县域国土空间碳排放时空演变特征与模拟研究: 以四川省邛崃市为例

    Spatial and Temporal Evolution Characteristics and Simulation of County Territorial Carbon Emission: Take Qionglai City of Sichuan Province as an Example

    • 摘要: 本文利用2009-2023年邛崃市社会经济与土地利用数据, 通过趋势、空间自相关和Hurst指数分析, 研究该县级行政区的国土空间碳排放时空格局演变特征。结果表明: (1)2009-2023年邛崃市碳排放总量呈缓慢增长-快速增长的变化趋势, 各类国土空间的碳排放量变化也可以划分为两个明显不同的阶段, 但乡村生产空间的碳排放量在国土空间碳排放总量的占比始终大于70%;(2)2009-2023年, 邛崃市国土空间碳排放量"东高西低"的空间分异格局越发明显, 空间正向集聚性显著, 并逐渐表现出"多中心热点集聚"和"冷点连片"特征; (3)全市有99.1%的国土空间表现出碳排放量变化的正向持续性, 未来将延续2009-2023年的变化趋势, 而全市仅有0.53%的国土空间未来碳排放量将由增长向降低转变, 并主要分布在回龙镇丘陵区和南河两岸。研究邛崃市碳排放量的时空演变特征及未来变化趋势, 可为县域低碳国土空间规划提供数据支撑与思路参考。

       

      Abstract: County-level administrative regions play a critical role in China's carbon control and emission reduction efforts, with territorial space serving as a key strategic area for implementing these tasks. This study, based on socio-economic and land use data from Qionglai City between 2010 and 2020, employs trend analysis, spatial autocorrelation analysis, and the Hurst index to investigate the spatiotemporal evolution of carbon emissions in this county-level region. The findings are as follows: (1) From 2010 to 2020, Qionglai City's total carbon emissions followed a pattern of "slow growth-rapid growth, " with emissions from various territorial spaces also exhibiting two distinct phases. Notably, carbon emissions from rural production spaces consistently accounted for over 70% of total emissions in the region; (2) Over the past decade, the spatial differentiation pattern of "high in the east, low in the west" has become increasingly pronounced, showing the emergence of "polycentric hotspot agglomerations" and "cold spot contiguities"; (3) A majority (99.1%) of Qionglai City's territorial space exhibits positive sustainability in carbon emission trends, suggesting that emissions will continue along the 2010-2020 trajectory, while only 0.53% of the region-primarily in Huilong Town's hilly areas and along the Nanhe River-will experience a shift from growth to decline in carbon emissions. This study provides valuable data and insights for low-carbon territorial space planning at the county level.

       

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