Contrasting the direct use of data from traffic radars and video-cameras with traffic simulation in the estimation of road emissions and PM hotspot analysis

This study investigates the effect of traffic volume and speed data on the simulation of vehicle emissions and hotspot analysis. Data from a microwave radar and video cameras were first used directly for emission modelling. They were then used as input to a traffic simulation model whereby vehicle drive cycles were extracted to estimate emissions. To reach this objective, hourly traffic data were collected from three periods including morning peak (6–9 am), midday (11–2 pm), and afternoon peak (3–6 pm) on a weekday (June 23, 2016) along a high-volume corridor in Toronto, Canada. Traffic volumes were detected by a single radar and two video cameras operated by the Southern Ontario Centre for Atmospheric Aerosol Research. Traffic volume and composition derived from the radar had lower accuracy than the video camera data and the radar performance varied by lane exhibiting poorer performance in the remote lanes. Radar speeds collected at a single point on the corridor had higher variability than simulated traffic speeds, and average speeds were closer after model calibration. Traffic emissions of nitrogen oxides (NOx) and particulate matter (PM₁₀ and PM₂.₅) were estimated using radar data as well as using simulated traffic based on various speed aggregation methods. The authors' results illustrate the range of emission estimates (NOx: 4.0–27.0 g; PM₁₀: 0.3–4.8 g; PM₂.₅: 0.2–1.3 g) for the corridor. The estimates based on radar speeds were at least three times lower than emissions derived from simulated vehicle trajectories. Finally, the PM₁₀ and PM₂.₅ near-road concentrations derived from emissions based on simulated speeds were two or three times higher than concentrations based on emissions derived using radar data. The authors' findings are relevant for project-level emission inventories and PM hot-spot analysis; caution must be exercised when using raw radar data for emission modeling purposes.

• Record URL:
  https://doi.org/10.1016/j.trd.2018.02.010
• Record URL:
  http://www.sciencedirect.com/science/article/pii/S1361920917307174
• Availability:
  • Find a library where document is available. Order URL: http://worldcat.org/issn/13619209
• Supplemental Notes:
  • © 2018 Elsevier Ltd. All rights reserved. Abstract reprinted with permission of Elsevier.
• Authors:
  • Xu, Junshi
  • Hilker, Nathan
  • 0000-0002-4404-4422
  • Turchet, Matheus
  • Al-Rijleh, Mohamad-Kenan
  • 0000-0002-1681-504X
  • Tu, Ran
  • Wang, An
  • Fallahshorshani, Masoud
  • Evans, Greg
  • Hatzopoulou, Marianne
  • 0000-0002-7107-7086
• Publication Date: 2018-7

Language

• English

Media Info

• Media Type: Web
• Features: Appendices; Figures; References; Tables;
• Pagination: pp 90-101
• Serial:
  • Transportation Research Part D: Transport and Environment
  • Volume: 62
  • Issue Number: 0
  • Publisher: Elsevier
  • ISSN: 1361-9209
  • Serial URL: http://www.sciencedirect.com/science/journal/13619209

Subject/Index Terms

• TRT Terms: Cameras; Concentration (Chemistry); Data analysis; Data collection; Estimation theory; Exhaust gases; High risk locations; Nitrogen oxides; Particulates; Traffic data; Traffic simulation; Traffic speed; Traffic volume
• Geographic Terms: Toronto (Canada)
• Subject Areas: Data and Information Technology; Environment; Highways; Planning and Forecasting;

Filing Info

• Accession Number: 01678186
• Record Type: Publication
• Files: TRIS
• Created Date: Aug 22 2018 9:17AM