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Application of the Bayesian spline method to analyze real-time measurements of ultrafine particle concentration in the Parisian subway

Authors :
Rémy Pétremand
Pascal Wild
Camille Crézé
Guillaume Suarez
Sophie Besançon
Valérie Jouannique
Amélie Debatisse
Irina Guseva Canu
Source :
Environment International, Vol 156, Iss , Pp 106773- (2021)
Publication Year :
2021
Publisher :
Elsevier, 2021.

Abstract

Background: Air pollution in subway environments is a growing concern as it often exceeds WHO recommendations for indoor air quality. Ultrafine particles (UFP), for which there is still no regulation nor a standardized exposure monitoring method, are the strongest contributor to this pollution when the number concentration is used as exposure metric. Objectives: We aimed to assess the real-time UFP number concentration in the personal breathing zone (PBZ) of three types of underground Parisian subway professionals and analyze it using a novel Bayesian spline approach. Consecutively, we investigated the effect of job, week day, subway station, worker location, and some further events on UFP number concentrations. Methods: The data collection procedure originated from a longitudinal study and lasted for a total duration of 6 weeks (from October 7 to November 15, 2019, i.e. two weeks per type of subway professionals). Time-series were built from the real-time particle number concentration (PNC) measured in the PBZ of professionals during their work-shifts. Complementarily, contextual information expressed as Station, Environment, and Event variables were extracted from activity logbooks completed for every work-shift. A Bayesian spline approach was applied to model the PNC within a Bayesian framework as a function of the mentioned contextual information. Results: Overall, the Bayesian spline method suited a real-time personal PNC data modeling approach. The model enabled estimating the differences in UFP exposure between subway professionals, stations, and various locations. Our results suggest a higher PNC closer to the subway tracks, with the highest PNC on subway station platforms. Studied event and week day variables had a lesser influence. Conclusion: It was shown that the Bayesian spline method is suitable to investigate individual exposure to UFP in underground subway settings. This method is informative for better documenting the magnitude and variability of UFP exposure, and for understanding the determinants in view of further regulation and control of this exposure.

Details

Language :
English
ISSN :
01604120
Volume :
156
Issue :
106773-
Database :
Directory of Open Access Journals
Journal :
Environment International
Publication Type :
Academic Journal
Accession number :
edsdoj.7202704ce58440d8b4be42017bff2cbf
Document Type :
article
Full Text :
https://doi.org/10.1016/j.envint.2021.106773