Nonlinear effects of environmental regulation on PM2.5 and CO2 in China: Evidence from a quantile-on-quantile approach

Mengyang Hou, Xuehua Cui, Liqi Chu, He Wang, Zenglei Xi and Yuanjie Deng

Energy, 2024, vol. 292, issue C

Abstract: Both environmental regulation (ER) and different pollutants emission are characterized by differentiation, but the nonlinear relationship between different intensities of ER and different levels of pollutants emission has not yet been elaborated. This paper examines the nonlinear effects of ER at different intensities on PM2.5 and CO2 at different states with the help of cutting-edge Quantile on Quantile Approach (QQA), comprehensively reveals the inner law of ER to promote pollutants synergistic reduction. This study found that, both PM2.5 and CO2 show obvious regional differences but are not polarized. ER can effectively help reduce PM2.5 and CO2 in average, and this reduction effect is more obvious for central-western cities. The effects of different intensities of ER on different states of PM2.5 and CO2 have obvious nonlinear spillover characteristics. The impact of ER on PM2.5 shows wave-like changes. Increasing ER intensity has a stronger inhibitory effect on PM2.5 of high scale, but when PM2.5 is relatively low, moderate ER is needed to match it, and excessive intensity of ER will be detrimental to reduce PM2.5. The negative impact of ER on CO2 fluctuates relatively stable. ER at high quantiles have more obvious reduction effect on CO2 of high levels, but excessive intensity of ER is not conducive to reduce CO2. Achieve the synergistic reduction of PM2.5 and CO2 should not only consider the differences in ER between regions, but also to combine the scale differences of pollution and carbon emission. Our study suggests that the improvement of synergistic emission reduction system needs to consider the strength of ER and the level of pollutants emission according to local conditions, which will help to realize green development more efficiently.

Keywords: Environmental regulation; PM2.5; CO2; Quantile on quantile approach (QQA); Nonlinear effects (search for similar items in EconPapers)
Date: 2024
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Citations: View citations in EconPapers (1)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:energy:v:292:y:2024:i:c:s0360544224002275

DOI: 10.1016/j.energy.2024.130456

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