A Spatial Analysis of Predictors of Ambient Sulfur Dioxide Concentrations in the United States Abstract: Despite the success of the US Environmental Protection Agency’s Acid Rain Program in reducing national sulfur dioxide emissions from electricity generation

Despite the success of the US Environmental Protection Agency’s Acid Rain Program in reducing national sulfur dioxide emissions from electricity generation in a timely and costsaving manner, expected improvements in the environment have not followed in a linear fashion. While ambient sulfur dioxide (SO2) concentrations and acid deposition have decreased across the US, the health and ecological benefits have not been evenly distributed. In this study, spatial analysis is used to investigate meteorological and anthropogenic factors that determine ambient SO2 concentration. We find that spatial analysis and theoretical knowledge indicate that an OLS regression with spatial lag can be used to predict ambient SO2 concentrations. Significant variables in the model included SO2 electricity generation and fossil fuel combustion emissions as well as precipitation and wind speed. By understanding how these mechanisms determine ambient SO2 concentrations, policy makers can improve air quality policy to more equitably and efficiently protect human health and the environment.