In the pursuit of China’s ambitious carbon neutrality goals, optimizing carbon-emission efficiency within the construction sector, a significant emitter, becomes critical. This study employs a super-Slacks-Based Measure (SBM) model and a Tobit regression model to analyze buildings’ heating-related carbon emissions across China, considering urban population density, electricity usage, and building energy consumption and the influencing factors that cause differences in carbon-emission efficiency difference. The results of this study show that the average building carbon-emission efficiency of 30 provinces in China is 0.789; carbon-emission efficiency is 0.89 in the south, higher than 0.69 in the north. After excluding centralized heating emissions, the value of buildings’ carbon-emission efficiency in the northern provinces increases by 0.01, of which the buildings’ carbon-emission efficiency in Jilin Province and Ningxia Hui Autonomous Region shows positive growth, respectively, by 0.12 and 0.17. In terms of influencing factors, there is a significant positive correlation between the scientific and technological levels, the regional economic scale, and carbon-emission efficiency; however, government intervention in the economy has a negative correlation with carbon-emission efficiency. Renewable energy utilization and green-policy adoption emerge as pivotal in enhancing efficiency. The contribution of this study is to underscore the necessity of fostering renewable energy, refining energy-consumption structures, and implementing green strategies to augment buildings’ heating-related carbon-emission efficiency.

With the rapid urbanization process, the construction industry has become a significant source of urban carbon emissions in China. The carbon emissions from buildings in the urban clusters of the Yangtze River Economic Belt, a crucial region for China’s economic development, have attracted considerable attention. This study focuses on urban buildings and aims to investigate the primary influencing factors of building carbon emissions in the urban clusters of the Yangtze River Economic Belt. The study highlights the innovative use of nighttime light remote sensing data to analyze urban carbon emissions and provides an in-depth exploration of the spatiotemporal characteristics of building carbon emissions in the urban clusters of the Yangtze River Economic Belt. Utilizing nighttime light remote sensing data similar to DMSP-OLS and provincial-level building carbon emissions, combined with spatial autocorrelation and spatiotemporal geographically weighted regression models, the study estimates and analyzes the building carbon emissions from 2012 to 2021 in 71 prefecture-level and above administrative regions within the three major urban clusters of the Yangtze River Economic Belt. The results indicate a continuous increase in total building carbon emissions in the three major urban clusters of the Yangtze River Economic Belt, with an accelerating growth rate. Spatially, urban building carbon emissions exhibit enhanced convergence but decreasing correlation over time, demonstrating evolving spatiotemporal patterns. Furthermore, the study identifies economic development level, population size, built-up area, and industrial structure as the main factors influencing building carbon emissions, with industrial structure showing significant impact.