中国各省碳中和准备指数的测算

Chuanbo Xu, Jiaming He, Junhao Wu, Shaoze Li, Xinying Li
{"title":"中国各省碳中和准备指数的测算","authors":"Chuanbo Xu, Jiaming He, Junhao Wu, Shaoze Li, Xinying Li","doi":"10.2139/ssrn.3898488","DOIUrl":null,"url":null,"abstract":"In this study, an index namely Carbon-Neutral Readiness Index (CNRI) is designed to compare the carbon-neutral readiness among China’s 30 provinces. The CNRI is decomposed into a hierarchical structure that combines four dimensions and associated 19 quantitative indicators. Several indicators are newly proposed such as ‘per capita carbon trading volume’, ‘maturity degree of carbon capture and storage deployment’, and ‘percentage of ocean cover’. To determine the importance weight of indicators, an improved Criteria Importance Though Intercriteria Correlation (CRITIC) approach is developed by considering the correlation between indicators. Then, the weighted averaging operator is used to evaluate the CNRI of China’s provinces. Our results indicate that: 1) the correlation between most indicators is significant, of which 3.51% has an extremely strong relationship; 2) the indicator ‘per capita steel production’ owns the largest weight (0.113); 3) Beijing provinces ranks first, followed by Sichuan and Yunnan province; 4) the spatial differences of CNPI show a pattern of ‘strong in the central and south provinces, week in north provinces’; 5) the sensitive analysis reveals that the ranking results are relatively robust.","PeriodicalId":9858,"journal":{"name":"Chemical Engineering (Engineering) eJournal","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2021-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Measuring Carbon-Neutral Readiness Index of China's Provinces\",\"authors\":\"Chuanbo Xu, Jiaming He, Junhao Wu, Shaoze Li, Xinying Li\",\"doi\":\"10.2139/ssrn.3898488\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In this study, an index namely Carbon-Neutral Readiness Index (CNRI) is designed to compare the carbon-neutral readiness among China’s 30 provinces. The CNRI is decomposed into a hierarchical structure that combines four dimensions and associated 19 quantitative indicators. Several indicators are newly proposed such as ‘per capita carbon trading volume’, ‘maturity degree of carbon capture and storage deployment’, and ‘percentage of ocean cover’. To determine the importance weight of indicators, an improved Criteria Importance Though Intercriteria Correlation (CRITIC) approach is developed by considering the correlation between indicators. Then, the weighted averaging operator is used to evaluate the CNRI of China’s provinces. Our results indicate that: 1) the correlation between most indicators is significant, of which 3.51% has an extremely strong relationship; 2) the indicator ‘per capita steel production’ owns the largest weight (0.113); 3) Beijing provinces ranks first, followed by Sichuan and Yunnan province; 4) the spatial differences of CNPI show a pattern of ‘strong in the central and south provinces, week in north provinces’; 5) the sensitive analysis reveals that the ranking results are relatively robust.\",\"PeriodicalId\":9858,\"journal\":{\"name\":\"Chemical Engineering (Engineering) eJournal\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2021-01-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Chemical Engineering (Engineering) eJournal\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.2139/ssrn.3898488\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Chemical Engineering (Engineering) eJournal","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.2139/ssrn.3898488","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0

摘要

本研究设计了碳中和准备度指数(CNRI)来比较中国30个省份的碳中和准备度。CNRI被分解成一个由四个维度和相关的19个定量指标组成的层次结构。新提出了几个指标,如“人均碳交易量”、“碳捕获和封存部署的成熟度”和“海洋覆盖百分比”。为了确定指标的重要性权重,通过考虑指标之间的相关性,提出了一种改进的标准重要性-标准间相关性(critical)方法。然后,采用加权平均算子对中国各省的CNRI进行评价。结果表明:1)大部分指标之间的相关性显著,其中3.51%的指标相关性极强;2)“人均钢铁产量”指标权重最大(0.113);3)北京市排名第一,四川、云南次之;④CNPI的空间差异呈现“中南部省份强,北部省份弱”的格局;5)敏感性分析表明,排名结果具有较强的鲁棒性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Measuring Carbon-Neutral Readiness Index of China's Provinces
In this study, an index namely Carbon-Neutral Readiness Index (CNRI) is designed to compare the carbon-neutral readiness among China’s 30 provinces. The CNRI is decomposed into a hierarchical structure that combines four dimensions and associated 19 quantitative indicators. Several indicators are newly proposed such as ‘per capita carbon trading volume’, ‘maturity degree of carbon capture and storage deployment’, and ‘percentage of ocean cover’. To determine the importance weight of indicators, an improved Criteria Importance Though Intercriteria Correlation (CRITIC) approach is developed by considering the correlation between indicators. Then, the weighted averaging operator is used to evaluate the CNRI of China’s provinces. Our results indicate that: 1) the correlation between most indicators is significant, of which 3.51% has an extremely strong relationship; 2) the indicator ‘per capita steel production’ owns the largest weight (0.113); 3) Beijing provinces ranks first, followed by Sichuan and Yunnan province; 4) the spatial differences of CNPI show a pattern of ‘strong in the central and south provinces, week in north provinces’; 5) the sensitive analysis reveals that the ranking results are relatively robust.
求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
来源期刊
自引率
0.00%
发文量
0
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术官方微信