广东省碳排放时空特征及影响因素数据驱动分析[j]。

Q2 Environmental Science
Yi-Ming Ke, Yuan Gao, Ming Yuan, Wei Liu, Fang-Tong Liu
{"title":"广东省碳排放时空特征及影响因素数据驱动分析[j]。","authors":"Yi-Ming Ke, Yuan Gao, Ming Yuan, Wei Liu, Fang-Tong Liu","doi":"10.13227/j.hjkx.202403060","DOIUrl":null,"url":null,"abstract":"<p><p>Scientific analysis of carbon emission characteristics is a key link for precise policy implementation and orderly achievement of Carbon Peak and Carbon Neutrality. Taking 21 prefecture level cities in Guangdong Province as research objects, data including their economic activity, energy consumption, and population distribution from 2013 to 2022 was collected. First, the carbon emission accounting method was used to analyze the time changes and spatial distribution characteristics of carbon emissions in the past decade. Second, the principal component analysis and K-means method was used to reduce the dimensionality and cluster division for Guangdong urban characteristics. Third, the Generalized Schur Decomposition model was applied to analyze the influencing factors. Furthermore, carbon reduction strategies for four typical cities in Guangdong Province were proposed. The results showed that: ① From 2013 to 2022, the total carbon emissions in Guangdong Province continued to increase and showed a significant regional imbalance in its spatial distribution. The carbon emissions contribution in the Pearl River Delta region was as high as 42.50%, whereas that in northern Guangdong was the lowest. ② Each city in Guangdong Province performed differently in green development, economic development, and industrial development. All 21 cities could be broadly divided into four categories, namely, Demonstration City, Resource-dependent City, Traditional Industrial City, and Emission-reducing City, accounting for approximately 14.29%, 28.57%, 19.05%, and 38.09%, respectively. ③ Economic activities were the common driving factors for carbon emissions in all cities, whereas energy consumption and lifestyle were the core driving factors for carbon emissions in resource-dependent cities and traditional industrial cities. After the proposal of Carbon Peak and Carbon Neutrality, energy composition became a key driving force for demonstration cities and emission-reducing cities.</p>","PeriodicalId":35937,"journal":{"name":"环境科学","volume":"46 3","pages":"1482-1491"},"PeriodicalIF":0.0000,"publicationDate":"2025-03-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"[Data-driven Analysis on the Spatio-temporal Characteristics and Influencing Factors of Carbon Emissions in Guangdong Province].\",\"authors\":\"Yi-Ming Ke, Yuan Gao, Ming Yuan, Wei Liu, Fang-Tong Liu\",\"doi\":\"10.13227/j.hjkx.202403060\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><p>Scientific analysis of carbon emission characteristics is a key link for precise policy implementation and orderly achievement of Carbon Peak and Carbon Neutrality. Taking 21 prefecture level cities in Guangdong Province as research objects, data including their economic activity, energy consumption, and population distribution from 2013 to 2022 was collected. First, the carbon emission accounting method was used to analyze the time changes and spatial distribution characteristics of carbon emissions in the past decade. Second, the principal component analysis and K-means method was used to reduce the dimensionality and cluster division for Guangdong urban characteristics. Third, the Generalized Schur Decomposition model was applied to analyze the influencing factors. Furthermore, carbon reduction strategies for four typical cities in Guangdong Province were proposed. The results showed that: ① From 2013 to 2022, the total carbon emissions in Guangdong Province continued to increase and showed a significant regional imbalance in its spatial distribution. The carbon emissions contribution in the Pearl River Delta region was as high as 42.50%, whereas that in northern Guangdong was the lowest. ② Each city in Guangdong Province performed differently in green development, economic development, and industrial development. All 21 cities could be broadly divided into four categories, namely, Demonstration City, Resource-dependent City, Traditional Industrial City, and Emission-reducing City, accounting for approximately 14.29%, 28.57%, 19.05%, and 38.09%, respectively. ③ Economic activities were the common driving factors for carbon emissions in all cities, whereas energy consumption and lifestyle were the core driving factors for carbon emissions in resource-dependent cities and traditional industrial cities. After the proposal of Carbon Peak and Carbon Neutrality, energy composition became a key driving force for demonstration cities and emission-reducing cities.</p>\",\"PeriodicalId\":35937,\"journal\":{\"name\":\"环境科学\",\"volume\":\"46 3\",\"pages\":\"1482-1491\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2025-03-08\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"环境科学\",\"FirstCategoryId\":\"1087\",\"ListUrlMain\":\"https://doi.org/10.13227/j.hjkx.202403060\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q2\",\"JCRName\":\"Environmental Science\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"环境科学","FirstCategoryId":"1087","ListUrlMain":"https://doi.org/10.13227/j.hjkx.202403060","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"Environmental Science","Score":null,"Total":0}
引用次数: 0

摘要

科学分析碳排放特征是精准实施政策、有序实现碳峰值和碳中和的关键环节。以广东省21个地级市为研究对象,收集了2013 - 2022年广东省21个地级市的经济活动、能源消费、人口分布等数据。首先,采用碳排放核算方法,分析了近10年中国碳排放的时间变化和空间分布特征。其次,采用主成分分析和k均值方法对广东城市特征进行降维和聚类划分;第三,应用广义Schur分解模型对影响因素进行分析。在此基础上,提出了广东省4个典型城市的碳减排策略。结果表明:①2013 - 2022年,广东省碳排放总量持续增加,空间分布呈现明显的区域不平衡;珠三角地区碳排放贡献率高达42.50%,粤北地区碳排放贡献率最低。②广东省各城市在绿色发展、经济发展和产业发展方面表现各异。21个城市大致可分为示范城市、资源型城市、传统工业城市和减排型城市4类,占比分别约为14.29%、28.57%、19.05%和38.09%。③经济活动是各城市碳排放的共同驱动因素,而能源消费和生活方式是资源依赖型城市和传统工业城市碳排放的核心驱动因素。碳峰值和碳中和提出后,能源构成成为示范城市和减排城市发展的关键驱动力。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
[Data-driven Analysis on the Spatio-temporal Characteristics and Influencing Factors of Carbon Emissions in Guangdong Province].

Scientific analysis of carbon emission characteristics is a key link for precise policy implementation and orderly achievement of Carbon Peak and Carbon Neutrality. Taking 21 prefecture level cities in Guangdong Province as research objects, data including their economic activity, energy consumption, and population distribution from 2013 to 2022 was collected. First, the carbon emission accounting method was used to analyze the time changes and spatial distribution characteristics of carbon emissions in the past decade. Second, the principal component analysis and K-means method was used to reduce the dimensionality and cluster division for Guangdong urban characteristics. Third, the Generalized Schur Decomposition model was applied to analyze the influencing factors. Furthermore, carbon reduction strategies for four typical cities in Guangdong Province were proposed. The results showed that: ① From 2013 to 2022, the total carbon emissions in Guangdong Province continued to increase and showed a significant regional imbalance in its spatial distribution. The carbon emissions contribution in the Pearl River Delta region was as high as 42.50%, whereas that in northern Guangdong was the lowest. ② Each city in Guangdong Province performed differently in green development, economic development, and industrial development. All 21 cities could be broadly divided into four categories, namely, Demonstration City, Resource-dependent City, Traditional Industrial City, and Emission-reducing City, accounting for approximately 14.29%, 28.57%, 19.05%, and 38.09%, respectively. ③ Economic activities were the common driving factors for carbon emissions in all cities, whereas energy consumption and lifestyle were the core driving factors for carbon emissions in resource-dependent cities and traditional industrial cities. After the proposal of Carbon Peak and Carbon Neutrality, energy composition became a key driving force for demonstration cities and emission-reducing cities.

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
环境科学
环境科学 Environmental Science-Environmental Science (all)
CiteScore
4.40
自引率
0.00%
发文量
15329
期刊介绍:
×
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