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- ItemOrganic aerosol components derived from 25 AMS data sets across Europe using a consistent ME-2 based source apportionment approach(München : European Geopyhsical Union, 2014) Crippa, M.; Canonaco, F.; Lanz, V.A.; Äijälä, M.; Allan, J.D.; Carbone, S.; Capes, G.; Ceburnis, D.; Dall'Osto, M.; Day, D.A.; DeCarlo, P.F.; Ehn, M.; Eriksson, A.; Freney, E.; Hildebrandt Ruiz, L.; Hillamo, R.; Jimenez, J.L.; Junninen, H.; Kiendler-Scharr, A.; Kortelainen, A.-M.; Kulmala, M.; Laaksonen, A.; Mensah, A.A.; Mohr, C.; Nemitz, E.; O'Dowd, C.; Ovadnevaite, J.; Pandis, S.N.; Petäjä, T.; Poulain, L.; Saarikoski, S.; Sellegri, K.; Swietlicki, E.; Tiitta, P.; Worsnop, D.R.; Baltensperger, U.; Prévôt, A.S.H.Organic aerosols (OA) represent one of the major constituents of submicron particulate matter (PM1) and comprise a huge variety of compounds emitted by different sources. Three intensive measurement field campaigns to investigate the aerosol chemical composition all over Europe were carried out within the framework of the European Integrated Project on Aerosol Cloud Climate and Air Quality Interactions (EUCAARI) and the intensive campaigns of European Monitoring and Evaluation Programme (EMEP) during 2008 (May–June and September–October) and 2009 (February–March). In this paper we focus on the identification of the main organic aerosol sources and we define a standardized methodology to perform source apportionment using positive matrix factorization (PMF) with the multilinear engine (ME-2) on Aerodyne aerosol mass spectrometer (AMS) data. Our source apportionment procedure is tested and applied on 25 data sets accounting for two urban, several rural and remote and two high altitude sites; therefore it is likely suitable for the treatment of AMS-related ambient data sets. For most of the sites, four organic components are retrieved, improving significantly previous source apportionment results where only a separation in primary and secondary OA sources was possible. Generally, our solutions include two primary OA sources, i.e. hydrocarbon-like OA (HOA) and biomass burning OA (BBOA) and two secondary OA components, i.e. semi-volatile oxygenated OA (SV-OOA) and low-volatility oxygenated OA (LV-OOA). For specific sites cooking-related (COA) and marine-related sources (MSA) are also separated. Finally, our work provides a large overview of organic aerosol sources in Europe and an interesting set of highly time resolved data for modeling purposes.
- ItemOrganic aerosol concentration and composition over Europe: Insights from comparison of regional model predictions with aerosol mass spectrometer factor analysis(München : European Geopyhsical Union, 2014) Fountoukis, C.; Megaritis, A.G.; Skyllakou, K.; Charalampidis, P.E.; Pilinis, C.; van der Gon, H.A.C. Denier; Crippa, M.; Canonaco, F.; Mohr, C.; Prévôt, A.S.H.; Allan, J.D.; Poulain, L.; Petäjä, T.; Tiitta, P.; Carbone, S.; Kiendler-Scharr, A.; Nemitz, E.; O'Dowd, C.; Swietlicki, E.; Pandis, S.N.A detailed three-dimensional regional chemical transport model (Particulate Matter Comprehensive Air Quality Model with Extensions, PMCAMx) was applied over Europe, focusing on the formation and chemical transformation of organic matter. Three periods representative of different seasons were simulated, corresponding to intensive field campaigns. An extensive set of AMS measurements was used to evaluate the model and, using factor-analysis results, gain more insight into the sources and transformations of organic aerosol (OA). Overall, the agreement between predictions and measurements for OA concentration is encouraging, with the model reproducing two-thirds of the data (daily average mass concentrations) within a factor of 2. Oxygenated OA (OOA) is predicted to contribute 93% to total OA during May, 87% during winter and 96% during autumn, with the rest consisting of fresh primary OA (POA). Predicted OOA concentrations compare well with the observed OOA values for all periods, with an average fractional error of 0.53 and a bias equal to −0.07 (mean error = 0.9 μg m−3, mean bias = −0.2 μg m−3). The model systematically underpredicts fresh POA at most sites during late spring and autumn (mean bias up to −0.8 μg m−3). Based on results from a source apportionment algorithm running in parallel with PMCAMx, most of the POA originates from biomass burning (fires and residential wood combustion), and therefore biomass burning OA is most likely underestimated in the emission inventory. The sensitivity of POA predictions to the corresponding emissions' volatility distribution is discussed. The model performs well at all sites when the Positive Matrix Factorization (PMF)-estimated low-volatility OOA is compared against the OA with saturation concentrations of the OA surrogate species C* ≤ 0.1 μg m−3 and semivolatile OOA against the OA with C* > 0.1 μg m−3.
- ItemACTRIS ACSM intercomparison - Part 1: Reproducibility of concentration and fragment results from 13 individual Quadrupole Aerosol Chemical Speciation Monitors (Q-ACSM) and consistency with co-located instruments(München : European Geopyhsical Union, 2015) Crenn, V.; Sciare, J.; Croteau, P.L.; Verlhac, S.; Fröhlich, R.; Belis, C.A.; Aas, W.; Äijälä, M.; Alastuey, A.; Artiñano, B.; Baisnée, D.; Bonnaire, N.; Bressi, M.; Canagaratna, M.; Canonaco, F.; Carbone, C.; Cavalli, F.; Coz, E.; Cubison, M.J.; Esser-Gietl, J.K.; Green, D.C.; Gros, V.; Heikkinen, L.; Herrmann, H.; Lunder, C.; Minguillón, M.C.; Močnik, G.; O'Dowd, C.D.; Ovadnevaite, J.; Petit, J.-E.; Petralia, E.; Poulain, L.; Priestman, M.; Riffault, V.; Ripoll, A.; Sarda-Estève, R.; Slowik, J.G.; Setyan, A.; Wiedensohler, A.; Baltensperger, U.; Prévôt, A.S.H.; Jayne, J.T.; Favez, O.As part of the European ACTRIS project, the first large Quadrupole Aerosol Chemical Speciation Monitor (Q-ACSM) intercomparison study was conducted in the region of Paris for 3 weeks during the late-fall – early-winter period (November–December 2013). The first week was dedicated to the tuning and calibration of each instrument, whereas the second and third were dedicated to side-by-side comparison in ambient conditions with co-located instruments providing independent information on submicron aerosol optical, physical, and chemical properties. Near real-time measurements of the major chemical species (organic matter, sulfate, nitrate, ammonium, and chloride) in the non-refractory submicron aerosols (NR-PM1) were obtained here from 13 Q-ACSM. The results show that these instruments can produce highly comparable and robust measurements of the NR-PM1 total mass and its major components. Taking the median of the 13 Q-ACSM as a reference for this study, strong correlations (r2 > 0.9) were observed systematically for each individual Q-ACSM across all chemical families except for chloride for which three Q-ACSMs showing weak correlations partly due to the very low concentrations during the study. Reproducibility expanded uncertainties of Q-ACSM concentration measurements were determined using appropriate methodologies defined by the International Standard Organization (ISO 17025, 1999) and were found to be 9, 15, 19, 28, and 36 % for NR-PM1, nitrate, organic matter, sulfate, and ammonium, respectively. However, discrepancies were observed in the relative concentrations of the constituent mass fragments for each chemical component. In particular, significant differences were observed for the organic fragment at mass-to-charge ratio 44, which is a key parameter describing the oxidation state of organic aerosol. Following this first major intercomparison exercise of a large number of Q-ACSMs, detailed intercomparison results are presented, along with a discussion of some recommendations about best calibration practices, standardized data processing, and data treatment.
- ItemEURODELTA III exercise: An evaluation of air quality models’ capacity to reproduce the carbonaceous aerosol(Amsterdam : Elsevier, 2019) Mircea, Mihaela; Bessagnet, Bertrand; D'Isidoro, Massimo; Pirovano, Guido; Aksoyoglu, Sebnem; Ciarelli, Giancarlo; Tsyro, Svetlana; Manders, Astrid; Bieser, Johannes; Stern, Rainer; Vivanco, Marta García; Cuvelier, Cornelius; Aas, Wenche; Prévôt, André S.H.; Aulinger, Armin; Briganti, Gino; Calori, Giuseppe; Cappelletti, Andrea; Colette, Augustin; Couvidat, Florian; Fagerli, Hilde; Finardi, Sandro; Kranenburg, Richard; Rouïl, Laurence; Silibello, Camillo; Spindler, Gerald; Poulain, Laurent; Herrmann, Hartmut; Jimenez, Jose L.; Day, Douglas A.; Tiitta, Petri; Carbone, SamaraThe carbonaceous aerosol accounts for an important part of total aerosol mass, affects human health and climate through its effects on physical and chemical properties of the aerosol, yet the understanding of its atmospheric sources and sinks is still incomplete. This study shows the state-of-the-art in modelling carbonaceous aerosol over Europe by comparing simulations performed with seven chemical transport models (CTMs) currently in air quality assessments in Europe: CAMx, CHIMERE, CMAQ, EMEP/MSC-W, LOTOS-EUROS, MINNI and RCGC. The simulations were carried out in the framework of the EURODELTA III modelling exercise and were evaluated against field measurements from intensive campaigns of European Monitoring and Evaluation Programme (EMEP) and the European Integrated Project on Aerosol Cloud Climate and Air Quality Interactions (EUCAARI). Model simulations were performed over the same domain, using as much as possible the same input data and covering four seasons: summer (1–30 June 2006), winter (8 January – 4 February 2007), autumn (17 September- 15 October 2008) and spring (25 February - 26 March 2009). The analyses of models’ performances in prediction of elemental carbon (EC) for the four seasons and organic aerosol components (OA) for the last two seasons show that all models generally underestimate the measured concentrations. The maximum underestimation of EC is about 60% and up to about 80% for total organic matter (TOM). The underestimation of TOM outside of highly polluted area is a consequence of an underestimation of secondary organic aerosol (SOA), in particular of its main contributor: biogenic secondary aerosol (BSOA). This result is independent on the SOA modelling approach used and season. The concentrations and daily cycles of total primary organic matter (TPOM) are generally better reproduced by the models since they used the same anthropogenic emissions. However, the combination of emissions and model formulation leads to overestimate TPOM concentrations in 2009 for most of the models. All models capture relatively well the SOA daily cycles at rural stations mainly due to the spatial resolution used in the simulations. For the investigated carbonaceous aerosol compounds, the differences between the concentrations simulated by different models are lower than the differences between the concentrations simulated with a model for different seasons. © 2019 The Authors
- ItemMulti-generation OH oxidation as a source for highly oxygenated organic molecules from aromatics(Katlenburg-Lindau : EGU, 2020) Garmash, Olga; Rissanen, Matti P.; Pullinen, Iida; Schmit, Sebastian; Kausiala, Oskari; Tillmann, Ralf; Zhao, Defeng; Percival, Carl; Bannan, Thomas J.; Priestley, Michael; Hallquist, Åsa M.; Kleist, Einhard; Kiendler-Scharr, Astrid; Hallquist, Mattias; Berndt, Torsten; McFiggans, Gordon; Wildt, Jürgen; Mentel, Thomas F.; Ehn, MikaelRecent studies have recognised highly oxygenated organic molecules (HOMs) in the atmosphere as important in the formation of secondary organic aerosol (SOA). A large number of studies have focused on HOM formation from oxidation of biogenically emitted monoterpenes. However, HOM formation from anthropogenic vapours has so far received much less attention. Previous studies have identified the importance of aromatic volatile organic compounds (VOCs) for SOA formation. In this study, we investigated several aromatic compounds, benzene (C6H6), toluene (C7H8), and naphthalene (C10H8), for their potential to form HOMs upon reaction with hydroxyl radicals (OH). We performed flow tube experiments with all three VOCs and focused in detail on benzene HOM formation in the Julich Plant Atmosphere Chamber (JPAC). In JPAC, we also investigated the response of HOMs to NOx and seed aerosol. Using a nitrate-based chemical ionisation mass spectrometer (CI-APi-TOF), we observed the formation of HOMs in the flow reactor oxidation of benzene from the first OH attack. However, in the oxidation of toluene and naphthalene, which were injected at lower concentrations, multigeneration OH oxidation seemed to impact the HOM composition. We tested this in more detail for the benzene system in the JPAC, which allowed for studying longer residence times. The results showed that the apparent molar benzene HOM yield under our experimental conditions varied from 4.1% to 14.0 %, with a strong dependence on the OH concentration, indicating that the majority of observed HOMs formed through multiple OH-oxidation steps. The composition of the identified HOMs in the mass spectrum also supported this hypothesis. By injecting only phenol into the chamber, we found that phenol oxidation cannot be solely responsible for the observed HOMs in benzene experiments. When NOx was added to the chamber, HOM composition changed and many oxygenated nitrogen-containing products were observed in CI-APi-TOF. Upon seed aerosol injection, the HOM loss rate was higher than predicted by irreversible condensation, suggesting that some undetected oxygenated intermediates also condensed onto seed aerosol, which is in line with the hypothesis that some of the HOMs were formed in multi-generation OH oxidation. Based on our results, we conclude that HOM yield and composition in aromatic systems strongly depend on OH and VOC concentration and more studies are needed to fully understand this effect on the formation of HOMs and, consequently, SOA. We also suggest that the dependence of HOM yield on chamber conditions may explain part of the variability in SOA yields reported in the literature and strongly advise monitoring HOMs in future SOA studies. © Author(s) 2020.
- ItemMarine organic matter in the remote environment of the Cape Verde islands-an introduction and overview to the MarParCloud campaign(Katlenburg-Lindau : EGU, 2020) van Pinxteren, Manuela; Fomba, KhannehWadinga; Triesch, Nadja; Stolle, Christian; Wurl, Oliver; Bahlmann, Enno; Gong, Xianda; Voigtländer, Jens; Wex, Heike; Robinson, Tiera-Brandy; Barthel, Stefan; Zeppenfeld, Sebastian; Hoffmann, Erik Hans; Roveretto, Marie; Li, Chunlin; Grosselin, Benoit; Daële, Veronique; Senf, Fabian; van Pinxteren, Dominik; Manzi, Malena; Zabalegui, Nicolás; Frka, Sanja; Gašparović, Blaženka; Pereira, Ryan; Li, Tao; Wen, Liang; Li, Jiarong; Zhu, Chao; Chen, Hui; Chen, Jianmin; Fiedler, Björn; von Tümpling, Wolf; Read, Katie Alana; Punjabi, Shalini; Lewis, Alastair Charles; Hopkins, James Roland; Carpenter, Lucy Jane; Peeken, Ilka; Rixen, Tim; Schulz-Bull, Detlef; Mong, María Eugenia; Mellouki, Abdelwahid; George, Christian; Stratmann, Frank; Herrmann, HartmutThe project MarParCloud (Marine biological production, organic aerosol Particles and marine Clouds: a process chain) aims to improve our understanding of the genesis, modification and impact of marine organic matter (OM) from its biological production, to its export to marine aerosol particles and, finally, to its ability to act as ice-nucleating particles (INPs) and cloud condensation nuclei (CCN). A field campaign at the Cape Verde Atmospheric Observatory (CVAO) in the tropics in September-October 2017 formed the core of this project that was jointly performed with the project MARSU (MARine atmospheric Science Unravelled). A suite of chemical, physical, biological and meteorological techniques was applied, and comprehensive measurements of bulk water, the sea surface microlayer (SML), cloud water and ambient aerosol particles collected at a ground-based and a mountain station took place. Key variables comprised the chemical characterization of the atmospherically relevant OM components in the ocean and the atmosphere as well as measurements of INPs and CCN. Moreover, bacterial cell counts, mercury species and trace gases were analyzed. To interpret the results, the measurements were accompanied by various auxiliary parameters such as air mass back-trajectory analysis, vertical atmospheric profile analysis, cloud observations and pigment measurements in seawater. Additional modeling studies supported the experimental analysis. During the campaign, the CVAO exhibited marine air masses with low and partly moderate dust influences. The marine boundary layer was well mixed as indicated by an almost uniform particle number size distribution within the boundary layer. Lipid biomarkers were present in the aerosol particles in typical concentrations of marine background conditions. Accumulation-and coarse-mode particles served as CCN and were efficiently transferred to the cloud water. The ascent of ocean-derived compounds, such as sea salt and sugar-like compounds, to the cloud level, as derived from chemical analysis and atmospheric transfer modeling results, denotes an influence of marine emissions on cloud formation. Organic nitrogen compounds (free amino acids) were enriched by several orders of magnitude in submicron aerosol particles and in cloud water compared to seawater. However, INP measurements also indicated a significant contribution of other non-marine sources to the local INP concentration, as (biologically active) INPs were mainly present in supermicron aerosol particles that are not suggested to undergo strong enrichment during ocean-atmosphere transfer. In addition, the number of CCN at the supersaturation of 0.30 % was about 2.5 times higher during dust periods compared to marine periods. Lipids, sugar-like compounds, UV-absorbing (UV: ultraviolet) humic-like substances and low-molecularweight neutral components were important organic compounds in the seawater, and highly surface-active lipids were enriched within the SML. The selective enrichment of specific organic compounds in the SML needs to be studied in further detail and implemented in an OM source function for emission modeling to better understand transfer patterns, the mechanisms of marine OM transformation in the atmosphere and the role of additional sources. In summary, when looking at particulate mass, we see oceanic compounds transferred to the atmospheric aerosol and to the cloud level, while from a perspective of particle number concentrations, sea spray aerosol (i.e., primary marine aerosol) contributions to both CCN and INPs are rather limited. © Author(s) 2020.