Assessment of the co-benefits of China's carbon trading policy on carbon emissions reduction and air pollution control in multiple sectors

Xian, Botong; Wang, Yanan; Xu, Yalin; Wang, Juan; Li, Xiaoyan

doi:10.1016/j.eap.2024.01.011

Cited by 15 publications

(3 citation statements)

References 51 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The results show that the coefficient of the core explanatory variable DID is negative with or without control variables and passes the significance test at the 1% level. The absolute value of the correlation coefficients between the variables in general is less than 0.5, ruling out the problem of multicollinearity, and the result is in agreement with Li, Xian (K. Li et al, 2024;Xian et al, 2024) et al However, some researchers have pointed out that the emission reduction effect of carbon trading policy is not significant, which may be caused by the sample differences between sub-sectors and regions (X. Feng et al, 2024b;G.…”

Section: Benchmark Regression Analysissupporting

confidence: 80%

“…The marginal contributions of this paper are as follows: 1) Scholars mainly focus on the policy pilot regions, and pay less attention to the real policy intensity and governance effects on the first pilot enterprises (J. Hou et al, 2024;Xian et al, 2024). This paper takes the enterprise perspective as the starting point, providing reference basis for the carbon emission reduction of enterprises and the technological transformation of neighboring enterprises, further promoting the decarbonization and greening of industries, and allowing more enterprises to participate in the practice of realizing the "dual-carbon" strategic goal.…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Study on the effect of carbon trading on the carbon emission intensity of enterprises—a mechanism test based on ESG performance

Han,

Yu,

et al. 2024

Front. Environ. Sci.

View full text Add to dashboard Cite

Facing the double constraints of the “double carbon” target and high-quality economic development, carbon trading policy is an important tool for realizing the emission reduction commitment; based on the perspective of microenterprises, the specific mechanism and spatial effect of carbon trading policy still need to be evaluated. Taking China’s carbon emissions trading pilot as a quasi-natural experiment, this paper empirically investigates the impact of carbon trading policy on the carbon emission intensity of pilot enterprises and its mechanism of action, and its impact on the carbon emission intensity of neighboring enterprises, based on the multi-temporal double-difference model, moderating effect model, and spatial Durbin model with the A-share-listed enterprises in the period of 2009–2019 as the samples. It is found that: 1) Carbon trading policy will reduce the carbon emission intensity of enterprises to different degrees, and there are significant differences under different ownership types, degrees of marketization and the level of digitization. 2) Under the influence of environmental uncertainty, ESG disclosure will weaken the effectiveness of carbon emission reduction in the pre-pilot stage of the policy; with the gradual improvement of the carbon trading policy and ESG disclosure mechanism, ESG ratings will positively regulate the inhibitory effect of the carbon trading policy on the carbon emission intensity of enterprises through multiple paths. 3) Carbon trading policy effectively reduces multiple negative spillovers through the demonstration effect and competition effect of neighboring enterprises, driving the carbon emission reduction behavior of non-pilot enterprise. The research in this paper enriches the research paradigm of carbon emission intensity influencing factors, provides reference suggestions for the government to improve its policies, and better contributes to the realization of the “dual-carbon” vision in China as soon as possible.

show abstract

Section: Benchmark Regression Analysissupporting

confidence: 80%

Section: Introductionmentioning

confidence: 99%

Study on the effect of carbon trading on the carbon emission intensity of enterprises—a mechanism test based on ESG performance

Han,

Yu,

et al. 2024

Front. Environ. Sci.

View full text Add to dashboard Cite

show abstract

“…For instance, Xian et al (2019) evaluated the synergistic effect and mechanism of the carbon trading pilot policy on carbon and air pollutant emissions in China using the double difference model (DID). This study covered the power, industry, transportation, and residential sectors [17]. Zhu et al (2020) analyzed the factors influencing hidden carbon emissions in China's construction industry using the extended STIRPAT mode [18].…”

Section: Introductionmentioning

confidence: 99%

Impact Factors of Industrial Pollution and Carbon Reduction under the “Dual Carbon” Target: A Case Study of Urban Aggregation in the Pearl River Delta and Yangtze River Delta

Wen,

Wang,

et al. 2024

Sustainability

View full text Add to dashboard Cite

China is facing pressure to reduce carbon emissions and control pollution. Promoting the synergy between pollution reduction and carbon reduction has become an inevitable choice to achieve the construction of a beautiful China and meet the dual carbon target. This study examines the main factors influencing industrial pollution and carbon reduction in the Pearl River Delta (PRD) and Yangtze River Delta (YRD) urban agglomerations based on data on industrial CO2 and local air pollutants (LAP) from 2002 to 2021, using the random forest regression model. The results indicate that (1) industrial CO2 emissions have increased overall, while intensity has decreased. Additionally, both industrial LAP emissions and intensity have decreased. (2) The main factor influencing industrial CO2 and LAP emissions is the proportion of industrial value added above the scale. Additionally, the proportion of R&D internal expenditure in GDP and total trade imports and exports are the main influencing factors of industrial CO2 emissions. The industrial fume and dust removal rate mainly affects industrial LAP emissions. (3) There is a clear non-linear relationship between industrial CO2- and LAP-influencing factors and emissions, which can be attributed to the scale effect factor, the lagging effect of R&D expenditure, and the inappropriate treatment of the “three wastes” by relevant departments that is non-linear. The urban agglomerations of PRD and YRD should prioritize the reduction of carbon emissions, upgrading and transforming their industrial structures, promoting the impact of foreign trade on pollution and carbon reduction, and achieving a balance between sustainable economic development and environmental protection.

show abstract

Digital technology innovation and synergy of pollution control and carbon reduction: empirical evidence from digital patents in Chinese cities

Feng,

Li,

Nie

2024

Econ Change Restruct

View full text Add to dashboard Cite

Assessment of the co-benefits of China's carbon trading policy on carbon emissions reduction and air pollution control in multiple sectors

Cited by 15 publications

References 51 publications

Study on the effect of carbon trading on the carbon emission intensity of enterprises—a mechanism test based on ESG performance

Study on the effect of carbon trading on the carbon emission intensity of enterprises—a mechanism test based on ESG performance

Impact Factors of Industrial Pollution and Carbon Reduction under the “Dual Carbon” Target: A Case Study of Urban Aggregation in the Pearl River Delta and Yangtze River Delta

Digital technology innovation and synergy of pollution control and carbon reduction: empirical evidence from digital patents in Chinese cities

Contact Info

Product

Resources

About