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A detailed physical and chemical characterization of coarse particulate matter (PM10) and fine particulate matter (PM2.5) in the city of Huelva (in Southwestern Spain) was carried out during 2001 and 2002. To identify the major emission sources with a significant influence on PM10 and PM2.5, a methodology was developed based on the combination of: (1) real-time measurements of levels of PM10, PM2.5, and very fine particulate matter (PM1); (2) chemical characterization and source apportionment analysis of PM10 and PM2.5; and (3) intensive measurements in field campaigns to characterize the emission plumes of several point sources. Annual means of 37, 19, and 16 µg/m³were obtained for the study period for PM10, PM2.5, and PM1, respectively. High PM episodes, characterized by a very fine grain size distribution, are frequently detected in Huelva mainly in the winter as the result of the impact of the industrial emission plumes on the city. Chemical analysis showed that PM at Huelva is characterized by high PO43- and As levels, as expected from the industrial activities. Source apportionment analyses identified a crustal source (36% of PM10 and 31% of PM2.5); a traffic-related source (33% of PM10 and 29% of PM2.5), and a marine aerosol contribution (only in PM10, 4%). In addition, two industrial emission sources were identified in PM10 and PM2.5: (1) a petrochemical source, 13% in PM10 and 8% in PM2.5; and (2) a mixed metallurgical-phosphate source, which accounts for 11-12% of PM10 and PM2.5. In PM2.5 a secondary source has been also identified, which contributed to 17% of the mass. A complete characterization of industrial emission plumes during their impact on the ground allowed for the identification of tracer species for specific point sources, such as petrochemical, metallurgic, and fertilizer and phosphate production industries. [ABSTRACT FROM AUTHOR]

Speciated coarse particulate matter (PM10) data obtained at three air quality monitoring sites in a highly industrialized area in Spain between 2002 and 2007 were analyzed for assessing source contribution of ambient particulate matter (PM). The source apportionment of PM in this area is an especially difficult task. There are industrial mineral dust emissions that need to be separately quantified from the natural sources of mineral PM. On the other hand, the diversity of industrial processes in the area results in a puzzling industrial emissions scenario. To solve this complex problem, a two-step methodology based on the possibilities of the Multilinear Engine was used. Application of positive matrix factorization to the dataset allowed the identification of nine factors relevant to the study area. This preliminary analysis permitted resolving two mineral factors. As a second step, a target rotation was implemented for transforming the mineral factors into experimentally characterized soil resuspension and industrial clay sources. In addition to improving the physical interpretation of these factors, the target rotation reduced the errors arising from the rotational freedom of the solution and the multicollinearity among sources. In this way, the main primary industrial emissions of PM in the zone were identified by this target factor analysis. A marked decrease was observed between 2002 and 2007 for the contributions of industrial sources coinciding with the implementation of mitigation measures in their processes. This study supports the utility of source apportionment methodologies for quantitatively evaluating the effectiveness of the abatement programs for air quality improvement. [ABSTRACT FROM AUTHOR]