The Environmental Kuznets Curve (EKC) provides a theoretical framework for exploring the evolution of human–nature relationships. However, existing EKC-based studies often oversimplify human systems and natural systems, and few studies have conducted a multidimensional analysis of EKC characteristics. To address these limitations, this study conceptualizes the human–nature relationship as the interaction between human activity intensity and environmental quality, quantified using the Human Activity Index (HAI) and the Ecological Quality Index (EQI), respectively. Using panel data from 368 Chinese cities during 2000–2020, we construct composite indicators to characterize the multidimensional states of human and natural systems and apply the EKC framework to analyze their coupled dynamics. Building on the conventional EKC model, we further develop a set of EKC characteristic metrics to systematically describe transition timing, HAI–EQI interactions at the turning point, and dynamic patterns before and after the turning point. Cities exhibiting EKC-type relationships are subsequently classified into distinct human–nature transition pathways, and key driving factors and their heterogeneous effects are examined. The results show that although HAI and EQI increased in most cities, only 147 cities exhibited clear EKC-type trajectories, which can be further grouped into five distinct clusters based on EKC characteristics. Urban expansion, slope, greenspace, forest resilience, and elevation emerged as dominant drivers with heterogeneous influences on EKC dynamics. By extending EKC analysis from simplified indicators to a multidimensional and process-oriented framework, this study advances EKC interpretation beyond pattern identification and provides policy-relevant insights for differentiated urban sustainability strategies and coordinated environmental governance in China.
Yu et al. (Sat,) studied this question.