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4. Evaluation of receptor and chemical transport models for PM10 source apportionment

Author

Belis, C.A., Pernigotti, D., Pirovano, G., Favez, O., Jaffrezo, J.L., Kuenen, J., Denier van Der Gon, H., Reizer, M., Riffault, V., Alleman, L.Y., Almeida, M., Amato, F., Angyal, A., Argyropoulos, G., Bande, S., Beslic, I., Besombes, J.-L., Bove, M.C., Brotto, P., Calori, G., Cesari, D., Colombi, C., Contini, D., De Gennaro, G., Di Gilio, A., Diapouli, E., El Haddad, I., Elbern, H., Eleftheriadis, K., Ferreira, J., Vivanco, M. Garcia, Gilardoni, S., Golly, B., Hellebust, S., Hopke, P.K., Izadmanesh, Y., Jorquera, H., Krajsek, K., Kranenburg, R., Lazzeri, P., Lenartz, F., Lucarelli, F., Maciejewska, K., Manders, A., Manousakas, M., Masiol, M., Mircea, M., Mooibroek, D., Nava, S., Oliveira, D., Paglione, M., Pandolfi, M., Perrone, M., Petralia, E., Pietrodangelo, A., Pillon, S., Pokorna, P., Prati, P., Salameh, D., Samara, C., Samek, L., Saraga, D., Sauvage, S., Schaap, M., Scotto, F., Sega, K., Siour, G., Tauler, R., Valli, G., Vecchi, R., Venturini, E., Vestenius, M., Waked, A., and Yubero, E.

Published
2020
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5. Aqueous phase oxidation of sulphur dioxide by ozone in cloud droplets

Author

Hoyle, CR, Fuchs, C, Jarvinen, E, Saathoff, H, Dias, A, El Haddad, I, Gysel, M, Coburn, SC, Trostl, J, Hansel, A, Bianchi, F, Breitenlechner, M, Corbin, JC, Craven, J, Donahue, NM, Duplissy, J, Ehrhart, S, Frege, C, Gordon, H, Hoppel, N, Heinritzi, M, Kristensen, TB, Molteni, U, Nichman, L, Pinterich, T, Prevôt, ASH, Simon, M, Slowik, JG, Steiner, G, Tome, A, Vogel, AL, Volkamer, R, Wagner, AC, Wagner, R, Wexler, AS, Williamson, C, Winkler, PM, Yan, C, Amorim, A, Dommen, J, Curtius, J, Gallagher, MW, Flagan, RC, Kirkby, J, Kulmala, M, Mohler, O, Stratmann, F, Worsnop, DR, and Baltensperger, U

Subjects
Meteorology & Atmospheric Sciences, Atmospheric Sciences, Astronomical and Space Sciences
Abstract

The growth of aerosol due to the aqueous phase oxidation of sulfur dioxide by ozone was measured in laboratory-generated clouds created in the Cosmics Leaving OUtdoor Droplets (CLOUD) chamber at the European Organization for Nuclear Research (CERN). Experiments were performed at 10 and-10 °C, on acidic (sulfuric acid) and on partially to fully neutralised (ammonium sulfate) seed aerosol. Clouds were generated by performing an adiabatic expansion-pressurising the chamber to 220 hPa above atmospheric pressure, and then rapidly releasing the excess pressure, resulting in a cooling, condensation of water on the aerosol and a cloud lifetime of approximately 6 min. A model was developed to compare the observed aerosol growth with that predicted using oxidation rate constants previously measured in bulk solutions. The model captured the measured aerosol growth very well for experiments performed at 10 and-10 °C, indicating that, in contrast to some previous studies, the oxidation rates of SO2 in a dispersed aqueous system can be well represented by using accepted rate constants, based on bulk measurements. To the best of our knowledge, these are the first laboratory-based measurements of aqueous phase oxidation in a dispersed, supercooled population of droplets. The measurements are therefore important in confirming that the extrapolation of currently accepted reaction rate constants to temperatures below 0 °C is correct.

Published
2016

6. Aqueous phase oxidation of sulphur dioxide by ozone in cloud droplets

Author

Hoyle, CR, Fuchs, C, Järvinen, E, Saathoff, H, Dias, A, El Haddad, I, Gysel, M, Coburn, SC, Tröstl, J, Bernhammer, A-K, Bianchi, F, Breitenlechner, M, Corbin, JC, Craven, J, Donahue, NM, Duplissy, J, Ehrhart, S, Frege, C, Gordon, H, Höppel, N, Heinritzi, M, Kristensen, TB, Molteni, U, Nichman, L, Pinterich, T, Prévôt, ASH, Simon, M, Slowik, JG, Steiner, G, Tomé, A, Vogel, AL, Volkamer, R, Wagner, AC, Wagner, R, Wexler, AS, Williamson, C, Winkler, PM, Yan, C, Amorim, A, Dommen, J, Curtius, J, Gallagher, MW, Flagan, RC, Hansel, A, Kirkby, J, Kulmala, M, Möhler, O, Stratmann, F, Worsnop, D, and Baltensperger, U

Subjects
Meteorology & Atmospheric Sciences
Abstract

Abstract. The growth of aerosol due to the aqueous phase oxidation of SO2 by O3 was measured in laboratory generated clouds created in the CLOUD chamber at CERN. Experiments were performed at 10 and −10 °C, on acidic (sulphuric acid) and on partially to fully neutralised (ammonium sulphate) seed aerosol. Clouds were generated by performing an adiabatic expansion – pressurising the chamber to 220 hPa above atmospheric pressure, and then rapidly releasing the excess pressure, resulting in a cooling, condensation of water on the aerosol and a cloud lifetime of approximately 6 min. A model was developed to compare the observed aerosol growth with that predicted by oxidation rates previously measured in bulk solutions. The model captured the measured aerosol growth very well for experiments performed at 10 and −10 °C, indicating that, in contrast to some previous studies, the oxidation rates of SO2 in a dispersed aqueous system are well represented by accepted rates, based on bulk measurements. To the best of our knowledge, these are the first laboratory based measurements of aqueous phase oxidation in a dispersed, super-cooled population of droplets. The measurements are therefore important in confirming that the extrapolation of currently accepted reaction rates to temperatures below 0 °C is correct.

Published
2015

11. Contribution of methane to aerosol carbon mass

Author

Bianchi, F., Barmet, P., Stirnweis, L., El Haddad, I., Platt, S.M., Saurer, M., Lötscher, C., Siegwolf, R., Bigi, A., Hoyle, C.R., DeCarlo, P.F., Slowik, J.G., Prévôt, A.S.H., Baltensperger, U., and Dommen, J.

Published
2016
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13. A new methodology to assess the performance and uncertainty of source apportionment models II: The results of two European intercomparison exercises

Author

Belis, C.A., Karagulian, F., Amato, F., Almeida, M., Artaxo, P., Beddows, D.C.S., Bernardoni, V., Bove, M.C., Carbone, S., Cesari, D., Contini, D., Cuccia, E., Diapouli, E., Eleftheriadis, K., Favez, O., El Haddad, I., Harrison, R.M., Hellebust, S., Hovorka, J., Jang, E., Jorquera, H., Kammermeier, T., Karl, M., Lucarelli, F., Mooibroek, D., Nava, S., Nøjgaard, J.K., Paatero, P., Pandolfi, M., Perrone, M.G., Petit, J.E., Pietrodangelo, A., Pokorná, P., Prati, P., Prevot, A.S.H., Quass, U., Querol, X., Saraga, D., Sciare, J., Sfetsos, A., Valli, G., Vecchi, R., Vestenius, M., Yubero, E., and Hopke, P.K.

Published
2015
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20. Role of iodine oxoacids in atmospheric aerosol nucleation

Author

European Organization for Nuclear Research, Academy of Finland, European Commission, Consejo Superior de Investigaciones Científicas (España), Austrian Science Fund, Swiss National Science Foundation, National Science Foundation (US), Federal Ministry of Education and Research (Germany), Fundação para a Ciência e a Tecnologia (Portugal), Jiangsu Collaborative Innovation Center of Climate Change, Estonian Research Council, National Research, Development and Innovation Office (Hungary), National Aeronautics and Space Administration (US), He, Xu-Cheng, Tham, Yee Jun, Dada, Lubna, Wang, Mingyi, Finkenzeller, Henning, Stolzenburg, D., Iyer, S., Simon, Mario, Kürten, A., Shen, Jiali, Rörup, Birte, Volkamer, Rainer, Kirkby, Jasper, Worsnop, Douglas R., Sipilä, Mikko, Rissanen, Matti, Schobesberger, Siegfried, Baalbaki, Rima, Wang, Dongyo S., Koenig, T.K., Jokinen, Tuija, Sarnela, Nina, Beck, Lisa J., Almeida, João, Amanatidis, Stavros, Amorim, António, Ataei, F., Baccarini, Andrea, Bertozzi, Barbara, Bianchi, Federico, Brilke, Sophia, Caudillo, Lucía, Chen, Dexian, Chiu, Randall, Chu, Biwu, Dias, A., Ding, Aijun, Dommen, J., Duplissy, Jonathan, El Haddad, I., González Carracedo, Loïc, Granzin, Manuel, Hansel, A., Heinritzi, Martin, Hofbauer, Victoria, Junninen, Heikki, Kangasluoma, Juha, Kemppainen, Deniz, Kim, Changyuk, Kong, Weimeng, Krechmer, Jordan E., Kvashin, Aleksander, Laitinen, Totti, Lamkaddam, Houssni, Lee, Chuan Ping, Lehtipalo, Katrianne, Leiminger, Markus, Li, Zijun, Makhmutov, Vladimir, Manninen, Hanna E., Marie, Guillaume, Marten, Ruby, Mathot, Serge, Mauldin, Roy L., Mentler, Bernhard, Möhler, Ottmar, Müller, Tatjana, Nie, Wei, Onnela, Antti, Petäjä, Tuukka, Pfeifer, Joschka, Philippov, Maxim, Ranjithkumar, Ananth, Saiz-Lopez, A., Salma, Imre, Scholz, Wiebke, Schuchmann, S., Schulze, Benjamin, Steiner, Gerhard, Stozhkov, Yuri, Tauber, Christian, Tomé, António, Thakur, Roseline C., Väisänen, Olli, Vazquez-Pufleau, Miguel, Wagner, Andrea C., Wang, Yonghong, Weber, Stefan K., Winkler, Paul M., Wu, Yusheng, Xiao, Mao, Yan, Chao, Ye, Qing, Ylisirniö, Arttu, Zauner-Wieczorek, Marcel, Zha, Qiaozhi, Zhou, Putian, Flagan, Richard C., Curtius, Joachim, Baltensperger, Urs, Kulmala, Markku, Kerminen, Veli Matti, Kurtén, Theo, Donahue, Neil M., European Organization for Nuclear Research, Academy of Finland, European Commission, Consejo Superior de Investigaciones Científicas (España), Austrian Science Fund, Swiss National Science Foundation, National Science Foundation (US), Federal Ministry of Education and Research (Germany), Fundação para a Ciência e a Tecnologia (Portugal), Jiangsu Collaborative Innovation Center of Climate Change, Estonian Research Council, National Research, Development and Innovation Office (Hungary), National Aeronautics and Space Administration (US), He, Xu-Cheng, Tham, Yee Jun, Dada, Lubna, Wang, Mingyi, Finkenzeller, Henning, Stolzenburg, D., Iyer, S., Simon, Mario, Kürten, A., Shen, Jiali, Rörup, Birte, Volkamer, Rainer, Kirkby, Jasper, Worsnop, Douglas R., Sipilä, Mikko, Rissanen, Matti, Schobesberger, Siegfried, Baalbaki, Rima, Wang, Dongyo S., Koenig, T.K., Jokinen, Tuija, Sarnela, Nina, Beck, Lisa J., Almeida, João, Amanatidis, Stavros, Amorim, António, Ataei, F., Baccarini, Andrea, Bertozzi, Barbara, Bianchi, Federico, Brilke, Sophia, Caudillo, Lucía, Chen, Dexian, Chiu, Randall, Chu, Biwu, Dias, A., Ding, Aijun, Dommen, J., Duplissy, Jonathan, El Haddad, I., González Carracedo, Loïc, Granzin, Manuel, Hansel, A., Heinritzi, Martin, Hofbauer, Victoria, Junninen, Heikki, Kangasluoma, Juha, Kemppainen, Deniz, Kim, Changyuk, Kong, Weimeng, Krechmer, Jordan E., Kvashin, Aleksander, Laitinen, Totti, Lamkaddam, Houssni, Lee, Chuan Ping, Lehtipalo, Katrianne, Leiminger, Markus, Li, Zijun, Makhmutov, Vladimir, Manninen, Hanna E., Marie, Guillaume, Marten, Ruby, Mathot, Serge, Mauldin, Roy L., Mentler, Bernhard, Möhler, Ottmar, Müller, Tatjana, Nie, Wei, Onnela, Antti, Petäjä, Tuukka, Pfeifer, Joschka, Philippov, Maxim, Ranjithkumar, Ananth, Saiz-Lopez, A., Salma, Imre, Scholz, Wiebke, Schuchmann, S., Schulze, Benjamin, Steiner, Gerhard, Stozhkov, Yuri, Tauber, Christian, Tomé, António, Thakur, Roseline C., Väisänen, Olli, Vazquez-Pufleau, Miguel, Wagner, Andrea C., Wang, Yonghong, Weber, Stefan K., Winkler, Paul M., Wu, Yusheng, Xiao, Mao, Yan, Chao, Ye, Qing, Ylisirniö, Arttu, Zauner-Wieczorek, Marcel, Zha, Qiaozhi, Zhou, Putian, Flagan, Richard C., Curtius, Joachim, Baltensperger, Urs, Kulmala, Markku, Kerminen, Veli Matti, Kurtén, Theo, and Donahue, Neil M.

Abstract

Iodic acid (HIO) is known to form aerosol particles in coastal marine regions, but predicted nucleation and growth rates are lacking. Using the CERN CLOUD (Cosmics Leaving Outdoor Droplets) chamber, we find that the nucleation rates of HIOparticles are rapid, even exceeding sulfuric acid-ammonia rates under similar conditions. We also find that ion-induced nucleation involves IOand the sequential addition of HIOand that it proceeds at the kinetic limit below +10°C. In contrast, neutral nucleation involves the repeated sequential addition of iodous acid (HIO) followed by HIO, showing that HIOplays a key stabilizing role. Freshly formed particles are composed almost entirely of HIO, which drives rapid particle growth at the kinetic limit. Our measurements indicate that iodine oxoacid particle formation can compete with sulfuric acid in pristine regions of the atmosphere.

Published
2021

21. On the fate of oxygenated organic molecules in atmospheric aerosol particles

Author

Pospisilova, V., Lopez-Hilfiker, F. D., Bell, D. M., El Haddad, I, Mohr, Claudia, Huang, W., Heikkinen, L., Xiao, M., Dommen, J., Prevot, A. S. H., Baltensperger, U., Slowik, J. G., Pospisilova, V., Lopez-Hilfiker, F. D., Bell, D. M., El Haddad, I, Mohr, Claudia, Huang, W., Heikkinen, L., Xiao, M., Dommen, J., Prevot, A. S. H., Baltensperger, U., and Slowik, J. G.

Abstract

Highly oxygenated organic molecules (HOMs) are formed from the oxidation of biogenic and anthropogenic gases and affect Earth's climate and air quality by their key role in particle formation and growth. While the formation of these molecules in the gas phase has been extensively studied, the complexity of organic aerosol (OA) and lack of suitable measurement techniques have hindered the investigation of their fate post-condensation, although further reactions have been proposed. We report here novel real-time measurements of these species in the particle phase, achieved using our recently developed extractive electrospray ionization time-of-flight mass spectrometer (EESI-TOF). Our results reveal that condensed-phase reactions rapidly alter OA composition and the contribution of HOMs to the particle mass. In consequence, the atmospheric fate of HOMs cannot be described solely in terms of volatility, but particle-phase reactions must be considered to describe HOM effects on the overall particle life cycle and global carbon budget.

Published
2020
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22. Evaluation of receptor and chemical transport models for PM10 source apportionment

Author

Belis, C. A., Pernigotti, D., Pirovano, G., Favez, O., Jaffrezo, J. L., Kuenen, J., van Der Gon, H. Denier, Reizer, M., Riffault, V, Alleman, L. Y., Almeida, M., Amato, F., Angyal, A., Argyropoulos, G., Bande, S., Beslic, I, Besombes, J-L, Bove, M. C., Brotto, P., Calori, G., Cesari, D., Colombi, C., Contini, D., De Gennaro, G., Di Gilio, A., Diapouli, E., El Haddad, I, Elbern, H., Eleftheriadis, K., Ferreira, J., Vivanco, M. Garcia, Gilardoni, S., Golly, B., Hellebust, S., Hopke, P. K., Izadmanesh, Y., Jorquera, H., Krajsek, K., Kranenburg, R., Lazzeri, P., Lenartz, F., Lucarelli, F., Maciejewska, K., Manders, A., Manousakas, M., Masiol, M., Mircea, M., Mooibroek, D., Nava, S., Oliveira, D., Paglione, M., Pandolfi, M., Perrone, M., Petralia, E., Pietrodangelo, A., Pillon, S., Pokorna, P., Prati, P., Salameh, D., Samara, C., Samek, L., Saraga, D., Sauvage, S., Schaap, M., Scotto, F., Sega, K., Siour, G., Tauler, R., Valli, G., Vecchi, R., Venturini, E., Vestenius, M., Waked, A., Yubero, E., Belis, C. A., Pernigotti, D., Pirovano, G., Favez, O., Jaffrezo, J. L., Kuenen, J., van Der Gon, H. Denier, Reizer, M., Riffault, V, Alleman, L. Y., Almeida, M., Amato, F., Angyal, A., Argyropoulos, G., Bande, S., Beslic, I, Besombes, J-L, Bove, M. C., Brotto, P., Calori, G., Cesari, D., Colombi, C., Contini, D., De Gennaro, G., Di Gilio, A., Diapouli, E., El Haddad, I, Elbern, H., Eleftheriadis, K., Ferreira, J., Vivanco, M. Garcia, Gilardoni, S., Golly, B., Hellebust, S., Hopke, P. K., Izadmanesh, Y., Jorquera, H., Krajsek, K., Kranenburg, R., Lazzeri, P., Lenartz, F., Lucarelli, F., Maciejewska, K., Manders, A., Manousakas, M., Masiol, M., Mircea, M., Mooibroek, D., Nava, S., Oliveira, D., Paglione, M., Pandolfi, M., Perrone, M., Petralia, E., Pietrodangelo, A., Pillon, S., Pokorna, P., Prati, P., Salameh, D., Samara, C., Samek, L., Saraga, D., Sauvage, S., Schaap, M., Scotto, F., Sega, K., Siour, G., Tauler, R., Valli, G., Vecchi, R., Venturini, E., Vestenius, M., Waked, A., and Yubero, E.

Abstract

In this study, the performance of two types of source apportionment models was evaluated by assessing the results provided by 40 different groups in the framework of an intercomparison organised by FAIRMODE WG3 (Forum for air quality modelling in Europe, Working Group 3). The evaluation was based on two performance indicators: z-scores and the root mean square error weighted by the reference uncertainty (RMSEu), with pre-established acceptability criteria. By involving models based on completely different and independent input data, such as receptor models (RMs) and chemical transport models (CTMs), the intercomparison provided a unique opportunity for their cross-validation. In addition, comparing the CTM chemical profiles with those measured directly at the source contributed to corroborate the consistency of the tested model results. The most commonly used RM was the US EPA- PMF version 5. RMs showed very good performance for the overall dataset (91% of z-scores accepted) while more difficulties were observed with the source contribution time series (72% of RMSEu accepted). Industrial activities proved to be the most difficult sources to be quantified by RMs, with high variability in the estimated contributions. In the CTMs, the sum of computed source contributions was lower than the measured gravimetric PM10 mass concentrations. The performance tests pointed out the differences between the two CTM approaches used for source apportionment in this study: brute force (or emission reduction impact) and tagged species methods. The sources meeting the z-score and RMSEu acceptability criteria tests were 50% and 86%, respectively. The CTM source contributions to PM10 were in the majority of cases lower than the RM averages for the corresponding source. The CTMs and RMs source contributions for the overall dataset were more comparable (83% of the z-scores accepted) than their time series (successful RMSEu in the range 25% - 34%). The comparability between CTMs and RMs va

Published
2020

23. Overview: Integrative and Comprehensive Understanding on Polar Environments (iCUPE) — concept and initial results

Author

Petäjä, T., Duplissy, E.-M., Tabakova, K., Schmale, J., Altstädter, B., Ancellet, G., Arshinov, M., Balin, Y., Baltensperger, U., Bange, J., Beamish, A., Belan, B., Berchet, A., Bossi, R., Cairns, W. R. L., Ebinghaus, R., El Haddad, I., Ferreira-Araujo, B., Franck, A., Huang, L., Hyvärinen, A., Humbert, A., Kalogridis, A.-C., Konstantinov, P., Lampert, A., MacLeod, M., Magand, O., Mahura, A., Marelle, L., Masloboev, V., Moisseev, D., Moschos, V., Neckel, N., Onishi, T., Osterwalder, S., Ovaska, A., Paasonen, P., Panchenko, M., Pankratov, F., Pernov, J. B., Platis, A., Popovicheva, O., Raut, J.-C., Riandet, A., Sachs, T., Salvatori, R., Salzano, R., Schröder, L., Schön, M., Shevchenko, V., Skov, H., Sonke, J. E., Spolaor, A., Stathopoulos, V. K., Strahlendorff, M., Thomas, J. L., Vitale, V., Vratolis, S., Barbante, C., Chabrillat, S., Dommergue, A., Eleftheriadis, K., Heilimo, J., Law, K. S., Massling, A., Noe, S. M., Paris, J.-D., Prévôt, A. S. H., Riipinen, I., Wehner, B., Xie, Z., Lappalainen, H. K., Petäjä, T., Duplissy, E.-M., Tabakova, K., Schmale, J., Altstädter, B., Ancellet, G., Arshinov, M., Balin, Y., Baltensperger, U., Bange, J., Beamish, A., Belan, B., Berchet, A., Bossi, R., Cairns, W. R. L., Ebinghaus, R., El Haddad, I., Ferreira-Araujo, B., Franck, A., Huang, L., Hyvärinen, A., Humbert, A., Kalogridis, A.-C., Konstantinov, P., Lampert, A., MacLeod, M., Magand, O., Mahura, A., Marelle, L., Masloboev, V., Moisseev, D., Moschos, V., Neckel, N., Onishi, T., Osterwalder, S., Ovaska, A., Paasonen, P., Panchenko, M., Pankratov, F., Pernov, J. B., Platis, A., Popovicheva, O., Raut, J.-C., Riandet, A., Sachs, T., Salvatori, R., Salzano, R., Schröder, L., Schön, M., Shevchenko, V., Skov, H., Sonke, J. E., Spolaor, A., Stathopoulos, V. K., Strahlendorff, M., Thomas, J. L., Vitale, V., Vratolis, S., Barbante, C., Chabrillat, S., Dommergue, A., Eleftheriadis, K., Heilimo, J., Law, K. S., Massling, A., Noe, S. M., Paris, J.-D., Prévôt, A. S. H., Riipinen, I., Wehner, B., Xie, Z., and Lappalainen, H. K.

Abstract

The role of polar regions is increasing in terms of megatrends such as globalization, new transport routes, demography, and the use of natural resources with consequent effects on regional and transported pollutant concentrations. We set up the ERA-PLANET Strand 4 project “iCUPE – integrative and Comprehensive Understanding on Polar Environments” to provide novel insights and observational data on global grand challenges with an Arctic focus. We utilize an integrated approach combining in situ observations, satellite remote sensing Earth observations (EOs), and multi-scale modeling to synthesize data from comprehensive long-term measurements, intensive campaigns, and satellites to deliver data products, metrics, and indicators to stakeholders concerning the environmental status, availability, and extraction of natural resources in the polar areas. The iCUPE work consists of thematic state-of-the-art research and the provision of novel data in atmospheric pollution, local sources and transboundary transport, the characterization of arctic surfaces and their changes, an assessment of the concentrations and impacts of heavy metals and persistent organic pollutants and their cycling, the quantification of emissions from natural resource extraction, and the validation and optimization of satellite Earth observation (EO) data streams. In this paper we introduce the iCUPE project and summarize initial results arising out of the integration of comprehensive in situ observations, satellite remote sensing, and multi-scale modeling in the Arctic context.

Published
2020

26. Observation of viscosity transition in a-pinene secondary organic aerosol

Author

Järvinen E., Ignatius K., Nichman L., Kristensen T. B., Fuchs C., Hoyle C. R., Höppel N., Corbin J. C., Craven J., Duplissy J., Ehrhart S., El Haddad I., Frege C., Gordon H., Jokinen T., Kallinger P., Kirkby J., Kiselev A., Naumann K. H., Petäjä T., Pinterich T., Prevot A. S. H., Saathoff H., Schiebel T., and Sengupta K.

Published
2016

27. Insights into organic-aerosol sources via a novel laser-desorption/ionization mass spectrometry technique applied to one year of PM10 samples from nine sites in central Europe

Author

Daellenbach, K. R., El-Haddad, I., Karvonen, L., Vlachou, A., Corbin, J. C., Slowik, J. G., Heringa, M. F., Bruns, E. A., Luedin, S. M., Jaffrezo, J.-L., Szidat, S., Piazzalunga, A., Gonzalez, R., Fermo, P., Pflueger, V., Vogel, G., Baltensperger, U., and Prévôt, A. S. H.

Abstract

We assess the benefits of offline laser-desorption/ionization mass spectrometry (LDI-MS) in understanding ambient particulate matter (PM) sources. The technique was optimized for measuring PM collected on quartz-fiber filters using silver nitrate as an internal standard for m/z calibration. This is the first application of this technique to samples collected at nine sites in central Europe throughout the entire year 2013 (819 samples). Different PM sources were identified by positive matrix factorization (PMF) including also concomitant measurements (such as NOx, levoglucosan, and temperature). By comparison to reference mass spectral signatures from laboratory wood burning experiments as well as samples from a traffic tunnel, three biomass-burning factors and two traffic factors were identified. The wood-burning factors could be linked to the burning conditions; the factors related to inefficient burns had a larger impact on air quality in southern Alpine valleys than in northern Switzerland. The traffic factors were identified as primary tailpipe exhaust and most possibly aged/secondary traffic emissions, respectively. The latter attribution was supported by radiocarbon analyses of both the organic and elemental carbon. Besides these sources, also factors related to secondary organic aerosol were separated. The contribution of the wood burning emissions based on LDI-PMF correlates well with that based on AMS-PMF analyses, while the comparison between the two techniques for other components is more complex.

Published
2017
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28. Assessing the influence of NOx concentrations and relative humidity on secondary organic aerosol yields from α-pinene photo-oxidation through smog chamber experiments and modelling calculations

Author

Stirnweis, L., Marcolli, C., Dommen, J., Barmet, P., Frege, C., Platt, S. M., Bruns, E. A., Krapf, M., Slowik, J. G., Wolf, R., Prévôt, A. S. H., Baltensperger, U., and El-Haddad, I.

Abstract

Secondary organic aerosol (SOA) yields from the photo-oxidation of α-pinene were investigated in smog chamber (SC) experiments at low (23–29 %) and high (60–69 %) relative humidity (RH), various NOx ∕ VOC ratios (0.04–3.8) and with different aerosol seed chemical compositions (acidic to neutralized sulfate-containing or hydrophobic organic). A combination of a scanning mobility particle sizer and an Aerodyne high-resolution time-of-flight aerosol mass spectrometer was used to determine SOA mass concentration and chemical composition. We used a Monte Carlo approach to parameterize smog chamber SOA yields as a function of the condensed phase absorptive mass, which includes the sum of OA and the corresponding bound liquid water content. High RH increased SOA yields by up to 6 times (1.5–6.4) compared to low RH. The yields at low NOx ∕ VOC ratios were in general higher compared to yields at high NOx ∕ VOC ratios. This NOx dependence follows the same trend as seen in previous studies for α-pinene SOA. A novel approach of data evaluation using volatility distributions derived from experimental data served as the basis for thermodynamic phase partitioning calculations of model mixtures in this study. These calculations predict liquid–liquid phase separation into organic-rich and electrolyte phases. At low NOx conditions, equilibrium partitioning between the gas and liquid phases can explain most of the increase in SOA yields observed at high RH, when in addition to the α-pinene photo-oxidation products described in the literature, fragmentation products are added to the model mixtures. This increase is driven by both the increase in the absorptive mass and the solution non-ideality described by the compounds' activity coefficients. In contrast, at high NOx, equilibrium partitioning alone could not explain the strong increase in the yields with RH. This suggests that other processes, e.g. reactive uptake of semi-volatile species into the liquid phase, may occur and be enhanced at higher RH, especially for compounds formed under high NOx conditions, e.g. carbonyls.

Published
2017

30. Brown and Black Carbon Emitted by a Marine Engine Operated on Heavy Fuel Oil and Distillate Fuels: Optical Properties, Size Distributions, and Emission Factors

Author

Corbin, J. C., primary, Pieber, S. M., additional, Czech, H., additional, Zanatta, M., additional, Jakobi, G., additional, Massabò, D., additional, Orasche, J., additional, El Haddad, I., additional, Mensah, A. A., additional, Stengel, B., additional, Drinovec, L., additional, Mocnik, G., additional, Zimmermann, R., additional, Prévôt, A. S. H., additional, and Gysel, M., additional

Published
2018
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31. Trace Metals in Soot and PM2.5 from Heavy-Fuel-Oil Combustion in a Marine Engine

Author

Corbin, J. C., primary, Mensah, A. A., additional, Pieber, S. M., additional, Orasche, J., additional, Michalke, B., additional, Zanatta, M., additional, Czech, H., additional, Massabò, D., additional, Buatier de Mongeot, F., additional, Mennucci, C., additional, El Haddad, I., additional, Kumar, N. K., additional, Stengel, B., additional, Huang, Y., additional, Zimmermann, R., additional, Prévôt, A. S. H., additional, and Gysel, M., additional

Published
2018
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32. Gasoline cars produce more carbonaceous particulate matter than modern filter-equipped diesel cars

Author

Platt, S. M., primary, El Haddad, I., additional, Pieber, S. M., additional, Zardini, A. A., additional, Suarez-Bertoa, R., additional, Clairotte, M., additional, Daellenbach, K. R., additional, Huang, R.-J., additional, Slowik, J. G., additional, Hellebust, S., additional, Temime-Roussel, B., additional, Marchand, N., additional, de Gouw, J., additional, Jimenez, J. L., additional, Hayes, P. L., additional, Robinson, A. L., additional, Baltensperger, U., additional, Astorga, C., additional, and Prévôt, A. S. H., additional

Published
2017
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35. European intercomparison for Receptor Models Using a Synthetic Database

Author

Belis, CA, Karagulian, F, Amato, F, Almeida, M, Argyropoulos, G, Artaxo, P, Bove, MC, Cesari, D, Contini, D, Diapouli, E, Eleftheriadis, K, El Haddad, I, Harrison, RM, Hellebust, S, Jang, E, Jorquera, H, Mooibroek, D, Nava, S, Nøjgaard, JK, Pandolfi, M, Pietrodangelo, A, Pirovano, G, Pokorná, P, Prati, P, Samara, S, Saraga, D, Sfetsos, A, Valli, G, Vecchi, R, Vestenius, M, Yubero, E, Hopke, PK, PERRONE, MARIA GRAZIA, Belis, C, Karagulian, F, Amato, F, Almeida, M, Argyropoulos, G, Artaxo, P, Bove, M, Cesari, D, Contini, D, Diapouli, E, Eleftheriadis, K, El Haddad, I, Harrison, R, Hellebust, S, Jang, E, Jorquera, H, Mooibroek, D, Nava, S, Nøjgaard, J, Pandolfi, M, Perrone, M, Pietrodangelo, A, Pirovano, G, Pokorná, P, Prati, P, Samara, S, Saraga, D, Sfetsos, A, Valli, G, Vecchi, R, Vestenius, M, Yubero, E, and Hopke, P

Subjects
intercomparison, source apportionment, receptor models, PM, CHIM/12 - CHIMICA DELL'AMBIENTE E DEI BENI CULTURALI
Published
2013

36. Aqueous phase oxidation of sulphur dioxide by ozone in cloud droplets

Author

University of Helsinki, Helsinki Institute of Physics, University of Helsinki, Department of Physics, Hoyle, C. R., Fuchs, C., Jaervinen, E., Saathoff, H., Dias, A., El Haddad, I., Gysel, M., Coburn, S. C., Troestl, J., Bernhammer, A. -K., Bianchi, F., Breitenlechner, M., Corbin, J. C., Craven, J., Donahue, N. M., Duplissy, J., Ehrhart, S., Frege, C., Gordon, H., Hoeppel, N., Heinritzi, M., Kristensen, T. B., Molteni, U., Nichman, L., Pinterich, T., Prevot, A. S. H., Simon, M., Slowik, J. G., Steiner, G., Tome, A., Vogel, A. L., Volkamer, R., Wagner, A. C., Wagner, R., Wexler, A. S., Williamson, C., Winkler, P. M., Yan, C., Amorim, A., Dommen, J., Curtius, J., Gallagher, M. W., Flagan, R. C., Hansel, A., Kirkby, J., Kulmala, M., Moehler, O., Stratmann, F., Worsnop, D. R., Baltensperger, U., University of Helsinki, Helsinki Institute of Physics, University of Helsinki, Department of Physics, Hoyle, C. R., Fuchs, C., Jaervinen, E., Saathoff, H., Dias, A., El Haddad, I., Gysel, M., Coburn, S. C., Troestl, J., Bernhammer, A. -K., Bianchi, F., Breitenlechner, M., Corbin, J. C., Craven, J., Donahue, N. M., Duplissy, J., Ehrhart, S., Frege, C., Gordon, H., Hoeppel, N., Heinritzi, M., Kristensen, T. B., Molteni, U., Nichman, L., Pinterich, T., Prevot, A. S. H., Simon, M., Slowik, J. G., Steiner, G., Tome, A., Vogel, A. L., Volkamer, R., Wagner, A. C., Wagner, R., Wexler, A. S., Williamson, C., Winkler, P. M., Yan, C., Amorim, A., Dommen, J., Curtius, J., Gallagher, M. W., Flagan, R. C., Hansel, A., Kirkby, J., Kulmala, M., Moehler, O., Stratmann, F., Worsnop, D. R., and Baltensperger, U.

Abstract

The growth of aerosol due to the aqueous phase oxidation of sulfur dioxide by ozone was measured in laboratory-generated clouds created in the Cosmics Leaving OUtdoor Droplets (CLOUD) chamber at the European Organization for Nuclear Research (CERN). Experiments were performed at 10 and -10 degrees C, on acidic (sulfuric acid) and on partially to fully neutralised (ammonium sulfate) seed aerosol. Clouds were generated by performing an adiabatic expansion-pressurising the chamber to 220 hPa above atmospheric pressure, and then rapidly releasing the excess pressure, resulting in a cooling, condensation of water on the aerosol and a cloud lifetime of approximately 6 min. A model was developed to compare the observed aerosol growth with that predicted using oxidation rate constants previously measured in bulk solutions. The model captured the measured aerosol growth very well for experiments performed at 10 and -10 degrees C, indicating that, in contrast to some previous studies, the oxidation rates of SO2 in a dispersed aqueous system can be well represented by using accepted rate constants, based on bulk measurements. To the best of our knowledge, these are the first laboratory-based measurements of aqueous phase oxidation in a dispersed, supercooled population of droplets. The measurements are therefore important in confirming that the extrapolation of currently accepted reaction rate constants to temperatures below 0 degrees C is correct.

Published
2016

37. Radiocarbon Analysis of Elemental and Organic Carbon in Switzerland during Winter-Smog Episodes from 2008 to 2012 – Part I: Source Apportionment and Spatial Variability

Author

Prévôt, A. S. H., Baltensperger, U., Fermo, P., Piazzalunga, A., Hueglin, C., Schwikowski, Margit, El-Haddad, I., Zhang, Yanlin, Wacker, L., Macchia, M., Salazar Quintero, Gary Abdiel, Huang, R.-J., Zotter, P., Szidat, Sönke, Ciobanu, V. G., and Daellenbach, K. R.

Subjects
550 Earth sciences & geology, 540 Chemistry, 570 Life sciences, biology
Abstract

While several studies have investigated winter-time air pollution with a wide range of concentration levels, hardly any results are available for longer time periods covering several winter-smog episodes at various locations; e.g., often only a few weeks from a single winter are investigated. Here, we present source apportionment results of winter-smog episodes from 16 air pollution monitoring stations across Switzerland from five consecutive winters. Radiocarbon (14C) analyses of the elemental (EC) and organic (OC) carbon fractions, as well as levoglucosan, major water-soluble ionic species and gas-phase pollutant measurements were used to characterize the different sources of PM10. The most important contributions to PM10 during winter-smog episodes in Switzerland were on average the secondary inorganic constituents (sum of nitrate, sulfate and ammonium = 41 ± 15%) followed by organic matter (OM) (34 ± 13%) and EC (5 ± 2%). The non-fossil fractions of OC (fNF,OC) ranged on average from 69 to 85 and 80 to 95% for stations north and south of the Alps, respectively, showing that traffic contributes on average only up to ~ 30% to OC. The non-fossil fraction of EC (fNF,EC), entirely attributable to primary wood burning, was on average 42 ± 13 and 49 ± 15% for north and south of the Alps, respectively. While a high correlation was observed between fossil EC and nitrogen oxides, both primarily emitted by traffic, these species did not significantly correlate with fossil OC (OCF), which seems to suggest that a considerable amount of OCF is secondary, from fossil precursors. Elevated fNF,EC and fNF,OC values and the high correlation of the latter with other wood burning markers, including levoglucosan and water soluble potassium (K+) indicate that residential wood burning is the major source of carbonaceous aerosols during winter-smog episodes in Switzerland. The inspection of the non-fossil OC and EC levels and the relation with levoglucosan and water-soluble K+ shows different ratios for stations north and south of the Alps (most likely because of differences in burning technologies) for these two regions in Switzerland.

Published
2014
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38. Supplementary material to "Argon offline-AMS source apportionment of organic aerosol over yearly cycles for an urban, rural and marine site in Northern Europe"

Author

Bozzetti, C., primary, Sosedova, Y., additional, Xiao, M., additional, Daellenbach, K. R., additional, Ulevicius, V., additional, Dudoitis, V., additional, Mordas, G., additional, Byčenkienė, S., additional, Plauškaitė, K., additional, Vlachou, A., additional, Golly, B., additional, Chazeau, B., additional, Besombes, J.-L., additional, Baltensperger, U., additional, Jaffrezo, J.-L., additional, Slowik, J. G., additional, El Haddad, I., additional, and Prévôt, A. S. H., additional

Published
2016
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39. Argon offline-AMS source apportionment of organic aerosol over yearly cycles for an urban, rural and marine site in Northern Europe

Author

Bozzetti, C., primary, Sosedova, Y., additional, Xiao, M., additional, Daellenbach, K. R., additional, Ulevicius, V., additional, Dudoitis, V., additional, Mordas, G., additional, Byčenkienė, S., additional, Plauškaitė, K., additional, Vlachou, A., additional, Golly, B., additional, Chazeau, B., additional, Besombes, J.-L., additional, Baltensperger, U., additional, Jaffrezo, J.-L., additional, Slowik, J. G., additional, El Haddad, I., additional, and Prévôt, A. S. H., additional

Published
2016
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42. Characterization and source apportionment of organic aerosol using offline aerosol mass spectrometry

Author

Daellenbach, K. R., primary, Bozzetti, C., additional, Křepelová, A., additional, Canonaco, F., additional, Wolf, R., additional, Zotter, P., additional, Fermo, P., additional, Crippa, M., additional, Slowik, J. G., additional, Sosedova, Y., additional, Zhang, Y., additional, Huang, R.-J., additional, Poulain, L., additional, Szidat, S., additional, Baltensperger, U., additional, El Haddad, I., additional, and Prévôt, A. S. H., additional

Published
2016
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43. A new methodology to assess the performance and uncertainty of source apportionment models II: The results of two European intercomparison exercises

Author

Belis, C, Karagulian, F, Amato, F, Almeida, M, Artaxo, P, Beddows, D, Bernardoni, V, Bove, M, Carbone, S, Cesari, D, Contini, D, Cuccia, E, Diapouli, E, Eleftheriadis, K, Favez, O, El Haddad, I, Harrison, R, Hellebust, S, Hovorka, J, Jang, E, Jorquera, H, Kammermeier, T, Karl, M, Lucarelli, F, Mooibroek, D, Nava, S, Nøjgaard, J, Paatero, P, Pandolfi, M, Perrone, M, Petit, J, Pietrodangelo, A, Pokorná, P, Prati, P, Prevot, A, Quass, U, Querol, X, Saraga, D, Sciare, J, Sfetsos, A, Valli, G, Vecchi, R, Vestenius, M, Yubero, E, Hopke, P, Belis, CA, Beddows, D. C. S, Bove, MC, Harrison, RM, Nøjgaard, J. K, PERRONE, MARIA GRAZIA, Petit, JE, Prevot, ASH, Hopke, PK, Belis, C, Karagulian, F, Amato, F, Almeida, M, Artaxo, P, Beddows, D, Bernardoni, V, Bove, M, Carbone, S, Cesari, D, Contini, D, Cuccia, E, Diapouli, E, Eleftheriadis, K, Favez, O, El Haddad, I, Harrison, R, Hellebust, S, Hovorka, J, Jang, E, Jorquera, H, Kammermeier, T, Karl, M, Lucarelli, F, Mooibroek, D, Nava, S, Nøjgaard, J, Paatero, P, Pandolfi, M, Perrone, M, Petit, J, Pietrodangelo, A, Pokorná, P, Prati, P, Prevot, A, Quass, U, Querol, X, Saraga, D, Sciare, J, Sfetsos, A, Valli, G, Vecchi, R, Vestenius, M, Yubero, E, Hopke, P, Belis, CA, Beddows, D. C. S, Bove, MC, Harrison, RM, Nøjgaard, J. K, PERRONE, MARIA GRAZIA, Petit, JE, Prevot, ASH, and Hopke, PK

Abstract

The performance and the uncertainty of receptor models (RMs) were assessed in intercomparison exercises employing real-world and synthetic input datasets. To that end, the results obtained by different practitioners using ten different RMs were compared with a reference. In order to explain the differences in the performances and uncertainties of the different approaches, the apportioned mass, the number of sources, the chemical profiles, the contribution-to-species and the time trends of the sources were all evaluated using the methodology described in Belis et al. (2015). In this study, 87% of the 344 source contribution estimates (SCEs) reported by participants in 47 different source apportionment model results met the 50% standard uncertainty quality objective established for the performance test. In addition, 68% of the SCE uncertainties reported in the results were coherent with the analytical uncertainties in the input data. The most used models, EPA-PMF v.3, PMF2 and EPA-CMB 8.2, presented quite satisfactory performances in the estimation of SCEs while unconstrained models, that do not account for the uncertainty in the input data (e.g. APCS and FA-MLRA), showed below average performance. Sources with well-defined chemical profiles and seasonal time trends, that make appreciable contributions (>10%), were those better quantified by the models while those with contributions to the PM mass close to 1% represented a challenge. The results of the assessment indicate that RMs are capable of estimating the contribution of the major pollution source categories over a given time window with a level of accuracy that is in line with the needs of air quality management.

Published
2015

45. Input of stable isotope carbon measurements in the source apportionment of aerosols

Author

Piot, C., El Haddad, I., Besombes, Jean-Luc, Cozic, J., Marchand, N., Jaffrezo, J.-L., Laboratoire de Chimie Moléculaire et Environnement (LCME), Université Savoie Mont Blanc (USMB [Université de Savoie] [Université de Chambéry]), Laboratoire Chimie de l'environnement (LCE), Aix Marseille Université (AMU)-Institut de Chimie du CNRS (INC)-Centre National de la Recherche Scientifique (CNRS), Laboratoire de glaciologie et géophysique de l'environnement (LGGE), Centre National de la Recherche Scientifique (CNRS)-Institut national des sciences de l'Univers (INSU - CNRS)-Observatoire des Sciences de l'Univers de Grenoble (OSUG), Centre National de la Recherche Scientifique (CNRS)-Université Joseph Fourier - Grenoble 1 (UJF)-Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP )-Institut national de recherche en sciences et technologies pour l'environnement et l'agriculture (IRSTEA)-Institut national des sciences de l'Univers (INSU - CNRS)-Université Savoie Mont Blanc (USMB [Université de Savoie] [Université de Chambéry])-Centre National de la Recherche Scientifique (CNRS)-Université Joseph Fourier - Grenoble 1 (UJF)-Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP )-Institut national de recherche en sciences et technologies pour l'environnement et l'agriculture (IRSTEA)-Université Savoie Mont Blanc (USMB [Université de Savoie] [Université de Chambéry]), Observatoire des Sciences de l'Univers de Grenoble (OSUG), Université Joseph Fourier - Grenoble 1 (UJF)-Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP )-Institut national des sciences de l'Univers (INSU - CNRS)-Institut national de recherche en sciences et technologies pour l'environnement et l'agriculture (IRSTEA)-Université Savoie Mont Blanc (USMB [Université de Savoie] [Université de Chambéry])-Centre National de la Recherche Scientifique (CNRS)-Université Joseph Fourier - Grenoble 1 (UJF)-Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP )-Institut national des sciences de l'Univers (INSU - CNRS)-Institut national de recherche en sciences et technologies pour l'environnement et l'agriculture (IRSTEA)-Université Savoie Mont Blanc (USMB [Université de Savoie] [Université de Chambéry])-Centre National de la Recherche Scientifique (CNRS)-Centre National de la Recherche Scientifique (CNRS), Université Savoie Mont Blanc (USMB [Université de Savoie] [Université de Chambéry])-Université Grenoble Alpes (UGA), Aix Marseille Université (AMU)-Centre National de la Recherche Scientifique (CNRS), and Université Savoie Mont Blanc (USMB [Université de Savoie] [Université de Chambéry])-Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP)-Institut national de recherche en sciences et technologies pour l'environnement et l'agriculture (IRSTEA)-Université Joseph Fourier - Grenoble 1 (UJF)-Institut national des sciences de l'Univers (INSU - CNRS)-Centre National de la Recherche Scientifique (CNRS)-Université Grenoble Alpes (UGA)-Université Savoie Mont Blanc (USMB [Université de Savoie] [Université de Chambéry])-Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP)-Institut national de recherche en sciences et technologies pour l'environnement et l'agriculture (IRSTEA)-Université Joseph Fourier - Grenoble 1 (UJF)-Institut national des sciences de l'Univers (INSU - CNRS)-Centre National de la Recherche Scientifique (CNRS)-Université Grenoble Alpes (UGA)-Centre National de la Recherche Scientifique (CNRS)

Subjects
[SDE]Environmental Sciences, [CHIM]Chemical Sciences, ComputingMilieux_MISCELLANEOUS
Abstract

International audience

Published
2012

46. Organic aerosols source apportionment: CMB methodology developed by three French groups

Author

Piot, C., L Jaffrezo, J., Jean-Luc Besombes, Cozic, J., Nicolas Marchand, El Haddad, I., Laboratoire de Chimie Moléculaire et Environnement (LCME), Université Savoie Mont Blanc (USMB [Université de Savoie] [Université de Chambéry])-Université Grenoble Alpes (UGA), Laboratoire de glaciologie et géophysique de l'environnement (LGGE), Observatoire des Sciences de l'Univers de Grenoble (OSUG), Université Savoie Mont Blanc (USMB [Université de Savoie] [Université de Chambéry])-Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP)-Institut national de recherche en sciences et technologies pour l'environnement et l'agriculture (IRSTEA)-Université Joseph Fourier - Grenoble 1 (UJF)-Institut national des sciences de l'Univers (INSU - CNRS)-Centre National de la Recherche Scientifique (CNRS)-Université Grenoble Alpes (UGA)-Université Savoie Mont Blanc (USMB [Université de Savoie] [Université de Chambéry])-Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP)-Institut national de recherche en sciences et technologies pour l'environnement et l'agriculture (IRSTEA)-Université Joseph Fourier - Grenoble 1 (UJF)-Institut national des sciences de l'Univers (INSU - CNRS)-Centre National de la Recherche Scientifique (CNRS)-Université Grenoble Alpes (UGA)-Centre National de la Recherche Scientifique (CNRS), Oumedjbeur, Abdelkrim, Université Savoie Mont Blanc (USMB [Université de Savoie] [Université de Chambéry]), Centre National de la Recherche Scientifique (CNRS)-Institut national des sciences de l'Univers (INSU - CNRS)-Observatoire des Sciences de l'Univers de Grenoble (OSUG), and Université Joseph Fourier - Grenoble 1 (UJF)-Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP )-Institut national des sciences de l'Univers (INSU - CNRS)-Institut national de recherche en sciences et technologies pour l'environnement et l'agriculture (IRSTEA)-Université Savoie Mont Blanc (USMB [Université de Savoie] [Université de Chambéry])-Centre National de la Recherche Scientifique (CNRS)-Université Joseph Fourier - Grenoble 1 (UJF)-Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP )-Institut national de recherche en sciences et technologies pour l'environnement et l'agriculture (IRSTEA)-Université Savoie Mont Blanc (USMB [Université de Savoie] [Université de Chambéry])-Centre National de la Recherche Scientifique (CNRS)

Subjects
[SDE] Environmental Sciences, [CHIM] Chemical Sciences, [SDE]Environmental Sciences, [CHIM]Chemical Sciences, ComputingMilieux_MISCELLANEOUS
Abstract

International audience

Published
2012

47. Towards a European common protocol for receptor modelling

Author

Belis, C.A., Karagulian, F., Larsen, B.R., Amato, F., Favez, Olivier, El Haddad, I., Harrison, R.M., Prevot, A., Quass, U., Vecchi, R., Viana, M., Paatero, P., Hopke, P.K., Civs, Gestionnaire, JRC Institute for Environment and Sustainability (IES), European Commission - Joint Research Centre [Ispra] (JRC), Institute for Health and Consumer Protection, European Commission - Joint Research Centre, Institute of Environmental Assessment and Water Research (IDAEA), Consejo Superior de Investigaciones Científicas [Madrid] (CSIC), and Institut National de l'Environnement Industriel et des Risques (INERIS)

Subjects
[SDE] Environmental Sciences, RECEPTOR MODELS, SOURCES, [SDE]Environmental Sciences, POLLUTION ATMOSPHERIQUE, MODELES RECEPTEURS---SOURCE APPORTIONMENT, MODEL HARMONIZATION, GUIDELINES
Abstract

The identification of sources is one of the prerequisites for the implementation of the Air Quality Directive (AQD). It provides scientific support to the development and periodic revision of air quality plans and short term action plans and to the quantification of categories with special status like long range transport, natural sources and winter road salting and sanding. The suitability of receptor models (RM) for the apportionment of pollutant sources in the implementa-tion of the AQD is testified by the amount of published studies in 2005 and 2010 in correspondence with the entry into force of new provisions for PM10 and PM2,5, respectively. In recent years, Member States were requested to provide official estimations of source contribution to the Commission like the quantification of natural sources in 2006 and PM10 time extension reports in 2009 (Fragkou et al., 2011). These experiences have shown that al-though this kind of methodology is used by about 60 % of the European experts involved in source apportion-ment there is a considerable variability in the methodo-logical approaches and adopted tools. Furthermore, there are critical steps that require strict quality assurance standards and skilled practitioners (e.g. identification of the appropriate number of sources). In order to foster harmonization in this field, the JRC has promoted a number of interconnected initiatives linked to FAIRMODE. One of those was to set up a group of experts with skills in different areas to assess RM methodologies and propose common criteria and procedures for source apportionment studies. The infor-mation collected was summarized in a document which is intended to serve as a basis for a common Receptor Model Technical Protocol (RMTP). The RMTP is addressed to different kinds of us-ers: Policy makers and managers interested in the output of RMs for development of mitigation measures, air quality experts and scientists unfamiliar with these tech-niques, and RM practitioners involved in the model ex-ecution and interpretation of results. In order to address such heterogeneous readership the document was designed to be accessible at different levels. The RMTP is organized in three sections : an introduction to present the methodology to the unskilled reader, illustrating its capabilities and recom-mending when and how to use it ; a core section concerning the most common RM methodologies for source apportionment with in-depth analysis boxes for more experienced readers. The section is structured in 13 chapters following, as a check list, the logical steps to accomplish a source apportionment study. The first chapters deal with preliminary activities like the evaluation of the study area, collection of exist-ing information and experimental design. In the follow-ing chapters data collection and data treatment are dis-cussed. The section includes also chapters regarding spe-cific aspects of widely used methodologies like CMB, Factor Analysis, and PMF. The evaluation of test per-formance and reporting are discussed in the last part of this section ; the third section of the document was conceived to give an insight on the capabilities and the possible future trends in RM methodology. It consists of four chapters dealing with advanced, innovative techniques for which ready- to-use tools are already available or under development : trajectory analysis combined with RM, constrained and expanded models, AMS data processing, and the aethalometer model. The document includes a number of annexes to provide additional and practical information on specific topics, and examples.

Published
2012

48. Chemical analysis of atmospheric PM and improvment of the knowledge on emissions sources

Author

Jaffrezo, Jean-Luc, Piot, Christine, Besombes, Jean-Luc, Marchand, Nicolas, El Haddad, I., Favez, Olivier, Brulfert, G., Laboratoire de glaciologie et géophysique de l'environnement (LGGE), Centre National de la Recherche Scientifique (CNRS)-Institut national des sciences de l'Univers (INSU - CNRS)-Observatoire des Sciences de l'Univers de Grenoble (OSUG), Université Joseph Fourier - Grenoble 1 (UJF)-Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP )-Institut national des sciences de l'Univers (INSU - CNRS)-Institut national de recherche en sciences et technologies pour l'environnement et l'agriculture (IRSTEA)-Université Savoie Mont Blanc (USMB [Université de Savoie] [Université de Chambéry])-Centre National de la Recherche Scientifique (CNRS)-Université Joseph Fourier - Grenoble 1 (UJF)-Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP )-Institut national de recherche en sciences et technologies pour l'environnement et l'agriculture (IRSTEA)-Université Savoie Mont Blanc (USMB [Université de Savoie] [Université de Chambéry])-Centre National de la Recherche Scientifique (CNRS), Laboratoire de Chimie Moléculaire et Environnement (LCME), Université Savoie Mont Blanc (USMB [Université de Savoie] [Université de Chambéry]), Laboratoire Chimie de l'environnement (LCE), Aix Marseille Université (AMU)-Institut de Chimie du CNRS (INC)-Centre National de la Recherche Scientifique (CNRS), Institut National de l'Environnement Industriel et des Risques (INERIS), Observatoire des Sciences de l'Univers de Grenoble (OSUG), Université Savoie Mont Blanc (USMB [Université de Savoie] [Université de Chambéry])-Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP)-Institut national de recherche en sciences et technologies pour l'environnement et l'agriculture (IRSTEA)-Université Joseph Fourier - Grenoble 1 (UJF)-Institut national des sciences de l'Univers (INSU - CNRS)-Centre National de la Recherche Scientifique (CNRS)-Université Grenoble Alpes (UGA)-Université Savoie Mont Blanc (USMB [Université de Savoie] [Université de Chambéry])-Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP)-Institut national de recherche en sciences et technologies pour l'environnement et l'agriculture (IRSTEA)-Université Joseph Fourier - Grenoble 1 (UJF)-Institut national des sciences de l'Univers (INSU - CNRS)-Centre National de la Recherche Scientifique (CNRS)-Université Grenoble Alpes (UGA)-Centre National de la Recherche Scientifique (CNRS), Université Savoie Mont Blanc (USMB [Université de Savoie] [Université de Chambéry])-Université Grenoble Alpes (UGA), Aix Marseille Université (AMU)-Centre National de la Recherche Scientifique (CNRS), and Université Joseph Fourier - Grenoble 1 (UJF)-Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP )-Institut national des sciences de l'Univers (INSU - CNRS)-Institut national de recherche en sciences et technologies pour l'environnement et l'agriculture (IRSTEA)-Université Savoie Mont Blanc (USMB [Université de Savoie] [Université de Chambéry])-Centre National de la Recherche Scientifique (CNRS)-Université Joseph Fourier - Grenoble 1 (UJF)-Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP )-Institut national des sciences de l'Univers (INSU - CNRS)-Institut national de recherche en sciences et technologies pour l'environnement et l'agriculture (IRSTEA)-Université Savoie Mont Blanc (USMB [Université de Savoie] [Université de Chambéry])-Centre National de la Recherche Scientifique (CNRS)-Centre National de la Recherche Scientifique (CNRS)

Subjects
PM CHEMISTRY, TRACERS, TRACEURS, ANALYSE ON-LINE, AEROSOLS ATMOSPHERIQUES, SOURCES D'EMISSION, [SDE]Environmental Sciences, CHIMIE DES PM, EMISSION SOURCES, OFF-LINE SAMPLING, PRELEVEMENTS OFF-LINE---ATMOSPHERIC PM, ComputingMilieux_MISCELLANEOUS, ON-LINE ANALYSIS
Abstract

National audience

Published
2012

49. Source Apportionment of Carbonaceous Aerosols: Receptor Model Intercomparisons at Various Urban Sites

Author

Favez O, Anna, B. D., George, C., Bressi, M., Sciare, J., Piot, C., L Jaffrezo, J., El Haddad, I., Nicolas Marchand, Jean-Luc Besombes, Ghersi, V., Leoz–garziandia, E., IRCELYON-Catalytic and Atmospheric Reactivity for the Environment (CARE), Institut de recherches sur la catalyse et l'environnement de Lyon (IRCELYON), Université Claude Bernard Lyon 1 (UCBL), Université de Lyon-Université de Lyon-Centre National de la Recherche Scientifique (CNRS)-Institut de Chimie du CNRS (INC)-Université Claude Bernard Lyon 1 (UCBL), Université de Lyon-Université de Lyon-Centre National de la Recherche Scientifique (CNRS)-Institut de Chimie du CNRS (INC), Laboratoire des Sciences du Climat et de l'Environnement [Gif-sur-Yvette] (LSCE), Institut national des sciences de l'Univers (INSU - CNRS)-Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Université de Versailles Saint-Quentin-en-Yvelines (UVSQ), Laboratoire de Chimie Moléculaire et Environnement (LCME), Université Savoie Mont Blanc (USMB [Université de Savoie] [Université de Chambéry]), Laboratoire de glaciologie et géophysique de l'environnement (LGGE), Centre National de la Recherche Scientifique (CNRS)-Institut national des sciences de l'Univers (INSU - CNRS)-Observatoire des Sciences de l'Univers de Grenoble (OSUG), Université Joseph Fourier - Grenoble 1 (UJF)-Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP )-Institut national des sciences de l'Univers (INSU - CNRS)-Institut national de recherche en sciences et technologies pour l'environnement et l'agriculture (IRSTEA)-Université Savoie Mont Blanc (USMB [Université de Savoie] [Université de Chambéry])-Centre National de la Recherche Scientifique (CNRS)-Université Joseph Fourier - Grenoble 1 (UJF)-Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP )-Institut national de recherche en sciences et technologies pour l'environnement et l'agriculture (IRSTEA)-Université Savoie Mont Blanc (USMB [Université de Savoie] [Université de Chambéry])-Centre National de la Recherche Scientifique (CNRS), Laboratoire Chimie de l'environnement (LCE), Aix Marseille Université (AMU)-Institut de Chimie du CNRS (INC)-Centre National de la Recherche Scientifique (CNRS), IRCELYON-Caractérisation et remédiation des polluants dans l'air et l'eau (CARE), Université de Lyon-Université de Lyon-Centre National de la Recherche Scientifique (CNRS)-Université Claude Bernard Lyon 1 (UCBL), Université de Lyon-Université de Lyon-Centre National de la Recherche Scientifique (CNRS), Université Paris-Saclay-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Centre National de la Recherche Scientifique (CNRS), Université Savoie Mont Blanc (USMB [Université de Savoie] [Université de Chambéry])-Université Grenoble Alpes (UGA), Observatoire des Sciences de l'Univers de Grenoble (OSUG), Université Savoie Mont Blanc (USMB [Université de Savoie] [Université de Chambéry])-Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP)-Institut national de recherche en sciences et technologies pour l'environnement et l'agriculture (IRSTEA)-Université Joseph Fourier - Grenoble 1 (UJF)-Institut national des sciences de l'Univers (INSU - CNRS)-Centre National de la Recherche Scientifique (CNRS)-Université Grenoble Alpes (UGA)-Université Savoie Mont Blanc (USMB [Université de Savoie] [Université de Chambéry])-Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP)-Institut national de recherche en sciences et technologies pour l'environnement et l'agriculture (IRSTEA)-Université Joseph Fourier - Grenoble 1 (UJF)-Institut national des sciences de l'Univers (INSU - CNRS)-Centre National de la Recherche Scientifique (CNRS)-Université Grenoble Alpes (UGA)-Centre National de la Recherche Scientifique (CNRS), Aix Marseille Université (AMU)-Centre National de la Recherche Scientifique (CNRS), Oumedjbeur, Abdelkrim, Université de Lyon-Université de Lyon-Institut de Chimie du CNRS (INC)-Centre National de la Recherche Scientifique (CNRS)-Université Claude Bernard Lyon 1 (UCBL), Université de Lyon-Université de Lyon-Institut de Chimie du CNRS (INC)-Centre National de la Recherche Scientifique (CNRS), Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Institut national des sciences de l'Univers (INSU - CNRS)-Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS), and Université Joseph Fourier - Grenoble 1 (UJF)-Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP )-Institut national des sciences de l'Univers (INSU - CNRS)-Institut national de recherche en sciences et technologies pour l'environnement et l'agriculture (IRSTEA)-Université Savoie Mont Blanc (USMB [Université de Savoie] [Université de Chambéry])-Centre National de la Recherche Scientifique (CNRS)-Université Joseph Fourier - Grenoble 1 (UJF)-Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP )-Institut national des sciences de l'Univers (INSU - CNRS)-Institut national de recherche en sciences et technologies pour l'environnement et l'agriculture (IRSTEA)-Université Savoie Mont Blanc (USMB [Université de Savoie] [Université de Chambéry])-Centre National de la Recherche Scientifique (CNRS)-Centre National de la Recherche Scientifique (CNRS)

Subjects
[SDE] Environmental Sciences, [CHIM] Chemical Sciences, [SDE]Environmental Sciences, [CHIM]Chemical Sciences, ComputingMilieux_MISCELLANEOUS
Abstract

International audience

Published
2011

50. Source apportionment of fine aerosol in Marseille and Grenoble

Author

Anna, B. D., Marchand, N., L Jaffrezo, J., George, C., Favez, O., Boreave, A., Nicolas Marchand, El Haddad, I., Wortham, H., Armengaud, A., Piot, C., Jean-Luc Besombes, Laboratoire Chimie de l'environnement (LCE), Aix Marseille Université (AMU)-Institut de Chimie du CNRS (INC)-Centre National de la Recherche Scientifique (CNRS), Laboratoire de glaciologie et géophysique de l'environnement (LGGE), Observatoire des Sciences de l'Univers de Grenoble (OSUG), Université Joseph Fourier - Grenoble 1 (UJF)-Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP )-Institut national des sciences de l'Univers (INSU - CNRS)-Institut national de recherche en sciences et technologies pour l'environnement et l'agriculture (IRSTEA)-Université Savoie Mont Blanc (USMB [Université de Savoie] [Université de Chambéry])-Centre National de la Recherche Scientifique (CNRS)-Université Joseph Fourier - Grenoble 1 (UJF)-Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP )-Institut national des sciences de l'Univers (INSU - CNRS)-Institut national de recherche en sciences et technologies pour l'environnement et l'agriculture (IRSTEA)-Université Savoie Mont Blanc (USMB [Université de Savoie] [Université de Chambéry])-Centre National de la Recherche Scientifique (CNRS)-Centre National de la Recherche Scientifique (CNRS), IRCELYON-Catalytic and Atmospheric Reactivity for the Environment (CARE), Institut de recherches sur la catalyse et l'environnement de Lyon (IRCELYON), Université Claude Bernard Lyon 1 (UCBL), Université de Lyon-Université de Lyon-Institut de Chimie du CNRS (INC)-Centre National de la Recherche Scientifique (CNRS)-Université Claude Bernard Lyon 1 (UCBL), Université de Lyon-Université de Lyon-Institut de Chimie du CNRS (INC)-Centre National de la Recherche Scientifique (CNRS), Laboratoire de parasitologie [Pointe-à-Pitre], CHU Pointe-à-Pitre/Abymes [Guadeloupe], Laboratoire de Chimie Moléculaire et Environnement (LCME), Université Savoie Mont Blanc (USMB [Université de Savoie] [Université de Chambéry]), Aix Marseille Université (AMU)-Centre National de la Recherche Scientifique (CNRS), Université Savoie Mont Blanc (USMB [Université de Savoie] [Université de Chambéry])-Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP)-Institut national de recherche en sciences et technologies pour l'environnement et l'agriculture (IRSTEA)-Université Joseph Fourier - Grenoble 1 (UJF)-Institut national des sciences de l'Univers (INSU - CNRS)-Centre National de la Recherche Scientifique (CNRS)-Université Grenoble Alpes (UGA)-Université Savoie Mont Blanc (USMB [Université de Savoie] [Université de Chambéry])-Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP)-Institut national de recherche en sciences et technologies pour l'environnement et l'agriculture (IRSTEA)-Université Joseph Fourier - Grenoble 1 (UJF)-Institut national des sciences de l'Univers (INSU - CNRS)-Centre National de la Recherche Scientifique (CNRS)-Université Grenoble Alpes (UGA)-Centre National de la Recherche Scientifique (CNRS), IRCELYON-Caractérisation et remédiation des polluants dans l'air et l'eau (CARE), Université de Lyon-Université de Lyon-Centre National de la Recherche Scientifique (CNRS)-Université Claude Bernard Lyon 1 (UCBL), Université de Lyon-Université de Lyon-Centre National de la Recherche Scientifique (CNRS), Université Savoie Mont Blanc (USMB [Université de Savoie] [Université de Chambéry])-Université Grenoble Alpes (UGA), Centre National de la Recherche Scientifique (CNRS)-Institut national des sciences de l'Univers (INSU - CNRS)-Observatoire des Sciences de l'Univers de Grenoble (OSUG), Université Joseph Fourier - Grenoble 1 (UJF)-Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP )-Institut national des sciences de l'Univers (INSU - CNRS)-Institut national de recherche en sciences et technologies pour l'environnement et l'agriculture (IRSTEA)-Université Savoie Mont Blanc (USMB [Université de Savoie] [Université de Chambéry])-Centre National de la Recherche Scientifique (CNRS)-Université Joseph Fourier - Grenoble 1 (UJF)-Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP )-Institut national de recherche en sciences et technologies pour l'environnement et l'agriculture (IRSTEA)-Université Savoie Mont Blanc (USMB [Université de Savoie] [Université de Chambéry])-Centre National de la Recherche Scientifique (CNRS), Université de Lyon-Université de Lyon-Centre National de la Recherche Scientifique (CNRS)-Institut de Chimie du CNRS (INC)-Université Claude Bernard Lyon 1 (UCBL), Université de Lyon-Université de Lyon-Centre National de la Recherche Scientifique (CNRS)-Institut de Chimie du CNRS (INC), and Oumedjbeur, Abdelkrim

Subjects
[SDE] Environmental Sciences, [CHIM] Chemical Sciences, [SDE]Environmental Sciences, [CHIM]Chemical Sciences, ComputingMilieux_MISCELLANEOUS
Abstract

International audience

Published
2011

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