Evaluating the effects of air pollution control policies in China using a difference-in-differences approach

Haimeng Liu; Chengxin Wang; Mi Zhang; Shaobin Wang

doi:10.1016/j.scitotenv.2022.157333

Evaluating the effects of air pollution control policies in China using a difference-in-differences approach

Sci Total Environ. 2022 Nov 1:845:157333. doi: 10.1016/j.scitotenv.2022.157333. Epub 2022 Jul 13.

Authors

Haimeng Liu¹, Chengxin Wang², Mi Zhang³, Shaobin Wang⁴

Affiliations

¹ Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China; College of Resources and Environment, University of Chinese Academy of Sciences, Beijing 100049, China. Electronic address: liuhm@igsnrr.ac.cn.
² College of Geography and Environment, Shandong Normal University, Jinan 250358, China. Electronic address: 404122665@qq.com.
³ School of International Trade and Economics, Central University of Finance and Economics, Beijing 100098, China.
⁴ Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China; College of Resources and Environment, University of Chinese Academy of Sciences, Beijing 100049, China.

PMID: 35842143
DOI: 10.1016/j.scitotenv.2022.157333

Abstract

Air pollution has caused wide concern in China, and many governance policies and plans have been implemented in recent years. Based on counterfactual quasi-natural experiments, we analyzed the implementation effects of autumn and winter air pollution control policies in the Jing-Jin-Ji region and surrounding areas using a difference-in-differences (DID) model. The control group was selected based on geographical and meteorological factors, and we analyzed the impact of the policies on six pollutants. The results show that the policies reduced air pollution overall, but not every pollutant. Due to the policy contribution, the concentrations of PM_2.5 and PM₁₀ in autumn and winter from 2017 to 2018 decreased by 6.9 % and 8.5 %, respectively. The numerical value of PM_2.5, PM₁₀, CO, and AQI in 2018-2019 decreased by 18.2 %, 7.2 %, 13.9 %, and 8.8 %, respectively. The role in the reduction of O₃, SO₂, and NO₂ was not obvious. This work provides a research paradigm for evaluating the effects of atmospheric environment policy which can be applied to other studies and provide references for formulating additional policies.

Keywords: Air quality; DID model; Environmental governance; Environmental policy; PM(2.5); Policy evaluation.

MeSH terms

Air Pollutants* / analysis
Air Pollution* / analysis
Air Pollution* / prevention & control
China
Environmental Monitoring / methods
Particulate Matter / analysis
Policy

Substances

Air Pollutants
Particulate Matter