Deciphering decarbonization trajectories in China by spatiotemporal-accumulation modeling of electricity carbon footprint
Summary: Recent climate-trade policies emphasize managing carbon embedded in goods, with electricity carbon footprints as a key metric. However, the rapid energy transition complicates this evaluation. An innovative spatiotemporal model, accounting for dynamically-installed low-carbon energy infrast...
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| Format: | Article |
| Language: | English |
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Elsevier
2025-03-01
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| Series: | iScience |
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| Online Access: | http://www.sciencedirect.com/science/article/pii/S2589004225002238 |
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| author | Jing Tang Rui Shan Peng Wang Wei-Qiang Chen Dungang Gu Guanghui Li Pinhua Rao Jinguo Wang Jiaqi Lu |
| author_facet | Jing Tang Rui Shan Peng Wang Wei-Qiang Chen Dungang Gu Guanghui Li Pinhua Rao Jinguo Wang Jiaqi Lu |
| author_sort | Jing Tang |
| collection | DOAJ |
| description | Summary: Recent climate-trade policies emphasize managing carbon embedded in goods, with electricity carbon footprints as a key metric. However, the rapid energy transition complicates this evaluation. An innovative spatiotemporal model, accounting for dynamically-installed low-carbon energy infrastructure (LCPI), was developed to assess electricity decarbonization trajectories. Applying to Chinese power grid, the national and provincial electricity carbon footprints are projected to analyze the impact of LCPI deployment. By 2050, under aggressive decarbonization scenarios, the electricity carbon footprint is projected to reach 0.12 kg CO2-eq/kWh—a 38.13% reduction compared to scenarios that ignore LCPI decarbonization, and a 19.18% difference when neglecting the heterogeneous carbon footprint of spatiotemporally accumulated LCPI. Meanwhile, up to 57.94% of China’s electricity carbon footprint stems from historical LCPI production emissions, thereby stressing the long-lasting impact of renewable investments. Such insights support targeted policies to systematically reduce energy-related carbon footprints, providing a scalable roadmap for global sustainable energy practices. |
| format | Article |
| id | doaj-art-1840322fc913477ea7ed417a21960cee |
| institution | DOAJ |
| issn | 2589-0042 |
| language | English |
| publishDate | 2025-03-01 |
| publisher | Elsevier |
| record_format | Article |
| series | iScience |
| spelling | doaj-art-1840322fc913477ea7ed417a21960cee2025-08-20T02:45:33ZengElsevieriScience2589-00422025-03-0128311196310.1016/j.isci.2025.111963Deciphering decarbonization trajectories in China by spatiotemporal-accumulation modeling of electricity carbon footprintJing Tang0Rui Shan1Peng Wang2Wei-Qiang Chen3Dungang Gu4Guanghui Li5Pinhua Rao6Jinguo Wang7Jiaqi Lu8Innovation Centre for Environment and Resources, Shanghai University of Engineering Science, No.333 Longteng Road, Songjiang District, Shanghai 201620, ChinaDepartment of Environmental Sciences and Engineering, Gillings School of Global Public Health, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA; Corresponding authorKey Lab of Urban Environment and Health, Institute of Urban Environment, Chinese Academy of Sciences, Xiamen, Fujian 361021, ChinaKey Lab of Urban Environment and Health, Institute of Urban Environment, Chinese Academy of Sciences, Xiamen, Fujian 361021, ChinaInnovation Centre for Environment and Resources, Shanghai University of Engineering Science, No.333 Longteng Road, Songjiang District, Shanghai 201620, ChinaInnovation Centre for Environment and Resources, Shanghai University of Engineering Science, No.333 Longteng Road, Songjiang District, Shanghai 201620, ChinaInnovation Centre for Environment and Resources, Shanghai University of Engineering Science, No.333 Longteng Road, Songjiang District, Shanghai 201620, ChinaInnovation Centre for Environment and Resources, Shanghai University of Engineering Science, No.333 Longteng Road, Songjiang District, Shanghai 201620, ChinaInnovation Centre for Environment and Resources, Shanghai University of Engineering Science, No.333 Longteng Road, Songjiang District, Shanghai 201620, China; Corresponding authorSummary: Recent climate-trade policies emphasize managing carbon embedded in goods, with electricity carbon footprints as a key metric. However, the rapid energy transition complicates this evaluation. An innovative spatiotemporal model, accounting for dynamically-installed low-carbon energy infrastructure (LCPI), was developed to assess electricity decarbonization trajectories. Applying to Chinese power grid, the national and provincial electricity carbon footprints are projected to analyze the impact of LCPI deployment. By 2050, under aggressive decarbonization scenarios, the electricity carbon footprint is projected to reach 0.12 kg CO2-eq/kWh—a 38.13% reduction compared to scenarios that ignore LCPI decarbonization, and a 19.18% difference when neglecting the heterogeneous carbon footprint of spatiotemporally accumulated LCPI. Meanwhile, up to 57.94% of China’s electricity carbon footprint stems from historical LCPI production emissions, thereby stressing the long-lasting impact of renewable investments. Such insights support targeted policies to systematically reduce energy-related carbon footprints, providing a scalable roadmap for global sustainable energy practices.http://www.sciencedirect.com/science/article/pii/S2589004225002238Environmental scienceEnergy policyEngineeringEnergy management |
| spellingShingle | Jing Tang Rui Shan Peng Wang Wei-Qiang Chen Dungang Gu Guanghui Li Pinhua Rao Jinguo Wang Jiaqi Lu Deciphering decarbonization trajectories in China by spatiotemporal-accumulation modeling of electricity carbon footprint iScience Environmental science Energy policy Engineering Energy management |
| title | Deciphering decarbonization trajectories in China by spatiotemporal-accumulation modeling of electricity carbon footprint |
| title_full | Deciphering decarbonization trajectories in China by spatiotemporal-accumulation modeling of electricity carbon footprint |
| title_fullStr | Deciphering decarbonization trajectories in China by spatiotemporal-accumulation modeling of electricity carbon footprint |
| title_full_unstemmed | Deciphering decarbonization trajectories in China by spatiotemporal-accumulation modeling of electricity carbon footprint |
| title_short | Deciphering decarbonization trajectories in China by spatiotemporal-accumulation modeling of electricity carbon footprint |
| title_sort | deciphering decarbonization trajectories in china by spatiotemporal accumulation modeling of electricity carbon footprint |
| topic | Environmental science Energy policy Engineering Energy management |
| url | http://www.sciencedirect.com/science/article/pii/S2589004225002238 |
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