## 4 Measurement Estimation and Analysis
### Estimation Results and Analysis Statistics of Spatial Correlation Effect
\begin{table}
\begin{tabular}{c c c c c c c} \hline \hline  & \multicolumn{2}{c}{**The Total Effect**} & \multicolumn{2}{c}{**The Direct Effect**} & \multicolumn{2}{c}{**The Indirect Effect**} \\ \hline
**Model** & **(1) SAR** & **(2) SDM** & **(1) SAR** & **(2) SDM** & **(1) SAR** & **(2) SDM** \\ \hline
**Variable** & **InAEP** & **InAEP** & **InAEP** & **InAEP** & **InAEP** & **InAEP** \\ \hline LR\_Direct & & & & & & \\ wlnAPI & \(-0.173\) & \(-1.553\)* & \(-0.094\) & \(-1.337\)*** & \(-0.079\) & \(-0.216\) \\  & \((-0.164)\) & \((-1.873)\) & \((-0.168)\) & \((-4.461)\) & \((-0.160)\) & \((-0.272)\) \\ Iner & \(-0.049\)* & \(-0.240\)*** & \(-0.026\)* & \(-0.023\) & \(-0.023\)* & \(-0.217\)*** \\  & \((-1.781)\) & \((-3.481)\) & \((-1.777)\) & \((-1.521)\) & \((-1.777)\) & \((-3.523)\) \\ Inden & \(-0.002\) & \(0.132\) & \(-0.001\) & \(-0.091\)*** & \(-0.001\) & \(0.223\)* \\  & \((-0.036)\) & \((0.958)\) & \((-0.040)\) & \((-2.644)\) & \((-0.031)\) & \((1.772)\) \\ lnbua & \(-1.013\)*** & \(-0.630\)* & \(-0.539\)*** & \(-0.380\)*** & \(-0.474\)*** & \(-0.251\) \\  & \((-6.635)\) & \((-1.903)\) & \((-6.667)\) & \((-5.447)\) & \((-6.343)\) & \((-0.850)\) \\ Iney & \(-2.408\)*** & \(-1.992\)*** & \(-1.281\)** & \(-1.583\)*** & \(-1.126\)** & \(-0.409\)** \\  & \((-2.5758)\) & \((-11.431)\) & \((-24.288)\) & \((-25.727)\) & \((-17.907)\) & \((-2.493)\) \\ Inin & \(0.672\)** & \(2.902\)*** & \(0.358\)** & \(0.523\)*** & \(0.314\)** & \(2.379\)*** \\  & \((2.453)\) & \((7.308)\) & \((2.447)\) & \((3.447)\) & \((2.443)\) & \((7.070)\) \\ \hline \(N\) & \(3990\) & \(3990\) & \(3990\) & \(3990\) & \(3990\) & \(3990\) \\ \(R^{2}\) & \(0.051\) & \(0.441\) & \(0.051\) & \(0.441\) & \(0.051\) & \(0.441\) \\ adj. \(R^{2}\) & & & & & & \\ \hline \hline \end{tabular} \(t\) statistics in parentheses * \(p<0.1\), ** \(p<0.05\), *** \(p<0.01\).  
\end{table} 
Table 2: The Analysis of Spatial Correlation Effect. attach more importance to environmental issues. By increasing urban greening coverage, transferring polluting industries, optimizing and upgrading industrial structure, and adjusting urban layout, one region can improve atmospheric self-purification capacity, thus strengthening the removal of environmental pollution by atmospheric self-purification capacity. For example, coastal regions like Fujian, Guangdong, and Zhejiang give full play to the purification of precipitation on environmental pollution. Simultaneously, in high-level cities, economic development plays a significant role in promoting atmospheric self-purification capacity, which remarkably reduces environmental pollution. As for the total effect or indirect effect of environmental regulation (Iner), the coefficient proves significantly negative and has a significant inhibitory effect on environmental pollution. Environmental regulation can form the reversed emission reduction effect and the compliance cost effect to alleviate environmental pollution and achieve emission reduction. As China formulates and implements a series of measures and policies on the governance of environmental pollution, environmental regulation scores a success in reducing pollution emission. Simultaneously, in neighboring regions, environmental regulation and environmental-pollution emission both have significant spatial spillover effects and show a symbiotic pattern of interdependence. In terms of the control variables, as the coefficient of population density (Inden) suggests, there is a significant negative correlation between local population density and local environmental pollution. The rise of population density facilitates the centralized supply and use of direct energy consumption, reduces the emission of polluting gases represented by carbon emission, and further mitigates environmental pollution. The indirect effect of population density has a significant positive correlation, indicating that the increase in population density in one region aggravates environmental pollution in neighboring regions.