As cities are the main carriers of carbon emissions, researchers have been continuously exploring the relationship between various elements in cities and carbon emissions. In this study, a multisource data set was produced for the Hefei Municipal District in Anhui Province, China, and the carbon emission data estimated by both direct and indirect methods were fitted and corrected by the function of nighttime lighting data. Carbon emission drivers were established in accordance with the current 5D spatial indicator system. Based on the current 5D spatial indicator system, the carbon emission driver indicators were established, taking into account the complex process of carbon sources and sinks, and incorporating natural spatial factors other than man-made space. The spatial autocorrelation model was used to analyze the distribution of carbon emissions and each indicator separately and spatially, and the driving force of each factor in the driving system was measured and verified by combining the characteristics of multiple models. The results showed that among the five dimensions of urban space, the driving forces of functional composite strength, public transport station density, and road network density are higher, which are 70.2%, 63.3%, and 63.3%, respectively, which are important factors affecting carbon emission intensity. By prioritizing the improvement of these factors and optimizing public transport and land use, valuable lessons can be provided for spatial planning for carbon reduction and the construction of low-carbon cities.
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Wei Xuan
Hefei University of Technology
Yanfei Lu
Hefei University of Technology
Junhan Tang
Hefei University of Technology
Journal of Urban Planning and Development
Hefei University of Technology
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Xuan et al. (Mon,) studied this question.
synapsesocial.com/papers/69b2577096eeacc4fcec616e — DOI: https://doi.org/10.1061/jupddm.upeng-5634
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