| Literature DB >> 24875261 |
A M Taiwo1, D C S Beddows1, G Calzolai2, Roy M Harrison3, F Lucarelli2, S Nava4, Z Shi1, G Valli5, R Vecchi5.
Abstract
In this study, the Multilinear Engine (ME-2) receptor model was applied to speciated particulate matter concentration data collected with two different measuring instruments upwind and downwind of a steelworks complex in Port Talbot, South Wales, United Kingdom. Hourly and daily PM samples were collected with Streaker and Partisol samplers, respectively, during a one month sampling campaign between April 18 and May 16, 2012. Daily samples (PM10, PM2.5, PM2.5-10) were analysed for trace metals and water-soluble ions using standard procedures. Hourly samples (PM2.5 and PM2.5-10) were assayed for 22 elements by Particle Induced X-ray Emission (PIXE). PM10 data analysis using ME-2 resolved 6 factors from both datasets identifying different steel processing units including emissions from the blast furnaces (BF), the basic oxygen furnace steelmaking plant (BOS), the coke-making plant, and the sinter plant. Steelworks emissions were the main contributors to PM10 accounting for 45% of the mass when including also secondary aerosol. The blast furnaces were the largest emitter of primary PM10 in the study area, explaining about one-fifth of the mass. Other source contributions to PM10 were from marine aerosol (28%), traffic (16%), and background aerosol (11%). ME-2 analysis was also performed on daily PM2.5 and PM2.5-10 data resolving 7 and 6 factors, respectively. The largest contributions to PM2.5-10 were from marine aerosol (30%) and blast furnace emissions (28%). Secondary components explained one-half of PM2.5 mass. The influence of steelworks sources on ambient particulate matter at Port Talbot was distinguishable for several separate processing sections within the steelworks in all PM fractions.Entities:
Keywords: Hourly resolution; ME-2; Receptor modelling; Source apportionment; Steelworks
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Year: 2014 PMID: 24875261 DOI: 10.1016/j.scitotenv.2014.04.118
Source DB: PubMed Journal: Sci Total Environ ISSN: 0048-9697 Impact factor: 7.963