| 基于夜间灯光影像的江苏省县域碳排放时空格局 |
| 摘要点击 276 全文点击 19 投稿时间：2025-03-24 修订日期：2025-05-19 |
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| 中文关键词 夜间灯光遥感影像数据 碳排放 时空格局 生态承载系数 低碳转型 |
| 英文关键词 nighttime light remote sensing data carbon emissions spatiotemporal patterns ecological carrying coefficient low-carbon transition |
| DOI 10.13227/j.hjkx.202503281 |
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| 中文摘要 |
| 在全球气候变暖背景下，科学评估区域碳排放时空格局对实现“双碳”目标具有重要意义. 以江苏省县域为典型案例，分析其碳排放时空演变规律及驱动机制，探究碳排放与经济发展和生态保护之间的协同关系，为区域低碳转型与可持续发展提供科学依据. 基于2003~2023年NPP-VIIRS夜间灯光数据与土地利用数据，结合IPCC碳排放系数法构建县域碳排放估算模型，运用空间自相关分析、碳排放经济贡献系数及生态承载系数等方法，系统揭示了碳排放时空演变特征. 结果表明：①江苏省碳排放呈现“南高北低”的异质性格局，苏南地区因经济密集与产业集中成为高排放核心区；苏北地区随工业化进程加速，碳排放增速显著；②碳排放的全局集聚效应逐渐减弱；③经济与生态指标揭示区域发展矛盾：苏南地区碳排放对经济贡献显著，但生态承载能力较弱；苏中地区因生态资源丰富，生态承载能力较强. 研究建议通过差异化政策调控、区域协同减排及生态修复等措施推动低碳转型. 研究结果可为县域尺度碳排放精细化研究提供方法参考，并为江苏省及其他类似区域碳减排政策制定提供科学依据. |
| 英文摘要 |
| Against the backdrop of global climate warming， scientifically assessing the spatiotemporal patterns of regional carbon emissions is of significant importance for achieving the “dual carbon” goals （carbon peaking and carbon neutrality）. As a highly developed economic region in China， the study of carbon emissions in Jiangsu Province not only provides critical guidance for regional low-carbon transformation but also serves as a reference for formulating carbon reduction policies in other similar regions. Taking the county-level units of Jiangsu Province as a case study， this research analyzes the spatiotemporal evolution patterns and driving mechanisms of carbon emissions； explores the synergistic relationship between carbon emissions， economic development， and ecological protection； and provides a scientific basis for regional low-carbon transformation and sustainable development. Based on NPP-VIIRS nighttime light data and land use data from 2003 to 2023， this study constructs a county-level carbon emission estimation model using the IPCC carbon emission coefficient method. Spatial autocorrelation analysis （Moran's I index）， the economic contribution coefficient of carbon emissions （ECC）， and the ecological carrying coefficient of carbon emissions （ESC） are employed to systematically reveal the spatiotemporal characteristics of carbon emissions. The results indicated that： ① Significant spatial heterogeneity of carbon emissions： Jiangsu Province exhibited a “high in the south， low in the north” spatial pattern of carbon emissions. Southern regions such as Nanjing and Suzhou， characterized by dense economic activities and industrial concentration， formed the core high-emission zones， accounting for over 30% of the province's net carbon emissions in 2023. In contrast， northern regions like Xuzhou experienced accelerated industrialization， leading to a significant increase in carbon emissions， with some counties approaching the emission levels of southern areas. ② Dynamic evolution of spatial agglomeration effects： The global Moran's I index decreased from 0.34 to 0.220， indicating a weakening of the global agglomeration effect of carbon emissions. The proportion of local high-high agglomeration areas decreased to 2.3%， while low-low agglomeration areas increased to 8.2%， reflecting the regulatory impact of regional emission reduction policies on spatial patterns. ③ Regional development contradictions revealed by economic and ecological indicators： Southern Jiangsu showed a significant economic contribution from carbon emissions （ECC > 1） but a weak ecological carrying capacity （ESC < 0.5）. Central Jiangsu， including regions like Yancheng and Yangzhou， benefitted from abundant ecological resources， resulting in stronger ecological carrying capacity （ESC > 1）. Based on these findings， this study proposes measures such as differentiated policy regulation， regional collaborative emission reduction， and ecological restoration to promote low-carbon transformation. The results provide methodological references for fine-grained carbon emission research at the county level and offer a scientific basis for carbon reduction policy formulation in Jiangsu Province and other similar regions. |
