This manuscript investigates the source-dependent optical, microphysical, and mineral signatures of four major dust outbreaks affecting the Mediterranean Basin during 2021–2022. The study combines a wide range of observational and modeling tools, including AERONET sun-photometer retrievals, MIDAS/MODIS dust optical depth, IASI dust products, HYSPLIT back-trajectories, lidar-based vertical information, ground-based in situ observations in Cyprus, UAV-based composition measurements, and METAL-WRF mineralogical simulations. The topic is scientifically relevant as mentioned in the manuscript that the Mediterranean is strongly affected by dust from both Saharan and Middle Eastern sources, and the optical properties of transported dust are essential for assessing radiative effects, air quality impacts, and model representation of dust aerosol. The manuscript is generally well organized and contains a valuable multi-platform analysis. A major issue is that some conclusions regarding the relative roles of mineralogy, mixing state, and anthropogenic influence are plausible but not yet fully demonstrated. Therefore, I would recommend publication if the following comments could be properly addressed after moderate revision.

Major Comments

#1. One of the key conclusions of the manuscript is that the dominant mineral fractions simulated by METAL-WRF are broadly similar across events, and therefore the observed optical variability is mainly driven by dust-to-total aerosol ratio and mixing state rather than mineralogical differences. This conclusion is not fully demonstrated. The mineralogical analysis is available mainly for selected events and stations, whereas the optical analysis covers a broader set of AERONET sites and events. Moreover, METAL-WRF mineralogy is itself subject to uncertainties in source mineral maps, emission size distribution, transport, and deposition. The authors should more clearly distinguish between what is directly supported by the combined observations and what is inferred from the model. If possible, it would be helpful to provide a more quantitative comparison between mineral composition, DOD-to-AOD ratio, FMF, SSA, and ASY across the events. Or the conclusion should be phrased more cautiously, emphasizing that the current evidence suggests, rather than definitively proves, that aerosol mixing and dust fraction dominate the observed optical variability.

#2. Another issue is that the manuscript states the Middle East event is characterized by finer and more absorbing particles, likely influenced by anthropogenic sources. This interpretation is reasonable and is supported by higher FMF, lower DOD-to-AOD ratios, lower ASY, and stronger absorption observed in Cyprus. Nevertheless, the evidence remains partly circumstantial. The manuscript would be strengthened if the authors provided additional support for the anthropogenic influence, such as co-variation with black carbon, organic aerosol, sulfate/nitrate, CO, or known emission regions along the transport pathways. It is also necessary to briefly discuss the source region and sector (e.g., oil industry) of anthropogenic pollution. It will be better if other possibilities, including source-specific mineral absorption, aging, coating by secondary aerosols, or mixed dust–pollution–marine aerosol states, could be discussed more systematically.

#3. The study focuses on four major dust outbreaks in 2021–2022, selected from widespread events affecting multiple AERONET stations. This is a reasonable design, but the conclusions are sometimes written in a way that may imply more general source-dependent behavior. Since only one Middle East event and a limited number of Saharan events are analyzed, it is important to clarify whether the findings are representative of broader source-region differences or mainly characteristic of these selected episodes. The authors should add a short discussion on the limitations of the case-study approach and specify which conclusions are robust across the selected events and which require confirmation with a larger event climatology.

Specific Comments

#1. The criterion for AERONET inversion quality is described as sky error < 6%, whereas the figure caption for Fig. 4 mentions sky error < 5%. Please check and make the threshold consistent throughout the text and figure captions.

#2. The station ordering by distance from source is useful, but for event D the manuscript acknowledges that the sequence is not straightforward because multiple sub-events occurred. In this case, the interpretation of evolution with distance should be treated cautiously.

#3. In Fig. 3, the manuscript should briefly discuss the uncertainty of assigning aerosol types based only on AOD–AE space, particularly in mixed dust–pollution and dust–marine aerosol conditions.

#4. The Cyprus case study is one of the strongest parts of the manuscript. It would be helpful to make the comparison between events A, C, and D more explicit in terms of dust mass, absorption coefficient, and elemental abundance. A compact summary table may improve clarity.

#5. In Fig. 11, the text states that event C exhibits the highest absorption “∼50% across the entire spectral range,” but the unit and meaning of this percentage are not clear. Please revise this sentence and specify whether this refers to a relative increase compared with Saharan events.

#6. The METAL-WRF analysis indicates broadly similar mineral fractions among events, but the comparison with UAV-based observations shows discrepancies in Al and Mg. These discrepancies should be discussed in more detail, because they may affect the conclusion about mineralogical similarity.

#7. The manuscript should more clearly explain how the dust-layer altitude used for METAL-WRF mineralogical averaging was selected and how sensitive the mineral fractions are to this vertical selection.

#8. Line#217 “at a vertical spacing of ±”, seems missing a number here.

The paper by Papetta et al. analyses four major dust outbreaks affecting the Mediterranean Basin during 2021–2022, using AERONET observations, satellite dust products from two passive sensors, HYSPLIT trajectories, lidar measurements , in situ aerosol measurements in Cyprus, UAV-based chemical observations, and METAL-WRF mineralogical simulations. This is a unique combination of available information to characterize mineral dust in the area and this multi-platform approach allows to connect optical properties, dust fraction, transport pathways, and mineralogical composition. The paper should be considered for publication in Atmospheric Chemistry and Physics after taking into account the following comments.

General comments

The paper presents a very large amount of material, but the way it is written and presented, e.g. large descriptive sections, makes it difficult for the reader to identify, what are the main messages and findings.  The fact that the authors present in detail four cases, requires a discussion for the presentativeness of them, otherwise the authors should avoid over-generalising source-dependent conclusions. The classification of events by source region should be supported more quantitatively, e.g by adding source-region maps, or a clearer explanation of how mixed-source cases are interpreted.

The mineralogical part seems somewhat underdeveloped relative to the strength of the conclusions. More particular the conclusion that mineralogical differences are small while optical variability is mainly driven by dust fraction and mixing state is important, but it should be supported in more detail.

The comparison between METAL-WRF and UAV observations which is performed for one even is more a first evaluation attempt rather than a broad model validation. The discrepancies for Al, Si, and Mg deserve more discussion, including possible causes (e.g. source mineralogy, size distribution, vertical sampling, model resolution, measurement uncertainties).

Some figures are dense and difficult to read, particularly the trajectory and multi-panel optical-property plots.