This study investigates 30 provinces in China between 2003 and 2014. Kernel density method is used to analyse the dynamic evolution of haze pollution and technological innovation research and development (R&D), while spatial econometric analysis is used to study the impact of technological innovation on the haze pollution. The results show that haze pollution presents global spatial autocorrelation and local spatial cluster in China. China’s haze pollution has a significant spatial dependence and spatial spillover. A disproportion distribution pattern of haze pollution exists among provinces in China: the central region is the most polluted area followed by the western region, the northeast region and the eastern region. The kernel density curve shows that the gap between technology innovations R&D among provinces has expanded year by year. There is a polarization between the technological innovations R&D. Dynamic evolution results showed that during 2003–2012, the kernel density distribution curve of haze pollution showed a leftward shift, indicating that provincial haze pollution decreased gradually. However, the kernel density distribution curve of haze pollution showed a rightward shift in 2014, and the provincial haze pollution increased. During 2003–2012, the gap of haze pollution among different provinces in China gradually narrowed, while in 2014, the gap increased significantly. Spatial econometric results show that the indirect effects and the total effects of technological innovation are significantly negative. Technological innovation can not only reduce the regional haze pollution but also indirectly lead to the decline in the haze pollution of adjacent provinces through the knowledge spillover effect. The increase of population density can effectively reduce the haze pollution. There is an inverted ‘U type’ relationship between economic development and haze pollution. The increase of traffic pressure will aggravate the degree of haze pollution.

This study highlights the significance of high-quality development of energy (EHQD) in achieving carbon neutrality. Researchers have explored how to successfully achieve carbon neutrality, but few studies have examined the impact of the EHQD on carbon neutrality. Accordingly, while considering the high-quality development of China’s economy, this study constructs a comprehensive evaluation index system for China’s EHQD using the technique for order preference by similarity to an ideal solution (TOPSIS) method based on entropy weight to measure the EHQD level of energy in 30 provinces in China from 2004 to 2019. Considering the possibility of endogeneities, the two-stage least squares (2SLS) regression is applied to empirically analyze the impact of the EHQD on carbon neutrality. Cointegration tests show a long-term cointegration relationship between the EHQD, real GDP per capita, urbanization, traffic pressure, industrial structure, and CO₂ emissions (CE). The 2SLS method empirically shows that the EHQD has a significant negative impact on CE. The EHQD can significantly reduce CE, which is conducive for China to achieve the goal of carbon neutrality. The results of this study indicate that to reduce CE and enable China to successfully achieve its goal of carbon neutrality by 2060, policymakers should take effective measures to promote the EHQD.

Based on spatial econometrics, this paper examines the impact of urbanization, coal consumption proportion, and traffic pressure on haze pollution and attempts to verify the environmental Kuznets curve hypothesis by using 30 provinces’ panel data in China from 2003 to 2015. The global Moran’s I index indicates the positive spatial correlation of haze pollution, and the local Moran’s I index indicates the clustering phenomenon of haze pollution in local regions. This model shows that haze pollution has spatial spillover effects in China. The relationship between urbanization and haze pollution is an inverse U-type curve, and the increase in coal consumption proportion and traffic pressure may enhance the degree of haze pollution. To govern China’s haze pollution, China should promote regional collaborative governance, expand urban afforestation areas, adopt green buildings, increase green elements, enhance ecological factors, optimize energy structure and implement energy substitution, and develop public traffic.

Based on the PM_2.5 concentration data of 253 prefecture-level cities, it empirically investigated the effect of urban density on PM_2.5 concentration in China using spatial econometric regression method. The results show that there is a spatial spillover effect of PM_2.5 concentration in China. The coefficient of urban density is significantly negative, and the increase in urban density will reduce haze pollution. In order to reduce haze pollution in Chinese cities, it is necessary to continue to implement regional joint prevention and control measures. The eastern region should focus on building small blocks and high-density networks to reduce haze pollution. The central region should focus on urban greening, increase green coverage, and reduce the heat island effect. While improving the level of greening in the western region, we should increase urban density, reduce urban sprawl, and build compact cities.

China is vigorously building a unified domestic market, with priority given to regional market integration while maintaining a national unified market. Limited research has been conducted on whether market integration affects renewable energy technology innovation (RETI). This paper empirically studies this topic based on panel data of 30 Chinese provinces from 2004 to 2020 using FMOLS (Fully Modified Ordinary Least Squares), DOLS (Dynamic Least Squares method), and FGLS (Feasible Generalized Least Squares). Research results have been verified by robustness tests. The main conclusions are as follows: (1) Market integration has an important positive impact on RETI, namely, boosting it. This conclusion remains robust when different indicators of innovation and market segmentation are included. (2) The regional impacts of market integration on RETI are heterogeneous, being the greatest in east China, followed by west China and central China. (3) Market integration affects RETI through energy structure and technological innovation. It can optimize energy structure, improve technological innovation, and thus enhance RETI. Based on the above conclusions, in order to improve RETI in China and expand its contribution to carbon neutrality and carbon peaking, China needs to strengthen the construction of a national unified market and implement differentiated market integration policies in east, central, and west China. Furthermore, it is necessary to give full play to the role of energy structure and technological innovation in market integration by optimizing energy structure and improving technological innovation.