Articles | Volume 17, issue 19
https://doi.org/10.5194/acp-17-12031-2017
© Author(s) 2017. 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-17-12031-2017
© Author(s) 2017. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
Research article
| 
10 Oct 2017
Research article |
| 10 Oct 2017
A modeling study of the nonlinear response of fine particles to air pollutant emissions in the Beijing–Tianjin–Hebei region
School of Environment and State Key Joint Laboratory of Environment Simulation and Pollution Control, Tsinghua University, Beijing 100084, China
State Environmental Protection Key Laboratory of Sources and Control of Air Pollution Complex, Beijing 100084, China
Joint Institute for Regional Earth System Science and Engineering and Department of Atmospheric and Oceanic Sciences,
University of California, Los Angeles, CA 90095, USA
Wenjing Wu
School of Environment and State Key Joint Laboratory of Environment Simulation and Pollution Control, Tsinghua University, Beijing 100084, China
State Environmental Protection Key Laboratory of Sources and Control of Air Pollution Complex, Beijing 100084, China
School of Environment and State Key Joint Laboratory of Environment Simulation and Pollution Control, Tsinghua University, Beijing 100084, China
State Environmental Protection Key Laboratory of Sources and Control of Air Pollution Complex, Beijing 100084, China
Jia Xing
School of Environment and State Key Joint Laboratory of Environment Simulation and Pollution Control, Tsinghua University, Beijing 100084, China
State Environmental Protection Key Laboratory of Sources and Control of Air Pollution Complex, Beijing 100084, China
Xing Chang
School of Environment and State Key Joint Laboratory of Environment Simulation and Pollution Control, Tsinghua University, Beijing 100084, China
State Environmental Protection Key Laboratory of Sources and Control of Air Pollution Complex, Beijing 100084, China
Kuo-Nan Liou
Joint Institute for Regional Earth System Science and Engineering and Department of Atmospheric and Oceanic Sciences,
University of California, Los Angeles, CA 90095, USA
Jonathan H. Jiang
Jet propulsion Laboratory, California Institute of Technology, Pasadena, CA 91109, USA
Joint Institute for Regional Earth System Science and Engineering and Department of Atmospheric and Oceanic Sciences,
University of California, Los Angeles, CA 90095, USA
Carey Jang
U.S. Environmental Protection Agency, Research Triangle Park, NC 27711, USA
Joshua S. Fu
Department of Civil and Environmental Engineering, University of Tennessee, Knoxville, TN 37996, USA
Yun Zhu
School of Environmental Science and Engineering, South China University of Technology, Guangzhou 510006, China
Jiandong Wang
School of Environment and State Key Joint Laboratory of Environment Simulation and Pollution Control, Tsinghua University, Beijing 100084, China
State Environmental Protection Key Laboratory of Sources and Control of Air Pollution Complex, Beijing 100084, China
Yan Lin
Norwegian Institute for Water Research, Oslo, 0349, Norway
Jiming Hao
School of Environment and State Key Joint Laboratory of Environment Simulation and Pollution Control, Tsinghua University, Beijing 100084, China
State Environmental Protection Key Laboratory of Sources and Control of Air Pollution Complex, Beijing 100084, China
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- Source and sectoral contribution analysis of PM2.5 based on efficient response surface modeling technique over Pearl River Delta Region of China Y. Pan et al. 10.1016/j.scitotenv.2020.139655
- Transition in source contributions of PM2.5 exposure and associated premature mortality in China during 2005–2015 H. Zheng et al. 10.1016/j.envint.2019.105111
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Latest update: 17 Apr 2024
Short summary
Using over 1000 chemical transport model simulations in the Beijing–Tianjin–Hebei region, we find that the emissions of primary inorganic PM2.5 make the largest contribution to PM2.5 concentrations and thus should be prioritized in PM2.5 control strategies. Among the precursors, PM2.5 concentrations are primarily sensitive to the emissions of NH3, NMVOC+IVOC, and POA, and the sensitivities increase substantially for NH3 and NHx with the increase in emission reduction ratio.
Using over 1000 chemical transport model simulations in the Beijing–Tianjin–Hebei region, we...
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