Monitoring and Evaluation of Terni (Central Italy) Air Quality through Spatially Resolved Analyses

Abstract

A study of spatial variability of PM10 elemental components was conducted in Terni city (Central Italy), situated in an intramountain depression characterized by the presence of several particulate matter emission sources. The meteorological conditions of Terni basin limit the dispersion and enhance the accumulation of the atmospheric pollutants. Thanks to the utilization of new smart samplers, used for the first time and working in parallel at 23 sampling sites, spatially resolved data were obtained. Localizations of the samplers were chosen in order to evaluate the impact of different local PM10 sources. Chemical composition of the samples was determined in combination with a chemical fractioning procedure, that allowed us to discriminate water-soluble and residual fractions of analyzed elements in which proved to be a valuable approach for increasing selectivity of elements as source tracers. Spatial variability of elements underlined the contribution of local emission sources and the different dispersion capacity of each element. Terni city resulted to be an ideal area to test and validate a new experimental method for the acquisition of spatially resolved data providing the possibility to properly evaluate the spatial variability of PM10 and its chemical components.

Innovative Characterization of Particulate Matter Deposited on Urban Vegetation Leaves through the Application of a Chemical Fractionation Procedure

“…On the other hand, the clustering of NA 2 and NA 4 underlines the emission impact of vehicular traffic at the sites located at high proximity to a trafficked street. Indeed, Cr, Cu and Fe are known to be related to vehicular traffic mechanical-abrasive emission processes, being component of brakes, tire dust and vehicle components [ 49 , 61 , 62 ]. Leaves collected from NA 2 seemed also to be affected by the South-West marine breeze with relative higher concentrations of marine salts components.…”

“…Based on the factor coordinates ( Figure 6 a), clear correlations exist among elemental concentrations per unit leaf area, such as: water-soluble Cd and insoluble Ni (positive PC1 values); water-soluble Ba, Cs, Rb, SO 4 2− and PO 4 3− (negative PC1 values); water-soluble Mo, insoluble Fe and Cr together with NO 3 2− (positive PC2 values); insoluble Cu and Zn (negative PC2 values). These elemental clusters can be considered as representative of the different PM emission sources present in Terni: water-soluble Mo and insoluble concentrations of Cr, Fe and Ni, were associated to the emission impact of the steel plant [ 46 , 49 ], since these elements are used as chemical components in the stainless-steel production to increase its ductility, strength and toughness [ 63 ]; water-soluble Cs and Rb and ionic species such as SO 4 2− and PO 4 3− could be related to the influence of biomass burning [ 47 , 64 ]; and finally, insoluble Cu and Zn are known to be elemental tracers related to the impact of mechanical and abrasive processes connected to vehicular traffic, being component of brakes and other vehicle parts [ 65 , 66 , 67 ]. However, the identification of the main emission sources is only slightly reflected in the case discrimination ( Figure 6 b): most of the tree species (eight over twelve) are clustered together in the positive PC1 region, without differentiation in PC2.…”

“…In addition to typical PM urban emission sources, such as vehicular traffic and domestic heating, Terni is characterized by the presence of a wide steel plant in the East of the city and an incinerator in the West [ 48 ]. The important presence of anthropogenic PM emission sources, in combination with the peculiar meteorological conditions of the city, located within an intramountain valley, determines the ideal conditions for increasing the accumulation of airborne particles and reducing their dispersion [ 49 ].…”

Performance Evaluation of a Very-low-volume Sampler for Atmospheric Particulate Matter

“…These devices are cheap enough to be set on the territory in a high number of units at affordable cost. Consequently, they can be used to draw up detailed concentration maps able, among others, to determine the strength of local pollution sources (Massimi et al, 2017). So far, concentration maps have been derived for gaseous pollutants and for particle number and particle mass concentration, while it would be very beneficial to obtain these spatial information also for PM chemical components (Hasenfratz et al, 2015;Rohde and Muller, 2015).…”