Chao Huang , Sau Chung Fu , Ka Chung Chan , Chili Wu , Christopher Y.H. Chao
{"title":"评估中国 2030 年碳峰值目标:后 COVID-19 系统综述","authors":"Chao Huang , Sau Chung Fu , Ka Chung Chan , Chili Wu , Christopher Y.H. Chao","doi":"10.1016/j.rser.2024.115128","DOIUrl":null,"url":null,"abstract":"<div><div>Following China's 2020 announcement of its commitment to reach a carbon peak by 2030 and achieve carbon neutrality by 2060, considerable debate has emerged regarding the feasibility of the 2030 carbon peak target. To contribute to this discourse, this review adopts a narrative review, comprehensively analysing 73 publications in the domain of carbon emissions prediction in China post-2020. Moreover, the results show that a predominant view among studies is that China is poised to achieve its carbon peak target from 2027 to 2030, anticipating a peak emission range of approximately 11.60–13.17 Gt CO<sub>2</sub>e. Besides, this research provides a comprehensive analysis of the research methodologies, parameter selection, and scenario settings in this field. It offers readers a thorough overview of the area, helping potential researchers to quickly enter the field. Key findings include: (1) the grey model, the artificial intelligence model, the IPAT-derived model, and the system dynamics model are the predominant forecasting models, with the IPAT-derived model being favoured for the national and regional areas and system dynamics for the industry. (2) Scenario settings are typically structured on a 5-year basis, with 3–5 scenarios considered reasonable for policy recommendation as they provide multi-faceted analysis while avoiding information overload and resource wastage. (3) The definition of ‘Carbon Peak’ needs to be taken seriously. Additionally, it highlights current research deficiencies and future directions and provides policy recommendations vital for China's 2030 and 2060 targets.</div></div>","PeriodicalId":418,"journal":{"name":"Renewable and Sustainable Energy Reviews","volume":"209 ","pages":"Article 115128"},"PeriodicalIF":16.3000,"publicationDate":"2024-11-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Evaluating China's 2030 carbon peak goal: Post-COVID-19 systematic review\",\"authors\":\"Chao Huang , Sau Chung Fu , Ka Chung Chan , Chili Wu , Christopher Y.H. Chao\",\"doi\":\"10.1016/j.rser.2024.115128\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><div>Following China's 2020 announcement of its commitment to reach a carbon peak by 2030 and achieve carbon neutrality by 2060, considerable debate has emerged regarding the feasibility of the 2030 carbon peak target. To contribute to this discourse, this review adopts a narrative review, comprehensively analysing 73 publications in the domain of carbon emissions prediction in China post-2020. Moreover, the results show that a predominant view among studies is that China is poised to achieve its carbon peak target from 2027 to 2030, anticipating a peak emission range of approximately 11.60–13.17 Gt CO<sub>2</sub>e. Besides, this research provides a comprehensive analysis of the research methodologies, parameter selection, and scenario settings in this field. It offers readers a thorough overview of the area, helping potential researchers to quickly enter the field. Key findings include: (1) the grey model, the artificial intelligence model, the IPAT-derived model, and the system dynamics model are the predominant forecasting models, with the IPAT-derived model being favoured for the national and regional areas and system dynamics for the industry. (2) Scenario settings are typically structured on a 5-year basis, with 3–5 scenarios considered reasonable for policy recommendation as they provide multi-faceted analysis while avoiding information overload and resource wastage. (3) The definition of ‘Carbon Peak’ needs to be taken seriously. Additionally, it highlights current research deficiencies and future directions and provides policy recommendations vital for China's 2030 and 2060 targets.</div></div>\",\"PeriodicalId\":418,\"journal\":{\"name\":\"Renewable and Sustainable Energy Reviews\",\"volume\":\"209 \",\"pages\":\"Article 115128\"},\"PeriodicalIF\":16.3000,\"publicationDate\":\"2024-11-28\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Renewable and Sustainable Energy Reviews\",\"FirstCategoryId\":\"1\",\"ListUrlMain\":\"https://www.sciencedirect.com/science/article/pii/S1364032124008542\",\"RegionNum\":1,\"RegionCategory\":\"工程技术\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"ENERGY & FUELS\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Renewable and Sustainable Energy Reviews","FirstCategoryId":"1","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S1364032124008542","RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"ENERGY & FUELS","Score":null,"Total":0}
Following China's 2020 announcement of its commitment to reach a carbon peak by 2030 and achieve carbon neutrality by 2060, considerable debate has emerged regarding the feasibility of the 2030 carbon peak target. To contribute to this discourse, this review adopts a narrative review, comprehensively analysing 73 publications in the domain of carbon emissions prediction in China post-2020. Moreover, the results show that a predominant view among studies is that China is poised to achieve its carbon peak target from 2027 to 2030, anticipating a peak emission range of approximately 11.60–13.17 Gt CO2e. Besides, this research provides a comprehensive analysis of the research methodologies, parameter selection, and scenario settings in this field. It offers readers a thorough overview of the area, helping potential researchers to quickly enter the field. Key findings include: (1) the grey model, the artificial intelligence model, the IPAT-derived model, and the system dynamics model are the predominant forecasting models, with the IPAT-derived model being favoured for the national and regional areas and system dynamics for the industry. (2) Scenario settings are typically structured on a 5-year basis, with 3–5 scenarios considered reasonable for policy recommendation as they provide multi-faceted analysis while avoiding information overload and resource wastage. (3) The definition of ‘Carbon Peak’ needs to be taken seriously. Additionally, it highlights current research deficiencies and future directions and provides policy recommendations vital for China's 2030 and 2060 targets.
期刊介绍:
The mission of Renewable and Sustainable Energy Reviews is to disseminate the most compelling and pertinent critical insights in renewable and sustainable energy, fostering collaboration among the research community, private sector, and policy and decision makers. The journal aims to exchange challenges, solutions, innovative concepts, and technologies, contributing to sustainable development, the transition to a low-carbon future, and the attainment of emissions targets outlined by the United Nations Framework Convention on Climate Change.
Renewable and Sustainable Energy Reviews publishes a diverse range of content, including review papers, original research, case studies, and analyses of new technologies, all featuring a substantial review component such as critique, comparison, or analysis. Introducing a distinctive paper type, Expert Insights, the journal presents commissioned mini-reviews authored by field leaders, addressing topics of significant interest. Case studies undergo consideration only if they showcase the work's applicability to other regions or contribute valuable insights to the broader field of renewable and sustainable energy. Notably, a bibliographic or literature review lacking critical analysis is deemed unsuitable for publication.