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Here, the remote-sensing observations, Modern-Era Retrospective analysis for Research and Applications, Version 2 (MERRA-2) products, backward-trajectory, and potential-source-contribution models are used to assess the impact of AOPs, vertical distribution, and possible sources on the atmosphere environment in North China Plain (NCP), Central China (CC), Yangtze River Delta (YRD), Pearl River Delta (PRD), and Sichuan Basin (SB) during the CLD period. The results demonstrate that both AOD (MODIS) and near-surface AEC (CALIPSO, &lt;2 km) decreased in most areas of China. Compared with previous years (average 2017\u20132019), the AOD (AEC) of NCP, CC, YRD, PRD, and SB reduced by 3.33% (10.76%), 14.36% (32.48%), 10.80% (29.64%), 31.44% (22.68%), and 15.50% (8.44%), respectively. In addition, MODIS (AODc) and MERRA-2 (AODc) decreased in the five study areas compared with previous years, so the reduction in dust activities also contributed to improving regional air quality during the epidemic. Despite the reduction of anthropogenic emissions (AODf) in most areas of China during the CLD periods, severe haze events (AODf &gt; 0.6) still occurred in some areas. Compared to previous years, there were increases in BC, OC (MERRA-2), and national raw coal consumption during CLD. Therefore, emissions from some key sectors (raw coal heating, thermal power generation, and residential coal) did not decrease, and this may have increased AODf during the CLD. Based on backward -rajectory and potential source contribution models, the study area was mainly influenced by local anthropogenic emissions, but some areas were also influenced by northwestern dust, Southeast Asian biomass burning, and marine aerosol transport. This paper underscores the importance of emissions from the residential sector and thermal power plants for atmospheric pollution in China and suggests that these sources must be taken into account in developing pollution-mitigation plans.<\/jats:p>","DOI":"10.3390\/rs14143336","type":"journal-article","created":{"date-parts":[[2022,7,12]],"date-time":"2022-07-12T03:50:36Z","timestamp":1657597836000},"page":"3336","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":8,"title":["Aerosol Characteristics during the COVID-19 Lockdown in China: Optical Properties, Vertical Distribution, and Potential Source"],"prefix":"10.3390","volume":"14","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-7602-360X","authenticated-orcid":false,"given":"Yinbao","family":"Jin","sequence":"first","affiliation":[{"name":"School of Atmospheric Sciences, Sun Yat-sen University, Zhuhai 519082, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Yingying","family":"Ma","sequence":"additional","affiliation":[{"name":"State Key Laboratory of Information Engineering in Surveying, Mapping and Remote-Sensing, Wuhan University, Wuhan 430079, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-8709-055X","authenticated-orcid":false,"given":"Ming","family":"Zhang","sequence":"additional","affiliation":[{"name":"Hubei Key Laboratory of Critical Zone Evolution, School of Geography and Information Engineering, China University of Geosciences, Wuhan 430074, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Yiming","family":"Liu","sequence":"additional","affiliation":[{"name":"School of Atmospheric Sciences, Sun Yat-sen University, Zhuhai 519082, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-5989-0912","authenticated-orcid":false,"given":"Xiao","family":"Lu","sequence":"additional","affiliation":[{"name":"School of Atmospheric Sciences, Sun Yat-sen University, Zhuhai 519082, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Boming","family":"Liu","sequence":"additional","affiliation":[{"name":"State Key Laboratory of Information Engineering in Surveying, Mapping and Remote-Sensing, Wuhan University, Wuhan 430079, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-0938-4202","authenticated-orcid":false,"given":"Shikuan","family":"Jin","sequence":"additional","affiliation":[{"name":"State Key Laboratory of Information Engineering in Surveying, Mapping and Remote-Sensing, Wuhan University, Wuhan 430079, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-7339-6654","authenticated-orcid":false,"given":"Ao","family":"Shen","sequence":"additional","affiliation":[{"name":"School of Atmospheric Sciences, Sun Yat-sen University, Zhuhai 519082, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Juan","family":"Zhang","sequence":"additional","affiliation":[{"name":"School of Atmospheric Sciences, Sun Yat-sen University, Zhuhai 519082, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Qi","family":"Fan","sequence":"additional","affiliation":[{"name":"School of Atmospheric Sciences, Sun Yat-sen University, Zhuhai 519082, China"},{"name":"Southern Marine Science and Engineering Guangdong Laboratory, Zhuhai 519082, China"},{"name":"Guangdong Province Key Laboratory for Climate Change and Natural Disaster Studies, School of Atmospheric Sciences, Sun Yat-sen University, Guangzhou 510275, China"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1968","published-online":{"date-parts":[[2022,7,11]]},"reference":[{"key":"ref_1","unstructured":"World Health Organization (2020). 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