## Quality Assurance Project Plan (Draft)

For

Central Regional Air Planning Association (CENRAP)

Emissions and Air Quality Modeling

Revision 3 March 29, 2004

Prepared for:

Ms. Annette Sharp

Executive Director

and

Mr. Jeff Peltola

Technical Director

Central Regional Air Planning Association 10005 S. Pennsylvania, Ste. C

Oklahoma City, OK 73159

Project Manager and Co-Principal Investigator: Mr. Ralph Morris ENVIRON International Corporation 101 Rowland Way, Site 220 Novato, CA 94945

Co-Principal Investigator:

Dr. Gail Tonnesen College of Engineering Center for Environmental Research and Technology University of California at Riverside Riverside, CA 92507Approvals

Title: Quality Assurance Project Plan for Central Regional Air Planning Association (CENRAP) Emissions and Air Quality Modeling, November 19, 2004.

Ms. Annette Sharp Date:

Technical Director Central Regional Air Planning Association (CENRAP)

(Name here) Date: Project Officer U.S. Environmental Protection Agency

Mr. Ralph Morris Date: Project Manager and Co-P rincipal Investigator ENVIRON International Corporation

Dr. Gail Tonnesen Date: Co-Principal Investigator University of California, Riverside

EVIRON International Corporation 101 Rowland Way, Suite 220

Novato, California 94945TABLE OF CONTENTS

Page

1.0 INTRODUCTION ............................................................................................................... ......1

1.1 Problem Definition........................................................................................................ .......2

2.0 PROJECT DESCRIPTION........................................................................................................ 2 2.1 Background................................................................................................................. .........2 2.2 CENRAP Long Range Plan.................................................................................................4

2.2.1 Tier One: Tasks........................................................................................................4

2.2.2 Tier Two: Activities.................................................................................................4 2.2.3 Tier Three: Projects..................................................................................................4

2.2.4 Tier Four: Deliverables............................................................................................5

2.2.5 Critical Milestones Dates.........................................................................................5

2.2.6 Role of Emissions and Air Quality Modeling in CENRAP Long Range Plan.....................................................................................6

2.3 Quality Assurance of the CENRAP 2002 Annual Emissions

2.3.6 and Air Quality Modeling........................................................................................6 2.3.1 Past Related Regional Modeling Studies.................................................................6

2.3.2 QA for the CENRAP 2002 Annual Emissions and Air Quality Modeling...............................................................................................7 2.3.2.1 Data Gatekeeping...............................................................................................8 2.3.2.2 Emissions QA/QC..............................................................................................9 2.3.2.3 Meteorology QA/QC .......................................................................................10 2.3.2.4 Air Quality Modeling QA/QC .........................................................................11 2.3.2.5 Overview of Data Flow and Quality Assurance Process.................................12

2.4 Scope of Work for CENRAP 2002 Annual Emissions and Air Quality Modeling ............................................................................................................. .18 2.4.1 Project Management ..............................................................................................19 2.4.2 Phase I Modeling Tasks.........................................................................................20

2.4.2.1 Task 1-1: Develop and Update Quality Assurance Project Plan (QAPP) and Modeling Protocol ..................................................20

2.4.2.2 Task 1-2: Develop Modeling Protocol/Work Plan for Performing 2002 Base Case Mode ling for the CENRAP Region ...................20 2.4.2.3 Task 1-3: Develop Mode l-Ready Meteorology Inputs ....................................21 2.4.2.4 Task 1-4: Develop Base Case Model-Ready 2002 Emission Inputs ...............22 2.4.2.5 Task 1-5: Perform 2002 Base Case Modeling and

Model Performance Evaluation .......................................................................25 2.4.2.6 Task 1-6: Develop Future Base Case Model-Ready Emission Inputs.............27 2.4.2.7 Task 1-7: Perform 2018 Modeling, Sensitivity Analysis and Control Strategy Evaluation 28 2.4.2.8 Task 1-8: Reports and Recommendations .......................................................29 2.4.3 Phase II Modeling Tasks........................................................................................30

2.4.3.1 Task 2-1: Revise and U pdate the CENRAP Modeling Quality Assurance Project Plan (QAPP)..........................................................30 2.4.3.2 Task 2-2: Develop Model- Ready Meteorological Inputs ................................30 2.4.3.3 Task 2-3: Generate Model-Ready Emissions ..................................................312.4.3.4 Task 2-4: Perform 2018 Base Case Modeling .................................................31

2.4.3.5 Task 2-5: Refine 2018 Ba se Case Modeling and Conduct Control Strategy Evaluations.............................................................32 2.4.3.6 Task 2-6: Final Report for Inclusion as CENRAP Technical Support Document ..........................................................................32

3.0 PROJECT MANAGEMENT...................................................................................................33 3.1 Project Organization ....................................................................................................... ...33 3.1.1 ENVIRON Project Manager a nd Co-Principal Investigator..................................37

3.1.2 ENVIRON and UCR Co-Pri ncipal Investigators ..................................................37

3.1.3 CENRAP Technical Direct or and Executive Director...........................................38 3.14 CENRAP Project Manager ....................................................................................39 3.1.5 CENRAP Modeling Workgroup............................................................................39 3.2 Project Schedule and Execution.........................................................................................39 3.3 Personnel Qualifications and Training...............................................................................40

3.4 Communications Plan ....................................................................................................... .40

3.5 Documentation and Records..............................................................................................41 4.0 MEASUREMENT AND DATA ACQUISTION....................................................................41 4.1 Computer Hardware/S ystems Administration ...................................................................41 4.1.1 ENVIRON Modeling Center Hardware.................................................................41 4.1.2 UCR Modeling Center Hardware ..........................................................................42 4.1.3 Backup Procedures.................................................................................................42 4.2 Sources for Data Used in Modeling...................................................................................43

5.0 EMISSIONS MODELING ......................................................................................................44 5.1 Quality Assurance Components of Emissions Modeling .................................................45 5.1.1 Modeling QA .........................................................................................................45 5.1.2 System QA.............................................................................................................4 5 5.1.3 Gatekeeping and Outside Review..........................................................................46

5.1.4 Documentation.......................................................................................................46 5.2 Implementation of the QA System ....................................................................................46 5.2.1 The Emissions QA Team.......................................................................................46

6.0 METEOROLOGICAL MODELING ......................................................................................49 7.0 CENRAP 2002 AIR QUALITY MODELING........................................................................50 7.1 CMAQ Overview ............................................................................................................ ..50 7.2 CMAQ Configuration for CENRAP Modeling .................................................................51 7.2.1 Updates to the CMAQ Secondary Organic Aerosol (SOA) Module.....................51

7.2.1.1 SOAmods Formation .......................................................................................52 7.2.1.2 Quality Assurance of SOAmods......................................................................55

7.3 CAMx Overview............................................................................................................. ...57 7.4 CAMx Configuration for CENRAP Modeling..................................................................58 7.5 Advantages of Operating Multiple Models........................................................................59

8.0 ASSESSMENTS AND OVERSIGHT ....................................................................................61 8.1 Assessment Responsibilities ..............................................................................................6 1 8.2 Assessment Types and Usage ............................................................................................61

8.3 Assessment Criteria ...................................................................................................... ....62

9.0 REFERENCES ................................................................................................................. .......62FIGURES

Figure 2-1a Data flow and quality assurance steps in the CENRAP Emissions and Air Quality Modeling ....................................................................16 Figure 2-1b Concluded. Data flow a nd quality assurance steps in the CENRAP Emissions and Air Quality Modeling....................................................17 Figure 3-1 CENRAP Emissions and Air Quality Modeling Project Organizational Chart..................................................................................34 Figure 5-1 Flow Diagram of Major SMOKE Processing Steps ..............................................45 Figure 5-2 Diagram of CENRAP Modeling Team Approach to SMOKE Modeling.............................................................................................48 Figure 7-1. Schematic describing th e addition of new SOA processes (bold italic) within the exis ting CMAQ SOA module (regular font) to treat polymerization and S OA from sesquiterpenes and isoprene.....................56

TABLES

Table 2-1. Model Performance goals us ed in Phase I to help interpret modeling results.....................................................................................................15 Table 2-2. Task 1-1: Develop Qual ity Assurance Project Plan (QAPP) and Modeling Protocol...........................................................................................20 Table 2-3. Task 1-2: Develop Mo deling Protocol/Plan for Performing

2002 Base Case Modeli ng for the CENRAP Region.............................................21 Table 2-4 Task 1-3: Develop Mo del-Ready Meteorological Inputs ......................................22 Table 2-5. Task 1-4: Develop Base Case Model-Ready 2002 Emissions Input .....................25

Table 2-6. Task 1-5: Perform 2002 Base Case and Model Performance Evaluation..............27 Table 2-7. Task 1-6: Develop Future Base Case Model-Read y Emissions Inputs .................28

Table 2-8. Task 1-7: Perform 2018 Modeling, Sensitivity Analysis and Control Strategy Evaluation............................................................................29 Table 2-9. Task 1-8: Reports and Recommendations .............................................................29 Table 2-10. Task 2-1: Revise and Update CENRAP Modeling QAPP.....................................30 Table 2-11. Task 2-2: Develop Mo del-Ready Meteorological Inputs ......................................31 Table 2-12. Task 2-3: General Model-Ready Emissions ..........................................................31

Table 2-13. Task 2-4: Perf orm 2018 Base Case Modeling .......................................................32

Table 2-14. Task 2-5: Refine 2018 base case modeling and conduct control strategy evaluations ...................................................................................32 Table 2-15. Task 2-6: Final report /Technical Support documentation (TSD)..........................33

Table 3-1. CENRAP 2002 Annua l Emissions and Air Quality Modeling project participants and contacts. ..........................................................35

Table 7-1. Parameters use in e nhanced SOA module (see Figure 7-1)...................................54 Table 7-2. Comparison of fractional bi as performance metric for Organic Carbon (OC) using the sta ndard CMAQ Version 4.4 (V4.4) and CMAQ V4.4 with he SOAmods enhancement......................................................55Quality Assurance Project Plan (Draft) Page 1 of 68 CENRAP Emissions and Air Quality Modeling Revision 3 ENVIRON International Corporation March 29, 2006

1.0 INTRODUCTION

This Quality Assurance Project Plan (QAPP) de scribes the quality mana gement functions and activities performed by the Cent ral Regional Air Planning Asso ciation (CENRAP) 2002 current and 2018 future-year annual Emissions and Ai r Quality Modeling, performed by ENVIRON International Corporation and the University of California at Riverside Co llege of Engineering –

Center for Environmental Research and Tec hnology (UCR/CE-CERT). This is the third revision (Revision 3) of the CENRAP Emissi ons and Air Quality Modeling QAPP and updates Revision 2 of the QAPP dated December 23, 2004. Revision 3 of the CENRAP Modeling QAPP updates the QAPP to include additional modeling analysis added with the CENRAP additional Award of Work dated December 15, 2005.

CENRAP is one of five Regiona l Planning Organizations (RPOs) that have responsibility for coordinating development of State Implementation Plans (SIPs) and Tribal Implementation Plans (TIPs) in selected areas of the U.S. to addres s the requirements of the EPA Regional Haze Rule (RHR). The RHR visibility SIPs/TIPs are due in 2007/2008. CENRAP modeling results may also form the regional component for 8-hour ozone and fine particulate (PM 2.5 ) SIPs/TIPs that are also expected to be due in 2007/2008. Th e CENRAP Emissions and Air Quality Modeling Team is comprised of staff from ENVIRON International Co rporation (ENVIRON) and the University of California, Riverside (UCR) . The ENVIRON/UCR Team will perform the emissions and air quality modeling simulations for states and tribes within the CENRAP region, providing analytical results us ed in developing implementati on plans under the EPA RHR.

The quality assurance approach utilized herein is generally based on the national consensus standard (ANSI/ASQC, 1994). This standard desc ribes the necessary management and technical elements for developing and implementing a quality system. It recommends a tiered approach to the design of the specific quality system used in each of the organization’s efforts. This approach has been adopted by the ENVIRON/UCR Team and is documented in the CENRAP 2002 Annual Modeling Protocol (ENVI RON and UCR, 2004) and in UCR’s Quality Management Plan (QMP; UCR, 2003). The CENRAP Modeling Protocol and UCR’s QMP formed the basis

for much of the content in this CENRAP Emissions and Air Quality Modeling QAPP.

This QAPP was prepared in accordance with th e EPA guidelines for quality assurance project plans for modeling (EPA, 2002), for QAPPs (EPA , 2001), and the North American Research Strategy for Tropospheric Ozone (NARSTO) Quality Handbook for modeling projects (NARSTO, 1998). The EPA and NARSTO guidance doc uments were developed specifically for modeling projects, which have different quality assurance concerns than environmental monitoring data collection projects . The work performed in this project involves modeling at the basic research level and for regulatory/policy ap plications. In order to utilize model outputs for these purposes, it must be established that each model is scientif ically sound, robust, and defensible. This is accomplished by following a pr oject planning process that incorporates the following elements as described in the EPA guidance document for modeling:

• A systematic planning process including id entification of assessments and related performance criteria;Quality Assurance Project Plan (Draft) Page 2 of 68 CENRAP Emissions and Air Quality Modeling Revision 3 ENVIRON International Corporation March 29, 2006

• Peer reviewed theory and equations;

• A carefully designed life-cycle developm ent process that minimizes errors;

• Documentation of any changes from original plans;

• Clear documentation of assumptions, theory, and parameterization that is detailed enough so others can under stand the model output;

• Input data and parameters that are accura te and appropriate for the problem; and

• Output data that can be used to help inform decision makers.

The purpose of this QAPP is to establish and en courage a continuous improvement process that will result in clearly defined data qual ity objectives, documentation, procedures, and requirements for QA benchmarks and reports. A rigorous quality system will assist in ensuring that the quality of the project products are known, defensible, and meet the user’s data quality objectives. This system will also enable the modeling team to systematically plan to

accommodate the additional work that will be required to ensure high-quality results.

1.1 Problem Definition

The 1990 Amendments to the Clean Air Act and the 1999 U.S. EPA Regional Haze Rule establishes special goals for visibility in 156 na tional parks, wilderness areas, and international parks. Through these amendments, Congress set a na tional goal for visibility as “the prevention of any future, and the remedying of any existing, impairment of vi sibility in mandatory Class I Federal areas which impairment results from manmade air pollution” (40 CFR 51.300). States are required to develop State Implementation Plan s (SIPs) to attain visi bility standards, and Tribes also may opt to assume responsibility for visibility programs under 40 CFR Part 49 by developing Tribal Implementation Plans (TIPs). States, and potentially Tribes, in the Central States are required to submit visibility SIPs unde r Section 308 of the Re gional Haze Rule (RHR).

The Central Regional Air Planni ng Association (CENRAP) ha s implemented a regional air quality planning process to provide the necessary technical and po licy tools needed by states and tribes to comply with Section 308 of the RHR. As part of this effort, CENRAP has funded modeling studies to support the development of SIPs and TIPs. In October 2004, CENRAP retained ENVIRON International Corporation a nd the University of California at Riverside (UCR) to perform Emissions and Air Qu ality Modeling of the 2002 annual period.

The results from these modeling studies will help determine the proper mitigation measures that will be necessary to comply with Section 308 of the RHR.

2.0 PROJECT DESCRIPTION

2.1 Background

CENRAP is a regional partnership of states, tribes, federal agencies, stakeholders and citizen groups established to initiate a nd coordinate activities associat ed with the management of regional haze and other air quality issues within the CENRAP states. The CENRAP region

includes states and tribal land s located within the boundaries of Arkansas, Iowa, Kansas,Quality Assurance Project Plan (Draft) Page 3 of 68 CENRAP Emissions and Air Quality Modeling Revision 3 ENVIRON International Corporation March 29, 2006

Louisiana, Minnesota, Missouri, Nebraska, Oklahoma and Texas. The governing body of CENRAP is the Policy Oversight Group (POG) that is made up of 18 voting members representing the states a nd tribes within the CENRAP region and non-voting members representing local agencies, the EPA and other federal agencies. The work of CENRAP is accomplished through five standing workgroups see Table 3-1 for contact information):

• Monitoring;

• Emissions Inventory;

• Modeling;

• Communications; and

• Implementation and Control Strategies.

•

Participation in workgroups is open to all intere sted parties and the POG may form additional ad hoc workgroups to address specific issues (e.g., a Data Analysis workgroup has been formed).

The RHR requires the states (the tribes may elect) to submit the first SIPs and TIPs in 2007/2008 that address progress toward natural conditions at federally mandated Class I areas. 40 CFR 51.308 (Section 308) discusses the following five core requirements to be included in SIPs/TIPs and Best Available Retrofit Technology (BART) requirements:

1. Reasonable progress goals;

2. Calculations of baseline and natural visibility conditions;

3. Long-term strategy for regional haze;

4. Monitoring strategy and other implem entation plan requirements; and

5. BART requirements for regional haze visibility impairment.

One of CENRAP’s goals is to provide support to states and tribes to meet each of these requirements of the RHR and to develop scientif ically supportable, economical and effective control strategies that the states and tribes ma y adopt to reduce manmade effects on visibility impairment at Class I areas. One component of this support is performing emissions and air quality modeling to obtain a bett er understanding of the causes of regional haze and potential mitigation measures for visibility impairment at Class I areas, to evaluate the effects of alternative control strategies fo r improving visibility, and for pr ojecting future-year air quality and visibility conditions. In October 2004, CENRAP selected a team of ENVIRON and UCR to perform their initial current and future year Emissions and Air Quality Modeling for the 2002 annual period. In December 2005 CENRAP awarde d additional work to ENVIRON and UCR to perform 2018 control strategy ev aluation, PM source apportionm ent and prepare a Technical Support Document (TSD) for the modeling as part of the RHR visibility SIP due in December

2007.

The CENRAP Emissions and Air Quality Modeling Team performs regional haze analyses by operating regional scale, three-dimensional air quality models that simulate the emissions, chemical transformations, and tr ansport of gaseous and partic ulate matter (PM) species and consequently effects on visibility in Class I Areas in the central U. S. A key element of this work includes the integration of emissi ons inventories and models with regional transport models. TheQuality Assurance Project Plan (Draft) Page 4 of 68 CENRAP Emissions and Air Quality Modeling Revision 3 ENVIRON International Corporation March 29, 2006

general services provided by the CENRAP Emis sions and Air Quality Modeling Team include,

but are not limited to:

• Emissions processing and modeling;

• Air quality and visibili ty modeling simulations;

• Analysis, display, and reporti ng of modeling results; and

• Storage/quality assurance of the modeling input and output files.

2.2 CENRAP Long Range Plan

CENRAP adopted an initial Long Range Plan in October 2003 (CENRAP, 2003) and will review this plan each spring and fall and update it as needed. The CENRAP Long Range Plan is organized into four primary tiers of work efforts: (1) Tasks; (2) Activities; (3) Projects; and (4) Deliverables. The CENRAP long-range plan was updated in the spring 2005 and was approved by the CENRAP POG on March 2-3, 2005 (http://www.cenrap.org/organization.asp#).

2.2.1 Tier One: Tasks

The first tier of the CENRAP Long Range Plan consis ts of a series of work efforts or Tasks that comprise the statuary requirements of the Regional Haze Rule (RHR):

• Develop reasonable progress goals;

• Establish baseline and natural conditions;

• Develop a long term strategy for reducing regional haze;

• Develop a monitoring strategy and other SIP/TIP requirements; and

• Establish BART requirements.

Each of these Tasks must be accomplished to achi eve the goal of providing states and tribes the information upon which supportable and effectiv e RHR SIPs and TIPs will be developed.

2.2.2 Tier Two: Activities

The second tier (Activities) consists of broad, categorized work effo rts that must be completed in order to complete a Task. For example, the 2002 annual Emissions and Air Quality Modeling effort is an Activity that needs to be comple ted in order to perfor m the “develop reasonable progress goals” and “develop a long term stra tegy for reducing regional haze” Tasks.

2.2.3 Tier Three: Projects

The third tier consists of specific Projects ai med at completing an Activity. For example, to perform the 2002 annual modeling, 2002 emissions are needed, thus a specific project would be to compile 2002 emissions for the CENRAP states and to provide them to the Emissions and Air Quality Modeling Team. Details on specific projec ts are identified in the Attachments to the Updated CENRAP Long Ra nge Plan (CENRAP, 2005).Quality Assurance Project Plan (Draft) Page 5 of 68 CENRAP Emissions and Air Quality Modeling Revision 3 ENVIRON International Corporation March 29, 2006

2.2.4 Tier Four: Deliverables

The fourth and final tier is the Deliverables that consist of the individua l components of the work effort necessary to complete a given Project. Deliverables for the 2002 Annual Emissions and Air Quality Modeling activities will include a Modeling Protocol, a QAPP, Base Case Modeling and Model Performance Evaluation Report, PowerPoi nt presentations of future-year base case modeling, control strategy evaluations and PM source apportionment modeling and a draft and final technical Support Document (TSD) that desc ribes the modeling and is suitable for including with the visibility SIP due December 2007.

2.2.5 Critical Milestones Dates

The Updated CENRAP Long Range Plan (CENRAP, 2005) contains a series of milestone dates by which critical decisions must be made to addre ss a regulatory or statut ory deadline. Critical milestone dates were assigned to the following activities:

• SIP submittal;

• SIP and TIP drafting and approval;

• Conducting future-year modeling; and

• Conducting base case modeling.

The Updated CENRAP Long Range Plan back-calcula ted critical milestone dates from the date that the RHR SIPs/TIPs are required to be su bmitted and developed the following timeline (see Attachment 2 of Updated CENRAP Long Range Plan):

SIP/TIPs Adopted and States Su bmit SIP to EPA – December 17, 2007 : Although SIP/TIP may be submitted later with the PM 2.5 SIP due April 2008, CENRAP is adopting the December 2007 submittal date in developing their critical milestone dates to assure

that CENRAP obtains the information nece ssary to develop the RHR SIP/TIPs in a timely fashion.

States and Tribes Begin to Draft an d Adopt SIPs and TIPs – July 1, 2006 : A survey of the timelines for SIP approval for states in the CENRAP region indica tes that the states can draft and adopt a SIP as long as the technical analysis has been completed 18 months

in advance.

Future-Year Modeling Begins – May 1, 2005 : States are to pr ovide BART reduction estimates and/or market trading estimates for their BART sources.

Base Case Modeling Begins – February 1, 2005 : The CENRAP Modeling Workgroup

has estimated that it will take six months to perform base year base case modeling and model performance evaluation.Quality Assurance Project Plan (Draft) Page 6 of 68 CENRAP Emissions and Air Quality Modeling Revision 3 ENVIRON International Corporation March 29, 2006

2.2.6 Role of Emissions and Air Quality Mo deling in CENRAP Long Range Plan

As seen above, the 2002 Annual Emissions and Air Quality Modeling is a critical part of the overall CENRAP efforts and is an essential comp onent for the development of the RHR SIPs and TIPs. The modeling information must be of hi gh quality and reliability in order to develop effective RHR control strategies . Thus, comprehensive and exha ustive quality assurance (QA) and quality control (QC) techniques are necessary.

2.3 Quality Assurance of the CENRAP 2002 Annua l Emissions and Air Quality Modeling

The CENRAP 2002 annual Emissions and Air Qua lity Modeling includes annual emissions and PM/regional haze simulations using a 36 km grid covering the continental US and adjacent regions, plus simulation of additi onal shorter duration episodes us ing a 12 km grid covering the Central States. After detailed performance tes ting, the modeling system will then be exercised with a variety of emissions cont rol scenarios aimed at enabling CENRAP to assess the effects of future year emission control strategies on visi bility and other air quality issues. The modeling system will also allow CENRAP to track reasonabl e progress toward regional haze goals. More specifically, the CENRAP Emissions and Air Qua lity Modeling effort will focus on the use of the SMOKE emissions and CMAQ and CAMx air quality modeling system s for calendar year

2002 over the Inter-RPO continental US 36 km horizontal grid, as well as potentially the CENRAP Central States 12 km grid.

2.3.1 Past Related Regional Modeling Studies

The CENRAP 2002 annual Emissions and Air Qu ality Modeling activities are built off of previous regional emissions, photochemical PM and visibility modeling effo rts performed in the

Central States and across the United States. Th e procedures used in these previous studies provide a guide to the modeling and QA approa ch for the CENRAP 2002 annual Emissions and Air Quality Modeling:

Big Bend Regional Aerosol sand Visibility Observational Study (BRAVO) : The BRAVO study examined the causes and sources of re gional haze at the Big Bend National Park, the most southwesterly Class I area in the CE NRAP states. It performed data collection activities, modeling and used numerous tec hniques to estimate PM source apportionment (Pitchford et al., 2004).

CENRAP Scoping Study : CENRAP commissioned a scoping study to identify the causes of visibility impairment at Cl ass I areas in the CENRAP stat es and identify the analytical tools that are available to investig ate regional haze (Green et al., 2002).

CENRAP Ammonia Emissions Inventory Study : CENRAP sponsored a study to develop an improved ammonia emissions inventory fo r the CENRAP states (Coe and Reid, 2003).Quality Assurance Project Plan (Draft) Page 7 of 68 CENRAP Emissions and Air Quality Modeling Revision 3 ENVIRON International Corporation March 29, 2006

CENRAP Agricultural and Prescribed Burns Study : In this study improved emissions inventories for prescribed burns and agri cultural burning were developed for the CENRAP states (Reid et al., 2004a).

Evaluation of CMAQ and CAMx Models Over the CENRAP States for Three Episodes : CMAQ and CAMx model simulations of a January 2002, July 1999 and July 2001 episodes were evaluated using measurement data in the CENRAP states (Tonnesen and Morris, 2004).

Development of Enhanced Mobile Source and Agricultural Dust Emissions for

CENRAP : This study developed on-road and non-ro ad mobile source and agricultural

dust emission inventories for the CE NRAP states (Reid et al., 2004b).

Development of 2002 Base Case Modeling Inventory for CENRAP : CENRAP sponsored this study to prepare a 2002 Base Case emissions inventory for the CENRAP

states that can be used in emissions and photochemi cal modeling of the 2002 annual period (Strait, Roe and Vukovich, 2004).

Preliminary PM and Visibility Modeling for CENRAP : Under this study preliminary regional PM and visibility modeling wa s conducted focused on the CENRAP region using the CMAQ and CAMx models (Pun, Chen and Seigneur, 2004).

VISTAS Phase I Model Sensitivity and Evaluation Study : This study, sponsored by VISTAS, performed extensive model sensitivity testing and evaluati on analysis using the CMAQ and CAMx models and three episodes, January 2002; July 1999 and July 2001 (Morris et al., 2004a).

WRAP Section 309 SIP/TIP Modeling Analysis : The WRAP performed a study to generate the necessary modeli ng data needed to develop Se ction 309 SIP/TIP for states that opt-in to this prog ram (Tonnesen et al., 2003).

VISTAS Phase II 2002 Annual Modeling : VISTAS is performing annual modeling of 2002 using a continental US 36 km domain and eastern US 12 km domain with attendant model evaluation and sensitivity an alysis (Morris et al., 2004b).

Many of the above studies are providing data (e.g., emissions) that will be used in the CENRAP Emissions and Air Quality Mode ling Study. Consequently, the quality assurance (QA) and quality control (QC) procedures employed are di rectly relevant to this QAPP. Others are companion modeling studies (e.g., BRAVO, VISTAS and WRAP) that provide information used in the development of this QAPP and the CENRAP Emissions and Air Quality Modeling Protocol (ENVIRON and UCR, 2004).

2.3.2 QA for the CENRAP 2002 Annual Emissions and Air Quality Modeling

The CENRAP 2002 annual Emissions and Air Quality Modeling Study will use 36km MM5 meteorological data provided by the Iowa De partment of Natural Resources (IDNR) (Johnson,Quality Assurance Project Plan (Draft) Page 8 of 68 CENRAP Emissions and Air Quality Modeling Revision 3 ENVIRON International Corporation March 29, 2006

2004), 12km MM5 meteorological da ta provide by other CENRAP participants and emissions data provided by CENRAP contractors (Strait, Roe and Vukovich, 2004) a nd EPA. These data will be used to perform emissions and air qua lity modeling of the 2002 annual period on a 36 km grid and for episodes of shorter duration using a 12 km grid. Additiona l annual 12 km modeling may also be performed.

Closely integrated with the a nnual (and possibly episodic) mete orological, emissions and air quality modeling will be ongoing project manage ment, technical review, and QA activities performed under the guidance of the CENRAP Project Manager, CENR AP Administrative Project Manager and the CENR AP Modeling Workgroup. The m odeling team members will conduct regular monthly conference calls with CENRAP management , as well as ad hoc topical conference calls as needed, and will attend pe riodic meetings with the CENRAP Modeling Workgroup as needed.

Complementing the data acqui sition, modeling input developm ent activities, and project management activities, the following four other CENRAP Emissions and Air Quality Modeling activities/functions will be performed, consis tent with the QAPP and CENRAP’s Long Range

Plan:

2.3.2.1 Data Gatekeeping

The CENRAP Emissions and Air Quality M odeling Team are receiving emissions, meteorological and air quality data from other CENRAP contractors, participants, or other sources. As a first line of QA, we have defined a Gatekeeping func tion to assure that the data have been received correctly, th e quality of the data has been evaluated, and that the data received have been documented. Separate air quality, meteorological and emissions Gatekeepers

have been identified whose roles are defined belo w. In addition, a Data Management Gatekeeper has been defined who will post data, reports and re sults to the project website and archive all key data generated in the project.

3⁄4 Air Quality Data Gatekeeper . Obtains air quality data as appropriate for model input development and model performance evaluation and assures that the quality of all air quality data obtained are consistent with th e approved QAPP. Provides documentation of evaluation and generate IC/ BC inputs for CMAQ and CAMx for all modeling runs.

3⁄4 Meteorological Gatekeeper . Obtains meteorological data as MM5 files for annual 2002 modeling runs (36 km) and other episode pe riods (12 km) and performs data quality checks as approved in the QAPP, together w ith the appropriate documentation of model performance evaluation activities.

3⁄4 Emissions Gatekeeper. Obtains emissions inventory da ta for CENRAP states from the CENRAP emissions contractor (Strait, Roe and Vukovich, 2004) necessary to support annual 2002 and future year modeling and r ecommend source of emissions data to be used for non-CENRAP states, Canada and Mexic o. Assures quality of all emissions data received are consistent with the approved QAPP, and develops all emissions modeling files to support modeling runs for 2002. De velops the chemical speciation files andQuality Assurance Project Plan (Draft) Page 9 of 68 CENRAP Emissions and Air Quality Modeling Revision 3 ENVIRON International Corporation March 29, 2006

temporal and spatial allocation files necessary to convert annual inve ntories into hourly and daily emissions modeling files, as appropr iate. Develops all emissions modeling files for non-CENRAP states to support modeling runs for future year base case.

3⁄4 Data Management Gatekeeper : Maintains the CENRAP Modeling Website including posting modeling input and output files, repor ts, interpretation of results, and other documents as requested by CENR AP. This includes, for exam ple, the storage of model inputs and outputs for annual (and episodic) runs and the tran sfer (via fire wire or alternative media) of elec tronic files to CENRAP stat es, other regional planning organizations, EPA, other cont ractors, and stakeholders.

2.3.2.2 Emissions QA/QC

Emissions Quality Assurance (QA) and Quality Cont rol (QC) are some of the most critical steps in performing air quality modeling studies. B ecause emissions processing is tedious, time consuming and involves complex manipulation of ma ny different types of large data sets, errors are frequently made in emissions processing and, if rigorous QA measures are not in place, these errors may remain undetected. In the CENRAP Emissions and Air Quality Modeling effort we will perform a multistep emissions QA/QC appr oach that was developed under WRAP and

VISTAS. This includes the initial emissions QA/QC by the Emissions Gatekeeper described above, as well as QA/QC by the Emissions Modeler during the processing of emissions, and then additional QA/QC by the air quality modeler of the processed mode l ready emission files. This multistep process with three separate groups invol ved in the QA/QC of the emissions is designed to detect and correct errors prior to the air quality model simulations.

Emissions QA/QC performed as part of the emissions modeling includes:

EPA Input Screening E rror Checking Algorithms : Although the SMOKE emissions model will be used for emissions proces sing, some additional input error checking algorithms like those used with the EMS and E PS emission models will be considered to screen the data and identify potential emissi on input errors. Additionally, EPA has issued a revised stack QA and augmentation procedur es memorandum that will be used to identify and augment any outlying stacks.

SMOKE Error Messages : SMOKE provides various cautionary or warning messages during the emissions processing. We will redi rect the SMOKE output to log files and review the log files for serious error message s. An archive of the log files will be maintained so that the error messages can be reviewed at a later date if necessary.

SMOKE Emissions Summaries : We will use QA functions built into the SMOKE processing system to provide summaries of pr ocessed emissions as da ily totals according to species, source category and county a nd state boundaries. These summaries will then be compared with summary data prepared fo r the pre-processed emissions, e.g., state and county totals for emissions from the augmented emissions data.Quality Assurance Project Plan (Draft) Page 10 of 68 CENRAP Emissions and Air Quality Modeling Revision 3 ENVIRON International Corporation March 29, 2006

After the CMAQ-ready emission inputs have b een prepared, we will perform additional emissions QA/QC as follows:

Spatial Summary : We will sum the emissions for all layers and for all 24 hours that is used to prepare a PAVE plot showing the da ily total emissions spa tial distribution. For a 20-day simulation, this produces approximate ly 20 days x 20 species x 5 emissions categories = 2,000 plots. In our base case simula tions these plots will be presented as tons per day. The 5 emission categories typically used are biogenic, fires, on-road mobile, other low-level anthropogenic (area plus non-road) and point sources. If possible, separate spatial QA plots will be generated for low-level and elevated point sources. The objective of this step is to identify erro rs in spatial distribution of emissions.

Vertical Profile : For point sources the emissions tota l for each layer will be summed and plotted by source category to show the verti cal distribution of emissions. These plots

show the emissions on the x-axis for each mode l layer on the y-axis. The objective of this step is to identify possible errors in vertical distribution of emissions.

Short Term Temporal Summary : The total domain emissions for each hour will be accumulated and time series plots prepared by source category that display the diurnal variation in total hourly emissions. The objective of this step is to identify errors in temporal profiles.

Long Term Temporal Summary : The total domain emissions for each day will be accumulated and displayed as time series plots that show the daily total emissions across

the domain as a function of time. The objective of this step is to identify particular days for which emissions appear to be inconsiste nt with other days fo r no reason (e.g., not a weekend) and compare ag ainst the general trend.

Control Strategy Spatial Displays : Spatial summary plots of the daily total emissions differences between a control strategy and base case emissions scenarios will be generated. These plots can be used to im mediately identify a problem in a control strategy. For example, if a CENRAP state’s SO 2 emissions control strategy is being analyzed and there are changes in em issions for other pollutants or for SO 2 outside of the CENRAP state, problems in emissions processing can be identified prior to the air quality

model simulation.

The emissions QA/QC displays ar e made available to CENRAP pa rticipants for review through the project website (see: http://pah.cer t.ucr.edu/aqm/cenrap/emissions.shtml).

2.3.2.3 Meteorology QA/QC

Participants performing the 36 km annual a nd 12 km MM5 modeling will conduct their own QA/QC and evaluation of the me teorological fields. For example, Johnson (2004) and Baller (2004) have performed an init ial evaluation of the 36 km MM5 results. In addition, the Emissions and Air Quality Modeling Team will also perform some QA/QC of the meteorologicalQuality Assurance Project Plan (Draft) Page 11 of 68 CENRAP Emissions and Air Quality Modeling Revision 3 ENVIRON International Corporation March 29, 2006

data to assure that it has been transferred correctly, to obtain an assessment of the quality of the data, and to assist in the interpretati on of the air quality modeling results.

The CENRAP Emissions and Air Quality Modeli ng Meteorological Gatekeeper will perform the following:

3⁄4 Analyses of the MM5 data to assure th at it has been tr ansferred correctly.

3⁄4 Evaluation of the MM5 data using METSTAT and the surface meteor ological network.

3⁄4 Evaluation of upper-air MM5 meteorological estimates by comparison them to upper-air observations and satellite images.

3⁄4 Comparison of the CENRAP 2002 36 km MM5 simulation with the ones generated by

WRAP and VISTAS.

3⁄4 Generation of the CMAQ-ready meteorologi cal inputs using the MCIP2.3 processor.

In October 2005 EPA released a new version of the CMAQ modeling system (V4.5) that included a new version of MCIP (M CIP3.0). In order to take full advantage of the new features of CMAQ V4.5 (e.g., Sea Salt emissions, AE3 aer osol module and spatially varying minimum Kz), the MCIP3.0 processor needs to be used. A new version of CAMx is also available (V4.3) that requires use of a new ve rsion of MM5CAMx to process ice-phase water. Thus, the following additional work was added to the Meteorological Gatekeepers with the December 2005 contract update:

3⁄4 Process 36 km and 12 km MM5 data for 2002 using the latest MCIP3.0 and MM5CAMx processors for CMAQ V4.5 and CAMx V4.3.

The Meteorological Gatekeeper report evaluation of the CENR AP 36 km MM5 results and comparison with the VISTAS and WRAP 36 km MM5 runs can be found on the project website (http://pah.cert.ucr.edu/aqm/cenrap/pp t_files/CENRAP_VISTAS_WRAP_2002_36km_MM5_ev al.ppt).

2.3.2.4 Air Quality Modeling QA/QC

Key aspects of QA for the CMAQ and CAMx i nput and output data include the following:

3⁄4 Verification that correct conf iguration and science options are used in compiling and running each model in the CMAQ modeling system, where these include the MCIP, JPROC, ICON, BCOM and the CCTM. Sa me procedures for the CAMx modeling system that includes MM5CAMx and TUV.

3⁄4 Verification that the correct configuration a nd science options are used in running each model in the CAMx modeling system wh ere these include MM5CAMx, TUV, CAMx, and the CMAQ-to-CAMx emissions and IC/BC processors.Quality Assurance Project Plan (Draft) Page 12 of 68 CENRAP Emissions and Air Quality Modeling Revision 3 ENVIRON International Corporation March 29, 2006

3⁄4 Verification that correct i nput data sets are used when running each model.

3⁄4 Evaluation of CCTM and CAMx results to veri fy that model output is reasonable and consistent with general expectations.

3⁄4 Processing of ambient monitoring data for use in the model performance evaluation.

3⁄4 Evaluation of the CCTM and CAMx results against concurrent observations and each

other.

3⁄4 Backup and archiving of cr itical model input data.

The most critical element for CM AQ and CAMx simulations is th e QA/QC of the meteorological and emissions input files, which is discussed ab ove. The major QA issue specifically associated with the air quality model simulations is verifi cation that the correct science options were specified in the model itself and that the correct input files were used when running the model. For CMAQ modeling we have employed a system of naming conventions using environment variables in the compile and run scripts that guara ntee that correct inputs and science options are used. Similar procedures are used in CA Mx modeling using file and directory naming conventions. We also have employed a redunda nt naming system so that the names of key science options or inputs are in cluded in the name of the CMAQ and CAMx executable program, in the name of the CMAQ and CAMx output files, and in the name of the directory in which the files are located. This is accomplished by using the environment variables in the scripts to specify the names and locations of key input files.

A second key QA procedure is to never “recycle” run scripts, i. e., we always preserve the original runs scripts and direct ory structure that were used in performing a model simulation.

We will also perform a post-processing QA of the CMAQ and CAMx output files similar to that described for the emissions proces sing. We will generate animated gif files using PAVE that can be viewed to search for unexpected patterns in the CMAQ and CAMx output files. In the case of model sensitivity studies, the animated gifs will be prepared as difference plots for the sensitivity case minus the base case. Often, errors in the emissions inputs can be discovered by viewing the animated GIFs. Finally, we will produce 24-hour average plots for each day of the CMAQ and CAMx simulations. This will provide a summary that can be useful for quickly comparing various model simulations. A spread sheet will be prepared and posted on the project website that tracks the model simulations providing a cl ear definition of the run and its purpose.

2.3.2.5 Overview of Data Flow and Quality Assurance Process

Figures 2-1a and 2-1b display an overview of the data flow and quality assurance process in the CENRAP Emissions and Air Quality Modeling study. The CENRAP Modeling Team receives different types of data from vari ous CENRAP participants and cont ractors and other sources that have performed their own QA and QC. Whenever data are receiv ed by the Modeling Team, it isQuality Assurance Project Plan (Draft) Page 13 of 68 CENRAP Emissions and Air Quality Modeling Revision 3 ENVIRON International Corporation March 29, 2006

first subjected to a QA check by a Gatekeeper who assess the accuracy and quality of the data and prepares a summary presentation on the QA ch eck. Figure 2-1a lists the Gatekeepers in the Modeling Team for emissions, boundary conditions , meteorological, ozone column (TOMS) and air quality data. If the Gatekeeper identifies any problems with the data, th e provider of the data

is contacted and asked to correct the data. After the Gatekeeper has conducted a QA check of the data it is passed on to the modeler who performs their own QA of the data. The data are then used in the modeling and resultant output (e.g., model-ready emissions or meteorological files), and are then subjected to anothe r round of QA to assure the integrity of the data is retained.

After the model-ready inputs have been developed and subjecte d to QA/QC, the models (e.g., CMAQ and/or CAMx) will be applied using Base Case emissions and the modeling results will be subjected to a model performance evalua tion. The model performance evaluation (MPE) represents an extensive QA effort and is one of the most time consuming components of the study. EPA has developed draft guidance for ev aluating regional PM and haze models that includes performance goals (EPA, 2001). In a ddition, the Modeling Team has adapted EPA MPE approaches and goals for 1-hour (EPA, 1991) and 8-hour (EPA, 1999) ozone modeling. The CENRAP Modeling Team will perform the MPE/QA process using as many different tools and analyses as possible in order to fully unders tand the accuracy, uncertainty and reliability of the model simulation. As seen in Figure 2-1b, the MPE process in CENRAP is a multistep process using several different techniques:

UCR Analysis Tools : The University of California at Riverside (UCR) Analysis Tools were used extensively in Ph ase I and are run on a Linux plat form separately for each network. Graphics are automatically genera ted using gnuplot and the software generates the following:

• Tabular statistical measures;

• Time Series Plots; and

• Scatter Plots by allsite_allday, al lday_onesite and allsite_oneday.

ENVIRON Analysis Tools : ENVIRON has developed speci alized evaluation tools to analyze visibility model performance for the Best and Worst 20% visibility days that are used in visibility projections for the Section 308 SIPs/TIPs. ENVIRON has also developed “Soccer Plots” that displays m odel performance across networks, episodes, species, models and sensitivity tests and compare them with performance goals. As part of VISTAS, the Georgia DNR has develo ped “Bugle Plots” th at display model performance as a function of observed concen tration that have been integrated with

ENVIRON’s evaluation tools.

CENRAP Model Evaluation Tool : CENRAP has developed a model evaluation tool that includes the observations in a MySQL data base for ease of manipulation of the

observation database. The CENRAP model evaluation tool can interface with Excel and/or gnuplot to generate the usual set of scatter plots, time series plots and similar

visual tools.Quality Assurance Project Plan (Draft) Page 14 of 68 CENRAP Emissions and Air Quality Modeling Revision 3 ENVIRON International Corporation March 29, 2006

The evaluation of the CENRAP 2002 CMAQ Base Case simulation will use ea ch of the analysis

tools listed above to take advant age of their different descriptive and complimentary nature. The use of multiple model evaluation tools is also a us eful QA/QC procedure to assure that errors are not introduced in the model evaluation process.

The issue of model performance goals for PM speci es is an area of ongoing research and debate. For ozone modeling, EPA has established perfor mance goals for 1-hour ozone normalized bias and gross error of # ± 15% and # 35%, respectively (EPA, 1991). EP A’s draft fine particulate modeling guidance notes that pe rformance goals for ozone shoul d be viewed as upper bounds of model performance, which PM models may not be able to always achieve, and we should demand better model performance for PM component s that make up a larger fraction of the PM

mass than those that are minor contributors (EPA, 2001). Measuring PM species is not as accurate as ozone monitoring. In fact, the di fferences in measurement techniques for some species likely exceed the more stringent perf ormance goals, such as those for ozone. For example, recent comparisons of the PM spec ies measurements using the IMPROVE and STN measurement technologies found differe nces of approximately ±20% (SO 4 ) to ±50% (EC) (Solomon et al., 2004).

In the CENRAP 2002 CMAQ Base Case modeling, we have adopted three levels of model performance goals for bias and gross error, as liste d in Table 2-1, that are used to help evaluate model performance. Note that we are not sugge sting that these performance goals be generally adopted or that they are the most appropriate goal s to use. Rather, we are just using them to frame and put the PM model performance into context and to facilitate model performance intercomparisons across episodes, species , models and sensitivity tests.

As noted in EPA’s draft PM modeling guidance, less abundant PM species should have less stringent performance goals. A ccordingly, we are also using performance goals that are a continuous function of average observed concentr ations proposed by Dr. James Boylan at the Georgia Department of Natural Resour ces that have the following features:

• Asymptotically approaching propos ed performance goals or crit eria when the mean of the

observed concentrations is greater than 2.5 μg/m 3

.

• Approaching 200% error and ±200% bias when the mean of the observed concentrations are extremely small.

Dr. Boylan uses bias/error goals and criteria of ± 30%/50% and ± 60%/75% and plots bias and error as a function of average observed concentrations. As th e mean observed concentration approaches zero the bias performan ce goal and criteria flare out to ± 200% creating a horn shape, hence the name “Bugle Plots.”Quality Assurance Project Plan (Draft) Page 15 of 68 CENRAP Emissions and Air Quality Modeling Revision 3 ENVIRON International Corporation March 29, 2006

Table 2-1. Model performance goals used in Phas e I to help interpret modeling results.

Fractional

Bias Fractional

Error Comments

# ±15% # 35% Ozone model performance goal for which PM model performance would be considered good.

# ±30% # 50% A level of model performance that we would hope each PM species could meet

# ±60% # 75% At or above this level of pe rformance indicates fundamental problems with the modeling system.

Model performance evaluation statistical measures will be calculated separately for each monitoring network and also stratified temp orally and geographically. Because different monitoring networks may use different measuremen t techniques it is important not to mix them when calculating statistical measures so that the results can be interpreted correctly. For example, the IMPROVE and STN Organic Car bon (OC) measurements contain significant differences. In addition, the calculation of st atistical measures by network also allows comparison of model performance at the more ur ban STN sites versus the more rural IMPROVE

and CASTNet sites. The CENRAP region will be divided up into several subdomains for the

model evaluation. At a minimum this would in clude north and south subdomain, but there may also be advantages to further geographic st ratifications (e.g., sout hern CENRAP subdomain could be split into west and east subdomains). Finally, temporal stratif ications will be at a minimum by month, but further stratifications will also be performed, including separate

evaluation for the Best 20% and Worst 20% visibility days at the Class I areas (i.e., IMPROVE sites).Quality Assurance Project Plan (Draft) Page 16 of 68CENRAP Emissions and Air Quality ModelingRevision 3ENVIRON International CorporationMarch 29, 2006Figure 2-1a.Data flow and quality assurance steps in the CENRAP Emissions and Air Quality Modeling.Quality Assurance Project Plan (Draft) Page 17 of 68CENRAP Emissions and Air Quality ModelingRevision 3ENVIRON International CorporationMarch 29, 2006Figure 2-1b.Concluded.Data flow and quality assurance steps in the CENRAP Emissions and Air Quality Modeling.Quality Assurance Project Plan (Draft) Page 18 of 68 CENRAP Emissions and Air Quality Modeling Revision 3 ENVIRON International Corporation March 29, 2006

2.4 Scope of Work for CENRAP 2002 Annual Emissions and Air Quality Modeling

The CENRAP 2002 annual Emissions and Air Qual ity Modeling work has been funded in two

Phases. The first Phase was authorized in a CENRAP Award of Work for ENVIRON/UCR dated October 22, 2004 and revised November 16 and December 16, 2004 and was initially divided up into eight tasks. A ninth task and additional work in other tasks was added to the Phase I work effort in a Change Work Order date d June 8, 2005. The Phase I work effort covers the period of October 2004 through April 2006. The nine Phase I tasks are as follows:

CENRAP Phase I Modeling Tasks

• Task 1-1 : Develop Quality Assurance Project Plan (QAPP)

• Task 1-2 : Develop Modeling Protocol/Plan for Performing 2002 Base Case Modeling for the CENRAP Region

• Task 1-3 : Develop Model-Ready Meteorological Inputs

• Task 1-4 : Develop Base Case Model-Ready 2002 Emission Inputs

• Task 1-5 : Perform 2002 Base Case Modeling and Model Performance Evaluation

• Task 1-6 : Develop Future-Year Base Case Model-Ready Emission Inputs

• Task 1-7 : Perform 2018 Modeling, Sensitivity Anal ysis and Control Strategy Evaluation

• Task 1-8 : Reports and Recommendations

• Task 1-9 : Processing, Reformatting and Quality Assurance Check of Midwest RPO Emissions Inventory Data

In December 2005 CENRAP issued ENVIRON/U CR an Award of Work dated December 15, 2005 for the Phase II 2002 annual modeling effo rts. The Phase II CENRAP 2002 annual Emissions and Air Quality Modelin g work is divided up into six tasks and covers the period of December 15, 2005 through December 31, 2006. The six Phase II tasks are as follows:

CENRAP Phase II Modeling Tasks

• Task 2-1 : Develop and Update Quality Assurance Project Plan (QAPP) and Modeling

Protocol

• Task 2-2 : Develop and Update Model- Ready Meteorological Inputs

• Task 2-3 : Generate Model-Ready Emissions

o Subtask 3a: Develop 2018 36 km SMOKE Emissions Modeling for CMAQ and

CAMx

o Subtask 3b: Develop 2018 12 km Emissi ons for CAMx using Flexi-Nesting

• Task 2-4 : Perform 2018 Base Case Modeling

o Subtask 2-4a: 2018 Base Case Modeling using CMAQ

o Subtask 2-4b: 2018 Base Case modeling using CAMx

o Subtask 2-4c: Up to 8 Sensitivity Runs with CMAQ

o Subtask 2-4d: Up to 8 Sensitivity Runs with CAMx

 Subtask 2-4e1: 2018 PM Source Appor tionment (CAMx/PSAT) for SO4, NO3, NH4 and Primary PMQuality Assurance Project Plan (Draft) Page 19 of 68 CENRAP Emissions and Air Quality Modeling Revision 3 ENVIRON International Corporation March 29, 2006

 Subtask 2-4e2: 2018 PM Source Apportionment (CAMx/PSAT) for SOA

o Subtask 2-4f: 2018 12 km “Flexi-Nesting” CMAQ and CAMx Model Runs

o Subtask 2-4g: Generate a Report on Model Results

• Task 2-5 : Refine Perform 2002 Base Case Mode ling and Model Performance Evaluation

• Task 2-6 : Generate a Final Report for inclus ion in the CENRAP Technical Support Document (TSD)

The previous studies discussed in Section 2.3.1 form the foundation for the CENRAP modeling and associated model QA/QC procedures. An important component of the QA/QC process is strong project management and project direction, which is discussed next.

2.4.1 Project Management

There are three aspects of Proj ect Management that are being performed under this task: (a) Project Management of the project’s resour ces and technical prog ress keeping CENRAP informed of progress; (b) Technical Management of the day-to-day technical activities of the ENVIRON/UCR Team keeping clear lines of communication, and (c) Communication Management of the data flow and expecta tions among the other CENRAP contractors.

Project Management : The Modeling Team Project Manager, Co-Principal Investigators (Co-PIs), and Task Managers have frequent communica tions with the CENRAP Project Manager and Administrative Project Manage r through regular conference calls , e-mails and meetings as needed. The ENVIRON and UCR Modeling Center s are headed by the two Co-PIs (Ralph Morris and Gail Tonnesen, respectively) with clear lines of communication and authority.

Technical Management : The two Co-PIs will be resp onsible and accountable for the management of the technical work within each of their respect ive research groups.

Communication Management : Key to the communications manage ment will be weekly internal conference calls among the two Co-Principal Investigators and the regular conference calls

between the two Co-PIs and the CENRAP Project Manager, Admini strative Project Manager and Modeling Workgroup and other CENRAP contractors and participants. When data are received from CENRAP contractors or other sources, th e CENRAP Modeling Team’s meteorological or emissions Gatekeeper will subj ect the data to extensive QA sc reening. Any problems identified will be reported to the two Co -PIs who will then immediately relay that information to the CENRAP Project Manager an d Administrative Project Ma nager and the relevant contractor/participant with the issue addressed in a conference call so that it can be resolved.

List servers related to emissi ons, meteorology, and modeling issues will be set up for prompt communication among the Modeling Team, CENR AP, and other CENRAP contractors.Quality Assurance Project Plan (Draft) Page 20 of 68 CENRAP Emissions and Air Quality Modeling Revision 3 ENVIRON International Corporation March 29, 2006

2.4.2 PHASE I MODELING TASKS

2.4.2.1 Task 1-1: Develop and Update Qualit y Assurance Project Plan (QAPP) and Modeling Protocol

The objective of this task is to prepare a Quality Assurance Project Plan (QAPP) and Modeling Protocol that documents the procedures for deve loping all model inputs, identifying sources of databases, identifying procedures for QA model inputs, developing model performance metrics and methodologies and is approvable by EPA. A QAPP will be prepared in accordance with EPA’s Quality Assurance Manuals including the “G uidance for Quality Assurance Project Plans for Modeling – EPA QA/G-5M” (EPA, 2002). EPA has developed specific format and content for QAPPs that will be followed. The steps that will be carried out to accomplish this task are as

follows:

• A preliminary draft CENRAP modeling QAPP and Modeling Protocol will be prepared following EPA guidelines using a preliminar y CENRAP Modeling Pr otocol developed under Task 1-2, CENRAP SOW and the CENRAP Long Range Plan.

• The two Co-PIs will revi ew and update the QAPP.

• A final review of the draft QAPP will be perf ormed to assure it adheres to EPA guidance.

• The draft QAPP will be submitted to CENR AP. If comments are received from CENRAP, the draft QAPP will be revised and submitted to CENRAP who will then submit the QAPP to EPA.

Table 2-2 summarizes the Task 1-1 deliverables and schedule.

Table 2-2. Task 1-1: Develop Quality Assurance Pr oject Plan (QAPP) and Modeling Protocol.

Item Description Due Date 1 Draft QAPP 11/19/04 2 Draft Final QAPP Within 1 week of comments

2.4.2.2 Task 1-2: Develop Modelin g Protocol/Work Plan for Performing 2002 Base Case Modeling for the CENRAP Region

The objective of this task is to develop a Modeling Protocol/Wor k Plan (MP/WP) that describes the CENRAP modeling approach including a revi ew of recent relevant regional modeling studies, sources of data, modeling approach, model evaluation approach and criteria, and schedule for completion.

A Modeling Protocol/Work Plan (MP/WP) will be prepared that summarizes current regional modeling studies, proposed modeling domain and gr id selection, proposed model configurations, details model input preparation, design of model ev aluation and sensitivity runs, discussions of model performance evaluation crite ria, an assessment of uncerta inties and actions needed to obtain better performance, and recommendations for future control strategy modeling. TheQuality Assurance Project Plan (Draft) Page 21 of 68 CENRAP Emissions and Air Quality Modeling Revision 3 ENVIRON International Corporation March 29, 2006

MP/WP will also describe the procedures that will be used to complete each task in this project. The MP/WP will also identify a list of input file s and resource needs that will be used for the model assessment, as well as the suite of mo deling systems (i.e. air quality, emissions, and meteorological modeling platforms) that it intend s to evaluate. The Task 1-2 draft MP/WP will be prepared concurrently with the QAPP and be submitted to CENRAP for approval before initiating Tasks 1-3 through 1-9. CENRAP may provide comments on the draft MP/WP and

ENVIRON/UCR will revise the MP/WP and submit a revised draft MP/WP to CENRAP within one week of receipt of comments. The MP /WP will be updated during the study as needed.

Specific steps in the development of th e CENRAP modeling MP/WP are as follows:

• The two Co-PIs will be responsible for developing the MP/WP.

• A preliminary draft CENRAP modeling MP /WP will be prepared by adapting and enhancing the VISTAS Phase II Modeling Protocol to incl ude CENRAP-specific issues and incorporating additional information fr om the CENRAP SOW, Long Range Plan and preliminary QAPP.

• We will then discuss the CENRAP MP/WP c ontents with the CENRAP Project Manager and representatives with the results integrated into the draft MP/WP.

• The draft MP/WP will be prepared following EPA guidance for preparing Modeling Protocols for 1-hour ozone (EPA, 1991) and 8-hour ozone (EPA, 1999) and PM 2.5 and regional haze (EPA, 2001) modeling.

Table 2-3 summarizes the task deliverables and sc hedule for this task. The draft MP/WP will be

submitted to CENRAP within 3 w eeks of authorization to proceed with the study. If comments are received from CENRAP, then a revised draf t MP/WP will be submitted within one week of receiving comments. The modeling team will con tinue to update the MP/WP during the project as necessary and in consultation with CENRAP.

Table 2-3. Task 1-2: Develop Modeling Protoc ol/Plan for Performing 2002 Base Case Modeling for the CENRAP Region.

Item Description Due Date 1 Draft Modeling Protocol/Workplan 11/19/04 2 Draft Final Modeling Protocol/Wor kplan Within 1 week of comments

2.4.2.3 Task 1-3: Develop Model-Ready Meteorology Inputs

The objective of this task is to develop 2002 mete orological inputs for emissions and air quality modeling. CENRAP Participants (Iowa Department of Natural Re sources, IDNR for the 36 km MM5 data, others for the 12 km MM5 data ) has conducted MM5 runs to develop 2002 meteorological fields for CENRAP 36 km m odeling grid and will conduct 12 km MM5 modeling for episodic periods. The ENVIRON/UCR Team will acquire the CENRAP 2002 36 km and 12 km MM5 outputs and process them using the la test versions of the Models-3 MCIP and MM5CAMx processors to generate hourly 2002 meteorological fields for the CMAQ and CAMx

models. Note that EPA has a new version of MCIP (Version 2.3) that includes some improvements (e.g., graupel pass through) and correcti ons (e.g., correction to errors in the Pleim-Quality Assurance Project Plan (Draft) Page 22 of 68 CENRAP Emissions and Air Quality Modeling Revision 3 ENVIRON International Corporation March 29, 2006

Xiu variables). MCIP version 2.3 will be used in this analysis. There is also a new version of the MM5CAMx processor that includes a new trea tment of subgrid-scale cloud processes that will be used in the CENRAP study; this version is currently available on the CAMx website ( www.camx.com ). We anticipate that MCIP and MM5 CAMx will be operated using the PBL pass through option, although if TKE output data are available we may consider using it. Specific steps to be undertaken to complete this task are as follows:

• Acquisition of the 2002 36 km and 12 km MM5 output from CENRAP;

• QA of the MM5 output through the Gatekeep er including running through the existing set up of METSTAT and comparison of model performance with the 2002 MM5 simulations performed by WRAP and VISTAS.

• Processing of the MM5 output using the latest version of the Models-3 MCIP processor to generate 2002 36/12 km mete orological inputs for CMAQ.

• Processing of the MM5 output using the late st version of MM5CAMx to generate 2002 36/12 km meteorological inputs for CAMx.

• QA/QC of the CMAQ and CAMx meteorological inputs.

Assuming receipt of the 2002 MM5 36 km and some of the 12 km model output during November 2004, this task will be completed in December 2004. A PowerPoint presentation on the summary evaluation and comparison of the CENRAP MM5 model performance with WRAP and VISTAS 2002 MM5 runs and QA/QC results will be ready by December 20, 2004. The CMAQ and CAMx 36 km meteorological inputs w ill be ready no later than December 31, 2004.

At this time it is unclear when CENRAP w ill provide the episodic 12km MM5 output. We anticipate that the Gatekeeper and processing into model-ready inputs will be accomplished within 3 weeks of receiving the 12 km MM5 out put. Table 2-4 summarizes the deliverables

under this task.

Table 2-4. Task 1-3: Develop Model- Ready Meteorological Inputs.

Item Description Due Date 1 Presentation (in electroni c form) of Meteorological Gatekeeper evaluation and MCIP/MM5CAMx processing

of 2002 36 km MM5 data 12/20/04

2 Model-ready 2002 36 km mete orological inputs for CMAQ

and CAMx 12/31/04

3 Model-ready 12km meteorol ogical inputs for CMAQ and CAMx and episodes in 2002 12/31/05

2.4.2.4 Task 1-4: Develop Base Case Model-Ready 2002 Emissions Inputs

The objective of this task is to develop 2002 Base Case mode l-ready hourly speciated gridded emissions inputs on the 36 km and 12 km grid for the CMAQ and CAMx models. The CENRAP emissions contractors will provide emissions data files for the CENRAP states necessary to develop a model-ready emissions inventory for the 2002 base cas e. Emissions for the other states, Mexico and Canada will be acquired from EPA and other sources. These data will beQuality Assurance Project Plan (Draft) Page 23 of 68 CENRAP Emissions and Air Quality Modeling Revision 3 ENVIRON International Corporation March 29, 2006

compiled and subjected to QA/QC by the Emissions Gatekeeper using the procedures described previously.

The SMOKE emissions model will be used to process the CENRAP emissions data. The existing WRAP and VISTAS SMOKE setups will be used as the starting point for the SMOKE emissions modeling and be augmented by emissions for CENRAP states and other information provided by CENRAP. There are two 2002 Base Case inventories th at need to be developed, an “Actual Base Case” to be used for model perfor mance evaluation and a “Typical Base Case” that is used for future year projections. These and other details (e.g., source da ta for fire emissions) will be worked out with CENRAP during the development of the Task 2 MP/WP. The provisional steps to be taken to generate the CENRAP CMAQ-r eady 2002 Base Case emission inputs will be the following; more details and refi nements will be provided to the Task 2 MP/WP after consultation with the CENRAP participants:

1. Yearly, seasonal, monthly or daily ASCII emissions inventor ies in IDA format for the area and point sources including fire sources.

a. Area sources will include non-road mobile sources, area sources, wind blown dust, and road dust.

b. Point sources will include stationary sources with large emissions, and fire

sources. 2. Yearly, seasonal, or monthly ASCII vehicle miles traveled (VMT) inventory for on road

mobile sources.

3. NetCDF files for gridded land use as i nput for BEIS3 and the emission factors.

4. Ancillary files which include:

a. Surrogate files for spatially allocating the area sources emissions,

b. Temporal and cross reference files for temporal allocation,

c. Speciation profiles and cross-refere nce files for chemical allocation.

5. Fire emissions: Will have prescribed burns and agricultural burns for CENTRAP state

from CENRAP. WRAP and VISTAS will have prescribed burns, agricultural burns and

wildfires for their states.

6. Wind Blown Fugitive Dust: Use data pr ovided by CENRAP, the new ENVIRON/UCR 2002 EI already prepared for WRAP or leave out.

7. Ammonia: Use data provided by CENR AP and the new EN VIRON/UCR 2002 EI already prepared for WRAP.

Emissions for the Entire 36 km Unified Grid Domain:

To process the emissions for CENRAP:

1. All the inventories provided by CENRAP w ill replace any default CENRAP emissions in

the current 2002 emissions inventor y that was prepared for WRAP.

2. Any new specific temporal profiles (if pr ovided by CENRAP) will be added to the current EPA temporal profiles and cross-referenc e files (or default to the values currently being used for WRAP).

3. The EPA spatial surrogate data will be used for area sources (as in WRAP and VISTAS inventories).Quality Assurance Project Plan (Draft) Page 24 of 68 CENRAP Emissions and Air Quality Modeling Revision 3 ENVIRON International Corporation March 29, 2006

4. The EPA Model speciation profile s and cross reference file, wh ich were distributed with SMOKE, will be used for chemical speciation.

5. For the biogenic emissions, the netCDF gridded land use inventory will be used.

6. All the emissions that are meteorology depe ndent will be processed using the MCIP2.3 files created using MM5 output to be provided by CENRAP.

Emissions Processing QA:

The following QA steps will be performed:

1. Use SMOKE reports to:

a. QA the inventory for total emissions per st ate and/or county fo r spatial allocation.

b. Check for irregularities in the temporal allocation.

c. Check for other irregularities, such as ve rtical allocation, inve ntory per SCC, etc.

2. Use RMC Post processing QA to create and review:

a. Spatial vertical daily total emissions,

b. Daily domain total emissions,

c. Diurnal domain total emissions, and

d. Domain total vertical distribution.

Emissions for the 12 km CENRAP Domain :

To process the emissions for 12 km grid cell the following steps will be taken:

1. Establish domain definition.

2. Create new 12 km surrogates by extracting the surrogates for the domain from the EPA 12 km surrogates using SMOKE or a program written by the RMC.

3. Create new gridded netCDF biogenic land us e inventory for 12 km cells (not yet available, we are working on a 1-km projection now of the landuse data).

4. Use the same temporal and speciation profiles and cross references as in the 36 km grid

cell.

5. Perform QA as in the 36 km grid cell domain.

There are extensive QA protocols in place for emissi ons modeling that were developed as part of the WRAP and VISTAS modeling efforts. These included both internal SMOKE QA procedures and post-SMOKE QA summaries. A variety of QA summary plots w ill be posted to the project webpage providing easy access to emissions QA results. In addition, the complete set of QA/QC results will be archived as well as made available to the CENRAP project participants through ftp transfer or CD.

Emissions modeling for the 2002 Base Case will be performed during the December 2004 through February 2005 time period. The deliverab les will be a technical memorandum suitable for inclusion as a chapter in the final report and PowerPoint presenta tion summarizing the 2002 emissions modeling and QA/QC results and th e 2002 CMAQ-ready emission inputs for the 36

km domain. Table 2-5 summarizes the deliver ables and schedule for the Task 1-4 emissions modeling.Quality Assurance Project Plan (Draft) Page 25 of 68 CENRAP Emissions and Air Quality Modeling Revision 3 ENVIRON International Corporation March 29, 2006

Table 2-5. Task 1-4: Develop Base Case Model-Ready 2002 Emission Inputs.

Item Description Due Date 1 Monthly Progress Reports 2 nd week of following month

2 Technical Memorandum on de velopment of 2002 Base Case emissions (Actual and Typical) 02/21/05

3 Presentation (electronic format) on development of

2002 Base Case emissions 02/21/05

4 Model-ready 2002 Actual Base A emissions completed 01/31/05 5 Model-ready 2002 Typical Base A emissions completed 02/28/05 6 Revised model-ready Actual Base Case emissions completed TBD

7 Revised model-ready Typi cal Base Case emissions completed TBD

2.4.2.5 Task 1-5: Perform 2002 Base Case Mode ling and Model Performance Evaluation

The objective of this task is to perform 2002 Base Case modeling using the CMAQ and CAMx models and to conduct a model performance evaluation. The first step in this task will be to set up a webpage for the pr oject to disseminate informati on and post documents and modeling

results. The ENVIRON/UCR Team has alread y set up a CENRAP modeling webpage for the initial modeling analysis work conducted previously at:

http://pah.cert.ucr.e du/aqm/cenrap/index.shtml

We will use the meteorological inputs developed in Task 1-3 and the emissions files developed in Task 1-4 as inputs to the CMAQ model, and perform an initial 2002 Actual Base Case

simulation and model evaluation on the 36 km grid. CAMx 2002 emi ssions and ICBC inputs will be prepared using the CMAQ-to-CAMx pr ocessors that will be used along with the meteorological inputs developed in Task 1-3 to perform a 2002 CAMx Base Case simulation. The CMAQ and CAMx model performance evaluati on and diagnostic sensit ivity tests will be conducted following the procedures in the Task 1-2 MP/WP, along with additional diagnostic tests that are identified during the course of the study. We w ill conduct 12 km sensitivity tests for several 2002 episodes and the compare model pe rformance with that using a 36 km grid. Our experience with 36/12 km modeling in the southeastern US for VISTAS is that although there can be large differences in model performance at a given time and location, at most times and locations and in general, the perf ormance attributes overa ll (both good and bad) ar e very similar.

Based on the model evaluation and diagnostic tests, an optimal model conf iguration(s) will be identified and, after approval from the CENRAP Project Manager, revi sed 2002 Actual Base Case simulation(s) and model performance evalua tion will be performed. We will also conduct sensitivity analyses and use available probing tools to c onduct sensitivity and source apportionment analyses following the procedures in the MP/WP.Quality Assurance Project Plan (Draft) Page 26 of 68 CENRAP Emissions and Air Quality Modeling Revision 3 ENVIRON International Corporation March 29, 2006

Model performance evaluation wi ll be completed using the UCR model performance evaluation (MPE) software, the CENRAP evaluation tool and ENVIRON’s performance tools for the AQS, IMPROVE/IMPROVE Protocol, CASTNet, STN, a nd NADP networks. Data from the St. Louis PM supersite will be analyzed individually taking advantage of the high time, size and species resolved measurements. Standard performance ev aluation plots will in clude time-series and scatter plots for individual and collective CE NRAP and nearby sites for each network, and over 20 different model performance me trics will be calculated includi ng several different formulas for estimating bias and error. A variety of su mmary plots will also be developed including stacked bar plots for individual sites and bugle and soccer plots su mmarizing performance at all sites in the CENRAP region. We will also examine performance in other subregions.

Specific steps to be take n under this task include:

• Preparation of CMAQ IC/BC and other inpu ts (e.g., photolysis rates) for 2002 and the CENRAP 36 km and 12 km grids.

• Development of CAMx emissions and IC/BC inputs using the CMAQ-to-CAMx processors and the CMAQ-ready emissions a nd IC/BC inputs, prep are remainder CAMx 2002 inputs.

• Performance of initial 2002 CMAQ and CAMx 36 km Actual Base Case simulations and 12 km runs for available time periods; conduct model performance evaluation and diagnostic sensitivity tests.

• Performance of diagnostic sensitivity test s, sensitivity analyses and limited source apportionment aimed at correcting potential flaws in the modeling system.

• Identification of optimal model configur ation(s) and make recommendations to CENRAP Project for revised 2002 Base Case simulation(s).

• After approval from CENRAP Project Manager, performa nce of a revised 2002 Actual and Typical Base Case simulation with appr oved model configuration(s) and conduct a model performance evaluation (MPE).

• Performance of sensitivity anal ysis using either brute force (i.e., emission reduction) or DDM sensitivities following pro cedures in Task 2 MP/WP.

• Performance of limited source apportionm ent modeling using TSSA (CMAQ) and/or PSAT (CAMx), as available.

• Performance of typical 2002 CM AQ and CAMx Base Case runs.

• Preparation of Monthly Progress Reports.

• Preparation of Draft Final a nd, after receiving comments fr om CENRAP, preparation of Final Reports.

Table 2-6 summarizes the deliverab les and schedule for Task 1-5.Quality Assurance Project Plan (Draft) Page 27 of 68 CENRAP Emissions and Air Quality Modeling Revision 3 ENVIRON International Corporation March 29, 2006

Table 2-6. Task 1-5: Perform 2002 Base Case and Model Performance Evaluation.

Item Description Due Date 1 Monthly Progress Reports 2 nd week of following month 2 Recommendations on model configuration 03/15/05 3 Draft Report on 2002 Base Case modeling and model performance evaluation 04/30/05

4 2002 Base Case model simulations completed 04/30/05 5 Second Draft Report on Revised 2002 Base Case modeling and model performance evaluation TBD

2.4.2.6 Task 1-6: Develop Future Base Ca se Model-Ready Emission Inputs

The Task 1-6 objective is to develop model-re ady 2018 Base Case emission inputs. CENRAP will provide 2018 point, area and non-road emissions data files and/or growth and control factors for CENRAP states necessary to develop a mode l-ready emissions inventory for the 2018 future

case. 2018 emissions for non-CENRAP states w ill be acquired from the other RPOs (e.g., WRAP and VISTAS). The 2018 mobile emissions will be developed using SMOKE to produce the model-ready emissions data files for 36km/12km modeling grids. The 2002 biogenic emissions prepared under Task 1-3 will be used in the 2018 modeling. It is important that the

2018 emission scenarios be constructed in a cons istent fashion to the 2002 Typical Base Case emissions in order to make reliable visibility proj ections. The steps to be taken to complete this

task include:

• Acquisition of 2018 point, area and non-road emissions or projection factors from

CENRAP.

• Processing of 2018 point, area and non-road emissions with SMOKE.

• Acquisition of fire emissi ons and processing by SMOKE.

• Review of 2018 on-road mobile source mo deling assumptions, and application of SMOKE to generate 2018 on-ro ad mobile source emissions.

• Merging of 2018 Base Case emissions to generate CMAQ-ready 2018 emissions for the 36 km and 12 km grids.

• Preparation of quality assurance and quality control (QA/QC) plots of the 2018 Base

Case emissions.

• Preparation of technical memorandum docum enting the development of the 2018 Base

Case emissions.

• Preparation of Monthly Progress Reports.

The types of QA/QC plots generated for the 2018 Ba se Case emissions scenario would be similar to those prepared for the 2002 Base Case discussed previously. In addition, we would generate difference plots of total emissions by major so urce category (e.g., on-road mobile, fires, point and other anthropogenic) between the 2018 Base Case and 2002 Typical Base Case emissions

scenarios. Animations of differences in hour ly emissions between the 2018 Base Case and 2002Quality Assurance Project Plan (Draft) Page 28 of 68 CENRAP Emissions and Air Quality Modeling Revision 3 ENVIRON International Corporation March 29, 2006

Typical Base Case emissions scenarios would also be examined to investigate potential errors in temporal allocation.

Table 2-7 summarizes the deliverables under Task 1-6. The 2018 model-ready Base Case

emissions and technical memorandum on their de velopment will be provided to CENRAP by April 30, 2005.

Table 2-7. Task 1-6: Develop Future Base Case Model-Ready Emissions Inputs.

Item Description Due Date 1 Monthly Progress Reports 2 nd week of following month

2 Technical Memorandum on Future-Year Base Case emissions development 04/30/05

3 Model-ready 2018 Base A emission inputs 04/30/05 4 Model-ready Revised 2018 Base Case emission inputs TBD

2.4.2.7 Task 1-7: Perform 2018 Modeling, Sensit ivity Analysis and Control Strategy

Evaluation

The objective of Task 1-7 is to perform 2018 se nsitivity and control strategy modeling to support the development of the visibility SIPs/TIPs. Under this task we will conduct 2018 sensitivity and control strategy modeling using the Task 3 meteor ological inputs and the Ta sk 6 2018 Base Case emissions inputs. Depending on the results of Tasks 1-1 through 1-5, either the CMAQ model or

the CAMx model or both will be used in th e 2018 sensitivity and control strategy analysis (decision to be made by CENRAP).

We will recommend model configuration(s), sensitiv ity tests, model diagnostic tests and source apportionment modeling to the CENRAP Project Ma nager. Unique feat ures/options of the

alternative models will be considered and employed if appropriate. A 2018 modeling approach will be developed with approval of the CENRAP Project Manager. Results will be compared with the annual Base Case simulation and pr ovide a means for corroborative analysis and diagnostic evaluation.

The exact scope of work for the 2018 modeling anal ysis cannot be completely defined at this time. It is expected that a combination of SMOKE emissi ons control strategy modeling, CMAQ and/or CAMx emissions sensitivity modeling a nd use of Probing Tools, such as Decoupled Direct Method (DDM) sensitivity; Process Analys is (PA) and PM Source Apportionment (PSAT and/or TSSA) will be used. At this time it is difficult to speculate which of these Probing Tools will be operational in the PM portions of CMAQ a nd/or CAMx models at the initiation of this Task in May 2005.

We will provide a Draft Report to the CENRAP Project Manager and Administrative Project Manager summarizing the sensitivity analysis a nd source apportionment analysis that can beQuality Assurance Project Plan (Draft) Page 29 of 68 CENRAP Emissions and Air Quality Modeling Revision 3 ENVIRON International Corporation March 29, 2006

used to help design effective emissions control strategies. A Final Report on the sensitivity/source apportionment analysis will be submitted to CENRAP within one week of receiving comments.

CENRAP will then provide a list of the control strategy evaluations to be conducted based on the results of the sensitivity and source apportionmen t analyses that will be modeled using SMOKE and CMAQ and/or alternative mode ls as directed by CENRAP. Th e control strategy results will be documented as they are performed with final documentation in the Task 1-8 report.

The Draft Report on 2018 sensitivity and source apportionment modeling will be submitted to CENRAP in April 2006, with the Final Report on the sensitivity/apportionment modeling being submitted a week after receiving comments from CE NRAP. Results of the 2018 control strategy simulations will be provided to CENRAP as th ey became available and incorporated into the Task 1-8 report. The Task 1-7 deliverables and their due dates ar e given in Table 2-8.

Table 2-8. Task 1-7: Perform 2018 Modeling, Sens itivity Analysis and Control Strategy

Evaluation.

Item Description Due Date 1 Monthly Progress Reports 2 nd week of following month 2 Draft sensitivity and source apportionment report 04/01/06 3 Final sensitivity and source appor tionment report Within 1 week of

comments 4 2018 model simulations completed 04/30/06

2.4.2.8 Task 1-8: Reports and Recommendations

The original intent of Task 1-8 was to document the work performed under Tasks 1-3 through 1- 7 in reports and develop portions of a Tec hnical Support Document (TSD) for the CENRAP states RHR SIPs/TIPs. However, because of the need to perform emission updates for CENRAP States and other RPOs, the development of the CENRAP RHR SIP/TIP TSD covering the modeling will now be performed in Phase II under Task 2-6.

Table 2-9. Task 1-8: Reports and Recommendations.

Item Description Due Date 1 Monthly Progress Reports 2 nd week of following month 2 Draft Technical Support Do cument (TSD) See Task 2-6 3 Final Technical Support Docu ment (TSD) See Task 2-6Quality Assurance Project Plan (Draft) Page 30 of 68 CENRAP Emissions and Air Quality Modeling Revision 3 ENVIRON International Corporation March 29, 2006

2.4.3 PHASE II MODELING TASKS

2.4.3.1 Task 2-1: Revise and Update the CE NRAP Modeling Quality Assurance Project Plan (QAPP)

The current CENRAP draft QAPP for Emissions and Air Quality Modeli ng (Revision 2 dated December 23, 2004) will be updated to include the work to be undertaken under Phase II of the modeling effort and any changes to the Phas e I work. A Draft Revision 3 QAPP will be

submitted to CENRAP and finalized within one w eek of receipt of CENRAP comments. Table

2-10 summarizes the Task 2-1 deliverables.

Table 2-10. Task 2-1: Revise and Update CENRAP Modeling QAPP

Item Description Due Date 1 Monthly Progress Reports 2 nd week of following month 2 Draft Updated Revision 3 QAPP March 31, 2006 3 Final Updated Revision 3 QAPP Within one week of receipt of CENRAP

comments

2.4.3.2 Task 2-2: Develop Model- Ready Meteorological Inputs

Since the development of the CMAQ and CAMx meteorological inputs using 36 km MM5 data for the annual 2002 period and 12 km MM5 data for several 2002 episodes under the Phase I Task 1-3, several changes have occurred that require the reproce ssing of the MM5 data:

• A new version of CMAQ (V4.5) has been rel eased along with a new version of the CMAQ meteorological processo r (MCIP3.0). In order to take advantage of all the features of the new version of CMAQ (e.g., the AE3 aerosol module with Sea Salt and the spatially varying minimum Kz), the MM5 data must be reprocessed using MCIP3.0.

• A new version of CAMx (V4.3) has been releas ed that includes treatment of solid phase precipitation not previously treated and a ne w MM5CAMx processor is needed to process the MM5 frozen cloud water and precipitation.

• The MM5 model has now been run for 2002 usi ng both a 36 km and 12 km resolution. At the February 6-8, 2006 CENRAP Workgroup meetings it was decided to perform most

of the model simulations at 36 km resoluti on, but process the 12 km MM5 data so that

annual 12 km runs could also be ma de to corroborate the 36 km runs. Based on these new events, the 2002 MM5 36/12 km annual data will be reprocessed using MCIP3.0 and the latest MM5CAMx to generate ne w meteorological inputs th at can be used to

run the latest versions of the CMAQ (V4.5) and CAMx (V4.3) mode ls. Also under this task we will evaluate the 12 km MM5 model and compare its performance with the 36 km MM5 results

that were evaluated under Task 1-3 in Phase I.

Table 2-11 summarizes the deliver ables and schedule for Tasks 2-2.Quality Assurance Project Plan (Draft) Page 31 of 68 CENRAP Emissions and Air Quality Modeling Revision 3 ENVIRON International Corporation March 29, 2006

Table 2-11. Task 2-2: Develop Mode l-Ready Meteorological Inputs

Item Description Due Date 1 Monthly Progress Reports 2 nd week of following month

2 PowerPoint Presentation on MM5 12 km Evaluation and Comparison with 36 km Results April 30, 2006

3 Model-ready 36 km and 12 km 2002 annual meteorological inputs for CMAQ and CAMx processed

with the latest MCIP3.0 and MM4CAMx processors. April 20, 2006

2.4.3.3 Task 2-3: Generate Model-Ready Emissions

Under this task we use the SMOKE emissions m odel to generate CMAQ-ready emissions for the

revised 2018 Base Case emissions scenario at 36 km and 2002. CAMx-ready emissions for 2018 Base Case would be generated using the 36 km CMAQ emissions results as was done for 2002. In addition, CAMx 12 km emissions would be gene rated using flexi-nesti ng. Table 2-12 lists the

deliverables and schedule for Tasks 2-3.

Table 2-12. Task 2-3: General Model-Ready Emissions.

Item Description Due Date 1 Monthly Progress Reports 2 nd week of following month 2 Revised 2018 36 km Base Case Model-Ready Emission Inputs for CMAQ and CAMx Within 6 weeks of receipt of 2018 growth and control factors (estimated March 31, 2006) 3 2018 12 km Emissions for CAMx using Flexi-Nesting April 15, 2006

2.4.3.4 Task 2-4: Perform 2018 Base Case Modeling

Under this task 2018 Base Case, Sensitivity and Source Apportionment modeling would be

conducted. There would be several Subtasks performance as part of this task:

• Subtask 2-4a: 2018 Base Case Modeling with CMAQ

• Subtask 2-4b: 2018 Base Case Modeling with CAMx

• Subtask 2-4c: Conduct up to 8 Sensitivity Runs with CMAQ

• Subtask 2-4d: Conduct up to 8 Sensitivity Runs with CAMx

• Subtask 2-4e: Conduct 2018 36 km CAMx PM Source Apportionment Technology (PSAT) runs for: 2-4e1 – SO4, NO3, NH4 and primary PM; and 4e2 -- SOA.

• Subtask 2-4f: Conduct 2018 12 km “fle xi-nesting” CMAQ and CAMx modeling

• Subtask 2-4g: Generate report on modeling results that can be included as part of the TSD (Task 6)Quality Assurance Project Plan (Draft) Page 32 of 68 CENRAP Emissions and Air Quality Modeling Revision 3 ENVIRON International Corporation March 29, 2006

Table 2-13 summarizes the deliver ables and schedule for Task 2-4.

Table 2-13. Task 2-4: Perform 2018 Base Case Modeling.

Item Description Due Date 1 Monthly Progress Reports 2 nd week of following month 2 2018 Base Case Modeling with CMAQ May 15, 2006 3 2018 Base Case Modeling with CAMx May 15, 2006 4 Conduct up to 8 Sensitivity Runs with CMAQ June 15, 2006 5 Conduct up to 8 Sensitivity Runs with CAMx June 15, 2006 6 2018 36 km PSAT Runs May 30, 2006 7 2018 12 km flexi-nesting runs using CMAQ/CAMx July 15, 2006 8 Draft Report on Modeling Results July 15, 2006

2.4.3.5 Task 2-5: Refine 2018 Base Case Mo deling and Conduct Control Strategy

Evaluations

Under this task ENVIRON/UCR would refine the 2018 emissions and air quality modeling. 2018 control strategy modeling will be conducte d using information provided by the CENRAP Implementation and Controls Strategies (ICS) Wo rkgroup. The exact control strategies to be evaluated are to be determined (TBD). Table 2- 14 summarizes the deliverables and schedule for

Task 2-5.

Table 2-14. Task 2-5: Refine 2018 base case modeli ng and conduct control strategy evaluations.

Item Description Due Date 1 Monthly Progress Reports 2 nd week of following month 2 Control strategy evaluations completed Within 6 weeks of receipt of control strategy definitions

from ICS

2.4.3.6 Task 2-6: Final Report for Inclus ion as CENRAP Technical Support Document

Under this task ENVIRON/UCR would document all of the mode ling results conducted in Phase I and II in a report that would be suitable fo r inclusion with the CENRAP Regional Haze SIPs/TIPs as the modeling Technical Support Docu ment (TSD). A draft final report (TSD)

would be submitted to CENRAP in MSWORD format. Based on comm ents received from CENRAP, the TSD would be updated and resubm itted. CENRAP and/or CENRAP States and Tribes may make further updates and modifications to the document prior to submission to EPA as part of each State’s SIP or Tribe’s TIP.Quality Assurance Project Plan (Draft) Page 33 of 68 CENRAP Emissions and Air Quality Modeling Revision 3 ENVIRON International Corporation March 29, 2006

Also under this task we would ar chive all model inputs and script s and selected model outputs on USB drives supplied by CENRAP and transfer the data to CENRAP.

Table 2-15. Task 2-6: Final report/T echnical Support document (TSD).

Item Description Due Date 1 Monthly Progress Reports 2 nd week of following month 2 Draft Report/TSD submitted to CENRAP July 15, 2006 3 Final Report/TSD Submitted to CENRAP Within 2 weeks of receipt of comments on draft report 4 Disk drives with model inputs a nd selected outputs June-July 2006

3.0 PROJECT MANAGEMENT

3.1 Project Organization

This project is being performed by the ENVIRON International Corporation and the University of California at Riverside (U CR), with input from the CENR AP Project Manager, CENRAP Administrative Project Mana ger, CENRAP Modeling Advi sor and CENRAP Modeling Workgroup and other CENRAP Wo rkgroups (e.g., ICS). Organizational commitment is an essential element for developing and implementing a successful research pr oject. Ralph Morris

of ENVIRON will be the CENRAP Emissions and Air Quality Modeling Project Manager (PM). The CENRAP Modeling Team has two Co-Principal Investigators that coordinate activities at each of the modeling centers, Ralph Morris of ENVIRON and Gail Tonnesen at UCR. The PM and two Co-PIs will be kept apprised of all project activities, from identifying the need to develop sound experimental and pr oject designs to delivering repor ts. Commitments to research and project activities, such as those described in this QAPP are made only after the activities are thoroughly reviewed and a pproved by the PM, Co-PIs and CENR AP Project Manager. Figure 3- 1 presents the organizational char t that shows the lines of respons ibility and information flow for activities under this project. Ta ble 3-1 lists the project responsib ilities for participants in the CENRAP Emissions and Air Quality Modeling st udy, with more details on their roles provided

next.Quality Assurance Project Plan (Draft) Page 34 of 68 CENRAP Emissions and Air Quality Modeling Revision 3 ENVIRON International Corporation March 29, 2006

Central Regional Air Planning Association (CENRAP)

(contracting agency)

CENRAP

Modeling Workgroup

Technical Project Manager

Lee Warden

Alternate Technical

Project Manager

Calvin Ku CENRAP

Executive Director

Annette Sharp

Technical Director

Jeff Peltola CENRAP

Modeling Advisor

T.W. Tesche

Alpine Geophysics, LLC

Other CENRAP

Contractors Contractor

ENVIRON
Project Manager and CoPrincipal Investigator

Ralph Morris

Staff Contractor

UC Riverside

Co-Principal Investigator

Gail Tonnesen

Staff

Figure 3-1. CENRAP Emissions and Air Quality M odeling Project Organizational Chart.Quality Assurance Project Plan (Draft) Page 35 of 68 CENRAP Emissions and Air Quality Modeling Revision 3 ENVIRON International Corporation March 29, 2006

Table 3-1. CENRAP 2002 Annual Emissions and Air Qual ity Modeling project participants and

contacts.

Person & Role Affiliation/Address Contact Information Annette Sharp (Executive Director) CENRAP 10005 S. Pennsylvania, Ste. C Oklahoma City, OK 73159 (405) 378-7377 asharp@censara.org

Jeff Peltola (Technical Director) CENRAP 10005 S. Pennsylvania, Ste. C Oklahoma City, OK 73159 (405) 378-7377 or (651) 293 1295 jpeltola@censara.org

Lee Warden (Technical Project Manager) Oklahoma DEQ

707 N. Robinson Oklahoma City, OK 73102 (405) 702-4201 Lee.Warden@deq.state.ok.us

Calvin Ku (Alternate Technical Project Manager) Missouri DNR
P.O. Box 176 Jefferson City, MO 65012 (573) 751-4817 calvin.ku@dnr.mo.gov

T.W. Tesche (CENRAP Modeling Advisor) Alpine Geophysics, LLC

3479 Reeves Drive Ft. Wright, KY 41017 (859) 341-7502 (Fax) (859) 341-7508 twt@iac.net Ralph Morris (Project Manager and Co-Principal Investigator) ENVIRON 101 Rowland Way Novato, CA 94945 (415) 899-0708 (Fax) (415) 899-0707 rmorris@environcorp.com

Gail Tonnesen (Co-Principal Investigator) UC Riverside

CE-CERT

1084 Columbia Avenue Riverside, CA 92507 (951) 781-5676 (Fax) (951) 781-5790 tonnesen@cert.ucr.edu

Key ENVIRON Participants Gerry Mansell (Emissions Modeling Coordinator) ENVIRON 101 Rowland Way Novato, CA 94945 (415) 899-0727 gmansell@environcorp.com

Bonyoung Koo ENVIRON (415) 899-0727 bkoo@environcorp.com

Edward Tai ENVIRON (415) 899-0725 etai@environcorp.com

Steven Lau ENVIRON (415) 899-0739 slau@environcorp.com Key UCR CE-CERT Participants Mohammed Omary (Chief Emissions Modeler) UC Riverside

CE-CERT

1084 Columbia Avenue Riverside, CA 92507 (951) 781-5652 omary@cert.ucr.edu

Zion Wang UC Riverside (951) 781-5655 zsw@cert.ucr.edu

Chao-Jung Chien UC Riverside (951) 781-5666 chien@cert.ucr.edu Glen Kaukola UC Riverside (951) 781-5630 glen@cert.ucr.edu CENRAP Workgroup Chairpersons (www.cenrap. org) Brandon Krogh (Monitoring) Minnesota Power (218) 723-3954 bkrogh@allete.com Ray Bishop Oklahoma Department of (405) 702-4218Quality Assurance Project Plan (Draft) Page 36 of 68 CENRAP Emissions and Air Quality Modeling Revision 3 ENVIRON International Corporation March 29, 2006

Person & Role Affiliation/Address Contact Information (Monitoring) Environmental Quality Ray.Bishop@deq.state.ok.us

Calvin Ku (Modeling) Missouri Department of Natural

Resources (573) 751-8406 Calvin.Ku@dnr.mo.gov

Lee Warden (Modeling) Oklahoma Department of Environmental Quality (405) 702-4201 Lee.Warden@deq.state.ok.us

Ron Hoofman (Emissions) Arkansas Department of Environmental Quality (501) 682-0357 hoofman@adeq.state.ar.us

Lisa Brenneman (Emissions) Eastern Shawnee Tribe of Oklahoma estoepa@hotmail.com

John Seltz (Implementation and Control Strategy) Minnesota Pollution Control Agency (651) 296-7801 John.Seltz@pca.state.mn.us

Mark McCorkle (Implementation and Control Strategy) Arkansas Department of Environmental Quality (501) 682-0736 mac@adeq.state.ar.us

Scott Weir,

Communications Kansas Department of Health and

the Environment (785) 291-3272 sweir@kdhe.state.ks.usQuality Assurance Project Plan (Draft) Page 37 of 68 CENRAP Emissions and Air Quality Modeling Revision 3 ENVIRON International Corporation March 29, 2006

3.1.1 ENVIRON/UCR Project Manager a nd Co-Principal Investigators

Mr. Ralph Morris of ENVIRON is the Project Manager (PM) and Co -Principal Investigator (CoPI) for the CENRAP Emissions and Air Quality Modeling Team. He provides overall direction to the project and establishes a policy relationship with the sponsor , ensuring that all issues of importance to the CENRAP Project Manager, Ex ecutive Director and Te chnical Director and Workgroups are addressed. The PM is respons ible for the overall c onduct of the project, experimental design, reportin g of the results, and interacting with the client, consultants, and project staff. The specific re sponsibilities of the PM include, but are not necessarily limited to, the following:

• Directs and coordinates the activities of th e project team and co mputer facilities to conduct the test program

• Ensures that this QAPP and the Modeling Prot ocol are followed during the course of the project

• Guides the overall approach fo r performing modeling evaluations

• Keeps current on project status and delivers progress reports

• Conducts initial modeling or analysis of expe riments to determine if inconsistencies or unexpected results suggest possible e xperimental or measurement problems

• Evaluates overall data quality, characterizat ion results, and overall system performance with regard to meeti ng project objectives

• Reviews and delivers modeling and assessment reports

• Interacts with external scientific reviewers, collaborators and other external groups in their area of expertise in the development of study priorities, reporting of results, and obtaining external input

• Oversees the project team in responding to a ny issues raised in assessment reports and initiates corrective actions as necessary

• Serves as ENVIRON’s primary point of contact for contract issues

• Establishes a project budget and monitors the effort to ensure that budget is not exceeded

• Assists in the performance of the modeling program in accordance with its contract and

the Work Plan

• Provides information to assist the CENRAP Project Manager, Ad ministrative Project Manager and Modeling Workgroup in achieving its goal s as stated in it s Work Plan and Long Range Plan

• Develops individual test protoc ols and reports as directed

• Analyzes modeling data and provides assessment reports

• Supports the CENRAP Project Manager and CE NRAP in responding to any issues raised in assessment reports

3.1.2 ENVIRON and UCR Co-Pri ncipal Investigators

The two Co-Principal Investig ators of Ralph Morris and Gail Tonnesen perform the following

functions:

• Direct and coordinate the day- to-day project activities of the project team and computerQuality Assurance Project Plan (Draft) Page 38 of 68 CENRAP Emissions and Air Quality Modeling Revision 3 ENVIRON International Corporation March 29, 2006

facilities to conduct the test program

• Ensure that this QAPP and Modeling Protoc ol are followed during the course of the project

• Manage the activities in each of the three modeling centers

• Directly supervise personnel working on this project

• Guide the approach for performing modeling ev aluations following th e direction of the Project Manager

• Keep current on project status and deliver information to Project Manager for progress

reports

• Conduct initial modeling or analysis of experi ments to determine if inconsistencies or unexpected results suggest possible e xperimental or measurement problems

• Evaluate overall data quality, characteriza tion results, and overall system performance with regard to meeti ng project objectives

• Review and deliver data and sections for integration into mode ling and assessment

reports

• With the Project Manager, interact with exte rnal scientific reviewers, collaborators and other external groups in their area of expertise in the development of study priorities, reporting of results, and obtaining external input

• Oversee the project team in each modeling ce nter responding to any issues raised in assessment reports and initiates corrective actio ns as necessary with the Project Manager

• Monitor the effort to ensure that budget is not exceeded

• Assist in the performance of the modeling program in accordance with its contract and

the Work Plan

• Develop individual test protoc ols and reports as directed

• Analyze modeling data and provide assessment reports

3.1.3 CENRAP Technical Director and Executive Director

The CENRAP Technical Director (Jeff Peltola) a nd Executive Director (A nnette Sharp) serve as the primary administrative contact between the Emissions and Air Quality Modeling Team and CENRAP and performs the following functions:

• Provides day-to-day oversight of CENRAP Emissions and Air Quality Modeling Team

activities

• Works with the CENRAP Project Manager and Modeling Team Project Manager and CoPrincipal Investigators, CENRAP Modeling Workgroup, States, Trib es oversight groups, collaborators, Stakeholders, etc. in assuring th at the interests and concerns of all of the CENRAP participants are approp riately represented as project priorities are developed or modified due to external input

• Assists in organizing and conducting meeti ngs, conference calls, and workshops where this and related projects are discussedQuality Assurance Project Plan (Draft) Page 39 of 68 CENRAP Emissions and Air Quality Modeling Revision 3 ENVIRON International Corporation March 29, 2006

3.1.4 CENRAP Project Manager

The CENRAP Project Manager (Lee Warden) for the Emissions and Air Quality Modeling Team works with the CENRAP Administrative Project Ma nager/Project Coordinato r in the day-to-day oversight and management of the modeling analysis:

• Provides day-to-day oversight of CENRAP Emissions and Air Quality Modeling Team

activities

• Works with the CENRAP Administrative Pr oject Manager and Modeling Team Project Manager and Co-Principal Invest igators to assure th at the study is being carried out in a technically correct fashion following the QAPP and Modeling Protocol

• Prepares and gives presentations to CENR AP groups on the activities of the Modeling

team as needed.

The CENRAP Alternate Project Manager (Calvin Ku) provides backup and seamless continuation of work should the prim ary Project Manager be unavailable.

3.1.5 CENRAP Modeling Workgroup

The CENRAP Modeling Workgroup is responsible for overseeing the re gional haze and fine particulate modeling that will be required for the CENRAP States and Tribes State Implementation Plans (SIPs) and Tribal Implem entation Plans (TIPs). This workgroup provides both emissions modeling and air quality mode ling technical support to CENRAP. Modeling efforts will include identification, evaluation, and application of air quality modeling tools (including emissions, mete orological and air quality models) to quantify the effects of emission management options upon air quality in Class I ar eas in the CENRAP region. Specific activities of the CENRAP Modeling Workgroup include:

• Oversees the activities of the CENRAP Emissions and Air Quality Modeling Team through the CENRAP Project Ma nager and Administrative Proj ect Manager, conference calls, and periodic in-person meetings and workshops

• Provides the CENRAP Project Manager, CENR AP Administrative Project Manager, and Modeling Team Project Manager and Co-Princ ipal Investigators input on the research plans and their ability to meet the needs of th e various stakeholders relevant to the overall objectives of the project

• Provides input as needed to assure that th e project has effective and appropriate peer

review

• Makes the Modeling Team Project Manager a nd Co-Principal Investigators aware of other projects that may be of relevance to this project

• Reviews the QAPP and conducts critical project reviews

3.2 Project Schedule and Execution

The schedule for each of the CENRAP Emissions and Air Quality Modeling Phase I and II Tasks are presented at the end of each Task Description in Section 2.4.Quality Assurance Project Plan (Draft) Page 40 of 68 CENRAP Emissions and Air Quality Modeling Revision 3 ENVIRON International Corporation March 29, 2006

3.3 Personnel Qualifications and Training

General education of all pr oject personnel lays the founda tion for successful project implementation. It is not intende d to provide detailed and specif ic knowledge of all components of the project, but it promotes an understandi ng of the nature of the overall project goals, ensuring that all personnel unders tand the part they are to play in the project. The members of this project team include resi dent experts in emissions, mete orological and air quality model development and operations.

All project personnel must have extensive experien ce in their particular disciplines. Each team

member must be familiar with the content of this QAPP and the CENRAP Modeling Protocol thus obtaining a project overvie w, including information on all functions of the modeling systems, from experimental design, objectiv es, and data validation and reporting. Where applicable, project personnel must be familiar w ith the SOPs applicable to their areas of responsibility. In addition, if ma jor revisions or enhancements are made to the QAPP and/or SOPs, all affected individuals must re view those revisions at that time.

3.4 Communications Plan

The CENRAP Emissions and Air Quality Modeli ng Team members, other CENRAP Contractors and CENRAP representatives are linked by e-mail correspondence, and also use this as a means to communicate and exchange data, either as e-mail attachments, we bsite or by networkaccessible files. A considerable amount of in formation is exchanged by e-mail within this project. The CENRAP Modeling Team mainta ins listservs to distribute information to

CENRAP.

The Modeling Team members and CENRAP Projec t Manager, Administrative Project Manager and other members of the Modeling Workgroup w ill hold periodic conferen ce calls and meetings to report results, discuss project status, and modify work pl ans as necessary. Unscheduled meetings or conference calls will also be held c oncerning specific issues as the needs arise. In addition, periodic project m eetings and conference calls will be held. In these meetings detailed technical information will be exchanged, project st atus will be discussed, and project direction

will be assessed.

Written progress reports on the CENRAP Emissions and Air Quality Modeling Team activities will be submitted to the CENRAP Project Manage r and Administrative Project Manager on a monthly basis. These reports will summarize project progress, results to date, problems encountered and necessary action items, a nd plans for the upcoming reporting period.

Key modeling results, quality assu rance reports, and re lated documents will be posted on the project web site.

http://pah.cert.ucr.e du/aqm/cenrap/index.shtmlQuality Assurance Project Plan (Draft) Page 41 of 68 CENRAP Emissions and Air Quality Modeling Revision 3 ENVIRON International Corporation March 29, 2006

3.5 Documentation and Records

After the project tasks describe d in Section 2.4 that require deliverables are completed, the ensuing documents will be poste d on the CENRAP Modeling proj ect website. In addition, during the project, the CENRAP participants will be provide d updates by e-mail or telephone.

Document control is the system that ensure s that the Modeling Team personnel engaging in project activities use only the latest revision s of the defined documents. The system includes retention of the document with original signed page(s) in a limited access storage area, a unique numbering system for all documents (typically id entified by revision number and/or date), and electronic storage of documents by da te so that the latest versions is clearly identifiable. Such documents are controlled documents, and can be re vised only by the personne l listed within each document or the project quality document. The following is a typical list of the controlled documents within the project folder:

1. The quality documents for the project such as the Quality Management Plan, Modeling Protocol and Quality Assurance Project Plan.

2. All applicable and referenced or attached Standard Operating Procedures and/or

Methods.

3. Project proposals, contracts, Work Plans, experimental designs, software documentation,

and/or similar documents.

4.0 MEASUREMENT AND DATA ACQUISITION

4.1 Computer Hardware/Systems Administration

All emissions and air quality modeling will be performed on computer equipment located at

either the ENVIRON or UCR modeling centers.

4.1.1 ENVIRON Modeling Center Hardware

The computing facilities at the ENVIRON Novato, CA office are built on current state-of-the-art hardware and software. The networked configur ation of personal computers, workstations and printers includes Linux and Window PCs, SGI, SUN and DEC Unix work stations and Linux Clusters all connected by a fast network with disk access to RAID systems. The ENVIRON computer center includes the very latest co mputing technology including both OMP (shared memory) and MPI (cluster) multi-processing capability. ENVIRON currently has three Linux

Clusters each with > 10 CPUs and each connected to RAID disk syst ems. All staff also has their own state-of-the-art PCs and has access to all workstations at all times, there are no problems with computer resource av ailability. ENVIRON’s high sp eed Linux and UNIX computing

environment includes workstations from three to p suppliers, Sun, Digital Equipment Corporation (DEC) and Silicon Graphics Incorp orated (SGI). ENVIRON also uses Linux PC workstations

with several different distributions of the Li nux OS (e.g., Red Hat, Debian, Mandrake) and these exceed the performance of fast UN IX workstations. Using workst ations from several suppliersQuality Assurance Project Plan (Draft) Page 42 of 68 CENRAP Emissions and Air Quality Modeling Revision 3 ENVIRON International Corporation March 29, 2006

allows us to develop and test model codes on mu ltiple computer platforms and means that we are experienced with most of the workstations used by our clients. The latest addition to the ENVIRON computing facilities is a 16 node Linux cluster usi ng the Athlon MP2200 chip set with gigabit Ethernet that is configured as two 8 node MPI multiprocessing platforms.

4.1.2 UCR Modeling Center Hardware

The UCR computer laboratory is designed to process large data se ts for air quali ty modeling. It includes over 30 high-performance, dual CPU Linux workstations configured as several small Linux clusters on a private network to facilitate parallel simulations. These systems include a 24 CPU Athlon 2000MP cluster, an 8 CPU Xeon 2.2 GHz cluster and an 8 CPU 64-bit Opteron 2GHz cluster. The data storage system include s over 23 TB of disk space configured as RAID5 disk systems. All computers and disk systems ar e networked using high speed Gigabit Ethernet for efficient simulation and analysis of large da tasets. To provide maximum data security the systems are located behind the UCR firewall and an additional firewall is used internally within the laboratory so that only project team memb ers have access to project computers and data.

Data are also routinely transferred from the UCR systems to other organizations using a variety of tape formats and portable hard drives. The data backup/archi ving system include 8mm tape drives and DLT and Super DLT auto loading cart ridge system capable of performing unattended archive/backups of over 1 TB (uncompressed). Key disk syst ems have hot-swappable hard drives with stand-by spare drives and redundant power supplie s. The compute clusters and disk systems are located in a locked, secure room with a dedicated climate c ontrol system and with backup air conditioning. UCR also uses the computer la boratory for air pollution modeling classes for graduate students and for profe ssional staff from State and Tr ibal air pollution agencies. The laboratory has a full time systems administrator to perform system backups, maintenance and updates and Dr. Tonnesen’s group includes a second full time systems administrator.

4.1.3 Backup Procedures

Different back-up procedures are ap plied to three different sets of computers that include (1) file servers; (2) user desktop Windows PCs; and (3) RAID5 disks storage syst ems. Several different File servers are used to host systems and user information, websites and ftp sites.

1. Each server receives a full Level 0 backup at least once every 14 days, and an incremental backup at least three times per week to an independent co mputer. In addition, incremental backups are peri odically made to tape.

2. Windows based PC’s are used to for editing project documents and reports. Each PC on the LAN receives a full Level 0 backup at least once every 14 days and incremental backups every three days.

3. Most of the project data are stored on RAID 5 disk systems. Because of the large volume of data (> 20 TBs) it cannot be routinely ba cked up. Moreover, most of the project data are output from model simulations, which can be regenerated more quickly by re-running the models than by restoring from tape. Th erefore, only critical model input data areQuality Assurance Project Plan (Draft) Page 43 of 68 CENRAP Emissions and Air Quality Modeling Revision 3 ENVIRON International Corporation March 29, 2006

backed-up. One 2 TB RAID5 disk system is re served for backup of critical project data. Backups are performed weekly. In addition, criti cal project input data is archived to IDE drives, firewire drives or DLT tape.

All incoming electronic mail receives virus sc anning using commercial software (Norton or McAffee Anti-Virus), which is updated routin ely. Windows PC receives automated, weekly

scans for viruses.

Three types of software are used in the projec t: (1) commercial software for word processing, project management, communications, and commer cial software compilers; (2) compilers and computer operating systems publicly availa ble through the GNU Public License (GPL) distribution channels; and (3) cu stom software used in comput er simulation modeling and data analysis. All commercial software used in th e CENRAP modeling project has been purchased

with licenses and is installed and tested as specified by the publisher. Commercial compilers include Portland Group compilers, and Intel and IBM FORTRAN compilers. All GPL software

is obtained from official distribution centers, such as Redhat, and are regularly maintained and updated with each official release from the code developers. Custom software is developed by UCR, EPA and other researcher s using commercial and GPL compilers for FORTRAN, C and

C++.

4.2 Sources for Data Used in Modeling

Most of the data used in the CENRAP Emissions and Air Quality Modeli ng will be provided by other CENRAP contractors or par ticipants. The data will be subj ected to QA/QC screening prior to delivery to the Modeling Team. In a ddition, the Modeling Team has formed data “Gatekeeper” functions to further screen the data prior to its use. Below the data used in the modeling and the function of the Gatekeeper role s is discussed, which are also described in

Section 2.3.2.1:

3⁄4 Air Quality Gatekeeper : The Air Quality Gatekeeper wi ll download air quality data from the VIEWS AIRS, and St. Louis Supersite websites and subject it to QA/QC. The data will be reformatted and processed for use in the modeling.

3⁄4 Meteorological Gatekeeper : The Meteorological Gatekeeper will evaluate the 36 km MM5 data provided by the Iowa Department of Natural Resources (IDNR), a CENRAP state, and 12 km MM5 data for 2002 episode s provided by other CENRAP participants, subjects it to QA/QC, and processes it for input to the CMAQ/CAMx air quality models.

3⁄4 Emissions Gatekeeper : The Emissions Gatekeeper will receive emissions data from the CENRAP Emissions Contractors (Pechan and STI) for CENRAP states and other sources for non-CENRAP states, subjects them to a comprehensive QA/QC, and will reject data that doesn’t pass the QA/QC a nd reformats the data for input into the SMOKE emissions

model.Quality Assurance Project Plan (Draft) Page 44 of 68 CENRAP Emissions and Air Quality Modeling Revision 3 ENVIRON International Corporation March 29, 2006

3⁄4 Data Management Gatekeeper : The Data Management Gatekeeper will maintain the project website, keep backups of data, respond to data requests and will update reports

and files on the website.

5.0 EMISSIONS MODELING

The project objective is to integrate mesoscale em issions and transport modeling efforts so that predictions of regional haze in Class I areas can be performed under different emissions and meteorological transport scenarios. Meeting this objective means that modeling outputs must be of known quality. This section addresses emissions modeling, Section 6.0 addresses meteorological modeling and Section 7 addresses air quality modeling as they apply to this project.

The CENRAP Modeling Team uses the Sparse Matrix Operator Kernel Emissions (SMOKE) emissions model to simulate the anthropogenic and biogenic gas and pa rticulate matter (PM) emissions needed for regional haze modeling. A deta iled quality assurance protocol for utilizing SMOKE has been prepared as part of the CENRAP Modeling Protocol (ENVIRON and UCR, 2004) and is summarized in this section.

The purpose of SMOKE is to conve rt the resolution of the raw emission inventory data to the resolution needed by an air quality model. Emissi on inventories are typically available with an annual total emissions value for each emissions source, or perhaps with an average-day emissions value. The air quality models, however , typically require emissions data on an hourly basis, for each model grid cell (and perhap s model layer), and for each model species. Consequently, emissions processing for this proj ect involve transformati on of emission inventory data by temporal allocation, chemical speciati on, spatial allocation, and layer assignment, to achieve the input requirements of the air quality model.

SMOKE formulates emissions m odeling in terms of sparse matrix operations. Figure 5-1 presents an example of how the matrix approach is used by the project team to organize the emissions processing steps for anthropogenic emi ssions, with the final step in creating the model-ready emissions being the merge step. This example does not include all processing steps, which can be different for each source categ ory in SMOKE, but does include the major processing steps listed above, ex cept for the layer as signment. Specifically, the inventory emissions are arranged as a vector of emi ssions, with associated vectors that include

characteristics about the sources such as it s state and county (SCC) . SMOKE also creates matrices that will apply the gridding, speciation, a nd temporal factors to the vector of emissions. In many cases, these matrices are independent fro m one another, and can therefore be generated in parallel. The processing approach ends with the merge step, which combines the inventory emissions vector (now an hourly inventory file) with the cont rol, speciation, and gridding matrices to create model-ready emissions.Quality Assurance Project Plan (Draft) Page 45 of 68 CENRAP Emissions and Air Quality Modeling Revision 3 ENVIRON International Corporation March 29, 2006

Merge Import Inventory Temporal

Allocation

Speciation

Gridding Inventory

Vectors

Controls Hourly

Emissions

Speciation

Matrix

Gridding

Matrix

Control

Matrix Model-ready

Emissions

Program Shows input or output File Merge Import Inventory Temporal

Allocation

Speciation

Gridding Inventory

Vectors

Controls Hourly

Emissions

Speciation

Matrix

Gridding

Matrix

Control

Matrix Model-ready

Emissions

Program Shows input or output File

Figure 5-1. Flow Diagram of Major SMOKE Processing Steps

5.1 Quality Assurance Components of Emissions Modeling

The quality assurance (QA) screening steps for the emissions modeling process has been divided into the four major classifications defined in the sections below.

5.1.1 Modeling QA

Modeling QA involves performing data quality checks, assuring simulation accuracy, and recognizing and identifying problems as they ha ppen; it is the proces s of looking for glaring faults in the model input and output data (I/O ) and determining whether the input data are producing the desired results. Scruti ny of the I/O using standard st atistical analyses can reveal problems in the data and/or the model setup. Usi ng a standard approach for analyzing emissions model I/O establishes reference poi nts to use when scrutinizing the data. Seeking these indicators of correct model performance allows project personnel to determine the accuracy of the

simulations and whether faults in the data or model configuration exist.

5.1.2 System QA

System QA addresses model installation and conf iguration issues, data accounting, and ensures that the modeling systems are producing results that are reasonable and reproducible. The first step in this process is to properly benchmark the model and assuring that the installation is complete. Confirmation of configuration settin gs, compile options, and other system-related parameters must then occur and be documented pr ior to producing any m odel results. Archiving the model installation at set “freeze points” in th e project is also required in order to keep accurate records of the modeling installation and run scripts. A key feature of System QA is facilitating the reproduction of mode l results in the futu re and the ability to revert back to a previous configuration or insta llation after the model has been re vised or updated. In addition to thorough documentation, version control software is required for archiving model executables, run and configuration scripts, and important data files. Combining documentation of the modeling procedures with archives of the model installation and data files will ensure that theQuality Assurance Project Plan (Draft) Page 46 of 68 CENRAP Emissions and Air Quality Modeling Revision 3 ENVIRON International Corporation March 29, 2006

model installation and configurat ion are correct and that past simulations are sufficiently documented and archived to allow their reproduction.

5.1.3 Gatekeeping and Outside Review

Gatekeeping and outside review is the process of ensuring that th e data entering and exiting the SMOKE modeling process meet a predetermined qua lity level. A gatekeeper screens model data before they pass from one major step of the modeling process to the next. In emissions QA, gatekeeping is applied to the em issions inventory and SMOKE input files on the front end of the modeling process, and to the SMOKE output files at the back end. A gate keeper (or gatekeeping team) is responsible for performing a series of reasonableness checks on both the input and output data streams. Outside reviewers are emi ssions experts who are not part of the CENRAP Modeling Team. They periodically review the en tire process—the emissions data, the modeling, and the QA steps taken—using their judgment as e xperts to decide what to review and how to

review it.

5.1.4 Documentation

Documentation, a critical component that is comm on to all of the other three QA classifications, provides the record of the QA process. Establis hing a detailed set of requirements for documenting every step in the QA process will ensure not only that the documentation is created as expected, but that the processes recorded by the documentation are co mpleted correctly. In

addition to records or lists of completed QA steps, documentation refers to summaries and interpretations of emissions in ventory reports and analyses. C overing the entire realm of the modeling process, QA documentation includes reco rds of model configuration, details about data files, simulation records, and final report generation.

5.2 Implementation of the QA System

5.2.1 The Emissions QA Team

The level of effort required to implement the CENRAP Emissions QA framework requires a team consisting of: a data gatekeeper(s), a production modeler(s), a QA manager, outside reviewers, and a project manager (See Sectio n 2.3.2.5 and Figure 2-1 for data flow and QA overview). Each team member contributes a di fferent critical perspective on the data and modeling.

• The Gatekeeper (or gatekeeping team ) is responsible for reviewing the SMOKE I/O data

streams for correctness. Before new datasets are used in SMOKE modeling, or new SMOKE output emissions datasets are us ed in air quality modeling, th ey must be reviewed by the gatekeeper. For all SMOKE input and output files, the gatekeeper ensures that the data are complete, are formatted correctly, and pass r easonableness checks. Checking completeness entails examining the files for the necessary data elements, spatial coverage, and temporal

extent. Data formats will be confirmed usi ng the SMOKE manual to check ASCII files and using PAVE to check binary netCDF files, su ch as the meteorological inputs. ReasonablenessQuality Assurance Project Plan (Draft) Page 47 of 68 CENRAP Emissions and Air Quality Modeling Revision 3 ENVIRON International Corporation March 29, 2006

checks consist of looking for glar ing errors in the file conten ts and ensuring that the data make sense in the context of how they will be used and relative to similar or reference datasets. Issues that arise during the gatekeep ing process are reported to the Project Manager

for resolution.

• The Production Modeler is responsible for receiving input data, maintaining the model run scripts, running the model per the work plan, producing default QA reports, delivering model output data, and assisting w ith compiling QA reports into summaries for documentation purposes. A Lead Modeler oversees the entire modeling process, performs the majority of the SMOKE modeling, and receives and ar chives input and output data. Secondary Modelers organize the SMOKE QA reports into emissi ons summaries for data QA and reporting, and generate custom QA summaries and reports for troubleshooting any problems encountered during the modeling process.

• The QA Manager performs and documents all of the checks required for determining model accuracy and revealing errors. Th e QA Manager also ensures that the software is configured correctly and that the data and model are being archived consistently and correctly. Overseeing the production modele rs, the QA Manager verifies that SMOKE is being applied correctly and that all QA summaries are consistent with the relevant input data. Leading the documentation efforts, the QA Manager ensures that all the necessary QA summaries are generated and certified and that they are compiled into th e project report.

• The Project Manager is ultimately responsible for the qu ality of the final products of the modeling process. Providing technical assistan ce to the production m odelers and clarifying any uncertainties about model input, configur ation, and operation for the QA Manager, the Project Manager addresses any questions in the modeling process. Working with the QA Manager, the Project Manager approves the results of all QA pro cedures, and thoroughly scrutinizes the QA summaries for problems to de termine whether the data are ready to be sent to the gate keepers and outside reviewers for final review be fore delivery to the air quality modelers. For the CENRAP project the Project Manager is the liaison between the emissions modeling team and the CENRAP Modeling Workgroup and in this role communicates any issues raised during the emissions QA process.

Figure 5-2 presents the QA fr amework developed by the CENRAP Modeling Team for SMOKE modeling. Identifying the specific participants in the CENRAP Modeling Team for performing

all of the tasks in the framework is the first step of the QA process for each new emissions modeling scenario. Two Production M odelers are shown in the diagram, with the Lead Modeler performing the SMOKE simulations and receiving the input data and the Secondary Modeler compiling the output of the SMOKE QA programs into the QA products for evaluating the quality of the simulations. Gatekeepers are po sitioned in the SMOKE input and output data streams to screen the data before they are used in either SMOKE or CMAQ modeling, respectively. Reviewers are solicited from out side the emissions modeling team on a volunteer basis to conduct periodic reviews/audits of the data and modeling process.Quality Assurance Project Plan (Draft) Page 48 of 68CENRAP Emissions and Air Quality ModelingRevision 3ENVIRON International CorporationMarch 29, 2006CENRAP ModelingWorkgroupCENRAPModeling TeamCENRAPFigure 5-2.Diagram of CENRAP Modeling Team Approach to SMOKE ModelingQuality Assurance Project Plan (Draft) Page 49 of 68 ASIP Emissions and Air Quality Modeling Revision 3 ENVIRON International Corporation March 29, 2006

6.0 METEOROLOGICAL MODELING

The EPA Models-3 Community Multiscale Air Quality (CMAQ) modeling system and the Comprehensive Air-quality Model with extens ions (CAMx) are the two regional ozone and particulate matter (PM) air quality models being used in the CENRAP projec t. Meteorological inputs for CMAQ and CAMx have been genera ted using output from the fifth generation Mesoscale Model (MM5). The 2002 MM5 36 km database for the continental US was developed by the Iowa Department of Na tural Resources (IDNR) (Johnson, 2004). Whereas, other CENRAP participants are developing th e 12 km MM5 database. The MM5 model was initial applied for the entire y ear of 2002 on a continental scale dom ain with 36 km grid spacing. Subsequent MM5 model runs were applied to a regional-scale domain with 12 km grid spacing covering the central United States for 2002. Th e CMAQ and CAMx models require inputs of three-dimensional gridded wind, temperature, humidity, cloud/precipitation, and boundary layer parameters. The MM5 meteorological model was developed and is maintained by the Pennsylvania State University and National Cent er for Atmospheric Research (PSU/NCAR).

The procedures used for applying MM5 for CENR AP are based on an ex tensive evaluation of MM5 and a series of sensitivity tests conducted by IDNR and the Lake Michigan Air Directors Consortium (LADCO) that was consequently u pdated based on the MM5 sensitivity modeling conducted as part of VISTAS ( www.baronams . Com/projects/VISTAS). A description of CENRAP 36 km MM5 modeling approach in cluding the modeling domain, MM5 physical configuration, and a model application a pproach can be found in Johnson (2004).

MM5 has proven useful for air qua lity applications and has been us ed extensively in past local, state, regional, and national modeling efforts. MM5 has undergone extens ive peer-review, with all of its components continually undergoing development and scrutiny by the modeling community. MM5 is the most widely used public-domain prognostic model. In-depth descriptions of MM5 can be found in Dudhia (1993) and Grell et al. (1994), and at the following

web site:

http://www.mmm.ucar.edu/mm5

.

The evaluation of the MM5 meteorological m odeling will be performed primarily by the meteorological modeler. For the CENRAP 2002 36 km MM5 modeling preliminary evaluation

of the MM5 model can be found at:

http://www.ladco.org/tech/photo/present/mm5v363_eval.pdf http://www.ladco.org/tech/photo/ present/rainfall_eval.pdf

In addition, the CENRAP Emissions and Air Quality Modeling Team has a Meteorological Gatekeeper role that is describe d in Section 2.3.2.3 that will eval uate the MM5 fields to provide an independent verification step an d assure that the data have been transferred correctly to the Modeling Team. The Modeling team Meteorological Gatekeeper reports will be posted on the project website at:Quality Assurance Project Plan (Draft) Page 50 of 68 ASIP Emissions and Air Quality Modeling Revision 3 ENVIRON International Corporation March 29, 2006

http://pah.cert.ucr.edu/aqm/cenrap/mm5.shtml

7.0 CENRAP 2002/2018 AIR QUALITY MODELING

For the 2002 annual modeling on the 36 km gri d, the CENRAP Emissions and Air Quality Modeling Team will apply and evaluation EPA’s Models-3 Community Multiscale Air Quality (CMAQ) modeling system and the Comprehensive Ai r-quality Model with ex tensions (CAMx).

7.1 CMAQ Overview

For more than a decade, EPA has been deve loping the Models-3 Community Multiscale Air Quality (CMAQ) modeling system with the ov erarching aim of producing a ‘One-Atmosphere’ air quality modeling system capable of addressi ng ozone, particulate matte r (PM), visibility and acid deposition within a common platform (Denni s, et al., 1996; Byun et al., 1998a; Byun and Ching, 1999, Pleim et al., 2003). The original ju stification for the Models-3 development emerged from the challenges posed by the 1990 Cl ean Air Act Amendments and EPA’s desire to develop an advanced modeling framework for ‘ho listic’ environmental modeling utilizing stateof-science representations of atmospheric processes in a high performance computing environment (Ching, et al., 1998). EPA completed the initial stage of development with Models3 and released the Community Multi-Scale Air Qu ality model (CMAQ) in mid-1999 as the initial operating science model under the Models-3 frame work (Byun et al., 1998b). The most recent rendition is CMAQ version 4.4, publicly released in October 2004, is the version that will be

used in the CENRAP Emissions and Air Quality Modeling Study.

CMAQ consists of a core Chemical Transport Model (CTM) and several pre-processors including the Meteorological-Chemistry Inte rface Processor (MCIP), initial and boundary conditions processors (ICON and BCON) and a phot olysis rates processor (JPROC). EPA is continuing to improve and develop new modules for the CMAQ model and typically provides a new release each year. In the past EPA has also provides patches for CMAQ as errors are discovered and corrected. More recently EP A has funded the Community Modeling and Analysis Systems (CMAS) cente r to support the coordination, upda te and distribution of the Models-3 system.

A number of features in CMAQ’s theoretical fo rmulation and technical implementation make the model well-suited for annual PM modeling. In CM AQ, the modal approach has been adapted to dynamically represent the PM size distribution using three log-normal modes (2 fine and 1 coarse). Transfer of mass between the aerosol a nd gas phases is assumed to be in equilibrium and all secondary aerosols (sulfates, nitrates and or ganics) are assumed to be in the fine modes. The thermodynamics of inorganic aerosol co mposition are treated using the ISORROPIA module. Aerosol composition is coupled to mass transfer between the aerosol and gas phases. For aqueous phase chemistry, the RADM model is currently employed. This scheme includes

oxidation of SO 2 to sulfate by ozone, hydrogen peroxide, oxygen catalyzed by metals and radicals. The impact of clouds on the PM size distribution is treated empirically. For wet deposition processes, CMAQ uses the RADM/RPM approach. Particle dry deposition isQuality Assurance Project Plan (Draft) Page 51 of 68 ASIP Emissions and Air Quality Modeling Revision 3 ENVIRON International Corporation March 29, 2006

included as well. CMAQ contains three options for treating secondary organic aerosol (SOA), the latest being the Secondary Organic Aero sol Model (SORGAM) that was updated in August

2003 to be a reversible semi-volatile scheme whereby VOCs can be converted to condensable gases that can then form SOA, and then evap orate back into condensable gases depending on atmospheric conditions.

A description of the features implemented in the version of CMAQ ver 4.4 (released October 2004) used in the initial CENR AO 2002 modeling is available fr om the CMAS Center website (www.cmascenter.org). Many of thes e features are mentioned above; others pertain to details in the model’s chemistry, transport, computer implementation, and model operation. In October 2005, a new version of CMAQ was released (V 4.5) that included se veral updates and was subsequently adopted by CENRAP.

7.2 CMAQ Configuration for CENRAP Modeling

Based on preliminary modeling performed by CENRAP (Pun, Chen and Seigneur, 2004; Tonnesen and Morris, 2004), BRAVO (Pitchford et al., 2004), VISTAS (Morris et al, 2004a) and WRAP (Tonnesen et al., 2003) we have identifi ed and justified a se t of initial recommended science options for the CENRAP CMAQ modeling. In this section we briefly identify the main science options recommended for annual PM mode ling with CMAQ, more details are provided in the Modeling Protocol (ENVIRON and UCR, 2004). The model will be set up and exercised

on the same 36 km Inter-RPO Continental US mo deling domain that is being used by WRAP and VISTAS. This domain is larger than the 36 km domain used in the preliminary CENRAP modeling (Pun, Chen and Seigneur, 2004). For the 12 km episodic modeling, the CMAQ modeling domain will be determined after receipt of the 12 km MM5 data. For the 12 km CMAQ modeling, one-way grid nesting will be us ed whereby the results of the 36 km simulation are used to provide hourly BCs to the 12 km simulation. A total of 19 vertical layers will be implemented, extending up to a region top of 100 mb (approximately 15 km AGL).

The latest versions of CMAQ (Version 4.4 and 4.5) will be used in the CENRAP modeling. The PPM advection solver will be used along with the spatially varying (Smagorinsky) horizontal diffusion approach and K-theory for vertical di ffusion. MM5 meteorologi cal output based on the Pleim-Xiu Land-Surface Model (LSM) and the ACM planetary boundary layer (PBL) scheme will be used and the latest CMAQ Meteorol ogical-Chemistry Interface Processor (latest MCIP2.3) will process the MM5 data using th e “pass through” option. The CB4 gas-phase, RADM aqueous-phase, and AERO3/ISORROPIA aer osol chemistry schemes are recommended for use in the CMAQ 2002 modeling. Treatment of reversible secondary organic aerosols will be simulated by the SORGAM implementation in CMAQ.

7.2.1 Updates to the CMAQ Secondary Organic Aerosol (SOA) Module

Initial simulations of the CMAQ V4.4 for the 20 02 annual period revealed that Organic Carbon (OC) was underestimated in the central and ea stern U.S. by approximate ly 80% to 100% during the summer. A review of the CMAQ model formulation and model inputs found that one potential reason the model was underestimating OC was because there are several processesQuality Assurance Project Plan (Draft) Page 52 of 68 ASIP Emissions and Air Quality Modeling Revision 3 ENVIRON International Corporation March 29, 2006

associated with SOA formation from biogenic VOCs believed important for SOA formation. These processes are not treated in the current CMAQ model. Thus, the CMAQ SOA module was enhanced to include several missing processes. The formulation and resulting model performance are discussed in detail in a manuscr ipt that has been accepted for publication in Atmospheric Environment (Morris, et al., 2006). The SO A module enhancement were first added to CMAQ V4.3 and then transferred to CM AQ V4.5 when it became available in October

2005.

7.2.1.1 SOAmods Formulation

The formulation of the standard CMAQ SOA m odule is described in Binkowski and Roselle (2003). SOA can be formed from aromatic VOCs and biogenic terpenes. The biogenic SOA precursors were modeled with the Biogenic Emi ssions Information System – Version 3 (BEIS3) model (Pierce et al., 20 02). BEIS3 generates three biogeni c VOC species: isoprene (ISOP), monoterpenes (TERP) and other biogenic VOC (OVOC). For this study, the Carbon Bond IV photochemical mechanism was used (Gery et al ., 1989) that represents VOC compounds based

on their carbon bond structure. The BEIS3 ISOP , TERP and OVOC species are speciated into the CB4 species for photochemical modeling in CMAQ and CAMx as follows (molar speciation):

• ISOP = ISOP (isoprene is an explicit species)

• ALD2 = 1.5 x TERP

• OLE = 0.5 x TERP

• PAR = 6.0 x TERP

• NR = 0.5 x OVOC

• OLE = 0.5 x OVOC

• PAR = 8.5 x OVOC

• TERPB = TERP

Here, ALD2, OLE, PAR and NR are the CB4 ch emical mechanism representations of the biogenic VOC emissions as high molecular we ight aldehydes, olefinic carbon bond, paraffin

carbon bond and non-reactive functional groups. In CMAQ, the TERPB spec ies is specified in the emissions inputs, along with its CB4 representation of AL D2, OLE and PAR, but does not participate in the photochemical mechanism and is only used in the SOA formation module. The TERPB species forms a SGTOT species based on oxidation parameters extracted from the photochemical module. SGTOT consists of the combined gaseous condensable gas (CG) plus particle SOA that are assumed to be in equili brium. CMAQ transports the SGTOT species and splits it to a CG gaseous and particle SOA for output.

The CMAQ TERB SOA formation rate is based on a fit to smog chamber da ta collected at the California Institute of Technology for severa l biogenic monoterpene species (Binkowski and Roselle, 2003). A review of recent literature of biogenic SOA measurements identified several processes that may be important to biogenic S OA formation that are not treated by the BEIS3 biogenic emissions and the CMAQ SOA module:Quality Assurance Project Plan (Draft) Page 53 of 68 ASIP Emissions and Air Quality Modeling Revision 3 ENVIRON International Corporation March 29, 2006

Polymerization : Recent measurements indicate that some SOA species may polymerize, resulting in species that are no longer volatile and ca nnot evaporate back to a CG. In this case, the equilibrium assumption between the CG and SOA will understate the amount of particle SOA present in the atmosphere (Kalberer et al., 2004; Jang et al., 2002). Sesquiterpenes : Sesquiterpenes are not accounted for in the BEIS3/CMAQ SOA modeling system (Guenther et al ., 2000; Vizuete et al., 2004). Isoprene : More recent evidence suggests that isoprene can also form particle SOA compounds that are not accounted for in CMAQ (Claeys et al., 2004; Matsunaga et al., 2003; 2005). Acid Catalyzation : Recent literature al so suggests that some SOA formation may have acid catalyzed reactions (Claeys et al., 2004; Jang et al., 2005). Heterogeneous Reactions : Recent evidence suggests th at some SOA formation may occur during heterogeneous aqueous-phase chemical reactions (Yu et al., 2005).

A prototype module was added to CMAQ that acc ounted for the first three processes listed above. The last two processes were not includ ed in this work because there are not enough quantitative experimental data ye t to establish a parameterization. Modules were added to the CMAQ SOA module under the following constraints:

• The existing CMAQ SOA module for m onoterpenes would remain unchanged;

• The same CMAQ model inputs would be used; and

• The basic CMAQ model formulation would re main unchanged, modules would be added to account for polymerization and SOA from sesquiterpenes and isoprene.

Figure 7-1 displays how the prototype repres entation of new processes to represent SOA polymerization and SOA formation from sesquiterp enes and isoprene were added to the CMAQ SOA module using the existing CMAQ structure a nd inputs. The new components of the SOA

module are indicated in bold italic, whereas the existing CM AQ SOA components (Binkowski and Roselle, 2002) use a regular font . There are several parameters that must be defined in the

new elements of the enhanced SOA module: em ission factors (EF), canopy escape efficiencies for gases (EEG) and aerosols (EEA) and SOA yiel ds (Y). Based on an analysis of recent measurements, primarily from a recent biogenic emissions field study in Duke Forest, North Carolina (Stroud et al., 2005; Matsunaga et al., 2005), a range of values for the factors in Figure 7-1 were developed as shown in Table 7-1. For the initial pr ototype of the enhanced SOA module, we selected the mid-point of the range values for the factors from the measurements (Table 7-1). No attempt was made to optimize the parameters in Table 7-1 for OC/TCM model performance.

The emission factors, EF1 and EF2, relate the monoterpene emissions estimated by BEIS3 to emissions of monoterpenes, EF1 (e.g., α -pinene), and sesquiterpenes (E F2). Table 2 displays the range of EF1 and EF2 factors based on recent fi eld study data (Stroud et al., 2005). Using the midpoint of the range results in emission factor s of 0.7 for EF1 and 0.4 for EF2. EF1 is assigned

a value of 0.7 based on field obs ervations that indicate that th e BEIS3 terpene emission factors are likely overestimated due to a tendency of earlier measurements approaches to artificially

increase the emissions due to disturbance when l eaves were enclosed in the measurement system.Quality Assurance Project Plan (Draft) Page 54 of 68 ASIP Emissions and Air Quality Modeling Revision 3 ENVIRON International Corporation March 29, 2006

As an initial approach for including sesquiterp ene emissions, we have assigned EF2 a value of 0.4 based on the ratio of the observed sesquiterp ene emission from the Duke Forest field study (Stroud et al, 2005) to the BEIS3 monoterpene emi ssion estimate. The net result is that BEIS3 TERP emissions are increased by 10% and split 64% as monoterpenes and 36% as sesquiterpenes. The CG yields from the sesquite rpenes are assumed to partly condense into a non-volatile SOA particle that is modeled in CMAQ using the new secondary organic carbon species (SOC2) species and only some of the gas and aerosol species associated with sesquiterpenes are assumed to escape from the canopy using the mid-range of the Escape Efficiencies (EE) estimated by St roud et al. (2005). The fracti on of BEIS3 TERP emissions that are assumed to be monoterpenes (i.e., 64% of the emissions) are treated with the standard CMAQ two-product SOA module (Binkowski and Roselle, 2003) assuming equilibrium between the CG and SOA with the SOA output in the standard AORGB species (Binkowski and Roselle, 2003). The isoprene SOA formation pathway forms a CG using the mid-point yi eld rate based on the range of recent measurements (Stroud et al., 2005) and a CG/SOA partitioning rate based on the mid-point of measurements from Matsunaga et al. (2003, 2005) (Table 7-1). The isoprene SOA

is assumed to be volatile and is modeled as a new secondary organic carbon species in CMAQ SOAmods (SOC3). Finally, all SOA species, w ith the exception of the already non-volatile SOC1 (polymerized SOA) and SOC2 (sesquite rpene) species, are as sumed to partially polymerize into non-volatile partic les that are stored in the SO C1 species. The polymerization

rate is based on the results of Kalberer et al (2004) who found that 50% of the SOA polymerized

in 20 hours.

Table 7-1. Parameters use in enhanced SOA module (s ee Figure 7-1). Parameter Mid-Point Range

EF1 0.7 0.4 ~ 1.0

EF2 0.4 0.2 ~ 0.6

EEG1 0.325 0.2 ~ 0.45

EEA1 0.2 0.05 ~ 0.35

Y2 0.875 0.75 ~ 1.0

Y1 0.11 0.06 ~ 0.16

P1 0.45 0.15 ~ 0.75 EF1 = emission factor of monoterpenes to the TERP emissions estimated by BEIS3

EF2 = emission factor of se squiterpenes relative to the TERP emissions estimated by BEIS3 EEG1 = escape efficiency of gas phase precursor of sesquiterpenes from canopy EEA1 = escape efficiency of SOA from sesquiterpenes from canopy Y1 = SOA yield of oxidated isoprenes Y2 = SOA yield of sesquiterpenesQuality Assurance Project Plan (Draft) Page 55 of 68 ASIP Emissions and Air Quality Modeling Revision 3 ENVIRON International Corporation March 29, 2006

7.2.1.2 Quality Assurance of SOAmods

Several levels of Quality Assurance and Qualit y Control of the enhanced SOAmods module in the CMAQ model were conducted as follows.

QA/QC of SOAmods Coding : The SOAmods implemen tation was conducted at ENVIRON. Staff at the University of Ca lifornia at Riverside performed independent QA/QC of the SOAmods code implementati on and independent te sting and evaluation.

QA of SOAmods Formulation : The new processes being added to the CMAQ SOA

module was discussed with researchers at EPA’s Office of Research and Development (ORD). Although they have not completed all the laboratory tests, the inclusion of SOA from sesquiterpene and isoprene have been observed and are supported.

Peer Review of SOAmods : The formulation of the SOAmods enhancement to the CMAQ SOA module was documented and comment s were received by several parties. The results were also written up and submitted to Atmospheric Environment where it was subjected to peer review and will be published (Morris et al., 2006).

Model Performance Evaluation of SOAmods : The final level of QA of the SOAmods was comparisons of CMAQ V4.4 model perfo rmance with and without including the SOAmods enhancement. Table 7-2 displays fractional bias error for Organic Carbon (OC) for regions corresponding to VISTAS , MRPO, MANE-VU and CENRAP states using the standard CMAQ Version 4.4 (V4.4) and then CMAQ V4.4 with the SOAmods

enhancement. Whereas the standard CM AQ V4.4 underestimates OC across IMPROVE sites of from –76% (MRPO) to –102% (VIS TAS), with the SOAmods enhancement the

fractional biases centere d on zero and ranges from –14% to +8%. Similar results are seen

for OC fractional bias across the more ur ban STN sites where the CMAQ V4.4 exhibits an underestimation bias of –67% to –105%, when using SOAmods the under-prediction

bias is –27% to –44%. Note that the continued underestimation of OC across the urban STN sites is likely due to missing primary OC emissions and uncertainties in the STN

OC measurements.

Table 7-2. Comparison of fractional bias performance metric fo r Organic Carbon (OC) using the standard CMAQ Version 4.4 (V4.4) and CMAQ V4.4 with the SOAmods enhancement.

IMPROVE OC STN OC July 2002

Fractional Bias V4.4 SOAmods V4.4 SOAmods

Southeastern U.S. -102% -2% -105% -32%

Midwestern U.S. -76% +12% -67% -24%

Northeast U.S. -82% -14% -95% -44%

Central U.S. -98% +8% -81% -27%Quality Assurance Project Plan (Draft)Page 56 of 68ASIP Emissions and Air Quality ModelingRevision 3ENVIRON International Corporation March 29, 2006Figure 7-1.Schematic describing the addition ofnew SOA processes (bold italic) withinthe existing CMAQ SOA module (regularfont) to treat polymerization and SOA from sesquiterpenes and isoprene.



## Biogenic emissionsTERPISOPISPDY1P1PAROLEALD2TERPRXNA_TRP1G_TRP1A_TRP2G_TRP2ISPRXNSGTOT_ISPG_ISPA_ISPEF2 * ( EEG1 * Y2 + EEA1 )AORGBASOC2ASOC3*Y3*Y4OOO: Oxidation reaction with OH, O3, and NO3ISPRXN: The amount of reacted ISPD with oxidantsTERPRXN: The amount of reacted TERP with oxidantsDotted box: Not implemented in the initial testBold italic: New processesASOC1PolymerizationAll SOAs except SOC1 & SOC2FPOLYEF1



## Biogenic emissionsTERPISOPOVOCPAROLENRISPDY1P1PAROLEALD2SGTOT_TRP1TERPRXNSGTOT_TRP2ISPRXNSGTOT_ISPG_ISPA_ISPEF2 * ( EEG1 * Y2 + EEA1 )ASOC2ASOC3**OOOO: Oxidation reaction with OH, O3, and NO3ISPRXN: The amount of reacted ISPD with oxidantsTERPRXN: The amount of reacted TERP with oxidantsDotted box: Not implemented in the initial testBold italic: New processesASOC1PolymerizationAll SOAs except SOC1 & SOC2FPOLYEF1Quality Assurance Project Plan (Draft) Page 57 of 68 CENRAP Emissions and Air Quality Modeling Revision 3 ENVIRON International Corporation March 29, 2006

7.3 CAMx Overview

The Comprehensive Model with Extensions (CAM x) modeling system is a publicly available (www.camx.com) three-dimensional multi-scale photochemical/aerosol grid modeling system that has been developed and maintained by E NVIRON International Corporation. CAMx was developed with all new code during the late 1990s using modern and modul ar coding practices. This has made the model an ideal platform for the extension to treat a variety of air quality issues including ozone, particulate matter (PM), visibility, acid deposition, and air toxics. The flexible CAMx framework has also made it a convenient and robust host model for the implementation of a variety of mass balance and sensitivity analysis techniques including Process Analysis (IRR and IPR), Decoupled Direct Method (DDM), and the Ozone and PM Source Apportionment Technology (OSAT and PSAT). Designed originally to address multiscale ozone issues from the urban- to regional-scale, CAMx has been widely used in recen t years by a variety regulatory agencies for 1-hr and 8-hr ozone SIP modeling st udies. Key attributes of the CAMx model for simulating gas-phase chemistry include the following:

• Two-way grid nesting that supports multi-levels of fully interactive grid nesting (e.g., 36/12/4/1.33 km).

• CB4 or SAPRC99 Chemical Mechanisms.

• Two chemical solvers, the CAMx Chemical Mechanism Compiler (CMC) Fast Solver or the highly accurate Implicit Explicit Hybrid (IEH) solver.

• Multiple numerical algorithms for horizontal transport including the Piecewise Parabolic Method (PPM), Bott, and Smolarkiewicz advection solvers.

• Subgrid-scale Plume-in-Grid (PiG) algorithm to treat the near-source plume dynamics and chemistry from large NO

x point source plumes.

• Ability to interface with a variety of mete orological models including the MM5 and RAMS prognostic hydrostatic meteorolog ical models and the CALMET diagnostic meteorological model (others also compatible).

• The Ozone Source Apportionment Technology (OSAT) ozone apportionment technique

that identifies the ozone c ontribution due to geographic source regions and source categories (e.g., mobile, point, biogenic, etc.).

• The Decoupled Direct Method (DDM) sensitiv ity method is implemented for emissions

and IC/BC to obtain first-or der sensitivity coefficients for all gas-phase species.

• Treatment of particulate matter (PM) us ing an empirical aerosol thermodynamics algorithm.Quality Assurance Project Plan (Draft) Page 58 of 68 CENRAP Emissions and Air Quality Modeling Revision 3 ENVIRON International Corporation March 29, 2006

Culminating extensive model development effort s at ENVIRON and other participating groups, the CAMx (ver 4.10s) code was released in th e autumn of 2004 as a truly “One-Atmosphere’ model that rigorously integrates the gas-phase ozone chemistry with the simulation of primary and secondary fine and course particulate aerosols. This ex tension of CAMx to treat PM

involved the addition of several science modules to represent important physical processes for aerosols. Noteworthy among these are:

• Two separate treatments of particulate matter (PM), Mechanism 4 (M4) “oneatmosphere” treatment uses two size sections and science modules comparable to CMAQ (e.g., RADM aqueous-phase chemistry and ISORROPIA equilibrium) and a multi-section “full-science” approach using aerosol modules developed at Carnegie Mellon University (CMU).

• Size distribution is represented using the Multi-component Aerosol Dynamics Model (MADM), which uses a sectional approach to represent the aerosol particle size distribution (Pilinis et al., 2000). MADM treat s the effects of condensation/evaporation, coagulation and nucleation upon th e particle size distribution.

• Inorganic aerosol thermodynami cs can be represented usin g ISORROPIA (Nenes et al, 1998; 1999) equilibrium approach within MADM, or a fully dynamic or hybrid approach

can also be used.

• Secondary organic aerosol thermodynamics are represented using the semi-volatile scheme of Strader and co-workers (1999).

• Aqueous-phase chemical reactions are mode led either using the RADM module (like CMAQ) or the Variable Size-Resolution M odel (VRSM) of Fahey and Pandis (2001), which automatically determine whether wate r droplets can be represented by a single ‘bulk’ droplet-size mode or wh ether it is necessary to use fi ne and coarse droplet-size

modes to account for the different pH effects on sulfate formation.

CAMx (ver 4.10s) provides two key options to us ers interested in simulating PM. For CPUefficient annual PM modeling applications, CAMx may be run using Mechanism 4 (M4) with only two size sections (fine a nd coarse) and the efficient RADM bulk aqueous-phase module (as used in CMAQ). Alternatively, more rigorous aero sol simulations (perhaps for shorter episodes) may be addressed using the vers ion that treats N-size sections (N is typically 10) and the rigorous, but computationally-ext ensive CMU multi-section aqueous -phase chemistry module.

Several updates have been made to CAMx si nce Version 4.10a was released. The current version is Version 4.3 that includes updates to treat frozen precipita tion over Version 4.2.

Version 4.3 of CAMx will be us ed in the CENRAP modeling.

7.4 CAMx Configuration for CENRAP Modeling

CAMx (ver 4.3) will be applied using many sim ilar science options and input data sets to CMAQ. However, in some instances, the CMAQ and CAMx model development teams choseQuality Assurance Project Plan (Draft) Page 59 of 68 CENRAP Emissions and Air Quality Modeling Revision 3 ENVIRON International Corporation March 29, 2006

different options for characteri zing physical and chem ical processes, or for implementing the governing equations on modern parallel computers. In these cases, we will utilize the science configurations embodied in the current release of CAMx.

The latest version of CAMx (ver 4.3 newer) wi ll be employed and the model will be set up and exercised on the same 36/12 km grid as CMAQ. However, CAMx will be run using two-way grid nesting. The base configur ation of CAMx will us e 19 vertical layers to a 100 mb region (~15 km AGL) that exactly match those used by CMAQ. The PPM advection solver will be used along with the spa tially varying (Smagorins ky) horizontal diffusion approach. Vertical diffusion in CAMx will be modeled by K-theor y. The MM5 simulation using the Pleim-Xiu Land-Surface Model (LSM) and the ACM Planetar y Boundary Layer (PBL) scheme will be used in the CAMx base configuration using the MM 5CAMx processor that is similar to the CMAQ MCIP2.3 “pass through” option of the MM5 data invoked. CAMx will be exercised with the CB4 gas-phase, RADM aqueous-phase, and CMU/IS ORROPIA aerosol chemistry schemes. The SOAP secondary organic aerosol scheme will be used for the base configuration in CAMx.

Note that it may be desirable to exercise CAMx using its “full-science” configuration for selected periods to investigate sc ientific issues that may be of interest that cannot be simulated by CMAQ, such as:

• The full sectional approach could be used to determine whether allowing secondary PM to grow into the coarse mode affects the model estimates;

• The model could be exercised with chemical active Sea Salt emissions; this could be important for fine particulate and visibility at key coastal sites in the CENRAP domain, especially when looking at clean days or natural background; and

• The full sectional aqueous-phase chemistr y module may be important for sulfate

formation.

7.5 Advantages of Operating Multiple Models

The use of both CMAQ and CAMx in the CENR AP 2002 annual modeli ng is a powerful and comprehensive diagnostic and quality assuranc e (QA) check of the modeling. There are numerous uncertainties in air quality models and the completely independent formulation of CMAQ and CAMx allow an independent QA check of one model against the other that will not be available if only one model was applied.

EPA’s guidance on model selection for PM 2.5 SIPs and Regional Haze “reasonable progress demonstrations” do not identify a preferred photochemical grid modeling system, recognizing that at present there is “no single model which has been extensively te sted and shown to be clearly superior or easier to use than seve ral alternatives” (EPA, 2001, pg. 169). The agency

recommends that models used for PM 2.5 SIPS or RH reasonable pr ogress requirements should meet the requirements for alternative mode ls. The CMAQ, CMAQ-AIM, CMAQ-MADRID and CAMx modeling systems all meet these requirements.Quality Assurance Project Plan (Draft) Page 60 of 68 CENRAP Emissions and Air Quality Modeling Revision 3 ENVIRON International Corporation March 29, 2006

We believe that there is potenti ally significant value in includi ng two or more regional modeling systems. Our testing of the CMAQ and CAMx model in some preliminary CENRAP model evaluation analysis (Tonnesen and Morris, 2004) f ound that their performance was generally similar for most species, with one model perfor ming slightly better for some species and vice versa. Similar findings were obtained by VISTAS (Morris et al., 2004a). There are numerous advantages in applying both the CMAQ an d CAMx models in the CENRAP 2002 annual modeling:

• Diagnosis: To serve as an efficient diagnostic t ool addressing model performance issues that may arise in the establishment of the CMAQ and CAMx annual 2002 base cases. CAMx’s suite of diagnostic probing tools plus its flexi-nesting al gorithms make it an attractive tool for assisting in the diagnosis of model perf ormance should this unexpected situation arise. CMAQ and CAMx both posse ss Process Analysis (PA) that can be a powerful diagnostic tool.

• Model Evaluation Corroboration: To provide corroboration of the base case model performance evaluation exercises and help identify any compensatory errors in the MM5/SMOKE/CMAQ or SMOKE/MM5/CAMx modeling systems.

• Emissions Control Response Corroboration: To provide corroboration of the response of the CMAQ or CAMx modeling system to generic and specific future year emissions changes on modeled gas-phase and particul ate aerosol concentrations and resultant regional haze impacts.

• Quantification of Model Uncertainty: To provide one estimate of the range of uncertainty that attends statements of CM AQ and/or CAMx model performance in the annual and episodic base case simula tions, and in the estimate of PM 2.5 and visibility

reductions associated with future emissions change scenarios.

• Alternative Science: CMAQ and CAMx contain alternative science algorithms that may elucidate model performance issues in one model or the other.

• Consistency with Other RPOs: The Midwest RPO (MRPO) may end up using CAMx for their regional haze modeling, whereas th e VISTAS and WRAP RPOs are currently using CMAQ as their primary model. As sources in the MRPO, VISTAS and WRAP likely influence visibility at Class I areas in the CENRAP regi on, having results from both models will be useful for reconciling any differences.

• Backup Contingency: To provide a ‘backstop’ model in the event that unforeseen

difficulties with one of the models make it ne cessary to switch to an alternative ‘OneAtmosphere’ model at some point during the CENRAP modeling effort.

The benefits of employing a pair of complimentar y state-of-science air qua lity models are thus quite significant. Es pecially considering that the same MM5 output (through MCIP and MM5CAMx) and SMOKE output and IC/BC file s (through CMAQ-to-CAMx emissions andQuality Assurance Project Plan (Draft) Page 61 of 68 CENRAP Emissions and Air Quality Modeling Revision 3 ENVIRON International Corporation March 29, 2006

IC/BC converters) can be used to operate CA MQ and CAMx without performing any additional meteorological or emissions modeling.

8.0 ASSESSMENTS AND OVERSIGHT

8.1 Assessment Responsibilities

The primary point of contact for CENRAP Modeling project assessment is that of the Modeling Team Project Manager (PM). This PM is av ailable to the CENRAP Project Manager and Administrative Project Mana ger, CENRAP Modeling Workgroup, external reviewers, and internal staff by direct contact through e-mail and telephone. Thes e links provide timely reviews of the project experimental de sign, implementation, and interpretation of the experimental

results.

The assessments of overall project quality ar e provided from a number of different sources. Internal reviews of selected project compone nts are periodically performed by the Project Manager and Co-Principal Investigators. The resu lts of this and other routine (e.g., QC checks) and special reviews of project data qualit y are documented in the monthly reports.

The project team is committed to achieving and ma intaining the highest level of quality possible throughout the performance of this program. The modeling information generated will be both technically sound, and, where appropriate, defensib le from a regulatory perspective. The former is an obvious requirement but is no t, in and of itself, sufficient to defend the data against an adversarial inquiry. The latter wi ll address, through documentation, the level of quality achieved. The quality of the project data will be mainta ined not only through the development and use of data quality objectives (DQOs), which place numerical limits on the QC indicators, but also through the use of subjective scie nce quality objectives. Science quality objectives are used to provide evaluations of the quality of the resear ch project and goals of the study. Evaluations of all research activities by internal and extern al peer review will assure that the methodology, experimental processes, conclusions and recommendations provided by this project are scientifically sound.

8.2 Assessment Types and Usage

Assessments of the quality of the products ge nerated on this project will be made by:

• Conducting internal performance reviews of the critical com ponents of the experimental setup and data processing systems. Where applicable, adherence to SOPs will be

evaluated. The results of these reviews will contain any suggested corrective actions, and be appended to the reports ge nerated in this project.

• Independent peer reviews of thesis material s, reports, and papers resulting from this project.Quality Assurance Project Plan (Draft) Page 62 of 68 CENRAP Emissions and Air Quality Modeling Revision 3 ENVIRON International Corporation March 29, 2006

The CENRAP Modeling Workgroup provides external review of all reports and plays an active role in the development of experimental matrices and to review researchprogress and plans for future project tasks.

8.3 Assessment Criteria

The project assessment criteria address the extent to which th e modeling runs and experiments provide the quality of data needed to satisfy the objectives of this project. A major objective of this project consists of providi ng the data and information n eeded for evaluating and improving models for predicting the effects of emissions on air quality. Therefore, the evaluation process includes assessments of model uncertainties, the ex tent to which the proposed actions or system improvements can reduce these uncertainties, and es timates of the certainty of this work in providing the data of th e type and quality needed. Criteria fo r assessing data ut ility and quality will include the following:

• Utility of the type of measurements for model evaluation. For example, are model predictions of the measurements sensitive to the uncertainties in the mechanism that are being evaluated? Are the available resources be ing applied to the highe st priority types of

measurements?

• Degree of characterization of experimental c onditions for modeling. For data to be useful for model evaluation, experiment al conditions must be suffic iently well characterized, so

that the data can be used for model eval uation without characterization uncertainties dominating the results.

• Accuracy, precision, and sensitivity of the me asurement data. The measurements in the concentration region of intere st should be sufficiently accu rate and precise to provide a meaningful test of model predictions.

• Procedures used to assure data quality, iden tify data not meeting qua lity objectives, and to minimize errors and other data quality problems.

• Degree to which the modeling appropriately in corporates the characterization results in the inputs, and the analysis of the modeli ng results appropriately take into account

characterization and measurement uncertainties and biases.

• Degree to which the experimental pro cedures, measurement methods, and data processing and analyses, and m odeling methods are documented.

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