A very-low volume sampler of particulate matter (PM) on membrane filters, recently developed with the purpose of allowing spatially-resolved determination of PM and of its chemical components, was employed from December 2016 to February 2018 in a wide and dense monitoring network across Terni, an urban and industrial hot-spot of Central Italy (23 sampling sites, about 1 km between each other). Terni basin can be considered as an open air laboratory for studying the spatial distribution of PM, as it includes several spatially disaggregated sources. PM10 samples were chemically characterized for the water-soluble and insoluble fraction of 33 elements (Al, As, Ba, Bi, Ca, Cd, Ce, Co, Cr, Cs, Cu, Fe, Ga, K, La, Li, Mg, Mn, Mo, Na, Nb, Ni, Pb, Rb, Sb, Sn, Sr, Ti, Tl, U, W, Zn, Zr). Spatial variability of the element concentrations across Terni was then mapped by using the ordinary kriging interpolation method. Spatial distribution of the analyzed elements successfully traced the various PM10 sources. In particular, the spatial mapping of Ba (water-soluble fraction), Bi, Cu, Sb, Sn and Zr (insoluble fraction) traced PM10 emission from the rail network and vehicular traffic, Ce, Cs, La, Li, Rb, Sr and U (insoluble fraction) traced soil resuspension, Cd, Cs, K, Rb and Tl (water-soluble fraction) biomass burning and Co, Cr, Mn, Nb, Ni, Pb (insoluble fraction), As, Cr, Ga, Li, Mo, Mn, W and Zn (water-soluble fraction) the steel industry pole. Principal component analysis was performed on the spatially-resolved chemical data to cluster the elements tracing the main PM10 sources. The winter and summer size distribution of the water-soluble and insoluble elements was analyzed to verify their link with the emission sources. The proposed experimental approach promises to be very effective for the assessment of population exposure to different PM10 sources.

High resolution spatial mapping of element concentrations in PM10. A powerful tool for localization of emission sources / Massimi, Lorenzo; Ristorini, Martina; Astolfi, Maria Luisa; Perrino, Cinzia; Canepari, Silvia. - In: ATMOSPHERIC RESEARCH. - ISSN 0169-8095. - 244(2020), pp. 1-11. [10.1016/j.atmosres.2020.105060]

High resolution spatial mapping of element concentrations in PM10. A powerful tool for localization of emission sources

Lorenzo Massimi
;
Martina Ristorini;Maria Luisa Astolfi;Silvia Canepari
2020

Abstract

A very-low volume sampler of particulate matter (PM) on membrane filters, recently developed with the purpose of allowing spatially-resolved determination of PM and of its chemical components, was employed from December 2016 to February 2018 in a wide and dense monitoring network across Terni, an urban and industrial hot-spot of Central Italy (23 sampling sites, about 1 km between each other). Terni basin can be considered as an open air laboratory for studying the spatial distribution of PM, as it includes several spatially disaggregated sources. PM10 samples were chemically characterized for the water-soluble and insoluble fraction of 33 elements (Al, As, Ba, Bi, Ca, Cd, Ce, Co, Cr, Cs, Cu, Fe, Ga, K, La, Li, Mg, Mn, Mo, Na, Nb, Ni, Pb, Rb, Sb, Sn, Sr, Ti, Tl, U, W, Zn, Zr). Spatial variability of the element concentrations across Terni was then mapped by using the ordinary kriging interpolation method. Spatial distribution of the analyzed elements successfully traced the various PM10 sources. In particular, the spatial mapping of Ba (water-soluble fraction), Bi, Cu, Sb, Sn and Zr (insoluble fraction) traced PM10 emission from the rail network and vehicular traffic, Ce, Cs, La, Li, Rb, Sr and U (insoluble fraction) traced soil resuspension, Cd, Cs, K, Rb and Tl (water-soluble fraction) biomass burning and Co, Cr, Mn, Nb, Ni, Pb (insoluble fraction), As, Cr, Ga, Li, Mo, Mn, W and Zn (water-soluble fraction) the steel industry pole. Principal component analysis was performed on the spatially-resolved chemical data to cluster the elements tracing the main PM10 sources. The winter and summer size distribution of the water-soluble and insoluble elements was analyzed to verify their link with the emission sources. The proposed experimental approach promises to be very effective for the assessment of population exposure to different PM10 sources.
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Utilizza questo identificativo per citare o creare un link a questo documento: http://hdl.handle.net/11573/1400248
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