{"doc_desc":{"title":"Real-time comparison of four particulate matter size fractions in personal breathing zone of Paris subway workers: A six-week prospective study","idno":"10.16909-DATASET-28","producers":[{"name":"Center for Primary Care and Public Health (Unisant\u00e9), University of Lausanne, Switzerland","abbreviation":"Unisant\u00e9","affiliation":"","role":"Data publisher"}],"version_statement":{"version":"Version 1.0 (December 2020)"}},"study_desc":{"title_statement":{"idno":"10.16909-DATASET-28","title":"Real-time comparison of four particulate matter size fractions in personal breathing zone of Paris subway workers: A six-week prospective study","translated_title":"Comparaison en temps r\u00e9el de quatre fractions de taille de particules dans la zone de respiration personnelle des travailleurs du m\u00e9tro de Paris : Une \u00e9tude prospective de six semaines"},"authoring_entity":[{"name":"Guseva Canu, Irina","affiliation":"Center for Primary Care and Public Health (Unisant\u00e9), Department of occupational and environmental health (DSTE)"}],"production_statement":{"producers":[{"name":"P\u00e9tremand, Remy","affiliation":"Center for Primary Care and Public Health (Unisant\u00e9), Department of occupational and environmental health (DSTE)","role":"Investigator, first author"},{"name":"Suarez, Guillaume","affiliation":"Center for Primary Care and Public Health (Unisant\u00e9), Department of occupational and environmental health (DSTE)","role":"Investigator, co-author"},{"name":"Besan\u00e7on, Sophie","affiliation":"R\u00e9gie autonome des transports parisiens (RATP)","role":"Investigator, co-author"},{"name":"Dil, Hugo","affiliation":"Ecole polytechnique f\u00e9d\u00e9rale de Lausanne (EPFL)","role":"Investigator, co-author"}],"copyright":"(c) 2021, Center for Primary Care and Public Health (Unisant\u00e9), University of Lausanne, Switzerland and R\u00e9gie autonome des transports parisiens (RATP), Paris, France","funding_agencies":[{"name":"Schweizerischer Nationalfonds zur F\u00f6rderung der Wissenschaftlichen Forschung (IZCOZ0_177067)","abbreviation":"FNS","role":""}]},"version_statement":{"version":"Version 1.1","version_date":"2022-04-19"},"study_info":{"keywords":[{"keyword":"Subway","vocab":"","uri":""},{"keyword":"Underground workplace","vocab":"","uri":""},{"keyword":"Exposure","vocab":"","uri":""},{"keyword":"Particulate matter","vocab":"","uri":""},{"keyword":"Ultrafine particles","vocab":"","uri":""},{"keyword":"Exposure assessment","vocab":"","uri":""},{"keyword":"Bayesian Inference","vocab":"","uri":""}],"abstract":"We developed a Bayesian spline model for the real-time mass concentrations of PM10, PM2.5, PM1, and PM0.3 measured simultaneously in personal breathing zone of Parisian subway workers. The measurements were performed by GRIMM, gravimetric method, and DiSCmini during the workers\u2019 work-shifts over two consecutive weeks. The PM0.3 concentrations were more than an order of magnitude lower compared to the other PM and showed the highest temporal variation, followed by PM1. The PM2.5 raised the highest exposure concern: 15 stations out of 37 had higher mass concentrations compared to the reference. Twelve of these also had significantly higher PM1 mass concentration. Station PM levels were not correlated with the annual number of passengers entering the station, year of station opening or renovation, or the number of platforms and tracks. The correlation with the number of station entrances was con-sistently negative for all PM sizes. The number of correspondence concourses was negatively correlated with PM0.3 and PM10 and positively correlated with PM1 and PM2.5. Almost all studied environments had higher PM exposure compared to the study room, although the highest levels of PM were measured outdoors. The highest PM10 exposure was observed at the station platform, followed by the subway cabin and train, while ticket counters had the highest PM0.3, PM1, and PM2.5 mass concentrations. Compared with gravimetric and DiSCmini meas-urements, GRIMM results showed some discrepancies, with an underestimation of exposure levels. Therefore, we suggest to use GRIMM, calibrated by gravimetric methods, for PM sizes above 1\u03bcm, and a DiSCmini for sizes below 700nm.","coll_dates":[{"start":"2019-09-01","end":"2021-03-30","cycle":""}],"nation":[{"name":"France","abbreviation":"FR"},{"name":"Switzerland","abbreviation":"CHE"}],"geog_coverage":"Paris, France","analysis_unit":"Particle Mass Concentration (\u03bcg\/cm3) \nParticle Number Concentration (#\/cm3)","data_kind":"One script of statistical analysis using R (Suppl_file_1_BUGS_model.R)\nFour Excel files:\nThe first one (File1_PM_daily_summary.xlsx) presents the summary statistics of particle mass concentration per day. \nThe second file (File2_Calibrated_PM10_&_PM25_Bayesian_Spline_coefficients.xlsx) presents the Summary statistics for coefficients \u03b4 and \u03c3(Day), Summary statistics for coefficients \u03bc\u03b4(Job) and \u03c3\u03b4(job), Summary statistics for coefficients \u03b1(Station) and Summary statistics for coefficients \u03b2(Environments) obtained using the calibrated PM2.5 and P\u00fcM10 time-series\nThe third file (File3_All_PM_Bayesian_Spline_Coefficients.xlsx) presents the same summary statistics for coefficients \u03b4 and \u03c3(Day), Summary statistics for coefficients \u03bc\u03b4(Job) and \u03c3\u03b4(job), Summary statistics for coefficients \u03b1(Station) and Summary statistics for coefficients \u03b2(Environments) but using row time-series data for PM0.3, PM1, PM2.5, and PM10\nFinally, the fourth file (File4_All_PM_Bayesian_Spline_Coefficients.xlsx) regroups the descriptive summary of Particulate Number Concentration (PNC) of PM0.3 for the following variables: days, stations, environments and events.  \nEach Excel sheet contains the descriptive summary for one variable and is names accordingly"},"data_access":{"dataset_use":{"contact":[{"name":"Racine, C\u00e9line (Repository manager)","affiliation":"Center for Primary Care and Public Health (Unisant\u00e9), University of Lausanne, Switzerland","email":"dfri.data@unisante.ch","uri":""}],"cit_req":"P\u00e9tremand, R\u00e9my, Suarez, Guillaume, Besan\u00e7on, Sophie, Dil, Hugo ,Guseva Canu, Irina. Real-time comparison of four particulate matter size fractions in personal breathing zone of Paris subway workers: A six-week prospective study Subway particle exposure. Supplementary material files. Center for Primary Care and Public Health (Unisant\u00e9), University of Lausanne, Switzerland. Version 1.0 of the licensed dataset (December 2021), provided by the Unisant\u00e9 Research Data Repository. DOI:10.16909\/DATASET\/28","disclaimer":"The user of the data acknowledges that the original collector of the data, the authorized distributor of the data, and the relevant funding agency bear no responsibility for use of the data or for interpretations or inferences based upon such uses."}}},"schematype":"survey"}