Quantifying and analyzing traffic emission reductions from ridesharing: A case study of Shanghai

Ridesharing has potential to mitigate traffic emissions. To better support policymaking, this paper endeavors to estimate and analyze emission reductions by large-scale ridesharing combining the Shareability-Network approach, the COPERT III emission model, and a speed-density traffic-flow model. Using Shanghai as a case, the authors show that ridesharing per se can reduce fuel-consumption (FC) by 22.88% and 15.09% in optimal and realistic scenarios, respectively, with corresponding emissions reductions. Ridesharing’s spontaneous first-order speed effect further reduces FC by 0.34–0.96%. Additionally, spatial analyses show that ridesharing reduces more emissions on severely polluted roads, leading to two spatial patterns; temporal analyses demonstrate patterns shifted from disorganized to organized. Both the phenomena can be explained by the aggregation of trips and the grading and topology of the roads. Moreover, ridesharing may also increase emissions on some branch roads, creating a new environmental injustice, which, however, is estimated to be less significant than expected.

• Record URL:
  https://doi.org/10.1016/j.trd.2020.102629
• Record URL:
  http://www.sciencedirect.com/science/article/pii/S1361920920308142
• Availability:
  • Find a library where document is available. Order URL: http://worldcat.org/issn/13619209
• Supplemental Notes:
  • © 2020 Elsevier Ltd. All rights reserved. Abstract reprinted with permission of Elsevier.
• Authors:
  • Yan, Longxu
  • Luo, Xiao
  • Zhu, Rui
  • Santi, Paolo
  • Wang, Huizi
  • Wang, De
  • Zhang, Shangwu
  • Ratti, Carlo
• Publication Date: 2020-12

Language

• English

Media Info

• Media Type: Web
• Features: References;
• Pagination: 102629
• Serial:
  • Transportation Research Part D: Transport and Environment
  • Volume: 89
  • Issue Number: 0
  • Publisher: Elsevier
  • ISSN: 1361-9209
  • Serial URL: http://www.sciencedirect.com/science/journal/13619209

Subject/Index Terms

• TRT Terms: Case studies; Environmental impacts; Environmental justice; Exhaust gases; Mathematical models; Ridesharing; Spatial analysis
• Geographic Terms: Shanghai (China)
• Subject Areas: Environment; Highways; Operations and Traffic Management;

Filing Info

• Accession Number: 01759946
• Record Type: Publication
• Files: TRIS
• Created Date: Nov 19 2020 3:19PM