Articles | Volume 18, issue 9
https://doi.org/10.5194/acp-18-6241-2018
© Author(s) 2018. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
Special issue:
https://doi.org/10.5194/acp-18-6241-2018
© Author(s) 2018. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
Research article
| 
03 May 2018
Research article |
| 03 May 2018
Detection of critical PM2.5 emission sources and their contributions to a heavy haze episode in Beijing, China, using an adjoint model
Shixian Zhai
Key Laboratory for Aerosol-Cloud-Precipitation of China
Meteorological Administration, Collaborative Innovation Center on Forecast
and Evaluation of Meteorological Disasters, Nanjing University of Information
Science & Technology, Nanjing 210044, China
Xingqin An
CORRESPONDING AUTHOR
Institute of Atmospheric Composition, Chinese Academy of Meteorological Sciences, Beijing 100081, China
State Key Laboratory of Severe Weather & Key Laboratory of Atmospheric Chemistry of CMA, Chinese
Academy of Meteorological Sciences, Beijing 100081, China
Tianliang Zhao
CORRESPONDING AUTHOR
Key Laboratory for Aerosol-Cloud-Precipitation of China
Meteorological Administration, Collaborative Innovation Center on Forecast
and Evaluation of Meteorological Disasters, Nanjing University of Information
Science & Technology, Nanjing 210044, China
Zhaobin Sun
Institute of Urban Meteorology, China Meteorological
Administration, Beijing 100089, China
Wei Wang
China National Environmental
Monitoring Center, Beijing, 100012, China
Qing Hou
Institute of Atmospheric Composition, Chinese Academy of Meteorological Sciences, Beijing 100081, China
State Key Laboratory of Severe Weather & Key Laboratory of Atmospheric Chemistry of CMA, Chinese
Academy of Meteorological Sciences, Beijing 100081, China
Zengyuan Guo
Institute of Atmospheric Composition, Chinese Academy of Meteorological Sciences, Beijing 100081, China
State Key Laboratory of Severe Weather & Key Laboratory of Atmospheric Chemistry of CMA, Chinese
Academy of Meteorological Sciences, Beijing 100081, China
Chao Wang
Institute of Atmospheric Composition, Chinese Academy of Meteorological Sciences, Beijing 100081, China
State Key Laboratory of Severe Weather & Key Laboratory of Atmospheric Chemistry of CMA, Chinese
Academy of Meteorological Sciences, Beijing 100081, China
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- Spatial Association Effect of Haze Pollution in Cheng-Yu Urban Agglomeration D. Zhang et al. 10.1038/s41598-020-66665-8
- Impact of emissions from a single urban source on air quality estimated from mobile observation and WRF-STILT model simulations H. Fan et al. 10.1007/s11869-021-01023-9
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- Sensitivity analysis and precursor emission sources reduction strategies of O3 for different pollution weather types based on the GRAPES-CUACE adjoint model C. Wang et al. 10.1016/j.atmosenv.2024.120632
- Mapping ozone source-receptor relationship and apportioning the health impact in the Pearl River Delta region using adjoint sensitivity analysis M. Wang et al. 10.1016/j.atmosenv.2019.117026
- Quantification of SO2 Emission Variations and the Corresponding Prediction Improvements Made by Assimilating Ground-Based Observations J. Mo et al. 10.3390/atmos13030470
- Sensitivity analysis of atmospheric oxidation capacity in Beijing based on the GRAPES-CUACE adjoint model C. Wang et al. 10.1016/j.atmosenv.2023.119641
- Progress in quantitative research on the relationship between atmospheric oxidation and air quality Y. Wang et al. 10.1016/j.jes.2022.06.029
- Source contributions of surface ozone in China using an adjoint sensitivity analysis M. Wang et al. 10.1016/j.scitotenv.2019.01.116
- Trans‐Regional Transport of Haze Particles From the North China Plain to Yangtze River Delta During Winter J. Zhang et al. 10.1029/2020JD033778
- Secondary aerosol formation in winter haze over the Beijing-Tianjin-Hebei Region, China D. Shang et al. 10.1007/s11783-020-1326-x
- The combined effects of heterogeneous chemistry and aerosol-radiation interaction on severe haze simulation by atmospheric chemistry model in Middle-Eastern China Z. Liu et al. 10.1016/j.atmosenv.2023.119729
- Sensitivity analysis of PM2.5 and O3 co-pollution in Beijing based on GRAPES-CUACE adjoint model Z. Liu et al. 10.1016/j.jes.2024.11.020
- Source backtracking for dust storm emission inversion using an adjoint method: case study of Northeast China J. Jin et al. 10.5194/acp-20-15207-2020
- Radiation fog properties in two consecutive events under polluted and clean conditions in the Yangtze River Delta, China: a simulation study N. Shao et al. 10.5194/acp-23-9873-2023
- The efforts of China to combat air pollution during the period of 2015–2018: A case study assessing the environmental, health and economic benefits in the Beijing-Tianjin-Hebei and surrounding “2 + 26” regions N. Zhao et al. 10.1016/j.scitotenv.2022.158437
- Monitoring history and change trends of ambient air quality in China during the past four decades F. Zhang et al. 10.1016/j.jenvman.2019.110031
- Haze Pollution in the Unstable Atmospheric Boundary Layer Over the West Bank of Taiwan Strait Induced by Regional Transport of PM2.5 Y. Jiang et al. 10.1029/2022EA002505
- Numerical study of air pollution over a typical basin topography: Source appointment of fine particulate matter during one severe haze in the megacity Xi'an X. Yang et al. 10.1016/j.scitotenv.2019.135213
- Quantified the influence of different synoptic weather patterns on the transport and local production processes of O3 events in Pearl River Delta, China Y. You et al. 10.1016/j.scitotenv.2023.169066
2 citations as recorded by crossref.
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- Impacts of Regional Transport on Particulate Matter Pollution in China: a Review of Methods and Results J. Sun et al. 10.1007/s40726-017-0065-5
Latest update: 14 Dec 2024
Short summary
The GRAPES–CUACE aerosol adjoint model was developed and applied in detecting PM2.5 sources for haze events in eastern China (EC). The response time of Beijing PM2.5 pollution peaks to local and surrounding emissions is quantized for regional transport of air pollution over the EC. The adjoint results agreed well with the Models-3/CMAQ assessments. The adjoint method is powerful in simulating the receptor–source relationship and can be utilized in dynamic air quality control scheme design.
The GRAPES–CUACE aerosol adjoint model was developed and applied in detecting PM2.5 sources for...
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