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Issues related to environment are one of the most important issues that confront communities in recent decades.   Resource scarcity and the necessity of development for Iran and other similar countries requires us to deal with carbon dioxide emissions as a manifestation of environmental crisis. In this study, we assess the relationship between carbon dioxide emissions as a dependent variable with population, gross domestic product, electrical energy productivity, electrical energy structure, and household consumption as independent variables, using panel data.  We first develop a model with a spatial lag of both the explanatory and dependent variables, which is called the Spatial Durbin Model (SDM). In this study, we modeled the  carbon dioxide  flow over the period 2005 to 2014 for thermal power plants using a dynamic spatial regression model and a spatial Hausmann test. This test highlights the strong preference for the fixed effect model.  We modified the Wald test for group wise hetero skedasticity in the fixed effect regression model and the Durbin-Watson test for the residual autocorrelation detection results.   Effects of the Spatial Durbin Models (SDM) confirm the assumption of the effectiveness of spatial effects. We estimate the elasticity of the overflow effects through positive and significant proximity.  Our research findings indicate that an increase in  gross domestic product of adjacent provinces increases carbon dioxide emissions the concerned province and neighboring provinces. We also observe that increased electrical energy productivity, electrical energy structure and increased share of electricity consumption by households reduces carbon dioxide emissions in the concerned province and neighboring provinces.
JEL Classification: C21,C23,Q01,Q48, Q54
Keywords: Carbon dioxide emissions, Electrical Energy Productivity, Spatial Durbin Models