期刊文献+

1997—2021年川渝地区区县尺度碳排放时空格局特征分析

Characterization of Spatial and Temporal Patterns of County-Scale Carbon Emissions in the Sichuan-Chongqing Region from 1997 to 2021
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摘要 川渝地区作为重要的西部发展先导区,要求实现绿色低碳与区域协调的协同发展,科学探究川渝两地精细尺度碳排放的区域化差异对于碳减排具有十分重要的意义。基于1997—2021年省级碳排放与夜间灯光数据集,利用面板数据模型估算出区县尺度碳排放数据,并运用ArcGIS软件,探索川渝221个区县碳排放的时空变化趋势。结果表明:构建的估算模型具有较高的估算精度(R^(2)为0.979,平均绝对百分比误差为5.716%);区县碳排放在时间和空间上存在显著区域性差异,并表现出明显的空间集聚特征;成渝城市群作为高碳排放的集聚区域,其碳排放量在2012年前后呈现先增后减的趋势,川西地区区县的碳排放量则相对较低且持续增长。总体而言,整个川渝地区及其区县层面上的碳不平衡现象逐年改善。研究结果说明,精细化数据能更好地反映大范围内部的小区域异质性现象。 The Sichuan-Chongqing region,as an important leading area for development in the western part of China,is required to realize synergistic development of green and low-carbon initiatives with regional coordination.Scientifically exploring the regional differences of fine-scale carbon emissions in Sichuan and Chongqing is of great importance for carbon emission reduction.Utilizing a panel data model,based on the provincial carbon emissions and nighttime light data from 1997 to 2021,county-level carbon emission data were estimated.Meanwhile,employing ArcGIS software,the spatiotemporal variation trends of carbon emissions across 221 districts and counties in the Sichuan-Chongqing region were investigate.The results indicated that the constructed estimation model demonstrates a high level of accuracy(R^(2)=0.979,with an average absolute percentage error(MAPE)of 5.716%).The carbon emissions at the county level in the Sichuan-Chongqing region exhibit significant regional differences in both time and space,along with distinct spatial agglomeration characteristics.The Chengdu-Chongqing urban agglomeration,as a high-carbon emission area,the carbon emissions there show a trend of increasing followed by a decrease around 2012.In contrast,the carbon emissions in the western Sichuan counties are relatively low but continue to grow.Overall,the carbon imbalance at the county level within the entire Sichuan-Chongqing region or either of the two provinces is improving year by year.The study findings suggest that fine-grained data can better reflect localized heterogeneity within a large area.
作者 唐先腾 唐章英 宋超 王成武 汪宙峰 林小军 TANG Xian-teng;TANG Zhang-ying;SONG Chao;WANG Cheng-wu;WANG Zhou-feng;LIN Xiao-jun(School of Geoscience and Technology,Southwest Petroleum University,Chengdu Sichuan 610500,China;West China School of Public Health/West China Fourth Hospital,Sichuan University,Chengdu Sichuan 610041,China)
出处 《西华师范大学学报(自然科学版)》 2025年第4期358-366,共9页 Journal of China West Normal University(Natural Sciences)
基金 国家自然科学基金面上项目(42071379) 四川省科技计划资助项目(2023YFS0406)。
关键词 碳排放 夜间灯光 川渝地区 时空变化特征 空间自相关 carbon emission nighttime lighting Sichuan-Chongqing region spatio-temporal variation spatial autocorrelation
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