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Using multi-site data to apportion PM-bound metal(loid)s: Impact of a manganese alloy plant in an urban area

Abstract: The identification and quantification of the PM emission sources influencing a specific area is vital to better assess the potential health effects related to the PM exposure of the local population. In this work, a multi-site PM10 sampling campaign was performed in seven sites located in the southern part of the Santander Bay (northern Spain), an urban area characterized by the proximity of some metal(loid) industrial sources (mainly a manganese alloy plant). The total content of V, Mn, Fe, Ni, Cu, Zn, As, Mo, Cd, Sb and Pb was determined by ICP-MS. This multi-site dataset was evaluated by positive matrix factorization(PMF) in order to identify the main anthropogenic metal(loid) sources impacting the studied area, and to quantify their contribution to the measured metal(loid) levels. The attribution of the sources was done by comparing the factor profiles obtained by the PMF analysis with representative profiles from known metal(loid) sources in the area, included in both the European database SPECIEUROPE (V2.0) and the US database EPA-SPECIATE (V4.5) or calculated from literature data. In addition, conditional bivariate probability functions (CBPF)s were used to assist in the identification of the sources. Four metal(loid) sources were identified: Fugitive and point source emissions from the manganese alloy plant (49.9% and 9.9%, respectively), non-exhaust traffic emissions (38.3%) and a minor source of mixed origin (1.8%). The PMF analysis was able to make a clear separation between two different sources from the manganese alloy plant, which represented almost 60% of the total measured metal(loid) levels, >80% of these emissions being assigned to fugitive emissions. These results will be useful for the assessment of the health risk associated with PM10-bound metal(loid) exposure and for the design of efficient abatement strategies in areas impacted by similar industries.

 Autoría: Hernández-Pellón A., Fernández-Olmo I.,

 Fuente: Science of the Total Environment, 2019, 651(1), 1476-1488

 Editorial: Elsevier

 Fecha de publicación: 15/02/2019

 Nº de páginas: 59

 Tipo de publicación: Artículo de Revista

 DOI: 10.1016/j.scitotenv.2018.09.261

 ISSN: 0048-9697,1879-1026

 Proyecto español: CTM2013-43904R

 Url de la publicación: https://doi.org/10.1016/j.scitotenv.2018.09.261