Articles | Volume 20, issue 23
https://doi.org/10.5194/acp-20-14787-2020
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/acp-20-14787-2020
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
02 Dec 2020
Research article |
| 02 Dec 2020
| 02 Dec 2020
Significant wintertime PM2.5 mitigation in the Yangtze River Delta, China, from 2016 to 2019: observational constraints on anthropogenic emission controls
Liqiang Wang
Research Center for Air Pollution and Health, Key Laboratory of
Environmental Remediation and Ecological Health, Ministry of Education,
College of Environment and Resource Sciences, Zhejiang University, Hangzhou, Zhejiang 310058, P.R. China
Research Center for Air Pollution and Health, Key Laboratory of
Environmental Remediation and Ecological Health, Ministry of Education,
College of Environment and Resource Sciences, Zhejiang University, Hangzhou, Zhejiang 310058, P.R. China
Division of Chemistry and Chemical Engineering, California Institute of Technology, Pasadena, CA 91125, USA
Pengfei Li
CORRESPONDING AUTHOR
College of Science and Technology, Hebei Agricultural University,
Baoding, Hebei 071000, P.R. China
Research Center for Air Pollution and Health, Key Laboratory of
Environmental Remediation and Ecological Health, Ministry of Education,
College of Environment and Resource Sciences, Zhejiang University, Hangzhou, Zhejiang 310058, P.R. China
Xue Chen
Research Center for Air Pollution and Health, Key Laboratory of
Environmental Remediation and Ecological Health, Ministry of Education,
College of Environment and Resource Sciences, Zhejiang University, Hangzhou, Zhejiang 310058, P.R. China
Zhen Li
Research Center for Air Pollution and Health, Key Laboratory of
Environmental Remediation and Ecological Health, Ministry of Education,
College of Environment and Resource Sciences, Zhejiang University, Hangzhou, Zhejiang 310058, P.R. China
Yibo Zhang
Research Center for Air Pollution and Health, Key Laboratory of
Environmental Remediation and Ecological Health, Ministry of Education,
College of Environment and Resource Sciences, Zhejiang University, Hangzhou, Zhejiang 310058, P.R. China
Mengying Li
Research Center for Air Pollution and Health, Key Laboratory of
Environmental Remediation and Ecological Health, Ministry of Education,
College of Environment and Resource Sciences, Zhejiang University, Hangzhou, Zhejiang 310058, P.R. China
Khalid Mehmood
Research Center for Air Pollution and Health, Key Laboratory of
Environmental Remediation and Ecological Health, Ministry of Education,
College of Environment and Resource Sciences, Zhejiang University, Hangzhou, Zhejiang 310058, P.R. China
Weiping Liu
Research Center for Air Pollution and Health, Key Laboratory of
Environmental Remediation and Ecological Health, Ministry of Education,
College of Environment and Resource Sciences, Zhejiang University, Hangzhou, Zhejiang 310058, P.R. China
Tianfeng Chai
Air Resources Laboratory, NOAA, Cooperative Institute for Satellite
Earth System Studies (CISESS), University of Maryland, College Park, USA
Yannian Zhu
Meteorological Institute of Shananxi Province, 36 Beiguanzhengjie,
Xi'an 710015, China
Daniel Rosenfeld
Institute of Earth Science, The Hebrew University of Jerusalem,
Jerusalem, Israel
John H. Seinfeld
Division of Chemistry and Chemical Engineering, California Institute of Technology, Pasadena, CA 91125, USA
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- Hyperfine-resolution mapping of on-road vehicle emissions with comprehensive traffic monitoring and an intelligent transportation system L. Jiang et al. 10.5194/acp-21-16985-2021
- Widespread missing super-emitters of nitrogen oxides across China inferred from year-round satellite observations Y. Pan et al. 10.1016/j.scitotenv.2022.161157
- Operational Data-Driven Intelligent Modelling and Visualization System for Real-World, On-Road Vehicle Emissions—A Case Study in Hangzhou City, China L. Wang et al. 10.3390/su14095434
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- 气象条件对京津冀地区<bold>O</bold><sub><bold>3</bold></sub>和<bold>PM</bold><sub><bold>2.5</bold></sub>双高污染的影响及对减排的启示作用 晓. 麻 et al. 10.1360/N072022-0216
- Predicting annual PM2.5 in mainland China from 2014 to 2020 using multi temporal satellite product: An improved deep learning approach with spatial generalization ability Z. Wang et al. 10.1016/j.isprsjprs.2022.03.002
- Analyses and Simulations of PM2.5 Pollution Characteristics under the Influence of the New Year’s Day Effects in China Q. Shi et al. 10.3390/atmos15050568
- Large contributions of emission reductions and meteorological conditions to the abatement of PM2.5 in Beijing during the 24th Winter Olympic Games in 2022 Y. Jiang et al. 10.1016/j.jes.2022.12.017
- Trends in secondary inorganic aerosol pollution in China and its responses to emission controls of precursors in wintertime F. Meng et al. 10.5194/acp-22-6291-2022
- 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
- Assessment of vertical characterization and potential sources of aerosols in different altitude layers: Combined application of MAX-DOAS observation and the 3D-CWT model J. Chen et al. 10.1016/j.atmosres.2023.107046
- Analysis of Emission Reduction Measures and Simulation of PM2.5 Concentrations in the Main Cotton Production Areas of Xinjiang in 2025 C. Fang et al. 10.3390/atmos15020201
14 citations as recorded by crossref.
- Development of an integrated machine learning model to improve the secondary inorganic aerosol simulation over the Beijing–Tianjin–Hebei region N. Ding et al. 10.1016/j.atmosenv.2024.120483
- Meteorological influences on co-occurrence of O3 and PM2.5 pollution and implication for emission reductions in Beijing-Tianjin-Hebei X. Ma et al. 10.1007/s11430-022-1070-y
- Hyperfine-resolution mapping of on-road vehicle emissions with comprehensive traffic monitoring and an intelligent transportation system L. Jiang et al. 10.5194/acp-21-16985-2021
- Widespread missing super-emitters of nitrogen oxides across China inferred from year-round satellite observations Y. Pan et al. 10.1016/j.scitotenv.2022.161157
- Operational Data-Driven Intelligent Modelling and Visualization System for Real-World, On-Road Vehicle Emissions—A Case Study in Hangzhou City, China L. Wang et al. 10.3390/su14095434
- The Potential of Monitoring Carbon Dioxide Emission in a Geostationary View with the GIIRS Meteorological Hyperspectral Infrared Sounder Q. Zhang et al. 10.3390/rs15040886
- 气象条件对京津冀地区<bold>O</bold><sub><bold>3</bold></sub>和<bold>PM</bold><sub><bold>2.5</bold></sub>双高污染的影响及对减排的启示作用 晓. 麻 et al. 10.1360/N072022-0216
- Predicting annual PM2.5 in mainland China from 2014 to 2020 using multi temporal satellite product: An improved deep learning approach with spatial generalization ability Z. Wang et al. 10.1016/j.isprsjprs.2022.03.002
- Analyses and Simulations of PM2.5 Pollution Characteristics under the Influence of the New Year’s Day Effects in China Q. Shi et al. 10.3390/atmos15050568
- Large contributions of emission reductions and meteorological conditions to the abatement of PM2.5 in Beijing during the 24th Winter Olympic Games in 2022 Y. Jiang et al. 10.1016/j.jes.2022.12.017
- Trends in secondary inorganic aerosol pollution in China and its responses to emission controls of precursors in wintertime F. Meng et al. 10.5194/acp-22-6291-2022
- 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
- Assessment of vertical characterization and potential sources of aerosols in different altitude layers: Combined application of MAX-DOAS observation and the 3D-CWT model J. Chen et al. 10.1016/j.atmosres.2023.107046
- Analysis of Emission Reduction Measures and Simulation of PM2.5 Concentrations in the Main Cotton Production Areas of Xinjiang in 2025 C. Fang et al. 10.3390/atmos15020201
Latest update: 20 Nov 2024
Short summary
The Chinese government has made major strides in curbing anthropogenic emissions. In this study, we constrain a state-of-the-art CTM by a reliable data assimilation method with extensive chemical and meteorological observations. This comprehensive technical design provides a crucial advance in isolating the influences of emission changes and meteorological perturbations over the Yangtze River Delta (YRD) from 2016 to 2019, thus establishing the first map of the PM2.5 mitigation across the YRD.
The Chinese government has made major strides in curbing anthropogenic emissions. In this study,...
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