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  • Qi, Lu; Vogel, Alexander L.; Esmaeilirad, Sepideh; Cao, Liming; Zheng, Jing; Jaffrezo, Jean-Luc; Fermo, Paola; Kasper-Giebl, Anne; Dällenbach, Kaspar; Chen, Mindong; Ge, Xinlei; Baltensperger, Urs; Prevot, Andre S. H.; Slowik, Jay G. (2020)
    The aerosol mass spectrometer (AMS), combined with statistical methods such as positive matrix factorization (PMF), has greatly advanced the quantification of primary organic aerosol (POA) sources and total secondary organic aerosol (SOA) mass. However, the use of thermal vaporization and electron ionization yields extensive thermal decomposition and ionization-induced fragmentation, which limit chemical information needed for SOA source apportionment. The recently developed extractive electrospray ionization time-of-flight mass spectrometer (EESI-TOF) provides mass spectra of the organic aerosol fraction with a linear response to mass and no thermal decomposition or ionization-induced fragmentation. However, the costs and operational requirements of online instruments make their use impractical for long-term or spatially dense monitoring applications. This challenge was overcome for AMS measurements by measuring re-nebulized water extracts from ambient filter samples. Here, we apply the same strategy for EESI-TOF measurements of 1 year of 24 h filter samples collected approximately every fourth day throughout 2013 at an urban site. The nebulized water extracts were measured simultaneously with an AMS. The application of positive matrix factorization (PMF) to EESI-TOF spectra resolved seven factors, which describe water-soluble OA: less and more aged biomass burning aerosol (LABB(EESI) and MABB(EESI), respectively), cigarette-smoke-related organic aerosol, primary biological organic aerosol, biogenic secondary organic aerosol, and a summer mixed oxygenated organic aerosol factor. Seasonal trends and relative contributions of the EESI-TOF OA sources were compared with AMS source apportionment factors, measured water-soluble ions, cellulose, and meteorological data. Cluster analysis was utilized to identify key factor-specific ions based on PMF. Both LABB and MABB contribute strongly during winter. LABB is distinguished by very high signals from C6H10O5 (levoglucosan and isomers) and C8H12O6, whereas MABB is characterized by a large number of CxHyOz and CxHyOzN species of two distinct populations: one with low H : C and high O : C and the other with high H : C and low O : C. Two oxygenated summertime SOA sources were attributed to terpene-derived biogenic SOA, a major summertime aerosol source in central Europe. Furthermore, a primary biological organic aerosol factor was identified, which was dominated by plant-derived fatty acids and correlated with free cellulose. The cigarette-smoke-related factor contained a high contribution of nicotine and high abundance of organic nitrate ions with low m/z.
  • 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 %.
  • Lihavainen, H.; Alghamdi, M. A.; Hyvärinen, A.; Hussein, T.; Neitola, Kimmo; Khoder, M.; Abdelmaksoud, A. S.; Al-Jeelani, H.; Shabbaj, I. I.; Almehmadi, F. M. (2017)
    To derive the comprehensive aerosol in situ characteristics at a rural background area in Saudi Arabia, an aerosol measurements station was established to Hada Al Sham, 60 km east from the Red Sea and the city of Jeddah. The present sturdy describes the observational data from February 2013 to February 2015 of scattering and absorption coefficients, Angstrom exponents and single scattering albedo over the measurement period. The average scattering and absorption coefficients at wavelength 525 nm were 109 +/- 71 Min(-1) (mean +/- SD, at STP conditions) and 15 +/- 17 Mm(-1) (at STP conditions), respectively. As expected, the scattering coefficient was dominated by large desert dust particles with low Angstrom scattering exponent, 0.49 +/- 0.62. Especially from February to June the Angstrom scattering exponent was clearly lower (0.23) and scattering coefficients higher (124 Mm(-1)) than total averages because of the dust outbreak season. Aerosol optical properties had clear diurnal cycle. The lowest scattering and absorption coefficients and aerosol optical depths were observed around noon. The observed diurnal variation is caused by wind direction and speed, during night time very calm easterly winds are dominating whereas during daytime the stronger westerly winds are dominating (sea breeze). Positive Matrix Factorization mathematical tool was applied to the scattering and absorption coefficients and PM2.5 and coarse mode (PM10-PM2.5) mass concentrations to identify source characteristics. Three different factors with clearly different properties were found; anthropogenic, BC source and desert dust. Mass absorption efficiencies for BC source and desert dust factors were, 6.0 m(2) g(-1) and 0.4 m(2) g(-1), respectively, and mass scattering efficiencies for anthropogenic (sulphate) and desert dust, 2.5 m(2) g(-1) and 0.8 m(2) g(-1), respectively.
  • Massoli, Paola; Stark, Harald; Canagaratna, Manjula R.; Krechmer, Jordan E.; Xu, Lu; Ng, Nga L.; Mauldin, Roy L.; Yan, Chao; Kimmel, Joel; Misztal, Pawel K.; Jimenez, Jose L.; Jayne, John T.; Worsnop, Douglas R. (2018)
    We present measurements of highly oxidized multifunctional molecules (HOMs) detected in the gas phase using a high-resolution time-of flight chemical ionization mass spectrometer with nitrate reagent ion (NO3- CIMS). The measurements took place during the 2013 Southern Oxidant and Aerosol Study (SOAS 2013) at a forest site in Alabama, where emissions were dominated by biogenic volatile organic compounds (BVOCs). Primary BVOC emissions were represented by isoprene mixed with various terpenes, making it a unique sampling location compared to previous NO3- CIMS deployments in monoterpene-dominated environments. During SOAS 2013, the NO3- CIMS detected HOMs with oxygen-to-carbon (O:C) ratios between 0.5 and 1.4 originating from both isoprene (C-5) and monoterpenes (C-10) as well as hundreds of additional HOMs with carbon numbers between C-3 and C-20. We used positive matrix factorization (PMF) to deconvolve the complex data set and extract information about classes of HOMs with similar temporal trends. This analysis revealed three isoprene-dominated and three monoterpene-dominated PMF factors. We observed significant amounts of isoprene- and monoterpene-derived organic nitrates (ONs) in most factors. The abundant presence of ONs was consistent with previous studies that have highlighted the importance of NOx-driven chemistry at the site. One of the isoprene-dominated factors had a strong correlation with SO2 plumes likely advected from nearby coal-fired power plants and was dominated by an isoprene derived ON (C5H10N2O8). These results indicate that anthropogenic emissions played a significant role in the formation of low volatility compounds from BVOC emissions in the region.
  • Nielsen, Ingeborg E.; Skov, Henrik; Massling, Andreas; Eriksson, Axel C.; Dall'Osto, Manuel; Junninen, Heikki; Sarnela, Nina; Lange, Robert; Collier, Sonya; Zhang, Qi; Cappa, Christopher D.; Nøjgaard, Jacob K. (2019)
    There are limited measurements of the chemical composition, abundance and sources of atmospheric particles in the High Arctic To address this, we report 93 d of soot particle aerosol mass spectrometer (SP-AMS) data collected from 20 February to 23 May 2015 at Villum Research Station (VRS) in northern Greenland (81 degrees 36' N). During this period, we observed the Arctic haze phenomenon with elevated PM1 concentrations ranging from an average of 2.3, 2.3 and 3.3 mu g m(-3) in February, March and April, respectively, to 1.2 mu g m(-3) in May. Particulate sulfate (SO42-) accounted for 66 % of the non-refractory PM1 with the highest concentration until the end of April and decreasing in May. The second most abundant species was organic aerosol (OA) (24 %). Both OA and PM1, estimated from the sum of all collected species, showed a marked decrease throughout May in accordance with the polar front moving north, together with changes in aerosol removal processes. The highest refractory black carbon (rBC) concentrations were found in the first month of the campaign, averaging 0.2 mu g m(-3). In March and April, rBC averaged 0.1 mu g m(-3) while decreasing to 0.02 mu g m(-3) in May. Positive matrix factorization (PMF) of the OA mass spectra yielded three factors: (1) a hydrocarbon-like organic aerosol (HOA) factor, which was dominated by primary aerosols and accounted for 12 % of OA mass, (2) an Arctic haze organic aerosol (AOA) factor and (3) a more oxygenated marine organic aerosol (MOA) factor. AOA dominated until mid-April (64 %-81 % of OA), while being nearly absent from the end of May and correlated significantly with SO42-, suggesting the main part of that factor is secondary OA. The MOA emerged late at the end of March, where it increased with solar radiation and reduced sea ice extent and dominated OA for the rest of the campaign until the end of May (24 %-74 % of OA), while AOA was nearly absent. The highest O/C ratio (0.95) and S/C ratio (0.011) was found for MOA. Our data support the current understanding that Arctic aerosols are highly influenced by secondary aerosol formation and receives an important contribution from marine emissions during Arctic spring in remote High Arctic areas. In view of a changing Arctic climate with changing sea-ice extent, biogenic processes and corresponding source strengths, highly time-resolved data are needed in order to elucidate the components dominating aerosol concentrations and enhance the understanding of the processes taking place.
  • Saarikoski, S.; Reyes, F.; Vázquez, Y.; Tagle, M.; Timonen, H.; Aurela, M.; Carbone, S.; Worsnop, D.R.; Hillamo, R.; Oyola, P. (2019)
    Chemical characteristics and the sources of submicron particles (<1 mu m in diameter) were investigated in Valle Alegre, the coastal area of Central Chile. The chemical composition of particles was studied by using a Soot particle Aerosol Mass Spectrometer and Multi-Angle Absorption Photometer. Submicron particles were dominated by organics (42% of mass) and sulfate (39% of mass) while the mass fractions of ammonium, nitrate and black carbon were much smaller (13, 2 and 4% of mass, respectively). Additionally, several metals (V, Zn, Fe, Cd, Cu, K, Na and Mg) were detected in submicron particles and also some of their inorganic salts (e.g. NaCl+, MgCl2+, CaCl2+, KCl+ and KNO3+). The sources of particles were examined by using Positive Matrix Factorization (PMF). Organic aerosol (OA) was divided into five factors by using PMF; hydrocarbon-like OA (HOA), biomass burning OA (BBOA), low-volatility oxygenated OA (LV-OOA), semi-volatile OA (SV-OOA) and marine oxygenated OOA (MOOA), Oxygenated factors (LV-OOA; SV-OOA and MOOA) comprised 75% of total OA with LV-OOA being the dominant factor (38% of OA). Sulfate had two major sources in Valle Alegre; similar to 70% of sulfate was related to anthropogenic sources through the oxidation of gas phase SO2 whereas similar to 24% of sulfate was associated with biogenic origin related to the oxidation of dimethyl sulfide in the marine environment. Regarding total submicron particle mass (campaign-average 9.5 mu g m(-3)), the contribution of anthropogenic sources was at least as large as that of biogenic origin.
  • Hao, Liqing; Garmash, Olga; Ehn, Mikael; Miettinen, Pasi; Massoli, Paola; Mikkonen, Santtu; Jokinen, Tuija; Roldin, Pontus; Aalto, Pasi; Yli-Juuti, Taina; Joutsensaari, Jorma; Petäjä, Tuukka; Kulmala, Markku; Lehtinen, Kari E. J.; Worsnop, Douglas R.; Virtanen, Annele (2018)
    Characterizing aerosol chemical composition in response to meteorological changes and atmospheric chemistry is important to gain insights into new particle formation mechanisms. A BAECC (Biogenic Aerosols - Effects on Clouds and Climate) campaign was conducted during the spring 2014 at the SMEAR II station (Station for Measuring Forest Ecosystem-Aerosol Relations) in Finland. The particles were characterized by a high-resolution time-of-flight aerosol mass spectrometer (HR-ToF-AMS). A PBL (planetary boundary layer) dilution model was developed to assist interpreting the measurement results. Right before nucleation events, the mass concentrations of organic and sulfate aerosol species were both decreased rapidly along with the growth of PBL heights. However, the mass fraction of sulfate aerosol of the total aerosol mass was increased, in contrast to a decrease for the organic mass fraction. Meanwhile, an increase in LVOOA (low-volatility oxygenated organic aerosol) mass fraction of the total organic mass was observed, in distinct comparison to a reduction of SVOOA (semi-volatile OOA) mass fraction. Our results demonstrate that, at the beginning of nucleation events, the observed sulfate aerosol mass was mainly driven by vertical turbulent mixing of sulfate-rich aerosols between the residual layer and the newly formed boundary layer, while the condensation of sulfuric acid (SA) played a minor role in interpreting the measured sulfate mass concentration. For the measured organic aerosols, their temporal profiles were mainly driven by dilution from PBL development, organic aerosol mixing in different boundary layers and/or partitioning of organic vapors, but accurate measurements of organic vapor concentrations and characterization on the spatial aerosol chemical composition are required. In general, the observed aerosol particles by AMS are subjected to joint effects of PBL dilution, atmospheric chemistry and aerosol mixing in different boundary layers. During aerosol growth periods in the nighttime, the mass concentrations of organic aerosols and organic nitrate aerosols were both increased. The increase in SVOOA mass correlated well with the calculated increase in condensed HOMs' (highly oxygenated organic molecules) mass. To our knowledge, our results are the first atmospheric observations showing a connection between increase in SVOOA and condensed HOMs during the nighttime.
  • Tikkanen, Olli-Pekka; Buchholz, Angela; Ylisirniö, Arttu; Schobesberger, Siegfried; Virtanen, Annele; Yli-Juuti, Taina (2020)
    The volatility distribution of the organic compounds present in secondary organic aerosol (SOA) at different conditions is a key quantity that has to be captured in order to describe SOA dynamics accurately. The development of the Filter Inlet for Gases and AEROsols (FIGAERO) and its coupling to a chemical ionization mass spectrometer (CIMS; collectively FIGAERO-CIMS) has enabled near-simultaneous sampling of the gas and particle phases of SOA through thermal desorption of the particles. The thermal desorption data have been recently shown to be interpretable as a volatility distribution with the use of the positive matrix factorization (PMF) method. Similarly, volatility distributions can be inferred from isothermal particle evaporation experiments when the particle size change measurements are analyzed with process-modeling techniques. In this study, we compare the volatility distributions that are retrieved from FIGAERO-CIMS and particle size change measurements during isothermal particle evaporation with process-modeling techniques. We compare the volatility distributions at two different relative humidities (RHs) and two oxidation conditions. In high-RH conditions, where particles are in a liquid state, we show that the volatility distributions derived via the two ways are similar within a reasonable assumption of uncertainty in the effective saturation mass concentrations that are derived from FIGAERO-CIMS data. In dry conditions, we demonstrate that the volatility distributions are comparable in one oxidation condition, and in the other oxidation condition, the volatility distribution derived from the PMF analysis shows considerably more high-volatility matter than the volatility distribution inferred from particle size change measurements. We also show that the Vogel-Tammann-Fulcher equation together with a recent glass transition temperature parametrization for organic compounds and PMF-derived volatility distribution estimates are consistent with the observed isothermal evaporation under dry conditions within the reported uncertainties. We conclude that the FIGAERO-CIMS measurements analyzed with the PMF method are a promising method for inferring the volatility distribution of organic compounds, but care has to be taken when the PMF factors are analyzed. Future process-modeling studies about SOA dynamics and properties could benefit from simultaneous FIGAERO-CIMS measurements.
  • 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.
  • Mohr, Claudia; Lopez-Hilfiker, Felipe D.; Zotter, Peter; Prevot, Andre S. H.; Xu, Lu; Ng, Nga L.; Herndon, Scott C.; Williams, Leah R.; Franklin, Jonathan P.; Zahniser, Mark S.; Worsnop, Douglas R.; Knighton, W. Berk; Aiken, Allison C.; Gorkowski, Kyle J.; Dubey, Manvendra K.; Allan, James D.; Thornton, Joel A. (2013)
  • Heikkinen, Liine; Äijälä, Mikko; Dällenbach, Kaspar; Chen, Gang; Garmash, Olga; Aliaga , Diego; Graeffe, Frans; Räty, Meri; Luoma, Krista; Aalto, Pasi; Kulmala, Markku; Petäjä, Tuukka; Worsnop, Douglas; Ehn, Mikael (2021)
    The Station for Measuring Ecosystem-Atmosphere Relations (SMEAR) II, located within the boreal forest of Finland, is a unique station in the world due to the wide range of long-term measurements tracking the Earth-atmosphere interface. In this study, we characterize the composition of organic aerosol (OA) at SMEAR II by quantifying its driving constituents. We utilize a multi-year data set of OA mass spectra measured in situ with an Aerosol Chemical Speciation Monitor (ACSM) at the station. To our knowledge, this mass spectral time series is the longest of its kind published to date. Similarly to other previously reported efforts in OA source apportionment from multi-seasonal or multi-annual data sets, we approached the OA characterization challenge through positive matrix factorization (PMF) using a rolling window approach. However, the existing methods for extracting minor OA components were found to be insufficient for our rather remote site. To overcome this issue, we tested a new statistical analysis framework. This included unsupervised feature extraction and classification stages to explore a large number of unconstrained PMF runs conducted on the measured OA mass spectra. Anchored by these results, we finally constructed a relaxed chemical mass balance (CMB) run that resolved different OA components from our observations. The presented combination of statistical tools provided a data-driven analysis methodology, which in our case achieved robust solutions with minimal subjectivity. Following the extensive statistical analyses, we were able to divide the 2012-2019 SMEAR II OA data (mass concentration interquartile range (IQR): 0.7, 1.3, and 2.6 mu gm(-3)) into three sub-categories - low-volatility oxygenated OA (LV-OOA), semi-volatile oxygenated OA (SV-OOA), and primary OA (POA) - proving that the tested methodology was able to provide results consistent with literature. LV-OOA was the most dominant OA type (organic mass fraction IQR: 49 %, 62 %, and 73 %). The seasonal cycle of LV-OOA was bimodal, with peaks both in summer and in February. We associated the wintertime LV-OOA with anthropogenic sources and assumed biogenic influence in LV-OOA formation in summer. Through a brief trajectory analysis, we estimated summertime natural LV-OOA formation of tens of ngm 3 h 1 over the boreal forest. SV-OOA was the second highest contributor to OA mass (organic mass fraction IQR: 19 %, 31 %, and 43 %). Due to SV-OOA's clear peak in summer, we estimate biogenic processes as the main drivers in its formation. Unlike for LV-OOA, the highest SV-OOA concentrations were detected in stable summertime nocturnal surface layers. Two nearby sawmills also played a significant role in SV-OOA production as also exemplified by previous studies at SMEAR II. POA, taken as a mix of two different OA types reported previously, hydrocarbon-like OA (HOA) and biomass burning OA (BBOA), made up a minimal OA mass fraction (IQR: 2 %, 6 %, and 13 %). Notably, the quantification of POA at SMEAR II using ACSM data was not possible following existing rolling PMF methodologies. Both POA organic mass fraction and mass concentration peaked in winter. Its appearance at SMEAR II was linked to strong southerly winds. Similar wind direction and speed dependence was not observed among other OA types. The high wind speeds probably enabled the POA transport to SMEAR II from faraway sources in a relatively fresh state. In the event of slower wind speeds, POA likely evaporated and/or aged into oxidized organic aerosol before detection. The POA organic mass fraction was significantly lower than reported by aerosol mass spectrometer (AMS) measurements 2 to 4 years prior to the ACSM measurements. While the co-located long-term measurements of black carbon supported the hypothesis of higher POA loadings prior to year 2012, it is also possible that short-term (POA) pollution plumes were averaged out due to the slow time resolution of the ACSM combined with the further 3 h data averaging needed to ensure good signal-to-noise ratios (SNRs). Despite the length of the ACSM data set, we did not focus on quantifying long-term trends of POA (nor other components) due to the high sensitivity of OA composition to meteorological anomalies, the occurrence of which is likely not normally distributed over the 8-year measurement period. Due to the unique and realistic seasonal cycles and meteorology dependences of the independent OA subtypes complemented by the reasonably low degree of unexplained OA variability, we believe that the presented data analysis approach performs well. Therefore, we hope that these results encourage also other researchers possessing several-yearlong time series of similar data to tackle the data analysis via similar semi- or unsupervised machine-learning approaches. This way the presented method could be further optimized and its usability explored and evaluated also in other environments.
  • Li, Jiayun; Liu, Zirui; Cao, Liming; Gao, Wenkang; Yan, Yingchao; Mao, Jia; Zhang, Xinghua; He, Lingyan; Xin, Jinyuan; Tang, Guiqian; Ji, Dongsheng; Hu, Bo; Wang, Lili; Wang, Yonghong; Dai, Lindong; Zhao, Dandan; Du, Wupeng; Wang, Yuesi (2020)
    To investigate the regional transport and formation mechanisms of submicron aerosols in the North China Plan (NCP), for the first time, we conducted simultaneous combined observations of the non-refractory submicron aerosols (NR-PM1) chemical compositions using aerosol mass spectrometer at urban Beijing (BJ) and at regional background area of the NCP (XL), from November 2018 to January 2019. During the observation period, average mass concentrations of PM1 in BJ and XL were 26.6 +/- 31.7 and 16.0 +/- 18.7 mu g m(-3) respectively. The aerosol composition in XL showed a lower contribution of organic aerosol (33% vs. 43%) and higher fractions of nitrate (35% vs. 30%), ammonium (16% vs. 13%), and chlorine (2% vs. 1%) than in BJ. Additionally, a higher contribution of secondary organic aerosol (SOA) was also observed in XL, suggesting low primary emissions and highly oxidized OA in the background area. Nitrate displayed a significantly enhanced contribution with the aggravation of aerosol pollution in both BJ and XL, which was completely neutralized by excess ammonium at both sites, that the abundant ammonia emissions in the NCP favor nitrate formation on a regional scale. In addition, a higher proportion of nitrate in XL can be attributed to the more neutral and higher oxidation capacity of the background atmosphere. Heterogeneous aqueous reaction plays an important role in sulfate and SOA formation, and is more efficient in BJ which can be attributed to the higher aerosol surface areas at urban site. Regional transport from the southwestern regions of NCP showed a significant impact on the formation of haze episodes. Beside the invasion of transported pollutants, the abundant water vapor associated with the air mass to the downwind background area further enhanced local secondary transformation and expanded the regional scope of the haze pollution in the NCP. (C) 2019 Elsevier B.V. All rights reserved.
  • Malinen, J.; Montier, L.; Montillaud, J.; Juvela, M.; Ristorcelli, I.; Clark, S. E.; Berne, O.; Bernard, J.-Ph.; Pelkonen, V.-M.; Collins, D. C. (2016)
    The nearby cloud L1642 is one of only two known very high latitude (b| > 30 deg) clouds actively forming stars. It is a rare example of star formation in isolated conditions, and can reveal important details of star formation in general, e.g. of the effect of magnetic fields. We compareHerschel dust emission structures and magnetic field orientation revealed byPlanck polarization maps in L1642. The high-resolution (similar to 20 arcsec)Herschel data reveal a complex structure including a dense, compressed central clump, and low-density striations. ThePlanck polarization data (at 10 arcmin resolution) reveal an ordered magnetic field pervading the cloud and aligned with the surrounding striations. There is a complex interplay between the cloud structure and large-scale magnetic field. This suggests that the magnetic field is closely linked to the formation and evolution of the cloud. CO rotational emission confirms that the striations are connected with the main clumps and likely to contain material either falling into or flowing out of the clumps. There is a clear transition from aligned to perpendicular structures approximately at a column density ofN(H) = 1.6 x 10(21) cm(-2). Comparing theHerschel maps with thePlanck polarization maps shows the close connection between the magnetic field and cloud structure even in the finest details of the cloud.
  • Brown, Steven G.; Eberly, Shelly; Paatero, Pentti; Norris, Gary A. (2015)
    The new version of EPA's positive matrix factorization (EPA PMF) software, 5.0, includes three error estimation (EE) methods for analyzing factor analytic solutions: classical bootstrap (BS), displacement of factor elements (DISP), and bootstrap enhanced by displacement (BS-DISP). These methods capture the uncertainty of PMF analyses due to randomerrors and rotational ambiguity. To demonstrate the utility of the EEmethods, results are presented for three data sets: (1) speciated PM2.5 data froma chemical speciation network (CSN) site in Sacramento, California (2003-2009); (2) trace metal, ammonia, and other species inwater quality samples taken at an inline storage system (ISS) in Milwaukee, Wisconsin (2006); and (3) an organic aerosol data set from high- resolution aerosolmass spectrometer (HR-AMS) measurements in Las Vegas, Nevada (January 2008). We present an interpretation of EE diagnostics for these data sets, results fromsensitivity tests of EE diagnostics using additional and fewer factors, and recommendations for reporting PMF results. BS-DISP and BS are found useful in understanding the uncertainty of factor profiles; they also suggest if the data are over-fitted by specifying toomany factors. DISP diagnosticswere consistently robust, indicating its use for understanding rotational uncertainty and as a first step in assessing a solution's viability. The uncertainty of each factor's identifying species is shown to be a useful gauge for evaluating multiple solutions, e.g., with a different number of factors. Published by Elsevier B.V. This is an open access article under the CC BY-NC-ND license (
  • Dall'Osto, M.; Beddows, D. C. S.; Asmi, A.; Poulain, L.; Hao, L.; Freney, E.; Allan, J. D.; Canagaratna, M.; Crippa, M.; Bianchi, F.; de Leeuw, G.; Eriksson, A.; Swietlicki, E.; Hansson, H. C.; Henzing, J. S.; Granier, C.; Zemankova, K.; Laj, P.; Onasch, T.; Prevot, A.; Putaud, J. P.; Sellegri, K.; Vidal, M.; Virtanen, A.; Simo, R.; Worsnop, D.; O'Dowd, C.; Kulmala, M.; Harrison, Roy M. (2018)
    The formation of new atmospheric particles involves an initial step forming stable clusters less than a nanometre in size (similar to 10 nm). Although at times, the same species can be responsible for both processes, it is thought that more generally each step comprises differing chemical contributors. Here, we present a novel analysis of measurements from a unique multi-station ground-based observing system which reveals new insights into continental-scale patterns associated with new particle formation. Statistical cluster analysis of this unique 2-year multi-station dataset comprising size distribution and chemical composition reveals that across Europe, there are different major seasonal trends depending on geographical location, concomitant with diversity in nucleating species while it seems that the growth phase is dominated by organic aerosol formation. The diversity and seasonality of these events requires an advanced observing system to elucidate the key processes and species driving particle formation, along with detecting continental scale changes in aerosol formation into the future.
  • Zhao, Jian; Qiu, Yanmei; Zhou, Wei; Xu, Weiqi; Wang, Junfeng; Zhang, Yingjie; Li, Linjie; Xie, Conghui; Wang, Qingqing; Du, Wei; Worsnop, Douglas R.; Canagaratna, Manjula R.; Zhou, Libo; Ge, Xinlei; Fu, Pingqing; Li, Jie; Wang, Zifa; Donahue, Neil M.; Sun, Yele (2019)
    Organic aerosol (OA) constituted a large fraction of aerosol particles during severe haze episodes in winter in northern China, yet our understanding of its physical and chemical processing was limited. Here we investigate the sources and processes of OA during four haze episodes in winter in 2016 using high-resolution aerosol mass spectrometer. The PM2.5 reached 400 mu g/m(3) during the severest episode (Ep1) when Beijing issued a red alert and implemented strict emission controls. Our results showed that secondary OA (SOA) dominated OA during haze episodes on average accounting for 46-66% of OA and was comparable to secondary inorganic aerosol (SIA) with the SOA/SIA ratios being 0.51-0.72. Primary OA from fossil-fuel combustion, biomass burning, and cooking presented very strong diurnal variations during haze episodes and contributed up to 60% in OA at night. Comparatively, the changes in semivolatile and low-volatility SOA were relatively small except a substantial increase in aqueous phase-related oxidized OA (aq-OOA) during Ep1 with high relative humidity and aerosol water content. aq-OOA fell well into a small region in the middle of the triangle plot of f(44) versus f(43) (fraction of m/z 44 and 43 in OA, respectively), which can be used as a diagnostic for the presence of aqueous phase processing of SOA. In addition, the increases of SO2+/SO3+ as a function of relative humidity, the triangle plot of f(H2SO4+) versus f(HSO3+), and high nitrogen-to-carbon ratio in aq-OOA suggest the potential formation of sulfur- and nitrogen-containing organic compounds through aqueous phase processing.
  • Äijälä, Mikko; Heikkinen, Liine; Fröhlich, Roman; Canonaco, Francesco; Prevot, Andre S. H.; Junninen, Heikki; Petäjä, Tuukka; Kulmala, Markku; Worsnop, Douglas; Ehn, Mikael (2017)
    Mass spectrometric measurements commonly yield data on hundreds of variables over thousands of points in time. Refining and synthesizing this raw data into chemical information necessitates the use of advanced, statisticsbased data analytical techniques. In the field of analytical aerosol chemistry, statistical, dimensionality reductive methods have become widespread in the last decade, yet comparable advanced chemometric techniques for data classification and identification remain marginal. Here we present an example of combining data dimensionality reduction (factorization) with exploratory classification (clustering), and show that the results cannot only reproduce and corroborate earlier findings, but also complement and broaden our current perspectives on aerosol chemical classification. We find that applying positive matrix factorization to extract spectral characteristics of the organic component of air pollution plumes, together with an unsupervised clustering algorithm, k -means C C, for classification, reproduces classical organic aerosol speciation schemes. Applying appropriately chosen metrics for spectral dissimilarity along with optimized data weighting, the source-specific pollution characteristics can be statistically resolved even for spectrally very similar aerosol types, such as different combustion-related anthropogenic aerosol species and atmospheric aerosols with similar degree of oxidation. In addition to the typical oxidation level and source-driven aerosol classification, we were also able to classify and characterize outlier groups that would likely be disregarded in a more conventional analysis. Evaluating solution quality for the classification also provides means to assess the performance of mass spectral simi-larity metrics and optimize weighting for mass spectral variables. This facilitates algorithm-based evaluation of aerosol spectra, which may prove invaluable for future development of automatic methods for spectra identification and classification. Robust, statistics-based results and data visualizations also provide important clues to a human analyst on the existence and chemical interpretation of data structures. Applying these methods to a test set of data, aerosol mass spectrometric data of organic aerosol from a boreal forest site, yielded five to seven different recurring pollution types from various sources, including traffic, cooking, biomass burning and nearby sawmills. Additionally, three distinct, minor pollution types were discovered and identified as amine-dominated aerosols.
  • Lee, Ben H.; Lopez-Hilfiker, Felipe D.; D'Ambro, Emma L.; Zhou, Putian; Boy, Michael; Petäjä, Tuukka; Hao, Liqing; Virtanen, Annele; Thornton, Joel A. (2018)
    We present hourly online observations of molecular compositions (CxHyOzN0-1) and abundances of oxygenated organic species in gas and submicron particle phases from April to June of 2014 as part of the Biogenic Aerosols-Effects on Cloud and Climate (BAECC) campaign. Measurements were made using the Filter Inlet for Gases and AEROsols coupled to a high-resolution time-of-flight iodide-adduct ionization mass spectrometer (FIGAERO-CIMS) located atop a 35m tall tower, about 10m above a boreal forest canopy at the SMEAR II research station in Hyytiala, Finland. Semi-volatile and highly oxygenated multifunctional (HOM) organic species possessing from 1 up to 20 carbon atoms, and with as few as 2 and as many as 16 oxygen atoms, were routinely observed. Utilizing non-negative matrix factorization, we determined that > 90 and > 99% of the organic mass in the gas and particle phases, respectively, exhibited one of three distinct diel trends: one in which abundances were enhanced at daytime, another in the early morning hours, and thirdly during nighttime. Particulate organic nitrates contributed similar to 35% to the total organic aerosol mass loading at night during BAECC, much higher than observed by the same instrument package at a mixed-deciduous forest site in the southeastern US that experienced higher nighttime concentrations of nitrogen oxides. Unique HOM monomers (defined here as those with 10 carbon and 7 or more oxygen atoms) and dimers (at least 16 carbon atoms), with and without a nitrogen atom, were found in most of the three subgroups of both phases. We show the potential to connect these groupings of compounds based on their distinct behavior in time to the expected chemical conditions (biogenic VOC precursor, oxidant type, etc.) responsible for their production. A suite of nitrated dimer-like compounds was detected in both the gas and particle phases, suggesting a potential role for the formation of low-volatility organics from NO3-radical-driven, as well as daytime NO-influenced, monoterpene chemistry.
  • Patel, Kanan; Bhandari, Sahil; Gani, Shahzad; Campmier, Mark Joseph; Kumar, Purushottam; Habib, Gazala; Apte, Joshua; Ruiz, Lea Hildebrandt (2021)
    New Delhi, India is the most polluted megacity in the world and routinely experiences high particulate matter (PM) concentrations. As part of the Delhi Aerosol Supersite Study, we have been measuring PM, concentration and composition in Delhi continuously since January 2017. This paper focuses on autumn, one of the most polluted seasons in Delhi when PM, concentrations steadily increase throughout the season and can exceed 1000 mu g m(-3) during episodic events. Positive matrix factorization on the organic aerosol (OA) spectrum suggests comparable seasonal average contributions from hydrocarbon-like OA (HOA), biomass burning OA (BBOA), and oxidized OA (OOA), with BBOA dominating during episodic events. We demonstrate the influence of regional sources such as agricultural burning during this season through temporal trends of pollutants, PMF factors, meteorology, and nonparametric wind regression analysis. We use inorganic fragment ratios to show the influence of metals during the festival of Diwali. Furthermore, we demonstrate the influence of transitioning meteorology in governing PM, composition through the season. Overall, our analysis provides novel insights into the factors controlling PM, during one of the most polluted seasons in Delhi.