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The Environmental Story During the COVID-19 Lockdown: How Human Activities Affect PM2.5 Concentration in China?
Tan, Zhenyu; Li, Xinghua; Gao, Meiling; Jiang, Liangcun.
  • Tan Z; College of Urban and Environmental SciencesNorthwest University Xi'an 710127 China.
  • Li X; School of Remote Sensing and Information EngineeringWuhan University Wuhan 430079 China.
  • Gao M; School of Geology Engineering and GeomaticsChang'an University Xi'an 710054 China.
  • Jiang L; School of Remote Sensing and Information EngineeringWuhan University Wuhan 430079 China.
IEEE Geosci Remote Sens Lett ; 19: 1001005, 2022.
Article in English | MEDLINE | ID: covidwho-998651
ABSTRACT
At the end of 2019, the very first COVID-19 coronavirus infection was reported and then it spread across the world just like wildfires. From late January to March 2020, most cities and villages in China were locked down, and consequently, human activities decreased dramatically. This letter presents an "offline learning and online inference" approach to explore the variation of PM2.5 pollution during this period. In the experiments, a deep regression model was trained to establish the complex relationship between remote sensing data and in situ PM2.5 observations, and then the spatially continuous monthly PM2.5 distribution map was simulated using the Google Earth Engine platform. The results reveal that the COVID-19 lockdown truly decreased the PM2.5 pollution with certain hysteresis and the fine particle pollution begins to increase when advancing resumption of work and production gradually.
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Full text: Available Collection: International databases Database: MEDLINE Type of study: Observational study / Prognostic study Language: English Journal: IEEE Geosci Remote Sens Lett Year: 2022 Document Type: Article

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Full text: Available Collection: International databases Database: MEDLINE Type of study: Observational study / Prognostic study Language: English Journal: IEEE Geosci Remote Sens Lett Year: 2022 Document Type: Article