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dc.contributor.authorMooibroek, Dennis
dc.contributor.authorSofowote, Uwayemi M
dc.contributor.authorHopke, Philp K
dc.date.accessioned2022-08-23T09:31:23Z
dc.date.available2022-08-23T09:31:23Z
dc.date.issued2022-08-11
dc.identifier.pmid35964756
dc.identifier.doi10.1016/j.scitotenv.2022.157981
dc.identifier.urihttp://hdl.handle.net/10029/626039
dc.description.abstractChemical speciation data for PM10, collected for annual trend analyses of health-relevant species, at three receptor sites in a highly industrialized area (IJmond) in the Netherlands were used in a multi-time resolution receptor model (ME-2) to identify the PM10 sources in this area. Despite the available data not being optimized for receptor modelling, five-factor solutions were obtained for all sites based on independent PMF analysis on PM10 data from the three sites (IJM, WAZ and BEV). Four factors were common to all three sites: nitrate-sulphate (average percentage contributions to PM10: IJM: 35.3 %, WAZ: 37.7 %, and BEV: 36.3 %); sea salt (20.2 %, 23.7 %, 15.2 %); industrial (8.1 %, 11.0 %, 18.1 %) and brake wear/traffic (31.4 %, 21.2 %, 20.6 %). At WAZ, a local/site-specific factor containing most of the PAH measurements was found (6.4 %) while a crustal matter factor was resolved at IJM (7.6 %) and BEV (9.8 %). Additionally, sludge-drying was a potential source of the marker species in the industrial factor at WAZ. Bootstrapping (BS) and factor displacement (DISP) were applied to the factor profiles in this work for error estimation. In general, the factor profiles at all three sites had very small intervals from both BS and DISP methods. To our knowledge, this is the first time DISP was applied in a complex model such as the multi-time resolution model. Most of the measured metal and PAH concentrations found in the IJmond area during the 2017-2019 period had local sources, with significant contributions from several processes related to the steel industry. This study shows that available detailed PM10 chemical speciation data, although primarily collected for annual trend analyses of health-relevant species, could also be used in receptor modelling by applying a multi-time framework. We propose general recommendations for the optimization of the measurement strategy for source apportionment of PM in areas with similar urban-industrial land use.en_US
dc.language.isoenen_US
dc.rightsCopyright © 2022. Published by Elsevier B.V.
dc.subjectDiagnosticsen_US
dc.subjectIndustrial areaen_US
dc.subjectME-2en_US
dc.subjectMulti-time resolutionen_US
dc.subjectPM(10)en_US
dc.subjectPMFen_US
dc.titleSource apportionment of ambient PM collected at three sites in an urban-industrial area with multi-time resolution factor analyses.en_US
dc.typeArticleen_US
dc.identifier.eissn1879-1026
dc.identifier.journalThe Science of the total environment 20 850:15798122;en_US
dc.source.journaltitleThe Science of the total environment
dc.source.beginpage157981
dc.source.endpage
dc.source.countryNetherlands


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