Estimation of Impact of Electronic Toll Collection on Air Pollution Levels: Estimation Using Microscopic Simulation Model of Large-Scale Transportation Network

This paper presents a microscopic simulation-based estimation of the spatiotemporal change in air pollution levels as a result of electronic toll collection (ETC) deployment on the New Jersey Turnpike (NJTPK), a large-scale traffic network. The study includes (a) the disaggregate spatial estimation and analysis of the emissions instead of aggregate systemwide estimations, (b) the use of a vehicle-based and well-calibrated traffic simulation model of NJTPK network in Paramics microscopic simulation software to perform this disaggregate emission estimation, (c) the use of a unique and realistic toll plaza model with a complete mainline model to capture complex mainline–toll plaza interactions, and (d) estimation of short- and long-term impacts of ETC systems. The simulation model is loaded with a recent network-specific data set, which includes origin–destination demand data for 1999 (before ETC deployment) and for 2005 (6 years after ETC deployment) and toll plaza service times obtained from toll plaza videotapes. The MOBILE6.2 mobile source emission model developed by the Environmental Protection Agency is integrated in Paramics. At each time step of the simulation, air pollution levels—namely, CO, HC, NOx, and PM10 emissions—are calculated for each vehicle type on the basis of its speed. The simulation network is used to estimate not only the change in systemwide air pollution levels but also the spatial changes throughout the system. Results show that ETC deployment reduces the overall network air pollution level in the short term; however, in the long term its benefits are not sufficient to compensate for the air pollution increase on the mainline because of annual traffic growth.

Language

  • English

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Filing Info

  • Accession Number: 01042497
  • Record Type: Publication
  • ISBN: 9780309104371
  • Files: TRIS, TRB
  • Created Date: Mar 1 2007 8:39AM