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CMAQ and PCAPS predicted air quality impacts offshore emissions sources
The Community Multiscale Air Quality (CMAQ) model version 5.4 (epa.gov/cmaq) was applied with 12 km sized grid cells for a domain covering the conterminous U.S. and areas offshore. The vertical atmosphere was resolved up to 50 mb with 35 layers. Vertical layers were thinner nearest the surface to best resolve diurnal fluctuation in the surface mixing layers. Lateral boundary inflow was extracted from a hemispheric scale simulation for the same year. Meteorological inputs were developed with the Weather Research and Forecasting model version 3.8.1 applied with the same grid domain as the photochemical model. The Pattern Constructed Air Pollution Surfaces (PCAPS) model has been applied for complex sector-specific emissions scenarios for stationary and mobile sources and predicted air quality results consistent with more sophisticated models. PCAPS version 1.1 was applied for each year between 2024 and 2031 with year-specific offshore wind project and EGU emissions. PCAPS was also applied using the same offshore wind and onshore EGU emissions for the 2026 and 2055 scenarios simulated with CMAQ to allow for a direct comparison of results. This dataset is associated with the following publication: Baker, K., R.B. Rice, and N. Fann. Characterizing Air Quality Impacts Related to North Atlantic Offshore Emissions Sources. ACS ES&T Air. American Chemical Society, Washington, DC, USA, 2(7): 1369-1378, (2025).
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Community Multi-scale Air Quality (CMAQ) Model Outputs
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The CMAQ Model Outputs data asset includes current and projected future levels of ambient concentrations and deposition to support regulatory impact analyses.
Community Multi-scale Air Quality (CMAQ) Model Outputs
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The CMAQ Model Outputs data asset includes current and projected future levels of ambient concentrations and deposition to support regulatory impact analyses.
Data contributed by EPA/ORD/CEMM/AESMD to the manuscript The Community Multiscale Air Quality (CMAQ) Model Versions 5.3 and 5.3.1: System Updates and Evaluation
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Annual CMAQ model output for 2016 for approximately six different simulations. This dataset is not publicly accessible because: Data are too large to upload to ScienceHub. It can be accessed through the following means: These data can be requested from the author. Format: Data formats include I/O API and csv. This dataset is associated with the following publication: Appel, K.W., J. Bash, K. Fahey, K. Foley, R. Gilliam, C. Hogrefe, B. Hutzell, D. Kang, R. Mathur, B. Murphy, S. Napelenok, C. Nolte, J. Pleim, G. Pouliot, H. Pye, G. Sarwar, D. Schwede, F. Sidi, T. Spero, D. Wong, L. Ran, and S. Roselle. The Community Multiscale Air Quality (CMAQ) Model Version 5.3: System Updates and Evaluation. Geoscientific Model Development. Copernicus Publications, Katlenburg-Lindau, GERMANY, 14: 2867-2897, (2021).
Data contributed by EPA/ORD/CEMM/AESMD to the manuscript The Community Multiscale Air Quality (CMAQ) Model Versions 5.3 and 5.3.1: System Updates and Evaluation
공공데이터포털
Annual CMAQ model output for 2016 for approximately six different simulations. This dataset is not publicly accessible because: Data are too large to upload to ScienceHub. It can be accessed through the following means: These data can be requested from the author. Format: Data formats include I/O API and csv. This dataset is associated with the following publication: Appel, K.W., J. Bash, K. Fahey, K. Foley, R. Gilliam, C. Hogrefe, B. Hutzell, D. Kang, R. Mathur, B. Murphy, S. Napelenok, C. Nolte, J. Pleim, G. Pouliot, H. Pye, G. Sarwar, D. Schwede, F. Sidi, T. Spero, D. Wong, L. Ran, and S. Roselle. The Community Multiscale Air Quality (CMAQ) Model Version 5.3: System Updates and Evaluation. Geoscientific Model Development. Copernicus Publications, Katlenburg-Lindau, GERMANY, 14: 2867-2897, (2021).
Multiscale predictions of aviation-attributable PM 2.5 for US airports modeled using CMAQ with plume-in-grid and an aircraft-specific 1-D emission model
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NA. This dataset is not publicly accessible because: No EPA generated data was used in this work. It can be accessed through the following means: NA. Format: No EPA generated data was used in this work. This dataset is associated with the following publication: Woody, M., H. Hsi-Wu Wong, J.J. West, and S. Arunachalam. Multiscale predictions of aviation-attributable PM2.5 for U.S. airports modeled using CMAQ with plume-in-grid and an aircraft-specific 1-D emission model. ATMOSPHERIC ENVIRONMENT. Elsevier Science Ltd, New York, NY, USA, 147: 384-394, (2016).
2002-2017 Anthropogenic Emissions Data for AQ Model US
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The US EPA developed a set of modeled meteorology, emissions, air quality and pollutant deposition spanning the years 2002 through 2019. Modeled datasets cover the Conterminous US (CONUS) at a 12km horizontal grid spacing (12US1) and the Northern Hemisphere at a 108km (108NHEMI) using WRFv4.1.1 for meteorology and CMAQv5.3.2 for air quality modeling. New hemispheric and North American emissions inventories were developed using, to the extent possible, consistent input data and methods across all years, including emissions from mobile, fire, and oil and gas sources. Collectively these model outputs represent 100s of TB of data. We have selected a subset of the model input and output datasets that we hope will be most useful to the air quality research community. These datasets include: - Emissions inventory files for the CONUS for 2002-2019 suitable for input into the Sparse Matrix Operator Kernel Emissions (SMOKE) emission processor - Emissions trends data with annual total emissions, summed by pollutant and emissions source category - CMAQ-ready emissions, initial conditions and boundary condition input files for the 12US1 domain for 2002-2019 - CMAQ-ready meteorology files for the 12US1 domain for 2002-2019. - Matched meteorology model output with surface observations for 2002-2019 - Daily average CMAQ output for the 12US1 domain for 2002-2019 for 14 pollutants - Daily average 3D CMAQ output for 44 layers for the 108NHEMI domain for 2002–2019 - Annual total wet and dry deposition for the 12US1 domain for 2002-2019 - Hourly surface and 3D modeled meteorology, deposition and air concentrations for the 12US1 and 108NHEMI domains for 2002-2019. This dataset is associated with the following publication: Foley, K., G. Pouliot, A. Eyth, M. Aldridge, C. Allen, K. Appel, J. Bash, M. Beardsley, J. Beidler, J. Choi, C. Farkas, R. Gilliam, J. Godfrey, B. Henderson, C. Hogrefe, S. Koplitz, R. Mason, R. Mathur, C. Misenis, N. Possiel, H. Pye, L. Reynolds, M. Roark, S. Roberts, D. Schwede, K. Seltzer, D. Sonntag, K. Talgo, C. Toro, J. Vukovich, J. Xing, and E. Adams. 2002-2017 Anthropogenic Emissions Data for Air Quality Modeling over the United States. Data in Brief. Elsevier B.V., Amsterdam, NETHERLANDS, 47: N/A, (2023).
The Detailed Emissions Scaling, Isolation, and Diagnostic (DESID) module in the Community Multiscale Air Quality (CMAQ) Modeling System version 5.3
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This dataset documents the simulations demonstrating the capabilities of the new DESID module, a part of CMAQ that allows for adjustment of emissions and expanded diagnostic output. There are three figures, each with four subpanels, that are provided here. They are all present in the supporting information of the manuscript. There are no figures with data in the main manuscript. This dataset is not publicly accessible because: See explanation above. It can be accessed through the following means: See explanation above. Format: This research paper is somewhat unique in that there is no data presented in the main manuscript. There are three figures presented in the supporting information which are generated from input and output data from CMAQ. The figures are for tutorial purposes only and do not directly contribute to any analysis or conclusions of any scientific hypothesis or policy recommendation. The CMAQ code, data and figure scripts used to generate the supporting information figures may be found on ASM in the folder: /asm/MOD3DEV/bmurphy/ScienceHub/DESID. This dataset is associated with the following publication: Murphy, B., C. Nolte, F. Sidi, J. Bash, K.W. Appel, C. Jang, D. Kang, J. Kelly, R. Mathur, S. Napelenok, G. Pouliot, and H. Pye. The Detailed Emissions Scaling, Isolation, and Diagnostic (DESID) module in the Community Multiscale Air Quality (CMAQ) Modeling System version 5.3.2. Geoscientific Model Development. Copernicus Publications, Katlenburg-Lindau, GERMANY, 14(6): 3407-3420, (2021).
The Detailed Emissions Scaling, Isolation, and Diagnostic (DESID) module in the Community Multiscale Air Quality (CMAQ) Modeling System version 5.3
공공데이터포털
This dataset documents the simulations demonstrating the capabilities of the new DESID module, a part of CMAQ that allows for adjustment of emissions and expanded diagnostic output. There are three figures, each with four subpanels, that are provided here. They are all present in the supporting information of the manuscript. There are no figures with data in the main manuscript. This dataset is not publicly accessible because: See explanation above. It can be accessed through the following means: See explanation above. Format: This research paper is somewhat unique in that there is no data presented in the main manuscript. There are three figures presented in the supporting information which are generated from input and output data from CMAQ. The figures are for tutorial purposes only and do not directly contribute to any analysis or conclusions of any scientific hypothesis or policy recommendation. The CMAQ code, data and figure scripts used to generate the supporting information figures may be found on ASM in the folder: /asm/MOD3DEV/bmurphy/ScienceHub/DESID. This dataset is associated with the following publication: Murphy, B., C. Nolte, F. Sidi, J. Bash, K.W. Appel, C. Jang, D. Kang, J. Kelly, R. Mathur, S. Napelenok, G. Pouliot, and H. Pye. The Detailed Emissions Scaling, Isolation, and Diagnostic (DESID) module in the Community Multiscale Air Quality (CMAQ) Modeling System version 5.3.2. Geoscientific Model Development. Copernicus Publications, Katlenburg-Lindau, GERMANY, 14(6): 3407-3420, (2021).
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