AERONET (AErosol RObotic NETwork) is a global network of ground-based sun–sky photometers that provides aerosol optical and radiative properties of more than 200 sites around the globe . The most widely used product of AERONET is the spectral aerosol optical depth (AOD), which is derived from direct sun irradiance measurements at wavelengths from 440 to 1640 nm and is proportional to the amount of aerosol in the atmospheric column. The spectral dependency of the AOD is expressed in terms of the scattering Ångström exponent (AE), which is an indicator of the aerosol particle size. In addition, AERONET measures sky radiances at different sky geometries, which are used in combination with AOD measurements to retrieve microphysical and optical aerosol properties using inversion algorithms . Its long-term, high-quality, and globally distributed observations have been instrumental in studying dust variability and aerosol properties across diverse regions .

In this study, data products from Level 1.5 Version 3.0 (v3) AERONET retrievals have been used. This decision is made against Level 2 data in order to achieve better data availability. For Level 1.5 products, as full re-calibration may not yet have been applied, we expect slightly larger uncertainties than Level 2.0 (0.01–0.02), with more relative impact in low AOD cases. AOD and AE data are primarily used to identify intense dust events in the Mediterranean basin. In addition, some inversion properties like the single scattering albedo (SSA), asymmetry parameter (ASY), and particle size distribution (PSD) are further analyzed to examine the evolution of the optical and microphysical aerosol properties.

More specifically, ASY is the integral of the energy distribution (phase function) weighted by the angle of scattering. Its value varies between -1 and 1, depending on whether the scattering is perfectly backward or forward with respect to the direction of incidence. It takes the value of zero in the case of isotropic scattering, which would correspond to scattering from gas molecules (Rayleigh scattering). For dust particles, which are 3 orders of magnitude larger in size, typical values are between 0.6 and 0.8 (e.g., ). The asymmetry factor is wavelength-dependent, providing insight into aerosol size and type. Higher values of the asymmetry parameter are associated with the presence of larger particles .

SSA describes the scattering efficiency of particles, such as aerosols or clouds, relative to the total extinction (scattering + absorption) of light. Particles with SSA ≃1, e.g., like sulfate aerosols, reflect sunlight and have a cooling effect, while highly absorbing particles (SSA ≃0.2), such as black carbon, contribute to warming by converting sunlight into heat. Aerosols with intermediate properties, like organic carbon or dust, can have varying climate direct impacts depending on their altitude and the surface albedo underlying them.

Finally PSD provides a quantitative description of aerosol concentrations across different particle sizes, which is important for understanding the mixture of fine and coarse particles during dust events.

For the inversions, the residual sky error was selected to be less than 6 %. A higher value for the sky error value than the commonly used 5 % threshold is chosen, as it is observed that 5 % cuts off a significant number of valid retrievals, as also mentioned in .

The MIDAS dataset, a MODIS-based dust aerosol product described by , provides global estimates of dust optical depth (DOD) on a high-resolution 0.1° × 0.1° grid. It is derived from MODIS-Aqua (and more recently MODIS-Terra) AOD retrievals, combined with dust fraction information from the MERRA-2 reanalysis. The original dataset spanned from 2003 to 2017 and has recently been extended to 2023. Only high-quality MODIS retrievals are used, after filtering for cloud contamination and applying standard quality assurance criteria. Validation of the dataset was performed through comparison with AERONET observations, showing strong agreement and minimal bias. This validation confirms the accuracy of the MIDAS product in representing dust aerosols, particularly over key dust regions such as North Africa and the Middle East. MIDAS offers significant advancements compared with existing datasets, with higher spatial resolution and more accurate dust-specific retrievals. Since its development, the dataset has been applied across a range of studies, including studies on dust climatology to modeling of emission and transport processes , as well as studies of dust impacts on solar energy production .

In this study, MIDAS is used to map the spatial extent and intensity of selected dust events over the Mediterranean by calculating daily mean DOD and AOD values at 550 nm at 0.1° × 0.1° resolution. These observations support the identification of the most affected regions and enable estimates of the dust fraction in the total aerosol load through DOD-to-AOD ratios. Maps of DOD overlaid with station locations are shown in Appendix .

To complement the observational analysis, we employ the METAL-WRF modelling system, which simulates the distribution of dust mineral fractions in the atmosphere . METAL-WRF couples the GOCART-AFWA dust emission scheme with prognostic tracers for nine mineral species – illite, kaolinite, smectite, calcite, quartz, feldspar, hematite, gypsum, and phosphorus – plus iron. Mineral fractions of the source regions are taken from the high-resolution GMINER30 and FERRUM30 databases. In the model, each mineral is treated as an independent prognostic scalar , allowing its full life cycle – emission, transport, gravitational settling, diffusion, and wet scavenging – to be explicitly resolved. This approach enables the airborne mineral mixture to evolve both spatially and temporally, producing spatially explicit fields of mineral-specific dust mass that can be used to trace source fingerprints and their evolution during Mediterranean transport.

The study uses ground-based in situ measurements recorded at the Cyprus Atmospheric Observatory (CAO) in Agia Marina Xyliatou, operated by the Climate and Atmosphere Research Centre (CARE-C) of the Cyprus Institute (CyI), to compare dust concentrations, elemental composition, and dust absorption during these events. PM₁₀ and PM_2.5 were measured at Agia Marina Xyliatou using pre- and post-weighted filters, providing insights into the temporal variation of the particulate matter (PM) levels. Applying acid digestion on integrated daily samples combined with inductively coupled plasma-mass spectrometer (ICP-MS) analysis on parts of the samples, the elemental composition could be directly estimated . Based on the method described in , dust concentrations were estimated by indirectly calculating Si and CO32- using the following empirical relationships: 1SiO2=3×Al2O32CO32-=1.5×Ca+2.5×Mg The absorption coefficient for the dust events is calculated using observations from two Aethelometers instruments (model AE33, Magee Scientific, USA) installed at CAO Agia Marina Xyliatou. The AE33 determines the light attenuation coefficient (bATN) by continuously collecting particles on a filter tape and measuring the change in optical transmission between a clear and a clean part and a sampled spot.

Two different inlet configurations were used to investigate size-resolved absorption properties. One AE33 was equipped with a PM₁ cyclone providing the submicron absorption coefficient. The second instrument was connected to a virtual impactor (VI), which enhances the coarse particle fraction by concentrating particles larger than approximately 2.5 µm in the minor flow. This setup allows the characterization of dust-dominated absorption associated with coarse-mode particles.

The dust absorption is then defined by subtracting the submicron absorption from the VI absorption following the methodology described in : 3babs,PM10-1=babs,VI-babs,PM1EF, where EF is the enhancement factor describing the enrichment of the coarse fraction in VI.

During the 2021 Cyprus Fall Campaign, carried out from 18 October to 18 November, the Unmanned Systems Research Laboratory (USRL, ) of the Cyprus Institute (CyI) utilized UAVs equipped with advanced instruments like OPCs and impactors to collect samples, alongside ground-based remote sensing and in situ instrumentation of the CAO of the CyI. The study investigated the microphysical and optical characteristics of mineral dust transported over Cyprus. For the sample collection at different altitudes, a 3D-printed miniaturized version of the Giant Particle Collector (GPAC or impactors) was deployed on the UAVs. Overall, the Scanning Electron Microscope (SEM) analysis of these samples identified silicates as the dominant component, with Ca-rich materials and clay minerals also present in significant proportions.

The vertical distribution of dust particles was estimated using European Aerosol Research Lidar Network (EARLINET; ) measurements from stations co-located with or located sufficiently close to the AERONET sites listed in Table , performed on the peak date of the event, as reported in the same table. For each measurement, the particle backscatter coefficient and the particle depolarization ratio were used to retrieve the dust backscatter coefficient profile. In particular, the dust component was separated from the total aerosol backscatter profile based on depolarization ratio values, following the methodology described by . The altitude of the dust layer was then determined by identifying the level at which the dust backscatter coefficient reached its maximum value, indicating the highest dust concentration (see Appendix ).

Aerosol optical properties profiles provided by Cloud–Aerosol Lidar with Orthogonal Polarization (CALIOP), the primary instrument onboard the Cloud–Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO; ) satellite, were applied under a similar approach, towards addressing the four-dimensional structure of dust aerosol layers transported over the broader Mediterranean region. More specifically, vertical profiles of dust extinction coefficient at 532 nm and total aerosol particulate depolarisation ratio at 532 nm, as well as peak height of the atmospheric dust component along the CALIPSO orbit path, were extracted by the European Space Agency (ESA) “LIdar climatology of Vertical Aerosol Structure” (LIVAS) dust climate data record and analysed as in the example seen in Fig.  (see Appendix ).

The IASI-MAPIR dataset (version 5.11, available at 10.18758/f7el2zbr, ) was used to independently identify and characterize the dust events. Specifically, the retrieved dust vertical profiles and integrated dust AOD were employed to (i) confirm the presence of mineral dust over the study region, (ii) determine the spatial extent of the dust plumes, and (iii) estimate the altitude of the dust layers upon arrival at the affected stations (Appendix ).

The dataset is particularly valuable because the thermal infrared retrieval allows direct separation of mineral dust from other aerosols without requiring post-processing. Although subject to some limitations in quality control (e.g., the data set is “cloud-free” only, sensitivity is reduced at low AOD, and when the surface and the dust layer are at similar temperatures), these data contribute valuable insight into the intensity, spatial spread, and vertical extent of dust plumes at the affected stations.

The Hybrid Single-Particle Lagrangian Integrated Trajectory (HYSPLIT) model was run with using Global Data Assimilation System (GDAS) meteorological reanalysis fields at approximately 50 km resolution to investigate the trajectories of observed airmasses over the stations affected by dust events. Grid ensemble 120 h backtrajectories were computed from each station arriving at the date, time, and altitude of the observed dust event. A set of trajectories is automatically calculated around a cube (3-dimensional), centered on the initial point. The cube comprises 27 points across three planes, with nine trajectories per plane located at a vertical spacing of ± 250 m. The horizontal spacing of these trajectories is 1° in latitude (∼111 km) and 1° in longitude (∼111 km ⋅ cosine latitude).

Figure  shows the relation between AOD at 500 nm and AE 440–675 nm, for the peak date at each station, during each event, which combined provides insight on the intensity and composition of each of the events at different locations. The AE parameter provides aerosol particle size; the lower this parameter is the bigger the particle size. Coarse particles usually present AE values below 1 since they have a lower spectral dependency. In particular, values of AE <0.3 have been found for very high AOD Saharan aerosol dust events .

Observations are categorized into four aerosol types following the boundaries defined in : desert dust, pollution, mixed aerosols, and background. The colour scheme in the plots corresponds to the direct distance of the affected stations from the source, with the closest station to the source shown in turquoise and the furthest in grey. The full sequence of colours is as follows: turquoise, green, orange, magenta, brown, and grey. The aerosol regimes inferred from the AOD–AE diagrams should be interpreted only as indicative classifications, particularly because dust–pollution and dust–marine mixtures may occupy overlapping regions of the AOD–AE space. They are therefore used only as complementary information alongside the additional optical, transport, observational, and modelling evidence presented in this study.

For event A (see Fig. a) a wide range of AOD values are observed reachin up to 1 for Cairo_EMA_2, Nicosia and CUT-TEPAK stations. Relatively similar AE values were observed in all stations on the peak day, with values below 0.5, indicating that a similar aerosol plume with large particles, classified as desert dust, was affecting these stations.

During event B (see Fig. b), the AOD and AE values remained above 0.5 and below 0.4, respectively, for almost all the stations, classifying the aerosols as desert dust. The only exception is seen for Magurele_Inoe (Romania), where the significantly lower AOD values and higher AE suggest the presence of a more mixed or polluted air mass. This station exhibited a weaker response to the dust event, as also reflected in the time series of AOD and AE (Figs. b and b).

With respect to event C (see Fig. c), this event shows a lower intensity than the rest of the analyzed events, with AOD values ∼ 0.4. In this case, AE is relatively high and constant (Fig. c) in all the stations, with values between 0.5 and 1.5, indicative of a mixed aerosol event likely influenced by both dust and anthropogenic pollution.

Event D (see Fig. d) is characterized by high AOD (>0.4), for all the stations, AE reaches values close to when the maximum AOD occurs. Looking at the time series of this event (see Figs. d and d), it is noticeable that the event is characterized by high variability in terms of AERONET observations, possibly attributed to the significant geographical extent of the event, between Eastern and Western Mediterranean. Most observations are classified as desert dust, with only a few measurements at Palma_de_Mallorca (Eastern Spain) corresponding to background aerosol conditions.

Detailed time series of both AOD and AE are found in the Appendix .

As a next step, the optical aerosol properties retrieved by AERONET at the selected stations are discussed. The average of the retrievals that meet the criteria considered (see Sect. ) are calculated for the day with the highest AOD value at each station for each event. Error bars with standard deviation are plotted for cases where more than one observation are available. For the Middle East and Central Sahara events, it was feasible to retrieve inversions only for some of the stations affected, as not all of the inversions were meeting the criteria.

The first parameter derived from inversion considered here is the asymmetry parameter. Figure  shows that the values of this parameter for these events are in the range expected for dust particles (0.6–0.8) . Low ASY values are observed for all the stations affected by event C (originating from Middle East), comparable to those recorded at Magurele during event B and at CUT-TEPAK during event D. These reduced ASY values may be associated with the presence of smaller particles in the dust mixture observed at these stations. In the case of Magurele, the relatively lower ASY values observed can possibly be attributed to the elevated levels of continental aerosols and the lower amount of dust reaching this site. There is a strong wavelength dependence in all cases at shorter wavelengths. A similar ASY behavior is observed between events A and B (originating from Eastern and Western Sahara, respectively). A wider spread in ASY is observed in the case of event D (originating from Central Sahara), which can be explained by dust particles of varying properties resulting from the wide source area these particles originated from initially.

It is possible to compare the ASY values obtained for the same station for different source regions (different events). Small differences are observed for Rome, with event D showing a slightly stronger spectral dependence than event B. A more pronounced effect is observed at the Cairo station, where ASY values are significantly lower (indicating smaller particles) when the dust originates from the Middle East (event C) compared to the East and Central Sahara (event A). A similar reduction in ASY pattern is observed at CUT-TEPAK when comparing events A and D, where the station in the latter event is influenced by Middle Eastern air masses, as shown in Figs. –. This consistent pattern suggests that the observed ASY behavior, characterized by lower ASY values, is primarily driven by source characteristics (Middle East) rather than by local mixing effects at the measurement stations.

Another parameter derived from inversion that can give us information on the scattering properties of the dust events is the single scattering albedo.

In Fig. , the SSA values are shown for all the inversions that fulfil the criteria explained above, at each station, for all the events. In general, the observed values and wavelength dependence are consistent with those found in previous works . For the three Saharan dust events (A, B and D), low values (0.86–0.94) are found around 440 nm wavelength, with higher values (0.94–0.99) at 675–1020 nm. During the Middle East event (C), Cairo and Agia Marina show relatively low SSA values (SSA ≤0.94), consistent with more absorbing particles. In contrast, Sede Boker and Weizmann display the highest SSA values observed across all events. HYSPLIT back-trajectories indicate that the air mass arriving at these two stations originated over inland Saudi Arabia and that other stations affected by the same airmass have also similar SSA behaviour (e.g., Technion_Haifa_IL, Israel and KAUST_Campus, Saudi Arabia). This inland trajectory excludes significant marine influence, suggesting that sea salt aerosols are unlikely to explain the very high SSA observed (∼0.99). Another speculation is that these inland trajectories are not affected by compastion while in the other cases the trajectories could be affected by combustion. Instead, the elevated SSA (also observed on 15 November 2021) may result from the presence of mineral dust with inherently low absorption or long-range transported dust internally mixed with secondary scattering aerosols, such as sulfates or nitrates. Such aging and coating processes are known to increase SSA significantly during transport as also described in . It should be noted that no level 2 data are available for the two stations on that date.

In the case of the East-Central Sahara event (A), it is noticeable that Nicosia has smaller values than the rest of the stations, especially when compared with CUT-TEPAK, which is the nearest. This suggests that there might be some local aerosol mixing with the dust, for example, through interaction with emissions from power stations in the outskirts of Limassol as the dust plume moves inland toward Nicosia. The decrease seen at Finokalia for longer wavelengths could be explained by the lower AOD values at Finokalia, since small variations in AOD can have a large effect on SSA retrievals . In the Western Sahara event (B), there is less variability between stations, except for Magurele, which has a higher SSA at 440 nm.

For event D, there is high variability in SSA, especially at the shortest wavelength, where dust is mostly absorbing. Palma de Mallorca station and Rome have in overall, the lowest values at the 440 nm wavelength indicating stronger absorption compared to other stations. Interestingly for Palma de Mallorca there is a decreasing trend of SSA at longer wavelengths, which, in combination with low AOD suggests locally mixed aerosols.

Figure  presents the volume size distributions for each event, at the corresponding stations. For each station, the daily averaged size distribution on the day with the highest AOD is shown. It is important to note that the sky error criterion of <6% is applied once again. Error bars correspond to the standard deviation of the size distributions during the day, when more than one observation is available.

For the East-Central Sahara event (A), the volume size distribution shapes are similar across different sites, with significant contribution by coarse-mode particles, with radius around 2.24 µm. The concentrations of coarse particles are more prominent at sites closer to the source (Cairo and Sede Boker).

Notably, for Western and Central Sahara events (B and D), in which the stations are widely distributed across the Mediterranean, the size distributions at different stations exhibit similar shapes and values, particularly for the coarse mode, which is predominant in these events. One exception is at Magurele site in event B, where the coarse mode is not significantly higher than the fine mode, suggesting the possibility that fewer particles arrive due to deposition during transport, as it is the furthest station from the source. In both cases, the peak of the coarse mode is between 1.7–2.24 µm while the concentrations at the peak are between 0.1–0.4 µm3 µm-2 with no clear link between distance form source and concentration magnitude.

For the Middle East event (C), the volume concentration is lower at all the stations compared with the rest of the events, reflecting the lower overall AOD values, and there are notable variations in the size distributions among the sites. At all sites, the coarse mode is dominant, however there is also a significant fraction of the fine mode, meaning that there is a mixture of different aerosols species. The radius for the maximum concentration value is found around 1.7 µm except at Cairo station, which has the highest volume concentration and the peak corresponds to the radius value of 3.86 µm (the highest amongst all events considered here), indicating significantly larger particles compared to the other stations affected by the same event. In Fig.  the fine-mode-fraction (FMF) product from AERONET at 500 nm, which describes the proportion of fine-mode aerosol optical depth to the total aerosol optical depth, is compared to the averaged ASY and SSA parameters for the four events discussed in this study. This analysis provides insight into the relative contribution of fine absorbing particles and coarse mineral dust, allowing a clearer assessment of aerosol mixing processes during each event. In this comparison, event C originating from the Middle East stands out from the rest of the events, exhibiting the highest FMF (∼0.6) and lowest ASY (<0.75). Although event C does not exhibit enhanced absorption at 440 nm on average based on SSA, it shows the lowest average SSA at 675 nm among all events. However, these averages are influenced by the relatively high SSA values observed at the Weizmann and Cairo stations, which increase the overall event mean. In contrast, events A,B and D generally displayed lower FMF. These findings are further supported by the retrieved particle size distributions and the dust fractions derived from the MIDAS dataset, which confirm the increased fine-mode influence during event C.

Cyprus was affected by three out of the four selected dust events (A, C, and D), making it possible to utilize ground-based observations on the island to compare the dust events (see Sect. ). Figure  compares dust concentrations over ±5 d from the peak of each event at the station (defined by the AERONET observations), highlighting differences in intensity and duration among the events. As seen from this figure whilst event A exhibits higher dust concentrations, event C shows a lower but more consistent concentration over a longer period. The few observations during event D exhibit similar concentrations with event A before the peak date. The second part of the event (arriving from Middle East) is seen 4 d following the peak day with significant concentrations. Similar trends are seen in the concentration of dominant elements during dust events, i.e., Fe, Al, and Ca, whereas there is no clear trend for Mg, as shown in Fig. . It is worth mentioning that, despite the overall lower dust loading during event C, the relative elemental abundance at comparable levels as in event A.

The average absorption coefficient calulated by the aethelometers at Agia Marina Xyliatou (see Sect. ) during events A, C, and D are compared in Fig. . When comparing the three events (events A, C, and D), event C exhibits the highest absorption (∼50 % more absorption than the other events across the entire spectral range, suggesting a greater concentration of absorbing aerosols. Events A and D show similar absorption levels, ∼0.6 Mm⁻¹ at 440 nm, and much lower for the larger wavelengths. These findings are consistent with previous indicators of mixed aerosol conditions during event C (i.e., lower SSA, Assymetry factor, DOD-to-AOD ratio and higher Angstrom Exponent). For the analysed cases, this indicates that source region and transport-related mixing may both contribute to the optical differences. In particular, dust transported from the Middle East appears to be mixed with more absorbing aerosols, potentially carrying anthropogenic pollutants.

Mineralogical composition of events C and D was simulated using METAL-WRF. The relative abundance of different elements typical for dust at the stations affected during the events is seen in Fig. . The elemental composition is calculated only at the altitudes with presence of dust. The altitude of dust in the model is derived by applying a concentration threshold for aluminum, with Al ≥0.5 µgm-3 considered indicative of dust. Aluminum was selected because it is commonly used as a tracer of mineral dust. The threshold was chosen to distinguish from background conditions, considering the concentrations during the two events. Whenever possible, the lidar profiles were also used to qualitatively assess whether the model-derived dust-layer altitudes were consistent with the observed vertical aerosol structure. A sensitivity analysis using different vertical averaging intervals indicated only minor changes in the relative elemental composition. In this analysis, Agia Marina Xyliatou station is examined for the region of Cyprus to facilitate a direct comparison with the in situ results presented herein. The analysis that was done here contributes to a better understanding of: (i) the composition differences between events C and D and (ii) the variability of composition during the same event across different stations.

As seen also from the observations, the simulated concentrations for event C are, in general, lower than event D. During both events, there is a consistent and intense elemental signature of dust across all stations, with higher concentrations of silica (Si), aluminum (Al), calcium (Ca) and iron (Fe), which are enhanced during dust events . Within event C, whilst silicon, aluminium and calcium are the dominant elements, there is a small variability across stations. Early stations like Weizmann and Sede Boker show higher iron and aluminum concentrations (nearly ∼20 % in both cases), while stations farther along the dust plume trajectories, like Agia Marina Xyliatou and IMS METU, show decreases in both concentration and elemental diversity. In event D, there is a relatively uniform composition across stations dominated also in this case by silicon, aluminum, calcium and iron. However, the total concentrations during event D vary significantly, with Lampedusa exhibiting the highest dust loading and Mallorca the lowest, suggesting weakening of the plume as it moved westward.

Overall, the relative contribution of the selected elements remains nearly constant (changing by only a few percent) despite large differences in total dust concentration. For example, stations exhibiting concentrations of ∼ 120 mg cm⁻³ (Lampedusa, event D) show nearly the same elemental percentage composition as stations with ∼15 mg cm⁻³ (Mallorca, event D). For Events C and D, this limited variability suggests that differences in modelled composition alone cannot explain the full range of observed optical differences. This conclusion is restricted to the two simulated events and does not exclude mineralogical effects or broader variability across other Saharan and Middle Eastern outbreaks.

To better assess the results of the mineralogical composition from METAL-WRF, the simulated compositions are compared to the in situ observations obtained during Fall Campaign 2021, in Cyprus , which coincided with event C (see Sect. ).

Figure  presents the first attempt for a case-specific comparison focused on event C between the model, ground and UAV-based observations for dominant dust elemental mass fractions (Ca, Al, Fe, Si and Mg). The comparison based on elemental mass fractions provides a more direct assessment of the simulated dust composition, as it reduces the influence of the differences in the total dust load between the two methods. The UAV-based mass fractions were derived from SEM analysis of particles collected on filters mounted on the UAVs, using the number of analysed particles, sampling duration, and UAV airspeed for the concentration calculation. The simulated values (blue dashed line) were extracted over the altitude intervals sampled by the UAV filters and corresponding to the identified dust layers. The resulting UAV-based estimates are shown by the red and green boxes, with their standard deviation shown with the shaded area. This approach allows direct comparison of the modelled and observed elevated concentrations. Ground-based observations from Agia Marina Xyliatou are also shown for reference (black line).

The statistical UAV-model comparison, which includes the relative deviations and z scores, is provided in Appendix . Here, the z score expresses the UAV–model difference relative to the standard deviation of the observed concentrations.

The comparison reveals element dependent variability. The best agreement is found for Al, with absolute z scores generally below unity and relative deviations mostly within approximately 30 %. Similarly, Fe and Si show a good agreement with positive biases, with average relative deviations of approximately 29 % and 31 %, respectively, and z scores generally close to unity.

In contrast, Ca and Mg are systematically underestimated by the model. Ca deviations exceed 70 % throughout the measurement period, while Mg deviations are consistently around 90 %. Interestingly, for Ca the UAV-based observed elemental mass fractions are closer to the ground-based observations rather than the simulations of the elevated mass fraction for Ca. This effect might partly reflect size-dependent transport and removal. For example, Ca-bearing minerals, which are often associated with coarse particles, and therefore can be removed faster during gravitational settling during transport. In the case of Mg, the large deviations could be linked to its very low absolute concentrations in the model. This analysis suggests that the main compositional discrepancies at elevated layers are associated with the representation of Ca- and Mg-bearing minerals.

The results herein complement the findings of , who reported the agreement of METAL-WRF for ground-level elemental concentrations during 2017 dust event at Agia Marina Xyliatou. The present analysis extends this evaluation by providing, for the first time, a comparison with UAV-based elemental observations within an elevated dust layer.