title: BTX concentrations near a stage II implemented petrol station.
abstract: A combined monitoring and dispersion modelling methodology was applied for assessing air quality at three different levels of proximity to the selected service station: (I) next to the fuel pumps, (II) in the surrounding environment, and (III) in the background. Continuous monitoring and passive sampling were used for achieving high temporal and spatial resolution, respectively. A Gaussian dispersion model (CALINE4) was used for assessing the road traffic contribution to the local concentrations under different meteorological conditions. It was established that Stage 2 vapour recovery reduces BTX concentrations not only near the pumps, but also in their surrounding environment. However, there is evidence that the efficiency of the system is wind speed dependent. The modelling simulation of the worst case wind scenario revealed the significance of local traffic emissions. It was shown that the traffic contribution even from a single road in the vicinity of the station can, under certain conditions, be higher than the contribution of the station itself to the local BTX levels. Finally, after comparison with previous studies, the concentrations measured near the service station (which was situated in a rural environment) appear to be lower than those observed in busy street canyons in city centres. It can be concluded, although Stage 2 recovery system effectively reduces working VOC losses in service stations, that it will only have a limited positive impact on local air quality if the service station is located in a heavily polluted area.
authors.affiliation: Institut National de l'Environnement Industriel et des Risques (INERIS), Parc Technologique ALATA, BP2, 60550 Verneuil-en-Halatte, France. Norbert.Gonzalez-Flesca@ineris.fr
authors.forename: Norbert
authors.initials: N
authors.lastname: Gonzalez-Flesca
authors.forename: Sotiris
authors.initials: S
authors.lastname: Vardoulakis
authors.forename: André
authors.initials: A
authors.lastname: Cicolella
mesh_terms: D000393:Air Pollutants / Q000032:analysis*; D000397:Air Pollution / Q000517:prevention & control*; D004784:Environmental Monitoring; D006838:Hydrocarbons / Q000032:analysis*; D008962:Models, Theoretical; D018986:Motor Vehicles; D010578:Petroleum; D014835:Volatilization
chemical_list: D000393:Air Pollutants; D006838:Hydrocarbons; D010578:Petroleum