317,657 3,655,153 0.0462 0.0467 0.0466 GA Nov 11 4,297,831 1,314,550 3,618,832 0.0458 0.0466 0.0461 GA Nov 12 4,228,371 1,283,989 3,561,181 0.0451 0.0455 0.0454 GA Nov 13 4,165,705 1,260,147 3,531,828 0.0444 0.0446 0.0450 GA Nov 14 4,131,484 1,247,108 3,519,628 0.0441 0.0442 0.0449 GA Nov 15 4,062,566 1,219,187 3,486,301 0.0433 0.0432 0.0444 GA Nov 16 4,031,658 1,215,620 3,499,167 0.0430 0.0431 0.0446 GA Nov 17 4,213,972 1,274,386 3,628,985 0.0449 0.0452 0.0463 GA Nov 18 4,521,904 1,386,003 3,960,477 0.0482 0.0491 0.0505 GA Nov 19 4,382,118 1,337,215 3,843,649 0.0467 0.0474 0.0490 GA Nov 20 4,320,515 1,309,486 3,677,802 0.0461 0.0464 0.0469 GA Nov 21 4,240,784 1,275,965 3,501,895 0.0452 0.0452 0.0446 GA Nov 22 4,064,271 1,209,613 3,259,259 0.0433 0.0429 0.0416 GA Nov 23 3,665,672 1,075,833 2,883,966 0.0391 0.0381 0.0368 GA Dec 0 3,837,633 1,131,780 3,093,718 0.0380 0.0370 0.0351 GA Dec 1 3,672,392 1,082,553 2,924,854 0.0364 0.0354 0.0332 GA Dec 2 3,621,449 1,073,040 2,894,487 0.0359 0.0351 0.0328 GA Dec 3 3,640,778 1,080,398 2,937,894 0.0360 0.0353 0.0333 GA Dec 4 3,721,883 1,112,084 3,085,335 0.0368 0.0364 0.0350 GA Dec 5 3,910,893 1,178,593 3,433,534 0.0387 0.0386 0.0389 GA Dec 6 4,226,394 1,282,594 3,879,233 0.0418 0.0420 0.0440 GA Dec 7 4,482,590 1,370,859 4,255,348 0.0444 0.0448 0.0482

H-16Atmospheric Sciences Group 

### Appendix H Average 2000-2004 State Level Monthly-Diurnal Profiles

CEM-Based Distribution Alpine Geophysics

SO2 Mass NOx Mass Heat Input State Month Hour [lbs] [lbs] [MMBtu] SO2 Ratio NOx Ratio Heat Input Average Values [2000-2004] Calculated Ratios

GA Dec 8 4,558,899 1,409,269 4,358,639 0.0451 0.0461 0.0494 GA Dec 9 4,612,392 1,424,630 4,293,378 0.0457 0.0466 0.0487 GA Dec 10 4,573,677 1,403,007 4,160,159 0.0453 0.0459 0.0472 GA Dec 11 4,458,898 1,355,399 3,887,129 0.0441 0.0443 0.0441 GA Dec 12 4,308,783 1,297,717 3,629,673 0.0427 0.0424 0.0411 GA Dec 13 4,156,484 1,255,626 3,506,045 0.0412 0.0411 0.0397 GA Dec 14 4,015,529 1,210,667 3,411,210 0.0398 0.0396 0.0387 GA Dec 15 3,959,067 1,196,777 3,433,052 0.0392 0.0391 0.0389 GA Dec 16 4,005,596 1,213,230 3,525,463 0.0397 0.0397 0.0400 GA Dec 17 4,309,394 1,323,255 3,849,614 0.0427 0.0433 0.0436 GA Dec 18 4,666,711 1,437,174 4,246,551 0.0462 0.0470 0.0481 GA Dec 19 4,572,719 1,403,027 4,144,171 0.0453 0.0459 0.0470 GA Dec 20 4,548,095 1,387,602 4,091,091 0.0450 0.0454 0.0464 GA Dec 21 4,571,509 1,388,237 4,027,651 0.0453 0.0454 0.0457 GA Dec 22 4,453,767 1,333,361 3,780,662 0.0441 0.0436 0.0429 GA Dec 23 4,121,076 1,219,656 3,374,982 0.0408 0.0399 0.0383 KY Jan 0 4,500,866 2,001,047 3,975,257 0.0393 0.0393 0.0385 KY Jan 1 4,436,772 1,977,257 3,908,176 0.0388 0.0388 0.0379 KY Jan 2 4,412,167 1,966,631 3,883,196 0.0386 0.0386 0.0376 KY Jan 3 4,405,383 1,974,544 3,894,925 0.0385 0.0387 0.0378 KY Jan 4 4,435,119 1,990,452 3,944,448 0.0388 0.0391 0.0382 KY Jan 5 4,513,939 2,035,915 4,082,797 0.0394 0.0399 0.0396 KY Jan 6 4,735,881 2,124,301 4,313,142 0.0414 0.0417 0.0418 KY Jan 7 4,881,373 2,179,241 4,507,545 0.0427 0.0428 0.0437 KY Jan 8 4,899,244 2,207,273 4,565,778 0.0428 0.0433 0.0443 KY Jan 9 4,959,430 2,220,561 4,581,241 0.0433 0.0436 0.0444 KY Jan 10 4,966,733 2,218,116 4,560,570 0.0434 0.0435 0.0442 KY Jan 11 4,926,481 2,185,309 4,469,160 0.0430 0.0429 0.0433 KY Jan 12 4,897,325 2,166,493 4,396,183 0.0428 0.0425 0.0426 KY Jan 13 4,858,282 2,145,888 4,334,245 0.0424 0.0421 0.0420 KY Jan 14 4,803,975 2,121,569 4,259,493 0.0420 0.0416 0.0413 KY Jan 15 4,787,506 2,116,853 4,251,772 0.0418 0.0415 0.0412 KY Jan 16 4,805,200 2,132,483 4,277,592 0.0420 0.0418 0.0415 KY Jan 17 4,902,475 2,173,992 4,377,939 0.0428 0.0427 0.0424 KY Jan 18 5,019,134 2,227,712 4,540,738 0.0439 0.0437 0.0440 KY Jan 19 5,000,308 2,222,379 4,582,619 0.0437 0.0436 0.0444 KY Jan 20 4,971,779 2,210,874 4,538,035 0.0434 0.0434 0.0440 KY Jan 21 4,910,317 2,179,426 4,432,861 0.0429 0.0428 0.0430 KY Jan 22 4,784,827 2,126,094 4,305,074 0.0418 0.0417 0.0417 KY Jan 23 4,636,595 2,057,219 4,173,941 0.0405 0.0404 0.0405 KY Feb 0 3,904,092 1,761,180 3,580,773 0.0392 0.0389 0.0386 KY Feb 1 3,816,587 1,728,628 3,495,285 0.0383 0.0382 0.0377 KY Feb 2 3,792,744 1,718,868 3,462,109 0.0381 0.0380 0.0374 KY Feb 3 3,810,281 1,726,383 3,467,620 0.0383 0.0381 0.0374 KY Feb 4 3,842,768 1,745,450 3,507,867 0.0386 0.0386 0.0378 KY Feb 5 3,947,749 1,806,439 3,628,623 0.0396 0.0399 0.0391 KY Feb 6 4,176,764 1,912,472 3,944,300 0.0419 0.0423 0.0426 KY Feb 7 4,281,095 1,958,390 4,125,044 0.0430 0.0433 0.0445 KY Feb 8 4,317,449 1,973,880 4,156,268 0.0434 0.0436 0.0448 KY Feb 9 4,356,226 1,969,929 4,130,960 0.0437 0.0435 0.0446 KY Feb 10 4,359,609 1,964,589 4,086,993 0.0438 0.0434 0.0441 KY Feb 11 4,311,166 1,943,159 4,039,097 0.0433 0.0429 0.0436 KY Feb 12 4,272,545 1,927,415 3,983,427 0.0429 0.0426 0.0430

H-17Atmospheric Sciences Group 

### Appendix H Average 2000-2004 State Level Monthly-Diurnal Profiles

CEM-Based Distribution Alpine Geophysics

SO2 Mass NOx Mass Heat Input State Month Hour [lbs] [lbs] [MMBtu] SO2 Ratio NOx Ratio Heat Input Average Values [2000-2004] Calculated Ratios

KY Feb 13 4,236,215 1,916,654 3,932,234 0.0425 0.0423 0.0424 KY Feb 14 4,167,600 1,882,801 3,848,899 0.0419 0.0416 0.0415 KY Feb 15 4,134,586 1,872,977 3,821,080 0.0415 0.0414 0.0412 KY Feb 16 4,147,038 1,884,240 3,828,076 0.0416 0.0416 0.0413 KY Feb 17 4,197,152 1,920,450 3,887,857 0.0421 0.0424 0.0419 KY Feb 18 4,301,661 1,971,850 4,016,102 0.0432 0.0436 0.0433 KY Feb 19 4,364,422 2,001,534 4,106,892 0.0438 0.0442 0.0443 KY Feb 20 4,344,268 1,987,726 4,061,985 0.0436 0.0439 0.0438 KY Feb 21 4,296,576 1,966,727 4,013,780 0.0431 0.0435 0.0433 KY Feb 22 4,179,160 1,894,824 3,854,612 0.0420 0.0419 0.0416 KY Feb 23 4,024,438 1,823,859 3,712,043 0.0404 0.0403 0.0400 KY Mar 0 4,086,927 1,934,000 3,943,944 0.0384 0.0390 0.0385 KY Mar 1 4,004,215 1,894,561 3,852,671 0.0376 0.0382 0.0376 KY Mar 2 3,977,961 1,875,819 3,810,690 0.0374 0.0378 0.0372 KY Mar 3 3,977,743 1,874,604 3,814,943 0.0374 0.0378 0.0372 KY Mar 4 4,040,951 1,904,597 3,857,613 0.0380 0.0384 0.0376 KY Mar 5 4,163,395 1,975,952 4,001,836 0.0391 0.0399 0.0390 KY Mar 6 4,382,627 2,082,066 4,297,761 0.0412 0.0420 0.0419 KY Mar 7 4,504,820 2,126,263 4,486,558 0.0423 0.0429 0.0438 KY Mar 8 4,562,347 2,144,795 4,534,086 0.0429 0.0433 0.0442 KY Mar 9 4,627,690 2,159,579 4,567,228 0.0435 0.0436 0.0445 KY Mar 10 4,653,192 2,151,241 4,511,098 0.0437 0.0434 0.0440 KY Mar 11 4,641,558 2,133,268 4,448,941 0.0436 0.0430 0.0434 KY Mar 12 4,622,702 2,121,208 4,411,987 0.0434 0.0428 0.0430 KY Mar 13 4,619,393 2,125,075 4,393,357 0.0434 0.0429 0.0429 KY Mar 14 4,552,286 2,088,576 4,330,586 0.0428 0.0421 0.0422 KY Mar 15 4,531,458 2,076,448 4,292,113 0.0426 0.0419 0.0419 KY Mar 16 4,559,495 2,082,061 4,299,148 0.0428 0.0420 0.0419 KY Mar 17 4,566,306 2,095,974 4,333,645 0.0429 0.0423 0.0423 KY Mar 18 4,614,477 2,131,694 4,403,611 0.0434 0.0430 0.0430 KY Mar 19 4,692,033 2,181,572 4,520,447 0.0441 0.0440 0.0441 KY Mar 20 4,691,985 2,182,351 4,554,215 0.0441 0.0440 0.0444 KY Mar 21 4,607,786 2,156,225 4,469,784 0.0433 0.0435 0.0436 KY Mar 22 4,453,423 2,076,668 4,283,360 0.0419 0.0419 0.0418 KY Mar 23 4,277,227 1,999,878 4,106,925 0.0402 0.0403 0.0401 KY Apr 0 3,751,872 1,682,748 3,623,721 0.0371 0.0373 0.0360 KY Apr 1 3,662,781 1,651,886 3,538,402 0.0362 0.0366 0.0352 KY Apr 2 3,620,832 1,638,447 3,506,688 0.0358 0.0363 0.0348 KY Apr 3 3,665,762 1,658,243 3,540,689 0.0363 0.0368 0.0352 KY Apr 4 3,808,138 1,716,346 3,665,877 0.0377 0.0381 0.0364 KY Apr 5 4,024,823 1,815,205 3,894,961 0.0398 0.0402 0.0387 KY Apr 6 4,208,966 1,884,379 4,124,667 0.0416 0.0418 0.0410 KY Apr 7 4,271,575 1,920,454 4,261,166 0.0422 0.0426 0.0423 KY Apr 8 4,393,556 1,942,695 4,351,959 0.0434 0.0431 0.0432 KY Apr 9 4,461,370 1,966,842 4,440,429 0.0441 0.0436 0.0441 KY Apr 10 4,462,912 1,971,490 4,461,202 0.0441 0.0437 0.0443 KY Apr 11 4,451,212 1,972,903 4,476,859 0.0440 0.0437 0.0445 KY Apr 12 4,470,687 1,978,658 4,533,135 0.0442 0.0439 0.0450 KY Apr 13 4,480,194 2,007,588 4,572,059 0.0443 0.0445 0.0454 KY Apr 14 4,443,252 1,988,851 4,545,641 0.0439 0.0441 0.0452 KY Apr 15 4,459,430 1,990,362 4,545,012 0.0441 0.0441 0.0452 KY Apr 16 4,426,122 1,974,950 4,512,511 0.0438 0.0438 0.0448 KY Apr 17 4,375,559 1,955,702 4,480,287 0.0433 0.0434 0.0445

H-18Atmospheric Sciences Group 

### Appendix H Average 2000-2004 State Level Monthly-Diurnal Profiles

CEM-Based Distribution Alpine Geophysics

SO2 Mass NOx Mass Heat Input State Month Hour [lbs] [lbs] [MMBtu] SO2 Ratio NOx Ratio Heat Input Average Values [2000-2004] Calculated Ratios

KY Apr 18 4,346,922 1,937,715 4,442,685 0.0430 0.0430 0.0441 KY Apr 19 4,451,615 1,983,979 4,497,189 0.0440 0.0440 0.0447 KY Apr 20 4,487,128 1,998,714 4,533,191 0.0444 0.0443 0.0450 KY Apr 21 4,346,269 1,920,820 4,312,822 0.0430 0.0426 0.0428 KY Apr 22 4,122,750 1,812,181 4,019,469 0.0408 0.0402 0.0399 KY Apr 23 3,924,575 1,734,979 3,773,132 0.0388 0.0385 0.0375 KY May 0 3,773,655 1,352,468 3,542,077 0.0363 0.0360 0.0356 KY May 1 3,626,105 1,306,849 3,428,995 0.0349 0.0348 0.0344 KY May 2 3,557,597 1,280,494 3,362,397 0.0342 0.0341 0.0338 KY May 3 3,555,469 1,284,693 3,358,152 0.0342 0.0342 0.0337 KY May 4 3,659,305 1,327,703 3,447,123 0.0352 0.0353 0.0346 KY May 5 3,905,440 1,411,666 3,625,333 0.0375 0.0376 0.0364 KY May 6 4,142,333 1,491,145 3,781,949 0.0398 0.0397 0.0380 KY May 7 4,318,983 1,568,459 3,929,856 0.0415 0.0417 0.0395 KY May 8 4,478,646 1,598,725 4,088,864 0.0431 0.0425 0.0411 KY May 9 4,581,002 1,652,673 4,264,629 0.0440 0.0440 0.0428 KY May 10 4,631,086 1,688,064 4,419,795 0.0445 0.0449 0.0444 KY May 11 4,669,476 1,710,802 4,522,994 0.0449 0.0455 0.0454 KY May 12 4,705,224 1,719,757 4,625,655 0.0452 0.0458 0.0465 KY May 13 4,706,169 1,724,945 4,685,196 0.0452 0.0459 0.0471 KY May 14 4,712,999 1,725,831 4,707,889 0.0453 0.0459 0.0473 KY May 15 4,719,302 1,735,212 4,763,219 0.0454 0.0462 0.0478 KY May 16 4,729,889 1,718,237 4,725,277 0.0455 0.0457 0.0475 KY May 17 4,719,789 1,706,360 4,680,119 0.0454 0.0454 0.0470 KY May 18 4,650,145 1,672,135 4,567,479 0.0447 0.0445 0.0459 KY May 19 4,675,073 1,667,803 4,484,805 0.0449 0.0444 0.0451 KY May 20 4,733,280 1,690,796 4,518,596 0.0455 0.0450 0.0454 KY May 21 4,535,352 1,614,490 4,301,519 0.0436 0.0430 0.0432 KY May 22 4,249,836 1,512,277 3,992,532 0.0409 0.0402 0.0401 KY May 23 3,985,492 1,418,470 3,721,915 0.0383 0.0377 0.0374 KY Jun 0 3,863,171 1,220,143 3,431,721 0.0365 0.0358 0.0351 KY Jun 1 3,700,537 1,165,437 3,302,332 0.0350 0.0341 0.0338 KY Jun 2 3,588,577 1,129,534 3,210,334 0.0339 0.0331 0.0328 KY Jun 3 3,586,996 1,129,886 3,190,439 0.0339 0.0331 0.0326 KY Jun 4 3,632,093 1,154,070 3,239,053 0.0343 0.0338 0.0331 KY Jun 5 3,772,311 1,205,869 3,353,578 0.0356 0.0353 0.0343 KY Jun 6 3,863,128 1,248,430 3,502,938 0.0365 0.0366 0.0358 KY Jun 7 4,206,029 1,359,881 3,735,013 0.0397 0.0398 0.0382 KY Jun 8 4,471,390 1,441,168 3,957,538 0.0422 0.0422 0.0405 KY Jun 9 4,645,909 1,506,312 4,129,541 0.0439 0.0441 0.0422 KY Jun 10 4,775,656 1,553,406 4,301,488 0.0451 0.0455 0.0440 KY Jun 11 4,835,680 1,581,661 4,493,449 0.0457 0.0463 0.0459 KY Jun 12 4,776,857 1,585,404 4,599,158 0.0451 0.0465 0.0470 KY Jun 13 4,910,861 1,611,741 4,741,756 0.0464 0.0472 0.0485 KY Jun 14 4,928,605 1,621,672 4,832,356 0.0466 0.0475 0.0494 KY Jun 15 4,942,474 1,619,521 4,850,437 0.0467 0.0475 0.0496 KY Jun 16 4,933,104 1,611,032 4,831,962 0.0466 0.0472 0.0494 KY Jun 17 4,916,801 1,592,114 4,755,486 0.0464 0.0466 0.0486 KY Jun 18 4,856,359 1,562,556 4,620,856 0.0459 0.0458 0.0472 KY Jun 19 4,816,576 1,539,277 4,493,010 0.0455 0.0451 0.0459 KY Jun 20 4,753,614 1,529,185 4,423,245 0.0449 0.0448 0.0452 KY Jun 21 4,655,054 1,482,923 4,278,389 0.0440 0.0435 0.0437 KY Jun 22 4,385,723 1,391,689 3,941,221 0.0414 0.0408 0.0403

H-19Atmospheric Sciences Group 

### Appendix H Average 2000-2004 State Level Monthly-Diurnal Profiles

CEM-Based Distribution Alpine Geophysics

SO2 Mass NOx Mass Heat Input State Month Hour [lbs] [lbs] [MMBtu] SO2 Ratio NOx Ratio Heat Input Average Values [2000-2004] Calculated Ratios

KY Jun 23 4,054,527 1,286,083 3,612,850 0.0383 0.0377 0.0369 KY Jul 0 4,049,096 1,282,804 3,688,261 0.0372 0.0366 0.0344 KY Jul 1 3,859,804 1,223,049 3,520,391 0.0354 0.0349 0.0328 KY Jul 2 3,714,990 1,176,808 3,405,973 0.0341 0.0336 0.0318 KY Jul 3 3,662,887 1,161,823 3,358,049 0.0336 0.0331 0.0313 KY Jul 4 3,704,383 1,178,366 3,395,477 0.0340 0.0336 0.0317 KY Jul 5 3,828,676 1,218,826 3,482,956 0.0352 0.0348 0.0325 KY Jul 6 3,986,423 1,267,527 3,619,712 0.0366 0.0362 0.0338 KY Jul 7 4,247,926 1,349,889 3,855,419 0.0390 0.0385 0.0360 KY Jul 8 4,535,396 1,444,423 4,155,868 0.0417 0.0412 0.0388 KY Jul 9 4,752,020 1,526,015 4,469,496 0.0436 0.0435 0.0417 KY Jul 10 4,884,645 1,578,497 4,770,162 0.0449 0.0450 0.0445 KY Jul 11 4,950,005 1,607,852 5,012,157 0.0455 0.0459 0.0468 KY Jul 12 5,016,008 1,626,016 5,146,206 0.0461 0.0464 0.0480 KY Jul 13 5,045,517 1,642,891 5,271,836 0.0463 0.0469 0.0492 KY Jul 14 5,061,500 1,650,629 5,322,911 0.0465 0.0471 0.0497 KY Jul 15 5,075,205 1,660,057 5,371,341 0.0466 0.0474 0.0501 KY Jul 16 5,056,500 1,657,780 5,382,711 0.0464 0.0473 0.0502 KY Jul 17 5,022,118 1,639,832 5,337,848 0.0461 0.0468 0.0498 KY Jul 18 4,951,315 1,607,513 5,209,080 0.0455 0.0459 0.0486 KY Jul 19 4,911,340 1,587,576 5,072,958 0.0451 0.0453 0.0473 KY Jul 20 4,909,883 1,586,904 5,030,514 0.0451 0.0453 0.0469 KY Jul 21 4,785,599 1,545,511 4,835,539 0.0440 0.0441 0.0451 KY Jul 22 4,570,546 1,464,509 4,450,048 0.0420 0.0418 0.0415 KY Jul 23 4,299,974 1,371,090 4,027,131 0.0395 0.0391 0.0376 KY Aug 0 3,868,606 1,253,876 3,668,033 0.0369 0.0364 0.0348 KY Aug 1 3,698,970 1,200,877 3,519,453 0.0353 0.0348 0.0334 KY Aug 2 3,585,674 1,166,312 3,418,823 0.0342 0.0338 0.0324 KY Aug 3 3,543,793 1,157,396 3,386,520 0.0338 0.0336 0.0321 KY Aug 4 3,621,646 1,183,818 3,458,499 0.0346 0.0343 0.0328 KY Aug 5 3,806,315 1,239,542 3,588,177 0.0363 0.0359 0.0340 KY Aug 6 3,936,819 1,277,616 3,689,986 0.0376 0.0370 0.0350 KY Aug 7 4,114,177 1,348,119 3,846,883 0.0393 0.0391 0.0365 KY Aug 8 4,361,613 1,424,818 4,072,241 0.0416 0.0413 0.0386 KY Aug 9 4,556,504 1,503,981 4,366,498 0.0435 0.0436 0.0414 KY Aug 10 4,676,703 1,547,003 4,636,588 0.0446 0.0449 0.0440 KY Aug 11 4,737,663 1,576,020 4,888,307 0.0452 0.0457 0.0463 KY Aug 12 4,814,736 1,602,156 5,042,982 0.0459 0.0465 0.0478 KY Aug 13 4,837,597 1,614,023 5,150,918 0.0462 0.0468 0.0488 KY Aug 14 4,856,220 1,626,339 5,243,914 0.0463 0.0472 0.0497 KY Aug 15 4,872,044 1,631,474 5,286,851 0.0465 0.0473 0.0501 KY Aug 16 4,852,491 1,626,072 5,274,429 0.0463 0.0472 0.0500 KY Aug 17 4,825,909 1,605,755 5,227,445 0.0460 0.0466 0.0496 KY Aug 18 4,776,144 1,575,964 5,098,419 0.0456 0.0457 0.0483 KY Aug 19 4,773,544 1,572,600 5,002,780 0.0455 0.0456 0.0474 KY Aug 20 4,745,844 1,558,889 4,908,751 0.0453 0.0452 0.0465 KY Aug 21 4,554,333 1,479,458 4,582,344 0.0435 0.0429 0.0434 KY Aug 22 4,322,024 1,398,382 4,233,380 0.0412 0.0405 0.0401 KY Aug 23 4,059,551 1,315,846 3,876,845 0.0387 0.0382 0.0368 KY Sep 0 3,595,868 1,141,883 3,329,502 0.0359 0.0357 0.0347 KY Sep 1 3,486,734 1,105,426 3,238,293 0.0348 0.0346 0.0337 KY Sep 2 3,410,086 1,089,099 3,177,867 0.0340 0.0341 0.0331 KY Sep 3 3,417,881 1,091,186 3,181,031 0.0341 0.0341 0.0331

H-20Atmospheric Sciences Group 

### Appendix H Average 2000-2004 State Level Monthly-Diurnal Profiles

CEM-Based Distribution Alpine Geophysics

SO2 Mass NOx Mass Heat Input State Month Hour [lbs] [lbs] [MMBtu] SO2 Ratio NOx Ratio Heat Input Average Values [2000-2004] Calculated Ratios

KY Sep 4 3,528,297 1,135,485 3,276,690 0.0352 0.0355 0.0341 KY Sep 5 3,739,213 1,213,349 3,456,769 0.0373 0.0380 0.0360 KY Sep 6 3,909,221 1,258,762 3,616,506 0.0390 0.0394 0.0377 KY Sep 7 4,008,091 1,292,595 3,689,943 0.0400 0.0405 0.0384 KY Sep 8 4,198,238 1,338,655 3,834,792 0.0419 0.0419 0.0399 KY Sep 9 4,341,058 1,380,097 3,985,620 0.0433 0.0432 0.0415 KY Sep 10 4,453,788 1,421,503 4,176,388 0.0445 0.0445 0.0435 KY Sep 11 4,536,502 1,453,187 4,334,552 0.0453 0.0455 0.0451 KY Sep 12 4,593,953 1,462,800 4,460,414 0.0459 0.0458 0.0465 KY Sep 13 4,628,123 1,482,574 4,597,150 0.0462 0.0464 0.0479 KY Sep 14 4,638,119 1,494,562 4,698,708 0.0463 0.0468 0.0489 KY Sep 15 4,652,224 1,500,168 4,721,765 0.0464 0.0469 0.0492 KY Sep 16 4,628,168 1,488,561 4,737,804 0.0462 0.0466 0.0493 KY Sep 17 4,609,485 1,465,982 4,696,333 0.0460 0.0459 0.0489 KY Sep 18 4,598,710 1,452,171 4,598,248 0.0459 0.0454 0.0479 KY Sep 19 4,652,661 1,463,449 4,572,473 0.0464 0.0458 0.0476 KY Sep 20 4,547,881 1,434,233 4,387,924 0.0454 0.0449 0.0457 KY Sep 21 4,279,254 1,347,403 4,039,635 0.0427 0.0422 0.0421 KY Sep 22 3,968,649 1,254,129 3,728,872 0.0396 0.0392 0.0388 KY Sep 23 3,745,030 1,186,129 3,474,766 0.0374 0.0371 0.0362 KY Oct 0 3,743,224 1,601,952 3,532,574 0.0362 0.0367 0.0362 KY Oct 1 3,676,531 1,576,043 3,476,375 0.0356 0.0361 0.0356 KY Oct 2 3,641,292 1,565,349 3,437,966 0.0352 0.0359 0.0352 KY Oct 3 3,681,681 1,581,523 3,468,699 0.0356 0.0363 0.0355 KY Oct 4 3,847,834 1,642,075 3,597,738 0.0372 0.0376 0.0368 KY Oct 5 4,098,543 1,738,160 3,794,676 0.0396 0.0399 0.0389 KY Oct 6 4,364,063 1,824,083 4,028,308 0.0422 0.0418 0.0412 KY Oct 7 4,439,117 1,859,253 4,154,973 0.0429 0.0426 0.0425 KY Oct 8 4,518,793 1,884,741 4,203,259 0.0437 0.0432 0.0430 KY Oct 9 4,572,090 1,908,542 4,241,582 0.0442 0.0438 0.0434 KY Oct 10 4,588,821 1,901,085 4,279,813 0.0444 0.0436 0.0438 KY Oct 11 4,591,634 1,910,189 4,355,897 0.0444 0.0438 0.0446 KY Oct 12 4,587,310 1,912,504 4,395,571 0.0444 0.0438 0.0450 KY Oct 13 4,564,707 1,913,776 4,412,969 0.0442 0.0439 0.0452 KY Oct 14 4,547,844 1,921,307 4,410,947 0.0440 0.0441 0.0452 KY Oct 15 4,536,425 1,922,594 4,399,521 0.0439 0.0441 0.0450 KY Oct 16 4,530,762 1,923,359 4,378,106 0.0438 0.0441 0.0448 KY Oct 17 4,559,994 1,931,107 4,380,389 0.0441 0.0443 0.0449 KY Oct 18 4,659,377 1,971,527 4,443,252 0.0451 0.0452 0.0455 KY Oct 19 4,679,388 1,963,456 4,437,459 0.0453 0.0450 0.0454 KY Oct 20 4,584,836 1,917,232 4,296,721 0.0443 0.0440 0.0440 KY Oct 21 4,379,886 1,835,392 4,061,547 0.0424 0.0421 0.0416 KY Oct 22 4,096,250 1,740,025 3,819,906 0.0396 0.0399 0.0391 KY Oct 23 3,893,430 1,670,287 3,652,729 0.0377 0.0383 0.0374 KY Nov 0 3,885,540 1,750,644 3,602,585 0.0385 0.0392 0.0382 KY Nov 1 3,806,089 1,712,194 3,515,552 0.0377 0.0384 0.0373 KY Nov 2 3,782,755 1,699,053 3,464,064 0.0374 0.0381 0.0367 KY Nov 3 3,761,073 1,689,317 3,436,481 0.0372 0.0379 0.0364 KY Nov 4 3,804,639 1,704,848 3,481,357 0.0377 0.0382 0.0369 KY Nov 5 3,910,926 1,750,748 3,597,416 0.0387 0.0392 0.0381 KY Nov 6 4,148,114 1,834,043 3,843,327 0.0411 0.0411 0.0407 KY Nov 7 4,287,622 1,889,795 3,994,287 0.0424 0.0424 0.0423 KY Nov 8 4,341,922 1,909,899 4,037,655 0.0430 0.0428 0.0428

H-21Atmospheric Sciences Group 

### Appendix H Average 2000-2004 State Level Monthly-Diurnal Profiles

CEM-Based Distribution Alpine Geophysics

SO2 Mass NOx Mass Heat Input State Month Hour [lbs] [lbs] [MMBtu] SO2 Ratio NOx Ratio Heat Input Average Values [2000-2004] Calculated Ratios

KY Nov 9 4,410,751 1,957,861 4,189,187 0.0437 0.0439 0.0444 KY Nov 10 4,418,332 1,949,448 4,205,116 0.0437 0.0437 0.0446 KY Nov 11 4,382,413 1,922,612 4,155,770 0.0434 0.0431 0.0440 KY Nov 12 4,350,220 1,906,738 4,103,225 0.0431 0.0427 0.0435 KY Nov 13 4,320,793 1,886,606 4,070,285 0.0428 0.0423 0.0431 KY Nov 14 4,275,911 1,873,512 4,040,693 0.0423 0.0420 0.0428 KY Nov 15 4,260,221 1,863,874 4,013,074 0.0422 0.0418 0.0425 KY Nov 16 4,313,487 1,885,821 4,020,640 0.0427 0.0423 0.0426 KY Nov 17 4,448,983 1,941,737 4,137,653 0.0440 0.0435 0.0439 KY Nov 18 4,530,551 1,984,254 4,283,590 0.0448 0.0445 0.0454 KY Nov 19 4,467,945 1,958,744 4,222,870 0.0442 0.0439 0.0448 KY Nov 20 4,431,262 1,946,314 4,171,257 0.0439 0.0436 0.0442 KY Nov 21 4,391,773 1,922,060 4,096,687 0.0435 0.0431 0.0434 KY Nov 22 4,254,473 1,872,895 3,932,831 0.0421 0.0420 0.0417 KY Nov 23 4,042,484 1,800,724 3,728,212 0.0400 0.0404 0.0395 KY Dec 0 4,096,348 1,833,401 3,841,112 0.0386 0.0389 0.0385 KY Dec 1 4,015,003 1,797,081 3,752,951 0.0379 0.0381 0.0376 KY Dec 2 3,977,439 1,781,198 3,716,696 0.0375 0.0378 0.0372 KY Dec 3 3,988,022 1,784,905 3,708,916 0.0376 0.0379 0.0371 KY Dec 4 4,032,701 1,809,153 3,754,042 0.0380 0.0384 0.0376 KY Dec 5 4,136,744 1,856,495 3,860,181 0.0390 0.0394 0.0387 KY Dec 6 4,384,290 1,943,801 4,105,937 0.0413 0.0412 0.0411 KY Dec 7 4,542,866 2,007,485 4,278,565 0.0428 0.0426 0.0428 KY Dec 8 4,614,637 2,053,177 4,352,720 0.0435 0.0436 0.0436 KY Dec 9 4,664,192 2,081,825 4,380,686 0.0440 0.0442 0.0439 KY Dec 10 4,673,389 2,062,430 4,369,361 0.0441 0.0438 0.0438 KY Dec 11 4,605,441 2,028,991 4,287,122 0.0434 0.0431 0.0429 KY Dec 12 4,553,175 2,004,430 4,233,054 0.0429 0.0425 0.0424 KY Dec 13 4,498,006 1,977,010 4,182,376 0.0424 0.0420 0.0419 KY Dec 14 4,415,048 1,947,384 4,126,576 0.0416 0.0413 0.0413 KY Dec 15 4,400,399 1,940,391 4,123,632 0.0415 0.0412 0.0413 KY Dec 16 4,465,730 1,977,764 4,216,038 0.0421 0.0420 0.0422 KY Dec 17 4,620,341 2,049,791 4,386,809 0.0436 0.0435 0.0439 KY Dec 18 4,698,027 2,102,642 4,549,990 0.0443 0.0446 0.0456 KY Dec 19 4,647,661 2,084,675 4,517,525 0.0438 0.0442 0.0452 KY Dec 20 4,654,175 2,083,508 4,489,359 0.0439 0.0442 0.0450 KY Dec 21 4,614,689 2,037,441 4,378,947 0.0435 0.0432 0.0438 KY Dec 22 4,490,234 1,977,015 4,228,895 0.0423 0.0420 0.0423 KY Dec 23 4,288,008 1,904,969 4,023,779 0.0404 0.0404 0.0403 MS Jan 0 976,875 498,392 1,739,588 0.0376 0.0333 0.0347 MS Jan 1 967,600 492,280 1,737,384 0.0372 0.0329 0.0347 MS Jan 2 966,502 493,295 1,747,320 0.0372 0.0330 0.0349 MS Jan 3 962,249 508,849 1,778,073 0.0370 0.0340 0.0355 MS Jan 4 981,931 549,003 1,904,800 0.0378 0.0367 0.0380 MS Jan 5 1,039,940 615,695 2,137,993 0.0400 0.0412 0.0427 MS Jan 6 1,119,075 681,717 2,401,350 0.0430 0.0456 0.0479 MS Jan 7 1,151,104 699,041 2,427,699 0.0443 0.0467 0.0485 MS Jan 8 1,166,258 695,736 2,384,436 0.0449 0.0465 0.0476 MS Jan 9 1,167,831 708,759 2,397,599 0.0449 0.0474 0.0479 MS Jan 10 1,146,639 687,503 2,299,806 0.0441 0.0460 0.0459 MS Jan 11 1,122,590 649,347 2,153,434 0.0432 0.0434 0.0430 MS Jan 12 1,096,730 609,196 2,022,231 0.0422 0.0407 0.0404 MS Jan 13 1,056,734 578,828 1,944,175 0.0406 0.0387 0.0388

H-22Atmospheric Sciences Group 

### Appendix H Average 2000-2004 State Level Monthly-Diurnal Profiles

CEM-Based Distribution Alpine Geophysics

SO2 Mass NOx Mass Heat Input State Month Hour [lbs] [lbs] [MMBtu] SO2 Ratio NOx Ratio Heat Input Average Values [2000-2004] Calculated Ratios

MS Jan 14 1,044,419 557,767 1,862,213 0.0402 0.0373 0.0372 MS Jan 15 1,032,758 552,681 1,873,015 0.0397 0.0369 0.0374 MS Jan 16 1,046,335 583,599 2,004,610 0.0402 0.0390 0.0400 MS Jan 17 1,135,430 648,329 2,225,482 0.0437 0.0433 0.0444 MS Jan 18 1,192,392 768,843 2,357,158 0.0459 0.0514 0.0471 MS Jan 19 1,189,077 762,937 2,339,568 0.0457 0.0510 0.0467 MS Jan 20 1,179,745 746,721 2,295,175 0.0454 0.0499 0.0458 MS Jan 21 1,145,469 689,003 2,183,575 0.0441 0.0461 0.0436 MS Jan 22 1,091,264 637,313 2,013,011 0.0420 0.0426 0.0402 MS Jan 23 1,023,481 544,166 1,852,825 0.0394 0.0364 0.0370 MS Feb 0 782,528 405,907 1,334,862 0.0369 0.0342 0.0330 MS Feb 1 761,745 401,506 1,337,948 0.0359 0.0338 0.0331 MS Feb 2 755,850 403,215 1,350,362 0.0356 0.0339 0.0334 MS Feb 3 763,382 411,139 1,398,640 0.0360 0.0346 0.0346 MS Feb 4 793,389 437,762 1,491,685 0.0374 0.0368 0.0369 MS Feb 5 857,681 544,057 1,775,888 0.0404 0.0458 0.0439 MS Feb 6 920,643 596,173 2,014,117 0.0434 0.0502 0.0498 MS Feb 7 947,559 608,252 2,067,668 0.0447 0.0512 0.0511 MS Feb 8 950,365 589,715 2,020,860 0.0448 0.0496 0.0499 MS Feb 9 950,211 565,430 1,979,216 0.0448 0.0476 0.0489 MS Feb 10 942,757 540,653 1,914,755 0.0445 0.0455 0.0473 MS Feb 11 914,688 511,901 1,752,373 0.0431 0.0431 0.0433 MS Feb 12 893,919 471,062 1,655,216 0.0422 0.0397 0.0409 MS Feb 13 879,496 456,988 1,617,049 0.0415 0.0385 0.0400 MS Feb 14 855,118 432,880 1,584,270 0.0403 0.0364 0.0391 MS Feb 15 848,094 421,215 1,607,720 0.0400 0.0355 0.0397 MS Feb 16 860,437 436,690 1,640,618 0.0406 0.0368 0.0405 MS Feb 17 908,058 483,560 1,725,576 0.0428 0.0407 0.0426 MS Feb 18 985,014 568,812 1,821,913 0.0464 0.0479 0.0450 MS Feb 19 989,298 579,566 1,825,118 0.0467 0.0488 0.0451 MS Feb 20 979,458 568,497 1,821,790 0.0462 0.0479 0.0450 MS Feb 21 940,195 527,405 1,766,089 0.0443 0.0444 0.0436 MS Feb 22 898,298 487,622 1,568,812 0.0424 0.0410 0.0388 MS Feb 23 828,050 430,352 1,398,637 0.0390 0.0362 0.0346 MS Mar 0 954,881 432,830 1,574,089 0.0374 0.0329 0.0334 MS Mar 1 935,148 415,563 1,553,449 0.0366 0.0316 0.0330 MS Mar 2 917,828 406,837 1,559,763 0.0360 0.0309 0.0331 MS Mar 3 917,621 412,039 1,568,383 0.0359 0.0313 0.0333 MS Mar 4 963,382 428,249 1,639,701 0.0377 0.0325 0.0348 MS Mar 5 1,034,739 534,402 1,864,996 0.0405 0.0406 0.0396 MS Mar 6 1,096,759 584,575 2,091,039 0.0430 0.0444 0.0444 MS Mar 7 1,153,326 626,345 2,154,794 0.0452 0.0476 0.0457 MS Mar 8 1,143,476 626,895 2,190,586 0.0448 0.0476 0.0465 MS Mar 9 1,165,825 623,847 2,199,674 0.0457 0.0474 0.0467 MS Mar 10 1,151,525 608,980 2,144,582 0.0451 0.0463 0.0455 MS Mar 11 1,125,374 589,039 2,091,865 0.0441 0.0448 0.0444 MS Mar 12 1,076,202 557,410 2,057,352 0.0422 0.0424 0.0437 MS Mar 13 1,068,691 550,131 2,043,582 0.0419 0.0418 0.0434 MS Mar 14 1,055,441 541,076 2,034,504 0.0413 0.0411 0.0432 MS Mar 15 1,049,146 534,740 1,992,792 0.0411 0.0406 0.0423 MS Mar 16 1,057,606 534,775 2,017,401 0.0414 0.0406 0.0428 MS Mar 17 1,092,432 560,060 2,056,732 0.0428 0.0426 0.0436 MS Mar 18 1,152,332 651,794 2,207,503 0.0451 0.0495 0.0468

H-23Atmospheric Sciences Group 

### Appendix H Average 2000-2004 State Level Monthly-Diurnal Profiles

CEM-Based Distribution Alpine Geophysics

SO2 Mass NOx Mass Heat Input State Month Hour [lbs] [lbs] [MMBtu] SO2 Ratio NOx Ratio Heat Input Average Values [2000-2004] Calculated Ratios

MS Mar 19 1,169,586 679,546 2,243,045 0.0458 0.0516 0.0476 MS Mar 20 1,139,946 655,626 2,209,640 0.0447 0.0498 0.0469 MS Mar 21 1,082,949 587,151 2,089,080 0.0424 0.0446 0.0443 MS Mar 22 1,048,288 550,462 1,873,115 0.0411 0.0418 0.0397 MS Mar 23 975,839 465,913 1,671,856 0.0382 0.0354 0.0355 MS Apr 0 772,566 395,311 1,407,007 0.0363 0.0324 0.0305 MS Apr 1 727,365 371,519 1,369,160 0.0342 0.0304 0.0296 MS Apr 2 695,726 356,402 1,368,820 0.0327 0.0292 0.0296 MS Apr 3 695,255 374,894 1,432,477 0.0327 0.0307 0.0310 MS Apr 4 762,780 412,138 1,592,961 0.0359 0.0337 0.0345 MS Apr 5 828,092 480,397 1,805,007 0.0389 0.0393 0.0391 MS Apr 6 869,604 505,058 1,968,219 0.0409 0.0414 0.0426 MS Apr 7 908,044 527,567 1,986,696 0.0427 0.0432 0.0430 MS Apr 8 926,930 537,431 2,031,932 0.0436 0.0440 0.0440 MS Apr 9 929,940 536,164 2,064,047 0.0437 0.0439 0.0447 MS Apr 10 937,093 548,544 2,110,221 0.0440 0.0449 0.0457 MS Apr 11 948,619 555,186 2,162,389 0.0446 0.0455 0.0468 MS Apr 12 950,648 565,077 2,185,293 0.0447 0.0463 0.0473 MS Apr 13 953,427 577,198 2,222,039 0.0448 0.0473 0.0481 MS Apr 14 954,511 585,989 2,255,173 0.0449 0.0480 0.0488 MS Apr 15 956,697 583,302 2,263,206 0.0450 0.0478 0.0490 MS Apr 16 959,172 577,035 2,253,560 0.0451 0.0472 0.0488 MS Apr 17 960,271 559,977 2,205,491 0.0451 0.0458 0.0477 MS Apr 18 952,015 551,979 2,198,435 0.0448 0.0452 0.0476 MS Apr 19 963,862 586,654 2,202,683 0.0453 0.0480 0.0477 MS Apr 20 955,924 575,209 2,102,011 0.0449 0.0471 0.0455 MS Apr 21 947,733 552,387 1,924,351 0.0445 0.0452 0.0417 MS Apr 22 890,373 478,750 1,639,137 0.0419 0.0392 0.0355 MS Apr 23 827,109 420,042 1,445,397 0.0389 0.0344 0.0313 MS May 0 715,201 330,126 1,298,404 0.0323 0.0280 0.0257 MS May 1 677,673 307,288 1,253,942 0.0306 0.0261 0.0249 MS May 2 656,721 300,770 1,219,929 0.0297 0.0255 0.0242 MS May 3 663,276 316,185 1,265,573 0.0300 0.0268 0.0251 MS May 4 709,047 340,140 1,392,627 0.0320 0.0288 0.0276 MS May 5 768,858 376,436 1,560,987 0.0348 0.0319 0.0309 MS May 6 829,693 418,639 1,720,209 0.0375 0.0355 0.0341 MS May 7 898,423 470,946 1,912,519 0.0406 0.0399 0.0379 MS May 8 955,768 514,322 2,110,543 0.0432 0.0436 0.0418 MS May 9 1,008,756 557,351 2,328,014 0.0456 0.0473 0.0462 MS May 10 1,032,535 567,895 2,486,836 0.0467 0.0482 0.0493 MS May 11 1,059,756 589,319 2,620,857 0.0479 0.0500 0.0520 MS May 12 1,079,462 616,742 2,717,455 0.0488 0.0523 0.0539 MS May 13 1,070,333 619,949 2,782,148 0.0484 0.0526 0.0552 MS May 14 1,078,912 624,270 2,802,049 0.0488 0.0529 0.0556 MS May 15 1,081,271 630,482 2,781,499 0.0489 0.0535 0.0551 MS May 16 1,070,065 615,326 2,736,638 0.0484 0.0522 0.0543 MS May 17 1,055,335 595,135 2,694,842 0.0477 0.0505 0.0534 MS May 18 1,034,974 570,012 2,603,665 0.0468 0.0483 0.0516 MS May 19 1,033,392 566,827 2,599,581 0.0467 0.0481 0.0515 MS May 20 1,013,439 548,786 2,399,707 0.0458 0.0465 0.0476 MS May 21 972,911 508,458 2,080,242 0.0440 0.0431 0.0412 MS May 22 875,080 435,618 1,683,078 0.0396 0.0369 0.0334 MS May 23 784,191 371,369 1,385,644 0.0354 0.0315 0.0275

H-24Atmospheric Sciences Group 

### Appendix H Average 2000-2004 State Level Monthly-Diurnal Profiles

CEM-Based Distribution Alpine Geophysics

SO2 Mass NOx Mass Heat Input State Month Hour [lbs] [lbs] [MMBtu] SO2 Ratio NOx Ratio Heat Input Average Values [2000-2004] Calculated Ratios

MS Jun 0 693,057 344,560 1,298,517 0.0338 0.0286 0.0266 MS Jun 1 641,024 315,711 1,228,335 0.0313 0.0262 0.0251 MS Jun 2 608,473 299,470 1,213,302 0.0297 0.0249 0.0248 MS Jun 3 604,057 305,099 1,248,131 0.0295 0.0253 0.0256 MS Jun 4 627,870 327,870 1,315,012 0.0306 0.0272 0.0269 MS Jun 5 658,954 348,172 1,440,853 0.0322 0.0289 0.0295 MS Jun 6 717,612 390,034 1,572,467 0.0350 0.0324 0.0322 MS Jun 7 809,271 455,342 1,749,532 0.0395 0.0378 0.0358 MS Jun 8 884,976 519,093 2,006,403 0.0432 0.0431 0.0411 MS Jun 9 936,419 567,045 2,253,920 0.0457 0.0471 0.0461 MS Jun 10 959,564 596,672 2,437,858 0.0468 0.0495 0.0499 MS Jun 11 987,549 628,365 2,566,208 0.0482 0.0522 0.0525 MS Jun 12 1,000,996 657,721 2,723,350 0.0488 0.0546 0.0558 MS Jun 13 1,007,469 664,717 2,791,149 0.0492 0.0552 0.0571 MS Jun 14 1,009,341 669,603 2,790,780 0.0493 0.0556 0.0571 MS Jun 15 1,005,767 665,511 2,774,655 0.0491 0.0552 0.0568 MS Jun 16 997,092 646,415 2,717,234 0.0487 0.0537 0.0556 MS Jun 17 979,915 610,289 2,583,011 0.0478 0.0507 0.0529 MS Jun 18 956,736 578,327 2,477,314 0.0467 0.0480 0.0507 MS Jun 19 953,737 565,651 2,428,028 0.0465 0.0470 0.0497 MS Jun 20 942,193 548,786 2,277,559 0.0460 0.0456 0.0466 MS Jun 21 908,344 507,922 1,932,253 0.0443 0.0422 0.0396 MS Jun 22 839,080 446,927 1,612,668 0.0409 0.0371 0.0330 MS Jun 23 761,741 387,710 1,402,334 0.0372 0.0322 0.0287 MS Jul 0 760,598 397,306 1,499,963 0.0351 0.0294 0.0258 MS Jul 1 711,370 364,853 1,452,523 0.0328 0.0270 0.0250 MS Jul 2 666,740 338,276 1,405,479 0.0308 0.0250 0.0242 MS Jul 3 643,773 337,333 1,404,755 0.0297 0.0249 0.0242 MS Jul 4 655,130 354,902 1,467,009 0.0303 0.0262 0.0253 MS Jul 5 676,286 374,686 1,758,070 0.0312 0.0277 0.0303 MS Jul 6 722,819 408,570 1,885,563 0.0334 0.0302 0.0325 MS Jul 7 817,648 475,561 2,076,359 0.0378 0.0352 0.0358 MS Jul 8 919,631 557,605 2,368,658 0.0425 0.0412 0.0408 MS Jul 9 993,779 630,222 2,728,777 0.0459 0.0466 0.0470 MS Jul 10 1,025,758 678,736 2,990,540 0.0474 0.0502 0.0515 MS Jul 11 1,042,649 714,015 3,169,150 0.0481 0.0528 0.0546 MS Jul 12 1,051,103 742,497 3,253,348 0.0485 0.0549 0.0560 MS Jul 13 1,052,791 756,236 3,285,360 0.0486 0.0559 0.0566 MS Jul 14 1,058,132 755,227 3,333,601 0.0489 0.0559 0.0574 MS Jul 15 1,055,069 750,217 3,315,158 0.0487 0.0555 0.0571 MS Jul 16 1,044,146 732,793 3,257,144 0.0482 0.0542 0.0561 MS Jul 17 1,037,635 704,258 3,185,647 0.0479 0.0521 0.0549 MS Jul 18 1,015,745 665,967 3,057,679 0.0469 0.0493 0.0527 MS Jul 19 1,017,161 648,713 2,913,409 0.0470 0.0480 0.0502 MS Jul 20 997,024 618,629 2,724,596 0.0460 0.0458 0.0469 MS Jul 21 964,773 566,178 2,103,852 0.0445 0.0419 0.0362 MS Jul 22 895,908 503,736 1,810,122 0.0414 0.0373 0.0312 MS Jul 23 830,653 444,290 1,625,263 0.0384 0.0329 0.0280 MS Aug 0 832,407 423,411 1,632,693 0.0360 0.0306 0.0287 MS Aug 1 774,523 385,152 1,564,862 0.0335 0.0278 0.0275 MS Aug 2 718,968 352,132 1,488,142 0.0311 0.0255 0.0262 MS Aug 3 696,007 354,736 1,466,857 0.0301 0.0256 0.0258 MS Aug 4 736,513 384,127 1,554,116 0.0319 0.0278 0.0274

H-25Atmospheric Sciences Group 

### Appendix H Average 2000-2004 State Level Monthly-Diurnal Profiles

CEM-Based Distribution Alpine Geophysics

SO2 Mass NOx Mass Heat Input State Month Hour [lbs] [lbs] [MMBtu] SO2 Ratio NOx Ratio Heat Input Average Values [2000-2004] Calculated Ratios

MS Aug 5 782,676 413,448 1,703,308 0.0339 0.0299 0.0300 MS Aug 6 821,293 440,409 1,786,431 0.0356 0.0318 0.0314 MS Aug 7 919,917 497,708 1,973,582 0.0398 0.0360 0.0347 MS Aug 8 1,010,016 569,031 2,215,648 0.0437 0.0411 0.0390 MS Aug 9 1,048,842 631,049 2,544,890 0.0454 0.0456 0.0448 MS Aug 10 1,075,499 671,487 2,787,078 0.0466 0.0485 0.0491 MS Aug 11 1,104,426 710,489 2,982,489 0.0478 0.0514 0.0525 MS Aug 12 1,111,768 746,322 3,109,940 0.0481 0.0539 0.0547 MS Aug 13 1,108,156 762,173 3,179,210 0.0480 0.0551 0.0560 MS Aug 14 1,106,101 757,714 3,195,332 0.0479 0.0548 0.0562 MS Aug 15 1,105,323 761,168 3,220,917 0.0479 0.0550 0.0567 MS Aug 16 1,090,817 746,486 3,199,653 0.0472 0.0540 0.0563 MS Aug 17 1,078,272 724,441 3,130,402 0.0467 0.0524 0.0551 MS Aug 18 1,066,795 683,503 2,981,841 0.0462 0.0494 0.0525 MS Aug 19 1,071,924 677,271 2,849,156 0.0464 0.0490 0.0501 MS Aug 20 1,039,562 627,485 2,559,854 0.0450 0.0454 0.0451 MS Aug 21 983,898 554,806 2,121,898 0.0426 0.0401 0.0373 MS Aug 22 933,076 502,633 1,873,343 0.0404 0.0363 0.0330 MS Aug 23 881,598 457,180 1,692,686 0.0382 0.0330 0.0298 MS Sep 0 677,459 331,288 1,326,078 0.0330 0.0274 0.0284 MS Sep 1 644,451 311,621 1,291,764 0.0314 0.0258 0.0277 MS Sep 2 620,103 295,726 1,270,350 0.0302 0.0245 0.0272 MS Sep 3 620,863 313,025 1,270,149 0.0303 0.0259 0.0272 MS Sep 4 675,330 350,263 1,365,677 0.0329 0.0290 0.0292 MS Sep 5 729,603 399,641 1,522,765 0.0356 0.0331 0.0326 MS Sep 6 765,053 424,637 1,573,078 0.0373 0.0352 0.0337 MS Sep 7 814,461 469,966 1,677,289 0.0397 0.0389 0.0359 MS Sep 8 868,577 498,987 1,832,422 0.0423 0.0413 0.0392 MS Sep 9 915,772 534,876 1,956,811 0.0446 0.0443 0.0419 MS Sep 10 941,466 581,876 2,136,604 0.0459 0.0482 0.0457 MS Sep 11 965,028 620,768 2,343,200 0.0470 0.0514 0.0502 MS Sep 12 994,287 647,175 2,462,775 0.0484 0.0536 0.0527 MS Sep 13 1,001,554 652,358 2,541,349 0.0488 0.0540 0.0544 MS Sep 14 1,002,505 665,235 2,587,460 0.0488 0.0551 0.0554 MS Sep 15 1,006,460 670,557 2,601,917 0.0490 0.0555 0.0557 MS Sep 16 1,002,423 649,414 2,570,001 0.0488 0.0538 0.0550 MS Sep 17 982,787 617,191 2,497,219 0.0479 0.0511 0.0535 MS Sep 18 975,939 612,714 2,462,554 0.0476 0.0507 0.0527 MS Sep 19 972,567 600,126 2,368,900 0.0474 0.0497 0.0507 MS Sep 20 931,131 542,176 2,112,019 0.0454 0.0449 0.0452 MS Sep 21 879,869 491,403 1,870,755 0.0429 0.0407 0.0401 MS Sep 22 807,921 428,259 1,618,622 0.0394 0.0355 0.0347 MS Sep 23 727,684 367,911 1,447,438 0.0355 0.0305 0.0310 MS Oct 0 871,339 400,670 1,438,404 0.0359 0.0294 0.0328 MS Oct 1 846,178 382,127 1,391,055 0.0349 0.0281 0.0317 MS Oct 2 828,495 374,997 1,378,269 0.0341 0.0275 0.0314 MS Oct 3 836,621 388,796 1,396,860 0.0345 0.0286 0.0318 MS Oct 4 908,179 483,350 1,466,201 0.0374 0.0355 0.0334 MS Oct 5 977,255 555,759 1,593,104 0.0403 0.0408 0.0363 MS Oct 6 1,015,219 594,592 1,675,235 0.0418 0.0437 0.0382 MS Oct 7 1,035,786 604,809 1,698,851 0.0427 0.0444 0.0387 MS Oct 8 1,050,150 614,722 1,759,169 0.0433 0.0452 0.0401 MS Oct 9 1,058,415 642,497 1,863,096 0.0436 0.0472 0.0424

H-26Atmospheric Sciences Group 

### Appendix H Average 2000-2004 State Level Monthly-Diurnal Profiles

CEM-Based Distribution Alpine Geophysics

SO2 Mass NOx Mass Heat Input State Month Hour [lbs] [lbs] [MMBtu] SO2 Ratio NOx Ratio Heat Input Average Values [2000-2004] Calculated Ratios

MS Oct 10 1,057,888 624,425 1,974,628 0.0436 0.0459 0.0450 MS Oct 11 1,058,906 625,425 2,027,461 0.0436 0.0459 0.0462 MS Oct 12 1,060,871 658,573 2,099,963 0.0437 0.0484 0.0478 MS Oct 13 1,067,447 672,788 2,137,711 0.0440 0.0494 0.0487 MS Oct 14 1,069,322 657,719 2,185,782 0.0441 0.0483 0.0498 MS Oct 15 1,077,341 657,106 2,169,737 0.0444 0.0483 0.0494 MS Oct 16 1,083,412 653,251 2,157,074 0.0446 0.0480 0.0491 MS Oct 17 1,105,122 658,900 2,175,847 0.0455 0.0484 0.0496 MS Oct 18 1,119,474 665,373 2,189,952 0.0461 0.0489 0.0499 MS Oct 19 1,097,619 629,441 2,103,011 0.0452 0.0462 0.0479 MS Oct 20 1,075,426 588,481 2,007,873 0.0443 0.0432 0.0457 MS Oct 21 1,056,396 553,395 1,863,573 0.0435 0.0406 0.0424 MS Oct 22 994,149 490,323 1,636,301 0.0410 0.0360 0.0373 MS Oct 23 924,165 437,325 1,518,220 0.0381 0.0321 0.0346 MS Nov 0 873,994 419,723 1,319,979 0.0361 0.0291 0.0319 MS Nov 1 852,947 401,495 1,283,359 0.0352 0.0279 0.0310 MS Nov 2 830,951 389,995 1,261,174 0.0343 0.0271 0.0305 MS Nov 3 826,026 391,038 1,262,690 0.0341 0.0272 0.0305 MS Nov 4 857,253 417,220 1,308,806 0.0354 0.0290 0.0316 MS Nov 5 958,948 508,090 1,458,443 0.0396 0.0353 0.0353 MS Nov 6 1,022,014 630,716 1,659,706 0.0422 0.0438 0.0401 MS Nov 7 1,060,943 640,532 1,755,027 0.0438 0.0445 0.0424 MS Nov 8 1,091,560 651,059 1,801,817 0.0451 0.0452 0.0436 MS Nov 9 1,103,148 683,533 1,857,927 0.0455 0.0475 0.0449 MS Nov 10 1,078,324 694,360 1,880,080 0.0445 0.0482 0.0455 MS Nov 11 1,065,364 668,754 1,889,916 0.0440 0.0464 0.0457 MS Nov 12 1,032,203 637,744 1,903,624 0.0426 0.0443 0.0460 MS Nov 13 1,017,096 632,959 1,918,195 0.0420 0.0440 0.0464 MS Nov 14 991,302 621,379 1,936,214 0.0409 0.0432 0.0468 MS Nov 15 991,334 615,452 1,910,301 0.0409 0.0427 0.0462 MS Nov 16 1,038,741 662,734 1,952,063 0.0429 0.0460 0.0472 MS Nov 17 1,118,397 752,304 2,049,173 0.0462 0.0522 0.0495 MS Nov 18 1,139,616 804,866 2,097,309 0.0470 0.0559 0.0507 MS Nov 19 1,122,336 781,325 2,065,487 0.0463 0.0543 0.0499 MS Nov 20 1,099,154 709,431 1,965,038 0.0454 0.0493 0.0475 MS Nov 21 1,068,182 620,932 1,794,635 0.0441 0.0431 0.0434 MS Nov 22 1,033,176 572,600 1,595,278 0.0427 0.0398 0.0386 MS Nov 23 949,071 490,972 1,433,679 0.0392 0.0341 0.0347 MS Dec 0 985,774 547,406 1,523,183 0.0382 0.0351 0.0338 MS Dec 1 958,678 534,960 1,512,551 0.0372 0.0343 0.0335 MS Dec 2 934,029 521,102 1,524,804 0.0362 0.0334 0.0338 MS Dec 3 934,104 526,929 1,560,808 0.0362 0.0338 0.0346 MS Dec 4 974,296 548,706 1,660,840 0.0378 0.0352 0.0368 MS Dec 5 1,039,798 612,444 1,841,503 0.0403 0.0393 0.0408 MS Dec 6 1,113,547 721,122 2,036,031 0.0432 0.0462 0.0452 MS Dec 7 1,159,345 753,347 2,071,427 0.0450 0.0483 0.0459 MS Dec 8 1,173,841 760,317 2,095,025 0.0455 0.0488 0.0465 MS Dec 9 1,176,528 727,906 2,045,553 0.0456 0.0467 0.0454 MS Dec 10 1,154,951 702,026 1,964,054 0.0448 0.0450 0.0436 MS Dec 11 1,121,403 667,756 1,869,824 0.0435 0.0428 0.0415 MS Dec 12 1,083,924 639,652 1,821,740 0.0420 0.0410 0.0404 MS Dec 13 1,047,128 607,261 1,783,500 0.0406 0.0389 0.0396 MS Dec 14 1,004,758 568,687 1,763,453 0.0390 0.0365 0.0391

H-27Atmospheric Sciences Group 

### Appendix H Average 2000-2004 State Level Monthly-Diurnal Profiles

CEM-Based Distribution Alpine Geophysics

SO2 Mass NOx Mass Heat Input State Month Hour [lbs] [lbs] [MMBtu] SO2 Ratio NOx Ratio Heat Input Average Values [2000-2004] Calculated Ratios

MS Dec 15 990,339 548,686 1,785,581 0.0384 0.0352 0.0396 MS Dec 16 1,034,926 600,093 1,877,670 0.0401 0.0385 0.0416 MS Dec 17 1,132,545 725,446 2,120,044 0.0439 0.0465 0.0470 MS Dec 18 1,182,372 785,125 2,220,651 0.0458 0.0503 0.0493 MS Dec 19 1,175,656 770,915 2,225,372 0.0456 0.0494 0.0494 MS Dec 20 1,169,944 758,124 2,203,589 0.0454 0.0486 0.0489 MS Dec 21 1,128,007 715,886 2,103,635 0.0437 0.0459 0.0467 MS Dec 22 1,085,539 659,297 1,851,805 0.0421 0.0423 0.0411 MS Dec 23 1,026,441 590,507 1,625,055 0.0398 0.0379 0.0360 NC Jan 0 3,625,870 1,340,390 3,136,181 0.0373 0.0362 0.0340 NC Jan 1 3,547,305 1,308,649 3,066,666 0.0364 0.0353 0.0332 NC Jan 2 3,547,177 1,317,699 3,090,405 0.0364 0.0356 0.0335 NC Jan 3 3,588,787 1,347,741 3,203,085 0.0369 0.0364 0.0347 NC Jan 4 3,699,352 1,403,864 3,417,648 0.0380 0.0379 0.0370 NC Jan 5 3,908,915 1,499,733 3,756,822 0.0402 0.0405 0.0407 NC Jan 6 4,256,587 1,655,285 4,258,104 0.0437 0.0447 0.0462 NC Jan 7 4,483,631 1,774,004 4,707,090 0.0461 0.0479 0.0510 NC Jan 8 4,515,366 1,766,638 4,645,775 0.0464 0.0477 0.0504 NC Jan 9 4,491,734 1,754,783 4,636,411 0.0461 0.0474 0.0503 NC Jan 10 4,393,796 1,702,344 4,374,553 0.0451 0.0459 0.0474 NC Jan 11 4,250,196 1,636,046 4,145,824 0.0437 0.0442 0.0449 NC Jan 12 4,086,233 1,544,270 3,809,889 0.0420 0.0417 0.0413 NC Jan 13 3,955,293 1,476,462 3,617,829 0.0406 0.0398 0.0392 NC Jan 14 3,816,633 1,418,449 3,450,107 0.0392 0.0383 0.0374 NC Jan 15 3,743,931 1,389,505 3,382,436 0.0385 0.0375 0.0367 NC Jan 16 3,815,007 1,417,757 3,483,763 0.0392 0.0383 0.0378 NC Jan 17 4,092,382 1,537,546 3,810,633 0.0420 0.0415 0.0413 NC Jan 18 4,420,054 1,716,940 4,361,423 0.0454 0.0463 0.0473 NC Jan 19 4,435,210 1,708,171 4,331,349 0.0456 0.0461 0.0469 NC Jan 20 4,392,805 1,679,293 4,212,749 0.0451 0.0453 0.0457 NC Jan 21 4,302,264 1,645,099 4,096,848 0.0442 0.0444 0.0444 NC Jan 22 4,123,178 1,572,475 3,824,535 0.0424 0.0424 0.0415 NC Jan 23 3,840,179 1,440,491 3,434,780 0.0395 0.0389 0.0372 NC Feb 0 3,184,603 1,111,659 2,584,219 0.0365 0.0355 0.0335 NC Feb 1 3,104,814 1,084,322 2,526,549 0.0356 0.0346 0.0327 NC Feb 2 3,102,384 1,084,226 2,523,155 0.0356 0.0346 0.0327 NC Feb 3 3,150,560 1,102,189 2,565,178 0.0362 0.0352 0.0332 NC Feb 4 3,265,151 1,154,184 2,727,067 0.0375 0.0369 0.0353 NC Feb 5 3,477,336 1,241,276 2,998,673 0.0399 0.0396 0.0388 NC Feb 6 3,822,164 1,386,221 3,442,195 0.0439 0.0443 0.0446 NC Feb 7 4,018,486 1,469,047 3,700,102 0.0461 0.0469 0.0479 NC Feb 8 4,046,941 1,482,539 3,747,404 0.0464 0.0474 0.0485 NC Feb 9 4,018,646 1,459,740 3,678,388 0.0461 0.0466 0.0476 NC Feb 10 3,950,541 1,421,953 3,537,090 0.0453 0.0454 0.0458 NC Feb 11 3,820,149 1,364,963 3,395,422 0.0438 0.0436 0.0440 NC Feb 12 3,695,389 1,319,860 3,286,832 0.0424 0.0422 0.0426 NC Feb 13 3,589,834 1,286,954 3,238,548 0.0412 0.0411 0.0419 NC Feb 14 3,480,630 1,245,758 3,140,457 0.0399 0.0398 0.0407 NC Feb 15 3,413,401 1,225,689 3,112,350 0.0392 0.0392 0.0403 NC Feb 16 3,436,366 1,238,232 3,156,097 0.0394 0.0396 0.0409 NC Feb 17 3,578,845 1,301,549 3,309,765 0.0411 0.0416 0.0429 NC Feb 18 3,916,367 1,444,037 3,687,236 0.0449 0.0461 0.0477 NC Feb 19 4,026,027 1,479,808 3,763,280 0.0462 0.0473 0.0487

H-28Atmospheric Sciences Group 

### Appendix H Average 2000-2004 State Level Monthly-Diurnal Profiles

CEM-Based Distribution Alpine Geophysics

SO2 Mass NOx Mass Heat Input State Month Hour [lbs] [lbs] [MMBtu] SO2 Ratio NOx Ratio Heat Input Average Values [2000-2004] Calculated Ratios

NC Feb 20 4,006,346 1,462,311 3,636,622 0.0460 0.0467 0.0471 NC Feb 21 3,910,149 1,416,593 3,470,296 0.0449 0.0452 0.0449 NC Feb 22 3,715,354 1,327,212 3,175,393 0.0426 0.0424 0.0411 NC Feb 23 3,406,957 1,195,674 2,817,750 0.0391 0.0382 0.0365 NC Mar 0 3,495,471 1,156,479 2,781,502 0.0357 0.0344 0.0338 NC Mar 1 3,364,317 1,111,545 2,674,119 0.0344 0.0331 0.0325 NC Mar 2 3,321,515 1,101,682 2,646,229 0.0340 0.0328 0.0321 NC Mar 3 3,325,853 1,110,846 2,677,665 0.0340 0.0330 0.0325 NC Mar 4 3,432,883 1,154,085 2,799,670 0.0351 0.0343 0.0340 NC Mar 5 3,679,438 1,253,842 3,101,527 0.0376 0.0373 0.0377 NC Mar 6 4,083,241 1,423,687 3,556,842 0.0417 0.0423 0.0432 NC Mar 7 4,325,741 1,523,695 3,835,215 0.0442 0.0453 0.0466 NC Mar 8 4,408,061 1,554,926 3,978,168 0.0451 0.0462 0.0483 NC Mar 9 4,446,596 1,560,347 3,954,716 0.0455 0.0464 0.0480 NC Mar 10 4,422,051 1,540,513 3,787,457 0.0452 0.0458 0.0460 NC Mar 11 4,368,120 1,515,980 3,696,220 0.0446 0.0451 0.0449 NC Mar 12 4,320,676 1,487,685 3,591,910 0.0442 0.0442 0.0436 NC Mar 13 4,260,564 1,462,294 3,552,480 0.0435 0.0435 0.0432 NC Mar 14 4,181,428 1,428,179 3,424,153 0.0427 0.0425 0.0416 NC Mar 15 4,125,296 1,400,339 3,358,859 0.0422 0.0417 0.0408 NC Mar 16 4,137,088 1,409,567 3,382,900 0.0423 0.0419 0.0411 NC Mar 17 4,186,812 1,437,864 3,490,868 0.0428 0.0428 0.0424 NC Mar 18 4,384,996 1,518,976 3,714,131 0.0448 0.0452 0.0451 NC Mar 19 4,597,710 1,613,055 3,968,091 0.0470 0.0480 0.0482 NC Mar 20 4,561,487 1,604,590 3,972,640 0.0466 0.0477 0.0483 NC Mar 21 4,431,834 1,545,633 3,790,920 0.0453 0.0460 0.0460 NC Mar 22 4,186,059 1,433,121 3,483,528 0.0428 0.0426 0.0423 NC Mar 23 3,785,976 1,271,907 3,103,453 0.0387 0.0378 0.0377 NC Apr 0 3,039,447 989,438 2,429,415 0.0328 0.0314 0.0296 NC Apr 1 2,910,931 945,386 2,307,952 0.0314 0.0300 0.0281 NC Apr 2 2,850,958 927,453 2,269,071 0.0308 0.0294 0.0276 NC Apr 3 2,896,556 942,765 2,335,243 0.0313 0.0299 0.0284 NC Apr 4 3,135,361 1,025,528 2,555,352 0.0339 0.0325 0.0311 NC Apr 5 3,584,481 1,188,997 2,979,186 0.0387 0.0377 0.0363 NC Apr 6 3,881,843 1,294,539 3,271,639 0.0419 0.0411 0.0398 NC Apr 7 4,047,382 1,346,556 3,417,421 0.0437 0.0427 0.0416 NC Apr 8 4,171,051 1,385,765 3,451,552 0.0451 0.0440 0.0420 NC Apr 9 4,231,500 1,414,685 3,525,438 0.0457 0.0449 0.0429 NC Apr 10 4,270,268 1,444,254 3,674,803 0.0461 0.0458 0.0448 NC Apr 11 4,286,067 1,471,462 3,829,895 0.0463 0.0467 0.0466 NC Apr 12 4,290,947 1,505,275 4,032,680 0.0463 0.0478 0.0491 NC Apr 13 4,262,841 1,500,242 4,108,312 0.0460 0.0476 0.0500 NC Apr 14 4,252,222 1,503,067 4,136,316 0.0459 0.0477 0.0504 NC Apr 15 4,260,951 1,532,047 4,188,783 0.0460 0.0486 0.0510 NC Apr 16 4,235,832 1,522,595 4,190,814 0.0458 0.0483 0.0510 NC Apr 17 4,180,904 1,484,742 4,120,053 0.0452 0.0471 0.0502 NC Apr 18 4,151,241 1,442,982 3,980,953 0.0448 0.0458 0.0485 NC Apr 19 4,327,964 1,496,496 4,079,513 0.0467 0.0475 0.0497 NC Apr 20 4,309,003 1,478,214 3,952,971 0.0465 0.0469 0.0481 NC Apr 21 4,083,738 1,377,185 3,538,885 0.0441 0.0437 0.0431 NC Apr 22 3,659,870 1,215,010 3,052,504 0.0395 0.0386 0.0372 NC Apr 23 3,262,225 1,075,490 2,685,449 0.0352 0.0341 0.0327 NC May 0 2,988,299 951,099 2,688,735 0.0321 0.0307 0.0290

H-29Atmospheric Sciences Group 

### Appendix H Average 2000-2004 State Level Monthly-Diurnal Profiles

CEM-Based Distribution Alpine Geophysics

SO2 Mass NOx Mass Heat Input State Month Hour [lbs] [lbs] [MMBtu] SO2 Ratio NOx Ratio Heat Input Average Values [2000-2004] Calculated Ratios

NC May 1 2,792,481 891,529 2,497,088 0.0300 0.0288 0.0269 NC May 2 2,674,871 855,789 2,392,481 0.0288 0.0276 0.0258 NC May 3 2,669,331 854,116 2,383,638 0.0287 0.0276 0.0257 NC May 4 2,890,248 927,239 2,554,672 0.0311 0.0299 0.0276 NC May 5 3,297,681 1,061,987 2,886,430 0.0355 0.0343 0.0311 NC May 6 3,634,181 1,170,557 3,184,623 0.0391 0.0378 0.0344 NC May 7 3,846,900 1,245,848 3,416,574 0.0414 0.0402 0.0369 NC May 8 4,034,773 1,310,353 3,667,525 0.0434 0.0423 0.0396 NC May 9 4,184,672 1,371,573 3,893,093 0.0450 0.0443 0.0420 NC May 10 4,305,947 1,424,820 4,141,648 0.0463 0.0460 0.0447 NC May 11 4,404,097 1,483,068 4,458,155 0.0474 0.0479 0.0481 NC May 12 4,475,259 1,539,283 4,697,419 0.0481 0.0497 0.0507 NC May 13 4,491,964 1,569,034 4,875,921 0.0483 0.0506 0.0526 NC May 14 4,498,554 1,561,658 4,951,990 0.0484 0.0504 0.0534 NC May 15 4,523,801 1,571,285 5,012,379 0.0486 0.0507 0.0541 NC May 16 4,523,778 1,568,349 5,003,593 0.0486 0.0506 0.0540 NC May 17 4,482,997 1,542,267 4,944,140 0.0482 0.0498 0.0533 NC May 18 4,391,547 1,496,982 4,799,984 0.0472 0.0483 0.0518 NC May 19 4,391,525 1,490,306 4,803,533 0.0472 0.0481 0.0518 NC May 20 4,395,887 1,482,807 4,719,101 0.0473 0.0478 0.0509 NC May 21 4,138,037 1,371,218 4,192,432 0.0445 0.0442 0.0452 NC May 22 3,688,336 1,200,680 3,546,431 0.0397 0.0387 0.0383 NC May 23 3,285,445 1,051,167 2,990,351 0.0353 0.0339 0.0323 NC Jun 0 2,965,187 875,221 2,530,360 0.0330 0.0313 0.0292 NC Jun 1 2,750,053 815,628 2,369,418 0.0306 0.0291 0.0273 NC Jun 2 2,598,072 773,177 2,259,001 0.0289 0.0276 0.0261 NC Jun 3 2,545,090 759,204 2,218,521 0.0283 0.0271 0.0256 NC Jun 4 2,651,641 791,787 2,303,803 0.0295 0.0283 0.0266 NC Jun 5 2,843,468 850,485 2,461,441 0.0317 0.0304 0.0284 NC Jun 6 3,072,903 914,963 2,644,430 0.0342 0.0327 0.0305 NC Jun 7 3,386,526 1,011,128 2,920,142 0.0377 0.0361 0.0337 NC Jun 8 3,709,883 1,115,505 3,237,030 0.0413 0.0399 0.0374 NC Jun 9 4,019,872 1,225,834 3,603,667 0.0448 0.0438 0.0416 NC Jun 10 4,235,939 1,310,821 3,971,825 0.0472 0.0468 0.0458 NC Jun 11 4,372,819 1,396,154 4,238,914 0.0487 0.0499 0.0489 NC Jun 12 4,454,747 1,447,004 4,513,322 0.0496 0.0517 0.0521 NC Jun 13 4,496,004 1,465,037 4,671,766 0.0501 0.0524 0.0539 NC Jun 14 4,506,747 1,470,722 4,793,038 0.0502 0.0526 0.0553 NC Jun 15 4,519,474 1,471,545 4,844,987 0.0503 0.0526 0.0559 NC Jun 16 4,508,458 1,466,571 4,842,407 0.0502 0.0524 0.0559 NC Jun 17 4,456,620 1,439,530 4,757,817 0.0496 0.0514 0.0549 NC Jun 18 4,327,832 1,388,804 4,596,146 0.0482 0.0496 0.0530 NC Jun 19 4,226,778 1,343,402 4,472,457 0.0471 0.0480 0.0516 NC Jun 20 4,229,304 1,336,758 4,374,033 0.0471 0.0478 0.0505 NC Jun 21 3,991,005 1,238,023 3,917,165 0.0445 0.0442 0.0452 NC Jun 22 3,644,049 1,106,567 3,327,381 0.0406 0.0395 0.0384 NC Jun 23 3,271,149 967,979 2,787,309 0.0364 0.0346 0.0322 NC Jul 0 3,203,381 924,262 2,845,009 0.0332 0.0312 0.0297 NC Jul 1 2,965,161 855,451 2,596,343 0.0308 0.0288 0.0271 NC Jul 2 2,800,743 813,580 2,476,811 0.0291 0.0274 0.0259 NC Jul 3 2,736,180 793,048 2,404,572 0.0284 0.0267 0.0251 NC Jul 4 2,830,295 824,684 2,476,064 0.0294 0.0278 0.0259 NC Jul 5 3,047,522 889,319 2,647,583 0.0316 0.0300 0.0277

H-30Atmospheric Sciences Group 

### Appendix H Average 2000-2004 State Level Monthly-Diurnal Profiles

CEM-Based Distribution Alpine Geophysics

SO2 Mass NOx Mass Heat Input State Month Hour [lbs] [lbs] [MMBtu] SO2 Ratio NOx Ratio Heat Input Average Values [2000-2004] Calculated Ratios

NC Jul 6 3,271,366 946,124 2,816,944 0.0339 0.0319 0.0294 NC Jul 7 3,616,680 1,052,025 3,223,059 0.0375 0.0355 0.0337 NC Jul 8 3,953,695 1,168,302 3,623,778 0.0410 0.0394 0.0379 NC Jul 9 4,291,848 1,283,942 3,984,938 0.0445 0.0433 0.0417 NC Jul 10 4,524,538 1,375,387 4,335,515 0.0469 0.0464 0.0453 NC Jul 11 4,668,460 1,454,562 4,648,805 0.0484 0.0490 0.0486 NC Jul 12 4,750,356 1,527,006 4,933,908 0.0493 0.0515 0.0516 NC Jul 13 4,798,813 1,559,248 5,125,858 0.0498 0.0526 0.0536 NC Jul 14 4,812,096 1,564,905 5,188,364 0.0499 0.0528 0.0542 NC Jul 15 4,821,883 1,575,434 5,266,185 0.0500 0.0531 0.0550 NC Jul 16 4,819,234 1,570,114 5,297,395 0.0500 0.0529 0.0554 NC Jul 17 4,778,497 1,549,473 5,257,998 0.0496 0.0522 0.0550 NC Jul 18 4,673,354 1,496,447 5,116,396 0.0485 0.0505 0.0535 NC Jul 19 4,583,203 1,443,042 4,962,470 0.0476 0.0487 0.0519 NC Jul 20 4,554,945 1,438,105 4,863,301 0.0473 0.0485 0.0508 NC Jul 21 4,324,076 1,333,900 4,447,802 0.0449 0.0450 0.0465 NC Jul 22 3,973,197 1,184,353 3,900,877 0.0412 0.0399 0.0408 NC Jul 23 3,573,947 1,033,602 3,224,929 0.0371 0.0349 0.0337 NC Aug 0 3,304,852 963,941 2,898,716 0.0337 0.0315 0.0295 NC Aug 1 3,081,864 895,575 2,683,361 0.0314 0.0292 0.0274 NC Aug 2 2,924,085 855,384 2,554,207 0.0298 0.0279 0.0260 NC Aug 3 2,863,192 840,718 2,510,575 0.0292 0.0274 0.0256 NC Aug 4 3,005,461 884,898 2,620,875 0.0306 0.0289 0.0267 NC Aug 5 3,356,686 990,812 2,913,206 0.0342 0.0323 0.0297 NC Aug 6 3,565,695 1,050,611 3,109,145 0.0363 0.0343 0.0317 NC Aug 7 3,823,159 1,133,457 3,368,494 0.0390 0.0370 0.0343 NC Aug 8 4,119,121 1,247,193 3,792,038 0.0420 0.0407 0.0387 NC Aug 9 4,379,709 1,338,095 4,201,047 0.0446 0.0437 0.0428 NC Aug 10 4,560,689 1,437,327 4,545,567 0.0465 0.0469 0.0463 NC Aug 11 4,679,909 1,487,234 4,789,916 0.0477 0.0486 0.0488 NC Aug 12 4,756,748 1,559,170 5,073,057 0.0485 0.0509 0.0517 NC Aug 13 4,774,631 1,580,678 5,225,795 0.0487 0.0516 0.0533 NC Aug 14 4,777,253 1,580,098 5,280,027 0.0487 0.0516 0.0538 NC Aug 15 4,794,051 1,587,918 5,331,244 0.0489 0.0518 0.0543 NC Aug 16 4,797,668 1,583,009 5,319,490 0.0489 0.0517 0.0542 NC Aug 17 4,755,560 1,559,949 5,259,749 0.0485 0.0509 0.0536 NC Aug 18 4,661,588 1,506,549 5,116,358 0.0475 0.0492 0.0522 NC Aug 19 4,629,150 1,490,605 5,077,271 0.0472 0.0487 0.0518 NC Aug 20 4,574,623 1,454,956 4,901,477 0.0466 0.0475 0.0500 NC Aug 21 4,333,660 1,342,227 4,457,401 0.0442 0.0438 0.0454 NC Aug 22 3,985,537 1,198,084 3,847,163 0.0406 0.0391 0.0392 NC Aug 23 3,604,838 1,059,628 3,227,349 0.0367 0.0346 0.0329 NC Sep 0 2,831,718 843,999 2,569,763 0.0314 0.0310 0.0304 NC Sep 1 2,671,813 806,005 2,439,499 0.0296 0.0296 0.0289 NC Sep 2 2,572,274 783,030 2,353,479 0.0285 0.0288 0.0279 NC Sep 3 2,562,140 782,625 2,362,933 0.0284 0.0287 0.0280 NC Sep 4 2,741,434 832,267 2,487,419 0.0304 0.0306 0.0295 NC Sep 5 3,169,190 949,868 2,725,482 0.0351 0.0349 0.0323 NC Sep 6 3,446,956 1,025,547 2,945,275 0.0382 0.0377 0.0349 NC Sep 7 3,602,068 1,070,749 3,070,781 0.0399 0.0393 0.0364 NC Sep 8 3,819,430 1,131,711 3,298,495 0.0423 0.0416 0.0391 NC Sep 9 4,029,055 1,202,680 3,585,863 0.0446 0.0442 0.0425 NC Sep 10 4,217,518 1,265,309 3,849,918 0.0467 0.0465 0.0456

H-31Atmospheric Sciences Group 

### Appendix H Average 2000-2004 State Level Monthly-Diurnal Profiles

CEM-Based Distribution Alpine Geophysics

SO2 Mass NOx Mass Heat Input State Month Hour [lbs] [lbs] [MMBtu] SO2 Ratio NOx Ratio Heat Input Average Values [2000-2004] Calculated Ratios

NC Sep 11 4,330,923 1,307,158 4,050,205 0.0480 0.0480 0.0480 NC Sep 12 4,419,852 1,350,136 4,214,846 0.0489 0.0496 0.0499 NC Sep 13 4,447,094 1,372,538 4,362,014 0.0492 0.0504 0.0516 NC Sep 14 4,464,546 1,372,945 4,435,916 0.0494 0.0504 0.0525 NC Sep 15 4,479,217 1,375,057 4,470,927 0.0496 0.0505 0.0529 NC Sep 16 4,465,511 1,365,792 4,432,498 0.0494 0.0502 0.0525 NC Sep 17 4,416,809 1,340,361 4,368,640 0.0489 0.0492 0.0517 NC Sep 18 4,382,304 1,322,191 4,323,960 0.0485 0.0486 0.0512 NC Sep 19 4,425,808 1,337,459 4,385,946 0.0490 0.0491 0.0519 NC Sep 20 4,265,207 1,269,439 4,077,678 0.0472 0.0466 0.0483 NC Sep 21 3,933,113 1,163,534 3,660,789 0.0436 0.0427 0.0433 NC Sep 22 3,508,261 1,035,938 3,191,631 0.0388 0.0381 0.0378 NC Sep 23 3,107,606 919,230 2,792,129 0.0344 0.0338 0.0331 NC Oct 0 2,885,070 928,449 2,442,398 0.0310 0.0298 0.0293 NC Oct 1 2,763,997 887,557 2,351,682 0.0297 0.0285 0.0282 NC Oct 2 2,720,289 873,564 2,300,310 0.0292 0.0281 0.0276 NC Oct 3 2,783,044 896,560 2,344,762 0.0299 0.0288 0.0281 NC Oct 4 3,082,324 1,006,245 2,601,114 0.0331 0.0323 0.0312 NC Oct 5 3,619,699 1,193,245 3,037,925 0.0389 0.0383 0.0364 NC Oct 6 4,009,044 1,336,083 3,415,044 0.0431 0.0429 0.0410 NC Oct 7 4,124,324 1,361,719 3,513,460 0.0443 0.0437 0.0422 NC Oct 8 4,246,949 1,415,941 3,666,854 0.0456 0.0455 0.0440 NC Oct 9 4,314,835 1,440,726 3,784,701 0.0464 0.0463 0.0454 NC Oct 10 4,339,629 1,450,914 3,816,711 0.0466 0.0466 0.0458 NC Oct 11 4,349,419 1,461,892 3,841,587 0.0467 0.0469 0.0461 NC Oct 12 4,357,347 1,476,232 3,953,621 0.0468 0.0474 0.0474 NC Oct 13 4,338,826 1,487,464 4,094,481 0.0466 0.0478 0.0491 NC Oct 14 4,314,366 1,488,527 4,131,106 0.0464 0.0478 0.0496 NC Oct 15 4,316,652 1,485,833 4,106,754 0.0464 0.0477 0.0493 NC Oct 16 4,309,747 1,474,424 4,093,656 0.0463 0.0473 0.0491 NC Oct 17 4,339,072 1,478,737 4,084,329 0.0466 0.0475 0.0490 NC Oct 18 4,493,664 1,540,332 4,212,273 0.0483 0.0495 0.0505 NC Oct 19 4,450,160 1,514,183 4,126,568 0.0478 0.0486 0.0495 NC Oct 20 4,284,031 1,443,363 3,900,011 0.0460 0.0464 0.0468 NC Oct 21 3,975,347 1,323,443 3,594,778 0.0427 0.0425 0.0431 NC Oct 22 3,512,993 1,149,489 3,134,673 0.0377 0.0369 0.0376 NC Oct 23 3,146,439 1,025,300 2,806,812 0.0338 0.0329 0.0337 NC Nov 0 3,150,839 1,015,387 2,449,180 0.0350 0.0339 0.0336 NC Nov 1 3,028,579 971,948 2,360,809 0.0337 0.0324 0.0324 NC Nov 2 2,980,393 959,450 2,315,231 0.0331 0.0320 0.0317 NC Nov 3 2,996,471 969,449 2,326,773 0.0333 0.0323 0.0319 NC Nov 4 3,110,091 1,013,456 2,432,433 0.0346 0.0338 0.0333 NC Nov 5 3,397,863 1,122,707 2,719,216 0.0378 0.0375 0.0373 NC Nov 6 3,816,334 1,281,051 3,145,075 0.0424 0.0427 0.0431 NC Nov 7 4,044,328 1,358,786 3,355,851 0.0450 0.0453 0.0460 NC Nov 8 4,121,076 1,380,735 3,392,485 0.0458 0.0461 0.0465 NC Nov 9 4,141,648 1,394,679 3,387,725 0.0460 0.0465 0.0464 NC Nov 10 4,108,343 1,378,482 3,320,442 0.0457 0.0460 0.0455 NC Nov 11 4,021,305 1,349,512 3,269,332 0.0447 0.0450 0.0448 NC Nov 12 3,904,488 1,315,604 3,216,716 0.0434 0.0439 0.0441 NC Nov 13 3,825,065 1,289,627 3,183,346 0.0425 0.0430 0.0436 NC Nov 14 3,746,599 1,261,138 3,114,744 0.0416 0.0421 0.0427 NC Nov 15 3,701,103 1,252,501 3,108,862 0.0411 0.0418 0.0426

H-32Atmospheric Sciences Group 

### Appendix H Average 2000-2004 State Level Monthly-Diurnal Profiles

CEM-Based Distribution Alpine Geophysics

SO2 Mass NOx Mass Heat Input State Month Hour [lbs] [lbs] [MMBtu] SO2 Ratio NOx Ratio Heat Input Average Values [2000-2004] Calculated Ratios

NC Nov 16 3,777,052 1,273,672 3,164,960 0.0420 0.0425 0.0434 NC Nov 17 4,062,557 1,381,041 3,395,008 0.0452 0.0461 0.0465 NC Nov 18 4,291,870 1,463,476 3,557,570 0.0477 0.0488 0.0488 NC Nov 19 4,247,162 1,429,480 3,479,287 0.0472 0.0477 0.0477 NC Nov 20 4,186,388 1,395,882 3,370,869 0.0465 0.0466 0.0462 NC Nov 21 4,049,659 1,347,541 3,230,259 0.0450 0.0450 0.0443 NC Nov 22 3,799,944 1,252,490 2,970,701 0.0422 0.0418 0.0407 NC Nov 23 3,445,867 1,119,348 2,674,017 0.0383 0.0373 0.0367 NC Dec 0 3,746,730 1,304,213 3,329,238 0.0381 0.0364 0.0343 NC Dec 1 3,640,826 1,249,301 3,111,292 0.0371 0.0349 0.0320 NC Dec 2 3,604,310 1,236,941 3,029,282 0.0367 0.0346 0.0312 NC Dec 3 3,629,794 1,243,360 3,030,814 0.0369 0.0347 0.0312 NC Dec 4 3,728,167 1,296,002 3,236,096 0.0379 0.0362 0.0333 NC Dec 5 3,902,435 1,395,928 3,643,907 0.0397 0.0390 0.0375 NC Dec 6 4,205,452 1,551,236 4,365,683 0.0428 0.0433 0.0449 NC Dec 7 4,435,132 1,683,579 4,874,322 0.0451 0.0470 0.0502 NC Dec 8 4,518,449 1,723,609 4,993,567 0.0460 0.0482 0.0514 NC Dec 9 4,494,805 1,704,798 4,884,158 0.0457 0.0476 0.0503 NC Dec 10 4,377,997 1,646,309 4,645,870 0.0446 0.0460 0.0478 NC Dec 11 4,201,701 1,574,751 4,439,375 0.0428 0.0440 0.0457 NC Dec 12 4,035,944 1,488,621 4,115,556 0.0411 0.0416 0.0423 NC Dec 13 3,895,872 1,379,646 3,606,995 0.0396 0.0385 0.0371 NC Dec 14 3,780,919 1,338,989 3,454,137 0.0385 0.0374 0.0355 NC Dec 15 3,725,324 1,326,372 3,466,080 0.0379 0.0371 0.0357 NC Dec 16 3,856,207 1,379,749 3,737,941 0.0392 0.0385 0.0385 NC Dec 17 4,270,038 1,574,946 4,407,860 0.0435 0.0440 0.0454 NC Dec 18 4,520,968 1,690,557 4,747,898 0.0460 0.0472 0.0489 NC Dec 19 4,528,494 1,690,133 4,819,407 0.0461 0.0472 0.0496 NC Dec 20 4,505,067 1,682,184 4,769,232 0.0458 0.0470 0.0491 NC Dec 21 4,432,600 1,659,975 4,657,151 0.0451 0.0464 0.0479 NC Dec 22 4,259,928 1,562,495 4,182,135 0.0434 0.0437 0.0430 NC Dec 23 3,968,211 1,409,786 3,637,388 0.0404 0.0394 0.0374 SC Jan 0 1,728,093 721,116 1,850,156 0.0395 0.0391 0.0373 SC Jan 1 1,700,006 706,997 1,809,948 0.0389 0.0384 0.0365 SC Jan 2 1,698,665 704,675 1,809,371 0.0389 0.0382 0.0365 SC Jan 3 1,707,947 709,505 1,821,754 0.0391 0.0385 0.0367 SC Jan 4 1,729,700 717,457 1,871,774 0.0396 0.0389 0.0378 SC Jan 5 1,776,301 752,197 2,094,917 0.0406 0.0408 0.0423 SC Jan 6 1,860,983 787,384 2,287,912 0.0426 0.0427 0.0461 SC Jan 7 1,923,567 829,128 2,465,540 0.0440 0.0450 0.0497 SC Jan 8 1,933,655 810,887 2,466,285 0.0442 0.0440 0.0497 SC Jan 9 1,936,894 813,441 2,411,559 0.0443 0.0441 0.0486 SC Jan 10 1,918,638 794,597 2,235,280 0.0439 0.0431 0.0451 SC Jan 11 1,876,381 778,460 2,130,643 0.0429 0.0422 0.0430 SC Jan 12 1,830,742 761,547 2,036,485 0.0419 0.0413 0.0411 SC Jan 13 1,789,149 745,241 1,995,539 0.0409 0.0404 0.0402 SC Jan 14 1,759,395 727,972 1,952,888 0.0402 0.0395 0.0394 SC Jan 15 1,744,819 723,566 1,906,404 0.0399 0.0393 0.0385 SC Jan 16 1,757,000 739,319 1,922,537 0.0402 0.0401 0.0388 SC Jan 17 1,823,893 777,143 2,023,581 0.0417 0.0422 0.0408 SC Jan 18 1,912,362 829,821 2,168,269 0.0437 0.0450 0.0437 SC Jan 19 1,913,185 836,772 2,171,758 0.0438 0.0454 0.0438 SC Jan 20 1,898,515 825,406 2,135,170 0.0434 0.0448 0.0431

H-33Atmospheric Sciences Group 

### Appendix H Average 2000-2004 State Level Monthly-Diurnal Profiles

CEM-Based Distribution Alpine Geophysics

SO2 Mass NOx Mass Heat Input State Month Hour [lbs] [lbs] [MMBtu] SO2 Ratio NOx Ratio Heat Input Average Values [2000-2004] Calculated Ratios

SC Jan 21 1,883,924 803,841 2,093,017 0.0431 0.0436 0.0422 SC Jan 22 1,838,539 781,559 2,006,926 0.0421 0.0424 0.0405 SC Jan 23 1,779,635 754,512 1,912,777 0.0407 0.0409 0.0386 SC Feb 0 1,491,213 613,334 1,607,464 0.0387 0.0381 0.0372 SC Feb 1 1,463,158 597,825 1,576,644 0.0380 0.0372 0.0365 SC Feb 2 1,460,769 595,351 1,569,584 0.0379 0.0370 0.0363 SC Feb 3 1,473,152 604,627 1,575,911 0.0382 0.0376 0.0365 SC Feb 4 1,496,362 618,267 1,614,304 0.0388 0.0384 0.0373 SC Feb 5 1,557,038 644,924 1,726,173 0.0404 0.0401 0.0399 SC Feb 6 1,653,909 683,041 1,882,275 0.0429 0.0425 0.0435 SC Feb 7 1,728,362 721,019 2,067,084 0.0448 0.0448 0.0478 SC Feb 8 1,736,534 759,406 2,064,784 0.0451 0.0472 0.0478 SC Feb 9 1,735,409 775,830 1,994,870 0.0450 0.0482 0.0461 SC Feb 10 1,721,097 711,635 1,913,585 0.0447 0.0442 0.0443 SC Feb 11 1,673,555 696,036 1,846,604 0.0434 0.0433 0.0427 SC Feb 12 1,619,888 682,489 1,794,420 0.0420 0.0424 0.0415 SC Feb 13 1,578,544 650,899 1,749,844 0.0410 0.0405 0.0405 SC Feb 14 1,547,477 644,188 1,721,217 0.0402 0.0401 0.0398 SC Feb 15 1,532,282 624,880 1,698,203 0.0398 0.0388 0.0393 SC Feb 16 1,539,109 631,259 1,713,567 0.0399 0.0392 0.0396 SC Feb 17 1,579,567 657,001 1,791,698 0.0410 0.0408 0.0414 SC Feb 18 1,663,058 701,384 1,921,503 0.0432 0.0436 0.0445 SC Feb 19 1,697,528 723,836 1,976,870 0.0440 0.0450 0.0457 SC Feb 20 1,697,268 705,811 1,953,211 0.0440 0.0439 0.0452 SC Feb 21 1,687,160 699,588 1,924,838 0.0438 0.0435 0.0445 SC Feb 22 1,645,415 681,704 1,829,540 0.0427 0.0424 0.0423 SC Feb 23 1,563,182 660,164 1,713,133 0.0406 0.0410 0.0396 SC Mar 0 1,570,028 617,676 1,729,461 0.0376 0.0366 0.0358 SC Mar 1 1,531,400 602,756 1,688,537 0.0366 0.0357 0.0350 SC Mar 2 1,521,077 591,850 1,683,137 0.0364 0.0351 0.0349 SC Mar 3 1,523,949 595,935 1,703,237 0.0365 0.0353 0.0353 SC Mar 4 1,548,871 605,469 1,742,061 0.0371 0.0359 0.0361 SC Mar 5 1,620,422 643,732 1,902,989 0.0388 0.0382 0.0394 SC Mar 6 1,745,903 702,598 2,107,986 0.0418 0.0417 0.0437 SC Mar 7 1,830,523 747,531 2,335,048 0.0438 0.0443 0.0484 SC Mar 8 1,844,727 759,818 2,341,894 0.0441 0.0451 0.0485 SC Mar 9 1,855,820 756,820 2,275,264 0.0444 0.0449 0.0471 SC Mar 10 1,838,923 749,713 2,162,459 0.0440 0.0445 0.0448 SC Mar 11 1,818,689 737,663 2,094,414 0.0435 0.0437 0.0434 SC Mar 12 1,799,958 730,198 2,050,291 0.0431 0.0433 0.0425 SC Mar 13 1,778,256 720,279 2,024,946 0.0425 0.0427 0.0419 SC Mar 14 1,762,992 716,285 2,004,596 0.0422 0.0425 0.0415 SC Mar 15 1,754,896 712,561 1,989,139 0.0420 0.0423 0.0412 SC Mar 16 1,763,911 714,222 1,989,251 0.0422 0.0424 0.0412 SC Mar 17 1,787,826 729,933 2,036,373 0.0428 0.0433 0.0422 SC Mar 18 1,825,407 741,845 2,106,974 0.0437 0.0440 0.0436 SC Mar 19 1,883,948 769,078 2,165,672 0.0451 0.0456 0.0449 SC Mar 20 1,885,767 774,288 2,171,867 0.0451 0.0459 0.0450 SC Mar 21 1,865,243 759,550 2,122,958 0.0446 0.0450 0.0440 SC Mar 22 1,796,203 724,800 2,006,710 0.0430 0.0430 0.0416 SC Mar 23 1,644,196 659,138 1,835,734 0.0393 0.0391 0.0380 SC Apr 0 1,449,915 578,366 1,541,052 0.0369 0.0355 0.0331 SC Apr 1 1,413,251 559,096 1,508,815 0.0360 0.0343 0.0324

H-34Atmospheric Sciences Group 

### Appendix H Average 2000-2004 State Level Monthly-Diurnal Profiles

CEM-Based Distribution Alpine Geophysics

SO2 Mass NOx Mass Heat Input State Month Hour [lbs] [lbs] [MMBtu] SO2 Ratio NOx Ratio Heat Input Average Values [2000-2004] Calculated Ratios

SC Apr 2 1,399,197 553,497 1,497,568 0.0356 0.0340 0.0322 SC Apr 3 1,395,975 554,522 1,498,333 0.0355 0.0340 0.0322 SC Apr 4 1,444,258 579,023 1,584,251 0.0367 0.0355 0.0340 SC Apr 5 1,541,273 627,007 1,735,422 0.0392 0.0385 0.0373 SC Apr 6 1,626,261 664,207 1,877,552 0.0414 0.0407 0.0403 SC Apr 7 1,651,226 691,226 1,961,326 0.0420 0.0424 0.0421 SC Apr 8 1,692,028 700,213 1,940,268 0.0430 0.0430 0.0417 SC Apr 9 1,719,835 714,123 1,947,967 0.0437 0.0438 0.0418 SC Apr 10 1,729,069 721,714 2,021,772 0.0440 0.0443 0.0434 SC Apr 11 1,737,657 729,330 2,128,857 0.0442 0.0447 0.0457 SC Apr 12 1,741,301 732,848 2,180,195 0.0443 0.0450 0.0468 SC Apr 13 1,736,903 735,831 2,235,280 0.0442 0.0451 0.0480 SC Apr 14 1,736,370 735,125 2,259,505 0.0442 0.0451 0.0485 SC Apr 15 1,740,580 739,391 2,251,512 0.0443 0.0454 0.0484 SC Apr 16 1,747,930 740,665 2,226,652 0.0445 0.0454 0.0478 SC Apr 17 1,741,543 742,101 2,206,888 0.0443 0.0455 0.0474 SC Apr 18 1,728,436 728,244 2,173,481 0.0440 0.0447 0.0467 SC Apr 19 1,755,766 735,011 2,190,506 0.0447 0.0451 0.0471 SC Apr 20 1,761,299 738,799 2,158,688 0.0448 0.0453 0.0464 SC Apr 21 1,705,932 721,195 2,017,954 0.0434 0.0442 0.0433 SC Apr 22 1,608,642 670,600 1,797,648 0.0409 0.0411 0.0386 SC Apr 23 1,506,893 610,338 1,608,882 0.0383 0.0374 0.0346 SC May 0 1,498,612 637,097 1,833,832 0.0362 0.0347 0.0316 SC May 1 1,450,392 615,904 1,771,923 0.0351 0.0336 0.0306 SC May 2 1,417,869 602,820 1,744,069 0.0343 0.0329 0.0301 SC May 3 1,400,882 600,357 1,733,497 0.0339 0.0327 0.0299 SC May 4 1,428,284 614,115 1,759,756 0.0345 0.0335 0.0304 SC May 5 1,519,500 652,482 1,859,793 0.0367 0.0356 0.0321 SC May 6 1,611,498 693,767 1,967,396 0.0390 0.0378 0.0339 SC May 7 1,648,860 723,968 2,049,759 0.0399 0.0395 0.0354 SC May 8 1,720,799 755,914 2,185,667 0.0416 0.0412 0.0377 SC May 9 1,779,287 792,359 2,389,819 0.0430 0.0432 0.0412 SC May 10 1,833,007 822,368 2,607,752 0.0443 0.0448 0.0450 SC May 11 1,873,194 849,691 2,835,887 0.0453 0.0463 0.0489 SC May 12 1,894,648 868,950 2,950,397 0.0458 0.0474 0.0509 SC May 13 1,910,942 888,796 2,995,481 0.0462 0.0485 0.0517 SC May 14 1,907,923 885,213 3,037,408 0.0461 0.0483 0.0524 SC May 15 1,918,453 876,112 3,069,418 0.0464 0.0478 0.0530 SC May 16 1,921,958 876,388 3,063,115 0.0465 0.0478 0.0529 SC May 17 1,904,834 867,684 3,023,165 0.0461 0.0473 0.0522 SC May 18 1,876,441 841,868 2,911,756 0.0454 0.0459 0.0502 SC May 19 1,868,291 830,060 2,862,350 0.0452 0.0453 0.0494 SC May 20 1,868,894 830,803 2,786,645 0.0452 0.0453 0.0481 SC May 21 1,817,535 803,046 2,460,990 0.0440 0.0438 0.0425 SC May 22 1,699,689 738,375 2,120,530 0.0411 0.0403 0.0366 SC May 23 1,576,820 673,205 1,933,990 0.0381 0.0367 0.0334 SC Jun 0 1,493,640 582,310 1,794,445 0.0364 0.0353 0.0323 SC Jun 1 1,432,120 558,309 1,727,493 0.0349 0.0339 0.0311 SC Jun 2 1,391,295 543,551 1,690,485 0.0339 0.0330 0.0304 SC Jun 3 1,374,261 540,031 1,666,058 0.0335 0.0328 0.0300 SC Jun 4 1,385,262 541,945 1,672,944 0.0338 0.0329 0.0301 SC Jun 5 1,428,870 557,257 1,718,034 0.0349 0.0338 0.0309 SC Jun 6 1,496,140 582,334 1,784,352 0.0365 0.0353 0.0321

H-35Atmospheric Sciences Group 

### Appendix H Average 2000-2004 State Level Monthly-Diurnal Profiles

CEM-Based Distribution Alpine Geophysics

SO2 Mass NOx Mass Heat Input State Month Hour [lbs] [lbs] [MMBtu] SO2 Ratio NOx Ratio Heat Input Average Values [2000-2004] Calculated Ratios

SC Jun 7 1,569,789 624,786 1,885,299 0.0383 0.0379 0.0339 SC Jun 8 1,687,007 681,249 2,089,132 0.0411 0.0413 0.0376 SC Jun 9 1,773,648 718,864 2,303,706 0.0433 0.0436 0.0414 SC Jun 10 1,849,785 758,252 2,555,332 0.0451 0.0460 0.0460 SC Jun 11 1,898,722 778,157 2,738,523 0.0463 0.0472 0.0492 SC Jun 12 1,919,728 793,701 2,834,378 0.0468 0.0481 0.0510 SC Jun 13 1,932,270 798,164 2,886,166 0.0471 0.0484 0.0519 SC Jun 14 1,936,457 797,934 2,921,888 0.0472 0.0484 0.0525 SC Jun 15 1,936,616 792,769 2,936,701 0.0472 0.0481 0.0528 SC Jun 16 1,928,347 785,587 2,920,656 0.0470 0.0477 0.0525 SC Jun 17 1,911,440 779,492 2,886,164 0.0466 0.0473 0.0519 SC Jun 18 1,882,383 761,132 2,799,440 0.0459 0.0462 0.0503 SC Jun 19 1,855,166 746,872 2,702,881 0.0453 0.0453 0.0486 SC Jun 20 1,851,233 746,366 2,676,326 0.0452 0.0453 0.0481 SC Jun 21 1,801,170 725,445 2,437,466 0.0439 0.0440 0.0438 SC Jun 22 1,692,344 673,917 2,079,593 0.0413 0.0409 0.0374 SC Jun 23 1,570,218 616,659 1,900,884 0.0383 0.0374 0.0342 SC Jul 0 1,620,900 617,147 1,915,031 0.0369 0.0358 0.0326 SC Jul 1 1,551,483 588,500 1,850,564 0.0354 0.0341 0.0315 SC Jul 2 1,500,227 571,371 1,806,669 0.0342 0.0331 0.0308 SC Jul 3 1,472,648 563,618 1,788,381 0.0336 0.0327 0.0304 SC Jul 4 1,479,367 567,725 1,795,608 0.0337 0.0329 0.0306 SC Jul 5 1,524,479 585,021 1,839,929 0.0348 0.0339 0.0313 SC Jul 6 1,587,303 606,797 1,891,656 0.0362 0.0352 0.0322 SC Jul 7 1,670,210 646,514 2,008,168 0.0381 0.0375 0.0342 SC Jul 8 1,793,230 704,890 2,254,461 0.0409 0.0409 0.0384 SC Jul 9 1,900,677 759,809 2,535,975 0.0433 0.0441 0.0432 SC Jul 10 1,974,755 791,754 2,719,318 0.0450 0.0459 0.0463 SC Jul 11 2,012,079 807,840 2,877,177 0.0459 0.0469 0.0490 SC Jul 12 2,040,709 822,946 2,967,171 0.0465 0.0477 0.0505 SC Jul 13 2,049,158 825,391 3,004,287 0.0467 0.0479 0.0511 SC Jul 14 2,052,040 833,307 3,047,656 0.0468 0.0483 0.0519 SC Jul 15 2,060,489 832,450 3,057,284 0.0470 0.0483 0.0520 SC Jul 16 2,055,686 825,135 3,025,976 0.0469 0.0479 0.0515 SC Jul 17 2,043,298 816,427 2,987,729 0.0466 0.0474 0.0509 SC Jul 18 2,018,525 798,095 2,919,358 0.0460 0.0463 0.0497 SC Jul 19 1,991,587 781,061 2,863,829 0.0454 0.0453 0.0488 SC Jul 20 1,992,241 778,797 2,817,732 0.0454 0.0452 0.0480 SC Jul 21 1,932,045 752,881 2,540,668 0.0440 0.0437 0.0433 SC Jul 22 1,830,533 705,997 2,211,035 0.0417 0.0409 0.0376 SC Jul 23 1,713,740 657,337 2,016,164 0.0391 0.0381 0.0343 SC Aug 0 1,669,000 626,459 1,923,024 0.0374 0.0366 0.0328 SC Aug 1 1,599,912 597,112 1,868,252 0.0358 0.0349 0.0319 SC Aug 2 1,549,850 579,237 1,827,890 0.0347 0.0339 0.0312 SC Aug 3 1,525,004 570,235 1,806,279 0.0342 0.0333 0.0308 SC Aug 4 1,545,884 575,793 1,820,358 0.0346 0.0337 0.0310 SC Aug 5 1,624,700 601,188 1,883,030 0.0364 0.0351 0.0321 SC Aug 6 1,690,450 623,077 1,925,134 0.0379 0.0364 0.0328 SC Aug 7 1,723,400 650,536 2,013,158 0.0386 0.0380 0.0343 SC Aug 8 1,814,519 684,468 2,197,919 0.0406 0.0400 0.0375 SC Aug 9 1,906,415 742,701 2,474,234 0.0427 0.0434 0.0422 SC Aug 10 1,980,397 776,292 2,713,602 0.0444 0.0454 0.0463 SC Aug 11 2,032,443 786,958 2,847,333 0.0455 0.0460 0.0486

H-36Atmospheric Sciences Group 

### Appendix H Average 2000-2004 State Level Monthly-Diurnal Profiles

CEM-Based Distribution Alpine Geophysics

SO2 Mass NOx Mass Heat Input State Month Hour [lbs] [lbs] [MMBtu] SO2 Ratio NOx Ratio Heat Input Average Values [2000-2004] Calculated Ratios

SC Aug 12 2,052,610 802,943 2,924,493 0.0460 0.0469 0.0499 SC Aug 13 2,056,243 814,991 2,990,621 0.0461 0.0476 0.0510 SC Aug 14 2,063,580 821,035 3,064,772 0.0462 0.0480 0.0523 SC Aug 15 2,069,925 820,542 3,065,071 0.0464 0.0480 0.0523 SC Aug 16 2,063,212 816,753 3,024,907 0.0462 0.0477 0.0516 SC Aug 17 2,052,183 799,002 2,966,453 0.0460 0.0467 0.0506 SC Aug 18 2,029,780 779,424 2,877,464 0.0455 0.0456 0.0491 SC Aug 19 2,026,175 773,835 2,859,409 0.0454 0.0452 0.0488 SC Aug 20 2,020,544 769,733 2,798,475 0.0453 0.0450 0.0477 SC Aug 21 1,956,666 743,184 2,558,532 0.0438 0.0434 0.0436 SC Aug 22 1,863,302 700,535 2,201,837 0.0417 0.0409 0.0375 SC Aug 23 1,735,189 654,070 2,012,343 0.0389 0.0382 0.0343 SC Sep 0 1,433,481 529,517 1,641,405 0.0355 0.0342 0.0322 SC Sep 1 1,389,388 511,584 1,593,230 0.0345 0.0330 0.0313 SC Sep 2 1,359,473 502,039 1,572,801 0.0337 0.0324 0.0309 SC Sep 3 1,348,909 500,153 1,562,637 0.0335 0.0323 0.0307 SC Sep 4 1,380,888 510,443 1,593,344 0.0342 0.0330 0.0313 SC Sep 5 1,492,551 550,177 1,702,039 0.0370 0.0355 0.0334 SC Sep 6 1,579,565 590,679 1,812,898 0.0392 0.0382 0.0356 SC Sep 7 1,593,015 604,185 1,865,786 0.0395 0.0390 0.0366 SC Sep 8 1,677,248 638,007 1,960,842 0.0416 0.0412 0.0385 SC Sep 9 1,746,822 679,229 2,095,183 0.0433 0.0439 0.0411 SC Sep 10 1,806,770 703,403 2,249,399 0.0448 0.0454 0.0441 SC Sep 11 1,847,957 722,659 2,412,048 0.0458 0.0467 0.0473 SC Sep 12 1,866,568 732,681 2,543,527 0.0463 0.0473 0.0499 SC Sep 13 1,871,396 737,879 2,614,316 0.0464 0.0477 0.0513 SC Sep 14 1,875,795 743,721 2,648,594 0.0465 0.0480 0.0520 SC Sep 15 1,881,431 748,017 2,675,173 0.0467 0.0483 0.0525 SC Sep 16 1,885,700 750,387 2,653,661 0.0468 0.0485 0.0521 SC Sep 17 1,870,019 736,902 2,605,312 0.0464 0.0476 0.0511 SC Sep 18 1,861,590 728,943 2,528,650 0.0462 0.0471 0.0496 SC Sep 19 1,868,290 725,154 2,512,852 0.0463 0.0468 0.0493 SC Sep 20 1,835,112 702,531 2,382,740 0.0455 0.0454 0.0467 SC Sep 21 1,740,640 664,927 2,132,217 0.0432 0.0430 0.0418 SC Sep 22 1,614,198 610,261 1,897,061 0.0400 0.0394 0.0372 SC Sep 23 1,496,236 557,588 1,722,445 0.0371 0.0360 0.0338 SC Oct 0 1,584,045 572,629 1,614,079 0.0372 0.0356 0.0336 SC Oct 1 1,563,179 560,778 1,593,106 0.0367 0.0348 0.0331 SC Oct 2 1,552,024 555,435 1,585,690 0.0365 0.0345 0.0330 SC Oct 3 1,563,378 558,152 1,592,294 0.0367 0.0347 0.0331 SC Oct 4 1,622,994 580,487 1,649,210 0.0381 0.0361 0.0343 SC Oct 5 1,736,202 627,877 1,768,874 0.0408 0.0390 0.0368 SC Oct 6 1,825,628 676,786 1,886,492 0.0429 0.0420 0.0392 SC Oct 7 1,821,919 686,702 1,951,542 0.0428 0.0426 0.0406 SC Oct 8 1,847,515 700,465 2,011,122 0.0434 0.0435 0.0418 SC Oct 9 1,859,064 707,811 2,060,220 0.0437 0.0440 0.0428 SC Oct 10 1,856,435 713,978 2,110,551 0.0436 0.0443 0.0439 SC Oct 11 1,856,542 718,014 2,185,946 0.0436 0.0446 0.0455 SC Oct 12 1,860,690 724,268 2,260,835 0.0437 0.0450 0.0470 SC Oct 13 1,852,592 726,262 2,313,236 0.0435 0.0451 0.0481 SC Oct 14 1,850,542 731,678 2,351,017 0.0435 0.0454 0.0489 SC Oct 15 1,849,413 726,668 2,355,006 0.0435 0.0451 0.0490 SC Oct 16 1,852,257 727,366 2,351,463 0.0435 0.0452 0.0489

H-37Atmospheric Sciences Group 

### Appendix H Average 2000-2004 State Level Monthly-Diurnal Profiles

CEM-Based Distribution Alpine Geophysics

SO2 Mass NOx Mass Heat Input State Month Hour [lbs] [lbs] [MMBtu] SO2 Ratio NOx Ratio Heat Input Average Values [2000-2004] Calculated Ratios

SC Oct 17 1,856,069 722,520 2,320,623 0.0436 0.0449 0.0483 SC Oct 18 1,877,238 724,131 2,326,335 0.0441 0.0450 0.0484 SC Oct 19 1,866,808 719,859 2,264,805 0.0439 0.0447 0.0471 SC Oct 20 1,846,455 709,888 2,120,661 0.0434 0.0441 0.0441 SC Oct 21 1,808,760 687,389 1,949,504 0.0425 0.0427 0.0405 SC Oct 22 1,719,502 642,997 1,780,385 0.0404 0.0399 0.0370 SC Oct 23 1,631,545 599,680 1,684,084 0.0383 0.0372 0.0350 SC Nov 0 1,634,166 594,383 1,624,338 0.0388 0.0380 0.0363 SC Nov 1 1,610,839 582,397 1,581,038 0.0382 0.0372 0.0353 SC Nov 2 1,596,014 575,703 1,568,622 0.0379 0.0368 0.0350 SC Nov 3 1,593,761 576,837 1,571,912 0.0378 0.0369 0.0351 SC Nov 4 1,617,385 588,331 1,616,640 0.0384 0.0376 0.0361 SC Nov 5 1,680,281 616,701 1,740,703 0.0399 0.0394 0.0389 SC Nov 6 1,776,053 662,254 1,965,145 0.0422 0.0423 0.0439 SC Nov 7 1,827,927 691,215 2,079,637 0.0434 0.0442 0.0465 SC Nov 8 1,827,180 687,112 2,072,905 0.0434 0.0439 0.0463 SC Nov 9 1,844,213 692,367 1,998,167 0.0438 0.0442 0.0446 SC Nov 10 1,835,738 684,115 1,937,503 0.0436 0.0437 0.0433 SC Nov 11 1,821,015 673,682 1,913,900 0.0432 0.0430 0.0428 SC Nov 12 1,798,370 667,312 1,914,041 0.0427 0.0426 0.0428 SC Nov 13 1,777,001 660,714 1,895,154 0.0422 0.0422 0.0423 SC Nov 14 1,759,967 658,086 1,914,232 0.0418 0.0421 0.0428 SC Nov 15 1,747,486 655,088 1,914,966 0.0415 0.0419 0.0428 SC Nov 16 1,755,083 656,719 1,932,851 0.0417 0.0420 0.0432 SC Nov 17 1,810,800 678,076 1,991,746 0.0430 0.0433 0.0445 SC Nov 18 1,863,271 701,664 2,081,308 0.0442 0.0448 0.0465 SC Nov 19 1,852,579 697,417 2,055,872 0.0440 0.0446 0.0459 SC Nov 20 1,830,891 688,044 1,988,740 0.0435 0.0440 0.0444 SC Nov 21 1,807,895 678,467 1,926,918 0.0429 0.0434 0.0430 SC Nov 22 1,772,932 660,130 1,801,442 0.0421 0.0422 0.0402 SC Nov 23 1,689,054 622,763 1,674,656 0.0401 0.0398 0.0374 SC Dec 0 1,790,705 674,127 1,908,284 0.0401 0.0395 0.0375 SC Dec 1 1,760,847 659,279 1,877,399 0.0395 0.0386 0.0369 SC Dec 2 1,766,498 660,719 1,890,957 0.0396 0.0387 0.0372 SC Dec 3 1,766,455 664,407 1,922,535 0.0396 0.0389 0.0378 SC Dec 4 1,788,023 677,882 2,005,041 0.0401 0.0397 0.0394 SC Dec 5 1,839,136 708,796 2,193,779 0.0412 0.0415 0.0431 SC Dec 6 1,903,431 736,781 2,379,535 0.0427 0.0432 0.0468 SC Dec 7 1,957,422 760,608 2,504,498 0.0439 0.0446 0.0492 SC Dec 8 1,958,923 768,669 2,515,860 0.0439 0.0450 0.0494 SC Dec 9 1,974,624 767,392 2,419,052 0.0443 0.0450 0.0475 SC Dec 10 1,944,825 751,207 2,264,252 0.0436 0.0440 0.0445 SC Dec 11 1,888,552 723,857 2,140,166 0.0423 0.0424 0.0421 SC Dec 12 1,833,408 694,261 2,022,036 0.0411 0.0407 0.0397 SC Dec 13 1,781,162 673,316 1,936,841 0.0399 0.0395 0.0381 SC Dec 14 1,755,403 663,791 1,911,001 0.0393 0.0389 0.0376 SC Dec 15 1,743,443 660,042 1,897,088 0.0391 0.0387 0.0373 SC Dec 16 1,775,717 669,264 1,937,000 0.0398 0.0392 0.0381 SC Dec 17 1,877,548 713,920 2,099,275 0.0421 0.0418 0.0413 SC Dec 18 1,948,165 753,627 2,255,923 0.0437 0.0442 0.0443 SC Dec 19 1,940,185 753,123 2,258,417 0.0435 0.0441 0.0444 SC Dec 20 1,941,859 750,942 2,221,568 0.0435 0.0440 0.0437 SC Dec 21 1,930,605 743,880 2,182,689 0.0433 0.0436 0.0429

H-38Atmospheric Sciences Group 

### Appendix H Average 2000-2004 State Level Monthly-Diurnal Profiles

CEM-Based Distribution Alpine Geophysics

SO2 Mass NOx Mass Heat Input State Month Hour [lbs] [lbs] [MMBtu] SO2 Ratio NOx Ratio Heat Input Average Values [2000-2004] Calculated Ratios

SC Dec 22 1,909,077 732,480 2,140,416 0.0428 0.0429 0.0421 SC Dec 23 1,841,457 702,464 2,003,560 0.0413 0.0412 0.0394 TN Jan 0 2,920,730 1,316,670 2,817,787 0.0408 0.0406 0.0399 TN Jan 1 2,905,383 1,309,968 2,787,169 0.0406 0.0404 0.0395 TN Jan 2 2,896,852 1,315,743 2,779,735 0.0405 0.0405 0.0394 TN Jan 3 2,903,214 1,311,102 2,795,456 0.0405 0.0404 0.0396 TN Jan 4 2,942,126 1,324,196 2,817,908 0.0411 0.0408 0.0399 TN Jan 5 2,996,259 1,367,394 2,947,753 0.0418 0.0421 0.0418 TN Jan 6 3,012,850 1,387,044 3,096,095 0.0421 0.0427 0.0439 TN Jan 7 2,990,321 1,386,216 3,127,023 0.0418 0.0427 0.0443 TN Jan 8 3,017,898 1,385,708 3,089,071 0.0421 0.0427 0.0438 TN Jan 9 3,024,338 1,380,461 3,016,715 0.0422 0.0425 0.0428 TN Jan 10 3,015,220 1,377,561 2,955,646 0.0421 0.0424 0.0419 TN Jan 11 2,997,070 1,360,861 2,908,329 0.0419 0.0419 0.0412 TN Jan 12 2,980,028 1,337,986 2,842,003 0.0416 0.0412 0.0403 TN Jan 13 2,963,100 1,326,028 2,807,869 0.0414 0.0408 0.0398 TN Jan 14 2,941,105 1,324,684 2,798,369 0.0411 0.0408 0.0397 TN Jan 15 2,954,133 1,330,977 2,803,884 0.0413 0.0410 0.0397 TN Jan 16 2,995,673 1,341,978 2,875,433 0.0418 0.0413 0.0408 TN Jan 17 3,039,411 1,375,915 3,031,799 0.0424 0.0424 0.0430 TN Jan 18 3,053,103 1,390,734 3,145,028 0.0426 0.0428 0.0446 TN Jan 19 3,047,225 1,383,178 3,101,091 0.0426 0.0426 0.0440 TN Jan 20 3,042,230 1,375,234 3,059,203 0.0425 0.0424 0.0434 TN Jan 21 3,028,915 1,367,629 3,027,200 0.0423 0.0421 0.0429 TN Jan 22 2,988,540 1,351,866 2,980,122 0.0417 0.0416 0.0422 TN Jan 23 2,952,443 1,334,516 2,933,297 0.0412 0.0411 0.0416 TN Feb 0 2,574,224 1,151,313 2,217,245 0.0406 0.0404 0.0384 TN Feb 1 2,557,366 1,145,383 2,206,566 0.0403 0.0402 0.0382 TN Feb 2 2,551,600 1,144,234 2,207,289 0.0402 0.0401 0.0382 TN Feb 3 2,559,011 1,148,687 2,216,546 0.0403 0.0403 0.0383 TN Feb 4 2,591,672 1,162,344 2,248,486 0.0408 0.0408 0.0389 TN Feb 5 2,651,923 1,189,079 2,344,707 0.0418 0.0417 0.0406 TN Feb 6 2,680,511 1,223,915 2,551,773 0.0422 0.0429 0.0441 TN Feb 7 2,650,988 1,211,667 2,578,810 0.0418 0.0425 0.0446 TN Feb 8 2,679,949 1,217,896 2,576,993 0.0422 0.0427 0.0446 TN Feb 9 2,683,101 1,211,581 2,564,322 0.0423 0.0425 0.0444 TN Feb 10 2,673,675 1,206,579 2,544,375 0.0421 0.0423 0.0440 TN Feb 11 2,664,060 1,202,952 2,520,062 0.0420 0.0422 0.0436 TN Feb 12 2,653,417 1,190,479 2,460,839 0.0418 0.0417 0.0426 TN Feb 13 2,639,218 1,180,516 2,413,891 0.0416 0.0414 0.0418 TN Feb 14 2,628,210 1,177,559 2,384,980 0.0414 0.0413 0.0413 TN Feb 15 2,628,281 1,178,523 2,372,935 0.0414 0.0413 0.0410 TN Feb 16 2,651,670 1,186,017 2,397,712 0.0418 0.0416 0.0415 TN Feb 17 2,685,519 1,202,328 2,475,913 0.0423 0.0422 0.0428 TN Feb 18 2,698,565 1,217,822 2,570,199 0.0425 0.0427 0.0445 TN Feb 19 2,701,659 1,216,684 2,552,752 0.0426 0.0427 0.0442 TN Feb 20 2,704,139 1,212,103 2,497,266 0.0426 0.0425 0.0432 TN Feb 21 2,690,620 1,196,275 2,377,774 0.0424 0.0419 0.0411 TN Feb 22 2,646,491 1,178,261 2,285,972 0.0417 0.0413 0.0395 TN Feb 23 2,601,231 1,164,774 2,240,497 0.0410 0.0408 0.0388 TN Mar 0 2,863,192 1,262,633 2,526,716 0.0407 0.0410 0.0401 TN Mar 1 2,837,249 1,251,145 2,507,599 0.0404 0.0406 0.0398 TN Mar 2 2,823,322 1,249,157 2,496,297 0.0402 0.0406 0.0396

H-39Atmospheric Sciences Group 

### Appendix H Average 2000-2004 State Level Monthly-Diurnal Profiles

CEM-Based Distribution Alpine Geophysics

SO2 Mass NOx Mass Heat Input State Month Hour [lbs] [lbs] [MMBtu] SO2 Ratio NOx Ratio Heat Input Average Values [2000-2004] Calculated Ratios

TN Mar 3 2,828,541 1,248,522 2,501,230 0.0402 0.0406 0.0397 TN Mar 4 2,869,746 1,260,202 2,544,223 0.0408 0.0409 0.0404 TN Mar 5 2,928,552 1,284,292 2,623,597 0.0417 0.0417 0.0417 TN Mar 6 2,953,220 1,306,974 2,753,518 0.0420 0.0424 0.0437 TN Mar 7 2,923,573 1,299,658 2,758,224 0.0416 0.0422 0.0438 TN Mar 8 2,957,454 1,304,343 2,741,578 0.0421 0.0424 0.0435 TN Mar 9 2,963,917 1,299,364 2,741,377 0.0422 0.0422 0.0435 TN Mar 10 2,968,817 1,300,732 2,714,868 0.0422 0.0422 0.0431 TN Mar 11 2,964,270 1,296,993 2,676,089 0.0422 0.0421 0.0425 TN Mar 12 2,950,743 1,287,801 2,649,580 0.0420 0.0418 0.0421 TN Mar 13 2,941,859 1,279,364 2,612,823 0.0419 0.0416 0.0415 TN Mar 14 2,930,183 1,277,018 2,593,250 0.0417 0.0415 0.0412 TN Mar 15 2,932,723 1,281,825 2,599,888 0.0417 0.0416 0.0413 TN Mar 16 2,943,762 1,284,331 2,636,583 0.0419 0.0417 0.0419 TN Mar 17 2,957,894 1,290,928 2,647,950 0.0421 0.0419 0.0420 TN Mar 18 2,993,900 1,301,854 2,674,917 0.0426 0.0423 0.0425 TN Mar 19 2,994,829 1,298,907 2,650,295 0.0426 0.0422 0.0421 TN Mar 20 2,989,464 1,292,354 2,613,530 0.0425 0.0420 0.0415 TN Mar 21 2,969,883 1,292,277 2,616,515 0.0423 0.0420 0.0415 TN Mar 22 2,916,682 1,274,315 2,562,055 0.0415 0.0414 0.0407 TN Mar 23 2,881,256 1,264,335 2,535,423 0.0410 0.0411 0.0403 TN Apr 0 2,625,217 1,172,033 2,299,120 0.0391 0.0397 0.0369 TN Apr 1 2,578,697 1,159,617 2,271,067 0.0384 0.0393 0.0365 TN Apr 2 2,574,083 1,158,195 2,265,690 0.0384 0.0392 0.0364 TN Apr 3 2,624,825 1,173,118 2,297,404 0.0391 0.0397 0.0369 TN Apr 4 2,720,941 1,202,595 2,359,428 0.0405 0.0407 0.0379 TN Apr 5 2,788,626 1,226,813 2,427,784 0.0415 0.0415 0.0390 TN Apr 6 2,788,759 1,227,899 2,474,661 0.0416 0.0416 0.0397 TN Apr 7 2,818,389 1,238,747 2,527,803 0.0420 0.0419 0.0406 TN Apr 8 2,849,956 1,246,791 2,586,541 0.0425 0.0422 0.0415 TN Apr 9 2,867,309 1,254,034 2,663,316 0.0427 0.0424 0.0428 TN Apr 10 2,867,472 1,253,711 2,698,362 0.0427 0.0424 0.0433 TN Apr 11 2,863,549 1,249,645 2,741,716 0.0427 0.0423 0.0440 TN Apr 12 2,867,333 1,252,766 2,759,701 0.0427 0.0424 0.0443 TN Apr 13 2,858,513 1,254,263 2,807,480 0.0426 0.0425 0.0451 TN Apr 14 2,856,845 1,260,763 2,853,766 0.0426 0.0427 0.0458 TN Apr 15 2,864,303 1,261,551 2,879,269 0.0427 0.0427 0.0462 TN Apr 16 2,868,405 1,267,334 2,886,568 0.0427 0.0429 0.0464 TN Apr 17 2,861,870 1,261,902 2,846,282 0.0426 0.0427 0.0457 TN Apr 18 2,880,421 1,265,115 2,844,539 0.0429 0.0428 0.0457 TN Apr 19 2,900,870 1,265,814 2,820,568 0.0432 0.0428 0.0453 TN Apr 20 2,880,610 1,256,356 2,697,267 0.0429 0.0425 0.0433 TN Apr 21 2,835,442 1,237,363 2,502,602 0.0422 0.0419 0.0402 TN Apr 22 2,769,167 1,209,273 2,405,900 0.0413 0.0409 0.0386 TN Apr 23 2,703,503 1,188,450 2,347,113 0.0403 0.0402 0.0377 TN May 0 2,631,555 1,160,164 2,615,593 0.0389 0.0384 0.0354 TN May 1 2,574,254 1,143,565 2,581,271 0.0381 0.0378 0.0349 TN May 2 2,548,784 1,137,709 2,564,942 0.0377 0.0376 0.0347 TN May 3 2,577,452 1,147,024 2,583,630 0.0381 0.0379 0.0349 TN May 4 2,663,387 1,172,451 2,638,991 0.0394 0.0388 0.0357 TN May 5 2,728,230 1,195,582 2,693,617 0.0404 0.0395 0.0364 TN May 6 2,740,909 1,207,176 2,733,403 0.0405 0.0399 0.0370 TN May 7 2,813,279 1,224,967 2,802,616 0.0416 0.0405 0.0379

H-40Atmospheric Sciences Group 

### Appendix H Average 2000-2004 State Level Monthly-Diurnal Profiles

CEM-Based Distribution Alpine Geophysics

SO2 Mass NOx Mass Heat Input State Month Hour [lbs] [lbs] [MMBtu] SO2 Ratio NOx Ratio Heat Input Average Values [2000-2004] Calculated Ratios

TN May 8 2,866,414 1,259,872 2,956,049 0.0424 0.0417 0.0400 TN May 9 2,897,754 1,290,113 3,148,346 0.0429 0.0427 0.0426 TN May 10 2,904,984 1,300,993 3,325,062 0.0430 0.0430 0.0450 TN May 11 2,909,001 1,312,403 3,428,253 0.0430 0.0434 0.0464 TN May 12 2,919,046 1,348,697 3,527,999 0.0432 0.0446 0.0477 TN May 13 2,937,062 1,358,846 3,575,834 0.0434 0.0449 0.0484 TN May 14 2,941,896 1,351,649 3,567,107 0.0435 0.0447 0.0483 TN May 15 2,942,890 1,349,174 3,547,924 0.0435 0.0446 0.0480 TN May 16 2,937,367 1,352,944 3,547,779 0.0434 0.0447 0.0480 TN May 17 2,930,449 1,327,585 3,484,890 0.0433 0.0439 0.0471 TN May 18 2,925,523 1,313,653 3,400,207 0.0433 0.0434 0.0460 TN May 19 2,944,354 1,341,489 3,438,419 0.0436 0.0444 0.0465 TN May 20 2,922,881 1,309,977 3,282,625 0.0432 0.0433 0.0444 TN May 21 2,856,276 1,253,934 3,031,131 0.0422 0.0415 0.0410 TN May 22 2,784,018 1,203,191 2,779,087 0.0412 0.0398 0.0376 TN May 23 2,707,081 1,176,836 2,669,865 0.0400 0.0389 0.0361 TN Jun 0 2,531,287 1,069,631 2,469,862 0.0389 0.0388 0.0353 TN Jun 1 2,443,469 1,043,386 2,397,826 0.0376 0.0378 0.0343 TN Jun 2 2,397,437 1,027,933 2,357,153 0.0369 0.0373 0.0337 TN Jun 3 2,396,925 1,025,848 2,357,414 0.0369 0.0372 0.0337 TN Jun 4 2,445,340 1,040,336 2,396,349 0.0376 0.0377 0.0342 TN Jun 5 2,482,825 1,053,426 2,436,201 0.0382 0.0382 0.0348 TN Jun 6 2,521,704 1,060,823 2,495,153 0.0388 0.0385 0.0357 TN Jun 7 2,635,894 1,101,150 2,593,679 0.0406 0.0399 0.0371 TN Jun 8 2,732,826 1,140,529 2,779,909 0.0420 0.0414 0.0397 TN Jun 9 2,800,274 1,162,971 2,984,580 0.0431 0.0422 0.0426 TN Jun 10 2,836,621 1,177,750 3,089,931 0.0436 0.0427 0.0442 TN Jun 11 2,849,870 1,210,074 3,219,989 0.0438 0.0439 0.0460 TN Jun 12 2,855,389 1,228,430 3,356,100 0.0439 0.0446 0.0480 TN Jun 13 2,866,373 1,247,300 3,439,845 0.0441 0.0452 0.0492 TN Jun 14 2,878,041 1,264,423 3,509,291 0.0443 0.0459 0.0501 TN Jun 15 2,881,635 1,267,266 3,520,666 0.0443 0.0460 0.0503 TN Jun 16 2,882,816 1,264,887 3,500,832 0.0444 0.0459 0.0500 TN Jun 17 2,869,204 1,246,990 3,480,150 0.0441 0.0452 0.0497 TN Jun 18 2,854,483 1,211,944 3,339,200 0.0439 0.0440 0.0477 TN Jun 19 2,864,838 1,207,185 3,253,969 0.0441 0.0438 0.0465 TN Jun 20 2,849,824 1,180,223 3,078,778 0.0438 0.0428 0.0440 TN Jun 21 2,789,397 1,137,460 2,774,259 0.0429 0.0413 0.0396 TN Jun 22 2,703,450 1,112,048 2,618,597 0.0416 0.0403 0.0374 TN Jun 23 2,625,264 1,088,507 2,533,520 0.0404 0.0395 0.0362 TN Jul 0 2,723,708 1,110,322 2,630,084 0.0394 0.0390 0.0348 TN Jul 1 2,624,427 1,086,640 2,553,484 0.0380 0.0382 0.0338 TN Jul 2 2,565,432 1,071,490 2,508,515 0.0371 0.0376 0.0332 TN Jul 3 2,558,337 1,065,857 2,500,314 0.0370 0.0374 0.0331 TN Jul 4 2,590,626 1,074,783 2,530,485 0.0375 0.0377 0.0335 TN Jul 5 2,613,348 1,095,830 2,605,724 0.0378 0.0385 0.0345 TN Jul 6 2,663,132 1,112,119 2,717,291 0.0385 0.0391 0.0359 TN Jul 7 2,792,800 1,160,549 2,861,812 0.0404 0.0408 0.0378 TN Jul 8 2,901,848 1,192,854 2,992,444 0.0420 0.0419 0.0396 TN Jul 9 2,986,710 1,215,248 3,154,026 0.0432 0.0427 0.0417 TN Jul 10 3,019,673 1,238,587 3,388,925 0.0437 0.0435 0.0448 TN Jul 11 3,030,857 1,258,066 3,546,524 0.0439 0.0442 0.0469 TN Jul 12 3,033,672 1,269,558 3,660,236 0.0439 0.0446 0.0484

H-41Atmospheric Sciences Group 

### Appendix H Average 2000-2004 State Level Monthly-Diurnal Profiles

CEM-Based Distribution Alpine Geophysics

SO2 Mass NOx Mass Heat Input State Month Hour [lbs] [lbs] [MMBtu] SO2 Ratio NOx Ratio Heat Input Average Values [2000-2004] Calculated Ratios

TN Jul 13 3,035,795 1,283,130 3,724,626 0.0439 0.0451 0.0492 TN Jul 14 3,049,375 1,271,091 3,739,835 0.0441 0.0446 0.0495 TN Jul 15 3,054,282 1,283,295 3,762,381 0.0442 0.0451 0.0497 TN Jul 16 3,051,969 1,267,330 3,729,801 0.0442 0.0445 0.0493 TN Jul 17 3,047,008 1,253,508 3,688,802 0.0441 0.0440 0.0488 TN Jul 18 3,032,675 1,244,605 3,616,111 0.0439 0.0437 0.0478 TN Jul 19 3,038,425 1,223,429 3,570,939 0.0440 0.0430 0.0472 TN Jul 20 3,019,713 1,214,702 3,458,750 0.0437 0.0427 0.0457 TN Jul 21 2,966,264 1,187,856 3,145,381 0.0429 0.0417 0.0416 TN Jul 22 2,887,611 1,156,287 2,829,045 0.0418 0.0406 0.0374 TN Jul 23 2,827,578 1,135,334 2,712,072 0.0409 0.0399 0.0359 TN Aug 0 2,704,871 1,102,508 2,637,888 0.0397 0.0395 0.0349 TN Aug 1 2,610,282 1,079,338 2,571,826 0.0383 0.0386 0.0341 TN Aug 2 2,545,750 1,061,310 2,520,123 0.0373 0.0380 0.0334 TN Aug 3 2,546,295 1,059,227 2,516,465 0.0373 0.0379 0.0333 TN Aug 4 2,611,452 1,075,701 2,573,329 0.0383 0.0385 0.0341 TN Aug 5 2,657,809 1,100,407 2,684,810 0.0390 0.0394 0.0356 TN Aug 6 2,663,412 1,101,584 2,720,984 0.0391 0.0394 0.0360 TN Aug 7 2,762,946 1,132,309 2,801,321 0.0405 0.0405 0.0371 TN Aug 8 2,842,089 1,151,929 2,910,709 0.0417 0.0412 0.0386 TN Aug 9 2,914,392 1,178,167 3,104,027 0.0427 0.0422 0.0411 TN Aug 10 2,951,929 1,198,192 3,378,553 0.0433 0.0429 0.0448 TN Aug 11 2,969,254 1,213,378 3,546,918 0.0435 0.0434 0.0470 TN Aug 12 2,993,434 1,227,359 3,643,276 0.0439 0.0439 0.0483 TN Aug 13 3,001,505 1,250,890 3,720,523 0.0440 0.0448 0.0493 TN Aug 14 3,007,352 1,268,602 3,812,830 0.0441 0.0454 0.0505 TN Aug 15 3,013,955 1,261,537 3,812,731 0.0442 0.0452 0.0505 TN Aug 16 3,003,960 1,233,673 3,706,531 0.0440 0.0442 0.0491 TN Aug 17 2,989,885 1,216,095 3,618,215 0.0438 0.0435 0.0479 TN Aug 18 2,985,473 1,210,229 3,621,920 0.0438 0.0433 0.0480 TN Aug 19 2,996,742 1,206,770 3,563,558 0.0439 0.0432 0.0472 TN Aug 20 2,948,212 1,188,294 3,391,834 0.0432 0.0425 0.0449 TN Aug 21 2,884,880 1,164,179 3,110,539 0.0423 0.0417 0.0412 TN Aug 22 2,823,438 1,137,206 2,829,114 0.0414 0.0407 0.0375 TN Aug 23 2,774,451 1,119,134 2,684,939 0.0407 0.0401 0.0356 TN Sep 0 2,488,084 1,035,716 2,445,041 0.0389 0.0395 0.0367 TN Sep 1 2,423,357 1,016,450 2,397,907 0.0378 0.0388 0.0360 TN Sep 2 2,384,567 1,003,630 2,368,491 0.0372 0.0383 0.0355 TN Sep 3 2,403,840 1,005,862 2,378,308 0.0375 0.0384 0.0357 TN Sep 4 2,488,355 1,035,930 2,444,261 0.0389 0.0395 0.0367 TN Sep 5 2,577,024 1,062,376 2,505,657 0.0402 0.0405 0.0376 TN Sep 6 2,557,078 1,057,122 2,504,384 0.0399 0.0403 0.0376 TN Sep 7 2,614,651 1,073,584 2,575,635 0.0408 0.0409 0.0386 TN Sep 8 2,685,130 1,087,661 2,645,223 0.0419 0.0415 0.0397 TN Sep 9 2,732,166 1,103,190 2,737,383 0.0427 0.0421 0.0411 TN Sep 10 2,762,113 1,117,353 2,842,572 0.0431 0.0426 0.0426 TN Sep 11 2,782,370 1,127,506 2,980,048 0.0435 0.0430 0.0447 TN Sep 12 2,800,262 1,134,332 3,067,131 0.0437 0.0433 0.0460 TN Sep 13 2,814,052 1,148,125 3,174,079 0.0440 0.0438 0.0476 TN Sep 14 2,821,888 1,145,774 3,240,123 0.0441 0.0437 0.0486 TN Sep 15 2,821,754 1,158,303 3,275,168 0.0441 0.0442 0.0491 TN Sep 16 2,813,655 1,150,036 3,261,138 0.0439 0.0439 0.0489 TN Sep 17 2,802,747 1,142,894 3,184,333 0.0438 0.0436 0.0478

H-42Atmospheric Sciences Group 

### Appendix H Average 2000-2004 State Level Monthly-Diurnal Profiles

CEM-Based Distribution Alpine Geophysics

SO2 Mass NOx Mass Heat Input State Month Hour [lbs] [lbs] [MMBtu] SO2 Ratio NOx Ratio Heat Input Average Values [2000-2004] Calculated Ratios

TN Sep 18 2,834,387 1,156,020 3,163,428 0.0443 0.0441 0.0475 TN Sep 19 2,822,964 1,138,348 3,033,651 0.0441 0.0434 0.0455 TN Sep 20 2,763,242 1,114,604 2,792,921 0.0432 0.0425 0.0419 TN Sep 21 2,677,231 1,087,394 2,604,748 0.0418 0.0415 0.0391 TN Sep 22 2,606,449 1,068,943 2,541,266 0.0407 0.0408 0.0381 TN Sep 23 2,550,642 1,052,066 2,494,745 0.0398 0.0401 0.0374 TN Oct 0 2,648,670 1,199,661 2,430,822 0.0394 0.0396 0.0382 TN Oct 1 2,606,559 1,184,587 2,386,665 0.0388 0.0391 0.0375 TN Oct 2 2,587,766 1,179,838 2,376,278 0.0385 0.0389 0.0374 TN Oct 3 2,629,687 1,190,681 2,401,778 0.0391 0.0393 0.0378 TN Oct 4 2,733,080 1,226,766 2,494,082 0.0407 0.0405 0.0392 TN Oct 5 2,816,578 1,262,228 2,583,919 0.0419 0.0417 0.0406 TN Oct 6 2,776,422 1,257,264 2,582,838 0.0413 0.0415 0.0406 TN Oct 7 2,808,840 1,268,614 2,596,248 0.0418 0.0419 0.0408 TN Oct 8 2,849,356 1,276,976 2,636,870 0.0424 0.0421 0.0415 TN Oct 9 2,864,222 1,282,922 2,695,881 0.0426 0.0423 0.0424 TN Oct 10 2,870,140 1,285,628 2,715,317 0.0427 0.0424 0.0427 TN Oct 11 2,863,848 1,285,491 2,766,329 0.0426 0.0424 0.0435 TN Oct 12 2,863,927 1,289,405 2,798,583 0.0426 0.0426 0.0440 TN Oct 13 2,860,159 1,288,937 2,845,583 0.0426 0.0425 0.0447 TN Oct 14 2,865,749 1,292,539 2,859,716 0.0426 0.0427 0.0450 TN Oct 15 2,872,462 1,293,765 2,868,969 0.0427 0.0427 0.0451 TN Oct 16 2,874,892 1,299,907 2,845,788 0.0428 0.0429 0.0447 TN Oct 17 2,903,047 1,304,194 2,829,086 0.0432 0.0430 0.0445 TN Oct 18 2,910,031 1,305,793 2,869,447 0.0433 0.0431 0.0451 TN Oct 19 2,881,997 1,298,066 2,793,512 0.0429 0.0428 0.0439 TN Oct 20 2,855,000 1,287,168 2,657,664 0.0425 0.0425 0.0418 TN Oct 21 2,808,338 1,270,931 2,575,916 0.0418 0.0419 0.0405 TN Oct 22 2,749,485 1,243,810 2,508,375 0.0409 0.0410 0.0394 TN Oct 23 2,707,486 1,226,915 2,480,437 0.0403 0.0405 0.0390 TN Nov 0 2,604,100 1,223,715 2,414,220 0.0405 0.0408 0.0396 TN Nov 1 2,578,310 1,211,595 2,389,128 0.0401 0.0404 0.0392 TN Nov 2 2,557,600 1,200,125 2,361,621 0.0397 0.0400 0.0388 TN Nov 3 2,568,661 1,204,600 2,366,562 0.0399 0.0401 0.0388 TN Nov 4 2,623,612 1,217,848 2,407,952 0.0408 0.0406 0.0395 TN Nov 5 2,687,151 1,248,059 2,523,039 0.0418 0.0416 0.0414 TN Nov 6 2,704,525 1,266,926 2,645,725 0.0420 0.0422 0.0434 TN Nov 7 2,670,826 1,255,243 2,629,014 0.0415 0.0418 0.0431 TN Nov 8 2,713,597 1,266,947 2,610,660 0.0422 0.0422 0.0428 TN Nov 9 2,720,609 1,262,270 2,566,911 0.0423 0.0420 0.0421 TN Nov 10 2,715,670 1,256,873 2,548,418 0.0422 0.0419 0.0418 TN Nov 11 2,712,072 1,260,680 2,561,064 0.0421 0.0420 0.0420 TN Nov 12 2,702,597 1,253,317 2,537,363 0.0420 0.0417 0.0416 TN Nov 13 2,695,535 1,252,529 2,535,453 0.0419 0.0417 0.0416 TN Nov 14 2,680,817 1,247,847 2,507,614 0.0417 0.0416 0.0412 TN Nov 15 2,687,063 1,252,224 2,534,862 0.0418 0.0417 0.0416 TN Nov 16 2,734,418 1,270,390 2,592,730 0.0425 0.0423 0.0426 TN Nov 17 2,779,092 1,292,706 2,717,599 0.0432 0.0431 0.0446 TN Nov 18 2,754,809 1,286,552 2,720,184 0.0428 0.0428 0.0446 TN Nov 19 2,737,104 1,278,157 2,665,501 0.0425 0.0426 0.0437 TN Nov 20 2,731,155 1,272,948 2,621,086 0.0424 0.0424 0.0430 TN Nov 21 2,709,698 1,262,720 2,554,839 0.0421 0.0421 0.0419 TN Nov 22 2,657,072 1,245,841 2,479,549 0.0413 0.0415 0.0407

H-43Atmospheric Sciences Group 

### Appendix H Average 2000-2004 State Level Monthly-Diurnal Profiles

CEM-Based Distribution Alpine Geophysics

SO2 Mass NOx Mass Heat Input State Month Hour [lbs] [lbs] [MMBtu] SO2 Ratio NOx Ratio Heat Input Average Values [2000-2004] Calculated Ratios

TN Nov 23 2,625,041 1,235,042 2,439,622 0.0408 0.0411 0.0400 TN Dec 0 2,663,981 1,289,065 2,507,568 0.0408 0.0408 0.0394 TN Dec 1 2,645,626 1,280,508 2,484,469 0.0405 0.0405 0.0390 TN Dec 2 2,634,110 1,286,252 2,484,816 0.0403 0.0407 0.0390 TN Dec 3 2,645,923 1,281,573 2,494,571 0.0405 0.0405 0.0392 TN Dec 4 2,672,147 1,295,077 2,508,733 0.0409 0.0410 0.0394 TN Dec 5 2,714,654 1,312,960 2,590,503 0.0416 0.0415 0.0407 TN Dec 6 2,739,343 1,333,082 2,753,101 0.0419 0.0422 0.0432 TN Dec 7 2,728,200 1,329,177 2,792,244 0.0418 0.0420 0.0438 TN Dec 8 2,762,203 1,339,330 2,740,797 0.0423 0.0424 0.0430 TN Dec 9 2,765,252 1,332,508 2,673,899 0.0423 0.0422 0.0420 TN Dec 10 2,747,708 1,326,693 2,660,846 0.0421 0.0420 0.0418 TN Dec 11 2,722,929 1,315,400 2,630,674 0.0417 0.0416 0.0413 TN Dec 12 2,706,948 1,303,174 2,606,085 0.0415 0.0412 0.0409 TN Dec 13 2,691,091 1,296,111 2,605,810 0.0412 0.0410 0.0409 TN Dec 14 2,676,333 1,296,782 2,611,653 0.0410 0.0410 0.0410 TN Dec 15 2,692,667 1,297,404 2,630,815 0.0412 0.0410 0.0413 TN Dec 16 2,753,111 1,328,902 2,705,495 0.0422 0.0420 0.0425 TN Dec 17 2,799,414 1,356,867 2,861,533 0.0429 0.0429 0.0449 TN Dec 18 2,797,651 1,360,399 2,894,345 0.0428 0.0430 0.0454 TN Dec 19 2,789,920 1,357,761 2,857,256 0.0427 0.0429 0.0449 TN Dec 20 2,781,081 1,346,472 2,804,239 0.0426 0.0426 0.0440 TN Dec 21 2,761,333 1,329,175 2,664,052 0.0423 0.0420 0.0418 TN Dec 22 2,724,350 1,315,984 2,583,267 0.0417 0.0416 0.0406 TN Dec 23 2,688,453 1,302,560 2,544,592 0.0412 0.0412 0.0400 VA Jan 0 1,870,379 709,902 2,270,410 0.0383 0.0367 0.0371 VA Jan 1 1,831,974 691,688 2,231,241 0.0375 0.0357 0.0365 VA Jan 2 1,827,302 691,721 2,231,915 0.0374 0.0357 0.0365 VA Jan 3 1,837,996 703,311 2,256,183 0.0376 0.0363 0.0369 VA Jan 4 1,866,693 724,798 2,302,253 0.0382 0.0374 0.0376 VA Jan 5 1,945,705 775,203 2,466,811 0.0399 0.0401 0.0403 VA Jan 6 2,062,853 836,803 2,725,271 0.0423 0.0432 0.0445 VA Jan 7 2,140,346 880,948 2,856,575 0.0438 0.0455 0.0467 VA Jan 8 2,159,894 888,955 2,855,767 0.0442 0.0459 0.0467 VA Jan 9 2,163,920 881,331 2,813,527 0.0443 0.0455 0.0460 VA Jan 10 2,153,422 866,893 2,735,486 0.0441 0.0448 0.0447 VA Jan 11 2,119,462 838,567 2,617,860 0.0434 0.0433 0.0428 VA Jan 12 2,078,796 813,172 2,521,855 0.0426 0.0420 0.0412 VA Jan 13 2,047,908 799,858 2,482,400 0.0419 0.0413 0.0406 VA Jan 14 1,997,935 786,336 2,448,434 0.0409 0.0406 0.0400 VA Jan 15 1,977,299 774,786 2,418,877 0.0405 0.0400 0.0395 VA Jan 16 2,013,541 798,569 2,495,827 0.0412 0.0413 0.0408 VA Jan 17 2,124,878 851,772 2,677,806 0.0435 0.0440 0.0438 VA Jan 18 2,164,716 880,522 2,774,355 0.0443 0.0455 0.0453 VA Jan 19 2,163,230 878,862 2,749,837 0.0443 0.0454 0.0449 VA Jan 20 2,146,022 867,355 2,731,130 0.0440 0.0448 0.0446 VA Jan 21 2,115,187 847,165 2,651,884 0.0433 0.0438 0.0433 VA Jan 22 2,042,874 803,242 2,491,078 0.0418 0.0415 0.0407 VA Jan 23 1,967,584 762,909 2,394,744 0.0403 0.0394 0.0391 VA Feb 0 1,599,388 582,578 1,818,400 0.0377 0.0361 0.0363 VA Feb 1 1,561,874 568,444 1,799,278 0.0368 0.0353 0.0359 VA Feb 2 1,541,608 563,050 1,790,993 0.0363 0.0349 0.0358 VA Feb 3 1,557,819 571,057 1,818,631 0.0367 0.0354 0.0363

H-44Atmospheric Sciences Group 

### Appendix H Average 2000-2004 State Level Monthly-Diurnal Profiles

CEM-Based Distribution Alpine Geophysics

SO2 Mass NOx Mass Heat Input State Month Hour [lbs] [lbs] [MMBtu] SO2 Ratio NOx Ratio Heat Input Average Values [2000-2004] Calculated Ratios

VA Feb 4 1,592,189 595,065 1,867,807 0.0375 0.0369 0.0373 VA Feb 5 1,683,408 645,839 1,998,704 0.0396 0.0401 0.0399 VA Feb 6 1,821,048 705,616 2,234,999 0.0429 0.0438 0.0446 VA Feb 7 1,905,874 747,449 2,377,369 0.0449 0.0464 0.0475 VA Feb 8 1,917,379 753,740 2,394,464 0.0452 0.0468 0.0478 VA Feb 9 1,910,638 746,578 2,316,944 0.0450 0.0463 0.0463 VA Feb 10 1,899,147 732,901 2,244,827 0.0447 0.0455 0.0448 VA Feb 11 1,872,042 718,408 2,198,206 0.0441 0.0446 0.0439 VA Feb 12 1,834,364 698,984 2,134,129 0.0432 0.0434 0.0426 VA Feb 13 1,793,426 677,313 2,084,720 0.0422 0.0420 0.0416 VA Feb 14 1,738,207 654,142 2,013,181 0.0409 0.0406 0.0402 VA Feb 15 1,711,206 641,374 1,995,756 0.0403 0.0398 0.0399 VA Feb 16 1,725,413 647,856 2,006,861 0.0406 0.0402 0.0401 VA Feb 17 1,791,324 677,478 2,110,886 0.0422 0.0420 0.0422 VA Feb 18 1,882,725 726,377 2,265,468 0.0443 0.0451 0.0453 VA Feb 19 1,895,405 735,420 2,280,882 0.0446 0.0456 0.0456 VA Feb 20 1,886,456 725,703 2,235,068 0.0444 0.0450 0.0446 VA Feb 21 1,864,672 711,588 2,160,640 0.0439 0.0441 0.0432 VA Feb 22 1,790,496 672,276 2,023,752 0.0422 0.0417 0.0404 VA Feb 23 1,683,098 621,449 1,887,921 0.0396 0.0385 0.0377 VA Mar 0 1,758,366 650,813 1,958,208 0.0379 0.0370 0.0373 VA Mar 1 1,699,884 625,566 1,912,678 0.0366 0.0355 0.0365 VA Mar 2 1,668,736 612,417 1,871,624 0.0359 0.0348 0.0357 VA Mar 3 1,666,394 615,889 1,869,659 0.0359 0.0350 0.0356 VA Mar 4 1,695,337 631,901 1,911,423 0.0365 0.0359 0.0364 VA Mar 5 1,806,545 688,144 2,080,880 0.0389 0.0391 0.0397 VA Mar 6 1,955,755 748,155 2,284,033 0.0421 0.0425 0.0435 VA Mar 7 2,030,859 782,349 2,391,046 0.0437 0.0444 0.0456 VA Mar 8 2,055,789 790,511 2,395,390 0.0443 0.0449 0.0457 VA Mar 9 2,060,765 790,080 2,362,747 0.0444 0.0449 0.0450 VA Mar 10 2,043,878 782,768 2,314,866 0.0440 0.0445 0.0441 VA Mar 11 2,049,188 786,663 2,318,184 0.0441 0.0447 0.0442 VA Mar 12 2,024,587 774,772 2,279,104 0.0436 0.0440 0.0434 VA Mar 13 1,986,131 754,057 2,214,779 0.0428 0.0428 0.0422 VA Mar 14 1,940,082 733,412 2,140,863 0.0418 0.0416 0.0408 VA Mar 15 1,925,488 723,075 2,112,312 0.0415 0.0411 0.0403 VA Mar 16 1,938,153 726,924 2,136,893 0.0417 0.0413 0.0407 VA Mar 17 1,976,195 745,490 2,206,656 0.0425 0.0423 0.0421 VA Mar 18 2,056,356 783,585 2,355,568 0.0443 0.0445 0.0449 VA Mar 19 2,120,327 817,470 2,443,217 0.0457 0.0464 0.0466 VA Mar 20 2,097,262 808,478 2,384,264 0.0452 0.0459 0.0455 VA Mar 21 2,051,980 788,969 2,291,897 0.0442 0.0448 0.0437 VA Mar 22 1,972,283 750,617 2,161,156 0.0425 0.0426 0.0412 VA Mar 23 1,865,522 697,871 2,059,027 0.0402 0.0396 0.0393 VA Apr 0 1,638,889 577,304 1,834,424 0.0361 0.0340 0.0330 VA Apr 1 1,594,698 559,341 1,802,263 0.0351 0.0329 0.0324 VA Apr 2 1,562,427 555,289 1,788,274 0.0344 0.0327 0.0321 VA Apr 3 1,576,066 563,216 1,802,304 0.0347 0.0332 0.0324 VA Apr 4 1,657,137 600,545 1,934,289 0.0365 0.0354 0.0348 VA Apr 5 1,826,177 677,142 2,168,369 0.0402 0.0399 0.0390 VA Apr 6 1,933,743 726,479 2,356,745 0.0426 0.0428 0.0424 VA Apr 7 1,993,353 748,843 2,477,510 0.0439 0.0441 0.0445 VA Apr 8 2,025,742 763,741 2,517,734 0.0446 0.0450 0.0453

H-45Atmospheric Sciences Group 

### Appendix H Average 2000-2004 State Level Monthly-Diurnal Profiles

CEM-Based Distribution Alpine Geophysics

SO2 Mass NOx Mass Heat Input State Month Hour [lbs] [lbs] [MMBtu] SO2 Ratio NOx Ratio Heat Input Average Values [2000-2004] Calculated Ratios

VA Apr 9 2,041,423 775,974 2,526,864 0.0449 0.0457 0.0454 VA Apr 10 2,038,005 775,956 2,495,178 0.0449 0.0457 0.0448 VA Apr 11 2,035,891 776,647 2,531,868 0.0448 0.0457 0.0455 VA Apr 12 2,028,858 776,330 2,563,478 0.0447 0.0457 0.0461 VA Apr 13 2,014,909 769,460 2,586,347 0.0443 0.0453 0.0465 VA Apr 14 1,990,455 758,601 2,572,695 0.0438 0.0447 0.0462 VA Apr 15 1,979,220 753,188 2,550,001 0.0436 0.0444 0.0458 VA Apr 16 1,973,384 753,216 2,559,697 0.0434 0.0444 0.0460 VA Apr 17 1,969,120 749,495 2,530,581 0.0433 0.0441 0.0455 VA Apr 18 1,965,055 747,742 2,526,264 0.0433 0.0440 0.0454 VA Apr 19 2,038,650 782,884 2,629,371 0.0449 0.0461 0.0473 VA Apr 20 2,031,218 775,341 2,571,418 0.0447 0.0457 0.0462 VA Apr 21 1,961,332 736,084 2,327,375 0.0432 0.0434 0.0418 VA Apr 22 1,834,270 663,387 2,075,886 0.0404 0.0391 0.0373 VA Apr 23 1,724,616 612,053 1,910,047 0.0380 0.0360 0.0343 VA May 0 1,545,919 654,334 2,088,904 0.0347 0.0323 0.0297 VA May 1 1,461,493 607,067 1,978,313 0.0328 0.0299 0.0282 VA May 2 1,405,092 585,011 1,925,685 0.0316 0.0289 0.0274 VA May 3 1,408,183 590,009 1,939,362 0.0316 0.0291 0.0276 VA May 4 1,502,013 633,614 2,066,155 0.0337 0.0312 0.0294 VA May 5 1,681,946 723,721 2,309,172 0.0378 0.0357 0.0329 VA May 6 1,818,634 788,660 2,548,153 0.0409 0.0389 0.0363 VA May 7 1,898,757 830,139 2,738,723 0.0427 0.0409 0.0390 VA May 8 1,965,350 861,379 2,942,454 0.0442 0.0425 0.0419 VA May 9 2,017,153 891,212 3,177,740 0.0453 0.0440 0.0452 VA May 10 2,027,359 899,446 3,310,099 0.0455 0.0444 0.0471 VA May 11 2,047,161 908,927 3,397,209 0.0460 0.0448 0.0483 VA May 12 2,056,265 918,265 3,452,711 0.0462 0.0453 0.0491 VA May 13 2,051,908 930,715 3,519,202 0.0461 0.0459 0.0501 VA May 14 2,045,504 980,043 3,570,203 0.0460 0.0483 0.0508 VA May 15 2,055,001 1,017,045 3,652,560 0.0462 0.0502 0.0520 VA May 16 2,052,028 1,032,844 3,671,994 0.0461 0.0509 0.0523 VA May 17 2,035,819 1,028,615 3,633,407 0.0457 0.0507 0.0517 VA May 18 2,003,778 989,684 3,506,801 0.0450 0.0488 0.0499 VA May 19 2,024,818 983,499 3,488,501 0.0455 0.0485 0.0496 VA May 20 2,012,754 977,582 3,362,578 0.0452 0.0482 0.0478 VA May 21 1,919,739 921,385 3,039,895 0.0431 0.0454 0.0433 VA May 22 1,803,204 807,713 2,640,306 0.0405 0.0398 0.0376 VA May 23 1,670,172 716,308 2,313,371 0.0375 0.0353 0.0329 VA Jun 0 1,535,718 564,493 1,955,809 0.0346 0.0303 0.0300 VA Jun 1 1,451,250 528,202 1,833,151 0.0327 0.0283 0.0281 VA Jun 2 1,405,228 508,902 1,781,072 0.0317 0.0273 0.0273 VA Jun 3 1,389,390 499,680 1,755,892 0.0313 0.0268 0.0270 VA Jun 4 1,425,828 516,426 1,809,811 0.0322 0.0277 0.0278 VA Jun 5 1,533,300 561,962 1,921,105 0.0346 0.0301 0.0295 VA Jun 6 1,652,876 625,775 2,097,904 0.0373 0.0336 0.0322 VA Jun 7 1,768,922 682,630 2,326,594 0.0399 0.0366 0.0357 VA Jun 8 1,893,400 732,207 2,550,700 0.0427 0.0393 0.0391 VA Jun 9 1,991,270 774,871 2,816,433 0.0449 0.0416 0.0432 VA Jun 10 2,041,222 806,659 3,032,658 0.0460 0.0433 0.0465 VA Jun 11 2,072,743 838,435 3,180,998 0.0467 0.0450 0.0488 VA Jun 12 2,085,477 877,111 3,323,443 0.0470 0.0470 0.0510 VA Jun 13 2,098,860 899,423 3,411,762 0.0473 0.0482 0.0524

H-46Atmospheric Sciences Group 

### Appendix H Average 2000-2004 State Level Monthly-Diurnal Profiles

CEM-Based Distribution Alpine Geophysics

SO2 Mass NOx Mass Heat Input State Month Hour [lbs] [lbs] [MMBtu] SO2 Ratio NOx Ratio Heat Input Average Values [2000-2004] Calculated Ratios

VA Jun 14 2,102,088 917,146 3,436,868 0.0474 0.0492 0.0528 VA Jun 15 2,119,470 1,003,475 3,530,180 0.0478 0.0538 0.0542 VA Jun 16 2,108,789 1,032,366 3,559,636 0.0476 0.0554 0.0546 VA Jun 17 2,089,661 1,011,585 3,493,026 0.0471 0.0543 0.0536 VA Jun 18 2,047,308 995,992 3,388,159 0.0462 0.0534 0.0520 VA Jun 19 2,029,003 984,707 3,283,292 0.0458 0.0528 0.0504 VA Jun 20 2,028,236 972,622 3,212,192 0.0457 0.0522 0.0493 VA Jun 21 1,951,798 896,752 2,825,095 0.0440 0.0481 0.0434 VA Jun 22 1,835,164 764,662 2,434,870 0.0414 0.0410 0.0374 VA Jun 23 1,679,820 647,799 2,192,048 0.0379 0.0347 0.0336 VA Jul 0 1,704,862 636,854 2,231,134 0.0362 0.0341 0.0311 VA Jul 1 1,604,772 591,512 2,103,040 0.0341 0.0317 0.0293 VA Jul 2 1,522,774 559,116 2,019,643 0.0323 0.0299 0.0281 VA Jul 3 1,498,593 549,833 1,994,835 0.0318 0.0294 0.0278 VA Jul 4 1,537,955 563,336 2,036,226 0.0326 0.0301 0.0283 VA Jul 5 1,646,697 609,949 2,147,751 0.0349 0.0326 0.0299 VA Jul 6 1,734,217 655,628 2,289,967 0.0368 0.0351 0.0319 VA Jul 7 1,861,090 726,201 2,516,843 0.0395 0.0389 0.0350 VA Jul 8 1,980,867 791,032 2,786,784 0.0420 0.0423 0.0388 VA Jul 9 2,087,828 840,961 3,145,276 0.0443 0.0450 0.0438 VA Jul 10 2,142,626 863,668 3,388,605 0.0455 0.0462 0.0472 VA Jul 11 2,181,701 876,762 3,551,120 0.0463 0.0469 0.0494 VA Jul 12 2,204,128 896,024 3,675,653 0.0468 0.0480 0.0512 VA Jul 13 2,212,650 912,529 3,758,506 0.0470 0.0488 0.0523 VA Jul 14 2,209,449 918,906 3,788,632 0.0469 0.0492 0.0527 VA Jul 15 2,214,598 928,365 3,808,015 0.0470 0.0497 0.0530 VA Jul 16 2,210,019 935,751 3,828,290 0.0469 0.0501 0.0533 VA Jul 17 2,202,293 926,825 3,788,591 0.0467 0.0496 0.0527 VA Jul 18 2,169,071 898,383 3,651,230 0.0460 0.0481 0.0508 VA Jul 19 2,151,777 872,785 3,552,127 0.0457 0.0467 0.0494 VA Jul 20 2,139,263 857,022 3,435,399 0.0454 0.0459 0.0478 VA Jul 21 2,078,706 817,698 3,105,858 0.0441 0.0438 0.0432 VA Jul 22 1,973,834 764,842 2,785,915 0.0419 0.0409 0.0388 VA Jul 23 1,846,230 692,049 2,463,293 0.0392 0.0370 0.0343 VA Aug 0 1,711,775 647,585 2,290,030 0.0364 0.0330 0.0305 VA Aug 1 1,605,465 606,484 2,133,784 0.0341 0.0309 0.0285 VA Aug 2 1,535,053 580,947 2,039,166 0.0326 0.0296 0.0272 VA Aug 3 1,517,699 571,203 2,008,252 0.0322 0.0291 0.0268 VA Aug 4 1,569,706 587,754 2,078,976 0.0333 0.0300 0.0277 VA Aug 5 1,694,608 644,673 2,243,588 0.0360 0.0329 0.0299 VA Aug 6 1,777,196 683,969 2,379,500 0.0378 0.0349 0.0317 VA Aug 7 1,865,924 747,614 2,601,536 0.0396 0.0381 0.0347 VA Aug 8 1,967,164 814,989 2,853,217 0.0418 0.0416 0.0381 VA Aug 9 2,072,030 885,577 3,285,050 0.0440 0.0451 0.0438 VA Aug 10 2,130,434 903,557 3,584,803 0.0453 0.0461 0.0478 VA Aug 11 2,173,665 925,152 3,754,210 0.0462 0.0472 0.0501 VA Aug 12 2,195,527 942,316 3,844,172 0.0466 0.0480 0.0513 VA Aug 13 2,211,728 945,287 3,926,084 0.0470 0.0482 0.0524 VA Aug 14 2,208,769 945,097 3,976,443 0.0469 0.0482 0.0530 VA Aug 15 2,212,499 994,435 4,061,200 0.0470 0.0507 0.0542 VA Aug 16 2,205,808 991,010 4,039,150 0.0469 0.0505 0.0539 VA Aug 17 2,187,955 983,714 3,994,992 0.0465 0.0502 0.0533 VA Aug 18 2,150,114 972,668 3,849,458 0.0457 0.0496 0.0513

H-47Atmospheric Sciences Group 

### Appendix H Average 2000-2004 State Level Monthly-Diurnal Profiles

CEM-Based Distribution Alpine Geophysics

SO2 Mass NOx Mass Heat Input State Month Hour [lbs] [lbs] [MMBtu] SO2 Ratio NOx Ratio Heat Input Average Values [2000-2004] Calculated Ratios

VA Aug 19 2,145,209 955,439 3,813,380 0.0456 0.0487 0.0509 VA Aug 20 2,122,441 918,658 3,591,925 0.0451 0.0468 0.0479 VA Aug 21 2,041,917 869,407 3,263,683 0.0434 0.0443 0.0435 VA Aug 22 1,945,967 798,195 2,879,613 0.0413 0.0407 0.0384 VA Aug 23 1,823,013 698,474 2,490,415 0.0387 0.0356 0.0332 VA Sep 0 1,461,731 556,344 1,955,407 0.0352 0.0335 0.0322 VA Sep 1 1,382,592 530,143 1,885,856 0.0333 0.0319 0.0311 VA Sep 2 1,339,279 515,282 1,842,656 0.0323 0.0311 0.0304 VA Sep 3 1,338,556 513,039 1,837,859 0.0323 0.0309 0.0303 VA Sep 4 1,415,967 539,645 1,911,194 0.0341 0.0325 0.0315 VA Sep 5 1,561,436 600,269 2,079,636 0.0376 0.0362 0.0343 VA Sep 6 1,632,176 637,192 2,183,543 0.0393 0.0384 0.0360 VA Sep 7 1,692,573 665,444 2,294,394 0.0408 0.0401 0.0378 VA Sep 8 1,774,399 707,846 2,444,289 0.0428 0.0427 0.0403 VA Sep 9 1,846,712 739,380 2,617,034 0.0445 0.0446 0.0431 VA Sep 10 1,883,020 762,275 2,784,859 0.0454 0.0459 0.0459 VA Sep 11 1,910,570 772,433 2,901,819 0.0461 0.0465 0.0478 VA Sep 12 1,919,899 782,398 2,973,831 0.0463 0.0471 0.0490 VA Sep 13 1,925,538 795,341 3,030,486 0.0464 0.0479 0.0499 VA Sep 14 1,926,222 810,628 3,088,146 0.0464 0.0488 0.0509 VA Sep 15 1,944,694 804,607 3,113,187 0.0469 0.0485 0.0513 VA Sep 16 1,935,466 800,161 3,110,833 0.0467 0.0482 0.0513 VA Sep 17 1,913,087 786,619 3,046,683 0.0461 0.0474 0.0502 VA Sep 18 1,906,905 778,185 2,993,230 0.0460 0.0469 0.0493 VA Sep 19 1,914,964 783,836 2,968,559 0.0462 0.0472 0.0489 VA Sep 20 1,854,886 752,391 2,770,907 0.0447 0.0453 0.0457 VA Sep 21 1,767,540 703,860 2,493,164 0.0426 0.0424 0.0411 VA Sep 22 1,681,509 665,591 2,285,052 0.0405 0.0401 0.0377 VA Sep 23 1,558,897 592,209 2,078,114 0.0376 0.0357 0.0342 VA Oct 0 1,459,155 527,767 1,557,534 0.0349 0.0326 0.0316 VA Oct 1 1,407,432 507,021 1,503,662 0.0336 0.0313 0.0305 VA Oct 2 1,375,083 494,354 1,474,394 0.0329 0.0305 0.0299 VA Oct 3 1,400,961 503,970 1,502,729 0.0335 0.0311 0.0305 VA Oct 4 1,518,711 561,887 1,643,656 0.0363 0.0347 0.0333 VA Oct 5 1,702,274 656,045 1,885,549 0.0407 0.0405 0.0383 VA Oct 6 1,796,400 707,685 2,041,507 0.0429 0.0437 0.0414 VA Oct 7 1,835,639 720,119 2,139,628 0.0439 0.0445 0.0434 VA Oct 8 1,853,898 733,272 2,198,294 0.0443 0.0453 0.0446 VA Oct 9 1,871,841 740,040 2,225,061 0.0447 0.0457 0.0451 VA Oct 10 1,859,894 730,019 2,237,954 0.0445 0.0451 0.0454 VA Oct 11 1,862,059 734,874 2,313,179 0.0445 0.0454 0.0469 VA Oct 12 1,861,698 735,906 2,341,942 0.0445 0.0454 0.0475 VA Oct 13 1,854,347 735,241 2,340,131 0.0443 0.0454 0.0475 VA Oct 14 1,832,371 729,339 2,329,439 0.0438 0.0450 0.0473 VA Oct 15 1,843,434 734,231 2,371,719 0.0441 0.0453 0.0481 VA Oct 16 1,850,521 734,549 2,378,945 0.0442 0.0454 0.0483 VA Oct 17 1,890,123 747,080 2,393,980 0.0452 0.0461 0.0486 VA Oct 18 1,932,878 772,163 2,452,793 0.0462 0.0477 0.0498 VA Oct 19 1,919,161 759,032 2,363,976 0.0459 0.0469 0.0480 VA Oct 20 1,881,186 736,427 2,180,428 0.0450 0.0455 0.0442 VA Oct 21 1,795,193 690,402 1,976,024 0.0429 0.0426 0.0401 VA Oct 22 1,671,660 624,826 1,779,365 0.0400 0.0386 0.0361 VA Oct 23 1,559,109 579,253 1,655,089 0.0373 0.0358 0.0336

H-48Atmospheric Sciences Group 

### Appendix H Average 2000-2004 State Level Monthly-Diurnal Profiles

CEM-Based Distribution Alpine Geophysics

SO2 Mass NOx Mass Heat Input State Month Hour [lbs] [lbs] [MMBtu] SO2 Ratio NOx Ratio Heat Input Average Values [2000-2004] Calculated Ratios

VA Nov 0 1,637,417 592,858 1,838,004 0.0379 0.0360 0.0351 VA Nov 1 1,552,704 555,410 1,728,485 0.0359 0.0337 0.0330 VA Nov 2 1,518,901 543,104 1,692,818 0.0352 0.0330 0.0323 VA Nov 3 1,514,254 545,644 1,713,103 0.0351 0.0331 0.0327 VA Nov 4 1,550,494 570,307 1,791,663 0.0359 0.0346 0.0342 VA Nov 5 1,672,278 629,969 1,981,937 0.0387 0.0382 0.0378 VA Nov 6 1,798,921 696,879 2,215,326 0.0416 0.0423 0.0423 VA Nov 7 1,872,624 732,474 2,366,203 0.0434 0.0445 0.0451 VA Nov 8 1,887,423 741,235 2,383,026 0.0437 0.0450 0.0455 VA Nov 9 1,908,394 747,384 2,404,329 0.0442 0.0454 0.0459 VA Nov 10 1,897,770 734,029 2,335,473 0.0439 0.0445 0.0446 VA Nov 11 1,885,066 731,676 2,315,386 0.0436 0.0444 0.0442 VA Nov 12 1,861,046 723,081 2,272,625 0.0431 0.0439 0.0434 VA Nov 13 1,838,977 716,864 2,271,855 0.0426 0.0435 0.0433 VA Nov 14 1,805,476 703,084 2,252,952 0.0418 0.0427 0.0430 VA Nov 15 1,805,630 705,871 2,250,979 0.0418 0.0428 0.0429 VA Nov 16 1,853,985 717,772 2,309,856 0.0429 0.0436 0.0441 VA Nov 17 1,961,704 761,798 2,485,751 0.0454 0.0462 0.0474 VA Nov 18 1,975,554 772,106 2,535,740 0.0457 0.0469 0.0484 VA Nov 19 1,967,820 762,064 2,489,163 0.0456 0.0462 0.0475 VA Nov 20 1,937,653 740,890 2,392,853 0.0449 0.0450 0.0456 VA Nov 21 1,901,085 721,691 2,294,533 0.0440 0.0438 0.0438 VA Nov 22 1,831,409 684,860 2,118,594 0.0424 0.0416 0.0404 VA Nov 23 1,757,588 647,451 1,982,226 0.0407 0.0393 0.0378 VA Dec 0 1,871,009 707,198 2,191,515 0.0393 0.0378 0.0366 VA Dec 1 1,797,581 678,009 2,131,867 0.0377 0.0363 0.0356 VA Dec 2 1,764,860 662,189 2,078,089 0.0370 0.0354 0.0347 VA Dec 3 1,765,502 664,438 2,105,390 0.0370 0.0356 0.0352 VA Dec 4 1,798,697 688,912 2,196,313 0.0377 0.0369 0.0367 VA Dec 5 1,892,914 739,064 2,373,134 0.0397 0.0396 0.0396 VA Dec 6 2,001,053 791,819 2,602,807 0.0420 0.0424 0.0435 VA Dec 7 2,078,075 828,793 2,774,223 0.0436 0.0444 0.0463 VA Dec 8 2,109,883 842,461 2,789,344 0.0443 0.0451 0.0466 VA Dec 9 2,109,922 839,269 2,739,040 0.0443 0.0449 0.0457 VA Dec 10 2,085,586 822,797 2,630,637 0.0438 0.0440 0.0439 VA Dec 11 2,037,597 801,933 2,542,300 0.0427 0.0429 0.0425 VA Dec 12 1,980,822 774,133 2,446,193 0.0416 0.0414 0.0409 VA Dec 13 1,936,750 754,310 2,393,210 0.0406 0.0404 0.0400 VA Dec 14 1,897,795 743,729 2,346,263 0.0398 0.0398 0.0392 VA Dec 15 1,890,263 738,259 2,356,067 0.0397 0.0395 0.0393 VA Dec 16 1,969,412 774,824 2,492,375 0.0413 0.0415 0.0416 VA Dec 17 2,125,408 856,294 2,793,917 0.0446 0.0458 0.0467 VA Dec 18 2,157,214 874,751 2,871,318 0.0453 0.0468 0.0480 VA Dec 19 2,151,564 863,628 2,799,458 0.0451 0.0462 0.0468 VA Dec 20 2,130,113 849,899 2,748,439 0.0447 0.0455 0.0459 VA Dec 21 2,108,469 836,597 2,675,403 0.0442 0.0448 0.0447 VA Dec 22 2,044,722 799,528 2,497,562 0.0429 0.0428 0.0417 VA Dec 23 1,963,746 752,627 2,302,076 0.0412 0.0403 0.0384 WV Jan 0 4,249,442 1,894,435 3,529,625 0.0380 0.0364 0.0381 WV Jan 1 4,155,781 1,843,877 3,454,729 0.0371 0.0354 0.0372 WV Jan 2 4,104,091 1,817,862 3,419,085 0.0367 0.0349 0.0369 WV Jan 3 4,088,203 1,810,242 3,403,126 0.0365 0.0348 0.0367 WV Jan 4 4,127,942 1,835,248 3,437,783 0.0369 0.0353 0.0371

H-49Atmospheric Sciences Group 

### Appendix H Average 2000-2004 State Level Monthly-Diurnal Profiles

CEM-Based Distribution Alpine Geophysics

SO2 Mass NOx Mass Heat Input State Month Hour [lbs] [lbs] [MMBtu] SO2 Ratio NOx Ratio Heat Input Average Values [2000-2004] Calculated Ratios

WV Jan 5 4,280,014 1,917,371 3,558,210 0.0383 0.0368 0.0384 WV Jan 6 4,573,064 2,088,359 3,776,220 0.0409 0.0401 0.0407 WV Jan 7 4,813,806 2,259,285 3,960,273 0.0430 0.0434 0.0427 WV Jan 8 4,879,139 2,300,620 4,017,639 0.0436 0.0442 0.0433 WV Jan 9 4,933,020 2,330,795 4,048,192 0.0441 0.0448 0.0436 WV Jan 10 4,943,863 2,336,407 4,064,235 0.0442 0.0449 0.0438 WV Jan 11 4,893,676 2,322,078 4,052,805 0.0437 0.0446 0.0437 WV Jan 12 4,848,694 2,295,186 4,014,446 0.0433 0.0441 0.0433 WV Jan 13 4,801,586 2,265,567 3,971,121 0.0429 0.0435 0.0428 WV Jan 14 4,754,843 2,232,995 3,942,716 0.0425 0.0429 0.0425 WV Jan 15 4,723,854 2,212,249 3,918,167 0.0422 0.0425 0.0422 WV Jan 16 4,760,189 2,238,053 3,969,454 0.0425 0.0430 0.0428 WV Jan 17 4,899,062 2,329,166 4,105,390 0.0438 0.0448 0.0443 WV Jan 18 5,004,069 2,413,424 4,193,319 0.0447 0.0464 0.0452 WV Jan 19 5,001,107 2,398,920 4,186,256 0.0447 0.0461 0.0451 WV Jan 20 4,967,170 2,366,811 4,115,894 0.0444 0.0455 0.0444 WV Jan 21 4,880,408 2,310,906 4,031,032 0.0436 0.0444 0.0435 WV Jan 22 4,714,799 2,190,675 3,892,699 0.0421 0.0421 0.0420 WV Jan 23 4,478,076 2,032,321 3,695,311 0.0400 0.0391 0.0398 WV Feb 0 3,869,369 1,753,162 3,236,329 0.0382 0.0369 0.0382 WV Feb 1 3,770,577 1,700,262 3,170,530 0.0372 0.0358 0.0374 WV Feb 2 3,733,964 1,680,205 3,142,389 0.0368 0.0353 0.0371 WV Feb 3 3,713,913 1,673,979 3,130,291 0.0366 0.0352 0.0369 WV Feb 4 3,764,787 1,703,968 3,176,549 0.0371 0.0358 0.0375 WV Feb 5 3,926,718 1,790,203 3,310,414 0.0387 0.0377 0.0391 WV Feb 6 4,194,362 1,950,867 3,502,900 0.0414 0.0410 0.0413 WV Feb 7 4,387,531 2,086,412 3,672,590 0.0433 0.0439 0.0433 WV Feb 8 4,445,016 2,125,658 3,720,802 0.0439 0.0447 0.0439 WV Feb 9 4,472,381 2,141,326 3,729,108 0.0441 0.0451 0.0440 WV Feb 10 4,479,402 2,143,699 3,737,825 0.0442 0.0451 0.0441 WV Feb 11 4,462,117 2,124,564 3,707,530 0.0440 0.0447 0.0438 WV Feb 12 4,408,304 2,093,781 3,653,998 0.0435 0.0440 0.0431 WV Feb 13 4,371,736 2,070,454 3,638,093 0.0431 0.0436 0.0429 WV Feb 14 4,295,638 2,021,150 3,577,435 0.0424 0.0425 0.0422 WV Feb 15 4,240,145 1,990,890 3,545,135 0.0418 0.0419 0.0418 WV Feb 16 4,251,408 2,003,139 3,553,782 0.0419 0.0421 0.0419 WV Feb 17 4,323,999 2,043,226 3,624,587 0.0427 0.0430 0.0428 WV Feb 18 4,465,413 2,143,792 3,753,621 0.0441 0.0451 0.0443 WV Feb 19 4,515,452 2,173,197 3,769,244 0.0446 0.0457 0.0445 WV Feb 20 4,491,732 2,151,329 3,750,907 0.0443 0.0453 0.0443 WV Feb 21 4,426,423 2,104,985 3,682,807 0.0437 0.0443 0.0435 WV Feb 22 4,276,431 1,998,377 3,554,922 0.0422 0.0420 0.0420 WV Feb 23 4,058,278 1,863,379 3,383,904 0.0400 0.0392 0.0399 WV Mar 0 4,118,452 1,798,426 3,471,235 0.0374 0.0359 0.0376 WV Mar 1 4,003,114 1,739,733 3,384,796 0.0364 0.0347 0.0367 WV Mar 2 3,943,335 1,717,039 3,348,712 0.0358 0.0343 0.0363 WV Mar 3 3,948,106 1,717,969 3,351,715 0.0359 0.0343 0.0363 WV Mar 4 4,013,975 1,753,160 3,409,329 0.0365 0.0350 0.0369 WV Mar 5 4,239,145 1,868,300 3,576,856 0.0385 0.0373 0.0387 WV Mar 6 4,548,297 2,063,518 3,837,582 0.0413 0.0412 0.0416 WV Mar 7 4,743,869 2,185,264 4,009,854 0.0431 0.0436 0.0434 WV Mar 8 4,832,323 2,242,822 4,082,783 0.0439 0.0448 0.0442 WV Mar 9 4,884,415 2,270,433 4,095,487 0.0444 0.0453 0.0444

H-50Atmospheric Sciences Group 

### Appendix H Average 2000-2004 State Level Monthly-Diurnal Profiles

CEM-Based Distribution Alpine Geophysics

SO2 Mass NOx Mass Heat Input State Month Hour [lbs] [lbs] [MMBtu] SO2 Ratio NOx Ratio Heat Input Average Values [2000-2004] Calculated Ratios

WV Mar 10 4,906,289 2,283,364 4,094,196 0.0446 0.0456 0.0443 WV Mar 11 4,893,727 2,272,244 4,069,624 0.0445 0.0454 0.0441 WV Mar 12 4,843,689 2,245,144 4,038,034 0.0440 0.0448 0.0437 WV Mar 13 4,803,944 2,216,099 4,015,612 0.0437 0.0442 0.0435 WV Mar 14 4,737,384 2,173,090 3,969,588 0.0431 0.0434 0.0430 WV Mar 15 4,659,118 2,130,057 3,916,365 0.0423 0.0425 0.0424 WV Mar 16 4,655,959 2,126,639 3,907,090 0.0423 0.0425 0.0423 WV Mar 17 4,708,997 2,160,066 3,939,650 0.0428 0.0431 0.0427 WV Mar 18 4,817,024 2,223,988 4,025,737 0.0438 0.0444 0.0436 WV Mar 19 4,951,627 2,316,098 4,123,755 0.0450 0.0462 0.0447 WV Mar 20 4,926,890 2,300,298 4,107,029 0.0448 0.0459 0.0445 WV Mar 21 4,844,452 2,247,796 4,039,020 0.0440 0.0449 0.0437 WV Mar 22 4,640,082 2,105,813 3,877,380 0.0422 0.0420 0.0420 WV Mar 23 4,357,781 1,924,858 3,646,142 0.0396 0.0384 0.0395 WV Apr 0 3,731,648 1,646,822 3,211,698 0.0358 0.0344 0.0359 WV Apr 1 3,646,046 1,608,033 3,152,817 0.0350 0.0336 0.0352 WV Apr 2 3,629,253 1,601,105 3,144,249 0.0348 0.0334 0.0351 WV Apr 3 3,654,980 1,611,201 3,159,810 0.0350 0.0336 0.0353 WV Apr 4 3,793,856 1,673,928 3,255,696 0.0364 0.0349 0.0364 WV Apr 5 4,113,071 1,836,218 3,507,644 0.0394 0.0383 0.0392 WV Apr 6 4,372,897 2,000,714 3,729,969 0.0419 0.0418 0.0417 WV Apr 7 4,521,742 2,097,030 3,854,921 0.0434 0.0438 0.0431 WV Apr 8 4,604,510 2,152,911 3,950,373 0.0441 0.0449 0.0442 WV Apr 9 4,672,995 2,194,434 4,008,133 0.0448 0.0458 0.0448 WV Apr 10 4,684,136 2,206,171 4,027,220 0.0449 0.0461 0.0450 WV Apr 11 4,663,471 2,191,299 3,994,709 0.0447 0.0457 0.0447 WV Apr 12 4,654,850 2,187,479 3,994,312 0.0446 0.0457 0.0447 WV Apr 13 4,639,780 2,178,588 3,992,917 0.0445 0.0455 0.0446 WV Apr 14 4,596,659 2,147,389 3,947,058 0.0441 0.0448 0.0441 WV Apr 15 4,597,268 2,150,804 3,961,040 0.0441 0.0449 0.0443 WV Apr 16 4,581,958 2,139,654 3,954,941 0.0439 0.0447 0.0442 WV Apr 17 4,563,950 2,122,381 3,923,906 0.0438 0.0443 0.0439 WV Apr 18 4,560,416 2,115,866 3,922,354 0.0437 0.0442 0.0438 WV Apr 19 4,663,756 2,177,061 4,007,298 0.0447 0.0454 0.0448 WV Apr 20 4,691,196 2,193,010 4,023,341 0.0450 0.0458 0.0450 WV Apr 21 4,527,465 2,067,526 3,828,168 0.0434 0.0432 0.0428 WV Apr 22 4,208,315 1,875,409 3,554,492 0.0403 0.0392 0.0397 WV Apr 23 3,923,150 1,727,144 3,346,359 0.0376 0.0361 0.0374 WV May 0 3,703,271 1,459,683 3,366,264 0.0355 0.0351 0.0364 WV May 1 3,608,320 1,418,524 3,298,432 0.0346 0.0341 0.0356 WV May 2 3,543,860 1,399,333 3,256,146 0.0340 0.0336 0.0352 WV May 3 3,577,232 1,411,771 3,284,512 0.0343 0.0339 0.0355 WV May 4 3,749,129 1,477,311 3,403,791 0.0359 0.0355 0.0368 WV May 5 4,030,588 1,589,148 3,617,389 0.0386 0.0382 0.0391 WV May 6 4,267,917 1,687,539 3,788,669 0.0409 0.0405 0.0409 WV May 7 4,464,301 1,782,705 3,935,179 0.0428 0.0428 0.0425 WV May 8 4,586,199 1,836,948 4,007,875 0.0439 0.0441 0.0433 WV May 9 4,675,983 1,879,607 4,119,060 0.0448 0.0452 0.0445 WV May 10 4,719,217 1,907,253 4,134,937 0.0452 0.0458 0.0447 WV May 11 4,724,379 1,908,904 4,143,719 0.0453 0.0459 0.0448 WV May 12 4,727,655 1,915,606 4,168,739 0.0453 0.0460 0.0450 WV May 13 4,720,532 1,908,164 4,151,268 0.0452 0.0458 0.0449 WV May 14 4,702,889 1,902,024 4,148,550 0.0451 0.0457 0.0448

H-51Atmospheric Sciences Group 

### Appendix H Average 2000-2004 State Level Monthly-Diurnal Profiles

CEM-Based Distribution Alpine Geophysics

SO2 Mass NOx Mass Heat Input State Month Hour [lbs] [lbs] [MMBtu] SO2 Ratio NOx Ratio Heat Input Average Values [2000-2004] Calculated Ratios

WV May 15 4,706,341 1,900,025 4,150,358 0.0451 0.0456 0.0448 WV May 16 4,680,703 1,879,212 4,131,555 0.0449 0.0451 0.0446 WV May 17 4,652,827 1,864,064 4,097,898 0.0446 0.0448 0.0443 WV May 18 4,617,372 1,841,005 4,044,140 0.0442 0.0442 0.0437 WV May 19 4,643,719 1,850,934 4,059,618 0.0445 0.0445 0.0439 WV May 20 4,690,038 1,876,110 4,092,223 0.0449 0.0451 0.0442 WV May 21 4,500,464 1,777,130 3,948,367 0.0431 0.0427 0.0427 WV May 22 4,176,506 1,631,243 3,701,583 0.0400 0.0392 0.0400 WV May 23 3,890,418 1,520,452 3,489,207 0.0373 0.0365 0.0377 WV Jun 0 3,526,345 1,276,527 3,194,799 0.0353 0.0346 0.0361 WV Jun 1 3,433,368 1,243,935 3,122,356 0.0344 0.0337 0.0353 WV Jun 2 3,356,399 1,219,119 3,069,736 0.0336 0.0331 0.0347 WV Jun 3 3,345,493 1,209,212 3,049,646 0.0335 0.0328 0.0345 WV Jun 4 3,435,049 1,241,041 3,115,593 0.0344 0.0337 0.0352 WV Jun 5 3,591,579 1,297,902 3,226,070 0.0360 0.0352 0.0365 WV Jun 6 3,815,818 1,381,086 3,397,933 0.0382 0.0375 0.0384 WV Jun 7 4,074,791 1,482,268 3,603,647 0.0408 0.0402 0.0407 WV Jun 8 4,276,798 1,566,502 3,751,856 0.0429 0.0425 0.0424 WV Jun 9 4,446,350 1,646,703 3,884,483 0.0446 0.0447 0.0439 WV Jun 10 4,553,449 1,701,459 3,987,246 0.0456 0.0462 0.0451 WV Jun 11 4,607,093 1,726,340 4,045,598 0.0462 0.0468 0.0457 WV Jun 12 4,631,195 1,748,354 4,097,366 0.0464 0.0474 0.0463 WV Jun 13 4,631,242 1,751,277 4,103,910 0.0464 0.0475 0.0464 WV Jun 14 4,616,662 1,749,726 4,091,018 0.0463 0.0475 0.0462 WV Jun 15 4,622,580 1,754,529 4,112,343 0.0463 0.0476 0.0465 WV Jun 16 4,617,336 1,749,965 4,088,543 0.0463 0.0475 0.0462 WV Jun 17 4,580,967 1,727,426 4,052,582 0.0459 0.0469 0.0458 WV Jun 18 4,532,265 1,692,096 3,989,552 0.0454 0.0459 0.0451 WV Jun 19 4,483,250 1,656,820 3,908,289 0.0449 0.0450 0.0442 WV Jun 20 4,505,031 1,659,174 3,912,114 0.0452 0.0450 0.0442 WV Jun 21 4,343,384 1,585,978 3,784,443 0.0435 0.0430 0.0428 WV Jun 22 4,024,747 1,452,580 3,547,404 0.0403 0.0394 0.0401 WV Jun 23 3,711,406 1,337,610 3,324,257 0.0372 0.0363 0.0376 WV Jul 0 3,743,508 1,383,466 3,456,762 0.0361 0.0354 0.0365 WV Jul 1 3,610,331 1,339,518 3,365,124 0.0348 0.0343 0.0355 WV Jul 2 3,524,932 1,309,072 3,298,397 0.0340 0.0335 0.0348 WV Jul 3 3,494,866 1,294,885 3,273,892 0.0337 0.0332 0.0346 WV Jul 4 3,569,280 1,321,295 3,328,862 0.0344 0.0338 0.0351 WV Jul 5 3,700,928 1,366,872 3,424,223 0.0357 0.0350 0.0362 WV Jul 6 3,893,625 1,439,413 3,557,209 0.0376 0.0369 0.0376 WV Jul 7 4,154,289 1,538,617 3,753,377 0.0401 0.0394 0.0396 WV Jul 8 4,385,314 1,630,970 3,944,418 0.0423 0.0418 0.0416 WV Jul 9 4,567,384 1,713,825 4,111,614 0.0441 0.0439 0.0434 WV Jul 10 4,682,749 1,783,318 4,235,872 0.0452 0.0457 0.0447 WV Jul 11 4,746,345 1,816,426 4,303,714 0.0458 0.0465 0.0454 WV Jul 12 4,775,065 1,833,806 4,349,875 0.0461 0.0470 0.0459 WV Jul 13 4,810,956 1,852,239 4,414,617 0.0464 0.0474 0.0466 WV Jul 14 4,816,485 1,858,710 4,433,846 0.0465 0.0476 0.0468 WV Jul 15 4,816,436 1,855,133 4,425,900 0.0465 0.0475 0.0467 WV Jul 16 4,815,910 1,853,918 4,422,182 0.0465 0.0475 0.0467 WV Jul 17 4,791,958 1,832,647 4,378,522 0.0462 0.0469 0.0462 WV Jul 18 4,730,850 1,798,833 4,300,188 0.0456 0.0461 0.0454 WV Jul 19 4,665,159 1,760,578 4,236,120 0.0450 0.0451 0.0447

H-52Atmospheric Sciences Group 

### Appendix H Average 2000-2004 State Level Monthly-Diurnal Profiles

CEM-Based Distribution Alpine Geophysics

SO2 Mass NOx Mass Heat Input State Month Hour [lbs] [lbs] [MMBtu] SO2 Ratio NOx Ratio Heat Input Average Values [2000-2004] Calculated Ratios

WV Jul 20 4,669,014 1,756,389 4,200,597 0.0450 0.0450 0.0443 WV Jul 21 4,504,520 1,684,422 4,057,296 0.0435 0.0431 0.0428 WV Jul 22 4,235,289 1,567,823 3,829,574 0.0409 0.0402 0.0404 WV Jul 23 3,946,975 1,456,164 3,616,258 0.0381 0.0373 0.0382 WV Aug 0 3,815,866 1,318,988 3,480,132 0.0363 0.0349 0.0360 WV Aug 1 3,704,477 1,280,416 3,400,927 0.0352 0.0339 0.0351 WV Aug 2 3,616,820 1,251,130 3,343,470 0.0344 0.0331 0.0346 WV Aug 3 3,586,321 1,239,763 3,321,327 0.0341 0.0328 0.0343 WV Aug 4 3,666,197 1,268,885 3,381,692 0.0348 0.0336 0.0349 WV Aug 5 3,853,805 1,337,138 3,537,563 0.0366 0.0354 0.0366 WV Aug 6 4,004,264 1,413,501 3,653,440 0.0380 0.0374 0.0378 WV Aug 7 4,215,225 1,492,878 3,822,830 0.0401 0.0395 0.0395 WV Aug 8 4,429,912 1,577,776 4,020,808 0.0421 0.0418 0.0416 WV Aug 9 4,595,394 1,648,263 4,200,879 0.0437 0.0437 0.0434 WV Aug 10 4,702,032 1,710,509 4,329,477 0.0447 0.0453 0.0447 WV Aug 11 4,777,262 1,755,067 4,401,562 0.0454 0.0465 0.0455 WV Aug 12 4,815,118 1,778,830 4,455,038 0.0458 0.0471 0.0460 WV Aug 13 4,830,298 1,786,874 4,485,768 0.0459 0.0473 0.0464 WV Aug 14 4,836,202 1,790,038 4,508,929 0.0460 0.0474 0.0466 WV Aug 15 4,863,624 1,795,929 4,509,896 0.0462 0.0476 0.0466 WV Aug 16 4,867,949 1,798,227 4,501,725 0.0463 0.0476 0.0465 WV Aug 17 4,841,578 1,778,250 4,474,502 0.0460 0.0471 0.0462 WV Aug 18 4,782,787 1,748,185 4,427,765 0.0454 0.0463 0.0458 WV Aug 19 4,782,890 1,734,883 4,400,760 0.0454 0.0460 0.0455 WV Aug 20 4,783,861 1,731,149 4,381,216 0.0455 0.0459 0.0453 WV Aug 21 4,571,284 1,631,975 4,161,064 0.0434 0.0432 0.0430 WV Aug 22 4,297,752 1,502,746 3,925,645 0.0408 0.0398 0.0406 WV Aug 23 4,000,028 1,379,902 3,642,811 0.0380 0.0366 0.0376 WV Sep 0 3,523,763 1,222,164 3,270,388 0.0350 0.0337 0.0359 WV Sep 1 3,438,300 1,194,098 3,216,142 0.0342 0.0330 0.0353 WV Sep 2 3,387,944 1,173,545 3,182,110 0.0337 0.0324 0.0350 WV Sep 3 3,383,266 1,177,349 3,186,215 0.0336 0.0325 0.0350 WV Sep 4 3,520,278 1,224,693 3,285,269 0.0350 0.0338 0.0361 WV Sep 5 3,808,971 1,336,444 3,494,425 0.0379 0.0369 0.0384 WV Sep 6 4,025,182 1,438,461 3,658,869 0.0400 0.0397 0.0402 WV Sep 7 4,174,065 1,508,426 3,767,733 0.0415 0.0416 0.0414 WV Sep 8 4,331,561 1,564,838 3,866,430 0.0431 0.0432 0.0425 WV Sep 9 4,445,198 1,614,392 3,946,971 0.0442 0.0446 0.0434 WV Sep 10 4,523,534 1,647,257 4,011,206 0.0450 0.0455 0.0441 WV Sep 11 4,574,930 1,672,820 4,057,023 0.0455 0.0462 0.0446 WV Sep 12 4,594,450 1,692,603 4,100,649 0.0457 0.0467 0.0451 WV Sep 13 4,595,168 1,701,257 4,131,734 0.0457 0.0470 0.0454 WV Sep 14 4,605,800 1,701,610 4,154,687 0.0458 0.0470 0.0457 WV Sep 15 4,599,618 1,703,620 4,171,726 0.0457 0.0470 0.0458 WV Sep 16 4,596,596 1,707,130 4,178,073 0.0457 0.0471 0.0459 WV Sep 17 4,569,107 1,681,107 4,130,915 0.0454 0.0464 0.0454 WV Sep 18 4,586,528 1,677,310 4,123,245 0.0456 0.0463 0.0453 WV Sep 19 4,642,216 1,704,072 4,140,909 0.0462 0.0470 0.0455 WV Sep 20 4,580,511 1,664,178 4,061,607 0.0456 0.0459 0.0446 WV Sep 21 4,337,546 1,540,779 3,854,213 0.0431 0.0425 0.0424 WV Sep 22 4,003,844 1,393,256 3,611,866 0.0398 0.0385 0.0397 WV Sep 23 3,699,525 1,288,883 3,400,905 0.0368 0.0356 0.0374 WV Oct 0 3,618,974 1,621,144 3,272,296 0.0348 0.0338 0.0360

H-53Atmospheric Sciences Group 

### Appendix H Average 2000-2004 State Level Monthly-Diurnal Profiles

CEM-Based Distribution Alpine Geophysics

SO2 Mass NOx Mass Heat Input State Month Hour [lbs] [lbs] [MMBtu] SO2 Ratio NOx Ratio Heat Input Average Values [2000-2004] Calculated Ratios

WV Oct 1 3,559,758 1,595,812 3,226,071 0.0342 0.0333 0.0355 WV Oct 2 3,534,706 1,586,482 3,207,668 0.0339 0.0331 0.0353 WV Oct 3 3,565,625 1,597,969 3,227,938 0.0342 0.0333 0.0355 WV Oct 4 3,741,408 1,671,527 3,352,988 0.0359 0.0349 0.0369 WV Oct 5 4,095,204 1,838,716 3,610,407 0.0393 0.0384 0.0397 WV Oct 6 4,418,184 2,029,335 3,865,236 0.0424 0.0423 0.0425 WV Oct 7 4,562,323 2,104,804 3,976,631 0.0438 0.0439 0.0437 WV Oct 8 4,652,025 2,152,739 4,019,973 0.0447 0.0449 0.0442 WV Oct 9 4,705,295 2,183,397 4,028,147 0.0452 0.0456 0.0443 WV Oct 10 4,710,830 2,185,421 4,032,132 0.0452 0.0456 0.0443 WV Oct 11 4,704,875 2,186,333 4,036,216 0.0452 0.0456 0.0444 WV Oct 12 4,688,124 2,181,432 4,033,725 0.0450 0.0455 0.0443 WV Oct 13 4,651,476 2,169,748 4,018,589 0.0447 0.0453 0.0442 WV Oct 14 4,610,580 2,140,643 3,987,181 0.0443 0.0447 0.0438 WV Oct 15 4,599,434 2,139,660 3,991,966 0.0442 0.0446 0.0439 WV Oct 16 4,592,520 2,139,428 3,995,499 0.0441 0.0446 0.0439 WV Oct 17 4,625,574 2,153,201 4,012,460 0.0444 0.0449 0.0441 WV Oct 18 4,756,187 2,234,812 4,120,427 0.0457 0.0466 0.0453 WV Oct 19 4,747,451 2,230,628 4,110,519 0.0456 0.0465 0.0452 WV Oct 20 4,665,754 2,174,455 4,022,393 0.0448 0.0454 0.0442 WV Oct 21 4,435,772 2,041,910 3,838,779 0.0426 0.0426 0.0422 WV Oct 22 4,101,607 1,860,468 3,602,312 0.0394 0.0388 0.0396 WV Oct 23 3,790,504 1,708,542 3,388,919 0.0364 0.0356 0.0372 WV Nov 0 3,780,067 1,750,447 3,309,421 0.0371 0.0364 0.0378 WV Nov 1 3,661,608 1,691,403 3,224,450 0.0360 0.0352 0.0369 WV Nov 2 3,613,349 1,660,122 3,180,830 0.0355 0.0345 0.0364 WV Nov 3 3,602,998 1,654,742 3,176,508 0.0354 0.0344 0.0363 WV Nov 4 3,643,413 1,674,743 3,202,564 0.0358 0.0348 0.0366 WV Nov 5 3,822,824 1,761,094 3,327,694 0.0376 0.0366 0.0380 WV Nov 6 4,157,762 1,942,323 3,562,470 0.0408 0.0404 0.0407 WV Nov 7 4,378,537 2,068,776 3,736,076 0.0430 0.0430 0.0427 WV Nov 8 4,471,261 2,126,790 3,816,344 0.0439 0.0442 0.0436 WV Nov 9 4,506,389 2,150,115 3,848,135 0.0443 0.0447 0.0440 WV Nov 10 4,533,363 2,165,649 3,864,271 0.0445 0.0450 0.0442 WV Nov 11 4,500,842 2,147,500 3,833,688 0.0442 0.0447 0.0438 WV Nov 12 4,467,510 2,128,701 3,799,494 0.0439 0.0443 0.0434 WV Nov 13 4,428,889 2,106,013 3,767,883 0.0435 0.0438 0.0431 WV Nov 14 4,378,096 2,079,127 3,749,338 0.0430 0.0432 0.0428 WV Nov 15 4,346,037 2,069,195 3,730,916 0.0427 0.0430 0.0426 WV Nov 16 4,385,192 2,092,295 3,764,646 0.0431 0.0435 0.0430 WV Nov 17 4,533,795 2,174,044 3,881,309 0.0445 0.0452 0.0444 WV Nov 18 4,603,067 2,211,814 3,956,061 0.0452 0.0460 0.0452 WV Nov 19 4,581,686 2,195,725 3,921,569 0.0450 0.0457 0.0448 WV Nov 20 4,563,731 2,185,415 3,875,566 0.0448 0.0454 0.0443 WV Nov 21 4,496,010 2,149,681 3,810,368 0.0442 0.0447 0.0435 WV Nov 22 4,288,692 2,023,264 3,666,694 0.0421 0.0421 0.0419 WV Nov 23 4,044,102 1,882,045 3,495,387 0.0397 0.0391 0.0399 WV Dec 0 3,940,230 1,799,753 3,420,736 0.0376 0.0365 0.0379 WV Dec 1 3,800,336 1,723,432 3,319,181 0.0363 0.0350 0.0368 WV Dec 2 3,751,357 1,705,779 3,289,072 0.0358 0.0346 0.0364 WV Dec 3 3,745,571 1,701,450 3,281,035 0.0358 0.0345 0.0364 WV Dec 4 3,794,848 1,727,318 3,316,106 0.0362 0.0350 0.0367 WV Dec 5 3,949,201 1,809,509 3,437,236 0.0377 0.0367 0.0381

H-54Atmospheric Sciences Group 

### Appendix H Average 2000-2004 State Level Monthly-Diurnal Profiles

CEM-Based Distribution Alpine Geophysics

SO2 Mass NOx Mass Heat Input State Month Hour [lbs] [lbs] [MMBtu] SO2 Ratio NOx Ratio Heat Input Average Values [2000-2004] Calculated Ratios

WV Dec 6 4,233,989 1,981,725 3,662,959 0.0404 0.0402 0.0406 WV Dec 7 4,474,020 2,117,521 3,862,515 0.0427 0.0429 0.0428 WV Dec 8 4,593,061 2,191,965 3,945,255 0.0438 0.0445 0.0437 WV Dec 9 4,651,094 2,225,221 3,991,071 0.0444 0.0451 0.0442 WV Dec 10 4,661,681 2,228,131 3,986,219 0.0445 0.0452 0.0442 WV Dec 11 4,606,381 2,195,141 3,936,405 0.0440 0.0445 0.0436 WV Dec 12 4,553,573 2,153,039 3,879,133 0.0435 0.0437 0.0430 WV Dec 13 4,495,870 2,121,901 3,840,522 0.0429 0.0430 0.0426 WV Dec 14 4,401,121 2,071,610 3,784,798 0.0420 0.0420 0.0419 WV Dec 15 4,354,333 2,044,563 3,760,254 0.0416 0.0415 0.0417 WV Dec 16 4,436,939 2,089,638 3,836,218 0.0424 0.0424 0.0425 WV Dec 17 4,663,174 2,228,940 4,013,471 0.0445 0.0452 0.0445 WV Dec 18 4,772,139 2,307,759 4,122,732 0.0456 0.0468 0.0457 WV Dec 19 4,769,498 2,299,340 4,097,800 0.0455 0.0466 0.0454 WV Dec 20 4,736,443 2,275,618 4,034,921 0.0452 0.0462 0.0447 WV Dec 21 4,680,463 2,238,335 3,976,665 0.0447 0.0454 0.0441 WV Dec 22 4,495,343 2,120,487 3,824,887 0.0429 0.0430 0.0424 WV Dec 23 4,203,589 1,947,792 3,616,058 0.0401 0.0395 0.0401

H-55

# Appendix D.4c White Paper on Mobile Source SMOKE Modeling

# Processing Mobile Emissions in SMOKE: Is it worth simulating everyday onroad mobile emissions to support 8-hr ozone modeling?

Mike Abraczinskas North Carolina Department of Environment and Natural Resources Division of Air Quality 1641 Mail Service Center Raleigh, NC 27699-1641 (919) 715-3743 Michael.Abraczinskas@ncmail.net
Cynthia Loomis Alpine Geophysics, LLC 7341 Poppy Way Arvada, CO 80007

(303) 421-2211 cfl@alpinegeophysics.com
Gregory Stella Alpine Geophysics, LLC

387 Pollard Mine Road Burnsville, NC 28714 (828) 675-9045 gms@alpinegeophysics.com

ABSTRACT

The most computationally limiting step in emissions modeling is typically the generation of onroad mobile sources. Motor vehicle emissions are influe nced by meteorological variability and the processing requirements for daily motor vehicle emissions have been determined to be rate limiting under most modeling schedules. Rather than utilizing averaged me teorological data or pre-calculated motor vehicle emissions, the Visibility Improvement State and Tr ibal Association of the Southeast (VISTAS) / Association for Southeastern Integrated Planni ng (ASIP) modeling team developed an emissions processing approach that models a representative week for each month of the year in order to make the SMOKE processing time more manageable and consis tent with VISTAS/ASIP modeling schedules. This representative week was selected from mid-month, to try to best represent the average temperature ranges for the month, and also adjusted to exclude holidays that would require atypical processing.
The purpose of this paper is to describe processing options for onroad mobile source emissions using the MOBILE module of the SMOKE emissions processor a nd to determine, based on air quality predictions and time and resource expenditure, benefits of si mulating everyday for onroad mobile emissions to support 8-hr ozone modeling. We will present 12km ev aluations of everyday vs. representative week emissions and associated air quality for a number of domains and discuss the benefits and limitations of the various methods relative to ozone, PM and regional haze prediction.

# INTRODUCTION

On December 17, 2004, EPA made fine particle (PM 2.5 

# ) nonattainment determinations for at least one area in seven of the states participating in the Visi bility Improvement State and Tribal Association of the Southeast (VISTAS) regional haze project. They ar e Alabama, Georgia, North Carolina, Kentucky, Tennessee, Virginia, and West Virginia. In additi on, South Carolina has one three-county area that was designated as unclassifiable in the same action. EP A’s Clean Air Interstate Rule (CAIR) modeling indicated that certain nonattainment areas may still be in nonattainment after full implementation of CAIR. These areas include Jefferson County, Alabam a and Clayton and Fulton Counties in Georgia.

The PM 2.5 

# compliance date is April 2010 unless a state de monstrates that more time is necessary in which case up to five additional years may be granted. The nonattainment designations triggered the requirement for development of state implementati on plans (SIPs) that will be due in April 2008. The draft guidance from EPA indicates th at a significant requirement of PM 2.5 

# SIPs will be attainment demonstrations using, at least in pa rt, modeling analyses to define effective emissions control strategies and confirm that attainment can be achieved after implementation of the strategies. 2009 is the modeling year for the PM 2.5 

# attainment demonstration and also is an in terim analysis year for the VISTAS regional haze demonstration.
In April of 2004, EPA determined areas that were not meeting the 8-hour ozone standard. States having one or more 8-hour ozone nonattainment areas in th e Southeast are Alabama, Georgia, Kentucky, North Carolina, South Carolina, Tennessee, Virginia, and We st Virginia. EPA will require attainment of the 8- hour ozone standard in basic nonattainment areas by June 15, 2009 and in moderate nonattainment areas by June 15, 2010. This will require states with basi c 8-hour ozone nonattainment areas to model 2008 as the SIP modeling demonstration year while moderate nonattainment areas will require 2009 as the modeling year. Given that North Carolina and Virginia have two year SIP approval processes, there is an immediate need to complete an analysis of ozone attainment using air quality modeling.
The states participating in the VISTAS project (t he SESARM EPA Region 4 states plus Virginia and West Virginia from Region 3) have concluded that a collaborative process will be the most efficient approach for the collective states to de velop information upon which to base the PM 2.5 

# and 8-hour ozone attainment demonstrations. The local air regul atory agencies for Jefferson County, AL, Jefferson County, KY, Mecklenburg County, NC, Forsyth C ounty, NC, Knox County, TN, and Shelby County, TN have also become signatory parties to this collaborative effort. SESARM will coordinate among participating agencies and oversee the performance of the inventory and modeling tasks in parallel with the VISTAS regional haze project tasks.
The name of this collaborative effort is the Association for Southeastern Integrated Planning (ASIP). SESARM was awarded a grant from EPA on February 8, 2005 to conduct what was originally called the fine particle SIP development support project but is now known as ASIP.

These states need to submit their 8-hour ozone Stat e Implementation Plans (SIPs) to EPA by June 2007; the PM 2.5 

# SIPs are due by April 2008. Some of the states involved in the ASIP ozone/PM modeling have two-year legislative review processes. Thus, the defi nition of the SIP control plans is needed in early 2006. Consequently, the ASIP regional ozone and PM modeling has an aggressive schedule.

# Figure 1. PM 2.5 

# nonattainment counties designed by EPA in December 2004.

Figure 2. 8-hour ozone nonattainment counties in the US designated by EPA in April 2004.

# By far the most computationally limiting step in emissions modeling is typically the generation of onroad mobile sources. Motor vehicle emissions ar e influenced by meteorological variability and the processing requirements for daily motor vehicle emi ssions have been determined to be rate limiting under most modeling schedules. Rather than utilizing averaged meteorological data or pre-calculated motor vehicle emissions, the VISTAS and ASIP m odeling team developed an emissions processing approach that models a representative week for each month of the year in order to make the SMOKE processing time more manageable and consistent with modeling schedule 1 

# . This representative week was selected from mid-month, to tr y to best represent the average temperature ranges for the month, and also adjusted to exclude holidays that would require atypical processing.
Based on the findings in the VISTAS Phase I and II modeling activities, ASIP selected the following models for use in modeling 8-hour ozone and partic ulate matter (PM) of size of 2.5 microns or less (PM 2.5 

# ):

3⁄4 MM5 2,3 

# : The Pennsylvania State University/Na tional Center for Atmospheric Research (PSU/NCAR) Mesoscale Meteorological Model (MM5) is a nonhydrostatic, prognostic meteorological model routinely used for ur ban- and regional-scale photochemical, fine particulate and regional haze regulatory modeling studies.

3⁄4 SMOKE 4 

# : The Sparse Matrix Operator Kernel Em issions (SMOKE) modeling system is an emissions modeling system that generates hourly gridded speciated emission inputs of mobile, nonroad, area, point, fire and biogenic emission sources for photochemical grid models.

3⁄4 CMAQ 5,6 

# : EPA’s Models-3/Community Multiscale Ai r Quality (CMAQ) modeling system is a ‘One-Atmosphere’ photochemical grid model capab le of addressing ozone, particulate matter (PM), visibility and acid deposition at regional scale for periods up to one year.
The purpose of this paper is to describe processing options for onroad mobile source emissions using the MOBILE module of the SMOKE emissions processor a nd to determine, based on air quality predictions and time and resource expenditure, benefits of si mulating everyday for onroad mobile emissions to support 8-hr ozone modeling. We will present 12km ev aluations of everyday vs. representative week emissions and associated air quality for a number of domains and discuss the benefits and limitations of the various methods relative to ozone and regional haze prediction.

MOBILE6 / SMOKE PREPARATION

For the VISTAS/ASIP 2009 annual emissions inventor y modeling, SMOKE was configured to generate point, area, nonroad, highway, and biogenic source emissi ons. In addition, certain subcategories, such as fires and EGUs were maintained in separate source category files in order to allow maximum flexibility in producing alternate strategies. With the excepti on of biogenic and highway mobile source emissions that are generated using the BEIS and MOBILE6 modules in SMOKE, pre-computed annual emissions will be processed using the month, day, and hour speci fic temporal profiles of the SMOKE model. Area, nonroad, and point sources were modeled as a bloc k of Thursday, Friday, Saturday, Sunday, Monday one per month (total of 60 days modeled). Biogenics were modeled for each day of the episode.
For this investigation, the onroad mobile source emissions were produced using two approaches:

1) Modeling every day of the annual episode, us ing the MM5 meteorology files for each model day. When full annual runs were executed, holidays were modeled as Sundays.

# 2) Modeling selected weeks (seven days) of each m onth and using these days as representative of the entire month. This selection criterion allows for th e representation of day-of-the-week variability in the onroad motor vehicles, and models a representation of the meteorological variability in each month. The modeled weeks were selected from mid-month, avoiding inclusion of major holidays.
The parameters for the SMOKE runs are as follows:
Episodes: 2002 Initial Base Year, and 2009 Future year, using 2009 inventory and modeled using the same meteorology and episode days as 2002.
Episode represented by the following weeks per month: January 15-21 February 12-18 March 12-18 April16-22 May 14-20 June 11-17 July 16-22 August 13-19 September 17-23 October 15-21 November 12-18 December 17-23
Days modeled as holidays for annual run: New Year’s Day - January 1 Good Friday – March 29 Memorial Day – May 27 July 4 th 

# Labor Day – September 2 Thanksgiving Day – November 28, 29 Christmas Eve – December 24 Christmas Day – December 25
Output time zone: Greenwich Mean Time (zone 0)
Projection: Lambert Conformal with Alpha=33, Beta=45, Gamma=-97, and center at (-97, 40).

Domain: 36 Kilometer Grid: Origin at (-2736, -2088) kilometers with 148 rows by 112 columns and 36-km square grid cells. 12 Kilometer Grid: Origin at (108, -1620) kilometers with 168 rows by 177 columns and 12-km square grid cells.
Layer structure: The CMAQ layer structure will be 19 layers, with specific layer positions defined in the meteorology files to be provided by VISTAS meteorological contractor.

# CMAQ model species: The CMAQ configuration will be for CB-IV with PM. The model species will be: CO, NO, NO2, ALD2, ETH, FORM, ISOP, NR, O LE, PAR, TERPB, TOL, XYL, NH3, SO2, SULF, PEC, PMFINE, PNO3, POA, PSO4, and PMC.
Meteorology data: Daily (25-hour). SMOKE requires the following five types of MCIP outputs: (1) Grid cross 2-d, (2) Grid cross 3-d, (3) Met cross 2-d, (4) Met cross 3-d, and (5), Met dot 3-d.

Elevated sources: All sources will be treated by SMOKE as potentially elevated. No plume-in-grid sources will be modeled. Wildfire emissions will be handled as point sources.

Figure 3. 36-km national unified RPO domain and VISTAS 12-km domain.

# DEVELOPMENT OF ONROAD MOTO R VEHICLE SOURCE EMISSIONS

The MOBILE6 module of SMOKE was used to devel op the onroad mobile source emissions estimates for CO, NOX, PM, and VOC emissi ons. The MOBILE6 parameters, vehicle fleet descriptions, and VMT estimates are combined with gridded, episode-specific temperature data to calculate the gridded, temporalized emission estimates. The MOBILE6 em issions factors are based on episode-specific temperatures predicted by the meteorological model. Further, the MOBILE6 emissions factors model accounts for the following:

• Hourly and daily minimum/maximum temperatures;

• Facility speeds;

• Locale-specific inspection/maintenance (I/M) control programs, if any;

• Adjustments for running losses;

• Splitting of evaporative and exhaust emissions into separate source categories;

• VMT, fleet turnover, and changes in fuel composition and Reid vapor pressure (RVP).
The primary input to MOBILE6 is the MOBILE she ll file. The MOBILE shell contains the various options (e.g. type of inspection and maintenance progr am in effect, type of oxygenated fuel program in effect, alternative vehicle mix profiles, RVP of in-use fuel, operating mode) that direct the calculation of the MOBILE6 emissions factors. The shells used in these runs were based on VISTAS/ASIP BaseF modeling inputs 7 

# . The options for all MOBILE6 parameters we re held constant between the annual and representative week runs.
Daily results of these model runs for a winter (Ja nuary 17) and summer (July 18) day are represented in Figures 4 through 6 below. These data provide a comparison of the magnitude difference between ozone and particulate matter precursor species for each of these seasonally different episodes. As can be seen in these figures, the variable inputs (temperature, VMT, seasonal fuels) associated with each month’s run have an impact on the overall emissions genera ted for the onroad mobile source category. It is through modeling these differences with CMAQ for both ozone and PM that we have based our conclusions.

Each of the onroad mobile source emissions r uns conducted with the MOBILE6 module of SMOKE were performed on a dual Athlon MP 2600+ with 1.5 G RAM. With this configuration, the modeling team experienced run times of approximately sixt y-three (63) minutes per run day on the 12km domain. Using this estimate, the representative week pr ocessing would require a total of 5,292 minutes (12 months x 7 days x 63 minutes per run day) or about 88.2 hours (3.5 days) of CPU runtime to generate the files necessary to simulate the annual episode . In comparison, actually running each day’s onroad mobile source emissions using the same confi guration would require 22,995 minutes (365 days x 63 minutes per run day) or about 383.25 hours (16 days) of CPU run time.

# Figure 4. Daily VOC emissions as generated with the MOBILE6 module of SMOKE for a winter (January 17) and summer (July 18) episode day.

Figure 5. Daily NOx emissions as generated with the MOBILE6 module of SMOKE for a winter (January 17) and summer (July 18) episode day.

# Figure 6. Daily PM-fine emissions as generated with the MOBILE6 module of SMOKE for a winter (January 17) and summer (July 18) episode day.

EMISSIONS SUMMARY

The reconstructed emissions based on the represen tative week run were calculated by mapping each day of week (Mon, Tue, Wed, etc.) from the modeled m onth to the same day of week generated in the representative week run. In the case of holidays, these days were mapped to representative week Sundays. An example of this mapping for the January episode is presented in Table 1. Note that although the emissions were generated for calenda r year 2009, the meteorology is based on 2002. Table 2 presents a comparison of January emissions as generated using the everyday MOBILE6 module run for each VISTAS/ASIP State and these emissions as reconstructed from the representative week MOBILE6 module runs. In comparison, Table 3 presents these emissions for the month of July.

Table 1. Representative day mapping for January episode (Highlighted representative week).

Modeled Representative Modeled Repres entative Modeled Representative Date Day Date Day Date Day 1/1/2002* 1/20/2002 1/ 11/2002 1/18/2002 1/22/2002 1/15/2002

1/2/2002 1/16/2002 1/ 12/2002 1/19/2002 1/23/2002 1/16/2002 1/3/2002 1/17/2002 1/ 13/2002 1/20/2002 1/24/2002 1/17/2002 1/4/2002 1/18/2002 1/ 14/2002 1/21/2002 1/25/2002 1/18/2002 1/5/2002 1/19/2002 1/15/2002 1/15/2002 1/26/2002 1/19/2002 1/6/2002 1/20/2002 1/16/2002 1/16/2002 1/27/2002 1/20/2002 1/7/2002 1/21/2002 1/17/2002 1/17/2002 1/28/2002 1/21/2002 1/8/2002 1/15/2002 1/18/2002 1/18/2002 1/29/2002 1/15/2002 1/9/2002 1/16/2002 1/19/2002 1/19/2002 1/30/2002 1/16/2002 1/10/2002 1/17/2002 1/20/2002 1/20/2002 1/31/2002 1/17/2002 1/21/2002 1/21/2002 * Modeled holiday

# Table 2. January 2009 onroad mobile emissions comparison.

State VOC NOx CO SO2 PM-10 PM-2.5 NH3 Alabama 6,567 8,774 105,011 51 266 174 500 Florida 28,354 26,686 336,541 171 834 529 1,736 Georgia 15,558 17,935 224,920 100 509 328 999 Kentucky 5,321 8,618 102,603 47 250 165 453 Mississippi 3,928 5,999 61,323 31 191 130 312 North Carolina 13,590 18,406 231,897 104 489 311 988 South Carolina 5,372 7,934 92,169 44 240 159 429 Tennessee 8,729 12,954 142,906 67 356 238 609 Virginia 7,377 11,708 156,617 72 311 190 716 West Virginia 2,025 3,177 41,742 18 91 59 168 96,821 122,190 1,495,728 705 3,536 2,283 6,910

State VOC NOx CO SO2 PM-10 PM-2.5 NH3 Alabama 6,394 8,765 102,800 51 266 174 500 Florida 28,852 26,476 333,248 171 833 529 1,736 Georgia 15,337 17,867 218,990 100 509 328 999 Kentucky 5,023 8,679 104,247 47 250 165 453 Mississippi 3,710 6,012 60,454 31 191 130 312 North Carolina 12,605 18,383 225,563 104 489 311 988 South Carolina 5,226 7,911 89,001 44 240 159 430 Tennessee 8,011 13,000 141,962 67 356 238 609 Virginia 7,005 11,735 155,321 72 311 190 715 West Virginia 1,941 3,194 42,096 18 91 59 168 94,104 122,021 1,473,682 705 3,536 2,283 6,909

State VOC NOx CO SO2 PM-10 PM-2.5 NH3 Alabama -2.6% -0.1% -2.1% 0.0% 0.0% 0.0% 0.0% Florida 1.8% -0.8% -1.0% 0.0% 0.0% 0.0% 0.0% Georgia -1.4% -0.4% -2.6% 0.0% 0.0% 0.0% 0.0% Kentucky -5.6% 0.7% 1.6% 0.0% 0.0% 0.0% 0.0% Mississippi -5.5% 0.2% -1.4% 0.0% 0.0% 0.0% 0.0% North Carolina -7.2% -0.1% -2.7% 0.0% 0.0% 0.0% 0.0% South Carolina -2.7% -0.3% -3.4% 0.0% 0.0% 0.0% 0.0% Tennessee -8.2% 0.4% -0.7% 0.0% 0.0% 0.0% 0.0% Virginia -5.0% 0.2% -0.8% 0.0% 0.0% 0.0% 0.0% West Virginia -4.1% 0.6 % 0.8% 0.0% 0.0% 0.0% 0.0% -2.8% -0.1% -1.5% 0.0% 0.0% 0.0% 0.0% January 2009 Emissions (Difference as Percent) January 2009 Emissions (Everyday Calculation)

January 2009 Emissions (Representative Day Calculation)

# Table 3. July 2009 onroad mobile emissions comparison.

State VOC NOx CO SO2 PM-10 PM-2.5 NH3 Alabama 5,968 8,654 61,362 58 278 175 584 Florida 21,715 27,067 208,947 190 864 531 1,971 Georgia 15,833 17,965 133,828 114 533 332 1,162 Kentucky 5,289 8,196 56,333 53 262 166 537 Mississippi 3,934 6,013 38,674 36 200 130 376 North Carolina 12,975 17,340 130,042 120 512 311 1,171 South Carolina 5,316 7,859 57,163 51 251 160 512 Tennessee 8,797 12,446 81,289 75 368 237 712 Virginia 7,064 11,221 87,946 82 331 195 832 West Virginia 2,038 3,006 23,429 21 96 61 205 88,930 119,768 879,013 800 3,695 2,299 8,063

State VOC NOx CO SO2 PM-10 PM-2.5 NH3 Alabama 6,017 8,682 61,581 58 278 175 585 Florida 22,006 27,217 210,901 190 864 531 1,971 Georgia 16,252 18,091 135,119 114 533 332 1,163 Kentucky 5,274 8,196 56,184 53 262 167 537 Mississippi 3,960 6,023 38,911 36 200 130 376 North Carolina 13,160 17,394 130,728 120 512 311 1,171 South Carolina 5,449 7,903 57,867 51 251 160 512 Tennessee 8,798 12,454 81,930 75 368 237 712 Virginia 7,104 11,248 87,523 82 331 195 832 West Virginia 2,047 3,010 23,419 21 96 61 205 90,068 120,218 884,162 800 3,695 2,299 8,063

State VOC NOx CO SO2 PM-10 PM-2.5 NH3 Alabama 0.8% 0.3% 0.4% 0.0% 0.0% 0.0% 0.0% Florida 1.3% 0.6% 0.9% 0.0% 0.0% 0.0% 0.0% Georgia 2.6% 0.7% 1.0% 0.0% 0.0% 0.0% 0.0% Kentucky -0.3% 0.0% -0.3% 0.0% 0.0% 0.0% 0.0% Mississippi 0.7% 0.2% 0.6% 0.0% 0.0% 0.0% 0.0% North Carolina 1.4% 0.3% 0 .5% 0.0% 0.0% 0.0% 0.0% South Carolina 2.5% 0.6% 1 .2% 0.0% 0.0% 0.0% 0.0% Tennessee 0.0% 0.1% 0.8% 0.0% 0.0% 0.0% 0.0% Virginia 0.6% 0.2% -0.5% 0.0% 0.0% 0.0% 0.0% West Virginia 0.5% 0.1% 0.0% 0.0% 0.0% 0.0% 0.0% 1.3% 0.4% 0.6% 0.0% 0.0% 0.0% 0.0% July 2009 Emissions (Difference as Percent) July 2009 Emissions (Everyday Calculation)

July 2009 Emissions (Representative Day Calculation)

# These aggregate emission summaries would lead one to believe that on an extended episode scale (like those required for PM or regional haze modeling), the use of representative week onroad mobile source emissions would be appropriate. However, in modeli ng either 1-hr or 8-hr ozone, there is enough of a temperature variability and therefore apparent ozone precursor emissions delta on an hour-to-hour basis that this same assumption could not be made without accompanying air quality simulations.

AIR QUALITY MODELING

The VISTAS/ASIP modeling team has applied the CMAQ Version 4.5 O 3 

# /PM 2.5 

# photochemical grid modeling system. The VISTAS/ASIP modeling team implemented a comprehensive evaluation of the meteorological 8 

# , emissions and air quality models. The CM AQ model performance evaluation indicated an underestimation of 8-hour ozone maximums duri ng the summer. The model demonstrated reasonably good performance for sulfate, winter overestimation bias and summer underestimation bias for nitrate and reasonably good performance for elemental carbon (EC), albeit with lots of scatter and low correlation. However, organic carbon (OC) was undere stimated with the summer OC underestimation bias being quite severe. After an intense focuse d analysis of the OC underestimation issue, the VISTAS/ASIP modeling team identified processes im portant to the formation of secondary organic aerosols (SOA) that were not included in the CMAQ SOA module that may be important to OC in the Southeastern U.S. 9 

# Consequently, VISTAS/ASIP enhanced the CMAQ SOA module by adding several new processes. This enhancement, called “SOAm ods”, was implemented in CMAQ Version 4.5 and exhibited much improved OC model perfor mance over the standard CMAQ SOA treatment 10 

# . A complete description of the modeling methods, configurations and performance are described elsewhere 1,7



# . CMAQ was applied using both of the mobile emissi ons modeling methods described above. Recall, all emissions and air quality model inputs and configurati ons were held constant, with the exception of the mobile source emissions. This will allow us to isolat e the air quality impacts of using the representative week mobile emissions versus the “actual” daily modeled mobile emissions. While the VISTAS/ASIP modeling is conducted on both 36-km National RPO and 12-km “VISTAS/ASIP” modeling domains as shown in Figure 3, this study focuses on evaluations of the 12-km air quality modeling results only.
Using each of the mobile emissions databases (da ily and the representative week) generated for the January and July study periods, we performed futu re-year air quality simulations for 2009 using CMAQ. We then post-processed the air quality model results to qualitatively evaluate the magnitude, location, and spatial extent of the differences in predicted ozone and PM 2.5 

# concentrations due to the different mobile emissions modeling methodologies. Spatial plots were generated for each day simulated, including:
1) daily maximum 8-hour ozone difference plots; 2) maximum 1-hour ozone maximum difference plots; and, 3) daily PM 2.5 

# difference plots.

# RESULTS

Our examination of the two air quality simulati ons began with the daily differences in PM 2.5 

# concentrations. Figures 7 and 8 represent the percent difference in the daily PM 2.5 

# concentrations between the air quality simulations with representa tive week mobile emissions and the daily mobile emissions for one winter day (January 22 nd 

# ) and one summer day (July 9 th 

# ). No change is seen in either plot indicating daily PM 2.5 

# concentrations changed less than one percent. Absolute differences in daily PM 2.5 

# concentrations are shown in Figures 9 and 10 for the same two days (January 22 nd 

# and July 9 th 

# ). Again, no change is seen in either plot indicating daily PM 2.5 

# concentrations changed less than 0.2 μg/m 3 

# . In fact, all of the fourteen days modeled (seven winter days and seven summer days) show no differences as high as 0.2 μg/m 3



# . We next examined the results of the two air quality simulations with the daily differences in maximum 8-hour ozone concentrations. Figures 11 and 12 presen t the percent difference in the daily maximum 8- hour ozone concentrations for one winter day (January 28 th 

# ) and one summer day (July 15 th 

# ). In most areas for the winter day, daily maximum 8-hour ozone concentrations changed less than one percent. In a few urban corridors, namely, near Chicago, IL, Atlanta, GA and Baltimore, MD, changes of one percent are noted. Near Philadelphia, PA, changes of up to two percent are noted. However, this was the only day of the seven wintertime days simulated th at showed a daily maximum 8-hour ozone difference as high as one percent anywhere in the modeling domain. It should also be noted that predicting wintertime ozone concentrations is not usually an inte rest because most, if not all high ozone events in the middle latitudes of the northern hemisphere occu r during the summertime. Therefore the remainder of the ozone analysis will focus on summer time differences. On the summer day, July 15 th 

# , presented in Figure 12, no changes are seen indicating daily ma ximum 8-hour ozone concentrations changed less than one percent. In fact, all seven of the summer days modeled showed no changes as high as one percent.
Absolute differences in daily maximum 8-hour ozone concentrations are shown in Figure 13 for July 15 th 

# . Again, no change as high as 0.5 ppb (0.0005 ppm) was noted on this day or any of the seven summer days modeled. In addition to the 8-hour ozone metrics discussed above, differences in 1-hour ozone maximums were examined. As shown in Fi gure14 and 15, only two days during the seven day summertime period simulated showed differences in 1-hour ozone maximums as high as 0.5 ppb (0.0005 ppm).

# Figure 7. Percent difference in 24-hour PM 2.5 

# concentrations for January 22nd (Representative week mobile emissions versus daily mobile emissions).

Figure 8. Percent difference in 24-hour PM 2.5 

# concentrations for July 9 th 

# (Representative week mobile emissions versus daily mobile emissions).

# Figure 9. Absolute differences in 24-hour PM 2.5 

# concentrations for January (Representative week mobile emissions versus daily mobile emissions).

Figure 10. Absolute differences in 24-hour PM 2.5 

# concentrations for July 9 th 

# (Representative week mobile emissions versus daily mobile emissions).

# Figure 11. Percent differences in daily 8-hour maximu m ozone concentrations for January 28th (Representative week mobile emissions versus daily mobile emissions).

Figure 12. Percent differences in daily 8-hour maxi mum ozone concentrations for July 15 th 

# (Representative week mobile emissions versus daily mobile emissions).

# Figure 13. Absolute differences in daily 8-hour ma ximum ozone concentrations for July 15 th 

# (Representative week mobile emissions versus daily mobile emissions).

# Figure 14. Absolute differences in 1-hour maximum ozone concentrations for July 12 th



# .

Figure 15. Absolute differences in 1-hour maximum ozone concentrations for July 14 th



# .

# CONCLUSIONS

U.S. EPA attainment demonstration modeling guidance 11,12 

# notes that in some cases it may be useful to evaluate how the response of an air quality model to emissions changes varies as a function of alternative model inputs or model algorithms. These t ypes of tests can be used to assess the robustness of a base case or control strategy modeling evaluati on. As an example, EPA remarks that States/Tribes could consider the effects of assumed boundary c onditions on predicted effectiveness of a control strategy. If the model response does not differ gr eatly over a variety of alternative plausible configurations, this increases confidence in the model results.
The parameters for these sensitivity tests can in clude, but are not limited to: different chemical mechanisms, finer or coarser grid resolution, me teorological inputs from alternative, credible meteorological model(s), different initial/boundary conditions, and multiple sets of reasonable emission projections . Sensitivity tests can and should be applied th roughout the modeling process, not just when model performance is being evaluated.
The modeling team’s research in using reasonable alternate sets of onroad emission projections has determined that the use of representative week onr oad mobile emissions for each month of our episodes within our 12km modeling domain predicts ozone and particulate matter concentration differences from annual, everyday onroad mobile modeling which could be considered insignificant from an air quality modeling standpoint. The small differences in the air quality results in combination with the length of time necessary to conduct daily onroad mobile runs using the MOBILE6 module of SMOKE has resulted in the project team’s recommendation that representative week onroad mobile emissions methodology be carried forward in the VIST AS regional haze modeling and the ASIP PM 2.5 

# and 8-hour ozone modeling.

REFERENCES

1. “Draft Modeling Protocol For Association fo r Southeastern Integrated Planning (ASIP) – Emissions and Air Quality Modeling to Address 8-Hour Ozone and PM2.5 Nonattainment in the Southeastern United States”; Prepared fo r ASIP by ENVIRON, Alpine Geophysics and University of California, Riverside, January 31, 2006.
2. Dudhia, J. "A Non-hydrostatic Version of th e Penn State/NCAR Mesoscale Model: Validation Tests and Simulation of an Atlantic Cyclone and Cold Front", Mon. Wea. Rev., 1993, Vol. 121. pp. 1493-1513.

3. Grell, G. A., J. Dudhia, and D. R. Stauffe r. "A Description of the Fifth Generation Penn State/NCAR Mesoscale Model (MM5). NCAR Tech. Note, 1994. NCAR TN-398-STR, 138 pp.
4. University of North Carolina at Chapel Hill, Sparse Matrix Operator Kernel Emissions (SMOKE) Modeling System
, http://cf.unc.edu/cep/empd/products/smoke/index.cfm

. 5. Byun, D.W., and J.K.S. Ching. “Science Al gorithms of the EPA Models-3 Community Multiscale Air Quality (CMAQ) Modeling System”, EPA/600/R-99/030. 1999.
6. Pleim J. et al. “New Developments in CMAQ Model Physics”, Presented at the 4 th 

# Annual CMAS Models-3 User’s Conference, Septembe r 26-28, 2005, Friday Center Chapel Hill North Carolina.

# 7. VISTAS Phase II Modeling website, http://pah.cert.ucr.edu/vistas/vistas2/

. 8. Abraczinskas, M.A., Olerud, D.T., Sims, A.P. “Characterizing Annual Meteorological Modeling Performance for Visibility Improvement Strategy M odeling in the Southeastern U.S.”, Presented at the 3 th 

# AMS Joint Conference on the Applications of Air Pollution Meteorology with the Air and Waste Management Association, Vancouver, BC, 2004.
9. Morris, R.E., McNally, D.E., Tesche, T.W ., Tonnesen, G., Boylan, J.W., Brewer, P. “Preliminary Evaluation of the Community Multiscale Air Quality Model for 2002 over the Southeastern United States”. 2005. J. Air & Waste Manag. Assoc. 55:1694-1708
10. Morris, R.E.; Koo, B.; Yarwood, G.; McNally, D. E.; Tesche, T.W.; Tonnesen, G.S.; Boylan, J.; Brewer, P. “Model Sensitivity Evaluation for Organic Carbon Using Two Multi-Pollutant Air Quality Models that Simulate Regional Haze in the Southeastern United States”, Atmos. Environ. Submitted for publication.

11. Guidance on the Use of Models and Other Analyses in Attainment Demonstrations for the 8-hour Ozone NAAQS , U.S. Environmental Protection Agency Office of Air Quality Planning and Standards Emissions, Monitoring, and Analysis Division Air Quality Modeling Group Research Triangle Park, North Carolina, 2005; EPA-454/R-05-002.

12. Guidance for Demonstrating Attainment of Air Quality Goals for PM 2.5 

# and Regional Haze
, Draft Report, U.S. Environmental Protecti on Agency, Research Triangle Park, NC. 2001.

ACKNOWLEDGEMENTS

VISTAS and ASIP are funded by grants to the South eastern States Air Resource Managers, Inc. from the United States Environmental Protection Agency and the VISTAS/ASIP state and local agencies. The authors of this paper would like to acknowledge VIST AS and ASIP State, local and Tribal air quality agencies, participating stakeholders, and associated contractors for their contribution and input in the emission inventory development and modeling. Additi onally, the authors would like to recognize the support of the North Carolina Department of Envi ronment and Natural Resources, Division of Air Quality and Dennis McNally, Alpine Geophysics for his time in preparing the CMAQ runs used in this analysis.

# KEYWORDS

ASIP MOBILE Modeling Onroad Mobile Ozone Particulate Matter Regional Haze Regional Planning Organization SMOKE VISTAS

# Appendix D.5 VISTAS Emission Inventory

Supporting Documentation

## Emissions Preparations & Results Appendix D.5 - 1 Regional Haze SIP for NC Class I Areas December 17, 2007

## Emissions Preparations & Results Appendix D.5 - 2 Regional Haze SIP for NC Class I Areas December 17, 2007 

# TABLE OF CONTENTS

Development of the VISTAS Draft 2002 Mobile Source Emission Inventory (February 2004 version), Pechan ................................................................................................ .....3

Documentation of the Base G 2002 Base Year, 2009 and 2018 Emissions Inventory for VISTAS, MACTEC, Inc............................................................................................................ ....62

Memorandum to VISTAS State Point Contacts and VISTAS EGU Special Interest Workgroup, from Gregory Stella, June 13, 2005............................................................................................. 318

# PECHAN

5528-B Hempstead Way Springfield, VA 22151

703-813-6700 telephone 703-813-6729 facsimile

3622 Lyckan Parkway Suite 2002 Durham, NC 27707

919-493-3144 telephone 919-493-3182 facsimile

P.O. Box 1345 El Dorado, CA 95623

530-295-2995 telephone 530-295-2999 facsimile 

# Development of the VISTAS Draft 2002 Mobile Source Emission Inventory (February 2004 Version)

Prepared for:

VISTAS 59 Woodfin Place Asheville, NC 28801

Prepared by:

Maureen A. Mullen Kirstin B. Thesing E.H. Pechan & Associates, Inc. 5528-B Hempstead Way Springfield, VA 22151

February 9, 2004

Pechan Rpt. No. 04.01.002/9440.000

# [ This page intentionally left blank]

# CONTENTS Page TABLES.........................................................................................................................

............... iv FIGURES....................................................................................................................................... v ACRONYMS AND ABBREVIATIONS.................................................................................... vi I. INTRODUCTION/BACKGROUND ................................................................................ 1 II. ONROAD METHODS AND DATA.................................................................................. 2 A. 2002 VMT DEVELOPMENT..................................................................................... 2 1. Conversion to Annual VMT................................................................................. 2 2. Projection to 2002................................................................................................. 3 3. Splitting VMT by Road Type............................................................................... 4 a. Allocation of VMT to Vehicle T ype using Default VMT Mix Data............. 4 b. Allocation of VMT to Vehicle Type using State-Provided VMT Mix Data . 6 c. Allocation of VMT by Month........................................................................ 6 B. 2002 ONROAD EMISSION FACTOR DE VELOPMENT USING MOBILE6.2 ..... 8 1. General MOBILE6.2 File Structure ..................................................................... 8 C. 2002 ONROAD EMISSION INVE NTORY CALCULATIONS ............................. 14 D. DATA PROVIDED BY STA TE AND LOCAL AGENCIES .................................. 14 1. Temperature........................................................................................................ 21 2. I/M and ATP Programs ...................................................................................... 21 3. RVP and Fuel Programs ..................................................................................... 21 III. NONROAD METHODS AND DATA............................................................................. 22 A. NONROAD MODEL CATEGORIES ...................................................................... 22 B. AIRCRAFT, COMMERCIAL MARINE VESSELS AND LOCOMOTIVES ........ 23 2. CMV Improvements........................................................................................... 28 a. Current Allocation Method.......................................................................... 28 b. Revised Port Allocation Method.................................................................. 29 3. Projection Methods............................................................................................. 40 IV. ONROAD REFUELING METHODS............................................................................. 42 A. CONTROLS .............................................................................................................. 42 B. METHODS................................................................................................................ 43 V. NONROAD REFUELING METHODS.......................................................................... 44 VI. SUMMARY OF RESULTS.............................................................................................. 45 A. ONROAD RESULTS................................................................................................ 45 B. NONROAD RESULTS............................................................................................. 47 VII. OBSERVATIONS AND RECOMMENDATIONS FOR IMPROVEMENT.............. 51 A. ONROAD SECTOR IMPROVEMENTS ................................................................. 51 B. NONROAD SECTOR IMPROVEMENTS .............................................................. 52 VIII. REFERENCES .................................................................................................................. 52

# TABLES

Table II-1. VMT Data Provide d by State/Local Agencies ............................................................ 3 Table II-2. VMT Growth Factors Used for Virginia ..................................................................... 4 Table II-3. Allocation of VMT from HPMS Vehi cle Categories to MOBILE6 Vehicle Types for 2001........................................................................................................................... ................ 5 Table II-4. Default VMT Seasonal and M onthly Temporal Allocation Factors............................ 7 Table II-5. Default Speeds Modeled by Road Type and Vehicle Type....................................... 13 Table II-6. Summary of Onroad Data Provided by Alabama ...................................................... 15 Table II-7. Summary of Onroad Data Provided by Florida......................................................... 15 Table II-8. Summary of Onroad Data Provided by Georgia........................................................ 16 Table II-9. Summary of Onroad Data Provided by Kentucky..................................................... 17 Table II-10. Summary of Onroad Data Provided by Mississippi ................................................ 18 Table II-11. Summary of Onroad Data Provided by North Carolina .......................................... 18 Table II-12. Summary of Onroad Data Provided by South Carolina .......................................... 19 Table II-13. Summary of Onroad Data Provided by Tennessee.................................................. 19 Table II-14. Summary of Onroad Data Provided by Virginia ..................................................... 20 Table II-15. Summary of Onroad Data Provided by West Virginia............................................ 20 Table III-1. Summary of Comments by S/L/ T Agencies on NONROAD Model Input Values Distributed in July 2003....................................................................................................... ... 22 Table III-2. Summary of S/L/T Agency Data In corporated into the Draft VISTAS 2002 Other Nonroad Inventory.................................................................................................................. 23 Table III-3a. Replacement Procedures for 1999 Locomotive Emissions for Pickens and Tuscaloosa County, Alabama ................................................................................................. 24 Table III-3b. Replacement Procedures for 1999 Aircraft, Locomotive, and Commercial Marine Vessel Emissions for Palm Beach County, Florida ................................................................ 25 Table III-3c. Replacement Procedures for 1999 Aircraft and Locomotive Emissions for Davidson County, Tennessee.................................................................................................. 26 Table III-3d. Replacement Procedures for 1999 Aircraft, Locomotive, and Commercial Marine Vessel Emissions for Sample Counties in Virginia ................................................................ 27 Table III-4. Port Areas Located in VISTAS and Adjoining States.............................................. 32 Table III-5. List of VISTAS Port s and Ports of Adjoining States ............................................... 33 Table III-6. Definition of Port Areas Obtained from Waterborne Commerce ............................ 36 Table III-7a. Growth Factors for Ra ilroad Distillate Fuel Oil Use.............................................. 40 Table III-7b. 2002 National Rail Trans portation Energy Use by Fuel Type............................... 41 Table III-8. Growth Factors for Commercial Marine Vessel Distillate and Residual Fuel Oil Use ....................................................................................................................... ............. 42 Table IV-1. Onroad Stage II Control Programs........................................................................... 43 Table V-1. 2002 Draft Stage II Re fueling Emissions by State.................................................... 45 Table VI-1. 2002 VISTAS Onroad Emissions and VMT by State.............................................. 46 Table VI-2. 1999 NEI Version 2 Onro ad Emissions and VMT by State .................................... 46 Table VI-3. Change in Onroad Emissions and VMT from 1999 NEI Version 2 to VISTAS 2002 Inventory...................................................................................................................... ........... 47 Table VI-4. 2002 VISTAS Annual Onroad Refueling Emissions............................................... 47 Table VI-5. Summary of Dr aft 2002 Nonroad Sector Annua l Emissions by State ..................... 48 Table VI-6. Summary of Dr aft 2002 NONROAD Model Emission Estimates by State............. 49

# Table VI-7. Summary of Dr aft 2002 Other Nonroad* Emission Estimates by State.................. 50



# FIGURES

Figure II-1. Header Section of MOBILE6.2 Input File Including VOC Exhaust and PM 10 

# Emission Factors............................................................................................................... .............. 9 Figure II-2. Header Section of MOBILE6.2 Input File Including VOC Evaporative and PM 2.5 

# Emission Factors............................................................................................................... .............. 9 Figure II-3. Run Data Secti on of a MOBILE6.2 Input File......................................................... 10 Figure II-4. Run Data Section of a MOBILE6.2 Input File with Significant Local Inputs......... 10 Figure II-5. Sample Scenario fo r a Typical MOBILE6.2 Input File ........................................... 12 Figure III-1. VISTAS Re gion and Surrounding States, Underway NO x 

# Emissions ................... 30 Figure III-2. VISTAS Re gion and Surrounding States, Port NO x 

# Emissions ............................. 31 Figure III-3. VISTAS Region and Surrounding States, Revised Port Emissions of NO X 

# ............ 35

# ACRONYMS AND ABBREVIATIONS

ATADS Air Traffic Activity Data System ATP anti-tampering program BTS Bureau of Transportation Statistics BTU British thermal unit CMV commercial marine vessels CNG compressed natural gas CO carbon monoxide DOT Department of Transportation EIA Energy Information Administration EPA U.S. Environmental Protection Agency FHWA Federal Highway Administration FIPS Federal Information Processing Standards GF growth factor HDDV heavy-duty diesel vehicle HDGV heavy-duty gasoline vehicle HPMS Highway Performance Monitoring System I/M inspection and maintenance LDDT light-duty diesel truck LDDV light-duty diesel vehicle LDGT light-duty gasoline truck LDGV light-duty gasoline vehicle LPG liquified petroleum gas LTO landing and takeoff MC motorcycle mg milligram NAPAP National Acid Precipitation Assessment Program NEI National Emission Inventory NH 3 

## ammonia NO x 

## oxides of nitrogen OTAQ Office of Transportation and Air Quality Pechan E.H. Pechan & Associates, Inc. PM 2.5 

## particulate matter with an aerodynamic diameter less than or equal to 2.5 micrometers PM 10 

## particulate matter with an aerodynamic diameter less than or equal to 10 micrometers ppmv parts per million volume RFG reformulated gasoline RVP Reid vapor pressure SCC source classification code S/L/T State/Local/Tribal SO 2 

## sulfur dioxide USACE U.S. Army Corps of Engineers VISTAS Visibility Improvement-State and Tribal Association of the Southeast VMT vehicle miles traveled VOC volatile organic compound

## 1 

# I. INTRODUCTION/BACKGROUND

The Visibility Improvement – State and Tribal Association of the Southeast (VISTAS) has contracted with E.H. Pechan & Associates, Inc. (Pechan) to prepare a 2002 mobile source emissions inventory. The purpose of this emi ssions inventory is to support the modeling and assessment of speciated particulate matter with an aerodynamic diameter less than or equal to 2.5 micrometers (PM 2.5 

## ). Through this contract, Pechan first prepared an inventory review document. This document summarized several regional and national emission inventory efforts and identified strengths and weaknesses associated with the use of these inventories in regional haze modeling. This document also summarized data submittals by State and local air agencies within the VISTAS region that could be used in the VISTAS 2002 mobile source emissions inventory.
Since that time, the State and local air agencies have updated their submittals for the mobile source sectors, including both onroad vehicles a nd nonroad engines. In July of 2003, Pechan delivered sets of inputs to the NONROAD model option files and MOBILE6.2 input files and vehicle miles traveled (VMT) data for each State and local agency to review. For the onroad sector, the MOBILE6.2 input files and VMT data represented Pechan’s processing of the State and local inputs in a consistent manner for use in calculating the 2002 onroad emissions inventory. The MOBILE6.2 input files and VMT data included as much of the local data supplied by the State and local agencies as possible, with missing information filled in with appropriate default data. The data delivered by Pechan for the State and local agencies to review related to the nonroad sector was primarily in the form of temperature and fuel data that would be used as inputs to the NONROAD model. It should be noted that the nonroad sector inputs were completed first and did not include some of the later temperature and fuel updates that did get incorporated in the onroad data.
The State and local agencies were given a brief period to review, comment upon, and make updated submittals to the onroad and nonroad inputs that were delivered in July 2003. After receiving these comments and updated data, Pechan updated the appropriate MOBILE6.2 input files, VMT data, and nonroad inputs with the revised State and local data. Pechan then calculated 2002 onroad and nonroad emissions from these inputs. Pechan presented the preliminary results of these emission inventories at a VISTAS meeting on August 28, 2003. These draft August 2003 emission estimates, including inputs and methodology, were documented in a draft report circulated to VISTAS in October 2003. This October 2003 report also included documentation of draft 2002 refueli ng emissions from onroad and nonroad sources. The VISTAS States were asked to review this document, as well as the supporting files provided by Pechan, and provide comments or revisions by December 2003. Onroad and nonroad 2002 emissions for the VISTAS States have since been calculated based on the updates provided by the States. This report documents the inputs and methodologies used in the February 2004 version of the VISTAS 2002 onroad and nonroad mobile source emission inventories.

## 2 

# II. ONROAD METHODS AND DATA

A. 2002 VMT DEVELOPMENT
Table II-1 summarizes the type of VMT data submitted by each agency. Depending upon the data submitted by the individual State or agency, up to three different procedures were performed on the data. First, VMT data that were not provided at the annual level were converted from daily VMT to annual VMT. Second, VMT provided for years other than 2002 were grown from the base year provided. Fina lly, the VMT were allocated by vehicle type, if not already at that level of detail. The section discusses each of these procedures in more detail.
It should be noted that although the format a nd content of the VMT provided by the VISTAS State and Local agencies varied significantly fr om agency to agency, this draft 2002 VISTAS inventory is based at a minimum on county/ro adway type specific VMT, as provided by the individual agencies. This is a significant improvement over the spatial allocation methods used in the U.S. Environmental Protection Agency’s (EPA’s) National Emission Inventory (NEI) for onroad vehicles.

1. Conversion to Annual VMT
For use in the emission calculations, Pechan’s ultimate goal with the VMT data was to develop an annual 2002 VMT database by county, roadway type , and vehicle type. As indicated in Table II-1, the VMT data were submitted using three different time periods: annual, average annual day, and summer day. No temporal adjustments were applied to VMT data submitted as annual VMT. VMT data submitted as average annual day VMT were multiplied by 365 to convert from an average day to the annual time period. The Jefferson County, Kentucky VMT were submitted as summer day VMT. All annual VMT values were converted to units of millions of miles per year. Therefore, any VMT values submitted as miles were divided by a factor of 1,000,000 and VMT values submitted in units of 1,000 miles were divided by a factor of 1,000.
The Jefferson County, Kentucky VMT submittal included a single factor for converting the summer day VMT to average annual day VMT. Thus, the Jefferson County summer day VMT data were first multiplied by a factor of 0.97752 (the temporal conversion factor provided by Jefferson County) to obtain average annual day VMT. The VMT data were then multiplied by 365 to obtain the annual VMT.

## 3 Table II-1. VMT Data Provided by State/Local Agencies

State/Area Time Period 2002 Actual VMT by County/Road Type/Vehicle Type 2002 Actual VMT by County/Road Type 2002 Projected VMT by County/Road Type 2002 VMT from TDM by County/Road Type/Vehicle Type 1999 Actual VMT by County/Road Type/Vehicle Type

Alabama AAD X

Florida AAD X
Georgia AAD X
Kentucky AAD X Jefferson County, KY SD X
Mississippi ANN X

North Carolina AAD X

South Carolina ANN X

Tennessee AAD X
Virginia ANN X
West Virginia ANN X X
Time Period Codes: AAD=Average Annual Day, SD=Summer Day, ANN=Annual



## 2. Projection to 2002
As indicated in Table II-1, the Virginia VMT submittal was for a base year of 1999 rather than 2002. Thus, these VMT data needed to be projected to 2002 before calculating emissions. For Virginia, growth factors were developed by roadway type for the period from 1999 to 2001 based on historical VMT data by roadway type fr om Table VM-2 “Functional System Travel” in DOT’s Highway Statistics series (DOT, 1999 and 2001). The growth factors, presented in Table II-2, were calculated by dividing Virginia’s 2001 VMT for each of the 12 roadway types from Highway Statistics 2001 by the corresponding 1999 VMT from Highway Statistics 1999 . For the period from 2001 to 2002, the growth factors were developed using data obtained from the U.S. Department of Transportation’s Traffic Volu me Trends report (DOT, 2002). This monthly publication provides a comparison of preliminary 2002 VMT estimates with comparable 2001 VMT. For several roadway types, these data are provided only at a national level. However, for the combined rural interstates and arterials, these data are presented by State. The resultant data, used to project the 2001 Virginia VMT to 2002, are shown in Table II-2. The 2001 to 2002 growth factors represent the 2002 VMT divided by the 2001 VMT, based on the data Virginia for the rural interstates and arterials and on the national data for the remaining roadway types. Once the growth factors were developed, the Virginia 1999 VMT data were first multiplied by the appropriate 1999 to 2001 growth factor and then by the appropriate 2001 to 2002 growth factor.

## 4 Table II-2. VMT Growth Factors Used for Virginia

Roadway Type Roadway Type Portion of

SCC Virginia 1999 to 2001 VMT Growth Factor Virginia 2001 to 2002 VMT Growth Factor Rural Interstate 110 1.043 1.035 Rural Other Principal Arterial 130 1.050 1.035 Rural Major Arterial 150 1.130 1.035 Rural Major Collector 170 0.982 1.011 Rural Minor Collector 190 1.032 1.011 Rural Local 210 0.923 1.011 Urban Interstate 230 1.050 1.024 Urban Other Freeway & Expressway 250 0.984 1.011 Urban Other Principal Arterial 270 1.061 1.011 Urban Minor Arterial 290 0.991 1.011 Urban Collector 310 0.925 1.013 Urban Local 330 0.690 1.013
Sources: U.S. Department of Transportation, Feder al Highway Administration, “Traffic Volume Trends, December 2002”, (http:// www.fhwa.dot.gov/ohi m/tvtw/tvtpage.htm); Highway Statistics 1999 , and Highway Statistics 2001 (http://www.fhwa.dot.gov/policy/ohpi/hss/hsspubs.htm)



## 3. Splitting VMT by Road Type
The final step in developing a consistent 2002 VMT data base was to allocate VMT from the county and roadway type level of detail to the county/roadway type/vehicle type level of detail. As shown in Table II-1, the Jefferson County, Kentucky; Mississippi; Virginia; and West Virginia VMT data supplied for these jurisdictions already included the vehicle type level of detail, so this final adjustment was not needed for these areas. For the remaining areas, some provided VMT mix by vehicle type fractions while others provided no information on the allocation of VMT by vehicle. In this latter case, default VMT fraction data from EPA’s MOBILE6 model were used.

The States for which MOBILE6 default VMT mix data were used are: Alabama, Florida, Georgia, Kentucky (excluding Boone County, Campbell County, Kenton County, and Jefferson County), and South Carolina. It should be noted that Georgia initially provided VMT fractions based on Georgia's HPMS classification count data, but after review of ten years of these data determined that they are not reflecting the trend towards increasing travel by light trucks. Georgia therefore decided it was more conservative to assume MOBILE6 default VMT fractions.
a. Allocation of VMT to Vehicle Type using Default VMT Mix Data
To calculate 2002 VMT at the county/roadway type/vehicle type level using national default data, the VMT totals by county and roadway type need to be allocated among the 28 MOBILE6 vehicle types. This was done based on the distribution of the 2001 rural and urban VMT among the six Highway Performance Monitoring System s (HPMS) vehicle types found in Table VM-1 (“Annual Vehicle Distance Traveled in Miles and Related Data - 1999 - by Highway Category and Vehicle Type”) of the Federal Highway Administration’s (FHWA’s) Highway Statistics

## 5 2001 ( http://www.fhwa.dot.gov/ohim/ hs01/index.htm) and a mapping of these HPMS vehicle categories to the 28 MOBILE6 vehicle types. This mapping of the MOBILE6 vehicle types to the HPMS vehicle types was developed by EPA’s Office of Transportation and Air Quality (OTAQ) and is used in the development of the NEI. The data first needed to be expanded to the 28 vehicle type level of detail to obtain the proper cross reference between the HPMS and MOBILE6 vehicle types since the eight vehicle t ypes used in the final VISTAS VMT data base cannot be directly mapped to the HPMS vehicle categories. First, the VMT totals for each of the six HPMS vehicle categories were calculated as a fraction of the total VMT. This calculation was performed separately for the rural VMT and the urban VMT. The resulting 2001 VMT fractions for rural VMT and urban VMT are shown in Table II-3. Note that 2002 VMT are not yet available at this level of detail. Using the default MOBILE6 VMT fractions for 2001 (since the HPMS data represents 2001), taken from a MOBILE6 output file for 2001, the MOBILE6 VMT fractions were renormalized among all MOBILE6 vehicle types mapped to a given HPMS vehicle category. This renormalization is shown in the final column of Table II-3.

Table II-3. Allocation of VMT fr om HPMS Vehicle Categories to MOBILE6 Vehicle Types for 2001

HPMS Vehicle Category HPMS 2001 Rural VMT Fractions HPMS 2001 Urban VMT Fractions MOBILE6 Vehicle Category MOBILE6 2001 VMT Fractions by HPMS Category Passenger Cars 0.5454 0.6065 LDGV 0.9980 LDDV 0.0020 Motorcycles 0.0039 0.0031 MC 1.0000 Other 2-Axle 4-Tire Vehicles 0.3368 0.3375 LDGT1 0.1565 LDGT2 0.5211 LDGT3 0.1585 LDGT4 0.0729 LDDT12 0.0005 LDDT34 0.0032 HDGV2B 0.0658 HDDV2B 0.0216 Single-Unit 2-Axle 6-Tire or More Trucks 0.0332 0.0212 HDGV3 0.0376

HDGV4 0.0206 HDGV5 0.0436 HDGV6 0.0934 HDGV7 0.0437 HDDV3 0.1023 HDDV4 0.0867 HDDV5 0.0380 HDDV6 0.2138 HDDV7 0.3205 Combination Trucks 0.0770 0.0300 HDGV8A 0.0001 HDGV8B 0.0000 HDDV8A 0.2191 HDDV8B 0.7808 Buses 0.0037 0.0017 HDGB 0.1920 HDDBT 0.3258 HDDBS 0.4822 Total 1.0000 1.0000

## 6 To calculate VMT by vehicle type, each VMT value representing a given county and road type was multiplied by the product of the HPMS VMT fraction (selected depending upon whether the road type represent VMT on rural or urban roads) and the corresponding MOBILE6 VMT fraction by HPMS category. This process resulted in 28 VMT values at the county/roadway type/vehicle type level of detail for each county/roadway type VMT value in the original VMT file.
As an example, Table II-3 shows that the HPMS Passenger Car vehicle category accounts for 54.54 percent of the total VMT on rural road types and that the MOBILE6 LDGV category accounts for 99.8 percent of the VMT in the HPMS Passenger Car category. Therefore, a VMT value representing rural interstates would be multiplied by 0.5454 times 0.9980 (0.5443), to obtain the VMT total on rural interstates from LDGVs. Once all county/roadway type VMT values were expanded to the corresponding set of values of VMT at the county/roadway type/28 MOBILE6 vehicle type level of detail, the VMT da ta base was then totaled at the eight vehicle type level of detail (LDGV, LDGT1, LDGT2, HDGV, LDDV, LDDT, HDDV, MC).
b. Allocation of VMT to Vehicle Type using State-Provided VMT Mix Data
Both North Carolina and Tennessee provided VMT mix data at the eight vehicle type level of detail. The Tennessee data was provided for ten different county groupings, with a VMT mix provided for six aggregated roadway type categories. North Carolina provided statewide VMT mix fractions for each of the 12 roadway types. Since the VMT mix data for these two States were already at the eight vehicle type level, the procedure for allocating VMT by vehicle type was simpler than the procedure described above using the default data. Each county/roadway type VMT value was matched to the corresponding VMT mix for that county and roadway type and then separately multiplied by each of the eight VMT mix fractions to create eight VMT values by county/roadway type/vehicle type that would sum to the original VMT value at the county/roadway type level of detail.
c. Allocation of VMT by Month
The resulting annual county-level, vehicle, and roadway type-specific VMT data were temporally allocated to months during the emission calculations. National Acid Precipitation Assessment Program (NAPAP) temporal allocation factors were used to apportion the VMT to the four seasons. Monthly VMT data were obtained using a ratio between the number of days in a month and the number of days in the corresponding season. These temporal factors are shown in Table II-4. Several States provided some leve l of information on temporal adjustment factors for their VMT. These data were not used in this draft version of the 2002 VISTAS emission inventory due to time constraints. However, a ny State or locally supplied temporal adjustment factors will be included in the final versi on of the 2002 VISTAS onroad emission inventory.7Table II-4. Default VMT Seasonal and Monthly Temporal Allocation FactorsRoadway Seasonal VMT FactorsVehicle Type Roadway Type Winter Spring Summer FallLDV,LDT,MC Rural0.2160 0.2390 0.2890 0.2560LDV,LDT,MC Urban0.2340 0.2550 0.2650 0.2450HDV All 0.2500 0.2500 0.2500 0.2500Monthly VMT FactorsVehicle Type Roadway Type Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov DecLDV,LDT,MC Rural 0.0744 0.0672 0.0805 0.07790.0805 0.0942 0.0974 0.09740.0844 0.0872 0.0844 0.0744LDV,LDT,MC Urban 0.0806 0.0728 0.0859 0.0832 0.08590.0864 0.0893 0.0893 0.0808 0.0835 0.0808 0.0806HDV All 0.0861 0.0778 0.08420.0815 0.0842 0.0815 0.0842 0.0842 0.0842 0.0852 0.0824 0.0861

## 8 

# B. 2002 ONROAD EMISSION FACTOR DEVELOPMENT USING MOBILE6.2

The onroad emission factors used in the calculation of the VISTAS 2002 onroad emission inventory were generated using EPA’s MOBILE6.2 emission factor model. In the development of the MOBILE6.2 input files, Pechan attempted to include as much of the relevant data supplied by the State and local agencies as possible, while at the same time, maintaining a generally similar overall structure to the MOBILE6.2 input files, such that the output emission factors could easily be matched to the appropriate VMT values. This section first discusses the overall general structure of the MOBILE6.2 input files. This is followed by details explaining how this general structure was adapted to include the State and local agency data and summaries of the types of data provided by each agency.

1. General MOBILE6.2 File Structure
Each MOBILE6.2 input file is divided into three sections: the header section, the run data section, and the scenario section. Information contained in the header section is primarily related to defining the output format and content desired by the user. For the processing of the VISTAS emission calculations, the database output format, aggregated to the daily level, was the desired output format. In addition, for proper modeling of the VOC emissions, it was desired to calculate the exhaust VOC emissions separately from the evaporative VOC emissions. However, within the constraints of MOBILE6.2 in the daily aggregated database output format, it is not possible to obtain evaporative and exhaust VOC emission factors broken out separately within each scenario. It is also not possibl e to obtain emission factors for both PM 10 

## and PM 2.5 

## within a single MOBILE6.2 scenario. Therefore, two sets of MOBILE6.2 input files were created—one set to model VOC exhaust, NO x 

## , CO, SO 2 

## , PM 10 

## , and NH 3 

## emission factors and a second set to model VOC evaporative and PM 2.5 

## emission factors. Figure II-1 illustrates the header section of a sample VISTAS MOBILE6.2 input file used to generate the VOC exhaust, NO x 

## , CO, SO 2 

## , PM 10 

## , and NH 3 

## emission factors. Similarly, Figure II-2 illustrates the header section of a sample VISTAS MOBILE6.2 input file used to generate the VOC evaporative and PM 2.5 

## emission factors. The primary difference between these tw o header sections is in the selection of the emission types included, using the DATABASE EMISSIONS command and in the selection of the pollutants to be included in the output. In Figure II-1, having the first two flags set to “2” following the DATABASE EMISSIONS command i ndicates that the startup and running exhaust emission factor components will be included in the output emission factor table. In Figure II-2, the last six flags of the DATABASE EMISSIONS command line are set to “2” to obtain the evaporative emission factor components in the emission factor output file. In Figure II-2, the pollutants SO 2 

## and NH 3 

## are eliminated from the PARTICULATES command line, as the emission factors for these pollutants will be reported in the output file resulting from the file shown in Figure II-1.

## 9 MOBILE6 INPUT FILE : > HEADER 01 0012002 - EXHAUST - PM 10.0
REPORT FILE : Vistas02/Output02/V0100110.TXT REPLACE DATABASE OUTPUT : WITH FIELDNAMES : DAILY OUTPUT : DATABASE EMISSIONS : 2211 1111 PARTICULATES : SO4 OCARBON ECARBON GASPM LEAD SO2 NH3 BRAKE TIRE AGGREGATED OUTPUT : EMISSIONS TABLE : Vistas02/TB1_02/V0100110.TB1 REPLACE

MOBILE6 INPUT FILE : > HEADER 01 0012002 - EVAPORATIVE - PM 2.50
REPORT FILE : Vistas02/Output02/V0100125.TXT REPLACE DATABASE OUTPUT : WITH FIELDNAMES : DAILY OUTPUT : DATABASE EMISSIONS : 1122 2222 POLLUTANTS : HC PARTICULATES : ECARBON SO4 OCARBON GASPM LEAD BRAKE TIRE AGGREGATED OUTPUT : EMISSIONS TABLE : Vistas02/TB1_02/V0100125.TB1 REPLACE



## The next section of the MOBILE6 input files is the run data section. This section includes data that applies to all scenarios in the input file. Figure II-3 shows an example of this section for a county using default data. The only commands included in this example tell MOBILE6 that the HC emission factors should be expressed in term s of VOC and that refueling emission factors should be excluded from the output. It should be noted that refueling emissions were calculated using a separate set of input files, but were excluded from the onroad input files here since refueling emissions are included in the area sour ce inventory rather than the onroad inventory. Chapter IV discusses the onroad refueling MOBI LE6 input files and emission calculations. Comments in Figure II-3 indicate that this input file is using default registration distributions and diesel sales fractions. For any input files that represent counties for which registration distribution, diesel sales fractions, or trip length di stributions have been provided or that have an inspection and maintenance (I/M) program, anti-tampering program (ATP), or low emission vehicle program in place in 2002, additional inputs are required in the run data section of the MOBILE6.2 input file. Figure II-4 shows an example of an input file including all of these data. Some of these data inputs are included directly in the MOBILE6.2 input file, while other data are contained in external text files that are named by the commands in the run data section. For questions regarding the specifics of any of the MOBILE6 input commands listed, the MOBILE6 User’s Guide should be consulted.

Figure II-1. Header Section of MOBILE 6.2 Input File Including VOC Exhaust and PM 10 

## Emission Factors

Figure II-2. Header Section of MOBILE 6.2 Input File Including VOC Evaporative and PM 2.5 

## Emission Factors

## 10 RUN DATA :
>

EXPRESS HC AS VOC : NO REFUELING :
* MOBILE6 Default Registration Distributions Applied * MOBILE6 Default Diesel Sales Fractions Applied

RUN DATA :
>

EXPRESS HC AS VOC : NO REFUELING :
REG DIST : Vistas02\ExtFiles\R02_ARLI.RDT

* Diesel Sales Fractions Source File - E:\TrendsM6_New\Vistas02\ExtFiles\D02_ARLI.DSF DIESEL FRACTIONS : 0.0012 0.0023 0.0026 0.0027 0.0029 0.0015 0.0008 0.0011 0.0001 0.0006 0.0013 0.0015 0.0006 0.0014 0.0006 0.0099 0.0087 0.0446 0.0685 0.0857 0.1922 0.1481 0.1132 0.0959 0.0126 0.0056 0.0221 0.0167 0.0235 0.0126 0.0119 0.0206 0.0136 0.0155 0.0127 0.0246 0.0206 0.0222 0.0184 0.0227 0.0115 0.0310 0.0568 0.0508 0.1211 0.1077 0.2126 0.0711 0.0286 0.0176 0.0056 0.0221 0.0167 0.0235 0.0126 0.0119 0.0206 0.0136 0.0155 0.0127 0.0246 0.0206 0.0222 0.0184 0.0227 0.0115 0.0310 0.0568 0.0508 0.1211 0.1077 0.2126 0.0711 0.0286 0.0176 0.0126 0.0126 0.0126 0.0126 0.0126 0.0126 0.0126 0.0115 0.0111 0.0145 0.0115 0.0129 0.0096 0.0083 0.0072 0.0082 0.0124 0.0135 0.0169 0.0209 0.0256 0.0013 0.0006 0.0011 0.0001 0.0126 0.0126 0.0126 0.0126 0.0126 0.0126 0.0126 0.0115 0.0111 0.0145 0.0115 0.0129 0.0096 0.0083 0.0072 0.0082 0.0124 0.0135 0.0169 0.0209 0.0256 0.0013 0.0006 0.0011 0.0001 0.1998 0.1998 0.1998 0.1998 0.1998 0.1998 0.1998 0.2578 0.2515 0.3263 0.2784 0.2963 0.2384 0.2058 0.1756 0.1958 0.2726 0.2743 0.3004 0.2918 0.2859 0.0138 0.0000 0.0000 0.0000 0.6774 0.6774 0.6774 0.6774 0.6774 0.6774 0.6774 0.7715 0.7910 0.8105 0.8068 0.8280 0.8477 0.7940 0.7488 0.7789 0.7842 0.6145 0.5139 0.5032 0.4277 0.0079 0.0000 0.0000 0.0001 0.8606 0.8606 0.8606 0.8606 0.8606 0.8606 0.8606 0.8473 0.8048 0.8331 0.7901 0.7316 0.7275 0.7158 0.5647 0.3178 0.2207 0.1968 0.1570 0.0738 0.0341 0.0414 0.0003 0.0000 0.0000 0.4647 0.4647 0.4647 0.4647 0.4647 0.4647 0.4647 0.4384 0.3670 0.4125 0.3462 0.2771 0.2730 0.2616 0.1543 0.0615 0.0383 0.0333 0.0255 0.0111 0.0049 0.0060 0.0000 0.0000 0.0000 0.6300 0.6300 0.6300 0.6300 0.6300 0.6300 0.6300 0.6078 0.5246 0.5767 

## Figure II-3. Run Data Secti on of a MOBILE6.2 Input File

Figure II-4. Run Data Section of a MOBI LE6.2 Input File with Significant Local Inputs

## 11 0.5289 0.5788 0.5617 0.4537 0.4216 0.4734 0.4705 0.4525 0.4310 0.3569 0.3690 0.4413 0.3094 0.1679 0.1390 0.8563 0.8563 0.8563 0.8563 0.8563 0.8563 0.8563 0.8443 0.7943 0.8266 0.7972 0.8279 0.8177 0.7440 0.7184 0.7588 0.7567 0.7431 0.7261 0.6602 0.6717 0.7344 0.6107 0.4140 0.3610 0.9992 0.9992 0.9992 0.9992 0.9992 0.9992 0.9992 0.9989 0.9987 0.9989 0.9977 0.9984 0.9982 0.9979 0.9969 0.9978 0.9980 0.9979 0.9976 0.9969 0.9978 0.9982 0.9974 0.9965 0.9964 1.0000 1.0000 1.0000 1.0000 1.0000 1.0000 1.0000 1.0000 1.0000 1.0000 1.0000 1.0000 1.0000 1.0000 1.0000 1.0000 1.0000 1.0000 1.0000 1.0000 1.0000 1.0000 1.0000 1.0000 1.0000 0.9585 0.9585 0.9585 0.9585 0.9585 0.9585 0.9585 0.8857 0.8525 0.8795 0.9900 0.9105 0.8760 0.7710 0.7502 0.7345 0.6733 0.5155 0.3845 0.3238 0.3260 0.2639 0.0594 0.0460 0.0291

> ANTI-TAMP PROG : E:\TrendsM6_New\Vistas02\ExtFiles\VA_ATP2002.ATP ANTI-TAMP PROG : 89 68 50 22222 21111111 1 12 098. 22112222

> Exhaust I/M - IDLE test program #1 I/M PROGRAM : 1 1983 2050 2 TRC 2500/IDLE I/M MODEL YEARS : 1 1968 1980 I/M VEHICLES : 1 22222 21111111 1 I/M STRINGENCY : 1 35.0 I/M COMPLIANCE : 1 98.0 I/M WAIVER RATES : 1 2.0 2.0
> Exhaust I/M - ASM final program #2 I/M PROGRAM : 2 1983 2050 2 TRC ASM 2525/5015 PHASE-IN I/M MODEL YEARS : 2 1981 2050 I/M VEHICLES : 2 22222 11111111 1 I/M STRINGENCY : 2 35.0 I/M COMPLIANCE : 2 98.0 I/M WAIVER RATES : 2 2.0 2.0 I/M EFFECTIVENESS : 0.94 0.94 0.94

> Exhaust I/M - IDLE test program #1 I/M PROGRAM : 3 1983 2050 2 TRC 2500/IDLE I/M MODEL YEARS : 3 1981 2050 I/M VEHICLES : 3 11111 21111111 1 I/M STRINGENCY : 3 35.0 I/M COMPLIANCE : 3 98.0 I/M WAIVER RATES : 3 2.0 2.0

> Evap I/M - Gas Cap test program #3 I/M PROGRAM : 4 1998 2050 2 TRC GC I/M MODEL YEARS : 4 1973 2050 I/M VEHICLES : 4 22222 21111111 1 I/M COMPLIANCE : 4 98.0 I/M WAIVER RATES : 4 2.0 2.0
94+ LDG IMP : Vistas02\ExtFiles\NLEVNE.D

> WeekDay Trip Length Distribution WE DA TRI LEN DI : Vistas02\ExtFiles\WeekTLD2.wdt

## 12 The third and final section of the MOBILE6.2 input files contains the scenario data. For this VISTAS inventory, each speed and road type comb ination or speed distribution were modeled in twelve consecutive scenarios representing the temperature and fuel properties applicable in each month. Thus, if a State agency supplied an average speed/road type combination for each of the 12 HPMS road categories, the corresponding MOBILE6.2 input file would have 144 scenarios. The first scenario would represent January temperature and fuel conditions at the speed and MOBILE6 roadway type for the first speed/roadway type provided (typically rural interstates). This would be followed by the February scenario modeled for the same speed and roadway type, and so on through the twelfth scenario representing December conditions for the same speed and roadway type combination.
Figure II-5 illustrates a sample scenario from one of the VISTAS MOBILE6.2 input files. This is the first scenario in the file—therefore, it represents January temperature and fuel conditions. The month of a given scenario in the VISTAS MOBILE6.2 input files can be determined by the last two digits of the SCENARIO RECORD command line. In this case, the last two digits are “01” indicating January. It should be noted that the only options for the EVALUATION MONTH command are “1” indicating January or “7 ” indicating July. For the VISTAS input files, the EVALUATION MONTH was set to “1” for all months from January through June and to 7 for months from July through December. When this flag is set to “1”, it indicates that MOBILE6 will use a January registration distribution. When the flag is set to “7”, MOBILE6 ages the registration by a half year, applying a half year of fleet turnover to the distribution. The EVALUATION MONTH setting can also affect the re ductions from reformulated gas programs. However, by including the SEASON command, as shown in Figure II-5, the EVALUATION MONTH flag setting will not affect reformulated gasoline reductions. With the SEASON flag set to “2”, winter reformulated gasoline rules will be applied in areas with a reformulated gas program modeled (using the FUEL PROGRAM command). Summer reformulated gas rules and reductions will be applied when the SEASON flag is set to “1” if reformulated gas has been modeled. In all of the VISTAS input files, the SEASON flag was included for all areas, whether or not a reformulated gasoline program was modeled. This flag has no effect when the FUEL PROGRAM command is not used. The SEASON flag was set to “1” for the months of May through September and to “2” for the remaining months.

SCENARIO RECORD : 010010215.0_M01 >FV FILE: SCENARIO: 1 CALENDAR YEAR : 2002 EVALUATION MONTH : 1 MIN/MAX TEMPERATURE: 38.0 60.0 ALTITUDE : 1 PARTICULATE EF : PMGZML.CSV PMGDR1.CSV PMGDR2.CSV PMDZML.CSV PMDDR1.CSV PMDDR2.CSV SEASON : 2 AVERAGE SPEED : 15.0 Arterial FUEL RVP : 12.5 PARTICLE SIZE : 10.0 DIESEL SULFUR : 500.0 

## Figure II-5. Sample Scenario fo r a Typical MOBI LE6.2 Input File

## 13 Local speed data were provided by the agencies in Georgia, Kentucky, North Carolina, Tennessee, and Virginia. A set of 12 monthly scenarios was developed for each speed input for these States, with one exception. The Northern Kentucky (Boone County, Campbell County, and Kenton County) and Jefferson County, Kentucky i nputs were speed distribution files, rather than average speeds by individual roadway types (one for Northern Kentucky and one for Jefferson County, Kentucky). In this case, only 12 scenarios were modeled in total in the Jefferson County and Northern Kentucky input f iles, with the Jefferson County or Northern Kentucky speed distribution referenced in each scenario, respectively. No speed information was provided for Alabama, Florida, Mississippi, South Carolina, or West Virginia. The average speeds modeled in these files were the default speeds used in the NEI. These speeds are shown in Table II-5 and vary by both roadway type a nd vehicle category. It should be noted that several agencies provided speed information for ramps. Since the VMT data file is organized by SCC and no SCC currently exists for ramp VMT, the ramp speed information could not be used directly. In some cases, the fraction of VMT occurring on ramps was provided. In these cases, this information was combined with the freeway speeds, following the guidance in the MOBILE6 user’s guide to determine the overall freeway speed including the ramp speed, at 34.6 mph (the assumed value for ramp speeds in MOBILE6), and the fraction of VMT occurring on the ramps.
Table II-5. Default Speeds Modeled by Road Type and Vehicle Type (mph)

Speed (mph) and MOBILE6 Road Type
HPMS Road Type Light Duty Vehicles Light Duty Trucks Heavy Duty Trucks Rural Interstate 60 Freeway 55 Freeway 40 Freeway Rural Principal Arterial 45 Arterial 45 Arterial 35 Arterial Rural Minor Arterial 40 Arterial 40 Arterial 30 Arterial Rural Major Collector 35 Arterial 35 Arterial 25 Arterial Rural Minor Collector 30 Arterial 30 Arterial 25 Arterial Rural Local 30 Arterial 30 Arterial 25 Arterial Urban Interstate 45 Freeway 45 Freeway 35 Freeway Urban Other Freeway and Expressway 45 Freeway 45 Freeway 35 Freeway Urban Principal Arterial 20 Arterial 20 Arterial 15 Arterial Urban Minor Arterial 20 Arterial 20 Arterial 15 Arterial Urban Collector 20 Arterial 20 Arterial 15 Arterial Urban Local Local Local Local



## Another optional input included in the scenario section of the MOBILE6 input files is the VMT mix by 16 MOBILE6 vehicle categories. These vehicle categories are based on the 28 MOBILE6 vehicle categories, but with gasoline and diesel vehicles of the same weight class combined together. When no information was provided on VMT mix, the MOBILE6 defaults were used. Local VMT mix information provided by Tennessee, Virginia, and Jefferson County, Kentucky were included in the MOBILE6.2 input files. In some cases, the same VMT mix was applied to all scenarios. In other cases, the VMT mixes were specific to roadway type, so the VMT mix would vary according to the roadway type being represented in the scenario.

## 14 

# C. 2002 ONROAD EMISSION INVENTORY CALCULATIONS
Once the MOBILE6.2 input files were set up and run through the MOBILE6.2 model, onroad emissions were calculated by multiplying the monthly VMT for a given county, roadway type, and vehicle type by the emission factor modele d for the same month, county, vehicle type and roadway type. Because the MOBILE6.2 input files were set up to create output files in the form of database tables, the output is provided by each of the 28 MOBILE6 vehicle types. Thus, the emission factors first were aggregated to the eight vehicle categories included in the VMT files. This was done using the VMT Fraction data provide d in each of the MOBILE6 output files. For each of the MOBILE6 vehicle types included in one of the eight vehicle types needed, the VMT fractions were renormalized within that category. These eight vehicle categories are sometimes referred to as the MOBILE5 vehicle categories. For example, the LDGT1 and LDGT2 MOBILE6 vehicle categories are both included in the MOBILE5 LDGT1 category. In this case, the MOBILE6 LDGT1 VMT fraction was divided by the sum of the MOBILE6 LDGT1 and LDGT2 VMT fractions. The same was done with the MOBILE6 LDGT2 VMT fraction, so that the renormalized MOBILE6 LDGT1 and LDGT2 VM T fractions should now sum to 1. Next, these normalized VMT fractions were multiplied by the corresponding MOBILE6 emission factor and all of these weighted emission factor s for a given scenario, within a MOBILE5 vehicle category were summed to obtain the weighted emission factors at the MOBILE5 vehicle category level. The VMT fractions included in the MOBILE6 output files are affected by the registration distribution, diesel sales fracti ons, and VMT mixes supplied in the MOBILE6.2 input files. Areas that used the MOBILE6 defaults for each of these inputs should all have the same VMT fractions, although even in these cases, there are two sets of VMT fractions—one for the months from January through June and another for the months July through December. This occurs due to the aging of the registration distribution caused by the use of the EVALUATION MONTH flag, as discussed above. These emi ssion factors, now at the MOBILE5 vehicle category level, were multiplied by the corresponding VMT values to obtain monthly emissions by county, roadway type, and vehicle category.



# D. DATA PROVIDED BY STATE AND LOCAL AGENCIES
The sections above describe some of the data that was supplied by the VISTAS State and local agencies for use in the development of the 2002 onroad emission inventory. Tables II-6 through II-15 summarize the data supplied by each agency in a consistent fashion. These tables primarily list the data that were actually used in this analysis. This section provides additional information on the data supplied by these agencies as well discussing why some of the data supplied could not be used.

## 15 Table II-6. Summary of Onroad Data Provided by Alabama

Data Element Data Supplied by Responsible Agency VMT Data 2002 actual daily VMT by county/road type MOBILE6 Input Files MOBILE5 Input Files VMT Mix Information Counties by Temperature Region Monthly Temperatures Monthl y 2002 temperatures by county RVP Data March-September RVP values Speed Data Registration Data Fuel Information I/M Program Information N/A Other



## Table II-7. Summary of Onroad Data Provided by Florida

Data Element Data Supplied by Responsible Agency VMT Data 2002 actual daily VMT by county/road type MOBILE6 Input Files MOBILE5 Input Files VMT Mix Information Counties by Temperature Region Supplied counties in each of 3 temperature regions Monthly Temperatures RVP Data Summer RVP values provided Speed Data Registration Data Fuel Information I/M Program Information N/A Other

## 16 Table II-8. Summary of Onroad Data Provided by Georgia

Data Element Data Supplied by Responsible Agency VMT Data 2002 actual average annual daily VMT by county and functional classification prepared by Georgia DOT MOBILE6 Input Files Provided MOBILE6 sample input files MOBILE5 Input Files VMT Mix Information Counties by Temperature Region Monthly Temperatures RVP Data Provided summer RVP values Speed Data Provided 2002 statewi de speeds by road type (speeds based on VMT-weighted average speeds, from a 2002 loaded highway network for the 13-county Atlanta area) Registration Data Provided one MOBILE 6 registration distribution for 13- county Atlanta area and one MOBILE6 registration distribution for rest-of-state Fuel Information Provided information on Georgia gasoline program, applied to 25 counties I/M Program Information Provided I/M inputs for 13-county Atlanta area in MOBILE6 format Other Provided VMT temporal adj ustment factors by month and day of week for each road type (not used in the 01/04 inventory)

## 17 Table II-9. Summary of Onroad Data Provided by Kentucky

Data Element Data Supplied by Responsible Agency VMT Data 2002 actual daily VMT by county/road type MOBILE6 Input Files Provided sample MO BILE6 input files for several counties MOBILE5 Input Files VMT Mix Information Counties by Temperature Region Provided temperature stations to be used for several counties Monthly Temperatures RVP Data Provided summer RVP for several counties Speed Data Provided average speed by road type for several county groupings Registration Data Fuel Information Verified counties in reformulated gasoline program I/M Program Information I/M program information provided Other Jefferson County, Kentucky Data Element Data Supplied by Responsible Agency VMT Data 2002 summer day VMT from TD M by county/road type/vehicle type
MOBILE6 Input Files Provided MOBILE6 input files repres enting the four different vehicle control combinations found in Jefferson County MOBILE5 Input Files VMT Mix Information Provided Jefferson County VMT mix in MOBILE6 format Counties by Temperature Region Monthly Temperatures Provided 2002 actual monthly temperature data for Louisville area RVP Data Provided summer and winter RVP values Speed Data Provided speed distribution file for Jefferson County
Registration Data Provided registration distribution for Jefferson County in MOBILE6 format Fuel Information Reformulated gasoline modeled I/M Program Information I/M program information provided Other Provided absolute humidity data Boone County, Campbell County, and Kenton County, Kentucky Data Element Data Supplied by Responsible Agency VMT Data 2002 actual daily VMT by county/road type MOBILE6 Input Files MOBILE5 Input Files Provided MOBILE5 input file for Northern Kentucky counties VMT Mix Information Counties by Temperature Region Monthly Temperatures RVP Data Provided summer and winter RVP values Speed Data Provided speed distribution file for Northern Kentucky
Registration Data Provided registration distribution for Northern Kentucky in MOBILE6 format—LDGVs and LDGT1s only Fuel Information Reformulated gasoline modeled I/M Program Information I/M program inform ation extracted from MOBILE5 input file

Other Provided Northern Kentucky VMT di stributions by facility type and by hour in MOBILE6 format

## 18 Table II-10. Summary of Onroad Data Provided by Mississippi

Data Element Data Supplied by Responsible Agency VMT Data Provided 2002 actual annual VM T by county/road type/vehicle type MOBILE6 Input Files MOBILE5 Input Files VMT Mix Information Counties by Temperature Region Monthly Temperatures RVP Data Provided statewide RVP by season Speed Data Registration Data Fuel Information I/M Program Information N/A Other


## Table II-11. Summary of Onroad Data Provided by North Carolina

Data Element Data Supplied by Responsible Agency VMT Data 2002 actual daily VMT by county/road type MOBILE6 Input Files MOBILE5 Input Files VMT Mix Information Counties by Temperature Region Indicated counties within each of several temperature regions in state Monthly Temperatures RVP Data Speed Data Provided average speed data by road type for several groups of counties and rest-of-state Registration Data Provided registration data for several groups of counties and rest-of-state based on 2001 data Fuel Information I/M Program Information Provided written description of I/M program Other

## 19 Table II-12. Summary of Onroad Data Provided by South Carolina

Data Element Data Supplied by Responsible Agency VMT Data 2002 actual annual VMT by county/road type MOBILE6 Input Files MOBILE5 Input Files VMT Mix Information Counties by Temperature Region Supplied counties in each of 7 temperature regions Monthly Temperatures RVP Data Speed Data Registration Data Fuel Information I/M Program Information N/A Other


## Table II-13. Summary of Onroad Data Provided by Tennessee

Data Element Data Supplied by Responsible Agency VMT Data 2002 actual daily VMT by county/road type
MOBILE6 Input Files Provided MOBILE6 input file s for groups of counties covering state MOBILE5 Input Files VMT Mix Information Provided VMT mix fractions by road type Counties by Temperature Region Monthly Temperatures RVP Data Provided summer RVP information
Speed Data Provided average speed data by road type for groups of counties Registration Data Provided registration data for most counties Fuel Information I/M Program Information Provided in MOBILE6 input files Other

## 20 Table II-14. Summary of Onroad Data Provided by Virginia

Data Element Data Supplied by Responsible Agency VMT Data 1999 actual annual VMT by county/road type/vehicle type MOBILE6 Input Files Provided MOBILE6 i nput files for representative counties MOBILE5 Input Files VMT Mix Information Counties by Temperature Region Provided listing of counties within each of several temperature regions Monthly Temperatures RVP Data Provided summer RVP data Speed Data Speed data provided for each VMT record Registration Data 2002 county-level regi stration data provided for nonattainment counties Fuel Information Verified counties in reformulated gasoline program I/M Program Information I/M and ATP inputs prov ided in MOBILE6 formats; verified counties that implement I/M Other LEV progam modeled statewide; provided diesel sales fractions



## Table II-15. Summary of Onroad Data Provided by West Virginia

Data Element Data Supplied by Responsible Agency VMT Data 2002 actual annual VMT by county/road type/vehicle type MOBILE6 Input Files Supplied several sample MOBILE6 input files MOBILE5 Input Files VMT Mix Information VMT data included vehicle type splits Counties by Temperature Region Supplied counties in each of 4 temperature regions Monthly Temperatures RVP Data Supplied summer RVP value statewide Speed Data Supplied speed data in MOBILE6 input files--speed data determined to be inappropriate for this analysis Registration Data Fuel Information I/M Program Information N/A Other

## 21 1. Temperature
The default average daily maximum and minimum temperature data for each month used in this analysis was obtained from the National Climatic Data Center. This temperature data was actual 2002 data. It should be noted that a number of agencies provided information on ozone season or summer temperatures. This information could not be used in this analysis, as the ozone season temperature data are based on several years of temperature data and do not represent the average daily minimum and maximum monthly temperatures that were needed for this analysis. Information was provided by Alabama, Kentucky, North Carolina, South Carolina, Virginia, and West Virginia related to monthly temperature. In some cases, this data divided the counties within the State into several temperature regions and listing a city that should be used for obtaining the temperature data. In these cases, a temperature station from the National Climatic Data Center database was selected from the de sired city, and this corresponding temperature set was applied to the counties listed by the States. Several of the States provided their own full set of 2002 temperature data either Statewide or by county. These data were included in the analysis, replacing the default temperature data for those States.
2. I/M and ATP Programs
Several agencies provided I/M and ATP inputs in the form of MOBILE5 input files. Pechan converted these inputs to MOBILE6 inputs, following the guidance in the MOBILE6 user’s guide. Agencies that provided the data in MOBILE5 format should review the MOBILE6 I/M and ATP inputs carefully to make sure that the conversions fully capture the actual programs as they were implemented in 2002. In addition, from information provided by North Carolina, Tennessee, and Jefferson County, Kentucky, the I/M and ATP programs should only be applied to a portion of the VMT in the corresponding counties. For the North Carolina and Tennessee I/M counties, duplicate MOBILE6.2 input files were created that eliminate the I/M and ATP programs. The VMT from these counties was divided according to the fraction of the VMT subject to I/M and the fraction of the VMT not subject to I/M. These fractions were provided by the corresponding agencies in North Carolina and Tennessee. The VMT data for each I/M county was then divided according to these VMT fractions to obtain one set of VMT for the portion of vehicles subject to I/M and another set for those not subject to I/M. The emission factors from the I/M files were multiplied by the portion of the VMT subject to I/M while the emission factors from the files without the I/M were multiplied by the remaining portion of the VMT. In Jefferson County, Kentucky, a similar pro cedure was followed. However, in this case, the county also has a significant portion of VMT from vehicles registered in Indiana that are not subject to I/M or that do not have reformulat ed gasoline. Thus, the Jefferson County VMT was divided into four subsets and four MOBILE6 i nput files were developed representing the four groups of vehicle types traveling in the county.
3. RVP and Fuel Programs
Default RVP by county and month were obtained from the data used in the 2002 NEI. The NEI fuel data are based on year 2000 fuel survey data for January and July, with data for intermediate months calculated by interpolation. RVP data for July were applied from May through September, the months when Phase II RVP regulations are in effect. For States that supplied

## 22 July, summer, or ozone season RVP values, these values were also applied from May through September. If winter RVP values were supplied, these values were applied directly in each of the remaining months. As mentioned above, reformulated gasoline programs were modeled where appropriate. Georgia provided additional fuel inputs to capture the RVP and sulfur content values of its low sulfur gasoline program.


# III. NONROAD METHODS AND DATA

A. NONROAD MODEL CATEGORIES
Pechan used EPA’s draft NONROAD2002a model to generate 2002 annual emissions for the majority of nonroad engines. To improve the accuracy of these model runs, we asked State/ Local/Tribal (S/L/T) contacts to provide seasonal or monthly gasoline Reid Vapor Pressure (RVP) and temperature; appropriate data on reformulated gasoline (RFG), oxygenated fuel and Stage II programs, and diesel fuel sulfur levels. In addition, to improve the activity data inputs, we asked whether S/L/T agencies had collected information on equipment populations or activity (e.g., hours of use or load factors) to use in place of default populations in the NONROAD model. No S/L/T agencies provided activity data to replace the model defaults.
Seasonal average RVP and average, maximum and minimum temperature values were calculated based on the county-level, monthly RVP and temperature data set prepared for onroad mobile sources. Information on RFG programs and oxyge nated fuels programs obtained for the onroad mobile sector was also used. In July 2003, Pechan distributed the input values (RVP, percent O2, temperature, and Stage II control efficiency) to be used for the draft NONROAD model 2002 inventory for review and comment by the VISTAS S/L/T agencies. Pechan obtained comments from the S/L/T agencies listed in Table III-1.
Table III-1. Summary of Comments by S/L/T Agencies on NONROAD Model Input Values Distributed in July 2003

State Comment Alabama Provided region specific data to repl ace the statewide default values for RVP and ambient temperature Georgia Changed oxygen weight percent to zero for all counties Kentucky No Stage II programs in Bullitt and Oldham Counties Tennessee Revised RVP value for Davidson County Mississippi Revised statewide RVP by season Virginia No Stage II program in Charles City County


## Additional comments on the August 2003 NONROAD model temperature and RVP inputs were incorporated for consistency with data submitted for the onroad mobile modeling (e.g., North Carolina). In addition, the State of West Virg inia provided revised geographic allocation files for certain nonroad categories to improve upon the NONROAD model’s default county allocation.
Using the inputs shown in the file “VISTA S NONROAD County Inputs.xls,” Pechan prepared seasonal option files for each of four seasons (winter, spring, summer, and autumn), and ran the

## 23 NONROAD model at the county level. Model default values were used for all other inputs, with the exception of diesel fuel sulfur. A value of 2,500 parts per million volume (ppmv) was used instead of the default 2,318 ppm, since the default represented a national average including California’s lower diesel fuel sulfur level. Pechan summed the seasonal results, and then processed the model output to develop a county-le vel, SCC-level annual emissions inventory for all pollutants except NH 3 

## .
The NH 3 

## emissions for NONROAD model categories were developed using the following procedures. OTAQ recently reviewed the basis of NH 3 

## data summarized in a report entitled, “A Study of the Potential Impact of Some Unregulated Motor Vehicle Emissions” (Harvey, 1983). In conducting this review, OTAQ performe d an analysis of the available light-duty noncatalyst engine data to develop defensible gasoline nonroad emission factors on a mg/gallon basis (Harvey, 2003). For both gasoline noncatalyst and diesel engines, fuel based emission factors were developed from emission factors expressed on a gram/mile basis by accounting for the reported fuel economy of each tested engine. For gasoline non-catalyst engines, this resulted in a value of 115.8 mg/gallon, which is applied to county-level fuel consumption estimates for 2-stroke gasoline, 4-stroke gasoline and liquified petroleum gas (LPG) equipment. From the diesel engine test data, a value of 83.3 mg/gall on was derived, which is applied to diesel fuel consumption estimates. County-level fuel consumption for these engines, expressed in gallons, is an output from EPA’s NONROAD model. 

# B. AIRCRAFT, COMMERCIAL MARINE VESSELS AND LOCOMOTIVES

For 2002 aircraft, commercial marine vessels (CMVs), and locomotives, Pechan used 1999 emission estimates developed for EPA’s 1999 NEI Version 2 as base year estimates for the VISTAS region. These categories are not incl uded in the NONROAD model, and are hereafter referred to as “other nonroad.” Pechan then incorporated revised S/L/T estimates summarized in Table III-2, using the replacement procedures summarized in Tables III-3a through III-3d. Pechan tracked changes by labeling the default 1999 NEI records as Version 2 (V2) and the revised S/L/T records as Version 3 (V3). In cases where PM2.5 estimates were not provided, they were developed using the following category-specific fractions applied to the available PM 10 

## emission estimates: 1) Aircraft: 0.69; 2) Locomotive: 0.90; and 3) CMV: 0.92 (EPA, 2002). Commercial marine adjustments are described in detail in the following section.

Table III-2. Summary of S/L/T Agency Data Incorporated into the Draft VISTAS 2002 Other Nonroad Inventory

State Description of Inventory Pollutants Alabama 1999 Locomotive emissions for Pickens and Tuscaloosa counties VOC, NO x 

### , and CO
Florida 2001 Aircraft, Locomotive and Commercial Marine Vessel emissions for Palm Beach County VOC, NO x 

### , CO, PM10, and SO x 

### Tennessee 1999 Aircraft and Locomotive emissions for Davidson County VOC, NO x 

### , CO, SO x 

### , and primary PM 10 

### Virginia 1999 Statewide Inventory for Aircraft, Locomotive and Commercial Marine Vessels VOC, NO x 

### , CO

## 24 Table III-3a. Replacement Procedur es for 1999 Locomotive Emissions for Pickens and Tuscaloosa County, Alabama

STATE_

FIPS COUNTY_ FIPS SCC Version Notes START_ DATE END_ DATE VOC NOX CO
01 107 2285002005 V3 7.73 179.7 22.81

01 107 2285002005 V2 Replace VOC, NOx, and CO emissions 19990101 19991231 1962.9 45643 5794.5
01 107 2285002010 V3 5.39 53.48 9.47

01 107 2285002010 V2 Replace VOC, NOx, and CO emissions 19990101 19991231 5.39 53.48 9.48
01 125 2285002005 V3 16.31 379.15 48.13

01 125 2285002005 V2 Replace VOC, NOx, and CO emissions 19990101 19991231 3384.9 78711.4 9992.6
01 125 2285002010 V3 9.29 92.15 16.33

01 125 2285002010 V2 Replace VOC, NOx, and CO emissions 19990101 19991231 9.29 92.15 16.3325Table III-3b. Replacement Procedures for 1999 Aircraft, Locomotive, and Commercial Marine Vessel Emissionsfor Palm Beach County, FloridaSTATE_FIPSCOUNTY_FIPSSCC VersionNotesSTART_DATEEND_DATEVOC NOX CO SO2PM10-PRIPM25-PRI12 099 2275000000 V3 Apply a Growth Factor to 2001state-supplied aircraft emissions tobackcast to 1999Estimate PM2.5-PRI off PM10-PRI19990101 19991231 470.39 805.94 4,121.41 1.98 0.0012 099 2275001000 V2 Delete all records for this SCC19990101 19991231 0.44 0.05 9.03 0 0.19 0.1312 099 2275020000 V2 Delete all records for this SCC19990101 19991231 79.1 275.5 330.6 26.3412 099 2275050000 V2 Delete all records for this SCC19990101 19991231 13.93 2.37 437.43 0.36 8.62 5.9512 099 2275060000 V2 Delete all records for this SCC19990101 19991231 9.23 1.19 212.32 0.11 4.55 3.1412 099 2280000000 V3 Apply a Growth Factor to 2001state-supplied cmv emissions tobackcast to 1999Estimate PM2.5-PRI off PM10-PRI19990101 19991231 10.42 115.60 0.97 9.94 33.9112 099 2280002100 V2 Delete all records for this SCC19990101 19991231 25.5 815.4 107.51 36.95 34.3 31.5512 099 2280002200 V2 Delete all records for this SCC19990101 19991231 0.22 7.05 0.93 0.32 0.3 0.2712 099 2280003100 V2 Delete all records for this SCC19990101 19991231 6.8 217.5 28.63 115.6 9.48 8.7312 099 2280003200 V2 Delete all records for this SCC19990101 19991231 0.06 1.93 0.25 1.43 0.11 0.112 099 2285002000 V3 Apply a Growth Factor to 2001state-supplied locomotive emissions tobackcast to 1999Estimate PM2.5-PRI off PM10-PRI19990101 19991231 28.19 658.78 83.64 48.09 15.5012 099 2285002006 V2 Delete all records for this SCC19990101 19991231 6.11 164.1 16.17 10.26 4.07 3.6612 099 2285002008 V2 Delete all records for this SCC19990101 19991231 0.45 12.15 1.2 0.76 0.3 0.2712 099 2285002009 V2 Delete all records for this SCC19990101 19991231 6.78 182.2 17.95 11.39 4.52 4.0712 099 2285002010 V2 Delete all records for this SCC19990101 19991231 3.75 64.36 6.77 3 1.64 1.471Palm Beach County provided emission estimates corresponding to 2001; as such, 2001 emission estimates were backcast to 1999 using growth factors presented in this reportbefore incorporation.

## 26 Table III-3c. Replacement Procedures for 1999 Aircraft and Locomotive Emissions for Davidson County, Tennessee

STATE_

FIPS COUNTY_ FIPS SCC Version Notes START_ DATE END_ DATE VOC NOX CO SO2 PM10- PRI PM25- PRI

47 037 2275000000 V3 Estimate PM2.5-PRI off PM10-PRI 19990101 19991231 232.125 634.35 1766 32.13 39.25

47 037 2275001000 V2 Delete all records for this SCC 19990101 19991231 1.7 0.2 35 0.02 0.75 0.52

47 037 2275020000 V2 Delete all records for this SCC 19990101 19991231 187.45 649.92 782.93 62.34

47 037 2275050000 V2 Delete all records for this SCC 19990101 19991231 4.72 0.8 148.3 0.12 2.92 2.02

47 037 2275060000 V2 Delete all records for this SCC 19990101 19991231 15.22 1.97 349.97 0.19 7.51 5.18

47 037 2285002000 V3 Estimate PM2.5-PRI off PM10-PRI 19990101 19991231 20.803 363.117 50.701 26.36 8.893

47 037 2285002006 V2 Delete all records for this SCC 19990101 19991231 31.91 857.26 84.46 53.6 21.27 19.15

47 037 2285002010 V2 Delete all records for this SCC 19990101 19991231 19.6 336.23 35.39 15.68 8.54 7.69

## 27 Table III-3d. Replacement Procedures for 1999 Aircraft, Locomotive, and

Commercial Marine Vessel Emissions for Sample Counties in Virginia

STATE_

FIPS COUNTY_ FIPS SCC Version Notes START_ DATE END_ DATE VOC NOX CO SO2 PM10- PRI PM25- PRI 51 001 2275001000 V3 19990101 19991231 3.47 0.78 3.74 51 001 2275001000 V2 Replace VOC, NOx, and CO emissions Keep SO2, PM10-PRI, and PM2.5-PRI emissions 19990101 19991231 0.31 0.04 6.38 0 0.14 0.09

51 013 2275020000 V3 19990101 19991231 145.821 992.23 1634.2 51 013 2275020000 V2 Replace VOC, NOx, and CO emissions Keep SO2 emissions 19990101 19991231 271.17 940.36 1132.7 90.2

51 001 2275050000 V3 19990101 19991231 1.25 0.21 39.34 51 001 2275050000 V2 Replace VOC, NOx, and CO emissions Keep SO2, PM10-PRI, and PM2.5-PRI emissions 19990101 19991231 0.25 0.04 7.81 0.01 0.15 0.11

51 001 2275060000 V3 19990101 19991231 0.05 0.01 1.26 51 001 2275060000 V2 Replace VOC, NOx, and CO emissions Keep SO2, PM10-PRI, and PM2.5-PRI emissions 19990101 19991231 1.47 0.19 33.8 0.02 0.72 0.5

51 670 2280002000 V3 Add SCC to the Inventory 19990101 19991231 3.3 18.16 6.94 51 670 2280002100 V2 Sum up SO2, PM10-PRI, and PM2.5-PRI emissions for SCCs 2280002100 and 2280002200 and add to SCC 280002000. After that, delete all records for SCC 2280002100 and 2280002200 19990101 19991231 10.12 323.52 42.66 14.7 13.61 12.52

51 670 2280002200 V2 Sum up SO2, PM10-PRI, and PM2.5-PRI emissions for SCCs 2280002100 and 2280002200 and add to SCC 2280002000. After that, delete all records for SCC 2280002100 and 2280002200 19990101 19991231 0.17 5.39 0.71 0.24 0.23 0.21

51 670 2280003000 V3 Add SCC to the Inventory 19990101 19991231 0.14 1.64 0 51 670 2280003100 V2 Sum up SO2, PM10-PRI, and PM2.5-PRI emissions for SCCs 2280003100 and 2280003200 and add to SCC 2280003000. After that, delete all records for SCC 2280003100 and 2280003200 19990101 19991231 2.7 86.31 11.36 45.9 3.76 3.46

51 670 2280003200 V2 Sum up SO2, PM10, and PM2.5 Emissions for SCCs 2280003100 and 2280003200 and add to SCC 2280003000. After that, delete all records for SCC 2280003100 and 2280003200 19990101 19991231 0.05 1.48 0.19 1.09 0.08 0.08

51 199 2283002000 V3 19990101 19991231 8.46 53.47 15.51 51 199 2283002000 V2 Replace VOC, NOx, and CO emissions 19990101 19991231 7.43 47.26 13.63 51 740 2285002005 V3 Add SCC to the Inventory 19990101 19991231 3.76 100.99 9.95 51 740 2285002006 V2 Sum up SO2, PM10-PRI, and PM2.5-PRI emissions for SCCs 2285002006 and 2285002007 and add to SCC 285002005. After that, delete all records for SCC 2285002006 and 2285002007. 1 19990101 19991231 0.7 18.77 1.85 1.17 0.47 0.42

51 740 2285002007 V2 Sum up SO2, PM10-PRI, and PM2.5-PRI emissions for SCCs 2285002006 and 2285002007 and add to SCC 285002005. After that, delete all records for SCC 2285002006 and 2285002007. 1 19990101 19991231 0.08 2.26 0.22 0.14 0.06 0.05

51 036 2285002010 V3 19990101 19991231 0.59 10.13 1.06 51 036 2285002010 V2 Replace VOC, NOx, and CO emissions Keep SO2, PM10-PRI, and PM2.5-PRI emissions 19990101 19991231 1.99 34.15 3.59 1.59 0.87 0.78

1 Other counties may also have emissions for SCCs 2285002008 and 2285002009. In these cases, sum up SO2, PM10-PRI, and PM2.5-PRI emissions for SCCs 2285002006, 2285002007, 2285002008, and 2285002009 and add to SCC 2285002005. After that, delete all records for SCC 2285002006, 2285002007, 2285002008, and 2285002009.

## 28 2. CMV Improvements
This section describes procedures for improving the spatial distribution of CMV emission estimates for the VISTAS region. States that share borders with non-VISTAS States along the Mississippi and Ohio Rivers have expressed concern about the representativeness of port emission estimates at a county-level. Revising the county-level emissions estimates would allow more accurate modeling of emissions in the VISTAS States.
Ideally, CMV emission estimates would be developed using local activity data that account for vessel type, engine type and mode of operation (cruise, maneuvering, and hotelling). Creating this type of “bottom-up” emission inventory require s a large amount of effort. Therefore, Pechan utilized port-specific emission estimates develope d for the 1999 NEI, distributed using a revised allocation methodology, which incorporates information on the number of port facilities in each county.

a. Current Allocation Method
The current 2002 VISTAS commercial marine inventory is based on EPA’s 1999 NEI Version 2.0, projected to 2002 using appropriate growth fact ors. State-supplied data were incorporated by EPA or by Pechan for some VISTAS States for this category, including Alabama, Virginia, West Virginia, and Palm Beach County, Florida.
The 1999 NEI estimated emissions for these categories according to the following SCCs:

SCC Descriptor 1 Descriptor 3 Descriptor 6 Descriptor 8 2280002100 Mobile Sources Marine Vessels, Commercial Diesel Port emissions 2280002200 Mobile Sources Marine Vessels, Commercial Diesel Underway emissions 2280003100 Mobile Sources Marine Vessels, Commercial Residual Port emissions 2280003200 Mobile Sources Marine Vessels, Commercial Residual Underway emissions


## For the 1999 NEI, commercial marine diesel emissions were developed by obtaining 2000 emission estimates for all pollutants except SO 2 

## from OTAQ’s marine diesel regulatory background documentation ( Draft Regulatory Impact Analysis - Control of Emissions from Compression-Ignition Marine Engines ). To estimate emissions for 1999, 2000 estimates were backcast using growth factors obtained from the draft RIA cited above. Steam-powered residual CMV emission estimates were developed by obtai ning fuel usage data from OTAQ and applying fuel-based emission factors (EPA, 1989). A similar method was used for diesel SO 2 

## emissions. National diesel usage was estimated assuming a sulfur content of 0.25 percent and EPA emission factors (EPA, 2002).
National diesel emissions were disaggregated into port and underway emissions estimates based on the assumption that 75 percent of distillate fuel is consumed within the port, while the remaining fuel is consumed while underway, consistent with EPA guidance. National residual emissions were disaggregated into port and underway emissions estimates based on the assumption that 25 percent of residual fuel is consumed within the port, while the remaining fuel is consumed while underway (EPA, 1989).

## 29 To allocate to counties, port emissions were assigned to the 150 largest U.S. ports based on activity obtained from the U.S. Army Corps of Engineers (USACE). The percentage of total traffic for each port was calculated by dividing th e port-level traffic by the total traffic. Emissions for each port were then assigned to a single county.
Underway emissions are assigned to counties based on a county = s shipping lane traffic. The Bureau of Transportation Statistics’ (BTS = ) National Transportation Atlas Databases-1999 contains data on the thousand tons per mile traveled for each shipping lane link in the United States (BTS-CD26). Where navigable rivers fo rm a county or State boundary, the shipping lane traffic is proportioned to individual counties based on the length of shoreline that is shared. For example, if two counties share a navigable river, and both counties have the same length of shoreline, the shipping traffic is split evenly between the two counties. Shipping lanes that are not within counties, for example in the ocean, are associated to States based on BTS assignments. These waterway weights are then evenly distributed among the counties within these States that have navigable waterways. All shipping activity is summed at the county-level and compared with national shipping activity to determine what portion of activity can be attributed to individual counties. These proportions were used in disaggregating the national CMV emission estimates to the county level.

b. Revised Port Allocation Method
Figures III-1 and III-2 present emission maps for CMV port and underway NO x 

## emissions created from the 1999 NEI Version 2.0 data. For underway emissions, Pechan believes that the allocation procedure results in a reasonable distribution of county-level emissions. However, the methodology to allocate port emissions results in all the emissions being assigned to a single county. For example, Cabell County in West Virginia is assigned all emissions for Huntington Port, but no emissions are allocated to Lawrence County in Ohio, the county on the opposite river bank.
Port areas encompass multiple States and counties and in some cases, multiple waterways. Therefore, the emissions allocation process must incorporate all counties in the vicinity of the port where activity is occurring. This is especially true for inland rivers where activity takes place on both riverbanks and for 10 river miles or more outside the port city. The revised methodology allocates port emissions based on a surrogate for port-related activity in each county, rather than using a single county to define the port.30

Figure 1. VISTAS Region and Surrounding States VISTAS Region an d Surrounding States Underway NOx EmissionsNOx Emissions(Tons per Year)00 - 400400 - 800800 - 1,3001,300 - 2,4002,400 - 3,680E.H. Pechan & Associates, Inc.Date: December 11, 2003.Figure III-1. VISTAS Region and Surrounding States,Underway NOxEmissions31

Figure 2. VISTAS Region and Surrounding States VISTAS Region and Surrounding States Port NOx EmissionsNOx Emissions(Tons per Year)00 - 3,0003,000 - 7,0007,000 - 13,00013,000 - 26,00026,000 - 67,000E.H. Pechan & Associates, Inc.Date: December 11, 2003.Figure III-2. VISTAS Region and Surrounding States,Port NOxEmissions

## 32 The report, Waterborne Commerce of the United States, Calendar Year 1999 (USACE, 2000), hereafter referred to as Waterborne Commerce
, presents the cargo tonnage and number of vessel trips in major waterways of the United States. The report defines port areas, which USACE uses to develop the Top 150 Ports in the United States by amount of cargo tonnage. As discussed in the previous section, the 1999 NEI allocates all th e port emissions to these 150 ports based on the cargo tonnage handled by the port.
Pechan uses this allocation of emissions to each port area as the starting point of its revised allocation process. Table III-4 presents the ports that are located in VISTAS and adjoining States, which are part of the Top 150 Ports.

Table III-4. Port Areas Located in VISTAS and Adjoining States

Port State Port State

Mobile AL Pascagoula MS Guntersville AL Vicksburg MS
Helena AR Biloxi MS Port Everglades FL Greenville MS Jacksonville FL Gulfport MS
Miami FL Wilmington NC Port Canaveral FL Morehead City NC Palm Beach FL Cincinnati OH Panama City FL Pittsburgh PA
Pensacola FL Charleston SC Tampa FL Georgetown SC Port Manatee FL Memphis TN Weedon Island FL Nashville TN Savannah GA Chattanooga TN Brunswick GA Norfolk Harbor VA Mount Vernon IN Newport News VA Louisville KY Hopewell VA New Orleans LA Huntington WV Baton Rouge LA



## The next step was to develop a list of counties that make up the port area. Port area definitions were obtained from Waterborne Commerce . Table III-6 presents the port definitions for the VISTAS States and adjoining Stat es. Using the port definitions by river mile, Pechan established which counties are included in each port area. In many cases, these port areas encompass multiple counties. For example, Pittsburgh is defined in Waterborne Commerce as: Ohio River from Pittsburgh, PA to mile 40 (Pennsylvania/Ohio State Line); Allegheny River from Pittsburgh, PA to mile 72 (to head of project); Monongahela River from Pittsburgh, PA to mile 91 (to head of project).

## 33 Therefore, the Port of Pittsburgh includes the following counties in Pennsylvania; Allegheny, Westmoreland, Armstrong, Washington, Fayette, Greene, Beaver. This process was repeated for all the port areas listed in Table III-4.
The next step in allocating emissions is to develop a surrogate for the amount of CMV activity in each county of the port area. Pechan assumed that the activity of vessels in each county is related to the number of port facilities operating in a given county. Port facilities include terminals, piers, wharves, and docks that are involved in all types of commercial activity and support services. Pechan obtained the number of port facilities in each county from The Port Series Reports (USACE, 2003). The USACE periodically surveys the commercial marine industry to obtain information on port facilities and publishes it in The Port Series Reports . The reports give the name, location, operations, and describe the physical and inter-modal characteristics of the facilities. The data includes the location of the facility by river mile, State, and county.
For each port area, Pechan calculated the ratio between the number of port facilities in each county to the total number of facilities in all counties that make up the port area. This ratio was used to allocate emissions for each port area to the county-level. Table III-5 presents the allocation ratios for each county in the port areas. Some port areas were still encompassed by one county using the definition of the port from Waterborne Commerce . However, a number of port areas include multiple counties. Note that New Orleans and Pittsburgh do not include any counties in VISTAS States.

Table III-5. List of VISTAS Po rts and Ports of Adjoining States

Port State County Ratio Port State County Ratio Port State County Ratio Port Everglades FL Broward 1.0 AR Phillips 0.7778 TN Hamilton 0.7692 Jacksonville FL Duval 1.0 Helena MS Coahoma 0.2222 Chattanooga TN Marion 0.2308 Miami FL Miami-Dade 1.0 FL Charlotte 0.7500 VA Norfolk City 0.5568
Port Canaveral FL Brevard 1.0 Charlotte FL Lee 0.2500 VA Chesapeake City 0.3068
Palm Beach FL Palm Beach 1.0 IN Vanderburgh 0.3182 Norfolk
VA Portsmouth 0.1364 Panama City FL Bay 1.0 IN Posey 0.4773 VA Newport News 0.6500 Pensacola FL Escambia 1.0 Mount Vernon KY Henderson 0.2045 Newport News VA Hampton 0.3500 Tampa FL Hillborough 1.0 KY Jefferson 0.6596 VA Hopewell 0.5000 Port Manatee FL Manatee 1.0 Louisville IN Clark 0.3404 Hopewell VA Charles City 0.5000 Weedon Island FL Pinellas 1.0 LA St. Bernard 0.0858 PA Allegheny 0.5206 Savannah GA Chatham 1.0 LA Plaquemines 0.1231 PA Westmoreland 0.0412 Brunswick GA Glynn 1.0 LA Orleans 0.3284 PA Armstrong 0.0309 Pascagoula MS Jackson 1.0 LA Jefferson 0.4366 PA Washington 0.1340 Vicksburg MS Warren 1.0 LA St. Tammany 0.0224 PA Fayette 0.0412 Biloxi MS Harrison 1.0 New Orleans

LA Tangipahoa 0.0037 PA Greene 0.0567 Greenville MS Washington 1.0 NC New Hanover 0.8974 Pittsburgh

PA Beaver 0.1753 Gulfport MS Harrison 1.0 Wilmington NC Brunswick 0.1026 KY Greenup 0.0795 Morehead City NC Carteret 1.0 OH Hamilton 0.7931 KY Boyd 0.1023 Georgetown SC Georgetown 1.0 KY Kenton 0.0862 OH Gallia 0.1136 Nashville TN Davidson 1.0 Cincinnati KY Boone 0.1207 OH Lawrence 0.2273 Mobile AL Mobile 1.0 SC Charleston 0.7097 OH Scioto 0.1364 Guntersville AL Marshall 1.0 Charleston SC Berkeley 0.2903 WV Wayne 0.1136 TN Shelby 0.9123 WV Cabell 0.0795 Memphis AR Crittenden 0.0877 Huntington

WV Mason 0.1477

## 34 Pechan was directed to perform the reallocation for all VISTAS ports. Figure III-3 presents the reallocation of port emissions in all States except Alabama. Alabama’s CMV data were provided to EPA and already incorporated into the 1999 NEI Version 2, and Pechan did not have access to the default 1999 NEI estimates for this State and category. Since State data take precedence, the inventory prepared by Pechan refl ects the incorporation of State data for those areas that developed independent CMV emission estimates, including Virginia and Palm Beach County, Florida. In addition, West Virginia provided their own county fractions to allocate emissions for the Port of Huntington, using District -level data from the Army Corps of Engineers on tonnage of freight shipped and received. West Virginia also requested that residual-fueled CMV activity/emissions be zeroed out for their State. States providing their own data are encouraged to review the allocations Pechan developed for their port areas, and to provide further comment or direction as needed.35Figure III-3. VISTAS Region and Surrounding States,Revised Port Emissions of NOX

## 36 Table III-6. Definition of Port Areas Obtained from Waterborne Commerce (USACE, 2000)

VISTAS PORTS
MOBILE, AL Entrance. bay and river channels, and channels into Chickasaw and Three Mile Creeks; Branch Channels; Theodore Ship Channel.

GUNTERSVILLE, AL Both banks of the Tennessee River at mile 358 to mile 363.
JACKSONVILLE HARBOR, FL Atlantic Ocean to the Florida East Coast Railway Bridge at Jacksonville, 26.8 miles.

TAMPA, FL Gulf of Mexico to and including the channels of upper Tampa Harbor, 49.8 miles; Channel to Port Tampa and thence to Courtney Campbell Parkway, 17.5 miles; Natural channel leading from Port Tampa Channel toward St. Petersburg, 1.8 miles; Alafia River Channel, 3.6 miles; Hillsborough River to City Waterworks Dam, 10 miles; Channels in “Little M anatee River, Fl; Port Manatee, Fl Harbor.”
MIAMI HARBOR, FL Atlantic Ocean to inner end of turning basin at Miami, 6 miles; Meloy Channel and thence natural channels along the easterly side of Biscayne Bay to Bakers Haulover Inlet, FL, about 11 miles; channel from turning basin to mouth of Miami River, 1.1 miles; existing Florida East Coast Railway Channel, Fishermans Channel from mouth of Miami River to Government Cut, 3.8 miles; and the channels reported under “Miami River, FL.”
EVERGLADES HARBOR, COLLIER COUNTY, FL - No definition given
CANAVERAL HARBOR, FL Entrance Channel (Atlantic Ocean) to Barrier Beac h inner channel and Turning Basins, thence a Barge canal through a lock in the perimeter dike and conti nuing to the Intracoastal Waterway, Jacksonville to Miami.
CHARLOTTE HARBOR, FL Gulf of Mexico to Municipal Terminal at Punta Go rda, about 29.5 miles; waterfront on Gasparilla Island from Port Boca Grande to Boca Grande, 4.5 miles; and Myakka River to El Jobean, 4 miles.

PALM BEACH HARBOR, FL Atlantic Ocean to Port of Palm Beach Terminals, 1. 7 miles; Lake Worth from Riviera Bridge to Southern Boulevard Bridge at West Palm Beach, 7.5 mile s; and “Palm Beach, FL side channel and basin.”
PORT MANATEE, FL 40 feet deep by 400 feet wide entrance channel and bas in. The entrance channel extends approximately 3 miles in length from the turning basin to its in tersection with Tampa Harbor main channel. Controlling Depth: 40 feet in entrance channel and turning basin.
PANAMA CITY HARBOR, FL Entrance channel, inside bay and Watson Bayou. Pr oject Depth: Approach channel, 34 feet; across Lands End, 32 feet; Watson Bayou, 10 feet.

## 37 Table III-6. Definition of Port Areas Obtained from Waterborne Commerce (USACE, 2000)

PENSACOLA HARBOR, FL Entrance channel and entire harbor, including Bayou Chico. Project Depth: entrance, 35 feet; Inner Ha rbor, 33 feet; Bayou Chico, 15 and 14 feet.
WEEDON ISLAND, FL – no definition
BRUNSWICK HARBOR, GA From 32-foot contour in the ocean across the Bart hrough St. Simon Sound, Brunswick River, and Turtle River to the upper end of the Allied Chemical Com pany’s Wharf, formerly Atlantic Refining Company Wharf, 20.4 miles; from Brunswick River through East River, to the upper end of the project in Academy Creek, 2.7 miles; from St. Simon Sound through Ba ck River to Mill Creek, the upper end of Back River improvement, 2.9 miles; from Back River through Terry Creek to the Glynn Canning Company’s Wharf, 1.8 miles; a total distance of 27.8 miles.
SAVANNAH HARBOR, GA From the 40-foot contour in the ocean to t he Continental Can Company Plant, 32.15 miles.
LOUISVILLE, KY Both banks of the Ohio River from mile 606 to mile 616 Controlling Depth: 9 feet. Project Depth: 9 feet at low water stages.
BILOXI HARBOR, MS Mississippi Sound, Biloxi Bay, Back Bay, and land cut to Gulfport Lake. Project Depth: East entrance channel, Mississippi Sound to Gulfport Lake, 12 feet: West entrance channel, Mississippi Sound to Biloxi Harbor, 10 feet; Ott Bayou, 12 feet.

GREENVILLE, MS From Mississippi River mile 537 AHP left descending bank in an easterly direction, an entrance channel, 8,000 feet long and 250 feet wide transitioning into the harbor and port area 10,000 feet long and 500 feet wide, then transitioning into Lake Ferguson, a channel 5,700 feet long and 250 feet wide.
GULFPORT HARBOR, MS Mississippi Sound Channel, Ship Island Pass Channel, and Small Craft Harbor about 4,300 feet long west of the anchorage basin. Project Depth: Mississippi Sound, 30 feet; Ship Island Pass, 32 feet; Small Craft Harbor, 8 feet.

PASCAGOULA HARBOR, MS Lower 4 miles of Dog River and lower 6.8 miles of Pascagoula River, Mississippi Sound, Bayou Casotte, and Horn Island Pass Channels.

VICKSBURG, MS From Mississippi River mile 437 AHP on left descending bank in a northerly direction, a channel 14,500 feet long by 150 feet wide in the Yazoo Divers ion Canal, thence a dredged entrance channel 4,800 feet long and 150 feet wide, transitioning into a 300-foot wide dredged slack water harbor and turning basin 10,700 feet long.
MOREHEAD CITY HARBOR, NC Morehead City Harbor, NC.

## 38 Table III-6. Definition of Port Areas Obtained from Waterborne Commerce (USACE, 2000)

PORT OF WILMINGTON, NC (see also Wilmington Harbor NC for waterway data) Both banks of the Cape Fear River extending from a poi nt about 18 miles below the foot of Castle St. in Wilmington to a point about 2 miles above the Ra ilroad Bridge at Navassa, and both banks of Northeast (Cape Fear) River from its mouth to a point about 1.67 miles above the Hilton Railroad Bridge.

CHARLESTON HARBOR, SC (Including Ashley River, Cooper River, Shem Creek And Shipyard River, SC) Ocean to Goose Creek via Cooper River and Town Creek ; to the Standard Wharf on Ashley River; to the Mount Pleasant Memorial Highway Bridge on Shem Creek ; to the Airco Alloys Wharf on Shipyard River; Wando River to Cainhoy.
GEORGETOWN HARBOR, SC (Winyah Bay) Atlantic Ocean Entrance to Winyah Bay, SC, to and including turning basin in Sampit River at the City of Georgetown, SC.

MEMPHIS, TN Section Inlcuded: From mile 715.5 to mile 741. 0 on Lower Mississippi River and includes Memphis Harbor (McKellar Lake) and Wolf River Harbor, Tennessee. Controlling Depth: 9 feet. Project Depth: 9 feet at low water stages.

PORT OF NASHVILLE, TN (included in traffic of Cumberland River, TN and KY) Both banks of Cumberland River, mile 182 to mile 194 Controlling Depth: 9 feet. Project Depth: 9 feet at low water stages.

CHATTANOOGA, TN Section Included: Both banks of the Tennessee River at mile 454 to 471. Controlling Depth: 9 feet. Project Depth: 9 feet at low water stages.
PORT OF RICHMOND, VA (Included in James River, VA Consolidated Report)
PORT OF NEWPORT NEWS, VA (Including Newport News Creek, VA) Lower east shore of James River from mouth to 1.8 miles, and portion of north shore of Hampton Roads covering approximately 15,000 linear feet of waterf ront at Newport News; and Newport News Creek.
PORT OF HOPEWELL, VA (Included In James River VA Consolidated Report) South side of James River, from City Point, at m outh of Appomattox River, 2 miles downstream to the mouth of Baileys Creek. Controlling Depth: 25 feet at mean low water. Project Depth: 35 feet, maintained to 25 feet.

NORFOLK HARBOR, VA From 55-foot contour in Hampton Roads to Norfolk & Western (formerly Virginia) Railway Bridge Crossing Southern Branch of Elizabeth River, 14.78 miles; t hence upstream in Southern Branch, 4.61 miles. In Eastern Branch, 2.54 miles upstream from the mouth of that branch; in Western Branch, 1.78 miles upstream from the mouth of that branc h; and 0.73 miles in Scotts Creek.
HUNTINGTON, WV Both banks of the Ohio River from mile 303 to mile 317 Controlling Depth: 9 feet. Project Depth: 9 feet at low water stages.

## 39 Table III-6. Definition of Port Areas Obtained from Waterborne Commerce (USACE, 2000)

NON-VISTAS PORTS

HELENA, AR Mile 659 through mile 663 on the Lower Mississippi River. The project provides for maintenance of an off-rive r harbor with dimensions of 9 feet deep and 450 feet wide for a length of 3,200 feet.

MOUNT VERNON, IN Section Included: Right Bank of Ohio River from mile 151 to mile 154. Controlling Depth: 9 feet. Project Depth: 9 feet at low water stages.
CINCINNATI, OH Both banks of the Ohio River from mile 465 to mile 491. Controlling Depth: 9 feet. Project Depth: 9 feet at low water stages.
PORT OF PITTSBURGH, PA Ohio River from Pittsburgh, PA to mile 40 (Pennsylvania/Ohio State Line); Allegheny River from Pittsburgh, PA to mile 72(to head of project); Monongahela River from Pittsburgh, PA to mile 91(to head of project). Includes Aliquippa-Roches ter, Pittsburgh, Clairton-Elizabeth. Controlling Depth: 9 feet. Project Depth: 9 feet.

PORT OF PLAQUEMINES, LA Both banks of Mississippi River from mile 0 A.H.P. through mile 81.2 A.H.P Controlling and Project Depths: 45 feet.
PORT OF BATON ROUGE, LA Both banks of Mississippi River from mile 168.5 A. H.P. through mile 253 A.H.P; including the Baton Rouge Barge Canal from a point on the east bank of the Mississippi River at mile 234.5 A.H.P., for a distance of 5 miles.
PORT OF NEW ORLEANS, LA Both banks of the Mississippi River from mile 81.2 A.H.P. through mile 114.9 A.H.P.; Innerharbor Navigation Canal, 5.5 miles; Mississippi River-Gulf Outl et from its junction with the Innerharbor Navigation Canal to Bayou Bienvenue, 7 miles; and Harvey Canal, 5.5 miles.
PORT OF SOUTH LOUISIANA (LA) Both banks of Mississippi River from mile 114.9 A.H.P. through mile 168.5 A.H.P. Controlling and Project Depths: 45 feet.

## 40 3. Projection Methods
Pechan then projected the revised 1999 inventory to 2002 using surrogate growth indicators. For the aircraft category, 1999 and 2002 approach opera tions by airport and aircraft type were compiled from the Federal Aviation Administration’s Air Traffic Activity Data System (ATADS). The airport-level landing and takeoffs (LTOs) were assigned to counties and summed for the county. For counties with aircraft em issions without a county match in ATADS, Stateaverage growth factors were calculated and app lied. The county-level growth factors are not presented in this report, but could be provided to VISTAS S/L/Ts if requested.
For locomotives, projected emissions were developed in two steps as described below. For 1999 to 2001, State-level vessel bunkering and rail fuel consumption was obtained from the Energy Information Administration’s (EIA’s) Fuel Oil and Kerosene Sales. For 2001 to 2002, Pechan applied national growth factors developed from fuel consumption projections in EIA’s Annual Energy Outlook. Table III-7a lists the growth factors for locomotives that were applied to the 1999 emissions to first develop 2001 emissions. Table III-7b lists the growth factors used to generate 2002 emissions. Locomotive emissions were not revised from the August 2003 draft VISTAS 2002 inventory.

Table III-7a. Growth Factors for Railroad Distillate Fuel Oil Use

Rail Distillate Fuel Oil Sales (Thousand Gallons) FIPSST State

1999 2001 Growth Factor (GF)

01 Alabama 42,137 55,777 1.3 12 Florida 127,269 107,084 0.8 13 Georgia 73,494 70,538 1.0 21 Kentucky 98,941 99,812 1.0 28 Mississippi 14,267 24,812 1.7 37 North Carolina 53,900 77,762 1.4 45 South Carolina 13,051 15,936 1.2 47 Tennessee 44,083 91,363 2.1 51 Virginia 32,202 61,154 1.9 54 West Virginia 9,160 8,787 1.0 Source: Department of Energy, Energy Information Administ ration Fuel Oil and Kerosene Sales 1999 & Fuel Oil and Kerosene Sales 2001 Table 23. Adjusted Sales for Transportati on Use: Distillate Fuel Oil and Residual Fuel Oil ( http://tonto.eia.doe.gov/FTPROOT/pertroleum/053599.pdf ), ( http://tonto.eia.doe.gov/FTPROOT/pertroleum/053501.pdf )

## 41 Table III-7b. 2002 National Rail Transportation Energy Use by Fuel Type (Trillion BTU)

2001 2002 Growth Factor (GF) Intercity Rail (Electric) 10.17 10.40 1.0226 Intercity Rail (Diesel) 16.60 16.88 1.0169 Transit Rail (Electric) 46.36 47.40 1.0224 INTERCITY/TRANSIT RAIL AVERAGE (SCC 2285002008) 1.0206 Commuter Rail (Electric) 16.13 16.49 1.0223 Commuter Rail (Diesel) 26.31 26.76 1.0171 COMMUTER RAIL AVERAGE (SCC 2285002009) 1.0197 Freight Rail (Distillate) (SCCs 2285002000, 2285002005, 2285002006, 2285002007, 2285002010) 512.81 492.32 0.9600

Source: Department of Energy, Energy Information Administration, Annual Energy Outlook 2003: Table 34. Transportation Sector Energy Use by Fuel Type Within a Mode ( http:// www.ei a.doe.gov/oiaf/aeo/supplement/sup_tran.pdf )



## Since the CMV emissions were revised for the 1999 base year, these emissions were projected using 2002 Fuel Oil and Kerosene Sales data, which became available in November 2003. Table III-8 lists the growth factors for CMVs that were applied to 1999 emissions to generate 2002 emissions. The same regional growth factor that accounts for an average regional growth rate was applied to CMV emissions for all VISTAS States. Because the State-level data represents sales and not use, and CMV activity spans State borders, a regional growth factor was deemed more appropriate. Pechan could make a similar adjustment for the locomotive growth factors, which are also based on fuel sales for 1999 to 2001, if requested by VISTAS.

## 42 Table III-8. Growth Factors for Commerc ial Marine Vessel Distillate and Residual Fuel Oil Use

Fuel Oil Sales (Thousand Gallons) Growth Factor (GF) FIPSST State

1999 2002 DISTILLATE 01 Alabama 67,455 73,400 1.1 12 Florida 139,809 143,577 1.0 13 Georgia 17,697 22,327 1.3 21 Kentucky 81,811 56,169 0.7 28 Mississippi 12,749 68,668 5.4 37 North Carolina 11,279 10,057 0.9 45 South Carolina 12,732 19,782 1.6 47 Tennessee 43,867 112,364 2.6 51 Virginia 29,444 28,235 1.0 54 West Virginia 54,560 46,981 0.9 Regional Distillate GF 471,403 581,560 1.2 RESIDUAL 01 Alabama 46,093 93,487 2.0 12 Florida 404,228 460,600 1.1 13 Georgia 40,117 79,191 2.0 21 Kentucky 1 

### 69 1.2 28 Mississippi 48,644 54,031 1.1 37 North Carolina 6,989 35,210 5.0 45 South Carolina 20,056 22,758 1.1 47 Tennessee 1 

### 124 1.2 51 Virginia 60,090 36,445 0.6 54 West Virginia 1.2 Regional Residual GF 626,217 781,915 1.2

1 For Kentucky, Tennessee and West Virginia, Pechan summed the 1999 and 2002 CMV residual fuel oil use to develop a total VISTAS State growth factor, which was then applied to the three States. Source: Department of Energy, Energy Information Administ ration, Fuel Oil and Kerosene Sales 1999 & Fuel Oil and Kerosene Sales 2002, Table 23. Adjusted Sales for Transportati on Use: Distillate Fuel Oil and Residual Fuel Oil. 

# IV. ONROAD REFUELING METHODS
Emissions were separately calculated from onroad refueling, also known as Stage II emissions. Since refueling is a category of evaporative rather than exhaust emissions, VOC is the only criteria pollutant of concern for this category. This chapter discusses the controls modeled for this emission category and the methods used to calculate these emissions. Refueling emissions for onroad sources were updated in February 2004 to account for the VMT updates provided by several States.



# A. CONTROLS
Based on default information from the NEI as well as some information provided by VISTAS agencies, portions of five of the VISTAS States ha ve onroad Stage II refueling controls in place. These States, along with the specific counties with onroad Stage II controls, are listed in Table IV-1. This table also shows information about the Stage II control program in each State including the year a Stage II program began, the number of years that the program was phased-in over, and the control efficiency of the program in reducing VOC emissions from Stage II

## 43 refueling for the LDGV, LDGT, and HDGV vehicle cat egories. These are the inputs required for modeling a Stage II control program using MOBILE6. States with Stage II programs should review this information and provide any corrections for the next round of emissions modeling.
Table IV-1. Onroad Stage II Control Programs

State Start Year Phase-In Years Control Efficiency Counties Florida 1993 2 95% Broward, Miami-Dade, Palm Beach Georgia 1992 3 81% Cherokee, Clayton, Cobb, Coweta, DeKalb, Douglas, Fayette, Forsyth, Fulton, Gwinnett, Henry, Paulding, Rockdale Kentucky 1999 2 86% B oone, Campbell, Kenton Kentucky 1992 2 95% Jefferson Tennessee 1993 3 95% Davidson, Ruther ford, Sumner, Williamson, Wilson Virginia 1993 2 95% Counties: Arlingt on, Chesterfield, Fairfax, Hanover, Henrico, Loudoun, Prince William, Stafford Independent Cities: Alexandria, Colonial Heights, Fairfax, Falls Church, Hopewell, Manassas, Manassas Park, Richmond



# B. METHODS
A simplified set of MOBILE6.2 input files was creat ed to simulate the onroad refueling emission factors. These input files were simplified becau se several of the inputs used for calculating the onroad exhaust and evaporative emission factors do not affect the refueling emission factors. For example, the refueling emission factors ar e unaffected by vehicle speed or I/M program. Thus, for each group of counties in a State with the same fuel parameters, temperature parameters, fleet characteristics (registration distribution, diesel sales fractions), and Stage II control program parameters, a MOBILE6.2 input file was created to model the onroad refueling emission factors. As mentioned above, speed does not affect the refueling emission factors, so each input file contained only 12 scenarios—one for each month of the year. Within each scenario, the temperature and fuel parameters were varied, using the same temperature and fuel data modeled in the onroad exhaust and evaporative MOBILE6.2 input files. Other fleet characteristics, such as registration distributions and diesel sales fractions, were included in the input files where applicable. The inputs shown in Table IV-1 were included for the input files representing counties with Stage II control programs. The header section of the MOBILE6.2 input files was set up so that only refueling emission factors would be included in the tabular output file.
After the MOBILE6.2 input files were generated, they were run through the MOBILE6.2 model to obtain refueling VOC emission factors in the database table format. These emission factors are produced for the 28 MOBILE6 vehicle types. The emission factors were then weighted using the VMT fraction information included in the MO BILE6 output tables to obtain VOC refueling emission factors for the 8 vehicle types incl uded in the VISTAS VMT database. The VMT fraction information contained in the MOBILE6 input files is based on the default MOBILE6 registration distributions, diesel sales fractions, and VMT fractions, or, when this information is

## 44 provided in the input files, based on area-specific fleet parameters. A database of emission factors by month, county, and 8 vehicle types was then prepared. In calculating monthly onroad refueling emissions, the VISTAS annual VMT data were temporally allocated by month in the same manner as described in Chapter II for the onroad exhaust and evaporative emission calculations. These VMT were then multiplied by the corresponding monthly emission factor (in terms of grams per mile) to obtain refueling emissions from onroad vehicles. The monthly emissions for each county were then summed to obtain annual refueling emissions. Also, since refueling emissions are included in the area sour ce inventory and are not distinguished by vehicle type, all refueling emissions from onroad vehicl es were summed for each county in the VISTAS region. Summaries of the refueling emissions from onroad vehicles are presented in Chapter VI. 

# V. NONROAD REFUELING METHODS

The NONROAD model accounts for refueling emissions from nonroad equipment under two separate components, vapor displacement and spillage. Vapor displacement emissions result when new liquid fuel being added to a fuel tank di splaces fuel vapors already present in the tank. Spillage emissions result when fuel is spilled during the refueling process.
Nonroad equipment may be fueled from a gaso line pump or a portable container. Refueling nonroad equipment from a portable container results in different emissions for both spillage and vapor displacement compared to refueling from a gasoline pump. In addition, the use of portable containers also results in extra refueling events. Both spillage and displacement emissions will also occur when the container is filled from a gasoline pump. However, due to lack of data, the NONROAD2002 model does not attempt to quantify this set of refueling emissions. As such, the NONROAD model refueling emissions associated with nonroad equipment being filled directly at the gasoline pumps will be used to represent the nonroad Stage II emission component. Stage II control factors listed in Table IV-1 were input in the county-specific NONROAD model option files. Once the model runs were performed, Pechan extracted the refueling and spillage emissions corresponding only to those engines (typically the larger horsepower engines) within each SCC assumed to be refueled at the pump. The list of SCC and horsepower ranges associated with pump versus container refueling is specified in the model since different emission rates are assumed for these two types of refueling.
Table V-1 presents draft annual Stage II VOC emission estimates by State. These emissions were combined with the onroad vehicle Stage II estimates described in Section IV of this report.

## 45 Table V-1. 2002 Draft Stage II Refueling Emissions by State

FIPSST NAME VOC Emissions, tpy 01 Alabama 167.25 12 Florida 842.60 13 Georgia 209.01 21 Kentucky 112.65 28 Mississippi 147.18 37 North Carolina 298.49 45 Tennessee 197.81 47 South Carolina 155.33 51 Virginia 174.70 54 West Virginia 39.33



# VI. SUMMARY OF RESULTS

This chapter presents the emission results from the February 2004 draft version of the 2002 mobile source emissions inventory for the VISTAS region. These emissions result from the data and procedures described in the preceding chapters of this report.



# A. ONROAD RESULTS

Table VI-1 summarizes the latest 2002 VISTAS onroa d emissions inventory by State. This table also summarizes the total VMT for each State. Tables VI-2 and VI-3 are provided here for the purpose of comparing this inventory with anot her existing onroad inventory. The emissions shown in Table VI-2 are taken from Version 2 of EPA’s 1999 NEI. Table VI-3 then shows the percentage change from the 1999 NEI to the 2002 draft VISTAS inventory. If the two inventories had been developed using comparable data, one would generally expect to see reductions in the onroad emissions from 1999 to 2002 due to fleet turnover resulting in the replacement of older, dirtier vehicles with vehicles meeting more stringent emission standards. However, this reduction in per-vehicle emissions also needs to overcome increases in VMT for the overall emissions to decrease. All of the VISTAS States show increases in VMT from 1999 to 2002, except North Carolina. This decrease in VMT needs to be further investigated by the State agency. States that were modeled with significant State or locally supplied inputs in the VISTAS modeling, such as Virginia and Georgia, would be expected to have more significant differences from the NEI data than States with no State-supplied information other than VMT. Some of the State inputs that cause significant de viations from the NEI estimates are registration distributions, VMT mixes by vehicle type, and speeds by road type. In addition, some of the pollutants are more affected by these inputs, while others (such as NH 3 

## ) are minimally affected by these inputs. The 2002 VISTAS onroad emissions will continue to undergo review. Any comments or questions on these emissions by the State or local agencies will be investigated as part of this review.

## 46 Table VI-1. 2002 VISTAS Onroad Emissions and VMT by State (February 2004 Version)

2002 Annual Emissions (tons per year) 2002 Annual VMT State VOC NOx CO SO2 PM10 PM2.5 NH3 (million miles) Alabama 99,650 154,908 1,275,969 6,515 4,344 3,231 5,619 55,723 Florida 457,309 463,419 4,678,471 19,739 12,666 9,232 18,240 178,681 Georgia 215,035 311,125 2,601,785 11,487 8,038 5,942 10,612 106,785 Kentucky 79,110 164,231 1,196, 211 5,718 4,083 3,048 5,103 51,020 Mississippi 68,508 107,047 845,990 4,354 3,152 2,399 3,603 36,278 North Carolina 147,977 278,265 2, 116,829 9,953 6,374 4,741 7,868 80,166 South Carolina 92,491 136,569 1, 192,894 5,647 3,825 2,867 4,719 47,074 Tennessee 126,959 255,090 1,785,136 8,115 5,445 4,059 6,855 68,316 Virginia 115,044 182,513 1,858, 629 6,110 4,413 3,032 7,937 76,566 West Virginia 34,197 57,941 512,592 2,361 1,550 1,155 1,947 19,544 VISTAS Total 1,436,279 2,111,108 18,064,506 79,999 53,890 39,705 72,504 720,153


## Table VI-2. 1999 NEI Version 2 Onroad Emissions and VMT by State

1999 Annual Emissions (tons per year) 1999 Annual VMT State VOC NOx CO SO2 PM10 PM2.5 NH3 (million miles) Alabama 121,201 163,024 1,412,343 6,280 4,712 3,599 5,249 52,914 Florida 328,412 424,969 3,379,563 16,581 12,259 9,318 14,162 141,903 Georgia 207,562 313,568 2,526,592 12,028 9,263 7,139 9,787 98,859 Kentucky 97,286 162,160 1,225, 414 6,006 4,772 3,715 4,703 47,816 Mississippi 74,579 126,344 830,477 4,478 3,908 3,106 3,406 34,955 North Carolina 187,346 285,380 2, 252,671 10,829 8,462 6,552 8,663 87,759 South Carolina 98,010 153,346 1, 207,336 5,616 4,515 3,527 4,330 44,146 Tennessee 138,629 211,133 1,697,778 7,876 6,108 4,716 6,392 64,570 Virginia 150,528 238,515 1,861, 417 8,972 6,892 5,307 7,320 73,904 West Virginia 40,060 68,580 539,578 2,471 2,023 1,589 1,859 19,033 VISTAS Total 1,443,613 2,147,019 16,933,170 81,137 62,913 48,567 65,871 665,859

## 47 Table VI-3. Change in Onroad Emissions and VMT from 1999 NEI Version 2 to VISTAS 2002 Inventory (February 2004 Version)

Change from 1999 NEI V2 to 2002 VISTAS Draft Inventory State VOC NOx CO SO2 PM10 PM2.5 NH3 VMT Alabama -18% -5% -10% 4% -8% -10% 7% 5% Florida 39% 9% 38% 19% 3% -1% 29% 26% Georgia 4% -1% 3% -4% -13% -17% 8% 8% Kentucky -19% 1% -2% -5% -14% -18% 9% 7% Mississippi -8% -15% 2% -3% -19% -23% 6% 4% North Carolina -21% -2% -6% -8% -25% -28% -9% -9% South Carolina -6% -11% -1% 1% -15% -19% 9% 7% Tennessee -8% 21% 5% 3% -11% -14% 7% 6% Virginia -24% -23% 0% -32% -36% -43% 8% 4% West Virginia -15% -16% -5% -4% -23% -27% 5% 3% VISTAS Total -1% -2% 7% -1% -14% -18% 10% 8%



## Table VI-4 presents the latest 2002 VISTAS onroad refueling emission estimates by State.These refueling emissions are NOT included in the emissions shown in Tables VI-1 through VI3.
Table VI-4. 2002 VISTAS Annual Onroad Refueling Emissions

State 2002 Annual Onroad VOC Refueling Emissions (tons per year) Alabama 8,408 Florida 28,367 Georgia 12,329 Kentucky 6,885 Mississippi 6,057 North Carolina 15,320 South Carolina 8,926 Tennessee 9,901 Virginia 8,657 West Virginia 3,383 VISTAS Total 108,233



# B. NONROAD RESULTS
Table VI-5 provides a summary of draft 2002 nonroad sector annual emissions by State, including Stage II refueling emission estimates. Table VI-6 provides a summary of the draft 2002 NONROAD model emission estimates by State, and compares the values to 2001 NONROAD model NEI Version 2 estimates by showing the percent difference. A similar comparison is shown in Table VI-7 for other nonroad emission estimates compared to the 1999 NEI Version 2.

## 48 For the NONROAD model categories, SO 2 

## , PM 10, 

## PM 2.5 

## , and NH 3 

## decrease consistently across all States. SO 2 

## emissions decrease due in part to a lower diesel fuel sulfur content input for the NONROAD model runs, which also contributes to decreases in particulate emissions. The decrease in NH 3 

## is due primarily to corrections made to compresses natural gas (CNG) engine NH 3 

## emissions, which involved zeroing out the estimates. The 1999 NEI erroneously applied emission factors on a grams per gallon basis to CNG fuel consumption. Although reported as uncompressed gallons in the NONROAD model, the CNG fuel consumption estimates represent a gaseous, not liquid, volume. Based on OTAQ’s recommendations, CNG NH 3 

## emissions are now reported as zero. CO and NO x 

## show little change for all States, and changes in VOC vary by State and are dependent on the contribution of specific equipment categories (detail not shown).
For other nonroad categories, the increase in PM 10 

## and PM 2.5 

## is due to the addition of commercial aircraft PM emissions. Commercial aircraft PM 10 

## and PM 2.5 

## emissions were zero in the 1999 NEI; hence, the large percent increase. To gap fill this portion of the inventory, Pechan calculated and applied an average air taxi PM/NO x 

## emission ratio to commercial aircraft NO x 

## emissions. States with a higher proportion of co mmercial aircraft show significant PM increases (e.g., FL, TN, VA). In addition, NO x 

## emissions decrease due to new State data for other nonroad from AL and VA.

Table VI-5. Summary of Draft 2002 Nonroa d Sector Annual Emissions by State, tons per year

FIPSST STATE VOC NOX CO PM10-PRI PM25-PRI SO2 NH3

01 Alabama 

### 46,788 64,367 373,634 5,504 4,895 7,529 32 12 Florida 

### 211,006 153,396 1,765,539 61,426 45,849 17,453 109 13 Georgia 

### 66,712 87,053 712,159 10,411 8,666 7,914 55 21 Kentucky 

### 35,537 100,989 294,929 8,538 7,249 13,771 28 28 Mississippi 

### 33,443 90,190 217,407 5,795 5,194 11,537 23 37 North Carolina 

### 75,020 81,264 742,822 12,814 10,379 7,281 62 45 South Carolina 

### 43,231 46,518 375,469 4,115 3,678 4,465 29 47 Tennessee 

### 52,333 118,690 461,976 14,727 11,692 12,478 41 51 Virginia 

### 61,655 69,668 614,958 21,580 16,497 11,068 44 54 West Virginia 

### 15,497 36,613 120,029 2,293 2,034 2,388 10

## 49 Table VI-6. Summary of Draft 2002 NONRO AD Model Emission Estimates by State

2002 DRAFT VISTAS NONROAD Model Inventory, tpy FIPSST STATE VOC_ANN NOX_ANN CO_ ANN PM10_ANN PM25_ANN SO2_ANN NH3_ANN

01 Alabama 44,501.18 28, 635.48 365,161.12 3,306.84 3,044.48 2,729.32 31.92 12 Florida 205,489.66 86, 654.40 1,730,125.77 12,890.06 11,862.13 9,113.26 109.02 13 Georgia 65,054.02 51, 452.93 705,292.75 5,493.33 5,057.34 5,025.11 54.97 21 Kentucky 32,836.91 28,253.72 283,488.53 3,152.29 2,901.82 2,777.69 28.00 28 Mississippi 31,097.14 23,549.89 207, 824.23 2,761.65 2,542. 05 2,375.53 23.37 37 North Carolina 73,610. 93 58,667.62 734,496. 85 6,095.96 5,613. 11 5,442.35 62.06 45 South Carolina 41,652. 41 26,212.76 366,737. 16 3,028.92 2,788. 66 2,461.79 29.29 47 Tennessee 48,626.66 39, 833.95 446,461.43 4,240.53 3,904.21 3,810.11 41.22 51 Virginia 56,973.85 40,914.48 594, 020.13 4,739.47 4,362. 61 4,103.01 44.22 54 West Virginia 14,498.68 9,502. 33 115,652.49 1,038.29 955.70 980.17 10.31 2001 NONROAD Model NEI Version 2, tpy FIPSST STATE VOC_ANN NOX_ANN CO_ ANN PM10_ANN PM25_ANN SOX_ANN NH3_ANN

01 Alabama 43,602.83 28, 786.95 360,439.36 3,422.60 3,150.91 3,110.79 581.69 12 Florida 188,868.96 86, 835.32 1,713,539.62 13,243.04 12,186.78 10,456.05 1,305.25 13 Georgia 63,927.85 51, 521.66 698,868.77 5,678.55 5,227.63 5,749.47 989.31 21 Kentucky 31,662.34 28,350.32 279,283.79 3,274.35 3,014.06 3,127.88 463.74 28 Mississippi 29,037.96 23,671.70 205, 664.64 2,877.28 2,648. 40 2,668.55 359.21 37 North Carolina 69,671. 36 58,742.13 724,908.46 6,300.02 5,800.72 6,196.92 1,223.82 45 South Carolina 39,310. 79 26,304.57 363,112. 01 3,130.17 2,881. 75 2,817.02 507.81 47 Tennessee 47,193.97 39, 916.38 440,915.76 4,395.90 4,047.06 4,337.42 749.51 51 Virginia 55,459.80 41,082.63 585, 850.58 4,887.90 4,499. 09 4,677.52 627.60 54 West Virginia 13,912.53 9,568. 82 113,766.38 1,076.32 990.67 1,113.21 179.75 Percent Difference FIPSST STATE VOC_ANN NOX_ANN CO_ ANN PM10_ANN PM25_ANN SOX_ANN NH3_ANN

01 Alabama 2.06% -0.53% 1.31% -3 .38% -3.38% -12.26% -94.51% 12 Florida 8.80% -0.21% 0.97% -2.67% -2.66% -12.84% -91.65% 13 Georgia 1.76% -0.13% 0.92% -3.26% -3.26% -12.60% -94.44% 21 Kentucky 3.71% -0.34% 1.51% -3.73% -3.72% -11.20% -93.96% 28 Mississippi 7.09% -0.51% 1.05% -4.02% -4.02% -10.98% -93.50% 37 North Carolina 5.65% -0.13% 1. 32% -3.24% -3.23% -12.18% -94.93% 45 South Carolina 5.96% -0.35% 1. 00% -3.23% -3.23% -12.61% -94.23% 47 Tennessee 3.04% -0.21% 1.26% -3.53% -3.53% -12.16% -94.50% 51 Virginia 2.73% -0.41% 1.39% -3.04% -3.03% -12.28% -92.95% 54 West Virginia 4.21% -0.69% 1.66% -3.53% -3.53% -11.95% -94.26%

## 50 Table VI-7. Summary of Draft 2002 Other Nonroad* Emission Estimates by State

2002 DRAFT VISTAS Other Nonroad Inventory, tpy FIPSST STATE VOC_ANN NOX_A NN CO_ANN PM10_ANN PM25_ANN SO2_ANN

01 Alabama 2,286.81 35,731.80 8, 473.33 2,196.87 1, 850.82 4,799.75 12 Florida 5,516.71 66,741.52 35, 413.13 48,536.33 33, 987.28 8,340.05 13 Georgia 1,657.99 35,599.76 6,865.94 4,917.40 3,609.14 2,889.06 21 Kentucky 2,699. 92 72,735.57 11,440.23 5, 385.61 4,346.83 10,992.91 28 Mississippi 2,345.96 66,640.48 9,582.89 3,033.69 2,652.14 9,161.66 37 North Carolina 1,409.01 22,596. 53 8,325.56 6,718.49 4,766.12 1,838.68 45 South Carolina 1,578.34 20,304. 80 8,732.26 1,086. 01 889.24 2,002.78 47 Tennessee 3,706.17 78,855.60 15, 514.17 10,486.01 7, 787.92 8,667.84 51 Virginia 4,681.39 28,753.43 20,938.22 16,840.30 12,134.84 6,965.04 54 West Virginia 998.41 27,110. 49 4,376.64 1,254.86 1,077.93 1,408.05 1999 Other Nonroad NEI Version 2, tpy FIPSST STATE VOC_ANN NOX_A NN CO_ANN PM10_ANN PM25_ANN SO2_ANN

01 Alabama 7,309.83 152,338.93 25, 075.50 1,315.93 1, 176.15 3,854.54 12 Florida 3,945.18 56,197.72 25, 350.10 2,110.74 1, 881.95 6,878.28 13 Georgia 2,594.07 39,245.14 12,198.09 1, 072.08 953.43 3,070.41 21 Kentucky 2,676. 93 62,930.31 12,388.06 2, 370.31 2,153.93 8,965.67 28 Mississippi 1,755.99 48,927.22 8,072.51 1,917.16 1,747.89 7,051.91 37 North Carolina 1,447.95 17, 999.44 8,739.21 540. 09 470.85 1,508.40 45 South Carolina 2,470.03 18, 034.10 13,291.47 561. 99 503.60 1,858.19 47 Tennessee 2,426.97 51,133.47 11, 127.02 1,786.06 1, 616.72 6,266.91 51 Virginia 2,682.78 51,592.64 13,083.30 1,632.38 1,462.82 4,769.97 54 West Virginia 1,133.03 30,991. 75 4,858.71 1,151.55 1,048.38 4,097.15 Percent Difference FIPSST STATE VOC_ANN NOX_A NN CO_ANN PM10_ANN PM25_ANN SO2_ANN

01 Alabama -69% -77% -66% 67% 57% 25% 12 Florida 40% 19% 40% 2199% 1706% 21% 13 Georgia -36% -9% -44% 359% 279% -6% 21 Kentucky 1% 16% -8% 127% 102% 23% 28 Mississippi 34% 36% 19% 58% 52% 30% 37 North Carolina -3% 26% -5% 1144% 912% 22% 45 South Carolina -36% 13% -34% 93% 77% 8% 47 Tennessee 53% 54% 39% 487% 382% 38% 51 Virginia 74% -44% 60% 932% 730% 46% 54 West Virginia -12% -13% -10% 9% 3% -66% *Includes emissions from aircraft, co mmercial marine and locomotive SCCs

## 51 

# VII. OBSERVATIONS AND RECOMMENDATIONS FOR IMPROVEMENT

This chapter lists several areas where the onroad and nonroad emission inventories could be improved. Some of these improvements require a long lead-time for the States and would not likely be available for the final 2002 VISTAS modeling, but could improve future State and regional inventory efforts.



# A. ONROAD SECTOR IMPROVEMENTS
In the onroad sector, significant improvements have been made to the inventory due to the State and local agencies providing 2002 VMT data by county and roadway type. For this February 2004 version of the VISTAS onroad inventory, only the Virginia VMT were projected by Pechan. It is anticipated that this States will be able to provide 2002 VMT data for use in the next revision of the inventory.
Local registration distribution data were provided by fewer than half of the VISTAS States. In many cases, registration data can be obtained from State Departments of Motor Vehicles. States that do not already do so should request a downl oad of the data summarizing registrations by model year and vehicle class from their appropriate motor vehicle agency. Although it is probably too late in many cases to obtain 2002 data, 2003 registration data could be used with some adjustments in developing the 2002 emission inventories. Registration data will become even more important as VISTAS prepares to project a 2018 onroad emission inventory, since the 2018 projections will be affected by the number of vehicles that are subject to the Tier 2 emission standards and the new heavy duty vehicl e standards. The registration distributions directly determine the proportion of vehicles subject to these new emission standards.
A relatively small amount of data was obtained regarding the distribution of VMT by season or month. Many State Departments of Transportation collect data that could be used to better distribute VMT by season or month. States should check to see what is available. These distributions will affect the episodic modeling that will be conducted by VISTAS. Pechan is currently performing a VMT scoping study for VISTAS to determine what data are available for better allocating VMT and emissions by month, day, and hour. These temporal improvements are expected to be incorporated into the next update of the VISTAS onroad emission inventory.
Due to the direct relationship between the VMT mix by vehicle type and the overall emissions, States should investigate potential sources of information for this data to replace the default data used here in most States.
EPA is currently in the process of preparing guidance on estimating emissions from heavy duty vehicles during long-term idling (sometimes referred to as hotelling). While these emissions are theoretically included in the MOBILE6 HDDV emission factors, they are not currently accounted for in the appropriate locations. For example, these emissions would typically occur at rest stops, trucking centers, and warehouse and distribution centers. With the current modeling, these emissions are spread over all counties, based on the VMT traveled by HDDVs in each county. If significant sources of truck idling emissions occur in or near Class I areas, the

## 52 current modeling may be underestimating the effect of these emissions. If States are able to obtain data on the locations and utilization of truck rest stops, some of this emissions effect could be more appropriately accounted for in future versions of VISTAS modeling.



# B. NONROAD SECTOR IMPROVEMENTS

NH 3 

## emissions for aircraft, commercial marine and locomotives are still reported as zero. As a result of recent communications with OTAQ, Pechan would suggest applying the updated nonroad diesel NH 3 

## emission factors used for the NONROAD model categories to activity data for commercial marine vessels and locomotives. To develop ammonia from commercial marine vessels and locomotives, Pechan would need to obtain or compile the county-level fuel consumption estimates used as the basis for 1999 emissions for these categories to use as the activity data for calculating updated NH 3 

## emissions. The presence of State or local data in the 1999 NEI does not allow for this to be determined easily by backing out the reported emission factors, and in some cases (e.g., diesel commercial marine), actual emissions (instead of activity) were obtained at a national level and allocated to counties (EPA, 2002). Alternatively, Pechan could use county level fuel consumption estimates developed for these categories for 2000 or 2001. These activity data were used by Pechan to estimate dioxin/furan emission estimates for the 2000 and 2001 NEI. Pechan could normalize the 2000 or 2001 county distribution to national level fuel consumption estimates for 1999. Due to the characteristics of aircraft jet and piston engines, Pechan does not recommend estimating aircraft NH 3 

## emissions using the available NH 3 

## emission factors.


# VIII. REFERENCES

EPA, 1989: “Procedures for Emission Inventory Preparation, Volume IV: Mobile Sources.” U.S. Environmental Protection Agency, Office of Mobile Sources and Office of Air Quality Planning and Standards, EPA 450/4-81-026d (Revised). July 1989.

EPA, 2002. “Documentation for Aircraft, Commercial Marine Vessel, Locomotive, and Other Nonroad Components of the National Emi ssions Inventory,” prepared by Eastern Research Group, Morrisville, NC for the U.S. Environmental Protection Agency, Office of Air Quality Planning and Standards, Re search Triangle Park, NC. September 30, 2002.
Harvey, 1983. Craig Harvey, et al. “A Study of the Potential Impact of Some Unregulated Motor Vehicle Emissions.,” SAE Paper 830987. June 1983.
Harvey, 2003. C. Harvey, U.S. Environmental Pr otection Agency, Office of Transportation and Air Quality, e-mail entitled “NH3 Emission Updates,” sent to K. Thesing, E.H. Pechan & Associates, Inc. June 30, 2003.

USACE, 2000: Waterborne Commerce of the United States, Calendar Year 1999 , IWR-WCUS99-2 U.S. Army Corps of Engineers. 2000.

## 53 USACE, 2003: U.S. Waterways Data, Port and Wa terway Facilities, [Data file]. Accessed from U.S. Army Corps of Engineers, http://www.iwr.usace.army.mil/ndc/data/datapwd.htm on December 12, 2003.MACTEC, Inc. 

# Documentation of the Base G 2002 Base Year, 2009 and 2018, Emission Inventories for VISTAS

Prepared for:

Visibility Improvement State and Tr ibal Association of the Southeast (VISTAS)

Prepared by:

MACTEC, Inc.

______________________ ______________________ William R. Barnard Edward Sabo Sr. Principal Scientist Principal ScientistMACTEC, Inc. 

### 2 

# Table of Contents

Introduction .................................................................................................................................................................1

1.0 2002 BASE YEAR INVENTORY DEVELOPMENT ....................................................................................... .4

1.1 P OINT 

### S OURCES



### ............................................................................................................................... ............4

1.1.1 Development of 2002 Po int Source Inventory ..................................................................................... ..4 1.1.1.1 Data Sources ................................................................................................................... ............................. 5 1.1.1.2 Initial Data Evaluation ........................................................................................................ ......................... 6 1.1.1.3 PM Augmen tation................................................................................................................ ........................ 7 1.1.1.4 EGU Analysis ................................................................................................................... ......................... 10 1.1.1.5 QA Review of Base F Inventory.................................................................................................. .............. 11 1.1.1.6 Additional Base G Upda tes and Co rrections...................................................................................... ........ 12 1.1.1.7 Summary of Base G 2002 Inve ntory............................................................................................... ........... 15 

### 1.1.2 Development of Typical Year EGU in ventory...................................................................................... 18 1.2 A REA 

### S OURCES



### ............................................................................................................................... ..........20

1.2.1 Development of a “typical ” year fire inventory ................................................................................. .22 1.2.2 Development of n on-fire inve ntory .............................................................................................. ........31 1.2.3 2002 Base G inventory updates .................................................................................................. .........34 1.2.3.1 Changes resulting from St ate review and comment ................................................................................ ... 34 

### 1.2.4 Ammonia and paved road emissions............................................................................................... .....37 1.2.5 Global Changes Ma de for Base G................................................................................................. ......38 1.2.6 Quality Assura nce steps........................................................................................................ ...............39 1.3 M OBILE 

### S OURCES



### ............................................................................................................................... ......40

1.3.1 Development of on-road mobile so urce input files and VMT estim ates...............................................41 1.3.1.1 Emissions from on-road mobile sources .......................................................................................... .......... 42 

### 1.3.2 Development of non-road emission estimates..................................................................................... .45 1.3.2.1 Emissions from NONRO AD model s ources........................................................................................... ... 45 1.3.2.2 Emissions from Commercial Marine Vesse ls, Locomotives, a nd Airpla nes.............................................. 61 

### Base G R evision s: ..............................................................................................................................................78 1.3.2.3 Emissions from NONROAD Model Sources in Illinois, Indian a, and Ohio .............................................. 85 

### 1.3.3 Quality Assura nce steps........................................................................................................ ...............87

2.0 PROJECTION INVENTORY DEVELOPMENT........................................................................................... .88

2.1 P OINT 

### S OURCES



### ............................................................................................................................... ..........88

2.1.1 EGU Emission Projec tions ....................................................................................................... ...........88 2.1.1.1 Chronology of the Development of EGU Projec tions............................................................................... . 88 2.1.1.2 VISTAS IPM runs for EGU sources................................................................................................ .......... 92 2.1.1.3 Post-Processing of IP M Parsed Files ............................................................................................ ............. 93 2.1.1.4 Eliminating Double C ounting of EGU Units ....................................................................................... ...... 95 2.1.1.5 Quality Assurance steps........................................................................................................ ..................... 96 2.1.1.6 S/L Adjustments to IPM Modeling Results for Base G Projections........................................................... 97 2.1.1.7 Summary of Base F and Base G 2009/2018 EGU Point Source Inventor ies ............................................. 98 

### 2.1.2 Non-EGU Emission Projections ................................................................................................... .....110 2.1.2.1 Growth assumptions for non-EGU sources......................................................................................... ..... 110 2.1.2.2 Source S hutdow ns............................................................................................................... ..................... 112 2.1.2.3 Control Programs applie d to non-E GU sour ces .................................................................................... ... 114MACTEC, Inc. 

### 3 2.1.2.4 Quality Assurance steps........................................................................................................ ................... 117 2.1.2.5 Additional Base G Upda tes and Co rrections...................................................................................... ...... 117 2.1.2.6 Summary of Revised 2009/2018 non-E GU Point Source I nventorie s...................................................... 117 

### 2.2 A REA 

### S OURCES



### ............................................................................................................................... ........123

2.2.1 Stationary ar ea sources ........................................................................................................ .............123 2.2.1.1 Stationary area source controls ................................................................................................ ................ 125 2.2.1.2 Stationary area source growth.................................................................................................. ................ 127 2.2.1.3 Differences be tween 2009/2018

.................................................................................................. ............. 127 

### 2.2.2 Agricultural ar ea sources ...................................................................................................... ............128 2.2.2.1 Control assumptions for agri cultural area sources .............................................................................. ..... 128 2.2.2.2 Growth assumptions for agri cultural area sources ............................................................................... .... 128 

### 2.2.3 Changes to Prescribed Fire for 2009/201 8 Base G...........................................................................133 2.2.4 Quality Assura nce steps........................................................................................................ .............138 2.3 M OBILE 

### S OURCES



### ............................................................................................................................... ....138

2.3.1 Development of on-road m obile source i nput file s ............................................................................141 2.3.1.1 Preparation of revised 2018 input data files................................................................................... .......... 141 2.3.1.2 Preparation of initial 2009 input data files ................................................................................... ............ 144 

### 2.3.2 VMT Data ....................................................................................................................... ...................145 2.3.3 Base G R evisions ............................................................................................................... ................150 2.3.4 Development of non-road emission estimat es....................................................................................1 50 2.3.4.1 NONROAD model source s.......................................................................................................... ............ 151 2.3.4.2 Non-NONROAD m odel s ources...................................................................................................... ........ 153 2.3.4.3 Emissions from NONROAD Model Sources in Illinois, Indian a, and Ohio ............................................ 188 2.3.4.4 Differences be tween 2009/2018

.................................................................................................. ............. 188 

### 2.3.5 Quality Assura nce steps........................................................................................................ .............189



## Appendix A: State Emission Totals by Pollutant and Sector



## Appendix B: State VMT totals



## Appendix C: State Tier 1 Emission Totals



## Appendix D : VISTAS Tier 1 Emission Totals


## Appendix E: Aircraft PM Excerpt from 2001 Tucson Report

Appendix F : Comparison of Base F and Base G On-Road Mobile Emissions

### Documentation of the Base G 2002 Base Year, 2009 and 2018, Emission Inventories for VISTAS

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# List of Tables
Table I-1. Inventory Version in Use by Y ear and Source Sector Through Base G - 2002 Table I-2. Inventory Version in Use by Y ear and Source Sector Through Base G - 2009 Table I-3. Inventory Version in Use by Y ear and Source Sector Through Base G - 2018 Table 1.1-1. State Data Submittals Used for the Base F 2002 Point Source Inventory Table 1.1-2. Comparison of Particulate Matter Emissions from the S/L Data Submittals and the Base G 2002 VISTAS Point Source Inventory Table 1.1-3. Summary of Updates and Corrections to the Base F 2002 Inventory Incorporated into the 2002 Base G Inventory Table 1.1-4. Base G 2002 VISTAS Point Source Inventory for SO 2 

## (tons/year) Table 1.1-5. Base G 2002 VISTAS Point Source Inventory for NO x 

## (tons/year) Table 1.1-6. Base G 2002 VISTAS Point Source Inventory for VOC (tons/year) Table 1.1-7. Base G 2002 VISTAS Point Source Inventory for CO (tons/year) Table 1.1-8. Base G 2002 VISTAS Point Source Inventory for PM 10 

## -PRI (tons/year) Table 1.1-9. Base G 2002 VISTAS Point Source Inventory for PM 2.5 

## -PRI (tons/year) Table 1.1-10. Base G 2002 VISTAS Point Source Inventory for NH 3 

## (tons/year) Table 1.1-11. Comparison of SO 2 

## and NO x 

## Emissions (tons/year) for EGUs from Base G Actual 2002 Inventory and Typical 2002 Inventory. Table 1.2-1. Emissions from Fires in the VI STAS Region – Comparison between Original Base Year 2002 (VISTAS 3.1), 2002 Actual and Typical Year Base G Emissions. Table 1.2-2. Summary of State Data Submittals for the 2002 VISTAS Area Source Base F Inventory Table 1.2-3. Data Source Codes and Data Sources for VISTAS 2002 Base F Area Source Emissions Inventory. Table 1.3-1. Representative day mapping for January episode Table 1.3-2. Summary of Base F NONROAD Modeling Revisions Table 1.3-3. Base F NONROAD Input File Sequence and Structural Revisions Table 1.3-4. Summary of Base G NONROAD Modeling Revisions Table 1.3-5. Spring 2006 NONROAD Input File Sequence and Structural Revisions Table 1.3-6. Initial 2002 Base Year Aircraft, Locomotive, and Non-Recreational Marine Emissions as Reported in February 2004 Pechan Report (annual tons) Table 1.3-7. PM-to-NO x 

## Ratios by Aircraft Type in Initial 2002 Base Year Inventory Table 1.3-8. Tucson, AZ PM-to-NO x 

## Ratios by Aircraft Type. Table 1.3-9. Non-Corresponding Aircraft Emissions Records Table 1.3-10. Initial 2002 Base Year Aircraft, Locomotive, and Non-Recreational Marine Emissions with Modified Aircraft PM Emission Rates (annual tons) Table 1.3-11. Change in Initial 2002 Base Year Em issions due to Aircraft PM Emission Rate Modifications Table 1.3-12. CERR Aircraft NO x 

## Records with No Corresponding PM Record.

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## List of Tables (continued)

Table 1.3-13. Calculated Emission Ratios for VA. Table 1.3-14. Base F 2002 Base Year Aircraft , Locomotive, and Non-Recreational Marine Emissions (tons/year) Table 1.3-15. Change in 2002 Emissions, Base F Inventory Relative to Initial Inventory Table 1.3-16. Base F Comparison of Aircraft Emissions (Airports with Aircraft NO x 

## > 200 tons per year) Table 1.3-17. Base G VA Aircraft Records Updates Table 1.3-18. Calculated Base G Emission Ratios for VA Table 1.3-19. Base G-Revised 2002 Base Year Aircraft, Locomotive, and Non-Recreational Marine Emissions (tons/year) Table 1.3-20. Change in 2002 Emissions, Base G Inventory Relative to Base F Inventory Table 1.3-21. Base G Comparison of Aircraft Emissions (Airports with Aircraft NO x 

## > 200 tons per year) Table 1.3-22. Non-Default Files Used for MRPO Modeling Table 2.1-1. Adjustments to IPM Control Determinations Specified by S/L Agencies for the Base G 2009/2018 EGU Inventories. Table 2.1-2. Other Adjustments to IPM Results Specified by S/L Agencies for the Base G 2009/2018 EGU Inventories. Table 2.1-3. EGU Point Source SO 2 

## Emission Comparison for 2002/2009/2018 Table 2.1-4. EGU Point Source NO x 

## Emission Comparison for 2002/2009/2018 Table 2.1-5. EGU Point Source VOC Emission Comparison for 2002/2009/2018 Table 2.1-6. EGU Point Source CO Emission Comparison for 2002/2009/2018 Table 2.1-7. EGU Point Source PM 10 

## -PRI Emission Comparison for 2002/2009/2018 Table 2.1-8. EGU Point Source PM 2.5 

## -PRI Emission Comparison for 2002/2009/2018 Table 2.1-9. EGU Point Source NH 3 

## Emission Comparison for 2002/2009/2018 Table 2.1-10. Summary of Source Shutdowns Incorporated in Base G Inventory Table 2.1-11. Non-EGU Point Source Control Programs Included in 2009/2018 Projection Inventories. Table 2.1-12. Summary of Updates and Corrections to the Base F 2009/2018 Inventories Incorporated into the Base G 2009/2018 Inventories Table 2.1-13. Non-EGU Point Source SO 2 

## Emission Comparison for 2002/2009/2018 Table 2.1-14. Non-EGU Point Source NO x 

## Emission Comparison for 2002/2009/2018 Table 2.1-15. Non-EGU Point Source VOC Emission Comparison for 2002/2009/2018 Table 2.1-16. Non-EGU Point Source CO Emission Comparison for 2002/2009/2018 Table 2.1-17. Non-EGU Point Source PM 10 

## -PRI Emission Comparison for 2002/2009/2018 Table 2.1-18. Non-EGU Point Source PM 2.5 

## -PRI Emission Comparison for 2002/2009/2018. Table 2.1-19. Non-EGU Point Source NH 3 

## Emission Comparison for 2002/2009/2018 List of Tables (continued)

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## Table 2.2-1 2002 Base Year Emissions and Per centage Difference for Base F and Base G (based on actual emissions). Table 2.2-2 2019 Projection Year Emissions &P ercentage Difference for Base F & Base G Table 2.2-3 2018 Projection Year Emissions & Pe rcentage Difference for Base F & Base G Table 2.2-4 Percentage Difference Between Base F and Base G Fire Emissions by State Table 2.3-1. 2002 versus 2018 VMT (million miles per year) Table 2.3-2. VMT and HDD Rule Estimates for North Carolina (million miles per year) Table 2.3-3. VMT and HDD Rule Estimates for South Carolina (million miles per year) Table 2.3-4. VMT and HDD Rule Estimates for Tennessee (million miles per year) Table 2.3-5. VMT and HDD Rule Estimates for Virginia (million miles per year) Table 2.3-6. Pre-Base F 2002 Aircraft, Locomotiv e, and Non-Recreational Marine Emissions (annual tons, as of the fall of 2004) Table 2.3-7. Locally Generated Growth Factors for North Carolina Table 2.3-8. Estimated Emission Reduction Impacts based on T-4 Rule Table 2.3-9. Estimated Emission Reduction Impacts Relative to VISTAS 2002 Base Year Values Table 2.3-10. Diesel CMV Adjustment Ratios for Palm Beach County, FL Table 2.3-11. Overall Adjustment Factors for Palm Beach County, FL Table 2.3-12. SO 2 

## Emissions for Diesel Rail in Autauga County, AL from the CAIR Projections Table 2.3-13 Growth Options based on CAIR Data Table 2.3-14. Base F 2009 Aircraft, Locomotive, and Non-Recreational Marine Emissions (annual tons) -- Based on Growth Using 1996 and 2020 EPA Inventories Table 2.3-15. Base F 2018 Aircraft, Locomotive, and Non-Recreational Marine Emissions (annual tons) -- Based on Growth Using 1996 and 2020 EPA Inventories Table 2.3-16. Change in Emissions between 2009 and 2002 Base F Inventories (Based on Growth Using 1996 and 2020 EPA Inventories) Table 2.3-17. Change in Emissions between 2018 and 2002 Base F Inventories (Based on Growth Using 1996 and 2020 EPA Inventories) Table 2.3-18. Base G 2002 Aircraft, Locomotive, and Non-Recreational Marine Emissions (annual tons) Table 2.3-19. Locally Generated Growth Factors for Kentucky Table 2.3-20. Base G 2009 Aircraft, Locomotive, and Non-Recreational Marine Emissions (annual tons) -- Based on Growth Using 1996 and 2020 EPA Inventories Table 2.3-21. Base G 2018 Aircraft, Locomotive, and Non-Recreational Marine Emissions (annual tons) -- Based on Growth Using 1996 and 2020 EPA Inventories Table 2.3-22. Change in Emissions between 2009 Base G and 2002 Base F Inventories (Based on Growth Using 1996 and 2020 EPA Inventories) Table 2.3-23. Change in Emissions between 2018 Base G and 2002 Base F Inventories (Based on Growth Using 1996 and 2020 EPA Inventories)

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# List of Figures

Figure 1.2-1. CO Emissions from Agricultura l Burning for the Original Base Year, 2002 Actual Base G, and 2002 Typical Base G Inventories. Figure 1.2-2. CO Emissions from Land Clearing Burning for the Original Base Year, 2002 Actual Base G and 2002 Typical Base G Inventories. Figure 1.2-3. CO Emissions from Prescribed Bu rning for the Original Base Year, 2002 Actual Base G and 2002 Typical Base G Inventories. Figure 1.2-4. CO Emissions from Wildfire Burn ing for the Original Base Year, 2002 Actual Base G and 2002 Typical Base G Inventories. Figure 2.2-1. Prescribed Fire Projection for Okeefenokee NWR for 2009 Figure 2.3-1. Impacts of the Apparent CAIR Inventory Discrepancy Figure 2.3-2. Total Aircraft, Locomotive, and CMV CO Emissions (Base F) Figure 2.3-3. Locomotive CO Emissions (Base F) Figure 2.3-4. Total Aircraft, Locomotive, and CMV NO x 

## Emissions (Base F) Figure 2.3-5. Locomotive NO x 

## Emissions (Base F) Figure 2.3-6. Total Aircraft, Locomotive, and CMV PM 10 

## Emissions (Base F) Figure 2.3-7. Locomotive PM 10 

## Emissions (Base F) Figure 2.3-8. Total Aircraft, Locomotive, and CMV PM 2.5 

## Emissions (Base F) Figure 2.3-9. Locomotive PM 2.5 

## Emissions (Base F) Figure 2.3-10. Total Aircraft, Locomotive, and CMV SO 2 

## Emissions (Base F) Figure 2.3-11. Locomotive SO 2 

## Emissions (Base F) Figure 2.3-12. Total Aircraft, Locomotive, and CMV VOC Emissions (Base F) Figure 2.3-13. Locomotive VOC Emissions (Base F) Figure 2.3-14. Total Aircraft, Locomotive, and CMV CO Emissions (Base G) Figure 2.3-15. Locomotive CO Emissions (Base G) Figure 2.3-16. Total Aircraft, Locomotive, and CMV NO x 

## Emissions (Base G) Figure 2.3-17. Locomotive NO x 

## Emissions (Base G) Figure 2.3-18. Total Aircraft, Locomotive, and CMV PM 10 

## Emissions (Base G) Figure 2.3-19. Locomotive PM 10 

## Emissions (Base G) Figure 2.3-20. Total Aircraft, Locomotive, and CMV PM 2.5 

## Emissions (Base G) Figure 2.3-21. Locomotive PM 2.5 

## Emissions (Base G) Figure 2.3-22. Total Aircraft, Locomotive, and CMV SO 2 

## Emissions (Base G) Figure 2.3-23. Locomotive SO 2 

## Emissions (Base G) Figure 2.3-24. Total Aircraft, Locomotive, and CMV VOC Emissions (Base G) Figure 2.3-25. Locomotive VOC Emissions (Base G)

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# Acronyms and Abbreviations

AEO Annual Energy Outlook AF&PA American Forest and Paper Association APCD Air Pollution Control District ATP Anti-Tampering Program BLRID Boiler Identification (Boiler ID) CAA Clean Air Act CAIR Clean Air Interstate Rule CEM Continuous Emissions Monitoring CAMD Clean Air Markets Division CERR Consolidated Emissions Reporting Rule CMU Carnegie Mellon University CMV commercial marine vessels CE Control Efficiency CO carbon monoxide DENR North Carolina Department of Environment and Natural Resources DHEC South Carolina Department of Health and Environmental Control EDMS Emissions Data Management Systems ESD Emissions Standards Division EPA Environmental Protection Agency EGU Electric Generating Unit ICF ICF International, Inc. FIP Federal Implementation Plan FLM Federal Land Manager FTP File transfer protocol FR Federal Register FS Forest Service HDD Heavy Duty Diesel HDD RULE Heavy Duty Diesel Rule ICF ICF International, Inc. ID Identification I/M Inspection and Maintenance IPM ® 

## Integrated Planning Model ® 

## IAQTR Interstate Air Quality Transport Rule LTO Landing and take off MACT Maximum achievable control technology

### Documentation of the Base G 2002 Base Year, 2009 and 2018, Emission Inventories for VISTAS

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## Acronyms and Abbreviations (continued) MACTEC MACTEC Engineering and Consulting, Inc. MOBILE 6 MOBILE emissions estimation model version 6 MRPO Midwest Regional Planning Organization
NH 3 

## Ammonia
NEI National Emission Inventory NIF National Emission Inventory Format NLEV National Low Emission Vehicle regulation NMIM National Mobile Inventory Model NONROAD no acronym (model name) NO x 

## Oxides of nitrogen NWR National Wildlife Refuge
OTB On the books OTW On the way ORIS Office of Regulatory Information Systems OTAQ Office of Transportation and Air Quality OTC Ozone Transport Commission PFC Portable fuel containers PM Particulate matter PM 10 

## -FIL Particulate matter less than or equal to 10 microns in diameter that can be captured on a filter PM 10 

## -PRI Particulate matter less than or equal to 10 microns in diameter that includes both the filterable and condensable components of particulate matter PM 2.5 

## -FIL Particulate matter less than or equal to 2.5 microns in diameter that can be captured on a filter PM 2.5 

## -PRI Particulate matter less than or equal to 2.5 microns in diameter that includes both the filterable and condensable components of particulate matter PM-CON Particulate matter created by the condensation of hot materials to form particulates, usually less than 2.5 microns in diameter ppmW parts per million by weight PRI Primary QA/QC Quality Assurance/Quality Control QAPP Quality Assurance Project Plan REMI Regional Economic Models, Inc. RFG Reformulated gasoline RVP Reid Vapor Pressure SCC Source Classification Code

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## Acronyms and Abbreviations (continued) SCR Selective Catalytic Reduction SIP State Implementation Plan SIWG Special Interest Workgroup S/L/T State/Local/Tribal SMOKE Sparse Matrix Operator Kernel Emissions Modeling System S/L State and Local SO 2 

## Oxides of Sulfur T4 Tier 4 VISTAS Visibility Improvement State and Tribal Association of the Southeast VMT Vehicle Miles Traveled VOC Volatile organic compounds WRAP Western Regional Air Partnership

### Documentation of the Base G 2002 Base Year, 2009 and 2018, Emission Inventories for VISTAS

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# Documentation of the Base G 2002 Base Year, 2009 and 2018, Emission Inventories for VISTAS

Introduction
History of VISTAS Base and Projection Year Emission Inventory Development
This section is provided to supply the hist ory behind the development of the base and projection year inventories provided to VISTAS. Through the various iterations, the inventories that have been developed have typically had version numbers provided by the contractors who developed the inventories and to a certain extent these were also based on their purpose. Different components of th e 2002 base year inventories have been supplied by E.H. Pechan and Associates, Inc. (Pechan), MACTEC Engineering and Consulting, Inc. (MACTEC), and by Alpine Geophysics, Inc.
The initial 2002 base year inventory was jo intly developed by Pechan and MACTEC. Pechan developed the on-road and non-road mobile source components of the inventory while MACTEC developed the point and area source component of the inventory. This version of the inventory included updates to on-road mobile that incorporated information from the 1999 NEI Version 2 fi nal along with updated information on VMT, fuel programs, and other inputs to the MOBI LE6 model to produce a draft version of the 2002 inventory. For non-road sources, a similar approach was used. Updated State information on temperatures and fuel charact eristics were obtained from VISTAS States and used with the NONROAD 2002 model to calculate 2002 emissions for NONROAD model sources. These estimates were coupled with data for commercial marine vessels, locomotives and airplanes projected to 2002 us ing appropriate growth surrogates. A draft version of these inventories was prepared in late 2003, with a final version in early 2004. An overview of the development of th e on-road component can be found at: http://www.vistas-sesarm.org/documents/Pechan_drafton-roadinventory_082803.ppt while an overview of the non-road component can be found at: http://www.vistas-sesarm.org/documents/Pechan_Non-roadInventory_082803.ppt

. Similarly, draft versions of the 2002 point a nd area source base year inventories were prepared by MACTEC in the same timeframe (late 2003 for the draft, final in early 2004). The point source component was based on data submitted by the VISTAS States or on the 1999 NEI. The data submitted by th e States ranged from 1999 to 2001 and was all projected to 2002 using appropriate gr owth surrogates from Economic Growth

### Documentation of the Base G 2002 Base Year, 2009 and 2018, Emission Inventories for VISTAS

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## Analysis System (EGAS) version 4. Toxic Rel ease Inventory (TRI) data were used to augment the inventory for NH 3 

## . Continuous Emissions Monitor (CEM) data from the U.S. EPA’s Clean Air Markets Division wa s used to supply emissions for electric generating utilities (EGUs). Particulate matter emissions were augmented (when missing) by using emission factor ratios. Details on all these calculations are discussed in Section 1.1.1.3 of this document.
The area source component of the 2002 draft base year emissions was prepared similarly to the point sources, using State submittals and the 1999 NEI Version 2 final as the basis for projecting emissions to 2002 using EGAS growth factors. For ammonia area sources the Carnegie Mellon University (CMU) ammoni a model was used to calculate emissions. Finally, data on acreage burned on a fire by fire basis was solicited from State forestry agencies in order to calculate fire emissions on a fire by fire basis. Virtually all VISTAS State forestry agencies provided data for these calculations at least for wild and prescribed fires. An overview of the point and area source development methods can be found at: http://www.vistas-sesarm.org/documen ts/MACTEC_draftpointareainventory_82803.ppt

. Three interim versions of the 2002 base year inventory were developed. The first was delivered in August of 2003, the second in Apr il of 2004 and the final one in October of 2004. The August 2003 and April 2004 inventor ies were prepared by MACTEC and Pechan. A draft version of the revised 2002 base year inventory was released in June of 2004, with a final version released in Oct ober 2004. That 2002 base year inventory was solely prepared by MACTEC. The Oc tober 2004 inventory incorporated 2002 Consolidated Emissions Reporting Rule (CERR) data into the inventory along with some updated data from the VISTAS States. This i nventory is typically referred to as version 3.1 of the VISTAS inventory
Closely following the version 3.1 2002 base year inventory, a “preliminary” 2018 projection inventory was developed. This “p reliminary” 2018 inventory was developed in late 2004 (Oct/Nov) and was designed solely for use in modeling sensitivity runs to provide a quick and dirty assessment of what “on the books” and “on the way” controls could be expected to provide in terms of improvements to visibility and regional haze impairment. A brief overview of the history of the three versions of the 2002 base year and the 2018 preliminary inventory use can be found at: http://www.vistassesarm.org/documents/STAD1204/2002and2018Emissions14Dec2004.ppt

. Following preparation of the final 3.1 versi on of the 2002 base year inventory, States were asked to review and provide comment s on that inventory to MACTEC for update

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## and revision. At the same time MACTEC prep ared a revised draft version of the 2018 projection inventory (January 2005) and a dr aft version of a 2009 projection inventory (April 2005). All of these were known as vers ion 3.1 and were provided to the VISTAS States for review and comment. Comments we re received and updates to the inventories based on these comments were prepared. The revised inventories were provided to the VISTAS States. At that time to be consiste nt with the modeling nomenclature being used by AG in performing their modeling runs, th e inventory became the Base F VISTAS inventory. The Base F inventory was deliver ed for review and comment in August of 2005. In addition, MACTEC delivered a report entitled Documentation of the Revised 2002 Base Year, Revised 2018, and Initial 2009 Emission Inventories for VISTAS on August 2, 2005 that described the methods used to develop the Base F inventories. For the Electric Generating Utilities (EGU) different versions of the Integrated Planning Model were used between Base D and Base F, resulting in different projections of future EGU emissions.
Over the period from August 2005 until J une/July 2006 MACTEC received comments and updates to some categories from VISTAS States, particularly EGU. In addition, a new NONROAD model (NONROAD05) was releas ed. Thus additional updates to the inventory were prepared based on the comments received along with revised NONROAD emission estimates from NONROAD05. The re sultant inventory became the Base G inventory.
This document details the development of the Base G inventories for 2002, 2009 and 2018. The information that follows describes the development of the VISTAS inventory by sector from version 3.1 forward. Unless sp ecific updates were made to an inventory sector, the methods used for version 3.1 were retained. Similarly unless specific changes were made to methods used for Base F, Base G methods were the same as Base F/version 3.1 (if unchanged in Base F).
Table I-1 through Table I-3 indicate roughly whic h version of the inventory is in use for each sector of the inventory as of Base G.

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## Table I-1: Inventory Version in Use by Year and Source Sector Through Base G - 2002

Source AL FL GA KY MS NC SC TN VA WV EGU Base G Base G Base G Base G Base G Base G Base G Base G Base G Base G Non-EGU Point Base F with

some source specific revisions in Base G Base F with

some source specific revisions in Base G Base F with

some source specific revisions in Base G Base F with

some source specific revisions in Base G Base F with

some source specific revisions in Base G Base F with

some source specific revisions in Base G Base F with

some source specific revisions in Base G Base F with

some source specific revisions in Base G Base F with

some source specific revisions in Base G Base F with

some source specific revisions in Base G Area 1 Base F for ammonia

sources (CMU Model) and for some area sources, Base G for selected

sources updated by the State with State supplied data Base F except for some emissions zeroed out (and records removed) for

some southern FL counties for Base G. Base F Base F Base F Base F for ammonia

sources (CMU Model) and for some area sources, Base G for selected

sources updated by the State with State supplied data. Some corrections applied by MACTEC to correct PM values Base F Base F Base F for ammonia Sources (CMU Model) and for some area sources, Base G for selected

sources updated by the State with State supplied data. Base F

On-road Base G Base G Base G Base G Base G Base G Base G Base G Base G Base G Non-road Base G for all

sources included in the NONROAD model.

Base F for

nonNONROAD model sources, except aircraft and locomotives updated for Base G. Base G for all

sources included in the NONROAD model.

Base F for

nonNONROAD model

sources Base G for all

sources included in the NONROAD model.

Base F for

nonNONROAD model

sources Base G for all

sources included in the NONROAD model.

Base F for

nonNONROAD model

sources except for aircraft in Cincinnati/N. KY Int. Airport, which are Base G. Base G for all

sources included in the NONROAD model.

Base F for

nonNONROAD model

sources Base G for all

sources included in the NONROAD model. NC moved from Southern to Mid-Atlantic State in seasonal adjustment file.

Base F for

nonNONROAD model

sources Base G for all

sources included in the NONROAD model.

Base F for

nonNONROAD model

sources Base G for all

sources included in the NONROAD model.

Base F for

nonNONROAD model

sources Base G for all

sources included in the NONROAD model.

Base F for

nonNONROAD model sources, except for aircraft emissions which are Base G. Base G for all

sources included in the NONROAD model.

Base F for

nonNONROAD model

sources

Fires Base F Typical Base F Typical Base F Typical Base F Typical Base F Typical Base F Typical Base F Typical Base F Typical Base F Typical Base F Typical Notes:

Base G global Area Source changes that apply to ALL States: A) removal of Stage II refueling from area source file to non-road and on-road; B) modification of PM2.5 ratio for several f ugitive dust sources per WRAP methodology; C) addition of portable fuel container (PFC ) emissions to all States based on OTAQ report.

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## Table I-2: Inventory Version in Use by Year and Source Sector Through Base G - 2009

Source AL FL GA KY MS NC SC TN VA WV EGU 1 Base G Base G Base G Base G Base G Base G Base G Base G Base G Base G Non-EGU Point 2 Base F methodology but with revised growth factors for fuel fired sources in Base G Base F methodology but with revised growth factors for fuel fired sources in Base G Base F methodology but with revised growth factors for fuel fired sources in Base G Base F methodology but with revised growth factors for fuel fired sources in Base G Base F methodology but with revised growth factors for fuel fired sources in Base G Base F methodology but with revised growth factors for fuel fired sources in Base G Base F methodology but with revised growth factors for fuel fired sources in Base G Base F methodology but with revised growth factors for fuel fired sources in Base G Base F methodology but with revised growth factors for fuel fired sources in Base G Base F methodology but with revised growth factors for fuel fired sources in Base G Area Base F with updated AEO growth factors for fuel fired

sources. Agricultural ammonia sources from CMU model. Base F with updated AEO growth factors for fuel fired

sources. Agricultural ammonia sources from CMU model. Base F with updated AEO growth factors for fuel fired

sources. Agricultural ammonia sources from CMU model. Base F with updated AEO growth factors for fuel fired

sources. Agricultural ammonia sources from CMU model. Base F with updated AEO growth factors for fuel fired

sources. Agricultural ammonia sources from CMU model. Base F with updated AEO growth factors for fuel fired

sources. Agricultural ammonia sources from CMU model.

Some specific

source categories updated using State supplied file to override projected values. Base F with updated AEO growth factors for fuel fired

sources. Agricultural ammonia sources from CMU model. Base F with updated AEO growth factors for fuel fired

sources. Agricultural ammonia sources from CMU model. Base F with updated AEO growth factors for fuel fired

sources. Agricultural ammonia sources from CMU model. Base F with updated AEO growth factors for fuel fired

sources. Agricultural ammonia sources from CMU model.

On-road Base G Base G Base G Base G Base G Base G Base G Base G Base G Base G Non-road Base G for all

sources included in the NONROAD model.

Base F projection methodologyused for nonNONROAD model

sources. Base G for all

sources included in the NONROAD model.

Base F projection methodologyused for nonNONROAD model

sources Base G for all

sources included in the NONROAD model.

Base F projection methodologyused for nonNONROAD model

sources Base G for all

sources included in the NONROAD model.

Base F projection methodologyused for nonNONROAD model

sources except for aircraft in Cincinnati/N. KY Int. Airport, which are Base G using State supplied growth factors. Base G for all

sources included in the NONROAD model.

Base F projection methodologyused for nonNONROAD model

sources Base G for all

sources included in the NONROAD model.

Base F projection methodologyused for nonNONROAD model

sources Base G for all

sources included in the NONROAD model.

Base F projection methodologyused for nonNONROAD model

sources Base G for all

sources included in the NONROAD model.

Base F projection methodologyused for nonNONROAD model

sources Base G for all

sources included in the NONROAD model.

Base F projection methodologyused for nonNONROAD model

sources Base G for all

sources included in the NONROAD model.

Base F projection methodologyused for nonNONROAD model

sources

Fires Base F typical except for Rx fires Base F typical Base F typical except for Rx fires Base F typical except for Rx fires Base F typical except for Rx fires Base F typical except for Rx fires Base F typical except for Rx fires Base F typical except for Rx fires Base F typical except for Rx fires Base F typical except for Rx fires Notes: 1. All EGU emissions updated with new IPM runs in Base G 2. Revised growth factors from DOE AEO2006 fuel use projections

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## Table I-3: Inventory Version in Use by Year and Source Sector Through Base G - 2018

Source AL FL GA KY MS NC SC TN VA WV EGU 1 Base G Base G Base G Base G Base G Base G Base G Base G Base G Base G Non-EGU Point 2 Base F methodology but with revised growth factors for fuel fired sources in Base G Base F methodology but with revised growth factors for fuel fired sources in Base G Base F methodology but with revised growth factors for fuel fired sources in Base G Base F methodology but with revised growth factors for fuel fired sources in Base G Base F methodology but with revised growth factors for fuel fired sources in Base G Base F methodology but with revised growth factors for fuel fired sources in Base G Base F methodology but with revised growth factors for fuel fired sources in Base G Base F methodology but with revised growth factors for fuel fired sources in Base G Base F methodology but with revised growth factors for fuel fired sources in Base G Base F methodology but with revised growth factors for fuel fired sources in Base G Area Base F with updated AEO growth factors for fuel fired

sources. Agricultural ammonia sources from CMU model. Base F with updated AEO growth factors for fuel fired

sources. Agricultural ammonia sources from CMU model. Base F with updated AEO growth factors for fuel fired

sources. Agricultural ammonia sources from CMU model. Base F with updated AEO growth factors for fuel fired

sources. Agricultural ammonia sources from CMU model. Base F with updated AEO growth factors for fuel fired

sources. Agricultural ammonia sources from CMU model. Base F with updated AEO growth factors for fuel fired

sources. Agricultural ammonia sources from CMU model.

Some specific

source categories updated using State supplied file to override projected values. Base F with updated AEO growth factors for fuel fired

sources. Agricultural ammonia sources from CMU model. Base F with updated AEO growth factors for fuel fired

sources. Agricultural ammonia sources from CMU model. Base F with updated AEO growth factors for fuel fired

sources. Agricultural ammonia sources from CMU model. Base F with updated AEO growth factors for fuel fired

sources. Agricultural ammonia sources from CMU model.

On-road Base G Base G Base G Base G Base G Base G Base G Base G Base G Base G Non-road Base G for all sources included in the NONROAD model.

Base F projection methodologyused for nonNONROAD model

sources. Base G for all sources included in the NONROAD model.

Base F projection methodologyused for nonNONROAD model

sources Base G for all sources included in the NONROAD model.

Base F projection methodologyused for nonNONROAD model

sources Base G for all sources included in the NONROAD model.

Base F projection methodologyused for nonNONROAD model

sources except for aircraft in Cincinnati/N. KY Int. Airport, which are Base G using State supplied growth factors. Base G for all sources included in the NONROAD model.

Base F projection methodologyused for nonNONROAD model

sources Base G for all sources included in the NONROAD model.

Base F projection methodologyused for nonNONROAD model

sources Base G for all sources included in the NONROAD model.

Base F projection methodologyused for nonNONROAD model

sources Base G for all sources included in the NONROAD model.

Base F projection methodologyused for nonNONROAD model

sources Base G for all sources included in the NONROAD model.

Base F projection methodologyused for nonNONROAD model

sources Base G for all sources included in the NONROAD model.

Base F projection methodologyused for nonNONROAD model

sources

Fires Base F typical except for Rx fires Base F typical Base F typical except for Rx fires Base F typical except for Rx fires Base F typical except for Rx fires Base F typical except for Rx fires Base F typical except for Rx fires Base F typical except for Rx fires Base F typical except for Rx fires Base F typical except for Rx fires Notes : 1. All EGU emissions updated with new IPM runs in Base G 2. Revised growth factors from DOE AEO2006 fuel use projections

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## 1.0 2002 Base Year Inventory Development

1.1 Point Sources
This section details the development of the 2002 base year inventory for point sources. There were two major components to the development of the point source sector of the inventory. The first component was the incorporation of data submitted by the Visibility Improvement State and Tribal Association of he Southeast (VISTAS) Stat es and local (S/L) agencies to the United States Environmental Protection Agency (EPA) as part of the Consolidated Emissions Reporting Rule (CERR) requirements Work on incorporating the CERR data into the revised base year involved: 1) obtaining the data from EPA or the S/L agency, 2) evaluating the emissions and pollutants reported in the CERR submittals, 3) augmenting CERR data with annual emission estimates for PM 10 

## -PRI and PM 2.5 

## -PRI; 4) evaluating the emissions from electric generating units, 5) completing quality assurance reviews for each component of the point source inventory, and 6) updating the database with corrections or new information from S/L agencies based on their review of the 2002 inventory. The processes used to perform those operations are described in the first portion of this section.
The second component was the development of a “t ypical” year inventory for electric generating units (EGUs). VISTAS determined that a typical year electric generating units (EGU) inventory was necessary to smooth out any anomalies in emissions from the EGU sector due to meteorology, economic, and outage factors in 2002. Th e typical year EGU inventory is intended to represent the five year (2000-2004) period that will be used to determine the regional haze reasonable progress goals. The second part of this section discusses the development of the typical year EGU inventory.
1.1.1 Development of 2002 Point Source Inventory MACTEC developed a draft 2002 emission inventory in June 2004 ( Development of the Draft 2002 VISTAS Emission Inventory for Regional Haze Modeling – Point Sources , MACTEC, June 18, 2004). The starting point for the draft 2002 emission inventory was EPA’s 1999 National Emission Inventory (NEI), Version 2 Final (N EI99V2). For several states, we replaced the NEI99V2 data with more recent inventories for either calendar year 1999, 2000, or 2001 as submitted by the S/L agencies. We also performed several other updates, including updating emission estimates for selected large source of ammonia, incorporating 2002 Continuous Emissions Monitoring-(CEM)-based SO 2 

## and NO x 

## emissions for electric utilities, adding PM 10 

## and PM 2.5 

## emissions when they were missing from an S/L submittal, and performing a variety of additional Quality assurance/Quality control (QA/QC) checks.

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## The next version of the 2002 inventory (referred to as Base F) was released in August 2005 ( Documentation of the Revised 2002 Base Year, Revised 2018, and Initial 2009 Emission Inventories for VISTAS , MACTEC, August 2, 2005). The primary task in preparing the Base F 2002 base year inventory was the replacement of NEI99V2 data with data submitted by the VISTAS S/L agencies as part of the CERR submittal and included in EPA’s 2002 NEI.
The current version of the 2002 inventory (referred to as Base G) was released in August 2006 and is documented in this report. The primary task in preparing the Base G 2002 base year inventory was the incorporation of corrections and new information as submitted by the S/L agencies based on their review of the Base F inventory. The following subsections document the data sources for the Base G inventory, the checks made on the CERR submittals, the process for augmenting the inventory with PM 10 

## and PM 2.5 

## emissions, the evaluation of EGU emissions, other QA/QC checks, and other Base G updates. The final subsection summarizes the Base G 2002 inventory by state, pollutant , and sector (EGU and non-EGU).

1.1.1.1 Data Sources Several data sources were used to compile the Ba se F point source inventory: 1) the inventories that the S/L submitted to EPA from May through July 2004 as required by the CERR; 2) supplemental data supplied by the S/L agencies that may have been revised or finalized after the CERR submittal to EPA, and 3) the draft VISTAS 2002 inventory in cases where S/L CERR data were not available. For the Base G i nventory, we replaced data from Hamilton County, Tennessee, using data from Hamilton County’s CERR submittal as contained in EPA’s 2002 NEI inventory (in Base F, the inventory for Ha milton County was based on the draft VISTAS 2002 inventory, which in turn was based on the 1999 NEI).
Table 1.1-1 summarizes the data used as the starting point for the Base F 2002 inventory. Once all of the files were obtained, MACTEC ran the files through the EPA National Emission Inventory Format (NIF) Basic Format and Content checking tool to ensure that the files were submitted in standard NIF format and that there were no referential integrity issues with those files. In a couple of cases small errors were found. For example, in one case non-standard pollutant designations were used for particulate matter (PM) and ammonia emissions. MACTEC contacted each VISTAS State point source contact person to resolve the issues with the files and corrections were made. Once all corrections to the native files were made, MACTEC continued with the incorporation of the data into the VISTAS point source files. S/L agencies completed a detailed review of the Base F inventory. Additional updates and corrections to the Base F inventory were requested by S/L agencies and incorporated into the Base G inventory. The Base G changes are documented in more detail in Section 1.1.1.6.

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## Table 1.1-1. State Data Submittals Used for the Base F 2002 Point Source Inventory.

State / Local Program Point Source Emissions Data Source AL C FL B GA B KY C MS B NC C SC C TN C VA B WV B Davidson County, TN B Hamilton County, TN D Memphis/Shelby County, TN B Knox County, TN B Jefferson County, AL B Jefferson County, KY B Buncombe County, NC B

Forsyth County, NC B Mecklenburg County, NC B Key A = Draft VISTAS 2002 B = CERR Submittal from EPA's file transfer protocol (FTP) site C = Other (CERR or other submittal sent directly from S/L agency to MACTEC) D = CERR Submittal from EPA’s NEI 2002 Final Inventory



## 1.1.1.2 Initial Data Evaluation For the Base F inventory, we conducted an initial review of the 2002 point source CERR data in accordance with the QA procedures specified in the Quality Assurance Project Plan (QAPP) for this project. The following evaluations were completed to identify potential data quality issues associated with the CERR data:

• 

## Compared the number of sites in the CERR submittal to the number of sites in the VISTAS draft 2002 inventory; for all States, the number of sites in the CERR submittal was less than in the VISTAS draft 2002 inventory, since the CERR data was limited to major sources, while the VISTAS draft 2002 inventory contained data for both major and minor sources; verified with S/L contacts th at minor sources not included in the CERR point source inventory were include d in the CERR area source inventory.

• 

## Checked for correct pollutant codes and corrected to make them NIF-compliant; for example, some S/L agencies reported ammonia emissions using the CAS Number or as “ammonia”, rather than the NIF-compliant “NH 3 

## ” code.

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## Checked for types of particulate matter codes reported (i.e., PM-FIL, PM-CON, PM-PRI, PM 10 

## -PRI, PM10-FIL, PM 2.5 

## -PRI, PM 2.5 

## -FIL); corrected codes with obvious errors (i.e., changed PMPRI to PM-PRI). (The PM augmentation process for filling in missing PM pollutants is discussed later in Section 1.1.1.3)

• 

## Converted all emission values that weren’t in tons to tons to allow for preparation of emission summaries using consistent units.

• 

## Checked start and end dates in the PE and EM tables to confirm consistency with the 2002 base year.

• 

## Compared annual and daily emissions when daily emissions were reported; in some cases, the daily value was non-zero (but very small) but the annual value was zero. This was generally the result of rounding in an S/L agency’s submittal.

• 

## Compared ammonia emissions as reported in the CERR submittals and the 2002 Toxics Release Inventory; worked with S/L agencies to resolve any outstanding discrepancies.

• 

## Compared SO 2 

## and NO x 

## emissions for EGUs to EPA’s Clean Air Markets Division CEM database to identify any outstanding discrepancies. (A full discussion of the EGU emissions analysis is discussed later in Section 1.1.1.4)

• 

## Prepared State-level emission summaries by pollutant for both the EGU and non-EGU sectors to allow S/L agencies to compare emissions as reported in the 1999 NEI Version 2, the VISTAS draft 2002 inventory, and the CERR submittals.

• 

## Prepared facility-level emission summaries by pollutant to allow S/L agencies to review facility level emissions for reasonableness and accuracy.
We communicated the results of these analyses through email/telephone exchanges with the S/L point source contacts as well as through Excel summary spreadsheets. S/L agencies submitted corrections and updates as necessary to resolve any QA/QC issues from these checks.
1.1.1.3 PM Augmentation Particulate matter emissions can be reported in many different forms, as follows:
PM Category Description PM-PRI Primary PM (includes filterable and condensable) PM-CON Primary PM, condensable portion only (all less than 1 micron) PM-FIL Primary PM, filterable portion only

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## PM 10 

## -PRI Primary PM 10 

## (includes filterable and condensable)

PM 10 

## -FIL Primary PM 10 

## filterable portion only

PM 2.5 

## -PRI Primary PM 2.5 

## (includes filterable and condensable)

PM 2.5 

## -FIL Primary PM 2.5 

## filterable portion only
S/L agencies did not report PM emissions in a consistent manner. The State/local inventories submitted for VISTAS included emissions data for either PM-FIL, PM-PRI, PM 10 

## -FIL, PM 10 

## -PRI, PM 2.5 

## -FIL, PM 2.5 

## -PRI, and/or PM-CON. From any one of these pollutants, EPA has developed augmentation procedures to estimate PM 10 

## -PRI, PM 10 

## -FIL, PM 2.5 

## -PRI, PM 2.5 

## -FIL, and PM-CON. If not included in a State/local inventory, PM 10 

## -PRI and PM 2.5 

## -PRI were calculated by adding PM 10 

## -FIL and PM-CON or PM 2.5 

## -FIL and PM-CON, respectively.
The procedures for augmenting point source PM emissions are documented in detail in Appendix C of Documentation for the Final 1999 National Emissions Inventory {Version 3} for Criteria Air Pollutants and Ammonia – Point Sources , January 31, 2004). Briefly, the PM data augmentation procedure includes the following five steps:

• 

## Step 1: Prepare S/L/T PM and PM 10 

## Emissions for Input to the PM Calculator

• 

## Step 2: Develop and Apply S ource-Specific Conversion Factors

• 

## Step 3: Prepare Factors from PM Calculator

• 

## Step 4: Develop and Apply Algorithms to Es timate Emissions from S/L/T Inventory Data

• 

## Step 5: Review Results and Update the NEI with Emission Estimates and Control Information. Please refer to the EPA documentation for a complete description of the PM augmentation procedures.
Table 1.1-2 compares the original PM emission estimates from the S/L CERR submittals and the revised 2002 VISTAS emissions estimates calculated using the above methodology. This table is intended to show that we took whatever States provided in the way of PM and filled in gaps to add in PM-CON where emissions were missing in order to calculate PM 10 

## -PRI and PM 2.5 

## -PRI for all processes to get a complete set of particulate data. We did not compare any other pollutants besides PM, since for other pollutant s CERR emissions equal VISTAS emissions. As noted in Table 1.1-2, we made significant revisions to the PM emissions for Kentucky in the Base F inventory and for South Carolina in the Base G inventory.

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## Table 1.1-2. Comparison of Particulate Matt er Emissions from the S/L Data Submittals and the Base G 2002 VISTAS Point Source Inventory

State Database PM-PRI PM-FIL PM-CON PM 10 

### -PRI PM 10 

### -FIL PM 2.5 

### -PRI PM 2.5 

### -FIL AL CERR 28,803 9,174 0 16,522 6,548 8,895 4,765

VISTAS 43,368 33,336 10,129 32,791 22,661 23,290 13,328 FL CERR 0 33,732 0 0 32,254 0 0

VISTAS 61,728 37,325 24,403 57,243 32,840 46,147 21,744 GA CERR 42,846 0 0 27,489 0 15,750 0

VISTAS 44,835 37,088 7,799 33,202 25,403 22,777 15,085 KY CERR 0 3,809 0 19,748 1,360 0 0

VISTAS 27,719 22,349 5,329 21,326 15,963 14,173 8,749 MS CERR 23,925 0 0 20,968 0 10,937 0

VISTAS 23,928 17,632 6,296 21,089 14,793 11,044 5,739 NC CERR 48,110 0 0 36,222 0 24,159 0

VISTAS 48,114 41,407 6,708 36,992 30,284 27,512 21,113 SC CERR 0 43,837 0 0 32,656 0 21,852

VISTAS 43,844 38,633 5,210 34,799 29,588 26,418 21,207 TN CERR 1,660 25,500 21,482 43,413 22,164 34,167 12,140

VISTAS 56,797 32,085 24,715 50,937 26,269 41,442 16,774 VA CERR 0 0 0 17,065 0 12,000 0

VISTAS 40,856 36,414 4,442 17,065 12,623 12,771 8,607 WV CERR 0 29,277 0 0 14,778 0 8445

VISTAS 36,188 29,392 6,795 22,053 15,258 15,523 8,733
Note 1: CERR refers to data as submitted by S/L agencies; VISTAS refers to data calculated by MACTEC using the PM augmentation methodologies described in this document. Note 2: KY DEP’s initial CERR submittal reported particulate matter emissions using only PM-PRI pollutant code. MACTEC used this pollutant code during the initial PM augmentation routine. In February 2005, KY DEP indicated that data reported using the PM-PRI c ode should actually have been reported using the PM 10 

### -PRI code. MACTEC performed a subsequent PM augmentation in April 2005 using the PM 10 

### -PRI code. These changes were reflected in the Base F emission inventory. Note 3: South Carolina Department of Health and Environmental Control (SC DHEC) initial CERR submittal reported particulate matter emissions using the PM-FIL, PM 10 

### -FIL, and PM 2.5 

### -FIL pollutant codes. MACTEC used these pollutant codes during the in itial PM augmentation routine. In August 2005, SC DHEC indicated that data reported using the PM-FIL, PM 10 

### -FIL, and PM 2.5 

### -FIL pollutant codes should actually have been reported using the PM-PRI, PM 10 

### -PRI, and PM 2.5 

### _PRI codes. MACTEC performed a subsequent PM augmentation in April 2006 using the revi sed pollutant codes. These changes were reflected in the Base G emission inventory. Note 4: The emission values in the VISTAS emission rows above differ slightly from the final values in the Base G inventory. This is due to several corrections and updates to the 2002 i nventory submitted by S/L agencies after the PM augmentation was performed as discussed in Section 1.1.1.6.

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## After the PM augmentation process was performed, we executed a series of checks to identify potential inconsistencies in the PM inventory. These checks included:

• PM-PRI less than PM 10 

## -PRI, PM 2.5 

## -PRI, PM 10 

## -FIL, PM 2.5 

## -FIL, or PM-CON;

• PM-FIL less than PM 10 

## -FIL, PM 2.5 

## -FIL;

• PM 10 

## -PRI less than PM 2.5 

## -PRI, PM 10 

## -FIL, PM 2.5 

## -FIL or PM-CON;

• PM 10 

## -FIL less than PM 2.5 

## -FIL;

• PM25-PRI less than PM 2.5 

## -FIL or PM-CON;

• The sum of PM 10 

## -FIL and PM-CON not equal to PM 10 

## -PRI; and

• The sum of PM 2.5 

## -FIL and PM-CON not equal to PM 2.5 

## -PRI. S/L agencies were asked to review this information and provide corrections where the inconsistencies were significant. In general, corrections (or general directions) were provided in the case of the potential inconsistency issues. In other cases, the agency provided specific process level pollutant corrections.
Note that for the Base G inventory, only the PM 10 

## -PRI and PM 2.5 

## -PRI emission estimates were retained since they are the only two PM species that are included in the air quality modeling. Other PM species were removed from the Base G inventory to facilitate emissions modeling.
1.1.1.4 EGU Analysis We made a comparison of the annual SO 2 

## and NO x 

## emissions for EGUs as reported in the S/L agencies CERR submittals and the data from EPA’s Clean Air Markets Division (CAMD) CEM database to identify any outstanding discrepancies. Facilities report hourly CEM data to EPA for units that are subject to CEM reporting requirements of the NO x 

## State Implementation Plan (SIP) Call rule and Title IV of the Clean Air Act (CAA). EPA sums the hourly CEM emissions to the annual level, and we compared these annual CEM emissions to those in the S/L inventories. The 2002 CEM inventory containing NO x 

## and SO 2 

## emissions and heat input data were downloaded from the EPA CAMD web site ( www.epa.gov/airmarkets ). The data were provided by quarter and emission unit.
The first step in the EGU analysis involved preparing a crosswalk file to match facilities and units in the CAMD inventory to facilities and units in the S/L inventories. In the CAMD inventory, the Office of Regulatory Informati on Systems (ORIS) identification (ID) code identifies unique facilities and the unit ID identifies unique boilers and internal combustion engines (i.e., turbines and reciprocating engines) . In the S/L inventories, the State and county FIPS and State facility ID together identify unique facilities and the emission unit ID identifies unique boilers or internal combustion engines. In most cases, there is a one-to-one correspondence between the CAMD identifiers and th e S/L identifiers. However, in some of the S/L inventories, the emissions for multiple emission units are summed and reported under one

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## emission unit ID. We created an Excel spreadsheet that contained an initial crosswalk with the ORIS ID and unit ID in the CEM inventory matched to the State and county Federal Implementation Plan (FIPS), State facility ID, and emission unit ID in the S/L inventory. The initial crosswalk contained both the annual emissions summed from the CAMD database as well as the S/L emission estimate. It should be noted that the initial matching of the IDs in both inventories was based on previous crosswalks that had been developed for the preliminary VISTAS 2002 inventory and in-house information compiled by MACTEC and Alpine Geophysics. The matching at the facility level was nearly complete. In some cases, however, S/L agency or stakeholder assistance was needed to match some of the CEM units to emission units in the S/L inventories.
The second step in the EGU analysis was to prepare an Excel spreadsheet that compared the annual emissions from the hourly CAMD inventory to the annual emissions reported in the S/L inventory. The facility-level comparison of CEM to emission inventory NO x 

## and SO 2 

## emissions found that for most facilities, the annual emissions from the S/L inventory equaled the CAMD CEM emissions. Minor differences could be explained because the facility in the S/L inventory contained additional small or emergency units that were not included in the CAMD database.
The final step in the EGU analysis was to compare the SO 2 

## and NO x 

## emissions for select Southern Company units in the VISTAS region. Southern Company is a super-regional company that owns EGUs in four VISTAS States – Al abama, Florida, Georgia, and Mississippi – and participates in VISTAS as an industry stake holder. Southern Company independently provided emission estimates for 2002 as part of the development of the preliminary VISTAS 2002 inventory. In most cases, these estimates were reviewed by the States and incorporated into the States CERR submittal. The exception to this was a decision made by Georgia’s Department of Environmental Protection (GDEP) to utilize CE M-based emissions for the actual 2002 emissions inventory for sources within the State when Southern Company also provided data. There were no major inconsistencies between the Southern Company data, the CAMD data, and the S/L CERR data.
The minor inconsistencies found included small differences in emission estimates (<2 percent difference), exclusion/inclusion of small gas-fired units in the different databases, and grouping of emission units in S/L CERR submittals where CAMD listed each unit individually. We compared SO 2 

## and NO x 

## emissions on a unit by unit basis and did not find any major inconsistencies.
1.1.1.5 QA Review of Base F Inventory QA checks were run on the Base F point source inventory data set to ensure that all corrections provided by the S/L agencies and stakeholders were correctly incorporated into the S/L

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## inventories and that there were no remaining QA issues. After exporting the inventory to ASCII text files in NIF 3.0, the EPA QA program was run on the ASCII files and the QA output was reviewed to verify that all QA issues that could be addressed were resolved
Throughout the inventory development process, QA steps were performed to ensure that no double counting of emissions occurred, and to ensure that a full and complete inventory was developed for VISTAS. QA was an important com ponent to the inventory development process and MACTEC performed the following QA steps on the point source component of the VISTAS revised 2002 base year inventory:
1. Facility level emission summaries were prepared and evaluated to ensure that emissions were consistent and that there were no missing sources. 2. State-level EGU and non-EGU comparisons (by pollutant) were developed between the Base F 2002 base year inventory, th e draft VISTAS 2002 inventory, and the 1999 NEI Version 2 inventory. 3. Data product summaries and raw NIF 3.0 data files were provided to the VISTAS Emission Inventory Technical Advisor and to the Point Source, EGU, and non-EGU Special Interest Work Group representatives for review and comment. Changes based on these comments were reviewed and approved by the S/L point source contact prior to implementing the changes in the files. 4. Version numbering was used for all inventory files developed. The version numbering process used a decimal system to track major and minor changes. For example, a major change would result in a version going from Base F1 to Base F2. 1.1.1.6 Additional Base G Updates and Corrections S/L agencies completed a detailed review of the Base F inventory. Table 1.1-3 summarizes the updates and corrections to the Base F inventory that were requested by S/L agencies and incorporated into the Base G inventory.
There was a discrepancy between the base year 2002 and 2009/2018 emissions for PM 10 

## -PRI, PM 2.5 

## -PRI, and NH 3 

## . The 2002 emissions were provided directly by the S/L agencies and were estimated using a variety of techniques (i.e., EP A emission factors, S/L emission factors, sitespecific emission factors, and source test data). The 2009/2018 emissions, on the other hand, were estimated by Pechan (see Section 2.1.1.3) using an emission factor file based solely on AP-42 emission factors. An adjustment was made for 2002 EGU PM and NH 3 

## emissions to reconcile these differences. The post-processed Integrated Planning Model ® ( 

## IPM ® 

## ) 2009/2018 output uses a set of PM and NH 3 

## emission factors that are “the most recent EPA approved uncontrolled emission factors” – these are most likely not the same emission factors used by States and emission inventory preparation contr actors for estimating these emissions in 2002 for EGUs in the VISTAS domain. VISTAS performe d a set of modifications to replace 2002 base

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## year PM and NH 3 

## emission estimates with estimates derived from the most recent EPA-approved emission factors. For further details of the methodology used to make this adjustment, see EGU Emission Factors and Emission Factor Assignment, memorandum from Greg Stella to VISTAS State Point Source Contacts and VISTAS EGU Special Interest Workgroup, June 13, 2005.

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## Table 1.1-3. Summary of Updates and Corrections to the Base F 2002 Inventory Incorporated into the 2002 Base G Inventory.

Affected State(s) Nature of Update/Correction

TN, WV The latitude and longitude values for TN (except the four local programs) and WV were truncated to two decimal places in the Base F inventory. MACTEC re-e xported the NIF ER tables in a manner that so that the latitude and longitude were not truncated in the Base G inventory. AL Corrected the latitude and longitude for two facilities: Ergon Terminalling (Site ID: 01-073-010730167) and Southern Power Franklin (Site ID: 01-081-0036). Corrections to stack parameters at 10 facilities for stack s with parameters that do not appear to fall into the ranges typically termed "acceptable" for AQ modeling. FL Corrected emission values for the Miami Dade RRF facility (Site ID: 12-086-0250348). GA Hercules Incorporated (12-051-05100005) had an errone ous process id (#3) within emission unit id SB9 and was deleted. This removes about 6,000 tons of SO 2 

### from the 2002 inventory. Provided a revised file of location coordinates at the stack level that was used to replace the location coordinated in the ER file. NC Made several changes to Base F inventory to correct the following errors: 1. Corrected emissions at Hooker Furniture (Site ID: 37-081-08100910), release point G-29, 9211.38 tons volatile organic compounds (VOC's) should be 212.2 tons, 529.58 tons PM 10 

### should be 17.02 tons, 529.58 tons PM2.5 should be 15.79 tons in 2002 inventory. 2. Identified many stack parameters in the ER file that were unrealistic. Several have zero for height, diameter, gas velocity, and flow rate. NC used th e procedures outlined in Section 8 of the document ""National Emission Inventory QA and Augmentation Report" to correct unrealistic stack parameters. 3. Identified truncated latitude and longitude values in Base F inventory. NC updated all Title V facility latitude and longitude that was submitted to EPA for those facilities in 2004. Smaller facilities with only two decimal places were not corrected. 4. Corrected emissions for International Paper (3709700045) Emission Unit ID, G-12, should be 1.8844 tons VOCs instead of 2819.19 tons in 2002 SC Corrected PM species emission values. SC DHEC’ s initial CERR submittal reported particulate matter emissions using the PM-FIL, PM 10 

### -FIL, and PM25-FIL pollutant c odes. In August 2005, SC DHEC indicated that data reported using the PM-FIL, PM 10 

### -FIL, and PM25-FIL pollutant codes should actually have been reported using the PM-PRI, PM 10 

### -PRI, and PM25_PRI codes. MACTEC performed a subsequent PM augmentation in April 2006 using th e revised pollutant codes. These changes were reflected in the Base G emission inventory. TN Identified six facilities that closed in 2000/2001 but had non-zero emissions in the 2002 Base F inventory. MACTEC changed emissions to zero for all pollutants in the Base G 2002 inventory. Supplied updated emission inventory for the Bowater facility (47-107-0012) based on the facility’s updated 2002 emission inventory update. Replaced data from Hamilton County, Tennessee, us ing data from Hamilton County’s CERR submittal as contained in EPA’s 2002 NEI (in Base F, the inventory for Hamilton County was based on the draft VISTAS 2002 inventory, which in turn was based on the 1999 NEI). Updated emissions for PCS Nitrogen Fertilizer LP (Site ID: 47-157-00146) WV Updated emissions for Steel of West Virginia (Site ID: 54-011-0009)

Made changes to several Site ID names due to changes in ownership Made corrections to latitude/longitude and stack parameters at a few facilities for stacks with parameters that do not appear to fall into the ranges typically termed "acceptable" for AQ modeling.

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## 1.1.1.7 Summary of Base G 2002 Inventory Tables 1.1-4 through 1.1-10 summarize the Base G 2002 base year inventory. All values are in tons. For the purposes of Tables 1.1-4 through 1.1-10, EGU emissions include the emissions from all processes with a Source Classificati on Code (SCC) of either 1-01-xxx-xx (External Combustion Boilers – Electric Generation) or 2-01-xxx-xx (Internal Combustion Engines – Electric Generation). Emissions for all other S CCs are included in the non-EGU column. Note that aggregating emissions into EGU and non-E GU sectors based on the above SCCs causes a minor inconsistency with the EGU emissions reported in EPA’s CAMD database. The EGU emissions summarized in these tables may include emissions from some smaller electric generating units in the VISTAS inventory that are not in CAMD’s 2002 CEM database or the IPM forecasted emissions. The minor inconsistencies result in a less than 2 percent difference between the summary tables below and the data from CAMD’s CEM database.

Table 1.1-4. Base G 2002 VISTAS Point Source Inventory for SO 2 

## (tons/year).

State All Point Sources EGUs Non-EGUs
AL 544,309 447,828 96,481
FL 518,721 453,631 65,090
GA 568,731 514,952 53,778
KY 518,086 484,057 34,029
MS 103,388 67,429 35,960
NC 522,113 477,990 44,123
SC 259,916 206,399 53,518
TN 413,755 334,151 79,604
VA 305,106 241,204 63,903
WV 570,153 516,084 54,070 Total 4,324,278 3,743,725 580,556

Note: EGU emissions include SCCs 1-01-xxx-xx and 2-01-xxx-xx; non-EGU has all other SCCs.

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## Table 1.1-5. Base G 2002 VISTAS Point Source Inventory for NO x 

## (tons/year).

State All Point Sources EGUs Non-EGUs
AL 244,348 161,038 83,310
FL 302,834 257,677 45,156
GA 196,767 147,517 49,251
KY 237,209 198,817 38,392
MS 104,661 43,135 61,526
NC 196,782 151,854 44,928
SC 130,394 88,241 42,153
TN 221,652 157,307 64,344
VA 147,300 86,886 60,415
WV 277,589 230,977 46,612 Total 2,059,536 1,523,449 536,087

Note: EGU emissions include SCCs 1-01-xxx-xx and 2-01-xxx-xx; non-EGU has all other SCCs. 

## Table 1.1-6. Base G 2002 VISTAS Point Source Inventory for VOC (tons/year).

State All Point Sources EGUs Non-EGUs
AL 49,332 2,295 47,037
FL 40,995 2,524 38,471
GA 34,952 1,244 33,709
KY 46,321 1,487 44,834
MS 43,852 648 43,204
NC 62,170 988 61,182
SC 38,927 470 38,458
TN 85,254 926 84,328
VA 43,906 754 43,152
WV 15,775 1,180 14,595 Total 461,484 12,516 448,970

Note: EGU emissions include SCCs 1-01-xxx-xx and 2-01-xxx-xx; non-EGU has all other SCCs.

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## Table 1.1-7. Base G 2002 VISTAS Point Source Inventory for CO (tons/year).

State All Point Sources EGUs Non-EGUs
AL 185,550 11,279 174,271
FL 139,045 57,113 81,933
GA 140,561 9,712 130,850
KY 122,555 12,619 109,936
MS 59,871 5,303 54,568
NC 64,461 13,885 50,576
SC 63,305 6,990 56,315
TN 122,348 7,084 115,264
VA 70,688 6,892 63,796
WV 100,220 10,341 89,879 Total 1,068,604 141,218 927,388

Note: EGU emissions include SCCs 1-01-xxx-xx and 2-01-xxx-xx; non-EGU has all other SCCs.



## Table 1.1-8. Base G 2002 VISTAS Point Source Inventory for PM 10 

## -PRI (tons/year).

State All Point Sources EGUs Non-EGUs
AL 32,886 7,646 25,240
FL 57,243 21,387 35,857
GA 32,834 11,224 21,610
KY 21,326 4,701 16,626
MS 21,106 1,633 19,472
NC 36,592 22,754 13,838
SC 35,542 21,400 14,142
TN 49,814 14,640 35,174
VA 17,211 3,960 13,252
WV 22,076 4,573 17,503 Total 326,630 113,918 212,714

Note: EGU emissions include SCCs 1-01-xxx-xx and 2-01-xxx-xx; non-EGU has all other SCCs.

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## Table 1.1-9. Base G 2002 VISTAS Point Source Inventory for PM 2.5 

## -PRI (tons/year).

State All Point Sources EGUs Non-EGUs
AL 23,291 4,113 19,178
FL 46,148 15,643 30,504
GA 22,401 4,939 17,462
KY 14,173 2,802 11,372
MS 11,044 1,138 9,906
NC 26,998 16,498 10,500
SC 27,399 17,154 10,245
TN 39,973 12,166 27,807
VA 12,771 2,606 10,165
WV 15,523 2,210 13,313 Total 239,721 79,269 160,452

Note: EGU emissions include SCCs 1-01-xxx-xx and 2-01-xxx-xx; non-EGU has all other SCCs. 

## Table 1.1-10. Base G 2002 VISTAS Point Source Inventory for NH 3 

## (tons/year).

State All Point Sources EGUs Non-EGUs
AL 2,200 317 1,883
FL 1,657 234 1,423
GA 3,697 83 3,613
KY 1,000 326 674
MS 1,359 190 1,169
NC 1,234 54 1,180
SC 1,553 142 1,411
TN 1,817 204 1,613
VA 3,230 127 3,104
WV 453 121 332 Total 18,200 1,798 16,402

Note: EGU emissions include SCCs 1-01-xxx-xx and 2-01-xxx-xx; non-EGU has all other SCCs. 

## 1.1.2 Development of Typical Year EGU inventory VISTAS developed a typical year 2002 emission inventory for EGUs to avoid anomalies in emissions due to variability in meteorology, economic, and outage factors in 2002. The typical year inventory represents the five year ( 2000-2004) starting period that would be used to determine the regional haze reasonable progress goals.

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## Data from EPA’s CAMD were used to de velop normalization factors for producing a 2002 typical year inventory for EGUs. We used the ratio of the 2000-2004 average heat input and the 2002 actual heat input to normalize the 2002 actua l emissions. MACTEC obtained data from EPA’s CAMD for utilities regulated by the Acid Rain program. Annual data for the period 2000 to 2004 were obtained from the CAMD web site ( www.epa.gov/airmarkets ). The parameters available were the SO 2 

## and NO x 

## emission rates, heat input, and operating hours.
We used the actual 2002 heat input and the average heat input for the 5-year period from 2000- 2004 as the normalization factor, as follows:
Normalization Factor: 2000-2004 average heat input 2002 actual heat input If the unit did not operate for all five years, then the 2000-2004 average heat input was calculated for the one or two years in which the unit did operate. For example, if the unit operated only during 2002, then the normalization factor would be 1.0. The annual actual emissions were multiplied by the normalization factor to determine the typical emissions for 2002, as follows:
Typical Emissions = 2002 actual emissions x Normalization Factor After applying the normalization factor, some adjustments were needed for special circumstances. For example, a unit may not have operated in 2002 and thus have zero emissions. If the unit had been permanently retired prior to 2002, then we used zero emissions for the typical year. If the unit had not been permanently retired and would normally operate in a typical year, then we used the 2001 (or 2000) heat input and emission rate to calculate the typical year emissions.
The Southern Company provided typical year data for their sources. Hourly emissions data for criteria pollutants were provided. MACTEC aggregated the hourly emissions into annual values. Further documentation of how Southern Company created the typical year inventory for their units can be found in Developing Southern Company Emissions and Flue Gas Characteristics for VISTAS Regional Haze Modeling (April 2005, presented at 14 th 

## International Emission Inventory Conference http://www.epa.gov/ttn/chief/conference/ei14/session9/kandasamy.pdf ). Since Southern Company only supplied filterable particulate emissions, we ran the PM 10 

## /PM 2.5 

## augmentation routine to calculate annual emission estimates for PM 10 

## -PRI and PM 2.5 

## -PRI.
The Southern Company typical year data were used for Southern Company sources in Alabama, Florida, and Mississippi. Georgia EPD elected to use the typical year normalization factor derived from the CAMD data instead of the Southe rn Company typical year data (as was used in the Base F inventory).

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## The final step was to replace the 2002 actual emissions with the 2002 typical year data described above. MACTEC provided the raw data and results of the typical year calculations in a spreadsheet for S/L agency review and comment. Any comments made were incorporated into the Base G inventory.
Table 1.1-11 summarizes emissions by State and pollutant for the actual 2002 EGU inventory and the typical year EGU inventory. For the entire VISTAS region, actual 2002 SO 2 

## emissions were about 0.5 percent higher than the typical year emissions. The differences on a state-be-state basis ranged from actual emissions being 6.6 percent lower in Florida to 10.9 percent higher in Mississippi. For the entire VISTAS region, actual 2002 NO x 

## emissions were about 0.1 percent lower than the typical year emissions. The differences on a state-be-state basis ranged from actual emissions being 9.6 percent lower in Florida to 6.3 percent higher in Mississippi.

Table 1.1-11. Comparison of SO 2 

## and NO x 

## Emissions (tons/year) for EGUs from Base G Actual 2002 Inventory and Typical 2002 Inventory.

SO 2 

### Emissions (tons/year) NO x 

### Emissions (tons/year)

State Actual 2002 Typical 2002 Percentage Difference Actual 2002 Typical 2002 Percentage Difference

AL 447,828 423,736 5.4 161,038 154,704 3.9
FL 453,631 483,590 -6.6 257,677 282,507 -9.6
GA 514,952 517,633 -0.5 147,517 148,126 -0.4
KY 484,057 495,153 -2.3 198,817 201,928 -1.6
MS 67,429 60,086 10.9 43,135 40,433 6.3
NC 477,990 478,489 -0.1 151,854 148,812 2.0
SC 206,399 210,272 -1.9 88,241 88,528 -0.3
TN 334,151 320,146 4.2 157,307 152,137 3.3
VA 241,204 233,691 3.1 86,886 85,081 2.1
WV 516,084 500,381 3.0 230,977 222,437 3.7 Total 3,743,725 3,723,177 0.5 1,523,449 1,524,693 -0.1



## 1.2 Area Sources
This section details the development of the Base G 2002 base year inventory for area sources. There are three major components of the area source sector of the inventory. The first component is the “typical” year fire inventory. Version 3.1 of the VISTAS base year fire inventory provided actual 2002 emissions estimates. Since fire emissions are not easily grown or projected, in order

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## to effectively represent fires in both the base and future year inventories, VISTAS determined that a typical year fire inventory was necessary. Development of the “typical” year fire inventory covered wildfire, prescribed burning, agricultural fires and land clearing fires. The first part of this section of the report discusses the development of the typical year fire inventory. The methodology provided in that section is identical to the documentation provided for Base F since the “typical” year inventory was developed as part of the Base F development effort. The major change in Base G for the fire component of the inventory was the development of projection year inventories that represent alternatives to the “typical” year inventory. These alternative projections incorporated projected changes in the acreage burned for prescribed fires on Federal lands. These projections are an augmentation of the “typical” year inventory.
The second component of the area source inventory was the incorporation of data submitted by the VISTAS States to the United States Environmental Protection Agency (EPA) as part of the CERR. Work on incorporating the CERR data into the revised base year involved: 1) obtaining the data from EPA, 2) evaluating the emissions and pollutants reported in order to avoid double counting and 3) backfilling from the existing VISTAS 2002 base year inventory for missing sources/pollutants. The processes used to perform those operations are described in the second portion of this section. That work was performed as part of the Base F inventory effort. In general no changes to that method were made as part of the Base G inventory updates. The methods used for the Base F inventory development effort using the CERR submittals have been maintained in this document. Where necessary, additional documentation has been added to 1) reflect changes that resulted from VISTAS States review of the Base F inventory and the incorporation of those changes into Base G, 2) changes made to how certain sources were estimated or 3) addition of new sources not found in Base F.
The final component of the area source inventory was related to the development of NH 3 

## emission estimates for livestock and fertilizers and paved road PM emissions. For the NH 3 

## emission estimates for livestock and fertilizers we used version 3.6 of the Carnegie Mellon University (CMU) NH 3 

## model. For the paved road PM emissions, we used the most recent estimates developed by EPA as part of the National Emission Inventory (NEI) development effort. EPA had developed an improved methodol ogy for estimating paved road emissions so those values were substituted directly into the inventory after receiving consensus from all of the VISTAS States to perform the replacement. Details on these methods are provided in the third portion of this section of the document. That section is virtually identical to that from the Base F inventory document as there were only a couple of changes to the ammonia portion of the inventory and some updates to all fugitive dust categories including paved roads on a global basis between Base F and Base G.
Finally, quality assurance steps for each component of the area source inventory are discussed.

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## 1.2.1 Development of a “typical” year fire inventory Typical year fire emissions were developed starting from the actual fire acreage data and emission calculated for each VISTAS State. The table below shows the data submitted by each State in the VISTAS region indicating what data was received from each State for the purposes of calculating actual fire emissions.
Fire Type AL FL GA KY MS NC SC TN VA WV Land Clearing 9 9 9 9 Ag Burning 9 9 9 9
Wildfires 9 9 9 9 9 9 9 9 9 9
Prescribed 9 9 9 9 9 9 9 9 9

In order to effectively characterize fire emissi ons in the VISTAS region, a typical (as opposed to strictly 2002 year based inventory) was required. Development of a typical year fire inventory provided the capability of using a comparable data set for both the base year and future years. Thus fire emissions would remain the same for air quality and visibility modeling in both the base and any future years. MACTEC originally proposed five different methods for developing the typical fire year to the VISTAS Fire Sp ecial Interest Work Group (SIWG) and requested their feedback and preference for developing the final typical year inventory. The method that was selected by SIWG members was to use a method similar to that used to develop an early version of a 2018 projection inventory. For that early 2018 inventory, State level ratios of acres over a longer term record (three or more years) developed for each fire type relative to 2002. The 2002 acreage was then scaled up or down based on these ratios to develop a typical year inventory. For Base F and G, the decision of the VISTAS Fire SIWG was to base the ratio oncounty level data for States that supplied long term fire-by-fire acreage data rather than Statelevel ratios. Where States did not supply long te rm fire-by-fire acreage data, MACTEC reverted to using State-level ratios. With one broad exception (wildfires) this method was implemented for all fires. MACTEC solicited long term fire-by-fire acreage data by fire type from each VISTAS State. A minimum of three or more years of data were used to develop the ratios. Those data were then used to develop a ratio for each county based on the number of acres burned in each county for each fire type relative to 2002.
Thus if we had long term county prescribed fi re data from a State, we developed a county acreage ratio of:

acreageRx levelcounty actual 2002 acresRx levelcounty average termLong

= Ratio

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## This ratio was then multiplied times the actual 2002 acreage to get a typical value (basically the long term average county level acres). Wherever possible this calculation was performed on a fire by fire basis. The acreage calculated using the ratio was then used with the fuel loading and emission factor values that we already had (and had been reviewed by the SIWG) to calculate emissions using the same method used for the 2002 actual values (which were previously documented). The following lists indicate which counties used the State ratios by fire type.
Land Clearing Agricultural Fires Prescribed Burning FIPS COUNTY FIPS COUNTY FIPS COUNTY 12086 Miami-Dade County 12037 Franklin County 12043 Glades County 12045 Gulf County 12049 Hardee County 12057 Hillsborough County 12073 Leon County 12077 Liberty County 12081 Manatee County 12095 Orange County 12097 Osceola County 12103 Pinellas County 12115 Sarasota County 13015 Bartow County 13021 Bibb County 13045 Carroll County 13047 Catoosa County 13057 Cherokee County 13059 Clarke County 13063 Clayton County 13073 Columbia County 13077 Coweta County 13083 Dade County 13089 Dekalb County 13097 Douglas County 13117 Forsyth County 13121 Fulton County 13129 Gordon County 13135 Gwinnett County 13137 Habersham County 13143 Haralson County 13147 Hart County 13151 Henry County 13169 Jones County 13215 Muscogee County 13237 Putnam County 13241 Rabun County 13291 Union County 13311 White County 13063 Clayton County 13083 Dade County 13089 Dekalb County 13097 Douglas County 13121 Fulton County 13135 Gwinnett County 13137 Habersham County 13215 Muscogee County 13227 Pickens County 13241 Rabun County 13247 Rockdale County 13311 White County 13059 Clarke County 13083 Dade County 13089 Dekalb County 13097 Douglas County 13121 Fulton County 13123 Gilmer County 13135 Gwinnett County 13139 Hall County 13215 Muscogee County 13241 Rabun County 13247 Rockdale County

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## There were three exceptions to this method. Exception 1: Use of State Ratios for Wildfires
The first exception was that wildfires estimates were developed using State ratios rather than county ratios. This change was made after initial quality assurance of the draft estimates revealed that some counties were showing unrealistic values created by very short term data records or missing data that created unrealistic ratios. In addition, exceptionally large and small fires were removed from the database since they were felt to be atypical. For example the Blackjack Complex fire in Georgia was removed from the dataset because the number of acres burned was “atypical” in that fire. We also removed all fires less than 0.1 acres from the dataset. Exception 2: Correction for Blackened Acres on Forest Service Lands
Following discussions with the United States Fore st Service (Forest Service) (memo from Cindy Huber and Bill Jackson, dated August 13, 2004), it was determined that the acres submitted by the Forest Service for wildfires and prescribed fires represented perimeter acres rather than “blackened” acres. Thus for wildfires and prescribed fires on Forest Service lands, a further correction was implemented to correct the perimeter acre values to blackened acres. The correction was made based on the size of the fire. For prescribed fires over 100 acres in size the acreage was adjusted to be 80 percent of the initial reported value. For prescribed fires of 100 acres or less the acreage values were maintained as reported. For wildfires, all reported acreage values were adjusted to be 66 percent of their initially reported values. These changes were made to all values reported for Forest Service managed lands. Exception 3: Missing/Non-reported data

When we did not receive data from a VISTAS State for a particular fire type, a composite average for the entire VISTAS region was used to determine the typical value for that type fire. For example, if no agricultural burning long term acreage data was reported for a particular State, MACTEC determined an overall VISTAS re gional average ratio that was used to multiply times the 2002 values to produce the “typical” values. This technique was applied to all fire types when data was missing.
In addition, for wildfires and prescribed burning, ratios were developed for “northern” and “southern” tier States within the VISTAS region and those ratios were applied to each State with missing data depending upon whether they were considered a “northern” or “southern” tier State. Development of “southern” and “northern” tier data was an attempt to account for a change from a predominantly pine/evergreen ecosystem (southern) to a pine/deciduous ecosystem (northern). States classified as “southern” included: AL , FL, GA, MS, and SC. States classified as “northern” included: KY, NC, TN, VA, and WV.

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## Finally for land clearing and agricultural fires, there are no NH 3 

## and SO 2 

## emissions. This is due to the lack of emission factors for these pollutants for these fire types.
Table 1.2-1 shows fire emissions from the original base year emission inventory (VISTAS 3.1), the actual 2002 emissions and the typical year emissions for the entire VISTAS region. The actual 2002 and typical fire emissions represen t the Base F and Base G 2002 emissions. The typical emissions also represent the 2009 and 2018 emissions for all fire types with the exception of prescribed burning. Revisions made to the typical year prescribed fire emissions for 2009 and 2018 are detailed in the projection section. Also, State level Base G emissions from fires for all years can be found in the tables in Appendix A. Values for fires in those tables are “typical” year values.
Figures 1.2-1 through 1.2-4 show the State by State changes in emissions between the original 2002 base year fire inventories, the actual 2002 and the typical year inventories for carbon monoxide (CO) by fire type. Due to the relative magnitude of CO emissions compared to other criteria and PM pollutants from fires; this pollutant is normally chosen to represent the distribution of fires in the example plots.Documentation of the Base G 2002 Base Year, 2009 and 2018, Emission Inventories for VISTASMACTEC, Inc.26Table 1.2-1. Emissions from Fires in the VISTAS Region –Comparison between Original Base Year 2002 (VISTAS 3.1), 2002Actual and Typical Year Base G Emissions.CONH3NOXPM10-FILPM10-PRIPM2.5-FILPM2.5-PRISO2VOCTotal LCActual (Base G) 492,409 0 14,568 62,146 62,146 62,146 62,146 0 33,799Typical (Base G) 675,838 0 19,995 80,598 80,598 80,598 80,598 0 46,389VISTAS 3.1 484,240 0 14,327 61,325 61,325 61,325 61,325 0 33,238Total AgActual (Base G) 164,273 0 903 30,958 30,958 30,385 30,385 0 21,946Typical (Base G) 161,667 0 903 30,465 30,465 29,892 29,892 0 21,595VISTAS 3.1 331,073 0 903 41,480 41,480 40,192 40,192 0 41,875Total WFActual (Base G) 298,835 1,333 6,628 28,923 28,923 24,926 24,926 1,611 16,804Typical (Base G) 547,174 2,451 11,955 53,070 53,070 45,635 45,635 3,072 28,491VISTAS 3.1 275,766 1,230 6,133 26,680 26,680 23,002 23,002 1,476 15,718Total RXActual (Base G) 1,678,216 7,616 36,561 168,938 168,938 145,175 145,175 9,839 78,988Typical (Base G) 1,635,776 7,425 35,650 164,811 164,811 141,636 141,636 9,590 76,990VISTAS 3.1 1,724,940 7,822 37,556 173,590 173,590 149,181 149,181 10,101 81,188Key: LC = Land Clearing; Ag = Agricultural burning; WF = wildfires; RX = prescribed burning. Actual and Typical represent BaseF and Base G (e.g., nochange in methodology for Base F and Base G) for 2002.Documentation of the Base G 2002 Base Year, 2009 and 2018, Emission Inventories for VISTASMACTEC, Inc.27Figure 1.2-1. CO Emissions from Agricultural Burning for the Original Base Year, 2002 Actual Base G, and 2002 TypicalBase G Inventories.CO Emissions0.0020,000.0040,000.0060,000.0080,000.00100,000.00120,000.00140,000.00160,000.00AL FL GA KY MS NC SC TN VA WV

tonsAg Burning - 2002 ActualAg Burning - TypicalAg Burning - VISTAS 3.1Documentation of the Base G 2002 Base Year, 2009 and 2018, Emission Inventories for VISTASMACTEC, Inc.28Figure 1.2-2. CO Emissions from Land Clearing Burning for the Original Base Year, 2002 Actual Base G and 2002 TypicalBase G Inventories.CO Emissions0.0020,000.0040,000.0060,000.0080,000.00100,000.00120,000.00140,000.00160,000.00180,000.00AL FL GA KY MS NC SC TN VA WV

tonsLand Clearing - 2002 ActualLand Clearing - TypicalLand Clearing - VISTAS 3.1Documentation of the Base G 2002 Base Year, 2009 and 2018, Emission Inventories for VISTASMACTEC, Inc.29Figure 1.2-3. CO Emissions from Prescribed Burning for theOriginal Base Year, 2002 Actual Base G and 2002 TypicalBase G Inventories.CO Emissions0.00100,000.00200,000.00300,000.00400,000.00500,000.00600,000.00700,000.00AL FL GA KY MS NC SC TN VA WV

tonsPrescribed - 2002 ActualPrescribed - TypicalPrescribed - VISTAS 3.1Documentation of the Base G 2002 Base Year, 2009 and 2018, Emission Inventories for VISTASMACTEC, Inc.30Figure 1.2-4. CO Emissions from Wildfire Burning for theOriginal Base Year, 2002 Actual Base G and 2002 TypicalBase G Inventories.CO Emissions0.0050,000.00100,000.00150,000.00200,000.00250,000.00AL FL GA KY MS NC SC TN VA WV

tonsWildfires - 2002 ActualWildfires - TypicalWildfires - VISTAS 3.1Documentation of the Base G 2002 Base Year, 2009 and 2018, Emission Inventories for VISTAS

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### 1.2.2 Development of non-fire inventory The second task in preparing the area source component of the Base F and Base G 2002 base year inventory was the incorporation of data s ubmitted by the VISTAS States to the EPA as part of the CERR. With few exceptions, Base F and Base G inventories for this component of the inventory are identical. Modifications to th e Base F methodology (described below) only resulted from modifications from the VISTAS States during review of the Base F inventory. The changes made to the inventory based on these reviews are described in the last portion of this section of the report. The information presented below describes the method used to incorporate CERR data as part of Base F.
Work on incorporating the CERR data into the 2002 Base F inventory involved: 1) obtaining the data from EPA, 2) evaluating the emissions and pollutants reported in order to avoid double counting and 3) backfilling from the earlier versi on of the VISTAS 2002 base year inventory for missing sources/pollutants. The processes used to perform those operations are described below. This work did not include any of the fire emission estimates described above. In addition it did not include emission estimates for ammonia from agricultural and fertilizer sources. Finally it did not include PM emissions from paved roads. Each of those categories was estimated separately.

Data on the CERR submittals was obtained from EPA’s Draft NEI download file transfer protocol (FTP) site where the data are stored after they’ve been processed for review. The data submitted in National Emission Inventory Format (NIF) was downloaded from that site. Once all of the files were obtained, MACTEC ran the files through the EPA NIF Format and Content checking tool to ensure that the files were submitted in standard NIF format and that there were no issues with those files. In a couple of cases small errors were found. For example, in one case a county FIPs code that was no longer in use was found. MACTEC contacted each VISTAS State area source contact person to resolve the issues with the files and corrections were made. Once all corrections to the native files were completed, MACTEC continued with the incorporation of the data into the VISTAS area source files.
Our general assumption was that unless we determined otherwise, the CERR submittals represented full and complete inventories. Where a State submitted a complete inventory, our plan was to simply delete the previous 2002 base year data and replace it with the CERR submittal. Prior to this replacement however, we stripped out the following emissions:
1. All wildfire, prescribed burning, land clearing and agricultural burning emissions submitted to EPA by the States as part of the CERR process were removed since they were to be replaced with emissions estimated using methods described earlier. 2. All fertilizer and agricultural ammonia emission records submitted to EPA by the States as part of the CERR process were removed. These were replaced with the estimates developed using the CMU Ammonia model.Documentation of the Base G 2002 Base Year, 2009 and 2018, Emission Inventories for VISTAS

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### 3. All emissions from paved roads submitted to EPA by the States as part of the CERR process were removed. These emissions were replaced with updated emissions developed by U.S. EPA as part of their 2002 NEI development effort. This approach was used for most State and Local emission submittals to prepare the Base F inventory. There were a few cases where alternative data were used to prepare the Base F inventory. In general, these alternatives involved submittal of alternative files to the CERR data by S/L agencies. Table 1.2-2 below summarizes the data used to prepare the Base F inventory. In general the data were derived from one of the following sources: 1. CERR submittal obtained from EPA FTP site as directed by VISTAS States; 2. State submitted file (either revised from CERR submittal or separate format); 3. VISTAS original 2002 base year (VISTAS version 3.1 base year file); or 4. EPA’s preliminary 2002 NEI. Table 1.2-2. Summary of State Data Submittals for the 2002 VISTAS Area Source Base F Inventory

State / Local Program Area Source Emissions Data Source AL B FL B GA C KY A MS B NC C SC B TN B VA B WV A/C Davidson County, TN B Hamilton County, TN C Memphis/Shelby County, TN A Knox County, TN B Jefferson County, AL * so B from State Jefferson County, KY B Buncombe County, NC * so C from State

Forsyth County, NC * so C from State Mecklenburg County, NC * so C from State

A = VISTAS 2002 (version 3.1) B = CERR Submittal from EPA's ftp site C = Other (CERR or other submittal sent directly from State to MACTEC) * = No responseDocumentation of the Base G 2002 Base Year, 2009 and 2018, Emission Inventories for VISTAS

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### In order to track the sources of data in the final Base F and Base G NIF files, a field was added to the NIF format files developed for VISTAS to track each data source. A field named Data_Source was added to the EM table. A series of codes were added to this field to mark the source of each emissions value in the Base F and Base G inventories. Values in this field are detailed in Table 1.2-3.

Table 1.2-3: Data Source Codes and Data Sources for VISTAS 2002 Base F Area Source Emissions Inventory.

Data Source Codes Data Source

Base F Codes

CMU Model CMU Ammonia model v 3.6

E-02-X or E-99-F or L-02-X or S-02-X EPA CERR submittal (from FTP site)

EPA Paved EPA Paved Road emissions estimates

EPAPRE02NEI EPA Preliminary 2002 NEI

STATEFILE State submitted file

VISTBASYR31 VISTAS 2002 Base Year version 3.1

VISTRATIO Developed from VISTAS Ratios (used only for missing pollutants)

Additional Base G Codes

ALBASEGFILE Base G update file provided by AL

NCBASEGFILE Base G update file provided by NC

OTAQRPT Portable Fuel Container Emissions from OTAQ Report

STELLA Revised data provided by VISTAS EI Advisor Greg Stella

VABASEGFILE Base G update file provided by VA

VAStateFile Revisions/additions to Base G update file provided by VA



### Most States submitted complete inventories for Ba se F. Virginia’s inventory required a two stage update. Virginia’s CERR submittal only contained ozone precursor pollutants (including CO). For Virginia, MACTEC’s original plan was to maintain the previous 2002 VISTAS base year emissions for non-ozone pollutants and then do a simple replacement for ozone pollutants. However during the QA phase of the work, MACTEC discovered that there were categories that had ozone precursor or CO emissions in the submittal that weren’t in the original 2002 VISTAS base year inventory that should have PM or SO 2 

### emissions. For those records, MACTEC used anDocumentation of the Base G 2002 Base Year, 2009 and 2018, Emission Inventories for VISTAS

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### emissions ratio to build records for emissions of these pollutants. Data for Virginia PM and SO 2 

### emissions were generated by developing SCC level ratios to NO x 

### from the VISTAS 2002 base year inventory (version 3.1) or from emission f actors and then calculating the emissions based on that ratio.
1.2.3 2002 Base G inventory updates After the Base F inventory was submitted and us ed for modeling, VISTAS States were provided an opportunity for further review and comment on the Base F inventory. As a result of this review and comment period, several VISTAS States provided revisions to the Base F inventory.
In addition to and as an outgrowth of some of the comments provided by the States during the review process, some of the changes made to the inventory were made globally across the entire VISTAS region. This section discusses the specific State changes followed by the global changes made to the area source component of the inventory for all VISTAS States.
1.2.3.1 Changes resulting from State review and comment
Alabama
Alabama suggested several changes and had questi ons concerning a few categories in the Base F inventory. The changes/questions were:
1. For Source Classification Code (SCC) 2102005000 (Industrial Boilers: Residual Oil) and SCC 2103007000 (Institutional/Commercial Heating: Liquefied Petroleum Gas) the Alabama noted that the Base F VISTAS inventory had values for NO x 

### , VOC and CO for the State, but no values for SO 2 

### , PM 10 

### or PM 2.5 

### . MACTEC evaluated this information and found that there were actually emissions for two counties in AL for that SCC that had either SO 2 

### and/or PM emissions. The data used to develop the 2002 Base F inventory for AL came from the preliminary 2002 CERR submittals (see above) which should have included SO 2 

### and PM but did not except for two counties. According to MACTEC’s protocol for use of these files, the f iles received from EPA were to be used “as is” unless the States provided comments during the Base F comment period to correct the CERR submittal. No comments were received from AL on the CERR submittal used for Base F. For 2002 Base G, AL provided an updated database file for these SCCs for all counties in the State that provided revised values for emissions and included SO 2 

### and PM. The revised file was used to update the Base F data for Base G.
2. AL noted that the Base F inventory included SCC 2401002000 (Solvent Utilization, Surface Coating, Architectural Coatings - Solvent-based, Total: All Solvent Types) and 2401003000 (Solvent Utilization, Surface Coating,Documentation of the Base G 2002 Base Year, 2009 and 2018, Emission Inventories for VISTAS

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### Architectural Coatings - Water-based, Total: All Solvent Types) as well as SCC 2401001000 (Solvent Utilization, Surface Coating, Architectural Coatings, Total: All Solvent Types). This resulted in double counting of the emissions for this category. AL suggested removal of the breakdown SCCs and use of the total SCC.

MACTEC deleted records for the breakdown S CCs and retained the total all solvents SCC emissions.
3. AL found the SCCs listed below missing from the Base F VISTAS inventory.

SCC VOC Emissions SCC Description 2401025000 1139.91 Surface Coatings: Metal Furniture, all coating types 2401030000 425.27 Surface Coatings: Paper, all coating types 2401065000 344.08 Surface Coatings: Electronic and Other Electrical, all coating types 2430000000 504.29 Solvent Utilization, Rubber/Plastics, All Processes, Total: All Solvent Types 2440020000 3043.78 Solvent Utilization, Miscellaneous Industrial, Adhesive (Industrial) Application, Total: All Solvent Types Total for AL 5457.32

MACTEC found that the emissions for these SCCs were included in the Base F inventory, but with slightly different total emissions. AL provided an updated county-level emissions file for use in updating the Base G inventory. That file was used to update the NIF records for AL for those SCCs.
4. AL noted that emissions in the Base F inventory were found for SCC 2465000000 and SCCs 2465100000, 2465200000, 2465400000, 2465600000, and 2465800000. These last five SCCs represent a subset of the emissions in the 246500000 SCC resulting in potential double counting of emissions.

MACTEC deleted all emissions associated with the Total SCC 2465000000 and retained the subset SCCs for the Base G inventory.

Florida Florida provided comments indicating that they felt that emissions from the following sources and counties were too high, especially for CO and PM and were likely zero:Documentation of the Base G 2002 Base Year, 2009 and 2018, Emission Inventories for VISTAS

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### • motor vehicle fire - Palm Beach County

• woodstoves - Miami Dade, Hillsborough, Orange, Polk, Ft Myers, Pasco and Sarasota Counties

• fireplaces - Miami Dade and Hillsborough Counties Emissions from these sources in the counties specified were set to zero by MACTEC for the Base G inventory.

North Carolina North Carolina provided corrected emission files for 2002 Base F. A text file with emission values was provided and used to update the Base F emissions to Base G. The updated emissions were applied directly to the Base F NIF file. The file provided was similar to the “EM” NIF table. An update query was used to update the data supplied in the text file to the Access database NIF file. All changes were implemented.

South Carolina South Carolina had two issues concerning the Base F inventory. These issues related to 1) additional SCCs that were in BASE F 2009 and 2018, but not in 2002 Base F and 2) SCCs that were in the U.S. EPA 2002 NEI inventory, but not in the VISTAS 2002, 2009, or 2018 Base F inventory.
MACTEC investigated the additional SCCs found in 2009 and 2018 Base F and found that the SCCs actually were not missing in the 2002 Base F inventory but only had emissions for PM. Thus the emissions were maintained as they were provided in Base F.
With respect to the SCCs that were found in the U.S. EPA 2002 NEI, MACTEC investigated and found that they were not included in the Base F inventory because they were not included in the 2002 CERR submittal used to produce the Base F updates. The SCCs were apparently added by EPA later in the NEI development process. In addition, MACTEC also evaluated whether or not the SCCs were found in other VISTAS States Base F inventories. MACTEC found that some States included them and some did not, there was no consistency between the States. MACTEC also found that typically emissions for these SCCs were low in emissions, generally with emissions of only a few tons to tens of tons pe r year. The decision was made with South Carolina concurrence not to add these SCCs to the Base G inventory. These SCCs were: 210205000, 2102011000, 2103007000, 2103011000, 2104007000, 2104011000, 2302002100, 2302002200, 2302003100, 2302003200, 2610000500, 2810001000, and 281001500.
Virginia Virginia provided an updated 2002 base year emissions file. The data in that file were used to update the Base F inventory emission values to t hose for Base G. In addition, Virginia providedDocumentation of the Base G 2002 Base Year, 2009 and 2018, Emission Inventories for VISTAS

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### information on several source categories that required controls for future year projections since the sources were located in counties/cities in northern Virginia and were subject to future year Ozone Transport Commission (OTC) regulations. MACTEC added in the base year control levels to the Base G inventory file for these categories so that they could be estimated correctly in future years. The controls added were for mobile equipment repair/refinishing sources, architectural and industrial maintenance coating sources, consumer products sources, and solvent metal cleaning sources. Minor errors were found in some entries for the initial file provided and VA provided a revised file with corrections and minor additions.
1.2.4 Ammonia and paved road emissions The final component of the Base F inventory development was estimation of NH 3 

### emission estimates for livestock and fertilizers and paved road PM emissions. For the NH 3 

### emission estimates for livestock and fertilizers we used version 3.6 of the CMU NH 3 

### model ( http://www.cmu.edu/ammonia/ ). Results from this model were used for all VISTAS States. The CMU model version 3.6 was used in large part because it had been just recently been updated to include the latest (2002) Census of Agriculture animal population statistics. Prior to inclusion of the CMU model estimates, MACTEC removed any ammonia records for agricultural livestock or fertilizer emissions from the VISTAS 2002 initial base year inventory. MACTEC also generated emissions from human perspiration and from wildlife using the CMU model and added those emissions for each State.
For the Base G ammonia inventory, MACTEC removed all wildlife and human perspiration emissions. VISTAS decided to remove these emissions from the inventory. Human perspiration was dropped due to a discrepancy in the units used for the emission factor that was not resolved prior to preparing the estimates and wildlife was dropped because VISTAS felt the activity data was too uncertain. Thus all emissions from these two categories were deleted in the Base G 2002 inventory.
For the paved road PM Base F emissions, we used the most recent estimates developed by EPA as part of the NEI development effort (Roy Huntley, U.S. EPA, email communication, 8/30/2004). EPA had developed an improved met hodology for estimating paved road emissions for 2002 and had used that method to calculate emissions for that source category. MACTEC obtained those emissions from EPA and those values were substituted directly into the inventory after receiving consensus from all of the VISTAS States to perform the replacement. These files were obtained in March of 2005 in NIF format from the EPA FTP site.
For the Base G emissions, modifications were made to the emissions estimates based on changes suggested by work of the Western Regional Air Partnership and U.S. EPA. Details of these changes are provided below in the section on global changes made as part of the Base G inventory updates.Documentation of the Base G 2002 Base Year, 2009 and 2018, Emission Inventories for VISTAS

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### 1.2.5 Global Changes Made for Base G There were three global changes made between the Base F and the Base G inventory (beyond the removal of wildlife and human perspiration NH 3 

### emissions). These changes were:
1. Removal of Stage II emissions from the area source inventory and inclusion in the mobile sector of the inventory,
2. Adjustment of fugitive dust PM 2.5 

### emissions, and
3. Addition of emissions from portable fuel containers.
As part of the Base F review process, several VISTAS States had expressed surprise that the Stage II refueling emission estimates were in the area source component of the inventory. This decision had been made with SIWG agreement early on in the inventory development process because 1) some States had included it in thei r CERR submittals and 2) because the non-road and on-road mobile estimates had differing activity factor units and could not be easily combined. However for Base G, the VISTAS States all agree d, especially in light of the different ways in which the emissions were reported in the CERR, to remove the Stage II refueling emissions from the area source inventory and include them in the non-road and on-road sectors. Thus all records related to Stage II refueling were removed from the area source component of the Base G inventory.

PM 2.5 

### emissions from several fugitive dust sources were also updated for Base G. The Western Regional Air Partnership (WRAP) and U.S. EPA had been investigating overestimation of the PM 2.5 

### / PM 10 

### ratio in several fugitive dust categories and U.S. EPA was in the process of making revisions to AP-42 for several categories during preparation of the Base G inventory. Based on data received from U.S. EPA, VISTAS decided to revise the PM 2.5 

### emissions from construction, paved roads and unpaved road sources. PM 2.5 

### emissions in Base F were multiplied by 0.67, 0.6, and 0.67 for construction, paved roads and unpaved roads respectively to produce the values found in Base G. No changes were made to PM 10 

### , only to PM 2.5 

### . Finally, as part of Virginia’s comments on the Base F inventory, emissions from portable fuel containers were mentioned as being absent from the inventory. MACTEC was tasked with developing a methodology that could be used to add these emissions to the Base G area source inventory. In investigating options for a met hod of estimating emissions, MACTEC found that the U.S. EPA had prepared a national invent ory of emissions by State for portable fuel containers. Data on emissions from this sour ce prepared by U.S. EPA were presented in, “Estimating Emissions Associated with Portable Fu el Containers (PFCs), Draft Report, Office of Transportation and Air Quality, United States Environmental Protection Agency, Report # EPA420-D-06-003, February 2006”.Documentation of the Base G 2002 Base Year, 2009 and 2018, Emission Inventories for VISTAS

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### State-level emission estimates for 2005 derived from Appendix Table B-2 of the PFCs report were used as the starting point for devel oping 2002 county-level emissions estimates. State emissions were derived from that table by using all of the emission estimates in that table with the exception of values for vapor displacement and spillage from refueling operations. Those components of the State emissions were left out of the State-level emissions to avoid double counting refueling emissions in the non-road sector. For the purposes of 2002 emission estimates for Base G, the 2005 values were assumed equal to 2002 values.

The 2005 State-level estimates minus the refueli ng component from Appendix Table B-2 of the report were summed for each State and then allocated to the county-level. The county-level allocation was based on the fuel usage information obtained from the NONROAD 2005 model runs conducted as part of the Base G inventory development effort (see the 2002 base year Base G non-road section below). MACTEC used the spillage file from the NONROAD model (normally located in the DATA\EMSFAC directory in a standard installation of NONROAD) to determine the SCCs that used containers for refueling. The spillage file contains information by SCC and horsepower indicating whether or not the refueling occurs using a container or a pump.All SCC and horsepower classes using containers were extracted from the file and crossreferenced with the fuel usage by county for those SCC/horsepower combinations from the appropriate year model runs (2002, 2009 or 2018). Then the fuel usages by county from the NONROAD 2005 runs prepared for VISTAS were summed for those SCCs by county. The county level fuel use was then divided by the State total fuel use for the same SCCs to determine the fraction of total State fuel usage and that fraction was used to allocate the State-level emissions to the county.
1.2.6 Quality Assurance steps Throughout the inventory development process, quality assurance steps were performed to ensure that no double counting of emissions occurred, and to ensure that a full and complete inventory was developed for VISTAS. Quality assurance was an important component to the inventory development process and MACTEC performed the following QA steps on the area source component of the 2002 Base F inventory:
1. All CERR and NIF format State supplied data submittals were run through EPA’s Format and Content checking software.
2. SCC level emission summaries were prepared and evaluated to ensure that emissions were consistent and that there were no missing sources.
3. Tier comparisons (by pollutant) were developed between the revised 2002 base year inventory and the previous (version 3.1) base year inventory.Documentation of the Base G 2002 Base Year, 2009 and 2018, Emission Inventories for VISTAS

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### 4. Fields were either added or used within each NIF data table to track the sources of data for each emission record.
5. Data product summaries were provided to both the VISTAS Emission Inventory Technical Advisor and to Area Source and Fires SIWG representatives for review and comment. Changes based on these comments were implemented in the files.
6. Version numbering was used for all inventory files developed. The version numbering process used a decimal system to track major and minor changes. For example, a major change would result in a version going from 1.0 to 2.0. A minor change would cause a version number to go from 1.0 to 1.1. Minor changes resulting from largely editorial changes would result in a change from 1.00 to 1.01.
In addition, for the fires inventory, data relate d to fuel loading and fuel consumption was reviewed and approved by the VISTAS Fire SIWG to ensure that values used for each type of fire and each individual fire were appropriate . Members of the VISTAS Fire SIWG included representatives from most State Divisions of Forestry (or equivalent) as well as U.S. Forest Service and National Park Service personnel.
For Base G, similar QA steps to those outlined a bove for Base F were undertaken. In addition, all final NIF files were checked using the EPA Format and Content checking software and summary information by State and pollutant were prepared comparing the Base F and Base G inventories.

1.3 Mobile Sources

This section describes the revisions made to the initial 2002 VISTAS Base Year emission inventory on-road mobile source input files. For this work actual emission estimates were not made, rather data files consistent with Mobile Emissions Estimation Model Version 6 (MOBILE6) were developed and provided to the VISTAS modeling contractor. These input data files were then run during the VISTAS modeling to generate on-road mobile source emissions using episodic and meteorological specific conditions configured in the sparse matrix operator Kernel Emissions modeling system (SMOKE) emissions processor.
During initial discussions with the VISTAS Mobile Source SIWG, some States indicated a desire to use CERR mobile source emissions data in place of the VISTAS 2002 inventories generated by E.H. Pechan and Associates, Inc. (the initial VISTAS 2002 Base Year inventory files).
However, the CERR emissions data by itself were not sufficient for an inventory process that includes both base and future year inventories. MACTEC needed to be able to replicate the CERR data rather than simply obtain CERR emissions estimates. The reason for this is that only input files were being prepared to provide revised 2002 estimates during the VISTAS modeling process, rather than the actual emission estimates and that the 2002 input data files would beDocumentation of the Base G 2002 Base Year, 2009 and 2018, Emission Inventories for VISTAS

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### used as a starting point for the projected emission estimates. This meant that the appropriate vehicle miles traveled (VMT), MOBILE6, and/ or NONROAD model input data needed to be provided. If these data were provided with the CERR emissions estimates we used it as the starting point for revision of the 2002 Base Y ear inventory. However MACTEC did not have access to the on-road mobile CERR submissions from EPA, so re-submittal of these data directly to MACTEC was requested in order to begin compiling the appropriate input file data.
In those cases where States did not provide CERR on-road mobile source input data files, our default approach was to maintain the data input files and VMT estimates for the initial 2002 Base Year inventory prepared by Pechan.
1.3.1 Development of on-road mobile source input files and VMT estimates Development of the 2002 on-road input files and VMT was a multi-step process depending upon what the State mobile source contacts instructed us to use as their data. Information provided below provides incremental revisions made to on-road mobile source inventories or inputs in series from one inventory version to the next. In general the process involved one of three steps from the original 2002 on-road mobile source data.

Base F Revisions
1. The first step was to evaluate the initial 2002 base year files and make any nonsubstantive changes (i.e., changes only to confirm that the files posted for 2002 by Pechan were executable and that all the necessary external files needed to run MOBILE6 were present). This approach was taken for AL, FL, GA, MS, SC, and WV. For these States the determination was made that the previous files would be okay to use as originally prepared. For SC, the VMT file was updated, but that did not affect the MOBILE6 input files.
2. For other States, modification to the input files was required. The information below indicates what changes were made for other States in the VISTAS region.
KY – For Kentucky, the Inspection and Maintenance (I/M) records in the input files for Jefferson County were updated in order to better reflect the actual I/M program in the Louisville metropolitan area.
NC - Substantial revisions were implemented to these input files based on input from the State. The modifications necessary to reflect the desires of the State led to complete replacement of the previous input files. Among the changes made were:

• The regrouping of counties (including the movement of some counties from one county group to another and the creation of new input files for previously groupedDocumentation of the Base G 2002 Base Year, 2009 and 2018, Emission Inventories for VISTAS

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### counties). There were originally 32 input files; after the changes there were 49. The pointer file was corrected to reflect these changes.

• Travel speeds were updated in over 3000 scenarios.

• All I/M records were updated.

• All registration distributions were updated.

• I/M VMT fractions were updated (which only affected the pointer file).

• VMT estimates were updated (which has no di rect effect on the MOBILE6 input files but does ultimately affect emissions).
3. VA and TN – For these States, new input files were provided due to substantive changes that the State wanted to make relative to the 2002 initial base year input files. In addition, revised VMT data were developed for each State.

Base G Revisions For the production of the VISTAS 2002 Base G inve ntory, VISTAS states reviewed the Base F inputs, and provided corrections, updates and supplemental data.
For all states modeled, the Base G updates include:
Adding Stage II refueling emissions calculations to the SMOKE processing.
Revised the HDD compliance for all states. (REBUILD EFFECTS = .1)
In addition to the global changes, individual VISTAS states made the following updates:
KY – updated VMT and M6 input values for selected counties.
NC – revised VMT and registration distributions.
TN - revised VMT and vehicle registrati on distributions for selected counties.
VA – revised winter RFG calculations in Mobile 6 inputs.
WV – revised VMT input data.
AL, FL, and GA did not provide updates for Base G and therefore the Base F inputs were used for these States.

1.3.1.1 Emissions from on-road mobile sources The MOBILE6 module of the Sparse Matrix Op erator Kernel Emissions (SMOKE) model was used to develop the on-road mobile source emissions estimates for CO, NO X 

### , NH 3 

### , SO 2 

### , PM, andDocumentation of the Base G 2002 Base Year, 2009 and 2018, Emission Inventories for VISTAS

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### VOC emissions. The MOBILE6 parameters, vehicl e fleet descriptions, and VMT estimates are combined with gridded, episode-specific temperature data to calculate the gridded, temporalized emission estimates. The MOBILE6 emissions factor s are based on episode-specific temperatures predicted by the meteorological model. Further, the MOBILE6 emissions factors model accounts for the following:

• Hourly and daily minimum/maximum temperatures;

• Facility speeds;

• Locale-specific inspection/maintenance (I/M) control programs, if any;

• Adjustments for running losses;

• Splitting of evaporative and exhaust emissions into separate source categories;

• VMT, fleet turnover, and changes in fuel composition and Reid vapor pressure (RVP).
The primary input to MOBILE6 is the MOBILE shell file. The MOBILE shell contains the various options (e.g. type of inspection and main tenance program in effect, type of oxygenated fuel program in effect, alternative vehicle mix pr ofiles, RVP of in-use fuel, operating mode) that direct the calculation of the MOBILE6 emissions factors. The shells used in these runs were based on VISTAS Base F modeling inputs as noted in the previous section.
For this analysis, the on-road mobile source emissions were produced using selected weeks (seven days) of each month and using these days as representative of the entire month. This selection criterion allows for the representation of day-of-the-week variability in the on-road motor vehicles, and models a representation of the meteorological variability in each month. The modeled weeks were selected from mid-month, avoiding inclusion of major holidays.
The parameters for the SMOKE runs are as follows:
Episodes: 2002 Initial Base Year, and 2009 and 2018 Future years, using 2009/2018 inventories and modeled using the same meteorology and episode days as 2002. Episode represented by the following weeks per month: January 15-21 February 12-18 March 12-18 April16-22Documentation of the Base G 2002 Base Year, 2009 and 2018, Emission Inventories for VISTAS

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### May 14-20 June 11-17 July 16-22 August 13-19 September 17-23 October 15-21 November 12-18 December 17-23 Days modeled as holidays for annual run: New Year’s Day - January 1 Good Friday – March 29 Memorial Day – May 27 July 4th Labor Day – September 2 Thanksgiving Day – November 28, 29 Christmas Eve – December 24 Christmas Day – December 25 Output time zone: Greenwich Mean Time (zone 0) Projection: Lambert Conformal with Alpha=33, Beta=45, Gamma=-97, and center at (-97, 40).

Domain: 36 Kilometer Grid: Origin at (-2736, -2088) kilometers with 148 rows by 112 columns and 36-km square grid cells. 12 Kilometer Grid: Origin at (108, -1620) kilometers with 168 rows by 177 columns and 12-km square grid cells. CMAQ model species: The CMAQ configuration was CB-IV with PM. The model species produced were: CO, NO, NO 2 

### , ALD 2 

### , ETH, FORM, ISOP, NR, OLE, PAR, TERPB, TOL, XYL, NH 3 

### , SO 2 

### , SULF, PEC, PMFINE, PNO 3 

### , POA, PSO 4 

### , and PMC. Meteorology data: Daily (25-hour). SMOKE requires the following five types of MCIP outputs: (1) Grid cross 2-d, (2) Grid cross 3-d, (3) Met cross 2-d, (4) Met cross 3-d, and (5), Met dot 3-d.Documentation of the Base G 2002 Base Year, 2009 and 2018, Emission Inventories for VISTAS

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### The reconstructed emissions based on the representative week run were calculated by mapping each day of week (Mon, Tue, Wed, etc.) from the modeled month to the same day of week generated in the representative week run. In the case of holidays, these days were mapped to representative week Sundays. An example of this mapping for the January episode is presented in Table 1.3-1 below. Note that although the emissions were generated for individual calendar years (2002, 2009 and 2018) the meteorology is based on 2002.
Table 1.3-1. Representative day mapping for January episode
(Highlighted representative week).

Modeled Representative Modeled Representative Modeled Representative

Date Day Date Day Date Day 1/1/2002* 1/20/2002 1/11/2002 1/18/2002 1/22/ 2002 1/15/2002 1/2/2002 1/16/2002 1/12/2002 1/19/2002 1/23/2002 1/16/2002 1/3/2002 1/17/2002 1/ 13/2002 1/20/2002 1/24/2002 1/17/2002 1/4/2002 1/18/2002 1/ 14/2002 1/21/2002 1/25/2002 1/18/2002 1/5/2002 1/19/2002 1/15/2002 1/15/2002 1/26/2002 1/19/2002 1/6/2002 1/20/2002 1/16/2002 1/16/2002 1/27/2002 1/20/2002 1/7/2002 1/21/2002 1/17/2002 1/17/2002 1/28/2002 1/21/2002 1/8/2002 1/15/2002 1/18/2002 1/18/2002 1/29/2002 1/15/2002 1/9/2002 1/16/2002 1/19/2002 1/19/2002 1/30/2002 1/16/2002 1/10/2002 1/17/2002 1/20/2002 1/20/2002 1/31/2002 1/17/2002 1/21/2002 1/21/2002 * Modeled holiday



### 1.3.2 Development of non-road emission estimates Emissions from non-road sources were estimated in two steps. First, emissions for non-road sources that are included in the NONROAD mode l were developed. Second, emissions from sources not included in the NONROAD model were estimated. The sections below detail the procedures used for each group of sources.

1.3.2.1 Emissions from NONROAD model sources An initial 2002 base year emissions inventory for non-road engines and equipment covered by the EPA NONROAD model was prepared for VISTAS in early 2004. The methods and assumptions used to develop the inventory are presented in a February 9, 2004 report

“ Development of the VISTAS Draft 2002 Mobile Source Emission Inventory (February 2004 Version) ” as prepared by E.H. Pechan & Associates, Inc. Except as otherwise stated below, all aspects of the preparation methodology documented in that report continue to apply to the revised NONROAD modeling discussed in this section.Documentation of the Base G 2002 Base Year, 2009 and 2018, Emission Inventories for VISTAS

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### Revisions to the initial 2002 NONROAD emissions inventory were implemented to ensure that the latest State and local data were considered, as well as to more accurately reflect gasoline sulfur contents for 2002 and correct other State-sp ecific discrepancies. Those revisions comprise the Base F VISTAS non-road inventory. This section details the specific revisions made to the NONROAD model input files for the Base F and Ba se G VISTAS base year inventories, and provides insight into some key differences between the versions of the NONROAD model employed for the Base F and Base G inventories and the previous version employed for the initial 2002 base year inventory prepared by Pechan.
Revisions to the initial 2002 emissions inventory prepared by Pechan were actually implemented in two stages. An initial set of revisions was implemented in the fall of 2004. Those revisions resulted in the Base F inventory. These were followed by a second set of revisions in the spring of 2006. Those estimates produced the Base G base year inventory. To accurately document the combined effects of both sets of revisions, each set is discussed separately below. Unless otherwise indicated, all revisions implemented in Base F were carried directly into the Base G revision process without change. Thus, the invent ories that resulted from the Base F revisions served as the starting point for the Base G revisions.
For Base F, three VISTAS States provided detailed data revisions for consideration in developing revised model inputs. These States were:

1. North Carolina 2. Tennessee (including a separate submission for Davidson County), and 3. Virginia. The remaining seven VISTAS States indicated that the initial 2002 VISTAS input files prepared by Pechan continued to reflect the most recent data available. These States were:
1. Alabama, 2. Florida, 3. Georgia, 4. Kentucky, 5. Mississippi, 6. South Carolina, and 7. West Virginia. However, it should be recognized that the NONROAD input files for all ten VISTAS States were updated to reflect gasoline sulfur content revisi ons for the Base F 2002 base year inventory (as discussed below). The original files prepared by Pechan are available on their FTP site in the /pub/VISTAS/MOB_0104/ directory.Documentation of the Base G 2002 Base Year, 2009 and 2018, Emission Inventories for VISTAS

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### Before presenting the specific implemented revisions, it is important to note that the Base F 2002 base year inventory utilized a newer release of the NONROAD model than was used for the initial 2002 base year inventory (prepared by Pechan). The Base F 2002 base year inventory, as developed in spring 2004, was based on the Draft NONROAD2004 model, which was released by the EPA in May of 2004. This model is no longer available on EPA’s website. The initial 2002 base year inventory (prepared by Pechan) was based on the Draft NONROAD2002a version of the model (which is also no longer available on EPA’s website). Key differences between the models are as follows:

• Draft NONROAD2004 included the effects of the Tier 4 non-road engine and equipment standards (this did not impact the Base F 2002 inventory estimates, but did affect Base F future year forecasts).

• Draft NONROAD2004 included the exhaust emission impacts of the large spark-ignition engine standards; the evaporative impacts of these standards are not incorporated (this does not impact 2002 inventory estimates, but does affect future year forecasts).

• Draft NONROAD2004 included revised equipment population estimates.

• The PM 2.5 

### fraction for diesel equipment in Draft NONROAD2004 had been updated from 0.92 to 0.97.

• Draft NONROAD2004 included revisions to recrea tional marine activity, useful life, and emission rates.
To the extent that these revisions affect 2002 emissions estimates, they will be reflected as differentials between the initial and Base F 2002 VISTAS base year inventories. It is perhaps important to identify that, at the time of the Base F inventory revisions; the EPA recognized the Draft NONROAD2004 model as an appropriate mechanism for SIP development. Although the model was designated as a draft update, it reflected the latest and most accurate NONROAD planning data at that time, as evidenced by the EPA’s use of that version for the Tier 4 Final Rulemaking.
Prior to the Base G inventory revisions implemented in 2006, the EPA released another updated version of the NONROAD model, designated as Final NONROAD2005 (which can be downloaded from: http://www.epa.gov/OMSW WW/nonrdmdl.htm#model). This version ostensibly represents the final version of the model, although certain components of it have been updated since its first release in December 2005. For the Base G inventory developed in the first half of 2006, all updates of the Final NONROAD2005 model through March 2006 are included. Key differences between Final NONROAD2005 and Draft NONROAD2004 are as follows:

• Final NONROAD2005 reflects the latest basic emission rate and deterioration data.Documentation of the Base G 2002 Base Year, 2009 and 2018, Emission Inventories for VISTAS

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### • Final NONROAD2005 includes emission estimates for a range of evaporative emissions categories not included in Draft NONROAD2004 (tank and hose permeation, hot soak, and running loss emissions).

• Final NONROAD2005 includes a revised diurnal emissions algorithm.

• Final NONROAD2005 includes a revised equipment scrappage algorithm.

• Final NONROAD2005 includes revised state and county equipment allocation data.

• Final NONROAD2005 allows separate sulfur c ontent inputs for marine and land-based diesel fuel.

• Final NONROAD2005 includes revised convers ion factors for hydrocarbon emissions.

• Final NONROAD2005 includes the evaporative emission impacts of the large spark-ignition engine standards (this does not impact 2002 inventory estimates, but does affect future year forecasts).
Unfortunately, due to the extensive revisions associated with Final NONROAD2005, input files created for use with Draft NONROAD2004 (e.g., Base F input files) and earlier versions of the model cannot be used directly with Final NONROAD2005 (used for Base G). This created a rather significant impact in that the VISTAS NONROAD modeling process involves the consideration of over 200 unique sets of input data . To avoid creating new input files for each of these datasets, a conversion process was undertaken wherein each of the Draft NONROAD2004 (Base F) input data files were converted into the proper format required for proper execution in Final NONROAD2005 (Base G). 1 

### This process consisted of the following steps:

• Revise the Draft NONROAD2004 (Base F) input files to include the following two line EPA-developed comment at the end of the input file header (this is a nonsubstantive change implemented solely for consistency with input files produced directly using Final NONROAD2005):

9/2005 epa: Add growth & tech years to OPTIONS packet and Counties & Retrofit files to RUNFILES packet.

1 The necessary conversions where developed by comparing substantively identical input files created using the

graphical user interfaces for bot h Draft NONROAD2004 and Final NONROAD2005. The differences between the input files indicated the specific re visions necessary to convert existi ng VISTAS input files into Final NONROAD2005 format.Documentation of the Base G 2002 Base Year, 2009 and 2018, Emission Inventories for VISTAS

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### • Revise the Draft NONROAD2004 (Base F) input files to include the following two command lines after the “Weekday or weekend” command in the PERIOD packet:

Year of growth calc: Year of tech sel :



### • Revise the Draft NONROAD2004 (Base F) input files to include the following command line after the “Diesel sulfur percent” command in the OPTIONS packet:

Marine Dsl sulfur %: 0.2638


### Note that the value 0.2638 (2638 parts per million by weight [ppmW]) is applicable only for 2002 modeling and was accordingly revised (as described below) for both the 2009 and 2018 Base G forecast inventories. The 2638 ppmW sulfur value for 2002 marine diesel fuel was taken from the 48-State (excludes Alaska and Hawaii) tabulation presented in the April 27, 2004 EPA document “ Diesel Fuel Sulfur Inputs for the Draft NONROAD2004 Model used in the 2004 Non-road Diesel Engine Final Rule .” It should also be noted that this value differs by about 5 percent from the 2500 ppmW value previously used for the initial 2002 VISTAS modeling (performed by Pechan). Prior to Final NONROAD2005 (used for Base G), the NONROAD model allowed only a single diesel fuel sulfur input that was applied to both land-based and marine equipment. As documented in the February 9, 2004 report “ Development of the VISTAS Draft 2002 Mobile Source Emission Inventory (February 2004 Version) ” as prepared by E.H. Pechan & Associates, Inc., a value of 2500 ppmW sulfur was used for all 2002 VISTAS NONROAD modeling. Given the ability of Final NONROAD2005 to distinguish a separate sulfur content for marine equipment and the existing EPA guidance document suggesting an appropriate marine sulfur value of 2638 ppmW for 2002, the existing modeling value of 2500 ppmW was modified (for marine equipment only).

• Replace the Draft NONROAD2004 (Base F) input files RUNFILES packet command line:

TECHNOLOGY : c:\non-road\data\tech\tech.dat



### with the command lines:

EXH TECHNOLOGY : c:\non-road\data\tech\tech-exh.dat EVP TECHNOLOGY : c:\non-road\data\tech\tech-evp.dat



### • Revise the Draft NONROAD2004 (Base F) input files to include the following two command lines after the “EPS2 AMS” command in the RUNFILES packet:Documentation of the Base G 2002 Base Year, 2009 and 2018, Emission Inventories for VISTAS

MACTEC, Inc. 50 US COUNTIES FIPS : c:\non-road\data\allocate\fips.dat
RETROFIT :



### • Revise the Draft NONROAD2004 (Base F) input files to include the following command line after the “Rec marine outbrd” command in the ALLOC FILES packet:

Locomotive NOx : c:\non-road\data\allocate\XX_rail.alo


### Where “XX” varies across input files. For any given file, “XX” is the two digit abbreviation of the state associated with the scenario being modeled (e.g., for Alabama modeling, XX=AL).

• Replace the Draft NONROAD2004 (Base F) input files EMFAC FILES packet command line:

Diurnal : c:\non-road\data\emsfac\diurnal.emf


### with the eight command lines:

Diurnal : c:\non-road\data\emsfac\evdiu.emf TANK PERM : c:\non-road\data\emsfac\evtank.emf NON-RM HOSE PERM : c:\non-road\data\emsfac\evhose.emf RM FILL NECK PERM : c:\non-road\data\emsfac\evneck.emf RM SUPPLY/RETURN : c:\non-road\data\emsfac\evsupret.emf RM VENT PERM : c:\non-road\data\emsfac\evvent.emf HOT SOAKS : c:\non-road\data\emsfac\evhotsk.emf RUNINGLOSS : c:\non-road\data\emsfac\evrunls.emfEVP



### • Revise the Draft NONROAD2004 (Base F) input files to include the following command line after the “PM exhaust” command in the DETERIORATE FILES packet:

Diurnal : c:\non-road\data\detfac\evdiu.det 

### Once revised in this format, the VISTAS non-road input files developed for use with Draft NONROAD2004 (Base F) were executable under the Final NONROAD2005 model (Base G).
The only additional revisions implemented to develop a Final NONROAD2005-based inventory (Base G) involved elimination of non-default equipment allocation files for North Carolina and West Virginia. Due to concerns about improper equipment allocation across counties under the Draft NONROAD2004 model (used for Base F), as well as for earlier versions of the NONROAD model, North Carolina had produced alternative allocation data files indicating the number of employees in air transportation by county, the number of wholesale establishments by county, and the number of employees in landscaping services by county. For the same reason, West Virginia had produced alternative equipment allocation files indicating the number ofDocumentation of the Base G 2002 Base Year, 2009 and 2018, Emission Inventories for VISTAS

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### employees in air transportation by county, the tonnage of underground coal production by county, the number of golf courses and country clubs by county, the number of wholesale establishments by county, the number of employees in logging operations by county, the number of employees in landscaping services by county, the number of employees in manufacturing operations by county, the number of employees in oil and gas drilling and extraction operations by county, and the number of recreational vehicle parks and campgrounds by county. These alternative equipment allocation files were used for all VISTAS inventory modeling conducted prior to the release of Final NONROAD2005 (i.e., through Base F). However, both North Carolina and West Virginia determined that the default allocation file revisions associated with the release of Final NONROAD2005 were appropriate to address the concerns that led to the development of the alternative allocation files. As a result, all alternative allocation file commands were removed from VISTAS NONR OAD2005 (Base G) input files for North Carolina and West Virginia, so that the entire region under the Base G inventory is now modeled using the default allocation files provided with NONROAD2005.
In addition to the alternative equipment allocation files, North Carolina had previously developed an alternative seasonal adjustment file that was used for the Base F inventory in place of the default file provided with Draft NONROAD2004 (and earlier model versions). The alternative data file implemented a single change, namely reclassifying North Carolina as a southeastern state rather than a mid-Atlantic state (as identified in the default data file). Since Final NONROAD2005 continues to identify North Carolina as a mid-Atlantic state, North Carolina requested that the southeastern r eclassification be continued for all NONROAD2005 modeling (Base G). To ensure that any other revisions associated with the seasonal adjustment file released with NONROAD2005 were not overlooked, the previously developed alternative seasonal adjustment file for North Carolina was scrapped and a new alternative file was created from the default seasonal adjustment file provided with Final NONROAD2005 for Base G inventory development. The alternative file, which was used for all North Carolina modeling, reclassifies North Carolina from a mid-Atlantic to a southeastern state. This represents the only non-default data file used for VISTAS NONROAD2005-based (Base G) modeling.
The remainder of this section documents all changes to the originally established VISTAS input file values as documented in the February 9, 2004 report “ Development of the VISTAS Draft 2002 Mobile Source Emission Inventory (February 2004 Version) ” as prepared by E.H. Pechan & Associates, Inc. Unless specifically stated below, all values from that report continue to be used without change in the latest VISTAS modeling.

Base F Revisions: For the initial 2002 base year inventory (developed by Pechan), all NONROAD modeling runs for VISTAS were performed utilizing a gasoline sulfur content of 339 ppmW and a diesel sulfurDocumentation of the Base G 2002 Base Year, 2009 and 2018, Emission Inventories for VISTAS

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### content of 2,500 ppmW. Although the EPA-recommended non-road diesel fuel sulfur content for 2002 is 2,283 ppmW, the 2,500 ppmW sulfur content used for the initial 2002 base year VISTAS inventory was designed to remove the effect of lower non-road diesel fuel sulfur limits applicable only in California. (The EPA recommended inputs can be found in “ Diesel Fuel Sulfur Inputs for the Draft NONROAD2004 Model used in the 2004 Non-road Diesel Engine Final Rule ,” EPA, April 27, 2004.) This correction is appropriate and was retained for the Base F 2002 inventory. Thus, the Base F inventory continue d to assume a diesel fuel sulfur content of 2,500 ppmW across the VISTAS region.
However, 339 ppmW is not the EPA recommended 2002 gasoline sulfur content for either eastern conventional gasoline areas or Federal Reformulated Gasoline (RFG) areas. The recommended sulfur content for eastern conventional gasoline is 279 ppmW year-round, while the recommended sulfur content for RFG areas is 129 ppmW during the summer season and 279 ppmW during the winter season. (Conventional gasoline and RFG sulfur contents for 2002 can be found in “ User’s Guide to MOBILE6.1 and MOBILE6.2, Mobile Source Emission Factor Model ,” EPA420-R-03-010, U.S. EPA, August 2003 [pages 149-155] (available at link at http://www.epa.gov/otaq/m6.htm ) and in the source code for MOBILE6.2 at Block Data BD05.) Given the differences in the EPA-recommended values and the value used to generate the initial 2002 base year inventory, the input files for Base F for all VISTAS areas were updated to reflect revised gasoline sulfur content assumptions.
Since the VISTAS NONROAD modeling is performed on a seasonal basis, and since gasoline sulfur content in RFG areas varies with the RFG season, seasonally-specific gasoline sulfur content values were estimated for use in RFG area modeling. In addition, 25 counties in Georgia are subject to a summertime gasoline sulfur limit of 150 ppmW, so that seasonal sulfur content estimates were also estimated for these counties. The initial 2002 base year NONROAD inventory (prepared by Pechan) for these Georgia counties was based on a year-round 339 ppmW gasoline sulfur content, but that oversight was corrected in the Base F 2002 base year inventory. Based on the seasonal definitions em ployed in the NONROAD model, monthly sulfur contents were averaged to estimate seasonal gasoline sulfur contents as follows:

Month/Season RFG Areas Conventional Gasoline Areas Georgia Gasoline Control Areas
March 279 ppmW 279 ppmW 279 ppmW April 279 ppmW 279 ppmW 279 ppmW May 129 ppmW 279 ppmW 150 ppmW Spring 229 ppmW 279 ppmW 236 ppmW
June 129 ppmW 279 ppmW 150 ppmW July 129 ppmW 279 ppmW 150 ppmWDocumentation of the Base G 2002 Base Year, 2009 and 2018, Emission Inventories for VISTAS

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Summer 129 ppmW 279 ppmW 150 ppmW September 129 ppmW 279 ppmW 150 ppmW
October 279 ppmW 279 ppmW 279 ppmW
November 279 ppmW 279 ppmW 279 ppmW
Fall 229 ppmW 279 ppmW 236 ppmW
December 279 ppmW 279 ppmW 279 ppmW January 279 ppmW 279 ppmW 279 ppmW February 279 ppmW 279 ppmW 279 ppmW
Winter 279 ppmW 279 ppmW 279 ppmW



### Note that the seasonal data are based on simple arithmetic averages and do not consider any monthly variation in activity (and fuel sales), and that the transition between summer and winter seasons is also not considered. Additionally, the summer fuel control season is treated as though it applies from May through September, while the summer RFG season actually ends on September 15 and the Georgia fuel control season does not officially begin until June 1. This treatment is consistent with the treatment of both fuel control programs in the VISTAS on-road vehicle modeling. Each of these influences will result in some error in the estimated sulfur content estimates, but it is expected that this error is small relative to the overall correction from a year-round sulfur content estimate of 339 ppmW.
All NONROAD modeling revisions made as part of the Base F inventory preparation process are presented in Table 1.3-2. Due to more involved updates in several areas, the number of NONROAD input files as well as sequence numbers used to represent these files was alsoupdated in a few instances (as compared to the files used to create the initial 2002 VISTAS nonroad inventory, as documented in the February 9, 2004 report “ Development of the VISTAS Draft 2002 Mobile Source Emission Inventory (February 2004 Version) ” as prepared by E.H. Pechan & Associates, Inc. These structural revisions are presented in Table 1.3-3, and are provided solely for the benefit of NONROAD modelers as the indicated revisions have no impact on generated emission estimates.Documentation of the Base G 2002 Base Year, 2009 and 2018, Emission Inventories for VISTAS

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### Table 1.3-2. Summary of Base F NONROAD Modeling Revisions

State Revisions Implemented

AL (1) Gasoline sulfur content changed from 339 ppmW to 279 ppmW in all counties and all seasons (all are conventional gasoline areas).

FL (1) Gasoline sulfur content changed from 339 ppmW to 279 ppmW in all counties and all seasons (all are conventional gasoline areas).

GA (1) Gasoline sulfur content changed from 339 ppm W to 279 ppmW in all seasons for conventional gasoline counties. (2) Gasoline sulfur content changed from 339 ppmW to 150 ppmW in the summer for all gasoline control counties. (3) Gasoline sulfur content changed from 339 ppmW to 236 ppmW in the spring and fall for all gasoline control counties. (4) Gasoline sulfur content changed from 339 ppmW to 279 ppmW in the winter for all gasoline control counties. Gasoline control counties: Barro w, Bartow, Butts, Carroll, Chero kee (a), Clayton (a), Cobb (a), Coweta (a), Dawson, De Kalb (a), Douglas (a), Fayette (a), Forsyth (a), Fulton (a), Gwinnett (a), Hall, Haralson, Henry (a), Jackson, Newton, Paulding (a), Pickens, Rockdale (a), Spalding, and Walton

KY (1) Gasoline sulfur content changed from 339 ppm W to 279 ppmW in all seasons for conventional gasoline counties. (2) Gasoline sulfur content changed from 339 ppmW to 129 ppmW in the summer for all gasoline control counties. (3) Gasoline sulfur content changed from 339 ppmW to 229 ppmW in the spring and fall for all gasoline control counties. (4) Gasoline sulfur content changed from 339 ppmW to 279 ppmW in the winter for all gasoline control counties. Gasoline control counties: Boone, Bullitt (b), Campbell, Jefferson, Kenton, and Oldham (b)

MS (1) Gasoline sulfur content changed from 339 ppmW to 279 ppmW in all counties and all seasons (all are conventional gasoline areas).

NC (1) Gasoline sulfur content changed from 339 ppmW to 279 ppmW in all counties and all seasons (all are conventional gasoline areas). (2) Utilize revised (i.e., local) allocation files for three equipment categories. (3) Utilize revised (i.e., local) seasonal activity data.

SC (1) Gasoline sulfur content changed from 339 ppmW to 279 ppmW in all counties and all seasons (all are conventional gasoline areas).

TN (1) Gasoline sulfur content changed from 339 ppmW to 279 ppmW in all counties and all seasons (all are conventional gasoline areas). (2) Gasoline Reid Vapor Pressure (RVP) values changed in accordance with local recommendations. (3) Temperature data changed in accordance with local recommendations. (4) Counties regrouped in accordan ce with local recommendations.

- continued -Documentation of the Base G 2002 Base Year, 2009 and 2018, Emission Inventories for VISTAS

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### Table 1.3-2. Summary of Base F NONRO AD Modeling Revisions (continued)

State Revisions Implemented

VA (1) Gasoline sulfur content changed from 339 ppm W to 279 ppmW in all seasons for conventional gasoline counties. (2) Gasoline sulfur content changed from 339 ppmW to 129 ppmW in the summer for all gasoline control counties. (3) Gasoline sulfur content changed from 339 ppmW to 229 ppmW in the spring and fall for all gasoline control counties. (4) Gasoline sulfur content changed from 339 ppmW to 279 ppmW in the winter for all gasoline control counties. (5) Gasoline RVP values changed in accordance with local recommendations. (6) Counties regrouped in accordan ce with local recommendations. (7) The control effectiveness for c ounties subject to Stage II controls revised to 77 percent in accordance with local recommendations. Gasoline control counties: Arlington Co ., Fairfax Co., Loudoun Co., Prince William Co., Stafford Co., Alexandria City, Fairfax City, Falls Church City, Manassas City, Manassas Park City, Chesterfield Co., Hanover Co., Henrico Co., Colonial Heights City, Hopewell City, Richmond City, James City, York Co., Chesapeake City, Hampton City, Newport News City, Norfolk City, Poquoson City, Portsmouth City, Suffolk City, Virginia Beach City, and Williamsburg City (c)

WV (1) Gasoline sulfur content changed from 339 ppmW to 279 ppmW in all counties and all seasons (all are conventional gasoline areas). (2) Continue to utilize local allocation files for nine equipment categories.

Notes:
(a) County is subject to local control currently, but is scheduled to join the RFG program in January 2005. (b) Control area is a portion of the county, but modeling is performed as though the control applies countywide. (c) The EPA also lists Charles City County as an RFG area, but local planners indicate that Charles City County is a convention al gasoline area and it is modeled as such.Documentation of the Base G 2002 Base Year, 2009 and 2018, Emission Inventories for VISTAS

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### Table 1.3-3. Base F NONROAD Input File Sequence and Structural Revisions

State Initial 2002 Base Year Inventory Input File Sequence Numbers Revised 2002 Inventory Input File Sequence Numbers Reason(s) for Change Number of Revised 2002 Inventory NONROAD Input Files

AL 01-08 01-08 No Structural Changes 32 (at 8 per season)

FL 09-10 09-10 No Structural Changes 8 (at 2 per season)
GA 11-13 11-13 No Structural Changes 12 (at 3 per season)

KY 14-22 14-22 No Structural Changes 36 (at 9 per season)
MS 48 48 No Structural Changes 4 (at 1 per season)
NC 23-25 23-25 No Structural Changes 12 (at 3 per season)
SC 26-32 26-32 No Structural Changes 28 (at 7 per season)
TN 33-34 33-34, 49-52 Counties Regrouped 24 (at 6 per season)
VA 35-43 35-38, 40-43 Counties Regrouped 32 (at 8 per season)
WV 44-47 44-47 No Structural Changes 16 (at 4 per season)
All 01-48 01-38, 40-52 204 (at 51 per season)

Note: (1) All files include internal revisions to reflect the data changes summarized in Table 1.3-3 above. This table is intended t o present structural revisions that are of interest in assembling the NONROAD model input files in to a complete VISTAS region inventory. The indicated revisions do not (in and of themselves) result in emission estimate changes.
(2) The NONROAD model imposes an eight digit input file name lim it, so all input files for the revised 2002 base year inventor y follow a modified naming convention to allow each to be distingui shed from the input files for the initial 2002 base year inven tory. For the initial 2002 base year invent ory, the naming convention was:
ss02aaqq , where: ss = the two character State abbreviation, aa = a two character season indicator as follows: AU = autumn, WI = winter, SP = spring, and SU = summer, and qq = the two digit sequence number indicated above.
For the revised 2002 inventory, the naming convention was modified to:
ss02aFqq , where: ss = the two character State abbreviation, a = a one character season indicator as follows: A = autumn, W = winter, S = spring, and X = summer, and qq = the two digit sequence number indicated above.Documentation of the Base G 2002 Base Year, 2009 and 2018, Emission Inventories for VISTAS

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### Base G Revisions: As described above, the primary modeling revision implemented for the Base G 2002 inventory was the use of the Final NONROAD2005 model (in place of the Base F use of Draft NONROAD2004). However, there were other minor revisions implemented for 13 Georgia counties and somewhat more significant revisions implemented for Tennessee. In Georgia, Stage II refueling control was assumed for 13 counties that previously were modeled as having no refueling control under Base F. In addition, to accommodate this Stage II change as well as forecast year changes in gasoline vapor pressure, corresponding changes in the structure and sequence of Georgia NONROAD input files were made. With the exception of the minor Stage II impacts, these structural and sequence changes have no impact on 2002 emission estimates, but allow for consistency between 2002 and forecast year input file structure and sequence. In Tennessee, more significant changes were implemented to gasoline vapor pressure assumptions, as well as similar minor changes in Stage II refueling control assumptions.
In accordance with instructions from Georgia regulators, Stage II refueling control was assumed in the following 13 Georgia counties at a control efficiency value of 81 percent for the Base G inventory:
Cherokee, Clayton, Cobb, Coweta, DeKa lb, Douglas, Fayette, Forsyth, Fulton, Gwinnett, Henry, Paulding, and Rockdale.
No Stage II control was assumed in these counties in prior inventories.
Tennessee regulators provided revised monthly valu es for gasoline vapor pressure. Based on the seasonal definitions employed in the NONROAD mode l, monthly vapor pressures were averaged to estimate seasonal vapor pressures as follows:Documentation of the Base G 2002 Base Year, 2009 and 2018, Emission Inventories for VISTAS

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March 13.5 psi 13.5 psi 13.5 psi April 13.5 psi 13.5 psi 13.5 psi May 9.0 psi 9.0 psi 9.0 psi Spring 12.0 psi 12.0 psi 12.0 psi
June 7.8 psi 7.8 psi 9.0 psi July 7.8 psi 7.8 psi 9.0 psi August 7.8 psi 7.8 psi 9.0 psi
Summer 7.8 psi 7.8 psi 9.0 psi September 1-15 7.8 psi 7.8 psi 9.0 psi September 16-30 11.5 psi 11.5 psi 11.5 psi
October 13.5 psi 13.5 psi 13.5 psi
November 13.5 psi 13.5 psi 13.5 psi
Fall 12.2 psi 12.2 psi 12.4 psi
December 15.0 psi 15.0 psi 15.0 psi January 15.0 psi 15.0 psi 15.0 psi February 13.5 psi 13.5 psi 13.5 psi
Winter 14.5 psi 14.5 psi 14.5 psi
Note: The Nashville area consists of Davidson, Rutherford, Sumner, Williamson and Wilson counties, the Memphis area consists of Shelby County.



### As with the Base F revisions, the seasonal data are based on simple arithmetic averages and do not consider any monthly variation in activity (and fuel sales), nor is the transition between summer and winter seasons considered. Additionally, a monthly average of the September 1-15 and September 16-30 data is calculated prior to averaging the September-November data to estimate a fall average vapor pressure, so that the month of September is weighted identically to the months of October and November.
Tennessee regulators also indicated that Stage II vapor recovery was not in effect in Shelby County, so the Base F NONROAD input files for the county (which assumed Stage II was in place) were revised accordingly.
All Base G NONROAD modeling revisions are presen ted in Table 1.3-4. As indicated above, the differentiation of inputs across previously groupe d counties also required revision to the overall number and sequence of VISTAS NONROAD input files (as compared to the files used to createDocumentation of the Base G 2002 Base Year, 2009 and 2018, Emission Inventories for VISTAS

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### both the initial VISTAS non-road inventory, as documented in the February 9, 2004 report

“ Development of the VISTAS Draft 2002 Mobile Source Emission Inventory (February 2004 Version) ” as prepared by E.H. Pechan & Associates, Inc., and the Base F revised inventory as documented above. These structural revisions are presented in Table 1.3-5, and are provided solely for the benefit of NONROAD modelers as the indicated revisions have no impact on generated emission estimates.
Table 1.3-4. Summary of Base G NONROAD Modeling Revisions

State Revisions Implemented AL (1) Marine diesel sulfur content changed from 2500 ppmW to 2638 ppmW in all counties and seasons. FL (1) Marine diesel sulfur content changed from 2500 ppmW to 2638 ppmW in all counties and seasons.

GA (1) Marine diesel sulfur content changed fro m 2500 ppmW to 2638 ppmW in all counties and seasons. (2) Stage II refueling vapor recovery implemented in 13 counties at an efficiency of 81 percent. (3) Counties regrouped to accommodate base and forecast year data differentiations. Stage II control counties: Cherokee, Clayt on, Cobb, Coweta, De Kalb, Douglas, Fayette, Forsyth, Fulton, Gwinnett, Henry, Paulding, and Rockdale KY (1) Marine diesel sulfur content changed fro m 2500 ppmW to 2638 ppmW in all counties and seasons. MS (1) Marine diesel sulfur content changed from 2500 ppmW to 2638 ppmW in all counties and seasons.

NC (1) Marine diesel sulfur content changed fro m 2500 ppmW to 2638 ppmW in all counties and seasons. (2) Revert to default equipment allocation files for all equipment categories. (3) Utilize revised (i.e., local) seasonal activity data. SC (1) Marine diesel sulfur content changed from 2500 ppmW to 2638 ppmW in all counties and seasons.

TN (1) Marine diesel sulfur content changed fro m 2500 ppmW to 2638 ppmW in all counties and seasons. (2) Gasoline RVP values changed in accordance with local recommendations. (3) Stage II vapor recovery eliminated from Shelby County modeling. VA (1) Marine diesel sulfur content changed fro m 2500 ppmW to 2638 ppmW in all counties and seasons.

WV (1) Marine diesel sulfur content changed fro m 2500 ppmW to 2638 ppmW in all counties and seasons. (2) Revert to default equipment allocation files for all equipment categories.Documentation of the Base G 2002 Base Year, 2009 and 2018, Emission Inventories for VISTAS

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### Table 1.3-5. Spring 2006 NONROAD Input File Sequence and Structural Revisions

State 2002 Inventory Input File Sequence Numbers (Fall 2004) 2002 Inventory Input File Sequence Numbers

(Spring 2006) Reason(s) for Change Number of Final 2002 Inventory NONROAD Input Files

AL 01-08 01-08 No Structural Changes 32 (at 8 per season)

FL 09-10 09-10 No Structural Changes 8 (at 2 per season)
GA 11-13 11-13, 53-54 Counties Regrouped 20 (at 5 per season)

KY 14-22 14-22 No Structural Changes 36 (at 9 per season)
MS 48 48 No Structural Changes 4 (at 1 per season)
NC 23-25 23-25 No Structural Changes 12 (at 3 per season)
SC 26-32 26-32 No Structural Changes 28 (at 7 per season) TN 33-34, 49-52 33-34, 49-52 No Structural Changes 24 (at 6 per season) VA 35-38, 40-43 35-38, 40-43 No Structural Changes 32 (at 8 per season)
WV 44-47 44-47 No Structural Changes 16 (at 4 per season)
All 01-38, 40-52 01-38, 40-54 212 (at 53 per season)

Note: (1) All files include internal revisions to reflect the data changes summarized in Table 1.3-5 above. This table is intended t o present structural revisions that are of interest in assembling the NONROAD model input files in to a complete VISTAS region inventory. The indicated revisions do not (in and of themselves) result in emission estimate changes.
(2) The NONROAD model imposes an eight digit input file name lim it, so all input files for the revised 2002 base year inventor y follow a modified naming convention to allow each to be di stinguished from the input files for the initial 2002 and fall 2004-revised 2002 base year inventory. For the initial 2002 base year inventory, th e naming convention was:
ss02aaqq , where: ss = the two character State abbreviation, aa = a two character season indicator as follows: AU = autumn, WI = winter, SP = spring, and SU = summer, and qq = the two digit sequence number indicated above.
For the fall 2004-revised 2002 inventory, th e naming convention was modified to:
ss02aFqq , where: ss = the two character State abbreviation, a = a one character season indicator as follows: A = autumn, W = winter, S = spring, and X = summer, and qq = the two digit sequence number indicated above.
For the spring 2006-revised 2002 inventory, the naming convention was modified to:
ss02aCqq , where: ss = the two character State abbreviation, a = a one character season indicator as follows: A = autumn, W = winter, S = spring, and X = summer, and qq = the two digit sequence number indicated above.Documentation of the Base G 2002 Base Year, 2009 and 2018, Emission Inventories for VISTAS

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### 1.3.2.2 Emissions from Commercial Marine Vessels, Locomotives, and Airplanes An initial 2002 base year emissions inventory for aircraft, locomotives, and commercial marine vessels (CMV) was prepared for VISTAS in early 2004. The methods and data used to develop the inventory are presented in a February 9, 2004 report “ Development of the VISTAS Draft 2002 Mobile Source Emission Inventory (February 2004 Version) ” as prepared by E.H. Pechan & Associates, Inc. A summary of the initial 2002 base year emissions inventory is presented in Table 1.3-6. Except as otherwise stated below, all aspects of the preparation methodology continue to apply to the Base F and Base G emission inventories.
Revisions to the initial 2002 emissions inventory (prepared by Pechan) were implemented to ensure that the latest State and local data were incorporated as well as to correct an overestimation of PM emissions from aircraft. Revisions were actually implemented in two stages. An initial set of revisions was implemented in the fall of 2004. Those revisions constitute the Base F inventory. These were followed by a second set of revisions in 2006, which constitute the Base G inventory. To accurately document the combined effects of both sets of revisions, each set is discussed separately below. Unless otherwise indicated, all revisions implemented for Base F were carried directly into the Base G revision process without change. Thus, the inventories that resulted from the Base F revisi ons served as the starting point for the Base G revisions.

Base F Revisions: Revisions to the initial 2002 base year emissions inventory were implemented to ensure that the latest State and local data were incorporated as well as to correct an overestimation of PM emissions from aircraft. Seven of the ten VISTAS States provided revised inventory data in the form of emissions reported to the EPA under the CERR. States providing CERR data were Alabama, Georgia, Mississippi, North Carolina, Tennessee (excluding Davidson, Hamilton, Knox, and Shelby Counties), Virginia, and West Virginia.
In many cases, the CERR data were only marginally different than the initial 2002 base year inventory data, but there were several instances where significant updates were evident. The remaining three VISTAS States (Florida, Kentucky, and South Carolina), plus Davidson, Hamilton, Knox, and Shelby counties in Tennessee, indicated that the initial 2002 VISTAS inventory continued to reflect the most recent data available. Florida did provide updated aircraft emissions data for one county (Miami-Dade) and these data were incorporated into the Base F 2002 inventory as described below.
Since several States recommended retaining the initial 2002 base year inventory data for Base F, the initial step toward revising the 2002 inventory consisted of modifying the estimated aircraft PM emissions of the initial inventory. The overestimation of aircraft PM became evident shortlyDocumentation of the Base G 2002 Base Year, 2009 and 2018, Emission Inventories for VISTAS

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### after the release of the initial 2002 base year inventory, when it was determined that VISTAS region airports would constitute the top seven, and 11 of the top 15, PM sources in the nation. Moreover, PM emissions for one airport (Miami International) were a full order of magnitude larger than all other modeled elemental carbon PM emission sources. In addition, unexpected relationships across airports were also obser ved, with emissions for Atlanta’s Hartsfield International being substantially less than those of Miami International, even though Atlanta handles over twice as many aircraft operations annually. Given the pervasiveness of this problem, and since the CERR data submitted by States was based on the initial 2002 VISTAS inventory data, aircraft PM emissions for the entire VISTAS region were recalculated.Documentation of the Base G 2002 Base Year, 2009 and 2018, Emission Inventories for VISTAS

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### Table 1.3-6. Initial 2002 Base Year Aircraft, Locomotive, and Non-Recreational Marine Emissions as Reported in February 2004 Pechan Report (annual tons)

Source State CO NO x PM 10 PM 2.5 SO 2 VOC AL 3,787 175 688 475 17 196 FL 28,518 11,955 46,352 31,983 1,050 3,703 GA 3,175 992 3,919 2,704 94 353 KY 2,666 657 2,597 1,792 63 263 MS 1,593 140 553 381 13 96 NC 6,088 1,548 6,115 4,219 148 613 SC 6,505 515 452 312 88 863 TN 6,854 2,665 7,986 5,510 225 920 VA 17,676 5,607 14,476 9,988 234 3,229 WV 1,178 78 310 214 8 66 Aircraft (2275)

Total 78,040 24,332 83,448 57,578 1,940 10,302 AL 1,195 9,217 917 843 3,337 736 FL 5,888 44,817 1,936 1,781 6,683 1,409 GA 1,038 7,874 334 307 1,173 246 KY 6,607 50,267 2,246 2,066 9,608 1,569 MS 5,687 43,233 1,903 1,750 7,719 1,351 NC 599 4,547 193 178 690 142 SC 1,067 8,100 343 316 1,205 253 TN 4,129 31,397 1,390 1,278 5,753 980 VA 1,198 3,426 929 855 3,258 596 WV 2,094 15,882 668 614 720 497 Commercial

Marine (2280)

Total 29,503 218,760 10,858 9,989 40,146 7,779 VA 136 387 28 26 30 59 Military Marine (2283) Total 136 387 28 26 30 59 AL 3,490 26,339 592 533 1,446 1,354 FL 1,006 9,969 247 222 605 404 GA 2,654 26,733 664 598 1,622 1,059 KY 2,166 21,811 542 488 1,321 867 MS 2,302 23,267 578 520 1,429 899 NC 1,638 16,502 410 369 1,001 654 SC 1,160 11,690 291 261 710 462 TN 4,530 44,793 1,110 999 2,689 1,805 VA 1,928 19,334 1,407 1,266 3,443 798 WV 1,105 11,150 277 249 681 436 Locomotives

(2285)

Total 21,980 211,588 6,118 5,505 14,947 8,738 Grand Total 129,659 455,067 100,452 73,099 57,062 26,877Documentation of the Base G 2002 Base Year, 2009 and 2018, Emission Inventories for VISTAS

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### Aircraft do emit PM while operating. However, offi cial EPA inventory procedures for aircraft generally do not include PM emission factors and, th erefore, aircraft PM is generally erroneously reported as zero. In an effort to overcome this deficiency, the developers of the initial VISTAS 2002 base year aircraft inventory (Pechan) estimated PM emission rates for aircraft using estimated NO x 

### emissions and an unreported PM-to-NO x 

### ratio (i.e., PM = NO x 

### times a PM-to-NO x 

### ratio). According to the initial 2002 base year inventory documentation, this approach was applied only to commercial aircraft NO x 

### , but a review of that inventory indicates that the technique was also applied to military, general aviation, and air taxi aircraft in many, but not all, instances. Although there is nothing inherently incorrect with this approach, the accuracy and inconsistent application of the assumed PM-to-NO x 

### ratio results in grossly overestimated aircraft PM.
Through examination of the initial 2002 base year aircraft inventory (prepared by E.H. Pechan and Associates, Inc.), it is apparent that the commercial aircraft PM-to-NO x 

### ratio used to generate PM emission estimates was approximately equal to 3.95 (i.e., PM = NO x 

### times 3.95). While the majority of observed commercial aircraft PM-to-NO x 

### ratios in that inventory are equal to 3.95, a few range as low as 3.00. If all aircraft estimates are included (i.e., commercial plus military, general aviation, and air taxi), observed PM-to-NO x 

### ratios range from 0 to 123.0, and average 3.43 as illustrated in Table 1.3-7

Table 1.3-7 PM-to-NO x 

### Ratios by Aircraft Type In Initial 2002 Base Year Inventory.

Aircraft Type Average PM-to-NO x Range of PM-to-NO x Average PM 2.5 / PM 10 Range of PM 2.5 / PM 10
Undefined (1) 0.046 0-0.062 0.690 0.690-0.690 Military 0.073 0-92. 3 0.688 0.333-1.000
Commercial 3.953 3.00-3.953 0.690 0.667-0.696
General Aviation 2.059 0-9.00 0.689 0.500-1.000
Air Taxi 2.734 0-123.0 0.690 0.500-1.000 Aggregate 3.427 0-123.0 0.690 0.333-1.000

Note: (1) Two counties report aircraft em issions as SCC 2275000000 “all aircraft.”



### As indicated, the aggregate PM-to-NO x 

### ratio is similar in magnitude to the ratio for commercial aircraft. This results from the dominant nature of commercial aircraft NO x 

### emissions relative to NO x 

### from other aircraft types. It is surmised that ratios that deviate from 3.95 are based on PM emission estimates generated by local planners, which were retained without change in the PM estimation process (although a considerable number of unexplained “zero PM” records also existDocumentation of the Base G 2002 Base Year, 2009 and 2018, Emission Inventories for VISTAS

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### in the initial 2002 base year inventory dataset). Regardless, based on previous statistical analyses performed in support of aircraft emissions inventory development outside the VISTAS region, a PM-to-NO x 

### ratio of 3.95 is too large by over an order of magnitude.
In analyses performed for the Tucson, Arizona planning area, PM-to-NO x 

### ratios for aircraft over a standard aircraft landing and takeoff (LTO) cycl e are shown in Table 1.3-8. Data for this table is taken from “Emissions Inventories for th e Tucson Air Planning Area, Volume I., Study Description and Results,” prepared for the Pima Association of Governments, Tucson, AZ, November 2001. Pages 4-40 through 4-42 of that report, which document the statistical derivation of these ratios, are included in this report as Appendix E.
Table 1.3-8. Tucson, AZ PM-to-NO x 

### Ratios by Aircraft Type.

Aircraft Type PM-to-NO x Commercial Aircraft 0.26

Military Aircraft 0.88
Air Taxi Aircraft 0.50
General Aviation Aircraft 1.90
Note: The PM and NO x emission estimates presented in the Tucson study are for local aircraft operating mode times. For this work, emission estimates for Tucson were recalcu lated for a standard LTO cycle, so that the ratios presented are applicable to the sta ndard LTO cycle and not a Tucson-specifi c cycle. Thus, the ratios presented herein vary somewhat from those asso ciated with the emission estimates pr esented in the Tucson study report.



### In reviewing these data, it should be considered th at they apply to a standard (i.e., EPA-defined) commercial aircraft LTO cycle. 2 

### Aircraft PM-to-NO x 

### ratios vary with operating mode, so that aircraft at airports with mode times that differ from the standard cycle will exhibit varying ratios. However, conducting an airport-specific analysis for all airports in the VISTAS region was beyond the scope of this work. While local PM-to-NO x 

### ratios could vary somewhat from the indicated standard cycle ratios, any error due to this variation will be significantly less than the order of magnitude error associated with the 3.95 commercial aircraft ratio used for the initial 2002 base year inventory.
It should be recognized that while the Tucson area is far removed from the VISTAS region, the data analyzed to generate the PM-to-NO x 

### ratios is standard aircraft emission factor data routinely

2 As defined in AP-42, Compilation of Air Pollutant Emission Factors, Volume II, Mobile Sources, a standard

commercial aircraft LTO cycle consists of 4 minutes of approach tim e, 26 minutes of taxi (7 minutes in plus 19 minutes out), 0.7 minutes of takeoff, and 2.2 minutes of climbout time (approach and climbout times being based on a 3000 foot mixing height).Documentation of the Base G 2002 Base Year, 2009 and 2018, Emission Inventories for VISTAS

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### employed for inventory purposes throughout the United States (as encoded in models such as the Federal Aviation Administration’s Emissions Da ta Management Systems [EDMS]). With the exception of aircraft operating conditions, there are no inherent geographic implications associated with the use of data from the Tucson study. As indicated above, issues associated with local operating conditions have been eliminated by recalculating the Tucson study ratios for a standard LTO cycle.
To implement the revised PM-to-NO x 

### ratios in the Base F inventory, all aircraft PM records were removed from the initial 2002 base year inventory (prepared by Pechan). This includes records for which local planners may have estimated PM emissions. This approach was taken for two reasons. First, there is no way to distinguish which records may have been generated by local planners. Second, the data available to local planners may be no better than that used to generate the presented PM-to-NO x 

### ratio data, so the consistent application of these data to the entire VISTAS region was determined to be the most appropriate approach to generating consistent inventories throughout the region. In undertaking this removal, it became apparent that there was an imbalance in the aircraft NO x 

### and PM records in the initial 2002 base year inventory. Whereas there were 1,531 NO x 

### records in the NIF emission data sets for this source category, there were only 1,212 PM records. The imbalance was distributed between three States, South Carolina, Tennessee, and Virginia as follows:
Table 1.3-9 Non-Corresponding Aircraft Emissions Records

Aircraft NO x records with no corresponding PM record: Aircraft Type South Carolina Virginia Total Military Aircraft 8 100 108
General Aviation Aircraft 14 94 108
Air Taxi Aircraft 5 99 104

Aggregate 27 293 320 Aircraft PM records with no corresponding NO x record: Aircraft Type Tennessee Total
Air Taxi Aircraft 1 1

Aggregate 1 1



### The unmatched PM record was for Hamilton County (Chattanooga), Tennessee and when removed, was not replaced since there was no corresponding NO x 

### record with which to estimate revised PM emissions. It is unclear how this orpha ned record originated, but clearly there can be no air taxi PM emissions without other combustion-related emissions. Thus, the removal of theDocumentation of the Base G 2002 Base Year, 2009 and 2018, Emission Inventories for VISTAS

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### PM 10 

### and PM 2.5 

### records for Hamilton County permanently reduced the overall size of the 2002 initial base year inventory database used as a starting point for Base F by two records.

Of the 320 unmatched NO x 

### records, 269 were records for which the reported emission rate was zero. Therefore, even though associated PM reco rds were missing, the overall inventory was not affected. However, the 51 missing records for which NO x 

### emissions were non-zero, did impact PM estimates for the overall inventory.
Replacement PM 10 

### records were calculated for all aircraft NO x 

### records using the PM-to-NO x 

### ratios presented above. Aircraft type-specific ratios were utilized in all cases, except for two counties where aircraft emissions were reported under the generic aircraft SCC 2275000000. For these counties (Palm Beach County, Florida and Davidson County, Tennessee), the commercial aircraft PM-to-NO x 

### ratio was applied since both contain commercial airports (Palm Beach International and Nashville International).
Replacement aircraft PM 2.5 

### records were also developed. The initial 2002 base year inventory assumed that aircraft PM 2.5 

### was 69 percent of aircraft PM 10 

### . The origin of this fraction is not clear, but it is very low for combustion related PM. The majority of internal combustion engine related PM is typically 1 micron or smaller (PM 1.0 

### ), so that typical internal combustion engine PM 2.5 

### fractions approach 100 percent. For example, the EPA NONROAD model assumes 92 percent for gasoline engine particulate and 97 percent for diesel engine particulate. Based on recent correspondence from the EPA, it appears that the agency is preparing to recommend a PM 2.5 

### fraction of 98 percent for aircraft. (August 12, 2004 e-mail correspondence from U.S. EPA to Gregory Stella of Alpine Geophysics.) This is substantially more consistent with expectations based on emissions test data for other internal combustion engine sources and was used as the basis for the recalculated aircraft PM 2.5 

### emission estimates in the Base F inventory.
Although a substantial portion of the initial 2002 base year inventory was ultimately replaced with data prepared by State and local planners under CERR requirements in developing the Base F inventory, it was necessary to first revise the initial 2002 base year aircraft inventory as described so that records extracted from the i nventory for areas not supplying CERR data for the Base F update would be accurate. Therefore, in no case is the aggregated State data reported for the Base F inventory identical to that of the initial 2002 base year inventory. Even areas relying on the initial 2002 base year inventory will reflect updates in Base F due to changes in emissions of PM 10 

### and PM 2.5 

### from aircraft.
Table 1.3-10 presents the updated initial 2002 base year inventory estimates. These estimates do not reflect any changes related to modifications made to incorporate the CERR data, but instead indicate the impacts associated solely with the recalculation of aircraft PM emissions alone to apply the more appropriate PM to NO x 

### ratios. Table 1.3-11 presents a summary of the netDocumentation of the Base G 2002 Base Year, 2009 and 2018, Emission Inventories for VISTAS

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### impacts of these changes, where an over 90 percent reduction in aircraft PM is observed for all VISTAS areas except South Carolina and Virginia. The reasons for the lesser changes in these two States is that the overall aircraft NO x 

### inventories for both include a large share of military aircraft NO x 

### to which no (or very low) particulate estimates were assigned in the initial 2002 base year inventory. Since these operations are assigned non-zero PM emissions under the revised approach, the increase in military aircraft PM offsets a portion of the reduction in commercial aircraft PM. In Virginia, zero (or near zero) PM military operations were responsible for about 35 percent of total aircraft NO x 

### , while the corresponding fraction in South Carolina was almost 70 percent. As indicated, aggregate aircraft, locomotive, and commercial marine vessel PM is 70-75 percent lower in the updated 2002 base year inventory.Documentation of the Base G 2002 Base Year, 2009 and 2018, Emission Inventories for VISTAS

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### Table 1.3-10. Initial 2002 Base Year Aircraft, Locomotive, and Non-Recreational Marine Emissions with Modified Aircraft PM Emission Rates (annual tons)

Source State CO NO x PM 10 PM 2.5 SO 2 VOC AL 3,787 175 64 62 17 196 FL 28,518 11,955 3,193 3,129 1,050 3,703 GA 3,175 992 269 264 94 353 KY 2,666 657 179 175 63 263 MS 1,593 140 44 43 13 96 NC 6,088 1,548 419 411 148 613 SC 6,505 515 409 401 88 863 TN 6,854 2,665 707 692 225 920 VA 17,676 5,607 2,722 2,667 234 3,229 WV 1,178 78 25 24 8 66 Aircraft (2275)

Total 78,040 24,332 8,030 7,870 1,940 10,302 AL 1,195 9,217 917 843 3,337 736 FL 5,888 44,817 1,936 1,781 6,683 1,409 GA 1,038 7,874 334 307 1,173 246 KY 6,607 50,267 2,246 2,066 9,608 1,569 MS 5,687 43,233 1,903 1,750 7,719 1,351 NC 599 4,547 193 178 690 142 SC 1,067 8,100 343 316 1,205 253 TN 4,129 31,397 1,390 1,278 5,753 980 VA 1,198 3,426 929 855 3,258 596 WV 2,094 15,882 668 614 720 497 Commercial

Marine (2280)

Total 29,503 218,760 10,858 9,989 40,146 7,779 VA 136 387 28 26 30 59 Military Marine (2283) Total 136 387 28 26 30 59 AL 3,490 26,339 592 533 1,446 1,354 FL 1,006 9,969 247 222 605 404 GA 2,654 26,733 664 598 1,622 1,059 KY 2,166 21,811 542 488 1,321 867 MS 2,302 23,267 578 520 1,429 899 NC 1,638 16,502 410 369 1,001 654 SC 1,160 11,690 291 261 710 462 TN 4,530 44,793 1,110 999 2,689 1,805 VA 1,928 19,334 1,407 1,266 3,443 798 WV 1,105 11,150 277 249 681 436 Locomotives

(2285)

Total 21,980 211,588 6,118 5,505 14,947 8,738 Grand Total 129,659 455,067 25,034 23,390 57,062 26,877Documentation of the Base G 2002 Base Year, 2009 and 2018, Emission Inventories for VISTAS

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### Table 1.3-11. Change in Initial 2002 Base Year Emissions due to Aircraft PM Emission Rate Modifications.

Source State CO NO x PM 10 PM 2.5 SO 2 VOC AL 0% 0% -91% -87% 0% 0% FL 0% 0% -93% -90% 0% 0% GA 0% 0% -93% -90% 0% 0% KY 0% 0% -93% -90% 0% 0% MS 0% 0% -92% -89% 0% 0% NC 0% 0% -93% -90% 0% 0% SC 0% 0% -9% +29% 0% 0% TN 0% 0% -91% -87% 0% 0% VA 0% 0% -81% -73% 0% 0% WV 0% 0% -92% -89% 0% 0% Aircraft (2275)

Total 0% 0% -90% -86% 0% 0% AL 0% 0% 0% 0% 0% 0% FL 0% 0% 0% 0% 0% 0% GA 0% 0% 0% 0% 0% 0% KY 0% 0% 0% 0% 0% 0% MS 0% 0% 0% 0% 0% 0% NC 0% 0% 0% 0% 0% 0% SC 0% 0% 0% 0% 0% 0% TN 0% 0% 0% 0% 0% 0% VA 0% 0% 0% 0% 0% 0% WV 0% 0% 0% 0% 0% 0% Commercial

Marine (2280)

Total 0% 0% 0% 0% 0% 0% VA 0% 0% 0% 0% 0% 0% Military Marine (2283) Total 0% 0% 0% 0% 0% 0% AL 0% 0% 0% 0% 0% 0% FL 0% 0% 0% 0% 0% 0% GA 0% 0% 0% 0% 0% 0% KY 0% 0% 0% 0% 0% 0% MS 0% 0% 0% 0% 0% 0% NC 0% 0% 0% 0% 0% 0% SC 0% 0% 0% 0% 0% 0% TN 0% 0% 0% 0% 0% 0% VA 0% 0% 0% 0% 0% 0% WV 0% 0% 0% 0% 0% 0% Locomotives

(2285)

Total 0% 0% 0% 0% 0% 0% Grand Total 0% 0% -75% -68% 0% 0%



### As indicated above, for the Base F 2002 base year inventory, data for all or portions of seven VISTAS States were replaced with corresponding data from recent (as of the fall of 2004) CERR submissions for 2002. Before replacing these data, however, an analysis of the CERR data was performed to ensure consistency with VISTAS inventory methods. It should perhaps also be noted that three of the CERR datasets provided for the Base F 2002 base year inventory (specifically those for Tennessee, Virginia, and West Virginia) included both annual and daily emissions data. Only the annual data were used. Daily values were removed.Documentation of the Base G 2002 Base Year, 2009 and 2018, Emission Inventories for VISTAS

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### Several important observations resulted from this analysis. First, it was clear that all of the CERR data continued to rely on the inaccurate aircraft PM estimation approach employed for the initial 2002 base year inventory. Therefore, an identical aircraft PM replacement procedure as described above for updating the initial 2002 base year inventory was undertaken for CERR supplied data. As a result, the CERR data for all VISTAS States has been modified for inclusion in the Base F 2002 VISTAS base year inventory due to PM replacement procedures.
As was the case with the initial VISTAS 2002 base year inventory, there were a substantial number of aircraft NO x 

### records without corresponding PM records, so that the number of recalculated PM records added to the CERR dataset is greater than the number of PM records removed. The aggregated CERR inventory data, refl ecting data for all or parts of seven States, consisted of 13,656 records, of which 1,211 were aircraft NO x 

### records. However, the number of corresponding aircraft PM records was 662 (662 PM 10 

### records and 662 PM 2.5 

### records). This imbalance was distributed as follows:

Table 1.3-12 CERR Aircraft NO x 

### Records with No Corresponding PM Record.

Aircraft Type Georgia Tennessee Virginia Total Military Aircraft 136 136
Commercial Aircraft 4 136 140
General Aviation Aircraft 1 136 137
Air Taxi Aircraft 136 136

Aggregate 1 4 544 549



### From this tabulation, it is clear that virtually the entire imbalance is associated with the Virginia CERR submission, with minor imbalances in Georgia and Tennessee. Of the 549 unmatched NO x 

### records, 461 were records for which the reported emission rate was zero. Therefore, even though the associated PM records were missing, the overall inventory was not affected. However, the 88 missing records for which NO x 

### emissions were non-zero do impact PM emission estimates for the overall inventory.
Replacement aircraft PM records (both PM 10 

### and PM 2.5 

### ) were generated for the CERR dataset using procedures identical to those described above for the updated initial 2002 base year inventory.
Further analysis revealed that the CERR data for Virginia included only VOC, CO, and NO x 

### emissions for all aircraft, locomotives, and non-recreational marine vessels. Since SO 2 

### , PM 10 

### , and PM 2.5 

### records are included in the 2002 VISTAS inventory, an estimation method was developed for these emission species and applied to the Virginia CERR data. For PM, theDocumentation of the Base G 2002 Base Year, 2009 and 2018, Emission Inventories for VISTAS

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### developed methodology was only employed for locomotive and marine vessel data since aircraft PM was estimated using the PM-to-NO x 

### ratio methodology described above.
Consideration was given to simply adding the Virginia SO 2 

### and non-aircraft PM records from the initial 2002 VISTAS inventory dataset, but it is very unlikely that either the source distribution or associated emission rates are identical across the CERR and initial VISTAS inventories. This was confirmed through a comparative analysis of dataset CO records. Therefore, an estimation methodology was developed using Virginia source-specific SO 2 

### /CO, PM 10 

### /CO, and PM 2.5 

### /PM 10 

### ratios from the initial 2002 base year VISTAS inventory. The calculated ratios were then applied to the source-specific CERR CO emission estimat es to derive associated source-specific SO 2 

### , PM 10 

### , and PM 2.5 

### emissions for the Base F inventory.
Initially, the development of the emissions ratios from the initial 2002 base year inventory was performed at the State (i.e., Virginia), county, and SCC level of detail. However, it readily became clear that there were substantial inconsistencies in ratios for identical SCCs across counties. For example, in one county, the SO 2 

### /CO ratio might be 0.2, while in the next county it would be 2.0. Since the sources in question are virtually identical (e.g., diesel locomotives) and since the fueling infrastructure for these large non-road equipment sources is regional as opposed to local in nature, such variati ons in emission rates are not realistic. Therefore, a more aggregated approach was employed in which SCC-specific emission ratios were developed for the State as a whole. Through this approach county-to-county variation in emission ratios is eliminated, but the underlying variation in CO emissions does continue to influence the resulting aggregate emission estimates. The applied emission ratios are as follows:

Table 1.3-13 Calculated Emission Ratios for VA.

Source SCC SO 2 /CO PM 10 /CO PM 2.5 /CO PM 2.5 /PM 10 Military Airc raft 2275001000 0.0215
Commercial Aircraft 2275020000 0.3292
General Aviation Aircraft 2275050000 0.0002
Air Taxi Aircraft 2275060000 0.0015 Emissions estimated using PM-to-NO x ratios as described previously.

Aircraft Refueling 2275900000 0.0000 0.0000 0.0000
Diesel Commercial Marine 2280002000 0.3697 0.3434 0.3157 0.92
Residual Commercial Marine 2280003000 0.3697 0.3434 0.3157 0.92

Diesel Military Marine 2283002000 0.2422 0.2248 0.2068 0.92
Line Haul Locomotives 2285002005 3.2757 1.2999 1.1696 0.90

Yard Locomotives 2285002010 2.2908 1.2461 1.1205 0.90Documentation of the Base G 2002 Base Year, 2009 and 2018, Emission Inventories for VISTAS

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### It is important to recognize that the inconsistency of emissions ratios across Virginia counties for sources of virtually identical design, which utilize a regional rather than local fueling infrastructure, has potential implications for other VISTAS States. There is no immediately obvious reason to believe that such inconsistencies would be isolated to Virginia.

One final revision to the CERR dataset was undertaken as part of the Base F effort, and that was the removal of two records for unpaved airstrip particulate (SCC 2275085000) in Alabama. Otherwise identical records for these emissions were reported both in terms of filterable and primary particulate. The filterable particulate records were removed as all other particulate emissions in the VISTAS inventories are in terms of primary particulate. It is also perhaps worth noting that a series of aircraft refueling records (SCC 2275900000) for Virginia were left in place, even through typically such emissions would be reported under SCC 2501080XXX in the area source inventory. If additional VISTAS aircraft refueling emissions are reported under SCC 2501080XXX, then it may be desirable to recode these records.
Finally, data for areas of the VISTAS region not represented in the CERR dataset were added to the CERR data by extracting the appropriate records from the initial 2002 base year inventory (with revisions for aircraft PM to NO x 

### ratios). Specifically, records applicable to the States of Florida, Kentucky, South Carolina, and the Tennessee counties of Davidson, Hamilton, Knox, and Shelby were extracted from the revised initial 2002 inventory and added to the CERR dataset to establish the 2002 Base F inventory.
Following this aggregation, one last dataset revision was implemented to complete the development of the 2002 Base F inventory. As indi cated in the introduction of this section, the initial 2002 base year emission estimates for Miami International Airport were determined to be excessive. Although the reason for this inaccuracy was not apparent, revised estimates for aircraft emissions in Miami-Dade County were obtained from Florida planners and used to overwrite the erroneous estimates. (Aircraft emission estimates were provided in an August 10, 2004 e-mail transmittal from Bruce Coward of Miami-Dade County to Martin Costello of the Florida Department of Environmental Protection.)
Table 1.3-14 presents a summary of the resulti ng Base F VISTAS 2002 base year inventory estimates for aircraft, locomotives, and non-recreational marine vessels. Table 1.3-15 provides a comparison of the Base F 2002 base year inventory estimates to those of the initial 2002 base year inventory. As indicated, total emissions for VOC, CO, NO x 

### , and SO 2 

### are generally within 10 percent, but final PM emissions are reduced by 70-80 percent due to the approximate 90 percent reductions in aircraft PM estimates. In addition, the significant changes in Georgia aircraft emissions are due to the CERR correcti on of Atlanta Hartsfield International Airport emissions, which were significantly underestimated in the initial 2002 base year inventory. TheDocumentation of the Base G 2002 Base Year, 2009 and 2018, Emission Inventories for VISTAS

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### reduction in Florida aircraft emissions due to the correction of Miami International estimates is also apparent.
Lastly, Table 1.3-16 provides a direct comparison of emission estimates from the initial and Base F 2002 base year inventories for all 16 VISTAS re gion airports with estimated annual aircraft NO x 

### emissions of 200 tons or greater (as identified at the conclusion of the Base F revisions). 3 

### The table entries are sorted in order of decreasing NO x 

### and once again, the dramatic reduction in PM emissions is evident. However, in addition, the appropriate reversal of the relationship between Atlanta’s Hartsfield and Miami International Airport is also depicted. As a rough method of quality assurance, Table 1.3-15 also includes a gross estimate of expected airport NO x 

### emissions using detailed NO x 

### estimates developed for Tucson International Airport in conjunction with the ratio of local to Tucson LTOs. (The Tucson NO x 

### estimates are revised to reflect a standard LTO cycle rather than the Tu cson-specific LTO cycle. This should provide for a more realistic comparison to VISTAS estimates.) This is not meant to serve as anything other than a crude indicator of the propriety of the developed VISTAS estimates, and it is clear that the range of estimated-to-expected NO x 

### emissions has been substantially narrowed in the Base F 2002 base year inventory. Whereas estimated-to-expected ratios varied from about 0.2 to over 3.5 in the initial 2002 base year inventory, the range of variation is tightened on both ends, from about 0.5 to 1.75 for the Base F 2002 base year inventory. In effect, all estimates are now within a factor of two of the expected estimates, which is quite reasonable given likely variation in local and standard LTO cycles and variations in aircraft fleet mix across airports.
It is perhaps important to note that some shifting in county emissions assignments is evident between the initial and Base F 2002 base year aircraft inventories. For example, for the initial 2002 base year inventory, Atlanta Hartsfield estimates were assigned to Fulton County (FIP 13121), while they are assigned to Clayton County (FIP 13063) for the Base F 2002 base year inventory. Similarly, Dulles International Airport emissions were assigned solely to Fairfax County, Virginia (FIP 51059) in the initial 2002 base year inventory, but are split between Fairfax and Loudoun County (FIP 51107) for Base F. Such shifts reflect local planner decision-making and are not an artifact of the revisions described above.

3 Subsequent revisions performed for Base G result in the addition of the Cincinnati/Northern Kentucky

International Airport to the group of airports with aircraft operations generating at least 200 tons of NO x . These revisions are discussed below, including the addition of an appropriately modified version of the aircraft emissions table.Documentation of the Base G 2002 Base Year, 2009 and 2018, Emission Inventories for VISTAS

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### Table 1.3-14. Base F 2002 Base Year Aircraft, Locomotive, and Non-Recreational Marine Emissions (tons/year)

Source State CO NO x PM 10 PM 2.5 SO 2 VOC AL 3,787 175 226 87 17 196 FL 25,431 8,891 2,424 2,375 800 3,658 GA 6,622 5,372 1,475 1,446 451 443 KY 2,666 657 179 175 63 263 MS 1,593 140 44 43 13 96 NC 6,088 1,548 419 411 148 613 SC 6,505 515 409 401 88 863 TN 7,251 2,766 734 719 235 943 VA 9,763 2,756 1,137 1,115 786 2,529 WV 1,178 78 25 24 8 66 Aircraft (2275)

Total 70,884 22,899 7,072 6,797 2,607 9,670 AL 1,196 9,218 917 844 3,337 737 FL 5,888 44,817 1,936 1,781 6,683 1,409 GA 1,038 7,875 334 307 1,173 246 KY 6,607 50,267 2,246 2,066 9,608 1,569 MS 5,688 43,233 1,903 1,751 7,719 1,351 NC 599 4,547 193 178 690 142 SC 1,067 8,100 343 316 1,205 253 TN 3,624 27,555 1,217 1,120 4,974 860 VA 972 2,775 334 307 359 483 WV 1,528 11,586 487 448 525 362 Commercial

Marine (2280)

Total 28,207 209,972 9,911 9,118 36,275 7,413 VA 110 313 25 23 27 48 Military Marine (2283) Total 110 313 25 23 27 48 AL 3,490 26,339 592 533 1,446 1,354 FL 1,006 9,969 247 222 605 404 GA 2,725 27,453 682 614 1,667 1,086 KY 2,166 21,811 542 488 1,321 867 MS 2,302 23,267 578 520 1,429 899 NC 1,638 16,502 410 369 1,001 654 SC 1,160 11,690 291 261 710 462 TN 2,626 25,627 633 570 1,439 1,041 VA 1,186 11,882 1,529 1,375 3,641 492 WV 1,311 13,224 329 296 808 517 Locomotives

(2285)

Total 19,611 187,764 5,833 5,248 14,066 7,777 Grand Total 118,812 420,948 22,841 21,186 52,976 24,908Documentation of the Base G 2002 Base Year, 2009 and 2018, Emission Inventories for VISTAS

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### Table 1.3-15. Change in 2002 Emissions, Base F Inventory Relative to Initial Inventory

Source State CO NO x PM 10 PM 2.5 SO 2 VOC AL 0% 0% -67% -82% 0% 0% FL -11% -26% -95% -93% -24% -1% GA +109% +442% -62% -47% +379% +26% KY 0% 0% -93% -90% 0% 0% MS 0% 0% -92% -89% 0% 0% NC 0% 0% -93% -90% 0% 0% SC 0% 0% -9% +29% 0% 0% TN +6% +4% -91% -87% +4% +2% VA -45% -51% -92% -89% +236% -22% WV 0% 0% -92% -89% 0% 0% Aircraft (2275)

Total -9% -6% -92% -88% +34% -6% AL +0% +0% +0% +0% +0% +0% FL 0% 0% 0% 0% 0% 0% GA +0% +0% +0% +0% +0% +0% KY 0% 0% 0% 0% 0% 0% MS +0% +0% +0% +0% +0% +0% NC +0% +0% +0% +0% +0% +0% SC 0% 0% 0% 0% 0% 0% TN -12% -12% -12% -12% -14% -12% VA -19% -19% -64% -64% -89% -19% WV -27% -27% -27% -27% -27% -27% Commercial

Marine (2280)

Total -4% -4% -9% -9% -10% -5% VA -19% -19% -12% -12% -12% -19% Military Marine (2283) Total -19% -19% -12% -12% -12% -19% AL 0% 0% 0% 0% 0% 0% FL 0% 0% 0% 0% 0% 0% GA +3% +3% +3% +3% +3% +3% KY 0% 0% 0% 0% 0% 0% MS 0% 0% 0% 0% 0% 0% NC 0% 0% 0% 0% 0% 0% SC 0% 0% 0% 0% 0% 0% TN -42% -43% -43% -43% -46% -42% VA -38% -39% +9% +9% +6% -38% WV +19% +19% +19% +19% +19% +19% Locomotives

(2285)

Total -11% -11% -5% -5% -6% -11% Grand Total -8% -7% -77% -71% -7% -7%Documentation of the Base G 2002 Base Year, 2009 and 2018, Emission Inventories for VISTAS

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### Table 1.3-16. Base F Comparison of Aircraft Emissions (Airports with Aircraft NO x 

### > 200 tons per year)

Airport FIP CO NO x PM 10 PM 2.5 SO 2 VOC Approx. LTOs Predicted NO x VISTAS to Predicted Initial 2002 Base Year Inventory Miami 12086 9,757 5,997 23,706 16,357 525 1,641 150,000 1,680 3.57 Orlando 12095 3,456 2,170 8,578 5,919 204 642 150,000 1,680 1.29 Memphis 47157 3,462 1,934 7,645 5,275 185 603 125,000 1,400 1.38 Reagan 51013 3,892 1,806 7,138 4,925 164 302 100,000 1,120 1.61 Hampton 51650 2,690 1,705 0 0 0 611 Military

Dulles 51059 2,032 1,330 5,246 3,620 0 272 75,000 840 1.58 Orlando-Sanford 12117 3,615 1,225 4,837 3,337 100 351 Atlanta 13121 1,457 913 3,608 2,490 86 274 420,000 4,704 0.19 Fort Lauderdale 12011 1,930 809 3,196 2,206 75 257 75,000 840 0.96 Charlotte 37119 1,643 788 3,113 2,148 75 255 150,000 1,680 0.47 Tampa 12057 1,399 785 3,101 2,140 74 240 75,000 840 0.93 Nashville 47037 1,819 653 40 28 33 239 60,000 672 0.97 Raleigh 37183 1,584 592 2,338 1,613 56 204 75,000 840 0.70 Louisville 21111 1,073 468 1,851 1,277 45 155 60,000 672 0.70 Jacksonville 12031 871 325 1,284 886 31 112 30,000 336 0.97 Palm Beach 12099 1,156 226 0 0 1 132 30,000 336 0.67 Aggregate 41,836 21,724 75,682 52,220 1,655 6,290 0.19-3.57 Base F 2002 Base Year Inventory Atlanta 13063 4,121 5,288 1,435 1,406 443 337 420,000 4,704 1.12 Miami 12086 6,670 2,933 805 789 274 1,596 150,000 1,680 1.75 Orlando 12095 3,456 2,170 568 556 204 642 150,000 1,680 1.29 Memphis 47157 3,462 1,934 506 495 185 603 125,000 1,400 1.38 Orlando-Sanford 12117 3,615 1,225 338 332 100 351 Fort Lauderdale 12011 1,930 809 217 212 75 257 75,000 840 0.96 Charlotte 37119 1,643 788 206 202 75 255 150,000 1,680 0.47 Tampa 12057 1,399 785 206 202 74 240 75,000 840 0.93 Nashville 47037 1,819 653 170 166 33 239 60,000 672 0.97 Reagan 51013 1,269 635 171 168 193 97 100,000 1,120 0.57 Dulles 1 51107 1,807 595 164 161 252 153 37,500 420 1.42 Raleigh 37183 1,584 592 156 153 56 204 75,000 840 0.70 Dulles 2 51059 1,095 591 156 153 252 115 37,500 420 1.41 Hampton 51650 858 535 471 461 18 305 Military Louisville 21111 1,073 468 123 121 45 155 60,000 672 0.70 Jacksonville 12031 871 325 87 85 31 112 30,000 336 0.97 Palm Beach 12099 1,156 226 59 58 1 132 30,000 336 0.67 Aggregate 37,829 20,550 5,838 5,721 2,312 5,793 0.47-1.75 Net Change -10% -5% -92% -89% +40% -8% Note: For the Base F inventory, Dulles International Airport emissions are split betw een two Virginia counties. Predicted NO x is based on the ratio of airport LTOs to test airport (Tucson International Airport) LTOs and NO x . This is not a rigorous comparison, but rather an approximate indicator of expected magnitude.Documentation of the Base G 2002 Base Year, 2009 and 2018, Emission Inventories for VISTAS

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### Base G Revisions: Further revisions to the 2002 base year emissions inventory were implemented in response to additional state data submittals in the spring of 2006. The inventories developed through the Base F revision process (as described above) served as the starting point for the 2006 revisions. Thus, unless otherwise indicated below, all documented Base F revisions continue to apply to the Base G-revised 2002 base year inventory.
As part of the Base G review and update pr ocess, Virginia regulators provided 443 updated emission records for aircraft. These records re flected revisions to aircraft VOC, CO, and NO x 

### , and in a few cases SO 2 

### , emissions records that were already in the Base F VISTAS 2002 inventory (as opposed to the addition of previ ously unreported data). The specific revisions broke down as follows:

Table 1.3-17 Base G VA Aircraft Records Updates

Aircraft Type VOC CO NO x SO 2 Total Military Aircraft 9 9 9 1 28
Commercial Aircraft 12 12 12 17 53
General Aviation Aircraft 65 66 66 0 197
Air Taxi Aircraft 56 56 53 0 165

Aggregate 142 143 140 18 443



### Emissions values for each of the 443 records in the Base F 2002 VISTAS inventory were updated for Base G to reflect the revised data. However, as described above for the Base F revisions, all aircraft SO 2 

### , PM 10 

### , and PM 2.5 

### emissions in Virginia are estimated on the basis of CO (in the case of SO 2 

### ) and NO x 

### emissions (in the cases of PM 10 

### and PM 2.5 

### ). Therefore, since Virginia regulators did not provide updated SO 2 

### emissions for all updated CO emissions records, or updated PM 10 

### or PM 2.5 

### emissions for all updated NO x 

### emissions records, it was necessary to re-estimate aircraft SO 2 

### , PM 10 

### , and PM 2.5 

### emissions in all cases where updated CO or NO x 

### emissions were provided for Base G (and explicit SO 2 

### and/or PM 10 

### and PM 2.5 

### emissions were not).
The procedure used to estimate the SO 2 

### , PM 10 

### , and PM 2.5 

### emissions revisions was identical to that described above for the Base F inventory revisions, except that revised SO 2 

### -to-CO emissions ratios were calculated for commercial aircraft, where 12 pairs of revised CO and SO 2 

### emissions estimates were available. Although a single pair of revised CO and SO 2 

### emissions records was available for military aircraft, this was deemed an insufficient sample with which to replace the military aircraft SO 2 

### -to-CO emissions ratios previously calculated in Base F. However, it is worth noting that the SO 2 

### -to-CO emissions ratio for the revised military aircraft emissions pairDocumentation of the Base G 2002 Base Year, 2009 and 2018, Emission Inventories for VISTAS

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### was within 16 percent of the previously calculated ratio, so any error associated with retention of the Base F ratio will be minor. Table 1.3-18 presents the emissions ratios.

Table 1.3-18 Calculated Base G Emission Ratios for VA.

Source SCC SO 2 /CO (fall 2004) SO 2 /CO (spring 2006) SO 2 /CO (used in 2006) PM 10 /NO x PM 2.5 /PM 10 Military Aircra ft 2275001000 0.0215 0.0180 0.0215 0.88 0.98
Commercial Aircraft 2275020000 0.3292 0.0696 0.0696 0.26 0.98
General Aviation Aircraft 2275050000 0.00016 n/a 0.00016 1.9 0.98
Air Taxi Aircraft 2275060000 0.0015 n/a 0.0015 0.5 0.98



### Application of the SO 2 

### -to-CO emissions ratios to the 130 revised aircraft CO records, for which no corresponding SO 2 

### emission revisions were provided, resulted in an additional 130 aircraft SO 2 

### emission records updates for Virginia. Similarly, application of the PM 10 

### -to-NO x 

### emissions ratios to the 140 revised aircraft NO x 

### records for which no corresponding PM 10 

### emission revisions were provided, resulted in an additional 140 aircraft PM 10 

### emission records updates for Virginia. Application of the PM 2.5 

### -to-PM 10 

### emissions ratios to the 140 revised aircraft PM 10 

### records resulted in an additional 140 aircraft PM 2.5 

### emission records updates for Virginia. Thus, in total, 853 (443+130+140+140) Virginia aircraft emissions records were updated for Base G.
Also as part of the Base G review and update process, Alabama regulators provided 178 updated PM emission records for aircraft (89 records for PM 10 

### and 89 records for PM 2.5 

### ), 42 additional emissions records for locomotives (14 records for VOC, 14 records for CO, and 14 records for NO x 

### ), and 179 additional emission records for aircraft (30 records for VOC, 30 records for CO, 30 records for NO x 

### , 29 records for SO 2 

### , 30 records for PM 10 

### , and 30 records for PM 2.5 

### ). After review, it was determined that the 178 updated PM emission records for aircraft actually reflected the original (overestimated) aircraft PM data that was replaced universally throughout the VISTAS region for Base F. Implementing these latest revisions would, in effect, “undo” the Base F aircraft PM revisions. Following discussi ons with Alabama regulators, it was determined that the 178 aircraft PM records would not be updated for the Base G revisions.
The 42 additional emissions records for locomotives were determined to correspond exactly to existing SO 2 

### , PM 10 

### , and PM 2.5 

### emissions records already in the Base F VISTAS 2002 inventory. It is not clear why these existing records contained no corresponding data for VOC, CO, and NO x 

### , but those data are now reflected through the additional 42 records that have now been added to the Base G 2002 VISTAS inventory for Alabama.
After examining the 179 additional aircraft emissions records in conjunction with Alabama regulators, it was determined that 17 of the records (commercial aircraft records in Dale,Documentation of the Base G 2002 Base Year, 2009 and 2018, Emission Inventories for VISTAS

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### Limestone, and Talladega counties) were errone ous and should be excluded from the update. The remaining 162 records reflected additional general aviation, air taxi, and military aircraft activity in 20 counties and were specifically comprised of 27 records each for VOC, CO, NO x 

### , SO 2 

### , PM 10 

### , and PM 2.5 

### . There were no further issues with the VOC, CO, NO x 

### , and SO 2 

### records and these were added to the Base G 2002 VISTAS inventory without change. It was, however, apparent that the PM 10 

### and PM 2.5 

### records reflected an overestimation of aircraft PM similar to that which was previously corrected throughout the VISTAS region for Base F (as documented above). To overcome this overestimation, the additional aircraft PM 10 

### and PM 2.5 

### records provided by Alabama regulators were replaced with revised emission estimates developed on the basis of the PM 10 

### -to-NO x 

### and PM 2.5 

### -to-PM 10 

### ratios documented under the Base F revisions above. So although 27 aircraft PM 10 

### records and 27 aircraft PM 2.5 

### records were added to the 2002 Alabama inventory, they reflected different em issions values than those provided directly by Alabama regulators.
In total, 204 additional emissions records (42 for locomotives and 162 for aircraft) were added to the Base G 2002 Alabama inventory.
Finally, as part of the Base G review and update process, Kentucky regulators provided 12 updated aircraft emission records for Boone County, to correct previously underestimated aircraft emissions associated with the Cinci nnati/Northern Kentucky International Airport. VOC, CO, and NO x 

### emissions data were provided for military, commercial, general aviation, and air taxi aircraft. No associated updates for SO 2 

### , PM 10 

### , or PM 2.5 

### emissions were provided. Corresponding PM 10 

### emission estimates were developed by applying the PM 10 

### -to-NO x 

### ratios presented in Table 1.3-17 above to the updated NO x 

### emission estimates. PM 2.5 

### emission estimates were developed by applying the PM 2.5 

### -to-PM 10 

### ratios from that same table to the estimated PM 10 

### emissions. SO 2 

### emission estimates were developed by applying the SO 2 

### -to-PM 10 

### ratios developed from the older data (i.e., the data being replaced) for Boone County aircraft to the updated PM 10 

### emissions. Thus, a total of 24 inventory records for Kentucky were updated (VOC, CO, NO x 

### , SO 2 

### , PM 10 

### , and PM 2.5 

### for four aircraft types).
Upon implementation of the universe of updates, 877 existing emission records were revised (853 in Virginia and 24 in Kentucky) and 204 additional emission records (all in Alabama) were added to the 2002 VISTAS inventory. The total number of aircraft, locomotive, and commercial marine inventory records thus changed from 22,838 records in Base F to 23,042 records in Base G.
Table 1.3-19 presents a summary of the resulti ng Base G VISTAS 2002 base year inventory estimates for aircraft, locomotives, and non-recreational marine vessels. Table 1.3-20 provides a comparison of the Base G 2002 base year inventory estimates to those of the Base F 2002 baseDocumentation of the Base G 2002 Base Year, 2009 and 2018, Emission Inventories for VISTAS

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### year inventory. As indicated, total emissions for VOC, CO, NO x 

### , and SO 2 

### are generally within about 5 percent, with changes restricted to the states of Alabama, Kentucky, and Virginia.
Lastly, Table 1.3-21 provides an updated comparison of emission estimates from the Base F and Base G 2002 base year inventories for all 17 VI STAS region airports with estimated annual aircraft NO x 

### emissions of 200 tons or greater. As comp ared to Table 1.3-16, the table reflects the Base G addition of the Cincinnati/Northern Kent ucky International Airport. Aircraft emission estimates for the other 16 airports are unchanged from their Base F values.Documentation of the Base G 2002 Base Year, 2009 and 2018, Emission Inventories for VISTAS

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### Table 1.3-19. Base G-Revised 2002 Base Year Aircraft, Locomotive, and Non-Recreational Marine Emissions (tons/year)

Source State CO NO x PM 10 PM 2.5 SO 2 VOC AL 5,595 185 238 99 18 276 FL 25,431 8,891 2,424 2,375 800 3,658 GA 6,620 5,372 1,475 1,446 451 443 KY 5,577 925 251 246 88 397 MS 1,593 140 44 43 13 96 NC 6,088 1,548 419 411 148 613 SC 6,505 515 409 401 88 863 TN 7,251 2,766 734 719 235 943 VA 11,873 3,885 2,010 1,970 272 2,825 WV 1,178 78 25 24 8 66 Aircraft (2275)

Total 77,712 24,305 8,029 7,734 2,121 10,179 AL 1,196 9,218 917 844 3,337 737 FL 5,888 44,817 1,936 1,781 6,683 1,409 GA 1,038 7,875 334 307 1,173 246 KY 6,607 50,267 2,246 2,066 9,608 1,569 MS 5,688 43,233 1,903 1,751 7,719 1,351 NC 599 4,547 193 178 690 142 SC 1,067 8,100 343 316 1,205 253 TN 3,624 27,555 1,217 1,120 4,974 860 VA 972 2,775 334 307 359 483 WV 1,528 11,586 487 448 525 362 Commercial

Marine (2280)

Total 28,207 209,972 9,911 9,118 36,275 7,413 VA 110 313 25 23 27 48 Military Marine (2283) Total 110 313 25 23 27 48 AL 3,518 26,623 592 533 1,446 1,365 FL 1,006 9,969 247 222 605 404 GA 2,654 26,733 664 598 1,622 1,059 KY 2,166 21,811 542 488 1,321 867 MS 2,302 23,267 578 520 1,429 899 NC 1,638 16,502 410 369 1,001 654 SC 1,160 11,690 291 261 710 462 TN 2,626 25,627 633 570 1,439 1,041 VA 1,186 11,882 1,529 1,375 3,641 492 WV 1,311 13,224 329 296 808 517 Locomotives

(2285)

Total 19,568 187,328 5,815 5,232 14,022 7,761 Grand Total 125,597 421,918 23,780 22,107 52,444 25,401Documentation of the Base G 2002 Base Year, 2009 and 2018, Emission Inventories for VISTAS

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### Table 1.3-20. Change in 2002 Emissions, Base G Inventory Relative to Base F Inventory

Source State CO NO x PM 10 PM 2.5 SO 2 VOC AL +48% +6% +5% +14% +7% +41% FL 0% 0% 0% 0% 0% 0% GA 0% 0% 0% 0% 0% 0% KY +109% +41% +40% +40% +41% +51% MS 0% 0% 0% 0% 0% 0% NC 0% 0% 0% 0% 0% 0% SC 0% 0% 0% 0% 0% 0% TN 0% 0% 0% 0% 0% 0% VA +22% +41% +77% +77% -65% +12% WV 0% 0% 0% 0% 0% 0% Aircraft (2275)

Total +10% +6% +14% +14% -19% +5% AL 0% 0% 0% 0% 0% 0% FL 0% 0% 0% 0% 0% 0% GA 0% 0% 0% 0% 0% 0% KY 0% 0% 0% 0% 0% 0% MS 0% 0% 0% 0% 0% 0% NC 0% 0% 0% 0% 0% 0% SC 0% 0% 0% 0% 0% 0% TN 0% 0% 0% 0% 0% 0% VA 0% 0% 0% 0% 0% 0% WV 0% 0% 0% 0% 0% 0% Commercial

Marine (2280)

Total 0% 0% 0% 0% 0% 0% VA 0% 0% 0% 0% 0% 0% Military Marine (2283) Total 0% 0% 0% 0% 0% 0% AL +1% +1% 0% 0% 0% +1% FL 0% 0% 0% 0% 0% 0% GA 0% 0% 0% 0% 0% 0% KY 0% 0% 0% 0% 0% 0% MS 0% 0% 0% 0% 0% 0% NC 0% 0% 0% 0% 0% 0% SC 0% 0% 0% 0% 0% 0% TN 0% 0% 0% 0% 0% 0% VA 0% 0% 0% 0% 0% 0% WV 0% 0% 0% 0% 0% 0% Locomotives

(2285)

Total +0% +0% 0% 0% 0% +0% Grand Total +6% +0% +4% +4% -1% +2%Documentation of the Base G 2002 Base Year, 2009 and 2018, Emission Inventories for VISTAS

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### Table 1.3-21. Base G Comparison of Aircraft Emissions (Airports with Aircraft NO x 

### > 200 tons per year)

Airport FIP CO NO x PM 10 PM 2.5 SO 2 VOC Approx. LTOs Predicted NO x VISTAS to Predicted Base F 2002 Base Year Inventory Atlanta 13063 4,121 5,288 1,435 1,406 443 337 420,000 4,704 1.12 Miami 12086 6,670 2,933 805 789 274 1,596 150,000 1,680 1.75 Orlando 12095 3,456 2,170 568 556 204 642 150,000 1,680 1.29 Memphis 47157 3,462 1,934 506 495 185 603 125,000 1,400 1.38 Orlando-Sanford 12117 3,615 1,225 338 332 100 351 Fort Lauderdale 12011 1,930 809 217 212 75 257 75,000 840 0.96 Charlotte 37119 1,643 788 206 202 75 255 150,000 1,680 0.47 Tampa 12057 1,399 785 206 202 74 240 75,000 840 0.93 Nashville 47037 1,819 653 170 166 33 239 60,000 672 0.97 Reagan 51013 1,269 635 171 168 193 97 100,000 1,120 0.57 Dulles 1 51107 1,807 595 164 161 252 153 37,500 420 1.42 Raleigh 37183 1,584 592 156 153 56 204 75,000 840 0.70 Dulles 2 51059 1,095 591 156 153 252 115 37,500 420 1.41 Hampton 51650 858 535 471 461 18 305 Military Louisville 21111 1,073 468 123 121 45 155 60,000 672 0.70 Jacksonville 12031 871 325 87 85 31 112 30,000 336 0.97 Palm Beach 12099 1,156 226 59 58 1 132 30,000 336 0.67 Cincinnati 21015 467 144 38 37 14 54 50,000 560 0.26 Aggregate 38,296 20,694 5,876 5,758 2,326 5,847 0.26-1.75 Base G 2002 Base Year Inventory Atlanta 13063 4,121 5,288 1,435 1,406 443 337 420,000 4,704 1.12 Miami 12086 6,670 2,933 805 789 274 1,596 150,000 1,680 1.75 Orlando 12095 3,456 2,170 568 556 204 642 150,000 1,680 1.29 Memphis 47157 3,462 1,934 506 495 185 603 125,000 1,400 1.38 Orlando-Sanford 12117 3,615 1,225 338 332 100 351 Fort Lauderdale 12011 1,930 809 217 212 75 257 75,000 840 0.96 Charlotte 37119 1,643 788 206 202 75 255 150,000 1,680 0.47 Tampa 12057 1,399 785 206 202 74 240 75,000 840 0.93 Nashville 47037 1,819 653 170 166 33 239 60,000 672 0.97 Reagan 51013 1,269 635 171 168 193 97 100,000 1,120 0.57 Dulles 1 51107 1,807 595 164 161 252 153 37,500 420 1.42 Raleigh 37183 1,584 592 156 153 56 204 75,000 840 0.70 Dulles 2 51059 1,095 591 156 153 252 115 37,500 420 1.41 Hampton 51650 858 535 471 461 18 305 Military Louisville 21111 1,073 468 123 121 45 155 60,000 672 0.70 Cincinnati 21015 3,378 411 110 107 39 187 50,000 560 0.73 Jacksonville 12031 871 325 87 85 31 112 30,000 336 0.97 Palm Beach 12099 1,156 226 59 58 1 132 30,000 336 0.67 Aggregate 41,207 20,961 5,947 5,828 2,352 5,981 0.47-1.75 Net Change +8% +1% +1% +1% +1% +2% Note: For the revised inventory, Dulles International Ai rport emissions are split betw een two Virginia counties. Predicted NO x is based on the ratio of airport LTOs to test airport (Tucson International Airport) LTOs and NO x . This is not a rigorous comparison, but rather an approximate indicator of expected magnitude.Documentation of the Base G 2002 Base Year, 2009 and 2018, Emission Inventories for VISTAS

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### 1.3.2.3 Emissions from NONROAD Model Sources in Illinois, Indiana, and Ohio As part of the Base G update process, VISTAS requested that emissions estimates for 2002 be produced for the states of Illinois, Indiana, and Ohio. These estimates were to be produced at the same spatial (i.e., county level by SCC) and temporal resolution as estimates for the VISTAS region.
The requested estimates were produced by extracting a complete set of county-level input data applicable to each of the three states from the latest version of the EPA’s NMIM (National Mobile Inventory Model) model. This included appropriate consideration of all non-default NMIM input files generated by the Midwest Regional Planning Organization (MRPO), as described below. These input data were then assembled into appropriate input files for the Final NONROAD2005 model and emission estimates were produced using the same procedure employed for the VISTAS region as part of the Base G updates.
A complete set of monthly input data was deve loped for each county in Illinois, Indiana, and Ohio by extracting data from the following NMIM database files (using the NMIM MySQL query browser):
county, countrynrfile, countyyear, countyyearmonth, countyyearmonthhour, gasoline, diesel, and natural gas

The database files:
countrynrfile, countyyear, countyyearmonth, and gasoline
were non-default database files provided to VI STAS by the MRPO, and are intended to reflect the latest planning data being used by MRPO modelers.
From these files, monthly data for gasoline vapor pressure, gasoline oxygen content, gasoline sulfur content, diesel sulfur content for land-based equipment, diesel sulfur content for marine-based equipment, natural gas sulfur content, minimum daily temperature, maximum daily temperature, and average daily temperature were developed. In addition, the altitude and Stage II refueling control status of each county, as well as the identity of the associated equipment population, activity, growth, allocation, and seasonal distribution files, was determined. These data were then assembled into Final NONROAD2005 input files on a seasonal basis, with monthly data being arithmetically averaged to produce seasonal equivalents as follows:
Winter = Average of December, January, and February Spring = Average of March, April, and May Summer = Average of June, July, and August, Fall = Average of September, October, and NovemberDocumentation of the Base G 2002 Base Year, 2009 and 2018, Emission Inventories for VISTAS

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### Unlike the VISTAS Base G approach, this approach results in the use of the following non-default data files during the Final NONROAD2005 modeling process:
Table 1.3-22 Non-Default Files Used for MRPO Modeling

Data File Illinois Indiana Ohio Activity File 1700002.act 1800002.act 3900002.act Growth File 17000.grw 18000.grw 39000.grw Population File 17000.pop 18000.pop 39000.pop
Season File 17000.sea 18000.sea 39000.sea
Inboard Marine Allocation File 17000wib.alo 18000wib.alo 39000wib.alo

Outboard Marine Allocation File 17000wob.alo 18000wob.alo 39000wob.alo
Specific Fuel Consumption MRPO-specific file provided by MRPO modelers (arbitrarily named “mrpoBSFC.emf” for this work)

One compromise was made relative to the level of resolution that is available through the basic approach described above, that being the treatment of ambient temperature data. Because NMIM offers a unique temperature profile for every U.S. county -- developed by aggregating temperature data from included and surrounding weat her stations on the basis of their distances from the county population centroid -- it is not possible to explicitly group counties with otherwise identical input streams. Ungrouped however, there would be 1,128 distinct input streams to be processed (102 Illinois counties plus 92 Indiana counties plus 88 Ohio counties at four seasons each), or over five times the number of files processed for the entire VISTAS region.
To surmount this problem and allow counties with similar temperature profiles to be grouped an approach was employed wherein counties were considered groupable if all temperature inputs 4 

### are within ± 2 oF of the corresponding group average. This criterion is quite stringent in that it results in less tolerant grouping than that employed for VISTAS modeling, which uses temperature data from the nearest meteorological station as opposed to "unique" meteorological

4 Non-road temperature inputs used for county grouping are: winter minimum, spring minimum, summer minimum,

fall minimum, winter maximum, spring maximum, summer maximum, fall maximum, winter average, spring average, summer averag e, and fall average.Documentation of the Base G 2002 Base Year, 2009 and 2018, Emission Inventories for VISTAS

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### data for each county. Under this approach, the actual deviation for grouped counties is much less that ± 2 oF for the overwhelming majority of the 12 grouped temperature inputs.
In addition to the required temperature consistency, all other input data for counties to be grouped had to be identical for all four seasons. Using this criterion, Illinois emissions were modeled using 12 county groups, Indiana emissi ons were modeled using 9 county groups, and Ohio emissions were modeled using 10 c ounty groups. Thus, 31 iterations of NONROAD2002 were required per season, as compared to the 53 iterations per season required for the VISTAS region.
It should be noted that a potential quality assurance issue was noted in assembling the NONROAD2005 input data for a number of Indiana counties. Specifically, the gasoline vapor pressure for most Indiana counties reflects a value of 9.0 psi in all spring, summer, fall, and winter months. This is likely to indicate a problem with the accuracy of the NMIM databases for these counties, but these data were used as defined for this work.
1.3.3 Quality Assurance steps Throughout the inventory development process, quality assurance steps were performed to ensure that no double counting of emissions occurred, and to ensure that a full and complete inventory was developed for VISTAS. Quality assurance was an important component to the inventory development process and MACTEC performed the following QA steps on the area source component of the 2002 base year revised:
1. All CERR and NIF format State supplied data submittals were run through EPA’s Format and Content checking software.
2. SCC level emission summaries were prepared and evaluated to ensure that emissions were consistent and that there were no missing sources.
3. Tier comparisons (by pollutant) were developed between the revised 2002 base year inventory and the initial base year inventory.
4. Data product summaries were provided to both the VISTAS Emission Inventory Technical Advisor and to Mobile Source SIWG representatives for review and comment. Changes based on these comments were implemented in the files.
5. Version numbering was used for all inventory files developed. The version numbering process used a decimal system to track major and minor changes. For example, a major change would result in a version going from 1.0 to 2.0. A minor change would cause a version number to go from 1.0 to 1.1. Minor changes resulting from largely editorial changes would result in a change from 1.00 to 1.01.Documentation of the Base G 2002 Base Year, 2009 and 2018, Emission Inventories for VISTAS

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## 2.0 Projection Inventory Development

2.1 Point Sources
We used different approaches for different sectors of the point source inventory:

• For the EGUs, VISTAS relied primarily on the Integrated Planning Model ® 

### (IPM ® 

### ) to project future generation as well as to calculate the impact of future emission control programs. The IPM results were adjusted based on S/L agency knowledge of planned emission controls at specific EGUs.

• For non-EGUs, we used recently updated growth a nd control data consistent with the data used in EPA’s CAIR analyses, and supplemented these data with available S/L agency input and updated fuel use forecast data for the U.S. Department of Energy.
For both sectors, we generated 2009 and 2018 inventories for a combined on-the-books (OTB)and on-the-way (OTW) control scenario. The OTB/OTW control scenario accounts for post2002 emission reductions from promulgated and proposed federal, State, local, and site-specific control programs as of July 1, 2004. Section 2.1.1 discusses the EGU projection inventory development, while Section 2.1.2 discusses the non-EGU projection inventory development.
2.1.1 EGU Emission Projections The following subsections discuss the following specific aspects of the development of the EGU projections. First, we present a chronology of the EGU development process and discuss key decisions in selecting the final methods for performing the emissions projections. Next, we describe the development of the final set of IPM runs that are included in the VISTAS Base G inventory. Next, we describe the process of tran sforming the IPM parsed files into NIF format.Fourth, we discuss the process for ensuring that units accounted for in IPM were not doublecounted in the non-EGU inventory. Fifth, we desc ribe the QA/QC checks that were made to ensure that the IPM results were properly inco rporated into the VISTAS inventory. Sixth, we document the changes to the IPM results that S/L agencies specified they wanted included in the VISTAS inventory based on new information that was not accounted for in the IPM runs. Finally, we present summarize the Base G projected EGU emissions by year, state, and pollutant.
2.1.1.1 Chronology of the Development of EGU Projections At the beginning of the EGU inventory developmen t process, VISTAS considered three options for developing the VISTAS 2009 and 2018 pr ojection inventories for EGUs:

• 

### Option 1 – Use the results of IPM modeling conducted in support of the proposed Clean Air Interstate Rule (CAIR) base and control case analyses as the starting point and refine the projections with readily available inputs from stakeholders; these IPM runs wereDocumentation of the Base G 2002 Base Year, 2009 and 2018, Emission Inventories for VISTAS

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### conducted for 2010 and 2015, which VISTAS would use to represent projected emissions in 2009 and 2018 respectively.

• 

### Option 2 – Use the VISTAS 2002 typical year as the starting point, apply growth factors from the Energy Information Administration, and refine future emission rates with stakeholder input regarding utilization rates, capacity, retirements, and new unit information.

• 

### Option 3 – Use the results of a new round of IPM modeling sponsored by VISTAS and the Midwest Regional Planning Organization (M RPO). These runs incorporated VISTAS specific unit and regulation modified parameters, and generate results for 2009 and 2018 explicitly.
An additional consideration for each of the three options was the inclusion of emission projections developed by the Southern Company specifically for their units. Southern Company is a super-regional company which owns EGUs in Alabama, Florida, Georgia, and Mississippi and participates in VISTAS as an industry stakeholder. Southern Company used their energy budget forecast to project net generation and heat input for every existing and future Southern Company EGU for the years 2009 and 2018. Further documentation of how Southern Company generated the 2009/2018 inventory for their units can be found in Developing Southern Company Emissions and Flue Gas Characteristics fo r VISTAS Regional Haze Modeling (April 2005, presented at 14 th 

### International Emission Inventory Conference)

. Each of these three options and the Southern Company projections were discussed in a series of conference calls with the VISTAS EGU Special Interest Work Group (SIWG) during the fall of 2004. During a conference call on December 6, 2004, the VISTAS EGU SIWG approved the use of the latest VISTAS/MRPO sponsored IPM runs (Option 3) to represent the 2009 and 2018 EGU forecasts of emissions for the OTB and OTW cases. During the call, Alabama and Georgia specified that they did not wish to use Sout hern Company provided emissions forecasts of 2009 and 2018 to represent the sources in their States. Mississippi decided to utilize the Southern Company projections to represent activity at Southern Company facilities in Mississippi. After the call, Florida decided against using Southe rn Company provided emissions forecasts of 2009 and 2018 to represent the sources in their State. Thus, Southern Company data was used only for Southern Company units in Mississippi for both the Base F and Base G projections.
The Option 3 IPM modeling resulted from a joint agreement by VISTAS and MRPO to work together to develop future year utility emissions based on IPM modeling. The decision to use IPM modeling was based in part on a study of utility forecast methods by E.H. Pechan and Associates, Inc. (Pechan) for MRPO, which recommended IPM as a viable methodology (see Electricity Generating Unit {EGU} Growth Modeling Method Task 2 Evaluation , February 11,Documentation of the Base G 2002 Base Year, 2009 and 2018, Emission Inventories for VISTAS

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### 2004). Although IPM results were available from EPA’s modeling to support their rulemaking for the Clean Air Interstate Rule (CAIR), VIST AS stakeholders felt that certain model inputs needed to be improved. Thus, VISTAS and MRPO decided to hire contractors to conduct new IPM modeling and to post-process the IPM results. Southern Company projections in 2009 were roughly comparable with IPM. For 2018, Southern Company projections were generally less than IPM because of assumptions made by Southern Company on which units would be economical to control and incorrect data in the NEEDS database which feeds IPM.
In August 2004, VISTAS contracted with ICF International, Inc., to run IPM to provide utility forecasts for 2009 and 2018 under two future scenarios – Base Case and CAIR Case. The Base Case represents the current operation of the power system under currently known laws and regulations (as known at the time the run was made), including those that come into force in the study horizon. The CAIR Case is the Base Case with the proposed CAIR rule superimposed. The run results were parsed at the unit level for the 2009 and 2018 run years. Also in August 2004, MRPO contracted with E.H. Pechan to post-pr ocess the IPM outputs generated by ICF to provide model-ready emission files. The IPM output files were delivered by ICF to VISTAS in November ( Future Year Electricity Generating Sect or Emission Inventory Development Using the Integrated Planning Model (IPM ® 

### ) in Support of Fine Particulate Mass and Visibility Modeling in the VISTAS and Midwest RPO Regions , January 2005), and the post-processed data files were delivered by Pechan to the MRPO in December 2004 ( LADCO IPM Model Parsed File Post-Processing Methodology and File Preparation , February 8, 2005).
On March 10, 2005, EPA issued the final Clean Air Interstate Rule. VISTAS and MRPO, in conjunction with other RPOs, conducted another round of IPM modeling which reflected changes to control assumptions based on the final CAIR as well as additional changes to model inputs based on S/L agency and stakeholder comments. Several conference calls were conducted in the spring of 2005 to discuss and provide comments on IPM assumptions related to six main topics: power system operation, generating resources, emission control technologies, set-up parameters and rule, financial assumptions, and fuel assumptions. Based on these discussions, VISTAS sponsored a new set of IPM runs to reflect the final CAIR requirements as well as certain changes to IPM assumptions that were agreed to by the VISTAS states. This set of IPM runs is documented in Future Year Electricity Generating Sector Emission Inventory Development Using the Integrated Planning Model (IPM ® 

### ) in Support of Fine Particulate Mass and Visibility Modeling in the VISTAS and Midwest RPO Regions , April 2005 (these runs are referred to as the VISTAS Phase I analysis).
Further refinements to the IPM inputs and assumptions were made by the RPOs, and ICF performed the following four runs using IPM dur ing the summer of 2005 (these runs are referred to as the VISTAS/CENRAP Phase II analysis):Documentation of the Base G 2002 Base Year, 2009 and 2018, Emission Inventories for VISTAS

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### Base Case with EPA 2.1.9 coal, gas and oil price assumptions.

• Base Case with EPA 2.1.9 coal and gas supply curves adjusted for AEO 2005 reference case price and volume relationships.

• Strategy Case with EPA 2.1.9 coal, gas and oil price assumptions.

• Strategy Case with EPA 2.1.9 coal and gas supply curves adjusted for AEO 2005 reference case price and volume relationships.
The above runs were parsed for 2009 and 2018 run years. The above four runs were based on VISTAS Phase I and the EPA 2.1.9 assumptions. The changes that were implemented in the above four runs are summarized below:

• Unadjusted AEO 2005 electricity demand projections were incorporated in the above four runs.

• The gas supply curves were adjusted for AEO 2005 reference case price and volume relationships. The EPA 2.1.9 gas supply curves were scaled such that IPM will solve for AEO 2005 gas prices when the power sector gas demand in IPM is consistent with AEO 2005 power sector gas demand projections.

• The coal supply curves used in EPA 2.1.9 were scaled in such a manner that the average mine mouth coal prices that the IPM is solving in aggregated coal supply regions are comparable to AEO 2005. Due to the fact that the coal grades and supply regions between AEO 2005 and the EPA 2.1.9 are not directly comparable, this was an approximate approach and had to be performed in an iterative fashion. The coal transportation matrix was not updated with EIA assumptions due to significant differences between the EPA 2.1.9 and EIA AEO 2005 coal supply and coal demand region configurations.

• The cost and performance of new units were updated to AEO 2005 reference case levels in all of the above four funs.

• The run years 2008, 2009, 2012, 2015, 2018, 2020 and 2026 were modeled.

• The AEO 2005 life extension costs for fossil and nuclear units were incorporated in the above runs.

• The extensive NEEDS comments provided by VISTAS, MRPO, CENRAP and MANEVU were incorporated into the VISTAS Phase I NEEDS.Documentation of the Base G 2002 Base Year, 2009 and 2018, Emission Inventories for VISTAS

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### • MANE-VU’s comments in regards to the state regulations in the northeast were incorporated.

• Renewable Portfolio Standards (RPS) in the northeast was modeled based on the Regional Greenhouse Gas Initiative analysis. A single RPS cap was modeled for MA, RI, NY, NJ, MD and CT. These states could buy credits from NY, PJM and New England model regions.

• The investments required under the Illinoi s power, Mirant and First Energy NSR settlements were incorporated in the above runs.

For the VISTAS/CENRAP Phase II set of IPM runs , ICF generated two different parsed files. One file includes all fuel burning units (fossil, biomass, landfill gas) as well as non-fuel burning units (hydro, wind, etc.). The second file cont ains just the fossil-fuel burning units (e.g., emissions from biomass and landfill gas are omitted). The RPOs decided to use the fossil-only file for modeling to be consistent with EPA, since EPA used the fossil only results for CAIR analyses. For the 10 VISTAS states, non-fossil fuels accounted for only 0.13 percent of the NOx emissions and 0.04 percent of the SO 2 

### emissions in the 2009 IPM runs.
S/L agencies reviewed the results of the VIST AS/CENRAP Phase II set of IPM runs, which were incorporated into the VISTAS Base F inve ntory. S/L agencies primarily reviewed and commented on the IPM results with respect to IPM decisions on NO x 

### post-combustion controls and SO 2 

### scrubbers. S/L agencies provided the latest information on when and where new SO 2 

### and NO x 

### controls are planned to come online. S/L agencies also reviewed the IPM results to verify that existing controls and emission rates were properly reflected in the IPM runs. As directed by the S/L agencies, adjustments to the IPM results were made to specific units with any new information they had as part of the permitting process or other contact with the industry that indicates which units will install controls as a result of CAIR and when these new controls will come on-line. Mississippi decided to continue to use the Southern Company projections instead of the IPM projections to represent emissions at Southern Company facilities in Mississippi. The state-specified changes to the VISTAS/CENRAP Ph ase II set of IPM runs were used to create the Base G projection inventory (and are documented later in Section 2.1.1.6).

2.1.1.2 VISTAS IPM runs for EGU sources The following general summary of the VISTAS IPM ® 

### modeling is based on ICF’s documentation Future Year Electricity Generating Sector Emission Inventory Development Using the IPM ® 

### in Support of Fine Particulate Mass and Visibility Modeling in the VISTAS and Midwest RPO Regions , April 2005. The ICF documentation is to be used as an extension to EPA's proposed CAIR modeling runs documented in Documentation Supplement for EPA Modeling Applications (V.2.1.6) Using the IPM , EPA 430/R-03-007, July 2003.Documentation of the Base G 2002 Base Year, 2009 and 2018, Emission Inventories for VISTAS

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### IPM provides “forecasts of least-cost capacity expansion, electricity dispatch, and emission control strategies for meeting energy demand a nd environmental, transmission, dispatch, and reliability constraints.” The underlying database in this modeling is U.S. EPA’s National Electric Energy Data System (NEEDS) released with the CAIR Notice of Data Availability (NODA). The NEEDS database contains the existing and planned/committed unit data in EPA modeling applications of IPM. NEEDS includes basic geographic, operating, air emissions, and other data on these generating units. VISTAS St ates and stakeholders provided changes for:

• NO x 

### post-combustion control on existing units

• SO 2 

### scrubbers on existing units

• SO 2 

### emission limitations

• PM controls on existing units

• Summer net dependable capacity

• Heat rate for existing units

• SO 2 

### and NO x 

### control plans based on State rules or enforcement settlements
The years 2009 and 2018 were explicitly modeled.
2.1.1.3 Post-Processing of IPM Parsed Files The following summary of the VISTAS/Midwest Regional Planning Organization (MRPO) IPM modeling is based on Pechan’s documentation LADCO IPM Model Parsed File Post-Processing Methodology and File Preparation , February 8, 2005. The essence of the IPM model postprocessing methodology is to take an initial IPM model output file and transform it into air quality model input files. ICF via VISTAS/MRPO provides an initial spreadsheet file containing unit-level records of both
(1) “existing” units and
(2) committed or new generic aggregates.
All records have unit and fuel type data; existing, retrofit (for SO 2 

### and NO x 

### ), and separate NO x 

### control information; annual SO 2 

### and NO x 

### emissions and heat input; summer season (MaySeptember) NO x 

### and heat input; July day NO x 

### and heat input; coal heat input by coal type; nameplate capacity megawatt (MW), and State FI PS code. Existing units also have county FIPS code, a unique plant identifier (ORISPL) and unit ID (also called boiler ID) (BLRID); generic units do not have these data. The processing includes estimating various types of emissions and adding in control efficiencies, stack paramete rs, latitude-longitude coordinates, and State identifiers (plant ID, point ID, stack ID, process ID). Additionally, the generic units are sited in a county and given appropriate IDs. This processing is described in more detail below.Documentation of the Base G 2002 Base Year, 2009 and 2018, Emission Inventories for VISTAS

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### The data are prepared by transforming the generic aggregates into units similar to the existing units in terms of the available data. The generic aggregates are split into smaller generic units based on their unit types and capacity, are provided a dummy ORIS unique plant and boiler ID, and are given a county FIPS code based on an algorithm that sites each generic by assigning a sister plant that is in a county based on its attainment/nonattainment status. Within a State, plants (in county then ORIS plant code order) in attainment counties are used first as sister sites to generic units, followed by plants in PM nonattainment counties, followed by plants in 8-hour ozone nonattainment counties. Note that no LADCO or VISTAS States provided blackout counties that would not be considered when siting generics, so this process is identical to the one used for EPA IPM post-processing.
SCCs were assigned for all units; unit/fuel/firing/bottom type data were used for existing units’assignments, while only unit and fuel type were used for generic units’ assignments. Latitudelongitude coordinates were assigned, first using the EPA-provided data files, secondly using the September 17, 2004 Pechan in-house latitude-longitude file, and lastly using county centroids. These data were only used when the data were not provided in the 2002 NIF files. Stack parameters were attached, first using the EPA-provided data files, secondly using a March 9, 2004 Pechan in-house stack parameter file based on previous EIA-767 data, and lastly using an EPA June 2003 SCC-based default stack parameter file. These data were only used when the data were not provided in the 2002 NIF files.
Additional data were required for estimating VOC, CO, filterable primary PM 10 

### and PM2.5, PM condensable, and NH 3 

### emissions for all units. Thus, ash and sulfur contents were assigned by first using 2002 EIA-767 values for existing units or SCC-based defaults; filterable PM10 and PM2.5 efficiencies were obtained from th e 2002 EGU NEI that were based on 2002 EIA-767 control data and the PM Calculator program (a default of 99.2 percent is used for coal units if necessary); fuel use was back calculated from the given heat input and a default SCC-based heat content; and emission factors were obtained from an EPA-approved October 7, 2004 Pechan emission factor file based on AP-42 emission factor s. Note that this updated file is not the one used for estimating emissions for previous EPA post-processed IPM files. Emissions for 28 temporal-pollutant combinations were estimated since there are seven pollutants (VOC, CO, primary PM 10 

### and PM 2.5 

### , NH 3 

### , SO 2 

### and NO x 

### ) and four temporal periods (annual, summer season, winter season, July day).
The next step was to match the IPM unit IDs with the identifiers in VISTAS 2002 inventory. A crosswalk file was used to obtain FIPS State a nd county, plant ID (within State and county), and point ID. If the FIPS State and county, plant ID and point ID are in the 2002 VISTAS NIF tables, then the process ID and stack ID are obtained from the NIF; otherwise, defaults, described above, were used.Documentation of the Base G 2002 Base Year, 2009 and 2018, Emission Inventories for VISTAS

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### Pechan provided the post-processed files in NIF 3.0 format. Two sets of tables were developed : “NIF files” for IPM units that have a crosswalk match and are in the 2002 VISTAS inventory, and “NoNIF files” for IPM units that are not in the 2002 VISTAS inventory (which includes existing units with or without a crosswalk match as well as generic units).
For Base F and Base G projections, VISTAS reviewed the PM and NH 3 

### emissions from EGUs as provided by Pechan and identified significantly higher emissions in 2009/2018 than in 2002. VISTAS determined that Pechan used a set of PM and NH 3 

### emission factors that are “the most recent EPA approved uncontrolled emission factors” for estimating 2009/2018 emissions. These factors are most likely not the same emission factors used by States for estimating these emissions in 2002 for EGUs in the VISTAS domain. Thus, the emission increase from 2002 to 2009/2018 was simply an artifact of the change in emission factor, not anything to do with changes in activity or control technology application. Also, VISTAS identified an inconsistent use of SCCs for determining emission factors between the base and future years.

VISTAS resolution of the PM and NH 3 

### problem is fully documented in EGU Emission Factors and Emission Factor Assignment, memorandum from Greg Stella to VISTAS State Point Source Contacts and VISTAS EGU Special Interest Workgroup, June 13, 2005. The first step was the adjustment of the 2002 base year emissions inventory. Using the latest “EPA-approved” uncontrolled emission factors by SCC, Alpine Geophysics utilized CERR or VISTAS reported annual heat input, fuel throughput, heat, ash and sulfur content to estimate annual uncontrolled emissions for units identified as output by IPM. This step was conducted for non-CEM pollutants (CO, VOC, PM, and NH 3 

### ) only. For PM emissions, the condensable component of emissions was calculated and added to the resulting PM primary estimations. The resulting emissions were then adjusted by any control efficiency factors reported in the CERR or VISTAS data collection effort. The second adjustment was to the future year inventories. Alpine Geophysics updated the SCCs in the future year inventory to assign the same base year SCC. Using the same methods as described for the 2002 revisions, those non-IPM generated pollutants were estimated using IPM predicted fuel characteristics and base year 2002 SCC assignments.
2.1.1.4 Eliminating Double Counting of EGU Units The following procedures were used to avoid double counting of EGU emissions in the 2009/2018 point source inventory. The 2002 VISTAS point source emission inventory contains both EGUs and non-EGUs. Since this file contains both EGUs and non-EGU point sources, and EGU emissions are projected using the IPM, it was necessary to split the 2002 point source file into two components. The first component contains those emission units accounted for in the IPM forecasts. The second component contains all other point sources not accounted for in IPM.
As described in the previous section, Pechan developed 2009/2018 NIF files for EGUs from the IPM parsed files. All IPM matched units were initially removed from the 2009/2018 point sourceDocumentation of the Base G 2002 Base Year, 2009 and 2018, Emission Inventories for VISTAS

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### inventory to create the non-EGU inventory (which was projected to 2009/2018 using the nonEGU growth and control factors described in Section 2.1.2). This was done on a unit-by-unit basis based on a cross-reference table that matches IPM emission unit identifiers (ORISPL plant code and BLRID emission unit code) to VISTAS NIF emission unit identifiers (FIPSST state code, FIPSCNTY county code, State Plant ID, State Point ID). When there was a match between the IPM ORISPL/BLRID and the VISTAS emissi on unit ID, the unit was assigned to the EGU inventory; all other emission units we re assigned to the non-EGU inventory.
If an emission unit was contained in the NIF files created by Pechan from the IPM output, the corresponding unit was removed from the initial 2009/2018 point source inventory. The NIF 2009/2018 EGU files from the IPM parsed files were then merged with the non-EGU 2009/2018 files to create the 2009/2018 Base F point source files.
Next, we prepared several ad-hoc QA/QC queries to verify that there was no double-counting of emissions in the EGU and non-EGU inventories:

• We reviewed the IPM parsed files {VIS TASII_PC_1f_AllUnits_2009 (To Client).xls and VISTASII_PC_1f_AllUnits_2018 (To Client).xls} to identify EGUs accounted for in IPM. We compared this list of emission units to the non-EGU inventory derived from theVISTAS cross-reference table to verify that units accounted for in IPM were not doublecounted in the non-EGU inventory. As a result of this comparison, we made a few adjustments in the cross-reference table to add emission units for four plants to ensure these units accounted for in IPM were moved to the EGU inventory.

• We reviewed the non-EGU inventory to identify remaining emission units with an Standard Industrial Classification (SIC) c ode of “4911 Electrical Services” or Source Classification Code of “1-01-xxx-xx External Combustion Boiler, Electric Generation”. We compared the list of sources meeting these selection criteria to the IPM parsed file to ensure that these units were not double-counted.
S/L agencies also reviewed the 2009/2018 point source inventory to verify whether there was any double counting of EGU emissions. In two in stances, S/L agencies provided corrections where an emission unit was double counted.
2.1.1.5 Quality Assurance steps Quality assurance was an important component to the inventory development process and MACTEC performed the following QA steps on the EGU component of the VISTAS revised 2009/2018 EGU inventory:Documentation of the Base G 2002 Base Year, 2009 and 2018, Emission Inventories for VISTAS

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### 1. Provided parsed files (i.e., Excel spreadsheets that provide unit-level results derived from the model plant projections obtained by the IPM) to the VISTAS EGU SIWG for review and comment.
2. Provided facility level emission summaries for 2009/2018 for both the base case and CAIR case to the VISTAS EGU SIWG to ensure that emissions were consistent and that there were no missing sources.
3. Compared, at the State-level, emissions from the IPM parsed files and the post-processed NIF files to verify that the post-processed NIF files were consistent with the IPM parsed file results.
VISTAS requested S/L review of these files – the changes specified by states as a result of this review are documented in the following subsection.
2.1.1.6 S/L Adjustments to IPM Modeling Results for Base G Projections After S/L agency review of the final set of IPM r uns (as incorporated into the Base F inventory), S/L agencies specified a number of changes to the IPM results to better reflect current information on when and where future controls would occur. These changes to the IPM results primarily involved S/L agency addition or subtraction future emission controls based on the best available data from state rules, enforcement agreements, compliance plans, permits, and discussions/commitments from individual companies.
For example, Dominion Virginia Power released their company-wide plan to reduce emission to meet the requirements of CAIR and other programs. This plan varies substantially from the IPM results both in terms current and future controls and timing of these controls. As a result, VA DEQ developed their best estimates of future c ontrols on EGUs in Virginia. Also, Duke Energy and Progress Energy have updated their plans for complying with North Carolina’s Clean Smokestack Act. These plans vary substantially from the IPM results both in terms current and future controls and timing of these controls. As a result, NC DENR replaced the IPM emission projections for 2009 with projections from the Duke Energy and Progress Energy compliance plan. NC DENR elected to use the IPM results for 2018.
Some S/L agencies specified changes to the controls assigned by IPM to reflect their best estimates of emission controls. The changes specified by the S/L agencies are summarized in Table 2.1-1. These changes involved either 1) adding selective catalytic reduction (SCR) or scrubber controls to units where IPM did not predict SCR or scrubber controls, or 2) removing IPM-assigned SCR or scrubber controls at units where the S/L agency indicated their were no firm plans for controls at those units. We used a scrubber control efficiency of 90 percent when adding or removing SO 2 

### scrubber controls. We used a control efficiency of 90 percent when adding or removing NO x 

### SCR controls at coal-fired plants, 80 percent when adding or removingDocumentation of the Base G 2002 Base Year, 2009 and 2018, Emission Inventories for VISTAS

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### NO x 

### SCR controls at gas-fired plants, a nd 35 percent when adding or removing NO x 

### SNCR controls.
In addition to the changes to the IPM-assigned controls, the S/L agencies also specified other types of changes to the IPM results. These other specific changes to the IPM results are summarized in Table 2.1-2.
S/L agencies provided information and/or comment on changes in stack parameters from the 2002 inventory for 2009/2018 inventory. Changes to st ack parameters were also made in cases where new controls are scheduled to be installed. In cases where an emission unit projected to have a SO 2 

### scrubber in either 2009 or 2018, some states were able to provide revised stack parameters for some units based on design features for the new control system. Other units projected to install scrubbers by 2009 or 2018 are not far enough along in the design process to have specific design details. For those units, the VISTAS EGU SIWG made the following assumptions: 1) the scrubber is a wet scrubber; 2) keep the current stack height the same; 3) keep the current flow rate the same, and 4) change the stack exit temperature to 169 degrees F (this is the virtual temperature derived from a wet temp erature of 130 degrees F). VISTAS determined that exit temperature (wet) of 130 degrees F +/- 5 degrees F is representative of different size units and wet scrubber technology.
2.1.1.7 Summary of Base F and Base G 2009/2018 EGU Point Source Inventories Tables 2.1-3 through 2.1-9 compare the Base G 2002 base year inventory to the Base F4 and Base G 2009/2018 projection inventories. The Base F4 projections rely primarily on the results of the IPM, while the Base G projections include the adjustments to the IPM results specified by the S/L agencies in the previous section.Documentation of the Base G 2002 Base Year, 2009 and 2018, Emission Inventories for VISTASMACTEC, Inc.99Table 2.1-1 Adjustments to IPM Control Determinations Specified by S/L Agencies for the Base G 2009/2018 EGU Inventories.NOxEmission ControlsSO2Emission ControlsStatePlant Name and IDUnit2009201820092018IPMStateIPMStateIPMStateIPMStateAL James H. MillerORISID=60021 & 2 SCRduringozoneseasonSCRprobableyear rounddue toCAIRSCRduringozoneseasonSCRprobableyear rounddue toCAIRNone None None Scrubber3 & 4 SCRduringozoneseasonSCR yearround fromConsentDecreeSCRduringozoneseasonSCR yearround fromConsentDecreeNone None None ScrubberBarry1, 2, 3 None SNCR SCR SNCR None None None NoneORISID=3 4 None SNCR SCR SNCR None None Scrubber Scrubber5 None None SCR SCRNone None Scrubber ScrubberE C Gaston1 - 4 SCR None SCRNone None None Scrubber ScrubberORISID=26 5 SCR SCR SCR SCRScrubber None Scrubber ScrubberGorgas6 & 7 None None NoneNone None None None NoneORISID=88 & 9 None None NoneNone None Scrubber None Scrubber10 SCR SCR SCR SCR NoneScrubber Scrubber ScrubberCharles R. Lowman 1 None None None None None Scrubber None ScrubberORISID=56 2 & 3 SCR SCR SCR SCRScrubber Scrubber Scrubber ScrubberGA Bowen 1BLR SCR SCR SCR SCRNone Scrubber ScrubberORISID=703 2BLR SCR SCR SCR SCRNone Scrubber Scrubber3BLR SCR SCR SCR SCRScrubber Scrubber Scrubber4BLR SCR SCR SCR SCRIPM hadretrofitscrubbersbut littleemissionreductionsScrubber Scrubber ScrubberDocumentation of the Base G 2002 Base Year, 2009 and 2018, Emission Inventories for VISTASMACTEC, Inc.100Table 2.1-1 (continued)NOxEmission ControlsSO2Emission ControlsStatePlant Name and IDUnit2009201820092018IPMStateIPMStateIPMStateIPMStateGA Wansley 1 SCR SCR SCR SCRScrubber Scrubber ScrubberORISID=6052 2 SCR SCR SCR SCRIPM hadretrofitscrubbersbut littleemissionreductionsNone Scrubber ScrubberKraft1, 2 None None NoneNone None None None NoneORISID=733 3 None None SCRNone None None None NoneMcIntoshORISID=61241 None None SCR NoneNone None None NoneYates 1 None None None NoneScrubber Scrubber Scrubber ScrubberORISID=728 2, 3 None None NoneNone None None None None4 – 7 None None SCR SCR None None Scrubber NoneHammond 1 None None SCR SCRNone Scrubber Scrubber ScrubberORISID=708 2 None None SCR SCR None Scrubber Scrubber Scrubber3 None None SCR SCR None Scrubber Scrubber Scrubber4 SCR SCR SCR SCR Scrubber Scrubber Scrubber ScrubberKY Ghent 1 None SCR SCR SCR Scrubber Scrubber Scrubber ScrubberORISID=1356 2 None None SCR SCR None Scrubber Scrubber Scrubber3, 4 None SCR SCR SCR None Scrubber Scrubber ScrubberColeman C1 None None SCR SCR None Scrubber Scrubber ScrubberORISID=1381 C2 None None SCR SCR None Scrubber Scrubber ScrubberC3 None None SCR SCR None Scrubber Scrubber ScrubberHMP&L Station 2 H1 SCR SCR SCR SCR Scrubber Scrubber Scrubber ScrubberH2 None SCR SCR SCR Scrubber Scrubber Scrubber ScrubberDocumentation of the Base G 2002 Base Year, 2009 and 2018, Emission Inventories for VISTASMACTEC, Inc.101Table 2.1-1 (continued)NOxEmission ControlsSO2Emission ControlsStatePlant Name and IDUnit2009201820092018IPMStateIPMStateIPMStateIPMStateKY E W Brown 1 None None None None None Scrubber None ScrubberORISID=1355 2 None None SCR SCR None Scrubber Scrubber Scrubber3 None None SCR SCR None Scrubber Scrubber ScrubberSC Jeffries 3 SCR None SCR None None None None NoneORISID=3319 4 None None NoneNone None None None NoneWateree WAT1 SCR SCR SCR SCR None Scrubber None ScrubberORISID=3297 WAT2 SCR SCR SCR SCR None Scrubber Scrubber ScrubberCanadys CAN1 None None NoneNone None None None NoneORISID=3280 CAN2 None None NoneNone None None None NoneCAN3 None None None NoneNone Scrubber None ScrubberRainey CT1A None SCR None SCR None None None NoneORISID=7834 CT1B None SCR NoneSCR None None None NoneTN Kingston1 – 8 SCR SCR SCRSCR None None Scrubber ScrubberORISID=3407 9 None SCR SCR SCR None None Scrubber ScrubberJohnsonville 1 – 10 SCR None SCR SCR None None None NoneORISID=3406WV Willow Island 2 SCR None SCR SCR Scrubber None Scrubber ScrubberORISID=3946Kammer1 -3 SCR None SCR SCR Scrubber None Scrubber ScrubberORISID=3947Documentation of the Base G 2002 Base Year, 2009 and 2018, Emission Inventories for VISTAS

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### Table 2.1-2. Other Adjustments to IPM Results Specified by S/L Agencies for the Base G 2009/2018 EGU Inventories.

State Plant Name and ID Unit Nature of Update/Correction

FL Central Power and Lime ORISID= 10333 GEN1 Central Power and Lime (ORIS10333) is a duplicate entry. This is point 18 in Florida Crushed Stone (12-053-0530021). Removed IPM emissions for Central Power and Lime. Cedar Bay Generating ORISID=10672 GEN1 FLDEP disagrees with IPM projections - no knowledge of expansion of this facility and the cogeneration facility should not grow faster than the underlying industry. Cedar Bay is connected to Stone Container (12-031-0310067). Replaced IPM emissions with 2002 emissions for Cedar Bay (12-031-0310337) times the growth factors for Stone Container. Indiantown Cogeneration ORISID=50976 GEN1 FLDEP disagrees with IPM projections - no knowledge of expansion of this facility and the cogeneration facility should not grow faster than the underlying industry. Indiantown is connected to Louis Dreyfus Citrus (12-085- 0850002). Replaced IPM emissions with 2002 emissions for Indiantown (12-085-0850102) times the growth factors for Louis Drefus Citrus.
GA Bowen ORISID=703 1BLR 2BLR 3BLR 4BLR IPM indicated retrofit scrubbers on all 4 units in 2009, but the IPM emissions showed little reductions from 2002 levels. Changed emissions to reflect scrubbers on 3BLR and 4BLR by 2009. Wansley ORISID=6052 1, 2 IPM indicated retrofit scrubbers on both units in 2009, but the IPM emissions showed little reductions from 2002 levels. Changed emissions to reflect one scrubber on Unit 1 by 2009.
Riverside ORISID=734 4 All of plant Riverside was retired from service June 1, 2005; emissions set to zero in 2009 and 2018.

McIntosh ORISID=727 CT10A CT10B CT11A CT11B The McIntosh Combined Cycl e facility became commercial June 1, 2005. Added 346 tons of NO x and 121 tons of SO 2 per unit to the 2009 and 2018 inventories.

Longleaf Energy Station 1, 2 Longleaf Energy Station is being proposed by LS Power Development, Inc. GA specified that the emissions from this proposed plant be included in the 2018 projections. Boilers 1 and 2 added 1,882 tons of NO x and 3,227 tons of SO 2 per unit to the 2018 inventory. Duke Murray (55382) 1 Corrected coordinates to 34.7189 and -84.9353
MS R D Morrow ORISID=6061 1, 2 Revised the 2018 emissions to reflect controls not indicated by IPM. The SO 2 emissions are much lower than IPM, but their expected NO x emissions are actually higher than IPM. The controls will be coming online 2009 or 2010, so the 2009 inventory did not change. Jack Watson (2049) Victor J Daniel (6073) Chevron Oil (2047) All MS DEQ specified that the emission projections provided by the Southern Company for their units in Mississippi were to be used instead of the IPM results.Documentation of the Base G 2002 Base Year, 2009 and 2018, Emission Inventories for VISTAS

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### Table 2.1-2 (continued)

State Plant Name and ID Unit Nature of Update/Correction
NC G G Allen (2718) Belews Creek (8042)1 Buck (2720) Cliffside (2721) Dan River (2723) Marshall (2727) Riverbend (2732) All Replaced all IPM 2009 results with emission projections from Duke Power’s NC Clean Air Compliance Plan for 2006. Used IPM results for 2018

Asheville (2706) Cape Fear (2708) Lee (2709) Mayo (6250) Roxboro (2712) Sutton (2713) Weatherspoon (2716) All Replaced all IPM 2009 results with emission projections from Progress Energy’s NC Clean Smokestacks Act Calendar Year 2005 Progress Report. Used IPM results for 2018

Dwayne Collier Battle Cogeneration Facility ORISID=10384 GEN1 GEN2 Dwayne Collier Battle is a duplicate entry. This is Cogentrixof Rocky Mount (37-065-3706500146, stacks G-26 and G27). Duplicate entries were removed both the 2009 and 2018 inventories. Kannapolis Energy Partners ORISID=10626 GEN2 GEN3 Kannapolis Energy emissions are being used as credits for another facility. IPM emissions from this facility (37-025- ORIS10626) were removed from the EGU inventory for 2009 and 2018. Emissions from Kannapolis Energy (37-025- 3702500113) were carried forward in the 2009/2018 inventory.
SC Cross ORISID=130 1, 2 Unit 1: upgrade scrubber from 82 percent to 95 percent removal efficiency by June 30, 2006. Recalculate emissions based on upgrade in control efficiency. Unit 2: upgrade scrubber from 70 percent to 87 percent removal efficiency by June 30, 2006. Recalculate emissions based on upgrade in control efficiency. Winyah ORISID=6249 1 – 4 Unit 1: Install scrubber that meets 95 percent removal efficiency by Dec. 31, 2008; Upgrade ESP from 0.38 to 0.03 lb/mmBTU by Dec. 31, 2008 Unit 2: Replace scrubber with one that meets 95 percent removal efficiency from 45 percent by Dec. 31, 2008; Upgrade ESP from 0.10 to 0.03 lb/mmBTU by Dec. 31, 2008 Unit 3: Upgrade scrubber from 70 percent to 90 percent removal efficiency by Dec. 31, 2012; Upgrade ESP from 0.10 to 0.03 lb/mmBTU by Dec. 31, 2012 Unit 4: Upgrade scrubber from 70 percent to 90 percent removal efficiency by Dec. 31, 2007; Upgrade ESP from 0.10 to 0.03 lb/mmBTU by Dec. 31, 2007 Recalculated SO 2 and PM emissions based on upgrade in control efficiencies.Documentation of the Base G 2002 Base Year, 2009 and 2018, Emission Inventories for VISTAS

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### Table 2.1-2 (continued)

State Plant Name and ID Unit Nature of Update/Correction
SC Dolphus Grainger ORISID=3317 1, 2 Unit 1: Upgrade ESP from 0.60 to 0.03 lb/mmBTU by Dec. 31, 2012. Reduced PM 10 and PM25 emissions in 2018 by 95 percent based on change in allowable emission rate Unit 2: Install low NO x burners that meet 0.46 lb/mmBTU from 0.9 by May 1, 2004. Recalculated NO x emissions using 0.46/lbs/mmBtu and IPM heat input Unit 2: Upgrade ESP from 0.60 to 0.03 lb/mmBTU by Dec. 31, 2012. Reduced PM 10 and PM25 emissions in 2018 by 95 percent based on change in allowable emission rate
SC Jeffries ORISID=3319 3, 4 Unit 3: Upgrade ESP from 0.54 to 0.03 lb/mmBTU by Dec. 31, 2012. Reduced PM 10 and PM25 emissions in 2018 by 94.44 percent based on change in allowable emission rate Unit 4: Upgrade ESP from 0.54 to 0.03 lb/mmBTU by Dec. 31, 2012. Reduced PM 10 and PM25 emissions in 2018 by 94.44 percent based on change in allowable emission rate
W S Lee ORISID=3264 1, 2 IPM does not indicate that these units are installing SOFA NO x control technology by April 30, 2006 to meet 0.27 lb/mmBTU, down from 0.45 lb/mmBtu. Calculated NO x emissions using IPM heat input and 0.27 lbs/mmBtu
Generic Unit ORISID=900545 All All predictions for generic units appear reasonable with the exception of Plant ID ORIS900545 Point ID GSC45 which was modeled in Georgetown Count y. It will be very difficult to add new generation this close to the Cape Romain Class I area. Santee Cooper has no plans for future generation in Georgetown County, but does have plans for new future generation in Florence County. This unit was moved to coordinates specified in Florence County.
VA AEP Clinch River ORISID=3775 1, 2, 3 Used IPM results for 2009; replaced all 2018 IPM results with VADEQ’s growth and control estimates (no SCR or scrubbers). AEP Glen Lyn ORISID=3776 51, 52, 6 Used 2009/2018 IPM results for units 51 and 52; used 2009 IPM for unit 6; replaced 2018 IPM for unit 6 with VADEQ’s growth and control estimates (nor SCR or scrubber).
Dominion Clover ORISID=7213 1, 2 Used 2009/2018 IPM results.

Dominion Bremo ORISID=3796 3, 4 Used 2009/2018 IPM results.

Dominion Chesterfield ORISID=3797 3, 4, 5, 6 Replaced all 2009/2018 IPM results using VADEQ’s growth and control estimates.

Dominion Yorktown ORISID=3809 1, 2, 3 Units 1, 2: Used 2009/2018 IPM results for NOx and used VADEQ’s growth and control estimates for SO2. Unit 3: IPM predicts zero heat input for this 880 MW #6 oil fired unit. Dominion plans to continue to operate Unit 3. Replaced all 2009/2018 IPM results using VADEQ’s growth and control estimates.Documentation of the Base G 2002 Base Year, 2009 and 2018, Emission Inventories for VISTAS

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### Table 2.1-2 (continued)

State Plant Name and ID Unit Nature of Update/Correction
VA Dominion Chesapeake ORISID=3803 1 – 4 Unit 1: Used 2009/2018 IPM for NOx; used 2009 IPM for SO2; used VADEQ’s growth and control estimates for SO2 (added scrubber that IPM did not have) Unit 2: Used 2009/2018 IPM for NOx; used 2009 IPM for SO2; used VADEQ’s growth and control estimates for SO2 (added scrubber that IPM did not have) Unit 3: Used VA DEQ’s growth and control estimates for 2009 NOx (added SCR that IPM did not have); used IPM result for 2018 NOx; Used 2009/2018 IPM for SO2. Unit 4: Used VA DEQ’s growth and control estimates for 2009 NOx (added SCR that IPM did not have); used IPM result for 2018 NOx; Used 2009/2018 IPM for SO2.
Dominion Possum Point ORISID=3804 3 & 4 5 6 Unit 3&4: IPM had 137 tons of NO x for these units in 2009 and 111 tons in 2018. VA DEQ sp ecified that the permitted emission rates should be used, which equates to 3,066 tons in 2009 and 2018. Unit 5: IPM had zero heat input. Replaced all 2009/2018 IPM results using VADEQ’s growth and control estimates. Unit 6: Replaced all 2009/2018 IPM results using VADEQ’s growth and control estimates.
Potomac River ORISID=3788 1 - 5 Units 1&2: IPM retired these units. Mirant has no plans at this time to retire any units. Replaced all 2009/2018 IPM results using VADEQ’s growth and control estimates. Units 3, 4, 5: Replaced all 2009/2018 IPM results using VADEQ’s growth and control estimates. WV Albright ORISID=3942 1, 2 IPM predicted early retirement for these units. AEP indicated there are no plans for early retirement. For 2009, used 2002 actual emissions as these units are not likely to retire by 2009. For 2018, used IPM prediction of retirement.
Rivesville ORISID=3945 7, 8 IPM predicted early retirement for these units. AEP indicated there are no plans for early retirement. For 2009, used 2002 actual emissions as these units are not likely to retire by 2009. For 2018, used IPM prediction of retirement.
Willow Island ORISID=3946 1, 2 Unit 1: IPM predicted early retirement for these units. AEP indicated there are no plans for early retirement. For 2009, used 2002 emissions as these units are not likely to retire by 2009. For 2018, used IPM prediction of retirement. Unit 2: IPM predicted SCR and scrubber for 2009. These controls will not be in place by 2009.
North Branch Power Station ORISID=7537 1A, 1B SO 2 Permit Rate was corrected from 2.7 to 0.678 lb/MMBtu. Used SO 2 Permit Rate of 0.678 lb/MMBtu and IPM predicted total fuel used to calculate SO 2 emissions in 2009 and 2018
Mt. Storm ORISID=3954 1, 2, 3 SO 2 Permit Rate was corrected from 2.7 to 0.15 lb/MMBtu. Used SO 2 Permit Rate of 0.15 lb/MMBtu and IPM predicted total fuel used to calculate SO 2 emissions in 2009 and 2018Documentation of the Base G 2002 Base Year, 2009 and 2018, Emission Inventories for VISTAS

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### Table 2.1-3 EGU Point Source SO 2 

### Emission Comparison for 2002/2009/2018.

2002 2009 2018

State 2002 VISTAS BaseG Base F4 IPM Based Base G IPM Based

with S/L Adjustments Base F4 IPM Based Base G IPM Based

with S/L Adjustments
AL 447,828 340,194 378,052 190,099 305,262
FL 453,631 195,790 186,055 141,551 132,177
GA 514,952 534,469 417,449 180,178 230,856
KY 484,057 371,944 290,193 229,603 226,062
MS 67,429 85,629 76,579 27,230 15,146
NC 477,990 205,018 242,286 110,382 108,492
SC 206,399 171,206 124,608 121,694 93,274
TN 334,151 255,400 255,410 112,662 112,672
VA 241,204 169,714 225,653 90,935 140,233
WV 516,084 226,127 277,489 124,466 115,324 Total 3,743,725 2,555,491 2,473,774 1,328,800 1,479,498

Note: Emission summaries above are based on SCCs 1-01-xxx-xx and 2-01-xxx-xx.



### Table 2.1-4 EGU Point Source NO x 

### Emission Comparison for 2002/2009/2018.

2002 2009 2018

State 2002 VISTAS BaseG Base F4 IPM Based Base G IPM Based

with S/L Adjustments Base F4 IPM Based Base G IPM Based

with S/L Adjustments
AL 161,038 70,852 82,305 42,769 64,358
FL 257,677 89,610 86,165 77,080 73,125
GA 147,517 97,146 98,497 58,095 75,717
KY 198,817 107,890 92,021 64,378 64,378
MS 43,135 11,475 36,011 8,945 10,271
NC 151,854 66,431 66,522 60,914 62,353
SC 88,241 43,817 46,915 48,346 51,456
TN 157,307 41,767 66,405 31,725 31,715
VA 86,886 63,220 66,219 49,420 75,594
WV 230,977 63,510 86,328 51,241 51,241 Total 1,523,449 655,718 727,388 492,913 560,208

Note: Emission summaries above are based on SCCs 1-01-xxx-xx and 2-01-xxx-xx.Documentation of the Base G 2002 Base Year, 2009 and 2018, Emission Inventories for VISTAS

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### Table 2.1-5 EGU Point Source VOC Emission Comparison for 2002/2009/2018.

2002 2009 2018

State 2002 VISTAS BaseG Base F4 IPM Based Base G IPM Based

with S/L Adjustments Base F4 IPM Based Base G IPM Based

with S/L Adjustments
AL 2,295 2,441 2,473 2,952 2,952
FL 2,524 1,867 1,910 2,324 2,376
GA 1,244 1,571 2,314 1,903 2,841
KY 1,487 1,369 1,369 1,426 1,426
MS 648 406 404 1,124 1,114
NC 988 974 954 1,272 1,345
SC 470 660 660 906 906
TN 926 932 932 977 976
VA 754 685 778 903 996
WV 1,180 1,342 1,361 1,387 1,387 Total 12,516 12,247 13,155 15,174 16,319

Note: Emission summaries above are based on SCCs 1-01-xxx-xx and 2-01-xxx-xx. 

### Table 2.1-6 EGU Point Source CO Emission Comparison for 2002/2009/2018.

2002 2009 2018

State 2002 VISTAS BaseG Base F4 IPM Based Base G IPM Based

with S/L Adjustments Base F4 IPM Based Base G IPM Based

with S/L Adjustments
AL 11,279 14,948 14,986 24,342 24,342
FL 57,113 45,391 35,928 63,673 53,772
GA 9,712 20,066 23,721 32,744 44,476
KY 12,619 15,812 15,812 17,144 17,144
MS 5,303 5,078 5,051 15,364 15,282
NC 13,885 15,141 14,942 19,612 20,223
SC 6,990 11,135 11,135 14,786 14,786
TN 7,084 7,221 7,213 7,733 7,723
VA 6,892 11,869 12,509 14,755 15,420
WV 10,341 11,328 11,493 11,961 11,961 Total 141,218 157,989 152,790 222,114 225,129

Note: Emission summaries above are based on SCCs 1-01-xxx-xx and 2-01-xxx-xx.Documentation of the Base G 2002 Base Year, 2009 and 2018, Emission Inventories for VISTAS

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### Table 2.1-7 EGU Point Source PM 10 

### -PRI Emission Comparison for 2002/2009/2018.

2002 2009 2018

State 2002 VISTAS BaseG Base F4 IPM Based Base G IPM Based

with S/L Adjustments Base F4 IPM Based Base G IPM Based

with S/L Adjustments
AL 7,646 6,959 6,969 7,822 7,822
FL 21,387 9,384 9,007 10,310 9,953
GA 11,224 17,088 17,891 18,329 20,909
KY 4,701 6,463 6,463 6,694 6,694
MS 1,633 5,487 4,957 7,624 7,187
NC 22,754 22,888 22,152 33,742 37,376
SC 21,400 28,650 19,395 37,864 28,826
TN 14,640 15,608 15,608 15,941 15,941
VA 3,960 4,479 5,508 12,744 13,775
WV 4,573 5,471 5,657 6,349 6,349 Total 113,918 122,477 113,607 157,419 154,832

Note: Emission summaries above are based on SCCs 1-01-xxx-xx and 2-01-xxx-xx.



### Table 2.1-8 EGU Point Source PM 2.5 

### -PRI Emission Comparison for 2002/2009/2018.

2002 2009 2018

State 2002 VISTAS BaseG Base F4 IPM Based Base G IPM Based

with S/L Adjustments Base F4 IPM Based Base G IPM Based

with S/L Adjustments
AL 4,113 3,916 3,921 4,768 4,768
FL 15,643 6,250 5,910 7,171 6,843
GA 4,939 10,104 10,907 11,403 13,983
KY 2,802 4,279 4,279 4,434 4,434
MS 1,138 5,310 4,777 7,469 7,033
NC 16,498 16,514 15,949 26,966 29,792
SC 17,154 23,366 16,042 32,180 25,032
TN 12,166 13,092 13,092 13,387 13,387
VA 2,606 3,194 4,067 11,101 11,976
WV 2,210 2,850 2,940 3,648 3,648 Total 79,269 88,875 81,884 122,527 120,896

Note: Emission summaries above are based on SCCs 1-01-xxx-xx and 2-01-xxx-xx.Documentation of the Base G 2002 Base Year, 2009 and 2018, Emission Inventories for VISTAS

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### Table 2.1-9 EGU Point Source NH 3 

### Emission Comparison for 2002/2009/2018.

2002 2009 2018

State 2002 VISTAS BaseG Base F4 IPM Based Base G IPM Based

with S/L Adjustments Base F4 IPM Based Base G IPM Based

with S/L Adjustments
AL 317 359 359 1,072 1,072
FL 234 1,659 1,631 3,004 2,976
GA 83 686 686 1,677 1,677
KY 326 400 400 476 476
MS 190 333 333 827 827
NC 54 423 445 691 663
SC 142 343 343 617 617
TN 204 227 227 241 241
VA 127 632 694 558 622
WV 121 330 330 180 180
Total 1,798 5,392 5,448 9,343 9,351

Note: Emission summaries above are based on SCCs 1-01-xxx-xx and 2-01-xxx-xx.Documentation of the Base G 2002 Base Year, 2009 and 2018, Emission Inventories for VISTAS

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### 2.1.2 Non-EGU Emission Projections The general approach for assembling future year data was to use growth and control data consistent with the data used in EPA’s Clean Air Interstate Rule analyses, supplement these data with available stakeholder input, and provide the results for stakeholder review to ensure credibility. We used the revised 2002 VISTAS base year inventory, based on the 2002 CERR submittals as the starting point for the non-EGU pr ojection inventories. As described in Section 2.1.1.4, we split the point source inventory into EGU and non-EGU components. MACTEC performed the following activities to apply growth and control factors to the 2002 inventory to generate the 2009 and 2018 projection inventories:

• 

### Obtained, reviewed, and applied the most current growth factors developed by EPA, based on forecasts from an updated Regional Economic Models, Inc. (REMI) model (version 5.5) and the latest Annual Energy Outlook published by the Department of Energy (DOE);

• 

### Obtained, reviewed, and applied any State-sp ecific or sector-specific growth factors submitted by stakeholders;

• 

### Obtained and incorporated information regarding sources that have shut down after 2002 and set the emissions to zero in the projection inventories;

• 

### Obtained, reviewed, and applied control assumptions for programs “on-the-books” and “on-the-way”;

• 

### Provided data files in NIF3.0 format and emission summaries in EXCEL format for review and comment; and

• 

### Updated the database with corrections or new information from S/L agencies based on their review of the Base F 2009/2018 inventories. The following sections discuss each of these steps. 2.1.2.1 Growth assumptions for non-EGU sources This section describes the growth factor data used in developing the Base F inventory for 2009 and 2018, as well as the changes to the growth factor data made for the Base G inventory.
The growth factor data used in developing the Base F inventory were consistent with EPA’s analyses for the CAIR rulemaking. These growth factors are fully documented in the reports entitled Development of Growth Factors for Future Year Modeling Inventories (dated April 30, 2004) and CAIR Emission Inventory Overview (dated July 23, 2004). Three sources of data were used in developing the growth factors for the Base F inventory:

• 

### State-specific growth rates from the Regional Economic Model, Inc. (REMI) Policy Insight ® 

### model, version 5.5 (being used in the development of the EGAS Version 5.0). The REMI socioeconomic data (output by i ndustry sector, population, farm sector valueDocumentation of the Base G 2002 Base Year, 2009 and 2018, Emission Inventories for VISTAS

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### added, and gasoline and oil expenditures) are available by 4-digit SIC code at the State level.

• 

### Energy consumption data from the DOE’s Energy Information Administration’s (EIA) Annual Energy Outlook 2004, with Projections through 2025 for use in generating growth factors for non-EGU fuel combustion sources. These data include regional or national fuel-use forecast data that were mapped to specific SCCs for the non-EGU fuel use sectors (e.g., commercial coal, industrial natural gas). Growth factors for the residential natural gas combustion category, for example, are based on residential natural gas consumption forecasts that are reported at the Census division level. These Census divisions represent a group of States (e.g., the South Atlantic division includes eight southeastern States and the District of Co lumbia). Although one would expect different growth rates in each of these States due to unique demographic and socioeconomic trends, EIA’s projects all States within each division using the same growth rate.

• 

### Specific changes for sectors (e.g., plastics, synthetic rubber, carbon black, cement manufacturing, primary metals, fabricated metals, motor vehicles and equipment) where the REMI-based rates were unrealistic or highly uncertain. Growth projections for these sectors were based on industry group forecasts, Bureau of Labor Statistics (BLS) projections and Bureau of Economic Analys is (BEA) historical growth from 1987-2002.
In addition to the growth data described above, we received two sets of growth projections from VISTAS stakeholders.
The American Forest and Paper Association (AF&PA) supplied growth projections for the pulp and paper sector, which were applied to SIC 26xx Paper and Allied Products. The AF&PA projection factors are for the U.S. industry and apply to all States equally. The numbers come from the 15-year forecast for world pulp and recovered paper prepared by Resource Information Systems Inc. (RISI).

AF&PA Growth Factor SIC Code Sector 2002 to 2009 2002 to 2018

2611 Pulp Mills 1.067 1.169 2621 Paper Mills 1.067 1.169 2631 Paperboard Mills 1.067 1.169



### For both the Base F and Base G inventories, we used the above AF&PA growth factors by SIC instead of the factors obtained from EPA’s CAIR analysis.Documentation of the Base G 2002 Base Year, 2009 and 2018, Emission Inventories for VISTAS

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### For the Base F inventory, the NCDENR supplied recent projections for three key sectors in North Carolina where declining production was anticipated – SIC 22xx Textile Mill Products, 23xx Apparel and Other Fabrics, and 25xx Furniture and Fixtures. For the Base G inventory, NCDENR decided to use a growth factor of 1.0 for these SIC codes for both 2009 and 2018. Although NCDENR has data that shows a steady decline in these industries in NC, NCDENR wanted to maintain the emission levels at 2002 levels so the future emission reduction credits were available in the event that they are needed for nonattainment areas. The specific growth factors for these industrial sectors in North Carolina were:

NCDENR Growth Factors for Specific Industrial Sectors
2009 2018 SIC Code Industrial Sector Base F Base G Base F Base G

22xx Textile Mill Products 0.6239 1.00 0.2792 1.00

23xx Apparel and Other Fabrics 0.5867 1.00 0.2247 1.00

25xx Furniture and Fixtures 0.8970 1.00 0.7647 1.00



### For the Base G inventory, we made one additional change to the growth factors. The Base F inventory relied on DOE’s AEO2004 forecasts for projecting emissions for fuel-burning SCCs (applies mainly to ICI boilers 1-02-xxx-xx and 1-03-xxx-xx, as well as in-process fuel use). We replaced the AEO2004 data with the more recent AEO2006 forecasts (released in February 2006) to reflect changes in the energy market and to improve the emissions growth factors produced. We obtained the corresponding AEO2006 projection tables from DOE’s web site located at http://www.eia.doe.gov/oiaf/aeo/supplement/supref.html 

### . We developed tables comparing the growth factors based on AEO2004 and AEO2006. These comparison tables were reviewed by the S/L agencies. Based on this review, VISTAS decided to use the AEO2006 growth factors for fuel burning SCCs.
We used the EPA’s EGAS model and updated the corresponding AEO2006 projection tables to create growth factors by SCC. We applied the updated growth factors to 2002 actual emissions and replaced the 2009 and 2018 emissions in NIF EM tables for the affected SCCs.

2.1.2.2 Source Shutdowns A few states indicated that significant source shutdowns have occurred since 2002 and that emissions from these sources should not be included in the future year inventories. These sources are identified in Table 2.1-10.Documentation of the Base G 2002 Base Year, 2009 and 2018, Emission Inventories for VISTAS

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### Table 2.1-10. Summary of Source Shutdowns Incorporated in Base G Inventory.

State Description of Source Shutdowns AL None specified. FL The following facilities are shutdown and project ed emissions were set to zero in 2009/2018. 0570075 CORONET INDUSTRIES, INC. 1050050 U S AGRI-CHEMICALS CORP. 1050051 U.S. AGRI-CHEMICALS CORPORATION These facilities emitted 2,417 tons of SO 2 and 113 tons of NO x in 2002. GA Georgia indicated that the former Blue Circle (now LaFarge) facility in downtown Atlanta will likely shut down before 2009. The facility has two cement k ilns, one of which is already shut down. The second kiln will continue to operate until the new facility in Alabama has enough milling capacity, after which the entire Atlanta fac ility will be completely closed down. This facility emitted 1,617 tons of SO 2 and 587 tons of NO x in 2002. KY None specified.
MS AF&PA indicated that the International Paper Natchez Mill (28-001-2800100010) has shut down. This facility emitted 1,398 tons of SO 2 and 1,773 tons of NO x in 2002. The Magnolia Resources - Pachuta Harmony Gas Plant (28-023-00031) is out of business and no longer holds an air permit. This facility emitted 2,257 tons of SO 2 and 134 tons of NO x in 2002. NC In Base F, two paper mills were identified as being shut down in th e 2018 inventory. NCDENR indicated that these mills are not expected to close. The two facilities are Ecusta Business Development (37-175-3717500056) and International Paper (37-083-00007). Their emissions were added back into the Base G 2018 inventory. BASF Corporation (37-021-724) in Buncombe County is currently operating but has plans to shut down in 2007. This facility emitted 461 tons of SO 2 and 266 tons of NO x in 2002. SC South Carolina provided a list of facilities that were identified as closing down on or after Jan. 1, 2003. The emissions for these facilities were set to zero in the 2009 and 2018 projection inventories. Emissions from these plants in 2002 were: 6,195 tons of SO 2 , 2,994 tons of NO x , and 2,836 tons of VOC. Most of the emissions were from one fac ility – Celanese Acetate (45-091-2440-0010) in York County. TN Davidson County (Nashville) indi cated that significant source shut downs have occurred since data were submitted for the 2002 CERR. Source num ber 47-037-00002 (Dupont) shut down a portion of their facility, which was permanently taken out of service. Source 47-037-00050 (Nashville Thermal Transfer Corp.) shut down their municipal waste co mbustors and replaced them with natural gas fired boilers with propane stand by. Weyerhaeuser (AKA Willamette) Power Boiler 7 ( 47-163-0022, EU ID = 017) is being shut down. This emission unit emitted 4,297 tons of SO 2 and 1,443 tons of NO x in 2002. Liberty Fibers (47-063-0197) in Hamblen County has recently shut down. This facility emitted 5,377 tons of SO 2 ; 2,057 tons of NO x ; and 9,059 tons of VOC in 2002. VA Rock-Tenn (51-680-00097) received a permit dated 9/13/2003 which required th e shutdown of units 1 and 2 by 2/27/2004. This permit was part of a netting exercise that allowed the installation of a new NG/DO boiler. These two units emitted 507 tons of SO 2 and 276 tons of NO x in 2002. WV None specified.Documentation of the Base G 2002 Base Year, 2009 and 2018, Emission Inventories for VISTAS

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### 2.1.2.3 Control Programs applied to non-EGU sources We used the same control programs for both the 2009 and 2018 non-EGU point inventory. Two control scenarios were developed: on-the-books (OTB) controls and on-the-way (OTW) controls. The OTB control scenario accounts for post-2002 emission reductions from promulgated federal, State, local, and site-specific control programs. The OTW control scenario accounts for proposed (but not final) control programs that are reas onably anticipated to result in post-2002 emission reductions. The methodologies used to account for the emission reductions associated with these emission control programs are discussed in the following sections.
Table 2.1-11. Non-EGU Point Source Control Programs Included in 2009/2018 Projection Inventories.

On-the-Books (Cut-off of July 1, 2004 for Base 1 adoption)

• Atlanta / Northern Kentucky / Birmingham 1-hr SIPs

• Industrial Boiler/Process Heater/RICE MACT

• NO x 

### RACT in 1-hr NAA SIPs

• NO x 

### SIP Call (Phase I- except where States have adopted II already e.g. NC)

• Petroleum Refinery Initiative (October 1, 2003 notice; MS & WV)

• RFP 3 percent Plans where in place for one hour plans

• VOC 2-, 4-, 7-, and 10-year maximum achievable control technology (MACT0 Standards

• Combustion Turbine MACT On-the-Way

• NO x 

### SIP Call (Phase II – remaining States & IC engines)

2.1.2.3.1 OTB - NO x 

### SIP Call (Phase I)



### Phase I of the NO x 

### SIP call applies to certain large non-EGUs, including large industrial boilers and turbines, and cement kilns. States in the VISTAS region affected by the NO x 

### SIP call have developed rules for the control of NO x 

### emissions that have been approved by EPA. We reviewed the available State rules and guidance documents to determine the affected sources and ozone season allowances. We also obtained and reviewed information in the EPA’s CAMD NO x 

### Allowance Tracking System – Allowances Held Report. Since these controls are to be in effect by the year 2007, we capped the emissions for NO x 

### SIP call affected sources at 2007 levels andDocumentation of the Base G 2002 Base Year, 2009 and 2018, Emission Inventories for VISTAS

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### carried forward the capped levels for the 2009/2018 future year inventories. Since the NO x 

### SIP call allowances are given in terms of tons per ozone season (5 month period from May to September), we calculated annual emissions by multiplying the 5-month allowances by a factor of 12 divided by 5.

2.1.2.3.2 OTB - Industrial Boiler/Process Heater MACT 

### EPA anticipates reductions in PM and SO 2 

### as a result of the Industrial Boiler/Process Heater MACT standard. The methods used to account for these reductions are the same as those used for the CAIR analysis. Reductions were included for existing units firing solid fuel (coal, wood, waste, biomass) which had a design capacity greater than 10 mmBtu/hr. EPA prepared a list of SCCs for solid fuel industrial and commercial/ institutional boilers and process heaters. We identified boilers greater than 10 mmBtu/hr using either the boiler capacity from the VISTAS 2002 inventory, or if the boiler capacity was missing, a default capacity based on a methodology developed by EPA for assigning default capacities based on SCC. The applied MACT control efficiencies were 4 percent for SO 2 

### and 40 for percent for PM 10 

### and PM2.5 to account for the cobenefit from installation of acid gas scrubbers and other control equipment to reduce HAPs.
2.1.2.3.3 OTB - 2, 4, 7, and 10-year MACT Standards


### Maximum achievable control technology (MACT) requirements were also applied, as documented in the report entitled Control Packet Development and Data Sources, dated July 14, 2004. The point source MACTs and associated emission reductions were designed from Federal Register (FR) notices and discussions with EP A’s Emission Standards Division (ESD) staff. We did not apply reductions for MACT standards with an initial compliance date of 2001 or earlier, assuming that the effects of these controls are already accounted for in the 2002 inventories supplied by the States. Emission reductions were applied only for MACT standards with an initial compliance date of 2002 or greater.

2.1.2.3.4 OTB Combustion Turbine MACT 

### The projection inventories do not include the NO x 

### co-benefit effects of the MACT regulations for Gas Turbines or stationary Reciprocating In ternal Combustion Engines, which EPA estimates to be small compared to the overall inventory.
2.1.2.3.5 OTB - Petroleum Refinery Initiative (MS and WV)


### Three refineries in the VISTAS region ar e affected by two October 2003 Clean Air Act settlements under the EPA Petroleum Refinery Initiative. The refineries are: (1) the Chevron refinery in Pascagoula, MS; (2) the Ergon refinery in Vicksburg, MS; and (3) the Ergon refinery in Newell, WV.Documentation of the Base G 2002 Base Year, 2009 and 2018, Emission Inventories for VISTAS

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### The first consent decree pertained to Chevron refineries in Richmond and El Segundo, CA; Pascagoula, MS; Salt Lake City, UT; and Kapolei, HI. Actions required under the Consent Decree will reduce annual emissions of NO x 

### by 3,300 tons and SO 2 

### by 6,300 tons. The consent decree requires a program to reduce NO x 

### emissions from refinery heaters and boilers through the installation of NO x 

### controls that meet at least an SNCR level of control. The refineries are to eliminate fuel oil burning in any combustion unit. The consent decree also requires reductions of NO x 

### and SO 2 

### from the fluid catalytic cracking unit and control of acid gas flaring incidents. The consent decree does not provide sufficient information to calculate emission reductions for the FCCU or flaring at the Pascagoula refinery. Ther efore, we calculated a general percent reduction for NO x 

### and SO 2 

### by dividing the expected emission reducti ons at the five Chevron refineries by the total emissions from these five refineries (as reported in the 1999 NEI). This resulted in applying percent reductions of 45 percent for SO 2 

### and 28 percent for NO x 

### to FCCU and flaring emissions at the Chevron Pascagoula refinery.
The second consent decree pertained to the Ergon-West Virginia refinery in Newell, WV; and the Ergon Refining facility in Vicksburg, MS. Th e consent decree requires the two facilities to implement a 6-year program to reduce NO x 

### emission from all heaters and boilers greater than 40 mmBtu/hr, and to eliminate fuel oil burning in any combustion unit (except during periods of natural gas curtailment). Specifically, ultra low NO x 

### burners are required on Boilers A and B at Newell, a low NO x 

### -equivalent level of control for heat er H-101 at Newell and heaters H-1 and H-3 at Vicksburg, and an ultra low NO x 

### burner level of control for heater H-451 at Vicksburg.

2.1.2.3.6 OTW - NO x 

### SIP Call (Phase II)



### The final Phase II NO x 

### SIP call rule was finalized on April 21, 2004. States had until April 21, 2005, to submit SIPs meeting the Phase II NO x 

### budget requirements. The Phase II rule applies to large IC engines, which are primarily used in pipeline transmission service at compressor stations. We identified affected units using the same methodology as was used by EPA in the proposed Phase II rule (i.e., a large IC engine is one that emitted, on average, more than 1 ton per day during 2002). The final rule reflects a control level of 82 percent for natural gas-fired IC engines and 90 percent for diesel or dual fuel cat egories. As shown later in Table 2.1-12, several S/L agencies provided move specific information on the anticipated controls at the compressor stations. This information was used in the Base G inventory instead of the default approach used by EPA in the proposed Phase II rule.

2.1.2.3.7 Clean Air Interstate Rule 

### CAIR does not require or assume additional emission reductions from non-EGU boilers and turbines.Documentation of the Base G 2002 Base Year, 2009 and 2018, Emission Inventories for VISTAS

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### 2.1.2.4 Quality Assurance steps Final QA checks were run on the revised projection inventory data set to ensure that all corrections provided by the S/L agencies and stakeholders were correctly incorporated into the S/L inventories and that there were no remaini ng QA issues that could be addressed during the duration of the project. After exporting the invent ory to ASCII text files in NIF 3.0, the EPA QA program was run on the ASCII files and the QA output was reviewed to verify that all QA issues that could be addressed were resolved
Throughout the inventory development process, quality assurance steps were performed to ensure that no double counting of emissions occurred, and to ensure that a full and complete inventory was developed for VISTAS. Quality assurance was an important component to the inventory development process and MACTEC performed the following QA steps on the point source component of the VISTAS revised 2002 base year inventory:
1. Facility level emission summaries were prepared and evaluated to ensure that emissions were consistent and reasonable. The summaries included base year 2002 emissions, 2009/2018 projected emissions accounting only for growth, 2009/2018 projected emissions accounting for both gr owth and emission reductions from OTB and OTW controls. 2. State-level non-EGU comparisons (by pollutant) were developed for the base year 2002 emissions, 2009/2018 projected emissions accounting only for growth, 2009/2018 projected emissions accounting for both growth and emission reductions from OTB and OTW controls. 3. Data product summaries and raw NIF 3.0 data files were provided to the VISTAS Emission Inventory Technical Advisor and to the Point Source, EGU, and non-EGU Special Interest Work Group representatives for review and comment. Changes based on these comments were reviewed and approved by the S/L point source contact prior to implementing the changes in the files. 4. Version numbering was used for all inventory files developed. The version numbering process used a decimal system to track major and minor changes. For example, a major change would result in a version going from Base F1 to Base F2. 2.1.2.5 Additional Base G Updates and Corrections Table 2.1-12 summarizes the updates and corrections to the Base F inventory that were requested by S/L agencies and incorporated into the Base G 2009/2018 inventories.
2.1.2.6 Summary of Revised 2009/2018 non-EGU Point Source Inventories Tables 2.1-13 through 2.1-19 summarize th e revised 2009/2018 non-EGU point source inventories. The “growth only” column does not include the shutdowns (section 2.1.2.2) or control factors (section 2.1.2.3), only the growth factors described in section 2.1.2.1.Documentation of the Base G 2002 Base Year, 2009 and 2018, Emission Inventories for VISTAS

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### Table 2.1-12. Summary of Updates and Corrections to the Base F 2009/2018 Inventories Incorporated into the Base G 2009/2018 Inventories.

State Nature of Update/Correction AL Corrected the latitude and longitude for two facilities: Ergon Terminalling (Site ID: 01-073- 010730167) and Southern Power Franklin (Site ID: 01-081-0036). AL Corrections to stack parameters at 10 facilities for stacks with parameters that do not appear to fall into the ranges typically termed "acceptable" for AQ modeling.
FL Corrected 2009/2018 emission values for the Miami Dade RRF facility (Site ID: 12-086-0250348) based on revised 2002 emissions and applicati on of growth control factors for 2009/2018. GA Hercules Incorporated (12-051-05100005) had an erroneous process id (#3) within emission unit id SB9 and was deleted. This removes about 6,000 tons of SO 2 from the 2009/2018 inventories.
Provided a revised file of locati on coordinates at the stack level th at was used to replace the location coordinated in the ER file. There are several sources that have updated their emissions from their BART eligible units. most of these changes were for fairly small (<50 tpy) sources. NC Made several changes to Base F inventory to correct the following errors: 1. Corrected emissions at Hooker Furniture (Site ID: 37-081-3708100910), release point G-29, to use the corrected values in 2002 and carry those same numbers through to 2009 and 2018 since NCDENR assumes zero growth for furniture industry. 2. Identified many stack parameters in the ER file that were unrealistic. Several have zero for height, diameter, gas velocity, and flow rate. NC used the procedures outlined in Section 8 of the document ""National Emission Inventory QA and Augmentation Report" to correct unrealistic stack parameters. 3. Identified truncated latitude and longitude valu es in Base F inventory. NC updated all Title V facility latitude and longitude that was submitted to EPA for those facilities in 2004. Smaller facilities with only two decimal places were not corrected. 4. Corrected 2018 VOC emissions for International Paper (3709700045) Emission Unit ID, G-12, to reflect changes to the 2002 inventory. There are three Transcontinental Natural Gas Pipeline facilities in NC that are subject to the NO x SIP call. NCDENR took 2004 emissions and grew them to 2009 & 2018 and capped those units that are subject to the NO x SIP Call Rule. These facility IDs are 37-057-3705700300, 37-097-3709700225, and 37-157-3715700131. NCDENR applied NO x RACT to a two facilities located in the Charlotte nonattainment area. NCDENR provided 2009 & 2018 emissions for Philip Morris USA (37-025-3702500048) and Norandal USA (37-159-3715900057). SC Corrected PM species emission values. SC DHEC’s initial CERR submittal reported particulate matter emissions using the PM-FIL, PM 10 -FIL, and PM 2.5 -FIL pollutant codes. In August 2005, SC DHEC indicated that data reported using the PM-FIL, PM 10 -FIL, and PM 2.5 -FIL pollutant codes should actually have been reported using the PM-PRI, PM 10 -PRI, and PM 2.5 _PRI codes. MACTEC performed a subsequent PM augmentation in Apr il 2006 using the revised pollutant codes. These changes were reflected in the Base G 2009/2018 emission inventory. Specified that the Bowater In c. facility (45-091-2440-0005) in York County conducted an expansion in 2003/2004 and plans a future expansion. SC pr ovided updated emissions for 2009 and 2018 for this facility.Documentation of the Base G 2002 Base Year, 2009 and 2018, Emission Inventories for VISTAS

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### Table 2.1-12. Continued.

State Nature of Update/Correction TN Updated 2009/2018 emissions for Eastman Chemical (47-163-0003) based on final (Feb. 2005) BART rule. Updated 2009/2018 emission inventory for the Bowater facility (47-107-0012) based on the facility’s updated 2002 emission inventory update. Replaced 2009/2018 data from Ham ilton County, Tennessee, using data from Hamilton County’s CERR submittal as contained in EPA’s 2002 NEI (in Base F, the inventory for Hamilton County was based on the draft VISTAS 2002 inventory, which in turn was based on the 1999 NEI); applied growth and control factors to revised 2002 inventor y to generate emission projections for 2009/2018. Updated 2009/2018 emissions for PCS Nitrogen Fertilizer LP (Site ID: 47-157-00146) based on the facility’s updated 2002 emi ssion inventory update. The 2002 NEI correctly reports the actual emissions for CEMEX (47-093-0008) after the NO x SIP call. There is no reason to suspect that that rate would change in 2008, 2009, or 2018. Emissions for 2009/2018 were set equal to 2002 emissions. In the Base F 2009/2018 inventories, NO x controls were applied for two units at Columbia Gulf Transmission (47-111-0004). There are no plans for controls at these units, EO3 and EO4. The assumed control efficiency of 82 percent was backed out in the 2009/2018 inventories. VA VADEQ provided 2009/2018 NO x emission estimates for NO x Phase II gas transmission sources at three Transco facilities (51-011- 00011, 51-137-00027, 51-143-00120) which were used to replace the default NO x Phase II control assumptions for these facilities. VADEQ provided updated 2009/2018 NO x and SO 2 emissions based on new controls required by a November 2005 permit modification a nd netting exercise. The entire power plant facility is limited to 213 tons of NO x and 107 tons of SO 2 per year. The permit also allowed the installation of 3 new boilers, also under the 213 tons of NO x /year cap. WV Updated 2009/2018 emissions for Steel of West Virginia (Site ID: 54-011-0009) based on the facility’s updated 2002 emi ssion inventory update. Made changes to several Site ID names due to changes in ownership Base F emissions were much too high for Weirton Steel (54-021-0029). WV believes that the source is very unlikely to emit the NO x SIP Call budgeted amounts in 2009 or 2018. WV provided revised emission estimates based on EGAS for 2009/2018. Made corrections to latitude/longitude and stack parameters at a few facilities for stacks with parameters that do not appear to fall into the ra nges typically termed "accep table" for AQ modeling.Documentation of the Base G 2002 Base Year, 2009 and 2018, Emission Inventories for VISTAS

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### Table 2.1-13 Non-EGU Point Source SO 2 

### Emission Comparison for 2002/2009/2018.

2002 2009 2018
State Base G Base F4 Base G Base F4 Base G
AL 96,481 100,744 101,246 112,703 113,224
FL 65,090 68,549 65,511 79,015 75,047
GA 53,778 61,535 53,987 68,409 59,349
KY 34,029 35,470 36,418 38,806 40,682
MS 35,960 27,488 25,564 40,195 39,221
NC 44,123 48,751 42,536 50,415 46,314
SC 53,518 55,975 48,324 56,968 53,577
TN 79,604 89,149 70,678 96,606 77,247
VA 63,903 63,075 62,560 69,776 68,909
WV 54,070 54,698 55,973 60,137 62,193 Total 580,556 605,434 562,797 673,030 635,763

Note: Emission summaries above include all SCCs except 1-01-xxx-xx and 2-01-xxx-xx.



### Table 2.1-14 Non-EGU Point Source NO x 

### Emission Comparison for 2002/2009/2018.

2002 2009 2018
State BaseG Base F4 Base G Base F4 BaseG
AL 83,310 69,676 69,409 79,101 78,318
FL 45,156 44,859 46,020 50,635 51,902
GA 49,251 51,556 50,353 57,323 55,824
KY 38,392 36,526 37,758 40,363 41,034
MS 61,526 55,877 56,397 62,132 61,533
NC 44,928 44,877 34,767 47,200 37,801
SC 42,153 42,501 40,019 44,480 44,021
TN 64,344 63,431 57,883 70,313 63,453
VA 60,415 51,335 51,046 56,876 55,945
WV 46,612 40,433 38,031 44,902 43,359 Total 536,087 501,071 481,683 553,325 533,190

Note: Emission summaries above include all SCCs except 1-01-xxx-xx and 2-01-xxx-xx.Documentation of the Base G 2002 Base Year, 2009 and 2018, Emission Inventories for VISTAS

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### Table 2.1-15 Non-EGU Point Source VOC Emission Comparison for 2002/2009/2018.

2002 2009 2018
State Base G Base F4 Base G Base F4 Base G
AL 47,037 46,660 46,644 54,268 54,291
FL 38,471 36,675 36,880 42,787 42,811
GA 33,709 34,082 34,116 40,267 40,282
KY 44,834 47,648 47,785 55,564 55,861
MS 43,204 37,921 37,747 45,769 45,338
NC 61,182 70,464 61,925 76,027 70,875
SC 38,458 38,273 35,665 44,545 43,656
TN 84,328 89,380 74,089 111,608 93,266
VA 43,152 43,620 43,726 53,065 53,186
WV 14,595 14,012 13,810 16,632 16,565 Total 448,970 458,735 432,387 540,532 516,131

Note: Emission summaries above include all SCCs except 1-01-xxx-xx and 2-01-xxx-xx. 

### Table 2.1-16 Non-EGU Point Source CO Emission Comparison for 2002/2009/2018.

2002 2009 2018
State Base G Base F4 Base G Base F4 Base G
AL 174,271 176,899 180,369 194,280 201,794
FL 81,933 83,937 87,037 96,642 96,819
GA 130,850 147,362 147,427 168,570 167,904
KY 109,936 121,727 122,024 139,121 139,437
MS 54,568 58,023 57,748 67,764 66,858
NC 50,576 53,955 53,744 61,127 62,197
SC 56,315 62,144 60,473 71,318 68,988
TN 115,264 123,844 119,665 146,407 140,942
VA 63,796 67,046 68,346 74,364 76,998
WV 89,879 100,248 100,045 119,318 119,332 Total 927,388 995,185 996,878 1,138,911 1,141,269

Note: Emission summaries above include all SCCs except 1-01-xxx-xx and 2-01-xxx-xx.Documentation of the Base G 2002 Base Year, 2009 and 2018, Emission Inventories for VISTAS

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### Table 2.1-17 Non-EGU Point Source PM 10 

### -PRI Emission Comparison for 2002/2009/2018.

2002 2009 2018
State Base G Base F4 Base G Base F4 Base G
AL 25,240 25,450 25,421 29,973 29,924
FL 35,857 39,363 39,872 46,573 46,456
GA 21,610 23,509 23,103 27,781 27,273
KY 16,626 17,164 17,174 20,142 20,153
MS 19,472 19,200 19,245 22,952 22,859
NC 13,838 14,738 13,910 15,816 15,737
SC 14,142 17,631 13,370 20,197 15,139
TN 35,174 37,040 34,833 45,168 42,280
VA 13,252 13,043 13,048 15,150 15,112
WV 17,503 17,723 17,090 21,699 21,735 Total 212,714 224,861 217,066 265,451 256,668

Note: Emission summaries above include all SCCs except 1-01-xxx-xx and 2-01-xxx-xx.



### Table 2.1-18 Non-EGU Point Source PM25-PRI Emission Comparison for 2002/2009/2018.

2002 2009 2018
State Base G Base F4 Base G Base F4 Base G
AL 19,178 19,256 19,230 22,628 22,598
FL 30,504 33,387 33,946 39,436 39,430
GA 17,462 19,361 18,982 22,882 22,416
KY 11,372 11,680 11,686 13,734 13,739
MS 9,906 9,144 9,199 10,768 10,739
NC 10,500 11,192 10,458 11,927 11,825
SC 10,245 13,101 9,390 14,947 11,086
TN 27,807 29,302 27,577 35,750 33,532
VA 10,165 9,980 9,988 11,604 11,594
WV 13,313 13,364 12,769 16,474 16,516 Total 160,452 169,767 163,225 200,150 193,475

Note: Emission summaries above include all SCCs except 1-01-xxx-xx and 2-01-xxx-xx.Documentation of the Base G 2002 Base Year, 2009 and 2018, Emission Inventories for VISTAS

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### Table 2.1-19 Non-EGU Point Source NH 3 

### Emission Comparison for 2002/2009/2018.

2002 2009 2018
State Base G Base F4 Base G Base F4 Base G
AL 1,883 2,132 2,132 2,464 2,464
FL 1,423 1,544 1,544 1,829 1,829
GA 3,613 3,963 3,963 4,799 4,797
KY 674 733 760 839 901
MS 1,169 667 668 761 764
NC 1,180 1,288 1,285 1,422 1,466
SC 1,411 1,578 1,578 1,779 1,779
TN 1,613 1,861 1,841 2,240 2,214
VA 3,104 3,050 3,049 3,613 3,604
WV 332 341 341 416 413 Total 16,402 17,157 17,161 20,162 20,231

Note: Emission summaries above include all SCCs except 1-01-xxx-xx and 2-01-xxx-xx.



### 2.2 Area Sources
This section describes the methodology used to develop the 2009 and 2018 projection Base F and Base G projection inventories. This section describes two approaches to these projections. Separate methods for projecting emissions were used for non-agricultural (stationary area) and agricultural area sources (predominantly NH 3 

### emissions). The two methods used for these sectors are described in the sections that follow.
2.2.1 Stationary area sources The general approach used to calculate Base F projected emissions for stationary area sources was as follows:
1. Use the VISTAS Base F 2002 base year invent ory as the starting point for projections.

2. MACTEC then worked with the VISTAS St ates (via the Stationary Area Source SIWG) to obtain any State specific growth factors and/or future controls from the States to use in developing the projections.
3. MACTEC then back calculated uncontrolled emissions from the Base F 2002 base year inventory based on existing controls reported in the 2002 Base F base year inventory.
4. Controls (including control efficiency, rule effectiveness and rule penetration) provided by the States or originally developed for use in estimating projected emissions for U.S. EPA’s Heavy Duty Diesel (HDD) rulemaking em ission projections and used in the CleanDocumentation of the Base G 2002 Base Year, 2009 and 2018, Emission Inventories for VISTAS

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### Air Interstate Rule (CAIR) projections were then used to calculate controlled emissions. State submitted controls had precedence over the U.S. EPA developed controls.
5. Growth factors supplied from the States or the U.S. EPA’s CAIR emission projections were then applied to project the controlled emissions to the appropriate year. In some cases EGAS Version 5 growth factors were used if no growth factor was available from either the States or the CAIR growth factor files. The use of EGAS Version 5 growth factors was on a case-by-case basis wherever State-supplied or CAIR factors were not available for SCCs found in the 2002 Base F inventory. Use of the EGAS factors was necessitated due to the CERR submittals used in constructing the Base F 2002 inventory. Use of the CERR data resulted in SCCs that were not found in the CAIR inventory and if no State-supplied growth factor was provided re quired the use of an EGAS growth factor.
6. MACTEC then provided the final draft Ba se F projection inventory for review and comment by the VISTAS States.
For Base F stationary area sources, no State-supplied growth or control factors were provided. Thus for all of the sources in this sector of the inventory, growth and controls for Base F were applied based on controls initially identified for the CAIR and growth factors identified for the CAIR projections.
For the Base G projections, the Base G 2002 base year inventory (see section 1.2.3) was used as a starting point. States provided some updated future controls but growth factors used were identical to those used for Base F. The revised controls for Base G were largely for new sources added as part of the 2002 Base F comments. The calculation of Base G projections was identical to the six steps outlined above with the exception of revisions made to prescribed fire for 2009 and 2018 and for the State of North Carolina. North Carolina provided 2009 and 2018 updated emission files used to update the emissions for each year for several source categories. However not all sources in the inventory were included in these NC updates. As a consequence, the final Base G 2009 and 2018 inventory for NC included em issions updated using the NC supplied files and emissions developed using growth and control factors as outlined above.
In a few cases, additional growth factors had to be added for source categories that had not initially been included in the Base F inventory. These growth factors were obtained from EGAS 5.0. Finally updates to growth factors from EGAS 5.0 were made for fuel fired emission sources. The updated growth factors reflected the most recent data from the Department of Energy’s Annual Energy Outlook (AEO). These data were used to reflect changes in energy efficiency resulting from new or updated fuel firing technologies.Documentation of the Base G 2002 Base Year, 2009 and 2018, Emission Inventories for VISTAS

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### 2.2.1.1 Stationary area source controls The controls obtained by MACTEC for the HDD rulemaking were controls for the years 2007, 2020, and 2030. Since MACTEC was preparing 2009 and 2018 projections, control values for intermediate years were prepared using a strai ght line interpolation of control level between 2007 and 2020. The equation used to calculate the control level was as follows:
CE = (((2020 CE – 2007 CE)/13)*YRS) + 2007 CE

Where:
CE = Control Efficiency for either 2009 or 2018
2020 CE = HDD Control Efficiency value for 2020
2007 CE = HDD Control Efficiency value for 2007
13 = Number of years between 2020 and 2007
YRS = Number of years beyond 2007 to VISTAS Projection year

For 2009 the value of YRS would be two (2) and for 2018 the value would be eleven (11). Control efficiency values were determined for VOC, CO and PM. Rule penetration values for each year in the HDD controls tables obtained by MACTEC were always 100 percent so those values were maintained for the VISTAS projections.
Prior to performing the linear interpolation of the controls, MACTEC evaluated controls from the CAIR projections (NOTE: Initially the controls came from the IAQTR projections, however the controls used in CAIR were virtually identical to those in IAQTR). Those controls appeared to be identical to those used for the HDD rulemaking. In addition, MACTEC received some additional information on some controls for area source solvents (email from Jim Wilson, E.H. Pechan and Associates, Inc. to Gregory Stella , VISTAS Emission Inventory Technical Advisor, 3/5/04) that were used to check against the controls in the HDD rulemaking files. Where those controls proved to be more stringent than the HDD values, MACTEC updated the control file with those values (which were then used in the interpolation to develop 2009 and 2018 values). Finally, for VOC the HDD controls were initially provided at the State-county-SCC level. However, upon direction from the VISTAS Emi ssion Inventory Technical advisor, the VOC controls were consolidated at the SCC level and applied across all counties within the VISTAS region (email from Gregory Stella, Alpine Geophysics, 3/3/2004) to ensure that no controls were missed due to changes in county FIPS codes and/or SCC designations between the time the HDD controls were developed and 2002.Documentation of the Base G 2002 Base Year, 2009 and 2018, Emission Inventories for VISTAS

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### The equation below indicates how VOC emissions were projected for stationary area sources.

⎟ ⎟ ⎠ ⎞ ⎜ ⎜ ⎝ ⎛ ⎟ ⎠ ⎞ ⎜ ⎝ ⎛ ⎟ ⎠ ⎞ ⎜ ⎝ ⎛ ⎟ ⎠ ⎞ ⎜ ⎝ ⎛

− = 100 _ 100 _ 100 _ 1 2018 2018 2018 2002 2018 

### RPVOC REVOC CEVOC xVOC VOC



### Where:

VOC 2018 

### = VOC emissions for 2018

VOC 2002 

### = Uncontrolled VOC emissions for 2002
VOC_CE 2018 

### = Control Efficiency for VOC (in this example for 2018)
VOC_RE 2018 

### = Rule Effectiveness for VOC (in this example for 2018)
VOC_RP 2018 

### = Rule Penetration for VOC (in this example for 2018)
A similar equation could be constructed for either PM or CO. It should be noted that the control efficiencies calculated based on the HDD rulemaking were only applied if they were greater than any existing 2002 base year controls. No controls were found for SO 2 

### or NO x 

### area sources. In the pre-Base F 2018 emission estimates, an en ergy efficiency factor was applied to energy related stationary area sources. The energy effici ency factor was applied along with the growth factor to account for both growth and changes in energy efficiency. That factor was not applied to the Base F projections since information supplied by U.S. EPA related to the CAIR growth factors indicated that growth values for those cat egories were derived from U.S. Department of Energy (DOE) and were felt to account for changes in growth and projected energy efficiency. For the Base G inventory, these energy efficiency factors were re-instituted and used in conjunction with EGAS 5.0 growth factors in a manner identical to that used for the pre-Base F inventories. The energy efficiency factors were derived from U.S. DOE’s Annual Energy Outlook report.
One significant difference between the Base F and Base G control factors was for counties and independent cities in northern Virginia. Several counties and independent cities in northern Virginia are subject to Ozone Transport Commission rules. For these counties and independent cities, controls for portable fuel containers, mobile equipment repair/refinishing, consumer products, solvent metal cleaning, and the architectural and industrial maintenance rules were added. The counties/independent cities (FIPS code) included in the changes for Base G were: Alexandria City (51510), Arlington (51013) , Fairfax City (51600), Fairfax (51059), Falls Church City (51610), Fredericksburg City (51630), Loudoun (51107), Manassas City (51683), Manassas Park City (51685), Prince William County (51153), Spotsylvania (51177), and Stafford (51179). Not all OTC rules applied to all counties/cities.Documentation of the Base G 2002 Base Year, 2009 and 2018, Emission Inventories for VISTAS

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### 2.2.1.2 Stationary area source growth As indicated above, growth factors for the Base F and Base G 2009 and 2018 inventories were obtained from the U.S. EPA and are linear interpolations of the growth factors used for the Clean Air Interstate Rule (CAIR) projections. The gr owth factors for the CAIR obtained by MACTEC were developed using a base year of 2001 and provided growth factors for 2010 and 2015. MACTEC used the TREND function in Microsoft ExcelTM to calculate 2002, 2009 and 2018 values from the 2001, 2010 and 2015 values. The TREND function provides a linear interpolation of intermediate values from a known series of data points (in this case the 2001, 2010 and 2015 values) based on the equation for a straight line. These values were calculated at the State and SCC level with the exception of paved road emissions (SCC = 2294000000). The growth factors for paved roads were available in the CAIR data set at the State, county and SCC level so they were applied at that level.
Prior to utilizing the growth factors from the CAIR projections, MACTEC confirmed that all SCCs found in the VISTAS 2002 base year inventory were in the CAIR file (for Base F the starting point was the version 3.1 2002 base year inventory, for Base G the starting point was the Base F 2002 base year inventory). Some SCCs we re not found in the CAIR file. For those SCCs, the growth factors used were derived in one of five ways. First where possible, they were taken from a beta version of EGAS 5.0. In other cases, the growth factor was set to one (i.e., no growth). In other cases, a similar SCC that had a CAIR growth factor was used. In a few cases a growth factor based on an average CAIR growth at the 6 digit SCC level was calculated. Finally a number of records used population as the growth surrogate. For the Base G inventory, CAIR growth factors for fuel fired area sources were replaced with EGAS 5.0 growth factors (used in conjunction with AEO fuel efficiency factors). A comment field in the growth factor file was used to mark those records that were not taken di rectly from the CAIR projection growth factors.

2.2.1.3 Differences between 2009/2018 Methodologically, there was no difference in the way that 2009 and 2018 emissions were calculated for stationary area sources. The indivi dual control and growth factors were different (due to the linear interpolation used to calculate the values) but the calculation methods were identical. This applies to both Base F and Base G.
The only exception to this is for the State of North Carolina for Base G. North Carolina provided an emissions update file used to override calculated projections for a number of area source categories. The values in these files (provided for both 2009 and 2018) were used to overwrite the calculated projected emissions in the final NIF file.Documentation of the Base G 2002 Base Year, 2009 and 2018, Emission Inventories for VISTAS

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### 2.2.2 Agricultural area sources The general approach used to calculate projected emissions for agricultural area sources (predominantly NH 3 

### emission sources) was as follows:
1. MACTEC used the version 3.1 2002 base year inventory data (which was based on the CMU ammonia model version 3.6).

2. MACTEC worked with the VISTAS States (via the Agricultural Sources SIWG) to obtain any State specific growth and/or future controls from the States for agricultural

sources. 3. Since the base year emissions were uncontrolled, and no future controls for these sources were identified, MACTEC projected the agricultural emissions using State-specific growth if available, otherwise the U.S. EPA’s Interstate Air Quality Transport Rule (IAQTR)/Ammonia inventory was used to devel op the growth factors used to project the revised 2002 base year inventory to 2009 or 2018. Since the IAQTR inventory was only used to construct growth factors rather than using the emissions directly, no updated growth factors were prepared from the CAIR inventory values.
4. MACTEC then provided the final draft inventory for review and comment by the VISTAS States.
No change in the agricultural area source emission projections were made between Base F and Base G other than the removal of wild animal and human perspiration as a result of their removal from the 2002 base year file for Base G.
2.2.2.1 Control assumptions for agricultural area sources No controls were identified either by the individual VISTAS States or in the information provided in the EPA’s IAQTR or CAIR Ammoni a inventory documents. Thus all projected emissions for agricultural area sources represent simple growth with no controls.
2.2.2.2 Growth assumptions for agricultural area sources Growth for several agricultural area source livestock categories was developed using the actual emission estimates developed by the EPA as part of the NEI. That work included projections for the years 2002, 2010, 2015, 2020, and 2030. The actual emissions themselves were not used other than to develop growth factors since the 2002 NEI upon which the growth projections were based was prepared prior to the release of the 2002 Census of Agriculture data which was included in the CMU model (version 3.6) used to develop the Base F 2002 VISTAS base year inventory. Thus VISTAS Agricultural Sources SI WG decided to use the NEI ammonia inventoryDocumentation of the Base G 2002 Base Year, 2009 and 2018, Emission Inventories for VISTAS

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### projected emissions to develop the 2009 and re vised 2018 growth factors used to project emission for VISTAS. Details on the NEI inventory and projections can be found at:
http://www.epa.gov/ttn/chief/ap42/ch09/related/nh3inventorydraft_jan2004.pdf . The actual data files for the projected emissions can be found at:
http://www.epa.gov/ttn/chief/ap42/ch09/related/nh3output01_23_04.zip

. In order to use the NEI projected emissions as growth factors, several steps were required. These steps were as follows:
1. NEI projected emissions were only available for the years 2002, 2010, 2015, 2020, and 2030, thus the first task was to calculate intermediate year emissions for 2009 and 2018. These values were calculated based on linear interpolation of the existing data.
2. Once the intermediate emissions were calculated, MACTEC developed emission ratios to provide growth factors for 2009 and 2018. Ratios of emissions were established relative to the 2002 NEI emissions.
3. Once the growth factors were established, MACTEC then evaluated whether or not all agricultural SCCs within the revised 2002 base year inventory had corresponding growth factors. MACTEC established that not all SCCs within the base year inventory had growth factors. These SCCs fell into one of two categories:
a. SCCs that had multiple entries in the NEI but only a single SCC in the 2002 VISTAS base year inventory. The NEI was established using a process model and for some categories of animals, emissions were calculated for several aspects of the process. The CMU model version 3.6 which was the basis for the VISTAS 2002 Base F inventory did not use a process model. As a consequence a mapping of SCCs in the NEI projections and corresponding SCCs in the CMU inventory was made and for those SCCs an average growth factor was calculated from the NEI projections for use with the corresponding SCC in the CMU based 2002 Base F inventory.
b. There were also State, county, SCC trios in the 2002 VISTAS Base F inventory which had no corresponding emissions in the NEI files. For these instances, MACTEC first developed State level average growth factors from the NEI projections for use in growing these records. Even after developing State level average growth factors there were still some State/SCC pairs that did not have matching growth. For these records, MACTEC developed VISTAS regional average growth factors at the SCC level from the NEI data.Documentation of the Base G 2002 Base Year, 2009 and 2018, Emission Inventories for VISTAS

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### 4. Once all of the growth factors were developed, they were used to project the emissions to 2009 and 2018. Growth factors were first applied at the State, county and SCC level. Then remaining records were grown with the State/SCC specific growth factors. Finally, any remaining ungrown records were projected at the SCC level using the VISTAS regional growth factor.
For the livestock categories, the NEI emission projections only had data for beef and dairy cattle, poultry and swine. Thus for other livestock categories and for fertilizers alternative growth factors were required.
The growth factors for other livestock categories and fertilizers were obtained from growth factors used for the IAQTR projections made by the U.S. EPA. The methodology for these categories was identical to that used for dairy, beef, poultry and swine with the exception that State/SCC and VISTAS/SCC growth factors were not required for these categories since the IAQTR data contained State, county and SCC level growth factors. The IAQTR data provided growth factors for 1996, 2007, 2010, 2015 and 2020. Linear interpolation was used to develop the growth factors for the intermediate years 2009 and 2018 required for the VISTAS projections.
There were a few exceptions to the methods used for projecting agricultural sources for the VISTAS projections. These exceptions were:

1. All swine emissions for North Carolina were maintained at 2002 levels for each projection year to capture a moratorium on swine production in that State.
2. Ammonia growth factors for a few categories (mainly feedlots) were assigned to be the same as growth factors for PM emissions from the NEI projections. This assignment was made because the CMU model showed emissions from these categories but the NEI projections did not show ammonia em issions but did show PM emissions.
3. No growth factors were found for horse a nd pony emissions. These emissions were held constant at 2002 levels.
There was no change in this method between Base F and Base G. Thus Base F and Base G agricultural emissions are the same in each invent ory. Future efforts on the agricultural emissions category should look at any changes made to the CMU model to reflect the model farm approach used by EPA in their inventory plus any updated growth factors that may be more recent than the EPA inventory used to develop growth estimates for Base F/G.Documentation of the Base G 2002 Base Year, 2009 and 2018, Emission Inventories for VISTAS

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### 2.2.2.2.1 Differences between 2009/2018 

### Methodologically, there was no difference in the way that 2009 and 2018 emissions were calculated for agricultural area sources. The growth factors were different (due to the linear interpolation used to calculate the values) but the calculation methods were identical. In addition there was no difference between Base F and Base G for this category. Thus Base F and Base G agricultural emissions are the same in each inventory.

Tables 2.2-1 show the differences between Base F and Base G emissions for all area sources (including agricultural sources but excluding fires) for the 2002 base year and 2009 and 2018 by State and pollutant.

Table 2.2-1 2002 Base Year Emissions and Percentage Difference for Base F and Base G (based on actual emissions).

Actual Area 2002 - Base G State CO NH3 NOX PM10-PRI PM25-PRI SO2 VOC AL 83,958 58,318 23,444 393,588 56,654 52,253 182,674 FL 71,079 37,446 28,872 443,346 58,878 40,491 404,302 GA 108,083 80,913 36,142 695,414 103,794 57,559 299,679 KY 66,752 51,135 39,507 233,559 45,453 41,805 95,375 MS 37,905 58,721 4,200 343,377 50,401 771 131,808 NC 345,315 161,860 36,550 280,379 64,052 5,412 237,926 SC 113,714 28,166 19,332 260,858 40,291 12,900 161,000 TN 89,828 34,393 17,844 212,554 42,566 29,917 153,307 VA 155,873 43,905 51,418 237,577 43,989 105,890 174,116 WV 39,546 9,963 12,687 115,346 21,049 11,667 60,443 Base F AL 83,958 59,486 23,444 393,093 73,352 47,074 196,538 FL 105,849 44,902 29,477 446,821 81,341 40,537 439,019 GA 107,889 84,230 36,105 695,320 133,542 57,555 309,411 KY 66,752 51,097 39,507 233,559 52,765 41,805 100,174 MS 37,905 59,262 4,200 343,377 63,135 771 135,106 NC 373,585 164,467 48,730 303,492 69,663 7,096 346,060 SC 113,714 29,447 19,332 260,858 51,413 12,900 187,466 TN 89,235 35,571 17,829 211,903 49,131 29,897 161,069 VA 155,873 46,221 51,418 237,577 52,271 9,510 129,792 WV 39,546 10,779 12,687 115,346 25,850 11,667 61,490 Percentage Difference (negative values mea ns Base G increased from Base F) AL 0.00% 1.96% 0.00% -0.13% 22.76% -11.00% 7.05% FL 32.85% 16.61% 2.05% 0.78% 27.62% 0.12% 7.91% GA -0.18% 3.94% -0.10% -0. 01% 22.28% -0.01% 3.15% KY 0.00% -0.07% 0.00% 0.00% 13.86% 0.00% 4.79% MS 0.00% 0.91% 0.00% 0.00% 20.17% 0.00% 2.44% NC 7.57% 1.59% 24.99% 7.62% 8.05% 23.74% 31.25% SC 0.00% 4.35% 0.00% 0.00% 21.63% 0.00% 14.12% TN -0.67% 3.31% -0.09% -0. 31% 13.36% -0.07% 4.82% VA 0.00% 5.01% 0.00% 0.00% 15.84% -1013.45% -34.15% WV 0.00% 7.57% 0.00% 0.00% 18.57% 0.00% 1.70%Documentation of the Base G 2002 Base Year, 2009 and 2018, Emission Inventories for VISTAS

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### Table 2.2-2 2009 Projection Year Emissions and Percentage Difference for Base F and Base G (based on actual emissions).

Actual Area 2009 - Base G State CO NH3 NOX PM10-PRI PM25-PRI SO2 VOC AL 66,654 64,268 23,930 413,020 58,699 48,228 143,454 FL 57,011 38,616 28,187 503,230 64,589 36,699 420,172 GA 94,130 89,212 37,729 776,411 112,001 57,696 272,315 KY 57,887 53,005 42,088 242,177 46,243 43,087 94,042 MS 27,184 63,708 4,249 356,324 51,661 753 124,977 NC 301,163 170,314 39,954 292,443 69,457 5,751 187,769 SC 90,390 30,555 19,360 278,299 41,613 13,051 146,107 TN 74,189 35,253 18,499 226,098 44,124 30,577 154,377 VA 128,132 46,639 52,618 252,488 44,514 105,984 147,034 WV 31,640 10,625 13,439 115,089 20,664 12,284 55,288 Base F AL 68,882 65,441 26,482 411,614 76,248 17,818 157,405 FL 101,356 46,950 31,821 507,515 90,487 52,390 462,198 GA 103,579 92,838 38,876 776,935 146,691 57,377 294,204 KY 64,806 53,023 42,122 242,345 54,397 40,779 94,253 MS 37,161 64,289 4,789 356,516 65,321 637 125,382 NC 332,443 173,187 53,550 317,847 75,570 7,607 252,553 SC 95,826 31,966 20,852 278,852 54,230 12,945 176,104 TN 82,196 36,578 19,148 225,650 51,753 29,787 160,265 VA 133,738 49,173 53,344 252,924 54,587 10,619 120,022 WV 37,704 11,461 13,816 115,410 25,835 12,156 57,082 Percentage Difference (negative values mea ns Base G increased from Base F) AL 3.24% 1.79% 9.64% -0.34% 23.02% -170.67% 8.86% FL 43.75% 17.75% 11.42% 0.84% 28.62% 29.95% 9.09% GA 9.12% 3.91% 2.95% 0.07% 23.65% -0.56% 7.44% KY 10.68% 0.03% 0.08% 0.07% 14.99% -5.66% 0.22% MS 26.85% 0.90% 11.27% 0.05% 20.91% -18.10% 0.32% NC 9.41% 1.66% 25.39% 7.99% 8.09% 24.41% 25.65% SC 5.67% 4.41% 7.16% 0.20% 23.27% -0.82% 17.03% TN 9.74% 3.62% 3.39% -0.20% 14.74% -2.65% 3.67% VA 4.19% 5.15% 1.36% 0.17% 18. 45% -898.09% -22.51% WV 16.08% 7.29% 2.73% 0.28% 20.02% -1.06% 3.14%Documentation of the Base G 2002 Base Year, 2009 and 2018, Emission Inventories for VISTAS

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### Table 2.2-3 2018 Projection Year Emissions and Percentage Difference for Base F and Base G (based on actual emissions).

Actual Area 2018 - Base G State CO NH3 NOX PM10-PRI PM25-PRI SO2 VOC AL 59,626 71,915 25,028 445,256 62,323 50,264 153,577 FL 53,903 40,432 30,708 578,516 72,454 38,317 489,975 GA 93,827 99,885 41,332 880,199 123,704 59,729 319,328 KY 54,865 55,211 44,346 256,052 47,645 44,186 103,490 MS 22,099 69,910 4,483 375,495 53,222 746 140,134 NC 290,809 180,866 43,865 315,294 71,262 6,085 189,591 SC 83,167 33,496 20,592 304,251 44,319 13,457 161,228 TN 68,809 36,291 19,597 246,252 46,692 31,962 182,222 VA 121,690 50,175 56,158 275,351 46,697 109,380 150,919 WV 28,773 11,504 14,828 121,549 21,490 12,849 60,747 Base F AL 63,773 73,346 28,754 445,168 82,449 49,975 168,507 FL 100,952 49,889 35,047 582,832 101,872 59,413 533,141 GA 105,059 103,911 42,260 880,800 163,925 61,155 342,661 KY 65,297 55,356 45,597 256,544 57,110 42,326 102,117 MS 36,425 70,565 5,230 375,931 68,338 831 139,419 NC 327,871 184,167 60,073 345,275 85,018 8,273 234,207 SC 89,343 35,082 22,467 304,940 58,441 13,517 196,946 TN 81,242 37,812 20,928 245,893 55,712 31,047 188,977 VA 129,037 53,023 56,668 275,790 58,141 11,479 128,160 WV 36,809 12,390 15,079 121,964 27,088 13,450 62,164 Percentage Difference (negative values mea ns Base G increased from Base F) AL 6.50% 1.95% 12.96% -0.02% 24.41% -0.58% 8.86% FL 46.61% 18.96% 12.38% 0.74% 28.88% 35.51% 8.10% GA 10.69% 3.87% 2.20% 0.07% 24.54% 2.33% 6.81% KY 15.98% 0.26% 2.74% 0.19% 16.57% -4.40% -1.34% MS 39.33% 0.93% 14.28% 0.12% 22.12% 10.19% -0.51% NC 11.30% 1.79% 26.98% 8.68% 16.18% 26.45% 19.05% SC 6.91% 4.52% 8.34% 0.23% 24.16% 0.44% 18.14% TN 15.30% 4.02% 6.36% -0.15% 16.19% -2.95% 3.57% VA 5.69% 5.37% 0.90% 0.16% 19.68% -852.83% -17.76% WV 21.83% 7.15% 1.66% 0.34% 20.66% 4.46% 2.28%



### 2.2.3 Changes to Prescribed Fire for 2009/2018 Base G Just prior to release of version 3.1 of the VIST AS inventory. several Federal agencies indicated that they had plans for increased prescribed fire burning in future years and that the “typical” fire inventory would likely not adequately capture those increases (memo from Bill Jackson and Cindy Huber, August 13, 2004). However data were not readily available to incorporate those changes up through the Base F inventory. As a consequence MACTEC worked with Federal Land Managers to acquire the data necessary to provide 2009 and 2018 specific projections for the prescribed fire component of the Base G fire inventory. The 2009 and 2018 projections developed using the method described below are being used by VISTAS as the 2009 and 2018Documentation of the Base G 2002 Base Year, 2009 and 2018, Emission Inventories for VISTAS

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### base case inventories for all States except FL. For FL the supplied data from the FLMs is not being used as FL felt that their data adequately reflected current and future prescribed burning practices. The “typical” fire projection is the 2002 base prescribed fire projection.
One of the biggest issues in preparing the projection was how best to incorporate the data. Two agencies submitted data: Fish and Wildlife Service (FWS) and Forest Service (FS). FWS submitted annual acreage data by National Wildlife Refuge (NWR) and county with estimates of acres burned per day for each NWR. FS provide d fire-by-fire acreage estimates based on mapping projected burning acreage to current 2002 modeling days. However, FWS did not submit data for VISTAS original base year pr eparation process, thus there was no known FWS data in the 2002 actual or typical inventories. Thus MACTEC had to develop a method that could use the county level data submitted by FWS.
In addition, despite the fact that the FS submitted fire-by-fire data for the 2002 actual inventory and had mapped the projections to current burn days in the 2002 actual inventory, MACTEC could not do a simple replacement of those records with the 2009/2018 projections. This situation was created because several VISTAS States run a prescribed fire permitting program. To avoid double counting, only State data was used in those States for the 2002 actual inventory. Thus there were no Federal data in those States since the Federal data could have potentially duplicated State-supplied prescribed fire data. In VISTAS States without permit programs, the FS supplied data for 2002 was used and those records were marked in database. Thus for those States, the FS supplied 2009/2018 data could be directly substituted for the 2002 data.
The method used by MACTEC to include the FS data applied a county level data approach for FS data where a State had a prescribed fire pe rmitting program and a fire-by-fire replacement for FS data in States without permit programs. MACTEC used a county level approach for all of the FWS data. The approach used for each data set is discussed below.
For the FWS data MACTEC summed the annual acres burned supplied by the FWS across all NWRs in a county. We then subtracted out 2002 acreage for that county from the FWS projected acreage annual total to avoid double counting. The remaining acreage was then multiplied by 0.8 to account for blackened acres instead of the total perimeter acres that were reported. The revised total additional FWS acreage was then added to the total county “typical” acreage to determine future acreage burned for either 2009 or 2018. MACTEC then allocated the increased acreage to current modeling days. The average daily acres burned data provided by FWS per NWR/county was used to allocate the acreage to the correct number of days required to burn all of the acres. Guidance supplied by FWS indicated that up to three times the average daily acres burned could potentially be allocated to any one day. Thus if the estimated acreage per day were 100 acres then up to 300 acres could actually be allocated to a particular day. This approach (use of up to three times the average daily acres burned) was us ed if there were an insufficient number of 2002Documentation of the Base G 2002 Base Year, 2009 and 2018, Emission Inventories for VISTAS

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### modeling days available to account for all of the acreage increase. MACTEC used an incremental approach to using the increase above the base average daily acres. First we used twice the average daily acreage if that was suffici ent to completely allocate the increased acreage over the total number of days available. If that wasn’t sufficient then we used three times the average daily acres burned to allocate the acreage. We applied the highest increases to days in the database that already had the highest acreage burned since we felt those days were most likely to represent days with representative conditions for conducting prescribed burns.
The approach used by MACTEC for the FS was slightly different. For States that had permit programs, we used similar approach to the FWS county level approach. First we summed the FS data at county level, we then added that value to the typical acreage and then we allocated the acres to current modeling days. The mapping to current modeling days was performed by Bill Jackson of the USFS and provided to MACTEC. For States that do not have a prescribed fire permit program, MACTEC simply replaced the current fire-by-fire records in the database with fire-by-fire records from the FS and recalculated emissions based on fuel model and fuel loading. We also applied the same 0.8 correction for blackened acres applied to all FS supplied acreage as the supplied values represented perimeter acres.
An additional problem with developing year-speci fic prescribed fire projections was how to adequately capture the temporal profile for those fires. In the 2002 actual fire inventory, fires occur on same days as state/FLM records. In the 2002 “typical” year inventory, fire acreage increased or decreased from acreage on the same fire days as were in the 2002 actual inventory, since the acres were simply increased for each day based on a multiplier used to convert from actual to typical.
When prescribed fires acreage was added to a future year, MACTEC added acreage to individual fire days proportional to the annual increase (if acreage on a day is 10 percent of annual, add 10 percent of projected increase to that same day).

The table below shows how the FWS data for Okefenokee NWR were allocated for 2009 for Clinch County (Okefenokee NWR is located in four different counties). You can see that the total additional acres for the Clinch County portion of Okefenokee NWR was 1,956 acres. Two hundred eighty (280) acres were the estimated av erage daily acres burned for that NWR/county combination. Thus to allocate the entire 1,956 acres would require almost 7 burn days (1,956 divided by 280). However only 5 burn days were f ound for Clinch County in the 2002 actual fire database. Thus we allocated twice the average acreage to the burn day with the most acres burned in the 2002 actual fire database (since our method allowed us to increase the average daily acres burned up to three times the recommended level). Thus the first burn day received 560 acres and all others received 280 except the final day which received 276 to make the total equal to the required 1,956 acres. The table also indicates that the increased acres burnedDocumentation of the Base G 2002 Base Year, 2009 and 2018, Emission Inventories for VISTAS

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### 0 2000 4000 6000 8000 10000 12000 14000 16000

1 /1 / 2 0 0 2 2/

1 / 2 0 02

3 /1/2

0 02

4

/1 / 2 0 02

5 /1 / 2 0 0 2 6/

1 / 2 0 02

7 /1 / 2 0 02 8/ 1 /2

0 02
9

/1 / 2 002

10/

1 /2

002

11

/1 / 2002

1 2 /1 / 2002



# Date of Fire EventAcres Typical FWS Add USFS Add 

### provided increases of from 10-48 percent in the acres burned on the individual burn days and an average of approximately 14 percent for the year as a whole.

CLINCH COUNTY 3/1/2002 4/1/2002 2/1/2002 1/1/2002 11/1/2002 12/1/2002 Total Annual Acres (typical) 3,757 2,612 1,996 1,801 616 472 11,764 Add on FWS Projection 560 280 280 280 280 276 1,956

Total 4,316 2,891 2,276 2,080 895 747 13,720

Percent Increase 14.9% 10.7% 14.0% 15.6% 45.5% 58.5% 14.3%



### The figure below shows the increases for prescribed burning in the four counties that comprise the Okefenokee NWR area (which also includes FS land). In this figure you can see the additional acreage added for the burn days from FWS and the individual day increases caused by projected increases in prescribed burning based on FS data. It should be noted that while the emissions represent 2009, all fire event dates listed are for 2002 to match up with the base year meteorology used in modeling exercises.
Table 2.2-4 shows the percentage difference between the 2009 and 2018 projections developed for Base F and Base G. Base G includes the revised prescribed burning estimates described above. Values are calculated using Base F as the basis for change, thus negative values imply an increase in emissions for Base G.
Figure 2.2-1 Prescribed Fire Projection for Okeefenokee NWR for 2009Documentation of the Base G 2002 Base Year, 2009 and 2018, Emission Inventories for VISTASMACTEC, Inc.137Table 2.2-4 Percentage Difference Between BaseF and Base G Fire Emissions by StateStateCONH3NOXPM10-PRIPM25-PRISO2VOCCONH3NOXPM10-PRIPM25-PRISO2VOC2009 Fires Base G2018 Fires Base GAL 534,873 2,050 11,901 52,851 46,543 2,681 27,502 535,658 2,054 11,918 52,927 46,608 2,686 27,539FL 923,310 3,157 19,791 98,470 88,756 4,129 51,527 923,310 3,157 19,791 98,470 88,756 4,129 51,527GA 637,177 2,229 14,243 63,973 57,116 2,914 34,710 637,177 2,229 14,243 63,973 57,116 2,914 34,710KY 31,810 143 682 3,093 2,653 187 1,497 33,296 150 714 3,237 2,777 196 1,567MS 48,160 217 1,033 4,683 4,016 283 2,266 50,037 225 1,073 4,865 4,173 294 2,355NC 96,258 433 2,065 9,359 8,027 566 4,530 111,266 501 2,387 10,819 9,279 655 5,236SC 282,307 1,039 5,899 29,153 25,955 1,359 16,045 282,307 1,039 5,899 29,153 25,955 1,359 16,045TN 17,372 78 373 1,689 1,449 102 817 18,860 85 405 1,834 1,573 111 888VA 21,130 95 453 2,054 1,762 124 994 26,923 121 578 2,618 2,245 158 1,267WV 3,949 18 85 384 329 23 186 5,013 23 108 487 418 29 2362009 Fires Base F2018 Fires Base FAL 514,120 1,957 11,456 50,833 44,812 2,559 26,526 514,120 1,957 11,456 50,833 44,812 2,559 26,526FL 923,310 3,157 19,791 98,470 88,756 4,129 51,527 923,310 3,157 19,791 98,470 88,756 4,129 51,527GA 620,342 2,153 13,882 62,336 55,712 2,815 33,918 620,342 2,153 13,882 62,336 55,712 2,815 33,918KY 56,686 110 1,460 6,667 6,310 136 3,338 56,686 110 1,460 6,667 6,310 136 3,338MS 128,471 177 3,328 14,693 13,680 100 13,625 128,471 177 3,328 14,693 13,680 100 13,625NC 200,564 324 5,005 20,488 19,491 423 12,499 200,564 324 5,005 20,488 19,491 423 12,499SC 253,005 908 5,270 26,304 23,511 1,187 14,666 253,005 908 5,270 26,304 23,511 1,187 14,666TN 78,370 46 2,232 8,875 8,730 59 5,153 78,370 46 2,232 8,875 8,730 59 5,153VA 19,159 159 978 18,160 17,361 99 912 19,159 159 978 18,160 17,361 99 912WV 32,656 12 944 3,276 3,239 16 2,184 32,656 12 944 3,276 3,239 16 2,184Percentage Difference (negative number means an increase in Base G emissions)AL -4.04% -4.77% -3.89% -3.97% -3.86% -4.77% -3.68% -4.19% -4.95% -4.03% -4.12% -4.01% -4.95% -3.82%FL 0.00% 0.00% 0.00% 0.00% 0.00% 0.00% 0.00%0.00% 0.00% 0.00% 0.00% 0.00% 0.00% 0.00%GA -2.71% -3.52% -2.60% -2.63% -2.52% -3.52% -2.34% -2.71% -3.52% -2.60% -2.63% -2.52% -3.52% -2.34%KY 43.88% -29.52% 53.25% 53.61% 57.96% -37.90% 55.15%41.26% -35.57% 51.07% 51.44% 56.00% -44.34% 53.06%MS 62.51% -22.07% 68.95% 68.13% 70.64% -183.85% 83.37%61.05% -26.83% 67.74% 66.89% 69.50% -194.91% 82.72%NC 52.01% -33.75% 58.74% 54.32% 58.82% -33.75% 63.76%44.52% -54.60% 52.31% 47.19% 52.40% -54.60% 58.11%SC -11.58% -14.52% -11.93% -10.83% -10.39% -14.52% -9.40%-11.58% -14.52% -11.93% -10.83% -10.39% -14.52% -9.40%TN 77.83% -69.40% 83.30% 80.97% 83.41% -74.42% 84.14%75.93% -83.92% 81.87% 79.34% 81.98% -89.36% 82.78%VA -10.29% 40.36% 53.67% 88.69% 89.85% -25.40% -9.03%-40.53% 24.00% 40.97% 85.59% 87.07% -59.79% -38.93%WV 87.91% -48.65% 91.03% 88.28% 89.83% -49.46% 91.49%84.65% -88.70% 88.61% 85.12% 87.09% -89.73% 89.20%Documentation of the Base G 2002 Base Year, 2009 and 2018, Emission Inventories for VISTAS

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### 2.2.4 Quality Assurance steps Throughout the inventory development process, quality assurance steps were performed to ensure that no double counting of emissions occurred, to ensure that a full and complete inventory was developed for VISTAS, and to ma ke sure that projection calculations were working correctly. Quality assurance was an important component to the inventory development process and MACTEC performed the following QA steps on the stationary and agricultural area source components of the 2009 and revised 2018 projection inventories:
1. All final files were run through EPA’s Format and Content checking software.
2. SCC level emission summaries were prepared and evaluated to ensure that emissions were consistent and that there were no missing sources.
3. Tier comparisons (by pollutant) were developed between the 2002 base year inventory and the 2009 and 2018 projection inventories. In addition, total VISTAS pollutant summaries were prepared to compare total emissions by pollutant between versions of the inventory (e.g., between Base F and Base G).
4. Data product summaries were provided to both the VISTAS Emission Inventory Technical Advisor and to the SIWG representatives for review and comment. Changes based on these comments were implemented in the files.
5. Version numbering was used for all inventory files developed. The version numbering process used a decimal system to track major and minor changes. For example, a major change would result in a version going from 1.0 to 2.0. A minor change would cause a version number to go from 1.0 to 1.1. Minor changes resulting from largely editorial changes would result in a change from 1.00 to 1.01.

2.3 Mobile Sources
Our general approach for assembling data was to use as much existing data from the pre-Base F preliminary projections as possible for these inventories, supplement these data with easily available stakeholder input, and provide the results for stakeholder review to ensure credibility. To develop the “base case” projections, MACTEC originally assembled data to develop two 2009 and 2018 base case inventories: 1) an inve ntory that included all “on-the-books” controlprograms and 2) an “on-the-way” inventory that included controls that were likely to be “on-theway”. For the Base F and Base G emission forecasts to the mobile source sector, “on-the-books” and “on-the-way” are defined with the same st rategies and therefore only a single projection scenario was developed for each forecast year.
To ensure consistency across evaluation years, the 2009 and 2018 base case inventories were developed, to the maximum extent practical, using methodologies identical to those employed inDocumentation of the Base G 2002 Base Year, 2009 and 2018, Emission Inventories for VISTAS

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### developing the 2002 on-road portion of the revi sed 2002 VISTAS base year inventory. All modifications to the 2002 inventory methods were developed in consultation with the Mobile Source Special Interest Workgroup (MSSIWG). Generally, modifications were only made to properly account for actual changes expected in the intervening period (i.e., between 2002 and 2009 and between 2002 and 2018), but the underlyi ng inventory development methodology was identical, except to the extent requested by VISTAS or the MSSIWG.
MACTEC developed a preliminary 2018 inventor y in early 2004. That inventory was designed to 1) be used for modeling sensitivity evaluations and 2) help establish the methods that would be used for the final 2018 inventory and the initial 2009 inventory. Since that work took place prior to the revision of the 2002 base year invent ory data files, MACTEC provided a review of the data and methods used to develop on-road mobile source input files for the initial 2002 base year inventory prior to developing the pr eliminary 2018 inventory. Through this review, MACTEC determined the following:

• On-road VMT. Most States provided local data for 2002 (or a neighboring year that was converted to 2002 using appropriate VMT growth surrogates such as population). Since these data were not applicable to 2018 due to intervening growth, input for2018 was solicited from the MSSIWG. At the same time we researched countyspecific growth rate data utilized for recent national rulemakings as a backstop approach to State supplied VMT projections.

• Modeling Temperatures. Actual 2002 temperat ures were used for the initial 2002 base year inventory.

• Vehicle Registration Mix (age fractions by type of vehicle). A mix of State, local, and MOBILE6 default data were used for the 2002 initial base year inventory. Forecast data were solicited from the States, with a fallback position that we hold the fractions constant at their 2002 values.

• Vehicle Speed by Roadway Type. For the 2002 initial base year inventory, speeds varying by vehicle and road type were used.

• VMT Mixes (fraction of VMT by vehicle type). A mix of State, local, and quasi MOBILE6 default (i.e., MOBILE6 defaults normalized to better reflect local conditions) data were used for the 2002 initial base year inventory. Forecast data were solicited from the States.

• Diesel Sales Fractions. As with the VMT mix data, the diesel sales fraction data employed for the 2002 initial base year inventory represents a mix of State, local, and quasi MOBILE6 default data. The issues related to updating these data to 2018 areDocumentation of the Base G 2002 Base Year, 2009 and 2018, Emission Inventories for VISTAS

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### also similar, but are complicated by the fact that MOBILE6 treats diesel sales fraction on a model year, rather than age specific basis. Therefore, diesel sales fractions generally cannot be held constant across time. Once again, we solicited any local projections, with a fallback position that we would keep the data for 2002 and earlier model years constant for the forecast inventory, supplemented with MOBILE6 default data for 2003 and newer model years.

• State/Local Fuel Standards. For the 2002 initial base year inventory, these data were based on appropriate local requirements and updated data for 2018 was only required if changes were expected between 2002 a nd 2018. There are some national changes in required fuel quality for both on-road and non-road fuels that are expected to occur between 2002 and 2018 and these would be reflected in the 2018 inventory in the absence of more stringent local fuel controls. Expected changes in local fuel control programs were solicited.

• Vehicle Standards. The 2002 initial base year inventory assumed NLEV applicability. This was altered to reflect Tier 2 for 2018, unless a State indicated a specific plan to adopt the California LEV II program. If so, we made the required changes to implement those plans for the preliminary 2018 inventory.

• Other Local Controls. This includes vehicle emissions inspection (i.e., I/M) programs, Stage II vapor recovery programs, anti tampering programs, etc. By nature, the assumptions used for the 2002 initial base year inventory vary across the VISTAS region, but our presumption is that these data accurately reflected each State’s situation as it existed in 2002. If a State had no plans to change program requirements between 2002 and 2018, we proposed to maintain the 2002 program descriptions without change. However, if a State planned changes, we requested information on those plans. In the final implementation of the Base F and earlier inventories, Stage II controls were exercised in the area source component of the inventory, since the units used to develop Stage II refueling estimates are different between MOBILE6 and the NONROAD models. However, in the Base G inventories, Stage II refueling was moved to the on-road and non-road sectors.
Once the preliminary 2018 (pre-Base F) base case projection inventory data were compiled,MACTEC applied the data and methods selected and proceeded to develop the preliminary (prebase F) base case 2018 projection inventories. The resulting inventories were provided to the MSSIWG in a user-friendly format for review. After stakeholder review and comment, the final preliminary 2018 base case inventories and input files were provided to VISTAS in formats identified by the VISTAS Technical Advisor (in this case, MOBILE input files and VMT, NONROAD input files and annual inventory f iles for NONROAD in NIF 3.0 format). AnnualDocumentation of the Base G 2002 Base Year, 2009 and 2018, Emission Inventories for VISTAS

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### inventory files for MOBILE were not developed as part of this work, only input files and VMT forecasts. MOBILE emissions were calculated by VISTAS air quality modeling contractor using the provided files.
2.3.1 Development of on-road mobile source input files As indicated above, MACTEC prepared a preliminary version of the 2018 base case mobile inventory input data files. These files were then updated to provide a final set of 2018 base case inventory input data files as well as a set of input files for 2009. The information below describes the updates performed on the preliminary 2018 files and the development of the 2009 input data files for Base F emission estimation.
Our default approach to preparing the revise d 2018 and initial 2009 projection inventories for onroad mobile sources was to estimate the emissions by using either:
1. the revised 2002 data provided by each State coupled with the projection methods employed for the preliminary 2018 inventory, or
2. the same data and methods used to generate the preliminary 2018 inventory.
We also investigated whether or not there was more recent VMT forecasting data available (e.g., from the CAIR and if appropriate revised the default VMT growth rates accordingly. This did not affect any State that provided local VM T forecasting data, but would alter the VMT estimates used for other areas.
Since no preliminary 2009 inventory was developed there did not exist an option (2) above for 2009. As a consequence, MACTEC crafted the 2009 initial inventory for on-road mobile sources using methods identical to those employed for th e 2018 preliminary inventories coupled with any changes/revisions provided by the States during th e review of the revised 2002 base year and the 2018 preliminary inventories. Therefore, as was the case for 2018, we obtained from the States any input data revisions, methodological revisions , and local control program specifications (to the extent that they differed from 2002/2018).
2.3.1.1 Preparation of revised 2018 input data files Preparation of the revised 2018 inventories required the following updates:
1. The evaluation year was updated to 2018 in all files.
2. The diesel fuel sulfur content was revised from 500 ppm to 11 ppm, consistent with EPA data for 2018 in all files.
3. Since the input data is model year, rather than age, specific for diesel sales fractions (with data for the newest 25 model years required), we updated all files that includedDocumentation of the Base G 2002 Base Year, 2009 and 2018, Emission Inventories for VISTAS

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### diesel sales fractions. In the revised 2002 base year files, the data included applied to model years 1978-2002. For 2018, the data included would reflect model years 1994- 2018. To forecast the 2002 data, MACTEC took the data for 1994-2002 from the 2002 files and added data for 2003-2018. To estimate the data for these years, we employed the assumption employed by "default" in MOBILE6 -- namely that diesel sales fractions for 1996 and later are constant. Therefore, we set the diesel sales fractions for 2003-2018 at the same value as 2002.
4. VMT mix fractions must be updated to reflect expected changes in sales patterns between 2002 and 2018. If explicit VMT mix fractions are not provided, these changes are handled internally by MOBILE6 or externally through absolute VMT distributions. However, files that include explicit VMT mix fractions override the default MOBILE6 update and may or may not be consistent with external VMT distributions. MACTEC updated the VMT mix in such files as follows:
First, we calculated the VMT fractions for LDV, LDT1, LDT2, HDV, and MC from the external VMT files for 2018. This calculation was performed in accordance with section 5.3.2 of the MOBILE6 Users Guide which indicates:

LDV = LDGV + LDDV

LDT1 = LDGT1 + LDDT

LDT2 = LDGT2

HDV = HDGV + HDDV

MC = MC The resulting five VMT fractions were then split into the 16 fractions required by MOBILE6 using the distributions for 2018 provided in Appendix D of the MOBILE6 Users Guide. This approach ensures that explicit input file VMT fractions are consistent with the absolute VMT distributions prepared by MACTEC. These changes were made to all files that included VMT mixes.
5. All other input data were retained at 2002 values, except as otherwise instructed by the States. This includes all control program descriptions (I/M, Anti-Tampering Program [ATP], Stage II, etc.), all other fuel qualities (RVP, oxy content, etc.), all other vehicle descriptive data (registrations age distributions, etc.), and all scenario descriptive data. The State-specific updates performed are described below.
Kentucky: MACTEC revised the 2018 input files for the Louisville, Kentucky area (Louisville Air Pollution Control District [APCD]) based on comments received relative to several components ofDocumentation of the Base G 2002 Base Year, 2009 and 2018, Emission Inventories for VISTAS

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### MOBILE input data. Based on these comments, the input files for Jefferson County, Kentucky were updated accordingly as follows: a) I/M and tampering program definitions were removed since the program was discontinued at the end of 2003. b) The "Speed VMT", "Facility VMT" and "Registration Age Distribution" file pointers were updated to reflect revised 2002 files provided by the Louisville APCD. c) The "VMT Mix" data, which was previously based on the default approach of "growing" 2002 data, was replaced by 2018-specific data provided by the Louisville APCD.
North Carolina: North Carolina provided a wide range of revised input data, including complete MOBILE6 input files for July modeling. MACTEC did not use the provided input files directly as they did not match the 2002 NC input files for critical elements such as temperature distributions and gasoline RVP (while they were close, they were slightly different). To maintain continuity between 2002 and 2018 modeling, MACTEC instead elected to revise the 2002 input files to reflect all control program and vehicle-related changes implied by the new 2018 files, while retaining the basic temperature and gasoline RVP assumptions at their 2002 values. Under this approach, the following changes were made:
a) NC provided a county cross reference file specific to 2018 that differed from that used for 2002. We removed files that were referenced in the 2002 input data and replaced those files with those referenced in the 2018 data. In addition, since NC only provided 2018 input files for July, we estimated the basic data for these new files for the other months by cross referencing the target files for 2002 by county against the target files for 2018 by county. b) We then revised the 2002 version of each input file to reflect the 2018 "header" data included in the NC-provided 2018 files. These data are exclusively limited to I/M and ATP program descriptions, so that the 2002 I/M and ATP data were replaced with 2018 I/M and ATP data. c) We retained the registration age fractions at their 2002 "values" (external file pointers) as per NC instructions. d) We retained all scenario-specific data (i.e., temperatures, RVP, etc.) at 2002 values, which (as indicated above), were slightly different in most cases from data included in the 2018 files provided by NC. We believe these differences were due to small deviations between the data assembled to support VISTAS 2002 and the process used to generate the 2018 files provided by NC, and that revising the VISTAS 2002 data toDocumentation of the Base G 2002 Base Year, 2009 and 2018, Emission Inventories for VISTAS

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### reflect these variations was not appropriate given the resulting inconsistencies that would be reflected between VISTAS 2002 and VISTAS 2018. e) NC also provided non-I/M versions of th e 2018 input files that would generally be used to model the non-I/M portion of VMT. While these files were retained they were not used for the 2018 input data preparation. Finally, NC also provided a speed profile file and a speed profile cross reference file for 2018. We did not use these in our updates as they have no bearing on the MOBILE6 input files, but they were maintained in case they needed to be included in SMOKE control files for a future year control strategy scenario.
Virginia: In accordance with instructions from VA, the input files that referenced an external I/M descriptive program file (VAIM02.IM) were revised to reference an alternative external file (VAIM05.IM). This change was to make the I/M program more relevant to the year 2018.
One additional important difference was made with respect to the revised 2018 and initial 2009 on-road mobile source input data files for all States. MACTEC developed updated SMOKE ready input files rather than MOBILE6 files so th at the input data could be used directly by the VISTAS modeling contractor to estimate on-road mobile source emissions during modeling runs.
2.3.1.2 Preparation of initial 2009 input data files
The methodology used to develop the 2009 on-road input files was based on forecasting the previously developed revised 2002 base year input files and is identical to that previously described for the revised 2018 methodology except as follows: 1. The evaluation year was updated to 2009. 2. Diesel fuel sulfur content was revised from 500 ppm to 29 ppm. The 29 ppm value was derived from an EPA report entitled "Summary and Analysis of the Highway Diesel Fuel 2003 Pre-compliance Reports" (EPA420-R-03-013, October 2003), which includes the Agency's estimates for the year-to-year fuel volumes associated with the transition from 500 ppm to 15 ppm diesel fuel. According to Table 2 of the report, there will be 2,922,284 barrels per day of 15 ppm diesel distributed in 2009 along with 110,488 barrels per day of 500 ppm diesel. Treating the 15 ppm diesel as 11 ppm on average (consistent with EPA assumptions and assumptions employed for the 2018 input files) and sales weighting the two sulfur content fuels results in an average 2009 diesel fuel sulfur content estimate of 29 ppm.Documentation of the Base G 2002 Base Year, 2009 and 2018, Emission Inventories for VISTAS

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### 3. Diesel sales fractions were updated identically to 2018 except that the diesel sales fractions for 2003-2009 were set at the same value as those for 2002 (rather than 2003-2018). 4. VMT mix fractions were updated to 2009 using an identical method to that described for 2018. 5. All other input data were retained at 2002 values, except as otherwise instructed by individual States (see below). This includes all control program descriptions (I/M, ATP, Stage II, etc.), all other fuel qualities (RVP, oxy content, etc.), all other vehicle descriptive data (registration age distributions, etc.), and all scenario descriptive data. In addition to the updates described above that were applied to all VISTAS-region inputs, the following additional State-specific updates were performed:

KY – Identical changes to those made for 2018 (but specific to 2009) were made for the 2009 input files.
NC – Identical changes to those made for 2018 (but specific to 2009) were made for the 2009 input files.
VA – Identical changes to those made for 2018 were made for 2009.

2.3.2 VMT Data The basic methodology used to generate the 2009 and 2018 VMT for use in estimating on-road mobile source emissions was as follows: 1. All estimates start from the final VMT estimates used for the 2002 revised base year inventory. 2. Initial 2009 and 2018 VMT estimates were based on linear growth rates for each State, county, and vehicle type as derived from th e VMT data assembled by the U.S. EPA for their most recent HDD (heavy duty diesel) rulemaking. The methodology used to derive the growth factors is identical to that employed for the preliminary 2018 VMT estimates (which is described in the next section). 3. For States that provided no independent forecast data, the estimates derived in step 2 are also the final estimates. These States are: Alabama, Florida, Georgia, Kentucky, Mississippi, and West Virginia. For States th at provided forecast data, the provided data were used to either replace or augment the forecast data based on the HDD rule. These States, and the specific approaches employed, are detailed following the growth method description. The steps involved in performing the growth estimates for VMT were as follows:Documentation of the Base G 2002 Base Year, 2009 and 2018, Emission Inventories for VISTAS

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### 1. Linear growth estimates were used (although MACTEC investigated the potential use of nonlinear factors and presented that information to the MSSIWG, the decision was made to use linear growth factors instead of nonlinear). 2. Estimates were developed at the vehicle class (i.e., LDGV, LDGT1, LDGT2, etc.) level of detail since the base year 2002 estimates were presented at that level of resolution. In effect, the county and vehicle class specific growth factors were applied to the 2002 VMT estimates for each vehicle and road class. 3. Overall county-specific VMT estimates for each year (developed by summing the vehicle and road class specific forecasts) were then compared to overall county-specific growth. Since overall county growth is a more appropriate controlling factor as it includes the combined impacts of all vehicle classes, the initial year-specific vehicle and road class VMT forecasts were normalized so that they matched the overall county VMT growth. Mathematically, this process is as follows: (Est_rv_f) = (Est_rv_i) * (C_20XX / Sum(Est_rv_i))
where: Est_rv_f = the final road/vehicle class-specific estimates, Est_rv_i = the initial road/vehicle class-specific estimates, and C_20XX = the county-specific growth target for year 20XX. Table 2.3-1 presents a basic summary of the forecasts for the preliminary 2018 inventory for illustrative purposes:
Table 2.3-1 2002 versus 2018 VMT (million miles per year)

State 2002 2018 Growth Factor Alabama 55,723 72,966 1.309 Florida 178,681 258,191 1.445 Georgia 106,785 148,269 1.388 Kentucky 51,020 66,300 1.299 Mississippi 36,278 46,996 1.295 North Carolina 80,166 110,365 1.377 South Carolina 47,074 63,880 1.357

Tennessee 68,316 91,647 1.342 Virginia 76,566 102,971 1.345 West Virginia 19,544 24,891 1.274Documentation of the Base G 2002 Base Year, 2009 and 2018, Emission Inventories for VISTAS

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### The following States provided some types of for ecast data for VMT. The information presented below indicates how those data were processe d by MACTEC for use in the VISTAS projection inventories.
Kentucky: Revised 2009 and 2018 VMT mix data were provided by the Louisville APCD. Therefore, the distribution of Jefferson County VMT by vehicle type within the KY VMT file was revised to reflect the provided mix. This did not affect th e total forecasted VMT for either Jefferson County or the State, but does alter the fraction of that VMT accumulated by each of the eight vehicle types reflected in the VMT file. The following procedure was employed to make the VMT estimates consistent with the provided 2009/2018 VMT mix:
a) The 16 MOBILE6 VMT mix fractions were a ggregated into the following five vehicle types: LDV, LDT1, LDT2, HDV, and MC.
b) The 8 VMT mileage classes were aggregated into the same five vehicle types (across all roadway types) and converted to fractions by normalizing against the total Jefferson County VMT.
c) The ratio of the "desired" VMT fraction (i.e., that provided in the Louisville APCD VMT mix) to the "forecasted" VMT fraction (i.e., that calculated on the basis of the forecasted VMT data) was calculated for each of the five vehicle classes.
d) All forecasted VMT data for Jefferson County were multiplied by the applicable ratio from step c as follows:

new LDGV = old LDGV * LDV ratio new LDGT1 = old LDGT1 * LDT1 ratio new LDGT2 = old LDGT2 * LDT2 ratio new HDGV = old HDGV * HDV ratio new LDDV = old LDDV * LDV ratio new LDDT = old LDDT * LDT1 ratio new HDDV = old HDDV * HDV ratio new MC = old MC * MC ratio
The total forecasted VMT for Jefferson County was then checked to ensure that it was unchanged.
North Carolina:
North Carolina provided both VMT and VMT mix data by county and roadway type for 2018. Therefore, these data replaced the data developed for North Carolina using HDD rule growthDocumentation of the Base G 2002 Base Year, 2009 and 2018, Emission Inventories for VISTAS

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### rates in their entirety. Similar data were submitted for 2009. Table 2.3-2 presents the resulting VMT estimates which differ from the "default" HDD rule estimates as follows:

Table 2.3-2 VMT and HDD Rule Estimates for North Carolina (million miles per year)

North Carolina 2002 106,795
State Data HDD Data 2009 123,396 124,626 2018 129,552 146,989 

### As indicated, there are substantial reductions in the State-provided forecast data relative to that derived from the HDD rule. The growth rates for both 2009 and 2018 are only about half that implied by the HDD data (1.15 versus 1.17 for 2009 and 1.21 versus 1.38 for 2018). The resulting growth rates are the lowest in the VISTAS region.
NC did not provide VMT mix data for 2009. Theref ore, the VMT mix fractions estimated using the "default" HDD rule growth rates were applied to the State-provided VMT estimates to generate vehicle-specific VMT. Essentia lly, the default HDD methodology produces VMT estimates at the county-road type-vehicle type level of detail, and these data can be converted into VMT fractions at that same level of deta il. Note that these are not HDD VMT fractions, but VMT fractions developed from 2002 NC data us ing HDD vehicle-specific growth rates. In effect, they are 2002 NC VMT fractions "grown" to 2009.
The default VMT mix fraction was applied to the State-provided VMT data at the county and road type level of detail to generate VMT data at the county-road type-vehicle type level of detail. The one exception was for county 063, road 110, for which no VMT da ta were included in the HDD rule. For this single county/road combination, State-aggregate VMT mix fractions (using the HDD growth methodology) were applied to the county/road VMT data. The difference between road 110 VMT fractions across all NC counties is minimal, so there is no effective difference in utilizing this more aggregate approach vis-à-vis the more resolved county/road approach.

South Carolina: South Carolina provided county and roadway type-specific VMT data for several future years. Data for 2018 was included and was used dir ectly. Data for 2009 was not included, but was linearly interpolated from data provided for 2007 and 2010. The data were disaggregated into vehicle type-specific VMT using the VMT mixe s developed for South Carolina using the HDD rule VMT growth rates. Table 2.3-3 presents the resulting VMT estimates which differ from the "default" HDD rule estimates as follows:Documentation of the Base G 2002 Base Year, 2009 and 2018, Emission Inventories for VISTAS

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### Table 2.3-3 VMT and HDD Rule Estimates for South Carolina (million miles per year)

South Carolina 2002 47,074
State Data HDD Data 2009 55,147 54,543 2018 65,133 63,880


### Tennessee: In general, Tennessee estimates are based on the HDD rule growth rate as described in step two. However, Knox County provided independent VMT estimates for 2018 and these were used in place of the HDD rule-derived estimates. The Knox County estimates were total county VMT data only, so these were disaggregated into roadway and vehicle-type VMT using the distributions developed for Knox County in step two using the HDD rule VMT growth rates. No data for Knox County were provided for 2009, so the estimates derived using the HDD rule growth factors were adjusted by the ratio of "Knox County provided 2018 VMT" to "Knox County HDD Rule-derived 2018 VMT." Table 2.3-4 presents the resulting VMT estimates which differ from the "default" HDD rule estimates as follows:
Table 2.3-4 VMT and HDD Rule Estimates for Tennessee (million miles per year)

Tennessee 2002 68,316
State Data HDD Data 2009 78,615 78,813 2018 91,417 91,647 

### Virginia: Virginia provided county and roadway type-specific annual VMT growth rates and these data were applied to Virginia -provided VMT data for 2002 to estimate VMT in both 2009 and 2018. Virginia provided VMT mix data for 2002, but not 2009 or 2018. Therefore, the estimated VMT data for both 2009 and 2018 were disaggregated into vehicle type-specific VMT using the VMT mixes developed for VA using the HDD rule VMT growth rates. Table 2.3-5 presents the resulting VMT estimates which differ from the "default" HDD rule estimates as follows:Documentation of the Base G 2002 Base Year, 2009 and 2018, Emission Inventories for VISTAS

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### Table 2.3-5 VMT and HDD Rule Estimates for Virginia (million miles per year)

Virginia 2002 77,472
State Data HDD Data 2009 88,419 89,196 2018 104,944 104,164



### 2.3.3 Base G Revisions For the development of the VISTAS 2009 and 2018 Ba se G inventories and input files, VISTAS states reviewed the Base F inputs, and provided corrections, updates and supplemental data as noted below.
For all states modeled, the Base G updates include:

• Adding Stage II refueling emissions calculations to the SMOKE processing.

• Revised the HDD compliance. (REBUILD EFFECTS = .1)

• Revised Diesel sulfur values in 2009 to 43 ppm and 2018 to 11 ppm
In addition to the global changes, individual VISTAS states made the following updates:
KY – updated VMT and M6 input values for selected counties
NC – revised VMT estimates, speeds and vehicle distributions and updated registration distributions for Mobile 6.
TN - revised VMT and vehicle registrati on distributions for selected counties.
WV – revised VMT input data
AL, FL, and GA and VA did not provide updates for 2009/2018 Base G, and the Base F inputs were used for these States.
2.3.4 Development of non-road emission estimates The sections that follow describe the projection process used to develop 2009 and 2018 non-road projection estimates, as revised through the spring of 2006, for sources found in the NONROAD model and those sources estimated outside of the model (locomotives, airplanes and commercial marine vessels).Documentation of the Base G 2002 Base Year, 2009 and 2018, Emission Inventories for VISTAS

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### 2.3.4.1 NONROAD model sources NONROAD model input files were prepared in both the fall of 2004 (Base F) and the spring of 2006 (Base G) based on the corresponding 2002 base year inventory input files available at the time the forecasts were developed, with appropriate updates for the projection years. Generally, this means that the Base F 2002 base year input files (as updated through the fall of 2004) were used as the basis for Base F projection year i nput file development and Base G 2002 base year input files as updated through the spring of 2006 we re used as the basis for Base G projection year input file development. Thus, all base year revisions are inherently incorporated into the associated projection year revisions. Other specific updates for the projection years for NONROAD model sources consist of:
1. Revise the emission inventory year in the model (as well as various output file naming commands) to be reflective of the projection year. 2. Revise the fuel sulfur content for gasoline and diesel powered equipment. 3. Implement a limited number of local control program charges (national control program changes are handled internally within the NONROAD model, so explicit input file changes are not required). All equipment population growth and fleet turnover impacts are also handled internally within the NONROAD model, so that explicit changes input file changes are not required.
Base F Input File Changes:
To correctly account for diesel fuel sulfur content differences between the base and projectionyears, two sets of input and output files were prepared for each forecast year, one set for landbased equipment and one set for marine equipment. This two-step projection process was required for Base F, because diesel fuel sulfur contents varied between land-based and marine-based non-road equipment and the Draft NONROAD2004 used for Base F allowed only a single diesel fuel sulfur input. Thus, the model was executed separately for land-based and marine-based equipment for Base F, and the associated outputs subsequently combined. The specific diesel fuel sulfur contents modeled were as follows: Diesel S (ppm) 2002 2009 2018
Land-Based 2500 348 11
Marine-Based 2500 408 56 As indicated, the Draft NONROAD2004 model was r un with both sets of input files and the output file results were then combined to produce a single NONROAD output set.
To correctly account for the national reduction in gasoline sulfur content (a national control not explicitly handled by the NONROAD model), all NONROAD input files for both 2009 and 2018 were revised to reflect a gasoline fuel sulfur content of 30 ppmW.Documentation of the Base G 2002 Base Year, 2009 and 2018, Emission Inventories for VISTAS

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### Base G Input File Changes:
With the release of Final NONROAD2005 that was used for the Base G projection year inventory development, the NONROAD model is capable of handling separate diesel fuel sulfur inputs for land-based and marine-based non-road equipment in a single model execution. Therefore, the two step modeling process described above for Base F updates was no longer required. Instead, the differential diesel fuel sulfur values are assembled into a single NONROAD input file as follows: Diesel S (ppm) 2002 2009 2018
Land-Based 2500 348 11
Marine-Based 2638 408 56 Additionally, revised gasoline vapor pressure da ta were provided by Georgia regulators for 20 counties 5 

### where reduced volatility requirements were established in 2003. Since this requirement began after the 2002 base year, the vapor pressure values in the base year input files for these counties are not correct for either the 2009 or 2018 forecast years. Therefore, to correctly forecast emissions in these counties, the forecast year gasoline vapor pressure inputs were revised to: Gasoline RVP (psi) 2002 2009 2018 Spring 9.87 9.2 9.2
Summer 9.0 7.0 7.0
Fall 9.87 9.2 9.2
Winter 12.5 12.5 12.5 The summer vapor pressure was simply set equal to the 2003 control value, while the spring and fall vapor pressures were adjusted to reflect a single month of the reduced volatility limit. The winter volatility was assumed to be unaffected by the summertime control requirement.

2.3.4.1.1 Differences between 2009/2018 

### Other than diesel fuel sulfur content and the year of the projections, there are no differences in the methodology used to estimate emissions from NONROAD model sources. As indicated above, however the Base F 2009/2018 projecti ons were developed using Draft NONROAD2004, while the Base G 2009/2018 projections were made using Final NONROAD2005.

5 The specific counties are: Banks, Chattooga, Clarke, Floyd, Gordon, Heard, Jasper, Jones, Lamar, Lumpkin,

Madison, Meriwether, Monroe, Morgan, Oconee, Pike, Polk, Putnam, Troup, and Upson.Documentation of the Base G 2002 Base Year, 2009 and 2018, Emission Inventories for VISTAS

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### 2.3.4.2 Non-NONROAD model sources Using the 2002 base year emissions inventory for aircraft, locomotives, and commercial marine vessels (CMV) prepared as described earlier in this document, corresponding emission projections for 2009 and 2018 were developed in both the fall of 2004 (Base F) and the spring of 2006 (Base G). This section describes the procedur es employed in developing those inventories. The information presented is intended to build off of that presented in the section describing the 2002 Base F base year inventory. It should be r ecognized that for both the Base F and Base G inventories, the base year inventory used to develop the emission forecasts was the latest available at the time of forecast development. Generally, this means that the 2002 base year inventory as updated through the fall of 2004 was used as the basis for the Base F projection year inventory development, and the Base F 2002 base y ear inventory was used as the basis for Base G projection year inventory development. Thus, all base year revisions (as described earlier in this document) are inherently incorporated into the associated projection year revisions.

Base F Revisions:
Table 2.3-6 shows the 2002 base year emissions for each State in the VISTAS region for aircraft, locomotives and CMV (as they existed prior to Base F development).Documentation of the Base G 2002 Base Year, 2009 and 2018, Emission Inventories for VISTAS

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### Table 2.3-6. Pre-Base F 2002 Aircraft, Locomotive, and Non-Recreational Marine Emissions (annual tons, as of the fall of 2004)

Source State CO NO x PM 10 PM 2.5 SO 2 VOC AL 3,787 175 226 87 17 196 FL 25,431 8,891 2,424 2,375 800 3,658 GA 6,620 5,372 1,475 1,446 451 443 KY 2,666 657 179 175 63 263 MS 1,593 140 44 43 13 96 NC 6,088 1,548 419 411 148 613 SC 6,505 515 409 401 88 863 TN 7,251 2,766 734 719 235 943 VA 9,763 2,756 1,137 1,115 786 2,529 WV 1,178 78 25 24 8 66 Aircraft (2275)

Total 70,882 22,899 7,072 6,797 2,607 9,670 AL 1,196 9,218 917 844 3,337 737 FL 5,888 44,817 1,936 1,781 6,683 1,409 GA 1,038 7,875 334 307 1,173 246 KY 6,607 50,267 2,246 2,066 9,608 1,569 MS 5,688 43,233 1,903 1,751 7,719 1,351 NC 599 4,547 193 178 690 142 SC 1,067 8,100 343 316 1,205 253 TN 3,624 27,555 1,217 1,120 4,974 860 VA 972 2,775 334 307 359 483 WV 1,528 11,586 487 448 525 362 Commercial

Marine (2280)

Total 28,207 209,972 9,911 9,118 36,275 7,413 VA 110 313 25 23 27 48 Military Marine (2283) Total 110 313 25 23 27 48 AL 3,490 26,339 592 533 1,446 1,354 FL 1,006 9,969 247 222 605 404 GA 2,654 26,733 664 598 1,622 1,059 KY 2,166 21,811 542 488 1,321 867 MS 2,302 23,267 578 520 1,429 899 NC 1,638 16,502 410 369 1,001 654 SC 1,160 11,690 291 261 710 462 TN 2,626 25,627 633 570 1,439 1,041 VA 1,186 11,882 1,529 1,375 3,641 492 WV 1,311 13,224 329 296 808 517 Locomotives

(2285)

Total 19,540 187,044 5,815 5,232 14,022 7,750

Grand Total 118,739 420,228 22,823 21,170 52,931 24,881Documentation of the Base G 2002 Base Year, 2009 and 2018, Emission Inventories for VISTAS

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### Although some of the data utilized was updated, the methodology used to develop the Base F 2009 and 2018 emissions forecasts for aircraft, locomotives, and CMV is identical to that used earlier to develop preliminary 2018 Base 1 (“On the Books”) and 2018 Base 2 (“On the Way”) inventories. Briefly, the methodology relies on gr owth and control factors developed from inventories used in support of recent EPA rulemakings, and consists of the following steps:
(a) Begin with the 2002 base year emission estimates for aircraft, locomotive, and CMV as described above (at the State-county-SCC-pollutant level of detail).
(b) Detailed inventory data (both before and after controls) for these same emission sources for 1996, 2010, 2015, and 2020 were obtained from the EPA's Clean Air Interstate Rule (CAIR) Technical Support Document (which can be found at http://www.epa.gov/cair/pdfs/finaltech01.pdf). Using these data, combined growth and control factors for the period 2002-2009 and 2002-2018 were estimated using straight line interpolation between 1996 and 2010 (for 2009) and 2015 and 2020 (for 2018). This is done at the State-county-SCC-pollutant level of detail.
(c) The EPA growth and control data are matched against the 2002 VISTAS base year data using State-county-SCC-pollutant as the matc h key. Ideally, there would be a one-to-one match and the process would end at this point. Unfortunately, actual match results were not always ideal, so additional matching criteria were required. For subsequent reference, this initial (highest resolution) matching criterion is denoted as the “CAIR-Primary” criterion.
(d) A second matching criterion is applied that utilizes a similar, but higher-level SCC (lower resolution) matching approach. For example, SCC 2275020000 (commercial aircraft) in the 2002 base year inventory data would be matched with SCC 2275000000 (all aircraft) in the CAIR data. This criterion is applied to records in the 2002 base year emissions file that are not matched using the “CAIR-Primary” criterion, and is also performed at the State-county-SCC-pollutant level of detail. For subsequent reference, this is denoted as the “CAIR-Secondary” criterion. At the end of this process, a number of unmatched records remained, so a third level matching criterion was required.
(e) In the third matching step, the most frequently used SCC in the EPA CAIR files for each of the aircraft, locomotive, and commercial marine sectors was averaged at the State level to produce a “default” State and pollutant-specific growth and control factor for the sector. The resulting factor is used as a “default” growth factor for all unmatched county-SCC-pollutant level data in each State. In effect, State-specific growth data are applied to county level data for which an explicit match between the VISTAS 2002 base year data and EPA CAIR data could not be developed. The default growth and controlDocumentation of the Base G 2002 Base Year, 2009 and 2018, Emission Inventories for VISTAS

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### SCCs are 2275020000 (commercial aircraft) for the aircraft sector, 2280002000 (commercial marine diesel total) for the CMV sector, and 2285002000 (railroad equipment diesel total) for the locomotive sector. Matches made using this criterion are denoted as “CAIR-Tertiary” matches.
(f) According to EPA documentation, the CAIR baseline emissions include the impacts of the (then proposed) Tier 4 (T4) non-road diesel rulemaking, which implements a low sulfur fuel requirement that affects both future CMV and locomotive emissions. However, the impacts of this rule were originally intended to be excluded from the initial VISTAS 2018 forecast, which was to include only “on-the-books” controls. (The T4 rule was finalized subsequent to the development of the preliminary 2018 inventory in March of 2004.) Given its final status, T4 impacts were moved into the “on the books” inventory for non-road equipment. In addition, since there are no other proposed rules affecting the non-road sector between 2002 and 2018, there is no difference between the 2018 “on the books” and 2018 “on the way” inventories for the sector; so that only a single forecast inventory (for each evaluati on year) was developed. Nevertheless, since the algorithms developed to produce the VISTAS forecasts were developed when there was a distinction between the “on the books” and “on the way” inventories, the distinct algorithms used to produce the two inventories have been maintained even though the conceptual distinctions have been lost. This approach was taken for two reasons. First, it allowed the previously developed algorithms to be utilized without change. Second, it allowed for separate treatment of the T4 emissions impact which was important as those impacts changed between the proposed and final T4 rules. Thus, previous EPA inventories that include the proposed T4 impacts would not be accurate. Therefore, the procedural discussion continues to reflect the distinctions between non-T4 and T4 emissions, as these distinctions continue to be intrinsically important to the forecasting process. Therefore, a second set of EPA CA IR files that excluded the Tier 4 diesel impacts was obtained and the same matching exercise described above in steps (b) through (e) was performed using these “No T4” files. It is important to note that the matching exercise described in steps (b) through (e) cannot simply be replaced because the “No T4” files obtained from the EPA include only those SCCs specifically affected by the T4 rule (i.e., diesel CMV and locomotives). So in effect, the matching exercise was augmented (rather than replaced) with an additional three criteria analogous to those described in steps (c) through (e), and these are denoted as the “No T4-Primary,” “No T4-Secondary,” and “No T4-Tertiary” criteria. Because they exclude the impacts of the proposed T4 rule, matches using the “No T4” criteria supersede matches made using the basic CAIR criteria (as described in steps (c) through (e) above).Documentation of the Base G 2002 Base Year, 2009 and 2018, Emission Inventories for VISTAS

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### (g) The CAIR matching criteria were overridden for any record for which States provided local growth data. Only North Carolina provided these forecasts, as that State has provided specific growth factors for airport emissions in four counties. Because the provided data were based on forecasted changes in landings and takeoffs at major North Carolina airports, the factors were applied only to commercial (SCC 2275020000) and air taxi (SCC 2275060000) emissions. Emissions forecasts for military and general aviation aircraft operations, as well as all aircraft operations in counties other than the four identified in the North Carolina growth factor submission, continued to utilize the growth factors developed according to steps (b) through (f) above. Table 2.3-7 presents the locally generated growth factors applied in North Carolina.
Table 2.3-7 Locally Generated Growth Factors for North Carolina

FIP 2009 Factor 2018 Factor
37067 0.71 0.84
37081 0.97 0.89
37119 1.15 1.01
37183 0.88 0.81

Note: Growth factor = Year Emissions/2002 Emissions. Under CAIR approach, 2009 = 1.16 to 1.17 for all 4 counties. Under CAIR approach, 2018 = 1.36 to 1.37 for all 4 counties.



### (h) Using this approach, each State-county-SCC-pollutant was assigned a combined growth and control factor using the EPA CAIR forecast or locally provided data. The 22,838 data records for aircraft, locomotives, and CMV in the 2002 revised base year emissions file were assigned growth factors in accordance with the following breakdown:
48 records matched State-provided growth factors, 4,179 records matched using the CAIR-Primary criterion, 240 records matched using the CAIR-Secondary criterion, 7,463 records matched using the CAIR-Tertiary criterion, 720 records matched using the No T4-Primary criterion, 3,858 records matched using the No T4-Secondary criterion, and 6,330 records matched using the No T4-Tertiary criterion.
(i) Finally, the impacts of the T4 rule as adopted were applied to the grown “non T4” emission estimates. The actual T4 emission standards do not affect aircraft, locomotive, or CMV directly, but associated diesel fuel sulfur requirements do affect locomotives and CMV. Lower fuel sulfur content affects both SO 2 

### and PM emissions. Expected fuel sulfurDocumentation of the Base G 2002 Base Year, 2009 and 2018, Emission Inventories for VISTAS

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### contents were obtained for each evaluation year from the EPA technical support document for the final T4 rule ( Final Regulatory Analysis: Control of Emissions from Non-road Diesel Engines , EPA420-R-04-007, May 2004). According to that document, the average diesel fuel sulfur content for locomotives and CMV is expected to be 408 ppmW in 2009 and 56 ppmW in 2018. These compare to expected non-T4 fuel sulfur levels of 2599 ppmW in 2009 and 2336 ppmW in 2018. Table 2.3-8 uses calculated emissions estimates for base and T4 control scenarios to estimate emission reduction impacts.

Table 2.3-8 Estimated Emission Reduc tion Impacts based on T-4 Rule

2009 2018 CMV SO 2 = Non-T4 SO 2 × 0.1569 0.0241 Locomotive SO 2 = Non-T4 SO 2 × 0.1569 0.0241 CMV PM = Non-T4 PM × 0.8962 0.8762 Locomotive PM = Non-T4 PM × 0.8117 0.7734



### However, since the diesel fuel sulfur content assumed for the 2002 VISTAS base year inventory, upon which both the 2009 and 2018 inventories were based, is 2500 ppmW, a small adjustment to the emission reduction multipliers calculated from the T4 rule is appropriate since they are measured relative to modestly different sulfur contents (2599 ppmW for 2009 and 2336 ppmW for 2018). Correcting for these modest differences produces the emission reduction impact estimates relative to forecasts based on the VISTAS 2002 inventory shown in Table 2.3-9.

Table 2.3-9 Estimated Emission Reduction Impacts Relative to VISTAS 2002 Base Year Values

2009 2018 CMV SO 2 = Non-T4 SO 2 × 0.1632 0.0225 Locomotive SO 2 = Non-T4 SO 2 × 0.1632 0.0225 CMV PM = Non-T4 PM × 0.9004 0.8685 Locomotive PM = Non-T4 PM × 0.8187 0.7610



### These factors were applied directly to the non-T4 emission forecasts to produce the final VISTAS 2009 and 2018 emissions inventories for aircraft, locomotive, and CMV.
The only exception is for Palm Beach County, Florida, where CMV emissions are reported as “all fuels” rather than separately by residual and diesel fuel components. To estimate T4 impacts in Palm Beach County, the ratio of diesel CMV emissions to totalDocumentation of the Base G 2002 Base Year, 2009 and 2018, Emission Inventories for VISTAS

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### CMV emissions in the remainder of Florida was calculated and the T4 impact estimates for Palm Beach County were adjusted to reflect that ratio. Table 2.3-10 shows the calculated diesel CMV ratios.

Table 2.3-10 Diesel CMV Adjustment Ratios for Palm Beach County, FL

GROWTH BASIS SO 2 PM 2009 (1996, 2020 Growth Basis) 0.2410 0.7861 2009 (1996, 2010, 2015, and 2020 Growth Basis) 0.1279 0.7875 2018 (1996, 2020 Growth Basis) 0.2432 0.7925 2018 (1996, 2010, 2015, and 2020 Growth Basis) 0.2624 0.7918
The differences between the growth bases are discussed in detail below.



### Combining these ratios with the T4 impact estimates for diesel engines, as presented above, yields the following impact adjustment factors for Palm Beach County:
Table 2.3-11 Overall Adjustment Factors for Palm Beach County, FL

GROWTH BASIS

2009 SO 2 (19, 20 Growth Basis) 0.7894 [0.1632×0.2410+(1-0.2410)]
2009 SO 2 (96, 10, 15, and 20 Growth Basis) 0.8930 [0.1632×0.1279+(1-0.1279)]
2018 SO 2 (96, 20 Growth Basis) 0.7623 [0.0225×0.2432+(1-0.2432)]
2018 SO 2 (96, 10, 15, and 20 Growth Basis) 0.7436 [0.0225×0.2624+(1-0.2624)] 2009 PM (19, 20 Growth Basis) 0.9217 [0.9004×0.7861+(1-0.7861)] 2009 PM (96, 10, 15, and 20 Growth Basis) 0.9216 [0.9004×0.7875+(1-0.7875)] 2018 PM (96, 20 Growth Basis) 0.8958 [0.8685×0.7925+(1-0.7925)] 2018 PM (96, 10, 15, and 20 Growth Basis) 0.8959 [0.8685×0.7918+(1-0.7918)]
The differences between the growth bases are discussed in detail below.



### Utilizing this approach, emission inventory fo recasts for both 2009 and 2018 were developed. As indicated in step (b) above, basic growth factor s were developed using EP A CAIR inventory data for 1996, 2010, 2015, and 2020. From these data, equiva lent EPA CAIR inventories for 2002 and 2009 were developed through linear interpolati on of the 1996 and 2010 inventories, while an equivalent CAIR inventory for 2018 was devel oped through linear interpolation of the 2015 and 2020 inventories. Growth factors for 2009 and 2018 were then estimated as the ratios of the CAIR 2009 and 2018 inventories to the CAIR 2002 inventory.Documentation of the Base G 2002 Base Year, 2009 and 2018, Emission Inventories for VISTAS

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### During the development of the preliminary 2018 VISTAS inventory in March 2004, this process yielded reasonable results and exhibited no particular systematic concerns. However, when the 2009 Base F inventory was developed, significant concerns related to SO 2 

### and PM were encountered. Essentially, what was revealed by th e Base F 2009 forecast was a series of apparent inconsistencies in the CAIR 2010 and 2015 emission inventories (as compared to the 1996 and 2020 CAIR inventories) that were masked during the construction of the “longer-term” 2018 inventory.
The apparent inconsistencies are best illustrated by looking at the actual data extracted from the CAIR inventory files. Note that although a limited example is being presented, the same general issue applies throughout the CAIR files. For FIP 01001 (Autauga County, Alabama) and SCC 2285002000 (Diesel Rail), the CAIR inventories indicate SO 2 

### emission estimates as shown in Table 2.3-12.

Table 2.3-12 SO 2 

### Emissions for Diesel Rail in Autauga County, AL from the CAIR Projections

YEAR TONS 1996: 15.3445
2010: 2.7271
2015: 2.8178
2020: 16.6232



### Clearly, there is a major drop in emissions between 1996 and 2010, followed by a major increase in emissions between 2015 and 2020. Several observations regarding these changes are important. First, the CAIR data were reported to exclude the T4 rule, so that the drop in emissions should be related to something other than simply a change in diesel fuel sulfur content. Second, if the T4 rule impacts were “accidentally” included in the estimates, there should be a resultant 90 percent drop in diesel sulfur between 2010 and 2015; so such inclusion is unlikely. Third, the rate of growth between 2015 and 2020 (43 percent per year compound or 97 percent
per year linear) is well beyond any reasonable expectations for rail service; and fuel sulfur content during this period is constant both with and without T4. In short, there appeared to be no rational explanation for the data, yet the same ba sic relations are observed for thousands of CAIR inventory records.
For the most part, the issue seems to be centered on SO 2 

### and PM records, which are those records primarily affected by the T4 rule. But, as noted above, there does not seem to be any pattern of consistency that would indicate that eith er inclusion or exclusion of T4 rule impacts is the underlying cause. Moreover, where they occur, the observed growth extremes generally affect both SO 2 

### and PM equally, while one would expect PM effects to be buffered if the T4 ruleDocumentation of the Base G 2002 Base Year, 2009 and 2018, Emission Inventories for VISTAS

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### was the underlying cause, since changes in diesel fuel sulfur content will only affect a fraction of PM (i.e., sulfate), while directly reducing SO 2 

### . The data presented in Figure 2.3-1 illustrates what this meant to the VISTAS forecasting process. Figure 2.3-1 depicts the same data presented above for Autauga County, Alabama, but normalized so that the interpolated 2002 CAIR em issions estimate equals unity. The “raw” CAIR data is depicted by the markers labeled A, B, C, and D. Interpolated data for 2002 and 2009, based on 1996 and 2010 CAIR data, is depicted by the markers labeled “i” and “ii.” Interpolated data for 2018, based on 2015 and 2020 CAIR data is depicted by the marker labeled “iii.” The relationship between marker “iii” and marker “i” is exactly the relationship used to construct the preliminary (e.g., pre-Base F) 2018 VISTAS invent ory (i.e., a linear growth rate equal to 0.7 percent per year). Thus, it is easy to see that although there is a major “dip and rise” between 2002 and 2018, it is essentially masked unless data for intervening years are examined. Since no intervening year was examined for the preliminary 2018 inventory, the “dip and rise” was not discovered. However, upon the development of the 2009 inventory forecast, the issue became obvious, as the marker labeled “ii” readily illustrates. In effect, the 2009 inventory reflected very low negative “growth rates” for some SCCs and pollutants relative to the 2002 inventory, while the 2018 inventory reflected very high and positive growth rates for those same SCCs and pollutants. In effect, the path between 2002 and 2018 that previously looked like the dotted line connecting markers “i” and “iii,” now looks like the solid line connecting markers “i”, “ii,” and “iii.” For reference purposes, this path is hereafter referred to as the 1996, 2010, 2015, and 2020 growth basis, since all interpolated data is based on CAIR data for those four years.
Figure 2.3-1. Impacts of the Apparent CAIR Inventory Discrepancy

0.0 0.2 0.4 0.6 0.8 1.0 1.2 1.4 1.6 1.8

1990 1995 2000 2005 2010 2015 2020 2025 

### YearEmissions 1

iii

ii i D

C B A 3 2

A,B,C,D = EPA CAIR Data. i,ii,iii = 96-10-15-20 Interpolations. 1,2,3 = 96-20 Interpolations. All indicated growth is linear. i to ii = -9.1%/yr ii to iii = 22.9%/yr i to iii = 0.7%/yr 1 to 2 to 3 = 0.3%/yrDocumentation of the Base G 2002 Base Year, 2009 and 2018, Emission Inventories for VISTAS

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### In light of the apparent discrepancies inherent in the 1996, 2010, 2015, and 2020 growth basis data and the inconsistencies its use would impart into the 2009 and 2018 VISTAS inventories, a secondary forecasting method was developed. This second method relies on the apparent consistency between the 1996 and 2020 non-T4 CAIR inventories, interpolating equivalent 2002, 2009, and 2018 inventories solely from these two inventories. In effect, the CAIR inventories for 2010 and 2015 are ignored. In Figure 2.3-1, this secondary approach is depicted by the data points that lie along the lines connecting markers A and D. Markers A and D represent the 1996 and 2020 CAIR inventories, and the markers labeled 1, 2, and 3 represent the interpolated 2002, 2009, and 2018 CAIR equivalent inventories. The growth rate between 2009 and 2002 is then equal to the ratio of the 2009 and 2002 CAIR inventories, while that between 2018 and 2002 is equal to the ratio of the 2018 and 2002 CAIR inventories. For the example data, the resulting linear growth estimate is 0.3 percent per year. For reference purposes, this path is hereafter referred to as the 1996-2020 growth basis, since all interpolated data are based on CAIR data for only those two years.
It is perhaps worth noting that the only elements of Figure 2.3-1 that have any bearing on the VISTAS inventories are the growth rates. The absolute CAIR data are of importance only in determining those rates, as all VISTAS inventor ies were developed on the basis of the VISTAS 2002 base year inventory, not any of the CAIR i nventories. So referring to Figure 2.3-1, the two growth options are summarized in Table 2.3-13.
Table 2.3-13 Growth Options based on CAIR Data

GROWTH BASIS PERCENT PER YEAR 1996, 2010, 2015, 2020 Growth Basis: -9.1% per year (linear) between 2002 and 2009 1996-2020 Growth Basis: +0.3% per year (linear) between 2002 and 2009 1996, 2010, 2015, 2020 Growth Basis: +22.9% per year (linear) between 2009 and 2018 1996-2020 Growth Basis: +0.3% per year (linear) between 2009 and 2018 1996, 2010, 2015, 2020 Growth Basis: +0.7% per year (linear) between 2002 and 2018 1996-2020 Growth Basis: +0.3% per year (linear) between 2002 and 2018



### Of course, these specific rates are applicable only to the example case (i.e., diesel rail SO 2 

### in Autauga County, Alabama), but there are thousands of additional CAIR records that are virtually identical from a growth viewpoint.
While forecast inventories for aircraft, locomotives, and CMV were developed for 2009 and 2018 using both growth methods, it was ultimately decided to utilize the 1996-2020 growth basis for Base F since it provided more reasonable growth rates for 2009. Tables 2.3-14 and 2.3-15 present a summary of each Base F inventory, while Tables 2.3-16 and 2.3-17 present the associated change in emissions for each Base F forecast inventory relative to the Base F 2002Documentation of the Base G 2002 Base Year, 2009 and 2018, Emission Inventories for VISTAS

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### base year VISTAS inventory. The larger reduction in CMV SO 2 

### emissions in 2009 and 2018 (relative to 2002) for Virginia and West Virginia is notable relative to the other VISTAS States, but this has been checked and is attributable to a high diesel contribution to total CMV SO 2 

### in the 2002 inventories for these two States.
Figures 2.3-2 through 2.3-13 graphically depict the relationships between the various Base F inventories and preliminary 2002 and 2018 projections prepared prior to Base F. There are two figures for each pollutant, the first of which presents a comparison of total VISTAS regional emission estimates for aircraft, locomotives, and CMV, and the second of which presents total VISTAS region emission estimates for locomotives only. This two figure approach is intended to provide a more robust illustration of the differences between the various inventories, as some of the differences are less distinct when viewed through overall aggregate emissions totals. All of the figures include the following emissions estimates:

• The 2002 Base F base year VISTAS emi ssions inventory (labeled as “2002”),

• The 2002 pre-Base F base year VISTAS emissions inventory (labeled as “2002 Prelim”),

• The Base F 2009 VISTAS emissions inventor y developed using growth rates derived from 1996 and 2020 EPA CAIR data (labeled as “2009”),

• The Base F 2018 VISTAS emissions inventor y developed using growth rates derived from 1996 and 2020 EPA CAIR data (labeled as “2018”), and

• The pre-Base F 2018 VISTAS emissions i nventory estimates as developed using growth rates derived from 1996, 2010, 2015, and 2020 EPA CAIR data (labeled as “2018 Prelim”).
All 12 figures generally illustrate a reduction in emissions estimates between the 2002 pre-Base F emission estimates published in February 2004 (the initial 2002 VISTAS inventory) and the 2002 Base F emission estimates. This reduction generally results from emission updates reflected in the State 2002 CERR submittals used to develop the Base F 2002 base year inventory, although the major differences in aggregate PM emission estimates are driven to a greater extent by modifications in the methodology used to estimate aircraft PM in the Base F 2002 base year inventory (as documented under the base year inventory section of this report).Documentation of the Base G 2002 Base Year, 2009 and 2018, Emission Inventories for VISTAS

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### Table 2.3-14. Base F 2009 Aircraft, Locomotive, and Non-Recreational Marine Emissions (annual tons) -- Based on Growth Using 1996 and 2020 EPA Inventories

Source State CO NO x PM 10 PM 2.5 SO 2 VOC AL 4,178 202 278 102 19 217 FL 29,258 10,316 2,812 2,756 928 4,235 GA 7,635 6,233 1,712 1,678 523 512 KY 3,075 762 207 203 73 304 MS 1,765 162 51 50 16 108 NC 6,551 1,601 436 427 153 644 SC 7,372 559 446 437 98 975 TN 8,020 3,096 824 807 268 1,050 VA 10,994 3,094 1,239 1,214 907 2,892 WV 1,312 91 28 28 9 74 Aircraft (2275)

Total 80,159 26,116 8,033 7,704 2,993 11,011 AL 1,280 8,888 872 802 2,753 768 FL 6,236 43,198 1,838 1,691 5,864 1,467 GA 1,097 7,599 317 291 974 256 KY 7,087 48,039 2,158 1,985 8,350 1,649 MS 6,074 41,437 1,821 1,676 6,587 1,415 NC 634 4,386 184 169 584 148 SC 1,133 7,796 326 300 1,012 264 TN 3,887 26,333 1,168 1,074 4,512 904 VA 1,042 2,662 312 286 61 506 WV 1,638 11,073 455 419 89 381 Commercial

Marine (2280)

Total 30,109 201,412 9,450 8,693 30,786 7,759 VA 118 299 23 21 5 50 Military Marine (2283) Total 118 299 23 21 5 50 AL 3,648 23,529 452 406 242 1,279 FL 1,052 8,905 189 170 101 382 GA 2,769 24,398 507 456 271 1,003 KY 2,264 19,597 415 374 221 819 MS 2,406 20,785 441 397 239 849 NC 1,712 14,741 313 282 167 618 SC 1,213 10,443 222 200 119 437 TN 2,745 23,924 483 435 240 984 VA 1,236 11,134 1,167 1,050 608 467 WV 1,369 12,177 251 226 135 489 Locomotives

(2285)

Total 20,412 169,635 4,440 3,995 2,343 7,328

Grand Total 130,798 397,462 21,946 20,413 36,126 26,148Documentation of the Base G 2002 Base Year, 2009 and 2018, Emission Inventories for VISTAS

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### Table 2.3-15. Base F 2018 Aircraft, Locomotive, and Non-Recreational Marine Emissions (annual tons) -- Based on Growth Using 1996 and 2020 EPA Inventories

Source State CO NO x PM 10 PM 2.5 SO 2 VOC AL 4,681 236 345 122 23 245 FL 34,178 12,147 3,312 3,246 1,093 4,976 GA 8,939 7,340 2,016 1,976 616 601 KY 3,602 898 244 239 86 357 MS 1,986 190 60 58 18 122 NC 6,728 1,454 400 392 139 615 SC 8,487 616 493 484 112 1,119 TN 9,009 3,519 939 921 309 1,187 VA 12,578 3,528 1,370 1,342 1,063 3,358 WV 1,484 106 33 33 10 85 Aircraft (2275)

Total 91,670 30,035 9,213 8,814 3,468 12,666 AL 1,388 8,464 880 809 2,715 809 FL 6,684 41,117 1,853 1,705 6,248 1,543 GA 1,174 7,246 319 293 976 269 KY 7,703 45,174 2,199 2,023 8,383 1,752 MS 6,571 39,129 1,850 1,702 6,556 1,498 NC 679 4,179 185 170 596 155 SC 1,217 7,406 329 303 1,027 278 TN 4,225 24,763 1,190 1,095 4,808 960 VA 1,133 2,517 314 289 9 537 WV 1,781 10,412 459 422 13 404 Commercial

Marine (2280)

Total 32,554 190,407 9,578 8,811 31,330 8,205 VA 128 282 23 21 1 53 Military Marine (2283) Total 128 282 23 21 1 53 AL 3,850 19,917 381 343 34 1,183 FL 1,110 7,538 159 143 14 353 GA 2,917 21,395 427 385 38 932 KY 2,389 16,751 352 317 31 757 MS 2,540 17,594 372 335 34 785 NC 1,807 12,478 264 237 24 571 SC 1,280 8,840 187 168 17 404 TN 2,897 21,735 407 367 34 910 VA 1,300 10,173 983 885 86 436 WV 1,444 10,831 212 190 19 453 Locomotives

(2285)

Total 21,534 147,252 3,744 3,368 333 6,785

Grand Total 145,885 367,975 22,557 21,015 35,132 27,709Documentation of the Base G 2002 Base Year, 2009 and 2018, Emission Inventories for VISTAS

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### Table 2.3-16. Change in Emissions between 2009 and 2002 Base F Inventories (Based on Growth Using 1996 and 2020 EPA Inventories)

Source State CO NO x PM 10 PM 2.5 SO 2 VOC AL +10% +15% +23% +18% +16% +11% FL +15% +16% +16% +16% +16% +16% GA +15% +16% +16% +16% +16% +16% KY +15% +16% +16% +16% +16% +16% MS +11% +16% +15% +15% +16% +12% NC +8% +3% +4% +4% +3% +5% SC +13% +9% +9% +9% +12% +13% TN +11% +12% +12% +12% +14% +11% VA +13% +12% +9% +9% +15% +14% WV +11% +16% +15% +15% +16% +12% Aircraft (2275)

Total +13% +14% +14% +13% +15% +14% AL +7% -4% -5% -5% -18% +4% FL +6% -4% -5% -5% -12% +4% GA +6% -3% -5% -5% -17% +4% KY +7% -4% -4% -4% -13% +5% MS +7% -4% -4% -4% -15% +5% NC +6% -4% -5% -5% -15% +4% SC +6% -4% -5% -5% -16% +4% TN +7% -4% -4% -4% -9% +5% VA +7% -4% -7% -7% -83% +5% WV +7% -4% -7% -7% -83% +5% Commercial

Marine (2280)

Total +7% -4% -5% -5% -15% +5% VA +7% -4% -7% -7% -83% +5% Military Marine (2283) Total +7% -4% -7% -7% -83% +5% AL +5% -11% -24% -24% -83% -6% FL +5% -11% -24% -24% -83% -6% GA +4% -9% -24% -24% -83% -5% KY +5% -10% -23% -23% -83% -6% MS +5% -11% -24% -24% -83% -6% NC +5% -11% -24% -24% -83% -6% SC +5% -11% -24% -24% -83% -6% TN +5% -7% -24% -24% -83% -6% VA +4% -6% -24% -24% -83% -5% WV +4% -8% -24% -24% -83% -5% Locomotives

(2285)

Total +4% -9% -24% -24% -83% -5%

Grand Total +10% -5% -4% -4% -32% +5%Documentation of the Base G 2002 Base Year, 2009 and 2018, Emission Inventories for VISTAS

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### Table 2.3-17. Change in Emissions between 2018 and 2002 Base F Inventories (Based on Growth Using 1996 and 2020 EPA Inventories)

Source State CO NO x PM 10 PM 2.5 SO 2 VOC AL +24% +35% +53% +41% +36% +25% FL +34% +37% +37% +37% +37% +36% GA +35% +37% +37% +37% +37% +36% KY +35% +37% +37% +37% +37% +36% MS +25% +36% +35% +35% +36% +27% NC +10% -6% -5% -5% -6% 0% SC +30% +20% +21% +21% +27% +30% TN +24% +27% +28% +28% +31% +26% VA +29% +28% +20% +20% +35% +33% WV +26% +36% +35% +35% +36% +28% Aircraft (2275)

Total +29% +31% +30% +30% +33% +31% AL +16% -8% -4% -4% -19% +10% FL +14% -8% -4% -4% -7% +9% GA +13% -8% -5% -5% -17% +9% KY +17% -10% -2% -2% -13% +12% MS +16% -9% -3% -3% -15% +11% NC +13% -8% -4% -4% -14% +9% SC +14% -9% -4% -4% -15% +10% TN +17% -10% -2% -2% -3% +12% VA +17% -9% -6% -6% -98% +11% WV +17% -10% -6% -6% -98% +12% Commercial

Marine (2280)

Total +15% -9% -3% -3% -14% +11% VA +17% -10% -6% -6% -98% +12% Military Marine (2283) Total +17% -10% -6% -6% -98% +12% AL +10% -24% -36% -36% -98% -13% FL +10% -24% -36% -36% -98% -13% GA +10% -20% -36% -36% -98% -12% KY +10% -23% -35% -35% -98% -13% MS +10% -24% -36% -36% -98% -13% NC +10% -24% -36% -36% -98% -13% SC +10% -24% -36% -36% -98% -13% TN +10% -15% -36% -36% -98% -13% VA +10% -14% -36% -36% -98% -11% WV +10% -18% -36% -36% -98% -12% Locomotives

(2285)

Total +10% -21% -36% -36% -98% -12%

Grand Total +23% -12% -1% -1% -34% +11%Documentation of the Base G 2002 Base Year, 2009 and 2018, Emission Inventories for VISTAS

MACTEC, Inc. 168 118,739 130,798 145,885

129,659 159,122

0 20,000 40,000 60,000 80,000 100,000 120,000 140,000 160,000 180,000

2002 2009 2018 2002 Prelim 2018 Prelim T
o n s

p e r

Y
e a r

19,540 20,412 21,534 21,980 23,849

0 5,000 10,000 15,000 20,000 25,000 30,000

2002 2009 2018 2002 Prelim 2018 Prelim T
o n s

p e r

Y
e a r 

### Figure 2.3-2. Total Aircraft, Locomotive, and CMV CO Emissions (Base F)

Figure 2.3-3. Locomotive CO Emissions (Base F)Documentation of the Base G 2002 Base Year, 2009 and 2018, Emission Inventories for VISTAS

MACTEC, Inc. 169 420,228 397,462 367,975 455,067

395,049

0 50,000 100,000 150,000 200,000 250,000 300,000 350,000 400,000 450,000 500,000

2002 2009 2018 2002 Prelim 2018 Prelim T
o n s

p e r

Y
e a r

187,044 169,635

147,252 211,588

167,783

0 50,000 100,000 150,000 200,000 250,000

2002 2009 2018 2002 Prelim 2018 Prelim T
o n s

p e r

Y
e a r 

### Figure 2.3-4. Total Aircraft, Locomotive, and CMV NO x 

### Emissions (Base F)

Figure 2.3-5. Locomotive NO x 

### Emissions (Base F)Documentation of the Base G 2002 Base Year, 2009 and 2018, Emission Inventories for VISTAS

MACTEC, Inc. 170 22,823 21,946 22,557 100,452 128,715

0 20,000 40,000 60,000 80,000 100,000 120,000 140,000

2002 2009 2018 2002 Prelim 2018 Prelim T
o n s

p e r

Y
e a r

5,815

4,440

3,744 6,118

3,947

0 1,000 2,000 3,000 4,000 5,000 6,000 7,000

2002 2009 2018 2002 Prelim 2018 Prelim T
o n s

p e r

Y
e a r 

### Figure 2.3-6. Total Aircraft, Locomotive, and CMV PM 10 

### Emissions (Base F)

Figure 2.3-7. Locomotive PM 10 

### Emissions (Base F)Documentation of the Base G 2002 Base Year, 2009 and 2018, Emission Inventories for VISTAS

MACTEC, Inc. 171 5,232

3,995

3,368 5,505

3,552

0 1,000 2,000 3,000 4,000 5,000 6,000

2002 2009 2018 2002 Prelim 2018 Prelim T
o n s

p e r

Y
e a r 21,170 20,413 21,015 73,099 92,207

0 10,000 20,000 30,000 40,000 50,000 60,000 70,000 80,000 90,000 100,000

2002 2009 2018 2002 Prelim 2018 Prelim T
o n s

p e r

Y
e a r 

### Figure 2.3-8. Total Aircraft, Locomotive, and CMV PM 2.5 

### Emissions (Base F)

Figure 2.3-9. Locomotive PM 2.5 

### Emissions (Base F)Documentation of the Base G 2002 Base Year, 2009 and 2018, Emission Inventories for VISTAS

MACTEC, Inc. 172 14,022

2,343

333 14,947

1,553

0 2,000 4,000 6,000 8,000 10,000 12,000 14,000 16,000

2002 2009 2018 2002 Prelim 2018 Prelim T
o n s

p e r

Y
e a r 52,931

36,126 35,132 57,062

41,284

0 10,000 20,000 30,000 40,000 50,000 60,000

2002 2009 2018 2002 Prelim 2018 Prelim T
o n s

p e r

Y
e a r 

### Figure 2.3-10. Total Aircraft, Locomotive, and CMV SO 2 

### Emissions (Base F)

Figure 2.3-11. Locomotive SO 2 

### Emissions (Base F)Documentation of the Base G 2002 Base Year, 2009 and 2018, Emission Inventories for VISTAS

MACTEC, Inc. 173 7,750 7,328 6,785 8,738

7,544

0 1,000 2,000 3,000 4,000 5,000 6,000 7,000 8,000 9,000 10,000

2002 2009 2018 2002 Prelim 2018 Prelim T
o n s

p e r

Y
e a r 24,881 26,148 27,709

26,877 29,228

22,000 23,000 24,000 25,000 26,000 27,000 28,000 29,000 30,000

2002 2009 2018 2002 Prelim 2018 Prelim T
o n s

p e r

Y
e a r 

### Figure 2.3-12. Total Aircraft, Locomotive, and CMV VOC Emissions (Base F)

Figure 2.3-13. Locomotive VOC Emissions (Base F)Documentation of the Base G 2002 Base Year, 2009 and 2018, Emission Inventories for VISTAS

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### Base G Revisions:
Table 2.3-18 shows the Base G 2002 base year emissions for each State in the VISTAS region for aircraft, locomotives and CMV. Although some of these data are updated relative to those used as the basis of the Base F emissions forecasts, the methodology used to develop 2009 and 2018 emissions forecasts for aircraft, locomotives, and CMV for Base G is identical to that used for Base F (as documented above). The only exceptions are as follows:
(a) As indicated in the discussion of the Base F forecasts, the CAIR (growth rate) matching criteria were overridden for any record for which States provided local growth data. For Base F, only North Carolina provided such data. However, for Base G, Kentucky regulators provided growth data for aircraft emissions associated with Cincinnati/Northern Kentucky Internationa l Airport (located in Boone County, Kentucky). These data were applied to all pollutants and all aircraft types (i.e., military aircraft (SCC 2275001000), commercial aircraft (SCC 2275020000), general aviation aircraft (SCC 2275050000), and air taxi airc raft (SCC 2275060000)). Emissions forecasts for all aircraft operations in counties other than Boone continued to utilize the growth factors developed according to the CAIR matching criteria. Table 2.3-19 presents the locally generated growth factors applied in Kentucky. It should be recognized that although the locally provided growth factors presented in the table are significantly greater than those that would apply under the CAIR matching criteria, this is to be expected as local regulators noted a very significant decline in activity at the Cincinnati/Northern Kentucky International Airport in 2002 (relative to activity in preceding years). Moreover, this downward spike seems to have been alleviated since 2002, so that the provided growth factors represent not only “routine” growth expected between 2002 and the two forecast years, but growth required to offset the temporary decline observed in 2002.Documentation of the Base G 2002 Base Year, 2009 and 2018, Emission Inventories for VISTAS

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### Table 2.3-18. Base G 2002 Aircraft, Locomotive, and Non-Recreational Marine Emissions (annual tons)

Source State CO NO x PM 10 PM 2.5 SO 2 VOC AL 5,595 185 238 99 18 276 FL 25,431 8,891 2,424 2,375 800 3,658 GA 6,620 5,372 1,475 1,446 451 443 KY 5,577 925 251 246 88 397 MS 1,593 140 44 43 13 96 NC 6,088 1,548 419 411 148 613 SC 6,505 515 409 401 88 863 TN 7,251 2,766 734 719 235 943 VA 11,873 3,885 2,010 1,970 272 2,825 WV 1,178 78 25 24 8 66 Aircraft (2275)

Total 77,712 24,305 8,029 7,734 2,121 10,179 AL 1,196 9,218 917 844 3,337 737 FL 5,888 44,817 1,936 1,781 6,683 1,409 GA 1,038 7,875 334 307 1,173 246 KY 6,607 50,267 2,246 2,066 9,608 1,569 MS 5,688 43,233 1,903 1,751 7,719 1,351 NC 599 4,547 193 178 690 142 SC 1,067 8,100 343 316 1,205 253 TN 3,624 27,555 1,217 1,120 4,974 860 VA 972 2,775 334 307 359 483 WV 1,528 11,586 487 448 525 362 Commercial

Marine (2280)

Total 28,207 209,972 9,911 9,118 36,275 7,413 VA 110 313 25 23 27 48 Military Marine (2283) Total 110 313 25 23 27 48 AL 3,518 26,623 592 533 1,446 1,365 FL 1,006 9,969 247 222 605 404 GA 2,654 26,733 664 598 1,622 1,059 KY 2,166 21,811 542 488 1,321 867 MS 2,302 23,267 578 520 1,429 899 NC 1,638 16,502 410 369 1,001 654 SC 1,160 11,690 291 261 710 462 TN 2,626 25,627 633 570 1,439 1,041 VA 1,186 11,882 1,529 1,375 3,641 492 WV 1,311 13,224 329 296 808 517 Locomotives

(2285)

Total 19,568 187,328 5,815 5,232 14,022 7,761

Grand Total 125,597 421,918 23,780 22,107 52,444 25,401Documentation of the Base G 2002 Base Year, 2009 and 2018, Emission Inventories for VISTAS

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### Table 2.3-19 Locally Generated Growth Factors for Kentucky

FIP 2009 Factor 2018 Factor
21015 1.31 1.81

Note: Growth factor = Year Emissions/2002 Emissions. Under CAIR approach, 2009 = 0.99 to 1.17. Under CAIR approach, 2018 = 0.97 to 1.40.



### (b) Because of the additional emissions records added in Alabama, as discussed in the Base G 2002 base year inventory section of this report, the total number of emissions records in the Base G 2009 and 2018 forecasts increased to 23,042 (as compared to 22,838 for Base F). The 23,042 data records for aircraft, locomotives, and CMV were assigned growth factors in accordance with the following breakdown:
72 records matched State-provided growth factors, 4,287 records matched using the CAIR-Primary criterion, 240 records matched using the CAIR-Secondary criterion, 7,511 records matched using the CAIR-Tertiary criterion, 720 records matched using the No T4-Primary criterion, 3,858 records matched using the No T4-Secondary criterion, and 6,354 records matched using the No T4-Tertiary criterion.
Tables 2.3-20 and 2.3-21 present a summary of the resulting Base G 2009 and 2018 inventories, while Tables 2.3-22 and 2.3-23 present the associated change in emissions for each forecast inventory relative to the Base G 2002 base year VISTAS. As was the case with Base F, the larger reduction in CMV SO 2 

### emissions in 2009 and 2018 (relative to 2002) for Virginia and West Virginia is notable relative to the other VISTAS States, but is attributable to a high diesel contribution to total CMV SO 2 

### in the 2002 inventories for these two States.
Figures 2.3-14 through 2.3-25 graphically depict the relationships between the various inventories, as revised through Base G. There are two figures for each pollutant, the first of which presents a comparison of total VISTAS regional emission estimates for aircraft, locomotives, and CMV, and the second of which presents total VISTAS region emission estimates for locomotives only. This two figure approach is intended to provide a more robust illustration of the differences between the various inventories, as some of the differences are less distinct when viewed through overall aggregate emissions totals. All of the figures include the following emissions estimates:Documentation of the Base G 2002 Base Year, 2009 and 2018, Emission Inventories for VISTAS

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### • The Base G 2002 base year VISTAS emi ssions inventory (labeled as “2002”),

• The pre-Base F 2002 base year VISTAS emissions inventory (labeled as “2002 Prelim”),

• The Base G 2009 VISTAS emissions inventor y developed using growth rates derived from 1996 and 2020 EPA CAIR data (labeled as “2009”),

• The Base G 2018 VISTAS emissions inventor y developed using growth rates derived from 1996 and 2020 EPA CAIR data (labeled as “2018”), and

• The pre-Base F 2018 VISTAS emissions inve ntory estimates developed using growth rates derived from 1996, 2010, 2015, and 2020 EPA CAIR data (labeled as “2018 Prelim”).
All 12 figures generally illustrate a reduction in emissions estimates between the pre-Base F 2002 emission estimates published in February 2004 and the Base G 2002 base year emission estimates. This reduction generally results from emission updates reflected in the Base F State CERR submittals, although the major differences in aggregate PM emission estimates are driven to a greater extent by modifications in the methodology used to estimate aircraft PM in the Base F revisions to the 2002 Base F base year invent ory (as documented under the base year inventory section of this report).Documentation of the Base G 2002 Base Year, 2009 and 2018, Emission Inventories for VISTAS

MACTEC, Inc. 178 

### Table 2.3-20. Base G 2009 Aircraft, Locomotive, and Non-Recreational Marine Emissions (annual tons) -- Based on Growth Using 1996 and 2020 EPA Inventories

Source State CO NO x PM 10 PM 2.5 SO 2 VOC AL 6,265 213 292 116 21 309 FL 29,258 10,316 2,812 2,756 928 4,235 GA 7,635 6,233 1,712 1,678 523 512 KY 6,959 1,135 307 301 108 487 MS 1,765 162 51 50 16 108 NC 6,991 1,795 486 477 171 709 SC 7,372 559 446 437 98 975 TN 8,020 3,096 824 807 268 1,050 VA 13,141 4,244 2,124 2,082 306 3,153 WV 1,312 91 28 28 9 74 Aircraft (2275)

Total 88,716 27,844 9,083 8,732 2,447 11,612 AL 1,280 8,888 872 802 2,753 768 FL 6,236 43,198 1,838 1,691 5,864 1,467 GA 1,097 7,599 317 291 974 256 KY 7,087 48,039 2,158 1,985 8,350 1,649 MS 6,074 41,437 1,821 1,676 6,587 1,415 NC 634 4,386 184 169 584 148 SC 1,133 7,796 326 300 1,012 264 TN 3,887 26,333 1,168 1,074 4,512 904 VA 1,042 2,662 312 286 61 506 WV 1,638 11,073 455 419 89 381 Commercial

Marine (2280)

Total 30,108 201,412 9,450 8,693 30,786 7,759 VA 118 299 23 21 5 50 Military Marine (2283) Total 118 299 23 21 5 50 AL 3,677 23,783 452 406 242 1,289 FL 1,052 8,905 189 170 101 382 GA 2,769 24,398 507 456 271 1,003 KY 2,264 19,597 415 374 221 819 MS 2,406 20,785 441 397 239 849 NC 1,690 14,662 311 279 165 613 SC 1,213 10,443 222 200 119 437 TN 2,745 23,924 483 435 240 984 VA 1,236 11,134 1,167 1,050 608 467 WV 1,369 12,177 251 226 135 489 Locomotives

(2285)

Total 20,420 169,808 4,437 3,993 2,341 7,333

Grand Total 139,362 399,364 22,994 21,440 35,578 26,754Documentation of the Base G 2002 Base Year, 2009 and 2018, Emission Inventories for VISTAS

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### Table 2.3-21. Base G 2018 Aircraft, Locomotive, and Non-Recreational Marine Emissions (annual tons) -- Based on Growth Using 1996 and 2020 EPA Inventories

Source State CO NO x PM 10 PM 2.5 SO 2 VOC AL 7,126 249 361 139 24 352 FL 34,178 12,147 3,312 3,246 1,093 4,976 GA 8,939 7,340 2,016 1,976 616 601 KY 9,078 1,446 391 383 138 623 MS 1,986 190 60 58 18 122 NC 8,150 2,114 572 561 202 831 SC 8,487 616 493 484 112 1,119 TN 9,009 3,519 939 921 309 1,187 VA 14,770 4,706 2,271 2,226 349 3,574 WV 1,484 106 33 33 10 85 Aircraft (2275)

Total 103,206 32,435 10,450 10,027 2,871 13,472 AL 1,388 8,464 880 809 2,715 809 FL 6,684 41,117 1,853 1,705 6,248 1,543 GA 1,174 7,246 319 293 976 269 KY 7,703 45,174 2,199 2,023 8,383 1,752 MS 6,571 39,129 1,850 1,702 6,556 1,498 NC 678 4,179 185 170 596 155 SC 1,217 7,406 329 303 1,027 278 TN 4,225 24,763 1,190 1,095 4,808 960 VA 1,133 2,517 314 289 9 537 WV 1,781 10,412 459 422 13 404 Commercial

Marine (2280)

Total 32,554 190,407 9,578 8,811 31,330 8,205 VA 128 282 23 21 1 53 Military Marine (2283) Total 128 282 23 21 1 53 AL 3,881 20,131 381 343 34 1,192 FL 1,110 7,538 159 143 14 353 GA 2,917 21,395 427 385 38 932 KY 2,389 16,751 352 317 31 757 MS 2,540 17,594 372 335 34 785 NC 1,782 12,539 263 237 23 570 SC 1,280 8,840 187 168 17 404 TN 2,897 21,735 407 367 34 910 VA 1,300 10,173 983 885 86 436 WV 1,444 10,831 212 190 19 453 Locomotives

(2285)

Total 21,539 147,527 3,743 3,368 332 6,792

Grand Total 157,427 370,651 23,794 22,227 34,534 28,522Documentation of the Base G 2002 Base Year, 2009 and 2018, Emission Inventories for VISTAS

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### Table 2.3-22. Change in Emissions between 2009 Base G and 2002 Base F Inventories (Based on Growth Using 1996 and 2020 EPA Inventories)

Source State CO NO x PM 10 PM 2.5 SO 2 VOC AL +12% +15% +23% +18% +16% +12% FL +15% +16% +16% +16% +16% +16% GA +15% +16% +16% +16% +16% +16% KY +25% +23% +23% +23% +23% +23% MS +11% +16% +15% +15% +16% +12% NC +15% +16% +16% +16% +16% +16% SC +13% +9% +9% +9% +12% +13% TN +11% +12% +12% +12% +14% +11% VA +11% +9% +6% +6% +12% +12% WV +11% +16% +15% +15% +16% +12% Aircraft (2275)

Total +14% +15% +13% +13% +15% +14% AL +7% -4% -5% -5% -18% +4% FL +6% -4% -5% -5% -12% +4% GA +6% -3% -5% -5% -17% +4% KY +7% -4% -4% -4% -13% +5% MS +7% -4% -4% -4% -15% +5% NC +6% -4% -5% -5% -15% +4% SC +6% -4% -5% -5% -16% +4% TN +7% -4% -4% -4% -9% +5% VA +7% -4% -7% -7% -83% +5% WV +7% -4% -7% -7% -83% +5% Commercial

Marine (2280)

Total +7% -4% -5% -5% -15% +5% VA +7% -4% -7% -7% -83% +5% Military Marine (2283) Total +7% -4% -7% -7% -83% +5% AL +5% -11% -24% -24% -83% -6% FL +5% -11% -24% -24% -83% -6% GA +4% -9% -24% -24% -83% -5% KY +5% -10% -23% -23% -83% -6% MS +5% -11% -24% -24% -83% -6% NC +3% -11% -24% -24% -83% -6% SC +5% -11% -24% -24% -83% -6% TN +5% -7% -24% -24% -83% -6% VA +4% -6% -24% -24% -83% -5% WV +4% -8% -24% -24% -83% -5% Locomotives

(2285)

Total +4% -9% -24% -24% -83% -6%

Grand Total +11% -5% -3% -3% -32% +5%Documentation of the Base G 2002 Base Year, 2009 and 2018, Emission Inventories for VISTAS

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### Table 2.3-23. Change in Emissions between 2018 Base G and 2002 Base F Inventories (Based on Growth Using 1996 and 2020 EPA Inventories)

Source State CO NO x PM 10 PM 2.5 SO 2 VOC AL +27% +35% +52% +41% +36% +28% FL +34% +37% +37% +37% +37% +36% GA +35% +37% +37% +37% +37% +36% KY +63% +56% +56% +56% +56% +57% MS +25% +36% +35% +35% +36% +27% NC +34% +37% +36% +36% +37% +36% SC +30% +20% +21% +21% +27% +30% TN +24% +27% +28% +28% +31% +26% VA +24% +21% +13% +13% +28% +27% WV +26% +36% +35% +35% +36% +28% Aircraft (2275)

Total +33% +33% +30% +30% +35% +32% AL +16% -8% -4% -4% -19% +10% FL +14% -8% -4% -4% -7% +9% GA +13% -8% -5% -5% -17% +9% KY +17% -10% -2% -2% -13% +12% MS +16% -9% -3% -3% -15% +11% NC +13% -8% -4% -4% -14% +9% SC +14% -9% -4% -4% -15% +10% TN +17% -10% -2% -2% -3% +12% VA +17% -9% -6% -6% -98% +11% WV +17% -10% -6% -6% -98% +12% Commercial

Marine (2280)

Total +15% -9% -3% -3% -14% +11% VA +17% -10% -6% -6% -98% +12% Military Marine (2283) Total +17% -10% -6% -6% -98% +12% AL +10% -24% -36% -36% -98% -13% FL +10% -24% -36% -36% -98% -13% GA +10% -20% -36% -36% -98% -12% KY +10% -23% -35% -35% -98% -13% MS +10% -24% -36% -36% -98% -13% NC +9% -24% -36% -36% -98% -13% SC +10% -24% -36% -36% -98% -13% TN +10% -15% -36% -36% -98% -13% VA +10% -14% -36% -36% -98% -11% WV +10% -18% -36% -36% -98% -12% Locomotives

(2285)

Total +10% -21% -36% -36% -98% -12%

Grand Total +25% -12% +0% +1% -34% +12%Documentation of the Base G 2002 Base Year, 2009 and 2018, Emission Inventories for VISTAS

MACTEC, Inc. 182 125,597 139,362 157,427

129,659 159,122

0 20,000 40,000 60,000 80,000 100,000 120,000 140,000 160,000 180,000

2002 2009 2018 2002 Prelim 2018 Prelim T

o

n

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p

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19,568 20,420 21,539 21,980 23,849

0 5,000 10,000 15,000 20,000 25,000 30,000

2002 2009 2018 2002 Prelim 2018 Prelim T

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### Figure 2.3-14. Total Aircraft, Locomotive, and CMV CO Emissions (Base G)

Figure 2.3-15. Locomotive CO Emissions (Base G)Documentation of the Base G 2002 Base Year, 2009 and 2018, Emission Inventories for VISTAS

MACTEC, Inc. 183 421,918 399,364 370,651 455,067

395,049

0 50,000 100,000 150,000 200,000 250,000 300,000 350,000 400,000 450,000 500,000

2002 2009 2018 2002 Prelim 2018 Prelim T

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187,328 169,808
147,527 211,588

167,783

0 50,000 100,000 150,000 200,000 250,000

2002 2009 2018 2002 Prelim 2018 Prelim T

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### Figure 2.3-16. Total Aircraft, Locomotive, and CMV NO x 

### Emissions (Base G)

Figure 2.3-17. Locomotive NO x 

### Emissions (Base G)Documentation of the Base G 2002 Base Year, 2009 and 2018, Emission Inventories for VISTAS

MACTEC, Inc. 184 23,780 22,994 23,794 100,452 128,715

0 20,000 40,000 60,000 80,000 100,000 120,000 140,000

2002 2009 2018 2002 Prelim 2018 Prelim T

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5,815

4,437

3,743 6,118

3,947

0 1,000 2,000 3,000 4,000 5,000 6,000 7,000

2002 2009 2018 2002 Prelim 2018 Prelim T

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n

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### Figure 2.3-18. Total Aircraft, Locomotive, and CMV PM 10 

### Emissions (Base G)

Figure 2.3-19. Locomotive PM 10 

### Emissions (Base G)Documentation of the Base G 2002 Base Year, 2009 and 2018, Emission Inventories for VISTAS

MACTEC, Inc. 185 22,107 21,440 22,227 73,099 92,207

0 10,000 20,000 30,000 40,000 50,000 60,000 70,000 80,000 90,000 100,000

2002 2009 2018 2002 Prelim 2018 Prelim T

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5,232

3,993

3,368 5,505

3,552

0 1,000 2,000 3,000 4,000 5,000 6,000

2002 2009 2018 2002 Prelim 2018 Prelim T

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### Figure 2.3-20. Total Aircraft, Locomotive, and CMV PM 2.5 

### Emissions (Base G)

Figure 2.3-21. Locomotive PM 2.5 

### Emissions (Base G)Documentation of the Base G 2002 Base Year, 2009 and 2018, Emission Inventories for VISTAS

MACTEC, Inc. 186 52,444

35,578 34,534 57,062

41,284

0 10,000 20,000 30,000 40,000 50,000 60,000

2002 2009 2018 2002 Prelim 2018 Prelim T

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14,022

2,341

332 14,947

1,553

0 2,000 4,000 6,000 8,000 10,000 12,000 14,000 16,000 18,000

2002 2009 2018 2002 Prelim 2018 Prelim T

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### Figure 2.3-22. Total Aircraft, Locomotive, and CMV SO 2 

### Emissions (Base G)

Figure 2.3-23. Locomotive SO 2 

### Emissions (Base G)Documentation of the Base G 2002 Base Year, 2009 and 2018, Emission Inventories for VISTAS

MACTEC, Inc. 187 25,401 26,754 28,522 26,877 29,228

0 5,000 10,000 15,000 20,000 25,000 30,000 35,000

2002 2009 2018 2002 Prelim 2018 Prelim T

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7,761 7,333 6,792 8,738

7,544

0 1,000 2,000 3,000 4,000 5,000 6,000 7,000 8,000 9,000 10,000

2002 2009 2018 2002 Prelim 2018 Prelim T

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### Figure 2.3-24. Total Aircraft, Locomotive, and CMV VOC Emissions (Base G)

Figure 2.3-25. Locomotive VOC Emissions (Base G)Documentation of the Base G 2002 Base Year, 2009 and 2018, Emission Inventories for VISTAS

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### 2.3.4.3 Emissions from NONROAD Model Sources in Illinois, Indiana, and Ohio Base G projection inventories for 2009 and 2018 for NONROAD model sources in the states of Illinois, Indiana, and Ohio were produced using a methodology identical to that employed to develop a Base G 2002 base year inventory for the same states (as documented earlier in this report). This method consists of the extraction of a complete set of county-level input data applicable to each of the three states (in each of the two projection years) from the latest version of the EPA’s NMIM model. This includes appropriate consideration of all non-default NMIM input files generated by the Midwest Regional Planning Organization as documented earlier in the discussion of the Base G 2002 base year inve ntory. These input data were then assembled into appropriate input files for the Final NONROAD2005 model and emission estimates were produced using the same procedure employed for the VISTAS region.
Changes noted between the base year (2002) and forecast year (2009 and 2018) input data extracted from NMIM include differences in gasoline vapor pressure, gasoline sulfur content, and diesel sulfur content in most counties. All temperature data (minimum, maximum, and average daily temperatures) was constant across years.
As described in the discussion of the Base G 2002 base year inventory, counties in the three states were grouped for modeling purposes using a temperature aggregation scheme that allowed for county-specific temperature variations of no more that 2 oF from group average temperatures (for all temperature inputs). The same grouping sc heme was applied to projection year modeling, so that Illinois emissions were modeled using 12 county groups, Indiana emissions were modeled using 9 county groups, and Ohio emissions were modeled using 10 county groups. Thus, 31 iterations of NONROAD2002 were required per season per projection year, as compared to the 53 iterations per season per projection year required for the VISTAS region.
As was also described in the discussion of the Base G 2002 base year inventory, several non-default equipment population, growth, activity, seasonal distribution, and county allocation files are assigned by NMIM model inputs for these counties. As was the case for the base year inventory development, these same non-default assignments were retained for both projection inventories.

2.3.4.4 Differences between 2009/2018 Methodologically, there was no difference in the way that 2009 and 2018 emissions were calculated for non-road mobile sources. The actual value of the growth factors were different for each type of mobile source considered, but the calculation methods were identical.Documentation of the Base G 2002 Base Year, 2009 and 2018, Emission Inventories for VISTAS

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### 2.3.5 Quality Assurance steps Throughout the inventory development process, quality assurance steps were performed to ensure that no double counting of emissions occurred, to ensure that a full and complete inventory was developed for VISTAS, and to ma ke sure that projection calculations were working correctly. Quality assurance was an important component to the inventory development process and MACTEC performed the following QA steps on mobile source components of the 2009 and revised 2018 projection inventories:
1. All final files (NONROAD only) were run through EPA’s Format and Content checking software. Input data files for MOBILE and VMT growth estimates were reviewed by the corresponding SIWG and by the VISTAS Emission Inventory Technical Advisor.
2. SCC level emission summaries were prepared and evaluated to ensure that emissions were consistent and that there were no missing sources (NONROAD only).
3. Tier comparisons (by pollutant) were developed between the 2002 base year inventory and the 2009 and 2018 projecti on inventories (NONROAD only). Total VISTAS level summaries by pollutant were developed for these sources to compare Base F and Base G emission levels.
4. Data product summaries were provided to both the VISTAS Emission Inventory Technical Advisor and to the SIWG representatives for review and comment. Changes based on these comments were implemented in the files.
5. Version numbering was used for all inventory files developed. The version numbering process used a decimal system to track major and minor changes. For example, a major change would result in a version going from 1.0 to 2.0. A minor change would cause a version number to go from 1.0 to 1.1. Minor changes resulting from largely editorial changes would result in a change from 1.00 to 1.01.Documentation of the Base G 2002 Base Year, 2009 and 2018, Emission Inventories for VISTAS

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### APPENDIX A:

STATE EMISSION TOTALS BY POLLUTANT AND SECTORDocumentation of the Base G 2002 Base Year, 2009 and 2018, Emission Inventories for VISTASMACTEC, Inc.191Annual CO Emissions by Source Sector01,000,0002,000,0003,000,0004,000,0005,000,0006,000,0007,000,0008,000,000 A L F L G A K Y M S N C S C T N V A W V

Tons per yearFIRESAREANONROADONROADNONEGUEGU2002 Actual EGU and Fires2002 Typical EGU and Fires20092018Documentation of the Base G 2002 Base Year, 2009 and 2018, Emission Inventories for VISTAS

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### Annual CO Emissions by Source Sector

Name EGU NONEGU ONROAD NONROAD AREA FIRES YEAR 11,279 174,271 1,366,056 414,385 83,958 474,959 2002 Actual 11,460 174,260 942,793 414,385 83,958 514,120 2002 Typical AL 14,986 180,369 942,793 454,686 66,654 534,873 2009 24,342 201,794 797,966 488,924 59,626 535,658 2018
57,113 81,933 4,693,893 1,920,729 71,079 790,620 2002 Actual 55,899 81,928 3,446,095 1,920,729 71,079 923,310 2002 Typical FL 35,928 87,037 3,446,095 2,104,920 57,011 923,310 2009 53,772 96,819 3,086,330 2,323,327 53,903 923,310 2018
9,712 130,656 2,833,468 791,158 108,083 654,411 2002 Actual 9,650 130,656 2,053,694 791,158 108,083 620,342 2002 Typical GA 23,721 147,215 2,053,694 882,970 94,130 637,177 2009 44,476 167,644 1,765,020 973,872 93,827 637,177 2018

12,619 109,936 1,260,682 325,993 66,752 8,703 2002 Actual 12,607 109,937 942,350 325,993 66,752 24,900 2002 Typical KY 15,812 122,024 942,350 357,800 57,887 31,810 2009 17,144 139,437 782,423 381,215 54,865 33,296 2018

5,303 54,568 894,639 236,752 37,905 13,209 2002 Actual 5,219 54,567 628,151 236,752 37,905 14,353 2002 Typical MS 5,051 57,748 628,151 257,453 27,184 48,160 2009 15,282 66,858 528,898 270,726 22,099 50,037 2018

13,885 50,531 3,176,811 808,231 345,315 34,515 2002 Actual 14,074 50,531 2,184,901 808,231 345,315 71,970 2002 Typical NC 14,942 53,696 2,184,901 887,605 301,163 96,258 2009 20,223 62,145 1,510,848 960,709 290,809 111,266 2018

6,990 56,315 1,275,161 413,964 113,714 248,341 2002 Actual 6,969 56,315 912,280 413,964 113,714 253,005 2002 Typical SC 11,135 60,473 912,280 448,625 90,390 282,307 2009 14,786 68,988 800,619 481,332 83,167 282,307 2018

7,084 114,681 1,967,658 505,163 89,828 4,302 2002 Actual 6,787 114,681 1,361,408 505,163 89,828 10,124 2002 Typical TN 7,214 119,039 1,361,408 554,121 74,189 17,372 2009 7,723 140,138 1,150,516 593,100 68,809 18,860 2018

6,892 63,796 2,170,508 660,105 155,873 15,625 2002 Actual 6,797 63,784 1,495,771 660,105 155,873 12,611 2002 Typical VA 12,509 68,346 1,495,771 726,815 128,132 21,130 2009 15,420 76,998 1,310,698 797,683 121,690 26,923 2018

10,341 89,879 560,717 133,113 39,546 6,738 2002 Actual 10,117 89,878 385,994 133,113 39,546 2,652 2002 Typical WV 11,493 100,045 385,994 152,862 31,640 3,949 2009 11,961 119,332 319,030 167,424 28,773 5,013 2018Documentation of the Base G 2002 Base Year, 2009 and 2018, Emission Inventories for VISTASMACTEC, Inc.193Annual NH3Emissions by Source Sector050,000100,000150,000200,000250,000 A L F L G A K Y M S N C S C T N V A W V

Tons per yearFIRESAREANONROADONROADNONEGUEGU2002 Actual EGU and Fires2002 Typical EGU and Fires20092018Documentation of the Base G 2002 Base Year, 2009 and 2018, Emission Inventories for VISTAS

MACTEC, Inc. 194 

### Annual NH 3 

### Emissions by Source Sector

Name EGU NONEGU ONROAD NONROAD AREA FIRES YEAR 317 1,883 5,576 33 58,318 1,689 2002 Actual 239 1,883 6,350 33 58,318 1,957 2002 Typical AL 359 2,132 6,350 36 64,268 2,050 2009 1,072 2,464 7,296 42 71,915 2,054 2018

234 1,423 18,078 134 37,446 3,102 2002 Actual 222 1,423 21,737 134 37,446 3,157 2002 Typical FL 1,631 1,544 21,737 148 38,616 3,157 2009 2,976 1,829 26,154 171 40,432 3,157 2018

83 3,613 10,524 60 80,913 2,578 2002 Actual 86 3,613 12,660 60 80,913 2,153 2002 Typical GA 686 3,963 12,660 68 89,212 2,229 2009 1,677 4,797 14,871 79 99,885 2,229 2018

326 674 5,044 31 51,135 39 2002 Actual 321 674 5,795 31 51,135 112 2002 Typical KY 400 760 5,795 34 53,005 143 2009 476 901 6,584 40 55,211 150 2018

190 1,169 3,577 23 58,721 59 2002 Actual 198 1,169 4,026 23 58,721 65 2002 Typical MS 334 668 4,026 25 63,708 217 2009 827 764 4,565 29 69,910 225 2018

54 1,179 10,455 65 161,860 155 2002 Actual 55 1,179 12,637 65 161,860 324 2002 Typical NC 445 1,285 12,637 72 170,314 433 2009 663 1,465 13,077 83 180,866 501 2018

142 1,411 4,684 33 28,166 980 2002 Actual 141 1,411 5,510 33 28,166 908 2002 Typical SC 343 1,578 5,510 36 30,555 1,039 2009 617 1,779 6,472 41 33,496 1,039 2018

204 1,542 6,616 43 34,393 19 2002 Actual 197 1,542 7,738 43 34,393 46 2002 Typical TN 227 1,764 7,738 48 35,253 78 2009 241 2,115 8,962 55 36,291 85 2018

127 3,104 7,837 48 43,905 70 2002 Actual 130 3,104 9,066 48 43,905 57 2002 Typical VA 694 3,049 9,066 53 46,639 95 2009 622 3,604 10,757 61 50,175 121 2018

121 332 1,933 9 9,963 30 2002 Actual 121 332 2,183 9 9,963 12 2002 Typical WV 330 341 2,183 11 10,625 18 2009 180 413 2,484 13 11,504 23 2018Documentation of the Base G 2002 Base Year, 2009 and 2018, Emission Inventories for VISTASMACTEC, Inc.195Annual NOx Emissions by Source Sector0200,000400,000600,000800,0001,000,0001,200,000 A L F L G A K Y M S N C S C T N V A W V

Tons per yearFIRESAREANONROADONROADNONEGUEGU2002 Actual EGU and Fires2002 Typical EGU and Fires20092018Documentation of the Base G 2002 Base Year, 2009 and 2018, Emission Inventories for VISTAS

MACTEC, Inc. 196 

### Annual NO x 

### Emissions by Source Sector

Name EGU NONEGU ONROAD NONROAD AREA FIRES YEAR 161,038 83,310 158,423 65,366 23,444 10,728 2002 Actual 154,704 83,302 101,323 65,366 23,444 11,456 2002 Typical AL 82,305 69,409 101,323 56,862 23,930 11,901 2009 64,358 78,318 46,222 43,799 25,028 11,918 2018

257,677 45,156 466,098 180,627 28,872 15,942 2002 Actual 282,507 45,150 314,307 180,627 28,872 19,791 2002 Typical FL 86,165 46,020 314,307 163,794 28,187 19,791 2009 73,125 51,902 154,611 127,885 30,708 19,791 2018

147,517 49,214 308,013 97,961 36,142 14,203 2002 Actual 148,126 49,214 208,393 97,961 36,142 13,882 2002 Typical GA 98,497 50,312 208,393 85,733 37,729 14,243 2009 75,717 55,775 99,821 64,579 41,332 14,243 2018

198,817 38,392 154,899 104,571 39,507 187 2002 Actual 201,928 38,434 97,912 104,571 39,507 534 2002 Typical KY 92,021 37,758 97,912 94,752 42,088 682 2009 64,378 41,034 42,104 79,392 44,346 714 2018

43,135 61,526 111,791 88,787 4,200 283 2002 Actual 40,433 61,553 69,949 88,787 4,200 308 2002 Typical MS 36,011 56,398 69,949 80,567 4,249 1,033 2009 10,271 61,533 29,717 68,252 4,483 1,073 2018

151,850 44,881 341,198 84,284 36,550 740 2002 Actual 148,809 44,881 207,648 84,284 36,550 1,544 2002 Typical NC 66,517 34,719 207,648 70,997 39,954 2,065 2009 62,346 37,750 81,706 49,046 43,865 2,387 2018

88,241 42,153 140,428 50,249 19,332 4,932 2002 Actual 88,528 42,153 91,696 50,249 19,332 5,270 2002 Typical

SC 46,915 40,019 91,696 43,235 19,360 5,899 2009 51,456 44,021 42,354 31,758 20,592 5,899 2018

157,307 64,331 233,324 96,827 17,844 92 2002 Actual 152,137 64,331 147,757 96,827 17,844 217 2002 Typical TN 66,405 57,869 147,757 86,641 18,499 373 2009 31,715 63,435 65,242 70,226 19,597 405 2018

86,886 60,415 219,602 63,219 51,418 335 2002 Actual 85,081 60,390 133,170 63,219 51,418 271 2002 Typical VA 66,219 51,046 133,170 54,993 52,618 453 2009 75,594 55,945 61,881 40,393 56,158 578 2018

230,977 46,612 59,612 33,239 12,687 145 2002 Actual 222,437 46,618 36,049 33,239 12,687 57 2002 Typical WV 86,328 38,031 36,049 30,133 13,439 85 2009 51,241 43,359 16,274 25,710 14,828 108 2018Documentation of the Base G 2002 Base Year, 2009 and 2018, Emission Inventories for VISTASMACTEC, Inc.197Annual PM10Emissions by Source Sector0200,000400,000600,000800,0001,000,0001,200,000 A L F L G A K Y M S N C S C T N V A W V

Tons per yearFIRESAREANONROADONROADNONEGUEGU2002 Actual EGU and Fires2002 Typical EGU and Fires20092018Documentation of the Base G 2002 Base Year, 2009 and 2018, Emission Inventories for VISTAS

MACTEC, Inc. 198 

### Annual PM 10 

### Emissions by Source Sector

Name EGU NONEGU ONROAD NONROAD AREA FIRES YEAR 7,646 25,240 3,898 4,787 393,588 47,237 2002 Actual 7,845 25,239 3,188 4,787 393,588 50,833 2002 Typical AL 6,969 25,421 3,188 4,027 413,020 52,851 2009 7,822 29,924 2,488 3,041 445,256 52,927 2018

21,387 35,857 11,253 18,281 443,346 85,263 2002 Actual 21,391 35,856 9,953 18,281 443,346 98,470 2002 Typical FL 9,007 39,872 9,953 15,613 503,230 98,470 2009 9,953 46,456 8,489 12,497 578,516 98,470 2018

11,224 21,516 7,236 8,618 695,414 65,227 2002 Actual 11,467 21,516 6,103 8,618 695,414 62,336 2002 Typical GA 17,891 22,997 6,103 7,521 776,411 63,973 2009 20,909 27,143 4,995 6,015 880,199 63,973 2018

4,701 16,626 3,720 6,425 233,559 846 2002 Actual 4,795 16,626 3,002 6,425 233,559 2,421 2002 Typical KY 6,463 17,174 3,002 5,544 242,177 3,093 2009 6,694 20,153 2,283 4,556 256,052 3,237 2018

1,633 19,472 2,856 5,010 343,377 1,284 2002 Actual 1,706 19,469 2,290 5,010 343,377 1,396 2002 Typical MS 4,957 19,245 2,290 4,270 356,324 4,683 2009 7,187 22,859 1,688 3,452 375,495 4,865 2018

22,754 13,785 6,905 7,348 280,379 3,356 2002 Actual 22,994 13,785 5,861 7,348 280,379 6,998 2002 Typical NC 22,152 13,855 5,861 6,055 292,443 9,359 2009 37,376 15,678 4,299 4,298 315,294 10,819 2018

21,400 14,142 3,446 4,152 260,858 25,968 2002 Actual 21,827 14,142 2,878 4,152 260,858 26,304 2002 Typical SC 19,395 13,370 2,878 3,471 278,299 29,153 2009 28,826 15,139 2,258 2,617 304,251 29,153 2018

14,640 34,534 5,338 6,819 212,554 418 2002 Actual 13,866 34,534 4,238 6,819 212,554 984 2002 Typical TN 15,608 34,145 4,238 5,877 226,098 1,689 2009 15,941 41,397 3,199 4,672 246,252 1,834 2018

3,960 13,252 4,537 8,728 237,577 1,519 2002 Actual 3,892 13,252 3,760 8,728 237,577 1,226 2002 Typical VA 5,508 13,048 3,760 7,510 252,488 2,054 2009 13,775 15,112 3,343 6,208 275,351 2,618 2018

4,573 17,503 1,395 1,850 115,346 655 2002 Actual 4,472 17,503 1,096 1,850 115,346 258 2002 Typical WV 5,657 17,090 1,096 1,640 115,089 384 2009 6,349 21,735 844 1,292 121,549 487 2018Documentation of the Base G 2002 Base Year, 2009 and 2018, Emission Inventories for VISTASMACTEC, Inc.199Annual PM2.5Emissions by Source Sector050,000100,000150,000200,000250,000 A L F L G A K Y M S N C S C T N V A W V

Tons per yearFIRESAREANONROADONROADNONEGUEGU2002 Actual EGU and Fires2002 Typical EGU and Fires20092018Documentation of the Base G 2002 Base Year, 2009 and 2018, Emission Inventories for VISTAS

MACTEC, Inc. 200 

### Annual PM 2.5 

### Emissions by Source Sector

Name EGU NONEGU ONROAD NONROAD AREA FIRES YEAR 4,113 19,178 2,794 4,502 56,654 42,041 2002 Actual 4,176 19,177 2,049 4,502 56,654 44,812 2002 Typical

AL 3,921 19,230 2,049 3,776 58,699 46,543 2009 4,768 22,598 1,262 2,835 62,323 46,608 2018

15,643 30,504 7,852 17,415 58,878 75,717 2002 Actual 15,575 30,504 6,216 17,415 58,878 88,756 2002 Typical FL 5,910 33,946 6,216 14,866 64,589 88,756 2009 6,843 39,430 4,242 11,868 72,454 88,756 2018

4,939 17,394 5,158 8,226 103,794 57,293 2002 Actual 5,070 17,394 3,869 8,226 103,794 55,712 2002 Typical GA 10,907 18,906 3,869 7,175 112,001 57,116 2009 13,983 22,323 2,517 5,730 123,704 57,116 2018

2,802 11,372 2,693 6,046 45,453 726 2002 Actual 2,847 11,372 1,941 6,046 45,453 2,076 2002 Typical KY 4,279 11,686 1,941 5,203 46,243 2,653 2009 4,434 13,739 1,160 4,256 47,645 2,777 2018

1,138 9,906 2,109 4,690 50,401 1,102 2002 Actual 1,147 9,902 1,522 4,690 50,401 1,197 2002 Typical MS 4,777 9,199 1,522 3,985 51,661 4,016 2009 7,033 10,739 876 3,203 53,222 4,173 2018

16,498 10,455 4,816 7,005 64,052 2,878 2002 Actual 16,623 10,455 3,643 7,005 64,052 6,002 2002 Typical NC 15,949 10,411 3,643 5,760 69,457 8,027 2009 29,791 11,775 2,158 4,069 71,262 9,279 2018

17,154 10,245 2,496 3,945 40,291 22,953 2002 Actual 17,521 10,245 1,870 3,945 40,291 23,511 2002 Typical SC 16,042 9,390 1,870 3,294 41,613 25,955 2009 25,032 11,086 1,154 2,474 44,319 25,955 2018

12,166 27,345 3,919 6,458 42,566 359 2002 Actual 11,491 27,345 2,782 6,458 42,566 844 2002 Typical TN 13,092 27,079 2,782 5,557 44,124 1,449 2009 13,387 32,893 1,643 4,403 46,692 1,573 2018

2,606 10,165 3,090 8,288 43,989 1,303 2002 Actual 2,650 10,165 2,254 8,288 43,989 1,052 2002 Typical VA 4,067 9,988 2,254 7,136 44,514 1,762 '2009 11,976 11,594 1,641 5,891 46,697 2,245 2018

2,210 13,313 1,003 1,728 21,049 562 2002 Actual 2,163 13,313 703 1,728 21,049 221 2002 Typical WV 2,940 12,769 703 1,528 20,664 329 2009 3,648 16,516 428 1,198 21,490 418 2018Documentation of the Base G 2002 Base Year, 2009 and 2018, Emission Inventories for VISTASMACTEC, Inc.201Annual SO2Emissions by Source Sector0100,000200,000300,000400,000500,000600,000700,000 A L F L G A K Y M S N C S C T N V A W V

Tons per yearFIRESAREANONROADONROADNONEGUEGU2002 Actual EGU and Fires2002 Typical EGU and Fires20092018Documentation of the Base G 2002 Base Year, 2009 and 2018, Emission Inventories for VISTAS

MACTEC, Inc. 202 

### Annual SO 2 

### Emissions by Source Sector

Name EGU NONEGU ONROAD NONROAD AREA FIRES YEAR 447,828 96,481 6,885 7,584 52,253 2,208 2002 Actual 423,736 96,481 635 7,584 52,253 2,559 2002 Typical

AL 378,052 101,246 635 3,471 48,228 2,681 2009 305,262 113,224 720 2,818 50,264 2,686 2018

453,631 65,090 20,872 20,614 40,491 4,057 2002 Actual 483,590 65,090 2,120 20,614 40,491 4,129 2002 Typical FL 186,055 65,511 2,120 8,967 36,699 4,129 2009 132,177 75,047 2,533 7,536 38,317 4,129 2018

514,952 53,774 12,155 9,005 57,559 3,372 2002 Actual 517,633 53,774 1,254 9,005 57,559 2,815 2002 Typical GA 417,449 53,983 1,254 2,725 57,696 2,914 2009 230,856 59,343 1,458 1,709 59,729 2,914 2018

484,057 34,029 5,974 14,043 41,805 51 2002 Actual 495,153 34,029 585 14,043 41,805 146 2002 Typical KY 290,193 36,418 585 9,180 43,087 187 2009 226,062 40,682 651 8,592 44,186 196 2018

67,429 35,960 4,604 11,315 771 78 2002 Actual 60,086 35,954 397 11,315 771 84 2002 Typical MS 76,579 25,564 397 7,191 753 283 2009 15,146 39,221 441 6,638 746 294 2018

477,990 44,103 13,343 7,693 5,412 203 2002 Actual 478,488 44,103 1,311 7,693 5,412 423 2002 Typical NC 242,286 42,516 1,311 1,892 5,751 566 2009 108,492 46,292 1,323 905 6,085 655 2018

206,399 53,518 5,958 4,866 12,900 1,281 2002 Actual 210,272 53,518 556 4,866 12,900 1,187 2002 Typical SC 124,608 48,325 556 1,701 13,051 1,359 2009 93,274 53,577 643 1,198 13,457 1,359 2018

334,151 79,584 9,184 10,441 29,917 25 2002 Actual 320,146 79,584 831 10,441 29,917 60 2002 Typical TN 255,410 70,657 831 5,651 30,577 102 2009 112,672 77,219 944 5,207 31,962 111 2018

241,204 63,903 7,218 8,663 105,890 92 2002 Actual 233,691 63,900 900 8,663 105,890 74 2002 Typical VA 225,653 62,560 900 1,707 105,984 124 2009 140,233 68,909 1,059 507 109,380 158 2018

516,084 54,070 2,489 2,112 11,667 40 2002 Actual 500,381 54,077 227 2,112 11,667 16 2002 Typical WV 277,489 55,973 227 359 12,284 23 2009 115,324 62,193 255 56 12,849 29 2018Documentation of the Base G 2002 Base Year, 2009 and 2018, Emission Inventories for VISTASMACTEC, Inc.203Annual VOC Emissions by Source Sector0200,000400,000600,000800,0001,000,0001,200,0001,400,000 A L F L G A K Y M S N C S C T N V A W V

Tons per yearFIRESAREANONROADONROADNONEGUEGU2002 Actual EGU and Fires2002 Typical EGU and Fires20092018Documentation of the Base G 2002 Base Year, 2009 and 2018, Emission Inventories for VISTAS

MACTEC, Inc. 204 

### Annual VOC Emissions by Source Sector

Name EGU NONEGU ONROAD NONROAD AREA FIRES YEAR 2,295 47,037 119,790 60,487 182,674 25,278 2002 Actual 2,288 47,035 72,848 60,487 182,674 26,526 2002 Typical AL 2,473 46,644 72,848 50,249 143,454 27,502 2009 2,952 54,291 47,296 40,407 153,577 27,539 2018

2,524 38,471 495,225 272,072 404,302 42,724 2002 Actual 2,531 38,471 323,290 272,072 404,302 51,527 2002 Typical FL 1,910 36,880 323,290 209,543 420,172 51,527 2009 2,376 42,811 216,620 183,452 489,975 51,527 2018

1,244 33,157 267,378 85,965 299,679 33,979 2002 Actual 1,256 33,157 184,239 85,965 299,679 33,918 2002 Typical GA 2,314 33,444 184,239 67,686 272,315 34,710 2009 2,841 39,485 105,507 56,761 319,328 34,710 2018

1,487 44,834 98,311 44,805 95,375 410 2002 Actual 1,481 44,834 63,258 44,805 95,375 1,172 2002 Typical KY 1,369 47,786 63,258 38,558 94,042 1,497 2009 1,426 55,861 39,084 30,920 103,490 1,567 2018

648 43,204 82,810 41,081 131,808 622 2002 Actual 629 43,203 49,670 41,081 131,808 675 2002 Typical MS 404 37,747 49,670 36,197 124,977 2,266 2009 1,114 45,338 30,734 28,842 140,134 2,355 2018

988 60,496 253,374 94,480 237,926 1,624 2002 Actual 986 60,496 163,803 94,480 237,926 3,387 2002 Typical NC 954 61,207 163,803 74,056 187,769 4,530 2009 1,345 70,100 88,620 61,327 189,591 5,236 2018

470 38,458 106,792 55,016 161,000 14,202 2002 Actual 470 38,458 67,281 55,016 161,000 14,666 2002 Typical SC 660 35,665 67,281 43,061 146,107 16,045 2009 906 43,656 44,700 36,131 161,228 16,045 2018

926 77,304 169,914 66,450 153,307 202 2002 Actual 890 77,304 108,200 66,450 153,307 476 2002 Typical TN 932 66,538 108,200 55,358 154,377 817 2009 976 83,573 64,665 45,084 182,222 888 2018

754 43,152 144,684 74,866 174,116 735 2002 Actual 747 43,152 89,678 74,866 174,116 593 2002 Typical VA 778 43,726 89,678 57,009 147,034 994 2009 997 53,186 60,454 49,052 150,919 1,267 2018

1,180 14,595 40,066 18,566 60,443 317 2002 Actual 1,140 14,595 23,907 18,566 60,443 125 2002 Typical WV 1,361 13,810 23,907 18,069 55,288 186 2009 1,387 16,565 15,463 14,086 60,747 236 2018Documentation of the Base G 2002 Base Year, 2009 and 2018, Emission Inventories for VISTASMACTEC, Inc.205Annual CO Emissions by Source Sector01,000,0002,000,0003,000,0004,000,0005,000,0006,000,0007,000,0008,000,000 A L F L G A K Y M S N C S C T N V A W V

Tons per yearFIRESAREANONROADONROADNONEGUEGU20022009 OTB2009 OTW2018 OTB2018 OTWEGU and NonEGU values based on 2002 Typical EmissionsAll Fire emissions based on Typical Year valuesDocumentation of the Base G 2002 Base Year, 2009 and 2018, Emission Inventories for VISTAS

MACTEC, Inc. 206 

### Annual CO Emissions by Source Sector

Name AREA EGU FIRES NONEGU NONROAD ONROAD YEAR Basis 83,958 10,812 514,120 174,306 367,038 1,366,056 2002 OTB - Typical 2002 68,882 16,494 514,120 177,145 408,424 942,793 2009 OTB - Typical 2002 AL 68,882 19,205 514,120 177,145 408,424 942,793 2009 OTW - Typical 2002 63,773 26,600 514,120 194,801 443,100 797,966 2018 OTB - Typical 2002 63,773 29,893 514,120 194,801 443,100 797,966 2018 OTW - Typical 2002
105,849 51,165 923,310 84,920 1,731,519 4,693,893 2002 OTB - Typical 2002 101,356 40,642 923,310 98,325 1,934,550 3,446,095 2009 OTB - Typical 2002 FL 101,356 40,641 923,310 98,325 1,934,550 3,446,095 2009 OTW - Typical 2002 100,952 59,793 923,310 113,923 2,179,296 3,086,330 2018 OTB - Typical 2002 100,952 57,759 923,310 113,923 2,179,296 3,086,330 2018 OTW - Typical 2002
107,889 8,098 620,342 131,417 700,427 2,833,468 2002 OTB - Typical 2002 103,579 19,170 620,342 147,835 783,990 2,053,694 2009 OTB - Typical 2002 GA 103,579 20,024 620,342 147,835 783,990 2,053,694 2009 OTW - Typical 2002 105,059 27,152 620,342 169,156 868,018 1,765,020 2018 OTB - Typical 2002 105,059 28,895 620,342 169,156 868,018 1,765,020 2018 OTW - Typical 2002
66,752 12,888 56,686 110,141 289,967 1,260,682 2002 OTB - Typical 2002 64,806 15,273 56,686 121,981 306,884 942,350 2009 OTB - Typical 2002 KY 64,806 15,119 56,686 121,981 306,884 942,350 2009 OTW - Typical 2002 65,297 16,974 56,686 139,395 349,285 782,423 2018 OTB - Typical 2002 65,297 14,954 56,686 139,395 349,285 782,423 2018 OTW - Typical 2002
37,905 3,831 128,471 57,711 213,779 894,639 2002 OTB - Typical 2002 37,161 6,714 128,471 60,709 237,297 628,151 2009 OTB - Typical 2002 MS 37,161 6,954 128,471 60,709 237,297 628,151 2009 OTW - Typical 2002 36,425 10,553 128,471 70,454 252,658 528,898 2018 OTB - Typical 2002 36,425 12,928 128,471 70,454 252,658 528,898 2018 OTW - Typical 2002
373,585 12,027 200,564 52,542 725,734 3,176,811 2002 OTB - Typical 2002 332,443 11,091 200,564 54,791 797,360 2,184,901 2009 OTB - Typical 2002 NC 332,443 11,170 200,564 54,791 797,360 2,184,901 2009 OTW - Typical 2002 327,871 13,482 200,564 63,699 863,536 1,510,848 2018 OTB - Typical 2002 327,871 13,777 200,564 63,699 863,536 1,510,848 2018 OTW - Typical 2002
113,714 3,675 253,005 59,605 367,575 1,275,161 2002 OTB - Typical 2002 95,826 6,316 253,005 65,612 402,871 912,280 2009 OTB - Typical 2002 SC 95,826 6,526 253,005 65,612 402,871 912,280 2009 OTW - Typical 2002 89,343 10,175 253,005 75,209 438,027 800,619 2018 OTB - Typical 2002 89,343 10,671 253,005 75,209 438,027 800,619 2018 OTW - Typical 2002
89,235 6,339 78,370 119,405 451,480 1,967,658 2002 OTB - Typical 2002 82,196 6,750 78,370 121,420 500,186 1,361,408 2009 OTB - Typical 2002 TN 82,196 6,651 78,370 121,420 500,186 1,361,408 2009 OTW - Typical 2002 81,242 7,074 78,370 143,845 540,143 1,150,516 2018 OTB - Typical 2002 81,242 6,509 78,370 143,845 540,143 1,150,516 2018 OTW - Typical 2002
155,873 5,958 19,159 62,534 595,311 2,170,508 2002 OTB - Typical 2002 133,738 9,811 19,159 69,822 661,295 1,495,771 2009 OTB - Typical 2002 VA 133,738 10,245 19,159 69,822 661,295 1,495,771 2009 OTW - Typical 2002 129,037 14,788 19,159 77,590 734,294 1,310,698 2018 OTB - Typical 2002 129,037 14,839 19,159 77,590 734,294 1,310,698 2018 OTW - Typical 2002
39,546 9,927 32,656 89,928 119,089 560,717 2002 OTB - Typical 2002 37,704 12,622 32,656 100,292 138,999 385,994 2009 OTB - Typical 2002 WV 37,704 12,328 32,656 100,292 138,999 385,994 2009 OTW - Typical 2002 36,809 13,064 32,656 119,367 152,932 319,030 2018 OTB - Typical 2002 36,809 12,992 32,656 119,367 152,932 319,030 2018 OTW - Typical 2002Documentation of the Base G 2002 Base Year, 2009 and 2018, Emission Inventories for VISTASMACTEC, Inc.207Annual NH3Emissions by Source Sector050,000100,000150,000200,000250,000 A L F L G A K Y M S N C S C T N V A W V

Tons per yearFIRESAREANONROADONROADNONEGUEGU20022009 OTB2009 OTW2018 OTB2018 OTWEGU and NonEGU values based on 2002 Typical EmissionsAll Fire emissions based on Typical Year valuesDocumentation of the Base G 2002 Base Year, 2009 and 2018, Emission Inventories for VISTAS

MACTEC, Inc. 208 

### Annual NH 3 

### Emissions by Source Sector

Name EGU NONEGU ONROAD NONROAD AREA FIRES YEAR Basis 89 1,883 5,576 32 59,486 1,957 2002 OTB - Typical 2002 1,128 2,112 6,350 35 65,441 1,957 2009 OTB - Typical 2002 AL 1,344 2,112 6,350 35 65,441 1,957 2009 OTW - Typical 2002 1,909 2,456 7,296 40 73,346 1,957 2018 OTB - Typical 2002 2,173 2,456 7,296 40 73,346 1,957 2018 OTW - Typical 2002

53 1,383 18,078 108 44,902 3,157 2002 OTB - Typical 2002 2,524 1,605 21,737 119 46,950 3,157 2009 OTB - Typical 2002 FL 2,524 1,605 21,737 119 46,950 3,157 2009 OTW - Typical 2002 4,022 1,905 26,154 138 49,889 3,157 2018 OTB - Typical 2002 3,865 1,905 26,154 138 49,889 3,157 2018 OTW - Typical 2002

5 3,613 10,524 54 84,230 2,153 2002 OTB - Typical 2002 1,305 3,963 12,660 60 92,838 2,153 2009 OTB - Typical 2002 GA 1,376 3,963 12,660 60 92,838 2,153 2009 OTW - Typical 2002 1,912 4,799 14,871 71 103,911 2,153 2018 OTB - Typical 2002 2,057 4,799 14,871 71 103,911 2,153 2018 OTW - Typical 2002

0 674 5,044 28 51,097 110 2002 OTB - Typical 2002 717 733 5,795 30 53,023 110 2009 OTB - Typical 2002 KY 710 733 5,795 30 53,023 110 2009 OTW - Typical 2002 763 839 6,584 36 55,356 110 2018 OTB - Typical 2002 771 839 6,584 36 55,356 110 2018 OTW - Typical 2002

97 1,169 3,577 23 59,262 177 2002 OTB - Typical 2002 388 667 4,026 26 64,289 177 2009 OTB - Typical 2002 MS 407 667 4,026 26 64,289 177 2009 OTW - Typical 2002 686 761 4,565 30 70,565 177 2018 OTB - Typical 2002 872 761 4,565 30 70,565 177 2018 OTW - Typical 2002

35 1,171 10,455 61 164,467 324 2002 OTB - Typical 2002 577 1,255 12,637 68 173,187 324 2009 OTB - Typical 2002 N C 574 1,255 12,637 68 173,187 324 2009 OTW - Typical 2002 740 1,412 13,077 79 184,167 324 2018 OTB - Typical 2002 781 1,412 13,077 79 184,167 324 2018 OTW - Typical 2002

0 1,411 4,684 29 29,447 908 2002 OTB - Typical 2002 409 1,578 5,510 32 31,966 908 2009 OTB - Typical 2002 SC 422 1,578 5,510 32 31,966 908 2009 OTW - Typical 2002 702 1,779 6,472 37 35,082 908 2018 OTB - Typical 2002 742 1,779 6,472 37 35,082 908 2018 OTW - Typical 2002

0 1,620 6,616 41 35,571 46 2002 OTB - Typical 2002 406 1,861 7,738 45 36,578 46 2009 OTB - Typical 2002 TN 400 1,861 7,738 45 36,578 46 2009 OTW - Typical 2002 427 2,240 8,962 53 37,812 46 2018 OTB - Typical 2002 394 2,240 8,962 53 37,812 46 2018 OTW - Typical 2002

122 3,097 7,837 44 46,221 159 2002 OTB - Typical 2002 396 3,057 9,066 48 49,173 159 2009 OTB - Typical 2002 VA 439 3,057 9,066 48 49,173 159 2009 OTW - Typical 2002 759 3,620 10,757 57 53,023 159 2018 OTB - Typical 2002 783 3,620 10,757 57 53,023 159 2018 OTW - Typical 2002

12 331 1,933 10 10,779 12 2002 OTB - Typical 2002 691 342 2,183 11 11,461 12 2009 OTB - Typical 2002 WV 673 342 2,183 11 11,461 12 2009 OTW - Typical 2002 722 416 2,484 13 12,390 12 2018 OTB - Typical 2002 719 416 2,484 13 12,390 12 2018 OTW - Typical 2002Documentation of the Base G 2002 Base Year, 2009 and 2018, Emission Inventories for VISTASMACTEC, Inc.209Annual NOx Emissions by Source Sector0200,000400,000600,000800,0001,000,0001,200,000 A L F L G A K Y M S N C S C T N V A W V

Tons per yearFIRESAREANONROADONROADNONEGUEGU20022009 OTB2009 OTW2018 OTB2018 OTWEGU and NonEGU values based on 2002 Typical EmissionsAll Fire emissions based on Typical Year valuesDocumentation of the Base G 2002 Base Year, 2009 and 2018, Emission Inventories for VISTAS

MACTEC, Inc. 210 

### Annual NO x 

### Emissions by Source Sector

Name EGU NONEGU ONROAD NONROAD AREA FIRES YEAR Basis 153,349 83,868 158,423 64,891 23,444 11,456 2002 OTB - Typical 2002 131,988 80,738 101,323 55,494 26,482 11,456 2009 OTB - Typical 2002 AL 132,323 70,644 101,323 55,494 26,482 11,456 2009 OTW - Typical 2002 135,010 91,052 46,222 42,573 28,754 11,456 2018 OTB - Typical 2002 39,942 80,031 46,222 42,573 28,754 11,456 2018 OTW - Typical 2002
247,099 59,517 466,098 150,519 29,477 19,791 2002 OTB - Typical 2002 148,522 67,533 314,307 136,851 31,821 19,791 2009 OTB - Typical 2002 FL 147,801 67,533 314,307 136,851 31,821 19,791 2009 OTW - Typical 2002 159,004 77,551 154,611 111,959 35,047 19,791 2018 OTB - Typical 2002 59,446 77,551 154,611 111,959 35,047 19,791 2018 OTW - Typical 2002

120,785 52,425 308,013 91,386 36,105 13,882 2002 OTB - Typical 2002 131,901 53,008 208,393 79,049 38,876 13,882 2009 OTB - Typical 2002 GA 119,425 53,008 208,393 79,049 38,876 13,882 2009 OTW - Typical 2002 128,938 59,005 99,821 60,650 42,260 13,882 2018 OTB - Typical 2002 65,559 59,005 99,821 60,650 42,260 13,882 2018 OTW - Typical 2002
209,802 38,460 154,899 101,261 39,507 1,460 2002 OTB - Typical 2002 178,930 37,960 97,912 90,803 42,122 1,460 2009 OTB - Typical 2002 KY 177,272 37,201 97,912 90,803 42,122 1,460 2009 OTW - Typical 2002 182,192 41,776 42,104 77,295 45,597 1,460 2018 OTB - Typical 2002 64,674 40,948 42,104 77,295 45,597 1,460 2018 OTW - Typical 2002

27,254 76,906 111,791 90,686 4,200 3,328 2002 OTB - Typical 2002 38,911 70,463 69,949 81,780 4,789 3,328 2009 OTB - Typical 2002 MS 38,978 70,463 69,949 81,780 4,789 3,328 2009 OTW - Typical 2002 38,355 76,738 29,717 68,781 5,230 3,328 2018 OTB - Typical 2002 11,206 76,738 29,717 68,781 5,230 3,328 2018 OTW - Typical 2002

144,730 50,393 341,198 81,448 48,730 5,005 2002 OTB - Typical 2002 66,598 46,242 207,648 66,382 53,550 5,005 2009 OTB - Typical 2002 N C 67,051 46,242 207,648 66,382 53,550 5,005 2009 OTW - Typical 2002 64,537 50,044 81,706 45,146 60,073 5,005 2018 OTB - Typical 2002 59,917 50,044 81,706 45,146 60,073 5,005 2018 OTW - Typical 2002

85,555 44,123 140,428 46,789 19,332 5,270 2002 OTB - Typical 2002 50,433 43,799 91,696 39,544 20,852 5,270 2009 OTB - Typical 2002 SC 50,128 42,944 91,696 39,544 20,852 5,270 2009 OTW - Typical 2002 55,103 48,314 42,354 29,512 22,467 5,270 2018 OTB - Typical 2002 36,264 47,403 42,354 29,512 22,467 5,270 2018 OTW - Typical 2002

155,028 73,384 233,324 95,968 17,829 2,232 2002 OTB - Typical 2002 106,979 62,435 147,757 85,084 19,148 2,232 2009 OTB - Typical 2002 TN 104,528 61,176 147,757 85,084 19,148 2,232 2009 OTW - Typical 2002 112,411 69,374 65,242 69,093 20,928 2,232 2018 OTB - Typical 2002 32,411 67,999 65,242 69,093 20,928 2,232 2018 OTW - Typical 2002

82,911 61,528 219,602 58,524 51,418 978 2002 OTB - Typical 2002 64,950 64,298 133,170 50,120 53,344 978 2009 OTB - Typical 2002 VA 62,810 60,027 133,170 50,120 53,344 978 2009 OTW - Typical 2002 56,716 71,480 61,881 36,970 56,668 978 2018 OTB - Typical 2002 40,045 66,931 61,881 36,970 56,668 978 2018 OTW - Typical 2002

222,090 46,715 59,612 34,442 12,687 944 2002 OTB - Typical 2002 173,977 42,140 36,049 31,148 13,816 944 2009 OTB - Typical 2002 WV 174,572 40,469 36,049 31,148 13,816 944 2009 OTW - Typical 2002 170,522 46,846 16,274 26,279 15,079 944 2018 OTB - Typical 2002 42,227 44,944 16,274 26,279 15,079 944 2018 OTW - Typical 2002Documentation of the Base G 2002 Base Year, 2009 and 2018, Emission Inventories for VISTASMACTEC, Inc.211Annual PM10Emissions by Source Sector0200,000400,000600,000800,0001,000,0001,200,000 A L F L G A K Y M S N C S C T N V A W V

Tons per yearFIRESAREANONROADONROADNONEGUEGU20022009 OTB2009 OTW2018 OTB2018 OTWEGU and NonEGU values based on 2002 Actual EmissionsAll Fire emissions based on Typical Year valuesDocumentation of the Base G 2002 Base Year, 2009 and 2018, Emission Inventories for VISTAS

MACTEC, Inc. 212 

### Annual PM 10 

### Emissions by Source Sector

Name EGU NONEGU ONROAD NONROAD AREA FIRES YEAR Basis 5,737 24,957 3,898 5,331 393,093 50,833 2002 OTB - Typical 2002 29,053 25,161 3,188 4,597 411,614 50,833 2009 OTB - Typical 2002 AL 23,250 25,161 3,188 4,597 411,614 50,833 2009 OTW - Typical 2002 31,815 29,278 2,488 3,690 445,168 50,833 2018 OTB - Typical 2002 20,450 29,278 2,488 3,690 445,168 50,833 2018 OTW - Typical 2002

33,182 28,882 11,253 17,692 446,821 98,470 2002 OTB - Typical 2002 25,779 27,531 9,953 15,630 507,515 98,470 2009 OTB - Typical 2002 FL 24,493 27,531 9,953 15,630 507,515 98,470 2009 OTW - Typical 2002 27,320 31,890 8,489 13,827 582,832 98,470 2018 OTB - Typical 2002 22,204 31,890 8,489 13,827 582,832 98,470 2018 OTW - Typical 2002

5,447 22,058 7,236 8,295 695,320 62,336 2002 OTB - Typical 2002 39,580 23,861 6,103 7,368 776,935 62,336 2009 OTB - Typical 2002 GA 28,118 23,861 6,103 7,368 776,935 62,336 2009 OTW - Typical 2002 41,221 28,177 4,995 6,068 880,800 62,336 2018 OTB - Typical 2002 26,905 28,177 4,995 6,068 880,800 62,336 2018 OTW - Typical 2002

6,000 15,613 3,720 6,389 233,559 6,667 2002 OTB - Typical 2002 32,406 15,858 3,002 5,312 242,345 6,667 2009 OTB - Typical 2002 KY 29,606 15,858 3,002 5,312 242,345 6,667 2009 OTW - Typical 2002 33,784 18,587 2,283 4,602 256,544 6,667 2018 OTB - Typical 2002 25,733 18,587 2,283 4,602 256,544 6,667 2018 OTW - Typical 2002

4,783 19,680 2,856 5,551 343,377 14,693 2002 OTB - Typical 2002 5,864 19,439 2,290 4,754 356,516 14,693 2009 OTB - Typical 2002 MS 5,883 19,439 2,290 4,754 356,516 14,693 2009 OTW - Typical 2002 6,268 23,145 1,688 3,873 375,931 14,693 2018 OTB - Typical 2002 6,459 23,145 1,688 3,873 375,931 14,693 2018 OTW - Typical 2002

22,689 14,507 6,905 7,449 303,492 20,488 2002 OTB - Typical 2002 23,028 14,301 5,861 6,210 317,847 20,488 2009 OTB - Typical 2002 N C 21,459 14,301 5,861 6,210 317,847 20,488 2009 OTW - Typical 2002 21,417 16,002 4,299 4,474 345,275 20,488 2018 OTB - Typical 2002 20,258 16,002 4,299 4,474 345,275 20,488 2018 OTW - Typical 2002

23,492 18,149 3,446 4,211 260,858 26,304 2002 OTB - Typical 2002 18,023 17,368 2,878 3,593 278,852 26,304 2009 OTB - Typical 2002 SC 17,493 17,368 2,878 3,593 278,852 26,304 2009 OTW - Typical 2002 19,290 20,272 2,258 2,889 304,940 26,304 2018 OTB - Typical 2002 19,182 20,272 2,258 2,889 304,940 26,304 2018 OTW - Typical 2002

14,537 35,982 5,338 7,145 211,903 8,875 2002 OTB - Typical 2002 17,735 33,838 4,238 6,218 225,650 8,875 2009 OTB - Typical 2002 TN 17,159 33,838 4,238 6,218 225,650 8,875 2009 OTW - Typical 2002 19,103 41,466 3,199 5,019 245,893 8,875 2018 OTB - Typical 2002 12,432 41,466 3,199 5,019 245,893 8,875 2018 OTW - Typical 2002

3,790 12,799 4,537 7,928 237,577 18,160 2002 OTB - Typical 2002 15,343 13,470 3,760 6,763 252,924 18,160 2009 OTB - Typical 2002 VA 12,804 13,470 3,760 6,763 252,924 18,160 2009 OTW - Typical 2002 14,390 15,661 3,343 5,564 275,790 18,160 2018 OTB - Typical 2002 12,653 15,661 3,343 5,564 275,790 18,160 2018 OTW - Typical 2002

7,145 14,866 1,395 2,072 115,346 3,276 2002 OTB - Typical 2002 36,442 14,926 1,096 1,819 115,410 3,276 2009 OTB - Typical 2002 WV 31,780 14,926 1,096 1,819 115,410 3,276 2009 OTW - Typical 2002 37,425 18,433 844 1,381 121,964 3,276 2018 OTB - Typical 2002 24,253 18,433 844 1,381 121,964 3,276 2018 OTW - Typical 2002Documentation of the Base G 2002 Base Year, 2009 and 2018, Emission Inventories for VISTASMACTEC, Inc.213Annual PM2.5Emissions by Source Sector050,000100,000150,000200,000250,000300,000 AL FL GA KY MS N C SC TN VA WV

Tons per yearFIRESAREANONROADONROADNONEGUEGU20022009 OTB2009 OTW2018 OTB2018 OTWEGU and NonEGU values based on 2002 Typical EmissionsAll Fire emissions based on Typical Year valuesDocumentation of the Base G 2002 Base Year, 2009 and 2018, Emission Inventories for VISTAS

MACTEC, Inc. 214 

### Annual PM 2.5 

### Emissions by Source Sector

Name EGU NONEGU ONROAD NONROAD AREA FIRES YEAR Basis 3,131 19,016 2,794 4,877 73,352 44,812 2002 OTB - Typical 2002 24,875 19,184 2,049 4,144 76,248 44,812 2009 OTB - Typical 2002 AL 19,190 19,184 2,049 4,144 76,248 44,812 2009 OTW - Typical 2002 27,280 22,268 1,262 3,231 82,449 44,812 2018 OTB - Typical 2002 16,279 22,268 1,262 3,231 82,449 44,812 2018 OTW - Typical 2002

25,761 24,569 7,852 16,739 81,341 88,756 2002 OTB - Typical 2002 19,307 23,063 6,216 14,786 90,487 88,756 2009 OTB - Typical 2002 FL 18,186 23,063 6,216 14,786 90,487 88,756 2009 OTW - Typical 2002 20,848 26,622 4,242 13,044 101,872 88,756 2018 OTB - Typical 2002 16,278 26,622 4,242 13,044 101,872 88,756 2018 OTW - Typical 2002

2,137 17,893 5,158 7,899 133,542 55,712 2002 OTB - Typical 2002 33,111 19,562 3,869 7,014 146,691 55,712 2009 OTB - Typical 2002 GA 22,163 19,562 3,869 7,014 146,691 55,712 2009 OTW - Typical 2002 34,361 23,110 2,517 5,769 163,925 55,712 2018 OTB - Typical 2002 20,549 23,110 2,517 5,769 163,925 55,712 2018 OTW - Typical 2002

3,605 10,729 2,693 5,998 52,765 6,310 2002 OTB - Typical 2002 26,640 10,837 1,941 4,978 54,397 6,310 2009 OTB - Typical 2002 KY 23,915 10,837 1,941 4,978 54,397 6,310 2009 OTW - Typical 2002 27,857 12,738 1,160 4,289 57,110 6,310 2018 OTB - Typical 2002 19,915 12,738 1,160 4,289 57,110 6,310 2018 OTW - Typical 2002

4,384 10,187 2,109 5,200 63,135 13,680 2002 OTB - Typical 2002 5,511 9,459 1,522 4,440 65,321 13,680 2009 OTB - Typical 2002 MS 5,530 9,459 1,522 4,440 65,321 13,680 2009 OTW - Typical 2002 5,919 11,068 876 3,597 68,338 13,680 2018 OTB - Typical 2002 6,110 11,068 876 3,597 68,338 13,680 2018 OTW - Typical 2002

16,428 11,204 4,816 7,079 69,663 19,491 2002 OTB - Typical 2002 17,449 10,888 3,643 5,889 75,570 19,491 2009 OTB - Typical 2002 N C 16,034 10,888 3,643 5,889 75,570 19,491 2009 OTW - Typical 2002 15,636 12,136 2,158 4,215 85,018 19,491 2018 OTB - Typical 2002 14,702 12,136 2,158 4,215 85,018 19,491 2018 OTW - Typical 2002

19,238 13,565 2,496 3,985 51,413 23,511 2002 OTB - Typical 2002 14,471 12,977 1,870 3,396 54,230 23,511 2009 OTB - Typical 2002 SC 14,079 12,977 1,870 3,396 54,230 23,511 2009 OTW - Typical 2002 15,601 15,092 1,154 2,718 58,441 23,511 2018 OTB - Typical 2002 15,509 15,092 1,154 2,718 58,441 23,511 2018 OTW - Typical 2002

11,918 29,130 3,919 6,756 49,131 8,730 2002 OTB - Typical 2002 15,770 27,313 2,782 5,873 51,753 8,730 2009 OTB - Typical 2002 TN 15,228 27,313 2,782 5,873 51,753 8,730 2009 OTW - Typical 2002 17,103 33,502 1,643 4,724 55,712 8,730 2018 OTB - Typical 2002 10,514 33,502 1,643 4,724 55,712 8,730 2018 OTW - Typical 2002

2,559 9,868 3,090 7,486 52,271 17,361 2002 OTB - Typical 2002 13,451 10,368 2,254 6,388 54,587 17,361 2009 OTB - Typical 2002 VA 11,237 10,368 2,254 6,388 54,587 17,361 2009 OTW - Typical 2002 12,366 12,062 1,641 5,241 58,141 17,361 2018 OTB - Typical 2002 10,755 12,062 1,641 5,241 58,141 17,361 2018 OTW - Typical 2002

3,356 12,154 1,003 1,941 25,850 3,239 2002 OTB - Typical 2002 29,773 12,138 703 1,699 25,835 3,239 2009 OTB - Typical 2002 WV 25,251 12,138 703 1,699 25,835 3,239 2009 OTW - Typical 2002 30,628 15,045 428 1,284 27,088 3,239 2018 OTB - Typical 2002 17,548 15,045 428 1,284 27,088 3,239 2018 OTW - Typical 2002Documentation of the Base G 2002 Base Year, 2009 and 2018, Emission Inventories for VISTASMACTEC, Inc.215Annual SO2Emissions by Source Sector0100,000200,000300,000400,000500,000600,000700,000800,000 A L A L A L F L F L F L G A G A G A K Y K Y K Y M S M S M S N C N C N C S C S C S C T N T N T N V A V A V A W V W V W V

Tons per yearFIRESAREANONROADONROADNONEGUEGU20022009 OTB2009 OTW2018 OTB2018 OTWEGU and NonEGU values based on 2002 Typical EmissionsAll Fire emissions based on Typical Year valuesDocumentation of the Base G 2002 Base Year, 2009 and 2018, Emission Inventories for VISTAS

MACTEC, Inc. 216 

### Annual SO 2 

### Emissions by Source Sector

Name EGU NONEGU ONROAD NONROAD AREA FIRES YEAR Basis AL 421,734 96,447 6,885 7,539 47,074 2,559 2002 OTB - Typical 2002 AL 465,576 100,845 635 3,463 17,818 2,559 2009 OTB - Typical 2002 AL 314,841 100,845 635 3,463 17,818 2,559 2009 OTW - Typical 2002 AL 375,305 112,771 720 2,815 49,975 2,559 2018 OTB - Typical 2002 AL 226,506 112,771 720 2,815 49,975 2,559 2018 OTW - Typical 2002

FL 443,152 70,165 20,872 17,023 40,537 4,129 2002 OTB - Typical 2002 FL 219,072 76,851 2,120 8,380 52,390 4,129 2009 OTB - Typical 2002 FL 199,834 76,851 2,120 8,380 52,390 4,129 2009 OTW - Typical 2002 FL 215,177 87,065 2,533 7,511 59,413 4,129 2018 OTB - Typical 2002 FL 126,280 87,065 2,533 7,511 59,413 4,129 2018 OTW - Typical 2002

GA 433,513 62,032 12,155 8,145 57,555 2,815 2002 OTB - Typical 2002 GA 582,078 63,348 1,254 2,588 57,377 2,815 2009 OTB - Typical 2002 GA 394,425 63,348 1,254 2,588 57,377 2,815 2009 OTW - Typical 2002 GA 554,013 70,386 1,458 1,702 61,155 2,815 2018 OTB - Typical 2002 GA 221,615 70,386 1,458 1,702 61,155 2,815 2018 OTW - Typical 2002

KY 508,139 34,026 5,974 13,739 41,805 136 2002 OTB - Typical 2002 KY 483,235 35,479 585 9,092 40,779 136 2009 OTB - Typical 2002 KY 342,670 35,479 585 9,092 40,779 136 2009 OTW - Typical 2002 KY 429,418 38,816 651 8,536 42,326 136 2018 OTB - Typical 2002 KY 225,772 38,816 651 8,536 42,326 136 2018 OTW - Typical 2002

MS 57,263 36,071 4,604 11,551 771 100 2002 OTB - Typical 2002 MS 76,855 35,028 397 7,232 637 100 2009 OTB - Typical 2002 MS 76,855 35,028 397 7,232 637 100 2009 OTW - Typical 2002 MS 74,505 40,318 441 6,638 831 100 2018 OTB - Typical 2002 MS 23,768 40,318 441 6,638 831 100 2018 OTW - Typical 2002

N C 472,192 51,049 13,343 7,207 7,096 423 2002 OTB - Typical 2002 N C 182,356 52,693 1,311 1,798 7,607 423 2009 OTB - Typical 2002 N C 132,054 52,693 1,311 1,798 7,607 423 2009 OTW - Typical 2002 N C 133,691 58,671 1,323 838 8,273 423 2018 OTB - Typical 2002 N C 78,205 58,671 1,323 838 8,273 423 2018 OTW - Typical 2002

SC 203,978 56,329 5,958 4,449 12,900 1,187 2002 OTB - Typical 2002 SC 163,560 53,746 556 1,633 12,945 1,187 2009 OTB - Typical 2002 SC 143,492 53,746 556 1,633 12,945 1,187 2009 OTW - Typical 2002 SC 178,938 60,300 643 1,195 13,517 1,187 2018 OTB - Typical 2002 SC 152,457 60,300 643 1,195 13,517 1,187 2018 OTW - Typical 2002

TN 325,779 90,374 9,184 10,413 29,897 59 2002 OTB - Typical 2002 TN 436,453 85,275 831 5,649 29,787 59 2009 OTB - Typical 2002 TN 279,931 85,275 831 5,649 29,787 59 2009 OTW - Typical 2002 TN 323,654 92,396 944 5,205 31,047 59 2018 OTB - Typical 2002 TN 103,602 92,396 944 5,205 31,047 59 2018 OTW - Typical 2002

VA 234,714 68,038 7,218 8,796 9,510 99 2002 OTB - Typical 2002 VA 220,686 76,081 900 2,248 10,619 99 2009 OTB - Typical 2002 VA 140,665 76,081 900 2,248 10,619 99 2009 OTW - Typical 2002 VA 181,338 85,351 1,059 1,217 11,479 99 2018 OTB - Typical 2002 VA 115,987 85,351 1,059 1,217 11,479 99 2018 OTW - Typical 2002

WV 497,991 54,045 2,489 2,305 11,667 16 2002 OTB - Typical 2002 WV 598,555 54,701 227 392 12,156 16 2009 OTB - Typical 2002 WV 246,851 54,701 227 392 12,156 16 2009 OTW - Typical 2002 WV 482,959 60,141 255 56 13,450 16 2018 OTB - Typical 2002 WV 111,937 60,141 255 56 13,450 16 2018 OTW - Typical 2002Documentation of the Base G 2002 Base Year, 2009 and 2018, Emission Inventories for VISTASMACTEC, Inc.217Annual VOC Emissions by Source Sector0200,000400,000600,000800,0001,000,0001,200,0001,400,000 A L F L G A K Y M S N C S C T N V A W V

Tons per yearFIRESAREANONROADONROADNONEGUEGU20022009 OTB2009 OTW2018 OTB2018 OTWEGU and NonEGU values based on 2002 Typical EmissionsAll Fire emissions based on Typical Year valuesDocumentation of the Base G 2002 Base Year, 2009 and 2018, Emission Inventories for VISTAS

MACTEC, Inc. 218 

### Annual VOC Emissions by Source Sector

Name EGU NONEGU ONROAD NONROAD AREA FIRES YEAR Basis 1,501 47,893 119,790 44,978 196,538 26,526 2002 OTB - Typical 2002 1,261 47,600 72,848 35,498 157,405 26,526 2009 OTB - Typical 2002 AL 1,312 47,600 72,848 35,498 157,405 26,526 2009 OTW - Typical 2002 1,574 55,373 47,296 26,338 168,507 26,526 2018 OTB - Typical 2002 1,612 55,373 47,296 26,338 168,507 26,526 2018 OTW - Typical 2002
2,362 36,301 495,225 201,960 439,019 51,527 2002 OTB - Typical 2002 1,562 39,255 323,290 144,749 462,198 51,527 2009 OTB - Typical 2002 FL 1,559 39,255 323,290 144,749 462,198 51,527 2009 OTW - Typical 2002 2,052 46,049 216,620 128,131 533,141 51,527 2018 OTB - Typical 2002 1,988 46,049 216,620 128,131 533,141 51,527 2018 OTW - Typical 2002

984 33,753 267,378 63,337 309,411 33,918 2002 OTB - Typical 2002 1,497 34,153 184,239 46,722 294,204 33,918 2009 OTB - Typical 2002 GA 1,499 34,153 184,239 46,722 294,204 33,918 2009 OTW - Typical 2002 1,794 40,354 105,507 36,014 342,661 33,918 2018 OTB - Typical 2002 1,790 40,354 105,507 36,014 342,661 33,918 2018 OTW - Typical 2002
1,518 44,854 98,311 34,156 100,174 3,338 2002 OTB - Typical 2002 1,594 47,733 63,258 23,980 94,253 3,338 2009 OTB - Typical 2002 KY 1,580 47,733 63,258 23,980 94,253 3,338 2009 OTW - Typical 2002 1,635 55,729 39,084 20,795 102,117 3,338 2018 OTB - Typical 2002 1,616 55,729 39,084 20,795 102,117 3,338 2018 OTW - Typical 2002

696 43,401 82,810 32,401 135,106 13,625 2002 OTB - Typical 2002 584 38,119 49,670 27,650 125,382 13,625 2009 OTB - Typical 2002 MS 590 38,119 49,670 27,650 125,382 13,625 2009 OTW - Typical 2002 766 45,966 30,734 20,576 139,419 13,625 2018 OTB - Typical 2002 827 45,966 30,734 20,576 139,419 13,625 2018 OTW - Typical 2002
1,043 72,856 253,374 71,378 346,060 12,499 2002 OTB - Typical 2002 1,100 70,146 163,803 52,430 252,553 12,499 2009 OTB - Typical 2002 NC 1,093 70,146 163,803 52,430 252,553 12,499 2009 OTW - Typical 2002 1,183 75,985 88,620 40,576 234,207 12,499 2018 OTB - Typical 2002 1,172 75,985 88,620 40,576 234,207 12,499 2018 OTW - Typical 2002
438 38,493 106,792 41,374 187,466 14,666 2002 OTB - Typical 2002 601 36,410 67,281 30,531 176,104 14,666 2009 OTB - Typical 2002 SC 626 36,410 67,281 30,531 176,104 14,666 2009 OTW - Typical 2002 745 44,586 44,700 24,989 196,946 14,666 2018 OTB - Typical 2002 754 44,586 44,700 24,989 196,946 14,666 2018 OTW - Typical 2002
819 87,975 169,914 49,056 161,069 5,153 2002 OTB - Typical 2002 866 89,128 108,200 38,686 160,265 5,153 2009 OTB - Typical 2002 TN 854 89,128 108,200 38,686 160,265 5,153 2009 OTW - Typical 2002 899 111,372 64,665 28,667 188,977 5,153 2018 OTB - Typical 2002 826 111,372 64,665 28,667 188,977 5,153 2018 OTW - Typical 2002
672 42,589 144,684 57,050 129,792 912 2002 OTB - Typical 2002 546 44,359 89,678 40,897 120,022 912 2009 OTB - Typical 2002 VA 503 44,359 89,678 40,897 120,022 912 2009 OTW - Typical 2002 694 53,968 60,454 34,412 128,160 912 2018 OTB - Typical 2002 674 53,968 60,454 34,412 128,160 912 2018 OTW - Typical 2002
1,128 14,599 40,066 14,805 61,490 2,184 2002 OTB - Typical 2002 1,442 14,015 23,907 14,249 57,082 2,184 2009 OTB - Typical 2002 WV 1,397 14,015 23,907 14,249 57,082 2,184 2009 OTW - Typical 2002 1,471 16,636 15,463 9,500 62,164 2,184 2018 OTB - Typical 2002 1,456 16,636 15,463 9,500 62,164 2,184 2018 OTW - Typical 2002Documentation of the Base G 2002 Base Year, 2009 and 2018, Emission Inventories for VISTAS

MACTEC, Inc. 219 

### APPENDIX B:

STATE VMT TOTALSDocumentation of the Base G 2002 Base Year, 2009 and 2018, Emission Inventories for VISTAS

MACTEC, Inc. 220 

### State VMT Totals

Million Miles Per Year

2002 LDGV LDGT1 LDGT2 HDDV LDDV LDDT HDDV MC TOTAL AL 31,982 12,728 4,347 1,630 63 69 4,709 196 55,723 FL 105,340 40,835 13,945 5,079 206 220 12,465 591 178,681 GA 61,660 24,394 8,331 3,103 121 132 8,673 371 106,785 KY 28,751 12,189 3,366 1,606 55 55 4,827 171 51,020 MS 23,933 6,724 439 1,025 330 125 3,610 92 36,278 NC 51,189 30,339 10,787 4,119 230 230 9,440 461 106,795 SC 26,672 10,750 3,671 1,395 52 58 4,306 171 47,074 TN 30,809 20,272 6,922 2,943 52 111 6,810 397 68,316 VA 36,336 24,784 8,667 2,148 61 139 4,969 369 77,472 WV 9,010 5,931 2,028 732 25 37 1,664 117 19,544

2009 LDGV LDGT1 LDGT2 HDDV LDDV LDDT HDDV MC TOTAL AL 30,638 18,598 5,511 2,069 65 72 5,976 249 63,178 FL 107,641 62,449 18,697 6,820 215 230 16,743 794 213,590 GA 61,569 36,641 10,933 4,077 126 137 11,374 487 125,343 KY 28,006 16,984 4,428 1,983 58 57 5,983 231 57,729 MS 23,641 10,131 573 1,341 356 135 4,719 120 41,017 NC 48,495 43,484 15,122 4,576 40 224 10,928 527 123,396 SC 26,451 16,119 4,796 1,824 55 61 5,617 223 55,147 TN 28,775 28,650 8,521 3,627 52 111 8,391 490 78,615 VA 33,663 34,814 10,597 2,624 61 137 6,073 451 88,419 WV 8,128 8,205 2,427 878 25 37 1,995 140 21,835

2018 LDGV LDGT1 LDGT2 HDDV LDDV LDDT HDDV MC TOTAL AL 31,706 23,562 6,990 2,634 67 84 7,607 317 72,966 FL 116,576 83,385 24,996 9,156 221 301 22,491 1,066 258,191 GA 65,214 47,687 14,245 5,332 129 171 14,853 637 148,269 KY 29,353 21,058 5,558 2,463 60 66 7,454 288 66,300 MS 24,787 12,984 736 1,727 372 159 6,076 155 46,996 NC 42,247 51,568 18,260 4,985 279 279 11,396 553 129,566 SC 27,930 20,880 6,220 2,375 57 75 7,306 290 65,133 TN 29,253 35,702 10,629 4,538 52 130 10,500 613 91,417 VA 35,030 44,438 13,543 3,358 62 164 7,770 578 104,944 WV 8,130 10,025 2,969 1,078 25 41 2,451 172 24,891Documentation of the Base G 2002 Base Year, 2009 and 2018, Emission Inventories for VISTAS

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### APPENDIX C:

STATE TIER 1 EMISSION TOTALSDocumentation of the Base G 2002 Base Year, 2009 and 2018, Emission Inventories for VISTAS

MACTEC, Inc. 222 

### State Tier 1 Emission Totals

State Year TIER1 TIER 1 NAME CO NH3 NOX PM10 PM2.5 SO2 VOC AL 2002 01 FUEL COMB. ELEC. UTIL. 11,460 239 154,704 7,845 4,176 423,736 2,288 AL 2002 02 FUEL COMB. INDUSTRIAL 67,121 234 51,527 6,729 3,791 40,918 2,237 AL 2002 03 FUEL COMB. OTHER 70, 498 169 19,237 6,411 5,528 39,606 56,120 AL 2002 04 CHEMICAL & ALLIED PRODUCT 5,721 35 2,032 1,220 888 12,770 7,273 AL 2002 05 METALS PROCESSING 38,247 376 6,011 9,107 7,803 14,039 3,299 AL 2002 06 PETROLEUM & RELATED 13,606 0 878 194 155 22,991 4,024 AL 2002 07 OTHER INDUSTRIAL PROCESSE S 47,676 1,468 25,252 22, 689 9,516 17,904 25,304 AL 2002 08 SOLVENT UTILIZATION 216 0 226 149 126 3 108,437 AL 2002 09 STORAGE & TRANSPORT 174 0 230 1,086 636 13 16,522 AL 2002 10 WASTE DISPOSAL & RECYCL ING 86,302 10 3,465 13,960 13,073 489 11,334 AL 2002 11 HIGHWAY VEHICLES 1,366, 056 5,576 158,423 3,898 2,794 6,885 119,790 AL 2002 12 OFF-HIGHWAY 414,385 33 65,366 4,787 4,502 7,584 60,487 AL 2002 14 MISCELLANEOUS 442,778 59,864 9,343 408,115 79,127 2,559 21,686 2002 Total 2,564,239 68,005 496, 695 486,190 132,115 589,499 438,800
AL 2009 01 FUEL COMB. ELEC. UTIL. 14,986 359 82,305 6,969 3,921 378,052 2,473 AL 2009 02 FUEL COMB. INDUSTRIAL 68,146 274 36,301 6,140 3,438 40,651 2,191 AL 2009 03 FUEL COMB. OTHER 52, 256 158 19,514 5,904 5,104 36,048 31,403 AL 2009 04 CHEMICAL & ALLIED PRODUCT 6,118 38 2,273 1,257 912 13,660 6,613 AL 2009 05 METALS PROCESSING 38,969 500 6,021 9,062 7,756 16,629 3,305 AL 2009 06 PETROLEUM & RELATED 13,241 0 858 221 177 22,495 3,336 AL 2009 07 OTHER INDUSTRIAL PROCESSE S 52,004 1,571 26,340 24, 196 10,197 19,383 26,519 AL 2009 08 SOLVENT UTILIZATION 247 0 257 165 139 4 92,631 AL 2009 09 STORAGE & TRANSPORT 192 0 253 1,146 584 14 17,738 AL 2009 10 WASTE DISPOSAL & RECYCL ING 87,225 11 3,634 14,504 13,485 590 11,207 AL 2009 11 HIGHWAY VEHICLES 942, 793 6,350 101,323 3,188 2,049 635 72,848 AL 2009 12 OFF-HIGHWAY 454,686 36 56,862 4,027 3,776 3,471 50,249 AL 2009 14 MISCELLANEOUS 463,498 65,899 9,788 428,698 82,679 2,681 22,657 2009 Total 2,194,361 75,195 345, 729 505,475 134,217 534,314 343,169
AL 2018 01 FUEL COMB. ELEC. UTIL. 24,342 1,072 64,358 7,822 4,768 305,262 2,952 AL 2018 02 FUEL COMB. INDUSTRIAL 69,198 275 38,781 6,462 3,613 43,170 2,295 AL 2018 03 FUEL COMB. OTHER 43, 744 164 20,185 5,641 4,818 37,162 21,215 AL 2018 04 CHEMICAL & ALLIED PRODUCT 7,384 46 2,804 1,523 1,106 16,509 8,040 AL 2018 05 METALS PROCESSING 49,770 674 7,519 11,036 9,423 21,824 4,234 AL 2018 06 PETROLEUM & RELATED 13,002 0 848 258 207 22,242 3,421 AL 2018 07 OTHER INDUSTRIAL PROCESSE S 60,452 1,732 30,831 27, 727 11,812 21,843 30,267 AL 2018 08 SOLVENT UTILIZATION 301 0 317 200 169 4 112,412 AL 2018 09 STORAGE & TRANSPORT 234 0 307 1,366 699 17 18,900 AL 2018 10 WASTE DISPOSAL & RECYCL ING 88,758 13 3,867 15,343 14,143 718 11,938 AL 2018 11 HIGHWAY VEHICLES 797, 966 7,296 46,222 2,488 1,262 720 47,296 AL 2018 12 OFF-HIGHWAY 488,924 42 43,799 3,041 2,835 2,818 40,407 AL 2018 14 MISCELLANEOUS 464,235 73,529 9,803 458,551 85,538 2,686 22,686 2018 Total 2,108,311 84,843 269, 643 541,458 140,394 474,974 326,063Documentation of the Base G 2002 Base Year, 2009 and 2018, Emission Inventories for VISTAS

MACTEC, Inc. 223 

### State Tier 1 Emission Totals

State Year TIER1 TIER 1 NAME CO NH3 NOX PM10 PM2.5 SO2 VOC FL 2002 01 FUEL COMB. ELEC. UTIL. 55,899 222 282,507 21,391 15,575 483,590 2,531 FL 2002 02 FUEL COMB. INDUSTRIAL 64,794 131 45,153 20,442 18,547 42,524 4,219 FL 2002 03 FUEL COMB. OTHER 49, 230 99 11,593 8,464 8,074 20,031 16,123 FL 2002 04 CHEMICAL & ALLIED PRODUCT 745 1,101 2,221 1,868 1,488 34,462 3,542 FL 2002 05 METALS PROCESSING 1,404 1 194 449 334 882 82 FL 2002 06 PETROLEUM & RELATED 1,070 0 560 259 129 470 724 FL 2002 07 OTHER INDUSTRIAL PROCE SSES 18,586 19 12,325 23, 419 11,844 6,515 27,024 FL 2002 08 SOLVENT UTILIZATION 0 0 1 128 110 0 304,582 FL 2002 09 STORAGE & TRANSPORT 161 0 561 1,645 720 38 79,281 FL 2002 10 WASTE DISPOSAL & RECYCL ING 175,989 351 6,123 22,142 21,604 659 17,449 FL 2002 11 HIGHWAY VEHICLES 4,693, 893 18,078 466,098 11,253 7,852 20,872 495,225 FL 2002 12 OFF-HIGHWAY 1,920,729 134 180,627 18,281 17,415 20,614 272,072 FL 2002 14 MISCELLANEOUS 764,337 40,324 15,083 498,855 115,287 4,129 41,274 2002 Total 7,746,839 60,460 1,023,045 628,597 218,979 634,786 1,264,128
FL 2009 01 FUEL COMB. ELEC. UTIL. 35,928 1,631 86,165 9,007 5,910 186,055 1,910 FL 2009 02 FUEL COMB. INDUSTRIAL 69,972 146 44,480 16,265 14,827 38,225 4,473 FL 2009 03 FUEL COMB. OTHER 33, 014 100 10,800 7,555 7,174 19,882 10,907 FL 2009 04 CHEMICAL & ALLIED PRODUCT 901 1,231 2,461 1,908 1,526 34,961 3,821 FL 2009 05 METALS PROCESSING 1,545 1 176 361 251 993 82 FL 2009 06 PETROLEUM & RELATED 1,190 0 612 304 156 519 748 FL 2009 07 OTHER INDUSTRIAL PROCE SSES 18,593 26 13,521 33, 084 19,357 6,881 26,413 FL 2009 08 SOLVENT UTILIZATION 0 0 1 132 113 0 319,723 FL 2009 09 STORAGE & TRANSPORT 187 0 621 1,661 727 50 83,880 FL 2009 10 WASTE DISPOSAL & RECYCL ING 177,953 342 6,251 22,971 22,364 698 17,241 FL 2009 11 HIGHWAY VEHICLES 3,446, 095 21,737 314,307 9,953 6,216 2,120 323,290 FL 2009 12 OFF-HIGHWAY 2,104,920 148 163,794 15,613 14,866 8,967 209,543 FL 2009 14 MISCELLANEOUS 764,004 41,471 15,075 557,331 120,796 4,129 41,290 2009 Total 6,654,301 66,833 658,265 676,145 214,282 303,479 1,043,321
FL 2018 01 FUEL COMB. ELEC. UTIL. 53,772 2,976 73,125 9,953 6,843 132,177 2,376 FL 2018 02 FUEL COMB. INDUSTRIAL 76,847 156 47,835 17,808 16,255 40,443 4,892 FL 2018 03 FUEL COMB. OTHER 27, 094 110 12,344 7,254 6,852 20,975 8,878 FL 2018 04 CHEMICAL & ALLIED PRODUCT 1,200 1,448 3,119 2,367 1,907 41,395 4,739 FL 2018 05 METALS PROCESSING 1,973 2 225 466 323 1,325 106 FL 2018 06 PETROLEUM & RELATED 1,513 0 778 387 198 659 918 FL 2018 07 OTHER INDUSTRIAL PROCE SSES 20,748 35 15,855 39, 871 23,301 7,741 29,716 FL 2018 08 SOLVENT UTILIZATION 0 0 1 158 135 0 387,657 FL 2018 09 STORAGE & TRANSPORT 226 0 690 2,008 879 58 87,732 FL 2018 10 WASTE DISPOSAL & RECYCL ING 180,730 418 6,486 24,140 23,427 769 18,335 FL 2018 11 HIGHWAY VEHICLES 3,086, 330 26,154 154,611 8,489 4,242 2,533 216,620 FL 2018 12 OFF-HIGHWAY 2,323,327 171 127,885 12,497 11,868 7,536 183,452 FL 2018 14 MISCELLANEOUS 763,701 43,251 15,068 628,984 127,364 4,129 41,338 2018 Total 6,537,461 74,720 458, 023 754,381 223,592 259,739 986,760Documentation of the Base G 2002 Base Year, 2009 and 2018, Emission Inventories for VISTAS

MACTEC, Inc. 224 

### State Tier 1 Emission Totals

State Year TIER1 TIER 1 NAME CO NH3 NOX PM10 PM2.5 SO2 VOC GA 2002 01 FUEL COMB. ELEC. UTIL. 9,650 86 148,126 11,467 5,070 517,633 1,256 GA 2002 02 FUEL COMB. INDUSTRIAL 59,492 27 53,039 12,037 7,886 88,791 3,956 GA 2002 03 FUEL COMB. OTHER 63, 314 17 14,465 10,142 10,057 10,740 27,226 GA 2002 04 CHEMICAL & ALLIED PRODUCT 5,387 920 2,277 391 305 2,721 2,668 GA 2002 05 METALS PROCESSING 330 0 60 147 94 0 70 GA 2002 06 PETROLEUM & RELATED 41 0 3 69 44 68 175 GA 2002 07 OTHER INDUSTRIAL PROCESSE S 27,960 2,666 12,215 39, 630 13,073 8,701 26,999 GA 2002 08 SOLVENT UTILIZATION 4 0 22 13 13 0 234,744 GA 2002 09 STORAGE & TRANSPORT 39 0 6 583 360 0 26,334 GA 2002 10 WASTE DISPOSAL & RECYCL ING 203,892 16 6,872 29,227 28,311 312 18,964 GA 2002 11 HIGHWAY VEHICLES 2,833,468 10,524 308,013 7,236 5,158 12,155 267,378 GA 2002 12 OFF-HIGHWAY 791,158 60 97,961 8,618 8,226 9,005 85,965 GA 2002 14 MISCELLANEOUS 498,622 83, 032 10,279 687,028 116,756 2,815 25,618 2002 Total 4,493,357 97,349 653, 338 806,587 195,354 652,942 721,352
GA 2009 01 FUEL COMB. ELEC. UTIL. 23,721 686 98,497 17,891 10,907 417,449 2,314 GA 2009 02 FUEL COMB. INDUSTRIAL 63,067 28 53,726 11,206 7,390 89,850 4,163 GA 2009 03 FUEL COMB. OTHER 45, 184 17 15,347 8,496 8,400 10,981 15,683 GA 2009 04 CHEMICAL & ALLIED PRODUCT 6,044 1,032 2,531 436 341 2,743 2,814 GA 2009 05 METALS PROCESSING 363 0 61 159 100 0 47 GA 2009 06 PETROLEUM & RELATED 50 0 4 83 54 82 154 GA 2009 07 OTHER INDUSTRIAL PROCESSE S 29,976 2,902 12,528 45, 339 14,758 7,662 28,441 GA 2009 08 SOLVENT UTILIZATION 4 0 25 14 14 0 216,248 GA 2009 09 STORAGE & TRANSPORT 45 0 7 649 401 0 27,821 GA 2009 10 WASTE DISPOSAL & RECYCL ING 218,460 18 7,419 31,955 30,900 360 18,711 GA 2009 11 HIGHWAY VEHICLES 2,053,694 12,660 208,393 6,103 3,869 1,254 184,239 GA 2009 12 OFF-HIGHWAY 882,970 68 85,733 7,521 7,175 2,725 67,686 GA 2009 14 MISCELLANEOUS 515,329 91, 406 10,637 765,043 125,665 2,914 26,388 2009 Total 3,838,907 108,817 494, 908 894,896 209,973 536,020 594,708 GA 2018 01 FUEL COMB. ELEC. UTIL. 44, 476 1,677 75,717 20,909 13,983 230,856 2,841 GA 2018 02 FUEL COMB. INDUSTRIAL 67,067 30 57,232 11,755 7,769 94,403 4,424 GA 2018 03 FUEL COMB. OTHER 39, 440 17 17,801 7,722 7,622 11,958 11,482 GA 2018 04 CHEMICAL & ALLIED PRODUCT 7,076 1,208 2,982 517 405 3,436 3,524 GA 2018 05 METALS PROCESSING 421 0 76 185 118 0 55 GA 2018 06 PETROLEUM & RELATED 63 0 5 105 68 104 191 GA 2018 07 OTHER INDUSTRIAL PROCESSE S 33,611 3,559 14,460 55, 130 17,899 8,748 33,333 GA 2018 08 SOLVENT UTILIZATION 5 0 30 22 22 0 264,326 GA 2018 09 STORAGE & TRANSPORT 54 0 9 764 470 0 29,409 GA 2018 10 WASTE DISPOSAL & RECYCL ING 235,690 22 8,120 35,280 34,038 423 20,411 GA 2018 11 HIGHWAY VEHICLES 1,765,020 14,871 99,821 4,995 2,517 1,458 105,507 GA 2018 12 OFF-HIGHWAY 973,872 79 64,579 6,015 5,730 1,709 56,761 GA 2018 14 MISCELLANEOUS 515,220 102, 075 10,635 859,835 134,730 2,914 26,368 2018 Total 3,682,015 123,537 351,467 1,003,235 225,372 356,010 558,631Documentation of the Base G 2002 Base Year, 2009 and 2018, Emission Inventories for VISTAS

MACTEC, Inc. 225 

### State Tier 1 Emission Totals

State Year TIER1 TIER 1 NAME CO NH3 NOX PM10 PM2.5 SO2 VOC KY 2002 01 FUEL COMB. ELEC. UTIL. 12,607 321 201,928 4,795 2,847 495,153 1,481 KY 2002 02 FUEL COMB. INDUSTRIAL 14,110 182 60,716 2,155 1,463 41,825 1,566 KY 2002 03 FUEL COMB. OTHER 40,806 55 4,997 7,679 7,352 9,647 12,711 KY 2002 04 CHEMICAL & ALLIED PRODUCT 176 214 296 774 581 2,345 3,462 KY 2002 05 METALS PROCESSING 89,197 6 1,082 3,396 2,720 12,328 1,508 KY 2002 06 PETROLEUM & RELATED 4,304 335 2,519 308 205 5,747 2,895 KY 2002 07 OTHER INDUSTRIAL PROCESSES 6,493 78 6,518 31,429 10,394 3,333 25,388 KY 2002 08 SOLVENT UTILIZATION 0 10 9 317 241 1 61,834 KY 2002 09 STORAGE & TRANSPORT 33 8 15 1,920 1,177 3 18,853 KY 2002 10 WASTE DISPOSAL & RECYCLING 20,622 8 1,768 7,229 6,476 606 7,927 KY 2002 11 HIGHWAY VEHICLES 1,260,682 5,044 154,899 3, 720 2,693 5,974 98,311 KY 2002 12 OFF-HIGHWAY 325,993 31 104,571 6,425 6,046 14,043 44,805 KY 2002 14 MISCELLANEOUS 25,849 51,026 556 197,402 28,291 146 5,238 2002 Total 1,800,871 57,318 539, 873 267,547 70,486 591,151 285,977
KY 2009 01 FUEL COMB. ELEC. UTIL. 15,812 400 92,021 6,463 4,279 290,193 1,369 KY 2009 02 FUEL COMB. INDUSTRIAL 14,986 195 61,683 2,105 1,456 42,433 1,476 KY 2009 03 FUEL COMB. OTHER 30,045 54 5,178 7,035 6,725 10,123 9,148 KY 2009 04 CHEMICAL & ALLIED PRODUCT 179 249 300 851 633 2,384 3,635 KY 2009 05 METALS PROCESSING 99,428 7 1,156 3,246 2,550 13,735 1,772 KY 2009 06 PETROLEUM & RELATED 4,818 377 2,828 344 230 6,460 3,052 KY 2009 07 OTHER INDUSTRIAL PROCESSES 7,212 84 6,674 32,194 10,912 3,634 27,548 KY 2009 08 SOLVENT UTILIZATION 0 10 11 371 283 1 62,595 KY 2009 09 STORAGE & TRANSPORT 38 9 18 2,064 1,268 3 20,038 KY 2009 10 WASTE DISPOSAL & RECYCLING 22,388 9 1,979 7,770 6,925 733 7,725 KY 2009 11 HIGHWAY VEHICLES 942,350 5,795 97,912 3,002 1,941 585 63,258 KY 2009 12 OFF-HIGHWAY 357,800 34 94,752 5,544 5,203 9,180 38,558 KY 2009 14 MISCELLANEOUS 32,627 52,915 702 206,463 29,601 187 6,335 2009 Total 1,527,684 60,137 365, 214 277,453 72,006 379,651 246,509
KY 2018 01 FUEL COMB. ELEC. UTIL. 17,144 476 64,378 6,694 4,434 226,062 1,426 KY 2018 02 FUEL COMB. INDUSTRIAL 15,692 205 64,533 2,203 1,528 43,772 1,555 KY 2018 03 FUEL COMB. OTHER 24,764 53 5,550 6,469 6,169 9,947 7,479 KY 2018 04 CHEMICAL & ALLIED PRODUCT 219 317 367 1,054 781 2,884 4,384 KY 2018 05 METALS PROCESSING 114,470 9 1,508 3,898 3,065 15,800 2,343 KY 2018 06 PETROLEUM & RELATED 5,495 434 3,244 392 262 7,426 3,394 KY 2018 07 OTHER INDUSTRIAL PROCESSES 8,303 93 7,872 35,349 12,377 4,141 31,394 KY 2018 08 SOLVENT UTILIZATION 0 12 14 464 352 1 73,525 KY 2018 09 STORAGE & TRANSPORT 44 10 21 2,408 1,481 4 21,196 KY 2018 10 WASTE DISPOSAL & RECYCLING 24,677 11 2,256 8,481 7,518 894 8,392 KY 2018 11 HIGHWAY VEHICLES 782,423 6,584 42,104 2,283 1,160 651 39,084 KY 2018 12 OFF-HIGHWAY 381,215 40 79,392 4,556 4,256 8,592 30,920 KY 2018 14 MISCELLANEOUS 33,931 55,118 729 218,725 30,626 196 7,254 2018 Total 1,408,378 63,361 271, 967 292,975 74,010 320,369 232,347Documentation of the Base G 2002 Base Year, 2009 and 2018, Emission Inventories for VISTAS

MACTEC, Inc. 226 

### State Tier 1 Emission Totals

State Year TIER1 TIER 1 NAME CO NH3 NOX PM10 PM2.5 SO2 VOC MS 2002 01 FUEL COMB. ELEC. UTIL. 5,219 198 40,433 1,706 1,147 60,086 629 MS 2002 02 FUEL COMB. INDUSTRIAL 22,710 28 48,726 5,007 3,634 9,740 8,023 MS 2002 03 FUEL COMB. OTHER 36,752 34 4,502 5,445 5,414 789 22,923 MS 2002 04 CHEMICAL & ALLIED PRODUCT 15,410 361 1,725 849 440 1,663 2,375 MS 2002 05 METALS PROCESSING 1,031 0 115 122 58 36 371 MS 2002 06 PETROLEUM & RELATED 975 20 1,187 790 335 15,560 20,788 MS 2002 07 OTHER INDUSTRIAL PROCESSES 13,884 747 9,219 27,617 8,051 8,866 15,525 MS 2002 08 SOLVENT UTILIZATION 45 7 105 219 178 1 80,760 MS 2002 09 STORAGE & TRANSPORT 74 0 80 124 38 40 23,327 MS 2002 10 WASTE DISPOSAL & RECYCLING 1,414 9 89 447 324 31 886 MS 2002 11 HIGHWAY VEHICLES 894,639 3,577 111,791 2,856 2,109 4,604 82,810 MS 2002 12 OFF-HIGHWAY 236,752 23 88,787 5,010 4,690 11,315 41,081 MS 2002 14 MISCELLANEOUS 14,529 58,746 312 323,622 43,028 84 708 2002 Total 1,243,435 63,753 307, 072 373,815 69,446 112,814 300,206
MS 2009 01 FUEL COMB. ELEC. UTIL. 5,051 334 36,011 4,957 4,777 76,579 404 MS 2009 02 FUEL COMB. INDUSTRIAL 24,607 30 44,095 3,728 2,787 7,388 8,007 MS 2009 03 FUEL COMB. OTHER 26,023 33 4,514 5,278 5,245 751 17,445 MS 2009 04 CHEMICAL & ALLIED PRODUCT 16,141 405 1,955 941 488 1,880 2,614 MS 2009 05 METALS PROCESSING 1,098 0 128 129 62 37 402 MS 2009 06 PETROLEUM & RELATED 1,101 23 1,262 894 379 7,926 13,317 MS 2009 07 OTHER INDUSTRIAL PROCESSES 14,181 197 8,376 31,381 8,629 8,254 16,282 MS 2009 08 SOLVENT UTILIZATION 50 8 118 239 194 1 80,393 MS 2009 09 STORAGE & TRANSPORT 92 0 100 172 59 49 23,494 MS 2009 10 WASTE DISPOSAL & RECYCLING 1,486 10 95 473 339 32 743 MS 2009 11 HIGHWAY VEHICLES 628,151 4,026 69,949 2,290 1,522 397 49,670 MS 2009 12 OFF-HIGHWAY 257,453 25 80,567 4,270 3,985 7,191 36,197 MS 2009 14 MISCELLANEOUS 48,314 63,886 1,037 337,018 46,695 283 2,295 2009 Total 1,023,747 68,978 248, 207 391,770 75,160 110,767 251,261
MS 2018 01 FUEL COMB. ELEC. UTIL. 15,282 827 10,271 7,187 7,033 15,146 1,114 MS 2018 02 FUEL COMB. INDUSTRIAL 27,056 33 46,929 4,093 3,058 8,169 8,559 MS 2018 03 FUEL COMB. OTHER 20,900 32 4,767 4,964 4,928 726 14,670 MS 2018 04 CHEMICAL & ALLIED PRODUCT 20,175 475 2,337 1,132 588 2,242 3,290 MS 2018 05 METALS PROCESSING 1,357 0 167 160 79 48 461 MS 2018 06 PETROLEUM & RELATED 1,267 26 1,438 1,010 430 19,028 14,407 MS 2018 07 OTHER INDUSTRIAL PROCESSES 16,267 216 9,996 38,494 10,494 9,657 20,301 MS 2018 08 SOLVENT UTILIZATION 60 9 141 301 244 1 98,354 MS 2018 09 STORAGE & TRANSPORT 115 0 124 210 73 62 24,537 MS 2018 10 WASTE DISPOSAL & RECYCLING 1,638 12 114 533 372 34 870 MS 2018 11 HIGHWAY VEHICLES 528,898 4,565 29,717 1,688 876 441 30,734 MS 2018 12 OFF-HIGHWAY 270,726 29 68,252 3,452 3,203 6,638 28,842 MS 2018 14 MISCELLANEOUS 50,160 70,096 1,076 352,321 47,869 294 2,377 2018 Total 953,900 76,320 175,329 415,546 79,246 62,486 248,517Documentation of the Base G 2002 Base Year, 2009 and 2018, Emission Inventories for VISTAS

MACTEC, Inc. 227 

### State Tier 1 Emission Totals

State Year TIER1 TIER 1 NAME CO NH3 NOX PM10 PM2.5 SO2 VOC NC 2002 01 FUEL COMB. ELEC. UTIL. 14,074 55 148,809 22,994 16,623 478,488 986 NC 2002 02 FUEL COMB. INDUSTRIAL 23,578 301 48,590 5,596 4,334 33,395 2,540 NC 2002 03 FUEL COMB. OTHER 217,008 2,318 16,460 31,777 26,746 3,971 87,985 NC 2002 04 CHEMICAL & ALLIED PRODUCT 13,952 535 859 866 538 5,736 4,313 NC 2002 05 METALS PROCESSING 5,876 60 201 564 467 1,010 2,512 NC 2002 06 PETROLEUM & RELATED 461 0 174 104 52 283 140 NC 2002 07 OTHER INDUSTRIAL PROCESSES 8,552 480 7,380 25,328 8,924 3,426 18,025 NC 2002 08 SOLVENT UTILIZATION 130 307 229 524 484 26 151,383 NC 2002 09 STORAGE & TRANSPORT 66 46 53 639 354 1 16,120 NC 2002 10 WASTE DISPOSAL & RECYCLING 125,528 247 7,482 2,239 2,218 1,666 15,568 NC 2002 11 HIGHWAY VEHICLES 3,176,811 10,455 341,198 6,905 4,816 13,343 253,374 NC 2002 12 OFF-HIGHWAY 808,231 65 84,284 7,348 7,005 7,693 94,480 NC 2002 14 MISCELLANEOUS 72,673 159,069 1,561 233,551 36,414 423 3,528 2002 Total 4,466,940 173,937 657, 279 338,434 108,975 549,463 650,954
NC 2009 01 FUEL COMB. ELEC. UTIL. 14,942 445 66,517 22,152 15,949 242,286 954 NC 2009 02 FUEL COMB. INDUSTRIAL 24,871 312 38,160 5,159 3,871 30,788 2,509 NC 2009 03 FUEL COMB. OTHER 158,837 2,723 18,441 25,334 19,467 4,060 49,819 NC 2009 04 CHEMICAL & ALLIED PRODUCT 14,732 599 933 981 607 6,286 4,925 NC 2009 05 METALS PROCESSING 6,358 67 207 627 528 1,130 2,790 NC 2009 06 PETROLEUM & RELATED 556 0 212 127 64 349 162 NC 2009 07 OTHER INDUSTRIAL PROCESSES 9,211 507 8,061 28,524 9,788 3,712 18,144 NC 2009 08 SOLVENT UTILIZATION 142 335 246 549 506 28 136,114 NC 2009 09 STORAGE & TRANSPORT 75 51 55 696 380 1 17,367 NC 2009 10 WASTE DISPOSAL & RECYCLING 139,518 307 8,354 2,774 2,750 1,913 17,331 NC 2009 11 HIGHWAY VEHICLES 2,184,901 12,637 207,648 5,861 3,643 1,311 163,803 NC 2009 12 OFF-HIGHWAY 887,605 72 70,997 6,055 5,760 1,892 74,056 NC 2009 14 MISCELLANEOUS 96,825 167,131 2,080 250,912 49,956 566 4,648 2009 Total 3,538,573 185,185 421, 913 349,750 113,268 294,321 492,624
NC 2018 01 FUEL COMB. ELEC. UTIL. 20,223 663 62,346 37,376 29,791 108,492 1,345 NC 2018 02 FUEL COMB. INDUSTRIAL 26,872 341 40,897 5,594 4,222 32,507 2,702 NC 2018 03 FUEL COMB. OTHER 131,365 2,857 20,027 21,847 16,231 4,050 34,104 NC 2018 04 CHEMICAL & ALLIED PRODUCT 18,463 702 1,105 1,175 726 7,414 6,113 NC 2018 05 METALS PROCESSING 7,576 76 255 771 657 1,335 3,516 NC 2018 06 PETROLEUM & RELATED 712 0 272 162 82 448 207 NC 2018 07 OTHER INDUSTRIAL PROCESSES 10,675 559 9,259 34,339 11,601 4,357 20,978 NC 2018 08 SOLVENT UTILIZATION 169 375 277 588 540 31 152,979 NC 2018 09 STORAGE & TRANSPORT 91 59 67 808 430 2 19,511 NC 2018 10 WASTE DISPOSAL & RECYCLING 156,599 387 9,456 3,502 3,474 2,234 19,789 NC 2018 11 HIGHWAY VEHICLES 1,510,848 13,077 81,706 4,299 2,158 1,323 88,620 NC 2018 12 OFF-HIGHWAY 960,709 83 49,046 4,298 4,069 905 61,327 NC 2018 14 MISCELLANEOUS 111,705 177,474 2,399 273,030 54,376 655 5,333 2018 Total 2,956,008 196,655 277, 112 387,788 128,356 163,752 416,523Documentation of the Base G 2002 Base Year, 2009 and 2018, Emission Inventories for VISTAS

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### State Tier 1 Emission Totals

State Year TIER1 TIER 1 NAME CO NH3 NOX PM10 PM2.5 SO2 VOC SC 2002 01 FUEL COMB. ELEC. UTIL. 6,969 141 88,528 21,827 17,521 210,272 470 SC 2002 02 FUEL COMB. INDUSTRIAL 31,771 97 38,081 5,308 3,641 44,958 1,338 SC 2002 03 FUEL COMB. OTHER 75,800 65 4,367 6,261 6,166 4,318 49,171 SC 2002 04 CHEMICAL & ALLIED PRODUCT 2,526 173 25 501 318 59 8,784 SC 2002 05 METALS PROCESSING 13,833 0 450 639 408 4,160 660 SC 2002 06 PETROLEUM & RELATED 248 0 283 120 71 170 114 SC 2002 07 OTHER INDUSTRIAL PROCESSES 9,502 1,237 15,145 15,224 6,981 12,128 16,342 SC 2002 08 SOLVENT UTILIZATION 0 1 1 78 60 0 88,878 SC 2002 09 STORAGE & TRANSPORT 10 0 4 1,025 626 0 21,009 SC 2002 10 WASTE DISPOSAL & RECYCLING 67,908 10 4,063 9,172 8,641 625 15,291 SC 2002 11 HIGHWAY VEHICLES 1,275,161 4,684 140,428 3,446 2,496 5,958 106,792 SC 2002 12 OFF-HIGHWAY 413,964 33 50,249 4,152 3,945 4,866 55,016 SC 2002 14 MISCELLANEOUS 221,436 28,903 4,335 262,974 47,136 1,187 12,535 2002 Total 2,119,129 35,343 345, 960 330,728 98,009 288,701 376,401
SC 2009 01 FUEL COMB. ELEC. UTIL. 11,135 343 46,915 19,395 16,042 124,608 660 SC 2009 02 FUEL COMB. INDUSTRIAL 33,201 105 35,660 3,307 2,370 37,792 1,414 SC 2009 03 FUEL COMB. OTHER 49,914 63 4,551 5,264 5,183 4,359 25,073 SC 2009 04 CHEMICAL & ALLIED PRODUCT 2,798 173 26 543 345 60 7,409 SC 2009 05 METALS PROCESSING 15,632 0 449 631 378 4,856 663 SC 2009 06 PETROLEUM & RELATED 302 0 340 145 86 200 131 SC 2009 07 OTHER INDUSTRIAL PROCESSES 10,241 1,403 15,069 18,267 8,045 13,443 15,697 SC 2009 08 SOLVENT UTILIZATION 1 1 1 90 69 0 95,538 SC 2009 09 STORAGE & TRANSPORT 13 0 5 569 352 0 21,989 SC 2009 10 WASTE DISPOSAL & RECYCLING 70,379 11 4,215 9,526 8,977 666 15,998 SC 2009 11 HIGHWAY VEHICLES 912,280 5,510 91,696 2,878 1,870 556 67,281 SC 2009 12 OFF-HIGHWAY 448,625 36 43,235 3,471 3,294 1,701 43,061 SC 2009 14 MISCELLANEOUS 250,690 31,416 4,962 282,480 51,151 1,359 13,906 2009 Total 1,805,210 39,061 247, 124 346,565 98,163 189,601 308,820
SC 2018 01 FUEL COMB. ELEC. UTIL. 14,786 617 51,456 28,826 25,032 93,274 906 SC 2018 02 FUEL COMB. INDUSTRIAL 36,105 113 37,333 4,037 2,855 39,714 1,525 SC 2018 03 FUEL COMB. OTHER 39,627 65 5,135 4,791 4,711 4,469 16,391 SC 2018 04 CHEMICAL & ALLIED PRODUCT 3,296 212 32 664 423 74 9,107 SC 2018 05 METALS PROCESSING 18,853 0 587 773 476 5,920 868 SC 2018 06 PETROLEUM & RELATED 389 0 438 186 110 258 166 SC 2018 07 OTHER INDUSTRIAL PROCESSES 12,136 1,566 17,507 20,215 9,044 15,863 18,636 SC 2018 08 SOLVENT UTILIZATION 1 1 1 116 89 0 120,433 SC 2018 09 STORAGE & TRANSPORT 16 0 6 1,380 842 0 22,742 SC 2018 10 WASTE DISPOSAL & RECYCLING 73,403 13 4,512 10,038 9,443 735 17,167 SC 2018 11 HIGHWAY VEHICLES 800,619 6,472 42,354 2,258 1,154 643 44,700 SC 2018 12 OFF-HIGHWAY 481,332 41 31,758 2,617 2,474 1,198 36,131 SC 2018 14 MISCELLANEOUS 250,637 34,345 4,961 306,342 53,367 1,359 13,896 2018 Total 1,731,198 43,446 196,081 382,244 110,019 163,509 302,665Documentation of the Base G 2002 Base Year, 2009 and 2018, Emission Inventories for VISTAS

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### State Tier 1 Emission Totals

State Year TIER1 TIER 1 NAME CO NH3 NOX PM10 PM2.5 SO2 VOC TN 2002 01 FUEL COMB. ELEC. UTIL. 6,787 197 152,137 13,866 11,491 320,146 890 TN 2002 02 FUEL COMB. INDUSTRIAL 15,257 6 44,510 8,015 6,649 74,146 2,021 TN 2002 03 FUEL COMB. OTHER 77,857 25 15,568 7,967 7,549 16,253 18,346 TN 2002 04 CHEMICAL & ALLIED PRODUCT 36,920 1,518 1,772 3,246 2,201 6,516 24,047 TN 2002 05 METALS PROCESSING 41,371 14 1,182 7,620 7,030 5,818 6,898 TN 2002 06 PETROLEUM & RELATED 543 0 331 314 243 383 1,850 TN 2002 07 OTHER INDUSTRIAL PROCESSES 9,420 44 11,794 30,484 12,867 5,845 27,336 TN 2002 08 SOLVENT UTILIZATION 275 1 5,066 2,103 1,818 58 110,872 TN 2002 09 STORAGE & TRANSPORT 22 24 105 1,249 736 134 21,962 TN 2002 10 WASTE DISPOSAL & RECYCLING 22,143 31 1,839 7,068 6,469 349 15,505 TN 2002 11 HIGHWAY VEHICLES 1,967,658 6,616 233,324 5,338 3,919 9,184 169,914 TN 2002 12 OFF-HIGHWAY 505,163 43 96,827 6,819 6,458 10,441 66,450 TN 2002 14 MISCELLANEOUS 10,824 34,318 225 180,006 25,193 60 2,252 2002 Total 2,694,242 42,836 564, 680 274,095 92,622 449,332 468,342
TN 2009 01 FUEL COMB. ELEC. UTIL. 7,214 227 66,405 15,608 13,092 255,410 932 TN 2009 02 FUEL COMB. INDUSTRIAL 15,943 7 37,369 7,195 6,004 63,511 1,915 TN 2009 03 FUEL COMB. OTHER 61,443 27 14,793 7,134 6,786 16,955 12,781 TN 2009 04 CHEMICAL & ALLIED PRODUCT 35,440 1,719 1,958 3,519 2,400 7,056 15,594 TN 2009 05 METALS PROCESSING 45,183 15 1,245 7,337 6,823 6,537 7,676 TN 2009 06 PETROLEUM & RELATED 615 0 373 356 276 435 1,433 TN 2009 07 OTHER INDUSTRIAL PROCESSES 9,911 62 12,635 32,661 13,737 6,240 28,598 TN 2009 08 SOLVENT UTILIZATION 309 1 5,984 2,431 2,095 65 112,312 TN 2009 09 STORAGE & TRANSPORT 26 31 12 1,218 733 42 23,687 TN 2009 10 WASTE DISPOSAL & RECYCLING 23,810 35 1,993 7,618 6,968 393 14,922 TN 2009 11 HIGHWAY VEHICLES 1,361,408 7,738 147,757 4,238 2,782 831 108,200 TN 2009 12 OFF-HIGHWAY 554,121 48 86,641 5,877 5,557 5,651 55,358 TN 2009 14 MISCELLANEOUS 17,921 35,200 379 192,464 26,830 102 2,814 2009 Total 2,133,342 45,108 377, 545 287,655 94,083 363,228 386,222
TN 2018 01 FUEL COMB. ELEC. UTIL. 7,723 241 31,715 15,941 13,387 112,672 976 TN 2018 02 FUEL COMB. INDUSTRIAL 17,038 7 38,908 7,693 6,447 65,823 2,054 TN 2018 03 FUEL COMB. OTHER 54,486 30 15,503 6,757 6,412 18,091 10,269 TN 2018 04 CHEMICAL & ALLIED PRODUCT 45,455 2,053 2,424 4,443 3,044 9,088 20,071 TN 2018 05 METALS PROCESSING 52,834 17 1,589 9,579 8,953 7,790 9,956 TN 2018 06 PETROLEUM & RELATED 715 0 430 416 324 508 1,636 TN 2018 07 OTHER INDUSTRIAL PROCESSES 10,946 88 14,157 38,250 16,286 7,286 35,587 TN 2018 08 SOLVENT UTILIZATION 380 1 7,675 3,155 2,718 79 140,793 TN 2018 09 STORAGE & TRANSPORT 33 41 14 1,572 939 49 25,493 TN 2018 10 WASTE DISPOSAL & RECYCLING 26,712 42 2,326 8,562 7,828 468 17,530 TN 2018 11 HIGHWAY VEHICLES 1,150,516 8,962 65,242 3,199 1,643 944 64,665 TN 2018 12 OFF-HIGHWAY 593,100 55 70,226 4,672 4,403 5,207 45,084 TN 2018 14 MISCELLANEOUS 19,210 36,213 408 209,058 28,209 111 3,293 2018 Total 1,979,148 47,749 250, 619 313,294 100,592 228,116 377,408Documentation of the Base G 2002 Base Year, 2009 and 2018, Emission Inventories for VISTAS

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### State Tier 1 Emission Totals

State Year TIER1 TIER 1 NAME CO NH3 NOX PM10 PM2.5 SO2 VOC VA 2002 01 FUEL COMB. ELEC. UTIL. 6,797 130 85,081 3,892 2,650 233,691 747 VA 2002 02 FUEL COMB. INDUSTRIAL 64,386 100 75,807 18,480 8,453 137,448 5,332 VA 2002 03 FUEL COMB. OTHER 98,788 13 15,648 11,572 11,236 5,508 54,496 VA 2002 04 CHEMICAL & ALLIED PRODUCT 321 2,158 8,062 449 393 2,126 1,530 VA 2002 05 METALS PROCESSING 3,580 0 937 1,575 1,349 5,251 513 VA 2002 06 PETROLEUM & RELATED 23,384 0 182 255 153 170 501 VA 2002 07 OTHER INDUSTRIAL PROCESSES 12,002 726 9,279 33,409 9,795 17,702 13,086 VA 2002 08 SOLVENT UTILIZATION 0 4 0 225 210 2 111,511 VA 2002 09 STORAGE & TRANSPORT 16 7 11 745 505 0 26,121 VA 2002 10 WASTE DISPOSAL & RECYCLING 16,566 109 1,866 3,152 1,277 1,581 4,065 VA 2002 11 HIGHWAY VEHICLES 2,170,508 7,837 219,602 4,537 3,090 7,218 144,684 VA 2002 12 OFF-HIGHWAY 660,105 48 63,219 8,728 8,288 8,663 74,866 VA 2002 14 MISCELLANEOUS 13,225 43,948 285 182,193 21,835 74 706 2002 Total 3,069,678 55,080 479, 980 269,212 69,233 419,436 438,158
VA 2009 01 FUEL COMB. ELEC. UTIL. 12,509 694 66,219 5,508 4,067 225,653 778 VA 2009 02 FUEL COMB. INDUSTRIAL 67,422 105 67,263 18,346 8,345 135,612 5,483 VA 2009 03 FUEL COMB. OTHER 66,037 14 15,966 10,062 9,742 5,258 28,063 VA 2009 04 CHEMICAL & ALLIED PRODUCT 286 2,082 7,790 477 413 1,996 1,419 VA 2009 05 METALS PROCESSING 3,397 0 827 1,563 1,332 4,813 390 VA 2009 06 PETROLEUM & RELATED 26,288 0 197 275 169 187 557 VA 2009 07 OTHER INDUSTRIAL PROCESSES 12,471 733 9,425 33,961 9,984 18,871 13,394 VA 2009 08 SOLVENT UTILIZATION 0 5 0 248 231 3 110,127 VA 2009 09 STORAGE & TRANSPORT 17 7 12 797 544 0 26,456 VA 2009 10 WASTE DISPOSAL & RECYCLING 20,109 119 2,174 3,823 1,515 1,805 4,789 VA 2009 11 HIGHWAY VEHICLES 1,495,771 9,066 133,170 3,760 2,254 900 89,678 VA 2009 12 OFF-HIGHWAY 726,815 53 54,993 7,510 7,136 1,707 57,009 VA 2009 14 MISCELLANEOUS 21,582 46,719 464 198,040 23,990 124 1,077 2009 Total 2,452,703 59,596 358, 500 284,369 69,721 396,929 339,219
VA 2018 01 FUEL COMB. ELEC. UTIL. 15,420 622 75,594 13,775 11,976 140,233 997 VA 2018 02 FUEL COMB. INDUSTRIAL 72,218 114 70,343 19,248 8,892 140,995 5,861 VA 2018 03 FUEL COMB. OTHER 53,171 14 17,852 9,427 9,086 5,369 18,603 VA 2018 04 CHEMICAL & ALLIED PRODUCT 338 2,462 9,211 579 502 2,291 1,708 VA 2018 05 METALS PROCESSING 4,034 0 1,017 1,861 1,592 5,948 469 VA 2018 06 PETROLEUM & RELATED 30,284 0 228 315 194 217 642 VA 2018 07 OTHER INDUSTRIAL PROCESSES 14,029 877 10,836 37,553 11,276 21,294 15,636 VA 2018 08 SOLVENT UTILIZATION 0 6 0 314 293 3 127,953 VA 2018 09 STORAGE & TRANSPORT 21 8 15 949 648 0 27,357 VA 2018 10 WASTE DISPOSAL & RECYCLING 24,293 141 2,595 4,694 1,828 2,171 5,821 VA 2018 11 HIGHWAY VEHICLES 1,310,698 10,757 61,881 3,343 1,641 1,059 60,454 VA 2018 12 OFF-HIGHWAY 797,683 61 40,393 6,208 5,891 507 49,052 VA 2018 14 MISCELLANEOUS 27,223 50,279 584 218,141 26,225 158 1,322 2018 Total 2,349,413 65,342 290, 549 316,406 80,044 320,246 315,875Documentation of the Base G 2002 Base Year, 2009 and 2018, Emission Inventories for VISTAS

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### State Tier 1 Emission Totals

State Year TIER1 TIER 1 NAME CO NH3 NOX PM10 PM2.5 SO2 VOC WV 2002 01 FUEL COMB. ELEC. UTIL. 10,117 121 222,437 4,472 2,163 500,381 1,140 WV 2002 02 FUEL COMB. INDUSTRIAL 8,685 97 33,831 1,583 1,332 37,118 1,097 WV 2002 03 FUEL COMB. OTHER 29, 480 13 15,220 3,814 3,683 3,990 9,275
WV 2002 04 CHEMICAL & ALLIED PRODUCT MFG 50,835 80 1,627 950 831 9,052 5,755
WV 2002 05 METALS PROCESSING 28,837 143 1,570 8,749 7,515 5,619 1,393
WV 2002 06 PETROLEUM & RELATED INDUSTRIES 1 0 1,086 475 475 7,550 2,163
WV 2002 07 OTHER INDUSTRIAL PROCE SSES 2,003 56 5,347 18, 751 5,567 2,316 1,803 WV 2002 08 SOLVENT UTILIZATION 15 0 18 49 44 0 35,989 WV 2002 09 STORAGE & TRANSPORT 15 0 3 1,952 947 0 12,432 WV 2002 10 WASTE DISPOSAL & RECYCLING 9,395 8 599 4,153 3,731 100 5,098 WV 2002 11 HIGHWAY VEHICLES 560, 717 1,933 59,612 1,395 1,003 2,489 40,066 WV 2002 12 OFF-HIGHWAY 133,113 9 33,239 1,850 1,728 2,112 18,566 WV 2002 14 MISCELLANEOUS 2,811 9,909 61 92,633 10,458 16 157 2002 Total 836,024 12,371 374,650 140,825 39,478 570,742 134,936 WV 2009 01 FUEL COMB. ELEC. UTIL. 11,493 330 86,328 5,657 2,940 277,489 1,361 WV 2009 02 FUEL COMB. INDUSTRIAL 9,296 104 27,094 1,415 1,220 36,912 998 WV 2009 03 FUEL COMB. OTHER 21, 558 13 14,229 3,351 3,216 4,047 6,824
WV 2009 04 CHEMICAL & ALLIED PRODUCT MFG 58,271 82 1,804 987 864 10,166 5,426
WV 2009 05 METALS PROCESSING 30,939 142 1,517 7,985 6,724 5,971 1,380
WV 2009 06 PETROLEUM & RELATED INDUSTRIES 1 0 1,221 535 535 8,495 2,172
WV 2009 07 OTHER INDUSTRIAL PROCE SSES 2,288 59 4,995 19, 228 5,899 2,570 2,064 WV 2009 08 SOLVENT UTILIZATION 17 0 20 52 47 0 32,305 WV 2009 09 STORAGE & TRANSPORT 17 0 3 2,062 1,003 0 12,997 WV 2009 10 WASTE DISPOSAL & RECYCLING 9,131 8 583 4,050 3,632 97 4,898 WV 2009 11 HIGHWAY VEHICLES 385,994 2,183 36,049 1,096 703 227 23,907 WV 2009 12 OFF-HIGHWAY 152,862 11 30,133 1,640 1,528 359 18,069 WV 2009 14 MISCELLANEOUS 4,116 10,574 89 92,900 10,624 23 219 2009 Total 685,983 13,508 204,064 140,956 38,933 346,356 112,621 WV 2018 01 FUEL COMB. ELEC. UTIL. 11,961 180 51,241 6,349 3,648 115,324 1,387 WV 2018 02 FUEL COMB. INDUSTRIAL 9,917 111 28,710 1,493 1,290 38,531 1,072 WV 2018 03 FUEL COMB. OTHER 18, 891 16 17,254 3,160 3,024 4,065 6,270
WV 2018 04 CHEMICAL & ALLIED PRODUCT MFG 70,252 99 2,183 1,188 1,041 12,280 6,560
WV 2018 05 METALS PROCESSING 36,850 183 2,061 10,944 9,372 7,182 1,790
WV 2018 06 PETROLEUM & RELATED INDUSTRIES 1 0 1,407 616 616 9,786 2,338
WV 2018 07 OTHER INDUSTRIAL PROCE SSES 2,756 68 5,949 21, 347 6,794 3,101 2,561 WV 2018 08 SOLVENT UTILIZATION 20 0 24 61 55 0 38,023 WV 2018 09 STORAGE & TRANSPORT 19 0 4 2,522 1,225 0 13,394 WV 2018 10 WASTE DISPOSAL & RECYCLING 9,237 10 592 4,134 3,692 98 5,272 WV 2018 11 HIGHWAY VEHICLES 319,030 2,484 16,274 844 428 255 15,463 WV 2018 12 OFF-HIGHWAY 167,424 13 25,710 1,292 1,198 56 14,086 WV 2018 14 MISCELLANEOUS 5,175 11,453 112 98,307 11,316 29 268 2018 Total 651,532 14,617 151,521 152,256 43,699 190,706 108,484

CO NH3 NOX PM10 PM2.5 SO2 VOC VISTAS 2002 31,034,756 666,451 5,442,572 3,916,030 1,094,698 4,858,865 5,079,25 VISTAS 2009 25,854,812 722,418 3,721,469 4,155,033 1,119,806 3,454,666 4,118,4 7 VISTAS 2018 24,357,364 790,588 2,692,309 4,559,582 1,205,324 2,539,907 3,873,2 7Documentation of the Base G 2002 Base Year, 2009 and 2018, Emission Inventories for VISTAS

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### APPENDIX D:

VISTAS TIER 1 EMISSION TOTALSDocumentation of the Base G 2002 Base Year, 2009 and 2018, Emission Inventories for VISTAS

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### VISTAS Tier 1 Emission Totals

Year TIER1 TIER 1 NAME CO NH3 NOX PM10 PM2.5 SO2 VOC
2002 01 FUEL COMB. ELEC. UTIL. 139,579 1, 710 1,524,690 114,256 79, 263 3,723,175 12,417
2002 02 FUEL COMB. INDUSTRIAL 371, 905 1,204 499,981 85,353 59,731 550,864 32,330
2002 03 FUEL COMB. OTHER 759,534 2,810 122,058 99,532 91,805 114,852 354,375
2002 04 CHEMICAL & ALLIED PRODUCT MF G 131,993 7,093 20,896 11, 114 7,982 77,450 63,748
2002 05 METALS PROCESSING 223,705 601 11,801 32,367 27,778 49,143 17,306
2002 06 PETROLEUM & RELATED INDUSTR IES 44,633 355 7,204 2, 887 1,863 53,392 33,374
2002 07 OTHER INDUSTRIAL PROCESSES 156,077 7,520 114,474 267, 980 97,013 86,736 196,831
2002 08 SOLVENT UTILIZATION 687 331 5,677 3,805 3,284 90 1,288,990
2002 09 STORAGE & TRANSPORT 610 85 1,069 10,968 6,100 230 261,959
2002 10 WASTE DISPOSAL & RECYCLING 729,760 801 34,165 98,788 92,125 6,418 112,088
2002 11 HIGHWAY VEHICLES 20,199,593 74,325 2,193,387 50,584 35,929 88,684 1,778,345
2002 12 OFF-HIGHWAY 6,209,596 477 865,130 72,019 68,302 96,336 813,788
2002 14 MISCELLANEOUS 2, 067,084 569,139 42,039 3,066, 378 523,524 11,494 113,703
2002 Total 31,034,756 666,451 5,442,572 3,916,030 1,094,698 4,858,865 5,079,254

2009 01 FUEL COMB. ELEC. UTIL. 152,790 5,449 727,384 113,607 81, 884 2,473,773 13,155
2009 02 FUEL COMB. INDUSTRIAL 391, 510 1,305 445,832 74,864 51,709 523,163 32,629
2009 03 FUEL COMB. OTHER 544,310 3,201 123,331 85,412 77,042 112,463 207,146
2009 04 CHEMICAL & ALLIED PRODUCT MF G 140,910 7,611 22,031 11, 898 8,528 81,191 54,270
2009 05 METALS PROCESSING 242,911 732 11,788 31,098 26,505 54,700 18,507
2009 06 PETROLEUM & RELATED INDUSTR IES 48,161 399 7,908 3, 283 2,124 47,147 25,061
2009 07 OTHER INDUSTRIAL PROCESSES 166,088 7,545 117,625 298, 836 111,304 90,649 203,100
2009 08 SOLVENT UTILIZATION 771 360 6,662 4,290 3,690 100 1,257,986
2009 09 STORAGE & TRANSPORT 702 98 1,087 11,035 6,051 160 275,466
2009 10 WASTE DISPOSAL & RECYCLING 770,459 869 36,697 105,463 97,855 7,287 113,566
2009 11 HIGHWAY VEHICLES 14,353,436 87,703 1,408,206 42,370 26,848 8,817 1,146,174
2009 12 OFF-HIGHWAY 6,827,857 530 767,707 61,528 58,279 42,845 649,786
2009 14 MISCELLANEOUS 2, 214,906 606,617 45,212 3,311, 350 567,986 12,370 121,629
2009 Total 25,854,812 722,418 3,721,469 4,155,033 1,119,806 3,454,666 4,118,474

2018 01 FUEL COMB. ELEC. UTIL. 225,129 9,351 560,200 154,832 120, 895 1,479,499 16,318
2018 02 FUEL COMB. INDUSTRIAL 418, 010 1,384 471,501 80,386 55,928 547,527 34,938
2018 03 FUEL COMB. OTHER 453,482 3,358 136,418 78,031 69,853 116,812 149,363
2018 04 CHEMICAL & ALLIED PRODUCT MF G 173,857 9,023 26,564 14, 641 10,522 97,612 67,534
2018 05 METALS PROCESSING 288,138 961 15,006 39,673 34,058 67,170 23,798
2018 06 PETROLEUM & RELATED INDUSTR IES 53,442 460 9,088 3, 846 2,491 60,676 27,321
2018 07 OTHER INDUSTRIAL PROCESSES 189,922 8,793 136,722 348, 275 130,883 104,030 238,409
2018 08 SOLVENT UTILIZATION 936 404 8,480 5,378 4,618 119 1,516,454
2018 09 STORAGE & TRANSPORT 855 119 1,258 13,988 7,686 192 290,271
2018 10 WASTE DISPOSAL & RECYCLING 821,737 1,068 40,324 114,708 105,763 8,545 125,525
2018 11 HIGHWAY VEHICLES 12,052,347 101,223 639,931 33,884 17,080 10,027 713,143
2018 12 OFF-HIGHWAY 7,438,312 612 601,040 48,648 45,927 35,166 546,062
2018 14 MISCELLANEOUS 2, 241,196 653,831 45,776 3,623, 293 599,620 12,532 124,137
2018 Total 24,357,364 790,588 2,692,309 4,559,582 1,205,324 2,539,907 3,873,273Documentation of the Base G 2002 Base Year, 2009 and 2018, Emission Inventories for VISTAS

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### APPENDIX E:

AIRCRAFT PM EXCERPT FROM 2001 TUCSON REPORTDocumentation of the Base G 2002 Base Year, 2009 and 2018, Emission Inventories for VISTAS

MACTEC, Inc. 235 

### APPENDIX F:

COMPARISON OF BASE F AND BASE G ON-ROAD MOBILE EMISSIONSDocumentation of the Base G 2002 Base Year, 2009 and 2018, Emission Inventories for VISTASMACTEC, Inc.236Base G Onroad Mobile Emissions (Annual Tons)FIPSST 2002 2009 2018 2002 2009 2018 2002 2009 2018 2002 2009 2018 2002 2009 2018 2002 2009 2018 2002 2009 2018AL 125,768 76,065 44,503 156,460 100,693 42,622 1,303,508 902,469 594,725 6,827 802 654 3,861 3,136 2,193 2,768 2,010 1,085 5,530 6,298 6,630FL 520,757 336,707 199,050 460,503 312,321 136,040 4,493,820 3,308,863 2,263,190 20,687 2,584 2,302 11,148 9,801 7,516 7,779 6,104 3,671 17,922 21,549 23,778GA279,975 192,773 99,464 304,309 207,024 92,113 2,699,650 1,956,263 1,303,529 12,043 1,568 1,325 7,165 6,005 4,406 5,110 3,797 2,166 10,436 12,554 13,511KY102,362 73,142 42,810 154,634 100,025 46,993 1,214,191 950,912 711,211 6,238 751 694 3,682 2,944 2,348 2,667 1,899 1,158 5,003 5,737 7,095MS86,811 51,600 28,699 110,672 69,952 27,620 853,774 602,257 394,247 4,566 532 401 2,828 2,250 1,479 2,089 1,491 746 3,549 3,995 4,147NC260,895 166,844 91,720 323,606 199,281 79,433 2,839,283 1,966,195 1,207,391 12,286 1,487 1,346 6,505 5,510 3,994 4,571 3,453 1,931 9,601 11,702 12,776SC114,861 71,781 41,866 138,940 91,471 39,348 1,226,555 878,825 588,536 5,909 713 584 3,414 2,831 1,986 2,473 1,834 988 4,646 5,466 5,878TN177,943 114,032 61,339 235,869 150,179 62,446 1,893,704 1,320,562 863,682 9,127 1,065 862 5,312 4,160 2,813 3,904 2,720 1,405 6,556 7,702 8,196VA157,989 95,694 55,992 219,835 132,699 57,192 2,136,288 1,435,359 954,463 8,196 1,067 949 4,499 3,706 2,922 3,067 2,216 1,404 7,770 8,990 9,653WV41,703 24,570 14,652 58,340 35,234 15,530 526,841 360,865 243,683 2,438 276 231 1,366 1,057 747 984 676 369 1,889 2,126 2,268VISTAS 1,869,063 1,203,208 680,096 2,163,168 1,398,879 599,336 19,187,61313,682,570 9,124,656 88,316 10,844 9,348 49,780 41,400 30,403 35,411 26,200 14,922 72,902 86,118 93,932Base F Onroad Mobile (Annual Tons)FIPSST 2002 2009 2018 2002 2009 2018 2002 2009 2018 2002 2009 2018 2002 2009 2018 2002 2009 2018 2002 2009 2018AL 118,978 73,137 47,151 157,626 101,299 46,598 1,300,754 934,442 675,902 6,898 637 720 3,905 3,195 2,488 2,799 2,053 1,262 5,586 6,362 7,296FL 438,761 293,423 192,096 402,099 284,737 134,465 4,022,000 3,090,443 2,306,759 18,802 1,911 2,289 10,185 9,027 7,691 7,126 5,653 3,848 16,183 19,553 23,595GA 265,972 187,102 104,678 306,998 208,568 100,707 2,712,473 2,044,169 1,474,029 12,182 1,256 1,458 7,252 6,116 4,995 5,169 3,877 2,517 10,545 12,685 14,870KY96,202 63,210 38,814 154,093 97,731 43,014 1,195,656 932,296 669,8915,988 587 651 3,728 3,008 2,283 2,699 1,946 1,160 5,055 5,807 6,584MS81,701 49,986 30,337 110,242 69,949 29,829 849,049 624,575 445,150 4,614 398 441 2,863 2,296 1,688 2,114 1,525 876 3,585 4,035 4,565NC272,594 167,894 87,718 290,873 207,670 83,399 2,677,118 2,192,253 1,238,802 12,482 1,314 1,323 6,733 5,874 4,299 4,754 3,651 2,158 9,711 12,663 13,077SC107,236 69,026 44,121 139,403 91,832 42,641 1,220,825 921,308 663,597 5,972 558 643 3,454 2,884 2,258 2,502 1,874 1,154 4,694 5,522 6,472TN168,389 109,716 63,916 233,324 147,591 66,879 1,881,893 1,359,880 961,929 9,202 833 944 5,349 4,247 3,199 3,927 2,788 1,643 6,629 7,753 8,962VA143,969 91,230 59,737 222,830 133,039 64,079 1,996,287 1,483,125 1,091,5467,234 902 1,059 4,546 3,768 3,343 3,097 2,258 1,641 7,852 9,084 10,757WV39,581 23,914 15,375 60,335 36,000 16,940 533,258 379,272 273,900 2,495 228 255 1,399 1,099 844 1,005 705 428 1,938 2,188 2,484VISTAS 1,733,382 1,128,638 683,942 2,077,822 1,378,416 628,551 18,389,31213,961,764 9,801,505 85,868 8,622 9,783 49,414 41,513 33,086 35,191 26,330 16,687 71,778 85,652 98,664Emissions Change (Base G - Base F, Annual Tons) -- Positive Value Indicates Increase from Base FFIPSST 2002 2009 2018 2002 2009 2018 2002 2009 2018 2002 2009 2018 2002 2009 2018 2002 2009 2018 2002 2009 2018AL 6,789 2,928 -2,647 -1,166 -606 -3,977 2,754 -31,973 -81,178 -71 165 -66 -45 -58 -295 -31 -43 -178 -56 -63 -666FL81,997 43,284 6,955 58,404 27,584 1,575 471,820 218,420 -43,569 1,885 672 14 963 774 -175 653 451 -177 1,738 1,996 183GA14,003 5,671 -5,214 -2,689 -1,544 -8,594 -12,823 -87,906 -170,500 -139 312 -133 -86 -111 -589 -59 -80 -352 -109 -131 -1,359KY6,160 9,933 3,996 541 2,294 3,979 18,534 18,615 41,319 250 164 43 -46 -65 65 -32 -47 -2 -52 -70 512MS5,110 1,613 -1,638 4303 -2,209 4,724 -22,319 -50,903 -48 134 -41 -35 -46 -209 -25 -34 -130 -35 -40 -419NC-11,699 -1,049 4,001 32,734 -8,389 -3,966 162,165 -226,057 -31,411 -196 174 23 -228 -364 -304 -183 -198 -226 -111 -961 -302SC7,625 2,755 -2,255 -462 -362 -3,293 5,731 -42,483 -75,061 -63 156 -59 -40 -53 -272 -29 -40 -166 -48 -56 -594TN9,554 4,316 -2,577 2,545 2,589 -4,433 11,811 -39,318 -98,246 -75 232 -82 -37 -87 -385 -22 -68 -238 -73 -52 -766VA14,020 4,464 -3,744 -2,995 -340 -6,887 140,001 -47,766 -137,084 962 165 -110 -47 -62 -420 -30 -42 -237 -83 -94 -1,104WV2,122 656 -723 -1,995 -766 -1,410 -6,416 -18,407 -30,217 -57 49 -24 -32 -42 -97 -22 -29 -59 -49 -62 -217VISTAS 135,680 74,570 -3,846 85,346 20,462 -29,215 798,301 -279,194 -676,850 2,448 2,222 -435 367 -114 -2,683 219 -130 -1,764 1,123 466 -4,732Emissions Change (Base G - Base F/Base F, Annual %) -- Positive Value Indicates Increase from Base FFIPSST 2002 2009 2018 2002 2009 2018 2002 2009 2018 2002 2009 2018 2002 2009 2018 2002 2009 2018 2002 2009 2018AL 6% 4% -6% -1% -1% -9% 0% -3% -12% -1% 26% -9% -1% -2% -12% -1% -2% -14% -1% -1% -9%FL 19% 15% 4% 15% 10% 1% 12% 7% -2% 10% 35% 1% 9% 9% -2% 9% 8% -5% 11% 10% 1%GA 5% 3% -5% -1% -1% -9% 0% -4% -12% -1% 25% -9% -1% -2% -12% -1% -2% -14% -1% -1% -9%KY 6% 16% 10% 0% 2% 9% 2% 2% 6% 4% 28% 7% -1% -2% 3% -1% -2% 0% -1% -1% 8%MS6% 3% -5% 0% 0% -7%1% -4% -11% -1% 34% -9% -1% -2% -12% -1% -2% -15% -1% -1% -9%NC-4% -1% 5% 11% -4% -5%6% -10% -3% -2% 13% 2% -3% -6% -7% -4% -5% -10% -1% -8% -2%SC7% 4% -5% 0% 0% -8%0% -5% -11% -1% 28% -9% -1% -2% -12% -1% -2% -14% -1% -1% -9%TN6% 4% -4% 1% 2% -7%1% -3% -10% -1% 28% -9% -1% -2% -12% -1% -2% -14% -1% -1% -9%VA10% 5% -6% -1% 0% -11%7% -3% -13% 13% 18% -10% -1% -2% -13% -1% -2% -14% -1% -1% -10%WV5% 3% -5% -3% -2% -8% -1% -5% -11% -2% 21% -9% -2% -4% -12% -2% -4% -14% -3% -3% -9%VISTAS8% 7% -1% 4% 1% -5%4% -2% -7% 3% 26% -4% 1% 0% -8% 1% 0% -11% 2% 1% -5%VOCNOxCOSO2PM-10PM-2.5NH3VOCNOxCOSO2PM-10PM-2.5NH3VOCNOxCOSO2PM-10PM-2.5NH3VOCNOxCOSO2PM-10PM-2.5NH3Documentation of the Base G 2002 Base Year, 2009 and 2018, Emission Inventories for VISTASMACTEC, Inc.237Annual Onroad Emissions Comparison0100,000200,000300,000400,000500,000600,000AL FL GA KY MS NC SC TN VA WV

Annual VOC Emissions (Tons)2002 BaseG2002 BaseF2009 BaseG2009 BaseF2018 BaseG2018 BaseFDocumentation of the Base G 2002 Base Year, 2009 and 2018, Emission Inventories for VISTASMACTEC, Inc.238Annual Onroad Emissions Comparison050,000100,000150,000200,000250,000300,000350,000400,000450,000500,000AL FL GA KY MS NC SC TN VA WV

Annual NOx Emissions (Tons)2002 BaseG2002 BaseF2009 BaseG2009 BaseF2018 BaseG2018 BaseFDocumentation of the Base G 2002 Base Year, 2009 and 2018, Emission Inventories for VISTASMACTEC, Inc.239Annual Onroad Emissions Comparison05001,0001,5002,0002,5003,0003,5004,0004,5005,000AL FL GA KY MS NC SC TN VA WV

Thousands Annual CO Emissions (Tons)2002 BaseG2002 BaseF2009 BaseG2009 BaseF2018 BaseG2018 BaseFDocumentation of the Base G 2002 Base Year, 2009 and 2018, Emission Inventories for VISTASMACTEC, Inc.240Annual Onroad Emissions Comparison05,00010,00015,00020,00025,000AL FL GA KY MS NC SC TN VA WV

Annual SO2 Emissions (Tons)2002 BaseG2002 BaseF2009 BaseG2009 BaseF2018 BaseG2018 BaseFDocumentation of the Base G 2002 Base Year, 2009 and 2018, Emission Inventories for VISTASMACTEC, Inc.241Annual Onroad Emissions Comparison02,0004,0006,0008,00010,00012,000AL FL GA KY MS NC SC TN VA WV

Annual PM-10 Emissions (Tons)2002 BaseG2002 BaseF2009 BaseG2009 BaseF2018 BaseG2018 BaseFDocumentation of the Base G 2002 Base Year, 2009 and 2018, Emission Inventories for VISTASMACTEC, Inc.242Annual Onroad Emissions Comparison01,0002,0003,0004,0005,0006,0007,0008,0009,000AL FL GA KY MS NC SC TN VA WV

Annual PM-2.5 Emissions (Tons)2002 BaseG2002 BaseF2009 BaseG2009 BaseF2018 BaseG2018 BaseFDocumentation of the Base G 2002 Base Year, 2009 and 2018, Emission Inventories for VISTASMACTEC, Inc.243Annual Onroad Emissions Comparison05,00010,00015,00020,00025,000AL FL GA KY MS NC SC TN VA WV

Annual NH3 Emissions (Tons)2002 BaseG2002 BaseF2009 BaseG2009 BaseF2018 BaseG2018 BaseF

### Atmospheric Sciences Group

Alpine Geophysics, LLC ▪ 387 Pollard Mine Road ▪ Burnsville, NC 28714 ▪ (828) 675-9045 ▪ (828) 675-5801 FAX 

## MEMORANDUM

To: VISTAS State Point Source Contacts a nd VISTAS EGU Special Interest Workgroup From: Gregory Stella, VISTAS Techni cal Advisor - Emission Inventories Date: June 13, 2005 Re: EGU Emission Factors and Em ission Factor Assignment

Purpose
The purpose of this memorandum is to discuss the differences currently known to exist in the base year (2002) and future year (2009 and 2018) forecasts of EGU emission factors for PM and NH3. In particular, it has been identified that E. H. Pechan & Associates, Inc. (Pechan) in their development of post-processed IPM output into NIF structure uses a set of PM and NH3 emission factors that are “the most recent EP A approved uncontrolled emission factors” and which are most likely not the same emission factors used by States and emission inventory preparation contractors for estim ating these emissions in 2002 for EGUs in the VISTAS domain. Additionally, through re view of the code used to post-proce ss the IPM parsed files, it has also been determined that emission factors are assigned in future years based on Pechan assigned SCCs and not necessarily initial base year SCCs as coded in the original VISTAS NIF files.
A second objective of this memorandum is to pr opose a resolution to the issues at hand and to recommend a set of modifications to be made to the base year PM and NH3 emission estimates for this source category.
Background
VISTAS Base Year EGU Emissions Preparation
A major component to the development of the VI STAS point source sector of the inventory was the incorporation of data submitted by the VISTAS States and local (S/L) agencies to the United States Environmental Protection Agency (EPA) as part of the Consolidated Emissions Reporting Rule (CERR). Work on incorporating the CERR da ta into the revised base year involved: 1) obtaining the data from EPA or the S/L agenc y, 2) evaluating the em issions and pollutants reported in the submittal, 3) augmenting CERR da ta with annual emission estimates for PM10- PRI and PM25-PRI; 4) evaluating the emissi ons from electric generating units, and 5) completing quality assurance reviews for each component of the point source inventory.
Data from several sources were used: 1) the inventories that the S/L submitted to EPA from May through July 2004; 2) supplemental data supplied by the S/L agencies that may have been revised or finalized after submitta l to EPA, and 3) the original VISTAS 2002 inventory in cases where S/L CERR data were not available.

### Atmospheric Sciences Group

Alpine Geophysics, LLC ▪ 387 Pollard Mine Road ▪ Burnsville, NC 28714 ▪ (828) 675-9045 ▪ (828) 675-5801 FAX 

### Particulate matter emissions can be reporte d in many different forms, as follows:
PM Category Description PM-PRI Primary PM (include s filterable and condensable) PM-CON Primary PM, condensable por tion only (all less than 1 micron) PM-FIL Primary PM, filterable portion only PM10-PRI Primary PM10 (includes filterable and condensable) PM10-FIL Primary PM10, filterable portion only PM25-PRI Primary PM25 (includes filterable and condensable) PM25-FIL Primary PM25, filterable portion only
State/local agencies did not report PM emissi ons in a consistent manner. The State/local inventories submitted for VISTAS included emissions data for either PM-FIL, PM-PRI, PM10- FIL, PM10-PRI, PM25-FIL, PM25-PRI, and/or PM -CON. From any one of these pollutants, EPA has developed augmentation procedures to estimate PM10-PRI, PM10-FIL, PM25-PRI, PM25-FIL, and PM-CON. If not included in a State/local inventory, PM10-PRI and PM25-PRI were calculated by adding PM10-FIL and PM-C ON or PM25-FIL and PM-CON, respectively. The procedures for augmenting point source PM em issions are documented in detail in Appendix C of Documentation for the Final 1999 National Em issions Inventory (Version 3) for Criteria Air Pollutants and Ammonia – Point Sources , January 31, 2004 1



### .
Briefly, the PM data augmentation procedure includes the following five steps:

• 

### Step 1: Prepare S/L/T PM and PM10 Emi ssions for Input to the PM Calculator

• 

### Step 2: Develop and Apply Sour ce-Specific Conversion Factors

• 

### Step 3: Prepare Factor s from PM Calculator

• 

### Step 4: Develop and Apply Algorithms to Esti mate Emissions from S/L/T Inventory Data

• 

### Step 5: Review Results and Update the NEI with Emission Estimates and Control Information. Ammonia (NH3) emissions from these sources were assigned using direct incorporation of S/L/T provided emission estimates or via the applica tion of emission factors using ratios of NH3 emission factors to other reported pollutants (e.g., VOC, CO, etc.). IPM Post Processing ICF via VISTAS contracts provided an initial sp readsheet file containi ng unit-level records of both (1) “existing” units and (2) committed or new generic aggregates. All records have unit and fuel type data; exis ting, retrofit (for SO 2 

### and NO x 

### ), and separate NO x 

### control information; annual SO 2 

### and NO x 

### emissions and heat input; summer season (May-September) NO x 

### and heat input; July day NO x 

### and heat input; coal heat input by coal type; nameplate capacity (MW), and State FIPS code. Existing units also have county FIPS code, a unique plant identifier (ORISPL) and unit ID (also called boiler ID) (BLRID); generic units do not have these data.

1 

### ftp://ftp.epa.gov/EmisInventory/finalnei99ver3/crite ria/documentation/point/point_99nei_finalv3_0204.pdf

### Atmospheric Sciences Group

Alpine Geophysics, LLC ▪ 387 Pollard Mine Road ▪ Burnsville, NC 28714 ▪ (828) 675-9045 ▪ (828) 675-5801 FAX 

### The IPM data were further processed by Pech an using data files and methodology recently approved by EPA. The most current documentati on related to this subject is the EPA report titled, Documentation for the 2002 Electric Gene rating Unit (EGU) National Emissions Inventory (NEI), September 2004 2 

### . The processing includes estimating various types of emissions and adding in control efficiencies, stack parameters, latitude-longitude coordinates, and State identifiers (plant ID, point ID, stack ID, process ID). Additionally, the generic units were sited in a county and given IDs.

Pechan developed SCC assignments for all units; unit/fuel/firing/bottom type data were used for existing units’ assignments, while only unit and fuel type were used for generic units’ assignments. Additional review of the source code used in deve loping these post-processed files confirmed this fact. In actuality, not only does it exist that the post-processing code assigns different emission factors for the same SCC but that SCCs assigned in future year IPM output are potentially different than thos e assigned in the base year i nventory, leading to additional, propagating differences in the base year and future year estimates. The full extent of these issues is currently under review by VISTAS and MRPO.
Stack parameters were attache d, first using matches to data in the VISTAS 2002 NIF files, secondly using the EPA-provided data files, thir dly using a March 9, 2004 Pechan in-house stack parameter file based on previ ous EIA-767 data, and lastly using an EPA June 2003 SCC-based default stack parameter file.
Plant ID (within State and county) , point ID, process ID , and stack ID were then attached, first using the VISTAS-provided data files, or seco ndly using EPA or Pechan-generated defaults. Default stack IDs within a plant were assi gned for each unique stack height-diameter combination. The process ID and stack ID default data were only used when the data were not matched to the original VISTAS 2002 NIF files. Additional data were required for estimating VOC, CO, filterable primary PM 10 

### and PM 2.5 

### , PM condensable, and NH 3 

### emissions for all units. Thus, ash and sulfur contents were assigned by first using 2002 EIA-767 values for existing units or SCC-based defaults; filterable PM 10 

### and PM 2.5 

### efficiencies were obtained from the 200 2 EGU NEI that were based on 2002 EIA-767 control data and the PM Calcul ator program (a default of 99.2% was used for coal units if necessary); fuel use was back calculated from th e given heat input and a default SCC-based heat content; and emission factors were obtaine d from an EPA-approved October 7, 2004 Pechan emission factor file based on AP-42 emission f actors. Table 1 provides the emission factor differences between the “old” emission factor fi le (used in development of EPA’s 1999 NEI v.3) and the updated factors as used in VISTAS latest IPM conversion. Note that this updated file was not the one used for estimating emissions for pr evious EPA post-processed IPM files (including estimates for CAIR). It should also be noted that this component of emission estimation is only for the filterable component of PM and that th e emission factors used for condensable PM did not change between the two versions.

2 

### ftp://ftp.epa.gov/EmisInventory/draftn ei2002/point/documentation/egu2002doc.pdf

### Atmospheric Sciences Group

Alpine Geophysics, LLC ▪ 387 Pollard Mine Road ▪ Burnsville, NC 28714 ▪ (828) 675-9045 ▪ (828) 675-5801 FAX 

### Issue Identification
During a VISTAS TAWG meeting held at the Solu tion Center in Durham, NC on April 5 and 6, 2005, emission summaries were presented as co mparisons of 2002 to 2018 forecasts. Table 2 presents the slide originally used in identifying the increase in PM and NH3 emissions. In this comparison, it was noted that PM and NH3 emissions (highlighted in Tabl e 2) from EGUs were significantly higher in 2018 than in 2002 and based on known regulation and activity, no reason could be identified for this increase. After an initial review of the data, it was determined that the PM and NH3 emission factors used between the base year and future year were most likely the culprit. In fact, for some SCCs, the NH3 em ission factor increased by over 5,000% (0.000565 to 0.03 lbs/ton coal burned). Changes in PM emission factors were not as large and limited to only a few SCCs. However, this emissions increase was simply an artifact of the change in emission factor, not anything to do with changes in activity or control technology application.
Additionally, after further review of the post-processing code by VISTAS, it was determined that not only were differing emi ssion factors being used for similar SCCs between the base and future year estimates for those SCCs identified in Tabl e 2, but that the same S CCs were not necessarily being used for emission factor assignment in th e base and post-processed IPM scenarios. This issue has implications not only for the different PM and NH3 factors, but for other pollutants (CO, VOC) not initially estimated by IPM.
Table 3 presents those unit-segment (SCC) combinat ions which have been identified in the 2018 OTW run to have been assigned SCCs in the IPM post-processing step different than those in the 2002 base case. In some instances, the SCCs are comparable enough that the emission factors assigned were the same. However, there are additional instances where significant enough difference exists that review a nd correction may be warranted. An analysis of the differences in assignment of these SCCs and associated factors has not yet been completed.
Proposed Solution

There are two issues which need to be resolved in the estimation of relative differences in EGU emissions between VISTAS base year 2002 emissions inventory and any forecasts of this source sector using IPM and post-proces sing steps applied using exis ting programs provided by Pechan; (1) consistent use of emission f actors between the base and future years, and (2) the consistent use of SCCs for determining emission fact ors between the base and future years.
These issues can be resolved using a variety of ways but the proposal provided here positions VISTAS to regenerate some specific pollutant 2002 emissions for the EGU sector in a fashion consistent, and presumably, more up-to-date, than the estimates provided in the 2002 base year inventory. Additionally, this proposal allows for th e existing process to be completed in the postprocessing steps but adjusts the resulting non-IPM generated emissions using correct SCCs and emission factors.

### Atmospheric Sciences Group

Alpine Geophysics, LLC ▪ 387 Pollard Mine Road ▪ Burnsville, NC 28714 ▪ (828) 675-9045 ▪ (828) 675-5801 FAX 

### Base Year Emissions Adjustment
The first step is the adjustment of the 2002 ba se year emissions inve ntory. Using the latest “EPA-approved” uncontrolled emission factors by SCC, VISTAS contactors will utilize CERR or VISTAS reported annual heat input, fuel th roughput, heat, ash and sulfur content to estimate annual uncontrolled emissions for units identified as output by IPM. This step will be conducted for non-CEM pollutants (CO, VOC, PM, and NH3) only. For PM emissions, the condensable component of emissions will also be calcula ted and added to the resulting PM primary estimations. When these fuel characteristic va riables are found to be zero, out of range (as identified by AP-42 factors), or invalid, average fuel data collected from EPA’s AP-42 documentation on heat, sulfur, and/or ash content will be used. The resulting emissions will then be adjusted by any control efficiency factors re ported in the CERR or VISTAS data collection effort.
Future Year Scenario Adjustment
Because the assignment of the SCCs to IPM output is a post-processing step which involves the cross-reference file developed to match IPM units to VISTAS 2002 base year inventory, it should be relatively straightforwar d to modify the code to assign the same base year SCC to the future year. Then, through assignment of SCCs and associated emission factors (via another cross-reference), similar base year and future year emission factor assi gnments could be made; just using the projected controls and fuel throughput as pred icted by IPM. If modifications can not be made directly to the code for this cro ss-reference step, VISTAS can modify the resulting post-processed NIF files for those sources identified with alternate SCCs assigned in the future year. Using the same methods as described for the 2002 revisions, those non-IPM generated pollutants would be estimated using IPM predic ted fuel characteristics and base year 2002 SCC assignments.

### Atmospheric Sciences Group

Alpine Geophysics, LLC ▪ 387 Pollard Mine Road ▪ Burnsville, NC 28714 ▪ (828) 675-9045 ▪ (828) 675-5801 FAX 

### Table 1. Comparison of “Old” vs. “New” Em ission Factors for IPM Post-Processing

SCCEMFACforMRPOoldvsnew.xls -- PM+NH3 EF , 12/17/04
This file lists the "Old" and "N ew" EPA-approved Uncontrolled PM 10 

### , PM 2.5 

### , and NH 3 

### Emission Factors for the SCCs in the MRPO Scenarios.

SCC 1 

### FUEL "New" PM10EF 4 

### "Old" PM10EF 3 

### "New" PM25EF 4 

### "Old" PM25EF 3 

### PMFLAG 2 

### "New" NH3EF 4 

### "Old" NH3EF 3 

### 10100201 BIT 2.6000 2.6000 1.4800 1.4800 A 0.030000 0.000565 10100202 BIT 2.3000 2.3000 0.6000 0.6000 A 0.030000 0.000565 10100203 BIT 0.2600 0.2600 0.1100 0.1100 A 0.030000 0.000565 10100204 BIT 13.2000 13.2000 4.6000 4.6000 0.030000 0.000565 10100211 BIT 2.6000 2.6000 1.4800 1.4800 A 0.030000 0.000565 10100212 BIT 2.3000 2.3000 0.6000 0.6000 A 0.030000 0.000565 10100217 BIT 12.4000 12.4000 1.3640 3.2000 0.030000 0.000565 10100221 SUB 2.6000 2.6000 1.4800 1.4800 A 0.030000 0.000565 10100222 SUB 2.3000 2.3000 0.6000 0.6000 A 0.030000 0.000565 10100223 SUB 0.2600 0.2600 0.1100 0.1100 A 0.030000 0.000565 10100224 SUB 13.2000 13.2000 4.6000 4.6000 0.030000 0.000565 10100226 SUB 2.3000 2.3000 0.6000 0.6000 A 0.030000 0.000565 10100238 SUB 16.1000 16.1000 4.2000 4.2000 0.030000 0.000565 10100301 LIG 1.8170 1.8170 0.5214 0.5214 A 0.030000 0.000565 10100302 LIG 2.3000 2.3000 0.6600 0.6600 A 0.030000 0.000565 10100303 LIG 0.8710 0.8700 0.3690 0.1100 A 0.030000 0.000565 10100317 LIG 12.0000 12.0000 1.4000 1.4000 0.030000 0.000565 10100601 NG 1.9000 1.9000 1.9000 1.9000 3.200000 3.200000 10100801 PC 7.9000 7.9000 4.5000 4.5000 A 0.397000 --- 10102018 WC 12.0000 12.0000 1.4000 1.4000 0.030000 0.000565 20100201 NG 1.9380 1.9380 1.9380 1.9380 6.560000 --- 20100301 IGCC 11.5500 11.5500 11.5500 11.5500 6.560000 --- Notes: 1. SCCs beginning with 101002 (coal), 101003 (coal), 101008 (coke), or 101020 (waste coal), emission factors in LB/TON; SCCs beginning with 101006 (natural gas), 201002 (natural gas), or 201003 (IGCC), emission factors are in LB/E6FT3. 2. If PMFLAG = 'A', then apply ash content to PM emission factor. 3. "Old" emission factors are used for latest EPA IPM post-processing. 4. "New" emission factors are used for MRPO IPM post-processing.Atmospheric Sciences GroupAlpine Geophysics, LLC▪387 Pollard Mine Road▪Burnsville, NC 28714▪(828) 675-9045▪(828) 675-5801 FAXTable 2. Annual Emissions Comparison of 2002 Typical with 2018 OTW; VISTAS Tier 1 Category Totals.19%9%13%-50%-8%-52%-19%VISTAS Total15%5%14%0%0%0%2%Miscellaneous35%-29%-29%-61%23%-30%-40%Off-highway36%-53%-34%-89%-19%-70%-47%Highway Vehicles52%10%11%37%9%13%11%Waste Disposal & Recycling40%2%-4%34%46%28%-19%Storage & Transport20%32%34%23%36%48%22%Solvent Utilization16%25%28%19%21%15%22%Other Industrial Processes12%33%35%11%15%23%-19%Petroleum & Related Industries60%20%20%37%29%27%43%Metals Processing27%36%36%31%32%29%50%Chemical & Allied Product Mfg23%-8%-16%15%-28%19%-55%Fuel Comb. Other28%7%5%7%15%0%12%Fuel Comb. Industrial3024%82%69%-63%53%-68%13%Fuel Comb. Elec. Util.NH3PM-2.5PM-10SO2CONOxVOCSource CategoryAnnual 2018 OTW - 2002Typical Emissions (Percent)Atmospheric Sciences GroupAlpine Geophysics, LLC▪387 Pollard Mine Road▪Burnsville, NC 28714▪(828) 675-9045▪(828) 675-5801 FAXTable 3. Differences in VISTAS Base Year 2002 and IPMPost-Processed SCC Emission Factor AssignmentsFIPS Plant ID Plant NamePoint IDStack ID Segment 2002 SCC IPM SCC01039 0001 ALABAMA ELECTRIC COOPERATIVE - MCWILLIAMS005 002 01 10100201 2010020101055 0002 ALABAMA POWER COMPANY - GADSDEN002 001 01 10100202 2010020101055 0002 ALABAMA POWER COMPANY - GADSDEN003 001 01 10100201 2010020101063 0001 ALABAMA POWER COMPANY - GREENE COUNTY002 001 01 10100201 1010020201063 0001 ALABAMA POWER COMPANY - GREENE COUNTY003 001 01 10100201 1010020201071 0008 TVA - WIDOWS CREEK008 002 01 10100202 1010021201071 0008 TVA - WIDOWS CREEK009 003 01 10100202 1010021201085 0008 GENERAL ELECTRIC CO001 001 01 10200602 2010020101097 1001 ALABAMA POWER COMPANY - BARRY002 001 01 10100201 1010021201097 1001 ALABAMA POWER COMPANY - BARRY003 001 01 10100201 1010021201097 1001 ALABAMA POWER COMPANY - BARRY004 001 01 10100201 1010021201097 1001 ALABAMA POWER COMPANY - BARRY005 002 01 10100201 1010021201097 1001 ALABAMA POWER COMPANY - BARRY006 003 01 10100201 1010021201097 1001 ALABAMA POWER COMPANY - BARRY007 005 01 20200203 2010020101097 1001 ALABAMA POWER COMPANY - BARRY008 006 01 20200203 2010020101097 1001 ALABAMA POWER COMPANY - BARRY009 007 01 20200203 2010020101097 1001 ALABAMA POWER COMPANY - BARRY010 008 01 20200203 2010020101127 0001 ALABAMA POWER COMPANY - GORGAS004 003 01 10100201 1010020201127 0001 ALABAMA POWER COMPANY - GORGAS005 003 01 10100201 1010020201127 0001 ALABAMA POWER COMPANY - GORGAS006 004 01 10100201 1010021201127 0001 ALABAMA POWER COMPANY - GORGAS007 004 01 10100201 1010021201127 0001 ALABAMA POWER COMPANY - GORGAS008 004 01 10100201 1010021212001 0010001 PROGRESS ENERGY FLORIDA, INC. U OF FL COGEN11 1 20200203 2010020112009 0090006 FLORIDA POWER & LIGHT (PCC) CAPE CANAVERAL11 2 10100401 2010020112009 0090006 FLORIDA POWER & LIGHT (PCC) CAPE CANAVERAL22 2 10100401 2010020112027 0270016 DESOTO COUNTY GENERATING COMPANY, LLC22 1 20100101 2010020112031 0310047 JEA KENNEDY3 3 1 20100101 2010020112031 0310047 JEA KENNEDY4 4 1 20100101 2010020112031 0310047 JEA KENNEDY5 5 1 20100101 2010020112031 0310485 JEA BRANDY BRANCH FACILITY22 1 20100101 2010020112033 0330045 GULF POWER COMPANY CRIST ELECTRIC GENERATINGPLANT 2 1 1 10100601 2010020112033 0330045 GULF POWER COMPANY CRIST ELECTRIC GENERATINGPLANT 3 1 2 10100601 20100201Atmospheric Sciences GroupAlpine Geophysics, LLC▪387 Pollard Mine Road▪Burnsville, NC 28714▪(828) 675-9045▪(828) 675-5801 FAXFIPS Plant ID Plant NamePoint IDStack ID Segment 2002 SCC IPM SCC12049 0490043 VANDOLAH POWER COMPANY, LLC11 1 20100101 2010020112095 0950203 ORLANDO COGEN LIMITED, L.P.11 1 20200203 2010020112097 0970014 PROGRESS ENERGY FLORIDA, INC. INTERCESSION CITY PLANT 11 11 1 20100101 2010020112097 0970014 PROGRESS ENERGY FLORIDA, INC. INTERCESSION CITY PLANT 18 18 2 20100101 2010020112099 0990042 FLORIDA POWER & LIGHT (PRV) RIVIERA POWER PLANT33 3 10100401 2010020112099 0990042 FLORIDA POWER & LIGHT (PRV) RIVIERA POWER PLANT44 3 10100401 2010020112099 0990045 CITY OF LAKE WORTH UTILITIES TOM G. SMITH POWER PLANT 99 1 10100601 2010020112103 1030011 PROGRESS ENERGY FLORIDA, INC. BARTOW PLANT11 2 10100401 2010020112103 1030011 PROGRESS ENERGY FLORIDA, INC. BARTOW PLANT22 2 10100404 2010020112103 1030011 PROGRESS ENERGY FLORIDA, INC. BARTOW PLANT33 2 10100404 2010020112105 1050003 LAKELAND ELECTRIC CHARLES LARSEN MEMORIAL POWER PLANT 44 2 10100401 2010020112105 1050221 CALPINE/AUBURNDALE POWER PARTNERS, LP66 2 20100101 2010020112105 1050223PROGRESS ENERGY FLORIDA, INC. TIGER BAY COGENERATIONFACILITY3 3 1 10200602 2010020112105 1050233 TAMPA ELECTRIC COMPANY POLK POWER STATION11 2 20100201 2010030112121 1210003 PROGRESS ENERGY FLORIDA, INC. FL POWER SUWANNEE RVR PLANT 11 3 10100404 2010020112121 1210003 PROGRESS ENERGY FLORIDA, INC. FL POWER SUWANNEE RVR PLANT 22 3 10100401 2010020112121 1210003 PROGRESS ENERGY FLORIDA, INC. FL POWER SUWANNEE RVR PLANT 33 3 10100401 2010020112127 1270009 FLORIDA POWER & LIGHT (PSN) SANFORD POWER PLANT11 3 10100401 2010020112127 1270020 PROGRESS ENERGY FLORIDA, INC. TURNER PLANT10 10 1 20100101 2010020112127 1270020 PROGRESS ENERGY FLORIDA, INC. TURNER PLANT99 1 20100101 2010020112127 1270028 PROGRESS ENERGY FLORIDA, INC. DEBARY FACILITY17 17 1 20100101 2010020112127 1270028 PROGRESS ENERGY FLORIDA, INC. DEBARY FACILITY18 18 1 20100101 2010020113051 05100006 KRAFT STEAM - ELECTRIC GENERATING PLANTSG01 CS1 1 10100212 2010020113051 05100006 KRAFT STEAM - ELECTRIC GENERATING PLANTSG02 CS1 1 10100212 2010020113067 06700003GEORGIA POWER COMPANY, MCDONOUGH STEAM-ELECTRICGENERATING PLANTCT6M ST6M 1 20100101 2010020113067 06700003GEORGIA POWER COMPANY, MCDONOUGH STEAM-ELECTRICGENERATING PLANTCT7M ST7M 1 20100101 2010020113115 11500003GEORGIA POWER COMPANY, HAMMOND STEAM-ELECTRICGENERATING PLANTSG01 ST1 1 10100212 1010020213115 11500003GEORGIA POWER COMPANY, HAMMOND STEAM-ELECTRICGENERATING PLANTSG02 ST1 1 10100212 1010020213115 11500003GEORGIA POWER COMPANY, HAMMOND STEAM-ELECTRICGENERATING PLANTSG03 ST1 1 10100212 10100202Atmospheric Sciences GroupAlpine Geophysics, LLC▪387 Pollard Mine Road▪Burnsville, NC 28714▪(828) 675-9045▪(828) 675-5801 FAXFIPS Plant ID Plant NamePoint IDStack ID Segment 2002 SCC IPM SCC13115 11500003GEORGIA POWER COMPANY, HAMMOND STEAM-ELECTRICGENERATING PLANTSG04 ST2 1 10100212 1010020213207 20700008GEORGIA POWER COMPANY, SCHERER STEAM-ELECTRICGENERATING PLANTSG01 ST1 1 10100212 1010022613207 20700008GEORGIA POWER COMPANY, SCHERER STEAM-ELECTRICGENERATING PLANTSG02 ST2 1 10100212 1010022613207 20700008GEORGIA POWER COMPANY, SCHERER STEAM-ELECTRICGENERATING PLANTSG03 ST3 1 10100212 1010022613207 20700008GEORGIA POWER COMPANY, SCHERER STEAM-ELECTRICGENERATING PLANTSG04 ST4 1 10100212 1010022613237 23700008GEORGIA POWER COMPANY, BRANCH STEAM-ELECTRICGENERATING PLANTSG01 ST1 1 10100212 1010020213237 23700008GEORGIA POWER COMPANY, BRANCH STEAM-ELECTRICGENERATING PLANTSG02 ST1 1 10100212 1010020213237 23700008GEORGIA POWER COMPANY, BRANCH STEAM-ELECTRICGENERATING PLANTSG03 ST2 1 10100212 1010020213237 23700008GEORGIA POWER COMPANY, BRANCH STEAM-ELECTRICGENERATING PLANTSG04 ST2 1 10100212 1010020221111 0126 LOU GAS & ELEC, CANERUN 06 06 01 10100212 1010020221111 0127 LOUGAS & ELEC, MILL CREEK03 03 01 10100212 1010020221111 0127 LOUGAS & ELEC, MILL CREEK04 04 01 10100212 1010020221157 2115700053 DUKE ENERGY MARSHALL COUNTY,LLC001A 1 2 20100101 2010020121223 2122300002 LOUISVILLE GAS & ELECTRIC TRIMBLE COGEN STATION001 1 1 10100202 1010021228007 2800700032 ATTALA GENERATING COMPANY, LLC003 3 1 10100602 2010020128047 2804700055 MISSISSIPPI POWER COMPANY, PLANT JACK WATSON004 4 1 10100101 1010020228047 2804700055 MISSISSIPPI POWER COMPANY, PLANT JACK WATSON005 5 1 10100101 1010020228059 2805900090 MISSISSIPPI POWER COMPANY, PLANT DANIEL001 1 1 10100223 1010021228059 2805900090 MISSISSIPPI POWER COMPANY, PLANT DANIEL002 2 1 10100223 1010021228059 2805900090 MISSISSIPPI POWER COMPANY, PLANT DANIEL003 3 1 20100101 2010020128059 2805900090 MISSISSIPPI POWER COMPANY, PLANT DANIEL004 4 1 20100101 2010020128059 2805900090 MISSISSIPPI POWER COMPANY, PLANT DANIEL005 5 1 20100101 2010020128059 2805900090 MISSISSIPPI POWER COMPANY, PLANT DANIEL006 6 1 20100101 2010020137017 3701700043 ELIZABETHTOWN POWER, LLCG-17A S-1 8 10101202 1010020437035 3703500073 DUKE ENERGY CORPORATION - MARSHALL STEAM STATIONG-1 S-3 5 10100202 1010021237035 3703500073 DUKE ENERGY CORPORATION - MARSHALL STEAM STATIONG-2 S-4 13 10100202 1010021237035 3703500073 DUKE ENERGY CORPORATION - MARSHALL STEAM STATIONG-4 S-1 11 10100202 10100212Atmospheric Sciences GroupAlpine Geophysics, LLC▪387 Pollard Mine Road▪Burnsville, NC 28714▪(828) 675-9045▪(828) 675-5801 FAXFIPS Plant ID Plant NamePoint IDStack ID Segment 2002 SCC IPM SCC37035 3703500073 DUKE ENERGY CORPORATION - MARSHALL STEAM STATIONG-5 S-2 12 10100202 1010021237071 3707100039 DUKE ENERGY CORPORATION - ALLEN STEAM STATIONG-14 S-1 1 10100202 1010021237071 3707100039 DUKE ENERGY CORPORATION - ALLEN STEAM STATIONG-15 S-2 3 10100202 1010021237071 3707100039 DUKE ENERGY CORPORATION - ALLEN STEAM STATIONG-16 S-3 5 10100202 1010021237071 3707100039 DUKE ENERGY CORPORATION - ALLEN STEAM STATIONG-17 S-4 7 10100202 1010021237071 3707100039 DUKE ENERGY CORPORATION - ALLEN STEAM STATIONG-18 S-5 9 10100202 1010021237071 3707100040 DUKE ENERGY CORPORATION - RIVERBEND STEAM STATIONG-17 S-5 20 10100202 1010021237145 3714500029 CP&L - ROXBORO STEAM ELECTRICPLANT G-29S-11101002121010020237145 3714500029 CP&L - ROXBORO STEAM ELECTRICPLANT G-35AS-35101002121010020237145 3714500029 CP&L - ROXBORO STEAM ELECTRICPLANT G-35BS-35101002121010020237145 3714500029 CP&L - ROXBORO STEAM ELECTRICPLANT G-36AS-47101002121010020237145 3714500029 CP&L - ROXBORO STEAM ELECTRICPLANT G-36BS-47101002121010020237145 3714500045 CP&L - MAYO FACILITYG-46A S-1 1 10100212 1010020237145 3714500045 CP&L - MAYO FACILITYG-46B S-1 1 10100212 1010020237155 3715500147 PROGRESS ENERGY CAROLINAS, INC., W.H. WEATHERSPOON PLANT G-26 S-2 9 10100202 1010021237155 3715500166 LUMBERTON POWER, LLCG-17A S-1 7 10101202 1010020437159 3715900004 DUKE ENERGY CORPORATION - BUCK STEAM STATIONG-4 S-6 8 10100202 1010021237159 3715900163 ROWAN COUNTY POWER LLCG-1 S-1 1 10100604 2010020137159 3715900163 ROWAN COUNTY POWER LLCG-2 S-2 3 10100604 2010020137159 3715900163 ROWAN COUNTY POWER LLCG-3 S-3 5 10100604 2010020137169 3716900004 DUKE ENERGY CORP - BELEWS CREEK STEAM STATIONG-17 S-1 1 10100215 1010020237169 3716900004 DUKE ENERGY CORP - BELEWS CREEK STEAM STATIONG-18 S-2 2 10100215 1010020237191 3719100017 PROGRESS ENERGY - F LEE PLANTG-3 S-1 3 10100212 1010020237191 3719100017 PROGRESS ENERGY - F LEE PLANTG-4 S-2 5 10100212 1010020245021 0600-0081 DUKE ENERGY:MILL CREEKCA1 1 2 20100101 2010020145021 0600-0081 DUKE ENERGY:MILL CREEKCA2 2 2 20100101 2010020145021 0600-0081 DUKE ENERGY:MILL CREEKCA3 3 2 20100101 2010020147145 0013 TVA KINGSTON FOSSIL PLANT001 S-1 1 10100202 1010021247145 0013 TVA KINGSTON FOSSIL PLANT002 S-1 1 10100202 1010021247145 0013 TVA KINGSTON FOSSIL PLANT003 S-1 1 10100202 1010021247145 0013 TVA KINGSTON FOSSIL PLANT004 S-1 1 10100202 1010021247145 0013 TVA KINGSTON FOSSIL PLANT005 S-1 1 10100202 1010021247145 0013 TVA KINGSTON FOSSIL PLANT006 S-2 1 10100202 1010021247145 0013 TVA KINGSTON FOSSIL PLANT007 S-2 1 10100202 10100212Atmospheric Sciences GroupAlpine Geophysics, LLC▪387 Pollard Mine Road▪Burnsville, NC 28714▪(828) 675-9045▪(828) 675-5801 FAXFIPS Plant ID Plant NamePoint IDStack ID Segment 2002 SCC IPM SCC47145 0013 TVA KINGSTON FOSSIL PLANT008 S-2 1 10100202 1010021247145 0013 TVA KINGSTON FOSSIL PLANT009 S-2 1 10100202 1010021247157 00528 ALLEN FOSSIL PLANTCTrb10 CTrb10 13 20100101 2010020147161 0011 TVA CUMBERLAND FOSSIL PLANT001 S-01 1 10100215 1010020247161 0011 TVA CUMBERLAND FOSSIL PLANT002 S-02 1 10100215 1010020251001 00030 COMMONWEALTH CHESAPEAKE POWER STATION1A 1 1 20100101 2010020151001 00030 COMMONWEALTH CHESAPEAKE POWER STATION1B 1 2 20100101 2010020151001 00030 COMMONWEALTH CHESAPEAKE POWER STATION1C 1 3 20100101 2010020151001 00030 COMMONWEALTH CHESAPEAKE POWER STATION1D 1 4 20100101 2010020151001 00030 COMMONWEALTH CHESAPEAKE POWER STATION1E 1 5 20100101 2010020151001 00030 COMMONWEALTH CHESAPEAKE POWER STATION1F 1 6 20100101 2010020151001 00030 COMMONWEALTH CHESAPEAKE POWER STATION1G 1 7 20100101 2010020151083 00046 DOMINION - CLOVER POWER STATION11 4 10100501 1010021251083 00046 DOMINION - CLOVER POWER STATION22 4 10100501 1010021251153 00002 DOMINION - POSSUM POINT33 1 10100212 2010020151175 00051 DOMINION - SOUTHAMPTON POWER STATION11 1 10200219 1010020451191 00180 WOLF HILLS ENERGY LLC21 1 1 20100209 2010020151191 00180 WOLF HILLS ENERGY LLC22 2 1 20100202 2010020151191 00180 WOLF HILLS ENERGY LLC23 3 1 20100202 2010020151191 00180 WOLF HILLS ENERGY LLC24 4 1 20100202 2010020151191 00180 WOLF HILLS ENERGY LLC25 5 1 20100202 2010020151760 00389 DOMINION - BELLEMEADE 20 1 1 20100101 2010020151760 00389 DOMINION - BELLEMEADE 21 2 1 20100101 2010020154023 0014 NORTH BRANCH POWER STATION002 001 01 10100217 10100202