Docket ID: EPA-HQ-OAQ-2012-0056

October 2012

Summary of Public Comments

10th Conference on Air Quality Modeling

Research Triangle Park, NC.

March 13 – 15, 2012

Air Quality Modeling Group

Air Quality Analysis Division

Office of Air Quality Planning and Standards

U.S. Environmental Protection Agency

October 2012
(This Page Intentional Left Blank)
i

ACRONYMS – General

10th MC 10th Conference on Air Quality Models also known as 10th Modeling 

Conference

AERMAP Terrain preprocessor for AERMOD 

AERMET Meteorological data preprocessor for AERMOD

AERMIC American Meteorological Society (AMS)/United States Environmental 

Protection Agency (EPA) Regulatory Model Improvement Committee

AERMINUTE Processes 1-minute ASOS wind data to generate hourly average winds for 

input to AERMET in Stage 2

AERMOD EPA’s preferred model for near-field (up to 50 km) regulatory applications 

in simple and complex terrain,

http://www.epa.gov/ttn/scram/dispersion_prefrec.htm#aermod

AERSURFACE Tool that processes land cover data to determine the surface characteristics 

for use in AERMET

ADMS Atmospheric Dispersion Modeling System

AQRV Air Quality Related Value

ARM Ambient Ratio Method

ARM2 Ambient Ratio Method 2

ASOS Automated Surface Observing Stations

BACT Best Available Control Technology

BPIP Building Profile Input Program

BPIPPRM Building Profile Input Program for PRIME

CAA Clean Air Act

CALMET 3-D diagnostic meteorological model for CALPUFF

CALPOST Postprocessor for CALPUFF

CALPUFF EPA's preffered model for assessing long range transport of pollutants and 

their impacts (AQRVs) on Federal Class I areas, 

http://www.epa.gov/ttn/scram/dispersion_prefrec.htm#calpuff

CAMx Comprehensive Air Quality Model with Extensions, 

http://www.camx.com/

CMAQ Community Multi-scale Air Quality, http://www.cmaq-model.org/

CMAQ-APT CMAQ - Advanced Plume Treatment

CMAQ-MADRID CMAQ - Model of Aerosol Dynamics, Reaction, Ionization, and 

Dissolution

CEM Continuous Emissions Monitoring

EBDs Equivalent Building Dimensions

EMVAP Emissions Variability Processor

EPA U.S. Environmental Protection Agency

FLAG Federal Land Managers AQRV Work Group

FLM Federal Land Manager

Guideline Common reference to the Guideline on Air Quality Models, the Modeling 

Guideline or Appendix W to 40 CFR Part 51, 

http://www.epa.gov/ttn/scram/guidance/guide/appw_05.pdf

GEP Good Engineering Practice

HUSWO Hourly US Weather Observations
ii

ACRONYMS – General (Continued)

ISHD Integrated Surface Hourly Data (also known as TD-3505 format, it 

integrated METAR, TD-3280, and other formats)

IWAQM Interagency Workgroup on Air Quality Modeling

MACT Maximum Achievable Control Technology

MCB Model Change Bulletin

MM5 Fifth-Generation NCAR / Penn State Mesoscale Model, 

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

MMIF Mesoscale Model Interface Program

NAAQS National Ambient Air Quality Standard(s)

NPS U.S. National Park Service

NSPS New Source Performance Standards

NSR New Source Review

NWS National Weather Service

OAQPS U.S. EPA’s Office of Air Quality Planning and Standards

OLM Ozone Limiting Method

ORD U.S. EPA’s Office of Research and Development

PVMRM Plume Volume Molar Ratio Method

PSD Prevention of Significant Deterioration

SCICHEM SCIPUFF model with an embedded full chemistry mechanism

SCIPUFF Second-order Closure Integrated Puff model

SIA Significant Impact Area

SIL Significant Impact Level

SIP State Implementation Plan

USFS U.S. Forest Service

UTM Universal Transverse Mercator

WRF Weather Research and Forecasting model, http://www.wrf-model.org/
iii

ACRONYMS – Comment Submitters

ACW Alpha Coal West, Inc.

AEPSC American Electric Power Service Corporation

AF&PA American Forest and Paper Association

AISI American Iron and Steel Institute

API American Petroleum Institute

APS Arizona Public Service Company

A&WMA Air & Waste Management Association, AB-3 Committee on Meteorology

BGNA Barrick Gold of North America, Inc.

BP BP America, Inc.

Coulter Coulter Air Quality Services

DE Duke Energy Corporation

EEANC Environmental Energy Alliance of New York, LLC

EPRI Electric Power Research Institute

Exponent Exponent, Inc.

FI The Fertilizer Institute

NIC NAAQS Implementation Coalition (Prepared by Hunton & Williams)

Koogler Koogler and Associates, Inc.

NDDH North Dakota Department of Health

NEDA The National Environmental Development Associations’ Clean Air Project

NMA National Mining Association

OPC Oglethorpe Power Corporation

PE Peabody Energy

SC Southern Company

Sears Camille Sears

SRP Salt River Project Agricultural Improvement and Power District

Tri-State Tri-State Generation and Transmission Association, Inc.

UARG Utility Air Regulation Group (Prepared by Hunton & Williams)

West West Associates

WMA Wyoming Mining Association
iv

(This Page Intentional Left Blank)
v

TABLE OF CONTENTS

1.0 Introduction .......................................................................................................................... 1

2.0 Model Clearinghouse and Procedural Comments................................................................ 3

2.1 General Stakeholder Involvement ........................................................................................3

2.2 Expanded Access to the Model Clearinghouse ....................................................................4

2.3 Public Access to Model Evaluation Databases.....................................................................5

2.4 Requirements of “Data Quality Act”....................................................................................5

2.5 Modeling Guidelines and Guideline Models Update Process..............................................5

2.6 Ad-hoc Guidance, Clarification Memos, and Clearinghouse Activities ..............................6

3.0 Comments on Development of Schedule to Address Comments and Implement Model 

Changes................................................................................................................................ 7

3.1 Hunton and Williams for NAAQS Implementation Coalition .............................................7

3.2 American Petroleum Institute...............................................................................................9

3.3 BP America ........................................................................................................................10

3.4 The National Environmental Development Association’s Clean Air Project ....................12

4.0 Comments Related to AERMOD....................................................................................... 12

4.1 Low Wind Speeds...............................................................................................................12

4.2 Treatment of Downwash ....................................................................................................15

4.3 Modeling Domain Limitation.............................................................................................16

4.4 AERMOD Update Process.................................................................................................17

4.5 Buoyant Line Sources.........................................................................................................17

5.0 Fugitive Dust Comments.................................................................................................... 17

5.1 Treatment of Emissions and Modeling for Surface Mines.................................................17

5.2 Relevance to CAA, Section 234.........................................................................................19
vi

TABLE OF CONTENTS (Continued)

6.0 Comments Related to CALPUFF....................................................................................... 19

6.1 Adoption of Improvements to CALPUFF..........................................................................19

6.2 Relationship of CALPUFF v6.4 to BART Rule.................................................................20

6.3 Application of Appendix W, Section 3.2 to CALPUFF v6.4.............................................21

6.4 Application of CALPUFF to Nearby Sources....................................................................21

6.5 Individual Source Impacts on PM2.5 and Ozone.................................................................22

7.0 NAAQS Compliance Demonstration Comments............................................................... 23

7.1 NAAQS Compliance Demonstration General Comments .................................................23

7.2 Ambient Air........................................................................................................................23

7.3 Background Concentrations ...............................................................................................24

7.4 Significant Impact Levels for revised 1-hour NO2/SO2 and PM2.5 NAAQS ......................24

7.5 1-hour NO2/SO2 NAAQS ...................................................................................................25

7.5.1 1-hour NO2/SO2 NAAQS General Comments.........................................................25

7.5.2 1-hour NO2 – Refined Tier 2 and Tier 3 Methods, ARM2 Implementation, and Field 

Studies26

7.5.3 1-hour NO2 – NO2 to NOX Ambient Equilibrium Ratios and In-stack Emissions 

Ratios 26

7.5.4 1-hour SO2 – Use of Variable Emissions and EMVAP Implementation .................26

7.6 PM2.5 NAAQS ....................................................................................................................28

7.7 Monitoring in Lieu of Modeling.........................................................................................28

8.0 Emerging Models and Techniques Comments................................................................... 29

8.1 Mesoscale Model Interface Program (MMIF) Comments.................................................29

8.2 Single Source PM2.5 and Ozone Modeling .........................................................................30
vii

TABLE OF CONTENTS (Continued)

Attachment A.................................................................................................................................. 1

Summary of 10th Conference on Air Quality Modeling Comment Submissions..............................1

NAAQS Implementation Coalition (Prepared by Hunton & Williams)................................1

Utility Air Regulation Group (Prepared by Hunton & Williams)..........................................3

Electric Power Research Institute ..........................................................................................5

Environmental Energy Alliance of New York, LLC .............................................................7

Southern Company.................................................................................................................9

American Electric Power Service Corporation ....................................................................10

Duke Energy Company........................................................................................................11

Arizona Public Service Company ........................................................................................12

Salt River Project Agricultural Improvement and Power District .......................................13

Tri-State Generation and Transmission Association, Inc.....................................................13

Oglethorpe Power Corporation ............................................................................................13

West Associates ...................................................................................................................14

American Petroleum Institute ..............................................................................................15

BP America, Inc...................................................................................................................17

American Iron and Steel Institute ........................................................................................19

National Mining Association ...............................................................................................21

Wyoming Mining Association .............................................................................................23

Alpha Coal West, Inc. – .......................................................................................................23

Barrick Gold of North America, Inc. ...................................................................................24

Peabody Energy ...................................................................................................................25

The National Environmental Development Association’s Clean Air Project......................26

American Forest & Paper Association.................................................................................28

The Fertilizer Institute..........................................................................................................30

Koogler and Associates, Inc.................................................................................................32

Coulter Air Quality Services................................................................................................32

Camille Sears .......................................................................................................................33

North Dakota Department of Health....................................................................................34

Air & Waste Management Association, AB-3 Committee on Meteorology, includes 

Exponent, Inc. ......................................................................................................................35
viii

TABLE OF CONTENTS (Continued)

Attachment B .................................................................................................................................. 1

Summary of 10th Conference on Air Quality Modeling Individual Presentations...........................1

AERMOD Applications Development..............................................................................................1

Ron Petersen -- CPP Inc.........................................................................................................1

Bob Paine – AECOM for API and UARG.............................................................................2

Randy Robinson – EPA Region 5..........................................................................................2

Chatten Cowherd – MRI Global ............................................................................................3

Currently Preferred AQ Models -- CALPUFF ..................................................................................4

Gale Hoffnagle -- TRC Companies, Inc.................................................................................4

PM2.5 Modeling..................................................................................................................................4

Ryan Gesser – American Forest & Paper Association...........................................................4

1-hour NO2/SO2 Modeling ................................................................................................................5

Bob Paine, AECOM...............................................................................................................5

Mark Podrez – RTP Env. Assoc. Inc .....................................................................................6

Steven Hanna -- Hanna Consultants ......................................................................................6

Dan Dix – All4.......................................................................................................................7

Emerging Models / Techniques.........................................................................................................7

Ralph E. Morris -- ENVIRON International Corporation......................................................7

Public Presentations...........................................................................................................................8

Pietro Catizone, A&WMA AB-3 Meteorology Committee – Introductory Comments ........8

Lloyd L. Schulman -- Building Downwash Modeling with AERMOD (A&WMA AB-3)...8

Joseph S. Scire -- Assessment of EPA’s ETEX Evaluation Study (A&WMA AB-3)...........9

Joseph S. Scire -- New Developments and Evaluations of the CALPUFF Model (A&WMA 

AB-3) ...................................................................................................................................10

Andy Berger – West Associates...........................................................................................11

Steve Hanna – Hannah Consultants for API........................................................................11

Ryan Gesser – American Forest & Paper Association.........................................................15

Bob Paine – AECOM for Electric Power Research Institute...............................................15

Bob Paine – AECOM for Electric Power Research Institute...............................................15

Bob Paine – AECOM for Electric Power Research Institute...............................................16

Allen Dittenhoefer -- Enviroplan Consulting.......................................................................16

Qiguo Jing -- Breeze, Trinity Consultants ...........................................................................17
ix

TABLE OF CONTENTS (Continued)

Bob Paine – AECOM...........................................................................................................17

George Schewe -- Trinity Consultants.................................................................................17

Sergio Guerra -- Wenck Associates, Inc. .............................................................................17

Dana Wood – BP..................................................................................................................18

Nicole Downey -- Earth System Sciences, LLC..................................................................18

Cindy Langworthy – UARG ................................................................................................19

Mark Bennett – CH2M Hill for Rio Tinto ...........................................................................19

Stephen Mueller -- Tennessee Valley Authority..................................................................20

Steve Gossett – Eastman Chemical Company & Bob Paine -- AECOM.............................20

Ashley Jones – Trinity Consultants......................................................................................20

Anand Yegnan – ERM.........................................................................................................21

Anand Yegnan – ERM.........................................................................................................21

Eladio Knipping -- Electric Power Research Institute .........................................................22

Steven Hanna – Hanna Consultants on research supported by Defense Threat Reduction 

Agency .................................................................................................................................22

Steven Hanna – Hanna Consultants on research supported by Defense Threat Reduction 

Agency .................................................................................................................................23

David Long -- American Electric Power Service Corporation ............................................23

Tony Colombari – Trinity Consultants................................................................................23

Justin Walters – Southern Company ....................................................................................24

Attachment C .................................................................................................................................. 1

Presentations, Transcripts, and Docket Links ...................................................................................1

Attachment D.................................................................................................................................. 1

Modeling Action Items and Prioritization Summary Table ..............................................................1
x

(This Page Intentional Left Blank)
1

1.0 Introduction

Background

The Guideline on Air Quality Models (hereafter, called the Guideline, which is found in 

Appendix W to 40 CFR part 51), is used by the EPA, states and industry to prepare and review 

new source permits, source permit modifications, and State Implementation Plan submittals and 

revisions. The Guideline serves as a means by which national consistency is maintained in air 

quality analyses. We originally published the Guideline in April 1978, and it was incorporated 

by reference in the regulations for the Prevention of Significant Deterioration of Air Quality in 

June 1978. We revised the Guideline in 1986, and updated it with supplement A in 1987, 

supplement B in July 1993, and supplement C in August 1995. We published the Guideline as 

Appendix W to 40 CFR part 51 when we issued supplement B. We republished the Guideline in 

August 1996 (61 FR 41838) to adopt the CFR system for labeling paragraphs.

To support the process of developing and revising the Guideline during the period 1977–

1988, we held the First, Second, and Third Conferences on Air Quality Modeling as required by 

CAA Section 320 to help standardize modeling procedures. These modeling conferences 

provided us with comments on the Guideline and associated revisions, thereby helping us 

introduce improved modeling techniques into the regulatory process.

In October 1988, we held the Fourth Conference on Air Quality Modeling to advise the 

public on new modeling techniques and to solicit comments to guide our consideration of any 

rulemaking needed to further revise the Guideline. We held the Fifth Conference in March 1991, 

which served as a public hearing for the proposed revisions to the Guideline. In August 1995, 

we held the Sixth Conference as a forum to update our available modeling tools with state-ofthe-science techniques and for the public to offer new ideas. The Seventh Conference was held 

in June 2000 and served as a public hearing for the proposed changes to the recommended air 

quality models in the Guideline (now referred to as Appendix W) including the CALPUFF 

modeling system, AERMOD modeling system, and ISC–PRIME model. We held the Eighth 

Conference on Air Quality Modeling in September 2005, which provided details on changes to 

these recommended air quality models, including the Notice of Data Availability published in 

September 2003 related to the incorporation of the PRIME downwash algorithm in the 

AERMOD dispersion model in response to comments received from the Seventh Conference, 

and details on available methods for model performance evaluation. Additionally, at the Eighth 

Conference, there was a panel of experts discussion on the use of state-of-the-science prognostic 

meteorological data for informing the dispersion models.

The Ninth Conference on Air Quality Modeling held in October 2008. The conference 

began with an overview presentation and review of Appendix W and plans to reinstitute the 

Model Clearinghouse. Several presentations were made on non-guideline applications of 

dispersion models as well as a continuation of discussions from the Eighth Conference on the use 

of prognostic meteorological data with respect to informing the Appendix W models. Updates 

were provided on the regulatory status, recent coding changes, and future development of the 

AERMOD modeling system, the EPA’s preferred model for near-field regulatory applications, 

and the CALPUFF modeling system, the EPA’s preferred model for long-range transport of 

criteria pollutants and their impacts on Federal Class I areas. The Ninth Conference concluded 
2

with a collection of presentations reviewing the available model evaluation methods and 

reviewing new and emerging models and techniques for future consideration under Appendix W.

The most recent conference, the Tenth Conference on Air Quality Modeling, was 

conducted from March 13 through 15, 2012. The conference followed a familiar agenda with 

initial status presentations on Appendix W, the Model Clearinghouse, and the currently preferred 

air quality models (AERMOD and CALPUFF). To conclude the first day of the conference, 

there was a review of the prognostic meteorological data processing tool for dispersion models, 

MMIF. Almost a full day of presentation and discussion was devoted to compliance 

demonstration modeling for the PM2.5 NAAQS and the 1-hour NO2 and SO2 NAAQS, including 

an overview presentation of the draft PM2.5 (primary and secondary) modeling guidance and 

presentations from the AERMOD Implementation Workgroup summarizing an ongoing NO2 and 

SO2 modeling study. Completing the second day of the conference, there was a review of new 

and emerging models/techniques for future consideration under Appendix W to address longrange transport and chemistry. The Tenth Conference on Air Quality Modeling concluded with a 

full day of public presentation and oral comments. A transcript of the proceedings and a copy of 

all written comments can be found in Docket ID No. EPA–HQ–OAR–2012–0056.

Summary of the Public Comments

This Summary of Public Comments document package contains a summary of the public 

comments filed in the Docket (EPA-HQ-OAR-2012-0056) for the 10th Conference on Air 

Quality Modeling. The main portion of this document is divided into seven topical areas that 

mimics the order of presentation and discussion during the conference proceedings. The seven 

topical areas area as follows: Model Clearinghouse and Procedural Comments; Comments on 

Development of Schedule to Address Comments and Implement Model Changes; Comments 

Related to AERMOD; Fugitive Dust Comments; Comments Related to CALPUFF; NAAQS 

Compliance Demonstration Comments; and, Emerging Models and Techniques Comments.

A brief summary of each of the individual comment submissions are provided in 

Attachment A. A bulleted summary of the public (non-EPA) presentations delivered during the 

three days of the conference are provided in Attachment B. The brief comment summaries and 

bulleted presentation summaries are solely for general reference and are not intended to 

supersede the actual comments submitted to the Docket or the presentation material and 

transcripts from the 10th Conference on Air Quality Modeling. For additional clarity, Internet 

links to the main conference website, the conference Docket, and the conference presentations 

and transcripts are provided in Attachment C.

Finally, a Modeling Action Items and Prioritization Summary Table is provided in 

Attachment D. This summary table outlines the EPA’s near-term action items and long-term 

goals with respect to updates and modifications to the regulatory models (AERMOD and 

CALPUFF) and the Guideline that are necessary to address specific issues indentified with these 

models, with current and future NAAQS compliance demonstrations, and with emerging models 

and techniques.
3

2.0 Model Clearinghouse and Procedural Comments

2.1 General Stakeholder Involvement

Numerous commenters (UARG, EEANC, SC, API, BP, AISI, NMA, NEDA, FI) make a 

case for greater involvement with EPA to ensure that the best tools are used in implementing the 

Clean Air Act. Furthermore, they recommend that EPA give tools developed by industry groups, 

and provided to EPA, the same consideration given to tools developed by EPA; this is 

particularly true if those models improve accuracy for regulatory purposes. The commenters 

recommend that EPA more frequently consult/work with stakeholders (including the scientific 

community) to promote a community approach to model development and acceptance that 

supports continual improvement in modeling science/data and timely model acceptance for use 

in the regulatory arena. Some commenters indicate that the stakeholder community is prepared 

to assist EPA by providing useful information on model evaluation/improvement, and such 

efforts could involve considerable investment in resources by stakeholders.

More specifically, commenters (including UARG, SC, API) recommend that EPA engage 

not only the regional, state and local agencies, but also the private sector, including consultants 

and industry, to achieve goals of improving the performance of both preferred and alternative 

models and for updating Appendix W. EPA should provide a clear path forward for approving 

model improvements that come from the modeling community, (e.g., AECOM recommendations 

on low wind speed, the SHARP and AERMINUTEPlus processors for simulating sub-hourly 

meteorology in AERMOD). Also, the private sector should be invited to participate in the yearly 

State/local Modelers’ Workshops, in addition to the Modeling Conference. Regional Chemistry 

Models (CMAQ, CAMx, and others) should also have a larger role in the EPA Air Modeling 

Conferences; while there is an annual CMAS conference, it does not provide a formal 

mechanism for public review and comment.

Another, more general option (API) for engagement is a workgroup process to involve 

and expand stakeholder and scientific input, similar to the planning conferences. This could also 

include support for model development and application from industry associations. EPA should 

continue increasing their communications and collaborations with the many groups studying 

modeling issues and include the wider community in planning, model development and 

evaluation, and analysis and review of results. Collaboration among EPA, Stakeholders and 

Researchers could include some or all of the following actions/activities: (1) EPA’s 

consideration of comments from the 10th Modeling Conference and development of a research 

plan/schedule for addressing modeling issues; (2) communication and coordination within EPA 

(e.g., OAQPS and ORD), and external communication and collaboration with stakeholders such 

as industries, state agencies and consulting companies who must use the models, and with 

national and international scientists who are working on improving models; (3) EPA OAQPS’s 

continued use of a technical work group to suggest technical solutions and provide technical 

review of new models and model revisions; (4) industry association provision of various 

technical resources and expertise for workgroup efforts that could be targeted toward 

fundamental program development, or alternatively at source-specific applications.

An even broader approach suggested in part by a number of commenters (EEANC, BP, 

AISI, NMA NEDA) involves a spirit of collaboration with stakeholders, independent of any 
4

specific project. A panel of recognized experts (evenly split between state agencies, universities, 

public and industry) could be appointed to address modeling issues. The panel could: (1) 

provide short term research objectives along with measurable performance milestones; (2) 

provide feedback to EPA management regarding research needs; (3) help develop methods of 

reducing the time required to implement changes in the Modeling Guideline (Appendix W); (4) 

provide peer review of Model Clearinghouse actions; (5) provide technical peer review on 

changes to guideline models; (6) provide and publish determinations that demonstrate model 

accuracy is sufficient to meet the current policy needs; (7) address modeling issues and suggest 

changes to improve the accuracy of models used in NAAQS implementation; (8) help to develop 

a transparent process that solicits available expertise to refine air dispersion modeling and allows 

for public notice and comment rulemaking; (9) work with EPA, in advance of implementation 

guidance or changes to the modeling system, to exchange information and expertise that can 

avoid unintended or unforeseen consequences of EPA modeling tools and guidance.

2.2 Expanded Access to the Model Clearinghouse

Regarding the model clearinghouse, some commenters (EEANC, BP, NEDA) 

recommend that EPA re-invent and/or adopt another means of communicating technical 

developments to modelers on a regular basis. Toward this end, EPA should encourage and 

accept stakeholder input during efforts to improve the model clearinghouse process, contents and 

information; this will help reduce the likelihood of errors and deficiencies and the imposition of 

overly burdensome requirements in the resulting policies and guidance. Commenters expressed 

concern that the Model Clearinghouse process does not allow technical input by the affected 

parties (e.g., permit applicant). Typically, the permitting authority states their opinion and asks 

for Clearinghouse approval and no other involvement is allowed. Because more controversy is 

expected, the process needs to change and suggestions at the 10 Modeling Conference related to 

model acceptance criteria should be considered. Also, OAQPS needs to create a more dynamic 

tool in the near term for modelers to communicate to iron out problems and develop solutions 

that take advantage of technological innovations in the field. EPA should change the model 

clearinghouse process to allow the regulated community to bring questions and proposals 

directly to OAQPS if the states and the regions deny them; an approach whereby the affected 

parties are able to provide comment along with the permitting authority’s correspondence to the 

Clearinghouse is also endorsed. This approach would provide a more open platform than 

monthly conference calls for encouraging States and regional EPA officials’ participation and 

make existing models better by submitting them for discussion and resolution of issues in “real 

time.” OAQPS should also establish a regulatory mechanism akin to the quarterly publication of 

NSPS/MACT, then post at an Internet website case-specific modeling issues and decisions. If 

necessary, the existing technical modeling stakeholder committee and/or a regional EPA 

modeling committee could be tasked with monthly modeling conference calls to “peer-review” 

and/or prioritize issues brought to the committee’s attention. 

Since modeling “determinations” by the model clearinghouse tend to memorialize casespecific resolutions, a commenter (NEDA) notes that such resolutions need not establish 

“precedent” for other modeling decisions or be cast so broadly to be of “national significance,” 

as is the case with postings on the Model Clearinghouse. Instead the mechanism would provide a 

resource for modelers and regulators to exchange information. Resolutions, even temporary fixes 

and future rulemakings and shared data or Notices of Data Availability, also could be posted for 
5

the modeling community, which presently seems to be unusually dependent on word of mouth 

for what is permissible, possibly permissible, and might happen in the future. Historical model 

clearinghouse guidance should be revisited, and state/local agencies should be given the ability 

to apply flexibility and judgment in consideration of source-specific circumstances.

2.3 Public Access to Model Evaluation Databases

Commenters (EEANC, API) indicate that the modeling community should have easy 

access to all field and laboratory model evaluation data bases used by the EPA to develop and 

evaluate models. EPA should keep this information on a devoted server and include adequate 

metadata. All the dispersion field results should be placed in a single data archive for easy 

public access.

2.4 Requirements of “Data Quality Act”

Finally, commenters (Koogler, FI) noted that information disseminated by EPA 

Conferences on Air Quality Modeling does not comply with EPA guidelines for compliance with 

the Data Quality Act. Revisions that lack model evaluation support, run contrary to long 

standing regulatory policy and guidance, and produce demonstrably erroneous results are often 

without the opportunity for independent peer review or public comment. Stakeholder input, 

including independent peer review, is often ignored or not otherwise integrated into final 

decision-making on data dissemination. In other instances, known data quality errors are 

consistently ignored. EPA should review its procedures for prioritizing, determining and 

disseminating information through the Conferences on Air Quality Monitoring process to ensure 

that data disseminated from these meetings are in compliance with EPA Guidance and the Data 

Quality Act. EPA should examine when and how stakeholder input is integrated into decisionmaking, how data are prioritized for review and revision, and how proposed changes to air 

models are validated before data dissemination.

2.5 Modeling Guidelines and Guideline Models Update Process

A variety of commenters (including UARG, EPRI, SC, DE, BP, NMA, Koogler, FI, and 

AF&PA) address issues concerning changes to the modeling guideline and/or revisions to 

guideline models and their application. Generally, they argue that such changes/revisions should 

lead to the best available models and modeling methods in Appendix W through a systematic 

and expeditious process. In their view, such a process has not been consistently followed and 

many aspects of the process of updating Appendix W are deficient. The current version, issued in 

2005, of Appendix W is thought to be out of date with respect to both (1) the existence of 

known, but uncorrected, errors in the computer codes of the preferred models, and (2) the 

guidance needed to address the new and more stringent National Ambient Air Quality Standards 

(NAAQS) and Prevention of Significant Deterioration (PSD) increments that have been 

promulgated since 2005. The process of verifying reported errors in the preferred model codes 

needs to be accelerated, and known errors in the model codes must be corrected as soon as 

possible.

When it is necessary to add a model or modeling method to Appendix W (e.g., the 

“Modeling Guideline”), or to make revisions to the models and modeling methods currently in 

the Guideline that result in changes to modeled concentrations, each commenter made a case for 

one or more of the following steps. The steps should be taken by EPA as part of a public notice 
6

and rulemaking process before a significant change can be made to the Modeling Guideline, or to 

Guideline-referenced models and modeling techniques. The steps include: (1) formally propose 

any change to the Guideline models/modeling methods in the Federal Register; (2) explain the 

basis for such proposed change, including documentation on the satisfactory performance of any 

new model or modified model, especially for the conditions to which it is to be applied; (3) 

consider a peer review mechanism as part of this comment process that evaluates the scientific 

principles, implementation of the principles into the model, and verification of any changes (peer 

review should include EPA ORD, academia and stakeholders); (4) give the States, regulated 

entities, modeling community, and the public a meaningful opportunity to comment on the 

proposed change(s); and (5) review and respond to any significant comments received during the 

notice-and-comment rulemaking, and as a result of any peer review. One commenter (BP) 

suggested that EPA develop a multi-step process over the next two years that facilitates changes 

to Appendix W, and incorporates the changes by reference without having to update Appendix 

W in its entirety. In conclusion, it was argued that EPA must assure that the performance of 

Guideline models is unbiased and does not lead to over predictions that force unnecessary action 

to address problems that aren’t present in the real world. Modeling required by EPA should be 

transparent and open, facilitating engagement and collaboration with the modeling community. 

The turnaround time for evaluating changes to all guideline models, when those changes appear 

to better represent the current state of science, should be improved.

2.6 Ad-hoc Guidance, Clarification Memos, and Clearinghouse Activities

Commenters (DE, BP, NMA, Koogler, FI, AF&PA) also recommended that EPA propose 

implementation guidance/rulemaking at the same time new NAAQS are proposed through a 

notice and comment process that allows for stakeholder input, and necessitates an EPA response 

to those comments. It is postured that current regulatory practices consistently rely on untested 

models with hastily developed ad hoc agency “guidance”, including “clarification memoranda”, 

the Modeling Clearinghouse, internal memoranda to the EPA Regional Air Division Directors, 

general guidance memoranda, implementation guides, and draft/revised user’s guides. This ad 

hoc guidance has the effect of making promulgated standards significantly more stringent 

without formal rulemaking and is inconsistent with the Clean Air Act and basic principles of 

administrative law, relies on clearly unacceptable alternatives to notice-and comment 

rulemaking, and lacks any form of outside peer review, instead of encouraging and accepting 

stakeholder review and input. Moreover, repeated application of model algorithms beyond the 

scopes of their evaluated and recognized applicability and capability are simply not “good 

science”. Such EPA guidance was developed over the past two years to address a variety of 

previously unrecognized and/or underappreciated consequences of the new NAAQS. Even so, 

the most recent of such memos contain ambiguities, logical inconsistencies, unscientific 

recommendations and superfluous requirements, some of which are also contrary to the 

Appendix W modeling guidance. As a result of changes to the model, preprocessors and 

guidance, model performance must be reevaluated before use in demonstrating compliance with 

the SO2 NAAQS. Furthermore, EPA should provide appropriate notice, and an opportunity for 

comment, prior to finalizing the rule requirement to use ambient air quality modeling for any 

approach, including a “hybrid” approach, to establish nonattainment areas. Overall, a deliberate 

rulemaking approach that seeks formal public input would be a more appropriate means for 

establishing modeling requirements that are firmly grounded in fundamental scientific principles. 
7

Finally, as noted by one commenter (Koogler), the Model Clearinghouse should be 

revised in its content and its method of review and approval of updates to meet the demands of a 

shift to using modeling as a “hybrid” approach (i.e., monitoring to determine NAAQS status with 

modeling as an indicator). Also, EPA should not issue modeling guidance as non-binding if it 

intends to later treat that guidance as binding; there is a necessity for such guidance and related 

documentation in the Clearinghouse to undergo the rigors of proposed rules and the rulemaking 

process.

3.0 Comments on Development of Schedule to Address Comments and Implement 

Model Changes

Several commenters (Hunton & Williams for NAAQS Implementation Coalition, 

American Petroleum Institute, BP America, National Environmental Development Association’s 

Clean Air Project, Duke Energy, Camille Sears) recommended that EPA identify and develop a 

prioritized listing of all modeling deficiencies/issues, model fixes, and modeling studies that 

were identified as a result of the 10th Modeling Conference. A plan for near-term, mid-term and 

long-term focus should be developed (with outside peer review) that details specific Agency 

projects, budgets, timetables, completion dates, and methods to address these issues. Some 

commenters indicated a willingness to work with the Agency to appropriately address the issues.

EPA should discuss the plan with the modeling community, solicit input from 

stakeholders on the list of projects and the project priority, and publish the plan for public 

comment. During this planning and vetting process, EPA should provide interim solutions for 

situations where there is not an appropriate model at this time, and enhance case-by-case support 

to State and Local agencies on what models and protocols to use. At the end of this process, 

time to implement the modeling changes should be allowed, prior to requiring that sources 

demonstrate compliance with new NAAQS.

Following are general timetables and specific issues/projects that were suggested by 

individual commenters; Duke Energy and Camille Sears did not individually suggest detailed 

timetables

3.1 Hunton and Williams for NAAQS Implementation Coalition

1. Near-Term – Solutions for modeling problems that have already been developed and 

provided to EPA on which actions can be taken at least on an interim basis.

a. AERMOD overstates ambient impact of fugitive particulate emissions – use a 

preprocessing step that would reduce emission factors for fugitive sources of PM 

which parallel the EPA-approved approach to modeling fugitive emissions with 

CMAQ; similar fixes are also applicable to fugitive emissions of SO2 and NO2. (see 

references)

b. AERMOD substantially over-predicts at low wind speeds – adjust “critical wind 

speed” and minimum hourly averaged sigma (see reference)

c. AERMOD does not model buoyant line sources – use BLP for final plume rise and 

model sources in AERMOD as volume sources.

d. AERMOD can be improved for NO2 concentration estimates – implement ARM2 for 

predicting the ratio of NO2 to NOX as a more refined Tier 3 method.
8

e. Updates to CALPUFF (version 6) provided to EPA improves the chemistry and other 

upgrades that produce significantly improved performance for NO2 over the default 

FLAG chemistry options.

f. Improve implementation of newer NAAQS by clarifying or changing EPA policy

i. EPA should issue guidance reminding Regions/States that the use of monitoring 

data, particularly for existing sources, may be appropriate in characterizing source 

impacts.

ii. Provide guidance for prediction of ambient concentrations based on treatment of 

emissions from existing sources and determination of background concentrations. 

It is unrealistic to assume that all modeled point sources operate continuously at 

their maximum permitted or enforceable emission rate; modeling with actual 

emission should be considered if they are available. Variability of emissions 

should be considered and maximum allowed emissions should not be set at the 

level of the actual emissions, e.g., steel industry. Also, emphasize use of 

background concentrations based on monitors near sources and paired in time 

with relevant meteorological conditions.

iii. Less conservative levels should be used for SILs. They should be based on the 

percentile values on which compliance with the NO2 and SO2 NAAQS are 

judged, not the highest predicted impact.

2. Mid-Term – issues that require rulemaking over the next year or two; there is no need to 

wait for the next modeling conference.

a. Include both industry-developed model modifications, as well as EPA modifications 

including changes involving AERMINUTE, BPIP and AERSURFACE.

b. Consider AERMINUTEPlus developed by EPRI which is currently undergoing 

testing.

c. Establish SILs to define when a source’s impact is sufficiently small to eliminate the 

need for a comprehensive air quality analysis.

d. Provide interim solutions for situations where there is not an appropriate model at this 

time and provide a plan for developing appropriate models, e.g., hourly NO2 impacts 

of proposed sources could be limited to annual estimates based on BACT for NOX, 

monitoring to insure compliance with the 1-hour NAAQS, and a plan to end 

“unforeseen difficulties”.

3. Long-Term – issues that require new research.

a. A model to estimate the contribution of an individual source to ambient 

concentrations of PM2.5 and ozone with the required complex chemistry and 

meteorology.

b. The impact of fugitive PM2.5 emissions.

c. Performance re-evaluation of preferred models, e.g., AERMOD with newer 

modifications and for 1-hour concentrations in a probabilistic form consistent with 

new NAAQS. This may be accompanied by the need for new databases with respect 

to near-field impacts, impacts in complex terrain and low wind speed conditions.

d. Characterization of uncertainty in modeled concentrations and treatment of 

uncertainty in demonstrating NAAQS compliance. This is particularly important in 

multi-model applications such as those associated with the secondary NO2 and SO2

NAAQS.
9

Generally develop and demonstrate modeling tools that provide realistic and relatively certain 

predictions as new NAAQS are developed.

3.2 American Petroleum Institute

Key recommendations for EPA action are summarized below for implementation periods 

characterized as Short-Term (0 – 1 years), Mid-Term (1 – 3 years) or Long-Term (3+ years). 

1. AERMOD NO2 Plume Chemistry –

a. (ST) Issue guidance allowing use of Ambient Ratio Method 2 (ARM2) as a Tier 2 

method. 

b. (ST) Continue collaborating with the API on improvements to the PVMRM (a Tier 3 

method). Make the AERMOD PVMRM formulas (e.g., relative dispersion) consistent 

with the original formulations by Hanrahan. 

c. (MT) Evaluate other more sophisticated NO2 plume chemistry models such as 

SCICHEM and RPM; adopt those plume chemistry models if the more complete 

chemical mechanisms provide significantly better accuracy than AERMOD/PVMRM. 

d. (LT) Consider new NO2 field experiments involving shorter stacks, source emissions 

sampling, and ground level sampling where ozone, NO and NO2 are measured.

2. AERMOD Over-predictions in Stable Low Wind Conditions 

a. (ST) Resolve the stable low wind problem with AERMOD by means of sciencebased revisions to the boundary layer and dispersion formulas. Specific technical 

recommendations are listed in the attached report and are a combination of 

recommendations from the Paine et al. (2010) report plus more recent analyses. 

b. (ST) Change the critical wind speed in the AERMOD formula for deriving u* in very 

stable conditions, thus increasing u* as well as turbulent speeds and the derived 

mixing depth during low wind conditions. 

c. (ST) Increase the “minimum σv and σw” so as to avoid very low values which lead to 

unrealistic over-predictions of concentrations. 

d. (ST) Modify the weighting factors in the AERMOD low wind method of averaging 

the meander (pancake) and coherent plumes. The meander (pancake) component 

should receive a larger weighting than at present. 

e. (MT) Change the wind and temperature profiling methods in AERMOD so as to 

assure smoother profiles in conditions when the input wind observation height is 

above or near the mixing height at night. 

f. (LT) Explore better use of sub-hourly (2 min average) meteorological data available 

from the NWS airport sites.

3. CALPUFF Regulatory Model 

a. (ST) Adopt the current version of CALPUFF with improved chemistry (e.g., v 6.42) 

as the regulatory version. 

4. AERMOD GEP Stack Height Formula and Building Downwash Modeling 

a. (ST) Return to the previous practice of allowing “Equivalent Building Dimensions” 

(EBDs) for open lattice and porous structures and allow CFD models to contribute to 

the decision process. 

b. (MT) Evaluate the accuracy of plume downwash conditions for short stacks and light 

wind speeds using the AGA and other relevant databases; vertical profiles of 

meteorology in stable conditions should also be reviewed. 
10

5. AERMOD Extrapolation of Airport Wind Observations to Other Sites 

a. (ST) Return to the previous 3 km radius method for estimating surface roughness 

length zo around a site. The recent change to a 1 km radius is too small. 

b. (LT) Use resistance relations suggested by Blackadar and Zilitinkevich to more 

realistically develop wind profiles at the modeled site. 

6. Use of Observed Emissions and Monitored Concentrations 

a. (ST) EPA should issue a reminder to the Regional offices and the states regarding the 

availability of the option in Section 10.2.2 of Appendix W for use of monitoring in 

lieu of modeling when there are no suitable models for use in NSR permitting.

b. (ST) SO2 area designations should be made primarily using monitoring data as 

opposed to using model-predicted concentration estimates.

7. Regional Chemistry Models (CMAQ, CAMx, and others) 

a. (MT) Regional chemistry models should have a larger role in the EPA Air Modeling 

Conferences. While there is an annual CMAS conference, it does not provide a 

formal mechanism for public review and comment

8. Background Concentrations

a. (ST) The background concentrations should conform to the averaging times (e.g., one 

hour, one day, annual) and the spatial domain (e.g., 10 km, 100 km, 500 km) of the 

scenario being modeled. 

b. (LT) Methods should be devised for use in defining and determining background 

concentrations in areas with many sources at local and mesoscale distances to void 

problems such as double-counting in modeling for compliance determinations. 

9. Model Evaluation and Data Bases 

a. (ST) The modeling community should have easy access to all field and laboratory 

data bases used by the EPA to develop and evaluate models. EPA should keep this 

information on a devoted server and include adequate metadata. 

10. Collaboration among EPA, Stakeholders and Researchers 

a. (ST) EPA should consider the comments from the 10th Modeling Conference and 

develop a research plan and schedule for addressing modeling issues. 

b. (ST) There should be communication and coordination within EPA (e.g., OAQPS and 

ORD), and external communication and collaboration with stakeholders such as 

industries, state agencies and consulting companies who must use the models, and 

with national and international scientists who are working on improving models. 

(ST) EPA OAQPS should continue to use a technical work group to suggest technical solutions 

and provide technical review of new models and model revisions.

3.3 BP America

An EPA plan should address the recommendations provided below.

1. Use of Air Quality Models in a Regulatory Setting (ongoing activity over the next 0-2 

years) – EPA should get input from stakeholders and publish its determination that 

demonstrates model accuracy is sufficient to meet the current policy needs. If EPA 

concludes that model accuracy does not provide a tool for policy use, then alternative 

approaches that could be used for meeting current policy needs include coupling 

modeling and monitoring and use of modeling in more of a relative mode as in the case 
11

of PM and ozone modeling, or to base compliance with the NAAQS using a combination 

of BACT and ambient monitoring as allowed under Section 10 of the Guideline

2. Determination of Model Accuracy – EPA Model Evaluations (ongoing activity over the 

next 0-2 years) – EPA should re-examine the previous AERMOD evaluations for a 1-

hour period and determine what limitations exist in the current model evaluations that 

need further analysis; model accuracy should be tested and conclusions reached regarding 

sub-categories such as stack height, downwash, and meteorological conditions (including 

low wind speeds).

3. Low Wind Speeds (short term high priority to address over the next year) – EPA should 

review the API low wind speed modifications to AERMOD and suggest modifications to 

address deficiencies, then subject model revisions to peer review and public comment; 

until review and revisions to AERMOD are completed, EPA should revert to the previous 

definition of calm wind speed (<1 m/s = calm). 

4. NO2 1-hour Modeling (short term high priority to address over the next year) – EPA 

should review and implement the NO2 Ambient Ratio Method 2 and corrections to 

AERMOD PVMRM that API has identified; evaluate other NO2 models beyond 

AERMOD PVMRM and OLM such as SCICHEM. 

5. Overarching Procedural Concerns (ongoing activity over the next 0-2 years) – EPA 

should develop a process that facilitates changes to Appendix W. When changes are 

required, EPA needs to publish draft changes, accept comments, respond to comments in 

a final document, and incorporate the changes by reference without having to update the 

entire Appendix W. 

6. EPA also needs to develop a peer review process. Such a process needs to evaluate the 

scientific principles, implementation of the principles into the model and evaluate the 

verification of any changes. Peer review must include EPA ORD, academia and other 

stakeholders. In addition, EPA must adequately address the concerns raised by any peer 

review group. 

7. EPA should change the model clearinghouse process to allow the regulated community to 

bring questions and proposals directly to OAQPS if the states and the regions deny them.

8. AQRV Analysis (short term high priority to address over the next year) – EPA should 

incorporate the new version of CALPUFF that API had developed which includes both 

corrections to errors in the existing gas-phase chemistry module, as well as incorporation 

of new science modules for inorganic and organic aerosols and aqueous-phase chemistry 

into the Guideline. Related steps include:

a. Add a post-processing step to recalculate inorganic aerosol equilibrium at receptor 

locations to address lack of treatment of ammonia limitation for multiple or 

overlapping puffs. 

b. Add an upper limit for particulate nitrate formation that is based on the amount of 

ammonia available in the background in CALPUFF to prevent the output of 

particulate ammonium nitrate concentrations that are physically unrealistic and when 

CALPUFF does not conserve mass of ammonia (as is the case in the current model).

c. Incorporate into the Guideline CALPUFF with the improved RIVAD chemistry.

9. Portable Sources (short term high priority to address over the next year) – EPA needs to 

revise the February 2012 memo regarding modeling of temporary sources. BP has 

outlined an approach that can be used to address impacts or sources that do not remain at 

a fixed location for a 3-year period.
12

3.4 The National Environmental Development Association’s Clean Air Project

High priority, near-term (3 months) refinement of EPA’s preferred dispersion Models

1. Allow use of AERMINUTE permissively but do not mandate its use.

a. Allow sources to use available air monitoring data to pair monitored values and 

hourly emissions.

b. By waiving the use of AERMINUTE, incentivize partnerships between state air 

authorities and sources for the collection of real time meteorological data.

2. Aggressively prioritize refinements to AERMOD for modeling building downwash for 

low wind speeds and cases with large or long buildings.

a. Approve approaches for accurately modeling buoyant plumes from line/volume

sources.

b. Allow the use of post construction monitoring at receptors with high predicted 

impacts to allow construction of new sources and provide technical input for model 

refinements. If necessary, back up monitoring with permit conditions if certain values 

are exceeded.

3. Prioritize refinements to dispersion models for low wind speeds. In the interim, establish 

or set a lower wind speed threshold of 1 meter per second.

4. Allow a set ground level 1st layer mixing height at 68 meters (minimum) pending 

completion of technical work to confirm a lower mixing height is real and suitable for 

use.

5. Recognize and use the form of each NAAQS to determine the modeled design value. 

Just as EPA allows modeling of the 8th high for NO2 (98th percentile), and 4th high for 

SO2 (99th percentile), modeling for PM2.5 should evaluate the 8th high (98th percentile). 

6. Approve modelers’ use of the American Petroleum Institute’s corrections to AERMOD 

PVMRM for NO2, the NO2 Ambient Ratio Method 2, the low wind modifications to 

AERMOD, and the new version of CALPUFF with updated chemistry.

7. Give careful consideration to avoiding double-counting impacts in modeling and 

background. In particular, background should be determined on an event basis.

4.0 Comments Related to AERMOD

4.1 Low Wind Speeds

Since EPA is advocating the use of computer models to determine nonattainment for 

sources, several commenters (NIC, DE, AF&PA) note that EPA must provide accurate, stable 

modeling tools and guidance for industry during periods of significant capital investments to 

meet new regulatory requirements. EPA must also require improved model performance to 

ensure that the control measures required of sources are appropriate without being excessive. 

However, it is argued that AERMOD significantly over predicts SO2 concentrations, especially 

at low wind speeds, and thus the current models are not reliable enough to be used as the basis 

for classifying an area as nonattainment. An analysis by one commenter (DE) shows the model 

predicts that receptors located in the vicinity of the monitors would not attain the one-hour SO2

standard, while the actual on-site monitors show that the facility is complying with the standard. 

EPA should make needed changes to update the regulatory modeling system by addressing wellcharacterized bugs and systematic performance issues, prioritize refinements to dispersion 
13

models especially those for low wind speeds, and then establish a stable modeling platform for 

consistent use during implementation of new regulatory programs.

Commenters (NIC, UARG, EPRI, EEANC, OPC, API, BP, AISI, WMA, ACW, BGNA, 

PE, AF&PA, NDDH) indicate that a performance re-evaluation of preferred models, e.g., 

AERMOD, with newer modifications and for 1-hour concentrations in a probabilistic form 

consistent with new NAAQS is necessary; this may be accompanied by the need for new 

databases with respect to near-field impacts, impacts in complex terrain, and low wind speed 

conditions. Model performance evaluations should focus on the highest (upper quantile) 

predictions, and need not include distribution where observations have fallen to less than 

minimum detectable values. Topics such as treatment of low wind speeds, terrain height 

variations, AERMINUTE, downwash effects, actual emission rates, national consistency in 

selection of model input data, application of AERSURFACE with land cover data bases, and the 

basis for determining roughness length (AERMET) all require further attention by EPA, as well 

as the opportunity for public input. EPA should re-examine the previous AERMOD evaluations 

for a 1-hour period and determine what limitations exist in the current model evaluations that 

need further analysis; model accuracy should be tested and conclusions reached regarding subcategories such as stack height, downwash, and meteorological conditions (including low wind 

speeds). Commenters (NIC, UARG) urge that both industry-developed model modifications, as 

well as EPA modifications, should be considered in improvements to AERMOD, including 

changes involving AERMINUTEPlus, BPIP and AERSURFACE. One commenter (Sears) notes 

though that contrary to comment by some industry representatives, AERMOD’s evaluation 

analyses do include a number of site-specific meteorological data sets that incorporate low wind 

speed conditions.

A number of examples are given by commenters (NIC, UARG, EPRI, EEANC, OPC, 

API, BP, AISI, NMA, NEDA, AF&PA, FI) regarding a perceived lack of evaluation and 

consequence analysis for changes to AERMOD after it was formally promulgated. Inclusion of 

low wind speeds (<1 mps) which result in higher concentrations, especially with AERMOD and 

low level sources is most frequently addressed. It is claimed that AERMOD’s tendency to 

overestimate concentrations at low wind speeds is exacerbated by implementation of AERMET 

and AERMINUTE. There has not been sufficient justification and verification regarding the 

validity of the resulting estimates. AERMINUTE was implemented with access to many 

Automated Surface Observing System (ASOS) stations that have sonic anemometer 

instrumentation with a near-zero starting wind speed threshold; this change has not received 

public review and comment. In general, EPA should review low wind speed modifications to 

AERMOD to better simulate transport and dispersion that are proposed by various commenters 

and suggest modifications to address deficiencies; model revisions should then be subjected to 

peer review and public comment. For example, EPA is urged to act expeditiously to (1) adopt 

the fix developed by AECOM for AERMOD under low wind speed conditions, (2) adopt 

recommendations made by Paine & Heinold, (3) approve modelers’ use of API’s corrections to 

the low wind modifications to make AERMOD’s predictions more accurate, and/or (4) consider 

EPRI’s approach (SHARP) to run with AERMOD that allows the model to simulate low wind 

conditions more accurately and has undergone evaluation on two low wind speed databases. 

Generally, there should be a thorough review and attention to all associated model formulation 

issues. Until review and revisions to AERMOD are completed and tested to more accurately 
14

simulate transport and dispersion under low wind speed conditions, many commenters 

recommend that AERMOD results for low wind speeds (<1 mps) are not valid and should not be 

included in model results (as is currently the case for “calm” conditions) until these AERMOD 

revisions are implemented and tested. For the interim, EPA should revert to the previous 

definition of calm wind speed (<1 mps = calm); EPA should also allow a set ground level 1st 

layer mixing height at 68 meters (minimum) pending completion of technical work to confirm a 

lower mixing height is real and suitable for use. Furthermore, the use of AERMINUTE should 

be allowed permissively, but its use should not be mandated; by waiving the use of 

AERMINUTE, incentives for partnerships between state air authorities and sources for the 

collection of real time meteorological data can be pursued.

Other specific recommendations to deal with AERMOD over-predictions in stable low 

wind conditions include: (1) address API/UARG technical recommendations on AERSURFACE 

changes that have effectively reduced the surface roughness and consequently changed the wind 

profile in stable conditions, resulting in higher concentrations; (2) resolve the stable low wind 

problem with AERMOD by means of science-based revisions to the boundary layer and 

dispersion formulas (specific technical recommendations are listed in an attached report and are 

a combination of recommendations from the Paine et al. (2010) report plus more recent 

analyses); (3) change the critical wind speed in the AERMOD formula for deriving u* in very 

stable conditions, thus increasing u* as well as turbulent speeds and the derived mixing depth 

during low wind conditions; (4) increase the “minimum σv and σw” so as to avoid very low 

values which lead to unrealistic over-predictions of concentrations; (5) modify the weighting 

factors in the AERMOD low wind method of averaging the meander (pancake) and coherent 

plumes to receive a larger weighting than at present; (6) change the wind and temperature 

profiling methods in AERMOD so as to assure smoother profiles in conditions when the input 

wind observation height is above or near the mixing height at night; (7) explore better use of subhourly (2 min average) meteorological data available from the NWS airport sites; (8) incorporate 

urban canopy formulas in AERMOD for wind and turbulence profiles in urban dispersion 

conditions; and (9) treat industrial facilities with substantial “fugitive heat” releases as urban 

areas.

Commenters (API, NDDH) also suggest that, for AERMOD (AERMET) modeling, 

surface characteristics for the primary source location should be used, rather than the 

meteorological data (wind measurement) site. EPA has provided no substantive justification, nor 

side-by-side performance tests, on why use of surface characteristics for the primary source 

location isn’t preferable. A return to the previous 3 km radius method for estimating surface 

roughness length zo around a site is justified, since the recent change to a 1 km radius is too 

small; use of resistance relations suggested by Blackadar and Zilitinkevich to more realistically 

develop wind profiles at the modeled site is appropriate.

Another commenter (EEANC) argues that models use a one-hour time increment that is 

inappropriate for a one-hour standard. Too much weight is given to the rare times when the wind 

direction lines up with a particular receptor; the variation of wind direction within the hour is not 

accounted for in the meteorological data used in the modeling and therefore biases the results 

when compared to a one hour standard. AERMOD might be modified to more easily identify

meteorological conditions and model details which would promote broader understanding of 
15

sensitivities and case-specific model attributes. A suggestion by another commenter (AEPSC) 

for dealing with 1-hour issues is to use short term meteorological data in the model itself and 

integrate these shorter increments into a one hour value.

4.2 Treatment of Downwash

Several commenters (EEANC, OPC, API, A&WMA, FI, Exponent, Coulter) note that 

EPA has modified the AERMOD code to consider potential downwash effects for stack heights 

that equal or exceed the EPA GEP formula height. This code modification seems to represent a 

revision to the algorithms within the model and appears to overturn 25 years of regulatory policy 

and guidance with respect to modeling the emissions from stacks whose heights equal or exceed 

the Good Engineering Practice (GEP) formula height; emissions from stacks whose heights 

exceed the GEP formula height are now subject to the calculation of aerodynamic downwash in 

any Appendix W guideline model. One commenter (Exponent) further pointed out that the 

chances made to AERMOD are an extrapolation of the PRIME algorithm beyond the range of 

data used in its development. There has been no opportunity for public comment and no 

justification or consequence analysis has been provided. Until EPA provides a justification and 

consequence, the change to downwash procedures should be removed from the regulatory 

version of AERMOD and there should be a return to the previous practice of allowing (1) 

“Equivalent Building Dimensions” (EBDs) for open lattice and porous structures and (2) use of 

CFD models to contribute to the decision process. An independent peer review and evaluation 

should be conducted for stacks above formula height; the evaluations should be bundled with the 

independent review and evaluation of the effective length parameter in BPIPPRM. Ultimately, 

public peer review and comment should be allowed for this model change.

Several commenters (AISI, API, NMA, A&WMA, NEDA) note that changes made to the 

downwash code with AERMOD version 11059 lead to significant increases in predicted 

concentrations for light winds (<1 mps) and for unique building (wide/long) shapes with short 

stacks. EPA has presented no data to justify the technical basis for the specific algorithms used 

above GEP formula height or a consequence analysis of changes, especially for long buildings 

where the effects are greatest; also, the changes did not undergo public review or comment. As a 

result, the commenters indicate that: (1) the PRIME downwash algorithm for light winds (< 1 

mps) and excess heat releases should be limited until profiles of wind, temperature and 

turbulence during periods of light winds and stable conditions are improved; (2) the accuracy of 

plume downwash conditions for short stacks and light wind speeds should be evaluated using the 

AGA, and other relevant databases and vertical profiles of meteorology in stable conditions 

should also be reviewed; (3) EPA should aggressively prioritize refinements to AERMOD for 

modeling building downwash for low wind speeds and cases with large or long buildings; (4) 

any new model changes such as effective building dimensions should be subject to a transparent 

public review process with independent scientific review and evaluation prior to its use in 

regulatory applications; (5) EPA should consider proposed threshold wind speeds for downwash 

effects to minimize AERMOD over-prediction of building downwash for certain geometries and 

wind speeds; (6) while the known problems with AERMOD for long buildings are being 

addressed, EPA should allow Section 3.2 Petitions (use of alternative models) to address the 

problem with AERMOD for very wide buildings, such as aluminum reduction facilities; (7) EPA 

should approve approaches for accurately modeling buoyant plumes from line/volume sources; 

and (8) EPA should approve the use of post construction monitoring at receptors with high 
16

predicted impacts to allow construction of new sources, provide technical input for model 

refinements, and if necessary, back up monitoring with permit conditions if certain values are 

exceeded.

On commenter (A&WMA) suggests that, since EBD may be the only alternative to 

obtaining accurate concentration estimates for some building configurations, a method is needed 

to streamline the process for using EBDs. Some things that would help streamline this process 

are: (1) clear guidelines on how to conduct an EBD study; (2) interaction with the ultimate 

decision makers at EPA in the protocol development and approval process; (3) actual EPA 

approval of the EBD protocol prior to conducting the study; (4) cooperative interaction with EPA 

during the EBD study and preliminary report phase where results are reviewed and if necessary 

changes made to the EBD testing method prior to issuance of a final report; (5) a timely review 

and approval process; and (6) some assurance that once a final report is issued, the EBD values 

will be approved for use. Two optional methods whereby this streamlined process could be 

developed for EBD include: (1) form an Industry/EPA work group tasked with developing 

guidance for conducting EBD evaluations; this guidance could then be published like that for 

determining GEP stack heights and could include a checklist reviewed by EPA to ensure that all 

studies are conducted in a consistent manner; or (2) wait for the next EBD protocol to be 

submitted to the EPA Model Clearinghouse for review and comment; once the protocol is 

completed and approved, it could be used as a template for future EBD studies.

4.3 Modeling Domain Limitation

Several commenters (EPRI, API, WMA, ACW, BGNA, PE) note that EPA considers 50 

km as the appropriate distance for the applicability of a steady-state model without a clear 

scientific basis. Commenters claim that analyses have been conducted demonstrating that a more 

reasonable distance limit for steady-state models used for hourly applications, such as those 

required by the one-hour NO2 and SO2 NAAQS, is 20 km. The use of a steady-state model 

beyond 20 km can result in unrealistically high modeled concentrations and therefore is not 

recommended; it is highly likely that multiple hours of transport are required and as such, the 

typical hour-by-hour changes in the transport winds and dispersion conditions lead to distortions 

in steady-state model predictions. Inter-model comparisons reveal the expected over-prediction 

for a steady-state vs. a non-steady-state model, which are clearly evident for receptor distances 

exceeding 20 km.

Commenters recommend that, unless meteorological conditions are persistent (similar 

wind speed and direction) in succeeding hours, model-predicted concentrations at receptors 

beyond the one-hour travel distance should not be accepted as meaningful. AERMOD should be 

modified to delete such concentrations from the output, or at least provide a notification to the 

user to disregard such results in interpreting the model output. EPRI has developed additional 

code that provides warnings on predictions for transport exceeding one hour; the information in 

this file will be useful for determining general information for the plume transport from each 

source to the receptor with the highest hourly concentration.

More importantly, commenters (EPRI, NDDH, Koogler) point out that for cumulative 

modeling involving other sources, it is presumed that an inventory of sources out to the 

applicable modeling distance (50 km) must be obtained; the use of an overly large distance for
17

the applicability of a steady-state model is expected to generally result in a misrepresentation of 

the source-to-receptor transport and dispersion, as well as an over-prediction tendency for the 

worst-case concentration. This is another reason for limiting the application of AERMOD to 

distances of 20 kilometers or less; that is, AERMOD should be used only when all nearby 

sources are located within 20 kilometers of the subject or primary source. If nearby sources 

(which must be included in the cumulative analysis) are located more than 20 kilometers from 

the primary source, the steady-state AERMOD model will not be adequate, and CALPUFF (or 

possibly similar dynamic model) should be used instead. Similarly, there are limitations to 

AERMOD in areas of complex terrain and in areas where there is a significant land/water 

interface. Due to the steady-state transport limitation of AERMOD, there is a tendency to overprediction of impact at mid-range and long-range target receptors. As a consequence, 

commenters (EPRI, API) suggest that EPA plan for use of a Lagrangian puff model like 

CALPUFF/SCIPUFF at distances less than 50km, and at all distances within the next few years.

4.4 AERMOD Update Process

Several of the commenters (UARG, EPRI, SC, DE) noted, specifically with regard to 

changes in AERMOD, model updates and policy decisions that EPA has not offered the public a 

chance to review and comment, nor allowed for peer review. This is true since the time that 

AERMOD was promulgated, even though such developments have significantly changed the 

model’s predictions for various conditions and applications. These developments include: 

meteorological inputs to AERMOD (e.g., the performance of AERMOD with the AERMINUTE 

processor) and the treatment of GEP stack height and downwash (e.g., the change to AERMOD 

in MCB #4 that alters the PRIME downwash algorithms). Because of the potential impact on the 

regulated community and the wealth of external technical experience available, EPA must 

reconsider the entire AERMOD system (AERMOD, preprocessors and modeling guidance), 

including AERMAP, AERSURFACE, AERMET and AERMINUTE. It is noted that modeling 

systems for CALPUFF must be treated in a comparable way, and the above public notice and 

rulemaking process needs to be followed for all modeling systems. Also, the model version 

relied upon by the State and EPA must remain valid for clearly defined time periods or on the 

basis of some predictable measure that provides the regulated community assurance of the valid 

application of a model and its results, e.g. revision to AERMOD downwash.

4.5 Buoyant Line Sources

Commenters (NIC, AISI) note that AERMOD does not model buoyant line sources. As a 

result, they recommend that BLP be used for final plume rise on an hourly basis and that sources 

be modeled as volume sources in AERMOD.

5.0 Fugitive Dust Comments

5.1 Treatment of Emissions and Modeling for Surface Mines

Commenters (NIC, NMA, AISI) expressed concern that EPA emission factors and 

models like AERMOD overstate the short-term ambient impacts of fugitive particulate 

emissions, especially those from surface mines. This can be resolved by using a preprocessing 

step that reduces emission factors for fugitive sources of PM that parallels the EPA-approved 

approach to modeling fugitive emissions with CMAQ; similar fixes are also applicable to 
18

fugitive emissions of SO2 and NO2. A number of source modeling related issues/findings are 

identified: (1) AERMOD is designed to predict steady state emissions from stacks, and has not 

proven capable of accurately predicting contributions to ambient concentrations from the 

fugitive, mobile, and variable sources; (2) significant work has been done to assess the 

underlying technical problems contributing to the over-prediction bias for non-stack sources in 

AERMOD that are driven by multiple layers of conservative assumptions, including 

uncertainties associated with fugitive emissions or other non-stack sources and unique dispersion 

characteristics and depletion/removal features associated with these sources; (3) the overprediction bias can be reduced by use of actual hourly emissions or reasonable worst case 

emissions rates in their absence, actual meteorological data instead of worst case assumptions, 

and actual monitored background concentrations; (4) plausible receptor locations should be used 

where the public has reasonable access and can stay stationary for the entire period associated 

with an ambient standard, rather than including transportation corridors; and (5) use of ambient 

monitoring is the only way to reliably measure the ambient impact of surface mine fugitive 

sources.

To improve model performance, two commenters (NMA, AISI) recommend that EPA

implement several readily available revisions that address emissions preprocessing related to 

near-source plume-depletion mechanisms and conservative source configuration properties. 

These include: (1) considering the concept of “transportable fractions” of fugitive dust as a 

function of ground cover bordering the source of the fugitive dust in AERMOD applications; (2) 

applying a 50% reduction for haul road and for pits, as well as a 50% reduction for other fugitive 

particulate emissions from mining operations to account for plume depletion mechanisms and 

inadequate treatment of plume dynamics by AERMOD; (3) applying a preprocessing reduction 

of 75% for fugitive particulate emissions within the confines of the pit to account for 

AERMOD’s improper representation of pit retention; and (4) improving how AERMOD treats 

haul roads, slag pits, and material handling by how the source is represented in the model input 

using techniques described in attached materials. Field test data should subsequently be obtained

to confirm the magnitude of the reduction factor.

In addition, several commenters (WMA, ACW, BGNA, PE) note that EPA guidance for 

intermittent sources, e.g., blasting activities at surface mines, is vague and overly conservative 

and that States have adopted various interpretations. AERMOD, which assumes continuous and 

constant emissions over a one-hour time span, is not capable of validly modeling the nearly 

instantaneous blasting source; in its regulatory form it is not an appropriate methodology, as 

ground-level concentrations are generally over-predicted. Field studies that are well-designed 

are required to better define blasting emissions and dispersion, the results of which could be used 

to better analyze the assessment of blasting impacts. A probability approach to quantifying 

blasting impacts would be appropriate, rather than determining the maximum possible impact 

given blasting on some or all hours of the year. EPA should provide definitive guidance for 

modeling this type of source that is based on a realistic evaluation of the likelihood that an 

intermittent source will threaten the standards, and should be supported by sound science; see 

example relative to probability-based approaches. This approach would permit EPA to avoid the 

necessity for extensive modeling analyses, and would also prevent the need for unnecessary 

source modifications that result from overly conservative impact estimates.
19

5.2 Relevance to CAA, Section 234

Commenters (NMA, WMA, ACW, BGNA) indicated that the application of currentlyapproved models to fugitive particulate emissions from surface mining operations, as well as to 

the 1-hour NO2 and SO2 standards, is of concern. EPA’s assessment of these operations must 

begin with a longstanding congressional mandate (i.e., CAA Section 234). That section of the 

CAA indicates that there may be unacceptable performance of EPA models and emission factors 

when applied to fugitive particulate emissions from surface mining operations on a short term 

basis, and it establishes alternative regulatory approaches when EPA’s models and emission 

factors result in excessive and unacceptable levels of over-prediction. In addition, AP-42 notes 

that haul road emission factors should be used with caution and awareness of their likely 

limitations. To date, no satisfactory revisions have been made to models or emission factors. Yet 

current regulatory practice has required the modeling of fugitive emissions on a short term basis 

from surface mining operations in almost every state except Wyoming.

These commenters also state that a memorandum of agreement indicates that ISC3 will 

not be used for regulatory application involving surface coal mines, and that monitoring in lieu 

of modeling is acceptable for assessing coal mining-related impacts in the Powder River Basin. 

Replacement of ISC3 with AERMOD doesn’t rectify this. EPA must re-visit the statutory 

prohibition/mandate before either EPA or the States require future modeling of PM10 and PM2.5

emissions from surface mining operations on a short-term basis. In addition, one commenter 

(BGNA) notes, concerning unacceptable performance of EPA models, that even though Section 

234 specifically addresses surface coal mines, the factors and modeling algorithms that are 

uncertain for coal mining operations are equally uncertain for other types of surface mining 

activities; therefore, there is no scientific basis for these air models to treat hardrock surface 

mining different from surface coal mining. Until emission factors and modeling methods can be 

shown to provide accurate predictions, EPA has to adhere to the statutory prohibition that 

prevents it from relying on dispersion models for particulate impacts associated with surface coal 

mining activities.

6.0 Comments Related to CALPUFF

6.1 Adoption of Improvements to CALPUFF

Many Commenters (NIC, UARG, APS, SRP, Tri-State, West, API, BP, NDDH, NEDA, 

and FI) indicate that the EPA-recommended version of CALPUFF should always be the most 

technically advanced. As a result, they believe that EPA should replace out-dated CALPUFF 5.8 

with the scientifically superior version of CALPUFF (e.g., v 6.42). Updates/upgrades to 

CALPUFF (version 6) provided to EPA improve the chemistry and produce significantly better 

performance for NO2 over the default FLAG chemistry options. The new chemistry module has 

been proposed, tested and evaluated; studies demonstrate that CALPUFF 6.4 has superior 

predictive capability when compared to CALPUFF 5.8’s over prediction of nitrates. In addition, 

CALPUFF Version 6.4 has been found to provide equivalent results to the regulatory version 

(5.8) when the same options and data are used. The new version (6.4) is “backward compatible” 

with the regulatory version when run with the same inputs and data, if the new chemistry option 

is turned off and the bug-fixes are applied in CALPUFF 5.8. Supporting documentation on the 

relative performance of subject versions of CALPUFF is provided by commenters. Due to the 
20

demonstrated superiority of the chemistry in CALPUFF 6.4, its more accurate predictions of 

particulate nitrate formation, and its wide acceptance in the scientific community, EPA should 

encourage modeling demonstrations using CALPUFF 6.4 for NOX emission reductions.

In any case, these commenters believe that CALPUFF documentation needs to stay 

current with the recommended version of the model. CALPUFF should be upgraded to correct 

all known bug fixes and other minor updates should be implemented immediately as released in 

model change bulletins (or users should be allowed to implement bug fixes themselves) without 

any testing requirement. EPA should implement the well documented enhancements that have 

been developed since the 9th Modeling Conference, following the timely opportunity for public 

comment and participation. To save time, testing to support new versions should be based on 

third party as well as EPA evaluations. More specifically, for AQRV analyses, EPA should 

incorporate the new version of CALPUFF which includes both corrections to errors in the 

existing gas-phase chemistry module, as well as incorporation of new science modules for 

inorganic and organic aerosols and aqueous-phase chemistry into the Guideline. Related steps 

include: (1) adding a post-processing step to recalculate inorganic aerosol equilibrium at 

receptor locations to address lack of treatment of ammonia limitation for multiple or overlapping 

puffs; (2) adding an upper limit for particulate nitrate formation that is based on the amount of 

ammonia available in the background in CALPUFF to prevent the output of particulate 

ammonium nitrate concentrations that are physically unrealistic and when CALPUFF does not 

conserve mass of ammonia (as is the case in the current model); and (3) incorporating into the 

Guideline CALPUFF with the improved RIVAD chemistry. In addition, other improvements to 

CALPUFF’s chemistry modules developed by stakeholders should be considered; materials 

documenting these improvements have been provided, but EPA has not acted upon them.

6.2 Relationship of CALPUFF v6.4 to BART Rule

With regard to the BART rule, while EPA endorsed CALPUFF as the best modeling tool 

available in 2005, commenters (Tri-State, APS) indicate that EPA specifically recognized that 

the model was less than perfect. EPA committed in the 2005 BART rule to evaluate “newer” 

approaches, but has not acted on the matter in the following seven years. It is clear from the 

BART rule that each analysis should be based on the “best application [currently] available” to 

predict visibility impacts; the best application and information “currently available” is now the 

new, more refined version CALPUFF 6.42b. EPA should adopt enhancements to the regulatory 

version of CALPUFF (specifically CALPUFF 6.42) in implementing the Regional Haze Rule 

relative to BART as expeditiously as possible, particularly as applicable to NOX emission 

reductions. EPA should review and approve MCBs E, F, and G and conduct its own review of 

the tests/evaluations of the new version of the CALPUFF model as soon as possible before final 

BART determinations are made later this year. This updated version of CALPUFF has already 

been placed in the public domain and additional tests have been completed and reported at the 

10th Modeling Conference. As needed, EPA should conduct its own tests and evaluations of the 

new version of the CALPUFF model as soon as possible, before final BART determinations are 

made. If those tests duplicate findings described at the Tenth Modeling Conference, then EPA 

should move expeditiously to designate CALPUFF 6.4 as the regulatory version of the model for 

BART determinations. Such an approach is consistent with the process EPA has used for recent 

changes to the AERMOD model.
21

Commenters (Tri-State, APS, SRP, West) indicate that EPA’s 2005 BART Guidelines 

acknowledged the need for CALPUFF 5.8 updates, since the regulatory-approved CALPUFF 

version 5.8 may overestimate the amount of nitrate produced from point source NOX emissions, 

and chemistry modules in CALPUFF 5.8 are less advanced than more recent atmospheric 

chemistry simulations. Comparisons of field measurements of sulfates and nitrates with 

corresponding values predicted by CALPUFF 5.8 indicate that the model over predicts 

particulate nitrate formation by as much as a factor of three to four under wintertime conditions. 

Work has been done to improve the model’s chemistry module and reduce the over-prediction. 

Comparisons with the two versions of the model show conflicting results on benefits of 

additional control technology to improving visibility in Class I areas; CALPUFF 6.4 showed no 

perceptible improvement. In addition, predicted sulfate and nitrate concentrations obtained by 

applying the two versions of the model were compared with actual measured values obtained at 

the Bridger Wilderness Area site and the Pinedale site. For the two model configurations, the 

results for sulfates were very similar, which was expected because the improvements to the 

CALPUFF chemistry were anticipated to have the most impact on nitrate predictions. The EPAapproved CALPUFF version was found to over-predict nitrates by a factor of two to three.

6.3 Application of Appendix W, Section 3.2 to CALPUFF v6.4

In conclusion, commenters (APS, West) recommend that EPA move expeditiously to 

either designate CALPUFF 6.42b as the regulatory version of the model for BART 

determinations, or in the interim, under Section 3.2 of Appendix W, allow EPA Regional 

Administrators to approve use of CALPUFF 6.4b as an alternative model on a case-by-case basis 

in all proposed applications. Such an approach is consistent with the process EPA has used for 

recent changes to the AERMOD model. The new chemistry, as well as the entirety of 

CALPUFF version 6.4.2 can be accepted for BART determinations, since Section 3.2 is designed 

to allow use of important model enhancements or alternative models in a timely way on a case 

by case basis, without the 3 to 5 year wait for formal rulemaking. Appendix W Section 3.2.2 

indicates that an alternative model is acceptable if “a preferred air quality model is not 

appropriate for the particular application.” In this case, CALPUFF 5.8 chemistry, especially for 

formation of winter nitrate, appears to be inapplicable because the MESOPUFF II formulation is 

based upon field testing with ambient temperatures of 50°F and higher. It is evident from the 

chemistry mechanisms that the nitrate equilibrium is highly sensitive to temperature and is most 

critical in conditions for which there are no observations for the MESOPUFF II formulation. The 

weight of evidence of the new evaluation information provided here and the clear limitations of 

the chemistry in CALPUFF 5.8 makes it imperative for EPA to allow immediate use of 

CALPUFF 6.42b for nitrate chemistry. Additional industry-supported improved models and 

modeling techniques, such as SCICHEM, SHARP and EMVAP tools, are under development 

and will be shared with EPA soon.

6.4 Application of CALPUFF to Nearby Sources

Several commenters (NDDH, BGNA, AEPSC, NMA) suggest that the Gaussian model 

formulation (e.g., AERMOD) that has been used for many years for near-field modeling may not 

be appropriate for all modeling of short term standards, such as those for SO2, NO2, and possibly 

CO. This is particularly true where varied and extensive complex terrain exists in an area of 

multiple sources, and this terrain extends from the sources to the location of receptors where 

design concentrations are expected. Non-steady state models, such as a Lagrangian puff model 
22

like CALPUFF, are theoretically more appropriate for such applications, particularly when 

paired with meteorological models and their superior handling of atmospheric behavior in 

generating realistic input meteorology (e.g., three-dimensional wind fields). In contrast, 

AERMOD uses only meteorological data and surface characteristics from one site. CALPUFF’s 

handling of nearby sources (farther than 20 kilometers) is thus thought to be superior to 

AERMOD’s, and similar overall performance of CALPUFF should make it a preferred 

alternative in such cases involving nearby sources. EPA should acknowledge the potential 

applicability of alternative models for appropriate situations and consider making a replacement 

with a Lagrangian puff formulation, e.g., CALPUFF/SCIPUFF, as the preferred model for 

modeling of 1-hour standards, and work more diligently to review the updates being made to 

CALPUFF or SCIPUFF, as they may have a place in one hour modeling. Such a change (e.g., 

from AERMOD to CALPUFF for nearby sources) will require notice and comment rulemaking, 

along with the time to upgrade the existing models or develop a new model that would 

incorporate all of the necessary technical changes to significantly improve abilities to model the 

new 1-hour standards. EPA should begin moving down this path to allow the use of a superior 

model formulation for future SIP development and permit modeling.

More specifically, one commenter (Koogler) stated that CALPUFF should be an 

approved alternative model without the need for the justification required by Section 3.2, 

Appendix W, 40 CFR 51, rather than AERMOD, in multi-source situations (including those for 

which the impact of multiple sources are calculated to determine “background”). For 

consistency with AERMOD, another commenter (NDDH) suggests that the dispersion setting 

used with CALPUFF (MDISP) should be Option 2, turbulence-based dispersion, rather than the 

currently recommended PG dispersion. CALPUFF even provides an implementation of the 

turbulence dispersion which makes it equivalent to the AERMOD dispersion. Also, EPA should 

test use of MDISP=2, micrometeorological variables or turbulence dispersion, in CALPUFF and 

approve its use where it is shown to be superior.

Another commenter (NDDH) suggests that it may be advantageous to replace the 

“AERMOD near field” and “CALPUFF far field” scheme with a single dynamic model capable 

of covering all distances from 0 to 300 kilometers (or more). The SCIPUFF model may be an 

acceptable alternative to CALPUFF. It would appear that both CALPUFF and SCIPUFF could 

effectively serve as a single tool, even in their current iterations.

6.5 Individual Source Impacts on PM2.5 and Ozone

In addition to the comments on CALPUFF, commenters (AF&PA, NIC, NDDH) 

recommended that EPA develop PM2.5 guidance that can be practically implemented, e.g., adopt 

a reasonable approach to estimate impacts of secondary PM2.5 that appropriately reflect spatial 

and temporal impacts relative to primary PM2.5. Also, a priority long-term development effort is 

needed for a model to estimate the contribution of an individual source to ambient concentrations 

of PM2.5 and ozone with the required complex chemistry and meteorology.
23

7.0 NAAQS Compliance Demonstration Comments

7.1 NAAQS Compliance Demonstration General Comments

Several commenters (NIC, UARG, EEANC, SC, AISI, NMA, NEDA, AF&PA) indicate 

that EPA should develop and demonstrate modeling tools that support realistic predictions as 

new NAAQS are developed. It is inappropriate to use computer models to implement the CAA 

where modeling does not yield the best information.

Concern has been expressed (EEANC SC AISI NMA) that models are increasingly being 

given deference over measurements from ambient monitors for attainment designations; 

measurements should be the gold standard, and modeling used to inform those measurements. 

Continuing to apply models with existing but outdated guidance is inappropriate. EPA should 

perform an overall re-evaluation of the Agency’s policies and procedures that drive its 

determinations regarding the application of regulatory modeling; modeling should not used to 

determine nonattainment areas, or any other regulatory obligation, until AERMOD is validated 

with measured values. Then, EPA should revise Appendix W and establish modeling guidelines 

that allow for flexibility and more realistic assumptions in all modeling applications, and assure 

that guidelines allow the use of the most accurate and up to date models and techniques 

available. For example, EPA’s proposal to use modeling to designate attainment is different 

from past practice. Where AERMOD has been applied in New York modeling, results indicate 

large one-hour impacts. However, the extensive monitor network (current and retired monitors) 

does not show any NAAQS exceedances. This type of modeling should not be used to determine 

attainment designations.

Several commenters (NIC, AISI, NEDA, AF&PA) note that the models and modeling 

approaches set forth in Appendix W are inadequate for implementing EPA’s newer and most 

stringent NAAQS; they fail to realistically predict relevant concentrations of covered pollutants 

in ambient air. In many circumstances, modeled concentrations that spur regulatory attention 

are, in fact, unrealistically high and lead to unreasonably conservative outcomes. There will be 

significant difficulty in permitting new or expanded sources as a result of theses inadequate tools 

and guidance for addressing the implementation of new NAAQS. The requirements for states to 

model thousands of sources using flawed tools will result in mandates for unnecessary controls 

on existing sources and, in some cases, make continued operation infeasible. In addition, EPA 

should recognize and use the form of each NAAQS to determine the modeled design value. Just 

as EPA allows modeling of the 8th high for NO2 (98th percentile), and 4th high for SO2 (99th

percentile), modeling for PM2.5 should evaluate the 8th high (98th percentile). Also, EPA should 

reconsider the policy that considers NAAQS effective for PSD permitting purposes immediately 

upon issuance, and instead institute a minimum 1-year transition period before new NAAQS 

would be considered applicable. Implementation guidance should be developed at the same 

time, and such guidance subjected to a notice and comment process that allows for stakeholder 

input.

7.2 Ambient Air

Commenters (NMA, AISI, AF&PA) recommend that EPA should align expectations for 

modeled ambient air receptors with realistic expectations of general public exposure. Most 

important is the determination of the ambient air boundary to make a reasonable determination in 
24

cases where human exposure is unlikely. EPA should adopt more plausible assumptions about 

receptor locations where the public has reasonable access and can stay stationary for the entire 

period associated with an ambient standard, e.g., don’t include rights-of-way or transportation 

corridors such as public roads and railroads that transect facility property.

7.3 Background Concentrations

Several commenters (NIC, AEPSC, API, NEDA) emphasize use of enhanced background 

calculation procedures where the necessary data exist. Background concentrations should be 

based on monitors near sources, paired in time with relevant meteorological conditions, and 

should conform to the averaging times (e.g., one hour, one day, annual) and the spatial domain 

(e.g., 10 km, 100 km, 500 km) of the scenario being modeled. Some commenters (WMA, ACW, 

BGNA, PE) also indicate that current guidance based on use of the 98th or 99th percentile 

monitored background values are unrealistically conservative. Guidance is needed for pairing 

model-predicted concentrations with monitored concentrations in-time to obtain a realistic 

projection of whether or not a potential exceedance is likely, and to eliminate double counting of 

impacts from modeled sources and those impacts represented in background monitoring data, 

particularly in areas with many sources at local and mesoscale distances. Where representative 

regional monitoring data exist, there should be no requirement to model regional sources whose 

impacts can reasonably be presumed to be reflected in the monitoring data.

Commenters (FI, Koogler) claim that EPA’s recommendation for deriving NO2 and SO2

background concentrations is unnecessarily stringent and unscientific; there is a need for an 

improved method to account for background concentrations that better address the cause and 

effect relationships that exist between the actual hour-by-hour meteorological conditions that 

produce both the predicted impacts of the modeled sources and the actual measured background 

concentrations. To obtain the most appropriate background concentration for the target area, 

consideration should be given to using a “frequency of occurrence” approach, rather than the 

uniform background concentration typically used in AERMOD.

One commenter (AF&PA) suggests EPA’s interim guidance for PM2.5 screening analyses 

is impractical, and unreasonably overestimates the design concentration relative to the NAAQS, 

since it inherently assumes that the day with multi-year average maximum model impact is 

coincident with the day of the 98th percentile background concentration. The “Paired Sums” 

approach should be allowed to account for background PM2.5 in the calculation. Case studies are 

provided following current EPA guidance to assess PM2.5 impacts using prescribed screening 

techniques and compared with a “Paired Sums” approach; most sources cannot demonstrate 

compliance with the PM2.5 NAAQS under current EPA guidance despite being well controlled.

7.4 Significant Impact Levels for revised 1-hour NO2/SO2 and PM2.5 NAAQS

Several commenters (NIC, AISI, AF&PA, OPC) have expressed concern about the 

conservative nature of SILs for pollutants with new NAAQS. They argue that less conservative 

levels should be used for SILs that are based on the percentile values on which compliance with 

the NO2, SO2 and PM2.5 NAAQS are judged, not the highest predicted impact. SILs should be 

established to define when a source’s impact is sufficiently small to eliminate the need for a 

comprehensive air quality analysis.
25

Overly conservative SILs and conservative modeling assumptions can lead to large SIAs 

and, even relatively small maintenance and construction projects, can trigger permitting 

requirements. However, guidance on SIAs in not clear and help has not been provided to 

relevant State efforts. EPA’s interim guidance for PM2.5 screening analyses for PM2.5 is 

impractical, since measured background PM2.5 concentrations, except for designated 

nonattainment areas, are consistently below the current NAAQS by a small margin. Adequate 

tools and guidance for sources to quantify PM2.5 emissions, including off-site emissions, and to 

model ambient impacts for the 1-hour NAAQS are needed.

7.5 1-hour NO2/SO2 NAAQS

7.5.1 1-hour NO2/SO2 NAAQS General Comments

Several commenters (API, SC, DE, AEPSC) note that the promulgation of more stringent 

NAAQS and requirements for 1-hour modeling, including the proposed use of modeling for SO2

area designations have resulted in the need for improved modeling methods and evaluation. 

AERMOD has many flaws that come out when the new 1-hour SO2 and NO2 Standards are 

analyzed. AERMOD has not been thoroughly evaluated for performance in simulating the 

maximum daily 1-hour concentration at the 99th percentiles (or 98th for NO2), especially for low 

wind speed cases that are the most impacted situations. Prescribing emission limits for such a 

stringent standard from the results of an unproven model could result in significant and 

unnecessary costs and burdens. If EPA finalizes these modeling requirements for SIP submittals, 

it should allow States the discretion to use modeling and analysis tools to help demonstrate 

situations where sources have a low probability of violating the standard, rather than prescribe 

overly conservative models that lead to unnecessarily stringent controls. Furthermore, it is 

thought inappropriate to use AERMOD in its current form as the primary tool for determining 

attainment or non-attainment with the current one-hour SO2 NAAQS. It is argued that the model 

has demonstrated a high probability of over predicting actual ground level SO2 concentrations; 

this excessive conservatism will impose burdensome and unnecessary requirements on the 

regulated community that are not necessary for attainment of the standard or to protect public 

health. There were a number of good suggestions made as to ways to “fix” AERMOD, including 

a statistical method to formulate the emissions input data, use of short term meteorological data, 

and improvements to methods of converting NOX to NO2 in the model. While these 

improvements should be made to the preferred model, a far more significant change may be 

needed to be truly able to model the 1-hour. Additional modeling studies, model revisions, and 

guidance are needed. 

On the other hand, one commenter (Sears) offers the opinion that, in virtually all cases, 

air dispersion modeling should be used to determine one-hour SO2 impacts from coal-fired 

power plants and other major SO2 emission sources; modeling should be applied in all situations 

except where source-specific SO2 monitoring exists and the monitor is properly located to 

capture maximum facility impacts. All NO2, PM2.5, and SO2 NAAQS and PSD increment 

compliance verification analyses should be performed with air dispersion modeling, such as 

running AERMOD in a manner consistent with the Guideline on Air Quality Models. Another 

commenter (NIC) suggests that characterization of uncertainty in modeled concentrations and 

treatment of uncertainty in demonstrating NAAQS compliance is particularly important in multimodel applications such as those associated with the secondary NO2 and SO2 NAAQS.
26

Another commenter (EEANC) suggests that rather than classify large portions of the 

country as unclassifiable, EPA should classify those areas that are not obviously in nonattainment as unclassifiable/attainment, particularly where there is no monitoring evidence that 

there is a widespread attainment problem with the 1-hour SO2 NAAQS. Also, this commenter 

thought it necessary to develop guidance for a probabilistic emission limit, e.g., use of the 90th 

percentile actual emission rate and the 90th percentile predicted concentration to represent the 

“ambient” concentration at the 99th percentile level. The potential to establish this kind of limit 

and to be able to enforce it is particularly intriguing for electric generating units that have 

continuous emissions monitoring systems in place.

7.5.2 1-hour NO2 – Refined Tier 2 and Tier 3 Methods, ARM2 Implementation, and Field 

Studies

Several commenters (NIC, AEPSC, API, BP, AISI, NEDA, AF&PA) recommend that 

AERMOD be reviewed and improved for NO2 concentration estimates by implementing ARM2 

for predicting the ratio of NO2 to NOX, as a more refined Tier 2 or Tier 3 method. Also, 

improvements to the PVMRM (as a Tier 3 method) should be pursued; at a minimum, the 

AERMOD PVMRM formulas (e.g., relative dispersion) should be made consistent with the 

original formulations by Hanrahan and approved for use. Other more sophisticated NO2 plume 

chemistry models such as RPM and SCICHEM should be evaluated; those plume chemistry 

models should be adopted if the more complete chemical mechanisms provide significantly 

better accuracy than AERMOD/PVMRM. Once Tier 3 NO2 modeling techniques are updated, a 

streamlined approval process should be enabled at the state/local level for facilities applying 

sector/source-specific data. Also, new NO2 field experiments involving shorter stacks, source 

emissions sampling, and ground level sampling where ozone, NO and NO2 are measured should 

all be considered.

7.5.3 1-hour NO2 – NO2 to NOX Ambient Equilibrium Ratios and In-stack Emissions 

Ratios

Several commenters (AF&PA, OPC, FI) note that the NO2 to NOX ratio recommended by 

EPA is highly restrictive and conservative. Data provided for the 10th Modeling Conference 

should be reviewed and revisions to 1-hour NO2 NAAQS analyses (Tier 2) considered to better 

accommodate variations in the ambient ratio; it is also recommend that EPA allow in-stack 

NO2/NOX ratios that are significantly lower (e.g., 20%) than the EPA default value of 50% 

(examples are provided). Furthermore, there is a lack of clarity regarding the acceptance criteria 

for deriving and using both source-specific in-stack NO2/NOX emission rate ratios and a sitespecific NO2/NOX ambient equilibrium ratio, and when it is necessary to use “default” ratios of 

0.5 and 0.9, respectively, as AERMOD model input. There is also a lack of clarity regarding 

acceptance criteria for selecting and utilizing background O3 and NO2 ambient air quality 

monitoring sites and data, when utilizing the Plume Volume Molar Ratio Method (PVMRM) 

algorithm in AERMOD to calculate the total concentrations attributable to the modeled sources 

plus the background concentrations.

7.5.4 1-hour SO2 – Use of Variable Emissions and EMVAP Implementation

Several commenters (NIC, UARG, EPRI, AF&PA, BP) recommend that EPA develop 

guidance for prediction of ambient concentrations based on treatment of actual emissions from 
27

existing sources. It is unrealistic to assume that all modeled point sources operate continuously 

at their maximum permitted or enforceable emission rate; use of allowable emission rates at all 

times in AERMOD results in over-predictions. At a minimum, EPA should commit to 

development of modeling tools and implementation guidance that simulates actual emissions 

profiles, rather than the conservative assumption that all sources emit simultaneously and 

continuously at the maximum allowable rate; examples are provided. Development of an 

emissions variability processor should be made a priority to account for substantial differences in 

actual and allowable emissions. In the end, EPA should consider adopting a tiered approach --

the use of constant allowable emission rates with a more refined approach that accounts for 

inherent variability in emission rates; Tier 2 -- a conservative approach to estimating actual 

emissions; Tier 3 -- actual hourly emissions for model input.

More specifically, several commenters (EPRI, EEANC, SC, AEPSC, AISI, NMA) note 

that Appendix W stipulates that for sources subject to emission limitations, the short-term 

modeling should use allowable emission rates, design capacity, and assume continuous 

operation. However, for a modeling vs. monitoring study summarized at the 10th Modeling 

Conference, it is shown that use of allowable emission rates at all times in AERMOD results in 

over-predictions for retrospective applications, and leads to overly conservative estimates of 

future impacts when used in prospective applications. Any retrospective modeling of a source 

that is meant to estimate past impacts from the source (and other nearby sources) should use 

actual observed emissions, with actual meteorology and actual stack parameters. Any deviation 

from this approach leads to a misrepresentation of past conditions. For prospective modeling of 

potential future impacts from a point source, rather than “potential to emit”, a statistical approach 

to formulate the emissions input data, since the emission standard is statistical in nature, that 

implements a newly developed tool known as the Emissions Variability Processor (EMVAP) for 

AERMOD is recommended. Incorporation of emissions variability in any analysis of existing 

sources, particularly for electrical generating units that have extensive hourly records of 

emissions, by incorporating some sort of statistical emissions input would be appropriate; 

examples of other source types that can demonstrate compliance with the 1-hour average SO2

NAAQS with “typical”, rather than allowable, emissions operations are also provided. Ways to 

incorporate EMVAP for treating source emissions uncertainties and intermittent sources should 

be considered in implementing a variable emission rate limit. For example, AZ examples for 

multipoint rollback are available for enforceable permit limits based upon a probabilistic 

emissions model; States should have the discretion to use tools such as the Emissions Variability 

Processor with less restrictive emission limits that still achieve the NAAQS goals.

On the other hand, another commenter (Sears) notes that where actual emissions are used 

for nonattainment SIP modeling, a condition must be added to the facility permit requiring that 

emissions must not be greater than the level used in the modeling analysis. Also, actual 

emissions cannot be modeled using full load stack parameters; stack gas exit velocity and 

temperature is reduced under less than full load conditions, affecting plume rise and resulting 

modeled impacts. Any AERMOD modeling using actual emission levels must use corresponding 

actual stack gas exit velocity and temperature.
28

Finally, one commenter (BP) notes that EPA needs to revise the February 2012 memo 

regarding modeling of temporary sources. An approach is outlined that can be used to address 

impacts of sources that do not remain at a fixed location for a 3-year period.

7.6 PM2.5 NAAQS

Commenters (AISI, FI, APFA) express concern about significant over-prediction for 

particulate emissions and other pollutants, particularly when applied to complex facilities with 

multiple non-stack sources and irregular emission rates. Those over-predictions may prevent or 

hinder the development and construction of projects that in actuality would not have 

unacceptable ambient air quality impacts. Models used to implement the NAAQS must be 

improved to address such flaws prior to NAAQS implementation. Issues that have been 

identified as a problem and also have viable technical solutions include: fugitive particulate 

matter modeling; un-validated revisions to AERMOD that include over-predictions for low wind 

speed periods; the use of reasonable operating scenarios as inputs; and downwash algorithm 

anomalies; a presumption that secondary formation of PM2.5 from precursors occurs at the same 

time and location that primary pollutants have their greatest impact. Another issue is the small 

margins that exist between the NAAQS and the background concentrations that will greatly 

magnify the adverse consequences of the tendency of AERMOD to over predict air quality 

impacts. Generally, there is a need for PM2.5 modeling and implementation guidance that can be 

practically implemented, for example use of the 98th percentile design concentration consistent 

with the form of the standard; such guidance requires sufficient time for effective review and 

comment.

7.7 Monitoring in Lieu of Modeling

Several commenters (NIC, UARG, EEANC, API) recommend that when regulators, or 

regulated entities, have ambient measurements of pollutant concentrations, recorded by an EPAapproved monitor at an EPA-approved location, those data -- not model predictions – should be 

relied upon in determining the attainment status of areas and for other purposes. In particular, 

SO2 area designations should be made primarily using monitoring data, as opposed to using 

model-predicted concentration estimates. Guidance should “account for and consider the 

existing monitoring networks that are specifically designed to determine SO2 impacts from 

dominant sources”. In situations where an assessment determines that the monitoring network is 

adequate, then monitoring alone should be used to determine the attainment status of the area. 

When monitoring data from approved monitors are not yet available, regulators and regulated 

sources should be given a reasonable opportunity to collect needed monitored data in lieu of 

requiring them to rely on modeling predictions of the ambient impacts of existing sources.

Commenters (NIC, API, BP, AISI, NMA, NEDA, AF&PA, FI) provide additional details 

on how to enable permitting authorities to rely upon representative ambient monitoring results in 

lieu of, or as a supplement to, modeling results for decision–making. More specifically, EPA 

should issue a reminder to the Regional offices and the states regarding the availability of the 

option in Section 10.2.2 of Appendix W for use of monitoring in lieu of modeling when there are 

no suitable models or when modeling is less acceptable than monitoring to demonstrate 

compliance with the 1-hour average NO2 and SO2 NAAQS; see various examples given at the 

10th modeling conference. As indicated in Section 10, if EPA concludes that model accuracy 
29

does not provide a tool for policy use, then alternative approaches that could be used for meeting 

current policy needs include coupling modeling and monitoring and use of modeling in more of a 

relative mode (as in the case of PM and ozone modeling), or to base compliance with the 

NAAQS using a combination of BACT and ambient monitoring. State/local permitting 

authorities should be allowed to rely upon representative ambient monitoring data and emissions 

trends, to make decisions that reflect actual air quality conditions and impacts. For surface mine 

sources, EPA should authorize the use of monitoring data to demonstrate compliance with shortterm PM10, PM2.5, SO2 and NO2 NAAQS, just as it has for use of SO2 monitoring for “sources 

that may not be conducive to modeling”. EPA should reconsider its policy requiring PM2.5

modeling analyses for maximum modeled concentrations instead of more refined estimates of the 

design value; guidance must provide more flexible and refined approaches that enable the use of 

available monitoring data to make reasonable estimates of cumulative impacts. Finally, for 

proposed new sources or major modifications of existing sources, permits should include 

conditions that address how monitoring would be done and what happens if exceedances of 

standards are monitored.

On the other hand, another commenter (Sears) argues that air dispersion modeling should 

be the preferred method for determining one-hour SO2 impacts. In order to ensure consistency in 

how air impacts are determined, both existing sources and newly permitted sources should be 

assessed using the same methods. If existing sources are allowed to use monitoring, which are 

generally not “well-placed” for measuring the maximum ambient air impacts form existing 

sources, this results in a lower standard of compliance verification than that being used for new

permit applicants.

One commenter (EEANC) is concerned with an increasing quantity of issues that must be 

addressed and the resulting increase in the time necessary to prepare regulatory analyses. Prior 

to the latest revised NAAQS limits, air quality modeling had evolved into a pretty much 

standardized methodology that could be routinely prepared for the modeling protocol submittal 

and approved without much controversy. However, outside organizations are now running 

models that can project values exceeding the NAAQS limits and then demanding a response. The 

model clearinghouse will become embroiled in controversy when one modeling group makes a 

series of assumptions that result in predictions that contradict another modeling analysis. There 

are so many parameterizations, configurations and other tweaks that all are perfectly acceptable 

but lead to different results that controversy is the inevitable outcome. This is further justification 

for reliance on a robust monitoring network to determine attainment.

8.0 Emerging Models and Techniques Comments

8.1 Mesoscale Model Interface Program (MMIF) Comments

Commenters (EEANC, API) indicate that 3-D prognostic meteorological models for 

inputs to dispersion models are a useful modeling approach, particularly when coupled with a 

shorter time step for one-hour source assessments. However, until EPA has shown that the 

model field agrees well with measured wind fields, this approach may not be appropriate; see the 

Eastern Lake Ontario Meteorological Study. Test runs with AERMOD and CALPUFF must be 

completed, documented and made available for public comment to show that meteorological 
30

models provide comparable performance compared to standard inputs, before adoption of these 

techniques can go forward.

8.2 Single Source PM2.5 and Ozone Modeling

One commenter (Sears) specifically supports the use of single-source PM2.5 and ozone 

photochemical grid modeling for impact analyses and compliance demonstrations for major 

emission sources; comments on this same issue were provided at the 9th Modeling Conference 

and EPA responded in an affirmative manner relative to the Sierra Club Petition. State and 

Local agencies should be required to consult with the Regional meteorologists on a case-by-case 

basis for determining the best models to use for assessing such single-source impacts. Also, it is 

noted, with regard to Draft PM2.5 Permit Modeling Guidance, that further details/clarification are 

needed on various scenarios and on how they protect the PM2.5 PSD increments, not just 

compliance with the PM2.5 NAAQS.
A-1

Attachment A

Summary of 10th Conference on Air Quality Modeling Comment Submissions

A brief and bulleted summary of the comments formally submitted to Docket of the 10th

Conference on Air Quality Modeling are presented in this Attachment. This summary 

information is for general reference only and is not intended to supersede the actual comments 

submitted to the Docket. An Internet link to the conference Docket containing all of the 

comment submissions as well as the conference presentations and transcripts are listed in 

Attachment C.

NAAQS Implementation Coalition (Prepared by Hunton & Williams)

1. Overview

a. The models and modeling approaches set forth in Appendix W are inadequate for 

implementing EPA’s newer and most stringent NAAQS; they fail to realistically 

predict relevant concentrations of covered pollutants in ambient air. In many 

circumstances, modeled concentrations that spur regulatory attention are, in fact, 

unrealistically high. 

b. EPA should identify modeling issues for near-term, mid-term and long-term focus, 

and develop/share with the public a plan detailing the Agency’s anticipated dates and 

methods to address these issues (Coalition members would like to work with the 

Agency to appropriately address these issues).

2. Near-Term – Solutions for modeling problems that have already been developed and 

provided to EPA on which actions can be taken at least on an interim basis.

a. AERMOD overstates ambient impact of fugitive particulate emissions – use a 

preprocessing step that would reduce emission factors for fugitive sources of PM 

which parallel the EPA-approved approach to modeling fugitive emissions with 

CMAQ; similar fixes are also applicable to fugitive emissions of SO2 and NO2. (see 

references)

b. AERMOD substantially over-predicts at low wind speeds – adjust “critical wind 

speed” and minimum hourly averaged sigma (see reference)

c. AERMOD does not model buoyant line sources – use BLP for final plume rise and 

model sources in AERMOD as volume sources.

d. AERMOD can be improved for NO2 concentration estimates – implement ARM2 for 

predicting the ratio of NO2 to NOX as a more refined Tier 3 method.

e. Updates to CALPUFF (version 6) provided to EPA improves the chemistry and other 

upgrades that produce significantly improved performance for NO2 over the default 

FLAG chemistry options.

f. Improve implementation of newer NAAQS by clarifying or changing EPA policy

i. EPA should issue guidance reminding Regions/States that the use of monitoring 

data, particularly for existing sources, may be appropriate in characterizing source 

impacts.

ii. Provide guidance for prediction of ambient concentrations based on treatment of 

emissions from existing sources and determination of background concentrations. 

It is unrealistic to assume that all modeled point sources operate continuously at 

their maximum permitted or enforceable emission rate; modeling with actual 
A-2

emission should be considered if they are available. Variability of emissions 

should be considered and maximum allowed emissions should not be set at the 

level of the actual emissions, e.g., steel industry. Also, emphasize use of 

background concentrations based on monitors near sources and paired in time 

with relevant meteorological conditions.

iii. Less conservative levels should be used for SILs. They should be based on the 

percentile values on which compliance with the NO2 and SO2 NAAQS are 

judged, not the highest predicted impact.

3. Mid-Term – issues that require rulemaking over the next year or two; there is no need to 

wait for the next modeling conference.

a. Include both industry-developed model modifications, as well as EPA modifications 

including changes involving AERMINUTE, BPIP and AERSURFACE.

b. Consider AERMINUTEPlus developed by EPRI which is currently undergoing 

testing.

c. Establish SILs to define when a source’s impact is sufficiently small to eliminate the 

need for a comprehensive air quality analysis.

d. Provide interim solutions for situations where there is not an appropriate model at this 

time and provide a plan for developing appropriate models, e.g., hourly NO2 impacts 

of proposed sources could be limited to annual estimates based on BACT for NOX, 

monitoring to insure compliance with the 1-hour NAAQS, and a plan to end 

“unforeseen difficulties”.

4. Long-Term – issues that require new research.

a. A model to estimate the contribution of an individual source to ambient 

concentrations of PM2.5 and ozone with the required complex chemistry and 

meteorology.

b. The impact of fugitive PM2.5 emissions.

c. Performance re-evaluation of preferred models, e.g., AERMOD with newer 

modifications and for 1-hour concentrations in a probabilistic form consistent with 

new NAAQS. This may be accompanied by the need for new databases with respect 

to near-field impacts, impacts in complex terrain and low wind speed conditions.

d. Characterization of uncertainty in modeled concentrations and treatment of 

uncertainty in demonstrating NAAQS compliance. This is particularly important in 

multi-model applications such as those associated with the secondary NO2 and SO2

NAAQS.

e. Generally develop and demonstrate modeling tools that provide realistic and 

relatively certain predictions as new NAAQS are developed.
A-3

Utility Air Regulation Group (Prepared by Hunton & Williams)

1. Overview

a. Because modeling may play a role in so many CAA programs, it is vital that EPA 

include in Appendix W the best available models and modeling methods. EPA 

should take steps to ensure that improvements to Guideline models/methods are made 

systematically and expeditiously. 

b. EPA does not now consistently follow the best approaches for determining what 

models and modeling methods should be included in its Modeling Guideline, or for 

making revisions to Guideline models and modeling methods. 

c. EPA should continue to involve all stakeholders in helping to ensure that the best 

modeling tools are used in implementing the CAA.

2. Role of Models and modeling methods in CAA Implementation –

a. It is inappropriate to use computer models to implement the CAA where modeling 

does not yield the best information. 

b. When regulators or regulated entities have at hand ambient measurements of pollutant 

concentrations, recorded by an EPA-approved monitor at an EPA-approved location, 

those data -- not model predictions – should be relied upon in determining the 

attainment status of areas and for other purposes. 

c. In addition, when monitoring data from approved monitors are not yet available, 

regulators and regulated sources should be given a reasonable opportunity to collect 

needed monitored data in lieu of requiring them to rely on modeling predictions of the 

ambient impacts of existing sources.

3. Notice-and-comment rulemaking requirements for revising Guideline models/methods –

a. When it is necessary to add a model or modeling method to its Modeling Guideline, 

or to make revisions to the models and modeling methods currently in its Guideline,

EPA must first conduct notice-and-comment rulemaking on those actions. No 

significant change should be made to the Modeling Guideline or to Guidelinereferenced models and modeling techniques without EPA’s first (1) proposing any 

such change to the Guideline models/modeling methods; (2) explaining the basis for 

such proposed change, including documentation on how well any new model or 

modified model will perform for the conditions to which it would be applied; (3) 

giving the public a meaningful opportunity for comment on any proposed change; and 

(4) reviewing and responding to any significant comments that it receives during the 

notice-and-comment rulemaking. 

b. These general rulemaking requirements also apply to “clarification memoranda” 

concerning meteorological inputs to AERMOD and the treatment of GEP stack height 

and downwash when using AERMOD.

4. Following rules for including and revising models in the Guideline –

a. EPA should give tools developed by others, e.g., UARG and other industry groups 

and provided to EPA, that improve the accuracy of the models used for regulatory 

purposes the same consideration that it gives to tools developed by EPA. 

b. EPA is urged to act expeditiously to adopt the fix developed by AECOM for 

AERMOD under low wind speed conditions, and to adopt the other recommendations 

made by Paine & Heinold to make AERMOD’s predictions under these conditions 

more accurate. 
A-4

c. In addition, the development and evaluation of improvements to CALPUFF’s 

chemistry modules by West Associates and EPRI should be considered by EPA. 

Materials documenting these improvements have been provided, but the Agency has 

not acted on them. 

d. Additional industry-supported improved models and modeling techniques, such as the 

EPRI-sponsored SCICHEM, SHARP and EMVAP tools, are under development and 

will be shared with EPA soon.

5. Evaluation of models and modeling techniques for inclusion in the modeling guideline

a. Before a model can be approved for use, its performance must be evaluated and 

determined to be satisfactory. 

b. Not only must such an evaluation be conducted, but the conditions under which the 

model’s use is approved must be consistent with those under which its performance is 

evaluated, e.g., actual emissions or background concentrations.

6. Working with industry stakeholders –

EPA should work with stakeholders to promote a community approach to model 

development and acceptance that champions the use of best science, supports continual 

improvement in modeling science and data, and timely model acceptance for use in the 

regulatory arena, opening yearly state/local modeling meeting to all stakeholders.

7. Comments by AECOM –

a. Low Wind Speed – Evaluation and consequence analysis for AERMOD did not 

include low wind speeds, which result in higher concentrations, especially with 

AERMOD and low level sources. AERMINUTE makes it possible to utilize newer 

data with more frequent low wind speeds; this change has not received public review 

and comment. Likewise, changes to AERSURFACE have also been made with 

resulting higher concentrations. An API/UARG sponsored study has shown problems 

with low wind speed and AERSURFACE effects; a set of technical recommendations 

on AERSURFACE and treatment of low wind speed has been provided. There 

should be a thorough review and attention to all associated model formulation issues.

b. Model Emissions Input Data – Use of allowable emission rates at all times in 

AERMOD results in over-predictions. EPA should consider adopting a tiered 

approach. For example, Tier 1 -- the use of constant allowable emission rates with a 

more refined approach that accounts for inherent variability in emission rates; Tier 2 -

- a conservative approach to estimating actual emissions; Tier 3 -- actual hourly 

emissions for model input.

c. Model Updates and Policy Decisions – changes to AERMOD have been conducted 

without public review and comment, or peer review. EPA needs to provide the public 

with information regarding the change that would result from the model update and to 

develop a process by which the public could provide input and comment; a list of 

changes made without review for AERMOD and CALPUFF is provided.

d. Collaboration with the user community – It is desirable to involve and expand 

stakeholder and scientific input, similar to the planning conferences, into the future 

through a continued workgroup process. EPA needs to more frequently consult with 

and consider the advice of stakeholders, including the scientific community, into the 

future. The stakeholder community is prepared to assist EPA by providing useful 

information on model evaluation/improvement. These efforts could involve 

considerable investment in resources by stakeholders.
A-5

Electric Power Research Institute

1. Refinements for low wind speed modeling with AERMOD –

After AERMOD was promulgated, much higher predictions in comparison to other 

models such as ISC were experienced where wind speeds less than 1 mps were available; 

these concentrations often control the outcome of the modeling analysis. The peak 

concentrations are especially noticeable for low-level sources, which were not tested 

extensively during the AERMOD evaluation process. Since the time that AERMOD was 

promulgated, EPA has not offered the public a chance to review and comment on 

changes to AERMOD, even though developments since its promulgation have 

significantly changed the model’s predictions for light winds. Developments include: 

a. implementation of AERMINUTE with access to many Automated Surface Observing 

System (ASOS) stations that have sonic anemometer instrumentation with a near-zero 

starting wind speed threshold; 

b. introduction of AERSURFACE which has effectively reduced the surface roughness 

and consequent changes to the wind profile in stable conditions without adequate 

testing;

c. EPRI has developed an approach (SHARP) to run with AERMOD that allows the 

model to simulate low-wind conditions more accurately; the technique was presented 

at the 10th Modeling Conference and has undergone evaluation on two low-wind 

speed databases; after completion of evaluation. SHARP will be publicly released.

2. Distance applicability for steady-state Gaussian dispersion modeling –

a. EPA considers 50 km as the appropriate distance for the applicability of a steady-state 

model without a clear scientific basis. 

b. More importantly, for cumulative modeling involving other sources, it is presumed 

that an inventory of sources out to the applicable modeling distance (50 km) must be 

obtained; the use of an overly large distance for the applicability of a steady-state 

model is expected to generally result in a misrepresentation of the source-to-receptor 

transport and dispersion, as well as an over-prediction tendency for the worst-case 

concentration.

c. EPRI has conducted analysis that demonstrated that a more reasonable distance limit 

for steady-state models used for hourly applications, such as those required by the 

one-hour NO2 and SO2 NAAQS, is 20 km. The use of a steady-state model beyond 

20 km can result in unrealistically high modeled concentrations and therefore is not 

recommended. Beyond a distance of 20 km, it is highly likely that multiple hours of 

transport are required and as such, the typical hour-by-hour changes in the transport 

winds and dispersion conditions lead to distortions in steady-state model predictions. 

The inter-model comparisons reveal the expected over-prediction for a steady-state 

vs. a non-steady-state model, which are clearly evident for receptor distances 

exceeding 20 km.

d. EPRI has developed additional code (that does not interact with the dispersion 

modeling of AERMOD) that provides warnings for receptor-hour combinations that 

lead to predictions for transport exceeding one hour. The information in this file will 

be useful for determining general information for the plume transport from each 

source to the receptor with the highest hourly concentration. EPRI anticipates a 

release of this added code as a public beta before the end of July 2012 and will 

provide appropriate documentation and software.
A-6

3. Modeling Variable Emissions –

a. Appendix W stipulates that for sources subject to emission limitations, the short-term 

modeling should use allowable emission rates, design capacity, and assume 

continuous operation. For a modeling vs. monitoring study summarized at the 10th

Modeling Conference, it was shown that use of allowable emission rates at all times 

in AERMOD results in over-predictions for retrospective applications, and leads to 

overly conservative estimates of future impacts when used in prospective 

applications.

b. Any retrospective modeling of a source that is meant to estimate past impacts from 

the source (and other nearby sources) should use actual observed emissions, with 

actual meteorology and actual stack parameters. Any deviation from this approach 

leads to a misrepresentation of past conditions.

c. For prospective modeling of potential future impacts from a point source, EPRI 

recommends the use of a three-tier approach implementing a newly developed tool 

known as the Emissions Variability Processor (EMVAP) for AERMOD. EPRI is 

continuing to test EMVAP, and anticipates a release of this tool as a public beta 

before the end of July 2012. Consistent with such a public release, EPRI will provide 

appropriate documentation and software.
A-7

Environmental Energy Alliance of New York, LLC

1. Models use a one-hour time increment that is inappropriate to use for a one-hour 

standard. Too much weight is given to the rare times when the wind direction lines up 

with a particular receptor; the variation of wind direction within the hour is not accounted 

for in the meteorological data used in the modeling and therefore biases the results when 

compared to a one hour standard. 

2. Gridded meteorological analyses are a useful modeling approach, particularly when 

coupled with a shorter time step for one-hour source assessments. However, Until EPA 

has shown that the model field agrees well with measured wind fields, this approach may 

not be appropriate; see the Eastern Lake Ontario Meteorological Study. 

3. It is necessary to develop guidance for a probabilistic emission limit, e.g., use of the 90th 

percentile actual emission rate and the 90th percentile predicted concentration to 

represent the “ambient” concentration at the 99th percentile level. The potential to 

establish this kind of limit and to be able to enforce it is particularly intriguing for electric 

generating units that have continuous emissions monitoring systems in place. 

4. Rather than classify large portions of the country as unclassifiable, EPA should classify 

those areas that are not obviously in non-attainment as unclassifiable/attainment, 

particularly where there is no monitoring evidence that there is a widespread attainment 

problem with the 1-hour SO2 NAAQS. 

5. EPA’s proposal to use modeling to designate attainment is different than past practice. 

Where AERMOD has been applied in New York modeling results indicate large onehour impacts. However, the extensive monitor network (current and retired monitors) 

does not show any NAAQS exceedances. This type of modeling should be used to 

determine attainment designations.

6. NYSDEC previously recommended that guidance should “account for and consider the 

existing monitoring networks that are specifically designed to determine SO2 impacts 

from dominant sources”. In situations where an assessment determines that the 

monitoring network is adequate, then monitoring alone should be used to determine the 

attainment status of the area. That recommendation should be followed.

7. An over-arching issue has been the ever increasing quantity of issues that must be 

addressed and the resulting increase in the time necessary to prepare regulatory analyses. 

Prior to the latest revised NAAQS limits air quality modeling had evolved into a pretty 

much standardized methodology that could be routinely prepared for the modeling 

protocol submittal and approved without much controversy. This is undergoing 

significant change. Outside organizations are running the models that can project values 

exceeding the NAAQS limits and then demanding a response. The model clearinghouse 

will become embroiled in controversy when one modeling group makes a series of 

assumptions that result in predictions that contradict another modeling analysis. There are 

so many parameterizations, configurations and other tweaks that all are perfectly 

acceptable but lead to different results that controversy is the inevitable outcome. This is 

further justification for reliance on a robust monitoring network to determine attainment.

8. The Model Clearinghouse process does not allow technical input by the affected parties 

(e.g., permit applicant). Typically, the permitting authority states their opinion and asks 

for Clearinghouse approval and no other involvement is allowed. Because more 

controversy is expected the process needs to change. The Alliance endorses an approach 
A-8

whereby the affected parties are able to provide comment along with the permitting 

authority’s correspondence to the Clearinghouse.

9. Incorporation of emissions variability in any analysis of existing sources, particularly for 

electrical generating units that have extensive hourly records of emissions, by 

incorporating some sort of statistical emissions input would be appropriate; father 

development of the Emissions Variability Processor is appropriate. 

10. Low wind speed corrections, proposed by AECOM, should be implemented because 

wind speed is a critical factor in the elevated one hour concentration predictions. 

11. The change to downwash procedures should be removed from the regulatory version of 

AERMOD until independent peer review, consequence analyses, and evaluations are 

conducted for stacks above formula height; these evaluations should be bundled with the 

independent review and evaluation of the effective length parameter in BPIPPRM. 

12. All the dispersion field results should be placed in a single data archive for easy public 

access. Also suggestions at the 10 Modeling Conference related to model acceptance 

criteria should be considered in meeting concerns that the model clearinghouse is going 

to have to address more controversial issues. 

13. EPA should continue increasing their communications and collaborations with the many 

groups studying modeling issues and include the wider community in planning, model 

development and evaluation, and analysis and review of results.

14. AERMOD should be modified to more easily identify meteorological conditions and 

model details which would promote broader understanding of sensitivities and casespecific model attributes.
A-9

Southern Company

1. Overview – Models are increasingly being given greater deference than measurements 

from ambient monitors; measurements should be the gold standard, and modeling used to 

inform those measurements. Continuing to apply models with existing but outdated 

guidance is inappropriate. EPA should revise Appendix W and establish modeling 

guidelines that allow for flexibility and more realistic assumptions in all modeling 

applications, and assure that its guidelines allow the use of the most accurate and up to 

date models and techniques available.

2. The SO2 NAAQS – AERMOD has not been thoroughly evaluated for performance in 

simulating the maximum daily 1-hour concentration at the 99th percentiles (or 98th for 

NO2), especially for low wind speed cases that are the most impacted situations. 

Prescribing emission limits for such a stringent standard from the results of an unproven 

model could result in significant and unnecessary costs and burdens. If EPA finalizes 

these modeling requirements for SIP submittals, it should allow States the discretion to 

use modeling and analysis tools to help demonstrate situations where sources have a low 

probability of violating the standard, rather than prescribe overly conservative models 

that lead to unnecessarily stringent controls. For example, rather than “potential to emit”, 

States should have the discretion to use tools such as the Emissions Variability Processor 

with less restrictive emission limits that still achieve the NAAQS goals.

3. Making Modifications to Preferred Models – Model modifications that result in changes 

to modeled concentrations, must go through notice and comment rulemaking before 

being implemented in preferred models. Specifically, the change to AERMOD in MCB 

#4 that alters the PRIME downwash algorithms requires public notice and comment. 

Similarly, the performance of AERMOD with the AERMINUTE processor needs to be 

evaluated; EPA must consider the entire AERMOD system, including AERMAP, 

AERSURFACE, AERMET and AERMINUTE. Modeling systems for CALPUFF and 

AERMOD must be treated in a comparable way. Once an evaluation is complete, the 

model changes should be submitted for public notice and comment.

4. EPA Should Engage the Modeling Community – EPA should engage not only the 

regional, state and local agencies, but also the private sector, including consultants and 

industry, to achieve goals of improving the performance of both preferred and alternative 

models and for updating Appendix W. EPA should provide a clear path forward for 

approving model improvements that come from the modeling community, (e.g., AECOM 

recommendations on low wind speed, the SHARP and AERMINUTEPlus processors for 

simulating sub-hourly meteorology in AERMOD). The private sector should be invited 

to participate in the Modelers’ Workshops, in addition to the Modeling Conference.

5. Conclusions – EPA must assure that the performance of Guideline models is unbiased 

and does not lead to gross over predictions that forces unnecessary actions to address 

problems that aren’t present in the real world. EPA must perform a model performance 

evaluation for modifications and submit those for public notice and comment. EPA 

modeling should be transparent and open, and engage and seek collaboration with the 

modeling community.
A-10

American Electric Power Service Corporation

1. Determining Background for 1-hour Modeling – The method presented at the 10th

Modeling Conference is an improved method for determining background air quality 

levels for use in modeling analyses from areas with few monitors and those monitors 

have unrealistic background readings, where short term meteorological data are available. 

See attachment.

2. Model Issues for 1-hour Modeling – AERMOD has many flaws that come out when the 

new 1-hour SO2 and NO2 Standards are analyzed. There were a number of good 

suggestions made as to ways to “fix” AERMOD, including a statistical method to 

formulate the emissions input data, use of short term meteorological data, and 

improvements to methods of converting NOX to NO2 in the model. While these 

improvements should be made to the preferred model, a far more significant change may 

be needed to be truly able to model the 1-hour. The Gaussian model formulation that we 

have used for many years for near field modeling may not be appropriate for modeling of 

short term standards for SO2, NO2, and possibly CO and should be replaced by a model 

that uses a lagrangian puff formulation e.g., CALPUFF/SCIPUFF. USEPA must work 

more diligently to review the updates being made to CALPUFF. An updated CALPUFF 

or SCIPUFF may have a place in one hour modeling due to their superior handling of 

atmospheric behavior when paired with either their given meteorological model or 

prognostic meteorological models such as MM5 or WRF. Such a change requires notice 

and comment rulemaking, along with the time to upgrade the existing models or develop 

a new model that would incorporate all of the necessary technical changes to significantly 

improve our abilities to model the new 1-hour standards. USEPA should begin moving 

down this path to allow the use of a superior model formulation for future SIP 

development and permit modeling.

3. In conclusion, the issues that EPA should address include: 

a. Allowing the use of enhanced background determination procedures where the 

necessary data exists 

b. Use a statistical method to formulate the emissions input data since the emission 

standard is statistical in nature. 

c. Use short term meteorological data in the model itself and integrate these shorter 

increments into a one hour value 

d. Improve the methods of converting NOX to NO2 in the model 

e. Improve the turnaround time for evaluating changes to ALL guideline models when 

those changes appear to better represent the current state of the science 

f. Consider making a lagrangian puff type model the preferred model for modeling of 

1-hour standards
A-11

Duke Energy Company

1. Since EPA believes that computer models can determine nonattainment for sources, EPA 

must also require improved model performance to ensure that the control measures 

required of sources are appropriate without being excessive. AERMOD significantly over 

predicts SO2 concentrations and thus the current models are not reliable enough to be 

used as the basis for classifying an area as nonattainment. An extensive analysis 

(attached) by IDEM showed that overall modeled design values were more than 3 times 

those observed at monitors and showed over prediction of the model at regulatorily 

relevant levels of the standard, especially during periods of low wind speed and unstable 

conditions. In short, the model predicts that receptors located in the vicinity of the 

monitors would not attain the one-hour SO2 standard, while the actual on site monitors 

show that the facility is complying with the standard. Due to changes to the model, 

preprocessors and guidance model performance must be reevaluated before their use in 

demonstrating compliance with the SO2 NAAQS using modeling. New guidance 

documents should be subject to public notice and comment and EPA then response to 

those comments.

2. EPA should develop a prioritized listing of all modeling studies and model fixes it has 

received as a result of the 10th Modeling Conference, i.e., allowing sources to use actual 

hourly emissions instead of overly conservative maximum allowance emissions, and 

using a smaller and more representative modeling domain, 20km versus EPA’s stated 

50km domain. The EPA should solicit input from stakeholders on the list of projects and 

the project priority, and then allow the time needed to implement such changes prior to 

requiring sources demonstrate compliance with the new NAAQS.

3. It is not appropriate to use AERMOD in its current form as the primary tool for 

determining attainment or non-attainment with the current one-hour SO2 NAAQS. The 

model has demonstrated a high probability of over predicting actual ground level SO2

concentrations. This excessive conservatism will impose burdensome and un-necessary 

requirements on the regulated community that are not necessary for attainment of the 

standard or to protect public health. Additional modeling studies, model revisions, and 

guidance are needed. Because of the potential impact on the regulated community and 

the wealth of technical experience outside of EPA, changes to AERMOD, its 

preprocessor and modeling guidance should be subject to a public notice and comment 

process.
A-12

Arizona Public Service Company

1. EPA should replace out-dated CALPUFF 5.8 with the scientifically superior CALPUFF 

6.4 for BART determinations. APS endorses (and incorporates by reference) comments 

being submitted to the docket by the Utility Air Regulatory Group (“UARG”) and the 

Electric Power Research Institute (“EPRI”) on both the CALPUFF and AERMOD 

models. APS also supports the comments submitted by WEST Associates on the 

CALPUFF model. 

2. Supporting documentation on the relative performance of subject versions of CALPUFF 

is also provided. CALPUFF Version 6.4 has been found to provide equivalent results to 

the regulatory version when the same options and data are used. The new version is 

“backward compatible” with the regulatory version when run with the same inputs and 

data, if the new chemistry option is turned off and the bug-fixes are applied in CALPUFF 

5.8. Predicted sulfate and nitrate concentrations obtained by applying the two versions of 

the model were compared with actual measured values obtained at the Bridger 

Wilderness Area site and the Pinedale site. For the two model configurations, the results 

for sulfates were very similar, which was expected because the improvements to the 

CALPUFF chemistry were anticipated to have the most impact on nitrate predictions. 

The EPA-approved CALPUFF version was found to over-predict nitrates by a factor of 

two to three.

3. Appendix W Section 3.2.2 indicates that an alternative model is acceptable if “a preferred 

air quality model is not appropriate for the particular application.” In this case, 

CALPUFF 5.8 chemistry, especially for formation of winter nitrate, appears to be 

inapplicable because the MESOPUFF II formulation is based upon field testing with 

ambient temperatures of 50°F and higher. It is evident from the chemistry mechanisms 

that the nitrate equilibrium is highly sensitive to temperature and is most critical in 

conditions for which there are no observations for the MESOPUFF II formulation. The 

weight of evidence of the new evaluation information provided here and the clear 

limitations of the chemistry in CALPUFF 5.8 makes it imperative for EPA to allow 

immediate use of CALPUFF 6.42b for nitrate chemistry.

4. While EPA endorsed CALPUFF as the best modeling tool available in 2005, EPA 

specifically recognized that the model was less than perfect. EPA committed in the 2005 

BART rule to evaluate “newer” approaches, but has not acted on the matter in the 

following seven years. It clear from the BART rule that each analysis should be based on 

the “best application [currently] available” to predict visibility impacts; the best 

application and information “currently available” is now the new, more refined version 

CALPUFF 6.42b. EPA should review and approve MCBs E, F, and G and conduct its 

own review of the tests/evaluations of the new version of the CALPUFF model as soon 

as possible before final BART determinations are made later this year. If those tests 

duplicate findings described at the Tenth Modeling Conference, EPA should move 

expeditiously to either designate CALPUFF 6.42b as the regulatory version of the model 

for BART determinations, or allow its use as an alternate model in all proposed 

applications. Such an approach is consistent with the process EPA has used for recent 

changes to the AERMOD model.
A-13

Salt River Project Agricultural Improvement and Power District

CALPUFF has evolved continuously since its initial introduction, but EPA’s model approval 

process has not kept pace with the developmental process. Comparisons with field 

measurements have found that CALPUFF 5.8 over-predicts particulate nitrate formation by a 

factor of 3 to 4. Work has been done to improve the model’s chemistry module and reduce the 

over-prediction; as a result CALPUFF 6.4 has been released. Comparisons with the two versions 

of the model show conflicting results on benefits of additional control technology to improving 

visibility in Class I areas; CALPUFF 6.4 showed no perceptible improvement. EPA should 

move expeditiously in evaluating and adopting these enhancements as the regulatory version of 

CALPUFF. In the interim EPA Regional Administrators, may approve use of CALPUFF 6.4b as 

an alternative on a case-by-case basis.

Tri-State Generation and Transmission Association, Inc.

1. EPA should adopt enhancements to the regulatory version of CALPUFF (specifically 

CALPUFF 6.42) in implementing the Regional Haze Rule relative to BART as 

expeditiously as possible, particularly as applicable to NOX emission reductions. This 

updated version of CALPUFF has already been placed in the public domain and 

additional tests have been completed and reported at the 10th Modeling Conference. As 

needed, EPA should quickly conduct its own tests and evaluations.

2. Various studies have concluded that the current version CALPUFF 5.8 over-predicts 

particulate nitrate formation by a factor of 3 to 4 under wintertime conditions. EPA has 

recognized that the model may overstate the visibility effects of an individual source.

Oglethorpe Power Corporation

1. AERMOD Low Wind Speed Issue – AERMOD’s tendency to overestimate 

concentrations at low winds speed is exacerbated by implementation of AERMET and 

AERMINUTE. There has not been sufficient justification and verification regarding the 

validity of the resulting estimates. EPA should consider modifying u* and sigma v as 

recommended at the 10th Modeling Conference.

2. Development of Off-Site Emission Inventories for the 1-hour SO2 and NO2 NAAQS –

Interim SILs for the SO2 and NO2 NAAQS are very stringent, inconsistent with other 

historical SILs, and can lead to large SIAs; guidance on SIAs in not clear and help has 

not been provided to relevant State efforts. EPA should provide detailed guidance on offsite emission inventories for use in modeling analyses for the 1-hour NAAQS.

3. Reconsideration of the Ambient Ratio Method (ARM) Value to be used in 1-hour NO2

NAAQS Analysis – The relevant ratio is highly restrictive and conservative. EPA should 

review data as provided for the 10th Modeling Conference and provide a revised ARM 

method for Tier 2 for 1-hour NO2 NAAQS analyses.

4. AERMOD Version 11059 Model (and subsequent Versions) Changes Related to Building 

Downwash – EPA has modified the AERMOD code to consider potential downwash 

effects for stack heights that equal or exceed the EPA GEP formula height. This code 

modification seems to represent a revision to the algorithms within the model. There was 

no opportunity for public comment and no justification or consequence analysis has been 

provided. EPA should provide a justification and consequence analysis for this change to 

the AERMOD model. Public peer review and comment should be allowed for this model 

change.
A-14

West Associates

1. EPA’s 2005 BART Guidelines acknowledged the need for CALPUFF 5.8 updates, since 

the regulatory approved CALPUFF version 5.8 may overestimate the amount of nitrate 

produced from point source NOX emissions and chemistry modules in CALPUFF 5.8 are 

less advanced than more recent atmospheric chemistry simulations. Comparisons of field 

measurements of sulfates and nitrates with corresponding values predicted by CALPUFF 

5.8 indicate that the model over predicts particulate nitrate formation by as much as a 

factor of three to four under wintertime conditions.

2. Studies demonstrate that CALPUFF 6.4 has superior predictive capability. A new 

chemistry module to reduce CALPUFF 5.8’s over prediction of nitrates has been 

proposed, tested and evaluated; additional tests recommended by EPA have been 

completed (supporting documentation is provided).

3. EPA should conduct its own tests/evaluations of the new version of the CALPUFF model 

as soon as possible, before final BART determinations are made, then move 

expeditiously to designate CALPUFF 6.4 as the regulatory version of the model for 

BART determinations. Such an approach is consistent with the process EPA has used for 

recent changes to the AERMOD model.

4. Due to the demonstrated superiority of the chemistry in CALPUFF 6.4, its more accurate 

predictions of particulate nitrate formation, and its wide acceptance in the scientific 

community, EPA should encourage modeling demonstrations using CALPUFF 6.4 for 

NOX emission reductions. This new chemistry, as well as the entirety of CALPUFF 

version 6.4.2 can be accepted for BART determinations under Section 3.2 of Appendix 

W; this section is designed to allow use of important model enhancements or alternative 

models in a timely way on a case by case basis, without the 3 to 5 year wait for formal 

rulemaking.
A-15

American Petroleum Institute

The promulgation of more stringent NAAQS and requirements for 1-hour modeling, including 

the proposed use of modeling for SO2 area designations have resulted in the need for improved 

modeling methods and evaluation. Key recommendations for EPA action are summarized below 

for implementation periods characterized as Short-Term (0 – 1 years), Mid-Term (1 – 3 years) or 

Long-Term (3+ years). EPA should develop a research plan and schedule for addressing these 

modeling issues. This plan should be shared and discussed with the modeling community.

1. AERMOD NO2 Plume Chemistry –

a. (ST) Issue guidance allowing use of Ambient Ratio Method 2 (ARM2) as a Tier 2 

method. 

b. (ST) Continue collaborating with the API on improvements to the PVMRM (a Tier 3 

method). Make the AERMOD PVMRM formulas (e.g., relative dispersion) consistent 

with the original formulations by Hanrahan. 

c. (MT) Evaluate other more sophisticated NO2 plume chemistry models such as 

SCICHEM and RPM; adopt those plume chemistry models if the more complete 

chemical mechanisms provide significantly better accuracy than AERMOD/PVMRM. 

d. (LT) Consider new NO2 field experiments involving shorter stacks, source emissions 

sampling, and ground level sampling where ozone, NO and NO2 are measured.

2. AERMOD Over-predictions in Stable Low Wind Conditions 

a. (ST) Resolve the stable low wind problem with AERMOD by means of sciencebased revisions to the boundary layer and dispersion formulas. Specific technical 

recommendations are listed in the attached report and are a combination of 

recommendations from the Paine et al. (2010) report plus more recent analyses. 

b. (ST) Change the critical wind speed in the AERMOD formula for deriving u* in very 

stable conditions, thus increasing u* as well as turbulent speeds and the derived 

mixing depth during low wind conditions. 

c. (ST) Increase the “minimum σv and σw” so as to avoid very low values which lead to 

unrealistic over-predictions of concentrations. 

d. (ST) Modify the weighting factors in the AERMOD low wind method of averaging 

the meander (pancake) and coherent plumes. The meander (pancake) component 

should receive a larger weighting than at present. 

e. (MT) Change the wind and temperature profiling methods in AERMOD so as to 

assure smoother profiles in conditions when the input wind observation height is 

above or near the mixing height at night. 

f. (LT) Explore better use of sub-hourly (2 min average) meteorological data available 

from the NWS airport sites.

3. CALPUFF Regulatory Model 

a. (ST) Adopt the current version of CALPUFF with improved chemistry (e.g., v 6.42) 

as the regulatory version. 

4. AERMOD GEP Stack Height Formula and Building Downwash Modeling 

a. (ST) Return to the previous practice of allowing “Equivalent Building Dimensions” 

(EBDs) for open lattice and porous structures and allow CFD models to contribute to 

the decision process. 

b. (MT) Evaluate the accuracy of plume downwash conditions for short stacks and light 

wind speeds using the AGA and other relevant databases; vertical profiles of 

meteorology in stable conditions should also be reviewed. 
A-16

5. AERMOD Extrapolation of Airport Wind Observations to Other Sites 

a. (ST) Return to the previous 3 km radius method for estimating surface roughness 

length zo around a site. The recent change to a 1 km radius is too small. 

b. (LT) Use resistance relations suggested by Blackadar and Zilitinkevich to more 

realistically develop wind profiles at the modeled site. 

6. Use of Observed Emissions and Monitored Concentrations 

a. (ST) EPA should issue a reminder to the Regional offices and the states regarding the 

availability of the option in Section 10.2.2 of Appendix W for use of monitoring in 

lieu of modeling when there are no suitable models for use in NSR permitting.

b. (ST) SO2 area designations should be made primarily using monitoring data as 

opposed to using model-predicted concentration estimates.

7. Regional Chemistry Models (CMAQ, CAMx, and others) 

a. (MT) Regional chemistry models should have a larger role in the EPA Air Modeling 

Conferences. While there is an annual CMAS conference, it does not provide a 

formal mechanism for public review and comment

8. Background Concentrations

a. (ST) The background concentrations should conform to the averaging times (e.g., one 

hour, one day, annual) and the spatial domain (e.g., 10 km, 100 km, 500 km) of the 

scenario being modeled. 

b. (LT) Methods should be devised for use in defining and determining background 

concentrations in areas with many sources at local and mesoscale distances to void 

problems such as double-counting in modeling for compliance determinations. 

9. Model Evaluation and Data Bases 

a. (ST) The modeling community should have easy access to all field and laboratory 

data bases used by the EPA to develop and evaluate models. EPA should keep this 

information on a devoted server and include adequate metadata. 

10. Collaboration among EPA, Stakeholders and Researchers 

a. (ST) EPA should consider the comments from the 10th Modeling Conference and 

develop a research plan and schedule for addressing modeling issues. 

b. (ST) There should be communication and coordination within EPA (e.g., OAQPS and 

ORD), and external communication and collaboration with stakeholders such as 

industries, state agencies and consulting companies who must use the models, and 

with national and international scientists who are working on improving models. 

c. (ST) EPA OAQPS should continue to use a technical work group to suggest technical 

solutions and provide technical review of new models and model revisions.

In addition, the attached technical assessment makes recommendations on:

1. Urban dispersion methodology in AERMOD – incorporate urban canopy formulas for 

wind and turbulence profiles.

2. Straight-line assumption in AERMOD – reconsider and reduce the distance limits for 

AERMOD and other straight-line Gaussian plume models

3. Use of CALPUFF at distances less that 50km – plan for adopting a Lagrangian puff 

model, like CALPUFF or SCIPUFF, at all distances within the next few years.

4. Use of 3D prognostic meteorological models for inputs to dispersion models – make no 

major change such as adoption of MMIF until test runs with AERMOD and CALPUFF 

are completed, documented and made available for public comment to show that 

meteorological models provide comparable performance compared to standard inputs.
A-17

BP America, Inc.

1. Overview -- These comments identify issues with the current Guideline process, as well 

as attempt to provide suggestions to help address related issues. More detailed technical 

comments are provided in attachments.

2. EPA should offer a formal mechanism for the modeling community, including the states 

and the regulated community, to comment or provide peer review on the models and 

modeling methods. The current process that EPA uses including the Modeling 

Clearinghouse, internal memorandums to the EPA Regional Air Division Directors, and 

general guidance memorandums to issue modeling guidance precludes public input and 

lacks any form of outside peer review.

3. EPA should develop a spirit of collaboration with stakeholders independent of any 

specific project. In addition, a panel of recognized experts (evenly split between state 

agencies, universities, public and industry) should be appointed to address modeling 

issues. The panel should

a. provide short term research objectives along with measurable performance milestones

b. provide feedback to EPA management regarding research needs

c. help develop methods of reducing the time required to implement changes in the 

Modeling Guideline (Appendix W)

d. provide peer review of Model Clearinghouse actions

e. provide technical peer review on changes to guideline models

4. EPA should take comments regarding modeling deficiencies and develop a research work 

plan. This work plan should be developed by EPA with outside peer review. The plan 

needs to include a timetable for research milestones and a budget. The plan should be 

published for public comment and should address the recommendations provided below.

a. Use of Air Quality Models in a Regulatory Setting (ongoing activity over the next 0-2 

years) -- EPA should get input from stakeholders and publish its determination that 

demonstrates model accuracy is sufficient to meet the current policy needs. If EPA 

concludes that model accuracy does not provide a tool for policy use, then alternative 

approaches that could be used for meeting current policy needs include coupling 

modeling and monitoring and use of modeling in more of a relative mode as in the 

case of PM and ozone modeling, or to base compliance with the NAAQS using a 

combination of BACT and ambient monitoring as allowed under Section 10 of the 

Guideline

b. Determination of Model Accuracy – EPA Model Evaluations (ongoing activity over 

the next 0-2 years) -- EPA should re-examine the previous AERMOD evaluations for 

a 1-hour period and determine what limitations exist in the current model evaluations 

that need further analysis; model accuracy should be tested and conclusions reached 

regarding sub-categories such as stack height, downwash, and meteorological 

conditions (including low wind speeds).

c. Low Wind Speeds (short term high priority to address over the next year) -- EPA 

should review the API low wind speed modifications to AERMOD and suggest 

modifications to address deficiencies, then subject model revisions to peer review and 

public comment; until review and revisions to AERMOD are completed, EPA should 

revert to the previous definition of calm wind speed (<1 m/s = calm). 

c. NO2 1-hour Modeling (short term high priority to address over the next year) – EPA 

should review and implement the NO2 Ambient Ratio Method 2 and corrections to 
A-18

AERMOD PVMRM that API has identified; evaluate other NO2 models beyond 

AERMOD PVMRM and OLM such as SCICHEM. 

d. Overarching Procedural Concerns (ongoing activity over the next 0-2 years) – EPA 

should develop a process that facilitates changes to Appendix W. When changes are 

required, EPA needs to publish draft changes, accept comments, respond to 

comments in a final document, and incorporate the changes by reference without 

having to update the entire Appendix W. 

e. EPA also needs to develop a peer review process. Such a process needs to evaluate 

the scientific principles, implementation of the principles into the model and evaluate 

the verification of any changes. Peer review must include EPA ORD, academia and 

other stakeholders. In addition, EPA must adequately address the concerns raised by 

any peer review group. 

f. EPA should change the model clearinghouse process to allow the regulated 

community to bring questions and proposals directly to OAQPS if the states and the 

regions deny them.

g. AQRV Analysis (short term high priority to address over the next year) – EPA should 

incorporate the new version of CALPUFF that API had developed which includes 

both corrections to errors in the existing gas-phase chemistry module, as well as 

incorporation of new science modules for inorganic and organic aerosols and 

aqueous-phase chemistry into the Guideline. Related steps include:

i. Add a post-processing step to recalculate inorganic aerosol equilibrium at 

receptor locations to address lack of treatment of ammonia limitation for 

multiple or overlapping puffs. 

ii. Add an upper limit for particulate nitrate formation that is based on the amount 

of ammonia available in the background in CALPUFF to prevent the output of 

particulate ammonium nitrate concentrations that are physically unrealistic and 

when CALPUFF does not conserve mass of ammonia (as is the case in the 

current model).

iii. Incorporate into the Guideline CALPUFF with the improved RIVAD 

chemistry.

h. Portable Sources (short term high priority to address over the next year) – EPA needs 

to revise the February 2012 memo regarding modeling of temporary sources. BP has 

outlined an approach that can be used to address impacts or sources that do not 

remain at a fixed location for a 3-year period.
A-19

American Iron and Steel Institute

1. Overview

a. There will be significant difficulty in permitting new or expanded sources as a result 

of inadequate tools and guidance for addressing the implementation of new NAAQS. 

The requirements for states to model thousands of sources using flawed tools will 

result in mandates for unnecessary controls on existing sources and, in some cases, 

make continued operation infeasible. 

b. Significant over-prediction continues for particulate emissions and other pollutants, 

particularly when applied to the complex facilities with multiple non-stack sources 

with irregular emission rates operated by AISI members. 

c. Models used to implement the NAAQS must be improved to address these flaws prior 

to NAAQS implementation. There are several issues discussed below that need to be 

addressed. Issues that have been identified as a problem and also have viable 

technical solutions include: fugitive particulate matter modeling; AERMOD overpredictions for low wind speed periods; the use of reasonable operating scenarios as 

inputs; and downwash algorithm anomalies. Technical details of some issues are 

provided in attachments to AISI comments. 

d. In addition, EPA should establish a process to formally address these modeling issues 

and make significant changes to improve the accuracy of models used in NAAQS 

implementation. One option is to continue to utilize the Technical Workgroup that 

the agency formed to plan for and prepare the agenda for the conference.

2. AERMOD was designed to predict steady state emissions from stacks, and has not 

proven capable of accurately predicting contributions to ambient concentrations from the 

fugitive, mobile, and variable sources operated by AISI members.

3. Significant work has been done to assess the underlying technical problems contributing

to the over-prediction bias for non-stack sources in AERMOD, including uncertainties 

associated with fugitive emissions or other non-stack sources and unique dispersion 

characteristics and depletion/removal features associated with these sources. Use of 

ambient monitoring is the only way to reliably measure the ambient impact of these 

sources.

4. Appendix procedures drive over-prediction bias with multiple layers of conservative 

assumptions. To reduce the over-prediction bias: (1) use actual hourly emissions, or 

reasonable worst case emissions rates in their absence; (2) actual meteorological data, 

instead of worst case assumptions; (3) actual monitored background concentrations.

5. Use more plausible receptor locations where the public has reasonable access and can 

stay stationary for the entire period associated with an ambient standard, e.g., don’t 

include transportation corridors. 

6. Address the low wind speed problem associated with use of AERMOD and 

AERMINUTE, and limit use for regulatory purposes until resolved.

7. Limit use of the PRIME downwash algorithm for light winds (< 1 mps) and excess heat 

releases until improved; refine profiles of wind, temperature and turbulence during 

periods of light winds and stable conditions.

8. Apply a pre-preprocessed adjustment (e.g., 50%) to particulate emissions from roadways 

and pits to compensate for inadequate treatment of plume dynamics by AERMOD.

9. Consider treatment of industrial facilities with substantial “fugitive heat” releases as 

urban areas.
A-20

10. Adjust AERMOD for buoyant volume sources by separately calculating hourly plume 

rise and then using the volume source feature.

11. Improve how AERMOD treats haul roads, slag pits, and material handling by how the 

source is represented in the model input using techniques described in the attachment.

12. AERMOD should not presume that secondary formation of PM2.5 from precursors occurs 

at the same time and location that primary pollutants have their greatest impact. 

Refinement and testing against field data are necessary before models like AERMOD can 

be appropriately used.

13. The use of ARM2 should be considered to better accommodate variation of the ambient 

NO2 to NOX ratio with the NOX concentration.

14. Modeling should not be used to determine nonattainment areas or any other regulatory 

obligation until AERMOD is validated with measured values.

15. Ways to incorporate EMVAP in taking into account source emissions uncertainties and 

intermittent sources should be considered in implementing a variable emission rate limit.

16. The use of monitoring in lieu of modeling should be clarified to enhance its use in 

characterizing source impacts.

17. Use less conservative levels for SILs that are consistent with percentile values on which 

NAAQS are based.

18. Implement a transparent process that solicits the broad expertise available to refine air 

dispersion modeling and allows for public notice and comment rulemaking.
A-21

National Mining Association

1. Overview. EPA should perform an overall re-evaluation of the Agency’s policies and 

procedures that drive its determinations regarding the application of regulatory modeling. 

Current regulatory practices consistently rely on untested models with hastily developed, 

ad hoc agency “guidance”. Modeling requirement that rely on a proliferation of guidance 

in the form of clarification memoranda, implementation guides, and draft/revised user’s 

guides which have the effect of making promulgated standards significantly more 

stringent without formal rulemaking is inconsistent with the Clean Air Act and basic 

principles of administrative law. Moreover, repeated application of model algorithms 

beyond the scopes of their evaluated and recognized applicability and capability are 

simply not “good science”. A deliberate rulemaking approach that seeks formal public 

input would be a more appropriate means for establishing modeling requirements that are 

firmly grounded in fundamental scientific principles. The application of currentlyapproved models to fugitive particulate emissions from surface mining operations as well 

as to the 1-hours NO2 and SO2 standards is of concern. For fugitive particulate emissions 

from surface mining operations, EPA’s assessment must begin with a longstanding 

congressional mandate that establishes certain alternative regulatory approaches when 

EPA’s models and emission factors result in excessive and unacceptable levels of overprediction. EPA must implement some of the readily available revisions that can improve 

model performance. EPA should also consider accepting CALPUFF for near-field 

application with complex terrain, such as that frequently encountered in industry mining 

operations.

2. EPA’s approach for modeling fugitive particulate emissions falls short of satisfying the 

Agency’s guiding principles for best scientific analysis, rule of law, and transparency.

a. EPA’s emissions factors and models over-predict short-term ambient impacts of 

fugitive PM10 emissions from surface coal mines.

b. EPA’s reliance on guidance documents to make significant alterations to modeling 

requirements circumvents the notice-and-comment rulemaking prescribed by law.

c. EPA’s Model Clearinghouse and its issuance of “clarification memoranda are clearly 

unacceptable alternatives to notice-and comment rulemaking.

3. Unacceptable performance of EPA’s models and emission factors when applied to 

fugitive particulate emissions and dust is well known and documented.

a. A memorandum of agreement indicates that ISC3 will not be used for regulatory 

application involving surface coal mines and that monitoring in lieu of modeling is 

acceptable.

b. EPA must re-visit the statutory prohibition and mandate before either EPA or the 

States require future modeling of PM10 and PM2.5 emission from surface mining 

operations. The fact that ISC3 has been replaced by the AERMOD model does not 

render sections 234 of the CAA as either irrelevant or no longer applicable.

4. Revisions are readily available to account for AERMOD deficiencies (see Cowherd 

paper).

a. Improved AERMOD predictions at low wind speeds – EPA should implement 

changes to AERMET/AERMOD that reduces prediction of unrealistically high 

ambient impacts during low wind speeds.

b. Emissions preprocessing to address near-source plume-depletion mechanisms and 

conservative source configuration properties – (1) EPA should consider the concept 
A-22

of “transportable fractions of fugitive dust as a function of ground cover bordering the 

source of the fugitive dust in AERMOD applications, and (2) EPA should apply a 

50% reduction for haul road emissions outside the confines of the quarry pit, as well 

as a 50% reduction for other fugitive particulate emissions from mining operations to 

account for plume depletion mechanisms. Field test data should subsequently be 

obtained to confirm the magnitude of the reduction factor.

c. Emission preprocessing to account for AERMOD’s improper representation of pit 

retention – EPA should apply a preprocessing reduction of 75% for fugitive 

particulate emissions within the confines of the pit.

d. Application of probabilistic approach to account for the intermittent nature of 

emissions from smelters – EPA should adopt presented methods for sources with 

intermittent emissions and adopt this approach for any modeling that may be required 

at smelters; AZ examples for multipoint rollback are available for enforceable permit 

limits based upon a probabilistic emissions model.

e. Use CALPUFF for near-field modeling in complex terrain – EPA should consider 

approving CALPUFF as a superior model because of its ability to handle threedimensional wind fields that more accurately reflects actual conditions.

f. Monitoring in lieu of modeling – EPA has endorsed use of SO2 monitoring for 

“sources that may not be as conducive to modeling as are larger SO2 sources”, so for 

such sources at surfaces mines, e.g., nonroad engines of various types, EPA should 

authorize the use of monitoring data to demonstrate compliance with short-term 

PM10, PM2.5, SO2 and NO2 NAAQS.

g. Definition of ambient air – EPA should adopt more plausible assumptions about 

receptor locations where the public has reasonable access and can stay stationary for 

the entire period associated with an ambient standard.

h. AERMOD over-prediction of building downwash for certain geometries and wind 

speeds – EPA should consider proposed threshold wind speeds for downwash effects.

i. EPA should adopt a technical work group to support model development and 

application – EPA should include industry associations to provide various technical 

resources and expertise for workgroup efforts that could be targeted toward 

fundamental program development or alternatively at source-specific application.
A-23

Wyoming Mining Association – supports comments from National Mining Association

1. Unacceptable performance of EPA models and emission factors when applied to fugitive 

particulate emissions 

a. The over-predictive nature of current EPA models with respect to modeling fugitive 

dust emissions from surface mining operations on a short term basis has been 

identified as an on-going issue critical to the coal mining industry, e.g. Sec. 234 of the 

CAA.

b. A Memorandum of Agreement (MOA) allows WY to conduct monitoring in lieu of 

modeling for assessing coal mining-related impacts in the Powder River Basin. In 

addition, AP-42 notes that haul road emission factors should be used with caution and 

awareness of their likely limitations.

c. No other actions relative to Sec. 234 can be found, and EPA has failed to satisfy the 

Congressional mandate. Yet current regulatory practice has required the modeling of 

fugitive emissions on a short term basis from surface mining operations in almost 

every state except Wyoming. Replacement of ISC3 with AERMOD doesn’t rectify 

this.

d. EPA must re-visit the statutory prohibition and mandate before either EPA or the 

States require future modeling of PM10 emissions from surface mining operations on 

a short-term basis.

2. AERMOD predictions for low wind speeds – EPA should immediately initiate 

AERMOD revisions to better simulate transport and dispersion under low wind speed 

conditions; until such revisions are completed and tested, AERMOD results for low wind 

speeds (less than 1.0 m/s) should not be included in model results (as is currently the case 

for “calm” conditions).

3. Distance limitation to AERMOD validity – EPA considers AERMOD results to be 

applicable to a distance of 50 km; however, it has been shown that, for most 

circumstances, a steady state model is only applicable to 20 km or less. Unless 

meteorological conditions are persistent (similar wind speed and direction) in succeeding 

hours, model-predicted concentrations at receptors beyond the one-hour travel distance 

should not be accepted as meaningful. AERMOD should be modified to delete such 

concentrations from the output, or at least provide a notification to the user to disregard 

such results in interpreting the model output.

4. Intermittent sources – EPA guidance for intermittent sources, e.g., blasting activities at 

surface mines, is vague and overly conservative and States have adopted various 

interpretations. EPA should provide definitive guidance that is based on a realistic 

evaluation of the likelihood that an intermittent source will threaten the standards; see 

example relative to probability-based approaches.

5. Background concentrations – current guidance based on use of the 98th or 99th percentile 

monitored background values are unrealistically conservative. EPA should approve a 

method of pairing model-predicted concentrations with monitored concentrations that are 

paired in-time. Also, more appropriate guidance is required to eliminate double counting 

of impacts from modeled sources and those impacts represented in background 

monitoring data.

Alpha Coal West, Inc. – exact duplicate of comments from Wyoming Mining Association
A-24

Barrick Gold of North America, Inc. – supports comments from National Mining Association 

1. These comments largely duplicate those from Wyoming Mining Association and Alpha 

Coal West, Inc., either by paraphrasing similar reference materials or by an exact copy on 

topics such as low wind speeds, AERMOD distance limitation, and background 

concentrations.

2. Concerning unacceptable performance of EPA models, it is noted that even though 

Section 234 specifically addresses surface coal mines, the factors and modeling 

algorithms that are uncertain for coal mining operations are equally uncertain for other 

types of surface mining activities; therefore, there is no scientific basis for these air 

models to treat hardrock surface mining different from surface coal mining. 

3. Concerning complex terrain and alternative models, it is noted that AERMOD may not be 

an appropriate model, where varied and extensive complex terrain exists in the area of 

multiple sources and this terrain extends from the sources to the location of receptors 

where design concentrations are expected. Non-steady state models such as CALPUFF 

are theoretically more appropriate for such applications, particularly where mesoscale 

forecast models and their use in generating realistic input meteorology to CALPUFF 

make it a preferred alternative to AERMOD. EPA should acknowledge the potential 

applicability of alternative models for appropriate situations.
A-25

Peabody Energy

1. EPA models and emissions factors applied to fugitive particulate matter emissions –

Section 234 specified that EPA make revisions to eliminate over-prediction. To date, no 

satisfactory revisions have been made. Until emission factors and modeling methods can 

be shown to provide accurate predictions, EPA has to adhere to the statutory prohibition 

that prevents it from relying on dispersion models for particulate impacts associated with 

surface coal mining activities. 

2. AERMOD predictions for low wind speeds – EPA should introduce AERMOD revisions 

to more accurately simulate transport and dispersion under low wind speed conditions. 

Current AERMOD predictions for low wind speed (less than 1.0 mps) are not valid and 

should not be included in model results (which unfortunately is presently the case for 

"calm" conditions) until these AERMOD revisions are implemented and tested.

3. AERMOD distance limitation – Currently, EPA considers AERMOD results to be 

applicable to a 50km distance; however, it has been shown that applicability should be 

limited to 20km or less under most circumstances. Model-predicted concentrations at 

receptors beyond the one-hour travel distance should not be accepted as meaningful 

unless meteorological conditions are persistent (similar wind speed and direction) in 

succeeding hours. As such, AERMOD should be changed to remove these concentrations 

from the output, or provide a notification to the user to disregard these results in 

interpreting the model output.

4. Intermittent sources – The approach to modeling intermittent sources, e.g. blasting 

activities, should be based on a realistic evaluation of the likelihood that an intermittent 

source will threaten the standards, and should be supported by sound science. This would 

permit EPA to avoid the necessity for extensive modeling analyses. It would also prevent 

the need for unnecessary source modifications that result from overly conservative 

impact estimates. 

5. Blasting impacts – AERMOD, which assumes continuous and constant emissions over a 

one-hour time span, is not capable of validly modeling the nearly instantaneous source 

that is blasting. The application of AERMOD in its regulatory form is not an appropriate 

methodology for assessing blasting impacts, as ground-level concentrations are generally 

over-predicted. Field studies that are well-designed are required to better define blasting 

emissions and dispersion, the results of which could be used to better analyze the 

assessment of blasting impacts. A probability approach to quantifying blasting impacts 

would be appropriate, rather than determining the maximum possible impact given 

blasting on some or all hours of the year. 

6. Background concentrations – Current guidance on the use of background data is 

unrealistically conservative. Highest monitored background or 98th/99th percentile values 

usage causes an unreasonable limitation to allowable source impacts. Pairing of modelpredicted concentrations with monitored concentrations in time provides a means to 

obtain a realistic projection of whether or not a potential exceedance is likely. EPA 

should immediately approve this method of accounting for background concentrations in 

all situations where representative background data exist. Additionally, more appropriate 

direction is required to eliminate double counting of impacts from modeled sources and 

those impacts represented in background monitoring data. Where representative regional 

monitoring data exist, there should be no requirement to model regional sources whose 

impacts can reasonably be presumed to be reflected in the monitoring data.
A-26

The National Environmental Development Association’s Clean Air Project

1. General Comments

a. Refinements of Appendix W models are critical, as are improved “modules for 

processing inputs” into the models. 

b. Weather and timing elements are so critical to model predictions that collection of 

site-specific meteorological data can make or break a model outcome where use of 

regionally collected airport data once may have been sufficient.

c. Proposed priorities for EPA model refinements in 2 below and related policy 

priorities are respectively listed in 3 and 4 below.

2. High priority, near-term (3 months) refinement of EPA’s preferred dispersion Models 

a. Allow use of AERMINUTE permissively but do not mandate its use

i. Allow sources to use available air monitoring data to pair monitored values and 

hourly emissions.

ii. By waiving the use of AERMINUTE, incentivize partnerships between state air 

authorities and sources for the collection of real time meteorological data.

b. Aggressively prioritize refinements to AERMOD for modeling building downwash 

for low wind speeds and cases with large or long buildings. The currently mandated.

i. Approve approaches for accurately modeling buoyant plumes from line/volume 

sources.

ii. Allow the use of post construction monitoring at receptors with high predicted 

impacts to allow construction of new sources and provide technical input for 

model refinements. If necessary, back up monitoring with permit conditions if 

certain values are exceeded.

c. Prioritize refinements to dispersion models for low wind speeds. In the interim, 

establish or set a lower wind speed threshold of 1 meter per second.

d. Allow a set ground level 1st layer mixing height at 68 meters (minimum) pending 

completion of technical work to confirm a lower mixing height is real and suitable for 

use.

e. Recognize and use the form of each NAAQS to determine the modeled design value. 

Just as EPA allows modeling of the 8th high for NO2 (98th percentile), and 4th high for 

SO2 (99th percentile), modeling for PM2.5 should evaluate the 8th high (98th

percentile). 

f. Approve modelers’ use of the American Petroleum Institute’s corrections to 

AERMOD PVMRM for NO2, the NO2 Ambient Ratio Method 2, the low wind 

modifications to AERMOD, and the new version of CALPUFF with updated 

chemistry.

g. Give careful consideration to avoiding double-counting impacts in modeling and 

background. In particular, background should be determined on an event basis.

3. Communicate to EPA Regional and State modelers and permit authorities as soon as 

possible that Section 10 of Appendix W allows use of monitoring when a suitable model 

is not available or when modeling is less acceptable than monitoring, as indicated in 

Section 10 of Appendix W to Part 51.

a. See various examples given at the modeling conference. 

b. It is noted that for proposed new sources or major modifications of existing sources, 

permits would include conditions that address how monitoring would be done and 

what happens if exceedances of standards are monitored.
A-27

4. Re-Invent the Model Clearinghouse and/or Adopt Another Means of Communicating 

Technical Developments to Modelers on a Regular Basis. 

a. EPA needs a process to incorporate changes by reference without update to the entire 

Appendix W. EPA should publish the draft changes, accept comments, and respond 

to comments in the final document. EPA also needs some sort of peer review process 

that includes EPA ORD, academia, industry, and other stakeholders to evaluate 

scientific principles, implement the principles in the model, and evaluate the changes.

b. Regarding the Model Clearinghouse OAQPS needs to create a more dynamic tool in 

the near term for modelers to communicate to iron out problems and develop 

solutions that takes advantage of technological innovations in the field. This tool also 

would provide a more open platform than monthly conference calls for encouraging 

States and regional EPA officials’ participation making existing models better by 

submitting for discussion and resolution modeling issues in “real time.” OAQPS 

should establish a regulatory mechanism akin to the quarterly publication of 

NSPS/MACT, then post at an Internet website case-specific modeling issues and 

decisions. If necessary, the existing technical modeling stakeholder committee and/or 

a regional EPA modeling committee could be tasked with monthly modeling 

conference calls to “peer-review”/prioritize issues brought to the committee’s 

attention. 

c. Importantly, since the modeling “determinations” will memorialize case-specific 

resolutions, the resolutions need not establish “precedent” for other modeling 

decisions or be cast so broadly to be of “national significance,” as is the case with 

postings on the Model Clearinghouse. Instead the mechanism would provide a 

resource for modelers and regulators to exchange information. Resolutions, even 

temporary fixes and future rulemakings and shared data or Notices of Data 

Availability, also could be posted for the modeling community, which presently 

seems to be unusually dependent on word of mouth for what is permissible, possibly 

permissible, and might happen in the future.
A-28

American Forest & Paper Association

1. Challenges from EPA’s modeling guidance – Pulp and paper operations are subject to 

numerous federal emissions regulations that establish standards for pollutants (e.g., NO2, 

PM2.5, and SO2) regulated under NAAQS. Because of the low SILs associated with the 

new NAAQS and current conservative modeling assumptions, even relatively small 

maintenance and construction projects, can trigger permitting requirements.

2. EPA’s implementation procedures for recent NAAQS 

a. Implementation policies specific to dispersion modeling lead to unreasonably 

conservative outcomes as a result of technical limitations in regulatory modeling. 

b. EPA has adopted the practice of issuing “clarification memoranda” without the 

benefit of public notice and comment.

c. EPA has not provided adequate tools and guidance for sources to quantify PM2.5

emissions and to model ambient impacts. Screening tools for PM2.5 compliance 

demonstrations require a modeled design concentration that is very conservative.

d. A minimum 1-year transition period is appropriate before new NAAQS are 

applicable. Implementation guidance should be developed at the same time, and such 

guidance subjected to a notice and comment process that allows for stakeholder input.

3. Need to develop practical implementation guidance using suitable modeling techniques 

for current and future PM2.5 NAAQS.

a. EPA’s interim guidance for PM2.5 screening analyses for PM2.5 is impractical since

i. measured background PM2.5 concentrations, except for designated nonattainment 

areas, are consistently below the current NAAQS by a small margin.

ii. it inherently assumes that the day with multi-year average maximum model 

impact is coincident with the day of the 98th percentile background concentration, 

unreasonably overestimating the design concentration relative to the NAAQS.

b. Case studies are provided following current EPA guidance to assess PM2.5 impacts 

using prescribed screening techniques and compared with a “Paired Sums” approach; 

most sources cannot demonstrate compliance with the PM2.5 NAAQS under current 

EPA guidance despite being well controlled.

c. EPA should reconsider its policy requiring PM2.5 modeling analyses for maximum 

modeled concentration instead of more refined estimates of the design value. 

Guidance must provide more flexible and refined approaches that enable the use of 

available monitoring data to make reasonable estimates of cumulative impacts.

4. EPA must provide accurate, stable modeling tools and guidance for industry during 

periods of significant capital investments to meet new regulatory requirements.

a. An example shows a significant increase in the modeled design concentration results 

from implementation of the AERMINUTE meteorological data preprocessor.

b. EPA should make needed changes to update the regulatory modeling system by 

addressing well-characterized bugs and systematic performance issues (i.e., low wind 

speed performance), then establish a stable modeling platform for consistent use 

during implementation of new regulatory programs.

5. Pulp and paper mills can demonstrate compliance with the 1-hour average SO2 NAAQS 

when “typical” operations are considered.

6. Streamlined approval of Tier 3 NO2 analyses should be available. EPA should allow instack NO2/NOX ratios which are significantly lower, e.g. 20%, than the EPA default value 

of 50%; examples are provided.
A-29

7. Implementation guidance and modeling tools that account for emissions variability, 

instead of assuming that all emission units operate simultaneously and continuously at the 

maximum allowable emission rate should be developed; examples are provided. 

a. Development of an emissions variability processor should be made a priority to 

account for substantial differences in actual and allowable emissions to avoid 

overestimation of model impacts. 

b. Until such modeling tools are in place, EPA should enable state/local permitting 

authorities to rely upon representative ambient monitoring data and emissions trends, 

to make decisions that reflect actual air quality conditions and impacts.

c. The stringency of the current NAAQS and screening nature of available modeling 

techniques compel EPA to reconsider other aspects of modeling policy guidance. 

Most important is the determination of the ambient air boundary to make a reasonable 

determination in cases where human exposure is unlikely, which includes rights-ofway such as public roads and railroads that transect facility property.

8. Conclusion

a. Several areas of concern for which current EPA guidance implements unreasonable 

and impractical policies that cumulatively overestimate modeled impacts are 

identified. EPA should adopt priorities to improve modeling tools and guidance.

i. Reconsider the policy that considers NAAQS effective for PSD permitting 

purposes immediately upon issuance, and instead institute a minimum 1-year 

transition period before new NAAQS would be considered applicable.

ii. Propose implementation guidance/rulemaking at the same time new NAAQS are 

proposed through a notice and comment process that allows for stakeholder input.

iii. Implement identified improvements to AERMOD (e.g., resolve the low wind 

speed bias), AERMET, AERMINUTE, and AERSURFACE as soon as possible.

iv. Update Tier 3 NO2 modeling techniques and enable a streamlined approval 

process at the state/local level for facilities applying sector/source-specific data.

v. Develop PM2.5 guidance that can be practically implemented:

-- Use 98th percentile design concentration consistent with form of the standard.

-- Allow the “Paired Sums” approach to account for background PM2.5 in the 

calculation of the 98th percentile design concentration.

-- Adopt a reasonable approach to estimate impacts of secondary PM2.5 that 

appropriately reflect spatial and temporal impacts relative to primary PM2.5.

vi. Revisit historical model clearinghouse guidance and enable state/local agencies to 

apply flexibility and judgment in consideration of source-specific circumstances.

vii. Align expectations for modeled ambient air receptors with realistic expectations 

of general public exposure.

viii. Commit to development of modeling tools and implementation guidance that 

simulates actual emissions profiles, rather than the conservative assumption that 

all sources emit simultaneously and continuously at the maximum allowable rate.

ix. Enable permitting authorities to rely upon representative ambient monitoring 

results in lieu of, or as a supplement to, modeling results for decision–making.

b. EPA should continue to engage industrial stakeholders in advance of issuing 

implementation guidance or changes to the modeling system to allow for exchange of 

information and expertise that can avoid unintended or unforeseen consequences of 

EPA modeling tools and guidance.
A-30

The Fertilizer Institute

1. Model Clearinghouse Status and Update Process

a. EPA should encourage and accept stakeholder input during efforts to improve the 

model clearinghouse process, contents and information; this will help reduce the 

likelihood of errors and deficiencies and the imposition of overly burdensome 

requirements in the resulting policies and guidance.

b. Information disseminated by EPA Conferences on Air Quality Modeling does not 

comply with EPA guidelines for compliance with the Data Quality Act. Revisions 

that lack model evaluation support, run contrary to long standing regulatory policy 

and guidance, and produce demonstrably erroneous results are often without the 

opportunity for independent peer review or public comment. Stakeholder input, 

including independent peer review, is often ignored or not otherwise integrated into 

final decision-making on data dissemination. In other instances, known data quality 

errors are consistently ignored by EPA. 

c. EPA should review its procedures for prioritizing, determining and disseminating 

information through the Conferences on Air Quality Monitoring process to ensure 

that data disseminated from these meetings are in compliance with EPA Guidance 

and the Data Quality Act. EPA should examine when and how stakeholder input is 

integrated into decision-making, how data are prioritized for review and revision, and 

how proposed changes to air models are validated before data dissemination.

2. Appendix W of EPA Permit and Modeling Guidance and Clarification Memoranda

a. Many aspects of the process of updating Appendix W and its contents are deficient. 

The current version, issued in 2005, is now very out of date with respect to both the 

existence of known, but uncorrected, errors in the computer codes of the preferred 

models, and the guidance needed to address the new and more stringent National 

Ambient Air Quality Standards (NAAQS) and Prevention of Significant Deterioration 

(PSD) increments that have been promulgated since 2005. The process of verifying 

reported errors in the preferred model codes needs to be accelerated, and known 

errors in the model codes must be corrected as soon as possible. 

b. Numerous model revisions and Clarification Memos have been issued by EPA 

without the opportunity for public comment and any stakeholder input or 

participation. EPA should encourage and accept stakeholder review and input during 

the development and implementation of all model revisions and Clarification Memos.

3. Currently preferred air quality models – AERMOD

a. Building downwash – 25 years of regulatory policy and guidance were overturned 

with respect to modeling the emissions from stacks whose heights equal or exceed the 

Good Engineering Practice (GEP) formula height by indicating that emissions from 

stacks whose heights exceed the GEP formula height were subject to the calculation 

of aerodynamic downwash in any Appendix W guideline model.

b. Low wind speeds – The incorporation of AERMINUTE into AERMET radically 

changed the manner in which AERMOD treats wind speeds. These changes were 

made in the absence of any model validation using measured data or demonstration 

that AERMOD is capable of producing valid air pollutant concentrations during wind 

speed condition below 1.0 mps. The previous AERMOD system model code should 

be restored immediately in which a minimum wind speed of 1.0 m/s was used in all 

its dispersion calculations. In addition, future changes to AERMINUTE, AERMET 
A-31

and AERMOD that involve wind speeds below 1.0 m/s should not be made until they 

are supported by appropriate model performance evaluation(s) and have been subject 

to public comment and participation. 

4. Currently preferred air quality models – CALPUFF

a. CALPUFF should be upgraded to correct all known bugs.

b. EPA must implement the well documented enhancements that have been developed 

since the 9th Modeling Conference, following the timely opportunity for public 

comment and participation.

5. PM2.5 modeling issues 

a. Un-validated revisions to AERMOD will certainly result in predicted PM2.5

concentrations that are erroneously large. As such, those over-predictions will prevent 

or hinder the development and construction of projects that otherwise and in actuality 

would not have unacceptable ambient air quality impacts. 

b. In the case of PM2.5, the small margins that exist between the NAAQS and the 

background concentrations will greatly magnify the adverse consequences of the 

tendency of AERMOD to over predict air quality impacts. PM2.5 modeling guidance 

to address these extremely challenging issues will have insufficient time for effective 

review and comment. 

6. 1-hour NO2/SO2 Modeling

a. EPA guidance, e.g., “Clarification Memos”, was developed over the past two years to 

address a variety of previously unrecognized and/or underappreciated consequences 

of the new NAAQS. Even so, the most recent of such memos contain ambiguities, 

logical inconsistencies, unscientific recommendations and superfluous requirements, 

some of which are also contrary to the Appendix W modeling guidance. 

b. There is a lack of clarity regarding the acceptance criteria for deriving and using both 

source-specific in-stack NO2/NOX emission rate ratios and a site-specific NO2/NOX

ambient equilibrium ratio, and when it is necessary to use their “default” ratios of 0.5 

and 0.9, respectively, as AERMOD model input. There is also a lack of clarity 

regarding acceptance criteria for selecting and utilizing background ozone (O3) and 

NO2 ambient air quality monitoring sites and data, when utilizing the Plume Volume 

Molar Ratio Method (PVMRM) algorithm in AERMOD to calculate the total 

concentrations attributable to the modeled sources plus the background 

concentrations.

c. EPA’s recommendation for deriving NO2 and SO2 background concentrations is 

unnecessarily stringent and unscientific; the cause and effect relationships that exist 

between the actual hour-by-hour meteorological conditions that produce both the 

predicted impacts of the modeled sources and the actual measured background 

concentrations. 

d. EPA should allow and encourage the appropriate use of concurrent 1-hour average 

modeled and measured concentrations to demonstrate compliance with the 1-hour 

average NO2 and SO2 NAAQS.
A-32

Koogler and Associates, Inc. – supports comments of the Fertilizer Institute

1. General Comments

a. The Model Clearinghouse must be revised in its content and its method of review and 

approval of updates to meet the demands of a shift to using modeling as a “hybrid” 

approach (i.e., monitoring to determine NAAQS status with modeling as an 

indicator). 

b. EPA should not issue modeling guidance as non-binding if it intends to later treat that 

guidance as binding; there is a necessity for such guidance and related documentation 

in the Clearinghouse to undergo the rigors of proposed rules and the rulemaking 

process.

c. EPA should provide appropriate notice, and an opportunity for comment, prior to 

finalizing the rule requirement to use ambient air quality modeling for any approach, 

including a “hybrid” approach, to establish nonattainment areas.

d. The model version relied upon by the State and EPA must remain valid for clearly 

defined time periods or on the basis of some predictable measure that provides the 

regulated community assurance of the valid application of a model and its results, e.g. 

revision to AERMOD downwash.

2. Model Selection

a. CALPUFF should be an approved alternative model without the need for the 

justification required by Section 3.2, Appendix W, 40 CFR 51, rather than 

AERMOD, in multi-source situations (including those in which the impact of 

multiple sources are calculated to determine “background”).

b. There are limitations to AERMOD in areas of complex terrain, in areas where there is 

a significant land/water interface, and at distances greater that 20km.

c. Due to the steady-state transport limitation of AERMOD, there is a tendency to overprediction of impact at mid-range and long-range target receptors.

3. Background concentration

a. There is a need for an improved method to account for SO2 background

concentrations. 

b. To obtain the most appropriate background concentration for the target area, 

consideration should be given to using a “frequency of occurrence” approach (see 

example provided), rather than the uniform background concentration typically used 

in AERMOD.

Coulter Air Quality Services

EPA’s New Stack Downwash Policy Lacks Proper Demonstration and is Ill-posed – The change 

is aerodynamic downwash policy reflected in MCB#4 for AERMOD, is technically flawed, is 

inconsistent with EPA policy for good engineering stack height, is a subversion of the spirit and 

letter of the Administrative Procedures Act of 1946, and should have been subjected to public 

notice and comment procedures.
A-33

Camille Sears

1. Single-source ozone and PM2.5 modeling should be used in permit applications for major 

emission sources

a. USEPA should develop a time-table for model development for single-source ozone 

and PM2.5 impacts, which includes opportunities for public input and comments. In 

the interim, USEPA should provide enhanced case-by-case support to State and Local 

agencies on what models and protocols to use.

b. Comments on this same issue were provided at the 9th Modeling Conference and EPA 

responded in an affirmative manner relative to the Sierra Club Petition.

c. Opportunity for public comments on two Environ reports (WA #4-06) should be 

provided.

d. With respect to ozone, single-source ozone impact analyses, using photochemical grid 

modeling, should be required for major NOX and VOC emission sources. 

e. State and Local agencies should be required to consult with the Regional 

meteorologists on this issue and they must work with USEPA on a case-by-case basis 

for determining the best models to use for assessing single-source impacts from major 

NOX and VOC emitting facilities.

f. With regard to Draft PM2.5 Permit Modeling Guidance, further development is needed 

to provide additional details on how the four scenarios will also protect the PM2.5

PSD increments, not just compliance with the PM2.5 NAAQS; clarification of the four 

individual scenarios is also desirable.

2. Air dispersion modeling should be the preferred method for determining one-hour SO2

impacts

a. In virtually all cases air dispersion modeling should be used to determine one-hour 

SO2 impacts from coal-fired power plants and other major SO2 emission sources; 

modeling should be applied in all situations except where source-specific SO2

monitoring exists and the monitor is properly located to capture maximum facility 

impacts. All NO2, PM2.5, and SO2 NAAQS and PSD increment compliance 

verification analyses are performed with air dispersion modeling, such as running 

AERMOD in a manner consistent with the Guideline on Air Quality Models. In order 

to ensure consistency in how air impacts are determined, both existing sources and 

newly permitted sources should be assessed using the same methods. If existing 

sources are allowed to use monitoring, which are generally not “well-placed” for 

measuring the maximum ambient air impacts form existing sources, this results in a 

lower standard of compliance verification than that being used for new permit 

applicants.

b. It should be noted that contrary to comment by some industry representatives, 

AERMOD’s evaluation analyses include a number of site-specific meteorological 

data sets that incorporate low wind speed conditions.

c. Concerning the use of actual emissions for nonattainment SIP modeling, a condition 

must be added to the facility’s permit requiring that emissions must not be greater 

than the level used in the modeling analysis. Also, actual emissions cannot be 

modeled using full load stack parameters; stack gas exit velocity and temperature is 

reduced under less than full load conditions, affecting plume rise and resulting 

modeled impacts. Any AERMOD modeling using actual emission levels must use 

corresponding actual stack gas exit velocity and temperature.
A-34

North Dakota Department of Health

1. Application of AERMOD should be limited to distances of 20 kilometers or less. That is,

AERMOD should be used only when all nearby sources are located within 20 kilometers 

of the subject or primary source. If nearby sources (which must be included in the 

cumulative analysis) are located more than 20 kilometers from the primary source, the 

steady-state AERMOD model will not be adequate, and CALPUFF (or possibly similar 

dynamic model) should be used instead.

2. If nearby-source impacts are important in an analysis, CALPUFF’s handling of nearby 

sources is superior to AERMOD’s, and similar overall performance of CALPUFF should 

make it preferred in such a case involving nearby sources. AERMOD’s handling of 

nearby sources (farther than 20 kilometers) is inferior to CALPUFF’s capability. 

AERMOD uses only meteorological data and surface characteristics from one site,

whereas CALPUFF uses spatially gridded data based on meteorological data and surface 

characteristics from many locations.

3. The EPA-recommended version of CALPUFF should always be the most technically 

advanced version (currently Version 6.4). To save time, testing to support new versions 

should be based on third party as well as EPA evaluations. Bug fixes and other minor 

updates should be implemented immediately as released in model change bulletins (or 

users should be allowed to implement bug fixes themselves) without any testing 

requirement. CALPUFF documentation needs to stay current with the recommended 

version of the model.

4. It may be advantageous to replace the “AERMOD near field” and “CALPUFF far field” 

scheme with a single dynamic model capable of covering all distances from 0 to 300 

kilometers (or more). The SCIPUFF model may be an acceptable alternative to 

CALPUFF. It would appear that both CALPUFF and SCIPUFF could effectively serve as 

a single tool, even in their current iterations. 

5. A priority for EPA and IWAQM is development/approval of models for single-source 

ozone and secondary PM2.5. 

6. For consistency with AERMOD, the dispersion setting used with CALPUFF (MDISP) 

should be Option 2, turbulence-based dispersion, rather than the currently recommended 

PG dispersion. CALPUFF even provides an implementation of the turbulence dispersion 

which makes it equivalent to the AERMOD dispersion. 

7. EPA should test use of MDISP=2, micrometeorological variables or turbulence 

dispersion, in CALPUFF and approve its use where it is shown to be superior.

8. For AERMOD (AERMET) modeling, surface characteristics for the primary source 

location should be used, rather than the meteorological data (wind measurement) site.

EPA has provided no substantive justification, nor side-by-side performance test results, 

on why use of surface characteristics for the primary source location is not preferable.

9. Topics such as treatment of terrain height variations, AERMINUTE, downwash effects, 

actual emission rates, national consistency in selection of model input data, in-stack 

conversion ratios for NOX to NO2, application of AERSURFACE with land cover data 

bases, the basis for determining roughness length (AERMET) all require further attention 

by EPA, as well as the opportunity for public input.

10. Model performance evaluations should focus on the highest (upper quantile) predictions, 

and need not include distribution where observations have fallen to less than minimum 

detectable values.
A-35

Air & Waste Management Association, AB-3 Committee on Meteorology, includes 

Exponent, Inc.

1. Changes made to the downwash code with AERMOD version 11059 lead to significant 

increases in predicted concentrations for wide buildings. The changes did not undergo 

public review or comment. The EPA has presented no data to justify the technical basis 

for the specific algorithms used above GEP formula height, especially for long buildings 

where the effects are greatest. The EPA did not release a consequence analysis of 

changes. As a result: 

a. The change to building downwash procedures introduced in AERMOD version 11059 

should be removed from the regulatory version of AERMOD until independent peer 

review, consequence analyses, and model evaluations are conducted.

b. Any new model changes such as the effective building length introduced at the 10th

Conference should be subject to a transparent public review process with independent 

scientific review and evaluation prior to its use in regulatory applications.

c. While the known problems with AERMOD for long buildings are being addressed, 

EPA should allow Section 3.2 Petitions (use of alternative models) to address the 

problem with AERMOD for very wide buildings, such as aluminum reduction 

facilities.

2. Since EBD may be the only alternative to obtaining accurate concentration estimates for 

some building configurations, a method is needed to streamline the process for using 

EBDs. Some things that would help streamline this process are: 

a. Clear guidelines on how to conduct an EBD study; 

b. Interaction with the ultimate decision makers at EPA in the protocol development and 

approval process; 

c. Actual EPA approval of the EBD protocol prior to conducting the study; 

d. Cooperative interaction with EPA during the EBD study and preliminary report phase 

where results are reviewed and if necessary changes made to the EBD testing method 

prior to issuance of a final report; 

e. A timely review and approval process; and 

d. Some assurance that once a final report is issued, the EBD values will be approved 

for use. 

3. There are a couple optional methods whereby this streamlined process could be developed 

for EBD. 

a. Form an Industry/EPA work group tasked with developing guidance for conducting 

EBD evaluations. This guidance could then be published like those published for 

determining GEP stack heights (EPA, 1985). The guidance would include a checklist 

that could be reviewed by EPA to ensure that all studies are conducted in a consistent 

manner. 

b. Wait for the next EBD protocol to be submitted to EPA. At this time, the EPA Model 

Clearinghouse could get involved and review and comment on the protocol. Once this 

protocol is completed and approved, it could be used as a template for future EBD 

studies. Also, once the report is submitted and approved it could also be used as a 

report template for future studies.
A-36

(This Page Intentional Left Blank)
B-1

Attachment B

Summary of 10th Conference on Air Quality Modeling Individual Presentations

The summary of individual presentations in this Attachment are (1) largely excised from 

conference presentation materials and (2) supplemented where necessary by information from 

the conference transcripts. Internet links to both the conference presentations and transcripts are 

listed in Attachment C. Presentations by U.S. EPA staff that are of informative or status nature 

are not summarized in this documentation package but are available via the provided Internet 

links; including those by Wayland, Fox, Bridgers, Brode, Thurman, Patulski, Baker, Snyder, 

Kelly, and Anderson (USFS).

AERMOD Applications Development

Ron Petersen -- CPP Inc.

• Background to use of equivalent building dimensions (EBDs) in AERMOD

o Equivalent Building Dimensions” (EBDs) are the dimensions (height, width, 

length and location) that are input into AERMOD (or ISC) in place of BPIP 

dimensions to more accurately predict building wake effects.

• Summary of AERMOD Modeling Conducted to Support the Assessment of Alcoa 

Davenport Works EBD Study

o Compared wind tunnel observations with AERMOD predictions

o Results used to provide additional justification regarding concerns about large 

roughness

o Problems with analysis

 Appears EPA used model speed at reference height – should use simulated 

full scale speeds versus height

 EPA used roughness length input for dispersion calculations: should use 

measured turbulence profiles in wind tunnel

 Assumed stable conditions: neutral simulated

 Used combination of model and full scale inputs: should use model values 

appropriately scaled to full scale

 Not enough data collected during wind tunnel testing to do a valid 

comparison

o Attachment B conclusions flawed – here is where collaboration would have been 

useful

• Path Forward

o Option 1:

 Create an Industry/EPA work group to develop a guideline for conducting 

EBD evaluations; then publish guideline much like the EPA Fluid 

Modeling Guideline

o Option 2:

 Wait for next EBD protocol submitted to EPA with EPA Clearinghouse 

review and comment on protocol

 Collaboration as needed during the review process and approve final 

protocol – not done in that past
B-2

 Conduct the study in a collaborative fashion with near real-time feedback 

and make adjustments as needed

 Use final protocol as a template for future studies

Bob Paine – AECOM for API and UARG

• Concerns noted by EPA and the modeling community on AERMOD low wind speed 

applications

o Brode USEPA 2007 Modeling Workshop from AERMOD Implementation 

Workgroup Highlights

 “Mandatory work: Light winds. Revise AERMOD’s treatment of light 

winds to avoid unrealistically high concentrations”

o Reported at USEPA’s 9th Modeling Conference - Air & Waste Management 

Association Comments

 Many investigators report that the worst-case AERMOD impacts occur for 

very low wind speeds at night, especially for low-level sources

o AERMOD has limited evaluation for these conditions very few hours with wind 

speed < 1 m/s

• Findings and Recommendations

o API provided results, code, and modeler’s archive to EPA for review 2 years ago

o We encouraged EPA to add our code changes as a beta option to an 

AERMET/AERMOD release:

 Set minimum sigma-v = 0.4 m/s instead of 0.2 m/s

 Use alternative u* formulation for both single-level and 2-level 

approaches

o Low u* has other implications – results in very low mechanical mixing heights 

which leads to extremely low plume spreading for releases above the mixing 

height

Randy Robinson – EPA Region 5

• Haul Road Workgroup Concerns

o Modeled impacts substantial

o Sources difficult to characterize

o Lack of state-to-state consistency

• Recommendations

o Volume source

 A volume source characterization is recommended for all haul roads, 

except for cases where ambient air receptors are within the volume’s 

exclusion zone

 Rationale: Volume source contains meander algorithm, and limited study 

using Cordero Rojo Mine measured data supports volume source use over 

area source

o Area source

 Recommended for cases where ambient receptors are located within 

source dimensions
B-3

 Length – length of roadway; Width – VW + 6m for single lane : Road 

width + 6m for two-lane; Top of plume height – 1.7 x vehicle height; 

Release height – 0.5 x top of plume height; Sigma Z - top of plume / 2.1

o Future efforts

 Encourage more field studies examining initial plume dimensions, 

including the impact of vehicle speed

 Point source modeling has some potential benefits, such as the ability to 

consider the influence of facility structures near roadways, and the 

workgroup supports further study of this approach

 New line source work may eventually replace need to model fugitive 

roadway dust as either volume or area source

Chatten Cowherd – MRI Global

• Modeling concerns for fugitive sources in the iron, steel and mining industries

o Emission factors

o Particle size distributions

o Source representation

o PM10 and PM2.5 depletion issues

• Recommendations to improve accuracy

o Air dispersion models are not currently accurate enough to meet regulatory 

challenges – especially for fugitive, area, volume, and low-stack sources that are 

prevalent in the iron, steel and mining industry

o Steps to improve accuracy should include

 Incorporate the emission deposition pre-processing step into the standard 

modeling protocol

• Adopt an emissions pre-processing step (similar to CMAQ areawide fugitive dust modeling)

• Develop a set of emission reduction factors that offset AERMOD 

modeling deficiencies, based on the distinguishing characteristics 

of roadways and other source categories and the near-source 

dispersion environment

 Adjust the model to address wind speed-dependent emissions to avoid 

positive bias for fugitive and volume/area sources during low wind speed 

events

 Re-examine the applicability of AP-42 emission factors and particle size 

distributions and adjust as necessary
B-4

Currently Preferred AQ Models -- CALPUFF

Gale Hoffnagle -- TRC Companies, Inc.

• CALPUFF 5.8 modeling system status and availability

o TRC maintains the EPA approved code for free use by the public

o TRC provides the CALPOST version 6.221 which supports the Federal Land 

Manager’s FLAG assessments and the BART process

o EPA has not yet approved the bug fixes for Version 5.8 submitted in 2005. Model 

Change Bulletins E and F

o EPA’s work to date on CALPUFF is meant to confine it’s use (April 2008 memo) 

and to sponsor one study which uses CALPUFF as a long range transport model

• CALPUFF 6.4

o Several studies have demonstrated that version 5.8 significantly overestimates 

sulfate and nitrate production and thus visibility impacts

o CALPUFF Version 6.4 incorporates more sophisticated handling of the 

atmospheric chemistry of sulfate and nitrate formation. This leads to more 

accurate reproduction of both particulate formation and visibility impact 

calculations

 RIVAD ozone chemical mechanism

 ISORROPIA inorganic gas particle equilibrium

 RADM for aqueous phase transformation

 Secondary organic aerosol formation from CalTech

o TRC urges EPA to consider version 6.4 for application to these assessments

o Version 6.4 is “backward compatible” with Version 5.8

o Version 6.4 will provide much more accurate determinations of sulfate and nitrate 

production and thus, much more accurate determinations of visibility impact and 

BART determinations

o TRC urges EPA to consider version 6.4 for application to these assessments

PM2.5 Modeling

Ryan Gesser – American Forest & Paper Association

• Challenges to the pulp & paper industry on PM2.5 modeling methods

o Like many industrial sectors, integrated pulp & paper mills find it difficult to 

demonstrate compliance with applicable NAAQS following current EPA 

modeling guidance resulting in numerous consequences... 

 New projects cannot move forward until modeling issues are resolved

 Existing operations without projects may be required to evaluate controls 

if NAAQS evaluation is required as part of operating permit renewals

 “Better than BACT/MACT” levels of control may be necessary to 

demonstrate compliance, which may require...

• ...significant capital investments in new or upgraded controls

• ...”on-paper” reductions to permit limits

• ...reduced fuels/operational flexibility
B-5

• Observations/Comments

o AF&PA is concerned that current EPA guidance is overly conservative and 

cannot be practically implemented

o AF&PA appreciates efforts to ... 

 ...develop best practices for fugitive source modeling

 ...identify and correct systematic deficiencies in model performance

o AF&PA eagerly anticipates draft PM2.5 guidance and appreciates opportunity to 

comment

 Sound, unbiased estimates of impacts, including background and 

secondary formation

 Temporal consistency of background concentrations

 Spatial consistency of secondary impacts

o AF&PA promotes reasonable, practical implementation of new standards and 

modeling guidance

 Critical application of EPA guidance in practice to provide stability during 

regulatory implementation periods

 Revisit traditional approaches (ambient air, variable emissions)

1-hour NO2/SO2 Modeling

Bob Paine, AECOM

• Emissions Variability Processor (EMVAP)

o Large variation possible over the course of a year

o Intermittent sources (e.g., emergency backup engines or bypass stacks) present 

modeling challenges

o For these sources, assuming fixed peak 1‐hour emissions on a continuous basis 

will result in unrealistic modeled results

o Better approach is to assume a prescribed distribution of emission rates

o EMVAP (Emissions Variability Processor) uses this information to develop 

alternative ways to indicate modeled compliance using a range of emission rates 

instead of just one value

• Conclusions and status

o EMVAP is currently operational for EPRI beta testing and consideration of 

implementation approaches

o Evaluation against field data shows expected results: critical predictions are 

somewhat higher than those from actual emissions and lower than those from 

peak emissions

o Further development and testing is currently underway by EPRI

• Additional factors

o There will be a need to determine how an emissions distribution is assigned to a 

new source and how this is put into an enforceable regulation; this requires public 

comment

o A change in Appendix W and in Tables 8.1 and 8.2 will be required

o Multiple sources with variable emissions will have to be addressed
B-6

Mark Podrez – RTP Env. Assoc. Inc

• Ambient Ratio Method (ARM) for 1-hour NO2 NAAQS analyses

o ARM was originally developed for annual NO2 modeling, using annual ambient 

NO2/NOX ratios for all monitoring sites in 1987-1989

o EPA has cited two recent studies to support the current recommendation of a 

fixed ARM ratio of 0.80 for 1-hour analyses

o However, both of these studies, as well as other monitoring data evaluations, 

demonstrate that variable ratios are observed as a function of distance/time from 

the source. This indicates that the current fixed-value ARM method may be 

overly conservative for 1- hour NO2 analyses, especially when nearby “fenceline” concentrations are the controlling impact.

o A variable ratio ARM method (“ARM2”) could be less conservative than current 

fixed 0.8 ARM guidance, yet more conservative than refined Tier 3 methods.

o Current fixed ratio ARM is not very useful for 1-hour modeling; ARM2 could fill 

a gap in Tier 2 and 3 techniques.

o If a variable ratio 1-hour ARM2 is based on a large enough data set of 1-hour 

ambient monitoring data, it would implicitly address the range of entrainment, 

mixing, and conversion processes that are occurring over a wide range of total 

NOX concentrations.

• Conclusions

o ARM2 is more conservative than PVMRM and OLM at low and mid-range NO2

concentrations. At the higher NO2 concentrations in the test data sets, ARM2 

compares well to the best performing Tier 3 method.

o ARM2 fills the gap between current fixed-ratio 1-hour ARM guidance and the 

more refined Tier 3 methods. EPA should adopt a revised ARM2 method for 1-

hour NO2 analyses via an updated guidance memorandum.

o Additional test data sets with elevated NO2 impacts at or above the NAAQS, and 

with better source data, are needed to evaluate the various conversion methods.

Steven Hanna -- Hanna Consultants

• NO2 modeling - PVMRM and OLM evaluation using a new data set

o Identify existing dataset that could be used to evaluate AERMOD and the 

PVMRM and OLM options for predicting 1‐hour NO2 concentrations

o Evaluate:

 AERMOD predictions of NOX

 OLM and PVMRM predictions of NO2/NOX ratio

 AERMOD/PVMRM and AERMOD/OLM predictions of NO2

concentrations

• Conclusions

o PVMRM is doing well at predicting the NO2/NOX ratio (minimal bias, with most 

ratios from 0.2 to 0.4).

o OLM has a general 70 % over prediction tendency for the NO2/NOX ratio.

o Both AERMOD/OLM and AERMOD/PVMRM over predict the high end NO2

concentrations by about a factor of two (OLM by more) (But this may be caused 

by the fact that AERMOD over predicts the high end NOX concentrations).

o There was little skill (correlations) evident in both
B-7

o To be robust, many data sets should be used in a model evaluation so that a 

multitude of conditions, source data, etc. can be included.

o This evaluation using the Wainwright data set should be considered an additional 

piece of information to supplement the limited number of data sets used by EPA 

to date to evaluate the PVMRM and OLM options in AERMOD for predicting 

1‐hour NO2.

o A detailed field experiment is needed.

Dan Dix – All4

• Collection of in-stack NO2/NOX ratio information

• The collection of in-stack NO2/NOX data for use in AERMOD’s OLM and PVMRM 

option has become more important since the promulgation of the new 1-hour NO2

NAAQS.

o Many facilities are currently collecting NOX data using CEMs

o CEMs collecting NOX data use the Chemiluminescence method which also 

measures NO and NO2.

• Conclusions and considerations 

o Cost effective and simple (less invasive) way to collect in-stack NO2/NOX

information for use modeling NO2 using AERMOD’s OLM or PVMRM 

options.

 It was easier and more cost effective to install a temporary datalogger 

than set up NO2 readings in their current DAHS and PLC Systems.

 A Campbell Scientific CR1000 data logger was hooked up to unused 

ports on the 42i and programmed to take 1 minute readings of NO, 

NO2, and NOX.

o Many facilities currently operate NOX CEMs under a variety of programs.

o DAHS systems could also be set up to collect this information.

o If no NOX CEMs is in place this data can also be collected during NOX

testing.

o Protocol Considerations

 Statistical Analysis

 QA/QC

Emerging Models / Techniques

Ralph E. Morris -- ENVIRON International Corporation

• Conclusions of long range tracer model intercomparison and evaluation study

o GP80 Tracer Field Experiment

 Using different valid CALMET configurations, the maximum CALPUFF 

concentrations vary by factor of 3

 Since less option, less variation using MMIF

 CALPUFF “SLUG” near‐field option needed to reproduce “good” model 

performance on 600 km arc from 1998 EPA study

o SRL75 Tracer Field Experiment

 Fitted Gaussian plume evaluation approach can be flawed
B-8

o CAPTEX Tracer Field Experiment

 RMAX1/RMAX2 = 100/200 (EPA‐FLM recommendation) produces best 

WS/WD but worst CALPUFF tracer

 CALPUFF/MMIF performs better than CALPUFF/CALMET for CTEX3 

but worst for CTEX5

 CTEX3: CAMx & SCIPUFF perform best followed by CALPUFF & 

FLEXPART with HYSPLIT & CALGRID worst

 CTEX5: CAMx/HYSPLIT performs best followed by 

SCIPUFF/FLEXPART with CALPUFF/CALGRID worst

o ETEX Tracer Field Experiment

 CAMx, HYSPLIT & SCIPUFF perform best

 FLEXPART & CALPUFF perform worst

Public Presentations

Pietro Catizone, A&WMA AB-3 Meteorology Committee – Introductory Comments

(Comments left over from the 9th Modeling Conference)

• Clearinghouse turnaround and input

o Traditionally, the Model Clearinghouse process does not allow technical input by 

the affected parties (e.g., permit applicant)

o Typically, the permitting authority states their opinion and asks for Clearinghouse 

approval; no other involvement allowed

o AB-3 recommends that the affected parties be able to provide comment along 

with the permitting authority’s correspondence to the Clearinghouse; involvement 

would result in quick and faster resolution of the issues with a common consensus

• Status and timeline of modeling Guidance – SO2 and PM2.5

o Issuance of modeling Guidance has been lengthy and the lack of final guidance 

can affect the viability of project schedules

 SO2 draft guidance out since September 22, 2011, final guidance is 

forthcoming?

 Secondary PM2.5 guidance expected for some time, but not yet available!

o Collaborative efforts might help to expedite process – how can groups like AB-3 

get involved and help?

• What is the availability of the long range transport data base for model evaluation? Is it 

publicly available?

Lloyd L. Schulman -- Building Downwash Modeling with AERMOD (A&WMA AB-3)

• AERMOD status

o Changes made to the downwash code with AERMOD version 11059 lead to 

significant, but unverified, increases in predicted concentrations for wide 

buildings

o Even without the code change, documented over‐predictions exist for very wide 

buildings
B-9

o Change described in MCB #4 (2‐28‐2011) states: “Subroutine WAKFLG was 

modified to no longer ignore potential downwash effects for stack heights that 

equal or exceed the EPA formula height. The determination of whether building 

downwash effects apply is based on the criterion implemented within the PRIME 

downwash algorithm.”

o Previous policy was to only model downwash effects for stacks less than GEP 

formula height

o AERMOD downwash change:

 Change was made to eliminate discontinuities for stacks straddling the 

GEP formula height

 The change will be justified by a pending clarification memorandum

 No consequence analyses provided by EPA

 No public comment or review of this significant change to the model

 There is downwash at formula height for most buildings, but does PRIME 

model it correctly?

 PRIME algorithm was developed using data from buildings with W/H 

<4.4 and sub‐GEP stacks

 Over‐prediction already demonstrated for very wide buildings –

unrealistically long projected lengths from BPIPPRM

 Allowing downwash for stacks greater than formula height will exacerbate 

this problem.

 Proposed definition of an effective building length is a step in the right 

direction but needs further testing and confirmation

• Conclusions and recommendations

o Change to downwash procedures in AERMOD are significant

o Predicted building influences are inconsistent with theoretical estimates and wind 

tunnel studies

o No public peer review or comment on these changes; a clarification memo is not 

sufficient

o The change to downwash procedures should be removed from the regulatory 

version of AERMOD until independent peer review, consequence analyses, and 

evaluations are conducted for stacks above formula height

o These evaluations should be bundled with the independent review and evaluation 

of the effective length parameter in BPIPPRM

Joseph S. Scire -- Assessment of EPA’s ETEX Evaluation Study (A&WMA AB-3)

• Evaluation Conclusions:

o EPA‐ENVIRON study on the ETEX‐1 model evaluation contains flaws which 

significantly affect model conclusions regarding CALPUFF and which model 

performs best

 Errors in model setup

 Inappropriate model configuration settings

 Inadequate coarse resolution (36‐km) MM5 data

o Alternative CALPUFF configuration with EPA met data significantly improves 

performance
B-10

o Simulation with higher resolution MM5 data produces CALPUFF model 

performance comparable with the best performing group of models

o Review of modeling conducted by EPA during 2008‐2012 is late in the process 

due to previous lack of access to datasets.

• Recommendation: Full and timely access to all model evaluation data be provided to the 

entire modeling community

o Evaluation process would benefit from direct involvement of model developers in 

the evaluation of their models

o Configuration mistakes and errors more likely to be caught and corrected

Joseph S. Scire -- New Developments and Evaluations of the CALPUFF Model 

(A&WMA AB-3)

• Overview of Changes:

o CALPUFF v6.42b chemical module updates

 ISORROPIA II (v2.1) used for nitric acid/nitrate aerosol partition

o ISORROPIA used in Eulerian models such as CMAQ and CAMx

 Aqueous-phase chemical transformation (adapted from RADM cloud 

module in CMAQ/SCICHEM)

o Oxidation of SO2 in cloud water and rain water

o V6.42b couples CALPUFF with MM5/WRF liquid water content

o Tracks location of plume and overlap with cloud layer

 New RIVAD module tracks depleted O3 and H2O2 in each puff

 Anthropogenic secondary organic aerosol (SOA) formation

 (from CalTech SOA routines implemented in CMAQ-MADRID)

• Summary:

o CALPUFF v6.42b includes significant improvements in the treatment of chemical 

reactions

 ISORROPIA II model for inorganic gas-particle equilibrium as in

• CMAQ

 Revised gas phase chemical transformation module for SO2

• conversion to sulfate and NOX conversion to nitric acid and nitrate

 Aqueous phase oxidation and wet scavenging module adapted from

• the RADM cloud implementation in CMAQ/SCICHEM, with 

access to

• 3D cloud water fields from MM5/WRF

 New option for anthropogenic secondary organic aerosol (SOA)

• formation based on the CalTech SOA routines implemented in 

CMAQ-MADRID

o SWWYTAF evaluations with enhanced resolution MM5 meteorological data 

demonstrates significant improvement in performance over the default FLAG--

(2010) chemistry options

o Large over prediction of average observed nitrate concentrations with the older 

chemistry mechanism is reduced or eliminated with new chemistry 

o Cumberland plume simulations indicate O3 depletion improves the modeled 

sulfate transformation rate, and both RIVAD module options improve modeled 

NOX transformation at large distances
B-11

• Conclusions

o New chemistry modules in v6.42b use well-established algorithms referenced in

 the referred literature and almost universally accepted in the modeling 

community as better science

o CALPUFF v6.42b is backwardly compatible with v5.8 (after bug fixes are

introduced to v5.8). 

 CALPUFF should be adopted as a replacement for v5.8 to allow access to 

7 years of optional model improvements, including the new chemistry.

 Because v6.42b is equivalent to v5.8 when run in the same mode, v6.42b 

is an equivalent model.

o New chemistry can and should be accepted under Section 3.2 of Appendix W

 Section 3.2 is designed to allow use of important model enhancements in a 

timely way on a case-by-case basis, without the 3-5 year wait for formal 

rulemaking

 BART rule indicates CALPUFF is acceptable but also allows for 

alternative models

o EPA should approve v6.42b on case-by-case basis for use in BART applications

Andy Berger – West Associates

• Specific enhancements to the regulatory version of CALPUFF need to be adopted for 

BART determinations and reasonable progress work.

• The 2005 BART rule indicates that the simplified chemistry in the CALPUFF model 

tends to magnify the actual visibility effects of a source and, in the next review of the 

modeling guideline on air quality models, EPA will evaluate these and other newer 

approaches. At the 9th (2008) modeling conference API recommended a new chemistry 

model to reduce CALPUFF over prediction of nitrates. In November 2010, based on 

successful completion of tests and evaluations, CALPUFF Version 6.4 with new 

chemistry and code fixes was placed in the public domain.

• EPA should conduct its own test and evaluation of CALPUFF Version 6.4, before final 

best-available retrofit technology determinations are made later this year under a consent 

decree. If findings for Version 6.4 are duplicated, EPA should move expeditiously to 

designate CALPUFF 6.42b as the regulatory version of the model for BART 

determinations, at least on a case-by-case basis. This approach is consistent with the 

process EPA used with recent changes to the AERMOD model.

Steve Hanna – Hannah Consultants for API

• To improve the use of models, it is necessary to

o Continue to develop and improve modeling science by conducting additional 

model evaluations that consider a variety of source characteristics and 

atmospheric conditions, e.g., low‐level sources, low wind speed conditions

o Improve guidance on modeling use and model inputs

 Guidance should undergo peer review/public comment prior to issuance

 Balance need for standardization and consistency against ability to use the 

best model for the source/conditions

 More realistic inputs mean more realistic results
B-12

o Help policy makers, model users, and those evaluating model results better 

understand the limitations and uncertainties of modeling tools

o Provide for better use of well‐sited air quality monitoring

• Previous Modeling Conference comments still appropriate

o Need for complete documentation and guidance

 All codes should be in public domain

 All documentation needs to be brought up to date and made publicly 

available

o General need for more EPA guidance, workshops, and training for the modeling 

community

o Encourage development and use of science‐based models through evaluation 

efforts and enhanced public involvement

• PM2.5 and SO2 NAAQS Guidance

o EPA should provide a minimum of 60 days for comments on PM2.5 Modeling 

Guidance

o Complete final SO2 NAAQS implementation guidance and an implementation 

rule that provides for:

 Use of monitoring data as the preferred method for attainment 

determinations.

 Non‐attainment SIPs should:

• Use modeling recognizing accuracy limitations

• Use weight of evidence assessments (other data and analyses to 

supplement modeling)

• Use actual emissions, not potential to emit

• AERMOD

o Low winds ‐ over predictions in low winds during stable conditions are now 

found and possible fixes to the AERMOD low wind parameterizations have been 

suggested by several groups. EPA should implement the results of the API/UARG 

Low Wind Speed Project.

o Urban dispersion ‐ The AERMOD modules rely on PRIME, which is intended for 

downwash scenarios with only a few buildings. For urban areas with several 

blocks of many buildings, a new urban dispersion module is needed and there are 

several well-tested urban dispersion modules that are available and that have been 

evaluated with data from recent large new urban tracer data bases. The EPA 

AMAG is developing an urban dispersion model system that could be directly 

implemented in AERMOD.

o NO2 chemistry ‐ is not adequately accounted for in AERMOD via PVMRM or 

OLM. Outside groups have suggested improved chemical formulations, including 

those in SCICHEM, ADMS, and RPM2. These should be tested. The ARM2 

method is a revised ambient ratio approach based on extensive observations, and 

should be implemented as an interim approach. It is essential that a new 

comprehensive NOX plume field experiment be carried out and used for model 

testing.
B-13

o Use of airport met observations for sites many km away - Methods should be 

developed to better extrapolate the airport observations to the local site. Various 

improved extrapolation methods are available that better account for the 

differences in surface roughness wind speed at the reference height. Prognostic 

meteorological models may also be useful for extrapolation, after testing.

o The straight‐line assumption in AERMOD - The 50 km assumption is much 

beyond the travel distance in one hour for most wind speeds encountered. EPA 

should either better justify the current arbitrary 50 km limit or provide guidance 

for reducing the distance limits during lighter winds. It may be necessary to use a 

Lagrangian puff model (CALPUFF or SCIPUFF) at distances beyond where the 

straight‐line assumption breaks down. 

o Use of realistic emissions ‐ The use of maximum allowable emissions all year in

modeling is not realistic and is overly conservative. If observed emissions are not 

available, it may be appropriate to allow a Monte Carlo random value that 

provides agreement with the known average and scatter of emissions. For multiple 

sources, the correlation of emissions between sources should be considered.

• CALPUFF

o The 50 km minimum distance limit should be reduced, since puff models are 

scientifically valid at much shorter distances. CALPUFF may need some 

modifications, though, to assure that it provides similar predictions to AERMOD 

at the overlap distances.

o Several other high‐quality widely‐used Lagrangian puff and particle models are 

available in the U.S. (e.g., SCIPUFF and LODI) and abroad (e.g., RIMPUFF and 

Flexpart). Some were recently evaluated by EPA using long‐range field data, 

found to provide similar results to CALPUFF, and should be considered by the 

EPA.

o The chemistry in the current version of CALPUFF and similar models should be 

(and is being) improved to account for more chemicals, for non‐linear reactions, 

and for heterogeneous conversions (such as gas to particle). Improved CALPUFF 

chemistry that has been carefully tested with field data should be incorporated 

into the regulatory version of CALPUFF.

• Regional chemistry models (CMAQ and CAMx)

o Regulatory applications of CMAQ and CAMx should take a more prominent role 

in the present conference

o We encourage the current EPA effort to incorporate the SCICHEM plume‐in‐grid 

model in CMAQ to more realistically treat a large point source plume.

• Prognostic meteorological models

o We are pleased that the EPA is investigating linking their dispersion models with 

the outputs of prognostic meteorological models.

o The EPA testing of the Mesoscale Interface (MMIF) program, which provides an 

interface between the met model outputs and the required dispersion model inputs 

is a good first step.
B-14

o Uncertainties ‐ Many studies find that the use of the met models does not 

necessarily improve the dispersion model predictions. 

 Met models have inherent uncertainty themselves. 

 No major changes in the use of met models should be made until extensive 

testing is done over a wide range of scenarios, in order to demonstrate that 

the changes produce improved or at least similar performance compared to 

current methods (such as use of single met sites in AERMOD or 

diagnostic met models in CALPUFF).

• Background concentrations

o If a local monitor is used to establish background, double‐counting the 

contribution of sources can be avoided by using more than one monitor and 

adding background determined from the lowest monitored concentration each 

hour in a paired in time procedure with the modeled concentrations.

o The background should conform to the averaging times and the spatial domain of 

the scenario being modeled.

• Model evaluation and data bases

o The EPA model evaluation methods are inconsistent and rely too much on the 

Quantile‐Quantile (Q‐Q) plots. No estimates of statistical significance are given.

o The EPA should revisit their model evaluation method derived 15 years ago and 

included in an ASTM guideline. These are similar to the Hanna and Chang BOOT 

model evaluation methodology, which determines whether differences between 

performance measures are significant for two different models.

o There is a need for the EPA to put all of their dispersion field data sets into a 

single data archive for easy public access. 

o The Chang and Hanna suggestions of model acceptance criteria should be 

considered, since they have been tested using many field experiments and are in

wide use. 

o Separate criteria are suggested for performance measures such as FB and NMSE 

for rural and urban areas. 

o Additional OAQPS‐specific acceptance criteria could be developed for measures 

such as “2nd‐high” and for routine sampling networks (i.e., not research‐grade). 

Together with significance tests, the model acceptance criteria allow quantitative 

comparisons of models.

• Recommendations

o The NO2 Modeling Guidance Tier 2 methods should include ARM2.

o PVMRM has some deficiencies that need to be corrected and evaluated with field 

data.

o EPA should implement the results of the API/UARG Low Wind Speed project.

o The regulatory version of CALPUFF should be the improved chemistry version.

o The Hanna and Chang BOOT model evaluation methodology should be 

considered in addition to QQ plots.

o Well‐placed monitors should be used for SO2 NAAQS attainment determinations.

o If SO2 SIP modeling is needed, it should use actual emissions, not potential 

emissions.
B-15

o EPA/OAQPS should continue increasing their communications and collaborations 

with the many groups studying modeling issues and include the wider community 

in planning, model development and evaluation, and analysis and review of 

results.

Ryan Gesser – American Forest & Paper Association

• Like many industrial sectors, pulp & paper mills find it difficult to demonstrate 

compliance with applicable NAAQS following current EPA modeling guidance 

• American Forest & Paper Association (AF&PA) analyses suggest AIWG study may 

overstate pulp & paper industry impacts 

• AF&PA appreciates efforts to... 

o improve upon Tier 3 NO2 models 

o identify and correct systematic deficiencies in model performance 

• AF&PA promotes reasonable, practical implementation of new standards and modeling 

guidance 

o Critical application of EPA guidance in practice to provide stability during 

regulatory implementation periods 

o Revisit traditional approaches (ambient air, variable emissions) 

o Streamlined approval of Tier 3 approaches 

Bob Paine – AECOM for Electric Power Research Institute

• Need for a sub‐hourly AERMOD capability?

o Hourly AERMOD predictions for low wind speeds overstate impacts from 

coherent plume and sub‐hourly meteorological data is now routinely available 

from both on‐site met and 1‐minute ASOS

o In low winds, winds can go in several directions during an hour, resulting in 

multiple concentration “lobes”

• Conclusions on development and evaluation of AERMINUTEPlus and Sub‐Hourly 

AERMOD (SHARP*)

o Sub‐hourly AERMOD capability has been developed and limited evaluation has 

been done on two databases

o Stable, light wind database clearly shows need to correct AERMOD over 

predictions for hourly averaged data – consistent with other research

o AERMOD hourly predictions perform much better in unstable conditions, but 

some cases with scattered winds could benefit from sub‐hourly modeling

o Hourly predicted plume footprint “too tight”, especially in stable conditions

o 5‐min sub‐hourly plume footprint “too loose”

o Best sub‐hourly averaging time might be ~10 minutes

o Further testing is recommended

Bob Paine – AECOM for Electric Power Research Institute

• Limitations of steady‐state 1‐hour dispersion models

o Plumes are assumed to travel to infinite distances within 1-hour (“lighthouse 

beam” effect)

o Each hour, the previous hour’s emissions are replaced and forgotten
B-16

o Worst‐case conditions, especially associated with low winds, are persisted to 

impossible distances

o Currently, though, US EPA considers these models to be applicable to a rather 

arbitrary distance of 50 km

o This study tried to more carefully quantify a reasonable distance for applicability 

of these models (such as AERMOD or ISC) 

• Conclusions on concentration comparison: Steady‐state vs. non‐steady‐state models

o ISC/CALPUFF concentration ratios are close to 1 within 5 km and within a factor 

of 2 within 20 km

o Beyond 20 km, there are some directions where this ratio can significantly exceed 

2 – higher differences may be possible for real terrain applications

o 20‐30 km is the extent a single hour’s travel for most of the hours

o Even after 4‐5 hours, more than half of air parcels followed with a 10‐m wind are 

still on the 50‐km modeling domain

o Results suggest that a 20‐km limit seems more appropriate for steady‐state model 

(e.g., AERMOD) applicability rather than the current limit of 50 km

o AERMOD should provide information to users regarding hourly plume travel 

time

o We are working on providing this information in an enhanced version of 

AERMOD to be provided to EPA

Bob Paine – AECOM for Electric Power Research Institute

• This presentation is a report on Model Evaluation of AERMOD at a Monitoring Network 

in North Dakota for a unique data base.

• AERMOD performance improves with the use of actual hourly emissions. For NAAQS 

compliance modeling for existing sources, actual hourly emissions are recommended to 

obtain the most accurate AERMOD results.

• Additionally, the assumption of flat terrain for areas of gentle slope (slope <2%) 

improves AERMOD performance and should be allowed.

• This was clearly demonstrated with the case of low winds and low mechanical mixing 

heights. In that case, the use of actual terrain with a 1% slope resulted in counterintuitive results at some distant location because of plume intersection with the terrain.

Allen Dittenhoefer -- Enviroplan Consulting

• Comments on a procedure for modeling buoyant line sources with AERMOD

• Until EPA develops a buoyant line source algorithm in AERMOD, a two-step hybrid 

modeling scheme has been proposed involving the application of two Guideline 

dispersion models (BLP and AERMOD)

• This procedure can treat enhanced plume rise from multiple buoyant line sources, but is 

more time- and resource-intensive (e.g., requires two meteorological data preprocessors –

RAMMET for BLP and AERMET for AERMOD)
B-17

Qiguo Jing -- Breeze, Trinity Consultants

• Comments on dispersion of buoyant emissions from a low level urban source; No 

specific recommendations

• Findings

o AERMOD provides an adequate description of concentrations associated with a 

buoyant release from the low level source during the daytime.

o AERMOD underestimates concentrations during the night when turbulence is 

generated by wind shear. A simple modification and onsite meteorology can 

improve its performance.

Bob Paine – AECOM

• Conclusions for non‐BLP alternative for buoyant volume sources

o AERMOD needs procedure to accommodate buoyant volume sources

o BLP approach has many source limitations

o Proposed approach avoids these limitations and uses AERMOD meteorological 

profiles to characterize plume rise without change to the model except for 

additional debug printout

• Comments on building downwash in light winds; no specific recommendations

o Unexpected AERMOD results for buoyant stacks with heights close to building 

heights

o Many recent AERMOD runs indicate predictions of design concentrations for 

buoyant point sources due to building downwash in stable, nearly calm 

conditions. 

o This is contrary to expectations, since building wake expected to be weak, and 

plume rise high 

o AERMOD evaluations show that modeling issues likely include buoyant volume 

sources and downwash under low wind speeds; even with annual average 

emissions, AERMOD design SO2 concentrations were several times higher than 

observations at 2 regional monitors

George Schewe -- Trinity Consultants

• Sensitivity of AERMOD to AERMINUTE-generated meteorology; demonstration of the 

differences in maximum concentration estimates between AERMET and AERMINUTEAERMET data sets for various source types.

• No specific recommendations.

Sergio Guerra -- Wenck Associates, Inc.

• Sensitivity analysis concerning effects of met data processing (using AERMINUTE) in 

AERMOD concentrations.

• Concerned with threshold wind speeds.

• Recommendation to EPA that the one knot threshold should be rethought and that a two 

knot threshold would be more appropriate until the low wind speed issues in AERMOD 

are fixed.
B-18

Dana Wood – BP

• AQRVs - CALPUFF

o Industry has provided critical comments over the past 12 years regarding:

 The basic formulation, accuracy and lack of model evaluation of 

MESOPUFF II chemistry in CALPUFF

 Model estimates of secondary SO4 and NO4 have not been evaluated 

against monitoring data.

o API has further developed a new chemistry mechanism that addresses many of the 

past comments

o As a result of industry comments and providing EPA with a revised model, 

nothing has changed regarding how visual range impacts are estimated through 

modeling –

o Regulatory modeling is still based on MESOPUFF II chemistry and impacts are 

not consistent with monitoring data

o In a regulatory setting, using models that contain better science can be a difficult 

process. To mitigate bias toward over estimating actual impacts, models should 

be used in a relative manner

• Recommendations and conclusions

o Modeling issues and challenges are substantial and models need to be improved

o There is a pressing need for independent peer review of EPA development

o EPA needs to publish a research plan to identify pressing modeling issues –

OAQPS and ORD need to develop a plan with stakeholder input and comment

o Better evaluation tools and databases are needed

Nicole Downey -- Earth System Sciences, LLC

• NO2 model performance for Empire Abo

o In spite of the uncertainties in emission data, NOX model performance is 

underestimated by almost a factor of two

o If NO2 is evaluated using NOX pairing, NO2 model performance is over stated by 

more than a factor of two – implies that matching NO2 conversion with NOX

dispersion overstates NO2 formation (compensating errors)

o If NO2 is compared to monitoring data independent of time, NO2 over predicts by 

a factor of two (compensating errors) 

o EPA’s analysis should be publicly available and described (i.e. what emission 

inventory was used, which ozone monitor, etc...)

• Conclusions and recommendations

o Code review of AERMOD PVMRM has formulation problems (Hanna 

presentation)

o Conversion of NO into NO2 overstates NO2 conversion (Empire Abo analysis)

o There is an urgent need for EPA to develop refined NO2 modeling procedures and 

databases for evaluation

o Until refined techniques occur, EPA should adopt ARM2
B-19

Cindy Langworthy – UARG

• Since EPA, States, and industries must rely on models for implementing some provisions 

of the CAA, it is important that the underlying regulatory models and related modeling 

tools and any changes to these regulatory models and modeling tools be fully tested and 

consistently evaluated before EPA accepts their use for regulatory purpose.

• For regulatory purposes, the model should run with actual emissions rather than with 

combinations of inputs that have not actually occurred and are unlikely to occur in the 

real world. 

• Background concentrations should be taken into account when the model is evaluated and 

monitored air- quality values should be the benchmark against which models are 

evaluated. 

• Concentrations measured by an EPA-approved monitor and an EPA-approved site should 

be relied upon and preference given, rather than to concentrations predicted by a model.

• Improvements to EPA’s guideline models should be made expeditiously but only under 

the framework provided by the CAA.

• Significant changes to the modeling guideline and the models it references must allow for 

the public to have a meaningful opportunity to comment. This public comment must 

precede finalization of modification to EPA’s models; documentation on how well the 

modified models will perform must be available for review. This procedure was not used 

for the addition of AERMET to AERMOD, or for how GEP stack height limits are 

modeled within AERMOD. This procedure applied to both the model code and to 

changes to the tools used in conjunction with those models to characterize source 

emissions and meteorology.

• EPA should simplify, expedite and make more transparent the procedures followed when 

those outside EPA suggest changes they believe should be made to EPA developed 

models, e.g., low wind speed conditions. A better program for considering changes on a 

timely basis is needed, e.g. responses to high priority concerns identified by industry; this 

is particularly true for improvements to CALPUFF.

• The annual EPA/State/local modeler’s meeting should be expanded to allow consistent, 

meaningful participation by all stakeholders. To assure real opportunities for public 

comment at these and other meetings, EPA should make sure that key documents on 

modeling policy are released well ahead of time, e.g., PM modeling guidance.

• EPA should become more agile and open in its approaches for improving models and 

modeling tools buy working more closely with industry to insure that the best modeling 

tools and procedures are used in all regulatory proceedings.

Mark Bennett – CH2M Hill for Rio Tinto

• Summary

o Stringency of new limits, forms of the standard and high background 

concentrations make dispersion modeling compliance demonstrations challenging 

for all three of these NAAQS

 Requires improved performance of AERMOD and expedited addressing 

of known deficiencies

o Specific Issues

 Low Wind Speed Algorithm Issues with Respect to Low-Level Sources

• AERMINUTE will result in more low wind speeds
B-20

 Buoyant Line Sources

 Pit Retention

 Impacts of Frequent Updates to AERMOD by EPA

• Conclusion

o As EPA prepares new NAAQS, coordination with stakeholders, including the 

regulated community, is necessary to identify real-world compliance issues

o Rio Tinto appreciates EPA’s increased collaborative efforts with the regulated 

community, and pledges its support of these and future collaborative approaches

o EPA has a responsibility to provide tools that accurately evaluate impacts in order 

to avoid unnecessary barriers to beneficial economically growth

Stephen Mueller -- Tennessee Valley Authority

• Issue: Does temporal resolution of meteorological data influence modeling outcomes for 

1-hour SO2 levels?

• Conclusions

o Time-scale of input meteorology does not always reduce simulated 99th percentile 

1-hour values.

o AERMOD over-estimated max. daily 1-hour SO2 by 80% on average when nonmodeled source influences can be neglected. Is it time for a new modeling 

paradigm, i.e., non steady-state plumes?

o Increase in plume meander due to sub-hourly winds can be offset by an increase 

in hours modeled with very low wind speeds increasing the number of hours 

when the steady-state plume assumption is least valid.

o As the switch from hourly to sub-hourly meteorological data was implemented, 

meander in the wind field was increased, but a lot of hours where the wind is very 

light were introduced. So actually there is a swap of one problem for another now 

that there are more hours under the sub-hourly processing when the steady state 

model assumption is less valid

o EPA should consider offering alternatives to a steady state modeling approach for 

near field plume impact evaluations.

Steve Gossett – Eastman Chemical Company & Bob Paine -- AECOM

Discussion of field study to support attainment demonstration and the importance of 

meteorological data. No specific recommendations.

Ashley Jones – Trinity Consultants

• Case study for an aluminum plant with challenges for the 1-hour SO2 NAAQS

o Focus on raising stack height is no longer a likely solution

o Evaluating what SO2 rate it takes to achieve modeled compliance, while 

considering that add-on SO2 controls for pot lines are not common 

o Modeling uses BLP model for roof vents and AERMOD for all other sources

• Summary

o Determining a modeled solution is still an on-going process as is the case with 

many trying to comply with the SO2 1-hour NAAQS. In this situation finding a 

solution has been made even more difficult with the recent change in the 

WAKFLAG routine.
B-21

o Will any relief come from the pending downwash guidance to achieve modeled 

compliance?

o The facility is initiating a field study to better understand the plant’s monitored 

impacts versus the modeled impacts.

Anand Yegnan – ERM

• Experiences and challenges of 1-hour SO2 compliance demonstration and designations 

modeling

o Significantly greater nonattainment than current situation based on monitoring, 

due to conservative approach (modeling) plus conservative inputs (potential 

emissions) plus conservative background

o 1-hour modeling results tend to point directly at individual facilities, not to 

regional scale emissions (e.g. ozone, PM2.5)

o Modeled non-attainment tends to be limited to small geographic areas “hot spots”

o Potential for “pseudo” nonattainment areas

• Findings

o Some simple solutions

 Low wind speeds: Limit dilution speed to 1.0 m/s

 Background: Seasonal/hour approach is helpful; should use average (per 

Appendix W 8.2.2b):

o Specifically for SO2 1-hour modeling: 

 Always include sensitivity analyses; allow time for consideration of caseby-case model sensitivity

 Always pay close attention to meteorological conditions and model 

“details” associated with high concentrations

 Allow for use of actual emissions: 

• in the form of a distribution (e.g. max monthly for each month)

• Monte Carlo simulations where data are available

o Modify AERMOD to more easily identify met conditions and model details; 

Promote broader understanding of sensitivities and case-specific model attributes

Anand Yegnan – ERM

Experience with CALPUFF 6.4, modeling for 1-hour NO2 and SO2 compliance in Baltimore, and 

using MM5 data for local scale modeling. No specific recommendations.

• Evaluations of CALPUFF 6.4

o CALPUFF has been used as a tool to help understand source and source sector 

contributions to N loading; compare and contrast with CMAQ

o New chemistry included in v. 6.4 holds promise in terms of improving predictions 

of N loading

o Work-in-Progress includes evaluations of CALPUFF predictions compared to 

aerosol and gas concentrations, and wet deposition, measured at CASTNET, 

IMPROVE, and NADP measurement stations

• Experience with modeling for 1-hour NO2 and SO2 compliance in Baltimore;

o OLMGROUP appears to produce better patterns of NO2/NOX ratios than 

PVMRM

o Evaluation suggests use of 0.1 in-stack ratio for all sources
B-22

o Problems with AERMINUTE processing; DNR currently recommending use of 

pre-ASOS meteorological data 

o Baltimore analysis points out shortcomings of AERMOD application at this scale; 

transport times are an issue... possible future application of CALPUFF

o Evaluating improvements in treating “urban core” plume

• Using MM5 data for local scale modeling 

o PPRP has used MM5 data to extract local winds for near field analyses in a 

number of cases;

o Evaluations of extracted winds compared to tall towers (primarily at nuclear 

stations) and profilers are encouraging;

o Initiating evaluations of beta version of MMIF

o Use of MM5 (and WRF) holds promise for improving local scale meteorology, 

particularly in situations where airports are somewhat remote

Eladio Knipping -- Electric Power Research Institute

SCICHEM development update. No specific recommendations.

o A new SCICHEM version is forthcoming in a few months; The model will be 

free, open-source and public-domain

o A prior version SCICHEM has been described in previous presentations at this 

conference; this version has some of but not all the future enhancement

o This presentation provides an update on the status of SCICHEM development

o In the 2000s, EPRI embedded the SCICHEM model into the EPA CMAQ model 

as a plume-in-grid module for sub-grid treatment of industrial plumes

o This PiG version of SCICHEM is known by the name “Advanced Plume 

Treatment” or APT, i.e. CMAQ-APT 

o A version of CMAQ-APT was publicly released via the CMAS Center based on 

CMAQ4.6 and sectional MADRID aerosol Treatment

o As derivative products of SCICHEM may be developed, EPRI will remain the 

“custodian” of the “core” SCICHEM model

o SCIPUFF and SCICHEM are being reconciled and at the end of this

reconciliation, there will be only one standalone model; however, the two names 

will remain in order to emphasize whether chemistry is “on” or “off”

o The SCIPUFF/SCICHEM equivalency may be thought of as: SCIPUFF is 

SCICHEM with chemistry “off” and SCICHEM is SCIPUFF with chemistry “on”

Steven Hanna – Hanna Consultants on research supported by Defense Threat Reduction 

Agency

• Comparison of CALPUFF and SCIPUFF with tracer gas observations at two mesoscale

field experiments – No specific recommendations

o Good performance at DP26; FAC 2 under predictions at OLAD for CALPUFF 

and SCIPUFF

o The two models’ performance is about the same for the two mesoscale tracer 

experiments (DP26 and OLAD)

o No significant difference (at 95 % level) between most performance measures for 

CALPUFF and SCIPUFF

o Similar performance even when both use the CALMET diagnostic wind models 
B-23

o Caveat – both models have changed somewhat since this study was done in 2002

Steven Hanna – Hanna Consultants on research supported by Defense Threat Reduction 

Agency

• Evaluations of prognostic meteorological models with field observations, with focus on 

meteorological variables used in dispersion models – No specific recommendations

o Wind speed (WS) RMS error has a minimum (inherent uncertainty) of about 1

m/s, large biases occasionally happen, especially at night

o Wind direction RMS error is typically 20 to 60°but is clearly proportional to 

1/WS

o Mixing depth has ±20 % error day, ±100 % night 

o dT/dz in capping inversion underestimated by models

o Obs TKE agrees within a factor of two with model simulations during the day. At 

night, TKE agreement is not so good

o These results are in general agreement with the Seaman 2000 review paper

David Long -- American Electric Power Service Corporation

• A proposed method to screen source impacts on potential background monitors using the 

ASOS surface 1-minute dataset – No specific recommendations

o The use of the 6405 Dataset to source the meteorology for doing this type of 

exclusion analysis is viable.

o Transit times up to 12 hours should be considered to maximize the capture of 

source impacts on 1-hour monitored values

o If we are considering upwind sources with a long transit time, the angle between 

average wind direction and source direction should be increased to 30 degrees in 

order to allow for plume meander over a longer transit time

o A Step 4 analysis option should be available in the event there are hours that do 

not conform to the normal behaviors.

o If there are a large number of sources in similar directions, consideration should 

be given to grouping the sources instead of using individual sources.

o While performed for 1-hour SO2, this technique should work equally well for any 

pollutant with a 1hour averaging time and possibly other short term averaging 

times

Tony Colombari – Trinity Consultants

• Top five conventional and unconventional ways to meet the NAAQS – No specific 

recommendations

o 5. Recharacterize ambient air as not

o 4. Reevaluate met and/or monitoring data

o 3. Building changes

o 2. Pursue alternative models/switches

o 1. Stratify impacts
B-24

Justin Walters – Southern Company

o With short-term standards that approach values that are closer to background 

concentrations, the models require a level of accuracy and precision beyond their current 

capability. Models are increasingly being given greater deference than ambient 

measurements. Continuing to apply models with existing but outdated guidance is 

inappropriate (e.g.SO2 NAAQS SIP submissions).

o EPA must assure that the performance of its guideline models is unbiased and does not 

lead to gross over predictions that could force costly and unnecessary actions to be taken. 

Performance evaluation for model modifications and submittal for public notice and 

comment are essential.

o EPA needs to evaluate the performance of AERMOD for the entire AERMOD 

system, including AERMAP, AERSURFACE, AERMET, AERMINUTE, etc. 

Changes to the system should be demonstrated to result in improved model 

performance for a wide range of meteorological conditions, particularly low wind 

speed and stable conditions. Only when the evaluation is complete, should model 

changes be submitted for public notice and comment.

o Model modifications that result in changes to model concentrations must go 

through notice and comment rule-making before being implement as preferred 

models. As a result, the recent change in AERMOD that is noted in MCB#4 that 

alters the PRIME downwash algorithms to apply to stacks that are greater than or

equal to the GEP formula height relegates the model to a non-preferred status

o AERMOD has not been thoroughly evaluated for performance in simulating the 

maximum daily one-hour concentration at the 99th percentile in the case of NO2.

o EPA should give states discretion to use modeling and analysis tools to help 

demonstrate situations where sources have a low probability of violating the 

standard; e.g., states should have discretion to allow sources to demonstrate 

through application of the emissions variability processor (MVEP).

EPA should engage the private sector, e.g. consultants and industry, and provide a clear path 

forward for approving tools and model improvements that come from the modeling community;

this applies to improvements in the performance of both preferred and alternative models. 

Invitation for the private sector to participate in annual regional/state/local modelers meetings 

would be a positive step.
C-1

Attachment C

Presentations, Transcripts, and Docket Links

A list of relevant Internet links for the 10th Conference on Air Quality Modeling 

presentations, transcripts, and Docket are listed below.

Conference Website:

http://www.epa.gov/ttn/scram/10thmodconf.htm

Conference Presentations:

http://www.epa.gov/ttn/scram/10thmodconfpres.htm

Conference Transcripts:

Day 1 – http://www.epa.gov/ttn/scram/10thmodconf/2012_Tenth_Modeling_ConferenceTranscripts_03-13-2012.pdf

Day 2 – http://www.epa.gov/ttn/scram/10thmodconf/2012_Tenth_Modeling_ConferenceTranscripts_03-14-2012.pdf

Day 3 – http://www.epa.gov/ttn/scram/10thmodconf/2012_Tenth_Modeling_ConferenceTranscripts_03-15-2012.pdf

Conference Docket: (includes formal comment submissions)

http://www.regulations.gov/#!docketDetail;dct=FR%252BPR%252BN%252BO%252BSR;r

pp=10;po=0;D=EPA-HQ-OAR-2012-0056
C-2

(This Page Intentional Left Blank)
D-1

Attachment D

Modeling Action Items and Prioritization Summary Table

The summary table outlining the EPA’s near-term action items and long-term goals with 

respect to updates and modifications to the regulatory models (AERMOD and CALPUFF) and 

the Guideline that are necessary to address specific issues indentified with these models, with 

current and future NAAQS compliance demonstrations, and with emerging models and 

techniques will eventually be included in the Summary of Comments document package. This 

summary table has often been referred to as the “Matrix” or some variant in various meetings 

and engagements with the modeling community since the 10th Conference on Air Quality 

Models. The Summary of Comments document package will be appropriately updated, noticed, 

and reposted on SCRAM once the summary table is available and incorporated into the 

document.
D-2

(This Page Intentional Left Blank)