Scenario analysis on co-benefits of air pollution control and carbon reduction in Yangtze River Delta based on STIRPAT model.

In a changing climate, it is vital to focus on the co-benefits of the pollution control and carbon emission reduction. Based on calculation of emission equivalent, the synergy coefficient is further calculated to quantitatively analyze the co-benefits of air pollution control and carbon reduction in the Yangtze River Delta; Scenario analysis in co-benefits in the Yangtze River Delta from 2026-2035 is thoroughly proposed after STIRPAT model is designed based on influencing factors confirmation including population size, economic scale, industrialization level, urbanization rate and energy intensity from measuring dimensions of synergy coefficient. The results show that the Yangtze River Delta region can partially achieve synergistic emission reduction by 2026 and realize comprehensive synergistic emission reduction of air pollution and carbon emissions not late than 2030, which provides a reference for promoting the decision-making of the new stage of long-term carbon and pollution reduction, and further, realizing carbon peak regulation and carbon neutrality.

Effects measurement and spatial differentiation in synergy between pollution and carbon reduction in national urban agglomerations.

Five national urban agglomerations are selected according to the Fourteenth Five-Year Plan, namely the Yangtze River Delta, the Pearl River Delta, Beijing-Tianjin-Hebei, the Middle reaches of the Yangtze River, and Chengdu-Chongqing. The study on synergistic effects of such national strategic planning urban agglomerations, defined as coordinated degrees, and their time-series trends from 2016 to 2021 is significant for the practice of the national "double carbon" goal. Spatial differentiation of coordinated degree in five agglomerations is analyzed based on the Theil Index, along with regional linkage strength of coordinated degree under the gravity model. Conclusions include: (1) a downward trend is shown from 2016 to 2021 for the coordinated degree, along with the Pearl River Delta is the best among the five agglomerations; (2) the Middle reaches of the Yangtze River is the highest, followed by the Pearl River Delta and the Yangtze River Delta of coordinated degree in 2021; (3) the main cause of downwards in coordinated degree combined by a stable decline in carbon emissions and fluctuating increase in pollutants; (4) intra-regional differences in the Yangtze River Delta and the Middle reaches of the Yangtze River are relatively large, compared with the smallest in the Pearl River Delta measured by Theil Index; (5) coefficients of variation are relatively higher in the Middle reaches of the Yangtze River and the Yangtze River Delta, followed by the Beijing-Tianjin-Hebei, the Pearl River Delta and Sichuan-Chongqing urban. Consequently, countermeasures are proposed from the perspective of government, including technology and regional cooperation, policy innovation by overall coordination, synergy promotion by technological innovation, and regional synergy by win-win cooperation.

Construction enterprises' green financing efficiency and its influencing factors including internal and external: Based on four-stage DEA model.

Under the background of carbon neutrality, green development is the theme of today's times. The construction industry is an important part of the green development plan, and it is of great significance to study its green financing efficiency. Based on this, this paper uses the four-stage DEA model to explore the green financing efficiency of listed construction companies from 2019 to 2020. The conclusion shows that: firstly, the green financing efficiency of listed construction companies is low, and the demand for green financing has not been met. It is necessary to strengthen the support of green finance to meet the needs of its expansion. Secondly, the efficiency of green financing is significantly and complexly affected by external influencing factors. It is necessary to dialectically treat external influencing factors such as local industry development support, financial development level, and the number of patent authorizations. Thirdly, among the internal influencing factors, the proportion of independent directors has a significant positive impact on the green financing efficiency of listed construction companies, and the proportion of R&D investment has a significant negative impact. Listed construction companies need to increase the proportion of independent directors and control the proportion of R&D investment.

Efficiency Evaluation and Influencing Factors of Green Innovation in Chinese Resource-Based Cities: Based on SBM-Undesirable and Spatial Durbin Model.

Based on data from 64 resource-based cities in China from 2010 to 2019, the efficiency of green innovation is evaluated by using the super-efficiency SBM Model with undesired outputs, while influencing factors of green innovation efficiency are analyzed by the spatial Durbin model. The results are as follows. First, as for the efficiency evaluation, the average green innovation efficiency in 62 resource-based cities from 2010 to 2019 is only 0.5689, while the green innovation efficiency of declining cities is the highest, and the growth type is the lowest in the comprehensive planning cities. Second, based on spatial self-correlation in resource-based cities, the government support, and the influencing factors including the industrial structure and economic development, have positive impacts, while the environmental regulations and opening to the outside world will inhibit the urban green innovation. Therefore, to enhance the green innovation efficiency in resource-based cities, some suggestions include formulating differentiated development strategies, forming regional cooperation mechanisms, increasing government scientific and technological support, determining the reasonable intensity of environmental regulations, setting entry barriers for polluting enterprises, and optimizing industrial structure.