ALBERT

Description: One of the challenges of understanding atmospheric organic aerosol (OA) stems from its complex composition. Mass spectrometry is commonly used to characterize the compositional variability of OA. Clustering of a mass spectral data set helps identify components that exhibit similar behavior or have similar properties, facilitating understanding of sources and processes that govern compositional variability. Here, we developed a novel clustering algorithm, Noise-Sorted Scanning Clustering (NSSC), and apply it to thermal desorption measurements from the Filter Inlet for Gases and AEROsols coupled to a chemical ionization mass spectrometer (FIGAERO CIMS). NSSC provides a robust, reproducible analysis of the FIGAERO temperature-dependent mass spectral data. The NSSC allows for determination of thermal profiles for compositionally distinct clusters, increasing the accessibility and enhancing the interpretation of FIGAERO data. Applications of NSSC to several laboratory biogenic secondary organic aerosol (BSOA) systems demonstrate the ability of NSSC to distinguish different types of thermal behaviors for the components comprising the particles along with the relative mass contributions and chemical properties (e.g. average molecular formula) of each cluster. For each of the systems examined, more than 80 % of the total mass is clustered into 9–13 clusters. Comparison of the average thermograms of the clusters between systems indicate some commonalty in terms of the thermal properties of different BSOA, although with some system-specific behavior. Application of NSSC to sets of experiments in which one experimental parameter, such as the concentration of NO, is varied demonstrates the potential for clustering to elucidate the chemical factors that drive changes in the thermal properties of OA. Further quantitative interpretation of the clustered thermograms followed by clustering will allow for more comprehensive understanding of the thermochemical properties of OA.

Description: The EURODELTA III exercise allows a very comprehensive inter-comparison and evaluation of chemistry transport models performance. Participating models were applied over four different one month period, within a rather limited number of years (from June 2006 to March 2009) thus allowing evaluating the influence of different meteorological conditions on model performance. The exercise was performed under strict requirements concerning the input data. As a consequence, there were very limited differences in the models set up, representing a sort of sensitivity analysis to several aspects of the modelling chains. The models were evaluated mainly on background stations. Even if the meteorology was prescribed, some variables like the planetary boundary layer (PBL) height, the vertical diffusion coefficient are diagnosed in the model pre-processors and explain the spread of models results. For ozone, this study shows the importance of boundary conditions on model calculations and then on the regime of the gas and particle chemistry. The worst performances are observed for sulphur dioxide concentrations that are poorly captured by the models. The performances of models are rather good very similar for the nitrogen dioxide. On average, the models provide a rather good picture of the particulate matter (PM) concentrations over Europe even if the highest concentrations are underestimated. For the PM, the mean diurnal cycles show a general tendency to overestimate the effect of the PBL height rise while the afternoon chemistry (formation of secondary species) is certainly underestimated, PM observations show very flat diurnal profiles whatever the season. In general the day time PBL height is underestimated by all models, the largest variability of predicted PBL is observed over the ocean and seas. More generally, in most cases model performances are more influenced by the model setup than the season. The temporal evolution of wind speed is most responsible of model skilfulness in reproducing the daily variability of pollutant concentrations (e.g. the development of peak episodes), while the reconstruction of the PBL diurnal cycle seems more influencing in driving the corresponding pollutant diurnal cycle and hence the presence of systematic positive and negative biases detectable on daily basis.

Description: While primary marine aerosol (PMA) is an important part of global aerosol total emissions, its chemical composition and physical flux as a function of the biogeochemical properties of the seawater still remain highly uncharacterized due to the multiplicity of physical, chemical and biological parameters that are involved in the emission process. Here, nutrient enriched-mesocosms filled with Mediterranean seawater were studied over a three-week period. PMA generated from the mesocosm waters were characterized in term of chemical composition, size distribution and size segregated cloud condensation nuclei (CCN), as a function of the seawater chlorophyll-a (Chl-a) concentration, pigment composition, virus and bacteria abundances. In all mesocosms (enriched and control mesocosms), we detected an enrichment of calcium and a deficit in chloride in the submicron PMA mass compared to the literature inorganic composition of the seawater. A positive linear correlation was found between the aerosol number concentration flux and the seawater temperature, that could be specific to the mediteranean seawater temperature and organic content. We found that the artificial phytoplankton bloom did not affect the condensation nuclei (CN) or CCN number concentration, the normalized size distribution, the CCN activation diameter or the organic fraction of the PMA compared to the control mesocosm. However, we observed correlations between the organic fraction of the Aitken mode particles and heterotrophic flagellates, viruses, and dissolved organic carbon (DOC). No correlation between the particle organic fraction and Chl-a was observed, contrary to previous observations in natural bloom mesocosm experiments. We believe that this could be due to (1) different complexities compared to natural bloom systems, or (2) longer time periods needed to observe correlation trends.

Description: We present measurements utilizing the Filter Inlet for Gases and Aerosols (FIGAERO) applied to chamber measurements of isoprene-derived epoxydiol (IEPOX) reactive uptake to aqueous acidic particles and associated SOA formation. Similar to recent field observations with the same instrument, we detect two molecular components desorbing from the IEPOX SOA in high abundance: C5H12O4 and C5H10O3. The thermal desorption signal of the former, presumably 2-methyltetrols, exhibits two distinct maxima, suggesting it arises from at least two different SOA components with significantly different effective volatilities. Isothermal evaporation experiments illustrate that the most abundant component giving rise to C5H12O4 is semi-volatile, undergoing nearly complete evaporation within 1 hour, while the second, less volatile, component remains unperturbed and even increases in abundance. We thus confirm, using controlled laboratory studies, recent analyses of ambient SOA measurements showing that IEPOX SOA is of very low volatility and commonly measured IEPOX SOA tracers, such as 2-methyltetrols and C5-alkene triols, result predominantly from artifacts of measurement techniques associated with thermal decomposition and/or hydrolysis. We further show that IEPOX SOA volatility continues to evolve via acidity enhanced accretion chemistry on the timescale of hours, potentially involving both 2-methyltetrols and organosulfates.

Description: The atmospheric deposition of mercury (Hg) occurs via several mechanisms including dry and wet scavenging by precipitation events. In an effort to understand the atmospheric cycling and seasonal depositional characteristics of Hg, wet deposition samples were collected for approximately five years at 17 selected GMOS monitoring sites located in the Northern and Southern Hemispheres in the framework of the Global Mercury Observation System (GMOS) project. Total mercury (THg) exhibited annual and seasonal patterns in Hg wet deposition samples. Inter-annual differences in total wet deposition are mostly linked with precipitation volume, with the greatest deposition flux occurring in the wettest years. This data set provides a new insight into baseline concentrations of THg concentrations in precipitation worldwide, particularly in regions, such as the Southern Hemisphere and tropical areas where wet deposition as well as atmospheric Hg species were not investigated before, opening the way for future and additional simultaneous measurements across the GMOS network as well as new findings in future modeling studies.

Description: We present an automatic aerosol classification method based solely on 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 un-classified measurement to a pre-defined 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 eight 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 analyse 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 literature further improves the accuracy: the accuracy range is 69–93% from 8 (69%) to 4 (93%) aerosol classes, respectively. 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 centralised processing suite.

Description: Chemical ionization mass spectrometer (CIMS) techniques have been developed that allow for quantitative and composition-resolved measurements of organic compounds as they desorb from secondary organic aerosol (SOA) particles, in particular during their heat-induced evaporation. One such technique employs the Filter Inlet for Gases and AEROsol (FIGAERO). Here, we present a newly-developed model framework with the main aim of reproducing FIGAERO-CIMS thermograms: signal vs. ramped desorption temperature. The model simulates the desorption of organic compounds during controlled heating of filter-sampled SOA particles, plus the subsequent transport of these compounds through the FIGAERO manifold into an iodide-CIMS. Desorption is described by a modified Hertz-Knudsen equation and controlled chiefly by the temperature-dependent saturation concentration C*, mass accommodation (evaporation) coefficient, and particle surface area. Subsequent transport is governed by interactions with filter and manifold surfaces. Reversible accretion reactions (oligomer formation and decomposition) and thermal decomposition are formally described following the Arrhenius relation. We use calibration experiments for tuning instrument-specific parameters, and then apply the model to a test case: measurements of SOA generated from dark ozonolysis of α-pinene. We then discuss the ability of the model to describe thermograms from simple calibration experiments and from complex SOA, and the associated implications for the chemical and physical properties of the SOA. We conclude with specific experimental designs to better constrain instrumental model parameters and to aid in resolving remaining ambiguities in the interpretation of more complex SOA thermogram behaviors. The model allows retrieval of quantitative volatility and mass transport information from FIGAERO thermograms, and for examining the effects of various environmental or chemical conditions on such properties.

Description: We present hourly on-line observations of molecular compositions (CxHyOzN0–1) and abundances of oxygenated organic species in gas and submicron particle phases from April to June of 2014 as part of the Biogenic Aerosols-Effects on Cloud and Climate (BAECC) campaign. Measurements were made using the Filter Inlet for Gases and AEROsols coupled to a high-resolution time-of-flight iodide-adduct ionization mass spectrometer (FIGAERO-CIMS) located atop a 35m tall tower, about 10m above a boreal forest canopy at the SMEAR II research station in Hyytiälä, Finland. Semi-volatile and highly oxygenated multifunctional (HOM) organic species possessing from 1 up to 20 carbon atoms, and with as few as 2 and as many as 16 oxygen atoms were routinely observed. Utilizing non-negative matrix factorization, we determined that 〉90% and 〉99% of the organic mass in the gas and particle phases, respectively, exhibited one of three distinct diel trends; one in which abundances were enhanced at daytime, another in the early morning hours, and thirdly during nighttime. Particulate organic nitrates contributed ∼35% to the total organic aerosol mass loading at night during BAECC, much higher than observed by the same instrument package at a mixed-deciduous forest site that experienced higher nighttime concentrations of nitrogen oxides. Unique HOM monomers (defined here as those with 10 carbon and 7 or more oxygen atoms) and dimers (at least 16 carbon atoms), with and without a nitrogen atom, were found in most of the three subgroups of both phases. We show the potential to connect these groupings of compounds based on their distinct behavior in time to the expected chemical conditions (biogenic VOC precursor, oxidant type, etc.) responsible for their production. A suite of nitrated dimer-like compounds was detected in both the gas and particle phases, suggesting a potential role for the formation of low volatility organics from NO3 radical driven, as well as daytime NO-influenced, monoterpene chemistry.

Description: The implementation of European emission abatement strategies has led to significant reduction in the emission of ozone precursors during the last decade. Ground level ozone is also influenced by meteorological factors such as temperature, which exhibit interannual variability, and are expected to change in the future. The impacts of climate change on air quality are usually investigated through air quality models that simulate interactions between emissions, meteorology and chemistry. Within a multi-model assessment, this study aims to better understand how air quality models represent the relationship between meteorological variables and surface ozone concentrations over Europe. A multiple linear regression (MLR) approach is applied to observed and modelled time series across ten European regions in springtime and summertime for the period of 2000–2010 for both models and observations. Overall, the air quality models are in better agreement with observations in summertime than in springtime, and particularly in certain regions, such as France, Mid-Europe or East-Europe, where local meteorological variables show a strong influence on surface ozone concentrations. Larger discrepancies are found for the southern regions, such as the Balkans, the Iberian Peninsula and the Mediterranean basin, especially in springtime. We show that the air quality models do not properly reproduce the sensitivity of surface ozone to some of the main meteorological drivers, such as maximum temperature, relative humidity and surface solar radiation. Specifically, all air quality models show more limitations to capture the strength of the relationship ozone-relative humidity detected in the observed time series in most of the regions, in both seasons. Here, we speculate that dry deposition schemes in the air quality models might play an essential role to capture this relationship. We further quantify the relationship between ozone and maximum temperature (mo3-T, climate penalty) in observations and air quality models. In summertime, most of the air quality models are able to reproduce reasonably well the observed climate penalty in certain regions such as France, Mid-Europe and North Italy. However, larger discrepancies are found in springtime, where air quality models tend to overestimate the magnitude of observed climate penalty.

Description: Measurements of aerosol composition and size distributions were taken during the summer of 2013 at the remote island of Lampedusa in the southern central Mediterranean Sea. These measurements were part of the ChArMEx/ADRIMED (Chemistry and Aerosol Mediterranean Experiment/Aerosol Direct Radiative Forcing on the Mediterranean Climate) framework and took place during the Special Observation Period 1a (SOP-1a) from 11 June until 5 July 2013. From compact time-of-flight aerosol mass spectrometer (cToF-AMS) measurements in the size range below 1 μm in aerodynamic diameter (PM1), particles were predominately comprised of ammonium and sulphate. On average, ammonium sulphate contributed 63 % to the non-refractory PM1 mass, followed by organics (33 %). The organic aerosol was generally very highly oxidised (f44 values were typically between 0.25 and 0.26). The contribution of ammonium sulphate was generally higher than organic aerosol in comparison to measurements taken in the western Mediterranean but is consistent with studies undertaken in the eastern basin. Source apportionment of organics using a statistical (positive matrix factorisation) model revealed four factors; a hydrocarbon-like organic aerosol (HOA), a methanesulfonic acid related oxygenated organic aerosol (MSA-OOA), a more oxidised oxygenated organic aerosol (MO-OOA) and a less oxidised oxygenated organic aerosol we label (LO-OOA). The MO-OOA was the dominant factor for most of the campaign (53 % of the PM1 OA mass). It was well correlated with SO42−, highly oxidised, and generally more dominant during easterly air masses originating from the eastern Mediterranean and central Europe. The LO-OOA factor had a very similar composition to the MO-OOA factor, but was more prevalent during westerly winds with air masses originating from the Atlantic Ocean, the western Mediterranean, and in high altitudes over France and Spain from mistral winds. The MSA-OOA factor contributed an average 12 % to the PM1 OA and was more dominant during the mistral winds. The HOA, representing observed primary organic aerosol only contributed 8 % of the average PM1 OA during the campaign. Even though Lampedusa is one of the most remote sites in the Mediterranean, PM1 concentrations (10 ± 5 μg m−3) were comparable to those observed in coastal cities and sites closer to continental Europe. Cleaner conditions corresponded to higher wind speeds. Nucleation and growth of new aerosol particles was observed during periods of northwesterly winds. From a climatology analysis from 1999 until 2012, these periods were much more prevalent during the measurement campaign than during the preceding 13 years. These results support previous findings that highlight the importance of different large-scale synoptic conditions in determining the regional and local aerosol composition and oxidation and also suggest that a non-polluted surface atmosphere over the Mediterranean is rare.