Assessments of Air Pollution Control Effectiveness Based on a Sharp Regression Discontinuity Design —Evidence From China’s Environmental Big Data
The Assessment andAppraisal Method for Ecological Construction Targets (the Method) was promulgated in 2016, which provided a concrete instruction for China’s air pollution control and established an explicit standard for reducing air pollutant concentration. This study implements a sharp regression...
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Frontiers Media S.A.
2021-09-01
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| Series: | Frontiers in Environmental Science |
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| Online Access: | https://www.frontiersin.org/articles/10.3389/fenvs.2021.724716/full |
| _version_ | 1818664266531602432 |
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| author | Ren Wang Jiaqi Huang Lizhi Zhang Yu Xia Xu Xu Tongli Nong |
| author_facet | Ren Wang Jiaqi Huang Lizhi Zhang Yu Xia Xu Xu Tongli Nong |
| author_sort | Ren Wang |
| collection | DOAJ |
| description | The Assessment andAppraisal Method for Ecological Construction Targets (the Method) was promulgated in 2016, which provided a concrete instruction for China’s air pollution control and established an explicit standard for reducing air pollutant concentration. This study implements a sharp regression discontinuity (RD) design and makes an assessment on air quality control effectiveness of the Method based on the high-volume big data acquired from 173 cities in China. The results show that the Method has significantly improved air pollution control on the overall air quality index (AQI) and reducing concentrations of PM2.5, PM10, SO2, NO2, and CO across the country in the observation periods. However, no reduction effect was observed for O3. The robustness tests support the conclusion as well. Besides, the heterogeneity analysis illustrates that the policy had a significant short-term treatment effect in East, South, Central, North, Northwest, Southwest, and Northeast China. However, the Method’s effect is found to decline over time either nationwide or regionally according to the persistence analysis. Therefore, this article puts forward several suggestions regarding the formulation of long-term regulations for air pollution control, the transformation of the growth model for sustainable development, and optimization of the incentive system for improved pollution control and prevention. |
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| id | doaj.art-385f505bcd1f4e37b0cf5ebb0a55465c |
| institution | Directory Open Access Journal |
| issn | 2296-665X |
| language | English |
| last_indexed | 2024-12-17T05:30:01Z |
| publishDate | 2021-09-01 |
| publisher | Frontiers Media S.A. |
| record_format | Article |
| series | Frontiers in Environmental Science |
| spelling | doaj.art-385f505bcd1f4e37b0cf5ebb0a55465c2022-12-21T22:01:45ZengFrontiers Media S.A.Frontiers in Environmental Science2296-665X2021-09-01910.3389/fenvs.2021.724716724716Assessments of Air Pollution Control Effectiveness Based on a Sharp Regression Discontinuity Design —Evidence From China’s Environmental Big DataRen Wang0Jiaqi Huang1Lizhi Zhang2Yu Xia3Xu Xu4Tongli Nong5School of Finance, Hunan University of Technology and Business, Changsha, ChinaSchool of Mathematics and Statistics, Hunan University of Technology and Business, Changsha, ChinaSchool of Finance, Hunan University of Technology and Business, Changsha, ChinaSchool of Finance, Hunan University of Technology and Business, Changsha, ChinaSchool of Economics, Beijing Technology and Business University, Beijing, ChinaSchool of Finance, Hunan University of Technology and Business, Changsha, ChinaThe Assessment andAppraisal Method for Ecological Construction Targets (the Method) was promulgated in 2016, which provided a concrete instruction for China’s air pollution control and established an explicit standard for reducing air pollutant concentration. This study implements a sharp regression discontinuity (RD) design and makes an assessment on air quality control effectiveness of the Method based on the high-volume big data acquired from 173 cities in China. The results show that the Method has significantly improved air pollution control on the overall air quality index (AQI) and reducing concentrations of PM2.5, PM10, SO2, NO2, and CO across the country in the observation periods. However, no reduction effect was observed for O3. The robustness tests support the conclusion as well. Besides, the heterogeneity analysis illustrates that the policy had a significant short-term treatment effect in East, South, Central, North, Northwest, Southwest, and Northeast China. However, the Method’s effect is found to decline over time either nationwide or regionally according to the persistence analysis. Therefore, this article puts forward several suggestions regarding the formulation of long-term regulations for air pollution control, the transformation of the growth model for sustainable development, and optimization of the incentive system for improved pollution control and prevention.https://www.frontiersin.org/articles/10.3389/fenvs.2021.724716/fullpolicy assessmentsbig dataair qualitypollutant concentrationsharp regression discontinuity design |
| spellingShingle | Ren Wang Jiaqi Huang Lizhi Zhang Yu Xia Xu Xu Tongli Nong Assessments of Air Pollution Control Effectiveness Based on a Sharp Regression Discontinuity Design —Evidence From China’s Environmental Big Data Frontiers in Environmental Science policy assessments big data air quality pollutant concentration sharp regression discontinuity design |
| title | Assessments of Air Pollution Control Effectiveness Based on a Sharp Regression Discontinuity Design —Evidence From China’s Environmental Big Data |
| title_full | Assessments of Air Pollution Control Effectiveness Based on a Sharp Regression Discontinuity Design —Evidence From China’s Environmental Big Data |
| title_fullStr | Assessments of Air Pollution Control Effectiveness Based on a Sharp Regression Discontinuity Design —Evidence From China’s Environmental Big Data |
| title_full_unstemmed | Assessments of Air Pollution Control Effectiveness Based on a Sharp Regression Discontinuity Design —Evidence From China’s Environmental Big Data |
| title_short | Assessments of Air Pollution Control Effectiveness Based on a Sharp Regression Discontinuity Design —Evidence From China’s Environmental Big Data |
| title_sort | assessments of air pollution control effectiveness based on a sharp regression discontinuity design evidence from china s environmental big data |
| topic | policy assessments big data air quality pollutant concentration sharp regression discontinuity design |
| url | https://www.frontiersin.org/articles/10.3389/fenvs.2021.724716/full |
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