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法国电动汽车生态金环保得分核算方法及对我国的影响研究OA

Environmental Score Calculation Under France's EV Eco-Bonus Policy and Its Impact on China

中文摘要英文摘要

为了推动中国电动汽车的出口业务,聚焦于法国电动乘用车生态奖金政策中的环保得分核算规则,并对比分析了不同国家电动汽车碳足迹的影响.研究结果表明,按照法国政策,中国电动汽车的碳足迹相对美国和法国分别高出87.4%和105.9%,环保得分仅为8分,无法获得补贴.关键原因在于中国碳足迹缺省因子普遍过高,尤其是电池和铝及其合金的因子,分别比法国高出28.3%和132.6%,以及海运因子过高.但依据中国本土标准及因子数据计算,样车总碳足迹较法国生态金政策下的"中国"降低55.3%,环保得分达到107分,从而具备获得补贴的条件.因此,迫切需要建立与中国电动汽车相适应的核算方法和本土因子,并尽快实现国际互认.

To support the export of Chinese electric vehicles(EVs),this paper studies the environmental score calculation rules in France's ecological bonus policy for electric passenger cars and compares the impact of EV carbon footprints across different countries.The research show that,under the French policy,the carbon footprint of Chinese electric vehicles is 87.4%and 105.9%higher than those from the United States and France,respectively.As a result,the environmental score is only 8 points,which makes the vehicles ineligible for subsidies.The primary reason is that the default carbon footprint factors for China are too high.In particular,the factors for batteries and for aluminum and its alloys are 28.3%and 132.6%higher than those for France,respectively,as well as the excessively high maritime transport factor.However,based on China's domestic standards,the total carbon footprint of the sample vehicle is 55.3%lower than the value calculated for"China"under the French ecological bonus policy,yielding an environmental score of 107 points,which is eligible for the subsidy.Therefore,it is urgent to establish calculation methods and domestic factors that are suitable for Chinese electric vehicles and to promote international mutual recognition as soon as possible.

张龙平;邹博文;王坤;冉梽乂;余浩;马毅

中国汽车工程研究院股份有限公司,重庆 401122中国汽车工程研究院股份有限公司,重庆 401122中国汽车工程研究院股份有限公司,重庆 401122中国汽车工程研究院股份有限公司,重庆 401122中国汽车工程研究院股份有限公司,重庆 401122中国汽车工程研究院股份有限公司,重庆 401122

资源环境

新能源汽车环保得分碳足迹核算缺省因子国际互认

new energy vehiclesenvironmental protection scorecarbon footprint calculationdefault factorsinternational mutual recognition

《汽车工程学报》 2026 (3)

406-413,8

重庆市技术预见与制度创新项目(CSTB2025jsyj-gkjzX0019):基于数据驱动的新能源汽车全生命周期低碳协同智能优化技术创新路径研究

10.3969/j.issn.2095-1469.2026.03.07

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