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Traffic data for local emissions monitoring at a signalized intersection

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Author: Bigazzi, A. · Lint, J.W.C. van · Klunder, G. · Stelwagen, U. · Ligterink, N.E.
Type:article
Date:2010
Institution: TNO Bouw en Ondergrond
Source:13th International IEEE Conference on Intelligent Transportation Systems, ITSC 2010, 19-22 September, 2010, Funchal, Madeira. Conference code: 82861, 210-215
series:
IEEE Conference on Intelligent Transportation Systems, Proceedings, ITSC
Identifier: 426216
ISBN: 9781424476572
Article number: No.: 5625302
Keywords: Traffic · Air quality · Emissions modeling · Emissions monitoring · Pollution-responsive DTM · Traffic data · Traffic simulation · Organisation · SM - Smart Mobility · BSS - Behavioural and Societal Sciences

Abstract

In order to assist planning efforts for air pollution-responsive dynamic traffic management (DTM) systems, this research assesses the accuracy of local emissions monitoring based on traffic data and models. The study quantifies the benefits of increased data resolution for short-term emissions estimates at a signalized intersection. The emissions estimates are also compared with air quality measurements in the immediate roadside environment. Results show that traffic-based emissions estimates require detailed knowledge of the local vehicle fleet and speed profiles. Traffic-based emissions monitoring enables pollution-responsive DTM, but these results indicate that this approach only applies over long time periods. This limit is due to the inherent stochasticity of vehicle arrivals and emissions rates. Using current tools, even detailed knowledge of on-road vehicles and traffic leaves uncertainty in short-term roadway emissions. ©2010 IEEE.