Carbon emission of urban transport with different data sources

Q1 Engineering
Ruo-yu Wu, Chun-fu Shao, Xin-yi Wang, Xu-yang Yin
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引用次数: 0

Abstract

The identification of critical sectors at the provincial level is important for achieving China’ s CO2 mitigation target. To scientifically subdivide the target of emission peak and carbon neutrality in public transport, this article employs a decision tree, taking into a combination of “top-down” and “bottom-up” approaches, to determine selection rules for carbon emission calculation under different data sources. The stepwise regression analysis determines length of vehicle is the key factor affecting bus 100 km energy consumption. The results reveal that, with 383.0 million tons of carbon dioxide being emit, the highest carbon emission from Inner Mongolia ground buses system happened in 2013. The results show that measures including replacing conventional vehicles with electric vehicles could effectively facilitate the road transport sector to gradually approach zero carbon emissions.

不同数据源下的城市交通碳排放
<p class="a"><span lang="EN-US">在省级层面确定关键部门对于实现中国的CO<sub>2</sub>减排目标。为了科学细分公共交通排放峰值和碳中和目标,<a name="_Hlk135899611"></a>本文采用决策树,采用“自上而下”和“自下而上”相结合的方法,确定不同数据源下碳排放计算的选择规则。逐步回归分析确定车辆长度是影响客车百公里能耗的关键因素。结果表明,2013年内蒙古地面公交系统的二氧化碳排放量最高,为3.83亿吨;结果表明,包括以电动汽车取代传统汽车在内的措施可以有效地促进道路运输部门逐步接近零碳排放。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
Journal of Modern Transportation
Journal of Modern Transportation TRANSPORTATION SCIENCE & TECHNOLOGY-
CiteScore
4.20
自引率
0.00%
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0
审稿时长
13 weeks
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