Atmos. Chem. Phys., 25, 16127–16145, 2025 https://doi.org/10.5194/acp-25-16127-2025 © Author(s) 2025. This work is distributed under the Creative Commons Attribution 4.0 License. R esearch article Elemental composition, iron mineralogy, and solubility of anthropogenic and natural mineral dust aerosols in Namibia: a case study analysis from the AEROCLO-sA campaign – Part 2 Paola Formenti1, Chiara Giorio2,3, Karine Desboeufs1, Alexander Zherebker2, Marco Gaetani4, Clarissa Baldo5, Gautier Landrot6, Simona Montebello2,7, Servanne Chevaillier1, Sylvain Triquet1, Guillaume Siour5, Claudia Di Biagio1, Francesco Battaglia1, Jean-François Doussin5, Anais Feron1,a, Andreas Namwoonde8, and Stuart John Piketh9 1Université Paris Cité and Univ. Paris Est Creteil, CNRS, LISA, 75013 Paris, France 2Yusuf Hamied Department of Chemistry, University of Cambridge, Lensfield Road, Cambridge, CB2 1EW, United Kingdom 3Dipartimento di Scienze Chimiche, Università degli Studi di Padova, 35131 Padua, Italy 4Classe di Scienze Tecnologie e Società, Scuola Universitaria Superiore IUSS, 27100, Pavia, Italy 5Univ Paris Est Creteil and Université Paris Cité, CNRS, LISA, 94010 Créteil, France 6Synchrotron SOLEIL, L’Orme des Merisiers, Saint-Aubin, France 7Department of Engineering “Enzo Ferrari”, University of Modena and Reggio Emilia, 41125 Modena, Italy 8Sam Nujoma Marine and Coastal Resources Research Centre, University of Namibia, Henties Bay, Namibia 9Climatology Research Group, North-West University, Potchefstroom, South Africa anow at: INRAE, Palaiseau, France Correspondence: Paola Formenti (paola.formenti@lisa.ipsl.fr) Received: 8 February 2025 – Discussion started: 8 April 2025 Revised: 16 July 2025 – Accepted: 17 July 2025 – Published: 19 November 2025 Abstract. This paper presents the results of 3 weeks of aerosol sampling at the Henties Bay coastal site in Namibia during the Aerosols, Radiation and Clouds in southern Africa (AEROCLO-sA) field campaign in August–September 2017. The campaign coincided with a transition period between two synoptic regimes and corresponded to a significant change in the aerosol composition measured at the site and in particular of that of mineral dust. During August, the dust was natural windblown from the southerly gravel plains, with a composi- tion consistent with that previously observed in Namibia. In September, the dust was fugitive from anthropogenic mining, possibly with a minor contribution of smelting emissions in northern Namibia or as far as the Copper Belt in Zambia, one of the regional hotspots of pollution. Chemical analysis of filter samples highlights the difference in elemental composition, in particular heavy metals, such as As, Cu, Cd, Pb, and Zn, but also silicon, in the anthropogenic dust. The metal solubility of the natural dust was higher, including that of iron (up to 5 % compared to less than 1 % for anthropogenic dust). Anthropogenic dust was associated with slight higher content of iron oxides and a larger proportion of coarse particles. Additionally, we found that the iron solubility, and, more in general, the metals’ solubility, correlated to the high concentrations of fluoride ions which are attributed to marine emissions from the Namibian shelf. In a renewed manner, these results highlight the importance of ocean–atmosphere exchanges affecting both the atmospheric composition and the marine biogeochemistry in the Benguela region. Published by Copernicus Publications on behalf of the European Geosciences Union. 16128 P. Formenti et al.: Composition of anthropogenic and natural mineral dust aerosols in Namibia 1 Introduction Mineral dust is an abundant component of the global atmo- sphere (Kok et al., 2023). Dust particles in the atmosphere are released by the natural wind erosion of natural arid and semi- arid areas of the globe. However, between 20 % and 30 % of global dust emissions are also contributed by anthropogenic activities such as labouring of bare soils for agriculture, pas- ture, or construction but also fugitive dust from mining and road traffic activities (Knippertz and Stuut, 2014; Chen et al., 2023). Mineral dust is a strong regulator of the Earth’s cli- mate and environment (Kok et al., 2023). In the atmosphere, it contributes to both the direct and indirect radiative effects on climate by scattering and absorbing solar and terrestrial radiation and forming cloud droplets in the liquid and ice phases (Kok et al., 2023). It also affects the atmospheric com- position and oxidative capacity by acting as a source or a re- active sink of species from the gas phase (Usher et al., 2003). It also acts as an irritating agent for the upper respiratory system and a vector of bacteria and infections (Adebiyi et al., 2023). By deposition, mineral dust can provide nutrients and pollutants to the sea water, changing the ocean’s primary production (Knippertz and Stuut, 2014). These considerations apply to the west coast of south- ern Africa, and Namibia in particular, a hyper-arid climate where many dust sources co-exist (Vickery et al., 2013). Nat- ural mineral dust is emitted from coastal riverine sources, salty pans such as the Etosha, and large gravel plains ubiqui- tous around the country (Vickery et al., 2013; Dansie et al., 2017a; von Holdt and Eckardt, 2018; Klopper et al., 2020; Shikwambana and Kganyago, 2022; Desboeufs et al., 2024). These sources are active throughout the year as emissions occur under various wind regimes (von Holdt and Eckardt, 2018). Natural mineral dust from Namibia is transported within the shallow boundary layer but being able to reach as far as Eastern Antarctica through long-range transport (Gili et al., 2022). Previous research in Namibia has shown that natural mineral dust from the coastal riverbeds and the gravel plains might contribute to oceanic productivity, par- ticularly along the coast (Dansie et al., 2022). This research also pointed to iron as a highly soluble element in both the soil and windblown aerosol fraction and the control for the impact of dust on oceanic productivity (Dansie et al., 2017a, b, 2018; Desboeufs et al., 2024). Furthermore, coastal pollution is an emerging issue of the present-day world (Strain et al., 2022). Increased human ac- tivities and coastal developments are quickly affecting the air quality but also the aquatic environment and biodiversity (Micella et al., 2024). Indeed, and despite its low popula- tion, Namibia also has intense and emerging economic ac- tivities such as mining (various heavy elements, including uranium; Mileusnić et al., 2014; Sracek, 2015; Liebenberg- Enslin et al., 2020) and marine traffic transporting merchan- dise along the coast of Africa and towards South America (Tournadre, 2014; Klopper et al., 2020). These activities re- lease fugitive dust from the mine locations as well as from the numerous road constructions from and to the major na- tional harbour, Walvis Bay (https://mwt.gov.na/projects, last access: 26 November 2024). In Namibia, the accumulation of heavy metals in the shore and coastal waters due to coastal mining (Onjefu et al., 2020) has been previously documented (Sylvanus et al., 2016; Omoregie et al., 2019; Nekhoroshkov et al., 2021). Furthermore, in the austral wintertime, Namibia is affected by anti-cyclonic circulation, resulting in the trans- port of light-absorbing particles, likely from forest fires and mining areas such as the Zambian Copper Belt (Formenti et al., 2018; Aurélien et al., 2022; Martinez-Alonso et al., 2023; Kříbek et al., 2023). The composition of these emissions is little characterized to date, though they have the potential to alter the oceanic productivity and microbial biogeochemistry (Adriano, 2001; Jordi et al., 2012; Mahowald et al., 2018; Yang et al., 2019). In this paper, we present a case study analysis of the differ- ences and similarities of the composition of natural and an- thropogenic mineral dust sampled during the ground-based field campaign of the Aerosols, Radiation and Clouds in southern Africa (AEROCLO-sA) project (Formenti et al., 2019). The campaign was conducted in August–September 2017 in Henties Bay (22°6′ S, 14°30′ E; 20 m a.s.l.) along the Namibian coast. Based on analysis of the chemical composition and mete- orological fields, we demonstrate the origin of the anthro- pogenic dust and contrast its elemental composition, iron mineralogy and solubility, and the type of organic matter with respect to those of natural dust measured at the be- ginning of the campaign. Our analysis focusses on the iron mineralogy and solubility but includes, for the first time, the evaluation of the solubility of heavy metals transported with these emissions. 2 Experiment The AEROCLO-sA field campaign took place from 21 Au- gust to 13 September 2017 at the Sam Nujoma Marine and Coastal Resources Research Centre (SANUMARC) of the University of Namibia at Henties Bay (Formenti et al., 2019). This sampling site, that has operated in the long term as de- scribed by Formenti et al. (2018) and Klopper et al. (2020), was augmented with the PortablE Gas and Aerosol Sampling UnitS (PEGASUS; https://pegasus.aeris-data.fr/, last access: 24 January 2025) mobile facility for the time of the cam- paign. The PEGASUS facility consists of two marine contain- ers (20 ft or 6 m long) customized and equipped for atmo- spheric research (Formenti et al., 2019). Air sampling is per- formed with two high-volume aerosol inlets delivering ap- proximately 450 L min−1 each. At wind speeds between 5 and 10 m s−1, typical for coastal Namibia (see Fig. S1 in the Supplement), sampling is almost isokinetic for particles up Atmos. Chem. Phys., 25, 16127–16145, 2025 https://doi.org/10.5194/acp-25-16127-2025 https://mwt.gov.na/projects https://pegasus.aeris-data.fr/ P. Formenti et al.: Composition of anthropogenic and natural mineral dust aerosols in Namibia 16129 to 40 µm in aerodynamic diameter (Rajot et al., 2008), which hereafter we named total suspended particulate (TSP). The total sampled flow rate is distributed to online analysers and to multiple- and single-stack sample collection units for off- line analysis of the bulk and size-resolved chemical and min- eralogical composition, soluble fraction, and mixing state. The details of the online instrumentation relevant to this pub- lication are listed in Table S1. 2.1 Sample collection During the campaign, aerosol samples were collected during both the daytime (approximately 07:00–17:00 UTC) and the night-time (approximately 17:30–06:30 UTC). The sampling duration was marginally adapted in real time to the nature and the aerosol load of air masses using the readings of the local wind speed and direction and of the aerosol mass con- centration, also measured online. Four custom-made filter holders were used in parallel for collecting aerosols in the TSP fraction. These were loaded with (i) one Teflon filter (Zefluor®, 2 µm pore size diameter, 47-mm filter diameter), (ii) two polycarbonate membranes (Nuclepore®, 0.4 µm pore size diameter, 37 and 47 mm fil- ter diameter, respectively), and (iii) a quartz filter (Pall, 2500QAT-UP Tissuquartz, 47 mm filter diameter). The av- erage sampling flow rate varied between 20 and 30 L min−1. Two samples of the composition of particles smaller than 1 µm in diameter (hereafter named PM1 size fraction) were collected in parallel using two 4-stage Dekati® PM10 Im- pactors, both operated at 10 L min−1. For these two sam- plers we used 25 mm polycarbonate membranes on three im- pactor stages (> 10, 10–2.5 and 2.5–1 µm), while the final filter stage, where the PM1 fraction is collected, was a poly- carbonate membrane (Nuclepore®, 0.4 µm pore size, 47-mm filter diameter) and a quartz filter (Pall, 2500QAT-UP Tis- suquartz, 47 mm filter diameter), respectively. Before the campaign, Teflon and quartz membranes were cleaned for sampling organic aerosols. Teflon membranes were rinsed with dichloromethane and baked at 100 °C for 10 min. Quartz membranes were baked at 550 °C for 12 h. Both were conditioned in pre-baked aluminium foils. The polycarbonate membranes were used for measuring the in- organic and water-soluble fraction composition. The 37 and 25 mm membranes were used as purchased, while the 47 mm ones were acid-washed according to the protocol described in Desboeufs et al. (2024). All material was sealed and opened only before collection. Immediately after exposure, all sam- ples were sealed and stored at −18 °C in the deep freezer available in the PEGASUS facility, from which they were transported back to the laboratory. TSP filter samples were collected between 21 August and 12 September 2017, while PM1 samples were collected from 26 August 2017 onwards. In total, 36 TSP and 31 PM1 sam- ples were collected per filter type during the field campaign (including blanks). 2.2 Sample analysis 2.2.1 Elements and water-soluble ions The analysis of the elemental and water-soluble ion concen- trations was performed at LISA according to the protocols previously detailed in Klopper et al. (2020) and Desboeufs et al. (2024). The elemental concentrations of 24 elements (Na, Mg, Al, Si, P, S, Cl, K, Ca, Ti, V, Cr, Mn, Fe, Co, Ni, Cu, Zn, As, Sr, Pb, Nd, Cd, Ba) were measured by wavelength- dispersive X-ray fluorescence (WD-XRF) using a PW-2404 spectrometer (Panalytical, Almelo, Netherlands). The instru- ment was calibrated with mono- and bi-elemental certified elemental standards (Micromatter Inc., Surrey, Canada). The concentrations of light-weight elements (Na to Ca) in the TSP fraction were corrected for X-ray self-attenuation as de- scribed in Formenti et al. (2010), assuming a mean diameter of 4.5 µm to represent the average coarse particle size. Ele- ments heavier than Ca, as well as concentrations measured in the PM1 fraction, were not corrected. The measured atmo- spheric concentrations are expressed in ng m−3, and the rel- ative analytical uncertainty was evaluated as 10 % (see Klop- per et al. (2020) for the full description). The analysis of the water-soluble fraction was performed by extracting the filters with 20 mL of ultrapure water (MilliQ® 18.2 M� cm) for 30 min. The solution was divided into two sub-samples filtered to 0.2 µm of porosity (Nucle- pore). One-half was analysed by ion chromatography (IC) using a Metrohm IC 850 device equipped with a column MetrosepA supp 7 (250/4.0 mm) for anions and with a Met- rosep C4 (250/4.0 mm) for cations. The IC analysis provided the concentrations of the following water-soluble ions: F−, formate, acetate, MSA− (methanesulfonic acid), Cl−, NO−3 , SO2− 4 , oxalate, Na+, NH+4 , K+, Ca2+, and Mg2+. A calibra- tion with certified standard multi-ions solutions of concen- trations ranging from 5 to 5000 ppb was performed, and the uncertainty of the analysis was estimated to be 5 % (Klopper et al., 2020). The second half of the solution was acidified to 1 % with ultrapure nitric acid (HNO3) and analysed by a combina- tion of inductively coupled plasma-atomic emission spec- troscopy (ICP AES) using Spectro ARCOS Ametek® ICP- AES and by high-resolution inductively coupled plasma- mass spectrometry (HR-ICP-MS) using a Neptune Plus™ in- strument by Thermo Scientific™ as described in Desboeufs et al. (2024). The calibration curve was performed using stan- dard multi-element solutions ranging from 1 to 1000 ppt. The elemental fractional solubility (FS) of elements is calculated as the ratio between the dissolved and the total concentration. Organic carbon (OC) and elemental carbon (EC) were measured using a thermo-optical carbon analyser (Sunset Laboratory Inc.) on a 1.5 cm2 filter following the EUSSAR-II protocol (Cavalli et al., 2010). The Sunset analyser was cali- brated using a sucrose solution (purity> 99.5 %) in the con- centration range between 0.42 and 40 µg cm−2. The limit of https://doi.org/10.5194/acp-25-16127-2025 Atmos. Chem. Phys., 25, 16127–16145, 2025 16130 P. Formenti et al.: Composition of anthropogenic and natural mineral dust aerosols in Namibia quantification for total carbon and organic carbon is hence- forth estimated to be equal to 0.42 µg cm−2. An instrumen- tal blank and a control point with a sucrose solution at 10 µg cm−2 were done at the beginning of each day of anal- ysis. OC and EC concentrations are automatically calculated with the software OCBC835 (Sunset Laboratory). The opti- cal split point was manually verified to ensure their assign- ment. All the concentration values presented in this paper were corrected for the average concentration measured for their corresponding analytical blanks, which was almost equal to the limit of detection. 2.2.2 Iron mineralogy The quantification of iron oxides and the partitioning of iron species in the II and III oxidation state was performed by X- Ray Absorption (XAS) analysis at the Fe K-edge. Analysis was performed on the Teflon TSP filters only as the concen- trations of the PM1 filters were not high enough for this kind of analysis. XAS analysis was conducted at the SAMBA (Spectro- scopies Applied to Materials based on Absorption) line at the SOLEIL synchrotron facility in Saclay, France (Briois et al., 2011), according to the protocols and procedures pre- viously presented in Formenti et al. (2014) and Caponi et al. (2017). A Si(220) double-crystal monochromator was used to produce a monochromatic X-ray beam, which was 4000× 1000 µm2 in size at the focal point. The energy of the X-ray beam was calibrated with an external Fe foil standard before the experiments. The energy range was scanned from 7050 to 7350 eV at a step resolution of 0.2 eV. Aerosol samples were mounted in an external setup. A portion of each aerosol filter sample was cut and mounted on a carton board holder with five available positions and anal- ysed in fluorescence mode without prior preparation. The number of scans per sample was set between 50 and 200, de- pending on the iron concentration, to improve the signal-to- noise ratio. One scan acquisition lasted approximately 100 s for a total of 1.3 to 5.5 h of measurements for 50 to 200 scans. The spectral analysis was conducted with the FASTOSH software package developed at SAMBA. As described in Wilke et al. (2001) and O’Day et al. (2004), the oxidation state and the bonding environment of Fe in dust samples give rise to different features in the XAS spectra. In the pre-edge region, the shape of the XAS spectra is determined by elec- tronic transitions to empty bound states, which are strongly influenced by the oxidation state of the absorbing atom but also by the local geometry around the absorbing atom due to hybridization effects. Wilke et al. (2001) found that for Fe(II)-bearing minerals, the position of the centroid of the pre-edge is found at 7112.1 eV, whereas it is at 7113.5 eV for Fe(III)-bearing minerals. The position of the rising edge, which also depends on the oxidation state, is found at ap- proximately 7120 eV. In the X-ray Absorption Near Edge Structure (XANES) region, extending approximately 50 eV above the K-edge peak, features are determined by multiple- scattering resonances of the photo-electron ejected at low ki- netic energies. The speciation of Fe was obtained by the least-squares fit of the measured XANES spectra based on the linear combi- nation of mineralogical references. Fits were conducted on the first derivative of the normalized spectral absorbance in the energy region between 7100 and 7180 eV, corresponding to −30 and +50 eV of the K-edge. Only the fits with a χ2 closest to 1 were retained for further analysis. The reference standards were chosen based on the ex- pected iron mineralogy in the area (White et al., 2007; Heine and Völkel, 2010; Formenti et al., 2014; Sracek, 2015; Zhang et al., 2022). Standards for clays (illite and montmorrilonite) and iron oxides as goethite, magnetite, and hematite were taken from Formenti et al. (2014) and Baldo et al. (2020). The ferrihydrite standard was derived by the database of the Advanced Light Source, Lawrence Berkeley National Lab (Sirine Frakra, personal communication, 2008). Standards for metal-ligand complexes expected to form in fog droplets and deliquescent aerosol at high RH (Giorio et al., 2022) is provided in Table S2. 2.2.3 Organic analysis The water-soluble fraction of organic aerosols (WSOC) was extracted, purified using hydrophobic resin (Bond Elut ppl), and analysed by high-resolution mass spectrometry (HRMS), namely by a hybrid LTQ-Orbitrap equipped with an electro- spray source (ESI) operated in negative ion mode. All the samples were directly injected into the ESI source using a sy- ringe pump. In each case spectra were recorded in triplicates in two mass diapasons to decrease the number of ions in the detector: 50–500 m/z and 150–700 m/z. Raw spectra were treated following the laboratory procedure reported in Zhere- bker et al. (2024). Files were converted to ∗.mzML format us- ing msconvert with a vendor-recommended peak-picking al- gorithm (https://proteowizard.sourceforge.io/, last access: 18 December 2024), which was suitable for a series of in-house written Python scripts, which included de-noising, calibra- tion, formulae assignment, and blank subtraction. Only for- mulae presented in triplicates were retained. Diapasons were combined with removing lower-intensity duplicates. For- mulae assignment was performed considering only single- charged ions, ignoring anion radicals with the following atomic constraints: O/C ratio≤ 2, 0.3 0.3) as well as highly unsaturated (AIcon >0.5) compounds was observed. More- over, reduced (low O/C) saturated compounds appear to be unique for the P1 period (Fig. 3b). This supports the bio- genic source brought by south-westerly winds. Further, the contribution of continental dust with a clear anthropogenic contribution is reflected as unique highly unsaturated com- pounds in the P2 period as well as an increase in S-containing compounds (Fig. 3c). P3 was depleted with highly unsatu- rated compounds, with a relative dominance of saturated N- containing compounds. The aerosol sources are similar be- tween the P2 and P3 periods, which resulted in an insignif- icant amount of unique molecular assignment in the latter (Fig. 3d). In addition, the double-bond equivalent vs molec- ular mass diagram in the Supplement indicates an increase in the contribution of biomass-burning aerosols and possi- bly sulfate-enriched dust from smelting in the P2–P3 peri- Atmos. Chem. Phys., 25, 16127–16145, 2025 https://doi.org/10.5194/acp-25-16127-2025 P. Formenti et al.: Composition of anthropogenic and natural mineral dust aerosols in Namibia 16133 Figure 1. Time series of contributed concentrations (µg m−3, a, c) and pie chart of average contributions of the factors obtained from the PMF analysis applied to TSP (a, b) and PM1 (c, d) chemical compositions. Dates are reported as “DD/MM/YYYY hh:mm”. ods compared to the P1 period, which is in line with the air mass origin. Further details of the organic composition are reported in the Supplement. 3.2.2 Fluoride and MSA concentrations The P1 and P2 periods were also characterized by extremely high concentrations of fluoride (up to 10 µg m−3) as shown in Fig. 4, in line with what reported by Klopper et al. (2020) for the PM10 aerosols measured during 2016 and 2017 at the site. In September (P3a and P3b), the concentration of F− dropped to zero, as a consequence of the change in the origin of the air masses transported to the site. Fluoride is a naturally occurring ion in marine envi- ronments as well as in mineral dust (Fuge, 2019). In Namibia, the release of dissolved fluoride to the atmo- sphere is due to the evaporation of fluoride-rich ground- water (Sracek et al., 2015) or the erosion of mineral de- posits of calcium fluoride (CaF2, Onipe et al., 2020). Flu- oride is present in significant amounts (> 1 wt % F) in francolite, a carbonate fluorapatite mineral (typical formula Ca4.7Na0.2Mg0.1(PO4)2.6(CO3)0.4F1.28), which can be found in phosphorite deposits on the Namibian shelf, notably in the area between 23 and 25.5° S south of Henties Bay (Compton and Bergh, 2016; Mänd et al., 2018). This could be the origin of the excessive fluoride concentrations observed during the P1 period of the campaign. Atlas and Pytkowicz (1977) and Hossein et al. (2024) describe the mechanism by which F− could be released into seawater by dissolution. Upon dissolu- tion, the release of F− into the atmosphere can be attributed to the reaction with hydrogen in water to form hydrogen fluo- ride gas (or a solution of hydrofluoric acid; Anbar and Neta, 1967). The high content of fluoride in the Namibian soil is also documented and attributed to weathering and dissolu- tion of fluoride-containing minerals (Hossein et al., 2024). Not only did the origin of air masses detected at Henties Bay coincide with the locations of the marine deposits, but dur- ing P1 the fluoride content also correlated with major marine tracers (Na, Cl, S; correlation coefficients R2 = 0.87, 0.85 and 0.75, respectively). Fluoride correlated with calcium, both its sea-salt and non-sea-salt fractions (nss-Ca2+/F− ra- tio ranging from 0.1 to 0.3, as in Klopper et al. (2020), cor- relation coefficients R2 = 0.67 with nss-Ca2+ and 0.79 with Ca2+). Finally, fluoride also correlated with P, K, and Sr (cor- https://doi.org/10.5194/acp-25-16127-2025 Atmos. Chem. Phys., 25, 16127–16145, 2025 16134 P. Formenti et al.: Composition of anthropogenic and natural mineral dust aerosols in Namibia Figure 2. (a, c) Time series of the elemental concentrations of Cl− and Na+ in the TSP and PM1 fractions. (b, d) Time series of elemental ratio of Cl−/Na+ in the TSP and PM1 fractions. The grey panels represent the different meteorological periods. Error bars on concentrations represent the analytical errors. Error bars on ratios represent the sum of percent analytical errors on measured concentrations. Figure 3. Population density of all molecular compositions based on AIcon classes (a) and van Krevelen diagrams for only unique molecular assignments in samples under study in the three periods (b–d), where unique formulae were only determined in a sample from the designated period. The size of the points reflects relative intensities in the mass spectra (not used in the analysis). Atmos. Chem. Phys., 25, 16127–16145, 2025 https://doi.org/10.5194/acp-25-16127-2025 P. Formenti et al.: Composition of anthropogenic and natural mineral dust aerosols in Namibia 16135 Figure 4. Time series of the elemental concentrations of F− and MSA in the TSP (a) and PM1 (b) fractions during the field campaign. Missing data correspond to periods when the measured concentrations were below the detection limits. Error bars on concentrations represent the analytical errors. Error bars on ratios represent the sum of percent analytical errors on measured concentrations. relation coefficients R2 = 0.68, 0.91, and 0.21, respectively); the latter can replace Ca in the francolite mineral structure (Compton and Bergh, 2016; Rakovan and Hughes, 2000). Note that, despite its high concentrations, fluoride was not included in the source apportionment because it was not mea- sured during the whole field campaign. The concentrations of methanesulfonic acid (MSA), a tracer of marine biogenic productivity, averaged at 61± 26 ng m−3 in the TSP fraction and 46± 26 ng m−3 in the PM1 fraction. These values are consistent with the yearly average in the PM10 reported by Klopper et al. (2020). While concentrations of F− and MSA appear unrelated in the TSP fraction, they remain above the detection limit in the PM1 fraction, where they were measured starting from the P2 pe- riod only. While the F− concentrations showed a certain de- gree of variability, the MSA remained constant with time. 3.2.3 Mineral dust composition Figure 5 presents the time series of the elemental concentra- tions of Al, Si, and Fe, major tracers of mineral dust, as well as of their ratios (Si/Al, Fe/Al, and Fe/Si) in the TSP and PM1 fractions. The elemental concentrations of Si and Al were up to 6 and 1 µg m−3 in the TSP fraction and up to 410 and 90 ng m−3 in the PM1 fraction, respectively. In the P1 and P2 periods, and with the exception of a peak value on 24 August, the Si/Al ratio was of the order of 3.8, consistent with the findings of Klopper et al. (2020) for natural mineral dust emitted from the Namibian gravel plains. After this date, that is during P3, the Si/Al ratio increased to values between 6 and 10 (TSP) and between 8 and 80 (PM1), indicating a very strong enrich- ment with respect to the composition of the regional mineral dust. In the TSP fraction, and regardless of the period, the Fe/Al ratio was in the range of 0.8–1.2, as previously found for the natural gravel plain dust in the area (Eltayeb et al., 1993; Klopper et al., 2020). Likewise, during P1 and P2 the Fe/Si ratio was consistent with those previous observations for mineral dust, and so was the Fe/Ca ratio (not shown), found in the range 0.2–0.8. However, during P3, the Fe/Si decreased from approximately 0.25 to 0.1, while the Fe/Ca ratio increased to between 0.09 and 0.15 (not shown). In the PM1 fraction, both the Fe/Al and the Fe/Si ratios were more variable with time (only the September period is doc- umented). The Fe/Al ratio was of the order of 1 as in the TSP fraction, except on the last day of the campaign when the ratio reached 18. The Fe/Si was higher between 29 Au- gust and 6 September (e.g. the P2 period), ranging from 0.2 to 0.4, and decreased to 0.1–0.2 in the last days of the cam- paign. That corresponded to the variability of several major elements and metals (K, Mg, Co, Cu, Nd, Ni, Sr, and Cd but Zn, As, and Pb in particular), whose ratios with Al were sig- nificantly higher during the last days of the campaign (7–12 September, Fig. S5). As for OC/Na+, the aerosol mineral composition of TSP during the P3 period could be split into https://doi.org/10.5194/acp-25-16127-2025 Atmos. Chem. Phys., 25, 16127–16145, 2025 16136 P. Formenti et al.: Composition of anthropogenic and natural mineral dust aerosols in Namibia Figure 5. Left panel, from top to bottom: time series of the elemental concentrations Al, SI, and Fe in the TSP and PM1 fractions. Right panel from top to bottom: time series of elemental ratio of Si/Al, Fe/Al and Fe/Si in TSP and PM1 fractions. Missing data correspond to periods when the measured concentrations were below the detection limit. Error bars on concentrations represent the analytical errors. Error bars on ratios represent the sum of percent analytical errors on measured concentrations. Atmos. Chem. Phys., 25, 16127–16145, 2025 https://doi.org/10.5194/acp-25-16127-2025 P. Formenti et al.: Composition of anthropogenic and natural mineral dust aerosols in Namibia 16137 two sub-periods before and after 6 September, with an en- richment in metals and OC at the end of the campaign. These observations are reflected by the PMF analysis, de- scribed in Text S2 in the Supplement. Note that, despite its high concentrations, fluoride was not included in the source apportionment because it was not measured during the whole field campaign. In the TSP fraction, the analysis separates two factors characterized by a high loading of metals. The first one is a “mineral dust” factor characterized by Al, Fe, and Si, as well as Ti, Mn, Na+, Ca2+, and SO2− 4 . Its contri- bution, significant only during the first part of the campaign, accounted, on average, for 5.8 % of total TSP mass. The sec- ond factor, called “Si-rich”, is characterized by the presence of a high loading of Si, As, and Pb, which are strongly corre- lated to each other (r = 0.97), and moderate loadings of Co, Cu, Ni, Nd, Sr, Zn, and EC, which are not correlated to Al or Fe, contrarily to “mineral dust”. The “Si-rich” factor, signifi- cant mostly during the P3 period, notably after the 6 Septem- ber, accounted for 23.3 % of TSP mass but was not found in the PM1 fraction where the concentrations of the majority of its tracers were very close to the detection limit. This is in agreement with the fact that the fraction of coarse particles with respect to the total number increased on the last days of the campaign (Fig. S6). The chemical fingerprinting of the “Si-rich” factor is sim- ilar to that reported from windblown dust from mines in the Otavi Mountainland in Namibia (Mileusnić et al., 2014; Sracek, 2015) as in the Zambian Copper Belt (Meter et al., 1999; Ettler et al., 2011, 2014; Mwaanga et al., 2019), a large and important mining area in the northern part of Zambia (Aurélien et al., 2022; Martínez-Alonso et al., 2023; Kříbek et al., 2023). Sracek (2015) found various associations of Fe with Cu, Co, Pb, V, As, Pb, and Zn for mines in Zambia and Namibia, characterized by different climates and ages of the core. At a receptor site on the Zambian Copperbelt in Zim- babwe, the analysis by Nyanganyura et al. (2007) identified the mixing of mineral dust and metal smelting emissions by distinguishing the long-range transport of aerosols contain- ing Fe, Al, and Si but also Co from a non-ferrous smelter component contributing to the fine aerosol fraction only and characterized by S, Zn, As, and Pb. Ettler et al. (2014) in- dicated that iron is enriched with respect to both Al and Si in dust liberated from Cu–Co metal smelters in the Zam- bian Copperbelt. However, Meter et al. (1999) showed that enrichment is variable on an event basis depending on the pyro-metallurgical processing of ores and their composition. We henceforth conclude that during P1 and P2 the aerosol composition was dominated by natural Namibian mineral dust sources with a composition very similar to the aver- age dust composition measured at the same site in 2016– 2017 (Klopper et al., 2020) and reaching the site within the southerly air flow. Conversely, during the last part of P3, the dust reaching Henties Bay was fugitive material from anthro- pogenic activities. The air masses during the second part of P3 could originate as far as from the Zambian Copper belt. These conclusions are further corroborated by the CAMS reanalysis shown in Fig. S7. During P1 and P2 the dust mass mixing ratio reached up to 120 µg m−3 (100 µg kg−1 on the CAMS map) at the surface in correspondence with the coastal sources in Namibia as a response to the prevailing south-easterly winds (Figure S3) dominating the near-surface circulation from 23 August to 3 September. Continental dust sources were activated on 22 August and 1 Septem- ber, in association with south-westerly near-surface winds, and on 28–29 August and 4–5 September, in association with near-surface convergence of south-westerly and north- easterly winds. From 6 September onwards, no remarkable dust activity was observed, while the circulation had changed (Fig. S7). The CAMS reanalysis also showed that the sul- fate mixing ratios at the surface reached 6 µg m−3 (5 µg kg−1 on the CAMS map) in the Zambian Copper Belt and in the urban area of Pretoria and Johannesburg (Fig. S7), also a known pollution hotspot (Martínez-Alonso et al., 2023). Sulfate aerosols remained close to their source regions un- til the end P2. With the installation of the continental high on the 3 September, sulfate aerosols were recirculated south- westwards towards Henties Bay during P3, in particular dur- ing 10–12 September. 3.3 Iron mineralogy The first derivative of the XANES normalized spectra for four samples collected during the different periods of AEROCLO-sA is shown in Fig. 6. The remaining spectra, in- cluding those of the standard minerals and compounds used for the deconvolution, are reported in Fig. S8. Because of the small quantities of particle mass collected on the filters, the XANES spectra are rather noisy. The main features can nevertheless be explored after smoothing. They all are rather similar. In the region between 7122 and 7128 eV, two to three peaks are present with different inten- sities depending on the sample. The peak at 7128 eV is mi- nor on sample T03 (P1 period), for which the peaks at 7122 and 7126 eV dominate. The peak at 7122 eV is not present afterwards. For samples T18 and T22 in the P2 period and the beginning of the P3 period, only the peaks at 7126 and 7128 eV are present, the intensity of the latter being higher than the one of the former, while those peaks have equal in- tensity on sample T032 in the P3 period. For mineral dust from northern Africa, Formenti et al. (2014) showed that the relative proportions of these peaks can be related to the type of clays but also to the presence of iron oxides in the form of hematite (Fe2O3) or goethite (FeOOH). Peaks between 7132 and 7136 eV are distinctive of clays and iron oxides in the form of hematite but are not present for goethite. In our sam- ples, a minor shoulder in this spectral region is observed only for a few samples (T24, T25, and T31) collected in Septem- ber. On the other hand, the pre-edge region between 7110 and 7116 eV is sensitive to the iron oxidation state. The majority of our samples seem to peak around 7113–7114 eV, indicat- https://doi.org/10.5194/acp-25-16127-2025 Atmos. Chem. Phys., 25, 16127–16145, 2025 16138 P. Formenti et al.: Composition of anthropogenic and natural mineral dust aerosols in Namibia Figure 6. First derivative of the four XANES normalized (black lines) spectra measured during AEROCLO-sA and corresponding to different periods and mineralogy. The red lines correspond to the fitted spectra. The contribution of the individual standards to the total measured signal is also reported. The dotted lines represent the contributions smaller than 10 %, which have been multiplied by a factor of 10 to ease their visualization. ing that iron is predominantly in the Fe(III) oxidation state. Only for a few samples (T10, T25, T26, T30, and T37) is the pre-edge peak closer to 7112 eV, indicating that Fe(II) could be the predominant oxidation state. Several attempts of least-squares reduction were done with a variable number of references to reflect the many miner- alogical forms in which iron can be found and verify the sta- bility of the solution. While the relative proportions might have changed by a few percent, the overall repartition was found to be consistent and independent of the selected refer- ences. The average least-squares apportionment of the total TSP elemental iron is presented in Table 1 in terms of the mean fractions par sampling period and mineralogical classes. The largest contribution to the total iron is by clays, be- tween 42 % and 58 %, with illite and montmorillonite con- tributing in equal proportions. While a clear temporal trend cannot be defined, the contribution of clays is lowest dur- ing the latest sampling period (6–12 September 2017). The second largest contribution is by iron oxides, accounting for between 38 % and 45 % of the total iron throughout the sam- pling period. The contribution of FeO, iron oxide in Fe(II) form, is low and extremely variable from sample to sam- ple and not necessarily retrieved for samples in which a shift towards the Fe(II) seems evident in the pre-edge region (T10, T25, T26, T30, and T37). The P3 period is also char- acterized by the lowest contribution of Fe(III) oxide (64 % vs 72 %–75 %). Ferrihydrite (14± 7 % of total iron) and goethite (8± 6 % of total iron) showed their highest contribu- tions during P2 (21 % and 12 % respectively), while hematite (8± 6 of total iron) was highest in September (P3). Sracek (2015) found that the formation of secondary hematite is Atmos. Chem. Phys., 25, 16127–16145, 2025 https://doi.org/10.5194/acp-25-16127-2025 P. Formenti et al.: Composition of anthropogenic and natural mineral dust aerosols in Namibia 16139 Table 1. Apportionment of total iron (percent mean and standard deviation) by the least-squares deconvolution of the XANES spectra obtained on the filter samples indicated in the first row. Results are grouped by period and by mineral class. 21–31 Aug 2017 1–2 Sep 2017 2–7 Sep 2017 8–12 Sep 2017 T01–T14 T15–T18 T20–T27 T28–T38 Clays 49± 13 58± 12 53± 11 42± 10 Goethite 10± 4 9± 2 6± 5 6± 3 Hematite 7± 5 8± 7 15± 11 9± 7 Magnetite 10± 5 9± 8 15± 11 14± 6 Oxalate 4± 4 3± 4 3± 4 5± 7 Pyrite 7± 5 3± 4 4± 5 7± 4 Ferrihydrite 17± 7 14± 12 8± 4 16± 4 favoured by tropical climate conditions in mines in Zam- bia compared to Namibia. In contrast to northern African dust, the least-squares reduction shows that the presence of magnetite is significant in the dust collected during the cam- paign, contributing 10 %–15 % to the total iron oxide frac- tion. Magnetite can be found in sediments in the Erongo re- gion of coastal Namibia (Lohmeier et al., 2021) but also in anthropogenic emissions, such as those from metal smelting (Rathod et al., 2020). Zhang et al. (2022) investigated the light-absorbing properties and single-particle composition from airborne measurements offshore central Africa during the ORACLES 2018 campaign, and attributed the presence of magnetite to the high-temperature conversion of hematite and/or goethite in biomass-burning plumes or to industrial or vehicular emissions, including from pyro-metallurgical pro- cessing in the Zambian Copperbelt. Pyrite (FeS) and Fe– oxalate complexes were also detected throughout the cam- paign, but their average contribution was extremely low, with the exceptions of 28–29 August 2017 (T10, approximately 19 %) and 11 September (T35–36, approximately 30 %). 3.4 Iron solubility Figure 7 presents the time series of the fractional solubility for Al, Si, and Fe, as well as those of fluoride (F−) and MSA measured in the TSP fraction during the field campaign. During P1 and P2, the fractional solubility was measurable and of the order of 2 %–8 % for Fe, 9 %–24 % for Al, 5 %– 17 % for Si, and 1.5 %–4 % for Ti (not shown). After that, during P3, their fractional solubility drastically dropped to 0.2 %–1.7 % for Fe and 0.2 %–2.6 % for Al, whereas the frac- tional solubility of Si and Ti was not measurable (dissolved concentrations under limit of detection). A similar behaviour was observed for most of the measured trace metals (As, Co, Cr, Cu, Ni, Pb, Ti, and Zn, Fig. S9). The percent fractional solubility of iron measured during P1 and P2 was of the same order of magnitude as the low- est solubility values reported at the same sampling site for PM10 dust particles by Desboeufs et al. (2024) for the pe- riod April to December 2017, when values as high as 20 % were measured when MSA in the particle phase was most concentrated. These authors attributed the enhanced solubil- ity to processing (photo-reduction) of the dust by gas-phase dimethyl sulfide (DMS) emitted by the coastal Benguela up- welling. In the present dataset, this association cannot be made. Figure 7 shows that the MSA concentrations were of the same order of magnitude throughout the campaign and actually slightly more concentrated during P2 and P3, when, on the other hand, the Fe fractional solubility was the low- est. Soluble Fe was also not correlated with oxalate (Pearson correlation coefficient r ∼ 0.3), another renown organic lig- and (Paris and Desboeufs, 2013). On the other hand, Fig. 7 shows that during P1 and P2, the temporal variability of the fractional solubility of Al, Si, and Fe closely followed that of the mass concentration of fluoride (correlation coefficients of 0.87, 0.85, and 0.81, re- spectively). Fluoride has been identified to be a good ligand of metals in aqueous solution, notably Fe(III) in comparison to Fe(II) (Connick et al., 1956; Bond and Hefter, 1980). The abundance of fluoride ions could act to facilitate the metal complexation on the particle surfaces, potentially promot- ing their release from the bulk oxide and dissolution at the solid/liquid interface (Arnesen, 1998; Tao et al., 2022). In particular, F− may contribute to the disruption of the Si–O lattice bond by forming SiF2− 6 complexes at acidic pH (Mi- tra and Rimstidt, 2009). 4 Conclusive remarks The 3 weeks of aerosol sampling at the Henties Bay coastal site in Namibia during the AEROCLO-sA field campaign coincided with a transition period between two synoptic regimes: the dominance of southerly air flow, associated with the reinforcement of the South Atlantic anticyclone (22 to 31 August 2017), and the dominance of north-easterly air flow (1 to 12 September 2017), associated with the instal- lation of the mid-tropospheric continental high. These syn- optic regimes corresponded to a significant change in the aerosol composition measured at the site and in particular of that of mineral dust. During August and the first few days of September, the dust was natural windblown from https://doi.org/10.5194/acp-25-16127-2025 Atmos. Chem. Phys., 25, 16127–16145, 2025 16140 P. Formenti et al.: Composition of anthropogenic and natural mineral dust aerosols in Namibia Figure 7. (a) Time series of the fractional solubility of Al, Si, and Fe in the TSP fraction. (b) Time series of concentrations of F− (blue) and MSA (red) in the TSP fraction. The MSA concentrations are reported on the right axis of (b). Missing data correspond to periods when the measured concentrations were below the detection limit. Error bars on concentrations represent the analytical errors. Error bars on ratios represent the sum of percent analytical errors on measured concentrations. the southerly gravel plains with a composition consistent with that previously found in Namibia (Klopper et al., 2020). Later, the dust was fugitive from anthropogenic mining and possibly also from smelting emissions as far as in the Zam- bian Copper Belt. The anthropogenic influence in the latter part of the campaign was also documented by the composi- tion of the organic aerosol, which was rich in highly unsat- urated compounds as well as saturated N-containing com- pounds in the latter two periods, more typical of anthro- pogenic pollution. A second major difference in the compo- sition of the air masses was the high fluoride content until 2 September, attributed to emissions from the marine shelf south of Henties Bay. Taking advantage of these differences, this paper presents the first case study analysis of differences and similarities in the composition of natural and anthropogenic dust, with two key findings: (1) the elemental composition of the anthro- pogenic dust is enriched in silicon and heavy metals, notably As, Mn, Cu, Cd, Pb, and Zn, and depleted in Al; (2) metals in anthropogenic dust are less water-soluble than in the natural aeolian dust. In particular, the fractional solubility of iron in the natural dust ranged between 2 % and 8 % but remained lower than 2 % in the anthropogenic dust. This is rather un- expected when taking into account the current literature on anthropogenic dust being influenced by combustion, report- ing that the iron solubility would be the order of 50 % (e.g. Li et al., 2017; Ueda et al., 2023). There are various possible explanations for this: first of all, the mineralogy of iron. The most soluble form, ferrihydrite (Journet et al., 2008; Shi et al., 2012), was slightly more abundant in the natural dust, while the less soluble forms of iron (iron oxides such as hematite and magnetite) were more frequent in the fugitive dust, which, conversely, could be more efficient in absorb- ing light at short wavelengths. Secondly, during the first part of the campaign, the aerosol particles were smaller in size, which is known to promote particle solubility, both directly and indirectly, allowing more intense atmospheric process- ing (Hamilton et al., 2022). Thirdly, our results indicate in a very clear way the extent of which the solubility of iron is linked to the abundance of fluoride ions during the first part of the campaign. While we do not have insights into the mineralogical forms of the metals other than iron, the sim- ilar behaviour of their dissolved concentrations, in particu- lar Al and Si, suggests that the marine emissions of fluoride from the Benguela shelf could play a key role in sustain- ing the complexation of metals dust particles and facilitate their dissolution, supplementing the processing by DMS de- scribed for iron in Desboeufs et al. (2024). Such high con- centrations of F− ions not only are unexpected but also open questions for further studies in this environment. Similarly, regarding what is known for chloride or bromine (Finlayson- Pitts, 2010, Simpson et al., 2015), one cannot exclude re- cycling F− into reactive fluorinated radicals through hetero- geneous processes. This calls for further targeted reanalysis Atmos. Chem. Phys., 25, 16127–16145, 2025 https://doi.org/10.5194/acp-25-16127-2025 P. Formenti et al.: Composition of anthropogenic and natural mineral dust aerosols in Namibia 16141 of the organic matter sampled during this campaign in both the gaseous and particulate phases and for further laboratory work to investigate this quite poorly known chemistry. Fi- nally, our results suggest that, in the absence of processing by DMS or oceanic fluoride, the transport of mining dust, in- cluding from the Zambian Copper Belt, is unlikely to be a significant source of dissolved iron but also of elements such as Mn, Cu, and Zn, which are toxic to phytoplankton even at low concentrations and, if assimilated, could alter the oceanic productivity and microbial biogeochemistry (Adriano, 2001; Jordi et al., 2012; Mahowald et al., 2018; Yang et al. 2019). Future work should expand these results by addressing the frequency and intensity of those occurrences on a longer timescale, as well as the mineralogy of metals and their pro- cessing by marine emissions in the laboratory. Code availability. The FASTOSH XANES data analysis package is available for download at https://www.synchrotron-soleil.fr/fr/ lignes-de-lumiere/samba (last access: 2 March 2024). Data availability. All data are made freely available by the French national service for atmospheric data, AERIS, at https://pegasus. aeris-data.fr/catalogue/ (last access: 2 March 2025). Supplement. The supplement related to this article is available online at https://doi.org/10.5194/acp-25-16127-2025-supplement. Author contributions. PF coordinated the AEROCLO-sA project and funding, led the field campaign and the data analysis, and wrote the manuscript with contributions from all the co-authors. SM performed PMF analysis. AZ performed ESI-HRMS analysis and analysed data. CG collected samples and supervised PMF and ESI-HRMS analyses and their data interpretation. CB contributed to the interpretation of the dust solubility and composition. KD analysed the fractional solubility measurements. MG analysed CAMS reanalysis. GS performed back-trajectory calculations. SC performed XRF analysis, ST performed IC/ICP analysis, and FB and CDB performed XANES measurements under the supervision of GL. AF, JFD, AN, and SJP facilitated the field campaign and participated in it. Competing interests. At least one of the (co-)authors is a mem- ber of the editorial board of Atmospheric Chemistry and Physics. The peer-review process was guided by an independent editor, and the authors also have no other competing interests to declare. Disclaimer. Publisher’s note: Copernicus Publications remains neutral with regard to jurisdictional claims made in the text, pub- lished maps, institutional affiliations, or any other geographical rep- resentation in this paper. While Copernicus Publications makes ev- ery effort to include appropriate place names, the final responsibility lies with the authors. Special issue statement. This article is part of the special issue “New observations and related modelling studies of the aerosol– cloud–climate system in the Southeast Atlantic and southern Africa regions (ACP/AMT inter-journal SI)”. It is not associated with a conference. Acknowledgements. Authors are grateful to the AEROCLO-sA consortium for their work in the field and during the preparation of the field campaign and SANUMARC for hosting the field cam- paign. The authors wish to thank AERIS (https://www.aeris-data. fr/, last access: 2 March 2025), the French atmospheric Data and Service Centre, for providing the campaign website and organizing the curation and open distribution of AEROCLO-sA data. Financial support. This work was supported by the French Na- tional Research Agency under grant agreement no. ANR-15-CE01- 0014-01, the French national program LEFE/INSU, the French Na- tional Agency for Space Studies (CNES), and the South African National Research Foundation (NRF) under grant UID 105958. Chiara Giorio’s work was supported by the Supporting TAlent in ReSearch@University of Padova STARS-StG “MOCAA” and a BP Next Generation fellowship awarded by the Yusuf Hamied Depart- ment of Chemistry at the University of Cambridge. This research re- ceived additional resources through the “The role of Secondary Or- ganic Aerosols on the climate over the west coast of southern Africa (SOA-Clim)”, an international research project supported by the University of Cambridge and CNRS. Marco Gaetani was supported by the project “Dipartimento di Eccellenza 2023–2027”, funded by the Italian Ministry of Education, University and Research at IUSS Pavia. The PEGASUS facility receives funding as a national facility (instrument national) of the CNRS INSU. Review statement. This paper was edited by Lea Hildebrandt Ruiz and reviewed by Akinori Ito and one anonymous referee. References Adebiyi, A., Kok, J. F., Murray, B. J., Ryder, C. L., Stuut, J.- B. W., Kahn, R. A., Knippertz, P., Formenti, P., Mahowald, N. M., Pérez García-Pando, C., Klose, M., Ansmann, A., Samset, B. H., Ito, A., Balkanski, Y., Di Biagio, C., Roma- nias, M. N., Huang, Y., and Meng, J.: A review of coarse mineral dust in the Earth system, Aeol. 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Phys., 25, 16127–16145, 2025 https://doi.org/10.5065/D68S4MVH https://doi.org/10.1016/j.gexplo.2014.08.012 https://doi.org/10.3389/fenvs.2014.00064 https://doi.org/10.1175/BAMS-D-14-00110.1 https://doi.org/10.3389/fmars.2022.918984 https://doi.org/10.3390/separations9120422 https://doi.org/10.1002/2014gl061786 https://doi.org/10.5194/acp-23-10117-2023 https://doi.org/10.5194/acp-23-10117-2023 https://doi.org/10.1002/grl.50968 https://doi.org/10.1080/03736245.2017.1339627 https://doi.org/10.3390/atmos10070414 https://doi.org/10.1016/j.geomorph.2006.08.014 https://doi.org/10.2138/am-2001-5-612 https://doi.org/10.5194/acp-22-9199-2022 https://doi.org/10.1021/acs.est.4c06749 Abstract Introduction Experiment Sample collection Sample analysis Elements and water-soluble ions Iron mineralogy Organic analysis Ancillary products Air mass back trajectories Atmospheric circulation Positive matrix factorization analysis Results Air mass origin and local meteorology Aerosol composition and origin Marine aerosols Fluoride and MSA concentrations Mineral dust composition Iron mineralogy Iron solubility Conclusive remarks Code availability Data availability Supplement Author contributions Competing interests Disclaimer Special issue statement Acknowledgements Financial support Review statement References