論文

2020年10月10日

Mining urban sustainable performance: GPS data-based spatio-temporal analysis on on-road braking emission

Journal of Cleaner Production
  • Jinyu Chen
  • ,
  • Wenjing Li
  • ,
  • Haoran Zhang
  • ,
  • Wenxiao Jiang
  • ,
  • Weifeng Li
  • ,
  • Yi Sui
  • ,
  • Xuan Song
  • ,
  • Ryosuke Shibasaki

270
記述言語
英語
掲載種別
研究論文(学術雑誌)
DOI
10.1016/j.jclepro.2020.122489
出版者・発行元
Elsevier Ltd

The on-road braking emission has been proved by former studies to account for a considerable part of on-road transportation. To improve cleaner air in urban area, the spatio-temporal analysis on emission performance of on-road braking is necessary as a guideline for decision-making. In this paper, we propose a framework for analysis on the particle matter emission of on-road vehicle braking events on an urban scale. We used massive vehicle trajectories in Tokyo area with short time interval as the database for analysis. From the result, we found that within the in the study area, the average driving distance during braking takes up about 20.60% of total driving distance. The average quantity of PM10 emission from braking for each driving trajectory is 14.09 mg and the one from exhaust emission is 35.36 mg. The emission from braking can averagely occupy 39.85% of exhaust emission. What's more, in our finding, the braking emission from heavy duty vehicle is 2.33 times of light duty vehicle. From the spatial distribution of PM10 braking emission, we found that braking emission usually happened in the city center and popular crowded areas due to the large traffic volume, as well as the main trunk roads of capital expressway or highway. We also found a different spatial pattern between the light duty vehicle and heavy-duty vehicle. In temporal change, we found that rapid peaks during the rush hour on weekday and contrastive stabilization on weekend. We believe our finding can provide a clearer pattern and understanding on the emission behavior of on-road vehicle braking.

リンク情報
DOI
https://doi.org/10.1016/j.jclepro.2020.122489
ID情報
  • DOI : 10.1016/j.jclepro.2020.122489
  • ISSN : 0959-6526
  • SCOPUS ID : 85087107467

エクスポート
BibTeX RIS