Spatial mapping of the winter and summer PM10 element concentrations in an urban and industrial hot-spot of Central Italy

Particulate matter (PM) air pollution is a serious threat to human health; various epidemiological studies have spotlighted strong correlations between exposure to PM and the onset of cardiovascular and respiratory diseases. Since in urban and industrial areas, PM air pollution largely depends on the type, number and rate of local emissions; the study of the spatial distribution of PM chemical compounds is essential for a reliable identification of emission sources and the assessment of personal exposure. However, due to the very high cost of a network based on traditional PM samplers, ambient air quality assessment and epidemiological studies are usually based on measurements taken at a few sampling points. For these reasons, in the last few years, a self-powered and very-low volume device for PM sampling on membrane filters has been developed with the purpose of allowing spatially-resolved determination of PM chemical compounds. The sampler has been employed from 12/2016 to 02/2018 in a dense (23 sampling sites, about 1 km between the sites) and low-cost monitoring network across Terni, an urban and industrial hot-spot of Central Italy (Massimi et al., 2017, 2019). PM10 samples were monthly collected and chemically characterized for the water-soluble and insoluble fraction of 35 elements (Al, As, B, 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, V, W, Zn, Zr) by using a chemical fractioning procedure (Canepari et al., 2006a, 2006b). Principal component analysis was performed on the spatially-resolved chemical data to individuate reliable tracers of the main local PM emission sources. Cu, Sb, Sn, Zr, Bi (insoluble fraction) and Ba (water-soluble fraction) were found to be good tracers of rail network and vehicular traffic; K, Tl, Rb, Cs and Cd (water-soluble fraction) were identified as reliable tracers of biomass burning; Co, Ni, Cr, Nb, Mn, Pb (insoluble fraction) and As, W, Mo, Cr, Zn, Li, Mn, Ga (water-soluble fraction) showed the steel plant role in the emission of PM10. Spatial distribution of the elements was mapped by using ordinary kriging interpolation method. The new experimental approach was found to be effective for the evaluation of the impact of PM10 emission sources and promises to be powerful for the optimization and validation of dispersion models through high spatial resolution chemical data and for a more accurate assessment of the population exposure to PM air pollutants.