Source apportionment by positive matrix factorization on elemental concentration obtained in PM10 and biomonitors collected in the vicinities of a steelworks

Lage, Joana; Wolterbeek, Hubert Th.; Reis, M.A.; Chaves, P.C.; Garcia, S.; Almeida, Susana Marta

doi:10.1007/s10967-016-4751-3

Cited by 12 publications

(7 citation statements)

References 31 publications

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“…The possible emission sources which contribute to the atmospheric PM in the study area can be qualitatively identified from the correlation matrix. Given the significant positive correlations between Al-Si (r = 0.97), Al-Fe (r = 0.87), Al-Ti (r = 0.84), Si-Fe (r = 0.87), Si-Ti (r = 0.84), Ti-Fe (r = 0.84), it is concluded that these elements come from a same source, namely soil, since Al, Si, and Ti are typical soil elements [53,54]. In fact, Al, Fe, Si, and trace elements, such as Rb, are associated with feldspars, quartz, micas and Ti is associated with the titanite silicate [43].…”

Section: Spearman Correlationsmentioning

confidence: 97%

“…USEPA-SPECIATE and SPECIEUROPE databases were used to identify emission sources, selecting source profiles from the steel industry (general and specific processes) and traffic (break and tire wearing, highway vehicles) [54]. Additionally, a comparison was also done with the elemental ratios determined in the settled dust collected in the study area in 2019 [7].…”

Section: Spearman Correlationsmentioning

confidence: 99%

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Spatial Distribution of Air Pollution, Hotspots and Sources in an Urban-Industrial Area in the Lisbon Metropolitan Area, Portugal—A Biomonitoring Approach

Abecasis

Gamelas

Justino

et al. 2022

IJERPH

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This study aimed to understand the influence of industries (including steelworks, lime factories, and industry of metal waste management and treatment) on the air quality of the urban-industrial area of Seixal (Portugal), where the local population has often expressed concerns regarding the air quality. The adopted strategy was based on biomonitoring of air pollution using transplanted lichens distributed over a grid to cover the study area. Moreover, the study was conducted during the first period of national lockdown due to COVID-19, whereas local industries kept their normal working schedule. Using a set of different statistical analysis approaches (such as enrichment and contamination factors, Spearman correlations, and evaluation of spatial patterns) to the chemical content of the exposed transplanted lichens, it was possible to assess hotspots of air pollution and to identify five sources affecting the local air quality: (i) a soil source of natural origin (based on Al, Si, and Ti), (ii) a soil source of natural and anthropogenic origins (based on Fe and Mg), (iii) a source from the local industrial activity, namely steelworks (based on Co, Cr, Mn, Pb, and Zn); (iv) a source from the road traffic (based on Cr, Cu, and Zn), and (v) a source of biomass burning (based on Br and K). The impact of the industries located in the study area on the local air quality was identified (namely, the steelworks), confirming the concerns of the local population. This valuable information is essential to improve future planning and optimize the assessment of particulate matter levels by reference methods, which will allow a quantitative analysis of the issue, based on national and European legislation, and to define the quantitative contribution of pollution sources and to design target mitigation measures to improve local air quality.

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Section: Spearman Correlationsmentioning

confidence: 97%

Section: Spearman Correlationsmentioning

confidence: 99%

Spatial Distribution of Air Pollution, Hotspots and Sources in an Urban-Industrial Area in the Lisbon Metropolitan Area, Portugal—A Biomonitoring Approach

Abecasis

Gamelas

Justino

et al. 2022

IJERPH

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“…The soil dust source was identified by the high contribution of crustal elements, such as Mg, Al, Ti, Si, Ca, Th, Ba, La, K, and Fe [57]. More than 40% of the mass of key crustal elements (such as Si, Ca, K, and Mg) was assigned to this factor by the model.…”

Section: Source Apportionment Of Elemental Concentrationsmentioning

confidence: 99%

First-Time Source Apportionment Analysis of Deposited Particulate Matter from a Moss Biomonitoring Study in Northern Greece

et al. 2021

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Moss biomonitoring is a widely used technique for monitoring the accumulation of trace elements in airborne pollution. A total of one hundred and five samples, mainly of the Hypnum cupressiforme Hedw. moss species, were collected from the Northern Greece during the 2015/2016 European ICP Vegetation (International Cooperative Program on Effects of Air Pollution on Natural Vegetation and Crops) moss survey, which also included samples from the metalipherous area of Skouries. They were analyzed by means of neutron activation analysis, and the elemental concentrations were determined. A positive matrix factorization (PMF) model was applied to the results obtained for source apportionment. According to the PMF model, five sources were identified: soil dust, aged sea salt, road dust, lignite power plants, and a Mn-rich source. The soil dust source contributed the most to almost all samples (46% of elemental concentrations, on average). Two areas with significant impact from anthropogenic activities were identified. In West Macedonia, the emissions from a lignite power plant complex located in the area have caused high concentrations of Ni, V, Cr, and Co. The second most impacted area was Skouries, where mining activities and vehicular traffic (probably related to the mining operations) led to high concentrations of Mn, Ni, V, Co, Sb, and Cr.

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“…2, it is possible to assess that the levels of Fe and Ca found in the studied settled dust are in agreement (below 30% of variability) to the ones found in industrial environments with steelworks. In fact, the possible anthropogenic sources for these elements may be iron and steel industries for Fe and the cement industry or from fugitive emissions from the sinter plant for Ca [26,43], respectively. Regarding the industrial environment with steelworks nearby, a good agreement between elemental mass fractions were also found for Ga and Sr (also below 30% of variability).…”

Section: Understanding the Origin Of The Settled Dustmentioning

confidence: 99%

Contribution of micro-PIXE to the characterization of settled dust events in an urban area affected by industrial activities

Justino

Canha

Gamelas

et al. 2019

J Radioanal Nucl Chem

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This study aimed to identify possible sources of settled dust events that occurred in an urban area nearby an industrial park, which alarmed the local population. Settled dust was collected in January 2019 and its chemical characterization was assessed by micro-PIXE, focusing on a total of 29 elements. Comparison with chemical profiles of particulate matter from different types of environment was conducted, along with the assessment of crustal enrichment factors and Spearman correlations, allowing to understand which sources were contributing to this settled dust event. A nearby industrial area's influence was identified due to the contents of Fe, Cr and Mn, which are typical tracers of iron and steel industries.

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Source apportionment by positive matrix factorization on elemental concentration obtained in PM10 and biomonitors collected in the vicinities of a steelworks

Cited by 12 publications

References 31 publications

Spatial Distribution of Air Pollution, Hotspots and Sources in an Urban-Industrial Area in the Lisbon Metropolitan Area, Portugal—A Biomonitoring Approach

Spatial Distribution of Air Pollution, Hotspots and Sources in an Urban-Industrial Area in the Lisbon Metropolitan Area, Portugal—A Biomonitoring Approach

First-Time Source Apportionment Analysis of Deposited Particulate Matter from a Moss Biomonitoring Study in Northern Greece

Contribution of micro-PIXE to the characterization of settled dust events in an urban area affected by industrial activities

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