scholarly journals Methylsiloxanes Release from One Landfill through Yearly Cycle and Their Removal Mechanisms (Especially Hydroxylation) In Leachates

2017 ◽  
Vol 51 (21) ◽  
pp. 12337-12346 ◽  
Author(s):  
Lin Xu ◽  
Shihe Xu ◽  
Liqin Zhi ◽  
Xudan He ◽  
Chunhui Zhang ◽  
...  
Keyword(s):  
Yearly Cycle ◽  
Removal Mechanisms

Removal Mechanisms for Calf Barn Aerosol Particles

1987 ◽  
Vol 30 (6) ◽  
pp. 1758-1763 ◽  
Author(s):  
G. L. Van Wicklen ◽  
L. D. Albright
Keyword(s):  
Aerosol Particles ◽  
Removal Mechanisms

scholarly journals 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

2019 ◽  
Vol 19 (11) ◽  
pp. 7279-7295 ◽  
Author(s):  
Athanasia Vlachou ◽  
Anna Tobler ◽  
Houssni Lamkaddam ◽  
Francesco Canonaco ◽  
Kaspar R. Daellenbach ◽  
...  
Keyword(s):  
Matrix Factorization ◽  
Organic Aerosol ◽  
Positive Matrix Factorization ◽  
Water Soluble ◽  
Oxidation Products ◽  
Positive Matrix ◽  
Bootstrap Analysis ◽  
Seasonal Behavior ◽  
Yearly Cycle ◽  
Aerosol Mass

Abstract. Bootstrap analysis is commonly used to capture the uncertainties of a bilinear receptor model such as the positive matrix factorization (PMF) model. This approach can estimate the factor-related uncertainties and partially assess the rotational ambiguity of the model. The selection of the environmentally plausible solutions, though, can be challenging, and a systematic approach to identify and sort the factors is needed. For this, comparison of the factors between each bootstrap run and the initial PMF output, as well as with externally determined markers, is crucial. As a result, certain solutions that exhibit suboptimal factor separation should be discarded. The retained solutions would then be used to test the robustness of the PMF output. Meanwhile, analysis of filter samples with the Aerodyne aerosol mass spectrometer and the application of PMF and bootstrap analysis on the bulk water-soluble organic aerosol mass spectra have provided insight into the source identification and their uncertainties. Here, we investigated a full yearly cycle of the sources of organic aerosol (OA) at three sites in Estonia: Tallinn (urban), Tartu (suburban) and Kohtla-Järve (KJ; industrial). We identified six OA sources and an inorganic dust factor. The primary OA types included biomass burning, dominant in winter in Tartu and accounting for 73 % ± 21 % of the total OA, primary biological OA which was abundant in Tartu and Tallinn in spring (21 % ± 8 % and 11 % ± 5 %, respectively), and two other primary OA types lower in mass. A sulfur-containing OA was related to road dust and tire abrasion which exhibited a rather stable yearly cycle, and an oil OA was connected to the oil shale industries in KJ prevailing at this site that comprises 36 % ± 14 % of the total OA in spring. The secondary OA sources were separated based on their seasonal behavior: a winter oxygenated OA dominated 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 anthropogenic origin. A summer oxygenated OA was the main source of OA in summer at all sites (26 % ± 5 % in KJ, 41 % ± 7 % in Tallinn and 35 % ± 7 % in Tartu) and exhibited high correlations with oxidation products of a-pinene-like pinic acid and 3-methyl-1, 2, 3-butanetricarboxylic acid (MBTCA), suggesting a biogenic origin.

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