Abstract
Dramatic changing in land cover and spatial pattern of carbon sources and sinks in cities exacerbating urban CO₂ emissions, threatens ecosystems, human health and economic development. While previous studies have explored the relationship between spatial patterns of land cover and carbon emissions, many are limited by focusing on a single type of land cover or by assuming spatial homogeneity. This study introduces an innovative approach to leveraging land cover spatial patterns for reducing CO₂ emissions. Based on the data from 304 Chinese cities in 2005, 2010, 2015 and 2020, the relationships between urban land cover (cropland, forest, grassland and impervious) and CO₂ emissions were explored by multiscale geographically weighted regression (MGWR) model. Our analysis revealed that the growth rate of total CO₂ emissions decreased from 45% to 5% between 2005 and 2020, with the Beijing-Tianjin-Hebei and Yangtze River Delta regions being high-emission areas. The area of cropland has a bidirectional effect on CO₂ emissions. Expanding the area of forest and fostering uniform distribution with other cover types contribute to reduce CO₂ emissions. Grassland needs to increase the spatial hierarchy and complexity. Impervious ground surface requires control of the rate of expansion and containment of the spread. These findings offer new insights into urban carbon reduction through comprehensive land use planning, providing an actionable strategy to optimize the spatial arrangement of land cover types.