Forecasting urban passenger transportation emissions: a green and new energy approach

被引：0
作者：
Bai F.-R. [1 ]
Sun G.-R. [1 ]
机构：
[1] School of Management, Xi’an University of Science and Technology, Xi’an
来源：
International Journal of Environmental Studies | 2024年 / 81卷 / 04期
关键词：
carbon emission; prediction; system dynamics; Transportation;
D O I：
10.1080/00207233.2024.2375859
中图分类号：
学科分类号：
摘要：
Passenger transportation significantly contributes to urban carbon dioxide emission. Decreasing these emissions is essential to achieving low-carbon development. This research focused on Xi’an City to enhance previous research works by considering factors such as road greening, online ride-hailing, and use of vehicles with new energy sources. Using system dynamics method, a carbon dioxide emission prediction model was developed for urban passenger transportation in Xi’an. The developed model estimated total emissions from 2012 to 2021 and projected carbon dioxide emission reduction plans through six different scenarios for the time period of 2023 to 2032. The analysis identified private cars as the main contributors to carbon emission in urban passenger transportation. Single scenario simulations indicated that passenger traffic in Xi’an would not achieve carbon emission peak by 2030, but multi-scenario simulations showed it would. Specific recommendations for carbon emission reduction in urban passenger transportation were provided, focusing on travel patterns, energy sources, and promotion of green initiatives. © 2024 Informa UK Limited, trading as Taylor & Francis Group.
引用
收藏
页码：1715 / 1732
页数：17
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