Spatiotemporal evolution and influencing mechanisms of carbon pressure at the county scale: A case study of central-south Liaoning urban agglomeration, China

Abstract

Achieving carbon neutrality necessitates a dual focus on minimizing carbon emissions and maximizing carbon sequestration, rather than solely concentrating on emission reduction. This study proposes a Carbon Pressure Index (CPI) to assess the equilibrium between emissions and sequestration, determine the factors influencing varying carbon pressure levels, and formulate region-specific strategies based on these levels. A nested methodological approach, combining spatiotemporal leaps analysis and quantile regression, is employed to appraise county-level carbon pressure dynamics across multiple quantiles in the central-south Liaoning urban agglomeration (CSLUA) from 2002 to 2021. Three principal findings were derived: Firstly, the spatiotemporal distribution of the CPI across CSLUA districts and counties demonstrates regional differentiations conforming to a gradient pattern, with values declining from urban centers toward peripheral areas. Carbon pressure is greater in the west, less in the east, and critically high in the central-western zones. Secondly, the spatial distribution of the CPI indicates clear high-high and low-low agglomeration clusters, suggesting persistent local structures that indicate path dependence and resistance to change in carbon pressure transfer. While the central-western regions exhibit further changes, the eastern areas maintain relative stability. Thirdly, environmental technology factors constrain most districts and counties, while the combined influence of industrial activity and population, along with economic and urbanization pressures, have predominant effects in smaller areas in the central-western region. This highlights the effectiveness of the nested spatiotemporal leaps and quantile regression model in explaining the driving forces underlying the spatiotemporal shifts in CPI. The results suggest that attaining superior regional low-carbon development requires rectifying the asymmetry between carbon sources and sinks, considering the driving forces of diverse transition pathways and their interactions, to finally achieve synergistic optimization that incorporates both shared and unique regional characteristics.

Keywords

• Carbon pressure
• Local Indicators of Spatial Association
• Spatiotemporal transition
• Quantile regression
• Urban agglomeration