Analysis of the impact of extreme weather on the synergistic efficiency of carbon and pollution reduction in China

Impact of green finance on China's pollution reduction and carbon efficiency: Based on the spatial panel model

Carbon and pollution reduction are highly synergistic elements of green development, and the detailed derivation of the synergistic relationship is urgently needed. Based on the research perspective of coupling coordination, this paper firstly bases on the research perspective of coupling synergy, takes 30 provinces in China as the research object from 2011 to 2022, and constructs a coupling coordination degree model to measure the synergistic effect of pollution reduction and carbon reduction; secondly, kernel density and Dagum coefficient are used to analyze the spatial and temporal characteristics, spatial differences and sources of differences in the synergistic effects of pollution reduction and carbon reduction in China as a whole, in the three major regions and in each province; finally, the Moran index is applied to test the spatial agglomeration characteristics of the synergistic effect of pollution reduction and carbon reduction, and the spatial panel model is applied to test its β-convergence. The study shows that (1) during the study period, the level of synergistic effect on carbon reduction in China changed from good coordination to good coordination, and the synergistic effect in the western region was significantly better than that in the eastern and central regions; (2) the synergistic effect of pollution reduction and carbon reduction in China as a whole and the three regions showed obvious spatial differences, but the differences were gradually narrowing, and the supervariable density was the dominant factor of the overall differences; (3) as a whole, the synergistic effect of pollution reduction and carbon reduction among provinces has a spatial agglomeration effect, and the level of synergistic effect of pollution reduction and carbon reduction across the country and east and west regions has a significant absolute β convergence trend, while there is a significant conditional β convergence trend across the country and the three major regions, and the eastern and central regions with a low synergy level have a higher convergence rate, indicating that as time goes by, under the influence of various factors, the synergistic effect will converge to the steady state level. The purpose of this paper is to analyze the spatial patterns and regional differences in the synergistic effects of pollution reduction and carbon reduction in Chinese provinces and also to provide a quantitative basis for the full implementation of the synergistic regulation of pollution reduction and carbon reduction.

This paper is based on the construction of the evaluation system of urban pollution reduction and carbon reduction synergistic governance efficiency indicators. Firstly, we used the NDDF model to measure the efficiency of urban pollution reduction and carbon reduction synergistic governance. We then used the ArcGIS technology and spatial autocorrelation method to explore its spatial distribution pattern, and the spatial econometric model is used to explore its driving factors. The results show that from 2006 to 2020, the synergistic governance efficiency of Chinese cities in terms of pollution reduction and carbon reduction is in a state of continuous improvement, with an increase of 38.07 per cent in 2020 compared with 2006, and overall the synergistic governance efficiency of cities in terms of pollution reduction and carbon reduction shows a pattern of development in which the east is high and the west is low, but there is a tendency for the gap to narrow from one year to the next. There is a positive spatial aggregation of urban pollution reduction and carbon synergistic governance efficiency, which is further shown by the Lisa aggregation diagram that the spatial aggregation of urban pollution reduction and carbon synergistic governance efficiency in China is characterized by urban agglomerations, with the high and high aggregation zones being concentrated in the central and eastern urban agglomerations, such as the urban agglomerations of the middle reaches of the Yangtze River and Guangdong-Fujian-Zhejiang, and the low and low aggregation zones being concentrated in the western urban agglomerations, such as the Lanzhou-Western urban agglomerations and the Guanzhong Plain urban agglomerations. The results of the SDM model indicate that the efficiency of urban pollution reduction and carbon synergistic governance can significantly promote the process of pollution reduction and carbon synergistic governance in neighboring areas. The six drivers, namely, industrial structure, economic development level, innovation level, urbanization rate, population size and foreign direct investment, all have a significant impact on the efficiency of urban pollution reduction and carbon synergistic governance in a local area. The spatial spillover effects of the remaining variables, except for urbanization rate, on the efficiency of urban pollution reduction and carbon synergistic governance are significantly negative. Based on this, corresponding countermeasures are proposed to improve the synergistic governance of urban pollution reduction and carbon reduction.

The impact of digital industrialization on regional pollution control and carbon reduction in China is an area that remains largely unexplored despite being a new driving force in promoting high-quality economic development. This study constructs a combined system synergy model to measure the synergistic governance effect of regional pollution and carbon reduction in China from 2011 to 2020 and then estimatesthe direct impact and spatial spillover effect using a spatial dual-weight model. Our findings indicate that digital industrialization has a greater impact on regional pollution reduction and carbon reduction as geographical distance decreases, with the spillover effect with close geographical relationships being higher than that of adjacent. Furthermore, the heterogeneity analysis reveals that the added value of digital technology and services has a significantly positive effect, while the spatial spillover effect of the added value of digital infrastructure is significantly negative. Finally, our mechanism judgements prove digital industrialization canimpact the level of regional co-governance of pollution and carbon reduction through source prevention, process control, and end-treatment. Our study provides a factual basis for further promoting China's environmental pollution control and carbon reduction behavior and offers a method to use different spatial weights in depth.

Synergetic benefits of pollution and carbon reduction from fly ash resource utilization—Based on the life cycle perspective

The industrial sector is a major source of CO2 and atmospheric pollutants in China, and it is important to promote industrial pollution reduction and carbon reduction to improve the quality of China’s atmospheric environment and meet CO2 peak targets. In this paper, based on 2005 to 2021’s panel data from the industrial sector, we construct a computational model of the synergistic effect of pollution reduction and carbon reduction, quantitatively evaluate the synergistic effect of industrial CO2 emissions and air pollutants, and explore its evolutionary mechanism. The results showed that between 2005 and 2021, there was a clear synergistic effect between CO2 and air pollutants in China’s industrial sector, and the synergistic effect is increasing. For different pollutants, CO2 and SO2 have the strongest synergies, and CO2 and particulate matter have relatively weak synergies. For different energy types, the synergies between coal-related carbon emissions and air pollutants gradually increase, while gas-related carbon emissions and pollutants tend to decrease. From different industry types, the synergies between CO2 and air pollutants are weaker in high-polluting and high-emission industries than in other industries. These results have strong policy implications. First, the focus of synergistic measures should be on source reduction. The second is to make high-polluting and high-emission industries the focus of pollution reduction and carbon reduction. Third is harmonized management of air quality standards and carbon peaking should be promoted. The formulation of relevant policies from the above three aspects will help synergize pollution reduction and carbon reduction in the industrial sector.

The synergistic effect of pollution and carbon reduction can alleviate the dual pressure of improving environmental quality and reducing greenhouse gas emissions in China. The carbon emission trading scheme (CETS) is a crucial market-based tool for carbon emission reduction, and understanding its synergistic impact on air pollution control is essential. Based on data from 30 provincial panels in China spanning from 2007 to 2021, we employ the difference-in-differences (DID) method to analyze the synergistic effects of the carbon emission trading plan in the power industry and its influence mechanisms are examined. We observe that the CETS significantly enhances both pollution and carbon reduction in China’s power sector, particularly demonstrating effective synergy in reducing CO2, SO2, and PM2.5 emissions. Furthermore, mechanism analysis reveals that the CETS achieves joint emission reductions by lowering energy consumption, influencing the power industry’s generation structure, promoting technological innovation among enterprises, and thereby realizing synergistic pollution and carbon reduction effects in China’s power sector. Heterogeneity analysis shows that regions with limited power facility, low electricity generation, and small economic scale exhibit the most pronounced synergistic benefits from pollution and carbon reduction efforts.

Based on the use of the coupling coordination model to calculate the coupling coordination degree of carbon emission and pollutant control, the national, regional, and provincial spatiotemporal characteristics of the synergistic effect of pollution control and carbon emissions reduction in China were further analyzed, facilitating the crucial to identification of key areas. The fixed effects regression models and provincial panel data from 2006 to 2020 were used to explore factors contributing to better synergizing the reduction of pollution and carbon emissions in China. On this basis, the adjustment variable of R&D investment intensity was introduced, and the regulation effect model was constructed to further explore the influence mechanism of the synergistic effect of pollution reduction and carbon reduction. The results showed that： synergy exists between carbon emission reduction and the air pollution control system, the evolution of the synergistic effect of pollution reduction and carbon reduction in China presented an inverted "U"-shaped trend from 2006 to 2020, and there was spatial aggregation and a spatial spillover effect in pollution reduction and carbon reduction. The synergistic governance of carbon emission and pollutant control was still at a relatively low level. The carbon emission and air pollutant emission systems were still in an unstable and uncoordinated state. The results showed that： The degree of coordination of eastern China, central China, and western China decreased in turn. At the national level, energy consumption structure, per capita GDP, and the proportion of green investment were the main factors affecting the synergistic effect of pollution reduction and carbon. The heterogeneity of the influencing factors existed in the central, eastern, and western regions on industrial structure, energy consumption structure, energy utilization efficiency, per capita GDP, urbanization rate, the proportion of green investment, and transportation structure. The intensity of R&D played a significant moderating effect in the whole country, eastern, and central regions. However, no significant moderating effect was identified in the western region. In the eastern region, the urbanization rate, the proportion of green investment, and the transportation structure could not have a significant effect on the synergistic effect of pollution reduction and carbon reduction alone, and it must be coordinated with the intensity of R&D.

In the context of China’s “double carbon” goal, pollution and carbon reduction is a consensus. As a demonstration area and model area for China’s development, how to take the lead in realizing the synergistic improvement of pollution and carbon reduction and embark on a green and low-carbon development path with Chinese characteristics is a common concern of the scientific community and the public. However, each city in Guangdong-Hong Kong-Macao Greater Bay Area (GBA) is different regarding resource endowment, energy structure, development conditions, and technical level. The efficiency, ability, and potential of pollution and carbon reduction must differ. The mission objectives, methods, and methods of promoting the “double carbon” work are also different. Only by considering it from the perspective of system collaboration can the “double carbon” work be safe and sustainable. The study proposes that we can, from the dynamic perspective of the production network and industrial transfer, integrate multi-source and multi-mode data and use a multi-scale evaluation method to analyze the multi-dimensional features and driving factors of the interaction effect of pollution and carbon reduction in GBA. The research results can help cities in GBA to understand their weak links in pollution and carbon reduction in a timely, comprehensive, and accurate manner. In addition, this study is conducive to providing decision-making reference for China to formulate regional synergistic effects.

Major economies, such as the United States, European Union (EU), Japan, and China have enacted Circular Economy Promotion Laws (CEPLs) to promote the development of the recycling industry. The Urban Mining Pilot Policy (UMPP) is an essential provision of the CEPL in China, which promotes a circular economy and environmentally friendly industries and society. In China, the Urban Mining Pilot City (UMPC) program facilitates the addressing of the negative environmental impacts of industrial and urban waste, and conservation of scarce primary resources, which are necessary for sustainable industrialization and urban sustainability in developing countries. In the present study, a time-varying difference-in-difference analysis of city-level panel data was conducted to investigate the impact of the UMPC program on pollution reduction in China. The results indicated that the UMPC program has improved municipal waste management efficiency and environmental quality significantly, with robust results across various models and datasets. Additionally, the mediation test showed the positive impacts of the UMPC program are mainly associated with the economy-of-scale effects. Finally, the UMPP had geographical and social-economic heterogeneous effects. To the best of our knowledge, this is the first study to quantify the impact of the UMPC program on recyclable solid waste management and pollution reduction in urban China, with potential contributions to resource and environmental economics.

Purpose Reducing construction waste generation and carbon emission in the construction industry is crucial for the “dual carbon” goal. Evaluating the efficiency of reducing construction waste generation and carbon emission in the construction industry at the regional level is an important evaluation basis for the sustainable development of the construction industry. It provides a basis for formulating construction waste and carbon reduction policies tailored to local conditions and comprehensively promote the sustainable development of the construction industry. Design/methodology/approach A three stage SBM-DEA model based on non-expected outputs is proposed by combining the SBM-DEA model with the SFA method. The proposed model is used to evaluate the efficiency of construction waste and carbon reduction in the construction industry in 30 regions of China from 2010 to 2020. Moreover, the study explores the impact of environmental variables such as urbanization level, proportion of construction industry employees, resident consumption level, and technological progress. Findings From 2010 to 2020, the efficiency of construction waste and carbon reduction in China’s construction industry has been increasing year by year. Provinces with higher efficiency of construction waste and carbon reduction in the construction industry are mainly concentrated in the eastern coastal areas, showing an overall pattern of “East>West>Northeast>Middle”. There is a clear correlation between the level of urbanization, the proportion of construction industry employees, residents’ consumption level, technological progress, labor input, machinery input, and capital investment. The construction waste and carbon emission efficiency of the construction industry in various provinces is greatly influenced by environmental factors. Practical implications The research results provide policy makers and business managers with effective policies for reducing construction waste generation and carbon emission in the construction industry, especially circular economy policies. To provide empirical support for further understanding the connotation of construction waste and carbon reduction in the construction industry, to create innovative models for construction waste and carbon reduction, and to promote the multiple benefits of construction waste and carbon reduction in the construction industry, and to provide empirical support for countries and enterprises with similar development backgrounds in China to formulate relevant policies and decision-making. Originality/value The construction industry is a high investment, high energy consumption, and high pollution industry. This study uses the three stage SBM-DEA model to explore the efficiency of construction waste and carbon reduction in the construction industry, providing a new perspective for the evaluation of sustainable development in the construction industry, enriching and improving the theory of sustainable development.

Spatial disparities and sources analysis of co-benefits between air pollution and carbon reduction in China

Synergistic strategies for pollution and carbon emission reduction in China's wastewater treatment: A comprehensive tiered assessment and benchmarking framework.

Co-benefits and influencing factors exploration of air pollution and carbon reduction in China: Based on marginal abatement costs

The effects of green finance on pollution and carbon reduction: Evidence from China’s industrial firms