Wei Liu , Zhijie Jia , Meng Du , Zhanfeng Dong , Jieyu Pan , Qinrui Li , Linyan Pan , Chris Umole
{"title":"四川省最终能源消费产生的CO2排放影响因素及贡献分析","authors":"Wei Liu , Zhijie Jia , Meng Du , Zhanfeng Dong , Jieyu Pan , Qinrui Li , Linyan Pan , Chris Umole","doi":"10.1016/j.regsus.2022.11.006","DOIUrl":null,"url":null,"abstract":"<div><p>Within the context of CO<sub>2</sub> emission peaking and carbon neutrality, the study of CO<sub>2</sub> emissions at the provincial level is few. Sichuan Province in China has not only superior clean energy resources endowment but also great potential for the reduction of CO<sub>2</sub> emissions. Therefore, using logarithmic mean Divisia index (LMDI) model to analysis the influence degree of different influencing factors on CO<sub>2</sub> emissions from final energy consumption in Sichuan Province, so as to formulate corresponding emission reduction countermeasures from different paths according to the influencing factors. Based on the data of final energy consumption in Sichuan Province from 2010 to 2019, we calculated CO<sub>2</sub> emission by the indirect emission calculation method. The influencing factors of CO<sub>2</sub> emissions originating from final energy consumption in Sichuan Province were decomposed into population size, economic development, industrial structure, energy consumption intensity, and energy consumption structure by the Kaya–logarithmic mean Divisia index (LMDI) decomposition model. At the same time, grey correlation analysis was used to identify the correlation between CO<sub>2</sub> emissions originating from final energy consumption and the influencing factors in Sichuan Province. The results showed that population size, economic development and energy consumption structure have positive contributions to CO<sub>2</sub> emissions from final energy consumption in Sichuan Province, and economic development has a significant contribution to CO<sub>2</sub> emissions from final energy consumption, with a contribution rate of 519.11%. The industrial structure and energy consumption intensity have negative contributions to CO<sub>2</sub> emissions in Sichuan Province, and both of them have significant contributions, among which the contribution rate of energy consumption structure was 325.96%. From the perspective of industrial structure, secondary industry makes significant contributions and will maintain a restraining effect; from the perspective of energy consumption structure, industry sector has a significant contribution. The results of this paper are conducive to the implementation of carbon emission reduction policies in Sichuan Province.</p></div>","PeriodicalId":34395,"journal":{"name":"Regional Sustainability","volume":"3 4","pages":"Pages 356-372"},"PeriodicalIF":0.0000,"publicationDate":"2022-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S2666660X22000688/pdfft?md5=2c924392cdc572e8636af26459b0f031&pid=1-s2.0-S2666660X22000688-main.pdf","citationCount":"3","resultStr":"{\"title\":\"Influencing factors and contribution analysis of CO2 emissions originating from final energy consumption in Sichuan Province, China\",\"authors\":\"Wei Liu , Zhijie Jia , Meng Du , Zhanfeng Dong , Jieyu Pan , Qinrui Li , Linyan Pan , Chris Umole\",\"doi\":\"10.1016/j.regsus.2022.11.006\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><p>Within the context of CO<sub>2</sub> emission peaking and carbon neutrality, the study of CO<sub>2</sub> emissions at the provincial level is few. Sichuan Province in China has not only superior clean energy resources endowment but also great potential for the reduction of CO<sub>2</sub> emissions. Therefore, using logarithmic mean Divisia index (LMDI) model to analysis the influence degree of different influencing factors on CO<sub>2</sub> emissions from final energy consumption in Sichuan Province, so as to formulate corresponding emission reduction countermeasures from different paths according to the influencing factors. Based on the data of final energy consumption in Sichuan Province from 2010 to 2019, we calculated CO<sub>2</sub> emission by the indirect emission calculation method. The influencing factors of CO<sub>2</sub> emissions originating from final energy consumption in Sichuan Province were decomposed into population size, economic development, industrial structure, energy consumption intensity, and energy consumption structure by the Kaya–logarithmic mean Divisia index (LMDI) decomposition model. At the same time, grey correlation analysis was used to identify the correlation between CO<sub>2</sub> emissions originating from final energy consumption and the influencing factors in Sichuan Province. The results showed that population size, economic development and energy consumption structure have positive contributions to CO<sub>2</sub> emissions from final energy consumption in Sichuan Province, and economic development has a significant contribution to CO<sub>2</sub> emissions from final energy consumption, with a contribution rate of 519.11%. The industrial structure and energy consumption intensity have negative contributions to CO<sub>2</sub> emissions in Sichuan Province, and both of them have significant contributions, among which the contribution rate of energy consumption structure was 325.96%. From the perspective of industrial structure, secondary industry makes significant contributions and will maintain a restraining effect; from the perspective of energy consumption structure, industry sector has a significant contribution. The results of this paper are conducive to the implementation of carbon emission reduction policies in Sichuan Province.</p></div>\",\"PeriodicalId\":34395,\"journal\":{\"name\":\"Regional Sustainability\",\"volume\":\"3 4\",\"pages\":\"Pages 356-372\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2022-12-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://www.sciencedirect.com/science/article/pii/S2666660X22000688/pdfft?md5=2c924392cdc572e8636af26459b0f031&pid=1-s2.0-S2666660X22000688-main.pdf\",\"citationCount\":\"3\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Regional Sustainability\",\"FirstCategoryId\":\"95\",\"ListUrlMain\":\"https://www.sciencedirect.com/science/article/pii/S2666660X22000688\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"Social Sciences\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Regional Sustainability","FirstCategoryId":"95","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S2666660X22000688","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"Social Sciences","Score":null,"Total":0}
Influencing factors and contribution analysis of CO2 emissions originating from final energy consumption in Sichuan Province, China
Within the context of CO2 emission peaking and carbon neutrality, the study of CO2 emissions at the provincial level is few. Sichuan Province in China has not only superior clean energy resources endowment but also great potential for the reduction of CO2 emissions. Therefore, using logarithmic mean Divisia index (LMDI) model to analysis the influence degree of different influencing factors on CO2 emissions from final energy consumption in Sichuan Province, so as to formulate corresponding emission reduction countermeasures from different paths according to the influencing factors. Based on the data of final energy consumption in Sichuan Province from 2010 to 2019, we calculated CO2 emission by the indirect emission calculation method. The influencing factors of CO2 emissions originating from final energy consumption in Sichuan Province were decomposed into population size, economic development, industrial structure, energy consumption intensity, and energy consumption structure by the Kaya–logarithmic mean Divisia index (LMDI) decomposition model. At the same time, grey correlation analysis was used to identify the correlation between CO2 emissions originating from final energy consumption and the influencing factors in Sichuan Province. The results showed that population size, economic development and energy consumption structure have positive contributions to CO2 emissions from final energy consumption in Sichuan Province, and economic development has a significant contribution to CO2 emissions from final energy consumption, with a contribution rate of 519.11%. The industrial structure and energy consumption intensity have negative contributions to CO2 emissions in Sichuan Province, and both of them have significant contributions, among which the contribution rate of energy consumption structure was 325.96%. From the perspective of industrial structure, secondary industry makes significant contributions and will maintain a restraining effect; from the perspective of energy consumption structure, industry sector has a significant contribution. The results of this paper are conducive to the implementation of carbon emission reduction policies in Sichuan Province.