||As the world’s largest developing country and greenhouse gas emitter, China’s residential energy consumption (REC) is now responsible for over 11% of the country’s total energy consumption. In this paper, we present a novel method that utilizes spatially distributed information from the Defense Meteorological Satellite Program’s Operational Linescan System (DMSP–OLS) and human activity index (HAI) to test the hypothesis that counties with similar carbon dioxide emissions from REC are more spatially clustered than would be expected by chance. Our results revealed a high degree of county-level clustering in the distribution of emissions per capita. However, further analysis showed that high-emission counties tended to be surrounded by counties with relatively low per capita GDP levels. Therefore, our results contrasted with other evidence that REC emissions were closely related to GDP levels. Accordingly, we stress the need for the consideration of other factors in determining emission patterns, such as residential consumption patterns (e.g., consumer choices, behavior, knowledge, and information diffusion).