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...
Saved in:
| Main Authors: | , , , , , , , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Elsevier
2025-03-01
|
| Series: | iScience |
| Subjects: | |
| Online Access: | http://www.sciencedirect.com/science/article/pii/S2589004225002238 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| Summary: | 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. |
|---|---|
| ISSN: | 2589-0042 |