Determination of PM1 sources at a Prague background site using PMF analysis of combined aerosol mass spectra.

0549879 - ÚCHP 2023 RIV CH eng J - Journal Article
Makeš, Otakar - Schwarz, Jaroslav - Vodička, Petr - Engling, G. - Ždímal, Vladimír
Determination of PM1 sources at a Prague background site using PMF analysis of combined aerosol mass spectra.
Atmosphere. Roč. 13, č. 1 (2022), č. článku 20. E-ISSN 2073-4433
R&D Projects: GA MŠMT(CZ) LM2018122; GA MŠMT(CZ) LTC18068; GA ČR(CZ) GAP209/11/1342
Institutional support: RVO:67985858
Keywords : NR-PM1 * atmospheric aerosol * source apportionment
OECD category: Meteorology and atmospheric sciences
Impact factor: 2.9, year: 2022
Method of publishing: Open access
https://www.mdpi.com/2073-4433/13/1/20

Two intensive measurement campaigns using a compact time-of-flight aerosol mass spectrometer were carried out at the suburban site in Prague (Czech Republic) in summer (2012) and winter (2013). The aim was to determine the aerosol sources of the NR-PM1 fraction by PMF analysis of organic (OA) and inorganic aerosol mass spectra. Firstly, an analysis of the OA mass spectra was performed. Hydrocarbon-like OA (HOA), biomass burning OA (BBOA), and two types of oxygenated OA (OOA1) and (OOA2) were identified in summer. In winter, HOA, BBOA, long-range oxygenated OA (LROOA), and local oxygenated OA (LOOA) were determined. The identified HOA and BBOA factors were then used as additional input for the subsequent ME-2 analysis of the combined organic and inorganic spectra. This analysis resulted in six factors in both seasons. All of the previously reported organic factors were reidentified and expanded with the inorganic part of the spectra in both seasons. Two predominantly inorganic factors ammonium sulphate (AMOS) and ammonium nitrate (AMON) were newly identified in both seasons. Despite very similar organic parts of the mass profiles, the daily cycles of HOA and LOOA differed significantly in winter. It appears that the addition of the inorganic part of the mass profile, in some cases, reduces the ability of the model to identify physically meaningful factors.
Permanent Link: http://hdl.handle.net/11104/0325979