Articles | Volume 14, issue 6
https://doi.org/10.5194/gmd-14-3407-2021
© Author(s) 2021. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/gmd-14-3407-2021
© Author(s) 2021. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Model description paper
| 
07 Jun 2021
Model description paper |
| 07 Jun 2021
| 07 Jun 2021
The Detailed Emissions Scaling, Isolation, and Diagnostic (DESID) module in the Community Multiscale Air Quality (CMAQ) modeling system version 5.3.2
Center for Environmental Measurement and Modeling, U.S. Environmental
Protection Agency, Research Triangle Park, NC 27711, USA
Christopher G. Nolte
Center for Environmental Measurement and Modeling, U.S. Environmental
Protection Agency, Research Triangle Park, NC 27711, USA
Fahim Sidi
Center for Environmental Measurement and Modeling, U.S. Environmental
Protection Agency, Research Triangle Park, NC 27711, USA
Jesse O. Bash
Center for Environmental Measurement and Modeling, U.S. Environmental
Protection Agency, Research Triangle Park, NC 27711, USA
K. Wyat Appel
Center for Environmental Measurement and Modeling, U.S. Environmental
Protection Agency, Research Triangle Park, NC 27711, USA
Carey Jang
Office of Air Quality Planning and Standards, U.S. Environmental
Protection Agency, Research Triangle Park, NC 27711, USA
Daiwen Kang
Center for Environmental Measurement and Modeling, U.S. Environmental
Protection Agency, Research Triangle Park, NC 27711, USA
James Kelly
Office of Air Quality Planning and Standards, U.S. Environmental
Protection Agency, Research Triangle Park, NC 27711, USA
Rohit Mathur
Center for Environmental Measurement and Modeling, U.S. Environmental
Protection Agency, Research Triangle Park, NC 27711, USA
Sergey Napelenok
Center for Environmental Measurement and Modeling, U.S. Environmental
Protection Agency, Research Triangle Park, NC 27711, USA
George Pouliot
Center for Environmental Measurement and Modeling, U.S. Environmental
Protection Agency, Research Triangle Park, NC 27711, USA
Havala O. T. Pye
Center for Environmental Measurement and Modeling, U.S. Environmental
Protection Agency, Research Triangle Park, NC 27711, USA
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- Temperature-Dependent Composition of Summertime PM2.5 in Observations and Model Predictions across the Eastern U.S. P. Vannucci et al. 10.1021/acsearthspacechem.3c00333
- Modeling secondary organic aerosol formation from volatile chemical products E. Pennington et al. 10.5194/acp-21-18247-2021
- Impacts of condensable particulate matter on atmospheric organic aerosols and fine particulate matter (PM2.5) in China M. Li et al. 10.5194/acp-22-11845-2022
- Human-Health Impacts of Controlling Secondary Air Pollution Precursors H. Pye et al. 10.1021/acs.estlett.1c00798
- Modeling regional nitrogen cycle in the atmosphere: Present situation and its response to the future emissions control strategy A. Shen et al. 10.1016/j.scitotenv.2023.164379
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- An updated modeling framework to simulate Los Angeles air quality – Part 1: Model development, evaluation, and source apportionment E. Pennington et al. 10.5194/acp-24-2345-2024
- The impacts of marine-emitted halogens on OH radicals in East Asia during summer S. Fan & Y. Li 10.5194/acp-22-7331-2022
- Volatile Chemical Product Enhancements to Criteria Pollutants in the United States K. Seltzer et al. 10.1021/acs.est.1c04298
- Characterizing variations in ambient PM2.5 concentrations at the U.S. Embassy in Dhaka, Bangladesh using observations and the CMAQ modeling system G. Sarwar et al. 10.1016/j.atmosenv.2023.119587
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- The Modeling Study about Impacts of Emission Control Policies for Chinese 14th Five-Year Plan on PM2.5 and O3 in Yangtze River Delta, China Z. Li et al. 10.3390/atmos13010026
- An Air Pollutants Prediction Method Integrating Numerical Models and Artificial Intelligence Models Targeting the Area around Busan Port in Korea H. Hong et al. 10.3390/atmos13091462
- Modeling polycyclic aromatic hydrocarbons (PAHs) concentrations from wildfires in California S. Zhu et al. 10.1016/j.agrformet.2024.110043
- Anthropogenic secondary organic aerosol and ozone production from asphalt-related emissions K. Seltzer et al. 10.1039/D3EA00066D
- Role of meteorology-driven regional transport on O3 pollution over the Chengdu Plain, southwestern China Y. Lei et al. 10.1016/j.atmosres.2023.106619
- How Have Divergent Global Emission Trends Influenced Long‐Range Transported Ozone to North America? R. Mathur et al. 10.1029/2022JD036926
- Predicting the Nonlinear Response of PM2.5 and Ozone to Precursor Emission Changes with a Response Surface Model J. Kelly et al. 10.3390/atmos12081044
20 citations as recorded by crossref.
- Atmospheric impact of isoprene-derived Criegee intermediates and isoprene hydroxy hydroperoxide on sulfate aerosol formation in the Asian region H. Hata et al. 10.1016/j.aeaoa.2023.100226
- Temperature-Dependent Composition of Summertime PM2.5 in Observations and Model Predictions across the Eastern U.S. P. Vannucci et al. 10.1021/acsearthspacechem.3c00333
- Modeling secondary organic aerosol formation from volatile chemical products E. Pennington et al. 10.5194/acp-21-18247-2021
- Impacts of condensable particulate matter on atmospheric organic aerosols and fine particulate matter (PM2.5) in China M. Li et al. 10.5194/acp-22-11845-2022
- Human-Health Impacts of Controlling Secondary Air Pollution Precursors H. Pye et al. 10.1021/acs.estlett.1c00798
- Modeling regional nitrogen cycle in the atmosphere: Present situation and its response to the future emissions control strategy A. Shen et al. 10.1016/j.scitotenv.2023.164379
- Sensitivity of northeastern US surface ozone predictions to the representation of atmospheric chemistry in the Community Regional Atmospheric Chemistry Multiphase Mechanism (CRACMMv1.0) B. Place et al. 10.5194/acp-23-9173-2023
- Sensitivity of air quality to vehicle ammonia emissions in the United States C. Toro et al. 10.1016/j.atmosenv.2024.120484
- Non-stop industries were the main source of air pollution during the 2020 coronavirus lockdown in the North China Plain Z. Li et al. 10.1007/s10311-021-01314-8
- An updated modeling framework to simulate Los Angeles air quality – Part 1: Model development, evaluation, and source apportionment E. Pennington et al. 10.5194/acp-24-2345-2024
- The impacts of marine-emitted halogens on OH radicals in East Asia during summer S. Fan & Y. Li 10.5194/acp-22-7331-2022
- Volatile Chemical Product Enhancements to Criteria Pollutants in the United States K. Seltzer et al. 10.1021/acs.est.1c04298
- Characterizing variations in ambient PM2.5 concentrations at the U.S. Embassy in Dhaka, Bangladesh using observations and the CMAQ modeling system G. Sarwar et al. 10.1016/j.atmosenv.2023.119587
- A quantitative assessment and process analysis of the contribution from meteorological conditions in an O3 pollution episode in Guangzhou, China Y. Xu et al. 10.1016/j.atmosenv.2023.119757
- The Modeling Study about Impacts of Emission Control Policies for Chinese 14th Five-Year Plan on PM2.5 and O3 in Yangtze River Delta, China Z. Li et al. 10.3390/atmos13010026
- An Air Pollutants Prediction Method Integrating Numerical Models and Artificial Intelligence Models Targeting the Area around Busan Port in Korea H. Hong et al. 10.3390/atmos13091462
- Modeling polycyclic aromatic hydrocarbons (PAHs) concentrations from wildfires in California S. Zhu et al. 10.1016/j.agrformet.2024.110043
- Anthropogenic secondary organic aerosol and ozone production from asphalt-related emissions K. Seltzer et al. 10.1039/D3EA00066D
- Role of meteorology-driven regional transport on O3 pollution over the Chengdu Plain, southwestern China Y. Lei et al. 10.1016/j.atmosres.2023.106619
- How Have Divergent Global Emission Trends Influenced Long‐Range Transported Ozone to North America? R. Mathur et al. 10.1029/2022JD036926
Latest update: 30 Jun 2024
Short summary
The algorithms for applying air pollution emission rates in the Community Multiscale Air Quality (CMAQ) model have been improved to better support users and developers. The new features accommodate emissions perturbation studies that are typical in atmospheric research and output a wealth of metadata for each model run so assumptions can be verified and documented. The new approach dramatically enhances the transparency and functionality of this critical aspect of atmospheric modeling.
The algorithms for applying air pollution emission rates in the Community Multiscale Air Quality...
