{"title":"基于复杂系统模型的英国气候变化政策综合研究:2001年至2020年的证据","authors":"Weiyi Jiang , Yihang Hong , Chun Xia Yang","doi":"10.1016/j.eswa.2025.130073","DOIUrl":null,"url":null,"abstract":"<div><div>The United Kingdom is a highly industrialized and economically developed country, with greenhouse gas (GHGs) emissions historically well above the global average, thereby significantly contributing to global climate change. Over the past two decades, the UK government has introduced a range of measures to mitigate emissions, such as enacting legislation and employing market-based mechanisms. Between 2001 and 2020, the number of climate policies issued by the government and think tanks increased by 73 and 171 times, respectively, accompanied by a 43% reduction in GHGs and a 44% reduction in CO<sub>2</sub> emissions. Although prior research has identified a negative correlation between policy quantity and emissions, the relative importance of specific policy themes remains unclear. In this study, we employed the Latent Dirichlet Allocation (LDA) model to identify key thematic topics within UK climate policies published from 2001 to 2020. Subsequently, Partial Least Squares (PLS) regression was applied to quantify the contribution of each policy theme to reductions in GHGs emissions. Our quantitative results show that policies emphasizing themes such as “climate”, “carbon”, “greenhouse”, “gas”, and “low” accounted for 73.3% of the total emission reduction. Furthermore, we modeled the policy system as a complex network to assess structural interactions. These findings provide actionable insights for policymakers seeking to design more effective climate strategies.</div></div>","PeriodicalId":50461,"journal":{"name":"Expert Systems with Applications","volume":"299 ","pages":"Article 130073"},"PeriodicalIF":7.5000,"publicationDate":"2025-10-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"A comprehensive study of UK climate change policies based on complex systems modeling: Evidence from 2001 to 2020\",\"authors\":\"Weiyi Jiang , Yihang Hong , Chun Xia Yang\",\"doi\":\"10.1016/j.eswa.2025.130073\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><div>The United Kingdom is a highly industrialized and economically developed country, with greenhouse gas (GHGs) emissions historically well above the global average, thereby significantly contributing to global climate change. Over the past two decades, the UK government has introduced a range of measures to mitigate emissions, such as enacting legislation and employing market-based mechanisms. Between 2001 and 2020, the number of climate policies issued by the government and think tanks increased by 73 and 171 times, respectively, accompanied by a 43% reduction in GHGs and a 44% reduction in CO<sub>2</sub> emissions. Although prior research has identified a negative correlation between policy quantity and emissions, the relative importance of specific policy themes remains unclear. In this study, we employed the Latent Dirichlet Allocation (LDA) model to identify key thematic topics within UK climate policies published from 2001 to 2020. Subsequently, Partial Least Squares (PLS) regression was applied to quantify the contribution of each policy theme to reductions in GHGs emissions. Our quantitative results show that policies emphasizing themes such as “climate”, “carbon”, “greenhouse”, “gas”, and “low” accounted for 73.3% of the total emission reduction. Furthermore, we modeled the policy system as a complex network to assess structural interactions. These findings provide actionable insights for policymakers seeking to design more effective climate strategies.</div></div>\",\"PeriodicalId\":50461,\"journal\":{\"name\":\"Expert Systems with Applications\",\"volume\":\"299 \",\"pages\":\"Article 130073\"},\"PeriodicalIF\":7.5000,\"publicationDate\":\"2025-10-21\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Expert Systems with Applications\",\"FirstCategoryId\":\"94\",\"ListUrlMain\":\"https://www.sciencedirect.com/science/article/pii/S0957417425036899\",\"RegionNum\":1,\"RegionCategory\":\"计算机科学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Expert Systems with Applications","FirstCategoryId":"94","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S0957417425036899","RegionNum":1,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE","Score":null,"Total":0}
A comprehensive study of UK climate change policies based on complex systems modeling: Evidence from 2001 to 2020
The United Kingdom is a highly industrialized and economically developed country, with greenhouse gas (GHGs) emissions historically well above the global average, thereby significantly contributing to global climate change. Over the past two decades, the UK government has introduced a range of measures to mitigate emissions, such as enacting legislation and employing market-based mechanisms. Between 2001 and 2020, the number of climate policies issued by the government and think tanks increased by 73 and 171 times, respectively, accompanied by a 43% reduction in GHGs and a 44% reduction in CO2 emissions. Although prior research has identified a negative correlation between policy quantity and emissions, the relative importance of specific policy themes remains unclear. In this study, we employed the Latent Dirichlet Allocation (LDA) model to identify key thematic topics within UK climate policies published from 2001 to 2020. Subsequently, Partial Least Squares (PLS) regression was applied to quantify the contribution of each policy theme to reductions in GHGs emissions. Our quantitative results show that policies emphasizing themes such as “climate”, “carbon”, “greenhouse”, “gas”, and “low” accounted for 73.3% of the total emission reduction. Furthermore, we modeled the policy system as a complex network to assess structural interactions. These findings provide actionable insights for policymakers seeking to design more effective climate strategies.
期刊介绍:
Expert Systems With Applications is an international journal dedicated to the exchange of information on expert and intelligent systems used globally in industry, government, and universities. The journal emphasizes original papers covering the design, development, testing, implementation, and management of these systems, offering practical guidelines. It spans various sectors such as finance, engineering, marketing, law, project management, information management, medicine, and more. The journal also welcomes papers on multi-agent systems, knowledge management, neural networks, knowledge discovery, data mining, and other related areas, excluding applications to military/defense systems.