Exploring Low-Carbon Urban Development at the Plot Scale: A Study of Carbon Emission Mechanisms and Empirical Exploration of Micro-Renovation for Emission Reduction

Abstract

In response to global climate change, cities - as key spatial carriers of human activity - must refine governance strategies. Focusing on Nanjing’s main urban area, this study integrates ODIAC global carbon emission data with multi-source big data and applies Multi-scale Geographically Weighted Regression (MGWR) and Geo-Detector models to analyze drivers of land-use carbon emissions. Results show that functional attributes, spatial forms and carrying capacity characteristics have a spatially heterogeneous impact on carbon emission intensity, with the carrying capacity factors contributing the most and about 60% of the influencing factors having significant synergistic effects. Based on this, a low-carbon planning strategy at the micro-plot level is constructed, and the carbon emission intensity of the plot in Liuhe District is reduced from 6.96 kg/m² to 6.38 kg/m², with an annual carbon emission reduction of 153 tons. This function-form-capacity collaborative control approach effectively reduces urban land-use carbon intensity and supports low-carbon city goals.