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可持续道路运输脱碳:中国新能源汽车的情景分析。

A Sustainable Road Transport Decarbonisation: The Scenario Analysis of New Energy Vehicle in China.

机构信息

Economics and Management School, Wuhan University, Wuhan 430072, China.

Merchants Union Consumer Finance Company Limited, Wuhan 430070, China.

出版信息

Int J Environ Res Public Health. 2023 Feb 15;20(4):3406. doi: 10.3390/ijerph20043406.

Abstract

Due to the prosperous development of the economy, the emissions of carbon dioxide (CO) and other greenhouse gases (GHGs) have intensified and attracted attention worldwide. China has set the "dual-carbon" aim to pursue sustainable development in the transport sector. Thus, this study created a generalised Bass model to forecast new energy vehicle (NEV) ownership by introducing a new factor, charging piles, to reflect the infrastructure effects. Using the improved model with the hypothesis of annual mileage, an empirical analysis was conducted with the subject of NEVs in China by using the NEV-related panel data from 2010 to 2020, and the forecast result is outstanding with a goodness-of-fit of 99.7%. With the forecasts, carbon emission reduction was calculated with a bottom-up method. To further discuss the pathway to achieve carbon neutrality in the transport sector of China, a scenario analysis was conducted with ideal, enhanced, and radical constraints. The results show that if all factors remain "as is" until 2050, China will be far from carbon neutrality. Thus, this paper proposes relevant policy implications to assist the government to obtain effective methods to assess carbon reduction benefits and find viable pathways to a sustainable road transport system.

摘要

由于经济的蓬勃发展,二氧化碳(CO)和其他温室气体(GHG)的排放加剧,引起了全球关注。中国设定了“双碳”目标,以追求交通领域的可持续发展。因此,本研究通过引入新的因素充电桩来反映基础设施的影响,创建了一个广义的巴斯模型来预测新能源汽车(NEV)的拥有量。使用改进后的模型,假设每年行驶里程,利用 2010 年至 2020 年中国新能源汽车相关面板数据,对中国新能源汽车进行了实证分析,预测结果非常出色,拟合优度为 99.7%。利用预测结果,采用自下而上的方法计算了碳减排量。为了进一步探讨中国交通部门实现碳中和的途径,采用理想、增强和激进约束进行了情景分析。结果表明,如果到 2050 年所有因素都保持不变,中国将远未实现碳中和。因此,本文提出了相关的政策建议,以协助政府获得有效方法来评估碳减排效益,并找到可行的途径,以实现可持续的道路运输系统。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/be27/9968230/13e08d10d42a/ijerph-20-03406-g001.jpg

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