Reconfirmation of the symbiosis on carbon emissions and air pollution: A spatial spillover perspective

Synergistic effects of a carbon emissions trading scheme on carbon emissions and air pollution: The case of China

Facing the dual pressures of the exacerbation of global climate change and the deterioration of the domestic environment caused by pollution, China has clearly adopted environmental regulatory measures to improve the climate environment. One measure is the carbon emissions trading scheme (CETS), which serves as a notable example of the country's efforts to improve the climate environment. We gathered panel data from 285 prefecture-level cities in China from 2005 to 2018 and used the Difference-in-Differences (DID) model to empirically examine the synergistic effects of the CETS on carbon emissions and air pollution. The results indicate that CETS have been effective in reducing urban carbon emissions by approximately 9.8%. Additionally, the schemes have caused a simultaneous reduction in particulate matter (PM)2.5 emissions by 11.7% and sulfur dioxide (SO2) emissions by approximately 9.7%, mitigating urban air pollution in China. It demonstrates that the scheme has significant synergistic effects on carbon emissions and air pollution. To achieve synergistic effects of CETS, effective measures include reducing energy intensity and upgrading the industrial structure. The implementation of CETS had heterogeneity in different conditions, and the synergistic effect of the scheme is more significant in eastern regions, large cities, and the final industrial stage. Our findings offer innovative solutions for the integrated management of carbon emissions and air pollution and provide valuable insights for policymakers to enhance China's CETS. Integr Environ Assess Manag 2024;20:1112-1124. © 2023 SETAC.

Digital economy and the synergistic governance of pollutants and carbon emissions: Facilitation or obstruction?

As an emerging force enabling high-quality economic development, digital economy (DE) still requires further investigation regarding its impact on synergistic governance of pollutants and carbon emissions (SGPCE). This study examines the impact of DE on SGPCE using two-way fixed effects model, intermediary effect model, and spatial Durbin model using provincial panel data from 2011 to 2020. The research reveals that: (1) DE has a significant promoting effect on SGPCE. (2) Enhancing the degree of green technology innovation is a crucial means of transmission for DE to propel SGPCE. (3) DE additionally exerts a constructive influence on SGPCE in adjacent regions, manifesting a spatial spillover effect. (4) Furthermore, DE demonstrates a notably heightened impact on SGPCE in the western region with respect to regional heterogeneity. Additionally, in the realm of dimension heterogeneity, the industrial digitization yields more favorable dividends for SGPCE compared to digital industrialization. The above conclusions provide novel insights and empirical evidence to validate the connection between DE and SGPCE. It also gives new policy recommendations for China to combat pollution prevention and climate warming under the wave of global digitization.

Trading our way to a greener future: how environmental rights trading reduces urban carbon emissions in China-empirical analysis based on China's emission rights trading

Environmental rights trading (ERT) is considered one of the crucial instruments for environmental governance in China, accelerating urban low-carbon sustainable development. This study utilized the Chinese Emissions Trading System (ETS), which has been implemented most widely, longest, and most typical, to represent ERT and examine its contribution to urban carbon emission reduction. Through a quasi-natural experiment perspective, urban panel data were collected from 2003 to 2019, and a time-varying difference-in-differences model and moderating models were developed. The study indicates that ERT can significantly reduce carbon emissions in cities, with robust results. In addition, the carbon reduction effect of ERT varies by city region, type, and size. This phenomenon is more obvious in central and western cities and resource-based cities. Finally, a framework to strengthen the carbon reduction effect of ERT was creatively constructed. The strengthening effects of green innovation, industrial structure, and clean energy are evident. This helps provide evidence for ERT layout and extension, especially in countries with high carbon reduction needs such as China. ERT affects not only policymakers but also a greener future for every organization and individual in the city.

Spatio-temporal effects of digital inclusive finance on the synergy between CO2 and air pollution emissions in 251 Chinese cities

Achieving the synergistic reduction of CO2 and air pollution emissions (SRCAPEs) holds great significance in promoting the green transformation. However, limited research has been conducted on the spatio-temporal impact of digital inclusive finance (DIF) on the synergy between CO2 and air pollution emissions (SCAPEs). To address this gap, we comprehensively employ the linear regression model, geographically and the temporally weighted regression (GTWR) model, and the ordered probit model to empirically analyze the influence of DIF on SCAPE. Our research reveals the following: (1) The linear regression model demonstrates that, on average, DIF can achieve a weak synergistic emission reduction effect. This result remains robust after a battery of robustness tests. (2) The GTWR model reveals that the impact of DIF on both emissions exhibits evident spatio-temporal characteristics. Its emission reduction effect gradually increases, especially after 2014. (3) On the basis of the estimates from the GTWR model, we can identify four distinct synergy types driven by DIF. The number of cities with the preferred type (i.e., achieving SRCAPE) increases the most, from 59 in 2011 to 233 in 2019. (4) On the basis of the built ordered probit models, green technology innovation is an important path for DIF to achieve synergistic emission reduction. The synergistic emission reduction effect is also significantly moderated by the regional economic level and environmental regulation intensity. Our findings have policy implications for central and local governments in achieving SRCAPE and support efforts to achieve sustainable development.

Can factor substitution reduce the shadow price of air pollution embodied in international trade? A worldwide perspective

The calculation of trade-embodied air pollution (TEAP) and its economic losses can be reasonably used to assess the impact of transboundary air pollution. However, these air pollutants, which are associated with international trade, can be easily ignored due to their concealment. Based on this, the global multiregional input‒output model (MRIO) is used to quantify the volume of five air pollutants that are embodied in the trade of 20 countries from 2000 to 2016. Then, the shadow price of trade-embodied air pollution (SPTEAP) and the elasticity of factor substitution (EFS) are both calculated by applying the translog production function. Finally, impulse response analysis is used to study the dynamic impact of EFS on the SPTEAP. The main conclusions are as follows: (1) All countries experienced a mass transfer of TEAP, among which China and the USA are the developing and developed countries with the largest amount of TEAP transfers, respectively. (2) The SPTEAP and EFS vary greatly among countries, and these values are generally higher in developed countries than in developing countries. The relationship between the three EFSs can be expressed as [Formula: see text] in all countries, thus indicating that improving the technological level of a country is the best solution for reducing the TEAP in that country while incurring the lowest cost and the least difficulty. (3) Over the long run, the increase in [Formula: see text] and [Formula: see text] reduces the SPTEAP. Conversely, an increase in [Formula: see text] increases the SPTEAP. Therefore, policymakers should weigh these three factors according to the fluctuation of the SPTEAP and constantly adjust the allocation structure and ratio of these factors to maximize the benefits of transboundary air pollution governance.

Synergistic relationship and interact driving factors of pollution and carbon reduction in the Yangtze River Delta urban agglomeration, China

The urban agglomeration is the most concentrated region of economy, population, and industry. It is also the key area of carbon emissions (CE) and air pollution management. CE and air pollution have the possibility of collaborative governance due to the same root and the same source of them. To achieve the goal of sustainable development, it is important to study the coordinated relationship of CE and atmosphere pollutants in urban agglomerations. However, most researches have ignored the synergistic relationship between CE and air pollutants. Furthermore, there is limited current study on the driving factors of the synergistic relationship between air pollutants and CE. To fill these research gaps, we first explore the spatial-temporal evolvement law of CE and PM2.5 utilizing satellite remote sensing data sets. Secondly, we analyze the synergistic relationship of CE and PM2.5 in the Yangtze River Delta (YRD) urban agglomeration using the coupling coordination degree (CCD) model from 2000 to 2020. At last, we further study the influencing factors of the synergistic relationship of CE and PM2.5 based on the geo-detector model. The findings display that (1) in 2020, the total CE in the YRD urban agglomeration is 2.24 billion tons, accounting for 22.5% of China, but its growth rate has gradually dropped to 7.25%. Besides, the PM2.5 concentration shows a waving upward-downward tendency. In 2020, the range of higher PM2.5 regions significantly decreased, and air quality gradually improved. (2) The CCD of PM2.5 and CE is at the coordination level in general (CCD > 0.6) between 2000 and 2020, which can realize the coordinated governance of pollution and carbon reduction. (3) Digital elevation model (DEM), topographic relief (RDLS), and population density have a higher degree of influence on the synergistic relationship between CE and PM2.5. Besides, the interaction of topographic and socio-economic factors is the main driving factor between the two. This paper can provide a referral for decision-makers to synergistically make plans for pollution and carbon reduction and facilitate the sustainable development of urban agglomerations.

Revealing the impact of China's clean air policies on synergetic control of CO2 and air pollutant emissions: Evidence from Chinese cities

China is presently confronted with the intricate challenge of simultaneously mitigating air pollution and decelerating the pace of climate change. An integrated perspective to investigate the synergetic control of CO2 and air pollutant emissions is in an urgent need. Using data for 284 Chinese cities from 2009 to 2017, we introduced an indicator called coupling and coordination degree of CO2 and air pollutant emissions control (CCD) and found an upward and spatial agglomeration trend of CCD distribution during the research period. Then, this study posed a specific focus on the impact of China's Air Pollution Prevention and Control Action Plan (APPCAP). The DID model revealed that implementation of the APPCAP resulted in a 4.0% increase in CCD for cities with special emission limits, attributed to industrial structural adjustments and the promotion of technology innovation. Furthermore, we also identified positive spillover effects of the APPCAP on neighboring control group cities situated within 350 km of the treatment group cities, providing an explanation for the spatial agglomeration trend observed in CCD distribution. These findings hold significant implications for the synergetic control in China and underscored the potential benefits of industrial structural adjustments and technology innovation in mitigating environmental pollution.

Towards sustainable development: what carbon trading pilot policy has been done for mitigating carbon emissions and air pollution?

This study examines the impact of carbon trading pilot policy (CTPP) on carbon emissions (CO2) and air pollution (Ap) using the difference in differences method (DID) utilizing panel data from 30 Chinese areas spanning from 2008 to 2020. The results indicate that CTPP implementation can effectively decrease CO2 and Ap. CTPP can reduce CO2 and Ap through positive incentive effects that promote industrial structure upgrading and drive technological progress. Moreover, CTPP exhibits significant regional variation, with CTPP significantly reducing CO2 in both the eastern and central and western regions. CTPP do not show an effective reduction in Ap in eastern region, while effectively reduce Ap in central and western regions.