Predicting changes in PM exposure over time at U.S. trucking terminals using structural equation modeling techniques...particulate matter
This study analyzes the temporal variability of occupational and environmental exposures to fine particulate matter in the U.S. trucking industry and tests the predictive ability of a novel multilayer statistical approach to occupational exposure modeling using structural equation modeling (SEM) tec...
| Publicado en: | Journal of Occupational & Environmental Hygiene Vol. 6; no. 7; pp. 396 - 404 |
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| Autores principales: | , , , , , |
| Formato: | equations & formulas research tables/charts Journal Article |
| Publicado: |
Taylor & Francis Ltd
Jul2009
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| Acceso en línea: | Ver este registro en EBSCOhost |
| fields | @attributes: recordID: 1 pdfLink: plink: https://search.ebscohost.com/login.aspx?direct=true&db=ccm&AN=105512477&site=ehost-live header: @attributes: shortDbName: ccm uiTerm: 105512477 longDbName: CINAHL Complete uiTag: AN controlInfo: bkinfo: dissinfo: jinfo: jid: 15459624 V1L jtl: Journal of Occupational & Environmental Hygiene issn: 15459624 maglogo: Y pubinfo: dt: Jul2009 vid: 6 iid: 7 pid: 377 pub: Taylor & Francis Ltd place: Philadelphia, Pennsylvania artinfo: ui: 105512477 2010260842 10.1080/15459620902914349 NLM19367483 105512477 ppf: 396 ppct: 8 formats: fmt: @attributes: type: P tig: atl: Predicting changes in PM exposure over time at U.S. trucking terminals using structural equation modeling techniques...particulate matter aug: au: Davis ME Laden F Hart JE Garshick E Blicharz A Smith TJ affil: Department of Urban and Environmental Policy and Planning, Tufts University, Medford, Massachusetts 02155, USA. mary.davis@tufts.edu sug: subj: Carbon Analysis Motor Vehicles Occupational Exposure Particulate Matter Analysis Time Factors Air Pollution Evaluation Data Analysis Software Education, Continuing (Credit) Funding Source Nonparametric Statistics Structural Equation Modeling Time United States Human ab: This study analyzes the temporal variability of occupational and environmental exposures to fine particulate matter in the U.S. trucking industry and tests the predictive ability of a novel multilayer statistical approach to occupational exposure modeling using structural equation modeling (SEM) techniques. For these purposes, elemental carbon mass in PM<1 microm at six U.S. trucking terminals were measured twice during the same season up to 2 years apart, observing concentrations in the indoor loading dock (median EC: period 1 = 0.65 microg/m(3); period 2 = 0.94 microg/m(3)) and outdoor background location (median EC: period 1 = 0.46 microg/m(3); period 2 = 0.67 microg/m(3)), as well as in the truck cabs of local drivers while on the road (median EC: period 1 = 1.09 microg/m(3); period 2 = 1.07 microg/m(3)). There was a general trend toward higher exposures during the second sampling trips; however, these differences were statistically significant in only a few cases and were largely attributable to changes in weather patterns (wind speed, precipitation, etc.). Once accounting for systematic prediction errors in background concentrations, the SEM approach provided a strong fit for work-related exposures in this occupational setting. pubtype: Academic Journal doctype: equations & formulas research tables/charts Journal Article ougenre: Article language: English refInfo: holdings: @attributes: islocal: N |
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