REGIQNAL AIR QUALITY MGDEL W
e take the Earth's atmo-
sphere for granted. Why shouldn't we? It is a literal fact of life: it is as it is because of life. We and all other living creatures have spent some 3 billion years evolving beneath its protective and sustaining umbrella. For all we know this may be a universal record for sustainability, and it is our nature to wish it extended far into the future for our descendants. For that to happen, humans must not perturb the atmospheric composition beyond the bounds of their sustainability. Not too long ago, the atmosphere seemed so vast and we so puny that the very idea of humankind having any influence on the mighty natural forces at play within it was surely in the realm of fiction. But as our population has soared with its concomitant demands for energy, space, shelter, and food, so has the quantity of industrial and agricultural emissions we pour into the atmosphere. We have come to understand that these emitted materials can impair, or at least shift, the health of not just compartments hut the whole global ecosystem-not to mention our aesthetic appreciation of it. Our emissions increasingly are doing just that. Accordingly, air
pollution and climate alteration are issues of immediate concern worldwide. This article describes an international initiative that addresses regional and smaller scale air pollution. It should provide an advanced set of tools for air quality managers to use in making scientifically
D. ALAN HANSEN Electric Power Research Institute Palo Alto, CA 94304
ROBIN L. DENNIS EPA Research Triangle Park, NC 27711
ADOLF EBEL Universitat Z u Koln 0-5000Koln I , Germany
STEVEN R. HANNA Sigma Research Corporation Concord, MA 01742
JACK KAYE NASA Headquarters Washington, DC 20546
RICHARD THUILLIER Pacific Gas and Electric Company San Ramon, CA 94583
based policy decisions. We will refer to these tools as comprehensive modeling systems [CMSs) because of the depth and breadth of their formulations and applications. The initiative is being carried out by the Consortium for Advanced Modeling of Region Air Quality (CAMRAQ). This article explains why the consortium feels the time for a CMS is opportune, what CAMRAQ's objectives are, how we are organized, what our roots are, how we are approaching coordinated research, where we currently are collaborating on projects, and what opportnnities we see for ftture collaboration.
Background Numerous issues confront those who must make and those who must respond to air quality management decisions. A particularly nettlesome issue at present is tropospheric ozone. For example, in North America dozens of urban areas are not in compliance with federal and other ambient air quality standards and guidelines for ozone. Similar conditions exist throughout the world near urhan and industrial complexes. Elevated ozone concentrations are usually the result of photochemical reactions involving nitrogen oxides and organic gases. Environ. Sci. Technol., Vol. 28, No. 2. 1994 71 A
(We s a y “ u s u a l l y ” b e c a u s e tropopause folding can allow stratospheric ozone to mix downward to the ground 13). What makes this problem especially perplexing is that the reactions are extremely complex and nonlinear; reducing one or the other of these ozone precursors does not necessarily lead to ozone reduction. Further, because of atmospheric transport, ozone or emissions of its precursors in one area can influence air quality hundreds of kilometers downwind. These and other scientific and technological complications-as well as questions of equity regarding whose emissions should be reduced because such reductions can require substantial capital outlays]-make the formulation of ozone attainment strategies very difficult. Other issues demanding the attention of air quality regulators are toxic airborne materials and visibility impairment. And even though the immediacy of the acid rain issue has diminished as precursor emission reductions have been mandated and other competing issues have arisen, it is still with us. In the final analysis, these issues are always addressed in the regulatory arena by requirements for emission controls. To estimate how exposures derived from concentrations in the atmosphere will respond to changes in emissions of undesirable materials and their precursors. we must understand where the emissions occur, how they are transported and dispersed through the atmosphere, what chemical and physical transformations occur, how they are removed, and the rates of all these processes. In the case of visibility, we must understand the optical properties of airborne materials and the response of human vision to them. As with ozone, this understanding is required to formulate strategies to ameliorate conditions. Some important nonregulatory issues include real or hypothetical emergencies in which we need to estimate exposures and effects resulting from the release of undesirable (or worse) substances into the atmosphere, such as occurred at Chernobyl, from the Kuwaiti oil fires, or from the use of chemical or nuclear weapons. And finally there is the issue of enhancing our theoretical understanding of the highly interactive chemical and physical d y n a m i c s of t h e t r o p o s p h e r e through a systematic analysis of the 72 A Envimn. Sci. Technol., VoI. 28. No. 2, 1994
processes involved. Each of these issues can be addressed wholly or in part through the use of numerical simulation models. We in CAMRAQ believe that these models are fundamentally the best available type of tool for establishing a workable link between scientific understanding and policy analysis. Other advantages of numerical models are their intrinsic ability to integrate all the relevant scientific knowledge we care to include, the control we have over
Icomputer sciencd and scientific understanding of the troposphere will soon allow convenient and sklllful computer simulations to be made that addre all air quality issues in concert
l
their governing conditions (i.e., their initial and boundary conditions and other inputs), and the ability they give us to examine details of complex, interacting systems. With models we have a degree of control and a capability for exploring virtual realities beyond those available to us through field and laboratory experimentation, particularly when dealing with atmospheric phenomena. Further, we in CAMRAQ have concluded that modeling, computer science, and scientific understanding of the troposphere will soon allow convenient and skillful com-
puter simulations to be made that address all the above issues in concert. We desire this capability for simultaneity because many of the issues are interrelated and should not be addressed in isolation. We also are aware that numerous high-quality environmental data sets are or soon will be available to support intensive and diverse analyses as well as comprehensive evaluations of model performance-an absolute prerequisite for establishing the reliability of models slated for regulatory or emergency response applications. To package all this science, technology, and information in a practical form requires a CMS. Further, a program designed to acquire a CMS (hardware, software, and supporting infrastructure) and to ensure access to the vast quantity of data needed for its applications would strain the resources of any single organization. Only through the collaboration of many organizations could a C M S capability be realized in a reasonable time frame. So where do we stand today? Many of the agencies participating in CAMRAQ develop or use a large variety of air quality models in tilfilling their missions. Unfortunately, most of these models have very different genealogies and target different issues. They vary in level of explicitness, parameterization of process representations, and underlying assumptions. Thus, when different models are applied to the same issue, for example, regional ozone, they often yield different results. Further, single or limited-issue models, such as those labeled “acid rain models,” may perform very poorly if applied to other issues, such as airborne particulate matter. Models typically have evolved over many years, have been designed and programmed by individuals having a wide range of skills and following no standardized methods, have not been adequately evaluated or compared, are not well documented, and are not computationally efficient. We believe the CMS approach we have adopted will avoid these problems. Objectives Our overall objective is to make available to our community a convenient set of tools that will allow us to reliably project what will happen to specific air quality indices over a broad range of temporal and spatial scales if the source term for
virtually any substance of interest is changed. A CMS that will provide this set of tools will have to have at least the following attributes: Regulatory approval. Many in the consortium either include air quality regulation in their mission or represent interests that must respond to such regulation. Thus, we require a CMS to be suitable for regulatory applications and endorsed by the pertinent agencies for such use. Accessibility. Convenient access to a CMS, including its supporting data files, must be assured for all CAMRAQ members. In all likelihood a CMS will reside in a distributed data-computing environment, and access would be via a workstation in this network. Versatility. A CAMRAQ CMS would be a hierarchy of user-selectable models that have at the high end the most complete and explicit schemes for estimating emissions, representing all relevant tropospheric processes and estimating initial and boundary conditions, that our scientific knowledge and computational capability will allow. Lower in the hierarchy, process representations would become more highly parameterized, and, in the absence of observational data, model inputs could be selected from pretabulated data sets that define conditions “typical” for the modeling domain selected. A CMS can therefore be used for anything from rapid screening exercises to full blown, research quality, multiissue assessments. Reliability. The performance of each selectable configuration would be evaluated through sensitivity analyses and against field data sets of defined uncertainty to establish the confidence that can be placed in the individual simulations produced. Because a criterion for inclusion of a component model in a CMS would be that it has been evaluated against field data, a high priority among CAMRAQ members would be the acquisition of appropriate data sets. The computer code itself would conform to modern standards and be thoroughly documented. Self consistency. As far as practical, consistent underlying assumptions would be maintained throughout the hierarchy to achieve as much comparability among CMS configurations as possible. Convenience. Advanced, menudriven user interfaces for input and output data access, generation,
management, display, analysis, and interpretation are required. Process representations would be modular for ease of replacement, substitution, and upgrading. An example of such a user interface and its display possibilities can be seen in Figure 1. These pictures were produced by a prototype CMS system currently under development at Carnegie Mellon University (Bruegge,B. et al. “GEMS: A Geographic Environmental Modeling System,” unpublished manuscript).
Only through the collaboration of many organizations could a comprehensive modeling system capability be realized in a reasonable
Efficiency. Process algorithms and numerical solvers would be selected for computational speed without sacrificing accuracy. A CMS should be exercisable in a computing environment having a combination of massively parallel, specialized, and vector-processing capabilities. Its software and hardware should be compatible and designed to allocate the computing problem according to the hardware and software combination yielding the optimum performance. CAMRAQ‘s secondary objectives relate to facilitating CMS acquisition, characterization, and application through coordination of re-
search and collaboration on highly focused projects and encouraging advancements in the relevant atmospheric and computer sciences. In carving out our niche, we understand that many of our agencies have substantial research programs on global issues as part of the international effort to elucidate the causes and consequences of climate change. CAMRAQ intends to complement, not duplicate this effort and to focus on regional and smaller scale applications of air quality models-including those dealing with climate change impacts. In addition, in response to the ozone-nonattainment issue intensified by the 1990 Clean Air Act Amendments, a North American Research Strategy for Tropospheric Ozone [NARSTO) is under way that involves many of the same organizations participating in CAMRAQ and embraces the same philosophy that we all benefit through cooperation. Although these activities are fueled by a single issue, we view them as contributing to the CAMRAQ objectives. Organization CAMRAQ members are symbolically bound by a memorandum of understanding that articulates our goals and willingness to cooperate in achieving them. A steering committee of one individual from each organization desiring representation guides CAMRAQs course (presently about 20, from North America and Europe). Very large agencies having several modeling groups with substantially different missions within “regional modeling,’’ such as the National Oceanographic and Atmospheric Administration, may have each group represented. Ad hoc subcommittees are formed to address programmatic: issues as they arise. Roots CAMRAQ‘s roots are in the spirit of cooperation nurtured for many of the participants by the success of consortia on related topics. The specific concept, however, began as an initiative of EPRI. EPRI was encouraged by its participation in two collaborative studies [the Eulerian Model Evaluation and Field Study (EMEFS)and the Subregional Coop erative Electric Power, National Park Service, Environmental Protection Agency, and Department of Defense Study (SCENES)] (see Table 1)and was convinced of the concept’s feasibility by the existing Envimn. Sci. Technol., Vol. 28, No. 2. 1994 73 A
FIGURE 1
1s modeling system
ANDSAT hic data II
wve modeling
74 A Environ. Sci. Techml., Vol. 2a. No. 2,1694
level of scientific understanding and rapidly increasing computer power. Therefore, EPRI introduced a project entitled the “Tropospheric Model Development and Evaluation Project” (14). This project’s primary goal is to deliver a practical comprehensive modeling system that could be used to assess any conceivable air quality issue. I t integrates collaborative, regionally specific field studies and associated modeling exercises in which EPRI was and is involved. I was initiated with two plannint workshops and is scheduled to last about 10 years. Independently. EPA has embarked on a related mission as part of the Federal High Performance Computer and Communicationsinitiative; the CMS Models 3 will be its major product (1.5). Models 3 will share many features with a CAMRAQ CMS and should play a key role in integrating the results of EPA atmospheric research and in making advanced air quality modeling tools available to researchers and regulators in the EPA family. Although not the same, CAMRAQ‘s CMS a n d EPA’s Models 3 will share, exchange, and compare technologies. Modeling systems with similari ties to those proposed or under development by CAMRAQ, EPA and Carnegie Mellon University have been designed or implemented by the Department of Energy (161 and the U.S. Forest Service (171, but the h e groundwork for the spirit and science required by a CMS was laid in at least three model development programs, the models from which were viewed as “comprehensive” by their own contemporary standards. They are the Regional Acid Deposition Model, RADM (181, sponsoredby EPA;the Acid Deposition and Oxidant Model, ADOM (19), funded by the Ontario Ministry of the Environment, Environment Canada, the German Umweltbundesamt, and EPRI; and STEM-II (20), developed at the universities of Iowa and Kentucky. All three models operate on a fully three-dimensional Eulerian grid; require the generation of meteorological fields by separate mesoscale models for, among other things, simulating advection within the grid; have preprocessors for the input of emissions; treat gas phase photochemistry in moderate detail; and simulate cloud chemistry and physics, including gas and particle scavenging and wet and dry deposi-
Recent and existing combined field measurement and modeling studies involving participation by CAMRAQ members npproxlmate
EsllmaM cost OM) Relerer
Name 01 study*
dat@s
Major sponsors”
EMEFS SCAQS
1988-1993 1985-1987
47
4
14
5
SCENES
1984-1990
SJVAQS/ AUSPEW SARMAP
1988-1993
EPA, EPRI, AES, OME. FCG ARB, EPA, MVMA, SCE, SCAQMD, CRC, GMRL, Ford. EPRI. A R C 0 EPA, EPRI, NPS, SCE. SCE, DOD ARB. EPA. PG&E. EPRI! San Joaquin Valley cities and counties, Chevron, WSPA State of CO, Denver C of C, MVMA, EPA. EPRI, Public Serv. co. Of co EPA, WI, IL, IN, MI EPA, EPRI. SES, TVA, Duke Power, NOAA. DOE
European governments
15
Denver Air Quality 1987-1993 StudiedBrown Cloud II LMOS
SOS/SORP/ SERON EUROTRAC/ EUMAC
1969-1993 1990-1996 1987-1995
I!
13
*EMEFS = Eulerian Model Evaluation and Field Study; EUMAC = European Mcdeling of Atmospheric Constituents: EUROTRAC = European Experiment of Transpn and Transformation of Environmentally Relevant Trace Constituents in the Troposphere over Euro e, LMOS Lake Michian Ozone Study; SCAQS = Southern California Air Quality Study; gCENES ==Subregional Electric Power. National Park Service, Enviro?mental Protection A en ,and Depart ment of Oefen58 Study: SERON =Southern RegIO”a1 Oxidant Network: SJVAgSl%SPEX = S3; Joaquin Valley Air Quality StudylAtmospheric tility 8gnatures: Predictions and Experiments: SORP x Southem Oxidants Research Program: SOS = Southern Oxidants Study. hAES = Atmospheric Environment Service of Environment Canada, API = American Petroleum hstitute, ARB = California Air Resources Board, CRC = Cwrdinatin Research Council. DNA = Defense Nuclear Agency, OOD = U.S. Departmenl of Defense, DO? = U.S. Department Of Ener y EPA F U.S. Environmental Protection Agenc , EPRI Electric Power Research Institute. F C B Florida Electric Power Cwrdinating Group. G h = general Motors Research Labaratory, MVMA = Motor Vehicle Manufacturers Association. NOAA = National Oceanic and Atmospheric Administration. NPS = U.S. National Park Service, OME =Ontario Ministry of the Environment! PGBE = Pacific Gas & Electric Company, SCAQMD = South Coast Ai! Quality Mana ement District, SCF = Southem California Edison Company, SES = Southern Electrical S stem, S&=Salt River Pro], TVA = Tennessee Valley Authonty, WSPA = Westem State Petro!eum Association.
cooperative
tion. The impetus for the development of these models was the desire to assess the effect of contmlling the emissions of precursor gases on precipitation chemistry and acid deposition. Air quality planners and regulators have been hungry for more reliable, practical, and convenient modeling tools. An impressive start along these lines has been given in Figure 1,from the CMU GEMS.
Coordinated research The CAMRAQ Steering Committee has drawn up a Technical Work Plan (21)which summarizes their research plans for the next 10 years. The work plan recognizes three categories of CMS research components: Category 1, components created directly under the CAMRAQ framework; Category 2, components created by CAMRAQ members for specific organizational needs and intentionally contributed to function as a CMS element; and Category 3. components created independently of CAMRAQ but applied for CAMRAQ purposes. Obviously the degree of CAMRAQ control decreases from Cate-
gory 1 to Category 3; this imposes a significant challenge to CAMRAQ. Because it is not possible to foresee the degree of CAMRAQ involvement or coordination in the tasks involving research on scientific modules and investigations of software and hardware, they are grouped together in the figure under “Categories 2 and 3.” Details of the interactions and priorities have yet to be worked out. The Technical Work Plan guides the coordination of research within CAMRAQ, after it had been determined what research is already in progress by participants. This determination was made by compiling descriptions of each organization’s relevant research and distributing them to Steering Committee members. Work in progress is now being reconciled with the Technical Plan. Based on analysis of the composited programs, we plan to look closely at redirecting elements of our individual programs to create a more efficient and economical composite.
Collaborative activities The days of large data collection (field) and modeling studies funded Environ. Sci. Technol.. Vol. 28, No. 2, 1994 15 A
by a single agency-such as EPA’s Regional Air Pollution Study and EPRI’s Sulfate Regional Experiment in the late 1970s-are probably over. Regional air quality environmental issues are too large and complex for single agencies to justify mounting programs to make definitive assessments. The trend now, supported by budget-conscious managers, is toward collaboratively funded programs. Existing programs. Examples of recent activities in which subsets of CAMRAQ participants are key funders and planners are shown in Table 1. The list is not intended to be exhaustive. The results of these “pre-CAMRAQ’ studies (they were begun before CAMRAQs creation) will be used to further its objectives as well as the original regionally specific goals of the studies. Plans for 1994. CAMRAQ plans to fund two competing CMS design projects over the next year and will begin to develop the distributed data archive necessary for analysis and model development and testing. These “Category 1”projects are briefly described below: Design of optimum CMS. CAMRAQ intends to sponsor the preliminary design of optimum CMSs by two independent groups. These designs would cover all aspects of the CMS, including choices for model components, incorporation of new research results, software development, decisions regarding computer hardware, networks, and data archives. All related topics would be investigated to some extent and a design plan written for the longterm program. Develop distributed data archives and associated view servers and networks. CAMRAQ members would like to be able to test various regional air quality models and CMSs with comprehensive sets of field data (such as those from studies listed in Table 1). These data sets would be organized into a distributed data archive. The user would be able to find and access data via view servers at each node of the distributed data archive. This subtask would also involve setting up an appropriate network for communications among sites. Summary and invitation
Organizations interested in advancing the science and technology of regional air quality modeling on the “grand challenge” scale have joined to form CAMRAQ. They plan to leverage their research funds by 76 A Environ. Sei. Technol.. Vol. 28. No. 2. 1994
collaborating on the development and evaluation of CMSs so ambitious in scope that none could undertake the task alone. These CMSs will give each of them the capability of conveniently addressing virtually any air quality issue within a self-consistent framework, with established confidence limits on simulated results. Early collaborative efforts will focus on advancing computational and data handling capabilities for facilitating the modeling. These technological aspects are considered a high priority because many of the participating agencies already have research programs on the scientific underpinnings of the modeling systems. Nonetheless, many components of atmospheric science research will be coordinated among agencies to increase efficiency, and all participants will be attuned to opportunities for collaboration. CAMRAQ is not a closed consortium. It is open to all organizations interested in regional air quality issues who subscribe to the tenet that
D.Alan Hansen 11)is manager of tropaspheric studies in the Atmospheric Sciences Progmm at the Electric Power Research Institute. He received a B.A. degree from Southern Illinois Universi@ a Ph.D. from the University of California-lrvine, and did postdoctoral work at the Universityof California-Riverside. He is the founding ond present chair of CAMRAQ. He manages research on atmospheric measurement technology, tropospheric chemistry and physics, model development, model evaluation, and environmental data analysis.
Robin L. Dennis (r)is a senior pragmm manager with EPA’s Atmospheric Research and Exposure Assessment Lobomtory in Research Triangle Park, NC. He received his Ph.D. fmm the University of Wisconsin-Modisan. A key interest is environmental problem solving. At EPA he is responsiblefor regional modeling of acidic deposition, the evaluation of the Regional Acid Deposition Model, and its application to assessments and environmental problem solving. He is a leader of EPA’sHigh Performance Computing and CommunicationsProgmm.
AdolfEbel ( I ) is a professor of geophysics of the University of Cologne, Germany. He sewed on the Scientific Committee on Solar-Terrestrial Relotionships. The International Cammissian an the Meteorolagyof the Upper Atmosphere of IAMAP elected him as a honomry member. His research focuses on modeling of long-range tmnspart of air pollutants. He coordinates the Eurapeon Modelling of Atmospheric Canstituents subproject of the European environmental project EUROTRAC. Hanna [r) is chief scientist of Sigma Research Corporation in Cancord, MA. He received a Ph.D. in meteorology from Pennsylvania State University. He previously worked at NOAA’s Atmospheric Turbulence and Diffusion Laboratory in Oak Ridge, TN, and at ERT Inc.. in Concord. MA. He was the management coordinator for the CAMRAQprogmm 1991-93. Steve R.
Jack A. Koye [I) is a manager of the Atmospheric Chemistry Modeling and Analysis Program in NASA’s Earth Science and Applications Division. He received a B.A. degree in chemistry fmm Adelphi University and a Ph.D. in theoretical physical chemistryfrom the California Institute of Technology. Fallowing postdoctoral work at the Naval Research Laboratory in Washington, DC, he joined NASA’s Goddard Space Flight Center as an atmospheric chemical modeler, participatingin 3D simulations of stratospheric chemistry. Richard Thuillier (r) is a senior metearologist with Pacific Gas and Electric Co. in Son Francisco. He received a B.S. degree from Fordham College and an M.S. degree from New Yark University, and he is a certified consulting metearolagist. He has beeen an applied meteorologistfor 34 years and has done air quality research for 24 years. He manages the AUSPEX portion of the SJVAQSl A USPEXLSARMAPRegional Air Quality Project in centml California.
mitted through University Corporation for Atmospheric Research, Boulder, CO, 1990. (13) Ebel, A. et al. Proceedings, ECJROTRAC Symposium ’90; Borrell, P. et al., Eds.; 1991, 231-33, SPB Academic Publishing: The Hague. (14) Hansen, D. A. “A Concept Paper on Model Development and Evaluation”; Electric Power Research Institute: Palo Alto, CA, 1989. (15) Dennis, R. L.; Novak, J. H. “EPA’s Third Generation Modeling System (Models-3) An Overview”; presented at AWMA Speciality Conference on Tropospheric Ozone and the Environment 11, Atlanta, GA, Nov. 4-7,
progress toward ambitious goals is (6) Mueller, P. K.; Hansen, D. A,; Watson, J. G . “The Subregional Cooperative best made through the free exElectric Utility, Department of Dechange of information and consolifense, National Park Service, and EPA dation of resources to address a Study (SCENES) on Visibility: An common agenda. We welcome all Overview”; Electric Power Research Institute: Palo Alto, CA, 1986; Special organizations that can benefit from Report EA-4664-SR. and contribute to CAMRAQ objectives. Inquiries should be addressed (7) Ranzieri, A. J.; Thuiller, R. “San Joaquin Valley Air Quality Study to the CAMRAQ Steering Commit(SJVAQS) and Atmospheric Utility tee Chair, D. Alan Hansen, EPRI, Signatures, Predictions, and ExperiP.O. Box 10412, Palo Alto, CA ments (AUSPEX): A Collaborative Modeling Program”; 84th Annual 94303;telephone: (415)855-2738; Meeting, Air and Waste Management f a x : (415) 855-1069; e - m a i l : Association, Vancouver, BC, June
[email protected].
Acknowledgments The authors acknowledge the contributions of the 14 other members of the CAMRAQ Steering Committee. The figures were kindly provided by Bernd Buegge and Erik Riedel of Carnegie MelIon University.
References (1) . , Browell. E. V. et al. I. Geoohvs. Res. 1992,97(D15), 16433-50. I
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(2) Kato, H.; Fujita, S-I.; Nishinomiya, S. Atmos. Environ. 1990,24A(8],202333. (3) Holton, J. R. J. Atmos. Sci. 1990, 47, 392-95. (4) Hansen, D. A. et al. In Air Pollution Modeling and its Application VI& van Dop, H., Ed.; Plenum Press: New York, 1989; pp. 297-306. (5) Lawson, D. R. J. Air Waste Manage. ASSOC. 1990,40(2), 156-65.
21, 1991; paper 91-70.5. (8) “Workplan for the Development of the SARMAP Modeling System”; Draft Report; ENSR Consulting and Engineering: Camarillo, CA, 1991; Document No. 1200-010-002. (9) Watson, J. G. et al. “The 1987-88 Metro Denver Brown Cloud Study, Final Report, Vols. 1-3, Program Plan, Measurements, and Data Interpretation”; Desert Research Institute: Reno, NV, 1988; DRI Document Nos. 8810 1F1.8810 1F2.8810 lF3. (10) Middleton, P.; Burns, S. “Denver Air Quality Modeling Study”; 84th AnnuaI Meeting, Air and Waste Management Association, Vancouver, BC, 17-21, June 1991; Paper 91-48.7. (11) Koerber, M. “An Overview of the LMOS”; Lake Michigan Air Directors Consortium: Des Plains, IL, 1991; Lake Michigan Ozone Study publication TP08. (12) “SERON: The Southeastern Regional Oxidant Network”; a proposal sub-
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(16) Graham, M. J, “Vertical Integration of Science, Technology, and Applications (VISTA)”; Fiscal Year 1989 Report, Battelle Pacific Northwest Laboratory: Richland, WA, 1990; PNL7369/UC-402. (17) Fox, D. G. et al. “An Update on TAPAS and Its Model Components”; presented at Ninth Conference on Fire and Forest Meteorology, San Diego, CA, April 21-24,1987. (18) Chang, J. S. et al. J. Geophys. Res. 1987,92, 14,681-700. (19) Venkatram, A.; Karamchandani, P.; Misra, P. K. Atmos. Environ.. 1988, 22, 737-48. (20)Carmichael, G . R.; Peters, L. K.; Kitada, T. Atmos. Environ. 1980, 20, 173-88.
(21) Hanna, S. R. Technical Work Plan for Research on Comprehensive Modeling Systems; Sigma Research Corp.: Concord, MA, 1993.
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