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Modeling the dispersion of volcanic particles released during explosive eruptions is crucially dependent on the knowledge of the source term of the eruption and the source strength as a function of altitude and time. Forecasting volcanic ash transport is vital for aviation but rather inaccurate for quantitative predictions of the fate of volcanic particle emissions. Here we demonstrate an inverse modeling framework that couples the output of a Lagrangian dispersion model with remote sensing observations to estimate the emission rates of volcanic particles released from the Etna eruption. We use an inversion algorithm (Tichy et al., 2020) where the distance between the model and observations is optimized under the assumption that the source term is either sparse or smooth. The Bayesian formalism allows the algorithm to estimate these characteristics together with the source term itself and thus normalize the inversion problem. This methodology uses source receptor relationships as an input from the FLEXPART (flexible particle dispersion) model constrained by ground-based Lidar measurements and satellite observations of SO2 and ash emissions. The case study analyzed here refers to the Etna eruption on 12 March 2021, with the volcanic plume being well captured by the lidar measurements of the PANGEA observatory located at Antikythera island in southwest Greece. A dense aerosol layer, suspending in the height range between 7.5 and 12.5 km (19:30 - 21:30 UTC), has been captured by the PollyXT lidar. For the inversion simulations, we also use data acquired by the Spin-stabilised Enhanced Visible and Infrared Imager (SEVIRI) instrument, mounted on the Meteosat Second Generation (MSG) geostationary satellite. The aforementioned observations serve as a priori source information to estimate the volcanic ash and SO2 source strength, depending on altitude and time, coupled with the output of the FLEXPART model. Our results are efficient for real-time application and could supply ash forecasting models with an accurate estimation of the mass rate of very fine ash during explosive eruptions. Improved forecasts of the dispersed volcanic plumes following the suggested inverse modeling framework would then allow for more effective emergency preparedness for aviation to ensure safety during volcanic eruptions. This research was also supported by the following projects: ERC grant D-TECT (agreement no. 725698); EU H2020 E-shape project (Grant Agreement n. 820852); PANCEA project (MIS 502151) under the Action NSRF 2014-2020, co-financed by Greece and the European Union. The research was supported by data and services obtained from the PANhellenic Geophysical Observatory of Antikythera (PANGEA) of the National Observatory of Athens (NOA), Greece. O. Tichy was supported by the Czech Science Foundation, grant no. GA20-27939S. Tichy, O.; Ulrych, L.; Smidl, V.; Evangeliou, N.; Stohl, A. On the tuning of atmospheric inverse methods: comparisons with the European Tracer Experiment (ETEX) and Chernobyl datasets using the atmospheric transport model FLEXPART, Geosci. Model Dev. (2020), 13, 5917-5934.

A broad spectrum of environmental processes such as radiation, cloud formation, ocean fertilization and human health are affected from the presence of mineral dust. The transport of dust particles is dictated by the prevailing meteorological conditions as well as the composition and physiochemical properties of the particles themselves. Which, in turn, are bound to the soil mineralogy at the source region.Numerical weather prediction models can estimate the transport of dust particles, yet a more refined mineralogical categorization can significantly improve the dust transport estimations and increase preparedness for implications on weather, biogeochemistry and health. This novel mineralogical representation is derived from multi-spectral satellite remote sensing sensors (Sentinel 2A) over a limited area around Lake Chad in Sahara desert by taking into account dust particle characteristics such as size, composition and optical properties. The mineralogy map will be implemented in WRF/CHEM model to improve the accuracy of atmospheric simulations. The final product will be juxtaposed against current state-of-the-art mineralogical products such as the NASA’s Earth Surface Mineral Dust Source Investigation (EMIT) mission. Dust transport simulations will be compared against field measurements from Antikythera PANGEA station in the Mediterranean and ASKOS campaign in the Atlantic Ocean.

Forecasting volcanic ash atmospheric pathways is of utmost importance for aviation. Volcanic ash can interfere with aircraft navigational instruments and can damage engine parts. Early warning systems, activated after volcanic eruptions can alleviate the impacts on aviation by providing forecasts of the volcanic ash plume dispersion. The quality of these short-term forecasts is subject to the accuracy of the meteorological wind fields used for the initialization of regional models. Here, we use wind profiling data from the first High Spectral Resolution Lidar in Space, Aeolus, to examine the impact of measured wind fields on regional NWP and subsequent volcanic ash dispersion forecasts, focusing on the case of Etna’s eruption on March 2021. The results from this case study demonstrate a significant improvement of the volcanic ash simulation when using Aeolus-assimilated meteorological fields, with differences in wind speed reaching up to 8 m/s when compared to the control run. When comparing the volcanic ash forecast profiles with downwind surface-based aerosol lidar observations, the modeled field is consistent with the measurements only when Aeolus winds are assimilated. This result clearly illustrates the potential and importance of wind profiling from space for volcanic ash forecasting and hence aviation safety.

In August 2021, a historic heatwave was recorded in Greece which resulted in extreme wildfire events that strongly affected the air quality over the city of Athens. Saharan dust was also transferred over Greece in the same period due to the prevailing southern winds. The impact of these events on air quality and surface solar radiation are investigated in this study. Event characterization based on active and passive remote sensing instrumentation has been performed. The study shows that significantly increased levels of air pollution were recorded during the end of July/first week of August. The smoke led to unusually high AOD values (up to 3.6), high Ångström Exponent (AE) (up to 2.4) and a strong and negative dependence of single scattering albedo (SSA) on wavelength that was observed to decrease from 0.93 at 440 nm to 0.86 at 1020 nm signifying the presence of strong absorbing aerosols. While, the dust event led to high AOD (up to 1.4), low AE (up to 0.9) and positive dependence of SSA on wavelength that was observed to increase from 0.89 at 440 nm to 0.95 at 1020 nm indicating large forward scattering due to coarse particles. Furthermore, the analysis of the smoke aerosol optical properties during the transfer from the source to a distance of about 240 km revealed that the SSA and AE changed significantly during the transfer, which lasted approximately 9 h. The transport of the plume led to an impressive change in the spectral shape of SSA whose value significantly increased pointing to the aging of smoke and the dilution of plumes while the transport. The impact of dust and smoke on spectral solar irradiance reveals significant differences in the spectral shape of attenuation caused by the two different aerosol species. The attenuation of solar irradiance in UV-B irradiance was found to be least in case of dust and highest due to smoke (up to 60 % or more) and intermediate in the case of a mixture of smoke and dust. The attenuation was comparatively less in NIR region (mostly within 20 % but it even reached up to 40 % in the presence of smoke) and VIS region (but greater than NIR region). Also, the AOD variations from climatology led to decrease in UV Index up to 53 %, in vitamin-D up to 50 %, in photosynthetically active radiation up to 21 % and in GHI up to 17 %, with implications on health, agriculture and energy. This study highlights the wider impacts of wildfires that are part of the wider problem of the Mediterranean countries, whose frequency is predicted to increase in view of the projected increasing occurrence of summer heatwaves.

Ice particles in high-altitude cold clouds can obstruct aircraft functioning. Over the last 20 years, there have been more than 150 recorded cases with engine power-loss and damage caused by tiny cloud ice crystals, which are difficult to detect with aircraft radars. Herein, we examine two aircraft accidents for which icing linked to convective weather conditions has been officially reported as the most likely reason for catastrophic consequences. We analyze whether desert mineral dust, known to be very efficient ice nuclei and present along both aircraft routes, could further augment the icing process. Using numerical simulations performed by a coupled atmosphere-dust model with an included parameterization for ice nucleation triggered by dust aerosols, we show that the predicted ice particle number sharply increases at approximate locations and times of accidents where desert dust was brought by convective circulation to the upper troposphere. We propose a new icing parameter which, unlike existing icing indices, for the first time includes in its calculation the predicted dust concentration. This study opens up the opportunity to use integrated atmospheric-dust forecasts as warnings for ice formation enhanced by mineral dust presence.

Dust is the most abundant aerosol worldwide with multiple implications for radiative transfer, cloud processes and air quality. The dust emissions are usually represented in atmospheric models based on static dust source maps and surface wind properties. In operational dust forecasts, the models are commonly configured in warm start mode, meaning that each simulation cycle is initialized by the forecasted dust fields of the previous run. This technique inevitably inserts certain amounts of uncertainty due to the deviation of numerical solutions. In this study we present the development and evaluation of alternative methods for the initialization of dust emissions in the Georgia Tech Goddard Global Ozone Chemistry Aerosol Radiation and Transport of the Air Force Weather Agency (GOCART-AFWA) module of WRF model. First, we implement a time-varying dust source map based on the 16-day average Normalized Difference Vegetation (NDVI) from the MODIS-Terra instrument. Replacing the static dust source map with a dynamic satellite-based emissions map, allows a physically based representation of seasonal and annual variations of initial dust-source strength in the model. Second, we demonstrate the assimilation of dust Aerosol Optical Depth (AOD) satellite retrievals from the MSG/SEVIRI sensor in the Local Analysis and Prediction System (LAPS), for use in WRF model. A 3D-Var assimilation of satellite AOD retrievals from the MSG-SEVIRI instrument is performed in LAPS, similar to the standard assimilation of atmospheric variables. The forecasted WRF dust AOD is used as first-guess field for the generation of the assimilated AOD in LAPS. Finally, the LAPS AOD is used to initialize the WRF simulations, thus nudging the model towards the observational satellite values. Model runs with different configurations of the MODIS-NDVI and MSG-SEVIRI assimilation schemes are performed for the region of North Africa and the greater Mediterranean. First results verify the successful implementation of both assimilation parameterizations in WRF-Chem. The improvements and deviations between the original and the newly developed schemes in GOCART-AFWA are discussed in comparison with the AERONET station measurements of AOD.Acknowledgment This work is supported by the Hellenic Foundation for Research and Innovation project MegDeth (HFRI no.703)

Dust particles larger than 20 µm in diameter (0.2 μm < D < 100 µm) have been regularly observed to remain airborne during long-range transport. In this work we extend the parameterization of mineral dust cycle in the GOCART-AFWA dust scheme of WRFV4.2.1, to include also such coarse and giant particles. The initial particle size distribution in our parameterization is based on observations over desert dust sources and the Stokes’ drag coefficient has also been updated to account for dust particles of all sizes (Re < 105). The new code is applied to simulate dust transport over Cape Verde during the August 2015 AER -D campaign. Model results are evaluated using both airborne dust measurements and the CALIPSO-LIVAS pure dust product. The results show that the modeled lifetimes of the coarser particles are shorter than those observed. Various processes are proposed to explain such inaccuracies, such as the electric field inside dust plumes and non-spherical aerodynamics. Additional sensitivity runs are performed by artificially reducing the settling velocities of the particles to compensate for such underrepresented processes in the model. Our simulations show that particles with diameters of 5–17 μm and 40–100 μm are better represented assuming 80 % reduction in settling velocity (UR80) while particles at the range 17–40 μm are better represented in the UR60 scenario. The overall statistical analysis shows that the UR80 experiment presents the closest agreement with the airborne in situ measurements both in Cape Verde and over the sources. The UR80 experiment improves also the vertical distribution of dust in the model, as compared to the CALIPSO-LIVAS pure dust product. Further research is requested in order to understand the physical processes behind the reduction of settling velocity.

Climate and weather are significant factors in planning to visit a touristic destination, especially taking into consideration the global warming. In this respect, touristic areas will be significantly affected by the potential adverse effects of climate change. This is the case of the Mediterranean which is considered one of the most vulnerable regions in global climate change, regarding the observed but also the expected future thermal risk. The goal of this study is to highlight the bioclimatic conditions anticipated to prevail in the eastern Mediterranean, studying five touristic destinations; namely, Heraklion, Crete Island (Greece), Antalya (Turkey), Limassol (Cyprus), Valletta (Malta) and Cairo (Egypt).One of the most popular and widely applied human thermal index, the Physiologically Equivalent Temperature (PET), based on human energy balance, is utilized to quantify the regime of present and simulated future bioclimatic conditions. Air temperature, humidity, wind speed and global solar radiation (estimated at 1.1m where is the gravity center of the human body and builds the reference level for human biometeorological studies) are the parameters needed for the assessment of PET, using the RayMan model. The meteorological datasets concern 3-hour data from the SMHI RCA4 regional climate model (Rossby Center, Swedish Meteorological and Hydrological Institute, Norrkoping Sweden, spatial analysis 11 km), for the historical period 1971-2000 (reference period), as well as for the periods 2021-2050 and 2071-2100 under the two Representative Concentration Pathways, RCP4.5 (intermediate) and RCP8.5 (extreme).As far as the historical period is concerned, the findings of the analysis showed that Heraklion, Crete Island, appears the most favorable bioclimatic conditions at midday (UTC 12:00), followed by Limassol and Malta, while Cairo and Antalya show high frequency and duration of strong/extreme heat stress within the year. Regarding evening hours (UTC 21:00) during summertime, there is a slight cold stress/thermal comfort in Heraklion and Malta, followed by Limassol, Antalya and Cairo with worse bioclimatic conditions.Based on climate model simulations for 2021-2050 (near future) and 2071-2100 (far future) under RCP4.5 and RCP8.5, for midday (UTC 12:00), Heraklion, Crete Island depicts the best bioclimatic conditions, which can be attributed to the increased frequency and intensity of the Etesians winds, blowing during the summer period of the year contributing to the mitigation of the strong/extreme heat stress. The frequency and the duration of thermal comfort in the evening (UTC 21:00) is expected to increase for both RCPs. Malta shows similar bioclimatic behavior to Heraklion during evening hours, followed by Limassol, Antalya and Cairo, where the light/moderate heat stress occurs with increasing frequency and seasonality.The results of the bioclimatic analysis will help in the management/dissemination of climate information for tourism purposes. In addition, the methodology used, based on bioclimatic (PET) diagrams, can provide detailed information in order to assess and quantify the climate change impacts on the tourism potential in the eastern Mediterranean.

The proper representation of dust production in numerical weather prediction (NWP) models depends largely on the detailed mapping of the arid areas that act as natural dust sources. The extend and the strength of these sources varies throughout the year based on aridity and vegetation properties. Such changes are monitored from spaceborne platforms (e.g. MODIS NDVI index). In this work we present a methodology for including a dynamic dust source map in the state-of-the-art NMME-DREAM and WRF-Chem models. This time-varying dust source map is based on the 1000m 16-day averaged Normalized Difference Vegetation (NDVI) from the MODIS/Terra instrument. The methodology is first tested with DREAM-NMM over the Arabian Peninsula. The results indicate significant improvement in simulated AODs over AERONET stations compared to the runs driven by the standard static dust source map. The modeled AOD bias in NMME-DREAM is improved from -0.140 to 0.083 for AOD>0.25 and from -0.933 to -0.424 for dust episodes with AOD> 1. Afterwards we apply the above methodology to the Air Force Weather Agency (AFWA) dust emission module in WRF-Chem model. WRF-Chem has been selected due to its nesting capabilities that permit finer resolution simulations of local scale dust processes. Two sets of simulations have been performed covering the entire Saharan desert, the Mediterranean, Europe and part of the Arabian Peninsula, at a horizontal resolution of 12×12 Km: (1) WRF-Chem control simulations, where dust sources are defined based on the original AFWA code and (2) WRF-Chem experimental simulations where the erodibility of the selected domain is modified based on MODIS NDVI. The selected test period is April 2017 when significant Saharan dust outbreaks took place over the Mediterranean. The simulated AOD from both sets of model runs are validated against AERONET stations. First results verify the successful implementation of the dynamic dust source module in WRF-Chem. The experimental (NDVI) simulations showed an overall increase in dust loads over the entire domain and an improved performance, mostly in areas close to the Saharan desert.

Aerosol and cloud condensate nuclei (CCN) measurements in the area of Athens during HyGRA-CD campaign (May–June 2014) identified a significant diversity in particle properties. In this study we select two distinct cases in terms of meteorology and air mass origin in order to analyze the transport mechanisms inside the Planetary Boundary Layer (PBL) and in the free troposphere and discuss the possible contribution of aerosol in cloud formation. The detection of aerosol layers was based on the lidar technique using multi-wavelength detection schemes. The first case is characterized by a double dust layer arriving over Athens with a shallow and younger plume centered at about 1.8 km and a deeper and more aged plume centered at 3.4 km. These layers originate from different sources and follow different transport paths in the atmosphere which explains also their different optical/geometrical properties. The second case is typical of frontal activity and low cloud formation during daytime. Low level convergence of maritime and continental air masses enhances the updraft velocities inside Athens basin and results in CCN activation and cloud formation along the frontal line.

Ice particles in high-altitude cold clouds can obstruct aircraft functioning. Over the last 20 years, there have been more than 150 recorded cases with engine power-loss and damage caused by tiny cloud ice crystals, which are difficult to detect with aircraft radars. Herein, we examine two aircraft accidents for which icing linked to convective weather conditions has been officially reported as the most likely reason for catastrophic consequences. We analyze whether desert mineral dust, known to be very efficient ice nuclei and present along both aircraft routes, could further augment the icing process. Using numerical simulations performed by a coupled atmosphere-dust model with an included parameterization for ice nucleation triggered by dust aerosols, we show that the predicted ice particle number sharply increases at approximate locations and times of accidents where desert dust was brought by convective circulation to the upper troposphere. We propose a new icing parameter which, unlike existing icing indices, for the first time includes in its calculation the predicted dust concentration. This study opens up the opportunity to use integrated atmospheric-dust forecasts as warnings for ice formation enhanced by mineral dust presence.

Year-round carbon dioxide (CO2) and methane (CH4) concentration measurements, performed for the first time in the city of Athens, Greece from December 21, 2018 to December 31, 2019, are presented in this study and analyzed in relation to atmospheric circulation patterns at a local, regional and long-range transport scale. Clear diurnal and seasonal variations of both greenhouse gases were detected. The observed increased levels during night and early morning hours are attributed to traffic/heating emissions and leakages of residential natural gas for CO2 and CH4, respectively. Using CO2 and CH4 levels simultaneously measured at the regional background site at Finokalia (Greece), increments in their levels due to local and regional anthropogenic sources within the city were assessed. For CO2, maximum and minimum increments were clearly observed during winter and summer respectively, suggesting a greater impact of combustion of fossil fuel and especially of biomass on CO2 levels during winter. On the other hand, CH4 increments were similar in all seasons, suggesting that local sources of CH4 remain quite constant year-round. Through the implementation of the Conditional Probability Function (CPF), the emission sources of theses greenhouse gases have been localized to the northern and the eastern domains of the Athens basin. Stagnant atmospheric conditions were also associated with an increased likelihood of CO2 and CH4 episodes. Backward modeling simulations with FLEXPART and HYSPLIT models indicate an industrial zone and a petrochemical zone, situated to the north and to the west of Athens respectively, as possible CH4 regional sources as well as possible CO2 contributions from southern directions attributed to shipping emissions from the port of Piraeus. The present study provides knowledge needed for the determination of greenhouse gas emission mitigation strategies in Athens.

In the last years, several Etna eruption events are documented, forming lava flows and explosive activity. The Pilot EO4D_ash – Earth observation data for detection, discrimination & distribution (4D) of volcanic ash of the e-shape project provides the PANhellenic GEophysical observatory of Antikythera (PANGEA) of the National Observatory of Athens (NOA), in Greece with near-real-time alerts from Etna volcano eruptions. These alerts are used in the PANGEA station to monitor and reveal the presence of volcanic particles above the area the days following an eruption, also the station is supported by a volcanic particle monitoring and forecasting warning system. In this work, we investigate the volcano eruption between 30 May and 6 June 2019 which affected the southern parts of Greece and reaching the Antikythera station. Due to the prevailing meteorological conditions, volcanic particles and gases followed an easterly direction and were dispersed towards Greece. FLEXPART dispersion model simulations confirm the volcanic plume transport from Etna towards PANGEA, mixing also with co-existing desert dust particles. Model simulations are evaluated with PollyXT lidar measurements performed at PANGEA and satellite-based SO2 observations from the TROPOspheric Monitoring Instrument onboard the Sentinel-5 Precursor (TROPOMI/S5P). This is the first time that Etna volcanic products are monitored at the Antikythera station, in Greece with implications for the investigation of their role in the Mediterranean weather and climate.Acknowledgments: We acknowledge the support by EU H2020 E-shape project (Grant Agreement n. 820852). Also, this research was supported by data and services obtained from the PANhellenic Geophysical Observatory of Antikythera (PANGEA) of the National Observatory of Athens (NOA), Greece, and by the project “PANhellenic infrastructure for Atmospheric Composition and climatE change” (MIS 5021516) which is implemented under the Action “Reinforcement of the Research and Innovation Infrastructure”, funded by the Operational Programme "Competitiveness, Entrepreneurship and Innovation" (NSRF 2014-2020) and co-financed by Greece and the European Union (European Regional Development Fund). NOA team acknowledges the support of the Stavros Niarchos Foundation (SNF).

International audience; We use the Generalized Retrieval of Aerosol Surface Properties algorithm (GRASP) to compare with dust concentration profiles derived from the NMME-DREAM model for a specific dust episode. The GRASP algorithm provides the possibility of deriving columnar and vertically-resolved aerosol properties from a combination of lidar and sun-photometer observations. Herein, we apply GRASP for analysis of a Saharan dust outburst observed during the “PREparatory: does dust TriboElectrification affect our ClimaTe” campaign (PreTECT) that took place at the North coast of Crete, at the Finokalia ACTRIS station. GRASP provides column-averaged and vertically resolved microphysical and optical properties of the particles. The retrieved dust concentration profiles are compared with modeled concentration profiles derived from the NMME-DREAM dust model. To strengthen the results, we use dust concentration profiles from the POlarization-LIdar PHOtometer Networking method (POLIPHON). A strong underestimation of the maximum dust concentration is observed from the NMME-DREAM model. The reported differences between the retrievals and the model indicate a high potential of the GRASP algorithm for future studies of dust model evaluation.

Downslope winds and lee gravity waves are common features of mountainous environments. A similar weather type at Mt. Parnassos in Arachova, Greece is known as “Katevatos” and has devastating results for the population and visitors at the local touristic resorts. In this study, we analyze three incidents of this atmospheric pattern at local scale resolution (1 x 1 km) with WRF model. This is the first study of this local weather hazard, and the following key factors are identified. (I) The main synoptic forcing is the propagation of an upper-level trough from central Europe towards the Balkans. (II) The associated generation of a surface low-pressure system over the Aegean Sea results in a northeast flow in the lower troposphere that is perpendicular to the main topographic ridge of Mt. Parnassos. (III) Generation of gravity waves and downward reflection of wave energy at the critical level between the upper level flow and the undercutting northeast current result in the formation of “Katevatos” downslope wind at the lee side of the mountain. This hurricane-scale wind is accompanied with horizontal transport of frozen rain and snow from the mountain tops towards the village of Arachova. This wind pattern appeared also during the battle of Arachova in November 1826 between the Greek and Ottoman forces resulting in enormous casualties due to the adverse weather conditions.

Between 30 May and 6 June 2019 a series of new flanks eruptions interested the south-east flanks of Mt. Etna, Italy, forming lava flows and explosive activity that was most intense during the first day of the eruption, as a result, volcanic particles were dispersed towards Greece. Lidar measurements performed at the PANhellenic GEophysical observatory of Antikythera (PANGEA) of the National Observatory of Athens (NOA), in Greece, reveal the presence of particles of volcanic origin above the area the days following the eruption. FLEXible PARTicle dispersion model (FLEXPART) simulations and satellite-based SO2 observations from the TROPOspheric Monitoring Instrument onboard the Sentinel-5 Precursor (TROPOMI/S5P), confirm the volcanic plume transport from Etna towards PANGEA and possible mixing with co-existing desert dust particles. Lidar and modeled values are in agreement and the derived sulfate mass concentration is approximately 15 &mu, g/m3. This is the first time that Etna volcanic products are monitored at Antikythera station, in Greece with implications for the investigation of their role in the Mediterranean weather and climate.

Volcanic eruptions have the capacity to significantly impact human life, consequently, tools for mitigating them are of high importance. The early detection of a potentially hazardous volcanic eruption and the issuance of early warnings concerning volcanic hazards (e.g. ash dispersal), are key elements in the initiation of operational response procedures. Historically, lidars have not typically played a key operational role during volcanic eruptions, with other remote sensing instruments such as radars, infrared and ultraviolet cameras being preferred. Recently, a tailored product of the European Aerosol Research Lidar Network (EARLINET) for the early warning of the presence of volcanic ash and desert dust plumes at cruising altitudes has been developed. Here, we extend the applicability of this methodology to lidars and ceilometers near active volcanoes in Iceland and Mt. Etna in Italy. The tailored methodology and selected case studies will be presented, demonstrating its potential for real-time application during volcanic eruptions.Acknowledgements: This work has been conducted within the framework of the E-shape (Grant Agreement n. 820852) and EUNADICS-AV (Grant agreement no. 723986) H2020 projects. Furthermore, the authors acknowledge the ACTRIS-2 and ACTRIS Preparatory Phase projects that have received funding from the European Union’s Horizon 2020 research and innovation programme (grant agreement No. 654109) and from European Union’s Horizon 2020 Coordination and Support Action (grant agreement No. 739530), respectively.

Air pollution models play an important role in science because of their capability to give a description of the air quality problem including an analysis of factors and causes (emission sources, meteorological processes, and physical and chemical changes). Real-time forecast of urban air quality is highly important to the public as advanced information for both air quality and safety assessment. This study presents the development of a regional scale high-resolution modeling system for simulating air quality and forecasting changes in urban pollution levels. The air quality system based on the state-of-the-art Weather Research and Forecasting model coupled with chemistry (WRF-Chem) has been applied over the greater area of Thessaloniki, Greece. The model performance, in terms of simulated surface major air pollutants’ concentrations, is evaluated using ground-based measurements during the operational implementation period in winter-spring 2020. Our study highlights the importance of resolving local scale atmospheric conditions such as surface wind flow and boundary layer properties for describing the pollutants’ concentrations and the importance of constraining emissions over the study area.

The ability of three-dimensional dust models to accurately represent the dust life cycle is crucial for describing dust effects on radiation and clouds and for reducing the uncertainties on these processes. To improve the reliabilty of dust models, it is therefore imperative to carry out thorough evaluations of the dust properties. Dust optical and microphysical properties are accurately accessed through groundbased observations: multiwavelength lidars and sunphotometers. In this study we use the Generalized Retrieval of Atmospheric and Surface Properties (GRASP) data algorithm that combines the lidar and sunphotometer data to retrieve dust properties. GRASP is applied on a Saharan dust episode over Finokalia, Crete in Greece, on 14 May 2017. More precisely the measurements from PollyXT lidar participating in the European Aerosol Research Network (EARLINET) and the CIMEL sunphotometer participating in Aerosol Robotic Network (AERONET) are synergetically combined using the GRASP algorithm. The dust event is fully characterised through the retrieval of dust optical and microphysical properties. The retrieved properties are found to be in good agreement with the initial measurements from the AERONET sunphotometer and the lidar. Then the aforementioned tools are used to evaluate the performance of the regional dust model NMME-DREAM that has been developed to simulate and predict the atmospheric cycle of mineral dust aerosols. It is shown that the model has problems in simulating the high dust concentration values at low levels, probably due to the low spatial resolution of the model that causes difficulties in capturing the orography and the downdrafts winds.

In this paper we validate the Lidar-Radiometer Inversion Code (LIRIC) retrievals of the aerosol concentration in the fine mode, using the airborne aerosol chemical composition dataset obtained over the Greater Athens Area (GAA) in Greece, during the ACEMED campaign. The study focuses on the 2nd of September 2011, when a long-range transported smoke layer was observed in the free troposphere over Greece, in the height range from 2 to 3 km. CIMEL sun-photometric measurements revealed high AOD (~ 0.4 at 532 nm) and Ångström exponent values (~ 1.7 at 440/870 nm), in agreement with coincident ground-based lidar observations. Airborne chemical composition measurements performed over the GAA, revealed increased CO volume concentration (~ 110 ppbv), with 57% sulphate dominance in the PM1 fraction. For this case, we compare LIRIC retrievals of the aerosol concentration in the fine mode with the airborne Aerosol Mass Spectrometer (AMS) and Passive Cavity Aerosol Spectrometer Probe (PCASP) measurements. Our analysis shows that the remote sensing retrievals are in a good agreement with the measured airborne in-situ data from 2 to 4 km. The discrepancies observed between LIRIC and airborne measurements at the lower troposphere (below 2 km), could be explained by the spatial and temporal variability of the aerosol load within the area where the airborne data were averaged along with the different time windows of the retrievals. © 2016 Elsevier B.V.

Aerosols that are efficient ice-nucleating particles (INPs) are crucial for the formation of cloud ice via heterogeneous nucleation in the atmosphere. The distribution of INPs on a large spatial scale and as a function of height determines their impact on clouds and climate. However, in situ measurements of INPs provide sparse coverage over space and time. A promising approach to address this gap is to retrieve INP concentration profiles by combining particle concentration profiles derived by lidar measurements with INP efficiency parameterizations for different freezing mechanisms (immersion freezing, deposition nucleation). Here, we assess the feasibility of this new method for both ground-based and spaceborne lidar measurements, using in situ observations collected with unmanned aerial vehicles (UAVs) and subsequently analyzed with the FRIDGE (FRankfurt Ice nucleation Deposition freezinG Experiment) INP counter from an experimental campaign at Cyprus in April 2016. Analyzing five case studies we calculated the cloud-relevant particle number concentrations using lidar measurements (n250,drywith an uncertainty of 20 % to 40 % andSdrywith an uncertainty of 30 % to 50 %), and we assessed the suitability of the different INP parameterizations with respect to the temperature range and the type of particles considered. Specifically, our analysis suggests that our calculations using the parameterization ofUllrich et al.(2017)(applicable for the temperature range−50to−33 ∘C) agree within 1order of magnitude with the in situ observations ofnINP; thus, the parameterization ofUllrich et al.(2017)can efficiently address the deposition nucleation pathway in dust-dominated environments. Additionally, our calculations using the combination of the parameterizations ofDeMott et al.(2015,2010)(applicable for the temperature range−35 to−9 ∘C) agree within 2orders of magnitude with the in situ observations of INP concentrations (nINP) and can thus efficiently address the immersion/condensation pathway of dust and nondust particles. The same conclusion is derived from the compilation of the parameterizations ofDeMott et al.(2015)for dust andUllrich et al.(2017)for soot. Furthermore, we applied this methodology to estimate the INP concentration profiles before and after a cloud formation, indicating the seeding role of the particles and their subsequent impact on cloud formation and characteristics. More synergistic datasets are expected to become available in the future from EARLINET (European Aerosol Research Lidar Network) and in the frame of the European ACTRIS-RI (Aerosols, Clouds, and Trace gases Research Infrastructure). Our analysis shows that the developed techniques, when applied on CALIPSO (Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observations) spaceborne lidar observations, are in agreement with the in situ measurements. This study gives us confidence for the production of global 3-D products of cloud-relevant particle number concentrations (n250,dry,SdryandnINP) using the CALIPSO 13-year dataset. This could provide valuable insight into the global height-resolved distribution of INP concentrations related to mineral dust, as well as possibly other aerosol types.