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Scenario-based analysis of traffic-related PM2.5 concentration: Lisbon case study

  • Biomonitoring of atmospheric pollution: possibilities and future challenges
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Abstract

Air quality in urban centers constitutes a challenge ahead for most cities. For this reason, the objective of this research work was to evaluate the impacts of changing traffic-related parameters on particulate matter (PM) concentration for several hierarchical street levels using real-world data for the city of Lisbon, Portugal. For that purpose, 2014 data regarding meteorological conditions, traffic volumes, typical vehicle speed, and a vehicle representative of the fleet was used in an air quality dispersion model (CALINE4). The available data allowed building a baseline case for several streets that are representative of the traffic circulation conditions in Lisbon, which was compared with different scenarios: hypothetical introduction of a cordon toll (S1.1 to S1.4) and the implementation of a low emission zone (S2.1 and 2.2). The results indicate that reductions on PM2.5 concentrations from 5 to 42 % may be obtained from the implementation of the scenarios. Overall, this study demonstrates that modeling tools based on real-world data can provide a good approach to study urban policies regarding traffic-related PM exposure. Additionally, implementation of such measures requires an integrated strategy that enables proper enforcement and monitoring, as well as an adequate management of traffic flows between the implementation boundaries.

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Notes

  1. Level 1—arterial roads; level 2—collector and distributor roads; levels 3 and 4—local roads.

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Acknowledgments

The authors acknowledge Fundação para a Ciência e Tecnologia for the Doctoral (PD/BD/105714/2014) and Post-Doctoral (SFRH/BPD/79684/2011) financial support, as well as a project grant (SusCity Project, MITP-TB/C S/0026/2013). This work was also supported by Fundação para a Ciência e Tecnologia, through IDMEC, under LAETA, project UID/EMS/50022/2013. Thanks are also due to Project SoMoMUT—Soft Mode Modeling in Urban Trips (PTDC/ECMURB/1407/2012). The authors would also like to acknowledge Direcção de Mobilidade e Transportes Terrestres of Câmara Municipal de Lisboa for providing the traffic count data and the investigation group MARETEC/LARSYS, Grupo de Previsão Numérica do Tempo (Instituto Superior Técnico, Universidade de Lisboa) for providing the meteorological data.

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Correspondence to Marta V. Faria.

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Responsible editor: Constantini Samara

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Faria, M.V., Duarte, G.O., Baptista, P.C. et al. Scenario-based analysis of traffic-related PM2.5 concentration: Lisbon case study. Environ Sci Pollut Res 24, 12026–12037 (2017). https://doi.org/10.1007/s11356-015-5556-6

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