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A global analysis of climate-relevant aerosol properties retrieved from the network of Global Atmosphere Watch (GAW) near-surface observatories
2020, Laj, Paolo, Bigi, Alessandro, Rose, Clémence, Andrews, Elisabeth, Lund Myhre, Cathrine, Collaud Coen, Martine, Lin, Yong, Wiedensohler, Alfred, Schulz, Michael, Ogren, John A., Fiebig, Markus, Prenni, Anthony, Reisen, Fabienne, Romano, Salvatore, Sellegri, Karine, Sharma, Sangeeta, Schauer, Gerhard, Sheridan, Patrick, Sherman, James Patrick, Schütze, Maik, Schwerin, Andreas, Tuch, Thomas, Sohmer, Ralf, Sorribas, Mar, Steinbacher, Martin, Sun, Junying, Titos, Gloria, Toczko, Barbara, Tulet, Pierre, Tunved, Peter, Vakkari, Ville, Velarde, Fernando, Velasquez, Patricio, Villani, Paolo, Vratolis, Sterios, Wang, Sheng-Hsiang, Weinhold, Kay, Gliß, Jonas, Weller, Rolf, Yela, Margarita, Yus-Diez, Jesus, Zdimal, Vladimir, Zieger, Paul, Zikova, Nadezda, Mortier, Augustin, Pandolfi, Marco, Petäja, Tuukka, Kim, Sang-Woo, Aas, Wenche, Putaud, Jean-Philippe, Mayol-Bracero, Olga, Keywood, Melita, Labrador, Lorenzo, Aalto, Pasi, Ahlberg, Erik, Alados Arboledas, Lucas, Alastuey, Andrés, Andrade, Marcos, Artíñano, Begoña, Ausmeel, Stina, Arsov, Todor, Asmi, Eija, Backman, John, Baltensperger, Urs, Bastian, Susanne, Bath, Olaf, Beukes, Johan Paul, Brem, Benjamin T., Bukowiecki, Nicolas, Conil, Sébastien, Couret, Cedric, Day, Derek, Dayantolis, Wan, Degorska, Anna, Eleftheriadis, Konstantinos, Fetfatzis, Prodromos, Favez, Olivier, Flentje, Harald, Gini, Maria I., Gregorič, Asta, Gysel-Beer, Martin, Hallar, A. Gannet, Hand, Jenny, Hoffer, Andras, Hueglin, Christoph, Hooda, Rakesh K., Hyvärinen, Antti, Kalapov, Ivo, Kalivitis, Nikos, Kasper-Giebl, Anne, Kim, Jeong Eun, Kouvarakis, Giorgos, Kranjc, Irena, Krejci, Radovan, Kulmala, Markku, Labuschagne, Casper, Lee, Hae-Jung, Lihavainen, Heikki, Lin, Neng-Huei, Löschau, Gunter, Luoma, Krista, Marinoni, Angela, Martins Dos Santos, Sebastiao, Meinhardt, Frank, Merkel, Maik, Metzger, Jean-Marc, Mihalopoulos, Nikolaos, Nguyen, Nhat Anh, Ondracek, Jakub, Pérez, Noemi, Perrone, Maria Rita, Petit, Jean-Eudes, Picard, David, Pichon, Jean-Marc, Pont, Veronique, Prats, Natalia
Aerosol particles are essential constituents of the Earth's atmosphere, impacting the earth radiation balance directly by scattering and absorbing solar radiation, and indirectly by acting as cloud condensation nuclei. In contrast to most greenhouse gases, aerosol particles have short atmospheric residence times, resulting in a highly heterogeneous distribution in space and time. There is a clear need to document this variability at regional scale through observations involving, in particular, the in situ near-surface segment of the atmospheric observation system. This paper will provide the widest effort so far to document variability of climate-relevant in situ aerosol properties (namely wavelength dependent particle light scattering and absorption coefficients, particle number concentration and particle number size distribution) from all sites connected to the Global Atmosphere Watch network. High-quality data from almost 90 stations worldwide have been collected and controlled for quality and are reported for a reference year in 2017, providing a very extended and robust view of the variability of these variables worldwide. The range of variability observed worldwide for light scattering and absorption coefficients, single-scattering albedo, and particle number concentration are presented together with preliminary information on their long-term trends and comparison with model simulation for the different stations. The scope of the present paper is also to provide the necessary suite of information, including data provision procedures, quality control and analysis, data policy, and usage of the ground-based aerosol measurement network. It delivers to users of the World Data Centre on Aerosol, the required confidence in data products in the form of a fully characterized value chain, including uncertainty estimation and requirements for contributing to the global climate monitoring system.
A full year of aerosol size distribution data from the central Arctic under an extreme positive Arctic Oscillation: insights from the Multidisciplinary drifting Observatory for the Study of Arctic Climate (MOSAiC) expedition
2023, Boyer, Matthew, Aliaga, Diego, Pernov, Jakob Boyd, Angot, Hélène, Quéléver, Lauriane L. J., Dada, Lubna, Heutte, Benjamin, Dall'Osto, Manuel, Beddows, David C. S., Brasseur, Zoé, Beck, Ivo, Bucci, Silvia, Duetsch, Marina, Stohl, Andreas, Laurila, Tiia, Asmi, Eija, Massling, Andreas, Thomas, Daniel Charles, Nøjgaard, Jakob Klenø, Chan, Tak, Sharma, Sangeeta, Tunved, Peter, Krejci, Radovan, Hansson, Hans Christen, Bianchi, Federico, Lehtipalo, Katrianne, Wiedensohler, Alfred, Weinhold, Kay, Kulmala, Markku, Petäjä, Tuukka, Sipilä, Mikko, Schmale, Julia, Jokinen, Tuija
The Arctic environment is rapidly changing due to accelerated warming in the region. The warming trend is driving a decline in sea ice extent, which thereby enhances feedback loops in the surface energy budget in the Arctic. Arctic aerosols play an important role in the radiative balance and hence the climate response in the region, yet direct observations of aerosols over the Arctic Ocean are limited. In this study, we investigate the annual cycle in the aerosol particle number size distribution (PNSD), particle number concentration (PNC), and black carbon (BC) mass concentration in the central Arctic during the Multidisciplinary drifting Observatory for the Study of Arctic Climate (MOSAiC) expedition. This is the first continuous, year-long data set of aerosol PNSD ever collected over the sea ice in the central Arctic Ocean. We use a k-means cluster analysis, FLEXPART simulations, and inverse modeling to evaluate seasonal patterns and the influence of different source regions on the Arctic aerosol population. Furthermore, we compare the aerosol observations to land-based sites across the Arctic, using both long-term measurements and observations during the year of the MOSAiC expedition (2019-2020), to investigate interannual variability and to give context to the aerosol characteristics from within the central Arctic. Our analysis identifies that, overall, the central Arctic exhibits typical seasonal patterns of aerosols, including anthropogenic influence from Arctic haze in winter and secondary aerosol processes in summer. The seasonal pattern corresponds to the global radiation, surface air temperature, and timing of sea ice melting/freezing, which drive changes in transport patterns and secondary aerosol processes. In winter, the Norilsk region in Russia/Siberia was the dominant source of Arctic haze signals in the PNSD and BC observations, which contributed to higher accumulation-mode PNC and BC mass concentrations in the central Arctic than at land-based observatories. We also show that the wintertime Arctic Oscillation (AO) phenomenon, which was reported to achieve a record-breaking positive phase during January-March 2020, explains the unusual timing and magnitude of Arctic haze across the Arctic region compared to longer-term observations. In summer, the aerosol PNCs of the nucleation and Aitken modes are enhanced; however, concentrations were notably lower in the central Arctic over the ice pack than at land-based sites further south. The analysis presented herein provides a current snapshot of Arctic aerosol processes in an environment that is characterized by rapid changes, which will be crucial for improving climate model predictions, understanding linkages between different environmental processes, and investigating the impacts of climate change in future Arctic aerosol studies.
Measurement report: Long-range transport and the fate of dimethyl sulfide oxidation products in the free troposphere derived from observations at the high-altitude research station Chacaltaya (5240ma.s.l.) in the Bolivian Andes
2023, Scholz, Wiebke, Shen, Jiali, Aliaga, Diego, Wu, Cheng, Carbone, Samara, Moreno, Isabel, Zha, Qiaozhi, Huang, Wei, Heikkinen, Liine, Jaffrezo, Jean Luc, Uzu, Gaelle, Partoll, Eva, Leiminger, Markus, Velarde, Fernando, Laj, Paolo, Ginot, Patrick, Artaxo, Paolo, Wiedensohler, Alfred, Kulmala, Markku, Mohr, Claudia, Andrade, Marcos, Sinclair, Victoria, Bianchi, Federico, Hansel, Armin
Dimethyl sulfide (DMS) is the primary natural contributor to the atmospheric sulfur burden. Observations concerning the fate of DMS oxidation products after long-range transport in the remote free troposphere are, however, sparse. Here we present quantitative chemical ionization mass spectrometric measurements of DMS and its oxidation products sulfuric acid (H2SO4), methanesulfonic acid (MSA), dimethylsulfoxide (DMSO), dimethylsulfone (DMSO2), methanesulfinic acid (MSIA), methyl thioformate (MTF), methanesulfenic acid (MSEA, CH3SOH), and a compound of the likely structure CH3S(O)2OOH in the gas phase, as well as measurements of the sulfate and methanesulfonate aerosol mass fractions. The measurements were performed at the Global Atmosphere Watch (GAW) station Chacaltaya in the Bolivian Andes located at 5240m above sea level (a.s.l.). DMS and DMS oxidation products are brought to the Andean high-altitude station by Pacific air masses during the dry season after convective lifting over the remote Pacific ocean to 6000-8000ma.s.l. and subsequent long-range transport in the free troposphere (FT). Most of the DMS reaching the station is already converted to the rather unreactive sulfur reservoirs DMSO2 in the gas phase and methanesulfonate (MS-) in the particle phase, which carried nearly equal amounts of sulfur to the station. The particulate sulfate at Chacaltaya is however dominated by regional volcanic emissions during the time of the measurement and not significantly affected by the marine air masses. In one of the FT events, even some DMS was observed next to reactive intermediates such as methyl thioformate, dimethylsulfoxide, and methanesulfinic acid. Also for this event, back trajectory calculations show that the air masses came from above the ocean (distance >330km) with no local surface contacts. This study demonstrates the potential impact of marine DMS emissions on the availability of sulfur-containing vapors in the remote free troposphere far away from the ocean.
High Gas-Phase Methanesulfonic Acid Production in the OH-Initiated Oxidation of Dimethyl Sulfide at Low Temperatures
2022, Shen, Jiali, Scholz, Wiebke, He, Xu-Cheng, Zhou, Putian, Marie, Guillaume, Wang, Mingyi, Marten, Ruby, Surdu, Mihnea, Rörup, Birte, Baalbaki, Rima, Amorim, Antonio, Ataei, Farnoush, Bell, David M., Bertozzi, Barbara, Brasseur, Zoé, Caudillo, Lucía, Chen, Dexian, Chu, Biwu, Dada, Lubna, Duplissy, Jonathan, Finkenzeller, Henning, Granzin, Manuel, Guida, Roberto, Heinritzi, Martin, Hofbauer, Victoria, Iyer, Siddharth, Kemppainen, Deniz, Kong, Weimeng, Krechmer, Jordan E., Kürten, Andreas, Lamkaddam, Houssni, Lee, Chuan Ping, Lopez, Brandon, Mahfouz, Naser G. A., Manninen, Hanna E., Massabò, Dario, Mauldin, Roy L., Mentler, Bernhard, Müller, Tatjana, Pfeifer, Joschka, Philippov, Maxim, Piedehierro, Ana A., Roldin, Pontus, Schobesberger, Siegfried, Simon, Mario, Stolzenburg, Dominik, Tham, Yee Jun, Tomé, António, Umo, Nsikanabasi Silas, Wang, Dongyu, Wang, Yonghong, Weber, Stefan K., Welti, André, Wollesen de Jonge, Robin, Wu, Yusheng, Zauner-Wieczorek, Marcel, Zust, Felix, Baltensperger, Urs, Curtius, Joachim, Flagan, Richard C., Hansel, Armin, Möhler, Ottmar, Petäjä, Tuukka, Volkamer, Rainer, Kulmala, Markku, Lehtipalo, Katrianne, Rissanen, Matti, Kirkby, Jasper, El-Haddad, Imad, Bianchi, Federico, Sipilä, Mikko, Donahue, Neil M., Worsnop, Douglas R.
Dimethyl sulfide (DMS) influences climate via cloud condensation nuclei (CCN) formation resulting from its oxidation products (mainly methanesulfonic acid, MSA, and sulfuric acid, H2SO4). Despite their importance, accurate prediction of MSA and H2SO4from DMS oxidation remains challenging. With comprehensive experiments carried out in the Cosmics Leaving Outdoor Droplets (CLOUD) chamber at CERN, we show that decreasing the temperature from +25 to -10 °C enhances the gas-phase MSA production by an order of magnitude from OH-initiated DMS oxidation, while H2SO4production is modestly affected. This leads to a gas-phase H2SO4-to-MSA ratio (H2SO4/MSA) smaller than one at low temperatures, consistent with field observations in polar regions. With an updated DMS oxidation mechanism, we find that methanesulfinic acid, CH3S(O)OH, MSIA, forms large amounts of MSA. Overall, our results reveal that MSA yields are a factor of 2-10 higher than those predicted by the widely used Master Chemical Mechanism (MCMv3.3.1), and the NOxeffect is less significant than that of temperature. Our updated mechanism explains the high MSA production rates observed in field observations, especially at low temperatures, thus, substantiating the greater importance of MSA in the natural sulfur cycle and natural CCN formation. Our mechanism will improve the interpretation of present-day and historical gas-phase H2SO4/MSA measurements.
Comparison of particle number size distribution trends in ground measurements and climate models
2022, Leinonen, Ville, Kokkola, Harri, Yli-Juuti, Taina, Mielonen, Tero, Kühn, Thomas, Nieminen, Tuomo, Heikkinen, Simo, Miinalainen, Tuuli, Bergman, Tommi, Carslaw, Ken, Decesari, Stefano, Fiebig, Markus, Hussein, Tareq, Kivekäs, Niku, Krejci, Radovan, Kulmala, Markku, Leskinen, Ari, Massling, Andreas, Mihalopoulos, Nikos, Mulcahy, Jane P., Noe, Steffen M., van Noije, Twan, O'Connor, Fiona M., O'Dowd, Colin, Olivie, Dirk, Pernov, Jakob B., Petäjä, Tuukka, Seland, Øyvind, Schulz, Michael, Scott, Catherine E., Skov, Henrik, Swietlicki, Erik, Tuch, Thomas, Wiedensohler, Alfred, Virtanen, Annele, Mikkonen, Santtu
Despite a large number of studies, out of all drivers of radiative forcing, the effect of aerosols has the largest uncertainty in global climate model radiative forcing estimates. There have been studies of aerosol optical properties in climate models, but the effects of particle number size distribution need a more thorough inspection. We investigated the trends and seasonality of particle number concentrations in nucleation, Aitken, and accumulation modes at 21 measurement sites in Europe and the Arctic. For 13 of those sites, with longer measurement time series, we compared the field observations with the results from five climate models, namely EC-Earth3, ECHAM-M7, ECHAM-SALSA, NorESM1.2, and UKESM1. This is the first extensive comparison of detailed aerosol size distribution trends between in situ observations from Europe and five earth system models (ESMs). We found that the trends of particle number concentrations were mostly consistent and decreasing in both measurements and models. However, for many sites, climate models showed weaker decreasing trends than the measurements. Seasonal variability in measured number concentrations, quantified by the ratio between maximum and minimum monthly number concentration, was typically stronger at northern measurement sites compared to other locations. Models had large differences in their seasonal representation, and they can be roughly divided into two categories: for EC-Earth and NorESM, the seasonal cycle was relatively similar for all sites, and for other models the pattern of seasonality varied between northern and southern sites. In addition, the variability in concentrations across sites varied between models, some having relatively similar concentrations for all sites, whereas others showed clear differences in concentrations between remote and urban sites. To conclude, although all of the model simulations had identical input data to describe anthropogenic mass emissions, trends in differently sized particles vary among the models due to assumptions in emission sizes and differences in how models treat size-dependent aerosol processes. The inter-model variability was largest in the accumulation mode, i.e. sizes which have implications for aerosol-cloud interactions. Our analysis also indicates that between models there is a large variation in efficiency of long-range transportation of aerosols to remote locations. The differences in model results are most likely due to the more complex effect of different processes instead of one specific feature (e.g. the representation of aerosol or emission size distributions). Hence, a more detailed characterization of microphysical processes and deposition processes affecting the long-range transport is needed to understand the model variability.