NOAA Technical Memorandum OAR ARL-239 

FISCAL YEAR 2000 SUMMARY REPORT OF THE NOAA ATMOSPHERIC SCIENCES 

MODELING DIVISION TO THE U.S. ENVIRONMENTAL PROTECTION AGENCY 

Evelyn M. Poole-Kober

Herbert J. Viebrock

(Editors)

Atmospheric Sciences Modeling Division

Research Triangle Park, North Carolina

Air Resources Laboratory 

Silver Spring, Maryland 

June 2001 

~<;) ~IMOSPItc: 

~.if8~ UNITEDSTATES NATIONAL OCEANIC AND Oceanic and Atmospheric ATMOSPHERIC ADMINISTRATION Research Laboratories i

8' .. ) DEPARTMENT OF COMMERCE 

'"'G' .. Donald L.Evans .", r!J- Scott B. Gudes David L. Evans 

.<fA ~~-$ Secretary Acting Under Secretary for Oceans Director 'f<9lMENT Of dJ 

and AtmospherelAdministrator 
NOTICE 

Mention of a commercial company or product does not constitute an endorsement by NOAA. 

Use for publicity or advertising purposes of information from this publication concerning 

proprietary products or the tests of such products is not authorized. 

For sale by the National Technical Information Service, 5285 Port Royal Road, Springfield, VA 22161. 

ii 
PREFACE
 


This document summarizes the Fiscal Year 2000 research and operational activities of the 

Atmospheric Sciences Modeling Division (ASMD), Air Resources Laboratory, working under 

Interagency Agreements EPA DW13938483 and DW13948634 between the U.S. Environmental 

Protection Agency (EPA) and the National Oceanic and Atmospheric Administration (NOAA). 

The summary includes descriptions of research and operational efforts in air pollution 

meteorology, air pollution control activities, and abatement and compliance programs. 

Established in 1955, the Division serves as the vehicle for implementing the agreements 

with EPA, which funds the research efforts in air pollution meteorology. ASMD conducts 

research activities in-house and through contract and cooperative agreements for the National 

Exposure Research Laboratory and other EPA groups. With a staff consisting of NOAA, EPA, 

and Public Health Service Commissioned Corps personnel, ASMD also provides technical 

information, observational and forecasting support, and consulting on all meteorological aspects 

of the air pollution control program to many EPA offices, including the Office of Air Quality 

Planning and Standards. The primary groups within ASMD are the Atmospheric Model 

Development Branch, Modeling Systems Analysis Branch, Applied Modeling Research Branch, 

and Air Policy Support Branch. The staff is listed in Appendix G. Acronyms, publications, and 

other professional activities are listed in the remaining appendices. 

Any inquiry on the research or support activities outlined in this report should be sent to 

the Director, Atmospheric Sciences Modeling Division (MD-80), Environmental Protection 

Agency, Research Triangle Park, NC 27711. 

iii 
iv
 
CONTENTS
 


Page 

PREFACE .................................................................. iii
 


FIGURES ................................................................... ix
 


ABSTRACT .................................................................. 1
 


1. INTRODUCTION ........................................................... 1
 


2. PROGRAM REVIEW ....................................................... 2
 


2.1 Office of the Director ................................................. 2
 


2.1.1 NATO Committee on the Challenges of Modern Society .............. 2
 


2.1.1.1 	International Technical Meetings ......................... 2
 


2.1.1.2 Regional/Transboundary Transport of Air Pollution .......... 3
 


2.1.2 United States/Japan Environmental Agreement ..................... 3
 


2.1.3 United States/Russia Joint Environmental Committee ................ 3
 


2.1.4 Meteorological Coordinating Committees .......................... 4
 


2.1.4.1 Federal Meteorological Committee ....................... 4
 


2.1.4.2 Interdepartmental Meteorological Committee ............... 4
 


2.1.5 Board on Atmospheric Sciences and Climate ....................... 4
 


2.1.6 Standing Air Simulation Work Group ............................. 5
 


2.1.7 Trans-Pacific Transport of Atmospheric Contaminants ................ 5
 


2.1.8 NOAA Air Quality and Environmental Forecasting Modeling .......... 5
 


2.1.9 European Monitoring and Evaluation Program ...................... 6
 


2.1.10 Chesapeake Bay Program Air Subcommittee and Chesapeake Bay 
 


Program Modeling Subcommittee ............................... 6
 


2.1.11 Megacity Impact on Regional and Global Environments ............. 7
 


2.1.12 North American Research Strategy for Tropospheric Ozone .......... 7
 


2.1.13 	International Task Force on Forecasting Environmental Change ....... 8
 


2.1.14 Regional Acid Deposition Model Application Studies ............... 8
 


2.1.15 International Association of Aquatic and Marine Science Librarians and 	 
 


Information Centers .......................................... 9
 


2.1.16 Southeast Affiliate of IAMSLIC Librarians ........................ 9
 


2.1.17 Atmospheric Science Librarians International ..................... 10
 


2.1.18 	Atmospheric Sciences Modeling Division Library Home Page ....... 10
 


2.2 Atmospheric Model Development Branch ................................ 10
 


2.2.1 Models-3/Community Multiscale Air Quality Modeling ............. 11
 


2.2.1.1 Introduction ......................................... 11
 


v 
2.2.1.2 Research and Development Scope of the Community Multiscale 	
 


Air Quality Modeling System ........................... 11
 


2.2.1.3 	Transport Processes within the Community Multiscale Air Quality 
 


Modeling System .................................... 12
 


2.2.1.4 Photolysis Rates ..................................... 14
 


2.2.1.5 Cloud Dynamics and Aqueous-Phase Chemistry Module ..... 14
 


2.2.1.6 	Subgrid Scale Plume-in-Grid Modeling in the CMAQ Modeling 
 


System ............................................. 15
 


2.2.1.7 Air Quality Modeling of Particulate Matter and Air Toxics at 	 
 


Neighborhood Scales ................................. 16
 


2.2.1.8 Aggregation Research for Models-3/CMAQ ............... 17
 


2.2.1.9 Collaborative Model Evaluation Studies for Particulate 
 


Matter ............................................. 17
 


2.2.1.10 A Preliminary Evaluation of Models-3/CMAQ Using Visibility 
 


Parameters .......................................... 18
 


2.2.2 Aerosol Research and Modeling ................................ 19
 


2.2.3 Atmospheric Toxics Pollutant Research .......................... 20
 


2.2.3.1 Atmospheric Toxics Pollutant Modeling .................. 20
 


2.2.3.2 Atmospheric Mercury Field Research .................... 22
 


2.2.4 Meteorological Modeling Studies ............................... 23
 


2.2.4.1 Meteorology Modeling for Models-3/CMAQ Applications .... 24
 


2.2.4.2 Advanced Land-Surface and Planetary Boundary Layer 	 

 Modeling in MM5 .................................... 25
 


2.2.5 Dry Deposition Studies ....................................... 26
 


2.2.5.1 Dry Deposition Research .............................. 26
 


2.2.6 Technical Support ........................................... 29
 


2.2.6.1 North American Research Strategy for Tropospheric Ozone ... 29
 


2.2.6.2 Western Regional Air Partnership Air Quality Technical 	 
 


Forums ............................................ 29
 


2.2.6.3 Multimedia Integrated Modeling System Meteorological 	 
 


Team .............................................. 30
 


2.2.6.4 Climatological and Regional Analyses of CASTNet Data ..... 30
 


2.2.6.5 	NEXRAD Stage IV Data in the Multimedia Modeling 
 


of Pollutant Transport ................................. 31
 


2.3 Modeling Systems Analysis Branch ..................................... 31
 


2.3.1 Emission Modeling .......................................... 32
 


2.3.2 Biogenic Emissions .......................................... 33
 


2.3.3 Improvements in Vegetation Cover Data .......................... 34
 


2.3.4 Technology Transfer ......................................... 34
 


2.3.4.1 Visualization and Analysis Tools ........................ 35
 


2.3.4.2 Models-3 Workshop .................................. 35
 


2.3.4.3 Models-3 Support .................................... 35
 


2.3.4.4 Computing Platforms for the Models-3 Framework .......... 36
 


vi 
2.3.5 Cross-Platform Implementation of CMAQ Chemistry-Transport Model . 36
 


2.3.6 Multimedia Integrated Modeling ................................ 37
 


2.4 Applied Modeling Research Branch ..................................... 39
 


2.4.1 Remote Sensing ............................................. 39
 


2.4.2 Relating field-Scale Wind Blown Fugitive Dust Measurement to Large


 Scale Vertical Dust Flux ...................................... 40
 


2.4.3 Fugitive Emissions from Supply-Limited Sources .................. 41
 


2.4.4 Resuspension of PM10 Particles from Grass ....................... 43
 


2.4.5 Wind Tunnel Measurements of Mean Flow and Turbulence in an


 Array of Two-Dimensional Buildings ............................ 43
 


2.4.6 Meteorological Measurements .................................. 45
 


2.5 Air Policy Support Branch ............................................ 50
 


2.5.1 Modeling Studies ............................................ 51
 


2.5.1.1 Air Quality Assessment of Heavy-Duty Engine/Vehicle and 	
 


Highway Diesel Fuel Rulemaking ........................ 51
 


2.5.1.2 CMAQ Proof of Concept: Western United States Ozone 
 


Modeling ........................................... 52
 


2.5.1.3 Statistical Evaluation of Model Performance ............... 53
 


2.5.1.4 The Krakow Urban Air Pollution Project .................. 53
 


2.5.1.5 Improvements to the Regulatory Modeling System for Aerosols 	
 


and Deposition ....................................... 54
 


2.5.2 Modeling Guidance .......................................... 54
 


2.5.2.1 Support Center for Regulatory Air Models ................. 54
 


2.5.2.2 Models-3 Help Desk .................................. 55
 


2.5.2.3 Ad Hoc Meteorological Modeling Workgroup .............. 55
 


3. REFERENCES ............................................................ 56
 


vii 
APPENDIX A: ACRONYMS, ABBREVIATIONS, AND DEFINITIONS ................ 63
 


APPENDIX B: PUBLICATIONS ................................................ 66
 


APPENDIX C: PRESENTATIONS .............................................. 73
 


APPENDIX D: WORKSHOPS AND MEETINGS .................................. 81
 


APPENDIX E: VISITING SCIENTISTS .......................................... 90
 


APPENDIX F: HIGH SCHOOL, UNDERGRADUATE, AND GRADUATE STUDENTS, AND
 


POSTDOCTORAL RESEARCHERS ....................................... 93
 


APPENDIX G: ATMOSPHERIC SCIENCES MODELING DIVISION STAFF AND 
 


AWARDS ............................................................ 95
 


viii 
Page 

FIGURES 

1.	 	 Average diurnal cycle of O3 deposition velocity observed over Kane Forest,
 


Pennsylvania. 28
 


2.	 	 Modeled and measured radiance spectrum of the flood plain in the Neuse River
 


Basin, and component contributions from atmospheric backscatter and ground
 


reflectance. 40
 


3.	 	 Wind vector and turbulent kinetic energy fields measured along the centerline of an
 


array of buildings. The first three of seven buildings are shown here. 44
 


4.	 	 The Meteorological Instrumentation Cluster of 3 Trailers used to support field studies
 


of human exposure to air pollutants. 46
 


5.	 	 (a) Digital facsimile profile from the Model 2000 SODAR and temperature gradient
 


between 2 and 10 meters (September 8, 2000). Sunrise (SR) are indicated. (B) Tower
 


measured wind speed at 2,5, and 10 meters. (C) Temperature at 2 meters and wind
 


direction measured at 10 meters. 48
 


6.	 	 Diurnal wind speed profile from the Model 4000 miniSODAR on September 8, 2000. 
 


Wind speed is smoothed with a 1-hour moving window. Legend to the right is in meters
 


per second and height on the left is in meters. 48
 


7.	 	 Example of CFD simulation of the wind over Manhattan. 	 49
 


8.	 	 Example of CFD simulation of airflow between two moving vehicles and consequences
 


of leading vehicle tailpipe emission. 50
 


ix 
FISCAL YEAR 2000 SUMMARY REPORT OF THE NOAA
 


ATMOSPHERIC SCIENCES MODELING DIVISION TO THE


 U.S. ENVIRONMENTAL PROTECTION AGENCY
 


ABSTRACT. During Fiscal Year 2000, the Atmospheric Sciences Modeling 

Division provided meteorological and modeling assistance to the U.S. 

Environmental Protection Agency. This ranged from the conduct of research 

studies and model applications to the provision of advice and guidance. Research 

efforts emphasized the development and evaluation of air quality models using 

numerical and physical techniques supported by field studies. Among the 

significant research studies and results were the distribution of Models-3/CMAQ 

version 3, continued evaluation and modification of CMAQ, modification of 

CMAQ for toxic air pollutants, implementation of a new emission processing 

system, initiation of the modeling of particulate matter and air toxics at 

neighborhood scales, continuation of the work on the Multimedia Integrated 

Modeling System, analysis of dry deposition field data and development of the 

next generation deposition velocity model, SODAR and tower meteorological 

measurements for use in human exposure modeling, and continued study of the 

wind erosion of sand. 

1. INTRODUCTION 

In Fiscal Year 2000, the Atmospheric Sciences Modeling Division (ASMD) continued its 

commitment for providing goal-oriented, high-quality research and development, and operational 

support to the U.S. Environmental Protection Agency (EPA). Using an interdisciplinary 

approach emphasizing integration and close cooperation with EPA and public and private 

research communities, the Division's primary efforts were studying processes affecting dispersion 

of atmospheric pollutants, modeling pollutant dispersion on all temporal and spatial scales, and 

developing multi-media model frameworks in a high computing and communications 

environment. The technology and research products developed by the Division are transferred to 

the public and private national and international user communities. Section 2.1 discusses 

Division participation in international activities, while Sections 2.2 through 2.4 outline the 

Division research activities in support of the short- and long-term needs of the EPA and 

environmental community. Section 2.5 discusses Division support to the operational programs 

and general air quality model user community. 
2. PROGRAM REVIEW 

2.1 Office of the Director 

The Office of the Director provides direction, supervision, program management, and 

administrative support in performing the Division's mission and in achieving its goals of 

advancing the state of the atmospheric sciences and enhancing the protection of the environment. 

The Director's Office also engages in several domestic and international research exchange 

activities. 

2.1.1 NATO Committee on the Challenges of Modern Society 

The North Atlantic Treaty Organization (NATO) Committee on the Challenges of 

Modern Society (CCMS) was established in 1969 with the mandate to examine how to improve, 

in every practical way, the exchange of views and experience among the Allied countries in the 

task of creating a better environment for their societies. The Committee considers specific 

problems of the human environment with the deliberate objective of stimulating corrective action 

by member governments. The Committee's work is carried out on a decentralized basis through 

pilot studies, discussions on environmental issues, and fellowships. 

2.1.1.1 International Technical Meetings 

The Division Director serves as the United States representative on the Scientific 

Committee for International Technical Meetings (ITMs) on Air Pollution Modeling and Its 

Application, sponsored by NATO/CCMS. A primary activity within the NATO/CCMS Pilot 

Study on Air Pollution Control Strategies and Impact Modeling is organizing a symposium every 

eighteen months that deals with various aspects of air pollution dispersion modeling. The 

meetings are rotated among different NATO and Eastern Bloc countries, with every third ITM 

held in North America and the two intervening ITMs held in European countries. 

The Division Director served as the Conference Chairman of the Millennium (24th) 

NATO/CCMS International Technical Meeting held in Boulder, Colorado, May 15–19, 2000. 

The proceedings will be published by Plenum Press as were the proceedings from the 23rd ITM 

held in Varna, Bulgaria, during September–October 1998 (Air Pollution Modeling and Its 

Application XIII, 2000). A preliminary summary of the Millennium ITM is included in the 

Newsletter of the European Association for the Science of Air Pollution (Schiermeier, 2000). 

The NATO/CCMS Scientific Committee selected Louvain-La-Neuve, Belgium, as the site for the 

25th International Technical Meeting to be held during October 15–19, 2001. 

2
 

2.1.1.2 Regional/Transboundary Transport of Air Pollution 

The Division Director serves as the United States representative on the International 

Oversight Committee for the NATO/CCMS Pilot Study on Regional/Transboundary Transport of 

Air Pollution. The aim of the pilot study, sponsored by Greece and approved by NATO in March 

1998, is to improve the exchange of views and experience among participating countries in the 

field of regional/transboundary transport of air pollution. The initial organizing meeting was 

held in Varna, Bulgaria, during September 1998 in conjunction with the NATO/CCMS 

International Technical Meeting. The framework for the pilot study was revised to reflect inputs 

of the meeting participants. 

2.1.2 United States/Japan Environmental Agreement 

The Division Director serves as the United States Co-Chairman of the Air Pollution 

Meteorology Panel under the United States/Japan Agreement on Cooperation in the Field of 

Environment. The purpose of this 1975 agreement is to facilitate, through mutual visits and 

reciprocal assignments of personnel, the exchange of scientific and regulatory research results 

pertaining to control of air pollution. Interactions are maintained through correspondence and 

exchange of research findings. 

2.1.3 United States/Russia Joint Environmental Committee 

The Division Director serves as the United States Co-Chairman of the United States/ 

Russia Working Group 02.01-10 on Air Pollution Modeling, Instrumentation, and Measurement 

Methodology, and as Co-Leader of the United States/Russia Project 02.01-11 on Air Pollution 

Modeling and Standard Setting. The purpose of the 1972 Nixon-Podgorny Agreement forming 

the US/USSR Joint Committee on Cooperation in the Field of Environmental Protection was to 

promote, through mutual visits and reciprocal assignments of personnel, the sharing of scientific 

and regulatory research results related to the control of air pollution. Activities under this 

agreement were extended to also comply with the 1993 Gore-Chernomyrdin Agreement forming 

the United States/Russia Commission on Economic and Technological Cooperation. There are 

four Projects under Working Group 02.01-10: 

Project 02.01-11: Air Pollution Modeling and Standard Setting 

Project 02.01-12: Instrumentation and Measurement Methodology 

Project 02.01-13: Remote Sensing of Atmospheric Parameters 

Project 02.01-14: Statistical Analysis Methodology and Air Quality

 Trend Assessment 

Progress under this Working Group continued during FY-2000. An abbreviated Working 

Group meeting was held during May 2000 in conjunction with the NATO/CCMS International 

3
 

Technical Meeting in Boulder, Colorado. Plans were made for a full Working Group meeting to 

be held during November 2000 at the Main Geophysical Observatory in St. Petersburg, Russia. 

2.1.4 Meteorological Coordinating Committees 

2.1.4.1 Federal Meteorological Committee 

The Division Director serves as the Agency representative on the Federal Committee for 

Meteorological Services and Supporting Research (FCMSSR). The Committee is composed of 

representatives from 14 Federal government agencies and is chaired by the Under Secretary of 

Commerce for Oceans and Atmosphere, who is also the NOAA Administrator. FCMSSR was 

established in 1964 with high-level agency representation to provide policy guidance to the 

Federal Coordinator for Meteorology, and to resolve agency differences that arise during 

coordination of meteorological activities and the preparation of Federal plans in general. 

2.1.4.2 Interdepartmental Meteorological Committee 

The Division Director serves as the Agency representative on the Interdepartmental 

Committee for Meteorological Services and Supporting Research (ICMSSR). The Committee, 

composed of representatives from 14 Federal government agencies, was formed in 1964 under 

Public Law 87-843 and OMB Circular A-62 to provide the Executive Branch and the Congress 

with a coordinated, multi-agency plan for government meteorological services and for those 

research and development programs that directly support and improve these services. The 

Committee prepared the annual Federal Plan for Meteorological Services and Supporting 

Research (U.S. Department of Commerce, 2000). 

The Division Director also serves on the ICMSSR Committee for Cooperative Research 

and on the ICMSSR Joint Action Group for High Performance Computing and Communications. 

Other Division members serve on the ICMSSR Working Group for Atmospheric Transport and 

Diffusion and on the ICMSSR Working Group for Climate Services. 

2.1.5 Board on Atmospheric Sciences and Climate 

The Division Director serves as the Agency liaison to the Board on Atmospheric Sciences 

and Climate (BASC) of the National Research Council, National Academy of Sciences. BASC 

seeks to advance the understanding of the atmosphere and climate, and to improve the ability to 

apply this knowledge. The Board (1) reviews in broad perspectives both basic and applied 

research dealing with the atmosphere and with the geophysical systems influencing weather and 

climate; (2) provides advice and guidance to appropriate government agencies on problems and 

programs within the Board’s interest and expertise; and (3) counsels the United States 

4
 
participation in such international research and application programs relating to the atmosphere 

and climate as the World Climate Program and its research activities. 

2.1.6 Standing Air Simulation Work Group 

The Division Director serves as the EPA Office of Research and Development 

representative to the Standing Air Simulation Work Group (SASWG), which serves as a forum 

for issues relating to air quality simulation modeling of criteria and other air pollutants from 

point, area, and mobile sources. Its scope encompasses policies, procedures, programs, model 

development, and model application. The work group fosters a consensus between the Agency 

and the State and local air pollution control programs through semi-annual meetings of members 

representing all levels of enforcement. 

2.1.7 Trans-Pacific Transport of Atmospheric Contaminants 

The Division Director participated in the First International Conference on Trans-Pacific 

Transport of Atmospheric Contaminants held in Seattle, Washington, during July 27–29, 2000. 

The purposes of the conference were to (1) map the state of scientific knowledge on long-range 

transport of air pollutants into and across the Pacific Ocean from emission sources around the 

Pacific Rim and beyond; and (2) make recommendations on the next scientific steps needed to 

clarify uncertainties related to the state of knowledge about trans-Pacific air pollution. This 

includes identifying data gaps, requirements for integrating present programs, and possibilities 

for creation of new international cooperative research programs. The Conference Consensus 

Statement released by the EPA in the form of a press release is available at 

http://www.epa.gov/oia/iepi/transpac/htm. A related article by the conference organizers is in 

Science (Wilkening et al., 2000). 

2.1.8 NOAA Air Quality and Environmental Forecasting Modeling 

Division scientists were involved in a series of workshops to develop an initiative for 

NOAA to improve air quality forecasting and prediction. Air quality forecasting is potentially 

important for the management of urban and coastal areas, transportation, hazard response, and 

the conservation of water and air resources. NOAA plans to build its program upon the existing 

research capabilities and upon forming partnerships with the constituents. ASMD brings to the 

table its achievements in developing the Models-3 Community Multiscale Air Quality (CMAQ) 

modeling system. Of particular relevance to the air quality forecasting initiative are the 

Division’s research areas of adapting meteorology forecast models to air quality applications, the 

generation of model-ready source emissions fluxes modulated by meteorological forces, and the 

integration of gas-phase, aqueous, and aerosol chemistry in a comprehensive chemical-transport 

modeling system. 

5
 
2.1.9 European Monitoring and Evaluation Program 

A Division scientist serves as the United States representative to the European 

Monitoring and Evaluation Program (EMEP) that oversees the cooperative program for 

monitoring and evaluation of the long-range transmission of air pollutants in Europe. The 

primary goal of EMEP is to use regional air quality models to produce assessments evaluating 

the influence of one country's emissions on another country's air concentrations or deposition. 

The emphasis has shifted from acidic deposition to ozone and there are emerging interests in fine 

particulates and toxic chemicals. The United States and Canadian representatives report on 

North American activities related to long-range transport. The Division scientist also evaluates 

European studies of special relevance to the program, providing technical critiques of the EMEP 

work during formal and informal interactions, and develops and coordinates such programs with 

EMEP as the modeling studies of the Modeling Synthesizing Center West at the Norwegian 

Meteorological Institute in Oslo, Norway. 

2.1.10 Chesapeake Bay Program Air Subcommittee and Chesapeake Bay 

 Program Modeling Subcommittee 

A Division scientist is a member of the Air Subcommittee, a working subcommittee of 

the Chesapeake Bay Program. Previously this Subcommittee was an advisory group to the 

Implementation Committee. The subcommittee has responsibility for advice and leadership on 

issues of atmospheric deposition to the watershed and the Bay, on overseeing application of the 

Extended Regional Acid Deposition Model (Extended RADM) to link atmospheric deposition 

with watershed models, and in dealing with the potential role of atmospheric deposition on Bay 

restoration efforts. The Air Subcommittee also works with other Chesapeake Bay committees to 

define the top priority air quality scenarios to be simulated by the Extended RADM. The 

Division scientist is also an ex officio member of the Modeling Subcommittee of the 

Implementation Committee. This Subcommittee has responsibility for overseeing the application 

of water quality models and coordinating the linkage of Extended RADM with those models and 

the interpretation of the findings. 

Work in FY-2000 focused on completion of the development of the Extended RADM 

that incorporates the full dynamics of secondary inorganic fine particle formation to study 

ammonia deposition. Using the newly developed Extended RADM, National Acid Precipitation 

Assessment Program (NAPAP) ammonia emissions were adjusted through a primitive model 

inversion. Subsequently, the operational approach to map the reduced nitrogen range of 

influence was tested and finalized, and the range of influence for 30 subregions was generated 

with the Extended RADM. Based on this work the reduced nitrogen airshed for the Chesapeake 

Bay watershed was defined. It was larger than expected. Future work was also defined that 

would support the Year 2000 Chesapeake Bay Agreement. 

6
 

2.1.11 Megacity Impact on Regional and Global Environments 

A Division scientist was asked to serve as a member of the External Advisory Panel on 

the Megacity Impact on Regional And Global Environments (MIRAGE) project at the National 

Center for Atmospheric Research (NCAR) in Boulder, Colorado. The MIRAGE project is an 

official NCAR program jointly directed by the NCAR Research Aviation Facility and the 

Atmospheric Chemistry Division. The advisory panel is composed of 11 scientists from 

academia and Federal agencies, who are presently involved in urban environmental research. 

The panel is expected to review the overall program inception, review progress of various 

studies, and participate in the planning of field experiments. The objective of the project is to 

study how megacities affect the environment on local, regional, and global scales. The study will 

be carried out through field study data collection to better understand the physical processes and 

use of models to help diagnose how human activities in megacities produce their impacts. The 

initial focus will be on two megacities: Mexico City, Mexico, and Beijing, People’s Republic of 

China. In FY-1999, a proposal to the National Science Foundation (NSF) was developed for a 

first phase umbrella project relating to Mexico City under which universities could send 

collaborative proposals. Measurement campaigns in Mexico City are envisioned for the wet and 

dry season. In FY-2000, NSF continued to be interested in the project and suggested a delay in 

the inception of a field study. A new proposal may be drafted, and dates for the field study are 

uncertain. 

2.1.12 North American Research Strategy for Tropospheric Ozone 

The North American Research Strategy for Tropospheric Ozone (NARSTO) program was 

established in FY-1995 to address ozone research and coordinate collaborative research among 

all North American organizations performing and sponsoring tropospheric ozone studies. 

Sponsors include the private sector and State, Provincial and Federal governments of the United 

States, Canada, and Mexico. In March 2000, the NARSTO Associate Management Coordinator 

position was implemented and a Division scientist assigned. The primary duties associated with 

this position include support and continued improvement of the NARSTO Quality Systems 

Science Center (QSSC) and overall program support to the NARSTO Management 

Coordinator’s Office. The NARSTO QSSC was identified as the location of EPA’s national 

archive for the extensive particulate matter (PM) research data resulting from the Supersites 

Program. 

The coordination of NARSTO Federal research activities is facilitated by the 

Subcommittee on Air Quality Research of the Committee on Environment and Natural Resources 

within the National Science and Technology Council. Four science teams were established: 

Analysis and Assessment; Observations; Modeling and Chemistry; and Emissions. A Division 

scientist serves as the Co-Chair of the Modeling and Chemistry Team. One major goal of 

NARSTO is to produce an assessment of the state of tropospheric ozone science. A draft report 

was written and reviewed by the National Academy of Sciences (NAS). The NARSTO Ozone 

Assessment was published in FY-2000 (NARSTO Synthesis Team, 2000). Approximately three 

7
 

thousand copies of the report were printed for distribution. The Division scientist was chosen to 

co-author one of the 24 critical review papers that were commissioned to provide technical 

background to the NARSTO assessment group. During FY-2000, the critical review paper on 

modeling and evaluation of advanced models was published (Russell and Dennis, 2000). A total 

of 17 of the 24 critical review papers were published (Atmospheric Environment, 2000). 

In FY-1998, the NARSTO Executive Assembly decided to include fine-particle research 

activities under its purview. During FY-2000, a draft PM Science Research Plan was written by 

the science team chairs. The draft plan is under review by NAS and priorities for PM research 

are being developed. The next NARSTO state-of-science assessment will focus on particulate 

matter pollution and how science can be used to develop and implement effective control 

policies. A NARSTO PM assessment team was charged with completing the final draft 

assessment report by January 2002 and NAS will review the report by July 2002. The final 

NARSTO PM Assessment is scheduled for publication in early 2003. The NARSTO Associate 

Management Coordinator is an active member of the PM assessment team. 

2.1.13 International Task Force on Forecasting Environmental Change 

A Division scientist is a member of the International Task Force on Forecasting 

Environmental Change that addresses the methodological and philosophical problems of 

forecasting under the expectation of significant structural changes in the behavior of physical, 

chemical or biological systems. Three planned workshops were held at the International Institute 

for Applied Systems Analysis in Laxenburg, Austria. Internal reviews were completed, and a 

draft monograph of the workshop discussions was finished in FY-1999. A publisher for the 

monograph was found in FY-2000. 

2.1.14 Regional Acid Deposition Model Application Studies 

During FY-2000 an operational version of the Extended RADM that operates on the 

Cray® T3DTM1

 massively parallel computer was completed for application studies. The Extended 

RADM incorporates the full dynamics of secondary inorganic fine particle formation to be able 

to simulate ammonia (reduced nitrogen) deposition in addition to oxidized nitrogen deposition. 

The full coupling is required to account for ammonia deposition and partitioning of total 

ammonia into gaseous ammonia and particulate ammonium. Ammonia deposition is a major 

new focus of assessment for deposition to the Chesapeake Bay watershed and Bay surface 

waters, and to the Neuse River Estuary and Pamlico Sound of North Carolina. The new model 

will allow the extension of the estimation of airsheds to ammonia. As part of the preparation of 

the model for applications, the primitive model inversion done with RADM/RPM (Regional 

Particulate Model) to adjust the NAPAP ammonia emissions to more realistic values was redone 

1

Cray is a registered trademark and Cray T3D is a trademark of Cray Research. 

8 
with the Extended RADM, taking advantage of the full dynamics in the model. The Extended 

RADM represents a step in the transition to Models-3/CMAQ for application simulations. 

In FY-1999, oxidized nitrogen range of influence mapping was completed for more than 

100 emission source subregions to support the development of airshed estimates for coastal 

estuaries. RADM runs for these mappings were completed during FY-1998 and FY-1999, 

requiring more than 6,000 Cray®-C90TM2 computer hours. Using the procedure developed for the 

Chesapeake Bay and outlined in Dennis (1997), airsheds for 19 coastal watersheds along the East 

and Gulf Coasts were developed. In FY-2000, several airsheds were adjusted and a 20th coastal 

estuary was added. These oxidized nitrogen airsheds are expected to be available on the 

Division’s multi-media web site in FY-2001. This work is coordinated with the NOAA 

assessment of atmospheric deposition to coastal estuaries that will be published during the next 

fiscal year. 

In FY-2000, reduced nitrogen range of influence mapping was completed for 45 emission 

source subregions to support the development of airshed estimates for ammonia. Reduced 

nitrogen airsheds for Chesapeake Bay and Neuse/Pamlico Sound watersheds were developed. 

These reduced nitrogen airsheds will be available on the Division’s multi-media web site in 

FY-2001. 

2.1.15 International Association of Aquatic and Marine Science Librarians and 

Information Centers 

The Division Librarian participated in the 25th International Association of Aquatic and 

Marine Science Libraries and Information Centers (IAMSLIC) Annual Conference, October 

16–22, 1999, in Woods Hole, Massachusetts. At the conference, the Librarian presented an 

informational poster on the membership representation of the Atmospheric Science Librarians 

International (ASLI) organization. The Librarian worked with the IAMSLIC Vice Chair and 

Program Planner in selecting topics for the 2001 IAMSLIC Conference to be held in Victoria, 

British Columbia, Canada, September 28–October 6, 2000, and reviewed and rated abstracts 

submitted for presentation at the Conference. 

2.1.16 Southeast Affiliate of IAMSLIC Librarians 

The Division Librarian hosted the SAIL 2000 Conference during April 2000 in Research 

Triangle Park, North Carolina. The theme of the SAIL (Southeast Affiliate of IAMSLIC) 

Conference was Harness the Power of Information. Five of the invited speakers were faculty 

members from the University of North Carolina at Chapel Hill School of Law and the School of 

Information and Library Science, Chapel Hill, North Carolina. They addressed relevant topics, 

2

Cray is a registered trademark and Cray C90 is a trademark of Cray Research. 

9 
including the digital millennium copyright act, competencies for special librarians, crossdiscipline collaboration, marketing library services, and ethics at the virtual reference desk. Two 

invited scientists gave presentations on the short-term impacts of hurricanes on water quality and 

fisheries habitat in the Pamlico Sound, and on atmospheric deposition of nutrients to coastal 

waters of the East and Gulf Coasts. Other presentations were made by SAIL members and 

publishers and vendors. The 20 regional attendees included NOAA Librarians from the Miami 

Regional Library, Atlantic Oceanographic and Meteorological Laboratory, the NOS Center for 

Coastal Fisheries and Habitat Research, and NMFS Panama City Marine Fisheries Laboratory. 

Additional attendees included librarians and scientists from the academic community, a nonprofit laboratory, EPA, and Division staff. 

2.1.17 Atmospheric Science Librarians International 

The Division Librarian participated in the Third Annual Conference of the Atmospheric 

Science Librarians International (ASLI), which was held in conjunction with the 80th Annual 

Meeting of the American Meteorological Society, January 9–14, 2000, in Long Beach, 

California. The Librarian was elected Chair of ASLI for 2000. As Chair, the Librarian will plan 

the program for the Fourth Annual Conference, which will be held January 17–19, 2001, in 

Albuquerque, New Mexico. 

2.1.18 Atmospheric Sciences Modeling Division Library Home Page 

The ASMD Library maintains a world-wide web (WWW) home page 

(http://www.epa.gov/asmdnerl/library/library.htm), which provides a brief overview of the 

Library's history and location. The purpose of the home page is to make accessible information 

about the Library's collection, policies, and services to the Division staff and other users in 

Research Triangle Park, North Carolina, and other locations. The home page provides WWW 

interface connections to the EPA and NOAA on-line catalogs in which the Library's book and 

journal collections are cataloged. In addition, the page provides links to other information 

resources through the agencies' home pages and to other WWW resources that reflect the 

Library's collection and staff needs. Division library staff provided HTML (HyperText Markup 

Language) documents of the FY-1999 annual report and publication citations for inclusion on the 

Division’s home page (http://www.epa.gov/asmdnerl/) and publication citations for the NOAA 

Air Resources Laboratory home page (http://www.arl.noaa.gov/ ). 

2.2 Atmospheric Model Development Branch 

The Atmospheric Model Development Branch develops, evaluates, and validates 

analytical and numerical models that describe the transport, dispersion, transformation, and 

removal/resuspension of atmospheric pollutants on local, urban, and regional scales. These are 

10
 

comprehensive air quality modeling systems that incorporate state-of-science formulations 

describing physical and chemical processes. 

2.2.1 Models-3/Community Multiscale Air Quality Modeling 

2.2.1.1 Introduction 

EPA released the Models-3/Community Multiscale Air Quality (CMAQ) modeling 

system, initially in June 1998, and two subsequent revisions in FY-1999 and FY-2000. Models3/CMAQ is a numerical modeling system that can simultaneously simulate the transport, 

physical transformation, and chemical reactions of multiple pollutants across large geographic 

regions. The system is useful to states and other government agencies for making regulatory 

decisions on air quality management, as well as to research scientists for performing atmospheric 

research. It is a combination of Models-3, a flexible software framework, and the CMAQ 

modeling system for supporting air quality applications ranging from regulatory issues to 

scientific research on atmospheric processes. A modular science design of CMAQ allows the 

user to build different chemistry-transport models for various air quality problems. The CMAQ 

models can be operated independently of the Models-3 system framework, providing more 

flexibility for advanced research and applications. The CMAQ models were tested for several air 

quality studies, including photochemical ozone and particular matter episodes in the 1995 

northeastern United States (NARSTO-NorthEast field study) and southeastern United States 

(Nashville, Tennessee, Southern Oxidants Study (SOS)) for the period July 2–18, 1995. The test 

results are very promising when compared with observed surface ozone concentrations and 

aircraft measurements. A rigorous evaluation effort is continuing through FY-2001. 

In FY-2000, the EPA document, Science Algorithms of the EPA Models-3 Community 

Multiscale Air Quality (CMAQ) Modeling System (U.S. Environmental Protection Agency, 

1999), was distributed to many different air quality modeling groups in the United States and 

around the world. The document’s 18 chapters describe all the key state-of-science atmospheric 

science features and options that are embodied in the CMAQ system. Collectively, it provides 

the scientific basis and point of reference for the state of the science captured in the June 1999 

release of the CMAQ modeling system. The document is available for download at 

http://www.epa.gov/asmdnerl/models3/CMAQ/index.html. 

2.2.1.2 Research and Development Scope of the Community Multiscale Air 

Quality Modeling System 

After the initial release of the Models-3/CMAQ system, development continued to 

improve its science content and expand the operational platforms. The Models-3/CMAQ science 

paradigm embodies the one-atmosphere concept for air quality modeling. To simulate weather 

and air quality phenomena realistically, adaptation of a one-atmosphere perspective based mainly 

on first principle science descriptions of the atmospheric system is necessary. This perspective 

11
 

emphasizes the interactions among multiple air pollutants at different dynamic scales. For 

example, processes critical to producing oxidants, acid and nutrient depositions, and fine 

particles are too closely related to be treated separately. Proper modeling of these air pollutants 

requires simultaneous consideration of the broad range of temporal and spatial scales of multipollutant interactions. Another key aspect of the one-atmosphere perspective is the dynamic 

description of the atmosphere. Air quality modeling should be viewed as an integral part of 

atmospheric modeling and the governing equations and computational algorithms should be 

consistent and compatible. 

Science submodels in the CMAQ system are the Mesoscale Model Version 5 (MM5), 

Models-3 Emissions Processing and Projection System (MEPPS), and the CMAQ ChemicalTransport Model (CCTM). There are several interface processors that link other model input 

data to CCTM. The Meteorology-Chemistry Interface Processor (MCIP) processes MM5 output 

to provide a complete set of meteorological data needed for CCTM. Initial and boundary 

conditions are processed with the processors, ICON and BCON, respectively, and the EmissionsChemistry Interface Processor (ECIP) combines area- and point-source emissions to generate 

three-dimensional gridded emission data for CCTM. A photolytic rate constant processor, which 

is based on RADM’s JPROC, computes species-specific photolysis rates for a set of predefined 

zenith angles and altitudes. An alternative detailed-science version adopts state-of-the-science 

radiative transfer models with a possibility of taking into account the total ozone column from 

TOMS satellite data and turbidity. In addition, a Plume Dynamics Model (PDM) is used to 

provide major elevated point-source plume dispersion characteristics for driving the plume-ingrid processing within CMAQ. The continued improvement of many elements of the CMAQ 

system is described below. 

The third public release of the CMAQ modeling system occurred in July 2000. There 

were few science changes to CMAQ although significant changes were made in the emissions 

data and the physics options used with MM5. The FY-2000 CMAQ release was tested against 

data from the 1995 NARSTO-NorthEast field study and 1995 Nashville, Tennessee, SOS field 

experiment. This version of the model is configured for use by the EPA Office of Air Quality 

Planning and Standards (OAQPS) and other groups involved in policy and regulatory analyses 

for air quality management. CMAQ was configured with the Carbon Bond-IV (CB-IV) chemical 

mechanism for these tests, the same mechanism used in other ozone air quality models for 

regulatory purposes. Model testing will continue in FY-2001, and will include examining the 

impacts of decreasing the vertical resolution on simulation results. 

2.2.1.3 Transport Processes within the Community Multiscale Air Quality Modeling 

System 

CMAQ’s modular design promotes incorporation of several sets of science process 

modules representing different algorithms and parameterizations of physical and chemical 

processes. For example, there are several different atmospheric transport algorithms and 

chemistry solvers available within CMAQ. One objective of the study is to demonstrate benefit 

12
 

of the modularity of the CMAQ system. Another is to assess the effects of different transport 

algorithms and grid resolutions on air quality predictions. In principle, the atmospheric transport 

processes, except for the sub-grid scale cloud mixing, are divided into advection and diffusion 

processes. They are further separated both in the horizontal and vertical directions, respectively. 

Differences between the 36-km resolution CMAQ runs were studied with two vertical 

diffusion algorithms, a non-local asymmetric convective model (ACM), and a local eddy 

diffusion scheme. The results show that CMAQ with ACM produces higher ozone and NOy 

concentrations. ACM mixes NOx and VOC emissions much more rapidly, thus resulting in more 

vigorous photochemical reaction. VOC emissions are mostly from surface sources and NOx 

emissions are from both the surface (mobile and urban sources) and elevated sources. Therefore, 

VOC emissions injected into the lowest model layer are moved to the upper boundary layer very 

quickly by the nonlocal scheme, thus changing the relative composition of the nitrogen and VOC 

compounds in the simulated air. This may be due to the incoherent representation of the ACM 

mixing algorithm and the emissions in the system. Treatment of isoprene emissions, for example 

a species that is affected by the surface turbulence fluxes, and the ACM diffusion module, may 

not be consistent. An improved ACM version to reconcile these differences is being developed. 

CMAQ was tested with two advection algorithms, PPM (piecewise parabolic method) 

and the Bott scheme. PPM is a positive definite and monotonic scheme, while the Bott scheme is 

a non-monotonic scheme and could generate unwanted local extreme values for such trace 

species as aerosol number density that have large concentration gradients. Numerical tests with 

CMAQ revealed that PPM is more robust for multi-pollutant simulations under various 

meteorological and chemical conditions. Although simulations with gas-phase species alone 

were satisfactory, the runs with aerosol dynamics with Bott and the ACM modules were not 

successful. Apparently, a minor problem with CMAQ’s Bott module that replaces very small 

negative values with zero causes inadvertent re-initialization of aerosol number concentrations in 

certain cells. Analysis results show that the Bott scheme is less diffusive than PPM, and thus 

maintains peaks of concentrations better. 

In addition, CMAQ results were compared for the cases where emissions were injected 

either in the vertical diffusion module or in the gas-phase chemical reaction module. This 

modeling construct affects CMAQ results due to the different titration rates of ozone with fresh 

NO emissions, thus changing the propagation of radicals at different stages of photochemical 

evolution. The ozone concentrations were lower for the runs with emissions in chemistry than 

for those with emissions in the vertical diffusion routines. For the species that have short 

chemical time scales competing with the transport time scales, the concentration differences are 

substantial depending on where emissions are injected. Further studies are warranted to establish 

the proper configuration of process modules in Eulerian air quality models with the time-splitting 

approach and to determine optimal inter-process time steps. 

Finally, the sensitivity of CMAQ with respect to the grid resolution was studied. MM5 

runs were made with the nonhydrostatic version and Blackadar boundary-layer parameterization 

for 12- and 4-km grid resolutions (one way nesting). The Grell cumulus cloud scheme and 

13
 
analysis nudging were applied only to the 12-km grid. For similar meteorological conditions, 

higher maxima in the 4-km resolution case than in the 12-km resolution case would be expected, 

since the sources are resolved better and the initial cloud is smeared in a smaller volume. In the 

simulations, the wind speeds are higher in the 4-km grid, which would tend to lower the 

concentrations relative to the12-km grid. Still, in some cases the 4-km grid concentrations are 

higher than those in the 12-km grid. MM5 is being run at 4 km with an observation nudging 

technique to improve consistency in meteorology simulations at different resolutions. Further 

plans are to run the meteorological model at the 1.3-km grid resolution. It might require 

implementation of relevant parameterizations to include the drag and the heat balance in urban 

areas. 

It was demonstrated that the choice of modules in transport processes interacts with other 

model processes. Comparison with observations, especially with secondary species such as O3, 

may not be sufficient to allow selection of the best modules. For example, comparison of the 

first layer ozone concentrations with those from EPA’s AIRS database is not sufficient to 

determine which transport algorithms are superior. Such factors as the representation of 

emissions inputs, the treatment of plume-in-grid, the use of different chemical mechanisms, the 

selection of different chemical solvers, and the model grid structure (i.e., vertical and horizontal 

resolutions and domain size), all contribute to different model results. Establishment of the best 

configuration of science process modules in a comprehensive AQM requires balanced 

representations of transport algorithms with other physical and chemical processes. 

2.2.1.4 Photolysis Rates 

Photolysis rates for the Models-3/CMAQ are computed using a table-interpolation 

method (Roselle et al., 1999). A table was prepared of photolysis rates for different times of day, 

latitudes, and heights. Photolysis rates for individual grid cells of CMAQ were then computed 

by interpolating values from the table. In FY-2000, development continued in coupling aerosols 

and gas-phase chemistry to include the effects of aerosols on photolysis rate calculations 

(Kondragunta et al., 2000). Testing and evaluation will continue in FY-2001. 

2.2.1.5 Cloud Dynamics and Aqueous-Phase Chemistry Module 

The cloud module in CMAQ consists of a sub-grid cloud model and a grid-resolved cloud 

model (Roselle and Binkowski, 1999). The sub-grid cloud model, which is based on the RADM 

cloud module (Walcek and Taylor, 1986; Chang et al., 1990; Dennis et al., 1993), simulates 

convective precipitating and non-precipitating clouds. The grid-resolved cloud model simulates 

clouds that occupy the entire grid cell and were resolved by the meteorological model. Several 

changes were made to the cloud module in FY-2000. The cloud model was revised to consider 

additional aerosol size-distribution parameters, including surface area. Development was started 

on the Sulfate-Tracking Model, which will track the sources of sulfate (either gas-phase and 

aqueous-phase production) at any location and at any time. In addition to work on the cloud 

14
 

module, integration and testing of a new detailed grid-resolved cloud model continued in 

FY-2000. Evaluation of the CMAQ cloud model will continue in FY-2001. 

2.2.1.6 Subgrid Scale Plume-in-Grid Modeling in the CMAQ Modeling System 

The plume-in-grid (PinG) approach contained in the CMAQ modeling system provides a 

more realistic scientific treatment of the physical and chemical processes affecting pollutant 

concentrations in isolated, major point-source plumes. In contrast to the traditional Eulerian grid 

modeling method of instantly diluting point-source emissions into an entire grid-cell volume, the 

PinG algorithms simulate the gradual growth of subgrid scale plumes and more properly treat the 

temporal evolution of photochemistry in individual plume cells during the subgrid scale phase. 

The PinG algorithms were modified for use on different computer platforms and tested in the 

Models3/CMAQ modeling system. The revised PinG programs were made available in the June 

2000 public release of the CMAQ science algorithms. The capabilities of the PinG model and 

details of its technical formulation are described in Gillani and Godowitch (1999). 

The key modeling components, designed to simulate the relevant plume processes at the 

proper spatial and temporal scales, include a PDM processor and a Lagrangian reactive plume 

model (PinG module). The PDM processor determines the position and physical dimensions of 

individual plume sections by simulating plume rise, vertical and horizontal plume growth, and 

plume transport. The PinG model simulates the relevant plume processes with a moving array of 

attached cells representing a plume vertical cross-section (Godowitch et al., 1999). PinG is 

capable of simulating a single plume or multiple point-source plumes from hourly emission 

releases. The PinG module is fully integrated into the CCTM. PinG is exercised simultaneously 

with a CCTM simulation and applies grid concentrations as boundary conditions for the plume 

sections. An important feedback occurs when a plume section reaches grid cell size, since the 

subgrid plume treatment ceases and plume concentrations are included in the Eulerian grid. 

Simulations were performed with the PinG approach applied to a group of major point 

sources exhibiting a wide range of NOx emission rates within a regional modeling domain 

encompassing the greater Nashville, Tennessee area (Godowitch and Young, 2000). 

Qualitatively, the PinG results at various downwind distances were encouraging with the 

modeled plume NOx and ozone concentrations exhibiting the same evolutionary pattern found in 

real-world plume measurements. A quantitative evaluation of the PinG model is underway with 

modeled concentrations being compared to observed plume data collected by various airborne 

platforms during the SOS summer 1995 field experiment in the greater Nashville region with 

results to be reported in FY-2001. An effort to extend the PinG model to treat aerosol species is 

planned. 

15
 

2.2.1.7 Air Quality Modeling of Particulate Matter and Air Toxics at 
 

Neighborhood Scales
 

A project is under way to develop and test a methodology linking Eulerian grid-based air 

quality models to human exposure models as a tool for understanding, assessing, and quantifying 

the health impacts and risk of airborne particles and air toxics. Mechanisms under investigation 

for adverse health impacts consist of numerous causal hypotheses, including concentration 

loading of fine particulate matter and toxic pollutants and their chemical constituents and 

physical properties. However, the distribution of pollutant concentration fields for different 

causal pollutants may be highly complex at neighborhood scales. When formulating the 

linkages, an important property of air quality modeling simulation is to model at a spatial 

resolution commensurate with the spatial gradients of the air pollutant fields. Fresh sources of 

pollutants in urban areas introduced into a regional airmass produce significant sub-urban scale 

and highly complex spatial variability, and mixtures of particulate and toxic pollutant 

concentration fields, which correspondingly impact human exposure. For many pollutants that 

are introduced locally, the design requirement to capture the details of concentration variation 

requires a grid resolution on the scale of neighborhoods. The proof-of concept exercise, 

demonstrated the bridging of air quality models with exposure modeling by extending the range 

of the Models-3/CMAQ spatial resolution capability from its regional- (~36 km) and urban-scale 

(4 km) resolutions to 1.33 km. The CMAQ modeling system incorporates such state-of-science 

parametric formulations of all the critical science processes as atmospheric transport, deposition, 

cloud mixing, emissions, gas and aqueous-phase chemical transformation processes, and aerosol 

dynamics and chemistry that control the temporal and spatial distribution of the air quality fields. 

Using CMAQ, with its one-atmosphere paradigm, the scope of this prototype study can 

encompass the range of air quality and exposure model linkages for photochemical oxidants, 

particulate matter (PM10 and PM2.5) and air toxics. 

The initial study applied the CMAQ modeling system at three grid resolutions, 12, 4 and 

1.33 km, in the Philadelphia Metropolitan Area to illustrate the utility of linking CMAQ to the 

EPA Stochastic Human Exposure and Dose Simulations model for estimating population 

exposure in Philadelphia. Preliminary results show that the meteorological and subsequent 

pollutant fields of surface layer ozone and PM2.5 and its constituent species, as well as the 

distribution of population exposure, are significantly dependent on the scale of the grid 

resolution. However, the sensitivity to scale dependency varies between the different air quality 

fields. Efforts to introduce near-source dispersion modeling are underway. Additionally, studies 

will be conducted to provide a basis for more robust use of air quality models as a bridge to 

exposure modeling, including extensions toward modeling semi-volatile organic toxic 

compounds, improved parameterizations of urban canopies, and pollutant exchanges between 

microenvironments and the larger scale. Methods to extrapolate episodic model results to 

longer-term exposure time scales and the use of data-assimilation methods that combine 

monitoring data with model results will need to be explored. 

16
 

2.2.1.8 Aggregation Research for Models-3/CMAQ 

In support of studies mandated by the 1990 Clean Air Act Amendments (CAAA), the 

Models-3/CMAQ model is used by the EPA Program Offices to estimate deposition and air 

concentrations associated with specified levels of emissions. Assessment studies require 

CMAQ-based distributional estimates of ozone, acidic deposition, PM2.5, as well as visibility, on 

seasonal- and annual-time frames. Unfortunately, it is not financially feasible to execute CMAQ 

over such extended time periods. Therefore, in practice, CMAQ must be executed for a finite 

number of episodes or events, which are selected to represent a variety of meteorological classes. 

A statistical procedure called aggregation must then be applied to the outputs from CMAQ to 

derive the required seasonal and annual estimates. 

The objective of this research was to develop a new aggregation approach and set of 

events to support CMAQ-based distributional estimates of fine particles and other air quality 

parameters over the continental domain. The primary strategy involved categorizing many years 

of meteorological patterns into a few classes. This represents a very ambitious goal, and not 

surprisingly the wind vectors assigned to individual clusters varied substantially. Nevertheless, 

the results suggest that the approach reasonably characterizes flow patterns associated with 

synoptic-scale patterns and leads to strata that explain variation in extinction coefficient, 

temperature, and relative humidity (Eder et al., 2000). 

Defining seasonally based clusters further improved the ability of the clusters to explain 

the variation in these parameters, and therefore led to more precise estimates. The final scheme 

included 20 clusters (five per season), and stratified systematic sampling was used to select a 

sample of 40 events from the 20 clusters. The approach performed better than simple random 

sampling; relative efficiencies were 1.18 for extinction coefficient, 3.86 for temperature, and 1.36 

for relative humidity. A basic aggregation technique was also illustrated for the selected sample 

of events, and revealed aggregated estimates of the bext falling generally within ±10% of the 

observed mean bext for the period 1984-1992, consistent with independently estimated variability 

(Cohn et al., 1999; Cohn et al., in press). 

Future work will investigate the ability of the aggregation and episode selection scheme 

to replicate actual bext on finer temporal and spatial scales to accommodate various applications 

of CMAQ. For instance, will aggregated estimates of bext for an individual year such as 1988 (a 

meteorologically anomalous year) still fall within ±10% of the observed mean, or will the 

estimates deteriorate? 

2.2.1.9 Collaborative Model Evaluation Studies for Particulate Matter 

Three collaborative model evaluation projects are underway based upon utilization of the 

Models-3/CMAQ system. Through a cooperative agreement, a modeling center has been 

initiated at the University of Alabama-Huntsville to develop a Models-3/CMAQ capability to 

serve present and future needs of the SOS community. As part of the functions of this Center for 

17
 

Models-3/CMAQ, performance evaluation will be conducted for specific episode simulations. 

The initial model-data intercomparisons will be made for selected case studies using targeted 

data from aircraft, meteorological observations, and surface chemistry sites from the 1999 

SOS-Nashville field experiment. A research collaboration between the Washington University 

Center for Air Pollution Impacts and Trend Analysis (CAPITA) in St. Louis, Missouri, and 

ASMD is underway to evaluate the performance of Models-3/CMAQ, and assess the suitability 

of using visibility as a surrogate for PM2.5 concentrations in the Models-3/CMAQ aggregation 

technique for producing annual- and long-term averages. Both efforts will be utilizing CAPITA's 

consolidated database of PM data sets. This project serves to facilitate the use of 

Models-3/CMAQ by an extended community. This aids in its evaluation and utility to address 

major and pertinent issues of developing science-based strategic plans for dealing with NAAQS 

(National Ambient Air Quality Standards) issues, including PM2.5, PM10, and ozone. This 

research provides and utilizes methods to perform essential scientific evaluation of the 

performance of CMAQ in modeling fine particles. PM2.5 modeling is needed for performing 

environmental assessments and implementing the requirements of the PM2.5 State 

Implementation Plans (SIPS) and Regional Haze Rule (RHR). 

The development, implementation, and utilization of Models-3/CMAQ to assess and 

develop strategic and tactical strategies to deal with existing and emerging pollution issues 

pertinent to the Class I natural areas in the West is underway through an interagency agreement 

with the National Park Service (NPS). NPS, in collaboration with the Cooperative Institute for 

Research in the Atmosphere at the Colorado State University, Fort Collins, Colorado, has begun 

its implementation of Models-3/CMAQ and will begin to develop and incorporate algorithms for 

advanced smoke emission processing from fires (prescribed, agricultural, and natural) in Models3/CMAQ. This project will facilitate the use of Models-3/CMAQ in the West to develop 

science-based strategic plans for dealing with smoke emission management issues and interstate 

transport affecting regional haze, PM2.5, PM10, and ozone. 

2.2.1.10 A Preliminary Evaluation of Models-3/CMAQ Using Visibility Parameters 

Ambient air concentrations of PM2.5 continue to be a major concern for EPA. High 

concentrations of fine particles were linked to detrimental health effects (including an increase in 

mortality) and visibility degradation. Accordingly, the CAAA of 1990 called for an assessment 

of current and future regulations designed to protect human health and welfare. The most 

reliable tool for carrying out such assessments are air quality models, which simulate air 

concentrations and deposition of PM2.5, and various measures of visibility associated with 

specified levels of emissions. These simulations can be used by EPA Program Offices and 

research laboratories to support both regulatory assessment and scientific studies on a myriad of 

spatial and temporal scales. 

This research provides a preliminary evaluation of CMAQ using a visibility parameter 

called the deciview. The evaluation compares deciview values computed from visibility 

observations at 174 stations in the eastern half of the United States with those simulated by the 

18
 

model for the 5-day period, July 11–15, 1995. Visibility was selected for this evaluation for two 

reasons: it can serve as a surrogate for PM2.5 for which little observational data exist; and it has 

one of the most spatially and temporally comprehensive observational data sets available. 

The evaluation revealed a general agreement between the modeled and observed values, 

with over two-thirds of the simulated values falling within a factor of two of the observations 

(Eder et al., in press). The CMAQ simulation also captured the basic spatial and temporal 

patterns of visibility degradation, including major gradients and maxima/minima. The 

correlation coefficient between the observed and simulated deciviews for the entire 5-day 

simulation period was 0.56 and ranged from 0.38 on July 11 to 0.70 on July 13. The model 

generally underpredicted the visibility degradation by 10 deciviews; however, some of this 

discrepancy can be attributed to artifacts associated with the observed data. Other potential 

sources of CMAQ discrepancies, which will be the subject of future research, include possible 

errors in the emissions inventories, the input meteorological data, and the aerosol model itself. 

2.2.2 Aerosol Research and Modeling 

The FY-2000 release of CMAQ incorporated the latest version of the aerosol dynamics 

code. Integrating the new version within the three-dimensional structure of CMAQ required 

special treatment. In the FY-1999 release, the total aerosol number and species mass 

concentrations within the Aitken and accumulation modes were the history variables. Number is 

the zeroth moment of the size distribution, and mass defines the third moment of the distribution 

when scaled by a standard density. This means that the geometric standard deviation of each of 

the modes was a fixed value. In the new version, total surface area, which is a constant times the 

second moment of the distribution, was added as a history variable; thus, the geometric standard 

deviation is now a variable. However, this new history variable needs to be transported. This 

requires some careful analysis. In the real atmosphere, particles adjust to their immediate 

environment while being transported. Hydrophilic particles take up water in response to 

increasing relative humidity as, for example, in rising air parcels. In a numerical model, it is very 

difficult to model this adjustment process exactly as it happens in the atmosphere. The most 

common method is to take a transport step followed by a thermodynamic adjustment step. 

Because the model results are desired at a time granularity much coarser than the few seconds 

that the adjustment takes in the atmosphere, it is acceptable to use this common approach. Note 

that transport by atmospheric motion can be viewed as a mixing process. In an Eulerian model 

like CMAQ, transport includes advection of material from one grid cell to an adjacent grid cell. 

Transport also includes turbulent mixing that occurs in the planetary boundary layer (PBL). Both 

of these processes may be viewed as combining or mixing values from two grid cells, the source 

and target cells, with the result being placed in the target cell. 

When the aerosol module version with the fixed geometric standard deviation was 

integrated into the CMAQ code, number and mass concentrations were mixed, water content was 

adjusted, and the size distribution calculated from the moments. When, however, the second 

moment is included, the situation is more complex. The second moment (surface area) has 

19
 

specific information about the size distribution. It can represent the surface area of either wet or 

dry particles. The number concentration is insensitive to the presence of water. The species 

mass concentration transported in the FY-1999 version did not include water; this was 

determined at every time step from the thermodynamic calculations. When surface area was 

introduced, the first CMAQ calculations were done by transporting the surface area for wet 

particles. The results did not closely resemble real atmospheric size distributions. The geometric 

standard deviations appeared to be too large. It was determined that vertical diffusion was the 

major cause. This may be understood as follows. In the well-mixed daytime PBL, potential 

temperature and water vapor mixing ratio are very nearly constant with height. But, relative 

humidity increases in a rising air parcel under these circumstances. Thus, particles at higher 

altitudes will be larger than particles at lower altitudes. Now consider the mixing of the 

moments of two size distributions, one with a higher water content than the other. If the 

geometric standard deviations are equal, but the diameters are different, the resultant size 

distribution will have a larger geometric standard deviation. This was the cause of the problem 

with the modeled size distributions. If, however, the second moment is for a dry particle size 

distribution in the well-mixed PBL, the difference in the moments is much smaller, and the 

resulting size distributions are more realistic. Therefore, all transport is done with the surface 

area (second moment) being calculated for a dry particle size distribution in the FY-2000 release 

of CMAQ. After the transport step, but before any aerosol dynamics calculations are done, the 

distributions are adjusted for humidity. The new wet size distribution is used for all further 

dynamical and visual range calculations. Before the next transport step, the size distribution is 

readjusted to be a dry distribution to continue the model simulation. 

2.2.3 Atmospheric Toxics Pollutant Research 

2.2.3.1 Atmospheric Toxics Pollutant Modeling 

During FY-2000, a modeling study was concluded using previously developed simulation 

capabilities for atmospheric mercury based on the REgional Lagrangian Model of Air Pollution 

(RELMAP) (Eder et al., 1986) to investigate the incremental effects of mercury air emissions 

from Canada on the magnitude and pattern of mercury deposition across the United States. 

Development of new atmospheric simulation modeling capabilities for toxic pollutants during 

FY-2000 focused on two pollutants: mercury and the semi-volatile pesticide atrazine. Both 

modeling efforts involve the use of CMAQ as the basis for air toxics pollutant modeling, but 

their relevant scientific issues and modeling approaches differ somewhat. Each effort is 

discussed separately below. 

Modeling of Mercury. 

The RELMAP mercury model was developed to simulate the emission, transport, 

dispersion, atmospheric chemistry, and deposition of mercury across the continental United 

States (Bullock et al., 1997). This model was used in the development of the Mercury Study 

Report to Congress (U.S. Environmental Protection Agency, 1997) to estimate the magnitude 

20
 

and pattern of mercury deposition throughout the United States from domestic emissions and 

from the global average concentration of elemental mercury from sources all around the world. 

During FY-2000, an inventory of Canadian air emissions of mercury was added to the simulation 

to revise previous mercury deposition estimates. The atmospheric fate of Canadian mercury 

emissions was simulated in the same manner as previously done for United States emissions, and 

an assessment of the incremental effect of Canadian sources on the total mercury deposition 

pattern across the United States was obtained. These results suggest that Canadian sources 

account for no more than 20 percent of mercury deposition to any U.S. location, with the 

exception of the extreme northern section of the Rocky Mountain region near the Canadian 

border. An article describing this modeling exercise and its results was accepted for publication 

(Bullock, in press). 

In FY-2000, a number of gas- and aqueous-phase chemical reactions involving mercury 

were added to CMAQ. The standard CMAQ gas- and aqueous-phase chemistry mechanisms for 

tropospheric ozone and acid deposition simulation are used as a basis for the simulation of 

complex mercury chemistry. During FY-2000, new aqueous-phase reactions of elemental 

mercury with dissolved chlorine species OCl-

 and HOCl, and dissolved OH radical were added to 

CMAQ. Reactions of all modeled forms of dissolved Hg++ with HO2 radical to form elemental 

mercury were also added. These new reactions were based on Lin and Pehkonen (1999) and 

Pehkonen and Lin (1998). A previously included reaction of HgSO3 to form elemental mercury 

by spontaneous decomposition was modified based on the results of a new analysis of the 

reaction rate (Van Loon et al., 2000). This new information indicates that the production of 

elemental mercury is much slower than previously thought, and that additional mercury-reducing 

agents must be important to the overall reduction-oxidation balance of mercury in cloud water 

and precipitation. 

During FY-2000, Branch personnel participated in the first phase of an international 

atmospheric mercury model intercomparison sponsored by the European Monitoring and 

Evaluation Programme (EMEP) and organized by EMEP’s Meteorological Synthesizing Center ­

East (MSC-East) in Moscow, Russia. This first phase of the intercomparison involved the 

simulation of mercury chemistry in a closed cloud volume given a variety of initial conditions. 

Results obtained from the CMAQ mercury model and the other participating models from 

Russia, Germany, Sweden, and the United States are now being compared to identify key 

scientific and modeling uncertainties, and a report will be issued by the MSC-East. In FY-2001, 

a second phase of intercomparison is planned, which will involve full-scale model simulations of 

the emission, transport, transformation and deposition of mercury over Europe and comparison 

of the modeling results to corresponding field measurements. 

Modeling of Semi-Volatile Compounds. 

To simulate the fate of compounds that are considered semi-volatile and toxic, CMAQ 

was modified to introduce a semi-volatile compound into the atmosphere as gaseous emissions 

from an area source. Once emitted, the gas can transform via OH addition or partition onto 

ambient particulate matter as a trace species. The partitioning assumes equilibrium between the 

21
 

gas and particulate phases based on empirical and theoretical work (Pankow, 1987; 1994). 

Concentrations in each phase then depend on the total ambient concentration and partitioning 

ratios. Besides these chemical and physical processes, the compound undergoes advection, 

diffusion, and deposition. 

CMAQ was selected to address this issue based on how the model estimates particulate 

matter in the lower troposphere. The estimate uses a tri-modal distribution and internal mixture 

of inorganic and organic species to describe particulate matter. The inorganic species divide into 

two components: aqueous and dry. These aspects permit studying how a semi-volatile compound 

partitions onto particulate matter in different ways. The compound adsorbs onto surface areas 

from a combination of inorganic species within particulate matter. In addition, the semi-volatile 

compound absorbs into either the organic species or aqueous component within particulate 

matter. CMAQ then is able to help assess how meteorology and gas-to-particle partitioning 

combine to control the fate of semi-volatile compounds over regional and local scales. 

The modified model is being evaluated through the simulation of atrazine, a common 

agricultural herbicide. The effort uses atrazine emissions predicated on its usage, and a soil 

model under energy balance conditions. The model domain covers the eastern United States and 

the simulation spans the period from April to mid-July of 1995. Results include concentrations 

in air and precipitation. Baseline calculations are being used to support assessments conducted 

by the Lake Michigan Mass Balance Study. Comparisons of model results to observations 

(Majewski et al., 2000; Foreman et al., 2000) show on average that the model underpredicts 

precipitation concentrations while it overpredicts air concentrations. These findings imply that 

the model’s algorithms insufficiently scavenge airborne atrazine via wet deposition. Sensitivity 

calculations will be used to determine the causes of this underprediction of wet scavenging. 

Additional comparisons will use other observations (Miller et al., 2000; Harman-Fetcho et al., 

2000) and this evaluation will be completed during FY-2001. 

Research and development will continue in FY-2001 toward the production of a 

CMAQ/atrazine version for public release. Work will also be performed to expand the model to 

handle other semi-volatile compounds such as polychlorinated dibenzo-para-dioxins and other 

dioxin-like compounds. 

2.2.3.2 Atmospheric Mercury Field Research 

The Florida Atmospheric Mercury Study (FAMS) was conducted to characterize the 

atmospheric loadings of mercury to Florida (Guentzel, 1997). This study developed a simple box 

model that suggested the dominant source of mercury in rainfall to south Florida was from trade 

wind (long-range) transport from the Atlantic Ocean. The South Florida Atmospheric Mercury 

Monitoring Study (SoFAMMS) was conducted to investigate potential source-receptor 

relationships between anthropogenic point-source emissions in southeast Florida and 

atmospheric wet deposition of mercury (Dvonch et al., 1998). This study used a multivariate 

source apportionment approach and concluded that approximately 70 percent of the mercury in 

22
 

rainfall to southeast Florida was from waste incineration and oil combustion sources. The FAMS 

and SoFAMMS studies both identified atmospheric wet deposition as the dominant pathway for 

mercury into the Florida Everglades. The magnitude of local anthropogenic source contributions, 

however, remains a subject of contentious debate. Both studies highlighted the importance of 

reactive gaseous mercury (RGM) and meteorological transport in explaining the transport and 

deposition of mercury to south Florida. However, methods for measuring ambient 

concentrations of RGM were not available for the FAMS and SoFAMMS studies. 

Reliable methods for discriminative measurement of ambient RGM and Hg0

 have since 

been developed using annular denuder technology. Automated RGM monitoring systems are 

now available (e.g., http://www.tekran.com/access/1130.html). In FY-2000, this new annular 

denuder technology was used on a research aircraft in a manual sample collection mode to 

evaluate the FAMS study hypothesis of long-range transport of RGM to Florida in the marine 

free troposphere. In a cooperative effort involving personnel from the Division, NOAA, ARL 

Silver Spring, Maryland, and the EPA National Exposure Research Laboratory, Research 

Triangle Park, North Carolina, a NOAA DeHavilland Twin Otter (DHC-6-300) aircraft was used 

to obtain measurements of RGM, Hg0

, and other ancillary measurements, in upwind air off the 

coast of Florida during mid-January to mid-February and during June of 2000. Ancillary 

measurements of ozone (O3), carbon monoxide (CO), sulfur dioxide (SO2), nitrogen oxides (NO, 

NOX, NOY), condensation nuclei (CN), and various trace elements in aerosol form were also 

collected to be used to identify sources of observed RGM. The data collected were subject to 

QA/QC procedures at ARL Headquarters during FY-2000. A cooperative effort to analyze these 

data and arrive at scientific conclusions about the source of RGM impacting south Florida will 

continue through FY-2001. 

2.2.4 Meteorological Modeling Studies 

The fifth-generation Penn State/NCAR Mesoscale Model (MM5) is the primary tool for 

providing meteorological input for Models-3/CMAQ. MM5 is widely used for providing 

meteorological characterizations throughout the air quality modeling community. For 

Models-3/CMAQ, MM5 is applied to several case studies at a variety of spatial scales using a 

series of one-way nested domains. MM5 is run retrospectively using four-dimensional data 

assimilation (FDDA) for a dynamic analysis of the simulation period. The output represents a 

dynamically consistent multiscale meteorology simulation for continental scale (e.g., either 

108 km or 36 km), regional scale (e.g., 36 km, if 108-km simulation is made), mesoscale (e.g., 

12 km), and urban scale (e.g., 4 km). A 108-km simulation is performed if the background 

analyses used as input to the MM5 pre-processing have a coarse (e.g., 2.5/ latitude/longitude) 

horizontal grid spacing as is typical of archived global meteorological model output. The three 

finest resolutions are then run through the CMAQ emissions and chemistry modules. 

23
 

2.2.4.1 Meteorology Modeling for Models-3/CMAQ Applications 

Several projects were underway during FY-2000 using MM5 to support 

Models-3/CMAQ applications. MM5 Version 3 (MM5v3) was released by the National Center 

for Atmospheric Research (NCAR), Boulder, Colorado, in late FY-1999, and it was tested for air 

quality applications. MM5v3 includes major changes to the NCAR code in MM5v2, including a 

new input/output format, a year-2000-compliant date structure, and formal support for the 

software on various serial and parallel hardware architectures. MM5v3.3, released by NCAR in 

January 2000, was predominantly used in FY-2000, and MM5v3.4, to be released by NCAR in 

November 2000, will be used in FY-2001. MM5v3.3 was tailored for air quality applications 

with some minor modifications. The significant changes made to the NCAR release include 

standardizing the radius of the earth with the emissions and chemistry modules, enabling analysis 

nudging FDDA and initialization from one-way nesting to occur in the same simulation, and 

changing to the planetary boundary layer parameterization. With the exception of projects started 

prior to the release of MM5v3 from NCAR, the Division has fully transitioned to MM5v3, and 

the majority of utility code updated to accommodate the new MM5v3 output format. 

During FY-2000, initial testing of MM5v3.3 involved using Eta Data Assimilation 

System (EDAS) analyses from the National Centers for Environmental Prediction (NCEP). The 

EDAS analyses are archived for a domain over most of North America with full threedimensional fields at 3-hourly intervals on a horizontal grid spacing of 40 km. This represents a 

significant improvement in temporal and spatial resolution over the 2.5/ latitude/longitude at 

12-hourly interval analyses that were previously used. Since the horizontal grid spacing is 

dramatically improved using EDAS, the 108-km MM5 domain was eliminated, and the 36-km 

domain was set to cover the continental United States. The test case for MM5v3.3 was July 

13–30, 1998, selected to coincide with air quality simulation for an isoprene photochemical field 

study. MM5v3.3 was executed in four 4.5-day runs (including a 12-hour spin-up period in each 

run). A significant effort was placed on quality control of the new processors in MM5v3.3 and 

the EDAS analyses. MM5 successfully captured the placement of the oscillating stationary front 

and precipitation patterns through the period. The integration and trouble-shooting exercise 

using MM5v3.3 and EDAS was presented (Otte, 2000) at the Tenth PSU/NCAR Mesoscale 

Model Users’ Workshop. The MM5 simulations were also used for two studies (Schwede et al., 

in press; Pleim et al., in press) that were presented at The Sixth International Conference on AirSurface Exchange of Gases and Particles, Edinburgh, United Kingdom. The CMAQ simulations 

for the isoprene study have not been performed. 

Another research effort in FY-2000 was to use FDDA based on observation nudging in 

high-resolution MM5 runs. Using the July 1995 NARSTO-NE cases established in FY-2000, the 

observation nudging was implemented for sensitivities on a large 4-km domain covering the 

northeastern United States. More than 100 surface observation sites were available, as were 

radiosonde soundings and wind profilers. By partitioning the data into two sets (one for nudging 

and the other for verification), a series of simulations was performed to set user-definable 

parameters for observation nudging. Those parameters were applied to the full set of 

observations to generate an improved set of runs at 4-km for July 1995. Work with new 

24
 
observation nudging strategies will continue in FY-2001 as higher-resolution runs are 

considered. 

Lastly, a preliminary demonstration of anisotropic weighting functions in FDDA was 

completed in FY-2000. The research used an observing-system simulation experiment to 

illustrate that anisotropic weighting functions have subtle but important impacts in FDDA. The 

results of this research appear in Otte et al. (accepted for publication). An extension of this work 

to air quality modeling is planned. 

2.2.4.2 Advanced Land-Surface and Planetary Boundary Layer Modeling in MM5 

MM5 was coupled to an advanced land-surface and PBL model to improve simulation of 

surface fluxes and PBL characterization. Such surface and PBL quantities as surface air 

temperature and PBL height are critical to realistic air quality modeling. The new land-surface 

model, known as the PX LSM (Pleim and Xiu, 1995; Xiu and Pleim, accepted for publication), 

includes explicit soil moisture and vegetative evapotranspiration along with ACM (Pleim and 

Chang, 1992). The FY-2001 effort was dominated by collaboration with the MMM group at 

NCAR toward the MM5v3.4 release in November 2000, which includes the PX LSM as one of 

two LSM options. Evaluation and improvement through comparison to field experiment data 

also continued in FY-2000. 

The PX LSM is fully integrated in the NCAR-supported MM5v3.4 as a beta release. No 

modifications are necessary to MM5 preprocessor programs. However, certain options in Terrain 

are necessary to produce gridded fractional information of land use and soil type. Also, a new 

preprocessor InitPX is provided to process initial fields of soil moisture and soil temperature 

from previous model runs so that a continuous simulation over many multi-day runs can be 

made. Instructions for use of the PX LSM can be found in the MM5 tutorial that is on the NCAR 

MM5 website at http://www.mmm.ucar.edu/mm5/mm5-home.html. 

Evaluation and further improvement of the PX LSM through comparison to field 

experiment data is continuing. In addition to previous studies comparing model runs to surface 

fluxes over corn, grass, and soybeans, case studies were made for a mixed deciduous-coniferous 

forest field study in the Adirondack area of New York in July 1998, and two sites, grass and 

soybeans, near Nashville, Tennessee, that were part of the SOS 1999 field study. These 

comparison studies included evaluation of such meteorological parameters as surface level 

temperature, and humidity, and surface fluxes of heat, moisture, and net radiation as well as 

ozone dry deposition velocity from a dry deposition model that couples to the PX LSM. The 

results of these studies were presented at a meeting in Edinburgh, Scotland, in June 2000, and 

will be published in a special issue of Water, Air, and Soil Pollution (Pleim et al., in press). 

Such comparisons to field surface flux and meteorology measurements are extremely valuable 

for improvement of the model’s applicability to simulate a variety of vegetation types. 

25
 
A new feature in the latest modeling study for the SOS 1999 field study is an upgraded 

version of the ACM PBL model called ACM2. Rather than direct non-local transport from layer 

one to all other layers in the convective boundary layer, as in ACM, ACM2 includes a physical 

surface layer defined by the Obukhov Length. Within the surface layer, mixing is accomplished 

by eddy diffusion using eddy diffusion coefficients defined by surface layer similarity theory. 

Above the surface layer, non-local mixing is applied in the same manner as in the ACM. ACM2 

can better represent the surface based super-adiabatic layer since it can be multi-layer with a 

physical definition. ACM2 will also be applied to CMAQ, where it will result in more gradual 

mixing of surface emissions than in the ACM. 

2.2.5 Dry Deposition Studies 

2.2.5.1 Dry Deposition Research 

Field Studies. 

An analysis of dry deposition data from three forest field studies was completed. The 

forests were in central North Carolina, northwestern Pennsylvania, and the Adirondack region of 

New York. The study included a thorough description of deposition processes to forests, and an 

evaluation of the performance of the multi-layer deposition velocity model in a forest 

environment. A journal article on the studies was published (Finkelstein et al., 2000). 

The study found that average daily deposition velocities are quite similar among sites. 

For O3, they are 0.75, 0.75, and 0.79 cm/s at Kane Forest, Pennsylvania; Sand Flats, New York; 

and Duke Forest, North Carolina, respectively. For SO2, they are 1.04 and 1.01 cm/s at Kane and 

Sand Flats. The seasonal cycles of O3 deposition velocity are pronounced, and closely follow the 

green up and senescence of the foliage. The seasonal cycle for SO2 deposition velocity shows 

less variation between spring, summer, and fall, but still shows the effects of vegetative uptake 

superimposed on year-round surface uptake. Because the concentrations of SO2 in remote areas 

are usually substantially less than those for O3, the fluxes of O3 are usually higher. 

Average daytime values for O3 deposition velocity over forests peak in mid-morning 

when stomatal activity is greatest, and not near noon as it does over crops or as SO2 deposition 

velocity does over crops and forests. Minimum values of deposition velocity for both SO2 and 

O3 occur early in the night, and then tend to slowly increase, perhaps due to surface absorption 

caused by increases in wetness and/or early opening of the stomata. Even before any light 

reaches the trees, stomata may be open in some species, resulting in some uptake throughout the 

night. This was observed at the mixed and pine forests sites, but not at the deciduous forest sites. 

A comparison of the average daily maximum deposition velocity during fast growth 

periods with similar results over crops indicates that maximum O3 deposition velocity is higher 

to forests than to corn or pasture, but about the same to the more dense soybeans. SO2 deposition 

velocity to forests is only slightly higher than it was to corn or pasture, but less than to soybeans. 

26
 

The ratio of SO2 deposition velocity to O3 deposition velocity is greater over crops than over 

forests. 

Models. 

To help understand these processes, significant progress was made in developing the next 

generation deposition velocity model, which is called the Multi-Layer Bio-Chemical dry 

deposition model (MLBC). The model uses an improved Gaussian quadrature integration 

scheme, which reduces the number of layers needed in the integration and is more accurate; a 

significantly revised aerodynamic resistance model based on similarity theory; a simplified 

boundary layer resistance model; and a revised and enhanced short- and long-wave canopy 

radiation model. Stomatal resistance, rather than based on the typical Jarvis scheme, is based on 

a model of Farquhar et al. (1980), which calculates stomatal conductance by considering 

photosynthesis and respiration processes. This method provides more insights into the 

biochemical mechanisms governing photosynthesis and respiration, and how these are tied to 

stomatal conductance considering the direct and indirect effects of environmental factors. 

MLBC also has a new cuticular resistance model. Plant cuticles are a lipophilic polymer 

membrane that consists of an insoluble bipolymer cutin and waxlike lipids. Diffusion across this 

layer can be either directly from the air to the layer, or from the air to a thin water film that 

usually exists on outdoor surfaces, and from the water layer to the cuticle. Diffusion equations 

for each of these pathways are developed that depend on the chemistry of the cuticle, water, and 

each pollutant. 

Tests of this model against data collected in the field studies show significant 

improvement over the present generation of models. Figure 1 shows the average diurnal cycle of 

ozone deposition velocity observed over Kane Forest, and model results from MLM used in 

CASTNet, the RADM deposition model used in the present generation of Models-3/CMAQ, and 

the new MLBC. After its completion, MLBC will be modified for use in Models-3/CMAQ, and 

combined with other improvements in deposition velocity modeling discussed below. 

Methods Evaluation. 

Atmospheric fluxes are controlled to a significant degree by atmospheric turbulence, and 

particularly by large eddies in the planetary boundary layer. These large eddies are somewhat 

random, stochastic events. Thus, observations of atmospheric fluxes over normal time periods, 

i.e., 15 to 60 minutes, have a random error component that can be evaluated if the variance of the 

flux or covariance is known. The direct calculation of the variance of the covariance is a 

powerful and inclusive method for calculating the random sampling error in eddy correlation 

measurements. It takes into account sources of error not considered by previously published 

approaches, and as a consequence, tends to produce larger estimates for the error. For the 

approximately 100 samples taken from a variety of field programs over both low agricultural 

27
 

Figure 1. Average diurnal cycle of O3 deposition velocity observed 

over Kane Forest, Pennsylvania. 

crops and forests, the normalized sampling error ranged from approximately 10% for sensible 

heat to 25%-30% for trace gases. These rather large sampling errors in flux measurements 

should be kept in mind when considering problems related to closing the energy balance, CO2 

budgets, or comparing deposition model results to measurements. 

2.2.5.2 Dry Deposition Modeling 

As part of the CMAQ development, a new method for modeling dry deposition of 

gaseous chemical species was developed to take advantage of the more sophisticated surface 

model, PX LSM, implemented in MM5. Since PX LSM has an explicit parameterization for 

evapotranspiration, the same stomatal and canopy conductances can be used to compute dry 

deposition velocities of gaseous species. This technique has the advantage of using more 

realistic conductance estimates resulting from the integrated surface energy calculation where the 

soil moisture is continually adjusted to minimize model errors of temperature and humidity. The 

dry deposition model was previously evaluated for ozone deposition by comparing model results 

with field measurements at Bondville, Illinois, and Keysburg, Kentucky (Pleim et al., 1996; 

Pleim et al., 1997). Further evaluation studies were performed in FY-2000 for a 1998 mixed 

forest study in New York, and two sites, grass and soybeans, near Nashville, Tennessee, that 

were part of the SOS 1999 field study. Results of the forest study and a 1995 study for soybeans 

in Kentucky were presented at a meeting in Edinburgh, Scotland, in June 2000, and will be 

28
 
published in a special issue of Water, Air, and Soil Pollution (Pleim et al., in press). The impact 

of the new dry deposition model and PX LSM on the simulation of air chemistry by the CMAQ 

system was tested as part of the 1995 NARSTO-NE evaluation study. Results of this study were 

presented at the NATO/CCMS Millennium conference in May 2000 (Pleim and Byun, 2000). 

2.2.6 Technical Support 

2.2.6.1 North American Research Strategy for Tropospheric Ozone 

NARSTO (formerly known as the North American Research Strategy for Tropospheric 

Ozone) is a coordinated 10-year research strategy to pursue the science-based issues that will lead 

to better management of the North American tropospheric ozone, particulate matter, and other air 

quality problems. It includes a management function for performing this coordination across the 

public and private sector organizations sponsoring air quality research, as well as those groups 

performing the research, including the university community. Canada and Mexico are also 

participating in the continental NARSTO program. During FY-2000, the ongoing NARSTO 

science assessment of tropospheric ozone was brought partially to completion, with the 

publication of a special NARSTO issue of Atmospheric Environment (2000). This Special Issue 

contains a set of Critical Review papers, commissioned specially for the ozone assessment that 

covers relevant areas including ambient measurements and networks, field studies, source 

emissions, atmospheric chemistry, and meteorological and air quality models. The second part of 

the ozone assessment, an Assessment Report (NARSTO Synthesis Team, in press) relating the 

state-of-science to outstanding air quality management issues, will be published in FY-2001. 

2.2.6.2 Western Regional Air Partnership Air Quality Technical Forums 

The Western Regional Air Partnership (WRAP) is a broad-based regional air quality 

coordinating organization composed of States and Tribes in the western United States, U.S. 

Departments of Agriculture and Interior, EPA, and other affected stakeholders representing 

industry, environmental groups, and other interested parties. One Division scientist participated 

in the Air Quality Modeling Forum (AQMF) and Research and Development Forum (R&DF), 

which are two of several committees of WRAP formed to provide technical guidance. WRAP is 

a follow-on organization to the Grand Canyon Visibility Transport Commission, whose objective 

was to provide technical and policy input needed to regulate regional haze in the western United 

States. AQMF provides WRAP with technical analyses needed to meet practical, real-world 

objectives, especially as they relate to meeting the regulatory requirements of the EPA regional 

haze rule (RHR) published July 1, 1999. Specific AQMF modeling assessments on regional 

visibility include (1) relative incremental contribution of a given source or source control on 

visibility at one or more Class I areas; (2) cumulative impact of regional source growth or control 

on Class I areas throughout the region; (3) impact of regional sources during periods of high and 

low visibility conditions; and (4) evaluation of cost-effective alternatives for improving regional 

haze. Time frames required by the RHR are (1) near-term (SO2 regional emission trading 

29
 
program plan due October 1, 2000); (2) intermediate to long-term (additional requirements for 

regional visibility modeling by December 31, 2003); and (3) long-term (modeling to support SIPs 

due no later than December 31, 2008). WRAP AQMF is using Models-3/CMAQ for performing 

the intermediate- and long-term modeling for RHR. R&DF is sponsoring the development of 

science modules to handle fugitive dust emissions in CMAQ. A workshop based on technical 

recommendations from an expert panel is planned for December 2000. 

2.2.6.3 Multimedia Integrated Modeling System Meteorological Team 

Accurate characterization of the atmosphere is an essential part of any environmental 

modeling endeavor. During the development of the Multimedia Integrated Modeling System 

(MIMS), research will be ongoing to improve this characterization and its seamless integration 

into MIMS. MM5v3 is used to generate meteorological data for CMAQ; however, additional 

models will also be considered in the future. Two problems common to the meteorological 

models are the intensive computations involved because of their complexity and the tremendous 

amounts of data generated. These constraints are exacerbated with MIMS, because unlike 

episodic air quality studies, which typically simulate 10-day periods, MIMS will be required to 

perform much longer simulations to study the impact of nitrogen loading to the watershed. As a 

result, such statistical approaches as aggregation may be required. Such a procedure was applied 

successfully to air quality studies in the past, including CMAQ simulations (Cohn et al., 1999; 

Eder et al., accepted for publication; Cohn et al., in press). With aggregation, a limited set of 

meteorologically representative time periods are used to derive the required seasonal and annual 

estimates. Therefore, in practice, MM5 and MIMS may have to be executed for finite episodes 

or events, the results of which would be aggregated to achieve the requisite seasonal or annual 

results. 

2.2.6.4 Climatological and Regional Analyses of CASTNet Data 

- The spatial and temporal variability of ambient air concentrations of SO2, SO4

2-, NO3 , 

HNO3, NH4

+

 and O3 obtained from the EPA Clean Air Status and Trends Network (CASTNet) 

was examined using an objective, statistically based technique called rotated principal 

component analysis. This analysis, which covered the period October 24, 1989, through August 

15, 1995, allowed for the identification and subsequent characterization of homogeneous 

influence regimes associated with each of the six species. This identification of homogeneity 

across sites has added to the weight of evidence supporting regionality of species behavior, 

which has historically been difficult to estimate and understand because of complicating 

meteorological and chemical factors. 

Depending on the species, either two (NO3

-

); three (SO2, SO4

2-, NH4

+

, O3); or four (HNO3) 

influence regimes were identified by the analysis. Examination of the temporal variability of 

these homogeneous influence regimes through time series and spectral analysis revealed various 

seasonal and annual cycles of differing strengths and timing. Examination of these differences 

30
 

facilitated understanding of both the meteorological and chemical atmospheric processes that are 

responsible for the regimes (Eder and Sickles, in press). 

This analysis provided evidence of, and considerable insight into, the regional-scale 

behavior of these species’ air concentrations, which suggests that exclusively local strategies to 

reduce their concentrations through reductions in emissions may be wholly inadequate without 

parallel management of regional emissions. Such region-wide, homogeneous patterns seen over 

the eastern United States will require interstate strategies for the reduction of these pollutants. 

2.2.6.5 NEXRAD Stage IV Data in the Multimedia Modeling of Pollutant Transport 

MIMS is being designed to model the cycling of pollutants and nutrients between the 

atmosphere and the earth’s surface, including water bodies and groundwater. The ability to 

accurately model both atmospheric, hydrological, and surface processes that transport chemicals 

is highly dependent on precipitation types, rates, and totals. Of special interest are precipitation 

extremes and subsequent flooding, which can greatly enhance the movement of such chemicals. 

During such events, these chemicals can enter the surface water bodies via groundwater recharge 

as well as overland flow. For example, the extreme 1999 flooding of North Carolina associated 

with Hurricane Floyd, transported tremendous amounts of agricultural and industrial waste and 

pesticides into area estuaries and rivers. This Hurricane, which followed Hurricane Dennis, 

inundated sections of eastern North Carolina with more than 20 inches of rain. 

During the development of MIMS, the use of the National Weather Service NEXRAD 

(NEXt generation RADar) Stage IV precipitation estimates in modeling efforts is being 

investigated. The NEXRAD Stage IV data consist of precipitation data fields that have 

assimilated both rain gauge data and WSR-88D (Weather Surveillance Radar 1988 Doppler 

Version) data into a comprehensive hourly, national data set with a 4-km2 resolution. The 

purpose of this research is to evaluate the quality and identify limitations of the NEXRAD data 

through a comparison with ground truth data obtained from a network of 10 closely spaced rain 

gauges. The evaluation will use visualization tools and statistical analyses to determine if the 

spatial resolution of NEXRAD data is adequate to capture the spatial variability of precipitation 

on the watershed that is used in the surface hydrology models associated with MIMS (Eder et al., 

accepted for publication). 

2.3 Modeling Systems Analysis Branch 

The Modeling Systems Analysis Branch supports the Division by providing routine and 

high performance computing support needed in the development, evaluation, and application of 

environmental models. The Branch is the focal point for modeling software design and systems 

analysis in compliance with stated Agency requirements of quality control and assurance, and for 

conducting research in the interagency Information Technology Research and Development 

(ITR&D) program (formerly High Performance Computing and Communications), which 

31
 
includes parallel processing, visualization, advanced networking, and information management. 

Under the ITR&D program, the Branch is developing a flexible multi-media environmental 

modeling and decision support tool to deal with multiple scales and multiple pollutants 

simultaneously; thus, facilitating a more comprehensive and cost-effective approach to related 

single- and multi-stressor human and ecosystem problems. 

2.3.1 Emission Modeling 

The principal development in emission processing capability during FY-2000 was the 

Personal Computer (PC) with Microsoft® WindowsTM NT®3

 release of Models-3 Version 4 during 

the summer of 2000. The Models-3 Emission Processing and Projection System (MEPPS) was 

enhanced and stabilized by testing and debugging. In addition, work continued on MEPPS 

replacement, the Sparse Matrix Operator Kernel Emission (SMOKE©)

4

 system. Specific 

developments included: 

•	 	 The Models-3 Version 4 release (June 30, 2000, for the NT port) updated the SunTM5 

UNIX®6 port of the system using the Solaris 2.7 operating systemTM7, and updated the 

aerosol portions (aerosols 2) of the chemical mechanism options. 

•	 	 The SMOKE processing system was extensively streamlined and modified for use in the 

Models-3 framework. SMOKE was initially developed as a prototype by the MCNCNorth Carolina Supercomputing Center in cooperation with the Division (Houyoux and 

Vukovich, 1999). Its sparse matrix approach to the repetitive computations using very 

large emission databases decreases processing time by at least an order of magnitude. 

SMOKE was modified for incorporation and compliance within the Models-3 framework, 

unlike MEPPS, which is a SASTM8

-based system that can only be semi-compliant and 

requires much more data file space. Substantial data handling and quality control 

capability will be added to SMOKE to make it fully functional in Models-3. In addition, 

3

Microsoft and Windows NT are registered trademarks of Microsoft Corporation; and NT 

is a registered trademark of Northern Telcom Limited. 

4

Copyright 1999 MCNC-North Carolina Supercomputing Center, Research Triangle Park, 

NC. 

5

Sun is a trademark of Silicon Graphics, Inc. 

6

UNIX is a trademark of AT and T. 

7

Solaris 2.7 operating system is a trademark of Sun Microsystems. 

8

SAS is a registered trademark of SAS Institute, Inc. 

32 
an input file quality control and file formatting tool (SMOKE Tool) is being developed 

because SMOKE cannot create its own input files and grids from diverse sets of raw data. 

•	 	 A software interface was developed to allow the use of the Pesticide Emission Model©9 

(PEM) with SMOKE, under an agreement between the Agency and Ortech International, 

Mississauga, Ontario, Canada, the developers of PEM. To be operational in Models-3, 

the Models-3 Meteorological Chemistry Interface Processor (MCIP) needs to be modified 

and soil and vegetation databases added. PEM will allow a user to model hourly episodic 

pesticide emissions on a regional basis, consistent with geographic grids, meteorology 

data, and soil and vegetation data. 

•	 	 MEPPS generated multiple emission data sets from July 2–18, 1995, for evaluation runs 

of CMAQ for spatial domains covering the eastern half of the United States and Canada. 

These emission data sets were produced at 36 km, 12 km, and 4 km, with some tests at 

1.3-km spatial resolution for both CB-IV and RADM2 lumped species model chemistry 

approaches. 

2.3.2 Biogenic Emissions 

The Branch continues to develop and test algorithms for simulating airborne emissions 

from natural and biogenic sources. These sources include hydrocarbons from vegetation, nitric 

oxide and ammonia from soils, nitric oxide from lightning, and ammonia from livestock 

operations. The algorithms will be integrated into the Biogenic Emissions Inventory System 

(BEIS), the third generation of which should be released during FY-2001. 

The basis for BEIS3 was reported in a NARSTO critical review article (Guenther et al., 

2000). BEIS3 will produce hourly, gridded emission fluxes for 34 chemical species, including 

14 monoterpenes. It is thought that this enhanced speciation will help in modeling the secondary 

formation of organic aerosols. Late in FY-2000, Division scientists began to incorporate BEIS3 

into the SMOKE emission modeling system. Testing of SMOKE/BEIS3 in CMAQ will begin 

during early 2001. 

A presentation at the Global Climate and Hydrology Center in Huntsville, Alabama, 

highlighted the possible importance of lightning-produced nitric oxide for regional air quality 

modeling (http://www.epa.gov/asmdnerl/biogen.html). A simulation with RADM indicates that 

lightning may contribute ~10 percent of total nitrogen oxide (NOx) emissions during the summer 

in the eastern United States. This finding could be important because lightning NOx is not 

explicitly included in most regional model simulations. 

9

Copyright to CGEIC ORTECH and licensed to users by Ortech International. 

33 
A web site was created to provide additional information on the Division’s biogenic 

emissions research, slides of presentations, and access to data and computer algorithms. The web 

address is http://www.epa.gov/asmdnerl/biogen.html. 

2.3.3 Improvements in Vegetation Cover Data 

Regional air quality models need accurate characterization of vegetation cover to estimate 

biogenic emissions and dry deposition. However, most satellite-derived data sets, while 

providing good spatial resolution, do not resolve vegetation species and crop types. Isoprene 

emissions vary among tree species, with extremely high emissions from oaks, but negligible 

emissions from maples. Division scientists have constructed a 1-km vegetation database for 

North America, called the Biogenic Emissions Land use Database (BELD3). The USGS1-km 

land-use/land-cover (LULC) data set derived from the NOAA Advanced Very High Resolution 

Radiometer (AVHRR) satellite imagery was coupled with forest inventory data from the U.S. 

Forest Service and the 1992 Agricultural Census. The 1990 Census was used to denote 

urbanized regions. Each 1-km pixel includes percent forest cover, percent crop cover, Federal 

Information Processing Standard code, and the USGS LULC class. In the United States, each 

pixel is further divided into tree species and crop types. This data set provides much greater 

spatial resolution than earlier county-based land-use data sets developed for biogenic emission 

calculations. It should provide a more accurate basis for vegetation-sensitive calculations for 

such regional air quality models as CMAQ. The data set can be accessed at 

http://www.epa.gov/asmdnerl/biogen.html. 

2.3.4 Technology Transfer 

The release of Models-3/ CMAQ version 4 for the PC with a WindowsTM NT® operating 

system occurred July 28, 2000. Installation is simpler on the NT® than on a UNIX® platform. 

An installation screen is used and installation uses CD-ROMs rather than tape. The version for 

the WindowsTM NT® port is distributed by the National Technical Information Service 

(http://www.ntis.gov/fcpc/cpn8867.htm) and may be ordered online. In addition, a stand-alone 

version (science algorithms, supporting processors, and tutorial input files, but without the 

Models-3 framework), was made available by anonymous ftp (ftp://ftp.epa.gov/amd). Although 

many sites have downloaded the stand-alone version, there is no exact count. It is known that the 

stand-alone version, which was provided to run on a Sun workstation, was adapted by the user 

community to execute on other UNIX® platforms, including SGITM10 and DECTM AlphaTM11. 

Models-3 documentation can be obtained at http://www.epa.gov/asmdnerl/models3. 

10SGI is a trademark of Silicon Graphics, Inc. 

11DEC and DEC Alpha are registered trademarks of Digital Equipment Corporation. 

34 
2.3.4.1 Visualization and Analysis Tools 

Models-3/CMAQ is distributed with visualization tools that are integrated into the 

framework, including recent versions of PAVE©12 (Package for Analysis and Visualization), 

available at http://envpro.ncsc.org/EDSS/pave_doc/Pave.html; and Vis5D©13, available at 

http://www.ssec.wisc.edu/~billh/vis5d.html. The IBM® DX7®14 , was not distributed with 

version 4. To use the visualization software in a Microsoft® WindowsTM NT® computing 

environment, the UNIX computing environment must be emulated using Microsoft© InterixTM15 

(http://www.interix.com/products/matrix.html). 

2.3.4.2 Models-3 Workshop 

A workshop was held in Arlington, Virginia, June 12-14, 2000. Over 200 attendees heard 

presentations of user experiences using Models-3/CMAQ along with evaluation results and plans 

for future direction. Part of the conference focused on the plan to establish and fund an 

institution that would provide Models-3/CMAQ support, develop and integrate new science, and 

assist in the transfer of the Models-3 technology to the air quality modeling community. The 

institution would be funded through a 4-year cooperative agreement with the intent of the 

institution becoming self-sufficient. Presentations from the workshop can be found at 

http://www.epa.gov/asmdnerl/models3/workshop/agenda.html. 

2.3.4.3 Models-3 Support 

A Help Desk was established for Models-3/CMAQ. The Help Desk has a support 

structure consisting of a collection of individual scientists to answer user questions in specific 

areas. The telephone number for the Help Desk is 919-541-0157. The Models-3/CMAQ website 

(http://www.epa.gov/asmdnerl/models3/) was expanded to provide user support for a stand-alone 

version, i.e., without the Models-3 framework. These codes may be downloaded and adapted to 

execute on any computing platform. The downloaded files contain code that ingests the data sets 

for a second tutorial designed to use the CB-IV chemical mechanism. The web site also contains 

12Copyright1997-2000 MCNC North Carolina Supercomputing Center, Research 

Triangle Park, NC. 

13Copyright1990-1999 W. Hibbard, J. Kellum, B. Paul, D. Santek, and A. Battaiola. 

14IBM is a registered trademark of the International Business Machines Corporation. IBM DX Visualization Data Explorer is a registered trademark of International Business 

Machines Corporation; Open-source availability starting May 26, 1999. 

15Interix is a trademark of Softway systems, Inc. 

35 
Model Change Bulletins where known problems with the system are listed along with the 

instructions to solve the problem. Models-3 Public Forum area was established on the SCRAM 

(Support Center for Regulatory Air Models) web site (http://www.epa.gov/scram001). This area 

provides a central location for the discussion of issues related to the operation and use of 

Models-3. A listserv®16 was established to which Models-3 users can subscribe and 

communicate with others by sending messages to m3list@tempest.rtpnc.epa.gov. 

2.3.4.4 Computing Platforms for the Models-3 Framework 

The Models-3 framework was released only for SunTM workstations and Microsoft® 

WindowsTM NT® operating system. The framework has encountered problems with performance 

and licensing of OrbixTM17, a commercial software component of the framework supporting 

distributed applications using object-oriented client-server technology. Future development of 

Models-3 framework will be directed away from the use of products that require licensing fees to 

the runtime user. The science code can be run on a number of machines and operating systems, 

including SunTM, DECTM AlphaTM, Cray® C90TM, Cray® T3ETM18, SGITM, and Microsoft® WindowsTM 

NT®. 

The scientific evaluation of CMAQ is being done on multiple computing platforms 

through the Models-3 framework. The modeling of emissions with MEPPS is being done on Sun 

workstations, and the MM5 simulations are being done on a Cray® C90TM. CMAQ runs on a 

Cray® T3ETM with the initial and boundary conditions being executed on either a Sun workstation 

or a Cray® C90TM. Fortran 90 is used with the releases in FY-2000. The Fortran source code for 

the science modules is the same for multiple computing platforms, and is recompiled and linked 

on the host machine to create an executable for the specific host hardware. The use of a single 

scientific source code simplifies the management and maintenance of the software. 

2.3.5 Cross-Platform Implementation of CMAQ Chemistry-Transport Model 

Hundreds of CMAQ model runs are required, demanding rapid turnover for model 

evaluation, sensitivity studies, and other applications. The only computing platform that can 

meet the requirement is the Cray® T3ETM, a distributed memory, high performance parallel 

computer. To take advantage of its performance capabilities, CCTM, ECIP, and ICON were 

modified to run in parallel. The modifications are sufficiently general, using a standard 

16Listserv is a registered trademark licensed to L-Soft International, Inc. 

17Orbix is a registered trademark of IONA Technologies Ltd. 

18Cray is a registered trademark and Cray C90 and Cray T3E are trademarks of Cray 

Research. 

36 
message-passing protocol that can run on any distributed memory architecture, including 

workstation farms or PC clusters. 

The parallel implementation developed for CMAQ requires a horizontal grid domain 

decomposition involving near-neighbor communication (data transfer between adjacent 

processors) and file input/output (I/O) with data redistribution depending on processor 

location in the domain decomposition. The I/O is built on top of (layered on) the Models-3 I/O 

application programming interface. To manage and simplify the near-neighbor communication 

from the user's point of view, a stencil exchange library was developed that contains data 

communication calls, which can be inserted in the code. 

The code modifications from the serial version necessary for the parallel version are not 

trivial, and the issue of code maintenance and control demanded a solution to the problem that 

arises from maintaining the same essential science algorithms, but implemented on different 

architectures. The solution developed for CCTM consists of: 

•	 	 A single source code that contains a few precompiler options that are selected for 

execution on either serial or parallel platforms; 

•	 	 The use of parallel I/O and stencil exchange libraries linked in at the load step during 

code compilation; 

•	 	 Additions to existing Fortran including files containing the horizontal grid parameters 

associated with the domain decomposition; and, 

•	 	 Additional pre-compiler directives to select the appropriate stencil exchange and parallel 

I/O functions during the compile phase. 

To simplify the compilation and linking for different platforms, UNIX®9 C Shell scripts were 

developed, and the monocode was successfully tested on the Cray® T3ETM and Cray® T3DTM, the 

Cray® C90TM, SunTM and SGITM workstations, and PC WindowsTM NT® 

2.3.6 Multimedia Integrated Modeling 

The Branch is involved in a long-term project to develop a Multimedia Integrated 

Modeling System (MIMS). The MIMS software framework is being designed to 

comprehensively simulate the cross-media transport and fate of nutrients and chemical stressors 

over multiple and disparate scales. This system will provide a computer-based problem solving 

environment for studying such multimedia (atmosphere, land, water) environmental problems as 

over-loading of nutrients to aquatic ecosystems, which can result in anaerobic conditions and fish 

kills. As a test case, a multimedia model prototype is being designed to simulate the 

atmospheric, surface, and subsurface loading of nitrogen and the resulting effects on aquatic 

ecosystems and water quality of the Neuse River Estuary. The MIMS framework will provide 

37
 

advanced tools to build, couple, and execute the individual process models; to coordinate the 

transfer of data between these models; and to visualize and analyze results. 

The MIMS architecture design team was formed in FY-2000 and includes members from 

the Branch, EPA, and contractors. The team identified goals and desirable attributes for the 

MIMS framework, a software infrastructure for constructing, composing, executing, and 

evaluating cross-media models. The team also identified MIMS stakeholders and considered 

how MIMS might help them better accomplish their work. Based on that information, the team 

developed a draft MIMS software architecture, which it reviewed with interested groups. The 

architecture team explored technologies that could be used to implement the framework, 

including languages, object databases, and other modeling frameworks. The team decided that 

the framework will be implemented in Java, which is portable across platforms and often allows 

software to be developed with less effort than languages such as C and C++. The team is 

considering the use of the Dynamic Information Architecture System (DIAS), which was 

developed by Argonne National Laboratory, Argonne, Illinois. DIAS provides a paradigm and 

tools for coupling diverse models, including models that simulate physics, chemistry, and 

behaviors. 

In parallel with the framework design is the design and initial development of a 

multimedia modeling prototype for the Neuse River Estuary. This is being coordinated by the 

Branch as follows: 

•	 	 Upscaling of a spatially-explicit hydrology and nutrient cycling model (RHESSys or 

Regional Hydro-Ecological Simulation System). RHESSys was tested successfully at a 

variety of watersheds in past studies, and is being set up for several small instrumented 

watersheds within the Neuse River Basin. Because the spatially explicit approach may 

not be practical for the entire Basin, one or more approach(es) will then be suggested for 

upscaling RHESSys for the entire Neuse. The benefit from the spatially-explicit 

approach of RHESSys is that the regulatory modeling approaches cannot resolve the 

impact from localized (i.e., sub-grid) land-use or vegetation changes (i.e., riparian buffer 

zones) on nutrient loading. Sensitivity tests for such changes could help identify effective 

solutions when considering environmental management decisions. 

•	 	 Coupling of a surface hydrology and meteorology model (MM5) to simulate the dynamic 

land-atmosphere flux of energy and moisture. This work is being extended to a small, 

instrumented watershed within the Neuse River Basin for testing. 

•	 	 NWS NEXRAD (NEXt generation RADar) precipitation estimates will be provided in 

the MIMS system for a more accurate representation of precipitation than typically 

available from meteorological models on watershed scales. 

38
 

•	 	 The Surface Water Object-Oriented Modeling System (SWOOMS) is being developed 

under an EPA grant for the Neuse River Estuary. SWOOMS will be able to simulate the 

hydrodynamics and water quality conditions that were correlated with fish kills in the 

Neuse River Estuary. The SWOOMS development began in FY-2000 and will be 

completed in FY-2003. The MIMS project is closely coordinated with this grant. 

•	 	 Airborne ammonia emissions are a multimedia issue because the impact of such 

atmospheric conditions as temperature can affect the emission flux. However, emission 

inventories only provide annual estimates. For this reason, an inverse modeling study is 

underway to provide improved estimates of seasonal ammonia emissions, which should 

improve the air quality model’s predictions of atmospheric deposition of nitrogen 

compounds for MIMS. 

These efforts are being coordinated for incorporation into the MIMS multimedia model 

prototype. Annual workshops were held to bring EPA grantees together with MIMS researchers. 

In addition, a smaller working group was formed to meet on a quarterly basis for planning and 

review. 

2.4 Applied Modeling Research Branch 

The Applied Modeling Research Branch investigates and develops applied numerical 

simulation models of sources, transport, fate, and mitigation of air toxic pollutants in the near 

field and conducts research to develop and improve human exposure predictive models, focusing 

principally on urban environments where exposures are high. Databases are assembled and used 

for model development and research on flow characterization, dispersion modeling, and human 

exposure. Using the Fluid Modeling Facility (FMF), the Branch conducts simulations of 

atmospheric flow and pollutant dispersion in complex terrain, in and around such obstacles as 

buildings, in convective boundary layers and dense gas plumes, and in other situations not easily 

handled by mathematical models. 

2.4.1 Remote Sensing 

Large scale assessment of land use and ecological health is feasible only with remote 

sensing methods. One of the physical variables characterizing a landscape is its spectral albedo, 

or reflectance. The EPA Change Detection program is developing methodologies to extend 

remote sensing techniques to quantitative ecological assessments using NASA's Airborne Visible 

and Infrared Imaging Spectrometer (AVIRIS). The AVIRIS instrument is a nadir-looking 

spectral radiometer that measures upwelling radiance [W/m2/sr/nm] in 224 bands (nominal 10 

nm bandwidth) from 370 nm to 2510 nm, with a spacial resolution of 20 m. It is typically 

mounted aboard a converted U2 Air Force aircraft and flown at altitudes of up to 20 km above 

sea level. Geo-coded images permit atmospheric correction by comparing an AVIRIS absolute 

radiance with co-located ground-truth reflectance spectra. The MODTRAN (MODerate 

39
 
resolution TRANSmittance) radiative transfer model was employed for this task, calculating 

upwelling radiance for atmospheric conditions and geodesic configuration prevailing at the time 

of overflight. The lower Neuse River Basin is the first in a series of regions that will be 

characterized with respect to its land use and ecological state by the spacially-resolved 

reflectance (Figure 2). 

Figure 2. Modeled and measured radiance spectrum of the flood plain in the Neuse River 

Basin, and component contributions from atmospheric backscatter and ground reflectance. 

2.4.2 Relating field-Scale Wind Blown Fugitive Dust Measurement to Large Scale Vertical 

Dust Flux 

Work began on comparing measured concentrations of PM10 from fugitive dust sources to 

dust emissions from unpaved roads. A model of the diffusion and deposition of fugitive road 

dust was used. The model was presented at the Western Regional Air Pollution Expert Panel 

meeting in Ventura, California, on September 12-13, 2000 

(http://www.wrapair.org/commindex.htm). 

40
 
A lumped control volume approach was used to consider dust generated from a road 

surface. Two-dimensional symmetry, conservation of mass, and steady state conditions were 

assumed. A control volume was specified where none of the road dust passes through the control 

volume ceiling immediately above the road and is long enough for the flux of dust upwind of the 

road to be equal to the flux of dust through the downwind wall of the control volume. The 

equations for mass conservation, vertical diffusion through the ceiling of the control volume, and 

deposition at the floor of the control volume were solved. Equation 1 gives the dimensionless 

ratio M of the vertical flux of fugitive dust transported in a regional scale model to the microscale 

vertical dust flux: 

(1)
 


The ratio given by Equation 1 can be approximated using data from Gillette (1974) 

showing K = 0.08u* , where u* is friction velocity. Values for Vd versus size and environmental 

conditions are given by Slinn (1982). The resulting dimensionless values for M express the ratios 

of regional-effective fluxes of PM10 to the microscale vertical fluxes of PM10 at the source. 

The expression given in Equation 1 partially explains why observed concentrations of 

PM10 produced by road dust are smaller than predicted by large grid-scale models. Large-scale 

models do not presently correct for local scale deposition, but rather use the entire amount of dust 

emitted by roads. Because dust is deposited to the surface close to the source, dust vertical fluxes 

not corrected by the ratio M lead to overestimates of dust concentrations downwind of the source. 

Other expected effects are: 

•	 	 Large-scale vertical flux of dust would be a very large fraction of field-scale flux of wind 

erosion dust from road surfaces. 

•	 	 Dust devils should be considered effective sources of dust because dust devils have a high 

height of initial dust input, and M for dust devils should be close to one. Gillette and 

Sinclair (1989) describe dust devil dust fluxes. 

2.4.3 Fugitive Emissions from Supply-Limited Sources 

Wind erosion mechanisms were investigated for the scrape site at the Jornada 

Experimental Range in the Chihuahuan desert near Las Cruces, New Mexico. The scrape site 

was denuded of vegetation and scraped flat in 1991. Three meteorological towers, each 2 m in 

height, with wind speed sensors at 0.2, 0.5, 1.0 and 2.0 m above ground; air temperature at 0.2 

and 2 m height; rain gage; seven sets of particle collectors at 0.1, 0.5, and 1.0 m heights; and 

three fast-response particle mass flux sensors at 0.02, 0.1, 0.2, and 0.5 m heights were installed 

and operated for a period of 35 months along a transect crossing the site and parallel to the 

predominant southwesterly wind direction. The minimum threshold friction velocity for the 

41
 

scrape site with a thin layer of loose material was 25 cm s-1. This minimum threshold velocity 

increased to as high as 100 cm s-1, depending on the degree of particle depletion and the site's 

status that varied between supply-unlimited just after a high-wind episode, and the more typical 

supply-limited. Sandblasting of the surface crust was the dominant mechanism producing fresh 

sediment for transport. The measurements showed that supply and availability of loose, fine 

particles on the surface is the predominant control of erosion rates rather than wind energy. 

By measuring the horizontal sand flux, friction, and threshold friction velocities at three 

points on the Jornada scrape site, the sand flux could be related to the maximum potential flux, 

i.e., the sand flux from a crust-free and vegetation-free surface with thick deposits of loose sand 

for the same winds. This approach using potential flux was derived from wind and sand flux 

measurements at Owens Lake (Gillette et al., in press) for a thick layer of loose sand and no 

surface crust, i.e., a supply unlimited surface. The potential sand flux was calculated by using 

the friction velocity of the wind and the threshold friction velocity. The difference between the 

actual sand drift and the potential sand drift is a measure of the effect of particle supply 

limitation. 

Transport of sand from the scrape site was estimated based on the assumption that the 

direction of transport is to the northeast, which is the dominant wind direction for strong winds. 

It was further assumed that the source of new sand on the scrape site is abraded material from the 

crust. With these two assumptions, a simple model of transport of sand from the scrape site was 

developed. For large abrasion events, the amount of sediment cleared by wind transport is larger 

than for smaller events, but it is significantly smaller than particle production. Consequently, in 

months following a large abrasion event, there is still significant southwest-northeast sediment 

removal even if no new abrasion is taking place. This result would explain the observations that 

there were variable thicknesses of loose sand over time on the surface crust. Newly formed 

thick layers of sand would act like supply-unlimited sources. Eventually a thick layer of sand 

would be depleted by transport in the northeast direction. At some point during the removal 

stage the transport becomes more supply limited. 

When the surface was covered by a thin layer of loose particles of one or more 

millimeters in size, the transport of sand from the surface by winds slightly over the threshold 

friction velocity would deplete the surface of loose material. However, winds strong enough to 

abrade the surface by sandblasting would supply the surface with fresh loose material. This 

abrasion mainly occurred in a few episodes above a threshold of about 100 cm s-1 that were 

capable of transporting particles larger than 400 :m. The data showed that the observed 

transport rate is not as fast as the particle production for periods of large abrasion. However, for 

the 35 months of the experiment, transport was sufficient to remove most of the fresh material 

produced by sandblasting within about a month. 

42
 

2.4.4	 Resuspension of PM10 Particles from Grass 

Past research on the production of PM10 by the wind has shown that the dominant, but not 

the only, mechanism is the transfer of kinetic energy to the surface by particles larger than 50 

micrometers. The mechanism known as sandblasting by saltating grains utilizes sand-sized 

particles that are entrained by wind speed lower than those needed to entrain PM10 particles 

directly. Since the sand-sized particles are only airborne for short periods of time, the collision 

with loose and bound PM10 particles on the surface provides the primary energy transfer needed 

to produce the PM10 particles. Research is underway to develop a detailed understanding of the 

mechanisms of resuspension from vegetation surfaces and to develop a mechanistic model to 

describe these processes. In previous years, a methodology was developed to quantify the 

conversion of wind energy to the mechanical energy of impaction and rubbing of a single grass 

blade. An instrument was found that gives linear response to kinetic energies from both rubbing 

motions and impaction of 10-9 joules to 10-7 joules. Wind tunnel experiments were conducted to 

test the quantity of PM10 produced by impaction and rubbing of a grass blade. Turbulence 

characteristics in the wind tunnel were established using turbulence grids. A wheat grass was 

used along with a Grimm aerosol size distribution analyzer to test downwind aerosol 

concentrations of known-size polystyrene latex particles that were deposited on the surface of a 

grass blade. Following the analysis of this experimental work, models will be built for the 

resuspension of PM10 from surfaces that are bare or covered by vegetation. 

2.4.5 Wind Tunnel Measurements of Mean Flow and Turbulence in an Array of TwoDimensional Buildings 

A laboratory study of the complex flow patterns within an array of two-dimensional 

buildings simulating the flows that might be found in a cross-street flow over a number of blocks 

in an urban area was conducted in the meteorological wind tunnel at the FMF. Aside from using 

the study data for improving the understanding of the fundamental physics of airflow in urban 

environments, FMF collaborated with Los Alamos National Laboratory, Los Alamos, New 

Mexico, and Lawrence Livermore National Laboratory, Livermore, California, to utilize the 

study data for improving computational fluid dynamics models of flow and dispersion in urban 

and industrial areas. Previous annual report entries (Poole-Kober and Viebrock, 1999) 

describing this long-term project have discussed a series of flow visualizations and surface 

pressure measurements on the buildings. Here the focus is on the mean velocity and turbulence 

measurements. 

Each of the seven buildings, with height (H) and downwind dimension equal to 15 cm, 

spanned the width of the tunnel. The buildings were each separated in the downwind direction 

by one building height. High resolution measurements of the three components of mean and 

turbulent velocities were obtained around and above the array of seven two-dimensional 

buildings. Although the literature contains descriptions of a fairly abundant number of flow and 

tracer experiments performed around single buildings (e.g., Meroney, 1982; Hosker, 1984; Lee et 

al., 1991; and Snyder and Lawson, 1994), relatively few wind tunnel measurements of mean flow 

43
 

and turbulence intensities within the street canyons and above the buildings have been carried out 

for multi-building arrays (e.g., Roth and Ueda, 1998; Davidson et al., 1996). This study was 

designed to supplement these limited studies with high density measurements of mean flow and 

turbulent kinetic energy. 

The approach flow to the building array was a simulated neutral atmospheric boundary 

layer of a depth of approximately 12 H with sufficient upwind fetch to grow to equilibrium 

before reaching the upwind edge of the buildings. The approach flow at z = H was 3 m/s 

ensuring that Reynolds number independence was satisfied. Measurements of the three 

component velocities and the turbulence intensities were obtained with pulsed-wire anemometry 

(Bradbury and Castro, 1971). Measurements on the longitudinal centerline of the building array 

were collected from 3.5 H upstream to 7.5 H downstream of the building arrays and up to 3 H in 

the vertical. Figure 3 shows the mean wind vectors and the turbulent kinetic energy (tke) around 

and upstream of the first three buildings. Close inspection reveals a rotor that forms on the 

upwind face of the first building. More obvious are the single large vortices that form within 

each building canyon. Of particular interest is the separation zone and reverse flow that forms on 

the rooftop of the first building but not on subsequent rooftops. This agrees with smoke 

visualization studies and those of Meroney et al. (1996). Additionally, the streamlines above and 

just upwind of the leading edge of the second building are descending slightly, resulting in 

stronger downward motion in the first canyon vortex circulation compared to those in subsequent 

canyon circulations. Figure 3 also shows a large tke maximum at the leading edge of the first 

building’s rooftop and an envelope of large tke values extending above the first two buildings but 

dying out quickly with downwind distance. The region of highest turbulence above the first 

building is correlated with a region of strong shear in the flow. 

Figure 3. Wind vector and turbulent kinetic energy fields measured along the centerline of an 

array of buildings. The first three of seven buildings are shown here. 

44
 

2.4.6 Meteorological Measurements 

Local meteorology is a key factor in both diurnal and day-to-day changes in the ambient 

pollution concentration levels affecting human exposure. Routine meteorological models can 

provide gridded data for the entire United States, but the resolution of the grid is not always 

sufficient for determining local meteorology in support of human exposure modeling. Similarly, 

routine meteorology measured at airports or other stations is only representative of the 

surrounding area. The Meteorological Instrumentation Cluster of 3 Trailers (MIC3) is being used 

to support site specific field studies of human exposure to better identify meteorological factors 

related to human exposure to air pollutants. The three trailers presently include (See Figure 4): 

•	 	 AV Model 2000 SODAR19: 

Wind (3D) measurements from 60 m to 600 m (30 m intervals, 10 minute average). 

Portable but AC connection required. 

•	 	 AV Model 4000 miniSODAR: 

Wind (3D) measurements from 15 m to 200 m (5 m intervals, 5 minute average). 

Portable with battery operation for 3-4 days (or AC continuous). 

•	 	 10 Meter Tower: 

Wind (2D) measurements at 2, 5, and 10 m (5 minute average). 

Temperature and humidity measurements at 2 and 10 m (5 minute average). 

In addition, these measurements of local meteorology near the surface will be used to 

develop and evaluate a local scale meteorological modeling system for general application in 

support of human exposure modeling. Measurements may be retrievable in real time. 

Cooperative research is ongoing with the North Carolina Climate Office, Raleigh, North 

Carolina, in examining local meteorology models, including CALMET diagnostic model and the 

ARPS (Advanced Regional Prediction System) forecast model supported by measurements from 

the MIC3 as well as measurements at Raleigh-Durham Airport, Morrisville, North Carolina, and 

four other surface 10 m towers. Pilot studies are ongoing in the Research Triangle Park, North 

Carolina area. MIC3 started collecting data within the Research Triangle Park area when the 

equipment became operational in March 2000. Figures 5 and 6 display measurements observed 

for a typical clear summer day. Figure 5a displays the digital facsimile analysis (DFS) from the 

Model 2000 SODAR. After midnight the temperature difference corresponds to a slightly stable 

surface layer. The DFS data place the stable boundary layer below 100 meters. After sunrise at 

0800 LT, the static stability becomes unstable in response to surface heating. Late afternoon 

around 1800 LT the static stability becomes stable once again. At this point, the boundary layer 

quickly collapses to about 130 meters. It is worth noting that some echoes remain above the 

boundary layer after sunset. These are believed to be due to diminishing turbulence in the 

19SODAR: Sound Detection And Ranging 

45 
Figure 4. The Meteorological Instrumentation Cluster of 3 Trailers used to 

support field studies of human exposure to air pollutants. 

46
 

residual layer. Tower wind speed measurements, shown in Figure 5b, have periodic variation 

throughout the day. Qualitatively, it appears that the sharp changes in wind speed may be related 

to the convective thermals. Wind speed diminishes near sunset, when the boundary layer 

collapses (1800 LT). 

The miniSODAR vertical wind speed profile is shown in Figure 6. During stable 

conditions, light winds at the surface increase quickly with height to the top of the stable 

boundary layer (SBL). It is noticed that a wind speed maximum exists (nocturnal jet) near where 

the DFS analysis places the SBL height (100 meters). During boundary layer growth this 

momentum is quickly mixed and the wind speed becomes nearly constant with height. When the 

boundary layer collapses during the late afternoon, the wind speed becomes light near the surface 

increasing again with height to the top of the SBL where another nocturnal jet is formed (130 

meters). 

2.4.7 Local Scale Modeling of Human Exposure Microenvironments 

A project to specifically improve the methodology for real-time site specific modeling of 

human exposure to motor vehicle emissions is ongoing. This project is being pursued in 

collaboration with other projects by EPA. The goal is to develop improved methods for 

modeling air pollution from the source through the air pathway to human exposure in significant 

microenvironments. Local-scale modeling refers to spatial scales from the size of an individual 

vehicle to the order of 1 km. A complete modeling framework from source-to-exposure together 

with some measurements is principally being set up in the Research Triangle Park area of North 

Carolina, which can be transferred to other locations. Human exposure models use simplified 

assumptions based on a few fixed air monitoring stations or modeled concentrations from 

regional-scale motor vehicle emission/transport models resulting in great uncertainty in their 

estimations. 

The first component of the modeling framework is real-time site-specific motor vehicle 

emission models capable of capturing real-world emissions. Development of a real-time 

Microscale automobile emission Factor model for Carbon Monoxide (MicroFacCO) was 

completed (Singh and Huber, 2000). Performance evaluation studies of MicroFacCO are 

ongoing. Development of a particulate matter version should be completed during 2001. This 

work demonstrates the application and sensitivity of emission estimates from these models to 

real-time input parameters for vehicle fleet composition, vehicle speed, and meteorological 

conditions. The emission rates calculated from these models can be used in conjunction with a 

roadway air dispersion model to estimate the ambient concentrations near roadways for a range 

of traffic fleet and meteorological conditions. 

47
 

Figure 5. (a) Digital facsimile profile from the Model 2000 

SODAR and temperature gradient between 2 and 10 meters on 

September 8, 2000. Sunrise (SR) and sunset (SS) are indicated. 

(b) Tower measured wind speed at 2, 5, and 10 meters. (c) 

Temperature at 2 meters and wind direction measured at 10 meters. 

Figure 6. Diurnal wind speed profile from the Model 4000 miniSODAR on 

September 8, 2000. Wind speed is smoothed with a 1-hour moving window. 

Legend to the right is in meters per second and height on the left is in meters. 

48
 
The second component will be a local-scale meteorological and air dispersion model to 

provide ambient air concentrations resulting from transport and other human activities. Refined 

modeling using Computational Fluid Dynamics (CFD) simulations and measurements are being 

applied to develop refined air dispersion models for linkage to a roadway microenvironmental 

model. This modeling framework will help to establish the direct relationships between sourceto-exposure concentrations specific to the particular exposure microenvironment (e.g., standing 

by the roadside or actually inside the vehicle, inside the moving vehicle, living nearby a 

roadway). Output from this deterministic modeling of microenvironmental concentrations and 

measured microenvironmental concentrations for a range of scenarios will be used to develop 

distributions of potential exposure that is probabilistically-based to support population-based 

human exposure modeling. 

Figures 7 and 8 provide two examples of CFD simulation models that were set up for 

evaluation. CFD simulations provide opportunities for expanding and improving capabilities for 

modeling exposures to environmental pollutants. A cooperative research project with Fluent, 

Inc., is examining and evaluating the application of CFD models for simulating air pollution 

along the pathway from source to human exposures. The detailed spatial resolution of 

environmental pollution concentrations that is possible from CFD simulations can provide 

important information that is not available from a single point measurement. Output of CFD 

simulations can be used to develop better simplified modeling methods in the same way as field 

and wind tunnel study measurements are used. Through further research, validation and testing, 

CFD modeling has the potential to become a reliable tool for estimating pollutant concentrations 

for situations that today have no reliable modeling method. 

Figure 7. Example of simulation of the wind over Manhattan. 

49 
Figure 8. Example of CFD simulation of airflow between two moving vehicles 

and consequences of leading vehicle tailpipe emission. 

2.5 Air Policy Support Branch 

The Air Policy Support Branch supports the activities of the EPA Office of Air Quality 

Planning and Standards (OAQPS). The Branch responsibilities include evaluating, modifying, 

and improving atmospheric dispersion and related models to ensure adequacy, appropriateness, 

and consistency with established scientific principles and Agency policy; preparing guidance on 

evaluating models and simulation techniques that are used to assess, develop, or revise national, 

state, and local pollution control strategies for attainment and maintenance of National Ambient 

Air Quality Standards (NAAQS); and providing meteorological assistance and consultation to 

support OAQPS in developing and enforcing Federal regulations and standards and assisting the 

EPA Regional Offices. 

50
 

2.5.1 Modeling Studies 

2.5.1.1 Air Quality Assessment of Heavy-Duty Engine/Vehicle and 	Highway Diesel 

 Fuel Rulemaking 

Section 202(a)(3) of the Clear Air Act (CAA) requires EPA to set standards for heavyduty trucks that reflect the greatest degree of emission reduction achievable through available 

technology. Section 211(c) of CAA allows EPA to regulate fuels in those instances where the 

emission products of the fuel significantly impair the performance of any emission control 

device. Based on these two sections of CAA, EPA proposed new regulations to reduce PM and 

NOx emissions from heavy-duty vehicles. 

A substantial air quality modeling analysis was performed in FY-2000 to assess the need 

for the rulemaking and estimate the benefits of the proposed emission reductions. The modeling 

was closely patterned after the Tier 2/Low Gasoline Sulfur analyses that were successfully 

completed in FY-1999. A base-year emission inventory was developed for 1996 and projectionyear inventories were created for 2007, 2020, and 2030. The proposed heavy-duty engine (HDE) 

emission reductions were then applied to the 2020 and 2030 cases. Air quality modeling was 

performed for six scenarios: the base year, three-future year baseline scenarios, and two futureyear control scenarios. 

The ozone modeling was conducted using the variable-grid version of the Urban Airshed 

Model (UAM-V). Ozone was simulated over two large regional domains, one covering the 

eastern United States from the Plains States to the East Coast, and the other covering the 

remaining lower 48 states to the West Coast. For the eastern domain, three multi-day periods of 

high observed ozone during the summer of 1995 were selected for the analyses. The 

meteorological data used to drive the eastern United States UAM-V modeling were obtained 

from applications of RAMS. For the western domain, two multi-day periods of high observed 

ozone during the summer of 1996 were selected for the analyses. The meteorological data used 

to drive the western United States UAM-V modeling were obtained from applications of MM5. 

The ozone modeling results were evaluated against existing ambient ozone data to assess the 

quality of model performance. In general, the eastern United States application featured 

relatively small values of model bias and error (i.e., less than 10% bias, less than 25% error), 

whereas the western United States simulations consistently underestimated observed ozone by 

large amounts with a bias of about 40%. Ultimately, only the eastern United States modeling 

results were used to justify and quantify the effects of the rulemaking. 

The modeling runs indicated that in many metropolitan areas continued exceedances of 

the ozone NAAQS were possible in the future years of 2007, 2020, and 2030. It was estimated 

that 35-45 areas in the United States (128 million people) were at risk of exceeding the ozone 

standard sometime between 2007 and 2030. While the HDE emission reductions would not 

eliminate all of the projected exceedances in the future, the modeling results indicated that 

ambient ozone levels would be significantly lowered. In 2020, the domain-wide average daily 

peak 1-hour ozone value was reduced from 81.0 to 78.2 ppb for the episode days. In 2030, the 

51
 

average daily peak value was estimated to drop from 83.1 to 79.3 ppb when the HDE fleet is 

almost fully turned over, but overall emissions are rising. 

Simulations to estimate the impacts of the proposed HDE regulations on PM were 

obtained using the Regulatory Modeling System for Aerosols And Deposition (REMSAD). This 

model was applied for the 1996 base case and 2030 baseline and control scenarios for the entire 

year of 1996 at a 36-km resolution. The meteorological data were generated using MM5. The 

results of these simulations are being analyzed and interpreted to quantify the expected benefits 

of the HDE NOx and PM reductions. The full suite of ozone and PM modeling results will 

provide the air quality basis for the regulatory impact analysis portion of the HDE rulemaking, 

which is to be signed by the EPA Administrator by the end of 2000. 

2.5.1.2 CMAQ Proof of Concept: Western United States Ozone Modeling 

As part of a proof-of-concept effort designed to more fully understand the details of the 

Models-3/CMAQ modeling system, Models-3/CMAQ was configured and successfully applied 

for a July 1996 ozone episode over the western United States. The simulations were completed 

for a 36- and 12-km nested grid with 12 vertical layers. The meteorological input fields were 

developed using MM5 and the emissions were based on a version of the national emissions trend 

inventory. 

Several configurations of CMAQ were compiled and executed, and several diagnostic 

simulations were completed, before a successful base case simulation was achieved. In 

particular, the modeling applied two different chemical solvers and tested the effects of a plumein-grid algorithm. One solver (Hertel) was found to be significantly faster than the other solver 

(QSSA), yet yielded comparable results. Although the faster solver is still being evaluated, it is 

particularly appealing for large-scale CMAQ applications because of its greater computational 

efficiency. The CMAQ PinG algorithm was successfully applied for 100 point sources and 

generated results comparable to other PinG approaches. 

A limited model performance evaluation, consisting only of surface ozone comparisons, 

was conducted for one of the base cases. Underestimations of ozone were prevalent, with a mean 

bias of about -23 percent. Although CMAQ predictions were relatively accurate in the eastern 

portions of the domain (e.g., Denver, Albuquerque, and Salt Lake City), they were significantly 

lower than observations in the urbanized portions of California. Comparisons of CMAQ 

statistical performance results with those from a past UAM-V application for the same domain 

and episode showed somewhat better model performance within CMAQ. It is suspected that the 

causes of the under predictions in both exercises are due to underestimated motor vehicle and 

biogenic emission inventories. Work is underway to investigate the causes of the under 

predictions of ozone. 

52
 

2.5.1.3 Statistical Evaluation of Model Performance 

Within the American Society for Testing and Materials (ASTM) a Standard Guide 

(Z6849Z ) is being developed to provide guidance on construction of objective statistical 

procedures for comparing air quality simulation modeling results with tracer field data. Thus far, 

those most involved in the development of this ASTM Guide have been scientists within the 

European community, where there is still strong interest in short-range plume and puff dispersion 

models. To focus the discussion, a draft evaluation procedure was constructed that measures 

how well short-range dispersion models characterize the variation of the centerline maximum 

concentration at the surface as a function of transport distance and stability. The draft ASTM 

Guide was circulated for review in July 2000. Editorial changes are being addressed. The Guide 

will be resubmitted for approval in early 2001. 

2.5.1.4 The Krakow Urban Air Pollution Project 

Local urban air pollution, including pollution from mobile sources, was recognized by the 

Environment for Europe Ministerial Conference as an area of high priority for the countries of 

the region. The EPA and Polish Ministry of Environment made this environmental problem one 

of six focal points for their cooperation. By focusing on the City of Krakow, this project seeks to 

build upon five years of cooperation between Poland and the United States. in improving the air 

quality in the Krakow Metropolitan Area. The Krakow Urban Air Pollution project, under the 

sponsorship of the U.S. Agency for International Development, will assist local authorities to 

identify, quantify, and develop mitigation strategies for the control of air pollution in the City of 

Krakow, primarily from the transportation sector. 

This project builds on the EPA Office of International Activities work in the Krakow 

area, which assisted in the identification, quantification, and dissemination of air pollution 

information in Krakow, primarily from stationary sources and low-level emitters. At the heart of 

this project is the task of training local staff to conduct air quality modeling studies. This would 

allow the local authorities to assess their air pollution problems caused by the increase in mobile 

source pollution, while establishing a basis for more informed national decision-making through 

the use of improved data, improved analytical tools, and transportation control options. 

Following the initial training course in December 1998, a series of training sessions were 

scheduled over the following 18 months. This allowed the students to first learn the basics, and 

then gradually allowed hands-on training in the initial application of the modeling system to 

characterize pollutant impacts in the Krakow area. In May 2000, a training session was held in 

Krakow to review the procedures to be used in processing the meteorological data, and to 

initially review the just completed emission inventories. Based on a series of test runs, the 

modeling team began to suspect that the home heating sulfur-dioxide emissions appeared to be 

too high. Refinements in the characterization of land-use (pattern of surface roughness lengths 

and urban versus rural land-use) and emission characterizations (initial release heights and initial 

53
 

dilution volumes) were decided upon. A final training session will take place in November 2000, 

as well as a review of the test runs the students completed over the summer months. 

2.5.1.5 Improvements to the Regulatory Modeling System for Aerosols and 

Deposition 

In coordination with the EPA Office of Water, a review was conducted of REMSAD, and 

a number of errors and deficiencies in the model and several of the accompanying data sets were 

identified. The appropriate corrections to the model and data sets were determined and 

implemented. An MM5 to REMSAD conversion program was developed to provide the 

interface for using MM5 meteorological outputs to derive the specific meteorological inputs 

needed to run REMSAD. This interface was run to obtain 1996 36-km meteorological inputs for 

REMSAD. The 1996 36-km data represented a major scientific improvement to the previous set 

of meteorological inputs, which were derived from 80-km MM4 runs for 1990. 

In addition, several components of the REMSAD emission pre-processor were revised, 

reducing the time needed to process a set of annual emissions from two weeks to four days. With 

the model corrections, emission data from the revised processor, and the improved 

meteorological inputs, REMSAD was used to generate six policy-relevant emission scenarios. 

This version of REMSAD is being studied by the EPA Integrated Strategies and Economics 

Group as a quick turnaround PC-based screening tool to provide estimates of PM concentrations 

in support of cost-benefits analyses. 

2.5.2 Modeling Guidance 

2.5.2.1 Support Center for Regulatory Air Models 

During FY-2000, several activities were accomplished by the SCRAM (Support Center 

for Regulatory Air Models) web site manager. An extensive testing and checking operation was 

developed to ensure that all of the air quality models and programs were Y2K compliant. 

Changes made involved contract support as well as in-house resources. To make the SCRAM 

documents more universally accepted by all printers, the documents were converted from 

WordPerfect to PDF format. For the first time, presentations made at the Regional, State, and 

Local Modeler’s Workshop were provided via SCRAM. Due to potential security breaches, the 

EPA Enterprise Technology Services Division provided upgraded and more extensive firewalls 

to prevent security infractions from outside Internet connections. However, there were no 

security breaches encountered on the SCRAM website. There were a total of 41 activities (new 

items, updates, revisions, etc.) logged during FY-2000. 

54
 

2.5.2.2 Models-3 Help Desk 

The Models-3 Help Desk is an initiative to provide full-time assistance to Models-3 

users, during both installation and model application. Models-3 is a multiscale air quality model 

that provides modeling in a one-atmosphere environment using a graphical user interface based 

framework, accounting for such processes as chemistry and aerosol interactions, and providing 

graphical and tabular output. A formal support network comprises the Help Desk with capable 

and accessible technical experts knowledgeable in the different modules and scientific processes 

that are performed within the model. During FY-2000, the Models-3 Help Desk responded to 

various users from Regional and State environmental offices, Canada, and Great Britain. Two 

surveys were taken by the Help Desk to gather information on the progress and success of the 

original Models-3 tape installation and to ascertain the type of system the Models-3 users are 

using and prefer, along with any problems. 

2.5.2.3 Ad Hoc Meteorological Modeling Workgroup 

Over the past several years there was an encouraging increase in the amount of discussion 

among members of the regulatory air quality modeling community. Several ad hoc groups were 

formed as informal mechanisms for the exchange of knowledge between many of the most active 

State/Local/Federal modelers. A group focused on air quality modeling tools and databases was 

formed in 1998 and a group focused on emissions inventory development was formed in 1999. 

EPA staff identified the need for a separate group that focused on the development of 

meteorological input for regional air quality models, and with significant help from the 

community as a whole, formed the Ad Hoc Meteorological Modeling workgroup. 

The first meeting of the workgroup was held at the University of Maryland in August 

2000. A Branch staff member served as the Chair of the workgroup for FY-2000. It was agreed 

by the 33 meteorological modelers attending the inaugural meeting that the primary purpose of 

the group is to foster a community exchange of information related to numerical meteorological 

modeling for eventual air quality modeling purposes. Furthermore, group members agreed that 

the workgroup should work closely with the two other ad hoc groups, emission modeling and air 

quality modeling, to improve the overall practice of air quality modeling. 

55
 

3. REFERENCES
 


Air Pollution Modeling and Its Application XIII. S.-E. Gryning, and E. Batchvarova (Eds.). 

Proceedings of the Twenty-Third NATO-CCMS International Technical Meeting on Air 

Pollution Modeling and Its Application, September 28 –October 2, 1998, Varna, 

Bulgaria. Kluwer Academic/Plenum Publishers, New York, NY, 834 pp. (2000). 

Atmospheric Environment. Special Issue: The NARSTO ozone assessment — Critical Reviews. 

K.L. Schere, G.M. Hidy, and H.B. Singh (Guest Eds.). Atmospheric Environment 34(12­

14):1853–2332 (2000). 

Bradbury, L., and I. Castro. A pulsed-wire technique for velocity measurements in highly 

turbulent flows. Journal of Fluid Mechanics 49:657–691 (1971). 

Bullock, O.R., Jr. Modeling assessment of transport and deposition patterns of anthropogenic 

mercury air emissions in the United States and Canada. The Science of the Total 

Environment 259:145–157 (in press). 

Bullock, O.R., Jr., W.G. Benjey, and M.H. Keating. The modeling of regional-scale atmospheric 

mercury transport and deposition using RELMAP. In Atmospheric Deposition of 

Contaminants to the Great Lakes and Coastal Waters. J.E. Baker (Ed.). SETAC Press, 

Pensacola, FL, 323–347 (1997). 

Chang, J.S., P.B. Middleton, W.R. Stockwell, C.J. Walcek, J.E. Pleim, H.H. Lansford, F.S. 

Binkowski, S. Madronich, N.L. Seaman, D.R. Stauffer, D. Byun, J.N. McHenry, P.J. 

Samson, and H. Hass. The Regional Acid Deposition Model and Engineering Model. In 

Acidic Deposition: State of Science and Technology. Emissions, Atmospheric Processes, 

and Deposition. Volume I. Report 4. P.M. Irving (Ed.). National Acid Precipitation 

Assessment Program, Washington, DC, 3–F2 (1990). 

Cohn, R., B.K. Eder, and S.K. LeDuc. An aggregation and episode selection scheme designed to 

support Models-3 CMAQ. In Science algorithms of the EPA MODELS-3 Community 

Multiscale Air Quality (CMAQ) modeling system. Chapter 17. D.W. Byun, and J. Ching 

(Eds.). EPA/600/R/99/030, National Exposure Research Laboratory, U.S. Environmental 

Protection Agency, Research Triangle Park, NC, 1–66 (1999). 

Cohn, R., B.K. Eder, S.K. LeDuc, R.L. Dennis. Development of an aggregation and episode 

selection scheme to support Models-3 CMAQ. Journal of Applied Meteorology (in 

press). 

Davidson, M..J., W.H. Snyder, R.E. Lawson, Jr., and J.C.R. Hunt. Wind tunnel simulations of 

plume dispersion through groups of obstacles. Atmospheric Environment 30:3715–3731 

(1996). 

56
 
Dennis, R.L., J.N. McHenry, W.R. Barchet, F.S. Binkowski, and D.W. Byun. Correcting 

RADM’s sulfate underprediction: Discovery and correction of model errors and testing 

the corrections through comparisons against field data. Atmospheric Environment 

27A(6):975–997 (1993). 

Dvonch, J.T., J.R. Graney, F.J. Marsik, G.J. Keeler, and R.K. Stevens. An investigation of 

source-receptor relationships for mercury in south Florida using event precipitation data. 

The Science of the Total Environment 213:95–108 (1998). 

Eder, B.K., and J.E. Sickles, II. A climatology of air concentration data from the Clean Air 

Status and Trends Network (CASTNet). Atmospheric Environment (in press). 

Eder, B.K., D.H. Coventry, T.L. Clark, and C.E. Bollinger. RELMAP: REgional Lagrangian 

Model of Air Pollution - users guide. EPA-600/8-86/013, Atmospheric Sciences 

Research Laboratory, Research Triangle Park, NC, 137 pp. (1986). 

Eder, B.K., R. Cohn. S.K. LeDuc, and R. Dennis. An aggregation and episode selection scheme 

for EPA’s Models-3 CMAQ. Preprints, 12th Conference on Applied Climatology, May 

7-11, 2000, Asheville, North Carolina. American Meteorological Society, 

Boston,166–169 (2000). 

Eder, B.K., F.S. Binkowski, S.J. Roselle, and M. Mebust. A preliminary evaluation of Models-3 

CMAQ using the light extinction coefficient (bext). In International Symposium on the 

Measurement of Toxic and Related Air Pollutants, September 12-14, 2000, Research 

Triangle Park, North Carolina. VIP-100/CD. U.S. Environmental Protection Agency, 

Research Triangle Park, NC, and Air & Waste Management Association, Pittsburgh (in 

press). 

Eder, B.K., S.K. LeDuc, A.B. Gilliland, and P.L. Finkelstein. On the use of NEXRAD Stage IV 

data in the multimedia modeling of pollutant transport. Preprints, Symposium on 

Precipitation Extremes: Prediction, Impacts, and Responses, January 15–18, 2001, 

Albuquerque, New Mexico. American Meteorological Society, Boston (accepted for 

publication). 

Farquhar, G.D., S. von Caemmerer, and J.A. Berry. A biochemical model of photosynthetic CO2 

fixation in leaves of C3 species. Planta 149:78–90 (1980). 

Finkelstein, P.L., T.G. Ellestad, J.F. Clarke, T.P. Meyers, D.B. Schwede, E. Hebert, and J.F. 

Neal. Ozone and sulfur dioxide dry deposition to forests: Observations and model 

evaluation. Journal of Geophysical Research 105:15365-15377 (2000). 

Foreman, W.T., M.S. Majewski, D.A. Goolsby, F.W. Wiebe, and R.H. Coupe. Pesticides in the 

atmosphere of the Mississippi River Valley, part II 66 air. The Science of the Total 

Environment 248: 213–226 (2000). 

57
 
Gillani, N.V., and J.M. Godowitch. Plume-in-grid treatment of major point source emissions. In 

Science algorithms of the EPA Models-3 Community Multiscale Air Quality modeling 

system. Chapter 9. D.W. Byun, and J.K.S. Ching (Eds.). EPA-600/R-99/030, National 

Exposure Research Laboratory, U.S. Environmental Protection Agency, Research 

Triangle Park, NC, 1–40 (1999). 

Gillette, D.A. On the production of soil wind erosion aerosols having the potential for long 

range transport. Journal de Recherches Atmospheriques 8:735–744 (1974). 

Gillette, D.A., T.C. Niemeyer, and P.J. Helm. Changing horizontal sand drift at an ephemerally 

crusted, non-vegetated desert dry-lake site. Journal of Geophysical Research (in press). 

Gillette, D.A, and P.C. Sinclair. Estimation of suspension of alkaline material dust devils in the 

United States. Atmospheric Environment 24:1135–114 (1990). 

Godowitch, J.M., and J.O. Young. Photochemical simulations of point source emissions with the 

Models-3 CMAQ plume-in-grid approach. Proceedings of the 93rd Annual Meeting of the 

Air & Waste Management Association, Salt Lake City, Utah, June 18–22, 2000. (CDROM). Session AB-2. Regional Photochemical Modeling of Oxidants and Particles. Air 

& Waste Management Association, Pittsburgh, Paper No. 000-668 (2000). 

Godowitch, J.M., N. Gillani, A. Biazar, Y. Wu, and R. Imhoff. Photochemical plume-in-grid 

simulations of major point sources in the Community Multiscale Air Quality (CMAQ) 

modeling system. Preprints, Symposium on Interdisciplinary Issues in Atmospheric 

Chemistry, January 10-15, 1999, Dallas, Texas. American Meteorological Society, 

Boston, MA, 121–124 (1999). 

Guenther, A., C. Geron, T. Pierce, B. Lamb, P. Harley, and R. Fall. Natural emissions of nonmethane volatile organic compounds, carbon monoxide, and oxides of nitrogen from 

North America. Atmospheric Environment 34(12–14):2205–2230 (2000). 

Guentzel, J.L. The atmospheric sources, transport, and deposition of mercury in Florida. Ph.D. 

dissertation, Florida State University, Tallahassee, FL (1997). 

Harman-Fetcho, J.A., L.L. McConnell, C.P. Rice, and J.E. Baker. Wet deposition and air-water 

gas exchange of currently used pesticides to a subestuary of the Chesapeake Bay. 

Environmental Science & Technology 34:1462–1468 (2000). 

Hosker, R.P., Jr. The effects of buildings on local dispersion. In Modeling the Urban Boundary 

Layer. American Meteorological Society, Boston, 95–160 (1987). 

58
 

Houyoux, M.R., and J.M. Vukovich. Updates to the Sparse Matrix Operator Kernel Emissions 

(SMOKE) Modeling System and Integration with Models-3. The Emission Inventory: 

Regional Strategies for the Future. VIP-93. Proceedings of a Specialty Conference, 

October 26–28, 1999, Raleigh, North Carolina. U.S. Environmental Protection Agency, 

Office of Air Quality Planning and Standards, Research Triangle Park, NC, and Air & 

Waste Management Association, Pittsburgh, 430–440 (1999). 

Kondragunta, S., P.M. Udelhofen, K.L. Schere, S.J. Roselle, and B. Holben. Attenuation of solar 

UV radiation by aerosols during air pollution episodes. Preprints, Symposium on 

Atmospheric Chemistry Issues in the 21st Century, January 9-14, 2000, Long Beach, 

California. American Meteorological Society, Boston, 9–13, (2000). 

Lee, J.T., D.L. Call, R.E. Lawson, Jr., W.E. Clements, and D.E. Hoard. A video image analysis 

system for concentration measurements and flow visualization in building wakes. 

Atmospheric Environment 25A:1211–1225 (1991). 

Lin, C.-J., and S.O. Pehkonen. The chemistry of atmospheric mercury: A review. Atmospheric 

Environment 33:2067–2079 (1999). 

Majewski, M.S., W.T. Foreman, and D.A. Goolsby. Pesticides in the atmosphere of the 

Mississippi River Valley, part I 66 rain. The Science of the Total Environment 

248:201–212 (2000). 

Meroney, R.N. Turbulent diffusion near buildings. In Engineering Meteorology. (E. J. Plate, 

Ed.), Chapter 11, Elsevier, Amsterdam 481–525 (1982). 

Meroney, R.N., S. Rafailidis, and M. Paageau. Dispersion in idealized urban street canyons. In 

Air Pollution Modeling and Its Application XI. Vol. 21. S.-E. Gryning, and F.A. 

Schiermeier (Eds.). Plenum Press, New York, NY, 451-458 (1996). 

Miller, S.M., C.W. Sweet, J.V. Depinto, and K.C. Hornbuckle. Atrazine and nutrients in 

precipitation: Results from the Lake Michigan Mass Balance study. Environmental 

Science & Technology 34:55–61 (2000). 

NARSTO Synthesis Team. An assessment of tropospheric ozone pollution: A North American 

perspective. Published by EPRI, Palo Alto, CA, 168 pp. (2000). 

Otte, T.L. Using MM5v3 with Eta analyses for air-quality modeling at the EPA. Preprints, The 

Tenth PSU/NCAR Mesoscale Model Users’ Workshop, June 21–22, 2000, Boulder, 

Colorado. National Center for Atmospheric Research, Boulder, Colorado, 201–204 

(2000). 

59
 

Otte, T.L., N.L. Seaman, and D.R. Stauffer. A Heuristic study on the importance of anisotropic 

error distributions in data assimilation. Monthly Weather Review (accepted for 

publication). 

Pankow, J.F. Review and comparative analysis of the theories on partitioning between the gas 

and aerosol particulate phases in the atmosphere. Atmospheric Environment 

25A:2275–2283 (1987). 

Pankow, J.F. An absorption model of gas/particle partitioning of organic compound in the 

atmosphere. Atmospheric Environment 28:185–188 (1994). 

Pehkonen, S.O., and C.-J. Lin. Aqueous photochemistry of mercury with organic acids. Journal 

of the Air & Waste Management Association 48:144–150 (1998). 

Pleim, J.E., and D.W. Byun. Application of a new land-surface, dry deposition, and PBL model 

in the Models-3 Community Multiscale Air Quality (CMAQ) model system. Preprints, 

Millennium NATO/CCMS International Technical Meeting on Air Pollution Modelling 

and Its Application, May 15–19, 2000, Boulder, CO. American Meteorological Society, 

Boston, 180–187 (2000). 

Pleim, J.E., and J.S. Chang. A non-local closure model for vertical mixing in the convective 

boundary layer. Atmospheric Environment 26A:965–981 (1992). 

Pleim, J.E., and A. Xiu. Development and testing of a surface flux and planetary boundary layer 

model for application in mesoscale models. Journal of Applied Meteorology 34:16–32 

(1995). 

Pleim, J.E., J.F. Clarke, P.L. Finkelstein, E.J. Cooter, T.G. Ellestad, A. Xiu, and W.M. Angevine. 

Comparison of measured and modeled surface fluxes of heat, moisture and chemical dry 

deposition. In Air Pollution Modeling and Its Application XI. Volume 21. S.-E. 

Gryning, and F.A. Schiermeier (Eds.). Plenum Press, New York, NY, 613–621 (1996). 

Pleim, J.E., A. Xiu, P.L. Finkelstein, and J.F. Clarke. Evaluation of a coupled land-surface and 

dry deposition model through comparison to field measurements of surface heat, 

moisture, and ozone fluxes. Preprints, 12th Symposium on Boundary Layers and 

Turbulence, July 28–August 1, 1997, Vancouver, British Columbia, Canada. American 

Meteorological Society, Boston, 478–479 (1997) 

Pleim, J.E., A. Xiu, P.L. Finkelstein, and T.L. Otte. A coupled land-surface and dry deposition 

model and comparison to field measurements of surface heat, moisture, and ozone fluxes. 

Water, Air, and Soil Pollution (in press). 

60
 

Poole-Kober, E., and H. Viebrock. Fiscal year 1999 summary report of the NOAA Atmospheric 

Sciences Modeling Division to the U. S. Environmental Protection Agency. NOAA 

Technical Memorandum OAR ARL-236, 119 pp (1999). 

Roselle, S.J., and F.S. Binkowski. Cloud dynamics and chemistry. In Science algorithms of the 

EPA Models-3 Community Multiscale Air Quality (CMAQ) modeling system. Chapter 11. 

D.W. Byun, and J.K.S. Ching (Eds.). EPA/600/R-99/030, National Exposure Research 

Laboratory, U.S. Environmental Protection Agency, Research Triangle Park, NC, 1–10 

(1999). 

Roselle, S.J., K.L. Schere, J.E. Pleim, and A.F. Hanna. Photolysis rates for CMAQ. In Science 

algorithms of the EPA Models-3 Community Multiscale Air Quality (CMAQ) modeling 

system. Chapter 14. D.W. Byun, and J.K.S. Ching (Eds.). EPA/600/R-99/030, National 

Exposure Research Laboratory, U.S. Environmental Protection Agency, Research 

Triangle Park, NC, 1–8 (1999). 

Roth, M., and H. Ueda. A wind tunnel study of turbulent flow over a rough surface. Preprints, 

Second AMS Urban Environment Conference, November 2–6, 1998, Albuquerque, New 

Mexico. American Meteorological Society, Boston, 115–116 (1998). 

Russell, A.G., and R.L. Dennis. NARSTO critical review of air quality modeling. Atmospheric 

Environment 34:2283-2324 (2000). 

Schiermeier, F.A. The Millennium (24th) NATO/CCMS International Technical Meeting (ITM) 

on Air Pollution Modelling and Its Application. In EURASAP Newsletter, European 

Association for the Science of Air Pollution, Sophia, Bulgaria, 38:23–26 (2000). 

Schwede, D.B., S.K. LeDuc, and T.L. Otte. Using meteorological model output as a surrogate 

for on-site observations to predict deposition velocity. Water, Air, & Soil Pollution (in 

press). 

Singh, R.B., and A.H. Huber. Development of a Microscale Emission Factor Model for CO 

(MicroFacCO) for predicting real-time motor vehicle emissions. Journal of the Air & 

Waste Management Association 50:1980–1991 (2000). 

Slinn, W.G.N. Predictions for particle depositions to vegetative canopies. Atmospheric 

Environment 16:1785-1794 (1982). 

Snyder, W.H., and R.E. Lawson, Jr. Wind-tunnel measurements of flow fields in the vicinity of 

buildings. Preprints, Eighth AMS Joint Conference on Applications of Air Pollution 

Meteorology with A&WMA, January 23–28, 1994, Nashville, Tennessee. American 

Meteorological Society, Boston, 244-250 (1994). 

61
 
U.S. Department of Commerce. 	The Federal plan for meteorological services and supporting 

research – Fiscal year 2001. FCM P1-2000, Office of the Federal Coordinator for 

Meteorological Services and Supporting Research, National Oceanic and Atmospheric 

Administration, Washington, DC, 184 pp. (2000). 

U.S. Environmental Protection Agency. 	Mercury study report to Congress. Volume III: Fate 

and transport of mercury in the environment. G.E. Rice, R.B. Ambrose, Jr., O.R. 

Bullock, Jr., and J. Swartout (Contributors). EPA-452/R-97-005, Office of Air Quality 

Planning and Standards and Office of Research and Development, Research Triangle 

Park, NC (1997). (available at http://www.epa.gov/ttn/uatw/112nmerc/mercury.html). 

U.S. Environmental Protection Agency. 	Science algorithms of the EPA Models-3 Community 

Multiscale Air Quality (CMAQ) modeling system. D.W. Byun, and J.K.S. Ching (Eds.). 

EPA/600/R-99/030, National Exposure Research Laboratory, U.S. Environmental 

Protection Agency, Research Triangle Park, NC (1999). 

Van Loon, L., E. Mader, and S.L. Scott. Reduction of the aqueous mercuric ion by sulfite: UV 

spectrum of HgSO3 and its intramolecular redox reaction. Journal of Physical Chemistry 

104:1621–1626 (2000). 

Walcek, C.J., and G.R. Taylor. A theoretical method for computing vertical distributions of 

acidity and sulfate production within cumulus clouds. Journal of the Atmospheric 

Sciences 43:339–355 (1986). 

Wilkening, K.E., L.A. Barrie, and M. Engle. Trans-Pacific air pollution. Science 290:66–67 

(2000). 

Xiu, A., and J.E. Pleim. Development of a land surface model part I: Application in a mesoscale 

meteorology model. Journal of Applied Meteorology (accepted for publication). 

62
 

APPENDIX A: ACRONYMS, ABBREVIATIONS, AND DEFINITIONS 
 

ACM Asymmetric Convective Model 

AQM Air Quality Model 

AQMF Air Quality Modeling Forum 

ARL Air Resources Laboratory, NOAA 

ARPS Advanced Regional Prediction System 

ASLI Atmospheric Science Librarians International 

ASMD Atmospheric Sciences Modeling Division 

ASPEN Assessment System for Population Exposure Nationwide 

ASTM American Society for Testing and Materials 

AVHRR Advanced Very High Resolution Radiometer 

AVIRIS Airborne Visible and Infrared Imaging Spectrometer 

BASC Board on Atmospheric Sciences and Climate (NRC/NAS) 

BCON Boundary CONditions processor 

BEIS Biogenic Emissions Inventory System 

bext Extinction coefficient 

CAA Clean Air Act of 1970 

CAAA Clean Air Act Amendments of 1990 

CAPITA Center for Air Pollution Impacts and Trends Analysis 

CASTNet Clean Air Status and Trends Network 

CB-IV Carbon Bond-IV 

CBL Convective Boundary Layer 

CCTM CMAQ Chemistry-Transport Model 

CD-ROM Compact Disk - Read Only Memory 

CFD Computational Fluid Dynamics 

CMAQ Community Multiscale Air Quality model 

CTM Chemistry-Transport Model 

DFS Digital Facsimile Analysis 

DIAS Dynamic Information Architecture System 

ECIP Emissions-Chemistry Interface Processor 

EDAS Eta Data Assimilation System 

EMEP European Monitoring and Evaluation Programme 

EPA Environmental Protection Agency 

Extended RADM Regional Acid Deposition Model with full dynamics of secondary 

inorganic fine particle formation taken from the RPM 

FAMS Florida Atmospheric Mercury Study 

FCMSSR Federal Committee for Meteorological Services and Supporting 

Research 

FDDA Four-Dimensional Data Assimilation 

FMF Fluid Modeling Facility (EPA) 

FTP File Transfer Protocol 

FY Fiscal Year 

GIS Geographic Information System 

63
 
HDE Heavy Duty Engine 

HPCC High Performance Computing and Communications 

HTML HyperText Markup Language 

IAMSLIC International Association of Aquatic and Marine Science Libraries and 

Information Centers 

ICMSSR Interdepartmental Committee for Meteorological Services and 

Supporting Research 

ICON Initial CONditions processor 

I/O Input/Output 

ITM International Technical Meeting 

ITR&D Information Technology Research and Development 

JPROC Photolysis rate processor 

LULC Land Use/Land Cover 

MCIP Meteorology-Chemistry Interface Processor 

MEPPS Models-3 Emission Processing and Projection System 

MIC3 Meteorological Instrumentation Cluster of 3 trailers 

MicroFacCO Microscale automobile emission Factor model for carbon monoxide 

MIMS Multimedia Integrated Modeling System 

MIRAGE Megacity Impact on Regional And Global Environments 

MLBC Multi-Layer Bio-Chemical dry deposition model 

MM5 Mesoscale Model - Version 5 

Models-3 Third generation air quality modeling system 

MODTRAN MODerate resolution TRANSmittance 

MSC-East Meteorological Synthesizing Center - East 

NAAQS National Ambient Air Quality Standards 

NAPAP National Acid Precipitation Assessment Program 

NARSTO North American Research Strategy for Tropospheric Ozone 

NARSTO-NE NARSTO-NorthEast 

NAS National Academy of Sciences 

NASA National Aeronautics and Space Administration 

NATO/CCMS North Atlantic Treaty Organization Committee on the Challenges of 

 Modern Society 

NCAR National Center for Atmospheric Research 

NCEP National Centers for Environmental Prediction 

NERL National Exposure Research Laboratory 

NET National Emissions Trends 

NEXRAD NEXt generation RADar 

NOAA National Oceanic and Atmospheric Administration 

NPS National Park Service 

NSF National Science Foundation 

NWS National Weather Service 

OAQPS Office of Air Quality Planning and Standards (EPA) 

OMB Office of Management and Budget 

PAVE Package for Analysis and Visualization 

64
 
PBL Planetary Boundary Layer 

PC Personal Computer 

PDM Plume Dynamics Model 

PEM Pesticide Emissions Model 

PinG Plume-in-Grid algorithm 

PM Particulate Matter 

PPM Piecewise Parabolic Model 

PSU Pennsylvania State University 

PX LSM Land-Surface Model 

QA/QC Quality Assurance/Quality Control 

QSSC Quality Systems Science Center 

R&DF Research and Development Forum 

RADM Regional Acid Deposition Model 

RADM/RPM Regional Acid Deposition Model/Regional Particulate Model 

RAMS Regional Atmospheric Modeling System 

RELMAP REgional Lagrangian Model of Air Pollution 

REMSAD Regulatory Modeling System for Aerosols And Deposition 

RGM Reactive Gaseous Mercury 

RHESSys Regional Hydo-Ecological Simulation System 

RHR Regional Haze Rule 

RPM Regional Particulate Model 

SAEWG Standing Air Emission Work Group 

SAIL Southeast Affiliate of IAMSLIC Librarians 

SASWG Standing Air Simulation Work Group 

SBL Stable Boundary Layer 

SCRAM Support Center for Regulatory Air Models 

SGI Silicon Graphics Incorporated computing platform 

SIP State Implementation Plan 

SMOKE Sparse Matrix Operator Kernel Emission 

SODAR SOund Detection And Ranging 

SoFAMMS South Florida Atmospheric Mercury Monitoring Study 

SOS Southern Oxidants Study 

SWOOMS Surface Water Object-Oriented Modeling System 

TOMS Total Ozone Mapping Spectrometer 

UAM-V Urban Airshed Model - Variable grid 

URL Uniform Resource Locator 

URMM Urban-Regional Multiscale Model 

USGS U.S. Geological Survey 

Vis5D Visualizing five dimensional gridded data sets 

WRAP Western Regional Air Partnership 

WSR-88D Weather Surveillance Radar 1988 Doppler Version 

WWW World-Wide Web 

65
 
APPENDIX B: PUBLICATIONS
 


Atmospheric Modeling Division, and Science Applicaitons International Corporation. Models-3 

installation procedures for a PC with an NT operating system (Models-3 Version 4.0). 

EPA-600/R-00/061, National Exposure Research Laboratory, Research Triangle Park, 

NC (2000). 

Brashers, B., Y. Wu, and P.L. Finkelstein. Recent improvements to the Meyers multi-layer dry 

deposition model. Preprints, 24th Conference on Agricultural and Forest Meteorology, 

August 14–18, 2000, Davis, California. American Meteorological Society, Boston, 

82–83 (2000). 

Brown, M.J., R.E. Lawson, Jr., D.S. Decroix, and R.L. Lee. Mean flow and turbulence 

measurements around a 2-D array of buildings in a wind tunnel. Preprints, 11th Joint 

Conference on the Applications of Air Pollution Meteorology with the A&WMA, January 

9–14, 2000, Long Beach, CA. American Meteorological Society, Boston, 35–40 (2000). 

Bullock, O.R., Jr. Current methods and research strategies for modeling atmospheric mercury. 

Fuel Processing Technology 65-66:459–471 (2000). 

Bullock, O.R., Jr. Modeling assessment of transport and deposition patterns of anthropogenic 

mercury air emissions in the United States and Canada. The Science of the Total 

Environment 259:145–157 (2000). 

Byun, D.W. Dynamically consistent formulations in meteorological and air quality models for 

multiscale atmospheric studies. Part I: Governing equations in a generalized coordinate 

system. Journal of the Atmospheric Sciences 56:3789–3807 (1999). 

Byun, D.W. Dynamically consistent formulations in meteorological and air quality models for 

multiscale atmospheric studies. Part II: Mass conservation issues. Journal of the 

Atmospheric Sciences 56:3808–3820 (1999). 

Byun, D.W., and J.E. Pleim. Sensitivity of ozone and aerosol predictions to the transport 

algorithms in the Models-3 Community Multiscale Air Quality (CMAQ) modeling 

system. Preprints, Millennium NATO/CCMS International Technical Meeting on Air 

Pollution Modelling and Its Application, May 15–19, 2000, Boulder, Colorado. 

American Meteorological Society, Boston, 116–1123 (2000). 

Byun, D.W., A. Lacser, W. Benjey, and J.K.S. Ching. Effects of grid resolution on the 

simulation of urban air quality: Application of Models-3/CMAQ to the Philadelphia 

Metropolitan Area at 12, 4, and 1.3 km resolutions. Preprints, Third Symposium on the 

Urban Environment, August 14–18, 2000, Davis, California. American Meteorological 

Society, Boston, 88–89 (2000). 

66
 
Ching, J.K.S. Air quality modeling of PM and air toxics at neighborhood scales. Preprints, 11th 

Joint Conference on the Applications of Air Pollution Meteorology with the A&WMA , 

January 9–14, 2000, Long Beach, California. American Meteorological Society, Boston, 

178–181 (2000). 

Ching, J.K.S., A. Lacser, D.W. Byun, and W. Benjey. Air quality modeling of PM and air toxics 

at neighborhood scales to improve human exposure assessment. Preprints, Third 

Symposium on the Urban Environment, August 14–18, 2000, Davis, California. 

American Meteorological Society, Boston, 96–97 (2000). 

Cooter, E.J., and D.B. Schwede. Sensitivity of the National Oceanic and Atmospheric 

Administration multilayer model to instrument error and parameterization uncertainty. 

Journal of Geophysical Research 105:6695–6707 (1999). 

Cooter, E.J., M.B. Richman, P.J. Lamb, and D.A. Sampson. A climate change database for 

biological assessments in the southeastern United States: Development and case study. 

Climatic Change 44:89–121 (2000). 

Dennis, R.L., G.S. Tonnesen, and R. Mathur. Nonlinearities in the sulfate secondary fine 

particulate response to NOX emissions reductions as modeled by the Regional Acid 

Deposition Model. Preprints, Millennium NATO/CCMS International Technical Meeting 

on Air Pollution Modelling and Its Application, May 15–19, 2000, Boulder, Colorado. 

American Meteorological Society, Boston, 108–115 (2000). 

Eder, B.K., R. Cohn, S.K. LeDuc, and R. Dennis. An aggregation and episode selection scheme 

for EPA’s Models-3 CMAQ. Preprints, 12th Conference on Applied Climatology, May 

8–11, 2000, Asheville, North Carolina. American Meteorological Society, Boston, 

166–169 (2000). 

Finkelstein, P.L. Random error in atmospheric flux measurements. Preprints, 24th Conference 

on Agricultural and Forest Meteorology, August 14–18, 2000, Davis, California. 

American Meteorological Society, Boston, 116–117 (2000). 

Finkelstein, P.L., T.G. Ellestad, J.F. Clarke, T.P. Meyers, D.B. Schwede, E.O. Hebert, and J.A. 

Neal. Ozone and sulfur dioxide dry deposition to forests observations and model 

evaluation. Journal of Geophysical Research 105(D12):15,365–15,377 (2000). 

Gillette, D.A. Physics of aeolian movement emphasizing changing of the aerodynamic 

roughness height by saltating grains (the Owen Effect). In Aeolian Environments, 

Sediments and Landforms. A.S. Goudie, S. Stokes, and I. Livingstone (Eds.). John 

Wiley & Sons, New York/Chichester, 129–42, (1999). 

67
 

Gilliland, A.B. Introduction: MIMS ecosystem modeling integration efforts (abstract). In 

Proceedings of the Cross-Discipline Ecosystem Modeling and Analysis Workshop, 

August 15-17, 2000, Research Triangle Park, North Carolina. EPA-600/A-00/083, 

Atmospheric Modeling Division, National Exposure Research Laboratory, Research 

Triangle Park, NC, p. 7 (2000). 

Godowitch, J.M., and J.O. Young. Photochemical simulations of point source emissions with the 

Models-3 CMAQ plume-in-grid approach. Proceedings of the 93rd Annual Meeting of the 

Air & Waste Management Association, Salt Lake City, Utah, June 18–22, 2000. (CDROM). Session AB-2. Regional Photochemical Modeling of Oxidants and Particles. Air 

& Waste Management Association, Pittsburgh, Paper No. 000-668 (2000). 

Guenther, A., C. Geron, T. Pierce, B. Lamb, P. Harley, and R. Fall. Natural emissions of nonmethane volatile organic compounds, carbon monoxide, and oxides of nitrogen from 

North America. Atmospheric Environment 34:2205–2230 (2000). 

Huber, A.H., M. Bolstad, M Freeman, S. Rida, E. Bish, and K. Kuehlert. Addressing human 

exposures to air pollutants around buildings in urban areas with computational fluid 

dynamics (CFD) models. Preprints, Third Symposium on the Urban Environment, 

August 14–18, 2000, Davis, California. American Meteorological Society, Boston, 62-63 

(2000). 

Irwin, J.S. Effects of concentration fluctuations on statistical evaluations of centerline 

concentration estimates by atmospheric dispersion models. Proceedings of the 6th 

International Conference on Harmonisation Within Atmospheric Dispersion Modelling 

for Regulatory Purposes, Rouen, France, October 11–14, 1999. (CD-ROM). INSA de 

Rouen, France. Paper No. 38 (1999). 

Irwin, J.S. Comparison of two sampling procedures for the statistical evaluation of the 

performance of atmospheric dispersion models in estimating centerline concentration 

values. Preprints, Millennium NATO/CCMS International Technical Meeting on Air 

Pollution Modelling and Its Application, May 15–19, 2000, Boulder, Colorado. 

American Meteorological Society, Boston, 413–420 (2000). 

Johnston, J.M., J.H. Novak, and S.R. Kraemer. Multimedia integrated modeling for 

environmental protection: Introduction to a collaborative framework. Environmental 

Monitoring and Assessment 63:253–263 (2000). 

Jang, C.J., P. Dolwick, N. Possiel, E. Baldridge, D. Byun, and J. Tikvart. Applications and 

evaluation of U.S. EPA’s Models-3/Community Multiscale Air Quality (CMAQ) 

modeling system. Proceedings of the 93rd Annual Meeting of the Air & Waste 

Management Association, Salt Lake City, Utah, June 18–22, 2000. (CD-ROM). Session 

AB-2. Regional Photochemical Modeling of Oxidants and Particles. Air & Waste 

Management Association, Pittsburgh, Paper No. 380 (2000). 

68
 
Jones-Lepp, T., C.L. Gerlach, and E.J. Cooter. The power of analytical methods for measuring 

suspected endocrine disrupting compounds: A pilot study. Trends in Analytical 

Chemistry 19:286–291. 

Kastner-Klein, P., M.W. Rotach, M. Brown, E. Fedorovich, and R.E. Lawson, Jr. Spatial 

variability of mean flow and turbulence fields in street canyons. Preprints, Third 

Symposium on the Urban Environment, August 14–18, 2000, Davis, California. 

American Meteorological Society, Boston, 13–14 (2000). 

Kondragunta, S., P.M. Udelhofen, K.L. Schere, S.J. Roselle, and B. Holben. Attenuation of solar 

UV radiation by aerosols during air pollution episodes. Preprints, Symposium on 

Atmospheric Chemistry Issues in the 21st Century, January 9–14, 2000, Long Beach, 

California. American Meteorological Society, Boston, 9–13, (2000). 

Lacser, A., D.W. Byun, W. Benjey, and J.K.S. Ching. Sensitivity of pollutant concentrations to 

spatial resolution in an Eulerian air quality model. Proceedings of the Fourth Annual 

George Mason University Transport and Dispersion Modeling, Fairfax, Virginia, July 

11–12, 2000. (CD-ROM). Institute for Computational Sciences and Informatics, George 

Mason University, Fairfax, Virginia (2000). 

LeDuc, S.K., D. Byun, and K.L. Schere. NARSTO NewsFeature: Models-3. NARSTO News 3:2. 

Available online from (http://wwww.cgenv.com/Narsto) (1999). 

LeDuc, S.K., K.L. Schere, J.M. Godowitch, and G.L. Gipson. Models-3/CMAQ applications 

which illustrate capability and functionality. Preprints, Millennium NATO/CCMS 

International Technical Meeting on Air Pollution Modelling and Its Application, May 

15–19, 2000, Boulder, Colorado. American Meteorological Society, Boston, 224–225 

(2000). 

McCurdy, T., M.P. Zelenka, P.M. Lawrence, R.M. Houston, and R. Burton. Acid aerosols in the 

Pittsburgh Metropolitan area. Atmospheric Environment 33:5133–5145 (1999). 

Mathur, R., and R.L. Dennis. A regional modeling analysis of reduced nitrogen cycling in the 

eastern United States. Preprints, Symposium on Atmospheric Chemistry Issues in the 21st 

Century, January 9–14, 2000, Long Beach, California. American Meteorological 

Society, Boston, 85–88 (2000). 

Niemeyer, T.C., D.A. Gillette, J.J. DeLuisi, Y.J. Kim, W.F. Niemeyer, T. Ley, T.E. Gill, and D. 

Ono. Optical depth, size distribution and flux of dust from Owens Lake, California. 

Earth Surface Processes and Landforms 24:463–479 (1999). 

Otte, T.L. Using MM5 Version 2 with Models-3/CMAQ: A user’s guide and tutorial. 

EPA-600/R-99/065, National Exposure Research Laboratory, Research Triangle Park, 

NC (1999). 

69
 
Otte, T.L. Using MM5v3 with Eta analyses for air-quality modeling at the EPA. Preprints, The 

Tenth PSU/NCAR Mesoscale Model Users’ Workshop, June 21–22, 2000, Boulder, 

Colorado. National Center for Atmospheric Research, Boulder, Colorado, 201–204 

(2000). 

Pierce, T.E., and L.W. Bender. Examining the temporal variability of ammonia and nitric oxide 

emissions from agricultural processes. In The Emission Inventory: Regional Strategies 

for the Future. VIP-93. Proceedings of a Specialty Conference, October 26–28, 1999, 

Raleigh, North Carolina. U.S. Environmental Protection Agency, Research Triangle 

Park, NC, and Air & Waste Management Association, Pittsburgh, 373–385 (2000). 

Pleim, J.E., and D.W. Byun. Application of a new land-surface, dry deposition, and PBL model 

in the Models-3 Community Multiscale Air Quality (CMAQ) model system. Preprints, 

Millennium NATO/CCMS International Technical Meeting on Air Pollution Modelling 

and Its Application, May 15–19, 2000, Boulder, Colorado. American Meteorological 

Society, Boston, 180–187 (2000). 

Pleim, J.E., and A. Xiu. A new land-surface model in MM5. Preprints, The Tenth PSU/NCAR 

Mesoscale Model Users’ Workshop, June 21–22, 2000, Boulder, Colorado. National 

Center for Atmospheric Research, Boulder, Colorado, 37–40 (2000). 

Pleim, J.E., A. Xiu, and P. Finkelstein. A coupled land-surface and dry deposition model and 

comparison to field measurements of surface heat, moisture, and ozone fluxes. Preprints, 

The Sixth International Conference on Air-Surface Exchange of Gases and Particles, 

Edinburgh, UK, July 3–7, 2000. Natural Environment Research Council, Centre for 

Ecology & Hydrology, Edinburgh, UK, p. 29 (2000). 

Poole-Kober, E.M., H.J. Viebrock (Eds.) Fiscal year 1999 summary report of the NOAA 

Atmospheric Sciences Modeling Division to the U.S. Environmental Protection Agency. 

NOAA Technical Memorandum ERL ARL-236, Atmospheric Sciences Modeling 

Division, Research Triangle Park, NC, 119 pp. (2000). 

Proceedings of the Cross-Discipline Ecosystem Modeling and Analysis Workshop, August 

15–17, 2000, Research Triangle Park, North Carolina. Gilliland, A.B. (Ed.). 

EPA-600/A-00/083, Atmospheric Modeling Division, National Exposure Research 

Laboratory, Research Triangle Park, NC, 37 pp. (2000). 

Russell, A.G., and R.L. Dennis. NARSTO critical review of air quality modeling. Atmospheric 

Environment 34:2283–2324 (2000). 

Schere, K.L., and G. Hidy. Foreword to the NARSTO critical reviews. Atmospheric 

Environment 34:185–1860 (2000). 

70
 
Schiermeier, F.A. The Millennium NATO/CCMS International Technical Meeting (ITM) on Air 

Pollution Modelling and Its Application. In EURASAP Newsletter, European Association 

for the Science of Air Pollution, Sophia, Bulgaria, 38:23–26 (2000). 

Scholtz, M.T., B.J. Van Heyst, E.J. Cooter, and J.E. Pleim. Estimated hourly emissions of 

atrazine from agricultural lands for the Lake Michigan Mass Balance study. In The 

Emission Inventory: Living in a Global Environment. VIP-88. Proceedings of a 

Specialty Conference, New Orleans, Louisiana, December 8–10, 1998. Air & Waste 

Management Association, Pittsburgh, 1037–1048 (1999). 

Schwede, D.B., W.B. Petersen, and S.K. LeDuc. Simulating atmospheric exposure using an 

innovative meteorological sampling scheme. Preprints, Millennium NATO/CCMS 

International Technical Meeting on Air Pollution Modelling and Its Application, May 

15–19, 2000, Boulder, Colorado. American Meteorological Society, Boston, 222–223 

(2000). 

Singh, R.B., and A.H. Huber. Development of a microscale emission factor model for CO 

(MicroFacCO) for predicting real-time motor vehicle emissions. In The Emission 

Inventory: Regional Strategies for the Future. VIP-93. Proceedings of a Specialty 

Conference, Raleigh, North Carolina, October 26–28, 1999. Air & Waste Management 

Association, Pittsburgh, 495–526 (2000). 

Special Issue: The NARSTO Ozone Assessment - Critical Reviews. K.L. Schere, G.M. Hidy, 

and H.B. Singh (Guest Eds.). Atmospheric Environment 34:1853–2332 (2000). 

Strum, M., J.S. Touma, B. Battye, J. Langstaff, D. Lindermand, and A. Beidler. An emission 

modeling system for hazardous air pollutants. In The Emission Inventory: Regional 

Strategies for the Future. VIP-93. Proceedings of a Specialty Conference, October 

26–28, 1999, Raleigh, North Carolina. U.S. Environmental Protection Agency, Research 

Triangle Park, NC, and Air & Waste Management Association, Pittsburgh, 441–455 

(2000). 

Sugata, S., D.W. Byun, and I. Uno. Simulation of sulfate aerosol in East Asia using 

Models-3/CMAQ with RAMS meteorological data. Preprints, Millennium NATO/CCMS 

International Technical Meeting on Air Pollution Modelling and Its Application, May 

15–19, 2000, Boulder, Colorado. American Meteorological Society, Boston, 164–171 

(2000). 

Thompson, R.S., W.H. Snyder, and J.C. Weil. Laboratory simulation of the rise of buoyant 

thermals created by open detonations. Journal of Fluid Mechanics 417:127–156 (2000). 

Tonnesen, G.S., and R.L. Dennis. Analysis of radical propagation efficiency to assess ozone 

sensitivity to hydrocarbons and NOx. Part 1, Local indicators of instantaneous odd 

oxygen production sensitivity. Journal of Geophysical Research 105:9213–9225 (2000). 

71
 
Tonnesen, G.S., and R.L. Dennis. Analysis of radical propagation efficiency to assess ozone 

sensitivity to hydrocarbons and NOx. Part 2, Long-lived species as indicators of ozone 

concentration sensitivity. Journal of Geophysical Research 105:9227–9241 (2000). 

U.S. Environmental Protection Agency. 	Technical support document for the tier 2/gasoline 

sulfur ozone modeling analyses. EPA-420-R-99-031, Office of Air Quality Planning and 

Standards, Research Triangle Park, NC, 27 pp. (1999). 

Van den Berg, F., R. Kubiak, W.G. Benjey, M.S. Majewski, S.R. Yates, G.L. Reeves, J.H. Smelt, 

and A.M.A. Van der Linden. Emission of pesticides into the air. Water, Air, and Soil 

Pollution 115:195–218 (1999). 

Wesely, M.L., J.D. Shannon, P.V. Doskey, and J.S. Touma. Gaseous deposition described with 

the Industrial Source Complex model. Preprints, 11th Joint Conference on the 

Applications of Air Pollution Meteorology with the A&WMA, January 9–14, 2000, Long 

Beach, California. American Meteorological Society, Boston, 204–206 (2000). 

Wu, Y., B. Brasher, J. Pleim, and P.L. Finkelstein. Development of a multilayer biochemical dry 

deposition model. Preprints, 24th Conference on Agricultural and Forest Meteorology, 

August 14–18, 2000, Davis, California. American Meteorological Society, Boston, 

162–163 (2000) 

Zhang, Y., C. Seigneur, J.H. Seinfeld, M.Z. Jacobson, and F.S. Binkowski. Simulation of 

aerosol dynamics: A comparative review of algorithms used in air quality models. 

Aerosol Science and Technology 31:487–514 (1999). 

Zhang, Y., C. Seigneur, J.H. Seinfeld, M.Z. Jacobson, S.L. Clegg, and F.S. Binkowski. A 

comparative review of inorganic aerosol thermodynamic equilibrium modules: 

Similarities, differences, and their likely causes. Atmospheric Environment 34:117–137 

(2000). 

72
 

APPENDIX C: PRESENTATIONS 

Benjey, W.G. Experience with Models-3 emission (with and without the framework). 

Presentation at the First Models-3 Workshop, Washington, DC, June 13, 2000. 

Binkowski, F.S. CMAQ aerosol component. Presentation at Colorado State University, Ft. 

Collins, CO, March 9, 2000. 

Binkowski, F.S. Evaluation of predicted visual range using the Community Multiscale Air 

Quality modeling system. Presentation at the European Aerosol Conference, Dublin, 

Ireland, September 3, 2000. 

Bullock, O.R., Jr. Atmospheric mercury modeling - Investigation of a global pollutant. 

Presentation at the International Transport of Air Pollutants (ITAP) group meeting, 

Washington, DC (electronic presentation by conference call from Research Triangle Park, 

NC), June 27, 2000. 

Bullock, O.R., Jr. Overview of atmospheric mercury modeling at NERL. Presentation at the 

Ozone/Air Toxics Program Peer Review, Research Triangle Park, NC, June 28, 2000. 

Byun, D.W. One-atmosphere modeling concept: Models-3 Community Multiscale Air Quality 

(CMAQ) modeling system. Presentation at Arizona State University, Phoenix, AZ, 

November 10, 1999. 

Byun, D.W. EPA’s Models-3/CMAQ. Presentation at National Institute for Environmental 

Studies, Tsukuba, Japan, February 5, 2000. 

Byun, D.W. One-atmosphere dynamics in Models-3/CMAQ. Presentation at the Institute for 

Mathematics and Its Applications Workshop: Atmospheric Modeling, University of 

Minnesota, Minneapolis, MN, March 16, 2000. 

Byun, D.W. Trans-Pacific modeling - Investigation of a global pollutant. Presentation at the 

International Transport of Air Pollutants (ITAP) group meeting, Washington, DC 

(electronic presentation by conference call from Research Triangle Park, NC), June 27, 

2000. 

Byun, D.W. EPA’s Models-3: Community Multiscale Air Quality (CMAQ) modeling system. 

Presentation at the Air Quality Symposium, University of Houston, Houston, TX, 

September 29, 2000. 

Ching, J.K.S. BOSC (Board of Scientific Counselors) Review of NERL PM modeling research, 

Durham, NC, October 28, 1999. 

73
 
Ching, J.K.S. Air quality and exposure modeling: Potential and implementation for their linkage. 

Presentation at the Workshop on the Implementation of Long Term Exposure to PM for 

Epidemiology Studies, Research Triangle Park, NC, December 6, 1999. 

Ching, J.K.S. Mathematical and modeling issues: EPA’s Models-3/CMAQ modeling system. 

Presentation at the Air Quality Seminar for the University of Houston, Department of 

Mathematics, Houston, TX, April 27, 2000. 

Cooter, E.J. Atmospheric transport and deposition of atrazine to Lake Michigan. Presentation at 

the Lake Michigan Mass Balance Study Atrazine Modeling Peer Review Meeting, 

Romulus, Michigan, September 27, 2000. 

Dennis, R.L. Evaluating complex and/or multi-disciplinary models: The difficulty necessitates 

new, more diagnostic approaches. Presentation at the SETAC 20th Annual Meeting, 

Philadelphia, PA, November 15, 1999. 

Dennis, R.L. Atmospheric deposition of nutrients to coastal waters. Presentation at the SETAC 

20th Annual Meeting, Philadelphia, PA, November 17, 1999. 

Dennis, R.L. EPA’s third generation air quality model and modeling system: Models-3/CMAQ, 

a one-atmosphere approach. Presentation at the National Center for Atmospheric 

Research, Boulder, CO, December 7, 1999. 

Dennis, R.L. NOx: A one-atmosphere perspective. Presentation on the EPA Office of Air 

Quality Planning and Standards NOx Telecast, Raleigh, NC, December 8, 1999. 

Dennis, R.L. Atmospheric deposition of nutrients to coastal waters of the East and Gulf Coasts: 

From where does it originate - sources and airsheds. Presentation at the SAIL 2000 

Conference, Research Triangle Park, NC, April 5, 2000. 

Dennis, R.L. Regional air quality modeling perspective. Presentation at the EPA Dry Deposition 

Workshop, Washington, DC, May 24, 2000. 

Dennis, R.L. Characterization of principal airsheds of atmospheric deposition of nutrients to 

East and Gulf Coast estuarine watersheds. Presentation at the American Geophysical 

Union Spring 2000 Meeting, Washington, DC, June 1, 2000. 

Dennis, R.L. Principal airsheds of sulfur and oxidized nitrogen deposition to Shenandoah 

National Park. Presentation at the American Geophysical Union Spring 2000 Meeting, 

Washington, DC, June 2, 2000. 

Dennis, R.L. First results from testing the operational performance of the EPA Community 

Multiscale Air Quality model (CMAQ). Presentation at the First Annual Models-3 

Workshop, Arlington, VA, June 12, 2000. 

74
 
Dennis, R.L. Atmospheric transport and airsheds for Neuse/Pamlico System. Presentation at the 

EPA MIMS Workshop, Research Triangle Park, NC, August 15, 2000. 

Dennis, R.L. Atmospheric deposition of inorganic nitrogen to watersheds/estuarian waters. 

Presentation at the Cross Discipline Ecosystem Modeling and Analysis Workshop, 

Research Triangle Park, NC, August 16, 2000. 

Dolwick, P.D. CMAQ proof of concept: Western United States ozone modeling. Presentation at 

the First Annual Models-3 Workshop, Arlington, VA, June 12, 2000. 

Dolwick, P.D. U.S. EPA plans for meteorological modeling in FY-2001: CMAQ proof of 

concept — Eastern United States fine grid ozone/PM modeling for July 1995. 

Presentation at the Ad Hoc Meteorological Modeling Workgroup, College Park, MD, 

August 16, 2000. 

Eder, B.K. An aggregation and episode selection scheme for EPA’s Models-3 CMAQ. 

Presentation at the Environmental Statistics Seminar Series at North Carolina State 

University, Raleigh, NC, April 20, 2000. 

Eder, B.K. A Preliminary Evaluation of Models-3 CMAQ Using Visibility Parameters. 

Presentation at the 14th Annual International Symposium on the Measurement of Toxic 

and Related Air Pollutants, Research Triangle Park, NC, September 13, 2000. 

Fine, S.S. Status of MIMS architecture design. Presentation at Cross-Discipline Ecosystem 

Modeling and Analysis Workshop, Research Triangle Park, NC, August 16, 2000. 

Fine, S.S. A framework for creating and managing graphical analyses. Presentation at CrossDiscipline Ecosystem Modeling and Analysis Workshop, Research Triangle Park, NC, 

August 17, 2000. 

Fine, S.S. Multimedia Integrated Modeling System update. Presentation at Council on 

Regulatory Environmental Modeling, Washington, DC, September 7, 2000. 

Gillette, D.A. K factor comparisons with Fa/q. Presentation at the Review of Preliminary 

Findings of the Owens Lake Dust ID Project, Bishop, CA, June 15, 2000. 

Gilliland, A.B. Introduction: MIMS ecosystem modeling integration efforts. Presentation at the 

Cross-Discipline Ecosystem Modeling and Analysis Workshop, Research Triangle Park, 

NC, August 15, 2000. 

Lawson, R.E., Jr., R.S. Thompson, S.G. Perry, and W.H. Snyder. Modeling puff diffusion in a 

laboratory convection tank. Presentation at the 11th Joint Conference on the Applications 

of Air Pollution Meteorology with the A&WMA, Long Beach, CA, January 10, 2000. 

75
 
LeDuc, S.K. Lightning safety. Presentation to two Kindergarten classes at Sangamon 

Elementary School, Mahomet, IL, October 21, 1999. 

LeDuc, S.K. Lightning safety. Presentation to two 4th grade classes at Lincoln Trail Elementary 

School, Mahomet, IL, October 21, 1999. 

LeDuc, S.K. Lightning safety. Presentation to three 1st grade classes at Memorial Elementary 

School, Paris, IL, October 22, 1999. 

LeDuc, S.K. An overview of Models-3/CMAQ. Presentation to the Air Pollution Training 

Institutes Satellite Broadcast, Research Triangle Park, NC, December 9, 1999. 

LeDuc, S.K. An overview of Models-3/CMAQ. Presentation to the Mid-Atlantic Region Air 

Managers Association, Wilmington, DE, January 12, 2000. 

LeDuc, S.K. Expanding your horizons weather jeopardy. Presentation to an audience of 7th 

grade girls at North Carolina State University, Raleigh, NC, March 14, 2000. 

Otte, T.L. Lightning. Presentation to four 5th grade classes at Zebulon Elementary School, 

Zebulon, NC, December 3, 1999. 

Otte, T.L. Evaporation and condensation. Presentation to five 2nd grade classes, Smith 

Elementary School, Raleigh, NC, December 17, 1999. 

Otte, T.L. Careers in meteorology (3 sessions). Presentation at Carroll Middle School, Raleigh, 

NC, March 24, 2000. 

Otte, T.L. Evaporation and condensation (3 sessions). Presentation to the 2nd grade at West Lake 

Elementary School, Apex, NC, April 7, 2000. 

Otte, T.L. Evaporation and condensation (4 sessions). Presentation to the 2nd grade at Willow 

Springs Elementary School, Willow Springs, NC, May 5, 2000. 

Otte, T.L. Using Eta model analyses to initialize MM5 v3. (Brown bag seminar). Presentation 

to AMDB, Research Triangle Park, NC, May 25, 2000. 

Otte, T.L. MM5: A community prototype for CMAS. Presentation at the First Annual Models-3 

Workshop, Arlington, VA, June 13, 2000. 

Otte, T.L., and S.K. LeDuc. Weather jeopardy (2 sessions). Presentation at 8th Expanding Your 

Horizons Workshop, North Carolina State University, Raleigh, NC, March 14, 2000. 

Perry, S.G. Overview of AERMOD dispersion model. Presentation to the Neighborhood Scales 

Working Group, Research Triangle Park, NC, June 1, 2000. 

76
 
Pierce, T.E. Winter storms. Presentation at Durant Elementary School, Raleigh, NC, December 

20, 1999. 

Pierce, T.E. The importance of lightning and other natural sources of NOx and VOCs for 

regional air quality modeling. Invited presentation at the Universities Space Research 

Association, Huntsville, AL, October 20, 1999. 

Pierce, T.E. Overview of the OZark Isoprene Experiment (OZIE). Presentation at the Fall 

Meeting of the American Geophysical Union, San Francisco, CA, December 14, 1999. 

Pierce, T.E. Advances in biogenic emissions modeling. Invited presentation at the California 

Air Resources Board’s Workshop on Biogenic Emissions Research, Sacramento, CA, 

December 9, 1999. 

Pierce, T.E. Issues regarding isoprene emissions for ozone model simulations. Presentation at 

the Ad Hoc Emission Modeling Workshop, Baltimore, MD, January 20, 2000. 

Pierce, T.E. The evolution of biogenic emission inventory modeling systems for regional air 

quality modeling. Invited presentation at the Gordon Research Conference on Biogenic 

VOCs and the Atmosphere, Ventura, CA, March 2, 2000. 

Pierce, T.E. The role of agriculture on airborne nitrogen emissions. Presentation at the 

Ammonia Emission Modeling Workshop, Beltsville, MD, March 22, 2000. 

Pierce, T.E. Development of a 1-km vegetation database for modeling biogenic fluxes of 

hydrocarbons and nitric oxide, Sixth International Conference on Air-Surface Exchange 

of Gases and Particles, Edinburgh, United Kingdom, July 3, 2000. 

Pierce, T.E. Development of a 1-km vegetation cover database. Presentation at the CrossDiscipline Ecosystem Modeling and Analysis Workshop, Research Triangle Park, NC, 

August 17, 2000. 

Pleim, J.E. Dry deposition modeling in the Models-3 Community Multiscale Air Quality 

(CMAQ) model system. Presentation at the Workshop on Dry Deposition in North 

America, Washington, DC, May 22, 2000. 

Pleim, J.E. A coupled land-surface and dry deposition model and comparison to field 

measurements of surface heat, moisture, and ozone fluxes. Presentation at the 6th 

International Conference on Air-Surface Exchange of Gases and Particles in Edinburgh, 

Scotland, July 5, 2000. 

Poole-Kober, E.M. Atmospheric Science Librarians International. Poster presentation at the 25th 

IAMSLIC Annual Conference, Woods Hole, MA, October 20, 1999. 

77
 
Poole-Kober, E.M. Field study experience at the Atmospheric Sciences Modeling Division. 

Spring Field Experience Reception, Student Chapter of the Special Library Association, 

University of North Carolina at Chapel Hill, Chapel Hill, NC, April 13, 2000. 

Schere, K.L. Status and applications of Models-3/CMAQ. Presentation at US/German Ozone, 

Fine Particle Science and Environmental Chamber Workshop, Riverside, CA, October 5, 

1999. 

Schere, K.L. Models-3/CMAQ - The future of air quality modeling. Presentation at the 

Conference on Transportation Planning and Air Quality, Lake Lanier, GA, November 17, 

1999. 

Schere, K.L. CMAQ model overview. Presentation for the satellite broadcast course on 

Nitrogen Compounds and Air Quality in the Troposphere, Raleigh, NC, December 9, 

1999. 

Schere, K.L. Recent developments in air quality modeling. Presentation at the Conference on 

Environmental Monitoring, Evaluation, and Protection in New York: Linking Science 

and Policy, Albany, NY, December 8, 1999. 

Schere, K.L. Models-3/CMAQ and the community modeling concept. Presentation to the 

CENR-Air Quality Research Subcommittee in Washington, DC, February 18, 2000. 

Schere, K.L. Briefing on Models-3/CMAQ. Presentation to the Administrator, OAQPS, 

Durham, NC, March 29, 2000. 

Schere, K.L. Regional/urban air quality modeling with U.S. EPA's Models-3/CMAQ. 

Presentation at Harvard University, Department of Earth and Planetary Sciences, 

Cambridge, MA, April 7, 2000. 

Schere, K.L. Use of PM data in model evaluation. Presentation at the Eastern Supersites 

Meeting, Baltimore, MD, April 12, 2000. 

Schere, K.L. Urban/regional air quality modeling with U.S. EPA's Models-3/CMAQ. 

Presentation at the National Research Council, Committee on Atmospheric Chemistry, 

Washington, DC, May 11, 2000. 

Schere, K.L. Regional/urban tropospheric air quality modeling with U.S. EPA's 

Models-3/CMAQ. Presentation at the University of Alabama - Huntsville, Huntsville, 

AL, May 31, 2000. 

Schere, K.L. U.S. EPA Models-3/CMAQ: What's New in 2000? Presentation at the First 

Annual Models-3 Workshop, Arlington, VA, June 12, 2000. 

78
 
Schere, K.L. Models-3/CMAQ: A system for air quality modeling. Presentation at the Air 

Quality and Environmental Forecasting Workshop, Silver Spring, MD, June 15, 2000. 

Schere, K.L. Status of the Models-3/CMAQ modeling system. Presentation at the NARSTO 

Reactivity Research Work Group Meeting, Research Triangle Park, NC, June 30, 2000. 

Schiermeier, F.A. Demonstration of the Supercomputing Center and Scientific Visualization 

Laboratory. Presentation for the EPA/OEI Assistant Administrator, Research Triangle 

Park, NC, October 19, 1999. 

Schiermeier, F.A. Demonstration of the Supercomputing Center and Scientific Visualization 

Laboratory. Presentation for the Environmental Counselor of The Netherlands Embassy 

and the Director of RIVM in The Netherlands, Research Triangle Park, NC, March 15, 

2000. 

Schiermeier, F.A. Past history and future plans for International Technical Meetings on Air 

Pollution Modeling and Its Application. Presentation at the NATO/CCMS Plenary 

Meeting of Partner and Alliance Countries, Brussels, Belgium, March 21, 2000. 

Schiermeier, F.A. Great Waters and regional deposition applications. Presentation at the 

Standing Air Simulation Work Group Meeting, Asheville, NC, April 1, 2000. 

Schiermeier, F.A. Examples of AMD outreach activities. Presentation at the NERL Mid-Year 

Review by the EPA/ORD Assistant Administrator and the EPA/ORD Deputy Assistant 

Administrators, Research Triangle Park, NC, April 5, 2000. 

Schiermeier, F.A. Conference Chairman opening address, closing address, and banquet award 

conferrals. Presentations at the Millennium (24th) NATO/CCMS International Technical 

Meeting on Air Pollution Modeling and Its Application, Boulder, CO, May 15-19, 2000. 

Schiermeier, F.A. Past history and future plans for International Technical Meetings on Air 

Pollution Modeling and Its Application. Presentation at the Millennium (24th) 

NATO/CCMS International Technical Meeting on Air Pollution Modeling and Its 

Application, Boulder, CO, May 19, 2000. 

Schiermeier, F.A. Demonstration of the Supercomputing Center and Scientific Visualization 

Laboratory. Presentation to the EPA/OEI Assistant Administrator and Deputy Assistant 

Administrator, Research Triangle Park, NC, June 1, 2000. 

Schiermeier, F.A. Perspectives on the probability of success for CMAS (Community Modeling 

and Analysis System) and next steps. Presentation at the First Annual Models-3 

Workshop, Arlington, VA, June14, 2000. 

79
 
Schiermeier, F.A. Demonstration of the Supercomputing Center and Scientific Visualization 

Laboratory. Presentation for the EPA/OAR and EPA/OEI Assistant Administrators, 

Research Triangle Park, NC, September 11, 2000. 

Schiermeier, F.A. Contractual support required for the Atmospheric Modeling Division's 

research programs. Presentation at the Meeting on Federal Dollar$ and Sense for Women 

Owned Businesses, U.S. Small Business Administration, Research Triangle Park, NC, 

September 19, 2000. 

Schiermeier, F.A. Overview of the EPA/ORD atmospheric research programs. Presentation to 

the ICMSSR Committee for Agency Cooperative Research, Washington, DC, September 

21, 2000. 

Streicher, J.J.. Modeling acute exposure to solar radiation radiation. Presentation at the 

American Society for Photobiology Meeting, San Francisco, CA, July 3, 2000. 

80
 

APPENDIX D: WORKSHOPS AND MEETINGS
 


US/German O3/PM Science and Environmental Chamber Workshop, Riverside, CA, October 

4–6, 1999. 

K.L. Schere 

Workshop: Review of Persistent Organic Pollutants and Heavy Metals under the Convention on 

Long Range Transboundary Air Pollution (LRTAP), Durham, NC, October 5–7, 1999. 

J.K.S. Ching 

NARSTO Reactivity Research Work Group, Riverside, CA, October 7, 1999. 

K.L. Schere 

NARSTO Synthesis Team Meeting, Washington, DC, October 18–20, 1999. 

K.L. Schere 

Atmospheric Deposition of Toxics - Science & Policy Workshop, Chicago, IL, October 21–22, 

1999. 

O.R. Bullock, Jr. 

Fall 1999 Standing Air Emissions Working Group, Stevenson, WA, October 23–24, 1999. 

W.G. Benjey 

Texas 2000 Planning Meeting, Houston, TX, November 9–10, 1999. 

R.L. Dennis 

ASCE Conference on Transportation Planning and Air Quality, Lake Lanier, GA, November 

16–17, 1999. 

K.L. Schere 

UNEP/WMO Workshop on Modeling Heavy Metals and POPs, Geneva, Switzerland, November 

16–19, 1999. 

O.R. Bullock, Jr. 

81
 
Models-3/CMAQ for Western Regional Air Partnership (WRAP), Salt Lake City, UT, November 

30–December 3, 1999. 

J.K.S. Ching 

Particulate Matter Workshop, Research Triangle Park, NC, December 6–8, 1999. 

D.W. Byun 

J.K.S. Ching 

Conference on Environment Monitoring, Evaluation, and Protection in New York: Linking 

Science and Policy, Albany, NY, December 6–8, 1999. 

K.L. Schere 

Megacity Impact on Regional and Global Environments (MIRAGE) Meeting with NCAR 

Modelers, Boulder, CO, December 7, 1999. 

R.L. Dennis 

Workshop on Biogenic Emissions Research, Sacramento, CA, December 8–9, 1999. 

T.E. Pierce 

EPA/ORD Mercury Research Strategy Peer Review Workshop, Washington, DC, December 8–9, 

1999. 

O.R. Bullock, Jr. 

Gulf of Mexico Program Office Workshop on Nitrogen Deposition to Gulf Coast Estuaries, 

Houston, TX, December 8–10, 1999. 

R.L. Dennis 

Fall Meeting of the American Geophysical Union, San Francisco, CA, December 11–16, 1999. 

P.L. Finkelstein 

T.E. Pierce 

Third Annual Meeting of the Atmospheric Science Librarians International, Long Beach, CA, 

January 9–14, 2000. 

E.M. Poole-Kober 

82
 
Workshop on Coupling Multi-Physics Problems in Environmental Simulation, Vicksburg, MS, 

January 11–12, 2000. 

A.B. Gilliland 

ASTM D22.11 Subcommittee meeting, Long Beach, CA, January 13, 2000. 

J.S. Irwin 

RARE Field Project, Ft. Lauderdale, FL, January 15–22, 2000. 

O.R. Bullock, Jr. 

Ad Hoc Emission Modeling Workshop, Baltimore, MD, January 20–21, 2000. 

W.G. Benjey 

T.E. Pierce 

Technically Advanced Smoke Emissions Tools (TASET) Workshop, Ft. Collins, CO, February 

2–4, 2000. 

J.K.S. Ching 

NARSTO NorthEast Ozone and Particulate Study (NEOPS) Workshop, Wilmington, DE, 

February 7–9, 2000. 

R.L. Dennis 

North Carolina Regional Science Bowl, North Carolina Central University, Durham, NC, 

February 12, 2000. 

T.L. Otte 

Nitrogen 2001 Planning Workshop, Washington, DC, February 15–16, 2000. 

R.L. Dennis 

CENR Meeting on Models-3/CMAQ, Washington, DC, February 18, 2000. 

R.L. Dennis 

K.L. Schere 

F.A. Schiermeier 

83
 
Airborne Visible and InfraRed Spectrometer (AVIRIS) Workshop, Pasadena, CA, February 

23–25, 2000. 

J.J. Streicher 

NARSTO Synthesis Team Writing Workshop at Georgia Institute of Technology in Atlanta, 

Atlanta, GA, February 23–25, 2000. 

K.L. Schere 

Gordon Research Conference on Biogenic VOCs and the Atmosphere, Ventura, CA, 

February 27–March 3, 2000. 

T.E. Pierce 

Chesapeake Bay Air Subcommittee Meeting, Annapolis, MD, February 29, 2000. 

R.L. Dennis 

Workshop on Modeling Chemistry in Cloud and Air Quality Models, National Center for 

Atmospheric Research, Boulder, CO, March 6–8, 2000. 

F.S. Binkowski 

S.J. Roselle 

Southern Oxidants Study Data Workshop, Research Triangle Park, NC, March 6–10, 2000. 

J.R. Arnold T.L. Otte 

D.W. Byun J.E. Pleim 

J.K.S. Ching K.L. Schere 

R.L. Dennis 

NARSTO Executive Steering Committee Meeting, Washington DC, March 8–9, 2000. 

J.L. West 

Eighth Expanding Your Horizons Workshop, North Carolina State University, Raleigh, NC, 

March 14, 2000. 

S.K. LeDuc 

T.L. Otte 

84
 
Institute for Mathematics and Its Applications Workshop: Atmospheric Modeling, University of 

Minnesota, Minneapolis, MN, March 15–19, 2000. 

F.S. Binkowski 

D.W. Byun 

J.K.S. Ching 

J.E. Pleim 

Ammonia Emission Modeling Workshop, Beltsville, MD, March 21–23, 2000. 

W.G. Benjey 

T.E. Pierce 

Standing Air Emissions Working Group, Asheville, NC, March 31–April 1, 2000. 

W.G. Benjey 

F.A. Schiermeier 

Tenth Annual SAIL Conference, Research Triangle Park, NC, April 5–7, 2000. 

J.K.S. Ching J.E. Pleim 

R.L. Dennis E.M. Poole-Kober 

P.L. Finkelstein F.A. Schiermeier 

T.L. Otte 

Annual ASTM D22 Committee and Subcommittee Meetings, Toronto, Canada April 11–12, 

2000. 

J.S. Irwin 

EPA Supersites Principal Investigators Meeting, Baltimore MD, April 12–13, 2000. 

K.L. Schere 

J.L. West 

Shenandoah Assessment Planning Meeting, Shenandoah National Park, VA, April 12–13, 2000. 

R.L. Dennis 

Mercury Modeling Intercomparison Workshop Atmospheric Mercury Models, Meteorological 

Synthesizing Center - East, Moscow, Russia, April 13–14, 2000. 

O. R. Bullock, Jr. 

85
 
Mercury Source-Receptor Relationship Expert Panel, Madison, WI, May 22–23, 2000. 

O. R. Bullock, Jr. 

EPA Dry Deposition Workshop, Washington, DC, May 22–24, 2000. 

R.L. Dennis 

P.L. Finkelstein 

M. Fuentes 

NARSTO PM Assessment Team Meeting, Washington DC, May 24–26, 2000. 

J.L. West 

RARE Field Project, 2nd Phase, Ft. Lauderdale, FL, June 1–11, 2000. 

O.R. Bullock, Jr. 

MARAMA-SESARM/Metro 4 Workshop: PM2.5 Emissions Inventory Workshop, Raleigh, NC, 

June 5–7, 2000. 

W.G. Benjey 

F.S. Binkowski 

Research Uses of the UVB Monitoring Network, Albuquerque, NM, June 6–7, 1999. 

J..J. Streicher 

Workshop on Multiscale Atmospheric Dispersion Modeling, Washington, DC, June 6–8, 2000. 

A.H. Huber 

R.E. Lawson, Jr. 

W.B. Petersen 

First Annual Models-3 Workshop, Arlington, VA, June 12-14, 2000. 

D.A. Atkinson S.K. LeDuc 

W.G. Benjey J.H. Novak 

R.L. Dennis T.L. Otte 

P.D. Dolwick K.L. Schere 

M.L. Evangelista F.A. Schiermeier 

86
 
Regional/State Workshop, Arlington, VA June 14–16, 2000. 

J.S. Irwin 

NOAA/OAR Air Quality and Environmental Forecasting Modeling Workshop, Silver Spring, 

MD, June15, 2000. 

K.L. Schere 

F.A. Schiermeier 

Human Exposure Source-to-Dose Modeling Research University Partnership Agreements: 2nd 

Annual Planning Meeting, Research Triangle Park, NC, June 21, 2000. 

J.K.S. Ching 

K.L. Schere 

Tenth PSU/NCAR Mesoscale Model Users' Workshop, Boulder, CO, June 21–22, 2000. 

D.W. Byun 

T.L. Otte 

J.E. Pleim 

First Annual WRF Workshop, Boulder, CO, June 23, 2000. 

D.W. Byun 

T.L. Otte 

PSU/NCAR Mesoscale Modeling System Workgroup, Boulder, CO, June 26–29, 2000. 

P.D. Dolwick 

Workshop on Combining Environmental Fate and Air Quality Modeling, Research Triangle 

Park, NC, June 27–29, 2000. 

F.S. Binkowski 

NARSTO Reactivity Research Work Group Meeting, Research Triangle Park, NC, June 30, 

2000. 

K.L. Schere 

87
 
Sixth International Conference on Air-Surface Exchange of Gases and Particles, Edinburgh, 

United Kingdom, July 3–7, 2000. 

P.L. Finkelstein 

T.E. Pierce 

J.E. Pleim 

D.B. Schwede 

Fourth Annual George Mason University Transport and Dispersion Modeling Workshop, 

Fairfax, VA, July 11–12, 2000. 

D.W. Byun 

Place-Based Decision Support System Workshop, Denver, CO, July 15–17, 2000. 

S.S. Fine 

First International Workshop on Trans-Pacific Transport of Atmospheric Contaminants, Seattle, 

WA, July 27-29, 2000. 

F.A. Schiermeier 

NOAA Air Quality Forecasting and Prediction Workshop, Boulder, CO, August 3–4, 2000. 

K.L. Schere 

EPA Managing Quality Systems Training Conference, Chicago, IL, August 7–9, 2000. 

J.L. West 

EPA MIMS Workshop, Research Triangle Park, NC, August 15–17, 2000. 

R.L. Dennis J.H. Novak 

S.S. Fine T.E. Pierce 

P.L. Finkelstein D.B. Schwede 

A.B. Gilliland 

Ad Hoc Meteorological Modeling Workgroup, College Park, MD, August 16–17, 2000. 

P.D. Dolwick 

NARSTO Assessment Workshop, Baltimore, MD, September 18–20, 2000. 

R.L. Dennis 

88
 
NARSTO Model Intercomparison Workshop, Chicago, IL, September 26–27, 2000. 

J.R. Arnold 

R.L. Dennis 

Cross-Discipline Ecosystem Modeling and Analysis Workshop, Research Triangle Park, NC, 

August 15–17, 2000. 

W.G. Benjey J.H. Novak (co-chair 

D.W. Byun T.L. Otte 

J.K.S. Ching T.E. Pierce 

R.L. Dennis J.E. Pleim 

S.S. Fine S.J. Roselle 

A.B. Gilliland (organizer/co-chair) D.B. Schwede 

S.C. Howard A.R. Torian 

S.K. LeDuc J.O. Young 

International Symposium on Measurement of Toxic and Related Air Pollutants, Research 

Triangle Park, NC, September 12–14, 2000. 

O.R. Bullock, Jr. S.G. Perry 

J.K.S. Ching W.B. Petersen 

B.K. Eder T.E. Pierce 

B.W. Gay J.E. Pleim 

W.T. Hutzell S.J. Roselle 

S.K. LeDuc K.L. Schere 

M.R. Meburst J.L. West 

T.L. Otte 

Hyperspectral Imagery and Water Quality Workshop, Raleigh, NC, September 15, 2000. 

A.B. Gilliland 

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APPENDIX E: VISITING SCIENTISTS 

1.	 	 Dr. Deborah H. Bennett 

Lawrence Berkeley National laboratory 

Cyclotron Road, MS-903058 

Berkeley, CA 94720 

Dr. Bennett visited FMF on June 20, 2000, for the day to discuss potential collaboration on 

pesticide spray drift modeling. 

2.	 	 Mr. Alan Cimorelli 

EPA Region 3 

Philadelphia, PA 

Mr. Cimorelli visited FMF from March 6 to March 10, 2000, to collaborate on AERMOD 

development project. 

3.	 	 Dr. Thomas E. Gill 

Wind Science & Engineering 

Department of Civil Engineering 

Texas Tech University 

Lubbock, TX 

Dr. Gill visited FMF from May 31 to June 2, 2000, to discuss the collaborative project on aerosol 

chemistry. 

4.	 	 Dr. Sven-Erik Gryning 

Riso National Laboratory 

Roskilde, Denmark 

Dr. Sven-Erik Gryning visited the Division on November 17 and 18, 1999, to aid the Division 

Director in the final selection of papers and posters to be presented at the Millennium (24th) 

NATO/CCMS International Technical Meeting on Air Pollution Modeling and Its Application to 

be held in Boulder, CO, during May 2000. 

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5.	 	 Dr. Shan He 

University of Iowa 

Civil and Environmental Department 

Center for Global and Regional Environmental Research 

Iowa City, IA 

Dr. Shan He visited the Division on July 20, 2000, to present a seminar on The impact of 

tropospheric aerosol-radiation interaction on photochemical oxidant cycle and climate forcing. 

6.	 	 Dr. Gabriel Katul 

School of the Environment 

Duke University 

Durham, NC 

Dr. Katuland and six students visited FMF on March 29, 2000, as part of the Environmental 

Engineering 356 class to observe experiments in the wind tunnels and convection tank. 

7..	 	 Dr. Avi Lacser 

Israel Institute for Biological Research 

Ness Ziona 

Israel 

Dr. Avi Lacser arrived on October 25, 1999, to work for approximately two years with AMDB 

on neighborhood scale modeling. 

8.	 	 Mr. Chris Leigh 

Mr. David Mottershead 

Dr. Trudie McMullen 

UK Department of the Environment 

National Air Quality Strategies Group 

London, England 

Mr. Chris Leigh, Mr. David Mottershead, and Dr. Trudie McMullen visited the Division on 

November 19, 1999, to discuss Division modeling activities. 

9.	 	 Rokjin Park 

Department of Meteorology 

University of Maryland 

College Park, MD 

Mr. Park visited the Division on July 20 and 21, 2000, to coordinate work on the CMAQ 

photolysis rate model. 

91
 
10.	 	 Dr. S.T. Rao 

New York Department of Environmental Conservation 

Albany, NY 

Dr. Prasad Kasibhatla 
 


Duke University
 


Durham, NC
 


Dr. S.T. Rao and Dr. Prasad Kasibhatla visited the Division on February 10, 2000, to present a 

seminar entitled An intercomparison study of two regional-scale photochemical modeling 

systems. 

11.	 	 Dr. Qingyun Song 

Atmospheric Environment Service 

Ontario, Canada 

Dr. Song visited the Division from February 27 to March 10, 2000, to test a new resolved cloud 

model in CMAQ. 

12.	 	 Dr. Seiji Sugata 

Takezono 1-803-506 

Tsukuba, Ibaraki, 305-0032 

Japan 

Dr. Seiji Sugata visited the Division from May 22 to 26, 2000, to discuss Models-3/CMAQ. 

13.	 	 Dr. Jay Turner, and Mr. Brian Long 

Department of Environmental Policy 

Washington University 

St. Louis, MO 

Dr. Turner and Mr. Long visited the Division on February 25, 2000, to discuss research findings 

from the OZark Isoprene Experiment (OZIE). 

14.	 	 Dr. Jeffery Weil 

CIRES 

Boulder, CO 

Dr. Weil visited FMF on March 2 and 3, 2000, to collaborate on an internal grant project on 

convective boundary layer. 

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APPENDIX F: HIGH SCHOOL, UNDERGRADUATE, AND GRADUATE
 


STUDENTS, AND POSTDOCTORAL RESEARCHERS 

1.	 	 Dr. Jeffrey R. Arnold 

University Corporation for Atmospheric Research 

Boulder, Colorado 

Dr. Arnold, a postdoctoral researcher, is in his third year with the Division. Dr. Arnold is 

developing more advanced methods to extend the state of the art of diagnostic model evaluation 

applicable to complex, nonlinear photochemical models, to codify the new evaluation techniques, 

and to make weight-of-evidence approaches objective. 

2.	 	 Rokjin Park 

Department of Meteorology 

University of Maryland 

College Park, MD 

Mr. Park, a graduate student, is working with the Division to develop a method for adjusting 

photolysis rates for the presence of aerosols. 

3.	 	 Dr. Shan He 

University Corporation for Atmospheric Research 

Boulder, CO 

Dr. He, a post-doctoral researcher, is working with the Division on air quality model evaluation 

for particulate matter. He began a 2-year visit with the Division on August 21, 2000. 

4.	 	 Mr. Jason Smith 

University of North Carolina at Chapel Hill 

Chapel Hill, NC 

Mr. Smith, a research assistant funded through UCAR, assisted in the software framework design 

of the Multimedia Intergrated Modeling System (MIMS). 

93
 

5.	 	 Dr. Gail S. Tonnesen 

University Corporation for Atmospheric Research 

Boulder, Colorado 

Dr. Tonnesen, a postdoctoral researcher, completed her third year with the Division. Dr. 

Tonnesen investigated the identification of indicator ratios of ambient concentrations of 

photochemically active trace gases that might distinguish the sensitivity of the local production 

of ozone to NOX and VOC emissions in the ambient atmosphere for the testing of air quality 

models. The tests were developed from theoretical considerations of atmospheric 

photochemistry. 

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APPENDIX G: ATMOSPHERIC SCIENCES MODELING DIVISION
 


STAFF AND AWARDS
 


All personnel are assigned to the U.S. Environmental Protection Agency from the National 

Oceanic and Atmospheric Administration, except those designated EPA, who are employees of 

the EPA; PHS, who are members of the Public Health Service Commissioned Corps, or SEEP, 

who are part of the Senior Environmental Employment Program. 

Office of the Director 

Francis A. Schiermeier, Supervisory Meteorologist, Director
 


Herbert J. Viebrock, Meteorologist, Assistant to the Director
 


Dr. Robin L. Dennis, Physical Scientist
 


Dr. Basil Dimitriades (EPA), Physical Scientist (Until June 2000)
 


Dr. Peter L. Finkelstein, Physical Scientist
 


Bruce W. Gay, Jr. (EPA), Program Manager
 


Evelyn M. Poole-Kober, Librarian
 


Jeffrey L. West, Physical Science Administrator (Since May 2000)
 


Barbara R. Hinton (EPA), Secretary
 


Atmospheric Model Development Branch 

Kenneth L. Schere, Supervisory Meteorologist, Chief
 


Dr. Francis S. Binkowski, Meteorologist
 


O. Russell Bullock, Jr., Meteorologist
 


Dr. Daewon W. Byun, Physical Scientist
 


Dr. Jason K.S. Ching, Meteorologist
 


Dr. Brian K. Eder, Meteorologist
 


Gerald L. Gipson (EPA), Physical Scientist
 


James M. Godowitch, Meteorologist
 


Dr. William T. Hutzell (EPA), Physical Scientist 
 


Dr. Michelle R. Mebust (EPA), Physical Scientist
 


Tanya L. Otte, Meteorologist 
 


Dr. Jonathan E. Pleim, Physical Scientist
 


Shawn J. Roselle, Meteorologist
 


Tanya L. McDuffie, Secretary 
 


95
 

Modeling Systems Analysis Branch 

Joan H. Novak, Supervisory Computer Specialist, Chief (Until September 2000) 

Dr. William G. Benjey, Physical Scientist 

Dr. Steven S. Fine, Computer Specialist (Since June 2000) 

Dr. Alice B. Gilliland, Physical Science Administrator 

Steven C. Howard, Computer Specialist 

Dr. Sharon K. LeDuc, Physical Scientist 

Thomas E. Pierce, Meteorologist 

John H. Rudisill, III, Equipment Specialist 

Alfreida R. Torian, Computer Specialist 

Gary L. Walter, Computer Scientist 

Dr. Jeffrey O. Young, Mathematician 

Carol C. Paramore, Secretary (Until September 2000) 

Applied Modeling Research Branch 

William B. Petersen, Supervisory Physical Scientist, Chief 

Dr. Ellen J. Cooter, Meteorologist 

Dr. Dale A. Gillette, Physical Scientist 

Dr. Alan H. Huber, Physical Scientist 

Robert E. Lawson, Jr., Physical Scientist (Until September 2000) 

Dr. Steven G. Perry, Meteorologist 

Donna B. Schwede, Physical Scientist 

John J. Streicher, Physical Scientist 

CDR. Roger S. Thompson (PHS), Environmental Engineer (Until July 2000) 

Lawrence E. Truppi, Meteorologist 

Jonathan Petters (EPA), Engineering Technician (Summer) 

Ashok Patel (SEEP), Engineer 

John Rose (SEEP), Machinist/Model Maker 

Bruce Pagnani (SEEP), Computer Programmer 

Sherry A. Brown, Secretary 

Air Policy Support Branch 

Mark L. Evangelista, Supervisory Meteorologist, Chief 

Dennis A. Atkinson, Meteorologist 

Dr. Desmond T. Bailey, Meteorologist 

Patrick D. Dolwick, Physical Scientist 

John S. Irwin, Meteorologist 

Brian L. Orndorff, Meteorologist 

Norman C. Possiel, Jr., Meteorologist 

Jawad S. Touma, Meteorologist 

96
 
FY-2000 AWARD 

Air Resources Laboratory Paper of the Year Award - 1999, awarded in October 2000. 

Byun, D.W. Dynamically consistent formulations in meteorological and air quality models for 

multiscale atmospheric studies. Part I: Governing equations in a generalized coordinate 

system. Journal of the Atmospheric Sciences 56:3789–3807 (1999). 

Byun, D.W. Dynamically consistent formulations in meteorological and air quality models for 

multiscale atmospheric studies. Part II: Mass conservation issues. Journal of the 

Atmospheric Sciences 56:3808–3820 (1999). 

97