Articles | Volume 21, issue 9
https://doi.org/10.5194/acp-21-7023-2021
© Author(s) 2021. 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-21-7023-2021
© Author(s) 2021. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
07 May 2021
Research article |
| 07 May 2021
| 07 May 2021
Lidar vertical observation network and data assimilation reveal key processes driving the 3-D dynamic evolution of PM2.5 concentrations over the North China Plain
Institutes of Physical Science and Information Technology, Anhui
University, Hefei 230601, China
Tianshu Zhang
Key Laboratory of Environmental Optics and Technology, Anhui Institute of Optics and Fine Mechanics, Chinese Academy of Sciences, Hefei 230031, China
Institutes of Physical Science and Information Technology, Anhui
University, Hefei 230601, China
Chaoqun Ma
Minerva Research Group, Max Planck Institute for Chemistry, Mainz,
Germany
Lihui Lv
Institutes of Physical Science and Information Technology, Anhui
University, Hefei 230601, China
Jianguo Liu
Key Laboratory of Environmental Optics and Technology, Anhui Institute of Optics and Fine Mechanics, Chinese Academy of Sciences, Hefei 230031, China
Wenqing Liu
Key Laboratory of Environmental Optics and Technology, Anhui Institute of Optics and Fine Mechanics, Chinese Academy of Sciences, Hefei 230031, China
Institutes of Physical Science and Information Technology, Anhui
University, Hefei 230601, China
Minerva Research Group, Max Planck Institute for Chemistry, Mainz,
Germany
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Cited
17 citations as recorded by crossref.
- Application of data assimilation technology in source apportionment of PM2.5 during winter haze episodes in the Beijing-Tianjin-Hebei region in China T. Sun et al. 10.1016/j.apr.2022.101546
- A comprehensive review of the development of land use regression approaches for modeling spatiotemporal variations of ambient air pollution: A perspective from 2011 to 2023 X. Ma et al. 10.1016/j.envint.2024.108430
- Three-dimensional variational assimilation of Lidar extinction profiles: Application to PM2.5 prediction in north China L. Gao et al. 10.1016/j.atmosenv.2021.118828
- Needs and challenges of optical atmospheric monitoring on the background of carbon neutrality in China W. Liu & C. Xing 10.1007/s11783-024-1833-2
- Observing system simulation experiment (OSSE)-quantitative evaluation of lidar observation networks to improve 3D aerosol forecasting in China H. Ye et al. 10.1016/j.atmosres.2022.106069
- Seasonal patterns, vertical profiles, and sensitivity analysis of long-term O3 pollution observations in Hefei City, China X. Zhao et al. 10.1016/j.apr.2024.102145
- Insights into quantitative evaluation technology of PM2.5 transport at multi–perspective and multi–spatial and temporal scales in the north China plain H. Zhang et al. 10.1016/j.envpol.2023.122693
- Estimation of the vertical distribution of particle matter (PM<sub>2.5</sub>) concentration and its transport flux from lidar measurements based on machine learning algorithms Y. Ma et al. 10.5194/acp-21-17003-2021
- Practices and Empirical Insights from the National Research Program for Key Issues in Heavy Air Pollution in Beijing–Tianjin–Hebei and Surrounding Areas H. Li et al. 10.1016/j.eng.2022.08.021
- Vertical changes of PM2.5 driven by meteorology in the atmospheric boundary layer during a heavy air pollution event in central China X. Sun et al. 10.1016/j.scitotenv.2022.159830
- Vertical Changes of Pm2.5 Concentration Driven by Meteorology in the Atmospheric Boundary Layer During a Heavy Air Pollution Event in Central China X. Sun et al. 10.2139/ssrn.4135986
- Vertical profile of aerosols in the Himalayas revealed by lidar: New insights into their seasonal/diurnal patterns, sources, and transport Y. Xiang et al. 10.1016/j.envpol.2021.117686
- Investigation on the vertical distribution and transportation of PM2.5 in the Beijing-Tianjin-Hebei region based on stereoscopic observation network T. Sun et al. 10.1016/j.atmosenv.2022.119511
- Vertical profiles and regional transport of ozone in typical area of Yangtze-Huaihe River Basin during the autumn base on multiple lidars X. Wang et al. 10.1016/j.apr.2023.101983
- Downdraft influences on the differences of PM2.5 concentration: insights from a mega haze evolution in the winter of northern China Z. Chen et al. 10.1088/1748-9326/ad1229
- Vertical aerosol data assimilation technology and application based on satellite and ground lidar: A review and outlook T. Yang et al. 10.1016/j.jes.2022.04.012
- Evaluation of transport processes over North China Plain and Yangtze River Delta using MAX-DOAS observations Y. Song et al. 10.5194/acp-23-1803-2023
17 citations as recorded by crossref.
- Application of data assimilation technology in source apportionment of PM2.5 during winter haze episodes in the Beijing-Tianjin-Hebei region in China T. Sun et al. 10.1016/j.apr.2022.101546
- A comprehensive review of the development of land use regression approaches for modeling spatiotemporal variations of ambient air pollution: A perspective from 2011 to 2023 X. Ma et al. 10.1016/j.envint.2024.108430
- Three-dimensional variational assimilation of Lidar extinction profiles: Application to PM2.5 prediction in north China L. Gao et al. 10.1016/j.atmosenv.2021.118828
- Needs and challenges of optical atmospheric monitoring on the background of carbon neutrality in China W. Liu & C. Xing 10.1007/s11783-024-1833-2
- Observing system simulation experiment (OSSE)-quantitative evaluation of lidar observation networks to improve 3D aerosol forecasting in China H. Ye et al. 10.1016/j.atmosres.2022.106069
- Seasonal patterns, vertical profiles, and sensitivity analysis of long-term O3 pollution observations in Hefei City, China X. Zhao et al. 10.1016/j.apr.2024.102145
- Insights into quantitative evaluation technology of PM2.5 transport at multi–perspective and multi–spatial and temporal scales in the north China plain H. Zhang et al. 10.1016/j.envpol.2023.122693
- Estimation of the vertical distribution of particle matter (PM<sub>2.5</sub>) concentration and its transport flux from lidar measurements based on machine learning algorithms Y. Ma et al. 10.5194/acp-21-17003-2021
- Practices and Empirical Insights from the National Research Program for Key Issues in Heavy Air Pollution in Beijing–Tianjin–Hebei and Surrounding Areas H. Li et al. 10.1016/j.eng.2022.08.021
- Vertical changes of PM2.5 driven by meteorology in the atmospheric boundary layer during a heavy air pollution event in central China X. Sun et al. 10.1016/j.scitotenv.2022.159830
- Vertical Changes of Pm2.5 Concentration Driven by Meteorology in the Atmospheric Boundary Layer During a Heavy Air Pollution Event in Central China X. Sun et al. 10.2139/ssrn.4135986
- Vertical profile of aerosols in the Himalayas revealed by lidar: New insights into their seasonal/diurnal patterns, sources, and transport Y. Xiang et al. 10.1016/j.envpol.2021.117686
- Investigation on the vertical distribution and transportation of PM2.5 in the Beijing-Tianjin-Hebei region based on stereoscopic observation network T. Sun et al. 10.1016/j.atmosenv.2022.119511
- Vertical profiles and regional transport of ozone in typical area of Yangtze-Huaihe River Basin during the autumn base on multiple lidars X. Wang et al. 10.1016/j.apr.2023.101983
- Downdraft influences on the differences of PM2.5 concentration: insights from a mega haze evolution in the winter of northern China Z. Chen et al. 10.1088/1748-9326/ad1229
- Vertical aerosol data assimilation technology and application based on satellite and ground lidar: A review and outlook T. Yang et al. 10.1016/j.jes.2022.04.012
- Evaluation of transport processes over North China Plain and Yangtze River Delta using MAX-DOAS observations Y. Song et al. 10.5194/acp-23-1803-2023
Latest update: 17 Jul 2024
Short summary
For the first time, a vertical observation network consisting of 13 aerosol lidars and more than 1000 ground observation stations were combined with a data assimilation technique to reveal key processes driving the 3-D dynamic evolution of PM2.5 concentrations during extreme heavy aerosol pollution on the North China Plain.
For the first time, a vertical observation network consisting of 13 aerosol lidars and more than...
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