This study presents the methodology as well as a quantitative analysis of the influence of social and economic factors, namely GDP, population, economic growth rate, urbanization rate, and industrial structure on CO₂ emissions as a result of energy consumption in the 101 counties of Inner Mongolia’s industrial sector based on a geographically weighted regression model (GWR) and geographical information systems (GIS) from the perspectives of energy and environmental science. The results show significant differences in the measured CO₂ emission levels among different counties. Utilizing the GWR method (which was tested on the smallest scale that has been published thus far), the relationship between CO₂ emissions and these five explanatory variables produced an overall model fit of 99%. The GWR results showed that the parameters of variables in the GWR varied spatially, suggesting that the influencing factors had different effects on the CO₂ emissions among the various counties. Overall, population, GDP, and urbanization rates positively affect CO₂ emissions, industrial structure, and economic growth rate, and affect CO₂ emissions both positively and negatively. We also characterize the fact that varying industrial structures and economic growth rates result in different effects on the CO₂ emission of various regions.