Abstract. The mineralogical and chemical composition of desert dust particles strongly influences their cloud-forming ability and radiative effects. This study provides quantitative estimates of the main mineralogical and elemental components of desert dust during atmospheric transport above Cabo Verde based on in-situ measurements from the ASKOS campaign in summer 2022, obtained using impactors mounted on unmanned aerial vehicles. Simulations from the METAL-WRF model were used for comparison with sun-photometer observations of total dust load and with in-situ measurements of relative elemental mass fractions of key elements. Across all cases, particle chemical signatures were dominated by illite/muscovite (62%), followed by smectite (9%), kaolinite (9%), quartz (7%), feldspar (5%), calcite (4%), gypsum (3%), and Fe-oxide/Fe-hydroxide (1%). Trajectory and source–receptor analyses combined with satellite observations revealed enhanced calcite fractions for air-masses originating from northern Mali, whereas air masses from southern Mali exhibited increased proportions of Fe-oxide/hydroxide. Good agreement was found between METAL-WRF-derived total dust mass concentrations and independent AERONET observations (slope = 0.62, r = 0.87). Based on in-situ measurements, Si was the dominant elemental component (~25%), followed by Al (~12%), Fe (~6%), Ca (~2.7%), and S (~0.4%). While METAL-WRF reproduced the mean relative abundances of Fe and Ca over the 20-day period, it did not capture the case-to-case variability. Nevertheless, Fe exhibited good agreement, within overlapping uncertainty, between modelled and measured values for most cases, which is particularly relevant for studies of ocean biogeochemistry and dust-related radiative processes.

This study investigates observations of coarse particles during a Saharan dust event using low-cost optical particle counters (OPC) mounted on uncrewed aircraft systems (UAS). Measurements from an AlphaSense OPC-N3 and a Universal Cloud and Aerosol Sounding System (UCASS) are compared, and the impact of refractive index (R.I.) correction on OPC observations is examined. On 6 April 2022, a dust layer existing from 1250 to 2500 m a.g.l. advected over Orounda, Cyprus. Two UAS performed vertical profiles to examine meteorological and particle dynamics. Refractive index (R.I) corrections were applied to AlphaSense OPC-N3 size distributions to assess effects on aerosol particle load estimates. The correction substantially altered apparent number and volume concentrations, reducing discrepancies to an additional UAS (UCASS). Whereas varying the real part of the R.I. had a minor influence on the apparent distribution, sensitivity to the imaginary component was more pronounced. Assuming a R.I. of 1.53 + 0.0015i improved the fit of derived quantities with lidar and a TEOM observations; however, 1.53 + 0.0024i provided closer cross-instrument alignment, suggesting a higher imaginary component for the observed dust. The correction highlights long-range transport of super-coarse aerosol particles, and suggests that the OPC-N3's ability may be extended to detect particles with geometric mean diameter up to three times larger than nominal bin classifications during Saharan dust events. Observations from a 2025 dust event further support these results. R.I. corrections improve interpretation of OPC-N3 data and enhance its ability to characterize coarse, super-coarse, and giant particles, ultimately supporting aerosol particle transport dynamic studies and reducing persistent knowledge gaps.

AIMS: Ultrafine particles (UFPs) smaller than 100 nm are ubiquitous in polluted air. Although they carry little mass, UFPs have a large exposure surface area, can bypass respiratory defences, translocate into the brain and bloodstream, and impact the heart and other organs. Here, we assess the role of UFPs in air quality and the health burden they impose. METHODS AND RESULTS: We integrated Earth observations with machine learning to estimate long-term UFP exposure at 1 km resolution, demonstrating that they pose a major air quality concern in urban environments, with annual mean concentrations typically ranging between 10,000 and 30,000 particles/cm-3. Model calculations suggest that black and organic carbon are primary components of pollution UFPs. Based on a meta-analysis of epidemiological cohort studies in Europe and North America, we derived a pooled hazard ratio for mortality and combined it with our UFP data. We estimate a mortality density of 35.7 (15.8-65.5) per 100,000 people annually in Europe, and 27.4 (12.9-47.4) per 100,000 in North America, the latter being close to the global mean. We find that UFP exposure and mortality densities are particularly high in South and Eastern Europe. Since observational data for other regions are limited, global calculations primarily depend on modelling. We indicatively estimate that 1.99 (0.81-3.89) million excess deaths per year are attributable to UFP exposure. This could account for approximately 5% of total mortality from non-communicable diseases, to a large degree (about half) due to cardiovascular conditions. Globally, about 91% of UFP-related excess mortality occurs in urban and suburban environments, and much of that (78%) in densely populated urban areas. CONCLUSION: Health-improving interventions should target combustion sources in cities, particularly those related to energy consumption, industry, and traffic. An annual air quality limit of 5,000 cm-3 could reduce global excess mortality by about 45%.

Atmospheric new particle formation (NPF) is a major source of aerosol particles in the Earth's atmosphere. However, process-level understanding of the early stages of particle formation and growth remains poorly represented in climate models, limiting accurate estimates of aerosol effective radiative forcing. Here, we use comprehensive observations from the Spring Particles in Cyprus (SPICY) field campaign conducted at a rural background site in Cyprus. We report new observations of nanoparticle shrinkage (NPS), marked by the rapid decrease in size of sub-20 nm particles occurring in the absence of preceding NPF event. Thus, the particle size distributions exhibit a mirror image of the conventional “banana-shaped” NPF pattern, forming a distinctive “reverse-NPF” pattern. We identified three NPS events during the campaign and show that this phenomenon is not primarily driven by low concentrations of condensable vapours, their scavenging by pre-existing particles, or primary nanoparticle sources. Instead, it is associated with atmospheric dilution, as indicated by air-mass trajectory analysis. Furthermore, fast-moving air masses can enhance turbulent mixing, thereby altering particle size distributions. Together with volatility-resolved analysis, these results suggest that NPS is governed by atmospheric dilution, which reduces particle-phase organic mass and shift the gas-particle equilibrium toward evaporation, with contributions dominated by organic compounds of low and moderate volatility. Our results demonstrate that NPS events provide a previously unrecognised sink for nanoparticles, which are controlled by air-mass dynamics and organic vapour volatility.

Volatile organic compounds (VOCs) are key precursors of tropospheric ozone and secondary organic aerosol formation, yet multi-year observations in the Eastern Mediterranean and Middle East (EMME) remain limited. This study presents multi-year (April 2022-June 2024) high-resolution measurements of 76 VOCs using PTR-ToF-MS at a rural background site in Cyprus, combined with HYSPLIT air-mass analysis to examine the effects of regional transport on VOCs variability. Oxygenated VOCs (OVOCs) dominated the VOCs burden (similar to 79 %), followed by aliphatic hydrocarbons, aromatic hydrocarbons, and terpenes. Most VOCs exhibited clear diurnal patterns, observed highest during 08:00-14:00 UTC, varying by species, due to enhanced photochemical activity and temperature-driven emissions. Terpenes, particularly isoprene, increased exponentially with temperature upto 35-38 degrees C but decreased beyond this threshold, indicating heat-stress inhibition. Monoterpenes showed elevated levels both day and night, reflecting contributions from both biogenic and anthropogenic sources. OVOCs, including acetone, acetaldehyde, methanol, and acetic acid, showed sharp enhancement above 35 degrees C, consistent with intensified primary emissions and secondary formation under extreme heat. Aromatic hydrocarbons were mainly higher during winter, linked to combustion processes, but benzene levels were highest during summer particularly when temperature rose above 35 degrees C from evaporative and potential stress-related biogenic sources. HYSPLIT air-mass trajectory analysis revealed dominant contributions from Europe and Northwest Asia (similar to 68 %), transporting aged OVOCs, while Middle East winter inflows enhanced aromatic hydrocarbons. While WRF-Chem captured seasonal trends, most VOCs were underestimated, highlighting under-representation of emission sources and oxidation pathways in the model. Overall, the study emphasizes temperature and regional transport as key drivers of VOC variability in the Eastern Mediterranean.

Organic aerosol (OA) is a major component of atmospheric particulate matter (PM), affecting both human health and climate. However, high-resolution estimates of OA exposure needed for exposure analysis remain scarce. Here, we integrate a chemical transport model (CAMx) with a random forest (RF) machine learning approach to bias-correct and downscale daily OA concentrations across Europe. CAMx OA simulations at ∼15 km resolution show moderate agreement with observations (r = 0.55). By combining these outputs with high-resolution land-use data and training the RF model on ∼48,000 daily OA measurements from 137 sites, prediction accuracy improved (r = 0.65), with ∼l5% reduction in root mean square error. The resulting maps provide European daily OA concentrations at ∼250 m resolution for alternate years from 2011 to 2019. The model captures key spatial features, including elevated OA in the Po Valley, Southeastern, and Central Europe, as well as intracity variations due to local hotspots. Seasonal analysis reveals higher concentrations in winter, while long-term trends indicate a general decline in OA levels. Exposure estimates show that half of the European population experiences OA levels above 3 µg/m3, and ∼50 million people are exposed to more than 5 µg/m3, which is the current guideline level recommended by the world health organization for total PM2.5. These high-resolution OA maps offer vital critical support for epidemiological research and air quality policy.

The Eastern Mediterranean and Middle East (EMME) is one of the most vulnerable regions to climate change globally and is becoming one of the world leading emitters of green-house gas (GHG) and air pollutants. Among these, nitrogen oxides NOx (=NO+NO2) are crucial to tropospheric chemistry, due to their role in the formation of tropospheric ozone O3 and Particulate Matter (PM); both of which are harmful to human health and the ecosystem. NOx are primarily emitted from the combustion of fossil fuels, which occurs in several sectors including transportation, energy production, industrial activities, residential heating, and agriculture. In spite of the direct and indirect threats of NOx emissions, Saudi Arabia and the United Arab Emirates (UAE) continue expanding their fossil fuel production, with Saudi Arabia aiming to boost oil capacity to 13 million barrels per day by 2027, undermining its own 2060 net-zero pledge under the Saudi Green Initiative. The EMME region remains under studied regarding anthropogenic emissions, which highlights the need for accurate emission estimates to inform policy decisions.In this work, we estimate NOx emissions in the EMME region at a horizontal resolution of 0.5°, for the period 2019 to 2021. We employ the Community Inversion Framework (CIF) model, coupled to the CHIMERE chemistry transport model (CTM) and its adjoint, using a variational inversion method to construct NOx emissions. We assimilate nitrogen dioxide (NO2) observations from the TROPOspheric Monitoring Instrument (TROPOMI) on board the Copernicus Sentinel-5 Precursor (S-5P) satellite, and both anthropogenic and biogenic NOx estimates from the Copernicus Atmosphere Monitoring Service (CAMS). Our emission data are close to those provided by other inventories. We examine key emitters in the EMME region, including countries that are affected by economic changes and/or political instabilities; such as Palestine, Israel, Lebanon, Iraq, Iran, Qatar, the UAE, and Saudi Arabia, among others. Our results show that, from 2019 to 2021, NOx emissions exhibit a positive trend in most of the studied regions, except in Tehran (Iran) and Jeddah (Saudi Arabia), where we observe a decrease of NOx emissions by -27% and -12% respectively. In the UAE, however, emissions increased by +17%, and in Yanbu (Saudi Arabia) by +24%, in 2021 compared to 2019. In Lebanon, a rise in NOx emissions can be attributed to the country's economic crisis and shortages in national electricity supply, which led to a rapid increase in privately operated diesel-fueled energy producers. Our NOx emissions data are expected to help policy makers monitor emissions in the EMME, at regional and national scales, to better tackle challenges specific to this region.

Long-term daily PM2.5 and PM10 chemical speciation data was collected continuously from 2015 to 2023 at an urban traffic and regional background site in Cyprus, offering a unique opportunity to quantify the influence and trends of (i) local emissions on urban PM concentration levels and sources, and (ii) regional PM emissions over the Eastern Mediterranean basin. Despite a statistically significant drop in PM2.5 and PM10 at both sites over the last 19 years (2005–2023), concentration levels remain high with no further significant improvements observed over the last 9 years; making PM concentration levels well above the new EU annual limits. To refine this analysis, long-term trends (2015–2023) were explored for individual PM chemical species and sources derived by PMF source apportionment. A decreasing trend in traffic-related PM10 of 35 % was observed at the traffic site, suggesting the effectiveness of the gradual shift of the vehicle fleet towards the latest EURO-standard vehicles. On the other hand, this reduction in tailpipe traffic emissions was completely offset by an increase of uncontrolled urban emissions, such as road dust re-suspension and biomass burning from domestic heating, calling for the rapid implementation of abatement measures. Based on cluster analysis of air mass origins, the Middle East region was identified as a major hotspot of PM10 over the Eastern Mediterranean; with both high concentration levels of dust from the Arabian desert and substantial anthropogenic pollution with continuously increasing trends in biomass burning and sulfate-rich emissions from fossil fuel combustion over the past decade.

The rising frequency of mineral dust events in the eastern Mediterranean underscores the need for high-resolution observations to better characterize their properties and impacts. This study reports results from the Cyprus Fall Campaign 2021, which aimed to test and validate a new cost-effective methodology for quantitative dust measurements using Giant Particle Collector(GPaC), Portable Optical Particle Spectrometer(POPS), and Universal Cloud and Aerosol Sounding System(UCASS) sensors on-board Uncrewed Aerial Systems(UAS). The Cyprus Fall Campaign 2021 captured the microphysical characteristics of dust particles from two major global sources: North Africa (NA) and the Middle East (ME). The campaign was conducted from 18 October to 18 November 2021 and comprised 36 UAS flights. This work represents the first intensive UAS-based dust characterization campaign in Cyprus and the wider Mediterranean region during the autumn season. Remote-sensing and back-trajectory analyses revealed NA dust layers up to 7 kma.s.l. (above sea level) over Cyprus, compared to 3.8 km for ME dust. Impactor sampling demonstrated a near-1 collection efficiency for particles between 4-14 & micro;m, highlighting its effectiveness onboard the UAS. Particle volume size distributions showed a fine-mode peak at 0.25 & micro;m in both cases, and distinct coarse-mode peaks at 2.2 and 4.8 & micro;m for NA and ME dust, respectively. High-altitude impactor samples showed two distinct dust signatures: NA dust enriched in kaolinite-like and Ca-bearing phases, and ME dust dominated by illite/muscovite and Fe-rich components, indicating contrasting source characteristics influenced by granulometry, transport, and atmospheric processing. This study showcases the capability of high-resolution UAS sampling to characterize atmospheric dust and improve understanding of its regional and climatic impacts.

This study presents a comprehensive chemical characterization and source apportionment of PM2.5 in the Greater Cairo Area (GCA), one of the world's most polluted megacities. A total of 59 PM2.5 samples were collected continuously and on a 24-h basis during the winter of 2019-2020 at an urban background site and analyzed for a wide range of organic and inorganic species. The Positive Matrix Factorization (PMF) model was applied to identify and quantify as many as eleven sources contributing to PM2.5, highlighting the highly complex mixture of aerosols over the GCA. These sources include industrial emissions (coal combustion, lead and copper smelting), vehicular exhaust and non-exhaust emissions, open waste and wood burning, cooking, processed secondary aerosols, transported crustal dust, and mixed regional pollution. Local primary particulate controllable sources dominated elemental health risks, contributing 60% of the total non-cancer risk (NCR:1.7) and 52% of the total cancer risk (CR:2.1 & times; 10(-5)), despite representing a much smaller fraction of PM2.5 mass. Industrial emissions, though contributing only similar to 12% of PM2.5 mass, were responsible for 37% of elemental NCR and 29% of CR. These findings underscore the need for targeted mitigation strategies addressing the burden of air pollution in GCA.

This study presents an extensive intercomparison between a benchtop X-ray fluorescence (XRF) system and near real-time XRF monitors (Xact 625 and 625i) for measuring elemental concentrations in ambient aerosols. The measurements were conducted across three locations: Athens (Greece, March 2024), Nicosia (Cyprus, March 2022-January 2023), and Dublin (Ireland, December 2022-February 2023). The primary focus was on comparing the performance of these near real-time and benchtop XRF systems for determining the elemental composition of particulate matter (PM), alongside evaluating the impact of filter substrate choice on measurement consistency. The study specifically examines the elements Si, S, Cl, K, Ca, V, Ti, Mn, Fe, Cu, Ni, Zn, Sr, and Pb. The results highlight that filter type plays a crucial role in ensuring accurate measurements when utilizing the benchtop XRF system. At the Athens site, where PTFE filters were used, the agreement between the Xact 625i and the benchtop XRF system was stronger, with slopes across the evaluated elements generally remaining closer to unity compared to the quartz substrates. In contrast, quartz fiber filters at the Dublin and Nicosia sites led to systematic deviations, especially for light elements such as S, Cl, and K, even after applying correction factors. For heavier elements like Fe, Mn, and Cu, the filter effect was less pronounced, though some variation across sites remained. Zn consistently showed good agreement, while Pb exhibited weaker correlation, possibly due to differences in the calibration curves of the two systems. Overall, this study not only evaluates instrument performance across multiple environments but also highlights how filter substrate selection impacts the comparability of these techniques, emphasizing the need for substrate-specific considerations to enhance consistency in elemental aerosol measurements.

Abstract. Atmospheric aerosols in the free troposphere (FT) exert a disproportionate influence on climate forcing yet remain poorly constrained. Here, we present an 11-year (2011–2021) characterization of PM10 chemical composition at the High Altitude Research Station Jungfraujoch (3580 m above sea level), capturing both FT conditions and episodic planetary boundary layer intrusions (PBLi). We integrate long-term measurements of organic aerosol (OA), elemental carbon, sulfate, crustal elements, trace metals, and bulk and molecular-level organic composition with gas-phase observations and proxies for atmospheric transport and oxidative capacity to quantify the drivers of aerosol loading and composition. The concentrations of primary aerosol species, including metals and elemental carbon, are strongly controlled by episodic PBL-to-FT transport (2-3-fold seasonal amplitude, e.g. 0.15 to 0.3 ng m-3 for Pb). Secondary species, including sulfate and OA, also reflect PBLi impact, but their formation requires sustained oxidative processing, for which the atmospheric humidity ratio (ω) acts as a key control. OA exhibits the strongest seasonal amplitude (10-fold, 0.1 to 1 μg m-3), additionally reflecting enhanced biogenic emission intensities in the PBL. This is accompanied by a systematic shift in C9 and C10 compounds, likely related to seasonal maxima in monoterpene emissions. Together, these results demonstrate that FT aerosol is governed by a dynamic interplay between episodic PBL-FT transport, source emission intensities and oxidative processing. This dataset constrains their relative contributions, and provides decade-scale observational benchmarks for improving the representation of transport and aging in atmospheric models, with implications for reducing uncertainties in climate forcing.

Abstract. Dust events frequently affect the Mediterranean Basin, however, the evolution of their optical and microphysical properties during transport remains poorly characterized. This study examines four major dust outbreaks in 2021–2022 affecting the Mediterranean, originating from the Eastern, Western, and Central Sahara and the Middle East. Combining ground-based AERONET sun photometers (24 stations), satellite (IASI, MODIS MIDAS) dust optical depth (DOD) data, and HYSPLIT back-trajectories, we track these events across multiple Mediterranean sites. Results reveal clear regional differences in dust optical properties, such as aerosol optical depth, single scattering albedo, and asymmetry factor, arising from source regions and transport processes. Saharan events are dominated by coarse, scattering mineral dust, while the Middle East event featured finer, more absorbing particles, likely influenced by anthropogenic sources. MIDAS DOD-to-AOD ratios indicate that only one East-Central Saharan event maintained high dust fractions (DOD-to-AOD > 0.8), suggesting relatively pure dust, while other events exhibited stronger spatial variability, with the Middle East event showing the lowest ratios, reflecting enhanced mixing with anthropogenic or marine aerosols. A regional case study in Cyprus using in situ elemental and absorptionmeasurements shows that Middle East dust, despite lower mass concentrations, exhibits stronger absorption than Saharan dust.METAL-WRF mineralogical simulations indicate broadly similar dominant mineral fractions (silicates and calcium-rich minerals) across events, suggesting that optical variability was mainly driven by dust-to-total aerosol ratio and mixing state rather than mineralogy. UAV-based composition data further validate modeled variability, although discrepancies in aluminum and magnesium highlight limitations in current dust representations.

The volume-to-extinction ratio (ζ) is an important aerosol property, allowing to relate gravimetric and optical quantifications, widely used in remote sensing and in climate models. The ζ ratio is affected by the microphysical properties of aerosol particles, including their size, shape and composition. This study presents a synergistic approach combining airborne in-situ observations and ground-based remote sensing to study this ratio during dust events originating in the Middle East and Saharan regions, and to examine its vertical variability and general estimation uncertainty. The data were collected during the 2021 Cyprus Fall Campaign and the 2022 ASKOS campaign in Cabo Verde. The combination of observations offered vertically-resolved information on the particle size-distribution and volume-to-extinction ratio. The findings of this study reveal pronounced differences in the ζ ratio and effective radius across events and regions, reflecting variations in the degree of mixing with fine particles, as well as some variability with altitude due to varying particle size and shape. During Middle East dust events in Cyprus in fall 2021 the observed average ζ was the lowest with ζ=0.53±0.24 µm, whilst for a Saharan dust case in Cabo Verde in summer 2022 observations showed the highest values with ζ=1.14±1.01 µm, both values obtained at the dust layer altitude in some of the reported cases. The analysis highlights large discrepancies compared to AERONET-derived values and previous literature, especially in the presence of super-coarse and giant particles. Scattering computations allowed to evaluate the experimental results and provide insights into the role of particle asphericity. Atmospheric model simulations also showed discrepancies, mainly due to assumptions that neglect larger particles. These findings suggest that improved dust representation in models is essential for accurate climate assessment.

Abstract. Aerosol particles larger than roughly 50–100 nm in diameter are climatically important because they can act as cloud condensation nuclei (CCN), making their global number concentrations essential for understanding aerosol–cloud interactions. However, observationally constrained, long-term global datasets of particle number concentrations in this size range remain scarce. In this investigation, we present a global dataset of ground-level particle number concentrations for the period 2003–2024, produced by combining in situ observations with a machine-learning approach. The dataset includes two variables: the number concentrations for particles larger than 100 nm (N100) and larger than 50 nm (N50), provided at 0.75° × 0.75° spatial resolution and daily temporal resolution. To generate this dataset, we trained an eXtreme Gradient Boosting (XGB) model using measurements from 62 in situ stations as targets and reanalysis variables as predictors, enabling a data-driven representation of particle number concentrations at the global scale. We evaluated the dataset against independent observations from 12 additional stations. At 2/3 of these stations, the dataset shows good performance, capturing the median concentrations within a factor of 1.5 from the observations. Furthermore, we describe the main characteristics of the dataset in terms of global spatial patterns, temporal variability, and seasonal cycles, and demonstrate its ability to capture long-term trends in particle number concentrations, including both increasing and decreasing tendencies reported in the literature. This work provides the first observation-constrained, machine-learning-based global dataset of N50 and N100 at daily resolution over two decades, bridging the gap between sparse measurements and computationally expensive process-based models. The dataset, publicly available at https://doi.org/10.5281/zenodo.20202080, offers a valuable resource for evaluating model simulations, improving CCN-related parameterizations, and supporting weather and climate studies without the need for explicit knowledge of the aerosol particle microphysics.

Accurate quantification and long-term monitoring of tree biomass and carbon stock at high spatial resolution is critical for understanding forest ecosystems dynamics and supporting land-based mitigation efforts. This study presents the first high spatial-resolution assessment of tree biomass and carbon stock within and outside forests across the Republic of Cyprus, in the Eastern Mediterranean. This is achieved through the integration of field inventory data and 50 cm airborne optical remote sensing images with a deep learning model. The model was trained and locally adapted to detect, count, and map the crown area of individual trees, enabling tree-level mapping for the entire island. To estimate tree biomass, new allometric equations specific to terrain aspects were developed using field data and a high-resolution digital terrain model, compatible with remote sensing-derived tree crown area and height. These equations allowed the computation of individual tree biomass and carbon stock from their crown area, as well as aggregated tree densities and per-hectare values across forest and non-forest land-use types. This new database allows quantifying the number of burned trees, burned tree cover, and associated biomass and carbon stock losses-going beyond traditional burned-area assessments. To estimate biomass loss from fire, satellite-derived burned areas maps since 2016 are combined with our tree-level biomass maps. This study establishes a scalable, data-driven framework for precision long-term forest monitoring at country level. It provides the first detailed quantification of Cyprus' carbon resources at tree level, and sets the foundation for improved national greenhouse gas reporting, post-fire restoration planning, and cost-effective forest management.