北京师范大学学报（自然科学版）2025，Vol.61Issue(2)：178-190,13.DOI:10.12202/j.0476-0301.2024108
CGE模型在低碳转型研究领域的应用态势
Application trends of CGE models in low-carbon transition research:a bibliometric analysis
摘要
Abstract
The visualization tool CiteSpace 6.2.R4 is used in this study to identify publication trends,author collaboration networks,journal distribution patterns,research hotspots and frontiers in CGE model-based studies on low-carbon transition.Differences are identified between China and other countries in using CGE models to analyze low-carbon transitions.It is found that,from 2013 to 2023,the total number of publications showed two phases of growth:slow growth and rapid growth.Currently,the use of CGE models to study low-carbon transition has become a prominent research topic.Related studies are published in core journals across multiple disciplines such as economics,environmental science,and energy,indicating widespread attention to this area of research.Research teams are found to be relatively stable,with significant collaborations among institutions,universities and research institutions in China and Japan have emerged as pivotal forces.Research hotspots are found focused on impacts of carbon emission reduction policies,renewable energy development,and pathways to carbon neutrality on socio-economic aspects.Emerging frontiers include power sector transformation and comprehensive assessment of carbon reduction benefits.Significant differences are found to exist between China and other countries in using CGE models to study low-carbon transition.These differences primarily manifest in data availability,policy environments,and energy structures.In the future,CGE models should focus on social equity,technological advancement,and interdisciplinary collaboration,to address evolving research demands and complexities of economic environment.关键词
CGE/低碳转型/CiteSpace/文献计量Key words
CGE/low-carbon transition/CiteSpace/bibliometrics分类
环境科学引用本文复制引用
张立英,崔琦,张力小,郝岩..CGE模型在低碳转型研究领域的应用态势[J].北京师范大学学报（自然科学版）,2025,61(2):178-190,13.基金项目
国家自然科学基金资助项目(52170175,52225902,72373163,72222020,72342005) （52170175,52225902,72373163,72222020,72342005）
北京市自然科学基金资助项目(9222016) （9222016）
