Temporal-spatial evolution and formation mechanism of energy consumption carbon footprint at county scale in the Yellow River Basin
Abstract The development and implementation of county carbon control action plans in the Yellow River Basin (YRB) are crucial for realizing the “dual carbon” goals and modernizing national governance. Utilizing remote sensing data from 2001 to 2020, this study constructs a light-carbon conversion mo...
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Nature Portfolio
2025-01-01
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| Series: | Scientific Reports |
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| Online Access: | https://doi.org/10.1038/s41598-025-86383-3 |
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| author | Liyan Zhang Mei Song Yan Gao |
| author_facet | Liyan Zhang Mei Song Yan Gao |
| author_sort | Liyan Zhang |
| collection | DOAJ |
| description | Abstract The development and implementation of county carbon control action plans in the Yellow River Basin (YRB) are crucial for realizing the “dual carbon” goals and modernizing national governance. Utilizing remote sensing data from 2001 to 2020, this study constructs a light-carbon conversion model and a carbon footprint model to simulate the carbon footprint of county energy consumption in the YRB. Employing spatial autocorrelation and spatial Durbin models, the study examines the temporal-spatial evolution characteristics and spatial effect mechanism. The results show that: (1) The county carbon footprint increased year by year. The distribution of the high carbon footprint is consistent with that of energy-intensive areas. The carbon cycle system is significantly unbalanced, and the counties with carbon deficit spread inland. (2) The carbon footprint exhibits significant spatial dependence, and the high carbon spillover effect is significant. Regional joint prevention and control strategy is essential to control the carbon footprint. Otherwise, the inter-regional carbon leakage effect may occur. (3) The current stage of economic development and industrial structure upgrading is not conducive to low-carbon development. Because of the energy rebound effect, technology development has not played the expected emission reduction effect. Nevertheless, the technology level and residents’ living standard are critical factors in reducing the carbon footprint. Government intervention, urbanization, human capital, and agricultural energy inputs increase the carbon footprint. |
| format | Article |
| id | doaj-art-d9f6384a98364ef79f980c04b9ef388f |
| institution | Kabale University |
| issn | 2045-2322 |
| language | English |
| publishDate | 2025-01-01 |
| publisher | Nature Portfolio |
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| series | Scientific Reports |
| spelling | doaj-art-d9f6384a98364ef79f980c04b9ef388f2025-02-02T12:21:38ZengNature PortfolioScientific Reports2045-23222025-01-0115111510.1038/s41598-025-86383-3Temporal-spatial evolution and formation mechanism of energy consumption carbon footprint at county scale in the Yellow River BasinLiyan Zhang0Mei Song1Yan Gao2China People’s Police UniversitySchool of Management, China University of Mining and Technology-BeijingBusiness School, Hebei University of Economics and BusinessAbstract The development and implementation of county carbon control action plans in the Yellow River Basin (YRB) are crucial for realizing the “dual carbon” goals and modernizing national governance. Utilizing remote sensing data from 2001 to 2020, this study constructs a light-carbon conversion model and a carbon footprint model to simulate the carbon footprint of county energy consumption in the YRB. Employing spatial autocorrelation and spatial Durbin models, the study examines the temporal-spatial evolution characteristics and spatial effect mechanism. The results show that: (1) The county carbon footprint increased year by year. The distribution of the high carbon footprint is consistent with that of energy-intensive areas. The carbon cycle system is significantly unbalanced, and the counties with carbon deficit spread inland. (2) The carbon footprint exhibits significant spatial dependence, and the high carbon spillover effect is significant. Regional joint prevention and control strategy is essential to control the carbon footprint. Otherwise, the inter-regional carbon leakage effect may occur. (3) The current stage of economic development and industrial structure upgrading is not conducive to low-carbon development. Because of the energy rebound effect, technology development has not played the expected emission reduction effect. Nevertheless, the technology level and residents’ living standard are critical factors in reducing the carbon footprint. Government intervention, urbanization, human capital, and agricultural energy inputs increase the carbon footprint.https://doi.org/10.1038/s41598-025-86383-3Remote sensing dataLight-carbon conversion modelSpatial effect mechanismCounty carbon footprintEmission reduction |
| spellingShingle | Liyan Zhang Mei Song Yan Gao Temporal-spatial evolution and formation mechanism of energy consumption carbon footprint at county scale in the Yellow River Basin Scientific Reports Remote sensing data Light-carbon conversion model Spatial effect mechanism County carbon footprint Emission reduction |
| title | Temporal-spatial evolution and formation mechanism of energy consumption carbon footprint at county scale in the Yellow River Basin |
| title_full | Temporal-spatial evolution and formation mechanism of energy consumption carbon footprint at county scale in the Yellow River Basin |
| title_fullStr | Temporal-spatial evolution and formation mechanism of energy consumption carbon footprint at county scale in the Yellow River Basin |
| title_full_unstemmed | Temporal-spatial evolution and formation mechanism of energy consumption carbon footprint at county scale in the Yellow River Basin |
| title_short | Temporal-spatial evolution and formation mechanism of energy consumption carbon footprint at county scale in the Yellow River Basin |
| title_sort | temporal spatial evolution and formation mechanism of energy consumption carbon footprint at county scale in the yellow river basin |
| topic | Remote sensing data Light-carbon conversion model Spatial effect mechanism County carbon footprint Emission reduction |
| url | https://doi.org/10.1038/s41598-025-86383-3 |
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