2017, Baró, Rocío, Palacios-Peña, Laura, Baklanov, Alexander, Balzarini, Alessandra, Brunner, Dominik, Forkel, Renate, Hirtl, Marcus, Honzak, Luka, Pérez, Juan Luis, Pirovano, Guido, San José, Roberto, Schröder, Wolfram, Werhahn, Johannes, Wolke, Ralf, Žabkar, Rahela, Jiménez-Guerrero, Pedro

The climate effect of atmospheric aerosols is associated with their influence on the radiative budget of the Earth due to the direct aerosol-radiation interactions (ARIs) and indirect effects, resulting from aerosol-cloud-radiation interactions (ACIs). Online coupled meteorology-chemistry models permit the description of these effects on the basis of simulated atmospheric aerosol concentrations, although there is still some uncertainty associated with the use of these models. Thus, the objective of this work is to assess whether the inclusion of atmospheric aerosol radiative feedbacks of an ensemble of online coupled models improves the simulation results for maximum, mean and minimum temperature at 2m over Europe. The evaluated models outputs originate from EuMetChem COST Action ES1004 simulations for Europe, differing in the inclusion (or omission) of ARI and ACI in the various models. The cases studies cover two important atmospheric aerosol episodes over Europe in the year 2010: (i) a heat wave event and a forest fire episode (July-August 2010) and (ii) a more humid episode including a Saharan desert dust outbreak in October 2010. The simulation results are evaluated against observational data from the E-OBS gridded database. The results indicate that, although there is only a slight improvement in the bias of the simulation results when including the radiative feedbacks, the spatiotemporal variability and correlation coefficients are improved for the cases under study when atmospheric aerosol radiative effects are included.

2018, Papagiannopoulos, Nikolaos, Mona, Lucia, Amodeo, Aldo, D'Amico, Giuseppe, Gumà Claramunt, Pilar, Pappalardo, Gelsomina, Alados-Arboledas, Lucas, Guerrero-Rascado, Juan Luís, Amiridis, Vassilis, Kokkalis, Panagiotis, Apituley, Arnoud, Baars, Holger, Schwarz, Anja, Wandinger, Ulla, Binietoglou, Ioannis, Nicolae, Doina, Bortoli, Daniele, Comerón, Adolfo, Rodríguez-Gómez, Alejandro, Sicard, Michaël, Papayannis, Alex, Wiegner, Matthias

We present an automatic aerosol classification method based solely on the European Aerosol Research Lidar Network (EARLINET) intensive optical parameters with the aim of building a network-wide classification tool that could provide near-real-time aerosol typing information. The presented method depends on a supervised learning technique and makes use of the Mahalanobis distance function that relates each unclassified measurement to a predefined aerosol type. As a first step (training phase), a reference dataset is set up consisting of already classified EARLINET data. Using this dataset, we defined 8 aerosol classes: clean continental, polluted continental, dust, mixed dust, polluted dust, mixed marine, smoke, and volcanic ash. The effect of the number of aerosol classes has been explored, as well as the optimal set of intensive parameters to separate different aerosol types. Furthermore, the algorithm is trained with literature particle linear depolarization ratio values. As a second step (testing phase), we apply the method to an already classified EARLINET dataset and analyze the results of the comparison to this classified dataset. The predictive accuracy of the automatic classification varies between 59% (minimum) and 90% (maximum) from 8 to 4 aerosol classes, respectively, when evaluated against pre-classified EARLINET lidar. This indicates the potential use of the automatic classification to all network lidar data. Furthermore, the training of the algorithm with particle linear depolarization values found in the literature further improves the accuracy with values for all the aerosol classes around 80%. Additionally, the algorithm has proven to be highly versatile as it adapts to changes in the size of the training dataset and the number of aerosol classes and classifying parameters. Finally, the low computational time and demand for resources make the algorithm extremely suitable for the implementation within the single calculus chain (SCC), the EARLINET centralized processing suite.

2018, Dall’Osto, M., Beddows, D.C.S., Asmi, A., Poulain, L., Hao, L., Freney, E., Allan, J.D., Canagaratna, M., Crippa, M., Bianchi, F., de Leeuw, G., Eriksson, A., Swietlicki, E., Hansson, H.C., Henzing, J.S., Granier, C., Zemankova, K., Laj, P., Onasch, T., Prevot, A., Putaud, J. P., Sellegri, K., Vidal, M., Virtanen, A., Simo, R., Worsnop, D., O’Dowd, C., Kulmala, M., Harrison, Roy M.

The formation of new atmospheric particles involves an initial step forming stable clusters less than a nanometre in size (<~1 nm), followed by growth into quasi-stable aerosol particles a few nanometres (~1-10 nm) and larger (>~10 nm). Although at times, the same species can be responsible for both processes, it is thought that more generally each step comprises differing chemical contributors. Here, we present a novel analysis of measurements from a unique multi-station ground-based observing system which reveals new insights into continental-scale patterns associated with new particle formation. Statistical cluster analysis of this unique 2-year multi-station dataset comprising size distribution and chemical composition reveals that across Europe, there are different major seasonal trends depending on geographical location, concomitant with diversity in nucleating species while it seems that the growth phase is dominated by organic aerosol formation. The diversity and seasonality of these events requires an advanced observing system to elucidate the key processes and species driving particle formation, along with detecting continental scale changes in aerosol formation into the future.

2013, Groß, S., Esselborn, M., Abicht, F., Wirth, M., Fix, A., Minikin, A.

Airborne high spectral resolution lidar observations over Europe during the EUCAARI-LONGREX field experiment in May 2008 are analysed with respect to the optical properties of continental pollution aerosol. Continental pollution aerosol is characterized by its depolarisation and lidar ratio. Over all, the measurements of the lidar ratio and the particle linear depolarization ratio of pollution aerosols provide a narrow range of values. Therefore, this data set allows for a distinct characterization of the aerosol type "pollution aerosol" and thus is valuable both to distinguish continental pollution aerosol from other aerosol types and to determine mixtures with other types of aerosols.

2019, Yttri, Karl Espen, Simpson, David, Bergström, Robert, Kiss, Gyula, Szidat, Sönke, Ceburnis, Darius, Eckhardt, Sabine, Hueglin, Christoph, Nøjgaard, Jacob Klenø, Perrino, Cinzia, Pisso, Ignazio, Prevot, Andre Stephan Henry, Putaud, Jean-Philippe, Spindler, Gerald, Vana, Milan, Zhang, Yan-Lin, Aas, Wenche

Carbonaceous aerosol (total carbon, TCp) was source apportioned at nine European rural background sites, as part of the European Measurement and Evaluation Programme (EMEP) Intensive Measurement Periods in fall 2008 and winter/spring 2009. Five predefined fractions were apportioned based on ambient measurements: elemental and organic carbon, from combustion of biomass (ECbb and OCbb) and from fossil-fuel (ECff and OCff) sources, and remaining non-fossil organic carbon (OCrnf), dominated by natural sources.OCrnf made a larger contribution to TCp than anthropogenic sources (ECbb, OCbb, ECff, and OCff) at four out of nine sites in fall, reflecting the vegetative season, whereas anthropogenic sources dominated at all but one site in winter/spring. Biomass burning (OCbb + ECbb) was the major anthropogenic source at the central European sites in fall, whereas fossil-fuel (OCff + ECff) sources dominated at the southernmost and the two northernmost sites. Residential wood burning emissions explained 30 %-50 % of TCp at most sites in the first week of sampling in fall, showing that this source can be the dominant one, even outside the heating season. In winter/spring, biomass burning was the major anthropogenic source at all but two sites, reflecting increased residential wood burning emissions in the heating season. Fossil-fuel sources dominated EC at all sites in fall, whereas there was a shift towards biomass burning for the southernmost sites in winter/spring.Model calculations based on base-case emissions (mainly officially reported national emissions) strongly underpredicted observational derived levels of OCbb and ECbb outside Scandinavia. Emissions based on a consistent bottom-up inventory for residential wood burning (and including intermediate volatility compounds, IVOCs) improved model results compared to the base-case emissions, but modeled levels were still substantially underestimated compared to observational derived OCbb and ECbb levels at the southernmost sites.Our study shows that natural sources are a major contributor to carbonaceous aerosol in Europe, even in fall and in winter/spring, and that residential wood burning emissions are equally as large as or larger than that of fossil-fuel sources, depending on season and region. The poorly constrained residential wood burning emissions for large parts of Europe show the obvious need to improve emission inventories, with harmonization of emission factors between countries likely being the most important step to improve model calculations for biomass burning emissions, and European PM2.5 concentrations in general. © Author(s) 2019.

2019, Tegen, I., Neubauer, D., Ferrachat, S., Drian, C.S.-L., Bey, I., Schutgens, N., Stier, P., Watson-Parris, D., Stanelle, T., Schmidt, H., Rast, S., Kokkola, H., Schultz, M., Schroeder, S., Daskalakis, N., Barthel, S., Heinold, B., Lohmann, U.

We introduce and evaluate aerosol simulations with the global aerosol-climate model ECHAM6.3-HAM2.3, which is the aerosol component of the fully coupled aerosol-chemistry-climate model ECHAM-HAMMOZ. Both the host atmospheric climate model ECHAM6.3 and the aerosol model HAM2.3 were updated from previous versions. The updated version of the HAM aerosol model contains improved parameterizations of aerosol processes such as cloud activation, as well as updated emission fields for anthropogenic aerosol species and modifications in the online computation of sea salt and mineral dust aerosol emissions. Aerosol results from nudged and free-running simulations for the 10-year period 2003 to 2012 are compared to various measurements of aerosol properties. While there are regional deviations between the model and observations, the model performs well overall in terms of aerosol optical thickness, but may underestimate coarse-mode aerosol concentrations to some extent so that the modeled particles are smaller than indicated by the observations. Sulfate aerosol measurements in the US and Europe are reproduced well by the model, while carbonaceous aerosol species are biased low. Both mineral dust and sea salt aerosol concentrations are improved compared to previous versions of ECHAM-HAM. The evaluation of the simulated aerosol distributions serves as a basis for the suitability of the model for simulating aerosol-climate interactions in a changing climate.

2018, Huang, Shan, Wu, Zhijun, Poulain, Laurent, van Pinxteren, Manuela, Merkel, Maik, Assmann, Denise, Herrmann, Hartmut, Wiedensohler, Alfred

Marine aerosol particles are an important part of the natural aerosol systems and might have a significant impact on the global climate and biological cycle. It is widely accepted that truly pristine marine conditions are difficult to find over the ocean. However, the influence of continental and anthropogenic emissions on the marine boundary layer (MBL) aerosol is still less understood and non-quantitative, causing uncertainties in the estimation of the climate effect of marine aerosols. This study presents a detailed chemical characterization of the MBL aerosol as well as the source apportionment of the organic aerosol (OA) composition. The data set covers the Atlantic Ocean from 53∘ N to 53∘ S, based on four open-ocean cruises in 2011 and 2012. The aerosol particle composition was measured with a high-resolution time-of-flight aerosol mass spectrometer (HR-ToF-AMS), which indicated that sub-micrometer aerosol particles over the Atlantic Ocean are mainly composed of sulfates (50 % of the particle mass concentration), organics (21 %) and sea salt (12 %). OA has been apportioned into five factors, including three factors linked to marine sources and two with continental and/or anthropogenic origins. The marine oxygenated OA (MOOA, 16 % of the total OA mass) and marine nitrogen-containing OA (MNOA, 16 %) are identified as marine secondary products with gaseous biogenic precursors dimethyl sulfide (DMS) or amines. Marine hydrocarbon-like OA (MHOA, 19 %) was attributed to the primary emissions from the Atlantic Ocean. The factor for the anthropogenic oxygenated OA (Anth-OOA, 19 %) is related to continental long-range transport. Represented by the combustion oxygenated OA (Comb-OOA), aged combustion emissions from maritime traffic and wild fires in Africa contributed, on average, a large fraction to the total OA mass (30 %). This study provides the important finding that long-range transport was found to contribute averagely 49 % of the submicron OA mass over the Atlantic Ocean. This is almost equal to that from marine sources (51 %). Furthermore, a detailed latitudinal distribution of OA source contributions showed that DMS oxidation contributed markedly to the OA over the South Atlantic during spring, while continental-related long-range transport largely influenced the marine atmosphere near Europe and western and central Africa (15∘ N to 15∘ S). In addition, supported by a solid correlation between marine tracer methanesulfonic acid (MSA) and the DMS-oxidation OA (MOOA, R2>0.85), this study suggests that the DMS-related secondary organic aerosol (SOA) over the Atlantic Ocean could be estimated by MSA and a scaling factor of 1.79, especially in spring.