Search Results
Regional effects of atmospheric aerosols on temperature: An evaluation of an ensemble of online coupled models
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.
A European aerosol phenomenology -4: Harmonized concentrations of carbonaceous aerosol at 10 regional background sites across Europe
Although particulate organic and elemental carbon (OC and EC) are important constituents of the suspended atmospheric particulate matter (PM), measurements of OC and EC are much less common and more uncertain than measurements of e.g. the ionic components of PM. In the framework of atmospheric research infrastructures supported by the European Union, actions have been undertaken to determine and mitigate sampling artefacts, and assess the comparability of OC and EC data obtained in a network of 10 atmospheric observatories across Europe. Positive sampling artefacts (from 0.4 to 2.8 μg C/m3) and analytical discrepancies (between −50% and +40% for the EC/TC ratio) have been taken into account to generate a robust data set, from which we established the phenomenology of carbonaceous aerosols at regional background sites in Europe. Across the network, TC and EC annual average concentrations range from 0.4 to 9 μg C/m3, and from 0.1 to 2 μg C/m3, respectively. TC/PM10 annual mean ratios range from 0.11 at a Mediterranean site to 0.34 at the most polluted continental site, and TC/PM2.5 ratios are slightly greater at all sites (0.15–0.42). EC/TC annual mean ratios range from 0.10 to 0.22, and do not depend much on PM concentration levels, especially in winter. Seasonal variations in PM and TC concentrations, and in TC/PM and EC/TC ratios, differ across the network, which can be explained by seasonal changes in PM source contributions at some sites.
Source apportionment of the organic aerosol over the Atlantic Ocean from 53° N to 53° S: Significant contributions from marine emissions and long-range transport
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.
Three-dimensional evolution of Saharan dust transport towards Europe based on a 9-year EARLINET-optimized CALIPSO dataset
In this study we use a new dust product developed using CALIPSO (Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observation) observations and EARLINET (European Aerosol Research Lidar Network) measurements and methods to provide a 3-D multiyear analysis on the evolution of Saharan dust over North Africa and Europe. The product uses a CALIPSO L2 backscatter product corrected with a depolarization-based method to separate pure dust in external aerosol mixtures and a Saharan dust lidar ratio (LR) based on long-term EARLINET measurements to calculate the dust extinction profiles. The methodology is applied on a 9-year CALIPSO dataset (2007-2015) and the results are analyzed here to reveal for the first time the 3-D dust evolution and the seasonal patterns of dust over its transportation paths from the Sahara towards the Mediterranean and Continental Europe. During spring, the spatial distribution of dust shows a uniform pattern over the Sahara desert. The dust transport over the Mediterranean Sea results in mean dust optical depth (DOD) values up to 0.1. During summer, the dust activity is mostly shifted to the western part of the desert where mean DOD near the source is up to 0.6. Elevated dust plumes with mean extinction values between 10 and 75 Mm-1 are observed throughout the year at various heights between 2 and 6 km, extending up to latitudes of 40° N. Dust advection is identified even at latitudes of about 60° N, but this is due to rare events of episodic nature. Dust plumes of high DOD are also observed above the Balkans during the winter period and above northwest Europe during autumn at heights between 2 and 4 km, reaching mean extinction values up to 50 Mm-1. The dataset is considered unique with respect to its potential applications, including the evaluation of dust transport models and the estimation of cloud condensation nuclei (CCN) and ice nuclei (IN) concentration profiles. Finally, the product can be used to study dust dynamics during transportation, since it is capable of revealing even fine dynamical features such as the particle uplifting and deposition on European mountainous ridges such as the Alps and Carpathian Mountains.
A European aerosol phenomenology-5: Climatology of black carbon optical properties at 9 regional background sites across Europe
A reliable assessment of the optical properties of atmospheric black carbon is of crucial importance for an accurate estimation of radiative forcing. In this study we investigated the spatio-temporal variability of the mass absorption cross-section (MAC) of atmospheric black carbon, defined as light absorption coefficient (σap) divided by elemental carbon mass concentration (mEC). σap and mEC have been monitored at supersites of the ACTRIS network for a minimum period of one year. The 9 rural background sites considered in this study cover southern Scandinavia, central Europe and the Mediterranean. σap was determined using filter based absorption photometers and mEC using a thermal-optical technique. Homogeneity of the data-set was ensured by harmonization of all involved methods and instruments during extensive intercomparison exercises at the European Center for Aerosol Calibration (ECAC). Annual mean values of σap at a wavelength of 637 nm vary between 0.66 and 1.3 Mm−1 in southern Scandinavia, 3.7–11 Mm−1 in Central Europe and the British Isles, and 2.3–2.8 Mm−1 in the Mediterranean. Annual mean values of mEC vary between 0.084 and 0.23 μg m−3 in southern Scandinavia, 0.28–1.1 in Central Europe and the British Isles, and 0.22–0.26 in the Mediterranean. Both σap and mEC in southern Scandinavia and Central Europe have a distinct seasonality with maxima during the cold season and minima during summer, whereas at the Mediterranean sites an opposite trend was observed. Annual mean MAC values were quite similar across all sites and the seasonal variability was small at most sites. Consequently, a MAC value of 10.0 m2 g−1 (geometric standard deviation = 1.33) at a wavelength of 637 nm can be considered to be representative of the mixed boundary layer at European background sites, where BC is expected to be internally mixed to a large extent. The observed spatial variability is rather small compared to the variability of values in previous literature, indicating that the harmonization efforts resulted in substantially increased precision of the reported MAC. However, absolute uncertainties of the reported MAC values remain as high as ± 30–70% due to the lack of appropriate reference methods and calibration materials. The mass ratio between elemental carbon and non-light-absorbing matter was used as a proxy for the thickness of coatings around the BC cores, in order to assess the influence of the mixing state on the MAC of BC. Indeed, the MAC was found to increase with increasing values of the coating thickness proxy. This provides evidence that coatings do increase the MAC of atmospheric BC to some extent, which is commonly referred to as lensing effect.
Novel insights on new particle formation derived from a pan-european observing system
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.
An assessment of aerosol optical properties from remote-sensing observations and regional chemistry-climate coupled models over Europe
Atmospheric aerosols modify the radiative budget of the Earth due to their optical, microphysical and chemical properties, and are considered one of the most uncertain climate forcing agents. In order to characterise the uncertainties associated with satellite and modelling approaches to represent aerosol optical properties, mainly aerosol optical depth (AOD) and Ångström exponent (AE), their representation by different remote-sensing sensors and regional online coupled chemistry-climate models over Europe are evaluated. This work also characterises whether the inclusion of aerosol-radiation (ARI) or/and aerosol-cloud interactions (ACI) help improve the skills of modelling outputs. Two case studies were selected within the EuMetChem COST Action ES1004 framework when important aerosol episodes in 2010 all over Europe took place: a Russian wildfire episode and a Saharan desert dust outbreak that covered most of the Mediterranean Sea. The model data came from different regional air-quality-climate simulations performed by working group 2 of EuMetChem, which differed according to whether ARI or ACI was included or not. The remote-sensing data came from three different sensors: MODIS, OMI and SeaWIFS. The evaluation used classical statistical metrics to first compare satellite data versus the ground-based instrument network (AERONET) and then to evaluate model versus the observational data (both satellite and ground-based data). Regarding the uncertainty in the satellite representation of AOD, MODIS presented the best agreement with the AERONET observations compared to other satellite AOD observations. The differences found between remote-sensing sensors highlighted the uncertainty in the observations, which have to be taken into account when evaluating models. When modelling results were considered, a common trend for underestimating high AOD levels was observed. For the AE, models tended to underestimate its variability, except when considering a sectional approach in the aerosol representation. The modelling results showed better skills when ARI+ACI interactions were included; hence this improvement in the representation of AOD (above 30 % in the model error) and AE (between 20 and 75 %) is important to provide a better description of aerosol-radiation-cloud interactions in regional climate models.
An automatic observation-based aerosol typing method for EARLINET
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.