A multi-approach to study and communicate on the effect of highway infrastructures on the dispersion of traffic-related air pollutants.
Résumé
In this work, we will present 4 different approaches to study and visualize the effects of motorway infrastructures such as precast noise barriers or vegetated flat-top earth berms on the dispersion of traffic-related pollutants. The micrometeorological characteristics that directly affect the dispersion of pollutants in the atmosphere were first computed with a pseudo-3-dimensional CFD model by means of the openFoam toolbox. The strengths of this model based on the Reynolds-Averaged Navier–Stokes (RANS) equations with K-ε first-order closure model is to consider the traffic-induced momentum and turbulence (Letaïef et al., 2020). A second approach was to directly visualize the microturbulence from a 1/100 scale model of the motorway cross-section in a wind tunnel. To this end, we refracted the beam of a laser light with a glass rod to observe eddies along a thin plane through a fog generated by a fog machine. Simple shots with a camera can reveal coherent patterns in the chaos. To complete these two models, we conducted two types of field measurements of fine particle concentrations on the studied motorway sector. Direct and indirect measurements were carried out with low-cost microsensors and with environmental magnetism tools applied on dust depositions on accumulating surfaces (Hofman et al., 2017), respectively.These four approaches indicates similar results. A large recirculation wake region formed on the leeward side of the wall that brings back to the wall the pollutant generated by the traffic is evidenced. On the contrary, flat-top earth berms favor the dispersion of pollutants in the atmosphere. These 4 different approaches allowed us not only to establish these conclusions but also to communicate with all the actors concerned by this study site: scientists specialized in the metrology of atmospheric pollutants, the persons in charge of the motorway company, the elected representatives and the inhabitants of the city where the study site is located. References:Hofman, J., Maher, B. A., Muxworthy, A. R., Wuyts, K., Castanheiro, A., and Samson, R.: Biomagnetic Monitoring of Atmospheric Pollution: A Review of Magnetic Signatures from Biological Sensors, Environ Sci Technol, 51, 6648–6664, https://doi.org/10.1021/acs.est.7b00832, 2017.Letaïef, S., Camps, P., Poidras, T., Nicol, P., Bosch, D., and Pradeau, R.: Biomagnetic monitoring vs. CFD modeling: A real case study of near-source depositions of traffic-related particulate matter along a motorway, Atmosphere, 11, 1–23, https://doi.org/10.3390/atmos11121285, 2020.
Domaines
Ingénierie de l'environnementOrigine | Fichiers produits par l'(les) auteur(s) |
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