Could Air Quality Get Better during Epidemic Prevention and Control in China? An Analysis Based on Regression Discontinuity Design
Though many scholars and practitioners are paying more attention to the health and life of the public after the COVID-19 outbreak, extant literature has so far failed to explore the variation of ambient air quality during this pandemic. The current study attempts to fill the gap by disentangling the...
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| Format: | Article |
| Language: | English |
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MDPI AG
2021-04-01
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| Series: | Land |
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| Online Access: | https://www.mdpi.com/2073-445X/10/4/373 |
| _version_ | 1797538822762790912 |
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| author | Xinghua Zhao Zheng Cheng Chen Jiang |
| author_facet | Xinghua Zhao Zheng Cheng Chen Jiang |
| author_sort | Xinghua Zhao |
| collection | DOAJ |
| description | Though many scholars and practitioners are paying more attention to the health and life of the public after the COVID-19 outbreak, extant literature has so far failed to explore the variation of ambient air quality during this pandemic. The current study attempts to fill the gap by disentangling the causal effects of epidemic prevention on air quality in China, measured by the individual pollutant dimensionless index, from other confounding factors. Using the fixed effects model, this article finds that five air indicators, PM<sub>2.5</sub>, PM<sub>10</sub>, CO, NO<sub>2</sub>, and SO<sub>2</sub>, significantly improved during the shutdown period, with NO<sub>2</sub> showing the most improvement. On the contrary, O<sub>3</sub> shows an inverse pattern, that is, O<sub>3</sub> gets worse unexpectedly. The positive impact of epidemic prevention on air quality, especially in terms of PM<sub>2.5</sub>, PM<sub>10</sub>, and NO<sub>2</sub>, become manifest five days after the resumption of labor, indicated by the result of a regression discontinuity design. These findings are still robust and consistent after the dataset of 2019 as a counterfactual sample is utilized. The findings of this paper make contributions to both environmental governance and pandemic prevention, with relevant guidelines regarding the health and life of the public and governmental behavioral management strategies discussed. |
| first_indexed | 2024-03-10T12:36:53Z |
| format | Article |
| id | doaj.art-9704c3574e5f4ebdbbacdf549ec70ffb |
| institution | Directory Open Access Journal |
| issn | 2073-445X |
| language | English |
| last_indexed | 2024-03-10T12:36:53Z |
| publishDate | 2021-04-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Land |
| spelling | doaj.art-9704c3574e5f4ebdbbacdf549ec70ffb2023-11-21T14:11:15ZengMDPI AGLand2073-445X2021-04-0110437310.3390/land10040373Could Air Quality Get Better during Epidemic Prevention and Control in China? An Analysis Based on Regression Discontinuity DesignXinghua Zhao0Zheng Cheng1Chen Jiang2School of Political Science and Public Administration, Shandong University, Qingdao 266237, ChinaSchool of Political Science and Public Administration, Shandong University, Qingdao 266237, ChinaSchool of Political Science and Public Administration, Shandong University, Qingdao 266237, ChinaThough many scholars and practitioners are paying more attention to the health and life of the public after the COVID-19 outbreak, extant literature has so far failed to explore the variation of ambient air quality during this pandemic. The current study attempts to fill the gap by disentangling the causal effects of epidemic prevention on air quality in China, measured by the individual pollutant dimensionless index, from other confounding factors. Using the fixed effects model, this article finds that five air indicators, PM<sub>2.5</sub>, PM<sub>10</sub>, CO, NO<sub>2</sub>, and SO<sub>2</sub>, significantly improved during the shutdown period, with NO<sub>2</sub> showing the most improvement. On the contrary, O<sub>3</sub> shows an inverse pattern, that is, O<sub>3</sub> gets worse unexpectedly. The positive impact of epidemic prevention on air quality, especially in terms of PM<sub>2.5</sub>, PM<sub>10</sub>, and NO<sub>2</sub>, become manifest five days after the resumption of labor, indicated by the result of a regression discontinuity design. These findings are still robust and consistent after the dataset of 2019 as a counterfactual sample is utilized. The findings of this paper make contributions to both environmental governance and pandemic prevention, with relevant guidelines regarding the health and life of the public and governmental behavioral management strategies discussed.https://www.mdpi.com/2073-445X/10/4/373air qualityshutdown periodfixed effects modelregression discontinuity design |
| spellingShingle | Xinghua Zhao Zheng Cheng Chen Jiang Could Air Quality Get Better during Epidemic Prevention and Control in China? An Analysis Based on Regression Discontinuity Design Land air quality shutdown period fixed effects model regression discontinuity design |
| title | Could Air Quality Get Better during Epidemic Prevention and Control in China? An Analysis Based on Regression Discontinuity Design |
| title_full | Could Air Quality Get Better during Epidemic Prevention and Control in China? An Analysis Based on Regression Discontinuity Design |
| title_fullStr | Could Air Quality Get Better during Epidemic Prevention and Control in China? An Analysis Based on Regression Discontinuity Design |
| title_full_unstemmed | Could Air Quality Get Better during Epidemic Prevention and Control in China? An Analysis Based on Regression Discontinuity Design |
| title_short | Could Air Quality Get Better during Epidemic Prevention and Control in China? An Analysis Based on Regression Discontinuity Design |
| title_sort | could air quality get better during epidemic prevention and control in china an analysis based on regression discontinuity design |
| topic | air quality shutdown period fixed effects model regression discontinuity design |
| url | https://www.mdpi.com/2073-445X/10/4/373 |
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