Articles | Volume 16, issue 20
https://doi.org/10.5194/gmd-16-5949-2023
© Author(s) 2023. 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-16-5949-2023
© Author(s) 2023. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Model description paper
| 
20 Oct 2023
Model description paper |
| 20 Oct 2023
| 20 Oct 2023
A Regional multi-Air Pollutant Assimilation System (RAPAS v1.0) for emission estimates: system development and application
Shuzhuang Feng
Jiangsu Provincial Key Laboratory of Geographic Information Science and Technology, International Institute for Earth System Science, Nanjing University, Nanjing, 210023, China
Jiangsu Provincial Key Laboratory of Geographic Information Science and Technology, International Institute for Earth System Science, Nanjing University, Nanjing, 210023, China
Jiangsu Center for Collaborative Innovation in Geographical Information Resource Development and Application, Nanjing, 210023, China
Zheng Wu
CMA Key Open Laboratory of Transforming Climate Resources to Economy, Chongqing Institute of Meteorological Sciences, Chongqing 401147, China
Hengmao Wang
Jiangsu Provincial Key Laboratory of Geographic Information Science and Technology, International Institute for Earth System Science, Nanjing University, Nanjing, 210023, China
Jiangsu Center for Collaborative Innovation in Geographical Information Resource Development and Application, Nanjing, 210023, China
Jiangsu Provincial Key Laboratory of Geographic Information Science and Technology, International Institute for Earth System Science, Nanjing University, Nanjing, 210023, China
Yang Shen
Jiangsu Provincial Key Laboratory of Geographic Information Science and Technology, International Institute for Earth System Science, Nanjing University, Nanjing, 210023, China
Lingyu Zhang
Jiangsu Provincial Key Laboratory of Geographic Information Science and Technology, International Institute for Earth System Science, Nanjing University, Nanjing, 210023, China
Yanhua Zheng
Jiangsu Provincial Key Laboratory of Geographic Information Science and Technology, International Institute for Earth System Science, Nanjing University, Nanjing, 210023, China
Chenxi Lou
Jiangsu Provincial Key Laboratory of Geographic Information Science and Technology, International Institute for Earth System Science, Nanjing University, Nanjing, 210023, China
Ziqiang Jiang
Jiangsu Environmental Monitoring Center, Nanjing, 210019, China
Weimin Ju
Jiangsu Provincial Key Laboratory of Geographic Information Science and Technology, International Institute for Earth System Science, Nanjing University, Nanjing, 210023, China
Jiangsu Center for Collaborative Innovation in Geographical Information Resource Development and Application, Nanjing, 210023, China
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Cited
9 citations as recorded by crossref.
- Enhancing CO2 flux inversion accuracy in a coastal megacity: Impacts of land cover and topography in a regional carbon assimilation system J. Fang et al. https://doi.org/10.1016/j.indic.2026.101497
- A Multi-Agglomeration Assessment of Air Quality Responses to Top-Down NOx Emission Changes: Insights from Trends in Surface NO2 and O3 Across Urban China (2014–2021) Y. Shen et al. https://doi.org/10.3390/atmos17030313
- Constraining non-methane VOC emissions with TROPOMI HCHO observations: impact on summertime ozone simulation in August 2022 in China S. Feng et al. https://doi.org/10.5194/acp-24-7481-2024
- Constrained Estimates of Anthropogenic NOx Emissions in China (2014–2021) from Surface Observations Y. Shen et al. https://doi.org/10.3390/atmos17010051
- Sensitivity studies of a four-dimensional local ensemble transform Kalman filter coupled with WRF-Chem version 3.9.1 for improving particulate matter simulation accuracy J. Lin et al. https://doi.org/10.5194/gmd-18-2231-2025
- Development of a regional carbon assimilation system and its application for estimating fossil fuel carbon emissions in the Yangtze River Delta, China Z. Zhang et al. https://doi.org/10.1016/j.scitotenv.2024.177720
- China’s Fossil Fuel CO2 Emissions Estimated Using Surface Observations of Coemitted NO2 S. Feng et al. https://doi.org/10.1021/acs.est.3c07756
- High-resolution regional inversion reveals overestimation of anthropogenic methane emissions in China S. Feng et al. https://doi.org/10.5194/acp-25-15121-2025
- Impacts of multi-source data assimilation and model resolution on anthropogenic NOₓ emission inversions C. Wu et al. https://doi.org/10.1016/j.atmosres.2026.109105
9 citations as recorded by crossref.
- Enhancing CO2 flux inversion accuracy in a coastal megacity: Impacts of land cover and topography in a regional carbon assimilation system J. Fang et al. https://doi.org/10.1016/j.indic.2026.101497
- A Multi-Agglomeration Assessment of Air Quality Responses to Top-Down NOx Emission Changes: Insights from Trends in Surface NO2 and O3 Across Urban China (2014–2021) Y. Shen et al. https://doi.org/10.3390/atmos17030313
- Constraining non-methane VOC emissions with TROPOMI HCHO observations: impact on summertime ozone simulation in August 2022 in China S. Feng et al. https://doi.org/10.5194/acp-24-7481-2024
- Constrained Estimates of Anthropogenic NOx Emissions in China (2014–2021) from Surface Observations Y. Shen et al. https://doi.org/10.3390/atmos17010051
- Sensitivity studies of a four-dimensional local ensemble transform Kalman filter coupled with WRF-Chem version 3.9.1 for improving particulate matter simulation accuracy J. Lin et al. https://doi.org/10.5194/gmd-18-2231-2025
- Development of a regional carbon assimilation system and its application for estimating fossil fuel carbon emissions in the Yangtze River Delta, China Z. Zhang et al. https://doi.org/10.1016/j.scitotenv.2024.177720
- China’s Fossil Fuel CO2 Emissions Estimated Using Surface Observations of Coemitted NO2 S. Feng et al. https://doi.org/10.1021/acs.est.3c07756
- High-resolution regional inversion reveals overestimation of anthropogenic methane emissions in China S. Feng et al. https://doi.org/10.5194/acp-25-15121-2025
- Impacts of multi-source data assimilation and model resolution on anthropogenic NOₓ emission inversions C. Wu et al. https://doi.org/10.1016/j.atmosres.2026.109105
Saved (final revised paper)
Latest update: 20 Sep 2026
Short summary
We document the system development and application of a Regional multi-Air Pollutant Assimilation System (RAPAS v1.0). This system is developed to optimize gridded source emissions of CO, SO2, NOx, primary PM2.5, and coarse PM10 on a regional scale via simultaneously assimilating surface measurements of CO, SO2, NO2, PM2.5, and PM10. A series of sensitivity experiments demonstrates the advantage of the “two-step” inversion strategy and the robustness of the system in estimating the emissions.
We document the system development and application of a Regional multi-Air Pollutant...
