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10.1007/s11356-021-13980-w

http://scihub22266oqcxt.onion/10.1007/s11356-021-13980-w
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33876371!8055439!33876371
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suck abstract from ncbi


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pmid33876371      Environ+Sci+Pollut+Res+Int 2021 ; 28 (33): 45756-45764
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  • Threshold effects of COVID-19-confirmed cases on change in pollutants changes: evidence from the Chinese top ten cities #MMPMID33876371
  • Wang Q; Wang X
  • Environ Sci Pollut Res Int 2021[Sep]; 28 (33): 45756-45764 PMID33876371show ga
  • A more comprehensive understanding of the impact of the COVID-19 pandemic on changes in pollution could serve us to better deal with the environmental challenges caused by the pandemic. Existing studies mainly focused on the linear impact of the pandemic on the pollutants without considering the impact of other factors. To fill the research gap, the nonlinear relationship between pandemic and pollutants with considering the temperature factor was explored by developing panel threshold regression approach. In the proposed approach, the number of confirmed cases was set as explanatory variable, concentrations of NO(2) and PM2.5 were set as explained variables, temperature was used as threshold variable, and other air pollution indicators were used as control variables. The results showed that there is a threshold effect between the changes in confirmed COVID-19 cases and the concentrations of PM2.5 and NO(2), confirming the impact of the pandemic on pollutions was nonlinear. The results also show that the negative impact of pandemic on pollution increased when the temperature was rising. This work had theoretical and practical significance. The nonlinear research perspective of this article provided a methodological reference for exploring the relationship between epidemic and pollutant-related variables. Furthermore, this study expanded the scope of application of the threshold panel regression model and enriched the quantitative analysis of epidemics and pollutants.
  • |*Air Pollutants/analysis[MESH]
  • |*Air Pollution/analysis[MESH]
  • |*COVID-19[MESH]
  • |*Environmental Pollutants[MESH]
  • |China/epidemiology[MESH]
  • |Cities[MESH]
  • |Humans[MESH]
  • |Pandemics[MESH]
  • |Particulate Matter/analysis[MESH]


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