Assessing the divergent effects of green infrastructure landscape patterns on carbon emission and sequestration in 31 cities across China

Abstract

Green infrastructure (GI) serves as the effective measure for mitigation of carbon emission and adaption to climate changes. The deep understanding of the influences of GI landscape patterns on carbon emission and sequestration would help enhance the carbon management and support low-carbon city construction. In this study, we investigated the variation in carbon budget (carbon emission and sequestration) in 31 Chinese cities from 2001 to 2021, respectively, and examined their linear and non-linear correlations to GI landscape patterns by using random forest model and ridge regression method. The results illustrated a significant increase in carbon emission across 31 Chinese cities during the study period. However, not all the cities underwent significant growth in carbon sequestration. The study highlights the pivotal role of GI areas in reducing carbon emissions and enhancing carbon sequestration, while an expanding water area appeared to hinder carbon sequestration. The PD (Patch Density) and PLADJ (Percentage of Like Adjacencies) representing the landscape aggregation were negatively associated with carbon emission reduction and positively correlated with increased carbon sequestration; The shape metrics, including LSI (Landscape Shape Index) and FRAC_AM (Area-Weighted Mean Fractal Dimension Index), were found to positively correlate to both carbon emission and sequestration. Moreover, the study uncovered the divergent impacts of dominant GI patch and landscape diversity on carbon emission and sequestration across cities in different subregions. The findings of this study not only help understanding the relationships between GI landscape patterns and urban carbon environments, but also provide valuable insights for guiding future low-carbon urban planning.