Review of the Governing Equations, Computational Algorithms, and Other Components of the Models-3 Community Multiscale Air Quality (CMAQ) Modeling System
Tóm tắt
This article describes the governing equations, computational algorithms, and other components entering into the Community Multiscale Air Quality (CMAQ) modeling system. This system has been designed to approach air quality as a whole by including state-of-the-science capabilities for modeling multiple air quality issues, including tropospheric ozone, fine particles, acid deposition, and visibility degradation. CMAQ was also designed to have multiscale capabilities so that separate models were not needed for urban and regional scale air quality modeling. By making CMAQ a modeling system that addresses multiple pollutants and different spatial scales, it has a “one-atmosphere” perspective that combines the efforts of the scientific community. To implement multiscale capabilities in CMAQ, several issues (such as scalable atmospheric dynamics and generalized coordinates), which depend on the desired model resolution, are addressed. A set of governing equations for compressible nonhydrostatic atmospheres is available to better resolve atmospheric dynamics at smaller scales. Because CMAQ is designed to handle scale-dependent meteorological formulations and a large amount of flexibility, its governing equations are expressed in a generalized coordinate system. This approach ensures consistency between CMAQ and the meteorological modeling system. The generalized coordinate system determines the necessary grid and coordinate transformations, and it can accommodate various vertical coordinates and map projections. The CMAQ modeling system simulates various chemical and physical processes that are thought to be important for understanding atmospheric trace gas transformations and distributions. The modeling system contains three types of modeling components (Models-3): a meteorological modeling system for the description of atmospheric states and motions, emission models for man-made and natural emissions that are injected into the atmosphere, and a chemistry-transport modeling system for simulation of the chemical transformation and fate. The chemical transport model includes the following process modules: horizontal advection, vertical advection, mass conservation adjustments for advection processes, horizontal diffusion, vertical diffusion, gas-phase chemical reactions and solvers, photolytic rate computation, aqueous-phase reactions and cloud mixing, aerosol dynamics, size distributions and chemistry, plume chemistry effects, and gas and aerosol deposition velocity estimation. This paper describes the Models-3 CMAQ system, its governing equations, important science algorithms, and a few application examples. This review article cites 114 references.
Từ khóa
Tài liệu tham khảo
Novak, J. H., Dennis, R. L., Byun, D. W., Pleim, J. E., Galluppi, K. J., Coats, C. J., Chall, S., and Vouk, M. A., 1995, “EPA Third-Generation Air Quality Modeling System, Vol. 1, Concept, EPA 600/R95/084, U. S. Environmental Protection Agency, Research Triangle Park, NC.
Dennis, The Next Generation of Integrated Air Quality Modeling: EPA’S Models-3, Atmos. Environ., 30, 1925, 10.1016/1352-2310(95)00174-3
Byun, Description of the Models-3 Community Multiscale Air Quality (CMAQ) Model, 264
SAI, 1990, “User’s Guide for the Urban Airshed Model,” Volume I-V, Prepared by Systems Applications International, San Rafael, CA, Report No. SYSAPP-90/18a-e.
McRae, G. J., Russell, A. G., and Harley, R. A., 1992, “CIT Photochemical Airshed Model-Systems Manual,” Carnegie Mellon University Report, Pittsburgh.
Lamb, R. G. , 1983, “A Regional Scale (1000km) Model of Photochemical Air Pollution, Part 1: Theoretical Formulation,” EPA-600/3–83–035, U.S. Environmental Protection Agency, Research Triangle Park, NC.
Carmichael, The STEM-II Regional-Scale Acid Deposition and Photochemical Oxidant Model: I. An Overview of Model Development and Applications, Atmos. Environ., Part A, 25A, 2077
Kumar, Parallel and Distributed Application of an Urban and Regional Multiscale Model, Comput. Chem. Eng., 21, 399, 10.1016/S0098-1354(96)00006-3
Environ 1998, “User’s Guide for Comprehensive Air Quality Model With Extensions (CAMx) Version 2.0. Environ Corp.,” Novato, CA.
Chang, A Three-Dimensional Eulerian Acid Deposition Model: Physical Concepts and Formulation, J. Geophys. Res., 92, 14681, 10.1029/JD092iD12p14681
Anthes, Development of Hydrodynamic Models Suitable for Air Pollution and Other Mesometeorological Studies, Mon. Weather Rev., 106, 1045, 10.1175/1520-0493(1978)106<1045:DOHMSF>2.0.CO;2
Grell, G. A., Dudhia, J., and Stauffer, D. R., 1995, “A Description of the Fifth-Generation Penn State/NCAR Mesoscale Model (MM5),” NCAR Technical Note, NCAR/TN-398+STR, Boulder, CO., 138 pp.
Chang, J. S., Jin, S., Li, Y., Beauharnois, M., Chang, K.-H., Huang, H.-C., Lu, C.-H., Wojcik, G., Tanrikulu, S., and DaMassa, J., 1996, “The SARMAP Air Quality Model Part 1 of SAQM Final Report,” California Air Resources Board, Sacramento.
Hass, H. , 1991, “Description of the EURAD Chemistry Transport Module (CTM) Version 2,” In A.Ebel, F. M.Neubauer, and P.Speth, eds., Report 83, Institute of Geophysics and Meteorology, University of Cologne, Cologne, Germany.
Grell, Application of a Multiscale, Coupled MM5/Chemistry Model to the Complex Terrain of the VOTALP Valley Campaign, Atmos. Environ., 34, 1435, 10.1016/S1352-2310(99)00402-1
Jacobson, Development and Application of a New Air Pollution Modeling System—Part I: Gas-Phase Simulations, Atmos. Environ., 30, 1939, 10.1016/1352-2310(95)00139-5
Vautard, Validation of a Deterministic Forecasting System for the Ozone Concentrations Over the Paris Area, Atmos. Environ., 35, 2449, 10.1016/S1352-2310(00)00466-0
Robertson, An Eulerian Limited-Area Atmospheric Transport Model, J. Appl. Meteorol., 38, 190, 10.1175/1520-0450(1999)038<0190:AELAAT>2.0.CO;2
Källén, E. , 1996, “HIRLAM Documentation Manual—System 2.5,” (available from SMHI, SE-601 76 Norrköping, Sweden).
Brandt, Operational Air Pollution Forecast Modelling by Using the THOR System, Phys. Chem. Earth, Part B, 26, 117, 10.1016/S1464-1909(00)00227-6
Zlatev, Three-Dimensional Version of the Danish Eulerian Model, Z. Angew. Math. Mech., 76, 473
Fast, Effect of Regional-Scale Transport on Oxidants in the Vicinity of Philadelphia During the 1999 NE-OPS Field Campaign, J. Geophys. Res., 107, 4307, 10.1029/2001JD000980
Pielke, A Comprehensive Meteorological Modeling System-RAMS, Meteorol., Atmos. Phys., 49, 69, 10.1007/BF01025401
Coats, Fast Emissions Modeling With the Sparse Matrix Operator Kernel Emissions Modeling System, The Emissions Inventory: Key to Planning, Permits, Compliance, and Reporting, Air and Waste Management Association
Houyoux, Updates to the Sparse Matrix Operator Kernel Emission (SMOKE) Modeling System and Integration With Models-3, The Emission Inventory: Regional Strategies for the Future
Coats, C. J., Trayanov, A., McHenry, J. N., Xiu, A., Gibbs-Lario, A., and Peters-Lidard, C. D., 1999, “An Extension of the EDSS/Models-3 I/O API for Coupling Concurrent Environmental Models, In Applications to Air Quality and Hydrology,” Preprints, 15th IIPS Conf., Amer. MeteoR. Soc., Dallas, Jan. 10–15.
Rew, NetCDF: An Interface for Science Data Access, IEEE Comput. Graphics Appl., 10, 76, 10.1109/38.62698
Byun, Dynamically Consistent Formulations in Meteorological and Air Quality Models for Multi-Scale Atmospheric Applications, Part I: Governing Equations in Generalized Coordinate System, J. Atmos. Sci., 56, 3789, 10.1175/1520-0469(1999)056<3789:DCFIMA>2.0.CO;2
Byun, Dynamically Consistent Formulations in Meteorological and Air Quality Models for Multi-Scale Atmospheric Applications, Part II: Mass Conservation Issues, J. Atmos. Sci., 56, 3808, 10.1175/1520-0469(1999)056<3808:DCFIMA>2.0.CO;2
Ooyama, A Thermodynamic Foundation for Modeling the Moist Atmosphere, J. Atmos. Sci., 47, 2580, 10.1175/1520-0469(1990)047<2580:ATFFMT>2.0.CO;2
Seaman, Meteorological Modeling for Air-Quality Assessments, Atmos. Environ., 34, 2231, 10.1016/S1352-2310(99)00466-5
Stauffer, Multiscale Four-Dimensional Data Assimilation, J. Appl. Meteorol., 33, 416, 10.1175/1520-0450(1994)033<0416:MFDDA>2.0.CO;2
Tremback, C. J. , 1990, “Numerical Simulation of a Mesoscale Convective Complex: Model Development and Numerical Results,” Ph.D. dissertation, Colorado State University.
Sugata, Simulation of Sulfate Aerosol in East Asia Using Models-3/CMAQ With RAMS Meteorological Data, Millennium NATO/CCMS International Technical Meeting on Air Pollution Modelling and Its Applications
Seaman, Status of Meteorological Pre-Processors for Air-Quality Modeling, Proc. of Int. Conf. on Particulate Matter, 639
Vogel, Influence of Topography and Biogenic Volatile Organic Compounds Emission in the State of Baden-Wurttemberg on Ozone Concentrations During Episodes of High Air Temperatures, J. Geophys. Res., 100, 22, 10.1029/95JB02403
Xiu, On the Development of an Air Quality Modeling System With Integrated Meteorology, Chemistry, and Emissions, Proc. of Int. Symp. on Measurement of Toxic and Related Air Pollutants, 144
Dudhia, WRF: Current Status of Model Development and Plans for the Future, Preprint of Eighth PSU/NCAR Mesoscale Model User’s Workshop
Klemp, J. B., Skamarock, W. C., and Dudhia, J., 2001, “Conservative Split-Explicit Time Integration Methods for the Compressible Nonhydrostatic Equations,” available at http://www.mmm.ucar.edu/individual/skamarock/wrf_equations_eulerian.pdf
Benjey, Functionality of an Integrated Emission Preprocessing System for Air Quality Modeling: The Models-3 Emission Processor, The Emissions Inventory: Programs and Progress, 463
Benjey, Emission Subsystem, Science Algorithms of the EPA Models-3 Community Multiscale Air Quality (CMAQ) Modeling System
Fratt, D. B., Mudgett, D. F., and Walters, R. A., 1990, “The 1985 NAPAP Emissions Inventory: Development of Temporal Allocation Factors,” EPA-600/7-89-010d, U.S. Environmental Protection Agency, Office of Research and Development, Washington, DC, 209 pp.
Moody, T., Winkler, J. D., Wilson, T., and Kersteter, S., 1995, “The Development and Improvement of Temporal Allocation Factor Files,” EPA-600/R-95-004, U.S. Environmental Protection Agency, Office of Research and Development.
Carter, W. P. L. , 2000, “Implementation of the SAPRC-99 Chemical Mechanism Into the Models-3 Framework,” Final Report to U.S. EPA.
Pierce, The Influence of Increased Isoprene Emissions on Regional Ozone Modeling, J. Geophys. Res., 103, 25611, 10.1029/98JD01804
Guenther, Natural Emissions of Non-Methane Volatile Organic Compounds, Carbon Monoxide, and Oxides of Nitrogen From North America, Atmos. Environ., 34, 2205, 10.1016/S1352-2310(99)00465-3
U.S. EPA 2002, “User’s Guide to Mobile 6.1 and Mobile 6.2: Mobile Source Emission Factor Model,” EPA 420-R-02-028, Office of Air And Radiation, Office of Transportation and Air Quality.
Toon, A Multidimensional Model for Aerosols: Description of Computational Analogs, J. Atmos. Sci., 45, 2123, 10.1175/1520-0469(1988)045<2123:AMMFAD>2.0.CO;2
Pleim, J. E. , 1990, “Development and Application of New Modeling Techniques for Mesoscale Atmospheric Chemistry,” Ph.D. thesis, State University of New York at Albany.
Jeffries, A Comparison of Two Photochemical Reaction Mechanisms Using Mass Balance and Process Analysis, Atmos. Environ., 28, 2991, 10.1016/1352-2310(94)90345-X
Jang, Sensitivity of Ozone to Model Grid Resolution-I: Application of High-Resolution Regional Acid Deposition Model, Atmos. Environ., 29, 3085, 10.1016/1352-2310(95)00118-I
Jang, Sensitivity of Ozone to Model Grid Resolution-II: Detailed Process Analysis for Ozone Chemistry, Atmos. Environ., 29, 3101, 10.1016/1352-2310(95)00119-J
Colella, The Piecewise Parabolic Method (PPM) for Gas-Dynamical Simulations, J. Comput. Phys., 54, 174, 10.1016/0021-9991(84)90143-8
Bott, A Positive Definite Advection Scheme Obtained by Nonlinear Renormalization of the Advective Fluxes, Mon. Weather Rev., 117, 1006, 10.1175/1520-0493(1989)117<1006:APDASO>2.0.CO;2
Odman, M. T. , 1998, “Research on Numerical Transport Algorithms for Air Quality Simulation Models,” EPA Report. EPA/660/R-97/142, National Exposure Research Laboratory, U.S. EPA, Research Triangle Park, NC.
Byun, Numerical Transport Algorithms for the Community Multiscale Air Quality (CMAQ) Chemical Transport Model in Generalized Coordinates, Science Algorithms of the EPA Models-3 Community Multiscale Air Quality (CMAQ) Modeling System
Smagorinsky, General Circulation Experiments With the Primitive Equations, 1: The Basic Experiment, Mon. Weather Rev., 91, 99, 10.1175/1520-0493(1963)091<0099:GCEWTP>2.3.CO;2
von Rosenberg, Methods for the Numerical Solution of Partial Differential Equations, 113
Pleim, A Non-Local Closure Model for Vertical Mixing in the Convective Boundary Layer, Atmos. Environ., Part A, 26A, 965, 10.1016/0960-1686(92)90028-J
Chang, J. S., Jin, S., Li, Y., Beauharnois, M., Lu, C. H., Huang, H. C., Tanrikulu, S., and DaMassa, J., 1997, “The SARMAP Air Quality Model,” Final Report, SJVAQ/AUSPEX Regional Modeling Adaptation Project, 53 pp. (available from California Air Resources Board, 2020 L St, Sacramento, CA 95814).
Brost, A Model Study of the Stably Stratified Planetary Boundary Layer, J. Atmos. Sci., 35, 1427, 10.1175/1520-0469(1978)035<1427:AMSOTS>2.0.CO;2
Hass, Simulation of a Wet Deposition Case in Europe Using the European Acid Deposition Model (EURAD), Air Pollution Modelling and Its Applications, 205
Byun, Design Artifacts in Eulerian Air Quality Models: Evaluation of the Effects of Layer Thickness and Vertical Profile Correction on Surface Ozone Concentrations, Atmos. Environ., 29, 105, 10.1016/1352-2310(94)00225-A
Wesely, Parametrization of Surface Resistances to Gaseous Dry Deposition in Regional-Scale Numerical Models, Atmos. Environ., 23, 1293, 10.1016/0004-6981(89)90153-4
Pleim, Comparison of Measured and Modeled Surface Fluxes of Heat, Moisture and Chemical Dry Deposition, Air Pollution Modeling and its Applications XI, 10.1007/978-1-4615-5841-5_63
Byun, Science Algorithms of the EPA Models-3 Community Multiscale Air Quality (CMAQ) Modeling System
Madronich, Intercomparison of NO2 Photodissociation and UV Radiometer Measurements, Atmos. Environ., 21, 569, 10.1016/0004-6981(87)90039-4
Joseph, The Delta-Eddington Approximation for Radiative Flux Transfer, J. Atmos. Sci., 33, 2452, 10.1175/1520-0469(1976)033<2452:TDEAFR>2.0.CO;2
World Meteorological Organization, 1986, Atmospheric Ozone 1985: Assessment of our Understanding of the Processes Controlling its Present Distribution and Change, WMO Rep. No. 16; Global Ozone Research and Monitoring Project, Geneva.
Chang, J. S., Binkowski, F. S., Seaman, N. L., Byun, D. W., McHenry, J. N., Samson, P. J., Stockwell, W. R., Walcek, C. J., Madronich, S., Middleton, P. B., Pleim, J. E., and Landsford, H. L., 1990, The Regional Acid Deposition Model and Engineering Model, NAPAP SOS/T Report 4, in National Acid Precipitation Assessment Program, Acidic Deposition: State of Science and Technology, Volume I, Washington, D. C.
DeMore, W. B., Sander, S. P., Golden, D. M., Hampson, R. F., Kurylo, M. J., Howard, C. J., Ravishankara, A. R., Kolb, C. E., and Molina, M. J., 1994, Chemical Kinetics and Photochemical Data for Use in Stratospheric Modeling: Evaluation Number 11, JPL Pub. 94-26, National Aeronautics and Space Administration, Jet Propulsion Laboratory, Pasadena, CA.
Demerjian, Theoretical Estimates of Actinic (Spherically Integrated) Flux and Photolytic Rate Constants of Atmospheric Species in the Lower Troposphere, Advances in Environmental Science and Technology, 369
Elterman, L. , 1968, “UV, Visible, and IR Attenuation for Altitudes to 50km,” AFCRL-68–0153, Air Force Cambridge Res. Lab., Bedford, MA.
Stephens, Radiation Profiles in Extended Water Clouds, II: Parametrization Schemes, J. Atmos. Sci., 35, 2123, 10.1175/1520-0469(1978)035<2123:RPIEWC>2.0.CO;2
Gery, A Photochemical Kinetics Mechanism for Urban and Regional Scale Computer Modeling, J. Geophys. Res., 94, 12,925, 10.1029/JD094iD10p12925
Stockwell, The Second Generation Regional Acid Deposition Model Chemical Mechanism for Regional Air Quality Modeling, J. Geophys. Res., 95, 16,343, 10.1029/JD095iD10p16343
Carter, Development and Evaluation of a Detailed Mechanism for the Atmospheric Reactions of Isoprene and NOx, Int. J. Chem. Kinet., 28, 497, 10.1002/(SICI)1097-4601(1996)28:7<497::AID-KIN4>3.0.CO;2-Q
Carter, Condensed Atmospheric Photooxidation Mechanisms for Isoprene, Atmos. Environ., 30, 4275, 10.1016/1352-2310(96)00088-X
Carter, Development of Ozone Reactivity Scales for Volatile Organic Compounds, Air Waste, 44, 881, 10.1080/1073161X.1994.10467290
Carter, W. P. L. , 2000, “Documentation of the SAPRC-99 Chemical Mechanism for VOC Reactivity Assessment,” Final Report to the California Air Resources Board, Contracts No. 92-329 and No. 95-308.
Jacob, Heterogeneous Chemistry and Tropospheric Ozone, Atmos. Environ., 34, 2131, 10.1016/S1352-2310(99)00462-8
Gong, A Numerical Scheme for the Integration of the Gas-Phase Chemical Rate Equations in Three-Dimensional Atmospheric Models, Atmos. Environ., Part A, 27A, 2147
Gear, Numerical Initial Value Problems in Ordinary Differential Equations
Jacobson, SMVGEAR: A Sparse-Matrix, Vectorized Gear Code for Atmospheric Models, Atmos. Environ., 28, 273, 10.1016/1352-2310(94)90102-3
Carmichael, A Second Generation Model for Regional-Scale Transport/Chemistry/Deposition, Atmos. Environ., 20, 173, 10.1016/0004-6981(86)90218-0
Mathur, A Comparison of Numerical Techniques for Solution of Atmospheric Kinetic Equations, Atmos. Environ., 32, 1535, 10.1016/S1352-2310(97)00381-6
Young, J. O., Sills, E., and Jorge, D., 1993, Optimization of the Regional Oxidant Model for the Cray Y-MP, EPA/600/R-94–065, U. S. EPA, Research Triangle Park, NC.
Hertel, Test of Two Numerical Schemes for Use in Atmospheric Transport-Chemistry Models, Atmos. Environ., Part A, 27A, 2591
Huang, On the Performance of Numerical Solvers for a Chemistry Submodel in Three-Dimensional Air Quality Models, Part 1: Box-Model Simulations, J. Geophys. Res., 188, 20175
Binkowski, Models-3 Community Multiscale Air Quality (CMAQ] Model Aerosol Component. I: Model Description, J. Geophys. Res., 108, 4183
Binkowski, The Regional Particulate Model, I: Model Description and Preliminary Results, J. Geophys. Res., 100, 26191, 10.1029/95JD02093
Nenes, ISORROPIA: A New Thermodynamic Equilibrium Model for Multiphase Multicomponent Inorganic Aerosols, Aquat. Geochem., 4, 123, 10.1023/A:1009604003981
Nenes, Continued Development and Testing of a New Thermodynamic Aerosol Module for Urban and Regional Air Quality Models, Atmos. Environ., 33, 1553, 10.1016/S1352-2310(98)00352-5
Seigneur, Simulation of Aerosol Dynamics: A Comparative Review of Mathematical Models, Aerosol Sci. Technol., 5, 205, 10.1080/02786828608959088
Whitby, The Physical Characteristics of Sulfur Aerosols, Atmos. Environ., 12, 135, 10.1016/0004-6981(78)90196-8
Dentener, Reaction of N2O5 on the Tropospheric Aerosols: Impact on the Global Distributions of NOx, O3, and, OH, J. Geophys. Res., 98, 7149, 10.1029/92JD02979
Riemer, Impact of the heterogeneous hydrolysis of N2O5 on chemistry and nitrate aerosol formation in the lower troposphere under photosmog conditions, J. Geophys. Res., 108, 4144, 10.1029/2002JD002436
Mentel, Nitrate Effect on the Heterogeneous Hydrolysis of Dintrogen Pentoxide on Aqueous Aerosols, J. Phys. Chem., 1, 5451
Schell, Modeling the Formation of Secondary Organic Aerosol Within a Comprehensive Air Quality Model System, J. Geophys. Res., 106, 28275, 10.1029/2001JD000384
Odum, The Atmospheric Aerosol-Forming Potential of Whole Gasoline Vapor, Science, 276, 96, 10.1126/science.276.5309.96
Griffin, Organic Aerosol Formation from the Oxidation of Biogenic Hydrocarbons, J. Geophys. Res., 104, 3555, 10.1029/1998JD100049
Strader, Evaluation of Secondary Organic Aerosol Formation in Winter, Atmos. Environ., 33, 4849, 10.1016/S1352-2310(99)00310-6
Dennis, Correcting RADM’s Sulfate Underprediction: Discovery and Correction of Model Errors and Testing the Corrections Through Comparisons Against Field Data, Atmos. Environ., Part A, 26A, 975, 10.1016/0960-1686(93)90012-N
Walcek, A Theoretical Method for Computing Vertical Distributions of Acidity and Sulfate Production Within Cumulus Clouds, J. Atmos. Sci., 43, 339, 10.1175/1520-0469(1986)043<0339:ATMFCV>2.0.CO;2
Kim, Atmospheric Gas-Aerosol Equilibrium, I: Thermodynamics Model, Aerosol Sci. Technol., 19, 157, 10.1080/02786829308959628
Binkowski, Aerosols in Models-3 CMAQ, Science Algorithms of the EPA Models-3 Community Multiscale Air Quality (CMAQ) Modeling System
Gillani, Plume-in-Grid Treatment of Major Point Source Emissions, Science Algorithms of the EPA Models-3 Community Multiscale Air Quality (CMAQ) Modeling System
Godowitch, Photochemical Simulations of Point Source Emissions With The Models-3 CMAQ Plume-in-Grid Approach, A&WMA 91st Annual Meeting
Godowitch, Results of Photochemical Simulations of Subgrid Scale Point Source Emissions With the Models-3 CMAQ Modeling System, Millenium Symposium on Atmospheric Chemistry, Proc. of American Meteorological Society, 43
U. S. EPA, 2003, 1999 National Emission Inventory Documentation and Data, available at http://www.epa.gov/ttn/chief/net/1999inventory.html
TexAQS 2000 web site: http://www.utexas.edu/research/ceer/texaqs/participants/about.html
Allen, D. T., Estes, M., Smith, J., and Jeffries, H., 2002, “Accelerated Science Evaluation of Ozone Formation in the Houston-Galveston Area: Overview,” available at http://www.utexas.edu/research/ceer/texaqsarchive
Nielsen-Gammon, J. W. , 2002, “Meteorological Modeling for the August 2000 Houston-Galveston Ozone Episode: METSTAT Statistical Evaluation and Model Runs from March-June 2002,” Report to the Technical Analysis Division Texas Natural Resource Conservation Commission, June.