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. 2022 Jul 22;19(15):8932.
doi: 10.3390/ijerph19158932.

Can China's Carbon Emissions Trading System Achieve the Synergistic Effect of Carbon Reduction and Pollution Control?

Li Chen  1   2 , Di Wang  1   3 , Ruyi Shi  4   5
Affiliations

Can China's Carbon Emissions Trading System Achieve the Synergistic Effect of Carbon Reduction and Pollution Control?

Li Chen et al. Int J Environ Res Public Health. .

Abstract

Achieving synergistic governance of air pollution treatment and greenhouse gas emission reduction is the way for the Chinese government to achieve green transformational development. Against this background, this paper takes the implementation of the carbon emissions trading system (ETS) as the breakthrough point, using the time-varying difference-in-differences (DID) model to explore the synergistic emission reduction effect of ETS on air pollution and carbon emissions and its mechanism. The results indicate that the implementation of ETS not only significantly reduces CO2 emissions but also synergistically achieves the reduction of air pollutants, and the synergistic emission reduction effect is mainly achieved through the synergistic reduction of SO2. Moreover, the emission reduction effect of ETS has economic and regional heterogeneity. On the one hand, the ETS has a more prominent carbon reduction effect in less developed provinces and cities and has a significant synergistic emission reduction effect on SO2 and PM2.5; on the other hand, the carbon emission reduction effect of ETS is more potent in Beijing, Hubei, and Shanghai, followed by Tianjin and Chongqing, and the weakest in Guangdong. In addition, through the analysis of the mediating effect, this paper finds that reducing energy consumption, optimizing the energy structure, and improving energy efficiency are effective ways for ETS to achieve synergistic emission reduction. This study provides valuable policy enlightenment for promoting the synergistic governance of pollution and carbon reduction.

Keywords: air pollution; carbon emissions trading system; synergistic emission reduction; time-varying difference-in-differences model.

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Conflict of interest statement

The authors declare no conflict of interest.

Figures

Figure 1
Figure 1
Synergistic emission reduction mechanism of ETS.
Figure 2
Figure 2
The difference in CO2 emissions before and after the implementation of ETS.
Figure 3
Figure 3
The difference in SO2 emissions before and after the implementation of ETS.
Figure 4
Figure 4
The difference in PM2.5 emissions before and after the implementation of ETS; Note: The small circle in the above figures represents the estimated coefficient βk obtained from Equation (2), and the dotted line is the 95% upper and lower confidence interval of βk. “pre” is before the policy, and “current” is the current period, and “post” is after the policy is implemented. (The same below).
Figure 5
Figure 5
Subfigures (a–c) are the empirical cumulative distribution of placebo trial coefficients of CO2, SO2, and PM2.5, respectively. The solid line is the probability density distribution of the DID coefficients corresponding to the placebo test, the dashed line is the normal distribution, and the vertical dashed line indicates the estimated DID coefficients in columns (2) (4) (6) of Table 3.
See this image and copyright information in PMC

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