Identification and spatial mapping of tracers of PM10 emission sources using a high spatial resolution distributed network in an urban setting

Abstract

We employed an experimental approach for high spatial resolution sampling and analysis of PM10, allowing identification and spatial mapping of tracers of PM10 emission sources. Very-low-volume samplers were used at 17 sites in Amersfoort and at one regulatory reference site in Utrecht, The Netherlands, in a 5-month monitoring period (from September 2018 to February 2019), to assess the monthly spatial distribution of PM10 mass and PM10 chemical compounds. By performing principal component analysis on the obtained spatially-resolved data, selective and reliable source tracers were identified for soil dust (Ca+, Cl−, insoluble Al, Ce, Li, U and V), brake dust (insoluble Fe, Mn, Mo, Nb, Sb, Sn, W and Zr, water-soluble Fe, Mn, Mo and Sb), industrial and/or agricultural emissions (NH4+, water-soluble As, Co, Fe, Mn, Mo, Pb, Sb, Se, Sn and Ti), secondary organic and inorganic aerosols (water-soluble organic carbon, NO3− and SO42−), biomass domestic heating (water-soluble organic carbon, levoglucosan, water-soluble Cs, Li, Rb and Tl) and New Year's Eve fireworks (K+, Mg2+, Na+, water-soluble Al, Ba, Bi, Cr, Cu and Sr). The autumn and winter spatial mapping of the identified source tracers allowed us to effectively assess and localize the impact of the different PM10 sources and to evaluate the diffusion of the PM10 particles. This approach proved to be very effective to trace low-intensity PM10 sources and to map their seasonal spatial distribution. The obtained spatially-resolved chemical data can be used in further studies to evaluate spatial relationships between the concentration of PM10 air pollutants and adverse outcomes for human health. This approach promises to be a powerful tool for obtaining seasonal and spatially-resolved information about PM composition and sources in several study areas, having high impact on the air quality management.