Long-term chemical analysis and organic aerosol source apportionment at nine sites in central Europe: source identification and uncertainty assessment

Abstract

Abstract. Long-term monitoring of organic aerosol is important for epidemiological studies, validation of atmospheric models, and air quality management. In this study, we apply a recently developed filter-based offline methodology using an aerosol mass spectrometer (AMS) to investigate the regional and seasonal differences of contributing organic aerosol sources. We present offline AMS measurements for particulate matter smaller than 10 µm at nine stations in central Europe with different exposure characteristics for the entire year of 2013 (819 samples). The focus of this study is a detailed source apportionment analysis (using positive matrix factorization, PMF) including in-depth assessment of the related uncertainties. Primary organic aerosol (POA) is separated in three components: hydrocarbon-like OA related to traffic emissions (HOA), cooking OA (COA), and biomass burning OA (BBOA). We observe enhanced production of secondary organic aerosol (SOA) in summer, following the increase in biogenic emissions with temperature (summer oxygenated OA, SOOA). In addition, a SOA component was extracted that correlated with an anthropogenic secondary inorganic species that is dominant in winter (winter oxygenated OA, WOOA). A factor (sulfur-containing organic, SC-OA) explaining sulfur-containing fragments (CH 3 SO + 2 ), which has an event-driven temporal behaviour, was also identified. The relative yearly average factor contributions range from 4 to 14 % for HOA, from 3 to 11 % for COA, from 11 to 59 % for BBOA, from 5 to 23 % for SC-OA, from 14 to 27 % for WOOA, and from 15 to 38 % for SOOA. The uncertainty of the relative average factor contribution lies between 2 and 12 % of OA. At the sites north of the alpine crest, the sum of HOA, COA, and BBOA (POA) contributes less to OA (POA / OA = 0.3) than at the southern alpine valley sites (0.6). BBOA is the main contributor to POA with 87 % in alpine valleys and 42 % north of the alpine crest. Furthermore, the influence of primary biological particles (PBOAs), not resolved by PMF, is estimated and could contribute significantly to OA in PM 10 .

Arabitol, mannitol, and glucose as tracers of primary biogenic organic aerosol: the influence of environmental factors on ambient air concentrations and spatial distribution over France

“…Therefore, to reduce the possibility of spurious "anti-correlation" due to highly variable concentration ranges, data were amplitudenormalized prior to correlation analysis. A thorough discussion of the normalized cross-correlation method can be found elsewhere (Bardal and Saetran, 2016;Dai and Zhou, 2017;Eisner et al, 2009;Kaso, 2018;Lainer et al, 2016;Le Pichon et al, 2019). To achieve pair-wise correlation analysis between the sampling sites collected during the same periods, the original raw daily measurements were processed as follows: starting on identical days for each pairs of sites, the arrangement of the original daily data into consecutive 3 d intervals (or 6 d intervals in the case of OPE-ANDRA) and the calculation of the average concentration values for the middle day were performed.…”

Composition and origin of PM<sub>2.5</sub> aerosol particles in the upper Rhine valley in summer

“…The AMS measures the particle size-resolved bulk chemical composition, e.g. organic compounds, ammonium, nitrate, sulfate, and chloride, in mass concentrations with high time resolution and sensitivity (DeCarlo et al, 2006). Similarly as the LAAPTOF, aerosols are sampled with a flow rate of ∼ 84 cm 3 min −1 via a similar ADL (Peck et al, 2016) in the size range 70 nm to 2.5 µm d va and then pass through a PTOF chamber.…”

PM2.5 in Indoor Air of a Bakery: Chemical Characterization and Size Distribution

“…Several studies of indoor air quality have identified cooking and in particular cooking using biomass or wood as a heating source as one of the most significant activities that generates indoor particles [33][34][35][36][37]. In fact, cooking and biomass burning emissions are among the main sources of particulate matter (PM) [38][39][40]. Different styles of cooking generate aerosols with typical mass concentrations, size distribution and chemical compositions, and the presence of well-known chemical carcinogens, such as PAHs (polycyclic aromatic hydrocarbons).…”