west virginia department of environmental protection

Appendix C.2

VISTAS Modeling

Quality Assurance Project Plan

Promoting a healthy environment.

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Quality Assurance Project Plan (Draft) 

For 

Visibility Improvements for States and Tribal 

Associations for the Southeastern States (VISTAS) 

Emissions and Air Quality Modeling 

Revision 0 

November 17, 2004 

Prepared for: 

Ms. Patricia Brewer 

Technical Coordinator 

Western Governors’ Association 

Project Manager and Co-Principal Investigator: 

Mr. Ralph Morris 

ENVIRON International Corporation 

101 Rowland Way, Site 220 

Novato, CA 94945 

Contractors: 

Co-Principal Investigator: 

Dr. Tom Tesche 

Alpine Geophysics, LLC 

3479 Reeves Drive 

Ft. Wright, KY 41017 

Co-Principal Investigator: 

Dr. Gail Tonnesen 

College of Engineering 

Center for Environmental Research and Technology 

University of California at Riverside 

Riverside, CA 92507 

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Approvals 

Title: Quality Assurance Project Plan for Visibility Improvements for States and Tribal 

Associations for the Southeastern States (VISTAS) Emissions and Air Quality Modeling, 

November 17, 2004. 

Ms. Patricia Brewer Date: 

Technical Coordinator 

Visibility Improvements for States and Tribal Associations for the Southeastern States

(Name here) Date: 

Project Officer 

U.S. Environmental Protection Agency 

Mr. Ralph Morris Date: 

Project Manager and Co-Principal Investigator 

ENVIRON International Corporation 

Dr. Tom Tesche Date: 

Co-Principal Investigator 

Alpine Geophysics, LLC 

Dr. Gail Tonnesen Date: 

Co-Principal Investigator 

University of California at Riverside 

EVIRON International Corporation 

101 Rowland Way, Suite 220 

Novato, California 94945

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CONTENTS 

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

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

2.0 PROJECT DESCRIPTION ................................................................................................... 2 

2.1 Background............................................................................................................................... 2 

2.2 VISTAS Two-Phased Approach............................................................................................... 3 

2.2.1 VISTAS Phase I............................................................................................................. 3 

2.2.2 VISTAS Phase II............................................................................................................ 4 

2.2.2.1 Data Gatekeepers ................................................................................................... 5 

2.2.2.2 Emissions QA/QC................................................................................................... 6 

2.2.2.3 Meteorology QA/QC .............................................................................................. 8 

2.2.2.4 Air Qualtiy Modeling QA/QC ................................................................................ 8 

2.2.2.5 Overview of Data Flow and Quality Assurance Process........................................ 9 

2.3 VISTAS Phase I and II Modeling Protocols........................................................................... 14 

2.4 VISTAS Phase I Activities ..................................................................................................... 14 

2.4.1 Phase I Task 1: Project Management........................................................................... 14 

2.4.2 Phase I Task 2: Develop Model Configuration Evaluation Plan ................................. 15 

2.4.3 Phase I Task 3: Acquisition and Development of Modeling Data Bases .................... 15 

2.4.4 Phase I Task 4: Develop Optimal VISTAS Modeling Configuration ......................... 17 

2.4.5 Phase I Task 6: Phase II Modeling Protocol................................................................ 18 

2.4.6 Phase I Task 7: Website Development ........................................................................ 19 

2.5 VISTAS Phase II Activities.................................................................................................... 19 

2.5.1 Phase II Task 1: Project Management ......................................................................... 19 

2.5.2 Phase II Task 2: Develop IC/BCs for 2002 Annual Run ............................................. 21 

2.5.3 Phase II Task 3: 12002 Data Preparation and Model Inputs ....................................... 22 

2.5.3.1 Subtask 3a: Air Quality Data Gatekeeper............................................................. 22 

2.5.3.2 Subtask 3b: MM5 Meteorological Model Gatekeeper.......................................... 22 

2.5.3.3 Subtask 3c: Emissions Gatekeeper and Emissions Development 

 for Non-VISTAS States, Canada, and Mexico ..................................................... 22 

2.5.3.4 Subtask 3d: Emissinos Modeling.......................................................................... 23 

2.5.3.5 Subtask 3e: Future-Year Emissions Modeling for 

 Three VISTAS Phase I Episodes .......................................................................... 25 

2.5.3.6 Subtask 3f: Interim Future-Year Emissions Modeling using 2002 Meteorology. 25 

2.5.3.7 Phase II Task 3 Deliverables................................................................................. 25 

2.5.4 Phase II Task 4: 2002 Annual CMAQ Modeling ........................................................ 26 

2.5.4.1 Subtask 4a: Initial Base Case and Model Performance Evaluation...................... 26 

2.5.4.2 Subtask 4b: Revised Base Case Simulation.......................................................... 27 

2.5.4.3 Subtask 4c: Typical Year Emissions Simulation.................................................. 27 

2.5.4.4 Subtask 4d: Future-Year Modeling for Two Scenarios ........................................ 28 

2.5.4.5 Subtask 4e: Interim Future-Year using 2002 Database ........................................ 28 

2.5.4.6 Summary of Phase II Task 4 Deliverables............................................................ 28 

2.5.5 Phase II Task 5: Episodic Modleing ............................................................................ 29 

2.5.6 Phase II Task 6: Data Management ............................................................................. 29 

2.5.6.1 Subtask 6a: VISTAS Modeling Website .............................................................. 29 

2.5.6.2 Subtask 6b: Data Transfer, Storage and Retrieval................................................ 29 

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2.5.6.3 Phase II Task 6 Data Management Deliverables .................................................. 30 

2.5.7 Phase II Task 7: Emission Reduction Sensitivity Simulations using 

 CB4 and SAPRC Chemistry and 2 Phase I Episodes .................................................. 30 

2.5.8 Phase II Task 10: Journal Paper on VISTAS Phase I Modeling.................................. 31 

2.5.9 Phase II Task 13: Analysis and Processing of 2002 GEOS-CHEM Data ................... 31 

3.0 PROJECT MANAGEMENT............................................................................................... 32 

3.1 Project Organization ............................................................................................................... 32 

3.1.1 ENVIRON Project manager and Co-Principal Investigator ........................................ 35 

3.1.2 ENVIRON, Alpine and UCR Co-Principal Investigators............................................ 35 

3.1.3 VISTAS Contracting Officer ....................................................................................... 36 

3.1.4 VISTAS Technical Contact ........................................................................................ 36 

3.1.5 VISTAS Technical Analysis Workgroup (TAWG)..................................................... 37 

3.2 Project Schedule and Execution.............................................................................................. 37 

3.3 Personnel Qualifications and Training.................................................................................... 37 

3.4 Communications Plan ............................................................................................................. 38 

3.5 Documentation and Records................................................................................................... 39 

4.0 MEASUREMENT AND DATA ACQUISITION .............................................................. 39 

4.1 Computer Hardware/Systems Administration ........................................................................ 39 

4.1.1 ENVIRON Modeling Center Hardware....................................................................... 39 

4.1.2 Alpine Geophysics Modeling Center Hardware .......................................................... 40 

4.1.3 UCR Modeling Center Hardware ................................................................................ 40 

4.1.4 Backup Procedures....................................................................................................... 41 

4.2 Sources for Data Used in Modeling........................................................................................ 42

5.0 EMISSIONS MODELING................................................................................................... 42 

5.1. Quality Assurance Components of Emissions Modeling ...................................................... 44 

5.1.1 Modeling QA ............................................................................................................... 44 

5.1.2 System QA ................................................................................................................... 44 

5.1.3 Gatekeeping and Outside Review................................................................................ 44 

5.1.4 Documentation............................................................................................................. 45 

5.2 Implementation of the QA System ......................................................................................... 45 

5.2.1 The Emissions QA Team ............................................................................................. 45 

6.0 METEOROLOGICAL MODELING ................................................................................. 48 

7.0 CMAQ MODELING SYSTEM........................................................................................... 48 

7.1 CMAQ Overview.................................................................................................................... 49 

7.2 CMAQ Configuration for Phase II Modeling......................................................................... 50 

7.3 Alternative Models.................................................................................................................. 50 

7.3.1 CAMx Overview.......................................................................................................... 52

7.3.2 CAMx Configuration for Phase II Modeling............................................................... 54 

8.0 ASSESSMENTS AND OVERSIGHT................................................................................. 55 

8.1 Assessment Responsibilities ................................................................................................... 55 

8.2 Assessment Types and Usage ................................................................................................. 55 

8.3 Assessment Criteria ................................................................................................................ 56 

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9.0 REFERENCES...................................................................................................................... 56 

Figures 

Figure 2-1a. Data flow and quality assurance steps in the VISTAS 

 Emissions and Air Quality Modeling ....................................................................12 

Figure 2-1b. Data flow and quality assurance steps in the VISTAS 

 Emissions and Air Quality Modeling ....................................................................13 

Figure 3-1. VISTAS Emissions and Air Quality Modeling Project Organizational Chart ......33 

Figure 5-1. Flow Diagram of Major SMOKE Processing Steps ..............................................43 

Figure 5-2. Diagram of VISTAS Modeling Team Approach to SMOKE Modeling ...............47 

Tables 

Table 2-1. Model performance goals used in Phase I to help interpret modeling results .......11 

Table 2-2. Phase I Task 1 Project Management task deliverables and due dates ...................15 

Table 2-3. Phase I Task 2 Modeling Plan task deliverables and due dates.............................15 

Table 2-4. Phase I Task 3 Phase I Acquisition and Development of Model 

 Databases task deliverables and due dates.............................................................17 

Table 2-5. Phase I Task 4 Develop Optimal VISTAS Modeling Configuration task 

deliverables and due dates .....................................................................................18 

Table 2-6. Phase I Task 6 Phase II Modeling Protocol task deliverables and due dates ........19 

Table 2-7. Phase I Task 6 Develop Website task deliverables and due dates.........................19 

Table 2-8. Phase II Task 1 Project Management task deliverables and due dates..................21 

Table 2-9. Phase II Task 2 GEOS-CHEM Boundary Condition Analysis 

 task deliverables and due dates..............................................................................21 

Table 2-10. Phase II Task 3 2002 Data Preparation and Model Inputs 

 task deliverables and due dates..............................................................................25 

Table 2-11. Phase II Task 4 2002 CMAQ Modeling task deliverables and due dates..............28 

Table 2-12. Phase II Task 6 Data Management task deliverables and due dates......................30 

Table 2-13. Phase II Task 7 CB4/SAPRC Sensitivity modeling task 

 deliverables and due dates .....................................................................................31 

Table 2-14. Phase II Task 10 Phase I Journal Article task deliverables and due dates.............31 

Table 2-15. Phase II Task 13 2002 GEOS-CHEM Boundary Condition 

 Processing task deliverables and due dates............................................................32 

Table 3-1. VISTAS Phase II Emissions and Air Quality Modeling 

 project participants and contacts............................................................................34 

Table 3-2. VISTAS listservs maintained by the Emissions and 

 Air Quality Modeling Team...................................................................................38

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1.0 INTRODUCTION 

This Quality Assurance Project Plan (QAPP) describes the quality management functions and 

activities performed by the Visibility Improvements for States and Tribal Associations in the 

Southeast (VISTAS) Phases I and II Emissions and Air Quality Modeling performed by 

ENVIRON International Corporation (Prime Contractor), Alpine Geophysics, LLC 

(Subcontractor) and the University of California at Riverside College of Engineering – Center 

for Environmental Research and Technology (UCR/CE-CERT; Subcontractor). 

VISTAS is one of five Regional 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 address the requirements of the Regional Haze Rule (RHR) 

visibility SIPs/TIPs due in 2007/2008. VISTAS modeling results will also likely form the 

regional component for 8-hour ozone and fine particulate (PM2.5) SIPs/TIPs that are also 

expected to be due in 2007/2008. The VISTAS Emissions and Air Quality Modeling Team is 

comprised of staff from ENVIRON International Corporation (ENVIRON), Alpine Geophysics, 

LLC (Alpine) and the University of California, Riverside (UCR). The ENVIRON/Alpine/UCR 

Team performs the emissions and air quality modeling simulations for states and tribes within 

the VISTAS region, providing analytical results used in developing implementation plans under 

the EPA Regional Haze Rule. 

The quality assurance approach utilized herein is generally based on the national consensus 

standard (ANSI/ASQC, 1994). This standard describes 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/Alpine/UCR Team and is documented in the VISTAS Phase 

I and II Modeling Protocols (ENVIRON, 2003; 2004a) and in UCR’s Quality Management Plan 

(QMP; UCR, 2003). The VISTAS Modeling Protocols and UCR’s QMP formed the basis for 

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

This QAPP was prepared in accordance with the 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 documents were developed particularly 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 applications. In order to utilize model outputs for 

these purposes, it must be established that each model is scientifically sound, robust, and 

defensible. This is accomplished by following a project planning process that incorporates the 

following elements as described in the EPA guidance document for modeling: 

• A systematic planning process including identification of assessments and related 

performance criteria; 

• Peer reviewed theory and equations; 

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• A carefully designed life-cycle development 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 understand the model output; 

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

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

The purpose of this QAPP is to establish and encourage a continuous improvement process that 

will result in clearly defined data quality 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 national parks, wilderness areas, and international 

parks. Through these amendments, Congress set a national goal for visibility as “the prevention 

of any future, and the remedying of any existing, impairment of visibility in mandatory Class I 

Federal areas which impairment results from manmade air pollution” (40 CFR 51.300). States 

are required to develop State Implementation Plans (SIPs) to attain visibility 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 

Southeastern US are required to submit visibility SIPs under Section 308 of the Regional Haze 

Rule (RHR). 

Through the Southeastern States Air Resource Managers (SESARM), the Visibility 

Improvement State and Tribal Association of the Southeast (VISTAS) has implemented a 

regional air quality planning process to provide the necessary technical and policy tools needed 

by states and tribes to comply with the Section 308 of the RHR requirements. As part of this 

effort, VISTAS has funded modeling studies to support the development of SIPs and TIPs. In 

March 2003, VISTAS contracted with ENVIRON International Corporation, with Alpine 

Geophysics, LLC (Alpine) and University of California at Riverside (UCR) as Subcontractors, to 

perform Emissions and Air Quality Modeling. 

The results of the modeling studies performed by VISTAS 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 

The VISTAS Emissions and Air Quality Modeling Team performs regional haze analyses by 

operating regional scale, three-dimensional air quality models that simulate the emissions, 

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chemical transformations, and transport of gaseous and particulate matter (PM) species and 

consequently effects on visibility in Class I Areas in the southeastern U.S. A key element of this 

work includes the integration of emissions inventories and models with regional transport 

models. The general services provided by the VISTAS Emissions and Air Quality Modeling 

Team include, but are not limited to: 

• Emissions processing and modeling; 

• Air quality and visibility modeling simulations; 

• Analysis, display, and reporting of modeling results; and 

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

2.2 VISTAS Two-Phased Approach 

The VISTAS Emissions and Air Quality Modeling activities are being performed in two Phases. 

Phase I, which occurred primarily during the 2003 calendar year, consisted of emissions and 

regional haze modeling for three episodes to identify the optimal model configuration(s) for 

simulating regional haze in the southeastern US. Phase II, initiated in 2004, consists of operating 

the emissions and air quality models for the 2002 calendar year to develop the regional haze 

modeling databases needed to address the requirements of the Section 308 RHR SIPs and TIPs. 

2.2.1 VISTAS Phase I 

The objective of VISTAS Phase I was to determine the optimal modeling configuration for use 

in the subsequent Phase II visibility assessment. Accordingly, Phase I entailed a comprehensive 

literature review of recent relevant visibility studies using various photochemical/aerosol 

modeling platforms in order to assess and identify appropriate model configurations, data bases, 

and model testing methodologies that were appropriate for use in conducting the VISTAS Phase 

I emissions and PM modeling assessment. Key elements of Phase I included: 

3⁄4 Review all relevant air quality model simulations that have been completed related to 

regional haze and PM2.5 modeling and document the relevant sensitivity analyses, model 

configuration testing, and performance evaluations that have been performed 

(ENVIRON, 2003b); 

 

3⁄4 Review the current science in regional emissions modeling (e.g., EPS, EMS and 

SMOKE) and PM air quality modeling (e.g., CMAQ, CMAQ-MADRID, CMAQ-AIM, 

REMSAD, UAM-V/PM, CAMx4 and PMCAMx) to determine the most appropriate 

model(s) for use by VISTAS (ENVIRON, 2003b); 

3⁄4 Review available ambient data for evaluating one-atmosphere PM/ozone models 

(ENVIRON, 2003c);

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3⁄4 Develop and implement a plan or Modeling Protocol for testing and evaluating 

alternative science configurations of the recommended Phase I model(s) and document 

the results (ENVIRON, 2003a); and 

3⁄4 Prepare a Task 6 report prescribing the model set-up, data base development, 

performance testing, and control strategy evaluation procedures to be implemented in 

VISTAS Phase II (ENVIRON, 2004a). 

VISTAS formed three standing workgroups to plan and direct the project. These included: (a) the 

Technical Analysis (emissions and modeling) Workgroup; (b) the Data (monitoring) Workgroup; 

and (c) the Planning Workgroup. Under Phase I, the VISTAS Technical Analysis Workgroup 

(TAWG) managed the comprehensive model configuration testing program aimed, as noted 

above, at evaluating the capabilities of current state-of-science regional emissions, prognostic 

meteorological and PM/visibility models. The resultant modeling system (models and databases) 

identified and tested in Phase I were intended to be applied in Phase II (discussed below) 

following the procedures set forth in the Phase II Modeling Protocol (ENVIRON, 2004a). 

For the meteorological component of the Phase I modeling, SESARM contracted with Baron 

Advanced Meteorological Systems (BAMS) to apply the PSU/NCAR Mesoscale Model (MM5) 

in multiple configurations and to evaluate its performance against surface and aloft 

meteorological observations (Olerud, 2003a-f). The emissions modeling component of VISTAS 

Phase I was carried out by the research team of ENVIRON/Alpine/UCR with staff at Alpine 

Geophysics taking the lead role in setting up, testing, and applying the emissions modeling 

system. The air quality modeling component was performed by the team at the 

ENVIRON/Alpine/UCR modeling centers. A dominant theme during Phase I was the exchange 

of modeling codes, databases, and evaluation software between the three modeling centers as the 

air quality modeling was carried out. 

2.2.2 VISTAS Phase II 

The Phase II modeling includes annual PM/regional haze simulations plus potentially additional 

shorter duration episodes. After detailed performance testing, the modeling system will then be 

exercised with a variety of emissions control scenarios aimed at enabling VISTAS to assess the 

effects of future year emission control strategies on visibility and other air quality issues. The 

modeling system will also allow VISTAS to track reasonable progress toward regional haze 

goals. More specifically, the VISTAS Phase II program will focus on the use of the CMAQ 

modeling system for calendar year 2002 over the same 36/12 km horizontal grid system used in 

Phase I. A potentially large number of annual (and episodic) model simulations will be 

performed; the list below reflects current plans: 

3⁄4 2002 Initial Annual Run. The initial annual model simulations and performance 

evaluations using the 2002 inventory for VISTAS and non-VISTAS states, Canada and 

Mexico. Multiple iterations of the 2002 annual simulation will be required to confirm the 

appropriateness of the model science configuration(s) recommended by the Phase I work, 

to evaluate updates to the model and model inputs and to refine model performance. 

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3⁄4 2002 Revised Annual Run. A subsequent annual 2002 simulation using revised 2002 

modeling inventory for VISTAS and non-VISTAS states, Canada and Mexico. The 

primary objective of this run is model performance demonstration using updated 

emissions inventories and best science model configurations. Additional sensitivity tests 

will be conducted using the revised base case year annual run. 

3⁄4 2002 Annual Run with “Typical Year” EGU/Fire Inventory. An annual 2002 

simulation representing the 2000-2004 baseline period for EGU and fire emissions and 

using 2002 revised inventory for all other source sectors. The primary objective of this 

inventory is to provide the base line modeled air quality condition against which future 

year modeling runs will be compared to develop relative reduction factors for each 

pollutant species. 

3⁄4 Future Year Annual Runs. Future year simulations involving a base case inventory of 

typical EGU and fire emissions for VISTAS-selected future period. Additional future 

year inventories may also be modeled. The objective of these future year model runs is 

to establish the modeled air quality basis against which the effectiveness of emissions 

control strategies will be evaluated. 

3⁄4 Future Year Emission Control Strategies. Prescription of the future year emissions 

control strategies to be performed later in Phase II (e.g., 2005) will be defined after the 

foregoing simulations and analyses have been completed. A combination of annual and 

episodic runs is anticipated. 

Closely integrated with the annual (and possibly episodic) meteorological, emissions and air 

quality modeling will be ongoing project management, technical review, and quality assurance 

activities performed under the guidance of the VISTAS Contracting Officer and the TAWG. 

The modeling team members will participate with VISTAS management in regular monthly 

conference calls, as well as ad hoc topical conference calls as needed, and will attend periodic 

meetings with the TAWG members throughout Phase II. 

Complementing the data acquisition, modeling input development activities, and project 

management activities, four other Phase II activities will be performed, consistent with the 

Quality Assurance Project Plan (QAPP): 

2.2.2.1 Data Gatekeepers 

The VISTAS Phase II emissions and air quality modeling team are receiving emissions, 

meteorological and air quality data from other VISTAS contractors or other sources. As a first 

line of QA, we have defined a Gatekeeper function to assure the data have been received 

correctly, the 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 below. In addition, a Data Management Gatekeeper has been 

defined who will post data, reports and results to the project website and archive all key data 

generated in the project. 

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3⁄4 Air Quality Data Gatekeeper. Obtain air quality data as appropriate for 

model input development and model performance evaluation and assure that 

the quality of all air quality data obtained are consistent with the approved 

QAPP. Provide documentation of evaluation and generate IC/BC inputs for 

CMAQ for all modeling runs. 

3⁄4 Meteorological Gatekeeper. Obtain meteorological data, as MM5 or MCIP 

files, as appropriate for annual 2002 modeling runs and other episode periods 

and perform data quality checks as approved in the QAPP, together with 

appropriate documentation of model performance evaluation activities. 

3⁄4 Emissions Gatekeeper. Obtain emissions inventory data necessary to 

support annual 2002 and future year modeling and recommend source of 

emissions data to be used for Canada and Mexico. Assure quality of all 

emissions data received are consistent with the approved QAPP, and develop 

all emissions modeling files to support modeling runs for 2002. Develop the 

chemical speciation files and temporal and spatial allocation files necessary to 

convert annual inventories into hourly and daily emissions modeling files, as 

appropriate. Develop all emissions modeling files for non-VISTAS states to 

support modeling runs for future year base case and emissions strategies as 

defined by VISTAS. 

3⁄4 Data Management Gatekeeper: Maintain the VISTAS Modeling Website 

including posting modeling input and output files, reports, interpretation of 

results, and other documents as requested by VISTAS to support all Phase II 

tasks. This includes, for example, the storage of model inputs and outputs for 

annual (and episodic) runs and the transfer (via fire wire or alternative media) 

of electronic files to VISTAS states, other regional planning organizations, 

EPA, other contractors, and stakeholders. 

2.2.2.2 Emissions QA/QC 

Emissions Quality Assurance (QA) and Quality Control (QC) are the single most critical steps in 

performing air quality modeling studies. Because emissions processing is tedious, time 

consuming and involves complex manipulation of many 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 Phase II we will continue with the multistep emissions QA/QC 

approach applied in the Phase I modeling. This includes the initial emissions QA/QC by the 

Emissions Gatekeeper described above, as well as QA/AC by the Emissions Modeler during the 

processing of emissions and then additional QA/QC by the air quality modeler of the processed 

model ready emission files. This multistep process with three separate groups involved in the 

QA/QC of the emissions is designed to detect and correct errors prior to the air quality model 

simulations. 

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

EMS and EPA Input Screening Error Checking Algorithms: Although the SMOKE 

emissions model will be used for emissions processing, some of the more advanced EMS 

input error checking algorithms will be used to screen the data and identify potential 

emission input errors. Additionally, EPA has issued a revised stack QA and augmentation 

procedures 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 redirect the SMOKE output to log files and 

review the log files for serious error messages. 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 processed emissions as daily totals according 

to species, source category and county and state boundaries. These summaries will then 

be compared with summary data prepared for the pre-processed emissions, e.g., state and 

county totals for emissions from the augmented emissions data. 

Once the CMAQ-ready emission inputs have been 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 daily total emissions spatial distribution. For a 

20 day simulation this produces approximately 20 days x 20 species x 5 emissions 

categories = 2,000 plots. In our base case simulations these plots will be presented as tons 

per day. The objective of this step is to identify errors in spatial distribution of emissions. 

Vertical Profile: For point sources the emissions total for each layer will be summed and 

plotted to show the vertical distribution of emissions. These plots show the emissions on 

the x-axis for each model 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 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 inconsistent with other days for no reason (e.g., not a 

weekend) and compare against 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 immediately identify a problem in a control 

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strategy. For example, if a VISTAS state’s SO2 control strategy is being analyzed and 

there are changes in emissions for other pollutants or for SO2 outside of the VISTAS 

states problems in emissions processing can be identified prior to the air quality model 

simulation. 

2.2.2.3 Meteorology QA/QC 

The VISTAS meteorological modeling contractor (BAMS) will have primary responsibility in 

the QA/QC of the MM5 meteorological fields. However, the emissions and air quality modeling 

team will also perform some QA/QC of the meteorological data to assure that it has transferred 

correctly, to obtain an assessment of the quality of the data and to assist in the interpretation of 

the air quality modeling results. 

The VISTAS Phase II Meteorological Gatekeeper will perform the following: 

3⁄4 Analyze the MM5 data to assure it has been transferred correctly. 

 

3⁄4 Evaluate the MM5 using METSTAT and the surface meteorological network. 

3⁄4 Evaluate upper-air MM5 meteorological estimates by comparison them to upper-air 

observations and satellite images. 

3⁄4 Compare the VISTAS 2002 MM5 simulation with the one generated by WRAP. 

3⁄4 Generate the CMAQ-ready meteorological inputs using the MCIP2.2 processor. 

2.2.2.4 Air Quality Modeling QA/QC 

Key aspects of QA for the CMAQ input and output data include the following: 

3⁄4 Verification that correct configuration and science options are used in compiling and 

running each model of the in the CMAQ modeling system, where these include the 

MCIP, JPROC, ICON, BCOM and the CCTM. 

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

3⁄4 Evaluation of CCTM results to verify 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 results against concurrent observations. 

3⁄4 Backup and archiving of critical model input data. 

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The most critical element for CMAQ simulations is the QA/QC of the meteorological and 

emissions input files, which is discussed above. The major QA issue specifically associated with 

the air quality model simulations is verification that the correct science options were specified in 

the model itself and that the correct input files were used when running the model. For the 

CMAQ model we employ a system of naming conventions using environment variables in the 

compile and run scripts that guarantee that correct inputs and science options are used. We also 

employ a redundant naming system so that the names of key science options or inputs are 

included in the name of the CMAQ executable program, in the name of the CMAQ 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 directory structure that were used in performing a model simulation. 

We will also perform a post-processing QA of the CMAQ output files similar to that described 

for the emissions processing. We will generate animated gif files using PAVE that can be viewed 

to search for unexpected patterns in the CMAQ 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 simulations. This 

provides a summary that can be useful for quickly comparing various model simulations. 

2.2.2.5 Overview of Data Flow and Quality Assurance Process 

Figure 2-1 displays an overview of the data flow and quality assurance process in the VISTAS 

Emissions and Air Quality Modeling study. The VISTAS Modeling Team receives different 

types of data from various VISTAS contractors and other sources that have performed their own 

Quality Assurance (QA) and Quality Control (QC). Whenever data are received by the 

Modeling Team, it is 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 check. 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, 

the provider of the data is contacted and asked to correct the data. Once the Gatekeeper has 

conducted a QA check of the data it is passed on to the modeler who performs their QA of the 

data. The data are then used in the modeling and resultant output (e.g., model-ready emissions or 

meteorological files) are then subjected to another round of QA to assure the integrity of the data 

is retained. 

Once the model-ready inputs have been developed and subjected to QA/QC, the models (e.g., 

CMAQ and/or CAMx) are applied using Base Case emissions and the modeling results subjected 

to a model performance evaluation. The model performance evaluation (MPE) represents an 

extensive QA effort and is the most time consuming component of the study. EPA has 

developed draft guidance for evaluating regional PM and haze models that includes performance 

goals (EPA, 2001). In addition, the Modeling team has adapted EPA MPE approaches and goals 

for 1-hour (EPA, 1991) and 8-hour (EPA, 1999) ozone modeling. The VISTAS Modeling Team 

performs the MPE/QA process using as many different tools and analysis as possible in order to 

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fully understand the accuracy and reliability of the model simulation. As seen in Figure 2-1b, the 

MPE process in VISTAS is a multistep process using several different techniques: 

UCR Analysis Tools: The University of California at Riverside (UCR) Analysis Tools 

were used extensively in Phase I and are run on a Linux platform separately for each 

network. Graphics are automatically generated using gnuplot and the software generates 

the following: 

• Tabular statistical measures; 

• Time Series Plots; and 

• Scatter Plots by allsite_allday, allday_onesite and allsite_oneday. 

MAPS Analysis Tools: Alpine Geophysics (Alpine) has a MAPS Analysis Tool that also 

runs under Linux and is based on Fortran and NCAR Graphics. It was originally 

developed for evaluating ozone models and has been extended to treat PM species as 

well. In addition to calculating similar statistics, scatter plots and time series plots as the 

UCR Analysis Tools, it also can generate spatially averaged time series plots of 

concentrations, bias and error, performs analysis of peak concentrations and includes a 

Flying Data Grabber (FDB) for comparing modeling results with aircraft data. 

ENVIRON Analysis Tools: ENVIRON has developed specialized 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 model performance across networks, episodes, 

species, models and sensitivity tests and compare them with performance goals. 

GA DNR Analysis Plots: Dr. James Boylan of the Georgia Department of Natural 

Resources has extended the concept in EPA’s draft PM fine particulate and regional haze 

modeling guidance that model performance for species that make up a major contribution 

to visibility impairment be subjected to more stringent goals than species that are minor 

contributors by developing concentration-dependent performance goals and “Bugle 

Plots” to display them. 

The evaluation of the VISTAS Phase II initial 2002 CMAQ Base Case simulation used each of 

the analysis tools listed above demonstrating their descriptive and complimentary nature. 

The issue of model performance goals for PM species is an area of ongoing research and debate. 

For ozone modeling, EPA has established performance goals for 1-hour ozone normalized mean 

bias and gross error of #±15% and #35%, respectively (EPA, 1991). EPA’s draft fine particulate 

modeling guidance notes that performance goals for ozone should be viewed as upper bounds of 

model performance, that PM models may not be able to always achieve and we should demand 

better model performance for PM components that make up a larger fraction of the PM mass 

than those that are minor contributors (EPA, 2001). Measuring PM species is not as precise as 

ozone monitoring. In fact, the differences in measurement techniques for some species likely 

exceed the more stringent performance goals, such as those for ozone. For example, recent 

comparisons of the PM species measurements using the IMPROVE and STN measurement 

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technologies found differences of approximately "20% (SO4) to "50% (EC) (Solomon et al., 

2004). 

In the VISTAS 2002 CMAQ Base Case modeling, we have adopted three levels of model 

performance goals for bias and gross error as listed in Table 2-1 that are used to help evaluate 

model performance. Note that we are not suggesting that these performance goals be generally 

adopted or that they are the most appropriate goals to use. Rather, we are just using them to 

frame and put the PM model performance into context and to facilitate model performance 

intercomparison 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. Accordingly, we are also using performance goals that are a 

continuous function of average observed concentrations proposed by Dr. James Boylan at the 

Georgia Department of Natural Resources that have the following features: 

• Asymptotically approaching proposed performance goals or criteria when the mean of the 

observed concentrations are greater than 2.5 ug/m3

. 

• 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 the mean observed concentration 

approaches zero the bias performance goal and criteria flare out to ±200% creating a horn shape, 

hence the name “Bugle Plots”.

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

Fractional 

Bias Fractional 

Error 

Comment 

#"15% #35% Ozone model performance goal8

 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 performance indicates fundamental 

problems with the modeling system. 

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VISTAS Emissions and Air Quality Modeling Revision 0 ENVIRON International Corporation November 12, 2004 Figure 2-1a. Data flow and quality assurance steps in the VISTAS Emissions and Air Quality Modeling. 

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VISTAS Emissions and Air Quality Modeling ENVIRON International Corporation Figure 2-1b. Concluded. Data flow and quality assurance steps in the VISTAS Emissions and Air Quality Modelin

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2.3 VISTAS Phase I and II Modeling Protocols 

As recommended in EPA’s draft regional haze modeling guidance (EPA, 2001), the VISTAS 

Phase I and II modeling efforts were initiated by developing Modeling Protocols that described 

the procedures to be used to conduct, quality assure and quality control (QA/QC), evaluate and 

use the modeling results (ENVIRON, 2003a; ENVIRON, 2004a). These Modeling Protocols 

were reviewed and commented on by the VISTAS TAWG and others and are updated 

accordingly. 

2.4 VISTAS Phase I Activities 

The VISTAS Phase I Emissions and Air Quality Modeling work was carried out mainly during 

2003 with some final deliverables provided in early 2004. The Phase I activities formed the 

basis for the Phase II modeling and was the foundation of the Phase II quality assurance (QA) 

and quality control (QC). 

2.4.1 Phase I Task 1: Project Management 

There are three aspects of Project Management that were performed under this task: (a) Project 

Management of the project’s resources and technical progress keeping VISTAS informed of 

progress; (b) Technical Management of the day-to-day technical activities of the 

ENVIRON/Alpine/UCR Team keeping clear lines of communication, and (c) Communication 

Management of the data flow and expectations among the other VISTAS contractors. 

Project Management: The Project Manager, Co-Principal Investigators (Co-PIs), and Task 

Managers had frequent communications with the VISTAS technical and project management 

group through regular conference calls, e-mails and meetings as needed. The ENVIRON, Alpine 

and UCR Modeling Centers were headed by each of the three Co-PIs (Ralph Morris, T.W. 

Tesche and Gail Tonnesen, respectively) with clear lines of communication. 

Technical Management: The three Co-PIs are responsible for the management of the technical 

work within each of their respective research groups. With responsibility comes accountability. 

Communication Management: Key to the communications management will be weekly internal 

conference calls among the three Co-Principal Investigators and the regular conference calls 

between the three Co-PIs and the VISTAS TAWG and other VISTAS contractors. When data 

are received from VISTAS contractors, the Modeling Team’s meteorological or emissions 

Gatekeeper subjected the data to an extensive QA. Any problems identified will be reported to 

the three Co-PIs who will then relay immediately that information to the VISTAS TAWG and 

the relevant contractor with the issue addressed in a conference call so that it can be resolved. 

List servers related to emissions, meteorology, and modeling issues were set up for prompt 

communication among the Team, VISTAS, and other VISTAS contractors. 

Deliverables under this task were continuous project management and conference calls, plus two 

project meetings held in Research Triangle Park, North Carolina (see Table 2-2). The project 

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meetings were attended by the three Co-PIs and additional staff from the Emissions and Air 

Quality Modeling Team. 

Table 2-2. Phase I Task 1 Project Management task deliverables and due dates. 

Item Description Due Date 

1 VISTAS TAWG Modeling Meeting September 29-30, 2003 

at the Solution Center in Research Triangle Park, North 

Carolina 

09/29-30/03

2 VISTAS TAWG Modeling Meeting February 12-13, 2004 in 

Research Triangle Park, North Carolina 

02/12-13/04

2.4.2 Phase I Task 2: Develop Model Configuration Evaluation Plan 

The first activity under the VISTAS Phase I Emissions and Modeling Study was the 

development a detailed plan, or Modeling Protocol (ENVIRON, 2003a), outlining the data 

analysis procedures and statistical/graphical tools to be used in evaluating the core and 

alternative CMAQ configurations in Task 4. This plan identified the procedures used in 

producing internally consistent observational and modeling data sets for individual particulate 

species and species groupings. The main purpose of this plan is to provide a consistent set of 

procedures to be used in the early portion of the Phase I activities when the various CMAQ 

model configurations are being tested. The draft plan was submitted to VISTAS TAWG who 

provided comments that were incorporated in the final Phase I modeling plan (see Table 2-3). 

Table 2-3. Phase I Task 2 Phase I Modeling Plan task deliverables and due dates. 

Item Description Due Date 

1 Draft Report “VISTAS Emissions and Air Quality Modeling— 

Phase I Task 2 Report: Recommended Model Configurations and 

Evaluation Methodology For Phase I Modeling” 

06/03/03 

2 Revised Draft Report “VISTAS Emissions and Air Quality 

Modeling— Phase I Task 2 Report: Recommended Model 

Configurations and Evaluation Methodology For Phase I 

Modeling” Available at: 

http://pah.cert.ucr.edu/vistas/reports/VISTAS_Task2-

REPORT.pdf

08/04/03 

2.4.3 Phase I Task 3: Acquisition and Development of Modeling Data Bases 

Under this task we assembled the databases needed to operate and evaluate the CMAQ model for 

the three Phase I episodes. 

 

Subtask 3a: Assemble/QA Air Quality Data. Under this Subtask we assembled a comprehensive 

database of ambient measurements to evaluate model performance. As part of the WRAP model 

performance evaluation our team had previously assembled data from the CASTNet (weekly wet 

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and dry deposition of SO4, NO3, NH4, pH, base cations) and IMPROVE (daily fine particulate 

mass composition as SO4, NO3, NH4, OC, EC, and soils). Additional processing of data was 

needed to include ambient data from the SEARCH and STN networks in the analysis. Several 

issues must be addressed to use these data to evaluate model performance. In many cases there 

is not a 1-to-1 correspondence to model species. Accordingly, formulas must be developed to 

correctly map the data to the model species (for details, see the IMPROVE and CASTNET links 

at: http://pah.cert.ucr.edu/rmc/ambient/ambient.shtml. Moreover, model predictions are hourly 

while some ambient data are daily or weekly averages, so algorithms were developed to correctly 

treat averaging periods including correct representation of the time zone used for each 

monitoring site. QA of ambient data is a key step; we reviewed all data for reasonableness and 

completeness and flagged apparent outliers for exclusion from the model evaluation. We 

processed the AIRS data including O3, NOx and CO to convert it to the IO/API data format so 

that it can be used with PAVE for visualization of model and ambient data. For long term 

modeling (monthly to annual) it is essential that the QA’d ambient databases be designed to 

work with our model performance evaluation software. This will facilitate rapid model 

evaluation for multiple sensitivity simulations or repeats of base case simulations. 

Subtask 3b: Assemble/QA Emissions Data. CMAQ emissions inputs were prepared using data 

supplied by the VISTAS emissions contractors, the EPA NEI version 2 databases and the 

SMOKE emissions modeling system. The study team is currently working with the NEI formats 

and has developed the necessary QA tools to make effective use of these data. The NEI 

database, while the best available national inventory, must be examined for local modeling, 

particularly in point source locations and stack parameters. The QA tools developed as part of 

the EMS-2001 are a useful adjunct to the tools currently available in SMOKE. 

The study team has also developed a suite of tools designed to QA and evaluate episode specific 

emissions prior to inclusion into the modeling inventory. Since the magnitude of the dayspecific emissions for large stationary source is often significant in the modeling inventory, 

special attention is placed on the QA of these emissions data. The study team has processed the 

spatial surrogates and BELD-3/BEIS-3 databases over the Unified RPO grid under contract to 

the Midwest RPO. These data are currently under review and revision and the version most 

current will be used. 

Subtask 3c: Assemble/QA Meteorological Data. The meteorological model (MM5) output data 

was acquired from the VISTAS meteorological modeling contractor. While we recognize that 

the MM5 data will already have been validated by the meteorological modeling contractor, it has 

been our Team’s experience that an independent review is both time and cost effective. As part 

of our quality assurance activities, a full operational model evaluation was performed on the 

MM5 data sets. This operational evaluation covered surface and aloft wind direction, 

temperature, mixing ratio, and planetary boundary layer depths on both a domain-wide and 

subregional basis. The techniques used will follow the model performance protocol prepared for 

EPA for annual MM5 modeling (McNally and Tesche, 2002). 

Table 2-4 summarizes the VISTAS Phase I Task 3 deliverables. 

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Table 2-4. Phase I Task 3 Phase I Acquisition and Development of Model Databases task 

deliverables and due dates. 

Item Description 

Due 

Date 

1 Draft Report “VISTAS Emissions and Air Quality Modeling— Phase I Task 

3a Report: Review and Assessment of Available Ambient Air Quality Data 

to Support Modeling and Model Performance Evaluation for the Three 

VISTAS Phase I Episodes” Available at: 

http://pah.cert.ucr.edu/vistas/reports/VISTAS_Task_3_072203.pdf

07/22/03 

2 Draft Report “VISTAS Emissions and Air Quality Modeling— Phase I Task 

3b Report: CMAQ Emissions Inventory Development and Emissions 

QA/QC Summary Report for Episodes 1, 2 and 3” Available at: 

 http://pah.cert.ucr.edu/vistas/reports/VISTAS_subtask_3b_QA_report.pdf

09/25/03 

3 Subtask 3c-1 Report: “VISTAS Emissions and Air Quality Modeling— 

Phase I Task 3c-1 Report: MM5 Meteorology QA/QC Summary Report for 

Episode 1: 2-20 January 2002” Available at: 

http://pah.cert.ucr.edu/vistas/reports/met_episode_1_report.pdf

09/10/03 

4 Subtask 3c-2 Report: “VISTAS Emissions and Air Quality Modeling— 

Phase I Task 3c-2 Report: MM5 Meteorology QA/QC Summary Report for 

Episode 2: 13-22 July 1999” Available at: 

 http://pah.cert.ucr.edu/vistas/reports/met_episode_2_report.pdf

09/15/03 

5 Subtask 3c-3 Report: “VISTAS Emissions and Air Quality Modeling— 

Phase I Task 3c-3 Report: MM5 Meteorology QA/QC Summary Report for 

Episode 3: 11-27 July 2001” Available at: 

 http://pah.cert.ucr.edu/vistas/reports/met_episode_3_report.pdf

09/16/03 

2.4.4 Phase I Task 4: Develop Optimal VISTAS Modeling Configuration 

Under VISTAS Phase I Task 4, we developed plans for the initial testing and sensitivity 

modeling of the SMOKE and CMAQ modeling systems in order to identify the optimal model 

configurations) for simulating regional PM, ozone and visibility in the eastern US. We first 

reviewed and assessed recent relevant regional modeling studies from which we identified an 

initial configuration and list of sensitivity tests. We then performed the sensitivity tests to 

identify the optimal model configuration(s). 

Subtask 4a: Recent Literature Review. Initiating Task 4 we performed a literature review to 

identify and critically evaluate recent relevant fine particulate/regional haze modeling studies, 

field programs and related scientific investigations that shed light on: (a) the selection and 

evaluation of CMAQ model configuration options, (b) the availability and adequacy of gas-phase 

and PM data sets for model set up and performance testing, (c) the suitability of operational and 

diagnostic procedures for evaluating the performance of CMAQ, and (d) any pertinent 

information of future year emissions control evaluations (ENVIRON, 2003b). 

Subtask 4b: Recommend Initial SMOKE/CMAQ Configurations. Drawing from the Team’s 

experience with SMOKE and CMAQ, we identified a suite of initial model configurations to be 

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evaluated with the three test episodes. These alternative configurations included definition of: 

(a) vertical and horizontal grids, (b) gas-phase chemistry mechanism, (c) secondary aerosol 

mechanisms, (d) advection algorithms, (e) diffusion algorithms, (f) cloud and surface removal 

processes, (g) numerical integration scheme(s), and so on (ENVIRON, 2003b). 

Subtask 4c: Evaluate Approved SMOKE/CMAQ Configurations. The ENVIRON, Alpine, and 

UCR team collaboratively evaluated the various model configurations recommended in Subtask 

4b. These evaluations employed internally consistent statistical and graphical procedures and 

display software (Morris et al., 2004a). 

 

Subtask 4d: Perform Diagnostic/Sensitivity Experiments. Paralleling and supporting Subtask 4c, 

the study team conducted a series of diagnostic/sensitivity experiments aimed at identifying the 

most technically sound and reliable chemistry, transport, removal, and numerical algorithms 

available (Morris et al., 2004a). 

Subtask 4e: Recommend Optimal Model Configuration. The culmination of the literature 

review, CMAQ configuration testing and module sensitivity/diagnostic studies was the 

identification of a final, optimal configuration for the VISTAS modeling platform to be used in 

Phase II (Morris et al., 2004a).

Subtask 4f: Technical Documentation. Thorough documentation was performed for all aspects 

of Task 4 (Morris et al., 2004a). In addition, many of the findings in this task were relevant to 

VISTAS and other RPO’s and warranted publication of the technical findings at scientific 

conferences or in journals (Morris et al., 2004b,c,d; Tesche et al., 2004).

Table 2-5. Phase I Task 4 Develop Optimal VISTAS Modeling Configuration task deliverables 

and due dates.

Item Description 

Due 

Date 

1 “VISTAS Emissions and Air Quality Modeling— Phase I Task 4a/b Report: 

Review of Model Sensitivity Simulations and Recommendations of Initial 

CMAQ Model Configurations and Sensitivity Tests” Available at: 

http://pah.cert.ucr.edu/vistas/reports/VISTAS_Task4a_Report.pdf

07/25/03

2 Final Report “VISTAS Emissions and Air Quality Modeling— Phase I Task 

4cd Report: Model Performance Evaluation and Model Sensitivity Tests for 

Three Phase I Episodes” Available at: 

http://pah.cert.ucr.edu/vistas/reports/Final_Phase1/VISTAS_Task4cd_FinalRe

port_ExcSum-Sec3_only.pdf

09/07/04

2.4.5 Phase I Task 6: Phase II Modeling Protocol 

The VISTAS Phase II Modeling Protocol describes in detail the work to be performed and the 

specific quality assurance (QA) procedures to be used in performing, evaluating, and archiving the 

annual model simulations performed in Phase II. Particular emphasis in the protocol was given to: (a) 

model configurations, (b) specific science issues to be addressed, (c) model improvements, (d) model 

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input preparation, (e) model applications (base year, future year, and strategies), (f) model evaluation 

and sensitivity analyses, (g) documentation, (h) data transfer, backup and archiving, and (i) schedule 

and deliverables. As shown in Table 2-6, under this task a First Draft Modeling Protocol was 

prepared and submitted to the VISTAS TAWG for review and comment. Based on these comments 

a Revised First Draft Modeling Protocol was prepared and distributed to the entire group for review 

and comment. 

Table 2-6. Phase I Task 6 Phase II Modeling Protocol task deliverables and due dates. 

Item Description Due Date 

1 First Draft Report “VISTAS Emissions and Air Quality Modeling — 

Phase I Task 6 Report: Modeling Protocol for the VISTAS Phase II

Regional Haze Modeling”

03/03/04 

2 Revised First Draft Report “VISTAS Emissions and Air Quality 

Modeling — Phase I Task 6 Report: Modeling Protocol for the VISTAS 

Phase II Regional Haze Modeling.” Available at: 

http://pah.cert.ucr.edu/vistas/reports/VISTAS_PhaseII_Protocol_Mar12

_2004.pdf

03/12/04 

2.4.6 Phase I Task 7: Website Development 

We developed a technical web site that served as the primary means for distributing emissions 

and air quality modeling to the VISTAS TAWG. The website included model results, analyses, 

presentations and reports. We maintained 4 list-servs (all participants, general project 

management, emissions QA, and modeling results) for the VISTAS project that can be accessed 

from the website that provides a permanent archive for all email communications for the project. 

Separate list-servs provides better organization of communications and allow for detailed 

discussions of specific topics such as emissions QA. 

Table 2-7. Phase I Task 6 Develop Website task deliverables and due dates. 

Item Description Due Date 

1 VISTAS Phase I Emissions and Air Quality Modeling Project 

Website: http://pah.cert.ucr.edu/vistas/index.shtml

2003-2004 

2.5 VISTAS Phase II Activities 

Below we discuss the project and QA activities for the currently planned VISTAS Phase II 

Modeling work effort. 

2.5.1 Phase II Task 1: Project Management 

The objective of this task is to manage project activities, participate in conference calls, attend 3 

VISTAS meetings in the southeastern United States (US), project management with VISTAS 

contacts, subcontractor management and general oversight, and overall quality assurance. 

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The VISTAS Phase II management structure for Emissions and Air Quality Modeling is the 

same as used in Phase I with Ralph Morris of ENVIRON serving as Project Manager and Ralph 

Morris, T.W. Tesche and Gail Tonnesen serving as Co-Principal Investigators (Co-PIs) and 

managing the activities in each of the ENVIRON, Alpine and UCR modeling centers, 

respectively. Under this task we are performing all management activities for the VISTAS Phase 

II modeling study, including: 

• Attendance of two scientists of the ENVIRON/Alpine/UCR Team at 3 VISTAS 

meetings to be held in the southeastern US. 

• Participation in scheduled conference calls to be held approximately once per month 

as well as expected ad hoc conference calls to be held as needed. 

• Refine Draft Phase II annual modeling protocol due early March 2004. Final initial 

Phase II annual modeling protocol incorporating review comments as directed by 

Contract Officer due two weeks after direction received. The modeling protocol 

follows EPA guidance and includes the specific task descriptions, data quality and 

assurance plan, and model performance evaluation plan for VISTAS Phase II 2004 

work. The VISTAS Phase II modeling protocol is a living document that will be 

updated as tasks are added to project work scope and to document revisions in the 

technical approach. 

• Develop and refine the Scope of Work and conduct contract discussions with the 

VISTAS modeling team and the VISTAS technical and project representatives. 

• Preparation of subcontracts, invoicing and payments. 

• Internal project conference calls and discussions among the ENVIRON/Alpine/UCR 

project team. 

• Develop and implement the Quality Assurance Project Plan (QAPP). 

• Model performance evaluation report using revised 2002 inventories. Report of 

model response to changes in inventory from 2002 revised to 2002 base year with 

“typical” EGU and fire. 

• Executive Summary report summarizing key findings and results from the task 

summary reports. 

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Table 2-8. Phase II Task 1 Project Management task deliverables and due dates. 

Item Description Due Date 

1 Second Draft Report “VISTAS Emissions and Air Quality Modeling — 

Phase I Task 6 Report: Modeling Protocol for the VISTAS Phase II 

Regional Haze Modeling.” Available at: 

http://pah.cert.ucr.edu/vistas/vistas2/reports/vistasII_Final_Protocol_05_1

0_2004.pdf 

05/06/04 

2 Conference Calls with VISTAS among Modeling Team and with TAWG 2004-2005 

3 National Inter-RPO Modeling Meeting in Denver, Colorado May 25-26, 

2004 

05/25-26/04 

4 VISTAS TAWG Meeting in Atlanta, Georgia September 22-23, 2004 09/22-23/04 

5 VISTAS TAWG meeting to be determined (TBD) TBD 

6 Quality Assurance Project Plan (QAPP) November 2004 

7 Draft VISTAS Phase II Executive Summary Report 12/31/04 

8 Final VISTAS Phase II Executive Summary Report 01/15/05 

2.5.2 Phase II Task 2: Develop IC/BCs for 2002 Annual Run 

The objective of this task is to analyze the need for a high time resolution (e.g., 3-hourly) global 

climate model (e.g., GEOS-CHEM) output for generating Boundary Conditions (BCs) for 2002 

annual modeling of the 36 km national RPO grid. 

Under this task we are recommending a source of initial and boundary conditions (IC/BC) for 

2002 annual and 2003 episodic CMAQ modeling. We would analyze in more detail the VISTAS 

Phase I July 2001 episode CMAQ simulations using the BCs generated from GEOS-CHEM 

2001 3-hour concentrations outputs. The CMAQ model performance and output for the July 

2001 episode using BCs generated from GEOS-CHEM seasonal/monthly vs. 3-hour output 

performed under Phase I would be analyzed and compared with a run using the EPA CMAQ 

default BCs. This is followed by interaction with investigators at Harvard University and 

University of Houston to evaluate temporal and spatial variability between BC based on 3-hour 

average and monthly average GEOS-CHEM outputs for 2001. Based on these results we would 

recommend whether GEOS-CHEM 2002 day-specific outputs are justified to capture daily 

variability in BC concentrations. 

Table 2-9. Phase II Task 2 GEOS-CHEM Boundary Conditions Analysis task deliverables and due 

dates. 

Item Description Due Date 

1 PowerPoint Presentation: “VISTAS Phase I and II Modeling 

Boundary Condition Sensitivity” presented at February 12-13, 2004 

VISTAS Modeling Meeting in RTP, NC 

02/12-13/04 

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2.5.3 Phase II Task 3: 2002 Data Preparation and Model Inputs 

The development of the VISTAS Phase II 2002 annual CMAQ model inputs is being performed 

in several Subtasks as follows. 

2.5.3.1 Subtask 3a: Air Quality Data Gatekeeper 

The objective of Subtask 3a is to acquire, process and QA/QC air quality data, deposition data 

and other data that can be used to evaluate CMAQ and other air quality models for the 2002 

annual cycle and the 36 km national RPO grid with particular emphasis on the VISTAS 

southeastern US region. 

Under this Subtask the Air Quality Gatekeeper would perform the following activities: 

• Obtain air quality data as appropriate for model input development and model 

performance evaluation. At a minimum, the same data bases as used in Phase I should 

be used in Phase II. 

• Identify if any special aircraft (or other) measurements are available within the VISTAS 

12-km domain for the 2002 modeling year. 

• Assure quality of all air quality data obtained, are consistent with the approved QA/QC 

plan. 

• Provide documentation of evaluation. 

• Generate IC/BC inputs for CMAQ for all 2002 modeling runs described in Task 4 below. 

2.5.3.2 Subtask 3b: MM5 Meteorological Model Gatekeeper 

The objectives of this Subtask is to acquire the 2002 MM5 data from the VISTAS 

Meteorological Contractor (BAMS) and perform QA/QC, an independent evaluation, and 

process the data using MCIP for input into CMAQ. 

The Meteorological Gatekeeper’s function for the VISTAS Phase II 2002 MM5 modeling results 

would be the similar as was done in Phase I, only we would leverage off of the 2002 MM5 

model evaluation infrastructure set up at ENVIRON for WRAP. The MM5 output would be 

acquired from BAMS and subjected to an initial quality check. Any issues associated with the 

2002 MM5 output would be reported immediately back to BAMS and VISTAS. After an initial 

quality check is performed, a more thorough QA/QC and an independent evaluation would be 

conducted. Results would be compared with other 2002 MM5 simulations (e.g., WRAP). The 

CMAQ-ready meteorological inputs would also be generated under this subtask. The MM5 data 

would be provided in two installments of 8 months and 4 months, respectively. 

2.5.3.3 Subtask 3c: Emissions Gatekeeper and Emissions Development for Non-VISTAS 

States, Canada, and Mexico 

Under this Subtask we would coordinate activities with the VISTAS emissions contractor and 

perform initial QA/QC of emissions. We would also develop emissions for non-VISTAS States, 

Canada, and Mexico for the 2002 annual modeling period. The Emissions Gatekeeper would 

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coordinate activities with the VISTAS emissions contractors and technical advisors to assure that 

data are provided in the correct format and that there are no holes in the emissions inventory. 

They would also coordinate with EPA and other RPOs to determine the best sources of data for 

non-VISTAS States as well as Canada and Mexico. Once data are received from the VISTAS 

emissions contractor the Emissions Gatekeeper would perform a preliminary QA/QC and 

immediately report back to VISTAS and the emissions contractor any issues that are uncovered. 

These results would be documented in the Emissions Gatekeeper report. 

Under this task we would also develop emissions inventories for non-VISTAS States, Canada, 

and Mexico consistent with the RPO data exchange protocol, using existing national or regional 

modeling inventories, state CERR submittals, EPA National Emissions Inventories, or other 

sources, as appropriate 

2.5.3.4 Subtask 3d: Emissions Modeling 

The objective of this Subtask is to generate base- and future-year CMAQ-ready gridded, hourly, 

speciated, three-dimensional emission inputs for 2002. The SMOKE emissions processing 

system would be used along with the 2002 MM5 data to process the 2002 emissions for VISTAS 

states from the VISTAS emissions contractor and emissions from the non-VISTAS states, 

Canada and Mexico provided under Subtask 3c Emissions Gatekeeper. CMAQ emission 

modeling files would be generated to support four rounds of emissions modeling runs using the 

2002 meteorological conditions: 

1. An initial 2002 Base Case run of CMAQ-ready emission inputs using VISTAS States 

emissions data received by January 31, 2004, and MM5 meteorological data received by 

March 31, 2002 would be ready by May 30, 2004. 

2. Revised 2002 Base Case and 2002 Typical Year emission runs using the emissions 

submitted by September 15, 2004 that would be ready by October 15, 2004. 

3. Future-year emission scenarios using 2002 meteorology and emissions data submitted by 

October 15, 2004 would be ready by November 15, 2004. 

The initial 2002 Base Case emissions modeling would use the existing Phase I SMOKE 

emissions modeling set up. For the revised 2002 Base Case, 2002 Typical Year and Future-Year 

emissions modeling, the existing Phase I SMOKE emissions modeling set up would be updated 

and enhanced as follows: 

• Process emissions with SMOKE version 2 

• Implement EPA’s new spatial surrogate distributions 

• Implement EPA’s revised PM speciation profiles and SCC cross-references 

• Implement revised temporal profiles as collected and converted from data provided 

by VISTAS’ emissions contractors or other sources 

Biogenic emissions will be processed using SMOKE and the 2002 MM5 day-specific 

temperatures and held constant for all the 2002 and future-year emission scenarios (i.e., the 

effects of climate change and land cover changes will not be accounted for in the future-year 

biogenic emission estimates). 

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On-road mobile sources comprise a major computational component of the SMOKE emissions 

modeling. If day-specific adjustments are required using day-of-week and daily MM5 

temperature estimates that would increase the SMOKE processing time considerably and 

potentially impact the schedule. 

Currently, other RPOs are modeling the motor vehicle emissions using average monthly 

temperature data, or by modeling one weekday, Saturday and Sunday from each quarter. To 

better represent the day-of the-week variability typical to motor vehicle emissions, and to make 

the best possible use of the meteorological data available, we propose to model one full week 

from each month of the annual episode, for a total of 84 episode days modeled. Note that this 

approach will allow us to expand the number of motor vehicle days modeled, if particular 

periods of the annual episode warrant additional refinement in the modeling inventory. 

Area source and non-road mobile source emissions will also be modeled for one week per 

month, using seasonal, monthly and day-of-week adjustments available in the current SMOKE 

configuration. 

EGU emissions will be supplied by the VISTAS emissions contractor in an annual file. To 

temporally allocate the EGU point sources, heat input data from the 2002 CEM datasets will be 

used to develop facility or unit-level temporal distributions. The day-specific and facility-specific 

temporal profiles will be used in conjunction with the emissions contractor supplied emissions 

data to calculate hourly EGU emissions by facility. 

For the 2002 Typical Year and Future-Year emission scenarios the VISTAS emissions contractor 

would provide average emissions for EGUs for the current baseline (2000-2004) and the futureyear baseline (2014-2018) periods. 

Day-specific emissions for fires (wildfires, prescribed burns and agricultural fires) may be 

provided by the VISTAS emissions contractor and would be used in the 2002 Base Case 

emissions scenario. If other temporally allocated fire emissions are provided, we will generate a 

set of actual 2002 fire-based temporal profiles and cross-references to allocate emissions to hours 

in the modeled episodes. Typical year emissions for fires would be provided by the VISTAS 

emissions contractor and would be used in both the 2002 Typical Year and Future-Year emission 

scenarios. 

Ammonia emissions will be modeled as provided by the emissions contractor. Supplemental 

ammonia modeling is not expected during the emissions modeling phase. 

Wind blown dust emissions (i.e., PM10 and PM2.5 emissions from wind erosion of natural 

geogenic sources (SCCs 2730100000 [total] and 2730100001 [dust devils]), will be excluded 

from the modeling files consistent with Phase I. 

Each round of emissions modeling would be documented in emission summary tables and 

PowerPoint presentations that would contain tables and graphs of the emissions and QA/QC 

summaries. A final report on the VISTAS Phase II emissions modeling would be prepared that 

focuses on the differences in emissions in the different emissions scenarios including 

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documentation of the changes in emissions from the 2002 Typical Year to Future-Year emissions 

scenario that would assist in the interpretation of the visibility projections. 

2.5.3.5 Subtask 3e: Future-Year Emissions Modeling for Three VISTAS Phase I Episodes 

Under this Subtask we would develop emissions modeling files for the initial future-year base 

case inventory for the July 2001 and Jan 2002 Phase I episodes. These inventories will be used 

in emissions sensitivity modeling analyses between May 2004 and September 2004. The same 

SMOKE emissions set up from the Phase II Subtask 3d would be used. 

2.5.3.6 Subtask 3f: Interim Future-Year Emissions Modeling using 2002 Meteorology 

Under this Subtask we would generate CMAQ-ready emission inputs for an interim future-year 

and the 2002 meteorological year. The VISTAS emissions contractors would provide interim 

future-year emissions estimates. 

2.5.3.7 Phase II Task 3 Deliverables

The VISTAS Phase II Task 3 deliverables are summarized in Table 2-10. 

Table 2-10. Phase II Task 3 2002 Data Preparation and Model Inputs task deliverables and due 

dates. 

Item Description Due Date 

1 Subtask 3a 2002 Air Quality and Deposition Database for Model 

Performance Evaluation 

04/30/04 

2 PowerPoint Presentation for Subtask 3b: “VISTAS 2002 MM5 Annual 

Run Meteorological Gatekeeper Evaluation.” Available at: 

http://pah.cert.ucr.edu/vistas/vistas2/ppt_files/Task3b_VISTAS_II%20_

met_gatekeeper_.ppt 

06/30/04 

3 PowerPoint Presentation for Subtask 3c VISTAS Initial Base Year 2002 

Emissions Inventory Preparation.” Available at: 

http://pah.cert.ucr.edu/vistas/vistas2/ppt_files/Task3c_Initial_Base_Year

_EI_Preparation.ppt 

08/08/04 

4 PowerPoint Presentation for Subtask 3c VISTAS Future Year Emissions 

Inventory Preparation.” Available at: 

http://pah.cert.ucr.edu/vistas/vistas2/ppt_files/Task3c_Initial_Future_Ye

ar_EI_Preparation.ppt 

08/08/04 

5 Subtask 3d Initial 2002 Base Case CMAQ-ready Emission Inputs 05/30/04 

6 Subtask 3d Revised and Typical 2002 CMAQ-ready Emission Inputs 10/15/04 

7 Subtask 3d Future-Year (2018) CMAQ-ready Emission Inputs for Two 

Scenarios 

12/15/04 

8 Subtask 3e Future-Year (2018) CMAQ-ready Emission Inputs for Two 

Phase I Episodes 

06/15/04 

9 Subtask 3f Interim Future-Year (2009) CMAQ-ready Emission Inputs 12/15/04 

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2.5.4 Phase II Task 4: 2002 Annual CMAQ Modeling 

Under Phase II Task 4 we would apply the CMAQ model using Initial and Revised 2002 Actual 

Base Case emissions and other inputs and perform a model performance evaluation on the 

results. 

2.5.4.1 Subtask 4a: Initial Base Case and Model Performance Evaluation 

A preliminary 2002 CMAQ Actual Base Case simulation would be performed using the initial 

2002 inventory for VISTAS and Non-VISTAS states, Canada and Mexico that are to be 

delivered to modeling team by January 31, 2004. After subjecting the initial 2002 emissions to 

the Emissions Gatekeeper quality checks and QA/QC (Subtask 3c), CMAQ-ready emissions 

would be generated using the initial emissions for 2002 (Subtask 3d). The primary objective of 

this initial CMAQ run is to set up and streamline the modeling system and approach and obtain a 

preliminary model performance evaluation for the 2002 annual period. The focus of the analysis 

will be on model performance diagnostics and experience in running the annual simulations to 

optimize model performance both in terms of ability to estimate fine particulate matter in the 

southeastern US as well as optimize the ability of the modeling centers to perform 2002 annual 

CMAQ runs. 

Once the initial CMAQ base case simulation is generated, it will be subjected to a model 

performance evaluation. In Phase II multiple approaches will be utilized in the evaluation 

process: 

• Alpine will use their MAPS software to generate performance statistics and graphical 

displays by network and by subregion. The MAPS software generated some 

performance measures not supported by other software (e.g., spatial average time 

series) and once set up can easily generate performance measures and displays by 

subregion. 

• Alpine will also apply the UCR statistical performance package that was used in 

Phase I that includes model performance metrics, scatter plots and time series plots. 

This package has been extended to include PAVE spatial maps with superimposed 

observation to provide spatial information on model performance. 

• UCR will help analyze and interpret the model performance results and post them on 

the VISTAS modeling website. 

• ENVIRON will evaluate the results using techniques they developed for WRAP that 

focus on model performance at Class I areas for the 20% Best and 20% Worst 

visibility days that are the data used to project future-year visibility improvements. 

This performance would include predicted and observed stacked bar charts of 

extinction showing the contributions of each of the for the 7 components of extinction 

(SO4, NO3, EC, OC, Soil, CM and Rayleigh) of extinction averaged and separately 

for the 20% Best/Worst days. Days from then 20% Best/Worst days and Class I areas 

where the modeling results deviate greatly from the observed values would be flagged 

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for further analysis into model performance and possible exclusion for use in the 

visibility projections (i.e., calculating RRFs). 

Use of multiple MPE approaches will allow the quick identification of potential problems in the 

model estimates or the model performance evaluation software. The results would be shared 

among the group and with VISTAS. The operational model performance evaluation would be 

conducted using the same “routine” ambient databases as used in Phase I (e.g., IMPROVE, 

CASTNet, AQS, SEARCH, STN and SEARCH). 

Because the initial emissions may undergo significant changes, limited diagnostic sensitivity 

tests would be conducted using the initial 2002 CMAQ database. The limited sensitivity tests 

would be aimed at identifying and rectifying specific performance issues of the model that we 

don’t believe will be corrected by updated emissions. As in the VISTAS Phase I modeling, the 

sensitivity tests will be flexible and opportunistic to quickly identify and resolve areas of highest 

importance. However, the number of sensitivity tests will be limited by available funding and 

time constraints. 

2.5.4.2 Subtask 4b: Revised Base Case Simulation 

A 2002 CMAQ simulation would be conducted using the revised 2002 Base Case emissions 

inventory that is expected to be received from the VISTAS emissions contractor by September 

15, 2004. Several components of 2002 initial CMAQ set up could change including, but not 

limited to, emissions, meteorology, boundary conditions, CMAQ update, CMAQ chemical 

module. For example, if a 2002 GEOS-CHEM simulation is performed, then the revised BCs 

from Optional Task 13 would be used in the revised base case simulation. The revised 2002 

CMAQ simulation would be run using the “best configuration” identified in Subtask 4a. The 

results would be transferred to each of the modeling centers that would conduct their own 

operational MPE as was done under Subtask 4a. We have budgeted 8 annual 36 km and 4 

annual 12 km sensitivity simulations under this task to investigate alternative configurations, 

options and updates on model performance. The results would be documented in a draft final 

report submitted to VISTAS. 

2.5.4.3 Subtask 4c: Typical Year Emissions Simulation 

EPA guidance recommends using models in a relative sense to project future year visibility 

through relative reduction factors (RRFs). Thus, for projecting changes in visibility, the currentyear base case and future-year scenarios must be consistent. Thus, in this task typical emissions 

for fires and EGUs will be used for the 2002 Typical Year emissions scenario, instead of the 

episodic specific emissions used in the 2002 Base Case simulation. The 2002 typical year 

emissions generated under Subtask 3d would be used in this simulation. The results would be 

subjected to a QA/QC, compared with the 2002 Base Case simulation and a cursory evaluation 

would be conducted. 

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2.5.4.4 Subtask 4d: Future-Year Modeling for Two Scenarios 

Using the CMAQ-ready emissions for the two future-year emission scenarios prepared under 

Subtask 3d that would be ready by November 15, 2004 and December 15, 2004, we would 

perform the two future-year CMAQ simulations under this subtask. New future-year boundary 

conditions (BCs) may be used depending on the availability of data. The future-year CMAQ 

results for the two scenarios and the CMAQ results for the 2002 Typical Year scenario would be 

used to project visibility improvements at Class I areas using EPA guidance. 

2.5.4.5 Subtask 4e: Interim Future-Year using 2002 Database 

Using the CMAQ-ready emissions for the interim future-year emission scenario prepared under 

Subtask 3f that would be ready by December 15, 2004, we would perform the interim future-year 

CMAQ simulation under this subtask. New future-year boundary conditions (BCs) may be used 

depending on the availability of data. The future-year CMAQ results for the interim future-year 

scenario and the CMAQ results for the 2002 Typical Year scenario would be used to project 

visibility improvements at Class I areas using EPA guidance. 

2.5.4.6 Summary of Phase II Task 4 Deliverables 

Table 2-11 summarizes the VISTAS Phase II Task 4 deliverables and due dates. 

Table 2-11. Phase II Task 4 2002 CMAQ Modeling task deliverables and due dates. 

Item Description 

Due 

Date 

1 PowerPoint Presentation for Subtask 4a: “Initial Vistas 2002 CMAQ Run, 

Analysis of 36 km Performance for PM.” Presented at July 27, 2004 

VISTAS TAWG Conference Call. Available at: 

 http://pah.cert.ucr.edu/vistas/vistas2/reports/2002_CMAQ_initial.ppt 

07/27/04

2 PowerPoint Presentation for Subtask 4a: “Initial VISTAS 2002 CMAQ Run: 

36/12 km Diagnostic MPE” Presented at July 27, 2004 VISTAS TAWG 

Conference Call. Available at: 

 http://pah.cert.ucr.edu/vistas/vistas2/reports/2002_CMAQ_initial_AG.ppt 

07/27/04

3 Revised Draft Final Report for Subtask 4a: “VISTAS Phase II Emissions 

and Air Quality Modeling -- Task 4a Report: Evaluation of the Initial 

CMAQ 2002 Annual Simulation.” Dated September 27, 2004. 

09/27/04

4 PowerPoint Presentation for Subtask 4a: “Initial CMAQ Diagnostic MPE 

for 2002: VISTAS Task 4a Results.” Presented at VISTAS September 21-

22, 2004 TAWG meeting in Atlanta, Georgia. Available at: 

 files/Sept_2004_tawg/2002_CMAQ%20Diagnostic%20MPE_TWT.ppt 

09/21/04

5 PowerPoint Presentation for Subtask 4a: “Initial VISTAS Phase II 2002 

CMAQ Operational Model Performance Evaluation.” Presented at VISTAS 

September 21-22, 2004 TAWG meeting in Atlanta, Georgia. Available at: 

http://pah.cert.ucr.edu/vistas/vistas2/docs.shtml

09/21/04

6 PowerPoint Presentation for Subtask 4a on diagnostic analysis of the Initial 11/12/04

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Item Description 

Due 

Date 

2002 CMAQ Base Case simulation to identify OC and NO3 performance 

issues. 

7 PowerPoint Presentation for Subtask 4b on Revised 2002 XCMAQ Base 

Case Simulation and Model Performance Evaluation 

11/30/04

8 Subtask 4b Draft Report on Revised 2002 CMAQ Base Case simulation and 

model performance evaluation 

12/15/04

9 Subtask 4b Report on Model Sensitivity Tests 01/15/05

10 PowerPoint Presentation on Subtask 4c 2002 Typical Base Case simulation 12/31/04

11 Subtask 4d Draft Report on Future-Year (2018) Base Case modeling 01/31/04

12 PowerPoint Presentation on Subtask 4e Interim Future-Year modeling 01/31/05

2.5.5 Phase II Task 5: Episodic Modeling 

The VISTAS Phase II plan includes potential provisions for performing episodic modeling if 

needed. In particular, additional episodic modeling may be carried out to: (1) capture 

meteorological conditions for Worst 20% or Best 20% visibility days at Class I areas that did not 

occur during the 2002 annual modeling period; and (2) to obtain modeling periods during 2003 

when the FOCUS sites were operating that contain enhanced speciated PM measurements. The 

Phase II Task 5 Episodic Modeling work effort is currently not funded. Given that the 2003 year 

was fairly wet and atypical and the 2002 annual modeling year appears to capture most of the 

meteorological conditions, additional episodic modeling may not be carried out so is not 

addressed in this QAPP. 

2.5.6 Phase II Task 6: Data Management 

2.5.6.1 Subtask 6a: VISTAS Modeling Website 

Under this Subtask we would maintain the VISTAS Modeling Website including posting 

modeling input and output files, reports, interpretation of results, and other documents including 

Task Reports and PowerPoint Presentations presented during meetings and conference calls. 

2.5.6.2 Subtask 6b: Data Transfer, Storage and Retrieval 

Under this Subtask we would archive and store key model inputs and outputs and make them 

available to others. Storage of model inputs and outputs for up to 6 annual runs plus episodic 

runs or optional tasks to be defined. A firewire or IDE drive(s) of the key model inputs would be 

provided to VISTAS who could distribute it to states, stakeholders and others as desired (i.e., 

technology transfer). We would also perform data requests as directed by VISTAS under this 

Subtask. 

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2.5.6.3 Phase II Task 6 Data Management Deliverables 

Table 2-12 summarizes the deliverables and schedule for the Phase II Task 6 Data Management. 

The VISTAS Phase II modeling website would be operated and maintained continuously during 

the 2004-2005. We expect the Initial and Revised 2002 CMAQ databases to be delivered to 

VISTAS in October and December 2004, respectively. Finally, as directed by VISTAS we 

would provide additional data to others as requested. 

Table 2-12. Phase II Task 6 Data Management task deliverables and schedule. 

Item Description Due Date 

1 VISTAS Phase II Modeling Website. Available at: 

http://pah.cert.ucr.edu/vistas/vistas2/index.shtml

2004-2005 

2 Firewire disks of Initial 2002 CMAQ annual modeling databases 10/15/04 

3 Firewire disks of Revised 2002 CMAQ annual modeling databases 12/31/04 

4 Disks, CD, DVD, ftp files and e-mail files of data transfer as directed by 

VISTAS 

2004-2005 

2.5.7 Phase II Task 7: Emission Reduction Sensitivity Simulations using CB4 and SAPRC 

Chemistry and 2 Phase I Episodes

The objective of this optional task is to investigate the sensitivity of estimated PM concentrations 

to emissions reductions using the CB4 and SAPRC99 chemical mechanisms. If significant 

differences exist and there are reasons to believe that the SAPRC99 response may be more 

correct, then the revised 2002 Base Case modeling starting in September would be performed 

using the SAPRC99 chemistry. 

The CB4 and SAPRC99 emission reductions sensitivity tests would be performed using the 

January 2002 (winter) and July 2001 (summer) episodes. We would perform 30% emission 

reductions across all source categories and across the entire modeling domain for the 36 km grid 

for the following five precursors: 

• NOx 

• SO2 

• VOC 

• NH3 

• NOx+NH3 

With 2 episodes and 2 chemical mechanisms this results in 10 total CMAQ 36 km simulations. 

We would also perform two corroborative emissions reductions sensitivity simulations using the 

CAMx model for the July 2001 episode and 36 km grid. Table 2-13 summarizes the deliverables 

under Phase I Task 7. 

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Table 2-13. Phase II Task 7 CB4/SAPRC Sensitivity Modeling task deliverables and due dates. 

Item Description Due Date 

1 PowerPoint Presentation for Task 7: “VISTAS Phase II Task 7 Update: 

CMAQ Version 4.4beta CB4/SAPRC99 Comparisons” presented at July 27, 

2004 TAWG Conference Call. Available at: 

 http://pah.cert.ucr.edu/vistas/vistas2/reports/PhaseII_Task7_Update.ppt 

07/27/04 

2 PowerPoint Presentation for Task 7: “VISTAS Phase II Task 7 Results: 

CMAQ Version 4.4beta CB4/SAPRC99 Comparisons” presented at 

September 2, 2004 TAWG Conference Call. Available at: 

http://pah.cert.ucr.edu/vistas/vistas2/ppt_files/Task7_VISTAS_PhaseII_Tas

k7_CB4-SAPRC_Sep02_2004.ppt 

09/02/04 

3 PowerPoint Presentation for Task 7: “VISTAS Phase II Task 7 Results: 

CB4/SAPRC99 Comparisons for Urban Sites” presented at September 14, 

2004 TAWG Conference Call. Available at: 

http://pah.cert.ucr.edu/vistas/vistas2/ppt_files/Task7_VISTAS_PhaseII_CB

4-SAPRC_Urban_Sep14_2004.ppt 

09/14/04 

2.5.8 Phase II Task 10: Journal Paper on VISTAS Phase I Modeling 

The objective of this task is to write and submit the results of the VISTAS Phase I modeling 

results to a peer-review journal. An outline for a journal article on the VISTAS Phase I 

modeling would be prepared and distributed to VISTAS. Based on comments the outline would 

be updated and a draft paper written documenting the VISTAS Phase I modeling results. The 

draft paper would be distributed to VISTAS and updated based on their comments. In 

consultation with VISTAS a Journal would be selected and the paper submitted to the Journal for 

publication. The paper would be updated as needed to address comments of the Journal peerreviewers and a final manuscript submitted to the Journal for publication. 

Table 2-14. Phase II Task 10 Phase I Journal Article task deliverables and due dates. 

Item Description Due Date 

1 Draft Journal Article on VISTAS Phase I Modeling for VISTAS review 11/30/04 

2 Journal Article for Submission 12/31/04 

2.5.9 Phase II Task 13: Analysis and Processing of 2002 GEOS-CHEM Data 

Under this task we would process output from a 2002 GEOS-CHEM global climate model 

simulation performed by Harvard University to generate 2002 day-specific 3-hourly CMAQ 

boundary condition (BC) inputs for 2002. 

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Table 2-15. Phase II Task 13 2002 GEOS-CHEM Boundary Condition Processing task deliverables 

and due dates. 

Item Description Due Date 

1 PowerPoint Presentation: “Documentation and Evaluation of the 2002 

GEOS-CHEM Simulation.” Presented during VISTAS TAWG October 4, 

2004 conference call. Available at: 

http://pah.cert.ucr.edu/vistas/vistas2/ppt_files/2002_GEOS_CHEM_10040

4.ppt 

10/01/04 

2 CMAQ-ready Boundary Condition (BC) input files 10/15/04 

3.0 PROJECT MANAGEMENT 

3.1 Project Organization 

This project is conducted by the ENVIRON International Corporation, Alpine Geophysics, LLC 

(Alpine), and the University of California at Riverside (UCR), with input from the VISTAS 

Technical Analysis Workgroup (TAWG). Organizational commitment is an essential element for 

developing and implementing a successful research project. Ralph Morris of ENVIRON would 

be the VISTAS Emissions and Air Quality Modeling Project Manager (PM). The VISTAS 

Phase II Modeling Team has three Co-Principal Investigators that coordinate activities at each of 

the three modeling centers, Ralph Morris of ENVIRON, T.W. Tesche of Alpine and Gail 

Tonnesen at UCR. The PM and three Co-PIs are kept apprised of all project activities, from 

identifying the need to develop sound experimental and project designs to delivering reports. 

Commitments to research and project activities, such as those described in this QAPP are made 

only after the activities are thoroughly reviewed and approved by the PM and Co-PIs and 

VISTAS TAWG. Figure 3-1 presents the organizational chart that shows the lines of 

responsibility and information flow for activities under this project. Table 3-1 lists the project 

responsibilities for participants in the VISTAS Emissions and Air Quality Modeling study, with 

more details on their roles provided next. 

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 Southeastern States Air 

Resources Managers, Inc. 

(Contracting Agency) 

VISTAS 

Technical Analysis 

Workgroup (TAWG) 

Chairperson: 

Sheila Holman, North 

Carolina 

VISTAS 

Contracting Officer: 

Patricia Brewer, VISTAS 

VISTAS 

Technical Contact: 

James Boylan, Georgia 

Subcontractor 

Alpine Geophysics 

Co-Principal Investigator 

T. W. Tesche 

Staff 

Prime Contractor 

ENVIRON 

Project Manager and CoPrincipal Investigator 

Ralph Morris 

Staff 

Subcontractor 

UC Riverside 

Co-Principal Investigator 

Gail Tonnesen 

Staff 

Figure 3-1. VISTAS Emissions and Air Quality Modeling Project Organizational Chart. 

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Table 3-1. VISTAS Phase II Emissions and Air Quality Modeling project participants and 

contacts. 

Person & Role Affiliation/Address Contact Information 

Patricia Brewer 

(Contracting Officer) 

VISTAS Technical Coordinator 

2090 US Highway 70 

Asheville, NC 28778 

(828) 296-4500 

(Fax) (828) 299-7043 

pat.brewer@ncmail.net

James Boylan 

(Technical Contact for 

Emissions & AQ 

Modeling) 

Georgia DNR 

Air Protection Branch 

4244 International Pkwy, Ste 120 

Atlanta, GA 30354-3906 

(404) 362-4851 

(Fax) (404) 363-7100 

James_Boylan@mail.dnr.state.ga.us

Michael Abraczinskas 

(Technical Contact for 

MM5 Modeling) 

North Carolina DENR 

1641 Mail Service Center 

Raleigh, NC 27699-1641

(919) 715-3743 

Michael.Abraczinskas@ncmail.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

T.W Tesche 

(Co-Principal 

Investigator) 

Alpine Geophysics, LLC 

3479 Reeves Drive 

Ft. Wright, KY 41017 

(859) 341-7502 

(Fax) (859) 341-7502 

twt@iac.net

Gail Tonnesen 

(Co-Principal 

Investigator) 

UC Riverside 

CE-CERT 

1084 Columbia Avenue 

Riverside, CA 92507 

(951) 781-5676 

(Fax) (909) 781-5790 

tonnesen@cert.ucr.edu

Key ENVIRON Participants 

Bonyoung Koo ENVIRON 

101 Rowland Way 

Novato, CA 94945 

(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 Alpine Geophysics Participants 

Dennis McNally Alpine Geophysics, LLC 

7341 Poppy Way 

Arvada, CO 80007 

(303) 421-2211 

(Fax) (303) 421-9553 

dem@alpinegeophysics.com

Cyndi Loomis Alpine Geophysics, LLC 

7341 Poppy Way 

Arvada, CO 80007 

(303) 421-2211 

(Fax) (303) 421-9553 

cfl@alpinegeophysics.com

Greg Stella Alpine Geophysics, LLC 

387 Pollard Mine Road 

Burnsville, NC 28714 

(828) 675-9045 

gms@alpinegeophysics.com

Key UCR CE-CERT Participants 

Zion Wang UC Riverside 

CE-CERT 

1084 Columbia Avenue 

Riverside, CA 92507 

(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

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3.1.1 ENVIRON Project Manager and Co-Principal Investigator 

Mr. Ralph Morris of ENVIRON is the Project Manager (PM) and Co-Principal Investigator (CoPI) for the VISTAS 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 VISTAS TAWG are addressed. The PM is responsible for the overall conduct 

of the project, experimental design, reporting of the results, and interacting with the client, 

consultants, and project staff. The specific responsibilities of the PM include, but are not 

necessarily limited to, the following: 

• Directs and coordinates the activities of the project team and computer facilities to 

conduct the test program 

• Ensures that this QAPP and the Modeling Protocol are followed during the course of the 

project

• Guides the overall approach for performing modeling evaluations

• Keeps current on project status and delivers progress reports 

• Conducts initial modeling or analysis of experiments to determine if inconsistencies or 

unexpected results suggest possible experimental or measurement problems 

• Evaluates overall data quality, characterization results, and overall system performance 

with regard to meeting 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 any issues raised in assessment reports and 

initiates corrective actions as necessary 

• Serve 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

• Establishes a Subcontracts with Alpine and UCR to perform the work, and adhere to the 

terms and conditions of that contract 

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

the Work Plan 

• Provides information to assist the VISTAS TAWG in achieving its goals as stated in its 

Work Plan and Strategic Plan 

• Develops individual test protocols and reports as directed 

• Analyzes modeling data and provides assessment reports 

• Supports the Principal Investigator and VISTAS in responding to any issues raised in 

assessment reports 

3.1.2 ENVIRON, Alpine and UCR Co-Principal Investigators 

The three Co-Principal Investigators of Ralph Morris, T.W. Tesche and Gail Tonnesen perform 

the following functions: 

• Directs and coordinates the day-to-day project activities of the project team and computer 

facilities to conduct the test program 

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• Ensures that this QAPP and Modeling Protocol are followed during the course of the 

project

• Manages the activities in each of the three modeling centers

• Direct supervises personnel working on this project 

• Guides the approach for performing modeling evaluations following the direction of the 

Project Manager

• Keeps current on project status and delivers information to Project Manager for progress 

reports 

• Conducts initial modeling or analysis of experiments to determine if inconsistencies or 

unexpected results suggest possible experimental or measurement problems 

• Evaluates overall data quality, characterization results, and overall system performance 

with regard to meeting project objectives 

• Reviews and delivers data and sections for integration into modeling and assessment 

reports 

• With the Project Manager, 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 each modeling center responding to any issues raised in 

assessment reports and initiates corrective actions as necessary with the Project Manager 

• 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 

• Develops individual test protocols and reports as directed 

• Analyzes modeling data and provides assessment reports 

3.1.3 VISTAS Contracting Officer 

The VISTAS Contracting Officer (Patricia Brewer) serves as the primary contact between the 

Emissions and Air Quality Modeling Team and VISTAS and performs the following functions: 

• Provides day-to-day oversight of VISTAS Phase II Emissions and Air Quality Modeling 

Team activities 

• Works with the Project Manager, Co-Principal Investigators, TAWG, States, Tribes 

oversight groups, collaborators, Stakeholders, etc. in assuring that the interests and 

concerns of all of the VISTAS participants are appropriately represented as project 

priorities are developed or modified due to external input 

• Assists in organizing and conducting meetings, conference calls, and workshops where 

this and related projects are discussed 

3.1.4 VISTAS Technical Contact 

The VISTAS Technical Contact (James Boylan) for the Emissions and Air Quality Modeling 

Team works with the VISTAS Contacting Officer in the day-to-day oversight and management 

of the modeling analysis: 

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• Provides day-to-day oversight of VISTAS Phase II Emissions and Air Quality Modeling 

Team activities 

• Works with the VISTAS Contracting Officer, Project Manager, and Co-Principal 

Investigators to assure that the study is being carried out in a technically correct fashion 

following the QAPP and Modeling Protocol 

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

team. 

3.1.5 VISTAS Technical Analysis Workgroup (TAWG) 

The Technical Analysis Workgroup is responsible for overseeing the regional haze and fine 

particulate modeling that will be required for the State Implementation Plans (SIP's). This 

workgroup provides both emissions inventory and modeling technical support to VISTAS. 

Emissions Inventory efforts include the development of emissions inventories and forecasts to be 

utilized in VISTAS modeling efforts. Modeling efforts will include identification, evaluation, 

and application of air quality modeling tools (including meteorological and air quality models) to 

quantify the effects of emission management options upon air quality in Class I areas in the 

VISTAS region. Specific activities of the TAWG include:

• Oversees the activities of the VISTAS Emissions and Air Quality Modeling Team 

through the Contracting Officer, conference calls, and periodic in-person meetings and 

workshops 

• Provides the Contracting Officer, technical Contact, Project Manager and Co-Principal 

Investigators input on the research plans and their ability to meet the needs of the various 

stakeholders relevant to the overall objectives of the project 

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

review 

• Makes the Project Manager and 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 VISTAS Phase I and II Tasks are presented at the end of each Task 

Description in Sections 2.4 and 2.5. 

3.3 Personnel Qualifications and Training 

General education of all project personnel lays the foundation for successful project 

implementation. It is not intended to provide detailed and specific knowledge of all components 

of the project, but it promotes an understanding of the nature of the overall project goals, 

ensuring that all personnel understand the part they are to play in the project. The members of 

this project team include resident experts in emissions, meteorological and air quality model 

development and operations. 

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

member must be familiar with the content of this QAPP and all documents presented in Section 

8.0, thus obtaining a project overview, including information on all functions of the modeling 

systems, from experimental design, objectives, and data validation and reporting. Where 

applicable, project personnel must be familiar with the SOPs applicable to their areas of 

responsibility. In addition, if major revisions or enhancements are made to the QAPP and/or 

SOPs, all affected individuals must review those revisions at that time. 

3.4 Communications Plan 

The VISTAS Emissions and Air Quality Modeling Team members, other VISTAS Contractors 

and VISTAS representatives are linked by e-mail correspondence, and also use this as a means to 

communicate and exchange data, either as e-mail attachments, website or by network-accessible 

files. A considerable amount of information is exchanged by e-mail within this project. The 

VISTAS Modeling Team maintains four listservs to distribute information to different VISTAS 

groups as indicated in Table 3-2. 

Table 3-2. VISTAS listservs maintained by the Emissions and Air Quality Modeling Team. 

Listserv Purpose 

Vistas-all@cert.ucr.edu Contacts all participants including Modeling Team, VISTAS 

TAWG and Stakeholders 

Vistas-modeling@cert.ucr.edu Contacts Modeling team and VISTAS TAWG Modeling 

Contacts 

Vistas-emissions@cert.ucr.edu Contacts emissions staff in the Modeling team and emissions 

people in the VISTAS TAWG 

Vistas-met@cert.ucr.edu Contacts meteorology staff in the Modeling team and 

meteorology people in the VISTAS TAWG 

The Modeling Team members and VISTAS TAWG hold periodic conference calls and meetings 

to report results, discuss project status, and modify work plans as necessary. Unscheduled 

meetings or conference calls are also held concerning specific issues as the needs arise. In 

addition, periodic project meetings and conference calls are held. In these meetings detailed 

technical information is exchanged, project status is discussed, and project direction is assessed. 

Written progress reports on the VISTAS Emissions and Air Quality Modeling Team activities 

are submitted to the VISTAS Contracting Officer on a monthly basis. These reports summarize 

project progress, results to date, problems encountered and necessary action items, and plans for 

the upcoming reporting period. 

All modeling results, quality assurance reports, and related documents are posted on the project 

web site, as described in Section 3.5. 

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3.5 Documentation and Records 

After the project tasks in Sections 2.4 and 2.5 that require deliverables are completed, the 

ensuing documents are posted on the VISTAS Modeling Phase I and II project websites at: 

http://pah.cert.ucr.edu/vistas/

http://pah.cert.ucr.edu/vistas/vistas2/

In addition, during the project, VISTAS is provided updates by e-mail or telephone. 

Document control is the system that ensures that only the latest revisions of the defined 

documents are used by the Modeling Team personnel engaging in project activities. 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 identified by revision number and/or 

date), and electronic storage of documents by date so that the latest versions is clearly 

identifiable. Such documents are controlled documents, and can be revised only by the 

personnel 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, 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, meteorology and air quality modeling is performed on computer equipment 

located at either the ENVIRON, Alpine 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 configuration of personal computers, workstations and 

printers includes Linux and Window PCs, SGI, SUN and DEC Unix workstations and a Linux 

Cluster all connected by a fast network with disk access to RAID systems. The ENVIRON 

computer center includes the very latest computing technology including both OMP (shared 

memory) and MPI (cluster) multi-processing capability. All staff also have their own state-ofWV Regional Haze SIP Appendix C.2 - 46
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the-art PCs and have access to all workstations at all times, there are no problems with computer 

resource availability. ENVIRON’s high speed Linux and UNIX computing environment includes 

workstations from three top suppliers, Sun, Digital Equipment Corporation (DEC) and Silicon 

Graphics Incorporated (SGI). ENVIRON also uses Linux PC workstations with several different 

distributions of the Linux OS (e.g., Red Hat, Debian, Mandrake) and these exceed the 

performance of fast UNIX workstations. Using workstations from several suppliers allows us to 

develop and test model codes on multiple 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 using the Athlon MP2200 chip set with gigabit 

Ethernet that is configured as two 8 node MPI multiprocessing platforms. 

4.1.2 Alpine Geophysics Modeling Center Hardware 

Alpine Geophysics' computing facilities consist of SUN Microsystems SPARCstation computers 

and a very powerful array 10 multiprocessor Linux-based workstations. The aggregate network 

has over 7.3 Gbytes of memory and 2500 Gbytes of aggregate disk space with over 2000 Gbytes 

of SCSI and IDE Raid-5 protected space. All client data is stored on at least one RAID-5 

protected disk array. To further protect client data, two of our main servers backup their disk 

drives on a weekly basis to a second server that is physically disconnected from the power 

supply when not doing an active transfer. This way a catastrophic power failure will not 

compromise the ability for Alpine Geophysics to deliver. 

To efficiently share network resources, 100-BaseT fast ethernet switches interconnect the 

computers within each office. Additionally, the Arvada based computers have both the Parallel 

Virtual Machine (PVM) software package for computation on multiple nodes on the network and 

Open MP capabilities for shared memory multiprocessing within each computer. For the 

majority of model simulations, using a job level parallelization, where individual periods of a 

simulation are put onto each computational node, maximizes network throughput. However, the 

computational network also has the ability to share the multi-Gbyte memory and 20 processors 

on a single MM5 model simulation. 

A key feature of the AG computer network is the ability for AG to add computational resources 

quickly and cost effectively. Alpine scientists have been using Linux and Unix for 

meteorological and air quality modeling for over 16 years. This knowledge base, along with 

existing relationships with hardware vendors, software vendors, and system specialists, enable 

AG to meet the computational requirements of the VISTAS modeling study. 

4.1.3 UCR Modeling Center Hardware

The UCR computer laboratory is designed to process large data sets for air quality modeling. It 

includes 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 2.2GHz cluster and an 8 CPU 64-bit Opteron 2GHz 

cluster. The data storage system includes over 23 TB of disk space configured as RAID5 disk 

systems. All computers and disk systems are networked using high speed Gigabit Ethernet for 

efficient simulation and analysis of large datasets. To provide maximum data security the 

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systems are located behind the UCR firewall and an additional firewall is used internally within 

the laboratory so that only project team members 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/archiving system include 8mm tape 

drives and DLT and Super DLT auto loading cartridge system capable of performing unattended 

archive/backups of over 1 TB (uncompressed). Key disk systems have hot-swappable hard drives 

with stand-by spare drives and redundant power supplies. The compute clusters and disk systems 

are located in a locked, secure room with a dedicated climate control system and with backup air 

conditioning. UCR also uses the computer laboratory for air pollution modeling classes for 

graduate students and for professional staff from State and Tribal 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. 

4.1.4 Backup Procedures 

Different back-up procedures are applied to three different sets of computers that include (1) file 

servers; (2) user desktop Windows PCs; and (3) RAID5 disks storage systems. 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 computer. In addition, 

incremental backups are periodically 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 RAID5 disk systems. Because of the large volume 

of data (over 23 TB) it cannot be routinely backed 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. Therefore, only critical model input data are 

backed-up. One 2 TB RAID5 disk system is reserved for back up of critical project data. 

Back-ups are performed weekly. In addition, critical project input data is archived to IDE 

drives, firewire drives or DLT tape. 

All incoming electronic mail receives virus scanning using commercial software (Norton or 

McAffee Anti-Virus), which is updated routinely. Windows PC receives automated, weekly 

scans for viruses. 

Three types of software are used in the project: (1) commercial software for word processing, 

project management, communications, and commercial software compilers; (2) compilers and 

computer operating systems publicly available through the GNU Public License (GPL) 

distribution channels; and (3) custom software used in computer simulation modeling and data 

analysis. All commercial software used in the VISTAS modeling is purchased with licenses and 

is installed and tested as specified by the publisher. Commercial compilers include Portland 

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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 

researchers 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 VISTAS Emissions and Air Quality Modeling are provided by other 

VISTAS contractors with the data subjected to quality assurance and quality control (QA/QC) 

prior to delivery to the Modeling team. In addition the Modeling Team have formed data 

“Gatekeeper” functions to further QA/QC provided to the Modeling Team prior to its use. 

Below we discuss the data used in the modeling and the function of the Gatekeeper roles, which 

are described in detail in Section 2.2.2.1: 

Air Quality Gatekeeper: The Air Quality Gatekeeper downloads air quality data from the 

VIEWS, SEARCH and AIRS websites and subjects it to QA/QC. The data are 

reformatted and processed for use in the modeling. 

Meteorological Gatekeeper: The Meteorological Gatekeeper evaluates the MM5 data 

provided by the VISTAS Meteorological Modeling Contractor (BAMS), subjects it to 

QA/QC and processes it for input to the CMAQ/CAMx air quality models. 

Emissions Gatekeeper: The Emissions Gatekeeper receives emissions data from the 

VISTAS Emissions Contractor (MACTEC), subjects them to a comprehensive QA/QC 

and rejects data that doesn’t pass the QA/QC and reformats the data for input into the 

SMOKE emissions model. 

Data Management Gatekeeper: The Data Management Gatekeeper maintains the project 

website, keeps back ups of data, responds to data requests and updates reports and files 

on the website. 

5.0 EMISSIONS MODELING 

The project objective is to integrate mezoscale emissions 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 and Section 6.0 addresses 

meteorological modeling as they are applied to this project. 

The VISTAS Modeling Team uses the Sparse Matrix Operator Kernel Emissions (SMOKE) 

emissions model to model the anthropogenic and biogenic gas and particulate matter (PM) 

emissions needed for regional haze modeling. A detailed quality assurance protocol for utilizing 

SMOKE has been prepared as part of the Phase II Modeling Protocol (ENVIRON, 2004a) and is 

summarized in this section. 

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The purpose of SMOKE is to convert the resolution of the emission inventory data to the 

resolution needed by an air quality model. Emission 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 perhaps model layer), and for each model species. 

Consequently, emissions processing for this project involve transformation of emission inventory 

data by temporal allocation, chemical speciation, spatial allocation, and layer assignment, to 

achieve the input requirements of the air quality model. 

SMOKE formulates emissions modeling in terms of sparse matrix operations. Figure 5-1 shows 

an example of how the matrix approach organizes the emissions processing steps for 

anthropogenic emissions, 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 category in SMOKE, but does include the major processing steps listed above, except the 

layer assignment. Specifically, the inventory emissions are arranged as a vector of emissions, 

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, and temporal 

factors to the vector of emissions. In many cases, these matrices are independent from 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 

control, speciation, and gridding matrices to create model-ready emissions. 

Merge Import

Inventory

Temporal

Allocation

Speciation

Gridding

Inventory

Vectors

Controls

Hourly

Emissions

Speciation

Matrix

Gridding

Matrix

Control

Matrix

Model-ready

Emissions

Program File Shows input or output

Merge Import

Inventory

Temporal

Allocation

Speciation

Gridding

Inventory

Vectors

Controls

Hourly

Emissions

Speciation

Matrix

Gridding

Matrix

Control

Matrix

Model-ready

Emissions

Program File Shows input or output

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

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5.1 Quality Assurance Components of Emissions Modeling 

The quality assurance (QA) 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 happen; it is the process 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. Scrutiny of the I/O using standard statistical analyses can reveal 

problems in the data and/or the model setup. Using a standard approach for analyzing emissions 

model I/O establishes reference points 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 configuration 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 settings, compile options, and other system-related 

parameters must then occur and be documented prior to producing any model results. Archiving 

the model installation at set “freeze points” in the 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 model results in the future and the ability to revert back to a 

previous configuration or installation after the model has been revised 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 the 

model installation and configuration 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 the data entering and exiting the 

SMOKE modeling process meet a predetermined quality 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 emissions inventory and SMOKE input files on the front end of the 

modeling process, and to the SMOKE output files at the back end. A gatekeeper (or gatekeeping 

team) is responsible for performing a series of reasonableness checks on both the input and 

output data streams. Outside reviewers are emissions experts who are not part of the VISTAS 

Modeling Team. They periodically review the entire process—the emissions data, the modeling, 

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and the QA steps taken—using their judgment as experts to decide what to review and how to 

review it. 

5.1.4 Documentation 

Documentation, a component that is common to all of the other three QA classifications, 

provides the record of the QA process. Establishing 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 completed correctly. In addition to records or lists of completed QA steps, documentation refers to summaries and interpretations of emissions inventory reports and analyses. Covering the entire realm of the modeling 

process, QA documentation will include records 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 VISTAS 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 Section 2.2.2.5 and Figure 2-1 for data flow and QA overview). Each 

team member contributes a different 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 used in air quality modeling, they must be reviewed by the 

gatekeeper. For all SMOKE input and output files, the gatekeeper will ensure that the data 

are complete, are formatted correctly, and pass reasonableness checks. Checking 

completeness entails examining the files for the necessary data elements, spatial coverage, 

and temporal extent. Data formats will be confirmed using the SMOKE manual to check 

ASCII files and using PAVE to check binary netCDF files, such as the meteorology inputs. 

Reasonableness checks consist of looking for glaring errors in the file contents 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 gate keeping 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 with 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 archives input and output data. Secondary Modelers

organize the SMOKE QA reports into emissions summaries for data QA and reporting, and 

generate custom QA summaries and reports for troubleshooting any problems encountered 

during the modeling process. 

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• The QA Manager performs and documents all of the checks required for determining model 

accuracy and revealing errors. The 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 modelers, 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 the project report. 

• The Project Manager is ultimately responsible for the quality of the final products of the 

modeling process. Providing technical assistance to the production modelers and clarifying 

any uncertainties about model input, configuration, 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 procedures, and thoroughly 

scrutinizes the QA summaries for problems to determine whether the data are ready to be 

sent to the gatekeepers and outside reviewers for final review before delivery to the air 

quality modelers. For the VISTAS work, the Project Manager is the liaison between the 

emissions modeling team and the VISTAS TAWG and in this role communicates any issues 

raised during the emissions QA process. 

Figure 5-2 presents the QA framework developed by the VISTAS Modeling Team for SMOKE 

modeling. Identifying the specific participants in the VISTAS 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 Modelers 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 positioned 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 outside the emissions modeling team on a volunteer 

basis to conduct periodic reviews/audits of the data and modeling process. 

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Figure 5-2. Diagram of VISTAS Modeling Team Approach to SMOKE Modeling.

VISTAS TAWG

VIS

Modeli

VISTAS 

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6.0 METEOROLOGICAL MODELING 

The EPA Models-3/CMAQ system is the primary regional ozone and particulate matter (PM) air 

quality model being used in VISTAS modeling. Meteorological inputs for CMAQ are being 

generated by the VISTAS Meteorological Modeling Contractor using the MM5 meteorological 

model. The model will be applied for the entire year of 2002 on two grids: a continental scale 

domain with 36 km grid spacing and a regional-scale domain with 12 km grid spacing covering 

the eastern United States. The CMAQ model requires inputs of three-dimensional gridded wind, 

temperature, humidity, cloud/precipitation, and boundary layer parameters. The current version 

of CMAQ can only utilize output fields from the Fifth Generation Mesoscale Model (MM5), 

developed and maintained by the Pennsylvania State University and National Center for 

Atmospheric Research (PSU/NCAR). MM5 is being used to develop hourly meteorological 

fields on the 36 km and 12 km grids. 

A detailed protocol for utilizing MM5 as part of VISTAS has been prepared. The procedures 

used for applying MM5 for VISTAS are based on an extensive evaluation of MM5 and a series 

of sensitivity tests. The MM5 protocol contains a detailed description of MM5, the VISTAS 

modeling domain, the MM5 physical configuration, and a model application approach. The 

protocol also presents a plan for evaluating the performance of the model in replicating the 

evolution of observed winds, temperature, humidity, and boundary layer morphology to the 

extent that resources and data availability allow; this will serve as the primary approach to assess 

the reliability of the meteorological fields to adequately characterize the state of the atmosphere 

for input to CMAQ. Details on the VISTAS MM5 modeling can be found on the VISTS 

Meteorological Modeling website: 

http://www.baronams.com/projects/VISTAS/

MM5 is an atmosphere model that has proven useful for air quality applications and has been 

used extensively in past local, state, regional, and national modeling efforts. MM5 has undergone 

extensive 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. 

7.0 CMAQ MODELING SYSTEM 

EPA’s Models-3 CMAQ modeling system is the primary air quality modeling system used in the 

VISTAS Emissions and Air Quality Modeling activities. 

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7.1 CMAQ Overview 

For more than a decade, EPA has been developing the Models-3 Community Multiscale Air 

Quality (CMAQ) modeling system with the overarching aim of producing a ‘One-Atmosphere’ 

air quality modeling system capable of addressing ozone, particulate matter (PM), visibility and 

acid deposition within a common platform (Dennis, et al., 1996; Byun et al., 1998a; Byun and 

Ching, 1999, Pleim et al., 2003). The original justification for the Models-3 development 

emerged from the challenges posed by the 1990 Clean Air Act Amendments and EPA’s desire to 

develop an advanced modeling framework for ‘holistic’ 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 Quality model (CMAQ) in mid-1999 as the initial 

operating science model under the Models-3 framework (Byun et al., 1998b). The most recent 

rendition is CMAQ version 4.4, publicly released October 2004 and is the version that will be 

used in the VISTAS Phase II Revised 2002 Base Case modeling (Although the Phase I modeling 

runs used CMAQ version 4.3). 

CMAQ consists of a core Chemical Transport Model (CTM) and several pre-processors 

including the Meteorological-Chemistry Interface Processor (MCIP), initial and boundary 

conditions processors (ICON and BCON) and a photolysis 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 EPA has funded the Community Modeling and 

Analysis Systems (CMAS) center to support the coordination, update and distribution of the 

Models-3 system. 

A number of features in CMAQ’s theoretical formulation and technical implementation make the 

model well-suited for annual PM modeling. In CMAQ, 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 and gas phases is assumed to be in equilibrium 

and all secondary aerosols (sulfate, nitrate, SOA) is assumed to be in the fine modes. The 

thermodynamics of inorganic aerosol composition 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 SO2 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 is 

included as well. CMAQ contains three options for treating secondary organic aerosol (SOA), 

latest being the Secondary Organic Aerosol Model (SORGAM) that was updated in August 2003 

to be an reversible semi-volatile scheme whereby VOCs can be converted to condensable gases 

that can then form SOA and then evaporate back into condensable gases depending on 

atmospheric conditions. 

A description of the newest features implemented in CMAQ ver 4.4 (released October 2004) is 

available on the CMAS website (www.cmascenter.org). Many of these features are mentioned 

above; others pertain to details in the model’s chemistry, transport, computer implementation, 

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and model operation. For the VISTAS Phase I modeling and the Phase II Initial 2002 CMAQ 

run version 4.3 (released August 2003) was used, whereas for the Phase II Task 7 CB4/SAPRC 

sensitivity tests and Phase II Revised 2002 CMAQ runs Version 4.4beta (released March 2004) 

and 4.4, respectively, were used. 

7.2 CMAQ Configuration for Phase II Modeling 

One of the principal accomplishments in the Phase I modeling was the identification and 

justification of the CMAQ science options recommended for Phase II modeling. We 

summarized the Phase I findings briefly in the introduction. In this section we briefly identify 

the main science options we recommend for annual PM modeling with CMAQ, more details ate 

provided in the Modeling Protocols (ENVIRON, 2003a; 2004a). The model would be set up and 

exercised on the same nested 36/12 km grid domain used in Phase I, employing one-way grid 

nesting. That is, boundary conditions for the 12 km grid simulation are extracted from the 36 km 

run using the CMAQ BCON processor. A total of 19 vertical layers would be implemented, 

extending up to a region top of 100 mb (approximately 15 km AGL). 

The PPM advection solver would be used along with the spatially varying (Smagorinsky) 

horizontal diffusion approach and K-theory for vertical diffusion. MM5 meteorological 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 Meteorological-Chemistry Interface Processor 

(MCIP2.2 for Phase I and MCIP2.3 for Phase II) would process the MM5 data using the “pass 

through” option. The CB4 gas-phase, RADM aqueous-phase, and AERO3/ISORROPIA aerosol 

chemistry schemes are recommended for use in the initial CMAQ 2002 modeling. Treatment of 

reversible secondary organic aerosols would be simulated by the SORGAM implementation in 

CMAQ (ver 4.3). Under the Phase I modeling, VISTAS evaluated three photochemical 

mechanisms: CB4, CB4-2002 and SAPRC99. CB4-2002 produced nearly identical results as 

CB4 but took much longer to run since it is only implemented in the slower SMVGEAR 

chemistry solver, compared to CB4 that is also implemented in the faster EBI chemistry solver. 

Thus, CB4-2002 was dropped from consideration in Phase II. The Phase I comparisons of CB4 

and SAPRC99 found they produced mostly similar but different model performance. However, 

one mechanism was not performing better than the other across all species, sites and periods. 

The Phase I testing only evaluated the mechanism’s base case performance, not their response to 

emission reductions. Given that CB4 runs twice as fast as SAPRC99, for Phase II it was decided 

to perform initial 2002 CMAQ modeling using CB4 and evaluate CB4 and SAPRC99 responses 

to emission reductions using the Phase I episodes. 

7.3 Alternative Models 

EPA’s guidance on model selection for PM2.5 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 tested and shown to be 

clearly superior or easier to use than several alternatives” (EPA, 2001, pg. 169.) The agency 

recommends that models used for PM2.5 SIPS or RH reasonable progress requirements should 

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meet the requirements for alternative models. The CMAQ, CMAQ-AIM and CAMx modeling 

systems all meet these requirements. 

We believe that there is potentially significant value in including an alternative regional 

modeling system or multiple systems as an adjunct to the SMOKE/MM5/CMAQ system 

proposed as the mainstay of the Phase II analyses. Our testing of the CAMx model in Phase I 

and other recent PM2.5/regional haze applications demonstrates that the model is capable of 

producing results of comparable accuracy and reliability as CMAQ, given similar effort in 

preparing model inputs, diagnosing and improving model performance and in conducting 

weight-of-evidence investigations. The Phase I testing of CMAQ-AIM model raised questions 

on whether it was performing correctly; the differences with CMAQ could not be explained 

based on their differences in formulation with CMAQ-AIM performing poorer than CMAQ. 

Accordingly, at this time we cannot recommend adopting CMAQ-AIM in Phase II and 

recommend VISTAS consider the parallel use of CAMx in the Phase II program for seven 

specific purposes: 

• Diagnosis: To serve as an efficient diagnostic tool addressing model performance 

issues that may arise in the establishment of the CMAQ annual 2002 and episodic 

base cases. CAMx’s suite of diagnostic probing tools plus it’s flexi-nesting 

algorithms make it an attractive tool for assisting in the diagnosis of CMAQ 

performance should this unexpected situation arise. 

• Model Evaluation Corroboration: To provide corroboration of the base case model 

performance evaluation exercises to be performed with CMAQ and help identify any 

compensatory errors in the MM5/SMOKE/CMAQ modeling system. 

• Emissions Control Response Corroboration: To provide corroboration of the 

response of the CMAQ modeling system to generic and specific future year emissions 

changes on modeled gas-phase and particulate aerosol concentrations and resultant 

regional haze impacts. 

• Quantification of Model Uncertainty: To provide one estimate of the range of 

uncertainty that attends statements of CMAQ model performance in the annual and 

episodic base case simulations, and in the estimate of PM2.5 and visibility reductions 

associated with future emissions change scenarios. 

• Alternative Science: CAMx contains alternative science algorithms that may 

elucidate model performance issues with CMAQ or provide an alternative approach 

for simulating aerosols. 

• Consistency with Other RPOs: The Midwest RPO (MWRPO) may end up using 

CAMx for their regional haze modeling. As sources in the MWRPO likely influence 

visibility at Class I areas in VISTAS and vice versa, having results from a common 

model would be useful for reconciling any differences. 

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

unforeseen difficulties with the primary model make it necessary to switch to an 

alternative ‘One-Atmosphere’ model at some point during Phase II. 

The benefits of employing a pair of complimentary state-of-science air quality models are thus 

quite significant and well worth considering. Especially considering that the same MM5 output 

(through MM5CAMx) and SMOKE output and CMAQ IC/BC files (through CMAQ-to-CAMx 

emissions and IC/BC converters) can be used to operate CAMx without performing any 

additional meteorological or emissions modeling. Accordingly, below we provide an overview 

of the CAMx regional photochemical/PM modeling system and the science options 

recommended for use in Phase II. 

7.3.1 CAMx Overview 

The Comprehensive Model with Extensions (CAMx) modeling system is a publicly available 

(www.camx.com) three-dimensional multi-scale photochemical/aerosol grid modeling system 

that is developed and maintained by ENVIRON International Corporation. CAMx was 

developed with all new code during the late 1990s using modern and modular 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 Source Apportionment Technology 

(OSAT). Designed originally to address multiscale ozone issues from the urban- to regionalscale, CAMx has been widely used in recent years by a variety regulatory agencies for 1-hr and 

8-hr ozone SIP modeling studies. 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 NOx point source plumes. 

• Ability to interface with a variety of meteorological models including the MM5 and 

RAMS prognostic hydrostatic meteorological models and the CALMET diagnostic 

meteorological model (others also compatible). 

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• The Ozone Source Apportionment Technology (OSAT) ozone apportionment 

technique that identifies the ozone contribution due to geographic source regions and 

source categories (e.g., mobile, point, biogenic, etc.). 

• The Decoupled Direct Method (DDM) sensitivity method is implemented for 

emissions and IC/BC to obtain first-order sensitivity coefficients for all gas-phase 

species. 

• Treatment of particulate matter (PM) using an empirical aerosol thermodynamics 

algorithm. 

Culminating extensive model development efforts at ENVIRON and other participating groups, 

the CAMx (ver 4.3+) code was released in the autumn of 2003 as a truly “One-Atmosphere’ 

models that rigorously integrates the gas-phase ozone chemistry with the simulation of primary 

and secondary fine and course particulate aerosols. This extension 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 treats the effects of 

condensation/evaporation, coagulation and nucleation upon the particle size 

distribution. 

• Inorganic aerosol thermodynamics can be represented using 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 modeled either using the RADM module (like 

CMAQ) or the Variable Size-Resolution Model (VRSM) of Fahey and Pandis (2001), 

which automatically determine whether water droplets can be represented by a single 

‘bulk’ droplet-size mode or whether it is necessary to use fine and coarse droplet-size 

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

CAMx (ver 4.3+) provides two key options to users interested in simulating PM. For CPUefficient annual PM modeling applications, CAMx may be run using Mechanism 4 (M4) with 

only two size sections (fine and coarse) and the efficient RADM bulk aqueous-phase module (as 

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used in CMAQ). Alternatively, more rigorous aerosol simulations (perhaps for shorter episode) 

may be addressed using the version that treats N-size sections (N is typically 10) and the 

rigorous, but computationally-extensive CMU multi-section aqueous-phase chemistry module. 

7.3.2 CAMx Configuration for Phase II Modeling 

We recommend exercising CAMx (ver 4.10s) as a companion model to CMAQ using as many 

similar science options and input data sets as possible. However, in some instances, the CMAQ 

and CAMx model development teams chose different options for characterizing physical and 

chemical 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. At this time VISTAS has not budgeted any resources in Phase II for CAMx modeling, 

however it remains an option if desired at a later date. 

The latest version of CAMx (ver 4.10s) will be employed and the model will be set up and 

exercised on the same 36/12 km grid as CMAQ. However, CAMx would be run using two-way 

grid nesting. The base configuration of CAMx would use 19 vertical layers that exactly match 

those used by CMAQ. The PPM advection solver would be used along with the spatially 

varying (Smagorinsky) horizontal diffusion approach. Vertical diffusion in CAMx would be 

modeled by K-theory. The MM5 simulation using the Pleim-Xiu Land-Surface Model (LSM) 

and the ACM Planetary Boundary Layer (PBL) scheme would be used in the CAMx base 

configuration using the MM5CAMx processor that is similar to the CMAQ MCIP2.2 “pass 

through” option of the MM5 data invoked. CAMx would be exercised with the CB4 gas-phase, 

RADM aqueous-phase, and CMU/ISORROPIA aerosol chemistry schemes. The SOAP 

secondary organic aerosol scheme would 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 investigative scientific issues that may be of interest that can not 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 VISTAS 

domain, especially when looking at clean days or natural background; and 

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

formation. 

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8.0 ASSESSMENTS AND OVERSIGHT 

8.1 Assessment Responsibilities 

The primary point of contact for VISTAS Modeling project assessment is that of the Project 

Manager (PM). This PM is available to the VISTAS Contracting Officer, Technical Contact, 

TAWG, external reviewers, and internal staff by direct contact through e-mail and phone and is 

linked to each of the four VISTAS listservs (see Table 3-2). These links provide timely reviews 

of the project experimental design, implementation, and interpretation of the experimental 

results. 

The assessments of overall project quality are provided from a number of different sources. 

Internal reviews of selected project components are periodically performed by the Project 

Manager and Co-Principal Investigators. The results of this and other routine (e.g., QC checks) 

and special reviews of project data quality are documented in the monthly reports. 

The project team is committed to achieving and maintaining the highest level of quality possible 

throughout the performance of this program. The modeling information generated will be both 

technically sound, and, where appropriate, legally defensible. The former is an obvious 

requirement but is not, in and of itself, sufficient to defend the data against an adversarial 

inquiry. The latter will address, through documentation, the level of quality achieved. The 

quality of the project data will be maintained not only through the development and use of data 

quality objectives (DQOs), which place numerical limits on the quality control indicators, but 

also through the use of subjective science quality objectives. 

Science quality objectives are used to provide evaluations of the quality of the research project 

and goals of the study. Evaluations of all research activities by internal and external 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 generated on this project will be made by: 

• Conducting internal performance reviews of the critical components 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 generated in this project. 

• Independent peer reviews of thesis materials, reports, and papers resulting from this 

project. 

The VISTAS TAWG provides external review of all reports and plays an active role in the 

development of experimental matrices and to review research progress and plans for future 

project tasks. 

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8.3 Assessment Criteria 

The project assessment criteria address the extent to which the 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 providing the data and information needed for evaluating and improving 

models for predicting the effects of emissions on air quality. Therefore, the evaluation process 

includes assessments of model uncertainties, the extent to which the proposed actions or system 

improvements can reduce these uncertainties, and estimates of the certainty of this work in 

providing the data of the type and quality needed. Criteria for assessing data utility 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 being applied to the highest priority types of 

measurements? 

• Degree of characterization of experimental conditions for modeling. For data to be useful 

for model evaluation, experimental conditions must be sufficiently well characterized, so 

that the data can be used for model evaluation without characterization uncertainties 

dominating the results. 

• Accuracy, precision, and sensitivity of the measurement data. The measurements in the 

concentration region of interest should be sufficiently accurate and precise to provide a 

meaningful test of model predictions. 

• Procedures used to assure data quality, identify data not meeting quality objectives, and 

to minimize errors and other data quality problems. 

• Degree to which the modeling appropriately incorporates the characterization results in 

the inputs, and the analysis of the modeling results appropriately take into account 

characterization and measurement uncertainties and biases. 

• Degree to which the experimental procedures, measurement methods, and data 

processing and analyses, and modeling methods are documented. 

9.0 REFERENCES 

Adelman, Z. (2004) Quality Assurance Protocol: WRAP RMC Emissions Modeling with 

SMOKE, Prepared for WRAP Modeling Forum, January. 

Alpine Geophysics. 2003a. “VISTAS Emissions and Air Quality Modeling – Phase I Subtask 

3c-1 Report: MM5 Meteorology QA/QC Summary Report for Episode 1: 2-20 January 

2002.” Alpine Geophysics LLC, ENVIRON International Corporation and University of 

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California at Riverside. Ft. Wright, Kentucky (available at: 

http://pah.cert.ucr.edu/vistas/docs.shtml). September 10. 

Alpine Geophysics. 2003b. “VISTAS Emissions and Air Quality Modeling – Phase I Subtask 

3c-1 Report: MM5 Meteorology QA/QC Summary Report for Episode 1: 13-22 July 

1999.” Alpine Geophysics LLC, ENVIRON International Corporation and University of 

California at Riverside. Ft. Wright, Kentucky (available at: 

http://pah.cert.ucr.edu/vistas/docs.shtml). September 15. 

Alpine Geophysics. 2003c. “VISTAS Emissions and Air Quality Modeling – Phase I Subtask 

3c-1 Report: MM5 Meteorology QA/QC Summary Report for Episode 1: 11-27 July 

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