Excessive consumption of traditional fossil energy has led to more serious global air pollution. This article incorporates renewable energy green innovation (REGI), fossil energy consumption (FEC), and air pollution into a unified analysis framework. Using China’s provincial panel data, a spatial measurement model was used to investigate the spatial effects of renewable energy green innovation and fossil energy consumption on air pollution in China from 2011 to 2017. The global Moran index shows that over time, the spatial correlation of air pollution has gradually weakened, while the global correlation of renewable energy green innovation and fossil energy consumption is increasing year by year. ArcGIS visualization and partial Moran index show that air pollution, renewable energy green innovation, and fossil energy consumption are extremely uneven in geographic space. The spatial distribution of air pollution, renewable energy green innovations, and fossil energy consumption are all characterized by high in the east and low in the west and they all show a strong spatial aggregation. Applying the spatial adjacency matrix to the spatial Durbin model gave the results that China’s air pollution has a significant spatial spillover effect. Replacing fossil fuels with clean renewable energy will reduce air pollutant emissions. The Environment Kuznets Curve (EKC) hypothesis has not been supported and verified in China. The partial differential method test found that the spatial spillover benefits can be decomposed into direct effects and indirect effects. The direct and indirect effects of renewable energy green innovation on air pollution are both significantly negative, indicating that green innovation of renewable energy not only inhibits local air pollution, but also inhibits air pollution in nearby areas. The consumption of fossil energy will significantly increase the local air pollution, while the impact of sulfur dioxide (SO₂) and soot (DS) pollution in nearby areas is not obvious. It is recommended to increase investment in renewable energy green innovation, reduce the proportion of traditional fossil energy consumption, and pay attention to the spatial connection and overflow of renewable energy green innovation and air pollution.

Since entering the industrialized era, China’s greenhouse gas emissions and air pollutant emissions have increased rapidly. China is the country with the most greenhouse gas emissions, and it is also facing serious local air pollution problems. China’s industrial sector is the largest contributor to CO₂ and air pollutants. The resulting climate change and air pollution issues have caused China to face double pressures. This article uses the CO₂ and comprehensive air pollutant emission data of China’s industrial sector as a starting point and uses econometric research methods to explore the synergy between China’s industrial carbon emission reduction and industrial comprehensive air pollutant emission reduction. The synergistic effect between industrial carbon emissions and industrial comprehensive air pollutant emissions has been quantified, and the transmission path of the synergistic effect has been explored. The empirical results show that there are benefits of synergistic governance between climate change and air pollution in China’s industrial sector. Every 1000 tons of carbon reduction in the industrial sector will result in 1 ton of comprehensive air pollutant reduction. The increase in R&D expenditure in the energy and power sector can significantly promote the reduction of air pollutants in the industrial sector. Increasing the intensity of environmental regulations is the main expansion path for synergy. However, in eastern, central, and western China, the synergy is not the same. Therefore, it is necessary to formulate regionally differentiated emission reduction policies. The research conclusions of this article can provide policy references for the coordinated governance of climate change and air pollution in China.

Current emission reduction policies have struggled to adapt to the reality of industrial spatial agglomeration and increasing industrial linkages. In response, this paper incorporates new economic geography factors such as agglomeration production and industrial (trade) association into the analysis framework of carbon emission performance factors through China’s provincial panel data and conducts empirical research. It has been found that large-scale industrial production under economic agglomeration is conducive to improving carbon emission performance and that different forms of agglomeration at different degrees of agglomeration correspond to different carbon emission performances. As the degree of agglomeration increases, the effect of reducing emissions by specialized agglomeration decreases while the effect of reducing emissions by diversified agglomeration increases. Specialized agglomeration externalities and diversified agglomeration externalities can coexist at the same time, depending on the appropriate degree of agglomeration. There is a strong negative environmental efficiency effect in the provinces with close commodity trade links, which has triggered environmental dumping and pollution transfer between provinces. In the work of energy conservation and emission reduction, we must attach great importance to the hidden carbon in domestic merchandise trade and the resulting intergovernmental environmental game, and furthermore, give full play to the “self-purification” effect of aggregate production on energy conservation and emission reduction.

High hopes are placed on the production and use of clean energy during the decoupling between economic growth and environmental pollution. This article uses the decoupling model to study the temporal and spatial coupling characteristics of economic growth and environmental pollution in different regions of China. On this basis, a spatial measurement model is used to quantitatively evaluate the effects of clean energy consumption on the decoupling of economic growth and environmental pollution. The results show that during the study period, the areas where economic growth and environmental pollution generally showed strong decoupling gradually increased, and the areas showing coupling gradually decreased. Moreover, the decoupling state has obvious spatial heterogeneity and spatial aggregation characteristics. Clean energy consumption can significantly promote the decoupling of economic growth and environmental pollution. In addition, the analysis of direct effects shows that clean energy consumption has a significant negative effect on the decoupling of regional economic growth from SO2 emissions and DS (dust and smoke) emissions. But the indirect effect and total effect are not obvious. It further proves that clean energy consumption has no significant effect on promoting the decoupling of surrounding areas and all areas except the local area.