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

Athanasia Vlachou, Anna Tobler, Houssni Lamkaddam, Francesco Canonaco, Kaspar R. Daellenbach, Jean-Luc Jaffrezo, Maria Cruz Minguillon, Marek Maasikmets, Erik Teinemaa, Urs Baltensperger, Imad El Haddad, Andre S. H. Prevot

Tutkimustuotos: ArtikkelijulkaisuArtikkeliTieteellinenvertaisarvioitu

Kuvaus

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-Jarve (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.
Alkuperäiskielienglanti
LehtiAtmospheric Chemistry and Physics
Vuosikerta19
Numero11
Sivut7279-7295
Sivumäärä17
ISSN1680-7316
DOI - pysyväislinkit
TilaJulkaistu - 3 kesäkuuta 2019
Julkaistu ulkoisestiKyllä
OKM-julkaisutyyppiA1 Alkuperäisartikkeli tieteellisessä aikakauslehdessä, vertaisarvioitu

Tieteenalat

  • 116 Kemia
  • 114 Fysiikka
  • 1172 Ympäristötiede

Lainaa tätä

Vlachou, Athanasia ; Tobler, Anna ; Lamkaddam, Houssni ; Canonaco, Francesco ; Daellenbach, Kaspar R. ; Jaffrezo, Jean-Luc ; Cruz Minguillon, Maria ; Maasikmets, Marek ; Teinemaa, Erik ; Baltensperger, Urs ; El Haddad, Imad ; Prevot, Andre S. H. / 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. Julkaisussa: Atmospheric Chemistry and Physics. 2019 ; Vuosikerta 19, Nro 11. Sivut 7279-7295.
@article{d98baec607a54180b58dd02ed6b8271e,
title = "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",
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-Jarve (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.",
keywords = "MASS-SPECTROMETRY, ELEMENTAL CARBON, OFFLINE-AMS, CHEMICAL-COMPOSITION, MULTILINEAR ENGINE, DICARBOXYLIC-ACIDS, NONFOSSIL SOURCES, 9 SITES, URBAN, QUANTIFICATION, 116 Chemical sciences, 114 Physical sciences, 1172 Environmental sciences",
author = "Athanasia Vlachou and Anna Tobler and Houssni Lamkaddam and Francesco Canonaco and Daellenbach, {Kaspar R.} and Jean-Luc Jaffrezo and {Cruz Minguillon}, Maria and Marek Maasikmets and Erik Teinemaa and Urs Baltensperger and {El Haddad}, Imad and Prevot, {Andre S. H.}",
year = "2019",
month = "6",
day = "3",
doi = "10.5194/acp-19-7279-2019",
language = "English",
volume = "19",
pages = "7279--7295",
journal = "Atmospheric Chemistry and Physics",
issn = "1680-7316",
publisher = "COPERNICUS GESELLSCHAFT MBH",
number = "11",

}

Vlachou, A, Tobler, A, Lamkaddam, H, Canonaco, F, Daellenbach, KR, Jaffrezo, J-L, Cruz Minguillon, M, Maasikmets, M, Teinemaa, E, Baltensperger, U, El Haddad, I & Prevot, ASH 2019, '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', Atmospheric Chemistry and Physics, Vuosikerta 19, Nro 11, Sivut 7279-7295. https://doi.org/10.5194/acp-19-7279-2019

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. / Vlachou, Athanasia; Tobler, Anna; Lamkaddam, Houssni; Canonaco, Francesco; Daellenbach, Kaspar R.; Jaffrezo, Jean-Luc; Cruz Minguillon, Maria; Maasikmets, Marek; Teinemaa, Erik; Baltensperger, Urs; El Haddad, Imad; Prevot, Andre S. H.

julkaisussa: Atmospheric Chemistry and Physics, Vuosikerta 19, Nro 11, 03.06.2019, s. 7279-7295.

Tutkimustuotos: ArtikkelijulkaisuArtikkeliTieteellinenvertaisarvioitu

TY - JOUR

T1 - Development of a versatile source apportionment analysis based on positive matrix factorization

T2 - a case study of the seasonal variation of organic aerosol sources in Estonia

AU - Vlachou, Athanasia

AU - Tobler, Anna

AU - Lamkaddam, Houssni

AU - Canonaco, Francesco

AU - Daellenbach, Kaspar R.

AU - Jaffrezo, Jean-Luc

AU - Cruz Minguillon, Maria

AU - Maasikmets, Marek

AU - Teinemaa, Erik

AU - Baltensperger, Urs

AU - El Haddad, Imad

AU - Prevot, Andre S. H.

PY - 2019/6/3

Y1 - 2019/6/3

N2 - 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-Jarve (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.

AB - 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-Jarve (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.

KW - MASS-SPECTROMETRY

KW - ELEMENTAL CARBON

KW - OFFLINE-AMS

KW - CHEMICAL-COMPOSITION

KW - MULTILINEAR ENGINE

KW - DICARBOXYLIC-ACIDS

KW - NONFOSSIL SOURCES

KW - 9 SITES

KW - URBAN

KW - QUANTIFICATION

KW - 116 Chemical sciences

KW - 114 Physical sciences

KW - 1172 Environmental sciences

U2 - 10.5194/acp-19-7279-2019

DO - 10.5194/acp-19-7279-2019

M3 - Article

VL - 19

SP - 7279

EP - 7295

JO - Atmospheric Chemistry and Physics

JF - Atmospheric Chemistry and Physics

SN - 1680-7316

IS - 11

ER -