生态学报2025，Vol.45Issue(24)：12401-12415,15.DOI:10.20103/j.stxb.202504250991
基于多源数据融合的辽宁省旅游业碳排放脱钩效应
Research on the decoupling effect of tourism carbon emissions in Liaoning Province based on multi-source data fusion
摘要
Abstract
Under the strategic background of"carbon peak and carbon neutrality",clarifying the decoupling effect and driving mechanism between tourism economic growth and carbon emissions was a key link in achieving the green and low-carbon transition of the tourism industry.To address the existing problems of rough carbon emission measurement and neglected inter-city differences,this paper selected Liaoning Province from 2004 to 2022 as the research scope and innovatively combined the"bottom-up"tourism carbon accounting method with the entropy weight method to accurately calculate tourism-related emissions.Meanwhile,based on nighttime light remote sensing data and urban tourism characteristic data such as the total number of tourists,total tourism revenue,and the number of 4A and 5A scenic spots,the study dissected the carbon emission contributions of different cities.Moreover,based on the Tapio model and GTWR model,the decoupling effect and driving mechanism of carbon emissions from the tourism industry and economic growth were analyzed in depth from the spatiotemporal dimension.The results indicated that:(1)The tourism carbon emissions in Liaoning Province showed a trend of first gradually increasing and then significantly decreasing.The peak was reached in 2014 at 3.8223 million tons,and then decreased by 47.95%from 2020 to 2022.There were significant differences in carbon emissions among various sectors of the tourism industry,with tourism transportation accounting for 76.82%.Spatially,the emissions form a bimodal structure centered on Shenyang and Dalian,decreasing outward from these centers,and the eastern part was significantly higher than the western part.(2)The carbon emissions of Liaoning Province's tourism industry overall exhibited a weak decoupling state with fluctuating changes,achieving a positive situation where the growth of the tourism economy outpaced the growth of tourism carbon emissions.In 2019,the decoupling effect was the best,with 12 cities achieving strong decoupling.In 2022,the decoupling state was the worst,with 8 cities showing weak negative decoupling,indicating an adverse situation.(3)The decoupling trend of carbon emissions in Liaoning Province's tourism industry was the result of multiple factors working together.Urbanization level,residents'consumption capacity,and economic development significantly promoted decoupling,with average regression coefficients of 1.248,0.209,and 0.108,respectively.In contrast,tourism energy consumption and industrial structure had an inhibitory effect.This study broke through the limitations of scale and improved the accuracy of carbon emission calculations,providing support for Liaoning Province to formulate differentiated emission-reduction policies and build a low-carbon tourism system.关键词
旅游业碳排放/脱钩效应/夜光遥感/熵权法/时空地理加权回归Key words
tourism carbon emissions/decoupling effect/nighttime light remote sensing/entropy weight method/geographically and temporally weighted regression引用本文复制引用
JIANG Xuemei,CAO Yongqiang,YAO Jiaqi..基于多源数据融合的辽宁省旅游业碳排放脱钩效应[J].生态学报,2025,45(24):12401-12415,15.基金项目
国家自然科学基金项目(52379021) （52379021）
