EXPLUME v1.0: a model for personal exposure to ambient O<sub>3</sub> and PM<sub>2.5</sub>

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.

Environmental Health Surveillance System for a Population Using Advanced Exposure Assessment

“…Exposure was calculated based on the sum of the time spent by individuals in different microenvironments and the average concentration of time-weighted pollutants at this specific location [9]. The general structure of the model with the environmental health surveillance system and the input dataset required to calculate exposure of the population and risk management is shown in Figure 2.…”

“…Based on this assessment, environmental health policies may be developed for risk management. Exposure was conceptualized as the sum of the product of time spent by an individual or population in different microenvironments and the time-weighted average concentrations of air pollutants in those locations [9], as shown in the following equation [21].…”

“…Exposure was conceptualized as the sum of the product of time spent by an individual or population in different microenvironments and the time-weighted average concentrations of air pollutants in those locations [ 9 ], as shown in the following equation [ 21 ]. where exposure (E) may be defined as a function of the air pollutant concentration ( C ) and time intervals ( t ).…”

“…While Breen et al used [10] an exposure model (EMI) for individuals to conduct exposure assessments, the USEPA developed the air pollutants exposure model (APEX) to estimate exposure to PM 2.5 [57]. Valari et al [9] proposed exposure to atmospheric pollution modeling (EXPLUME), a local-scale individual exposure model that includes spatial activity event sequences and the infiltration of outdoor air pollutants into the indoor environment.…”

“…Although most air pollutants have been monitored, PM has been the most widely studied in terms of its environmental health risk and health effects; health risks from exposure to PM (PM 10 and PM 2.5 ) are more serious than those posed by other air pollutants [7]. Exposure to PM has been reported to have adverse respiratory and cardiovascular health effects, including decreased lung function, asthma, cardiopulmonary disease, and lung cancer [4,8,9].…”