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    The second ACTRIS inter-comparison (2016) for Aerosol Chemical Speciation Monitors (ACSM): Calibration protocols and instrument performance evaluations
    (Philadelphia, Pa.: Taylor & Francis, 2019) Freney, Evelyn; Zhang, Yunjiang; Croteau, Philip; Amodeo, Tanguy; Williams, Leah; Truong, François; Petit, Jean-Eudes; Sciare, Jean; Sarda-Esteve, Roland; Bonnaire, Nicolas; Arumae, Tarvo; Aurela, Minna; Bougiatioti, Aikaterini; Mihalopoulos, Nikolaos; Coz, Esther; Artinano, Begoña; Crenn, Vincent; Elste, Thomas; Heikkinen, Liine; Poulain, Laurent; Wiedensohler, Alfred; Herrmann, Hartmut; Priestman, Max; Alastuey, Andres; Stavroulas, Iasonas; Tobler, Anna; Vasilescu, Jeni; Zanca, Nicola; Canagaratna, Manjula; Carbone, Claudio; Flentje, Harald; Green, David; Maasikmets, Marek; Marmureanu, Luminita; Cruz Minguillon, Maria; Prevot, Andre S.H.; Gros, Valerie; Jayne, John; Favez, Olivier
    This work describes results obtained from the 2016 Aerosol Chemical Speciation Monitor (ACSM) intercomparison exercise performed at the Aerosol Chemical Monitor Calibration Center (ACMCC, France). Fifteen quadrupole ACSMs (Q_ACSM) from the European Research Infrastructure for the observation of Aerosols, Clouds and Trace gases (ACTRIS) network were calibrated using a new procedure that acquires calibration data under the same operating conditions as those used during sampling and hence gets information representative of instrument performance. The new calibration procedure notably resulted in a decrease in the spread of the measured sulfate mass concentrations, improving the reproducibility of inorganic species measurements between ACSMs as well as the consistency with co-located independent instruments. Tested calibration procedures also allowed for the investigation of artifacts in individual instruments, such as the overestimation of m/z 44 from organic aerosol. This effect was quantified by the m/z (mass-to-charge) 44 to nitrate ratio measured during ammonium nitrate calibrations, with values ranging from 0.03 to 0.26, showing that it can be significant for some instruments. The fragmentation table correction previously proposed to account for this artifact was applied to the measurements acquired during this study. For some instruments (those with high artifacts), this fragmentation table adjustment led to an “overcorrection” of the f44 (m/z 44/Org) signal. This correction based on measurements made with pure NH4NO3, assumes that the magnitude of the artifact is independent of chemical composition. Using data acquired at different NH4NO3 mixing ratios (from solutions of NH4NO3 and (NH4)2SO4) we observe that the magnitude of the artifact varies as a function of composition. Here we applied an updated correction, dependent on the ambient NO3 mass fraction, which resulted in an improved agreement in organic signal among instruments. This work illustrates the benefits of integrating new calibration procedures and artifact corrections, but also highlights the benefits of these intercomparison exercises to continue to improve our knowledge of how these instruments operate, and assist us in interpreting atmospheric chemistry. © 2019, © 2019 Author(s). Published with license by Taylor & Francis Group, LLC.
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    Variations of the aerosol chemical composition during Asian dust storm at Dushanbe, Tajikistan
    (Les Ulis : EDP Sciences, 2019) Fomba, Khanneh Wadinga; Müller, Konrad; Hofer, Julian; Makhmudov, Abduvosit N.; Althausen, Dietrich; Nazarov, Bahron I.; Abdullaev, Sabur F.; Herrmann, Hartmut
    Aerosol chemical composition was characterized during the Central Asian Dust Experiment (CADEX) at Dushanbe (Tajikistan). Aerosol samples were collected during a period of 2 months from March to May 2015 using a high volume DIGITEL DHA-80 sampler on quartz fiber filters. The filters were analyzed for their ionic, trace metals as well as organic and elemental carbon (OC/EC) content. The aerosol mass showed strong variation with mass concentration ranging from 18 μg/m3 to 110 μg/m3. The mineral dust concentrations varied between 0.9 μg/m3 and 88 μg/m3. Days of high aerosol mass loadings were dominated by mineral dust, which made up to about 80% of the aerosol mass while organic matter and inorganic ions made up about 70% of the aerosol mass during days of low aerosol mass loadings. The mineral dust composition showed different trace metal signatures in comparison to Saharan dust with higher Ca content and Ca/Fe ratios twice as high as that observed in Saharan dust. Strong influence of anthropogenic activities was observed in the trace metal concentrations with Zn and Pb concentrations ranging from 7 to 197 ng/m3 and 2 to 20 ng/m3, respectively. Mineral dust and anthropogenic activities relating to traffic, combustion as well as metallurgical industrial emissions are identified as the sources of the aerosol during this period. © 2019 The Authors, published by EDP Sciences.
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    Tropospheric aqueous-phase chemistry: kinetics, mechanisms, and its coupling to a changing gas phase
    (Washington, DC : ACS Publ., 2015) Herrmann, Hartmut; Schaefer, Thomas; Tilgner, Andreas; Styler, Sarah A.; Weller, Christian; Teich, Monique; Otto, Tobias
    [no abstract available]
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    The ocean's vital skin: Toward an integrated understanding of the sea surface microlayer
    (Lausanne : Frontiers Media, 2017) Engel, Anja; Bange, Hermann W.; Cunliffe, Michael; Burrows, Susannah M.; Friedrichs, Gernot; Galgani, Luisa; Herrmann, Hartmut; Hertkorn, Norbert; Johnson, Martin; Liss, Peter S.; Quinn, Patricia K.; Schartau, Markus; Soloviev, Alexander; Stolle, Christian; Upstill-Goddard, Robert C.; van Pinxteren, Manuela; Zäncker, Birthe
    Despite the huge extent of the ocean's surface, until now relatively little attention has been paid to the sea surface microlayer (SML) as the ultimate interface where heat, momentum and mass exchange between the ocean and the atmosphere takes place. Via the SML, large-scale environmental changes in the ocean such as warming, acidification, deoxygenation, and eutrophication potentially influence cloud formation, precipitation, and the global radiation balance. Due to the deep connectivity between biological, chemical, and physical processes, studies of the SML may reveal multiple sensitivities to global and regional changes. Understanding the processes at the ocean's surface, in particular involving the SML as an important and determinant interface, could therefore provide an essential contribution to the reduction of uncertainties regarding ocean-climate feedbacks. This review identifies gaps in our current knowledge of the SML and highlights a need to develop a holistic and mechanistic understanding of the diverse biological, chemical, and physical processes occurring at the ocean-atmosphere interface. We advocate the development of strong interdisciplinary expertise and collaboration in order to bridge between ocean and atmospheric sciences. Although this will pose significant methodological challenges, such an initiative would represent a new role model for interdisciplinary research in Earth System sciences.
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    EURODELTA 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, Samara
    The 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