Heterogeneous carbon decoupling and peaking pathways across county types in hunan province: an integrated tapio-STIRPAT-scenario analysis.

Abstract

Balancing economic growth with emission reductions presents a pivotal challenge under China's "dual-carbon" strategy. Hunan Province, characterized by its diverse industrial and ecological contexts, offers a quintessential setting for county-level analysis. This study investigates 122 counties within Hunan from 2000 to 2022, employing the Tapio decoupling model, spatial autocorrelation, ordinary least squares (OLS) regression, an augmented STIRPAT framework, and scenario simulations. It analyzes the spatiotemporal dynamics between carbon emissions and GDP, elucidates the principal driving mechanisms, and forecasts peaking trajectories under scenarios of low, medium, and high carbon emissions. The findings reveal a continued rise in emissions, albeit at a reduced pace post-2010, with the proportion of counties achieving strong decoupling escalating from 6% during 2006-2010 to 53% in 2016-2022. Counties dominated by eco-cultural (80%) and agricultural activities (67%) demonstrated the most significant transitions. Regression analyses, based on standardized coefficients, underscore the positive influence of carbon intensity (0.917), economic development (0.792), and population (0.447) on emissions, whereas industrial upgrading (-0.014), energy efficiency (-0.046), and urbanization (-0.010) contribute to mitigating impacts. GeoDetector analysis corroborates strong interaction effects. Scenario simulations indicate that only the low-carbon pathway might enable all four economic regions to achieve emission peaks between 2030 and 2035, while medium- and high-carbon trajectories fail to achieve effective peaking before 2040. These results highlight the imperative for tailored low-carbon strategies at the regional level, incorporating industrial restructuring, enhancement of energy efficiency, promotion of ecological-based industries, and implementation of county-level monitoring and market incentives.