Greenhouse gases, such as carbon dioxide (CO
2), released from excessive fossil fuel consumption, are major contributors to global warming. Understanding the spatial distribution of CO
2 emissions on a refined scale is crucial for promoting green economic development. Xi’an, a key
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Greenhouse gases, such as carbon dioxide (CO
2), released from excessive fossil fuel consumption, are major contributors to global warming. Understanding the spatial distribution of CO
2 emissions on a refined scale is crucial for promoting green economic development. Xi’an, a key central city in China, serves as the case study for this research. Using nighttime light data from Black Marble, combined with energy statistics and socio-economic information, this study employed spatial analysis to simulate CO
2 emissions on the district and county levels in Xi’an for the years 2012 and 2022. The results indicated that nighttime light data were significantly correlated with CO
2 emissions (linear function; coefficients of determination: 0.7838 and 0.7941 for 2012 and 2022, respectively). The spatial distribution analysis revealed a clear pattern in CO
2 emissions, with higher emissions concentrated in central urban areas and lower emissions in peripheral regions. Additionally, a comparative analysis of carbon emissions and carbon emission intensity across districts and counties between 2012 and 2022 showed that CO
2 emissions in central urban areas had continued to grow and expand, while emission intensity had declined. These findings suggest that the socio-economic development, policy interventions, and industrial structure in Xi’an influence the spatial distribution of CO
2 emissions.
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