Please use this identifier to cite or link to this item: http://hdl.handle.net/1942/29697
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dc.contributor.authorDONS, Evi-
dc.contributor.authorLAEREMANS, Michelle-
dc.contributor.authorOrjuela, Juan Pablo-
dc.contributor.authorAvila-Palencia, Ione-
dc.contributor.authorde Nazelle, Audrey-
dc.contributor.authorNieuwenhuijsene, Mark-
dc.contributor.authorVan Poppel, Martine-
dc.contributor.authorCarrasco-Turigas, Gloria-
dc.contributor.authorStandaert, Arnout-
dc.contributor.authorDE BOEVER, Patrick-
dc.contributor.authorNAWROT, Tim-
dc.contributor.authorINT PANIS, Luc-
dc.date.accessioned2019-10-08T14:34:34Z-
dc.date.available2019-10-08T14:34:34Z-
dc.date.issued2019-
dc.identifier.citationATMOSPHERIC ENVIRONMENT, 213, p. 424-432-
dc.identifier.issn1352-2310-
dc.identifier.urihttp://hdl.handle.net/1942/29697-
dc.description.abstractBackground: Air quality standards are typically based on long term averages - whereas a person may encounter exposure peaks throughout the day. Exposure peaks may contribute meaningfully to health impacts beyond their contribution to long term averages, and therefore should be considered alongside longer-term exposures. We aim to define and explain peak exposure to black carbon air pollution and look at the relationship between short peak exposures and longer term personal exposure. Methods: A peak detection algorithm was applied to pooled data from two independent studies. High-resolution personal black carbon monitoring was performed in 175 healthy adult volunteers for a minimum of two 24-h periods per person. At the same time, we retrieved information on the time-activity pattern. Data covered Belgium, Spain, and the United Kingdom. In total, 2053 monitoring days were included. Results: Exposure profiles revealed 2.8 +/- 1.6 (avg +/- SD) peaks per person per day. The average black carbon concentration during a peak was 4206 ng/m(3). On 5.5% of the time participants were exposed to peak concentrations, but this contributed to 21.0% of their total exposure. The short time in transport (8%), was responsible for 32.7% of the peaks. 24.1% of the measurements in transport were categorized as peak exposure; while sleeping this was only 0.9%. When considering transport modes, participants were most likely to encounter peaks while cycling (34.0%). Most peaks were encountered at rush hour, from Monday through Friday, and in the cold season. Gender and age had no impact on the presence of peaks. Daily average black carbon exposure showed only a moderate correlation with peak frequency (r = 0.44). This correlation coefficient increased when considering longer term exposure to r > 0.60 from 10 days onward. Conclusions: The occurrence of peaks varied substantially over time, across microenvironments and transport modes. Daily average exposure was moderately correlated with peak frequency. Real-time air pollution alerting systems may use the peak detection algorithm to support citizens in self-management of air pollution health effects.-
dc.description.sponsorshipEvi Dons is supported by a postdoctoral scholarship from FWO Research Foundation Flanders. Michelle Laeremans is supported by a VITO PhD scholarship (www.vito.be).This work was partly supported by the European project PASTA (Physical Activity through Sustainable Transport Approaches), a project funded by the European Union's Seventh Framework Program (EU FP7) under European Commission Grant Agreement 602624.-
dc.language.isoen-
dc.publisherPERGAMON-ELSEVIER SCIENCE LTD-
dc.rights2019 Elsevier Ltd. All rights reserved-
dc.subject.otherAir pollution; Black carbon; Peak; Spike; Exposure; Traffic-
dc.subject.otherAir pollution; Black carbon; Peak; Spike; Exposure; Traffic-
dc.titleTransport most likely to cause air pollution peak exposures in everyday life: Evidence from over 2000 days of personal monitoring-
dc.typeJournal Contribution-
dc.identifier.epage432-
dc.identifier.spage424-
dc.identifier.volume213-
local.format.pages9-
local.bibliographicCitation.jcatA1-
dc.description.notes[Dons, Evi; De Boever, Patrick; Nawrot, Tim] Hasselt Univ, Ctr Environm Sci, Martelarenlaan 42, B-3500 Hasselt, Belgium. [Dons, Evi; Laeremans, Michelle; Van Poppel, Martine; Standaert, Arnout; De Boever, Patrick; Panis, Luc Int] Flemish Inst Technol Res VITO, Mol, Belgium. [Laeremans, Michelle; Panis, Luc Int] Hasselt Univ, Transportat Res Inst IMOB, Hasselt, Belgium. [Orjuela, Juan Pablo; de Nazelle, Audrey] Imperial Coll London, Ctr Environm Policy, London, England. [Avila-Palencia, Ione; Nieuwenhuijsene, Mark; Carrasco-Turigas, Gloria] ISGlobal, Barcelona Inst Global Hlth, Barcelona, Spain. [Avila-Palencia, Ione; Nieuwenhuijsene, Mark; Carrasco-Turigas, Gloria] Pompeu Fabra Univ UPF, Barcelona, Spain. [Avila-Palencia, Ione; Nieuwenhuijsene, Mark; Carrasco-Turigas, Gloria] CIBER Epidemiol & Salud Publ CIBERESP, Madrid, Spain. [Nawrot, Tim] Katholieke Univ Leuven, Environm & Hlth Unit, Leuven, Belgium.-
local.publisher.placeOXFORD-
local.type.refereedRefereed-
local.type.specifiedArticle-
dc.identifier.doi10.1016/j.atmosenv.2019.06.035-
dc.identifier.isi000484870900039-
item.fullcitationDONS, Evi; LAEREMANS, Michelle; Orjuela, Juan Pablo; Avila-Palencia, Ione; de Nazelle, Audrey; Nieuwenhuijsene, Mark; Van Poppel, Martine; Carrasco-Turigas, Gloria; Standaert, Arnout; DE BOEVER, Patrick; NAWROT, Tim & INT PANIS, Luc (2019) Transport most likely to cause air pollution peak exposures in everyday life: Evidence from over 2000 days of personal monitoring. In: ATMOSPHERIC ENVIRONMENT, 213, p. 424-432.-
item.fulltextWith Fulltext-
item.validationecoom 2020-
item.contributorDONS, Evi-
item.contributorLAEREMANS, Michelle-
item.contributorOrjuela, Juan Pablo-
item.contributorAvila-Palencia, Ione-
item.contributorde Nazelle, Audrey-
item.contributorNieuwenhuijsene, Mark-
item.contributorVan Poppel, Martine-
item.contributorCarrasco-Turigas, Gloria-
item.contributorStandaert, Arnout-
item.contributorDE BOEVER, Patrick-
item.contributorNAWROT, Tim-
item.contributorINT PANIS, Luc-
item.accessRightsRestricted Access-
crisitem.journal.issn1352-2310-
crisitem.journal.eissn1873-2844-
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