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Estimating Emissions from Static Traffic Models: Problems and Solutions
Linköping University, Department of Science and Technology, Communications and Transport Systems. Linköping University, Faculty of Science & Engineering.ORCID iD: 0000-0003-2767-9415
Linköping University, Department of Science and Technology, Communications and Transport Systems. Linköping University, Faculty of Science & Engineering.ORCID iD: 0000-0002-1367-6793
Linköping University, Department of Science and Technology, Communications and Transport Systems. Linköping University, Faculty of Science & Engineering. Swedish Natl Rd and Transport Res Inst, SE-58195 Linkoping, Sweden.ORCID iD: 0000-0002-0336-6943
2020 (English)In: Journal of Advanced Transportation, ISSN 0197-6729, E-ISSN 2042-3195, Vol. 2020, article id 5401792Article in journal (Refereed) Published
Abstract [en]

In large urban areas, the estimation of vehicular traffic emissions is commonly based on the outputs of transport planning models, such as Static Traffic Assignment (STA) models. However, such models, being used in a strategic context, imply some important simplifications regarding the variation of traffic conditions, and their outputs are heavily aggregated in time. In addition, dynamic traffic flow phenomena, such as queue spillback, cannot be captured, leading to inaccurate modelling of congestion. As congestion is strongly correlated with increased emission rates, using STA may lead to unreliable emission estimations. The first objective of this paper is to identify the errors that STA models introduce into an emission estimation. Then, considering the type and the nature of the errors, our aim is to suggest potential solutions. According to our findings, the main errors are related to STA inability of accurately modelling the level and the location of congestion. For this reason, we suggest and evaluate the postprocessing of STA outputs through quasidynamic network loading. Then, we evaluate our suggested approach using the HBEFA emission factors and a 19 km long motorway segment in Stockholm as a case study. Although, in terms of total emissions, the differences compared to the simple static case are not so vital, the postprocessor performs better regarding the spatial distribution of emissions. Considering the location-specific effects of traffic emissions, the latter may lead to substantial improvements in applications of emission modelling such as dispersion, air quality, and exposure modelling.

Place, publisher, year, edition, pages
WILEY-HINDAWI , 2020. Vol. 2020, article id 5401792
National Category
Transport Systems and Logistics
Identifiers
URN: urn:nbn:se:liu:diva-164205DOI: 10.1155/2020/5401792ISI: 000514363900013OAI: oai:DiVA.org:liu-164205DiVA, id: diva2:1413457
Note

Funding Agencies|Swedish Energy AgencySwedish Energy Agency [38921-1]

Available from: 2020-03-10 Created: 2020-03-10 Last updated: 2020-04-01

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Tsanakas, NikolaosEkström, JoakimOlstam, Johan
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