Abstract
Abstract. This paper presents the first version of the regional-scale personal exposure model EXPLUME (EXposure to atmospheric PolLUtion ModEling). The model uses simulated gridded data of outdoor O3 and PM2.5 concentrations and several population and building-related datasets to simulate (1) space–time activity event sequences, (2) the infiltration of atmospheric contaminants indoors, and (3) daily aggregated personal exposure. The model is applied over the greater Paris region at 2 km×2 km resolution for the entire year of 2017. Annual averaged population exposure is discussed. We show that population mobility within the region, disregarding pollutant concentrations indoors, has only a small effect on average daily exposure. By contrast, considering the infiltration of PM2.5 in buildings decreases annual average exposure by 11 % (population average). Moreover, accounting for PM2.5 exposure during transportation (in vehicle, while waiting on subway platforms, and while crossing on-road tunnels) increases average population exposure by 5 %. We show that the spatial distribution of PM2.5 and O3 exposure is similar to the concentration maps over the region, but the exposure scale is very different when accounting for indoor exposure. We model large intra-population variability in PM2.5 exposure as a function of the transportation mode, especially for the upper percentiles of the distribution. Overall, 20 % of the population using bicycles or motorcycles is exposed to annual average PM2.5 concentrations above the EU target value (25 µg m−3), compared to 0 % for people travelling by car. Finally, we develop a 2050 horizon projection of the building stock to study how changes in the buildings' characteristics to comply with the thermal regulations will affect personal exposure. We show that exposure to ozone will decrease by as much as 14 % as a result of this projection, whereas there is no significant impact on exposure to PM2.5.
Highlights
Air pollution is the first environmental health risk with significant effects on morbidity and mortality (Lim et al, 2012; WHO, 2013)
In France, in 2004–2006, about 3000 deaths per year were attributed to levels of PM2.5 exceeding the WHO guideline value in nine French urban areas participating in the Aphekom project (Pascal et al, 2013)
This paper presents the first version of a regional-scale model for personal exposure to O3 and PM2.5
Summary
Air pollution is the first environmental health risk with significant effects on morbidity and mortality (Lim et al, 2012; WHO, 2013). To study the health risk on specific population groups – such as children, elderly people, asthma patients, or pregnant women (Olsson et al, 2014), or the health effects of co-pollutants (Olstrup et al, 2019b, a; Valari et al, 2011), or the risk associated with living or working near busy roads (Lipfert and Wyzga, 2008; Miranda et al, 2013) – one has to account for pollutant concentration at district level, population dynamics, and exposure indoors and during transport (Franklin et al, 2012; Hodas et al, 2012) To answer this emerging demand, several methods for estimating personal exposure have been developed. The originality of the model lies in the development of (i) individual activity sequences that are defined geographically in space and time and (ii) the modelling of seasonal distributions of indoor / outdoor ratios by building type and age This latter feature is unique in personal exposure modelling since, typically, indoor pollutant concentrations rely on measurements for a few locations that may not represent the area’s buildings. Personal exposure is simulated for the entire year of 2017 over the Île-de-France region (greater Paris)
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