Impact assessment of future fleet compositions in vehicle emissions in urban areas: A methodological framework and a case study

IF 2.4 Q3 TRANSPORTATION Case Studies on Transport Policy Pub Date : 2024-08-29 DOI:10.1016/j.cstp.2024.101285
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Abstract

This study explores the impact of emerging vehicle technologies on direct urban traffic emissions. It investigates emission reduction potential from shifts in fleet compositions and modal choices, especially considering climate change. To achieve this, three key research areas are explored for historical, current, and future scenarios (up to 2050): mode choice, emission factors for different vehicle categories, and diverse vehicle propulsion technologies. The estimation of the modal split is pivotal, developing a methodology utilizing Stated Preference survey data, discrete choice modeling, Monte Carlo simulations, and macroscopic traffic simulations. Future scenarios derive from the reference year’s modal split, and emission factors and fleet compositions are predetermined via an extensive literature review, aiding the assessment of their respective emissions. A subsequent sensitivity analysis identifies the impact of specific parameters on emissions, guiding future research focus. Study results underscore differences in greenhouse gas emissions and primary air pollutants between base and future scenarios.

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未来车队组成对城市地区汽车尾气排放的影响评估:方法框架和案例研究
本研究探讨了新兴汽车技术对城市交通直接排放的影响。它调查了车队组成和模式选择的变化所带来的减排潜力,特别是考虑到气候变化。为此,本研究针对历史、当前和未来(至 2050 年)情景,探讨了三个关键研究领域:模式选择、不同车辆类别的排放系数和多样化的车辆推进技术。其中,模式选择的估算至关重要,它利用陈述偏好调查数据、离散选择建模、蒙特卡洛模拟和宏观交通模拟来制定方法。未来情景源自参考年的模式划分,排放因子和车队组成是通过广泛的文献审查预先确定的,有助于评估各自的排放量。随后的敏感性分析确定了特定参数对排放量的影响,为未来的研究重点提供了指导。研究结果强调了基本方案和未来方案之间在温室气体排放和主要空气污染物方面的差异。
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CiteScore
5.00
自引率
12.00%
发文量
222
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