Spatiotemporal Effects and Optimization Strategies of Land-Use Carbon Emissions at the County Scale: A Case Study of Shaanxi Province, China

Abstract

Land use, as one of the major sources of carbon emissions, has profound implications for global climate change. County-level land-use systems play a critical role in national carbon emission management and control. Consequently, it is essential to explore the spatiotemporal effects and optimization strategies of land-use carbon emissions at the county scale to promote the achievement of regional dual carbon targets. This study, focusing on Shaanxi Province, analyzed the spatiotemporal characteristics of land use from 2000 to 2020. By establishing a carbon emission evaluation model, the spatiotemporal effects of county-level carbon emissions were clarified. Utilizing Geodetector and K-means clustering methods, the driving mechanisms and clustering characteristics of county-level carbon emissions were elucidated, and optimization strategies for land use carbon emission were explored. The results showed that during 2000–2020, land use in Shaanxi Province underwent significant spatiotemporal changes, with constructed land increasing by 97.62%, while cultivated land and grassland were substantially reduced. The overall county-level carbon emissions exhibited a pattern of North > Central > South. The total carbon emissions within the province increased nearly fourfold over 20 years, reaching 1.00 × 108 tons. Constructed land was the primary source of emissions, while forest land contributed significantly to the carbon sink of the study area. Interactions among factors had significant impacts on the spatial differentiation of total county-level carbon emissions. For counties with different types of carbon emissions, differentiated optimization strategies were recommended. Low-carbon emission counties should intensify ecological protection and rational utilization, medium-carbon emission counties need to strike a balance between economic development and environmental protection, while high-carbon emission counties should prioritize profound emission reduction and structural transformation.