As the major source of air pollution, sulfur dioxide (SO₂) emissions have become the focus of global attention. However, existing studies rarely consider spatial effects when discussing the relationship between foreign direct investment (FDI) and SO₂ emissions. This study took the Yangtze River Delta as the research area and used the spatial panel data of 26 cities in this region for 2004–2017. The study investigated the spatial agglomeration effects and dynamics at work in FDI and SO₂ emissions by using global and local measures of spatial autocorrelation. Then, based on regression analysis using a results of traditional ordinary least squares (OLS) model and a spatial econometric model, the spatial Durbin model (SDM) with spatial-time effects was adopted to quantify the impact of FDI on SO₂ emissions, so as to avoid the regression results bias caused by ignoring the spatial effects. The results revealed a significant spatial autocorrelation between FDI and SO₂ emissions, both of which displayed obvious path dependence characteristics in their geographical distribution. A series of agglomeration regions were observed on the spatial scale. The estimation results of the SDM showed that FDI inflow promoted SO₂ emissions, which supports the pollution haven hypothesis. The findings of this study are significant in the prevention and control of air pollution in the Yangtze River Delta.

作为空气污染的主要来源，二氧化硫（SO ₂）排放已成为全球关注的焦点。但是，现有研究在讨论外国直接投资（FDI）与SO ₂排放之间的关系时很少考虑空间效应。这项研究以长江三角洲为研究区域，并使用了该地区26个城市2004-2017年的空间面板数据。该研究调查了FDI和SO _2中的空间集聚效应和工作动态通过使用空间自相关的全局和局部度量来实现排放。然后，在使用传统普通最小二乘（OLS）模型和空间计量经济学模型的结果进行回归分析的基础上，采用具有时空效应的空间杜宾模型（SDM）来量化FDI对SO ₂排放的影响，因此这样可以避免由于忽略空间效应而导致的回归结果偏差。结果表明，FDI和SO ₂排放量之间存在显着的空间自相关，二者在其地理分布中均显示出明显的路径依赖性。在空间尺度上观察到一系列集聚区域。SDM的估算结果表明，外国直接投资的流入促进了SO _{2的产生。}排放，这支持了污染天堂的假设。这项研究的结果对长江三角洲空气污染的预防和控制具有重要意义。