Projection of regional carbon emissions and analysis of emission reduction potential under multiple scenarios
At the general debate of the 75th session of the United Nations General Assembly, president Xi Jinping proposed to reach ”carbon peak” by 2030 and strive to achieve the ”carbon neutrality” by 2060. Research on carbon emission projections is of positive significance to facilitate the effective applic...
| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
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Elsevier
2023-09-01
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| Series: | Energy Reports |
| Subjects: | |
| Online Access: | http://www.sciencedirect.com/science/article/pii/S2352484723004833 |
| _version_ | 1827824095352324096 |
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| author | Jingjing Zhai Lihui She Sipeng Hao Haoming Liu |
| author_facet | Jingjing Zhai Lihui She Sipeng Hao Haoming Liu |
| author_sort | Jingjing Zhai |
| collection | DOAJ |
| description | At the general debate of the 75th session of the United Nations General Assembly, president Xi Jinping proposed to reach ”carbon peak” by 2030 and strive to achieve the ”carbon neutrality” by 2060. Research on carbon emission projections is of positive significance to facilitate the effective application of ”double carbon” in China. Therefore, this paper proposes a regional carbon emission projection method. Firstly, based on the regional resource endowment and historical data on energy consumption, this paper forecasts the energy structure of each sector in the region through the Markov model and the energy demand of each sector in the region through the LEAP model. Then, the CO2 emission factor of each energy source is calculated. Finally, the projection of regional CO2 emissions under different policy and technology scenarios is provided by considering the influence of different factors on future regional carbon emissions, and the emission reduction potential is analyzed based on the projection results. To check the effectiveness of the presented method, this paper carries out a case study of regional CO2 emission in a city in China and analyzes the emission decrease effect of each proposed initiative according to the projected results. The results of the case study demonstrate that the presented method can effectively assess the regional CO2 emissions and the reduction potential of different emission reduction measures. |
| first_indexed | 2024-03-12T02:22:05Z |
| format | Article |
| id | doaj.art-5c8262bca7ff49bdbae53316319bd680 |
| institution | Directory Open Access Journal |
| issn | 2352-4847 |
| language | English |
| last_indexed | 2024-03-12T02:22:05Z |
| publishDate | 2023-09-01 |
| publisher | Elsevier |
| record_format | Article |
| series | Energy Reports |
| spelling | doaj.art-5c8262bca7ff49bdbae53316319bd6802023-09-06T04:51:49ZengElsevierEnergy Reports2352-48472023-09-019753761Projection of regional carbon emissions and analysis of emission reduction potential under multiple scenariosJingjing Zhai0Lihui She1Sipeng Hao2Haoming Liu3School of Electric Power Engineering, Nanjing Institute of Technology, Jiangsu, Nanjing 211167, ChinaCollege of Energy and Electrical Engineering, Hohai University, Jiangsu, Nanjing 211100, ChinaSchool of Electric Power Engineering, Nanjing Institute of Technology, Jiangsu, Nanjing 211167, ChinaCollege of Energy and Electrical Engineering, Hohai University, Jiangsu, Nanjing 211100, China; Corresponding author.At the general debate of the 75th session of the United Nations General Assembly, president Xi Jinping proposed to reach ”carbon peak” by 2030 and strive to achieve the ”carbon neutrality” by 2060. Research on carbon emission projections is of positive significance to facilitate the effective application of ”double carbon” in China. Therefore, this paper proposes a regional carbon emission projection method. Firstly, based on the regional resource endowment and historical data on energy consumption, this paper forecasts the energy structure of each sector in the region through the Markov model and the energy demand of each sector in the region through the LEAP model. Then, the CO2 emission factor of each energy source is calculated. Finally, the projection of regional CO2 emissions under different policy and technology scenarios is provided by considering the influence of different factors on future regional carbon emissions, and the emission reduction potential is analyzed based on the projection results. To check the effectiveness of the presented method, this paper carries out a case study of regional CO2 emission in a city in China and analyzes the emission decrease effect of each proposed initiative according to the projected results. The results of the case study demonstrate that the presented method can effectively assess the regional CO2 emissions and the reduction potential of different emission reduction measures.http://www.sciencedirect.com/science/article/pii/S2352484723004833Carbon emission predictionCarbon reductionScenario predictionMarkov modelLEAP model |
| spellingShingle | Jingjing Zhai Lihui She Sipeng Hao Haoming Liu Projection of regional carbon emissions and analysis of emission reduction potential under multiple scenarios Energy Reports Carbon emission prediction Carbon reduction Scenario prediction Markov model LEAP model |
| title | Projection of regional carbon emissions and analysis of emission reduction potential under multiple scenarios |
| title_full | Projection of regional carbon emissions and analysis of emission reduction potential under multiple scenarios |
| title_fullStr | Projection of regional carbon emissions and analysis of emission reduction potential under multiple scenarios |
| title_full_unstemmed | Projection of regional carbon emissions and analysis of emission reduction potential under multiple scenarios |
| title_short | Projection of regional carbon emissions and analysis of emission reduction potential under multiple scenarios |
| title_sort | projection of regional carbon emissions and analysis of emission reduction potential under multiple scenarios |
| topic | Carbon emission prediction Carbon reduction Scenario prediction Markov model LEAP model |
| url | http://www.sciencedirect.com/science/article/pii/S2352484723004833 |
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