Accounting for traffic speed dynamics when calculating COPERT and PHEM pollutant emissions at the urban scale

Lejri, Delphine; Can, Arnaud; Schiper, Nicole; Leclercq, Ludovic · 2018 · Crossref

DOI: 10.1016/j.trd.2018.06.023

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Summary

This study addresses the challenge of accurately estimating urban traffic pollutant emissions, specifically fuel consumption (FC) and nitrogen oxides (NOx), by investigating how traffic speed dynamics influence emission modeling. The research focuses on two primary questions: the sensitivity of the aggregated COPERT IV model to different definitions of mean speed, and the potential for adapting COPERT to account for vehicle speed distributions rather than single average values. These issues are critical because urban congestion creates rapid speed variations that standard mean-speed models often fail to capture accurately, leading to biased emission estimates. The methodology couples a traffic microsimulation platform (Symuvia) with two emission models: the aggregated COPERT IV and the instantaneous PHEM v11. The simulation covers a 3 km² urban area in the Paris region during a 2.5-hour morning rush hour, calibrated with real-world traffic flow data. The study evaluates three speed definitions for COPERT: the speed limit, punctual mean speeds (simulating loop detectors), and spatial mean speeds (Edie’s definition). Additionally, the authors adapt COPERT’s emission functions to accept speed distributions (time spent per speed class) rather than just mean speeds, treating idling separately. These adapted COPERT results are compared against PHEM, which uses individual vehicle trajectories at a 1-second resolution. The results demonstrate that COPERT emissions are highly sensitive to mean speed definitions, particularly under congested conditions. Using degraded speed definitions, such as speed limits or punctual loop measurements, leads to significant underestimations of emissions. Specifically, using speed limits underestimated FC by 19.8–25.3% and NOx by 30.7–36.0% compared to spatial mean speeds. Adapting COPERT to incorporate speed distributions yielded higher emissions, increasing FC by 13% and NOx by 16% during congestion compared to traditional mean-speed implementations. This approach better captures the impact of low speeds and idling, which are major contributors to emissions in congested traffic. The significance of this work lies in its demonstration that accounting for traffic speed dynamics substantially improves the accuracy of urban emission modeling. While the adapted COPERT model using speed distributions provides results closer to the high-resolution PHEM model than traditional mean-speed methods, it still underestimates emissions compared to instantaneous trajectory-based modeling. The study concludes that incorporating richer traffic information, such as speed distributions, is essential for reducing biases in aggregated emission models, particularly for assessing the environmental impact of traffic regulation strategies in congested urban environments.

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• speed choice