Based on the extended STIRPAT theoretical framework, the dynamic spatial panel data model analysis method is used to study the long-term and short-term spatial spillover effects of urbanization, FDI and industrial structural factors on China's environmental pollution. The results show that every 10% increase in the urbanization rate of a region will reduce the local CO₂ emission level by 0.02% in the short term, and reduce the CO₂ emission level by 0.04% in the neighboring area; and in the long term, it will reduce the local CO₂ emission level by 0.08% and the neighboring region's CO₂ emission level by 0.2%. Before 2006, every 1% reduction in energy intensity in a region will reduce the local CO₂ emission level by 0.31% in the short-term and reduce 0.09% of the neighboring region's CO₂ emission level; in the long term, it will reduce the local CO₂ emission level by 1.3% and reduce 0.55% of CO₂ emission level in neighboring region. After 2006, this change in energy intensity will reduce carbon emissions by a total of 0.45% in the short term and a total of 2.06% in the long term. Every 10% increase in urbanization rate will reduce the local 0.05% of SO₂ emissions, reduce the SO₂ emissions of neighboring areas by 0.1%. Every 10% reduction in the proportion of secondary industry will reduce the local and neighboring SO₂ emissions levels 0.03% and 0.09%, respectively. Every expanded 1% population size will be increased by 0.55% of the neighboring region's SO₂ emission levels. Every 1% reduction in energy intensity will be reduced by 0.12% local SO₂ emission levels.