Articles | Volume 23, issue 18
https://doi.org/10.5194/acp-23-10563-2023
© 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/acp-23-10563-2023
© Author(s) 2023. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
25 Sep 2023
Research article |
| 25 Sep 2023
| 25 Sep 2023
Evolution of atmospheric age of particles and its implications for the formation of a severe haze event in eastern China
Xiaodong Xie
Jiangsu Key Laboratory of Atmospheric Environment Monitoring and Pollution Control, Collaborative Innovation Center of Atmospheric Environment and Equipment Technology, Nanjing University of Information Science and Technology, Nanjing 210044, China
Jianlin Hu
CORRESPONDING AUTHOR
Jiangsu Key Laboratory of Atmospheric Environment Monitoring and Pollution Control, Collaborative Innovation Center of Atmospheric Environment and Equipment Technology, Nanjing University of Information Science and Technology, Nanjing 210044, China
Momei Qin
Jiangsu Key Laboratory of Atmospheric Environment Monitoring and Pollution Control, Collaborative Innovation Center of Atmospheric Environment and Equipment Technology, Nanjing University of Information Science and Technology, Nanjing 210044, China
State Key Joint Laboratory of Environmental Simulation and Pollution Control, College of Environmental Sciences and Engineering, Peking University, Beijing 100871, China
State Key Joint Laboratory of Environmental Simulation and Pollution Control, College of Environmental Sciences and Engineering, Peking University, Beijing 100871, China
Dongsheng Ji
State Key Laboratory of Atmospheric Boundary Layer Physics and Atmospheric Chemistry, Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing 100191, China
Hongli Wang
State Environmental Protection Key Laboratory of Formation and Prevention of Urban Air Pollution Complex, Shanghai Academy of Environmental Sciences, Shanghai 200233, China
Shengrong Lou
State Environmental Protection Key Laboratory of Formation and Prevention of Urban Air Pollution Complex, Shanghai Academy of Environmental Sciences, Shanghai 200233, China
Cheng Huang
State Environmental Protection Key Laboratory of Formation and Prevention of Urban Air Pollution Complex, Shanghai Academy of Environmental Sciences, Shanghai 200233, China
Chong Liu
CMA Earth System Modeling and Prediction Centre, State Key Laboratory of Severe Weather, China Meteorological Administration (CMA), Beijing 100081, China
Hongliang Zhang
Department of Environmental Science and Engineering, Fudan University, Shanghai 200438, China
Qi Ying
Zachry Department of Civil and Environmental Engineering, Texas A&M University, College Station, Texas 77843, USA
Hong Liao
Jiangsu Key Laboratory of Atmospheric Environment Monitoring and Pollution Control, Collaborative Innovation Center of Atmospheric Environment and Equipment Technology, Nanjing University of Information Science and Technology, Nanjing 210044, China
Yuanhang Zhang
State Key Joint Laboratory of Environmental Simulation and Pollution Control, College of Environmental Sciences and Engineering, Peking University, Beijing 100871, China
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Cited
5 citations as recorded by crossref.
- The Variation in Chemical Composition and Source Apportionment of PM2.5 before, during, and after COVID-19 Restrictions in Zhengzhou, China J. Huang et al. 10.3390/toxics12010081
- Source-specified atmospheric age distribution of black carbon and its impact on optical properties over the Yangtze River Delta J. Yin et al. 10.1016/j.scitotenv.2024.171353
- Seasonal quantification of the inter-city transport of PM2.5 in the Yangtze River Delta region of China based on a source-oriented chemical transport model and the Michaelis-Menten equation K. Gong et al. 10.1016/j.scitotenv.2024.173856
- Spatiotemporal source apportionment of ozone pollution over the Greater Bay Area Y. Chen et al. 10.5194/acp-24-8847-2024
- From Home and Abroad─Atmospheric Age-Resolved Modeling Reveals the Origin and Evolution of Photochemical Ozone in South Korea M. Choi & Q. Ying 10.1021/acsestair.4c00029
5 citations as recorded by crossref.
- The Variation in Chemical Composition and Source Apportionment of PM2.5 before, during, and after COVID-19 Restrictions in Zhengzhou, China J. Huang et al. 10.3390/toxics12010081
- Source-specified atmospheric age distribution of black carbon and its impact on optical properties over the Yangtze River Delta J. Yin et al. 10.1016/j.scitotenv.2024.171353
- Seasonal quantification of the inter-city transport of PM2.5 in the Yangtze River Delta region of China based on a source-oriented chemical transport model and the Michaelis-Menten equation K. Gong et al. 10.1016/j.scitotenv.2024.173856
- Spatiotemporal source apportionment of ozone pollution over the Greater Bay Area Y. Chen et al. 10.5194/acp-24-8847-2024
- From Home and Abroad─Atmospheric Age-Resolved Modeling Reveals the Origin and Evolution of Photochemical Ozone in South Korea M. Choi & Q. Ying 10.1021/acsestair.4c00029
Latest update: 20 Nov 2024
Short summary
The atmospheric age of particles reflects how long particles have been formed and suspended in the atmosphere, which is closely associated with the evolution processes of particles. An analysis of the atmospheric age of PM2.5 provides a unique perspective on the evolution processes of different PM2.5 components. The results also shed lights on how to design effective emission control actions under unfavorable meteorological conditions.
The atmospheric age of particles reflects how long particles have been formed and suspended in...
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