English (United Kingdom)

https://curated-unify.zendy.io/wp-json/zendy-region/v1/featured_content/oa?rat=en

https://curated-unify.zendy.io/wp-json/zendy-region/v1/highlighted_journal/

Global: Zendy Plus annual

Presents the access of premium content as premium feature

Premium Content

Presents the keyphrase highlighting as premium feature

Keyphrase Highlighting

Presents the summarisation as premium feature

Summarisation

Insights

Presents the pdf analysis as premium feature

PDF Analysis

Presents the zaia usage as premium feature

ZAIA

Global: Zendy Tools annual

Global: Zendy Free Plan

Global: Zendy Tools monthly

Global: Zendy Plus monthly

. Bootstrap analysis iscommonly used to capture the uncertainties of a bilinear receptor model suchas the positive matrix factorization (PMF) model. This approach can estimatethe factor-related uncertainties and partially assess the rotationalambiguity of the model. The selection of the environmentally plausiblesolutions, though, can be challenging, and a systematic approach to identifyand sort the factors is needed. For this, comparison of the factors betweeneach bootstrap run and the initial PMF output, as well as with externallydetermined markers, is crucial. As a result, certain solutions that exhibitsuboptimal factor separation should be discarded. The retained solutionswould then be used to test the robustness of the PMF output. Meanwhile,analysis of filter samples with the Aerodyne aerosol mass spectrometer andthe application of PMF and bootstrap analysis on the bulk water-solubleorganic aerosol mass spectra have provided insight into the sourceidentification and their uncertainties. Here, we investigated a full yearlycycle of the sources of organic aerosol (OA) at three sites in Estonia:Tallinn (urban), Tartu (suburban) and Kohtla-Jarve (KJ; industrial). Weidentified six OA sources and an inorganic dust factor. The primary OA typesincluded biomass burning, dominant in winter in Tartu and accounting for73 %  ±  21 % of the total OA, primary biological OA which wasabundant in Tartu and Tallinn in spring (21 %  ±  8 % and11 %  ±  5 %, respectively), and two other primary OA types lowerin mass. A sulfur-containing OA was related to road dust and tire abrasionwhich exhibited a rather stable yearly cycle, and an oil OA was connected tothe oil shale industries in KJ prevailing at this site that comprises36 %  ±  14 % of the total OA in spring. The secondary OA sourceswere separated based on their seasonal behavior: a winter oxygenated OAdominated in winter (36 %  ±  14 % for KJ,25 %  ±  9 % for Tallinn and 13 %  ±  5 % for Tartu)and was correlated with benzoic and phthalic acid, implying an anthropogenicorigin. A summer oxygenated OA was the main source of OA in summer at allsites (26 %  ±  5 % in KJ, 41 %  ±  7 % in Tallinnand 35 %  ±  7 % in Tartu) and exhibited high correlations withoxidation products of a -pinene-like pinic acid and 3-methyl-1, 2,3-butanetricarboxylic acid (MBTCA), suggesting a biogenicorigin.

atmospheric chemistry and physics

Development of a versatile source apportionment analysis based on positive matrix factorization: a case study of the seasonal variation of organic aerosol sources in Estonia