RESUMO
Urban air pollution is one of the most important environmental problems for human health and several strategies have been developed for its mitigation. The objective of this study is to assess the impact of single and combined mitigation measures on concentrations of air pollutants emitted by traffic at pedestrian level in the same urban environment. The effectiveness of different scenarios of green infrastructure (GI), the implementation of photocatalytic materials and traffic low emission zones (LEZ) are investigated, as well as several combinations of LEZ and GI. A wide set of scenarios is simulated through Computational Fluid Dynamics (CFD) modelling for two different wind directions (perpendicular (0°) and 45° wind directions). Wind flow for the BASE scenario without any measure implemented was previously evaluated using wind-tunnel measurements. Air pollutant concentrations for this scenario are compared with the results obtained from the different mitigation scenarios. Reduction of traffic emissions through LEZ is found to be the most effective single measure to improve local air quality. However, GI enhances the effects of LEZ, which makes the combination of LEZ + GI a very effective measure. The effectiveness of this combination depends on the GI layout, the intensity of emission reduction in the LEZ and the traffic diversion in streets surrounding the LEZ. These findings, in line with previous literature, suggest that the implementation of GI may increase air pollutant concentrations at pedestrian level for some cases. However, this study highlights that this negative effect on air quality can turn into positive when used in combination with reductions of local traffic emissions.
RESUMO
Health impacts of atmospheric pollution is an important issue in urban environments. Its magnitude depends on population exposure which have been frequently estimated by considering different approaches relating pollutant concentration and population exposed to it. However, the uncertainties due to the spatial resolution of the model used to estimate the pollutant concentration or due to the lack of representativeness of urban air quality monitoring station (AQMS) have not been evaluated in detail. In this context, NO2 annual average concentration at pedestrian level in the whole city of Pamplona (Spain) modelled at high spatial resolution (~1 m) by Computational Fluid Dynamic (CFD) simulations is used to estimate the total population exposure and health-related externalities by using different approaches. Air pollutant concentration and population are aggregated at different spatial resolutions ranging from a horizontal grid cell size of 100 m × 100 m to a coarser resolution where the whole city is covered by only one cell (6 km × 5 km). In addition, concentrations at AQMS locations are also extracted to assess the representativeness of those AQMS. The case with a spatial resolution of 100 m × 100 m for both pollutant-concentration distribution and population data is used as a reference (Base case) and compared with those obtained with the other approaches. This study indicates that the spatial resolution of concentration and population distribution in the city should be 1 km × 1 km or finer to obtain appropriate estimates of total population exposure (underestimations <13%) and health-related externalities (underestimations <37%). For the cases with coarser resolutions, a strong underestimation of total population exposure (>31%) and health-related externalities (>76%) was found. On the other hand, the use of AQMS concentrations can induce important errors due to the limited spatial representativeness, in particular in terms of population exposure.
