Abstract
The year 2020 marked the eve of the explosive growth in China’s BEV market, which may lead to substantial carbon emission implications. This study quantifies the full life-cycle carbon emissions of battery electric vehicles (BEVs) across China’s 31 provinces using a multi-regional input-output-based life-cycle assessment (MRIO-based LCA) model, covering four phases: manufacturing, driving, battery replacement, and scrapping. Moreover, the coupling coordination degree (CCD) model was employed to evaluate the coordination degree between provincial BEV deployment and a green electric system. Results show that the total carbon emissions amount to 48.95 million tons, with manufacturing contributing 58.4% and driving for 33.4%. Hebei (5.72 million tons) and Shandong (4.16 million tons) account for the largest shares, driven by embodied emissions from heavy industry and coal-intensive power systems. Interprovincial embodied carbon flows reveal a dominant north-to-south transfer pattern. Furthermore, coupling coordination between BEV deployment and a green electric system is generally medium (0.5 < CCD ≤ 0.7), with Guangdong (CCD = 0.73) standing out as an exemplary case, demonstrating an effective equilibrium between BEV industry expansion and the integration of renewable energy. These findings highlight that in provinces with rapidly growing BEV industries, such as Guangdong, policies promoting low-carbon supply chains and accelerating green electricity infrastructure development are crucial to reducing emissions.
| Original language | English |
|---|---|
| Article number | 137 |
| Journal | World Electric Vehicle Journal |
| Volume | 17 |
| Issue number | 3 |
| DOIs | |
| State | Published - Mar 2026 |
Bibliographical note
Publisher Copyright:© 2026 by the authors.
UN SDGs
This output contributes to the following UN Sustainable Development Goals (SDGs)
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SDG 7 Affordable and Clean Energy
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SDG 12 Responsible Consumption and Production
Keywords
- China
- MRIO-based LCA
- battery electric vehicles
- carbon emissions
- life-cycle assessment
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