This paper theoretically analyzes the direct impact of environmental regulation on carbon emissions and its indirect effects on carbon emissions through foreign direct investment (FDI), energy consumption, industrial structure, and technological innovation. Then, this paper constructs a spatial lag model to empirically test the dual effects of environmental regulation on carbon emissions based on the provincial panel data of 20032017 in China. The results show that the average Morans I value of carbon emissions during 20032017 is 0.2506, passing the significance test at 1 level, and carbon emissions have spatial correlation characteristics. The direct impact of environmental regulation on carbon emissions is significant and positive. Environmental regulation could indirectly influence carbon emissions by influencing FDI, energy consumption, and technological innovation, and meanwhile, FDI, energy consumption, and technological innovation help to reduce carbon emissions under the constraint of environmental regulation, specifically. However, the impact of environmental regulation on carbon emissions through industrial structure is not significant.

Based on the statistical data of 30 provinces in China from 2003 to 2014, this paper uses the spatial Durbin model to empirically test the influence of China’s urban environmental regulation on the introduction of foreign direct investment (FDI). The results show that there is significant spatial correlation between environmental regulation and FDI. Environmental regulation has a negative impact on the introduction of FDI, but the impact is not significant across the country, indicating that the evidence of the pollution haven hypothesis is insufficient in China. Then, the influential effect of environmental regulation on the introduction of FDI has obvious regional differences. The level of environmental regulation in the eastern region is positively correlated with the convenience in FDI introduction, while in the central and western regions, environmental regulation pose a hindrance to the introduction of FDI, which is remarkable only in the central area. In addition, labor costs and human capital levels have a direct effect on the introduction of FDI in the region. The level of regional economic development and R&D investment have a significant indirect impact on the introduction of FDI in surrounding areas, and economic openness has a significant impact on the introduction of FDI in all regions.

Identifying the differentiated effects of different environmental regulations is the basis for promoting China's zero carbon emissions and carbon neutrality. We used Chinese provincial panel data from 2003 to 2017 to empirically test the impact of different environmental regulations on carbon neutrality through spatial measurement models. The highlights of the study are as follows: (1) Environmental regulations exert significant impact on carbon emissions, but different types of environmental regulations exert significantly different effect on carbon emissions. Public participation environmental regulation has a control effect on regional carbon emissions, while command-based and market-based environmental regulations had no significant effect on regional carbon neutrality. (2) The heterogeneity of the impact of different types of environmental regulations on carbon emissions can also be identified from the regional impacts heterogeneity and lags impact heterogeneity. (3) The combined mandatory and market-based environmental regulations and the combined mandatory and public-participatory environmental regulations significantly inhibited regional carbon neutrality.

Rapid industrialization and urbanization have presented a dilemma to traditional environmental policies, and severe haze pollution has attracted particular attention in China. This paper employed the exploratory spatial data analysis technique to analyze global and local spatial auto-correlation of environmental regulations (ERS) and haze pollution. Static and dynamic spatial panel data models were further established to investigate the influence of ERS and its spatial spillover effect on haze pollution across 31 provinces of China in 2005-2015. Results showed that significant spatial autocorrelation existed for both ERS and haze pollution in China, forming different aggregation regions in terms of geographical distribution. There was strong evidence for the “inverted-U”-shaped EKC relationship between ERS and haze pollution regardless of whether it was the static or dynamic spatial econometric model. In addition, haze pollution was not only affected by economic growth, population size, and urbanization, but also by the haze pollution in the previous period. Conclusions and control strategies that would be of great significance for implementing effective management measures were synoptically discussed.