Ostrava in the Moravian-Silesian region (Czech Republic) is a European air pollution hot spot for airborne particulate matter (PM), polycyclic aromatic hydrocarbons (PAHs), and ultrafine particles (UFPs). Air pollution source apportionment is essential for implementation of successful abatement strategies. UFPs or nanoparticles of diameter <100 nm exhibit the highest deposition efficiency in human lungs. To permit apportionment of PM sources at the hot-spot including nanoparticles, Positive Matrix Factorization (PMF) was applied to highly time resolved particle number size distributions (NSD, 14 nm-10 μm) and PM0.09-1.15 chemical composition. Diurnal patterns, meteorological variables, gaseous pollutants, organic markers, and associations between the NSD factors and chemical composition factors were used to identify the pollution sources. The PMF on the NSD reveals two factors in the ultrafine size range: industrial UFPs (28%, number mode diameter - NMD 45 nm), industrial/fresh road traffic nanoparticles (26%, NMD 26 nm); three factors in the accumulation size range: urban background (24%, NMD 93 nm), coal burning (14%, volume mode diameter - VMD 0.5 μm), regional pollution (3%, VMD 0.8 μm) and one factor in the coarse size range: industrial coarse particles/road dust (2%, VMD 5 μm). The PMF analysis of PM0.09-1.15 revealed four factors: SIA/CC/BB (52%), road dust (18%), sinter/steel (16%), iron production (16%). The factors in the ultrafine size range resolved with NSD have a positive correlation with sinter/steel production and iron production factors resolved with chemical composition. Coal combustion factor resolved with NSD has moderate correlation with SIA/CC/BB factor. The organic markers homohopanes correlate with coal combustion and the levoglucosan correlates with urban background. The PMF applications to NSD and chemical composition datasets are complementary. PAHs in PM1 were found to be associated with coal combustion factor.

Source apportionment of aerosol particles at a European air pollution hot spot using particle number size distributions and chemical composition

MASIOL M;
2018-01-01

Abstract

Ostrava in the Moravian-Silesian region (Czech Republic) is a European air pollution hot spot for airborne particulate matter (PM), polycyclic aromatic hydrocarbons (PAHs), and ultrafine particles (UFPs). Air pollution source apportionment is essential for implementation of successful abatement strategies. UFPs or nanoparticles of diameter <100 nm exhibit the highest deposition efficiency in human lungs. To permit apportionment of PM sources at the hot-spot including nanoparticles, Positive Matrix Factorization (PMF) was applied to highly time resolved particle number size distributions (NSD, 14 nm-10 μm) and PM0.09-1.15 chemical composition. Diurnal patterns, meteorological variables, gaseous pollutants, organic markers, and associations between the NSD factors and chemical composition factors were used to identify the pollution sources. The PMF on the NSD reveals two factors in the ultrafine size range: industrial UFPs (28%, number mode diameter - NMD 45 nm), industrial/fresh road traffic nanoparticles (26%, NMD 26 nm); three factors in the accumulation size range: urban background (24%, NMD 93 nm), coal burning (14%, volume mode diameter - VMD 0.5 μm), regional pollution (3%, VMD 0.8 μm) and one factor in the coarse size range: industrial coarse particles/road dust (2%, VMD 5 μm). The PMF analysis of PM0.09-1.15 revealed four factors: SIA/CC/BB (52%), road dust (18%), sinter/steel (16%), iron production (16%). The factors in the ultrafine size range resolved with NSD have a positive correlation with sinter/steel production and iron production factors resolved with chemical composition. Coal combustion factor resolved with NSD has moderate correlation with SIA/CC/BB factor. The organic markers homohopanes correlate with coal combustion and the levoglucosan correlates with urban background. The PMF applications to NSD and chemical composition datasets are complementary. PAHs in PM1 were found to be associated with coal combustion factor.
2018
234
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/10278/3723777
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