Browsing by Subject "MULTILINEAR ENGINE"

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  • Zhang, Yanjun; Peräkylä, Otso; Yan, Chao; Heikkinen, Liine; Äijälä, Mikko; Dällenbach, Kaspar; Zha, Qiaozhi; Riva, Matthieu; Garmash, Olga; Junninen, Heikki; Paatero, Pentti; Worsnop, Douglas; Ehn, Mikael (2019)
    Recent advancements in atmospheric mass spectrometry provide huge amounts of new information but at the same time present considerable challenges for the data analysts. High-resolution (HR) peak identification and separation can be effort- and time-consuming yet still tricky and inaccurate due to the complexity of overlapping peaks, especially at larger mass-to-charge ratios. This study presents a simple and novel method, mass spectral binning combined with positive matrix factorization (binPMF), to address these problems. Different from unit mass resolution (UMR) analysis or HR peak fitting, which represent the routine data analysis approaches for mass spectrometry datasets, binPMF divides the mass spectra into small bins and takes advantage of the positive matrix factorization's (PMF) strength in separating different sources or processes based on different temporal patterns. In this study, we applied the novel approach to both ambient and synthetic datasets to evaluate its performance. It not only succeeded in separating overlapping ions but was found to be sensitive to subtle variations as well. Being fast and reliable, binPMF has no requirement for a priori peak information and can save much time and effort from conventional HR peak fitting, while still utilizing nearly the full potential of HR mass spectra. In addition, we identify several future improvements and applications for binPMF and believe it will become a powerful approach in the data analysis of mass spectra.
  • Froehlich, R.; Crenn, V.; Setyan, A.; Belis, C. A.; Canonaco, F.; Favez, O.; Riffault, V.; Slowik, J. G.; Aas, W.; Aijala, M.; Alastuey, A.; Artinano, B.; Bonnaire, N.; Bozzetti, C.; Bressi, M.; Carbone, C.; Coz, E.; Croteau, P. L.; Cubison, M. J.; Esser-Gietl, J. K.; Green, D. C.; Gros, V.; Heikkinen, L.; Herrmann, H.; Jayne, J. T.; Lunder, C. R.; Minguillon, M. C.; Mocnik, G.; O'Dowd, C. D.; Ovadnevaite, J.; Petralia, E.; Poulain, L.; Priestman, M.; Ripoll, A.; Sarda-Esteve, R.; Wiedensohler, A.; Baltensperger, U.; Sciare, J.; Prevot, A. S. H. (2015)
    Chemically resolved atmospheric aerosol data sets from the largest intercomparison of the Aerodyne aerosol chemical speciation monitors (ACSMs) performed to date were collected at the French atmospheric supersite SIRTA. In total 13 quadrupole ACSMs (Q-ACSM) from the European ACTRIS ACSM network, one time-of-flight ACSM (ToF-ACSM), and one high-resolution ToF aerosol mass spectrometer (AMS) were operated in parallel for about 3 weeks in November and December similar to 2013. Part 1 of this study reports on the accuracy and precision of the instruments for all the measured species. In this work we report on the intercomparison of organic components and the results from factor analysis source apportionment by positive matrix factorisation (PMF) utilising the multilinear engine 2 (ME-2). Except for the organic contribution of mass-to-charge ratio m/z 44 to the total organics (f(44)), which varied by factors between 0.6 and 1.3 compared to the mean, the peaks in the organic mass spectra were similar among instruments. The m/z 44 differences in the spectra resulted in a variable f(44) in the source profiles extracted by ME-2, but had only a minor influence on the extracted mass contributions of the sources. The presented source apportionment yielded four factors for all 15 instruments: hydrocarbon-like organic aerosol (HOA), cooking-related organic aerosol (COA), biomass burning-related organic aerosol (BBOA) and secondary oxygenated organic aerosol (OOA). ME-2 boundary conditions (profile constraints) were optimised individually by means of correlation to external data in order to achieve equivalent / comparable solutions for all ACSM instruments and the results are discussed together with the investigation of the influence of alternative anchors (reference profiles). A comparison of the ME-2 source apportionment output of all 15 instruments resulted in relative standard deviations (SD) from the mean between 13.7 and 22.7 % of the source's average mass contribution depending on the factors (HOA: 14.3 +/- 2.2 %, COA: 15.0 +/- 3.4 %, OOA: 41.5 +/- 5.7 %, BBOA: 29.3 +/- 5.0 %). Factors which tend to be subject to minor factor mixing (in this case COA) have higher relative uncertainties than factors which are recognised more readily like the OOA. Averaged over all factors and instruments the relative first SD from the mean of a source extracted with ME-2 was 17.2 %.
  • Kalivitis, N.; Kerminen, Veli-Matti; Kouvarakis, G.; Stavroulas, I.; Bougiatioti, A.; Nenes, A.; Manninen, Hanna; Petäjä, Tuukka; Kulmala, Markku; Mihalopoulos, N. (2015)
    While cloud condensation nuclei (CCN) production associated with atmospheric new particle formation (NPF) is thought to be frequent throughout the continental boundary layers, few studies on this phenomenon in marine air exist. Here, based on simultaneous measurement of particle number size distributions, CCN properties and aerosol chemical composition, we present the first direct evidence on CCN production resulting from NPF in the eastern Mediterranean atmosphere. We show that condensation of both gaseous sulfuric acid and organic compounds from multiple sources leads to the rapid growth of nucleated particles to CCN sizes in this environment during the summertime. Sub-100 nm particles were found to be substantially less hygroscopic than larger particles during the period with active NPF and growth (the value of kappa was lower by 0.2-0.4 for 60 nm particles compared with 120 nm particles), probably due to enrichment of organic material in the sub-100 nm size range. The aerosol hygroscopicity tended to be at minimum just before the noon and at maximum in the afternoon, which was very likely due to the higher sulfate-to-organic ratios and higher degree of oxidation of the organic material during the afternoon. Simultaneous with the formation of new particles during daytime, particles formed during the previous day or even earlier were growing into the size range relevant to cloud droplet activation, and the particles formed in the atmosphere were possibly mixed with long-range-transported particles.
  • Äijälä, Mikko; Dällenbach, Kaspar; Canonaco, Francesco; Heikkinen, Liine; Junninen, Heikki; Petäjä, Tuukka; Kulmala, Markku; Prevot, Andre S. H.; Ehn, Mikael (2019)
    The interactions between organic and inorganic aerosol chemical components are integral to understanding and modelling climate and health-relevant aerosol physicochemical properties, such as volatility, hygroscopicity, light scattering and toxicity. This study presents a synthesis analysis for eight data sets, of non-refractory aerosol composition, measured at a boreal forest site. The measurements, performed with an aerosol mass spectrometer, cover in total around 9 months over the course of 3 years. In our statistical analysis, we use the complete organic and inorganic unit-resolution mass spectra, as opposed to the more common approach of only including the organic fraction. The analysis is based on iterative, combined use of (1) data reduction, (2) classification and (3) scaling tools, producing a data-driven chemical mass balance type of model capable of describing site-specific aerosol composition. The receptor model we constructed was able to explain 83 +/- 8% of variation in data, which increased to 96 +/- 3% when signals from low signal-to-noise variables were not considered. The resulting interpretation of an extensive set of aerosol mass spectrometric data infers seven distinct aerosol chemical components for a rural boreal forest site: ammonium sulfate (35 +/- 7% of mass), low and semi-volatile oxidised organic aerosols (27 +/- 8% and 12 +/- 7 %), biomass burning organic aerosol (11 +/- 7 %), a nitrate-containing organic aerosol type (7 +/- 2 %), ammonium nitrate (5 +/- 2 %), and hydrocarbon-like organic aerosol (3 +/- 1 %). Some of the additionally observed, rare outlier aerosol types likely emerge due to surface ionisation effects and likely represent amine compounds from an unknown source and alkaline metals from emissions of a nearby district heating plant. Compared to traditional, ionbalance-based inorganics apportionment schemes for aerosol mass spectrometer data, our statistics-based method provides an improved, more robust approach, yielding readily useful information for the modelling of submicron atmospheric aerosols physical and chemical properties. The results also shed light on the division between organic and inorganic aerosol types and dynamics of salt formation in aerosol. Equally importantly, the combined methodology exemplifies an iterative analysis, using consequent analysis steps by a combination of statistical methods. Such an approach offers new ways to home in on physicochemically sensible solutions with minimal need for a priori information or analyst interference. We therefore suggest that similar statisticsbased approaches offer significant potential for un- or semi-supervised machine-learning applications in future analyses of aerosol mass spectrometric data.
  • Ciarelli, Giancarlo; Aksoyoglu, Sebnem; El Haddad, Imad; Bruns, Emily A.; Crippa, Monica; Poulain, Laurent; Äijälä, Mikko; Carbone, Samara; Freney, Evelyn; O'Dowd, Colin; Baltensperger, Urs; Prevot, Andre S. H. (2017)
    We evaluated a modified VBS (volatility basis set) scheme to treat biomass-burning-like organic aerosol (BBOA) implemented in CAMx (Comprehensive Air Quality Model with extensions). The updated scheme was parameterized with novel wood combustion smog chamber experiments using a hybrid VBS framework which accounts for a mixture of wood burning organic aerosol precursors and their further functionalization and fragmentation in the atmosphere. The new scheme was evaluated for one of the winter EMEP intensive campaigns (February March 2009) against aerosol mass spectrometer (AMS) measurements performed at 11 sites in Europe. We found a considerable improvement for the modelled organic aerosol (OA) mass compared to our previous model application with the mean fractional bias (MFB) reduced from 61 to 29 %. We performed model-based source apportionment studies and compared results against positive matrix factorization (PMF) analysis performed on OA AMS data. Both model and observations suggest that OA was mainly of secondary origin at almost all sites. Modelled secondary organic aerosol (SOA) contributions to total OA varied from 32 to 88 % (with an average contribution of 62 %) and absolute concentrations were generally under-predicted. Modelled primary hydrocarbon-like organic aerosol (HOA) and primary biomass-burning-like aerosol (BBPOA) fractions contributed to a lesser extent (HOA from 3 to 30 %, and BBPOA from 1 to 39 %) with average contributions of 13 and 25 %, respectively. Modelled BBPOA fractions were found to represent 12 to 64 % of the total residential-heating-related OA, with increasing contributions at stations located in the northern part of the domain. Source apportionment studies were performed to assess the contribution of residential and non-residential combustion precursors to the total SOA. Non-residential combustion and road transportation sector contributed about 30-40 % to SOA formation (with increasing contributions at urban and near industrialized sites), whereas residential combustion (mainly related to wood burning) contributed to a larger extent, around 60-70 %. Contributions to OA from residential combustion precursors in different volatility ranges were also assessed: our results indicate that residential combustion gas-phase precursors in the semivolatile range (SVOC) contributed from 6 to 30 %, with higher contributions predicted at stations located in the southern part of the domain On the other hand, the oxidation products of higher-volatility precursors (the sum of intermediate-volatility compounds (IVOCs) and volatile organic compounds (VOCs)) contribute from 15 to 38 % with no specific gradient among the stations. Although the new parameterization leads to a better agreement between model results and observations, it still under predicts the SOA fraction, suggesting that uncertainties in the new scheme and other sources and/or formation mechanisms remain to be elucidated. Moreover, a more detailed characterization of the semivolatile components of the emissions is needed.
  • Moschos, Vaios; Kumar, Nivedita K.; Dällenbach, Kaspar; Baltensperger, Urs; Prevot, Andre S. H.; El Haddad, Imad (2018)
    The impact of brown carbon (BrC) on climate has been widely acknowledged but remains uncertain, because either its contribution to absorption is being ignored in most climate models or the associated mixed emission sources and atmospheric lifetime are not accounted for. In this work, we propose positive matrix factorization as a framework to apportion the contributions of individual primary and secondary organic aerosol (OA) source components of BrC absorption, by combining long-term aerosol mass spectrometry (AMS) data with concurrent ultraviolet-visible (UV-vis) spectroscopy measurements. The former feature time-depend ent factor contributions to OA mass, and the latter consist of wavelength-dependent absorption coefficients. Using this approach for a full-year case study, we estimate for the first time the mass absorption efficiency (MAE) of major light-absorbing water soluble OA components in the atmosphere. We show that secondary biogenic OA contributes negligibly to absorption despite dominating the mass concentration in the summer. In contrast, primary and secondary wood burning emissions are highly absorbing up to 500 nm. The approach allowed us to constrain their MAE within a confined range consistent with previous laboratory work, which can be used in climate models to estimate the impact of BrC from these emissions on the overall absorption.