Characteristics of spatial and temporal distribution of carbon emissions and influencing factors in Hefei City based on nighttime lighting data

Urban areas are significant contributors to global carbon emissions. Investigating the spatiotemporal distribution characteristics of urban carbon emissions and their influencing factors is essential for formulating effective carbon reduction policies and enhancing urban environmental quality. This study utilized nighttime light data to analyse the spatiotemporal distribution of carbon emissions in Hefei City. We employed a Random Forest regression model to explore the impact of urban spatial morphology on carbon emissions. The findings indicated that carbon emissions in Hefei have shown a consistent annual increase without a clear spatial pattern. Regression analysis revealed a nonlinear positive correlation between carbon emissions and factors such as floor area ratio, building density, architectural volume and staggered degree. Conversely, the body mass index and enclosure factor demonstrated a nonlinear negative correlation with carbon emissions. Amongst them, the body mass index was shown to have the highest impact weight on urban carbon emission, which was 0.195, followed by architectural volume and floor area ratio, which were 0.155 and 0.145, respectively. This research highlights the complex influence of urban spatial morphology on carbon emissions and provides valuable insights for the development of urban carbon reduction strategies.