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- Publisher Website: 10.1016/j.trd.2018.02.010
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Article: 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
Title | 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 |
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Authors | |
Keywords | Emission modelling Microwave radar PM concentrations Speed aggregation Traffic camera Traffic simulation |
Issue Date | 2018 |
Citation | Transportation Research Part D: Transport and Environment, 2018, v. 62, p. 90-101 How to Cite? |
Abstract | 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. Our 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. Our 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. |
Persistent Identifier | http://hdl.handle.net/10722/346664 |
ISSN | 2023 Impact Factor: 7.3 2023 SCImago Journal Rankings: 2.328 |
DC Field | Value | Language |
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dc.contributor.author | Xu, Junshi | - |
dc.contributor.author | Hilker, Nathan | - |
dc.contributor.author | Turchet, Matheus | - |
dc.contributor.author | Al-Rijleh, Mohamad Kenan | - |
dc.contributor.author | Tu, Ran | - |
dc.contributor.author | Wang, An | - |
dc.contributor.author | Fallahshorshani, Masoud | - |
dc.contributor.author | Evans, Greg | - |
dc.contributor.author | Hatzopoulou, Marianne | - |
dc.date.accessioned | 2024-09-17T04:12:26Z | - |
dc.date.available | 2024-09-17T04:12:26Z | - |
dc.date.issued | 2018 | - |
dc.identifier.citation | Transportation Research Part D: Transport and Environment, 2018, v. 62, p. 90-101 | - |
dc.identifier.issn | 1361-9209 | - |
dc.identifier.uri | http://hdl.handle.net/10722/346664 | - |
dc.description.abstract | 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. Our 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. Our 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. | - |
dc.language | eng | - |
dc.relation.ispartof | Transportation Research Part D: Transport and Environment | - |
dc.subject | Emission modelling | - |
dc.subject | Microwave radar | - |
dc.subject | PM concentrations | - |
dc.subject | Speed aggregation | - |
dc.subject | Traffic camera | - |
dc.subject | Traffic simulation | - |
dc.title | 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 | - |
dc.type | Article | - |
dc.description.nature | link_to_subscribed_fulltext | - |
dc.identifier.doi | 10.1016/j.trd.2018.02.010 | - |
dc.identifier.scopus | eid_2-s2.0-85044769648 | - |
dc.identifier.volume | 62 | - |
dc.identifier.spage | 90 | - |
dc.identifier.epage | 101 | - |