source tracer

Source apportionment of PM10 in Terni (Central Italy) and spatial mapping of atmospheric element concentrations using high spatial resolution chemical data

Very-low volume, low-cost and automatic devices for PM sampling on membrane filters have been employed in Terni, an urban and industrial hot-spot of Central Italy, to evaluate the spatial distribution of PM10 and its main chemical components. The samplers, worked in parallel for 15 months at 23 monitoring sites and PM10 samples were analyzed for PM mass, ions, levoglucosan and water-soluble and insoluble elements.

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

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.

Evaluation of the efficiency of Arundo donax L. leaves as biomonitors for atmospheric element concentrations in an urban and industrial area of Central Italy

Washed and unwashed Arundo donax L. (A. donax) leaves were analyzed for elements, and results were compared with element concentrations detected in river water and particulate matter (PM) Samples were collected along a river in an urban and industrial hot spot of Central Italy, where element concentrations show relevant spatial gradients both in air and river water. The aim of this study is to identify the role of the two environmental matrices on leaves composition.

Spatial mapping of PM10 element concentrations in Terni (Central Italy) by using spatially-resolved chemical data

Particulate matter (PM) air pollution represents a major environmental and health issue which largely depends on the type and amount of local emissions in industrial and urban areas. Therefore, the evaluation of the spatial distribution of PM chemical components is fundamental for a reliable identification of emission sources and the assessment of personal exposure.

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