Research on driving mechanism and prediction of electric power carbon emission in Gansu Province under dual-carbon target
Abstract The electric power industry is a key industry for the country to achieve the double carbon target. Its low carbon development has a double effect on this industry and helps other industries to achieve the carbon peak target. This paper firstly uses the IPCC inventory method to calculate car...
| Main Authors: | , , , , , |
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| Format: | Article |
| Language: | English |
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Nature Portfolio
2024-03-01
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| Series: | Scientific Reports |
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| Online Access: | https://doi.org/10.1038/s41598-024-55721-2 |
| _version_ | 1797259363659808768 |
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| author | Fuwei Qiao Qinzhe Yang Wei Shi Xuedi Yang Guanwen Ouyang Lulu Zhao |
| author_facet | Fuwei Qiao Qinzhe Yang Wei Shi Xuedi Yang Guanwen Ouyang Lulu Zhao |
| author_sort | Fuwei Qiao |
| collection | DOAJ |
| description | Abstract The electric power industry is a key industry for the country to achieve the double carbon target. Its low carbon development has a double effect on this industry and helps other industries to achieve the carbon peak target. This paper firstly uses the IPCC inventory method to calculate carbon emissions in the production phase of the power industry in Gansu Province from 2000 to 2019, followed by the ridge regression method and the STIRPAT model to analyse the quantitative impact of six major drivers on carbon emissions, and finally, the scenario analysis method is used to forecast carbon emissions in this phase. The results show that the carbon emissions of Gansu Province show a trend of rising and then falling, and reached a peak of 65.66 million tons in 2013. For every 1% increase in population effect, urbanisation level, affluence, clean energy generation share, technology level and industrial structure, carbon emissions will grow by 4.939%, 0.625%, 0.224%, − 0.259%, 0.063% and 0.022% respectively. Because of the clean energy advantage in Gansu Province, the low-carbon development scenario will continue to have low carbon emissions during the scenario cycle, which can be reduced to 53.454 million tons in 2030; the baseline scenario will achieve a carbon peak in 2025, with a peak of 62.627 million tons; the economic development scenario has not achieved carbon peak during the scenario cycle, and carbon emissions will increase to 73.223 million tons in 2030. |
| first_indexed | 2024-04-24T23:08:15Z |
| format | Article |
| id | doaj.art-850c1cd3207e49e4b7f07178e76970af |
| institution | Directory Open Access Journal |
| issn | 2045-2322 |
| language | English |
| last_indexed | 2024-04-24T23:08:15Z |
| publishDate | 2024-03-01 |
| publisher | Nature Portfolio |
| record_format | Article |
| series | Scientific Reports |
| spelling | doaj.art-850c1cd3207e49e4b7f07178e76970af2024-03-17T12:23:32ZengNature PortfolioScientific Reports2045-23222024-03-011411910.1038/s41598-024-55721-2Research on driving mechanism and prediction of electric power carbon emission in Gansu Province under dual-carbon targetFuwei Qiao0Qinzhe Yang1Wei Shi2Xuedi Yang3Guanwen Ouyang4Lulu Zhao5College of Economics, Northwest Normal UniversityCollege of Economics, Northwest Normal UniversityCollege of Geography and Environmental Sciences, Northwest Normal UniversityCollege of Resources and Environment, Lanzhou UniversityCollege of Economics, Northwest Normal UniversityCollege of Economics, Northwest Normal UniversityAbstract The electric power industry is a key industry for the country to achieve the double carbon target. Its low carbon development has a double effect on this industry and helps other industries to achieve the carbon peak target. This paper firstly uses the IPCC inventory method to calculate carbon emissions in the production phase of the power industry in Gansu Province from 2000 to 2019, followed by the ridge regression method and the STIRPAT model to analyse the quantitative impact of six major drivers on carbon emissions, and finally, the scenario analysis method is used to forecast carbon emissions in this phase. The results show that the carbon emissions of Gansu Province show a trend of rising and then falling, and reached a peak of 65.66 million tons in 2013. For every 1% increase in population effect, urbanisation level, affluence, clean energy generation share, technology level and industrial structure, carbon emissions will grow by 4.939%, 0.625%, 0.224%, − 0.259%, 0.063% and 0.022% respectively. Because of the clean energy advantage in Gansu Province, the low-carbon development scenario will continue to have low carbon emissions during the scenario cycle, which can be reduced to 53.454 million tons in 2030; the baseline scenario will achieve a carbon peak in 2025, with a peak of 62.627 million tons; the economic development scenario has not achieved carbon peak during the scenario cycle, and carbon emissions will increase to 73.223 million tons in 2030.https://doi.org/10.1038/s41598-024-55721-2Power industryCarbon emissionsRidge regressionScenario prediction |
| spellingShingle | Fuwei Qiao Qinzhe Yang Wei Shi Xuedi Yang Guanwen Ouyang Lulu Zhao Research on driving mechanism and prediction of electric power carbon emission in Gansu Province under dual-carbon target Scientific Reports Power industry Carbon emissions Ridge regression Scenario prediction |
| title | Research on driving mechanism and prediction of electric power carbon emission in Gansu Province under dual-carbon target |
| title_full | Research on driving mechanism and prediction of electric power carbon emission in Gansu Province under dual-carbon target |
| title_fullStr | Research on driving mechanism and prediction of electric power carbon emission in Gansu Province under dual-carbon target |
| title_full_unstemmed | Research on driving mechanism and prediction of electric power carbon emission in Gansu Province under dual-carbon target |
| title_short | Research on driving mechanism and prediction of electric power carbon emission in Gansu Province under dual-carbon target |
| title_sort | research on driving mechanism and prediction of electric power carbon emission in gansu province under dual carbon target |
| topic | Power industry Carbon emissions Ridge regression Scenario prediction |
| url | https://doi.org/10.1038/s41598-024-55721-2 |
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