# Volcanic aerosols captured by plants: A study of nanoparticles and their chemical composition

Marine Gelin, Mickaël Tharaud, Marc F. Benedetti

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Marine Gelin, Mickaël Tharaud, Marc F. Benedetti. Volcanic aerosols captured by plants: A study of nanoparticles and their chemical composition. Science of the Total Environment, 2025, 963, pp.178505. 10.1016/j.scitotenv.2025.178505. hal-04934442v2

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Submitted on 10 Feb 2025

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Volcanic aerosols captured by plants: a study of nanoparticles and their
chemical composition.

Gelin Marine, Tharaud Mickael and Benedetti Marc F.*

Université Paris Cité – Institut de Physique du globe de Paris, CNRS,
F75005 Paris, France

*Corresponding author
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Abstract :

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Nanoparticles (NPs) exhibit high reactivity and mobility in the environment, and a significant capacity to penetrate living organisms, potentially leading to harmful effects. Volcanoes are the second major source of natural NPs emitted into the atmosphere, with an estimated flux of 342 Tg/year. Few studies have focused on their fate. Thanks to technological advances in single-particle inductively coupled plasma mass spectrometry (spICP-MS), this trend is starting to reverse. La Soufrière volcano in Guadeloupe, chosen as a case study, exhibits increasing hydrothermal activity since its last eruption in 1530. This study aims to characterize NPs produced during volcanic activity by analysing ancient ash deposits, as well as those formed during periods of volcanic inactivity by examining condensates near fumaroles, as ultrafine particles are primarily generated through gas condensation. In this study, plants are utilized as samplers for NPs produced by fumarole activity. The use of a ICP-MS time-of-flight in single particle mode (spICP-ToF-MS), combined with data processing techniques such as hierarchical agglomerative clustering, enables the detailed characterization of NPs by determining their multi-element composition, concentration, and mass distribution. The results demonstrate that plants can effectively serve as samplers, even under the extreme environmental conditions present at the volcano's summit. However, differences in their efficiency at trapping particles on leaf surfaces can be attributed to varying physical characteristics of the plants. The spICP-ToF-MS analysis identified three types of multi-elemental NPs (NP-Al+Si, NP-Al+Fe, NP-Ti+Al) and three mono-elemental NPs (NP-Al, NP-Si, NP-Fe). Additionally, NPs containing trace elements were detected exclusively in undiluted *Sphagnum* pore water, where one tri-elemental NP (Sr-Ce-La), one bi-elemental NP (Ce-La), and nine mono-elemental NP families (Cr, Cu, Zn, Sr, Y, Zr, Ba, La, Ce) were identified. Elements with potential negative effects on biota such as Cu, Zn, and Cr were also highlighted. Furthermore, the composition of the total of NPs (excluding families) is compared with elemental ratios from materials of different origins (volcanic, detrital, atmospheric) to validate their volcanic source.
38 I – Introduction

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40 Natural colloids and nanoparticles (NPs) are mainly produced by (bio)-geochemical or mechanical
41 processes due to volcanic activity, cosmic dust, alteration and wind erosion of rocks, combustion of
42 biomass, sandstorms, chemical precipitation (Hochella et al. 2019). While colloids are particles < 1 µm,
43 NPs are by definition particles ≤ 100 nm in all three dimensions, which exhibit high reactivity (Lowry
44 et al., 2012). All these particles, naturally occurring or anthropogenically produced, interact with each
45 other within the critical zone, influencing the biogeochemical and environmental cycles.

46 Understanding the fluxes, chemical composition, and transformations (e.g., precipitation, dissolution,
47 aggregation) of NPs is crucial to assess their role as potential carriers of contaminants and their
48 environmental impacts

49 Hochella et al. (2019) quantified natural NP fluxes, with airborne particles from volcanic emissions and
50 dust storms estimated at 342 Tg/year. Around 236 Tg/year of these particles are deposited on land
51 downwind from their source after airborne transport. Given their significant flux, understanding the
52 cycling of natural NPs is vital, not only to predict their environmental impact but also to assess the
53 behavior of less abundant anthropogenic NPs. The transformations of NPs—chemical, physical, and
54 biological—complicate predictions of their fate, transport, reactivity, and toxicity (Louie et al. 2014).

55 For example, inhaled NPs can penetrate lung membranes and enter the bloodstream, posing potential
56 health risks, including to vital organs such as the brain (Geiser and Kreyling, 2010; Miller et al., 2017).

57 Volcanoes emit NPs both during eruptions (via ash dispersal) and through the condensation of
58 magmatic gases during periods of inactivity. While the fate of volcanic ash has been widely studied,
59 ultrafine volcanic particles (NPs, < 100 nm) have been less investigated (Ammann and Burtscher, 1990;
60 Oberbeck et al., 1982; Reich et al., 2009; Rietmeijer and Mackinnon, 1997). Recent advances in
61 analytical techniques, such as single-particle inductively coupled plasma mass spectrometry (spICP-
62 MS), have increased research on volcanic NPs (Ermolin et al., 2021, 2018; Maters et al., 2016). These
studies have identified the presence of potentially toxic metals and essential nutrients within volcanic NPs, but links between these elements and major components of the volcanic ash remain unclear (Ermolin et al., 2021). Trejos et al., (2021) studied interactions between volcanic and anthropogenic NPs in the Andes, finding that porous volcanic NPs could sequester anthropogenic particles containing toxic elements like As, Hg, Cd, Pb, and V. These findings highlight the potential for volcanic NPs to act as carriers of harmful substances. The transport of volcanic NPs, especially after eruptions, has also been investigated, with studies showing that NPs and colloids from volcanic ash can influence trace element distribution in surface runoff, subsequently reaching coastal waters (Tepe and Bau, 2014). This suggests that volcanic NPs may contribute to nutrient cycling in ecosystems, even in areas distant from the eruption site.

Fumarolic emissions, often rich in hydrogen sulfide ($H_2S$), sulfur dioxide ($SO_2$), and metals like Fe and Cu, also contribute to NP formation (Strambeanu et al., 2015). These gases cool and condense into solid, liquid, and residual phases, with ultrafine particles being a primary product of this transformation (Ammann et al., 1992). Despite the importance of fumarolic fluxes in NP emissions, their study has been limited by the challenges in quantifying gas emissions (Tamburello et al., 2019). Recent advances in NP analysis and characterization are beginning to fill gaps in the understanding of the mechanisms and interactions between major and trace elements in volcanic NPs. Research on the sequestration of toxic metals by these particles and their widespread distribution remains critical, as does the study of NP emissions from fumaroles. There is also a need for improved methods to quantify NPs emitted from fumaroles.

The aim of this study is to provide new information on the nature of NPs produced by volcanoes, which encompasses interactions at the interface of multiple environmental spheres. This involves characterizing NPs emitted in the atmosphere from fumarole gases during inactivity and comparing them with ash material released during active periods. The volcanic origin of these NPs is linked to lithospheric processes, which have resulted in the formation of a subduction zone system located in
the Lesser Antilles intra-oceanic volcanic arc. The area chosen for this study is located around the
volcanic dome of La Soufrière volcano. To analyse hydrothermal fumarolic NPs emissions through
condensation, biospheric interactions are explored by using plants to collect NPs around the dome.
Plants can act as passive samplers, as they sorb contaminants (aerosols, particles and chemical
pollutants) present in the air (Mills et al., 2014). Moreover, leaves have previously been used as
passive collectors in volcanic studies (Barros et al., 2015; Martin et al., 2012). Their ability to act as
NPs passive sensors will be determined by comparing the plant's rate accumulation per species and
verify the origin of the collected NPs. The analysis of ash NPs from the Montserrat volcano eruptions
that occurred between the years 1996 and 2010 and were collected in Guadeloupe is a valuable tool
for identifying the origin. The ICP-MS time-of-flight in single particle mode (spICP-ToF-MS) will be used
to characterize the NPs produced by condensation near the steam vents or associated to ashes. These
natural NPs may act as vectors for contaminants, due to their porous structures which could trap
anthropogenic NPs.
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II – Sampling site : La Soufrière de Guadeloupe

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Located in the southern part of the island of Basse-Terre, Guadeloupe, La Grande Soufrière is one of
the most active stratovolcanoes in the Lesser Antilles intra-oceanic volcanic arc, formed in a context
of subduction. Its andesitic complex with domes and lava cones has been active since the Lower
Miocene, with its last magmatic eruption recorded in 1530 (Komorowski et al., 2008). The volcano has
since exhibited intense hydrothermal activity, marked by phreatic eruptions in 1797-1798, 1836-1837,
and 1976-1977 (Boudon et al., 1989; Komorowski et al., 2008). Currently, strong degassing of
fumaroles at the summit of the lava dome generates plume emissions (Bernard et al., 2006). Gas
plume between 2016 and 2021 is dispersed westward with potential impacts on the population's
health (Rave-Bonilla et al., 2023). The surrounding area within a radius of 0.5-5 km features numerous
hot springs (blue circles, Figure 1), and Tamburello et al. (2019) noted an increase in fumarole activity
(red stars, Figure 1) near the lava dome and along the Breislack fault system over the past decade.
This coincides with heightened shallow seismicity in this region.

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The island of Basse-Terre Guadeloupe, characterized by a warm tropical climate (average 27°C) and high humidity (average 75%), experiences an oceanic subequatorial type of climate influenced by trade winds. The island undergoes a dry season from December to May and a rainy season from June to November. Precipitation rates are approximately 6 m.year⁻¹ at the top of La Grande Soufrière, gradually decreasing to 2.5 m.year⁻¹ on the coast (Dessert et al., 2015). Drier seasons leading to an increase in atmospheric particles of varying sizes, can potentially impact both the population and natural ecosystems.
121 III-Materials and methods

122 3.1 Nanoparticles collection around La Soufrière de Guadeloupe and ashes from
123 eruptions.

124 Conditions at the summit of La Grande Soufrière are unique and the direct collection of NPs emitted
125 by fumaroles is difficult. Therefore, plants close to the emitters have been used as samplers of the
126 NPs. The sampling of endemic species, represented by green leaves in Figure 1a, is carried out around
127 the volcanic dome near active fumaroles. The collection of plant was done in March 2022 on the trail
128 downwind of the active fumaroles at an area that is most accessible and where the vegetation is
129 luxuriant. Chemical proportions and fluxes of sulphur compounds depend on the location of the vents
130 at La Soufrière, and show significant spatial and temporal variations (Tamburello et al., 2019). Thus,
131 the leaves will likely record a combined NP signal integrating the various sources. In November 2022,
132 a leaf control sample of *philodendron* species was taken from the Capesterre catchment area (LCCRW,
133 16°04′19.0″N 61°36′35.7″W) which is located to the south-east of the volcano and in opposition to the
134 westward gas plume emission. All samples were taken above the hot springs line located around the
135 volcanic dome, mainly in the SW, S and NE sectors (Figure 1). This preferential spatial distribution is
136 explained by the structure of the volcanic edifice as well as the important development of clay
137 hydrothermal alteration along the preferential zones. In addition, Inostroza et al. (2023) suggest that
138 the scavenging of heavy metals is significant in the conduits of magmatic-hydrothermal volcanoes,
139 influenced by factors such as the depth of the magma chamber and the influx of meteoric water.

140 Three plant species were singled out as the most representative of the ecosystem surrounding the
141 volcano (see Figure 1 in Supplementary Material 1). These species were identified based on their
142 abundance on the volcano and their potential effectiveness in trapping NPs from the fumarole plume.

143 1. *Sphagnum erythrocalyx* (Fig Sup 1a): mosses recognizable by a capitulum of short, tightly
144 packed branches above taking the form of a pompom. The *Sphagnum* mosses, able to absorb
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up to 20 times its own weight in water due to large, empty, hyaline, porous cells (Weber et al., 2017), were considered as optimized sensors to capture atmospheric particles at the wet and acidic top of the volcano.

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2. *Ruyschia clusiifolia* (Fig sup 1b): a semi-endemic flowering plant, selected because of the presence of a whitish deposit on the surface of its leaves, interpreted in the field as having a volcanic origin.

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3. *Philodendron giganteum* (Fig sup 1c): remarkable for the size of its leaves and the length of its stems. This species has a large depositional surface that could be less influenced by the contribution of NPs from the soil due to its greater distance from the ground.

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In the field, *Philodendron* and *Ruyschia* leaves were collected 1 m above the ground to minimize the contribution of soil particles and stored in plastic bags while the *Sphagnum* moss was preserved in 50 mL plastic tubes. In addition, we analysed 6 ash samples from La Soufrière volcano in Montserrat which is a neighbouring island located about 86 kilometres from Guadeloupe and having a similar volcanic system. These are essentially bulk samples of fine ash that fell on Guadeloupe during several eruptions between 1996 and 2010 and were taken at different point on the volcanic island of Guadeloupe (J-C. Komorowsky personal communication).

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## 3.2 Recovery of NPs collected by plants and in ashes

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The water accumulated in the *Sphagnum* mosses was later recovered by inserting the plant material in a syringe and compressing it. The collected water was reserved in 14 mL plastic tubes wrapped in aluminium foil to avoid the proliferation of photo-synthetic micro-organisms. Samples were stored at 4°C before recovery and analysis of the NPs.

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The *Ruyschia* and *Philodendron* leaves were prepared in the laboratory of the Institut de Physique du Globe de Paris. First of all, the leaves were photographed in order to measure the surface using the Mesurim 2 software (free and open source) to normalize the concentrations of the solutions leached from the leaves (*Ruyschia*, *Philodendron*), expressed in number of NPs.L⁻¹, to the surface area (cm²).

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The plastic bag, in which they were stored, was rinsed with 50 mL of milli Q water in order to recover as many particles as possible, then the leaves were inserted into a 50 mL tube and the rinsing solution was transferred from the plastic bag into this same tube. Then, the latter was sonicated using a VWR Ultrasonic Cleaner (45 kHz, 30 W) bath for 30 min at room temperature, enabling a semi-quantitative approach. Indeed, sonication tests (0 min, 2 min, 5 min, 15 min, 30 min) performed on the same plant species revealed, after (scanning electron microscopy) observations, the presence of residual particles (< 2 µm) on the surface of the leaves even after sonication at 30 min. Nevertheless, the sonication time was limited to 30 min to avoid an increase in the temperature of the leaching solution causing potential chemical breakdown of the organic materials constituting the leaves.

Concerning the preparation of the 6 ash samples, 1 g of ash powder was added to 50 mL of ultrapure water and the tubes were shaken manually to homogenize the solution. They were then stored at ambient temperature overnight to allow the settle of the larger particles. The next morning, the top 10 mL of supernatant was collected and transferred into a 10 mL plastic tube and sonicated during 5 min prior analysis. Following Stokes law, the first 10 mL contains NPs of Fe₂O₃, Al₂O₃ and SiO₂ that cannot exceed a size of 800 nm, 550 nm and 700 nm respectively.

### 3.3 Sample analysis, data treatment and SEM imaging

Major elements (K, Na, Mg, Ca, S) were analysed in leaf leach solutions and *Sphagnum*'s water samples, using a Spectrogreen ICP-OES spectrometer. The leaching solutions were filtered with an ultrapure water pre-washed acetate filter with a cutoff of 0.22 µm and later acidified with distilled concentrated nitric acid (16N). The *Sphagnum*'s water samples were centrifuged for 10 min at 4000 rpm to remove foam debris and 4 mL of the solution was diluted with 3 mL of 2% HNO₃ (v/v). For each element calibration with inhouse standards with concentration ranging from 50 ppb to 30,000 ppb, were analysed. The reproducibility error is below 4%.

To detect and characterize NPs in leaf leachate or *Sphagnum* water samples, each sample underwent analysis twice at varying dilutions. Dilutions ranging from 5 to 250 were specifically tailored for the
analysis of NPs predominantly composed of major elements. Undiluted samples were analysed to
investigate NPs at the surface of *Philodendron* leaves, including the control sample and for the least
abundant NPs containing trace elements. All samples were analysed on an Inductively Coupled Plasma
Time-of-Flight Mass Spectrometer (ICP-ToF-MS, Vitesse, Nu Instruments) from the PARI platform at
the Institut de physique du globe de Paris (IPGP), France with instrument parameters described in the
table 1 in Supplementary Material 2. In brief, the mass spectrum from <sup>25</sup>Mg to <sup>238</sup>U was monitored for
a minute in single particle mode. After each sample, the introduction system was rinsed with 1% HNO<sub>3</sub>
(v/v) and ultrapure water for 3 minutes. Because of unresolved polyatomic interferences and high
dissolved concentration Na, Mg, P, S, Cl, K and Ca-bearing NPs could not be identified.

The transport and nebulization efficiency were established using certified 20, 40, 60, and 80 nm gold NPs from BBI Solutions (UK) at a known concentration (in NPs.L⁻¹) and a dissolved gold calibration ranging from 0 to 20 ppb. Transport efficiency (η<sub>transport</sub> = 3 %) is defined as the loss of ions in an NP along the path from the plasma to the detector whereas nebulization efficiency (η<sub>nebulization</sub> = 5 %) represents the loss of NPs from aerosolization in the spray chamber (Tharaud et al., 2021). Goodall et al. (1993) investigated the upper diameter for the particle size distribution of a slurry by developing a model for slurry particle transport. They defined the maximum diameters at 2.9 µm for a material of density 1 g cm⁻³, which decreased to 1.5 µm for a material of density 7 g cm⁻³. ICP-ToF-MS data were acquired with NuCodaq (version 1.5.8084.1, Nu Instruments, UK) and processed using NuQuant Vitesse software (version 1.2.8076.1, Nu Instruments, UK). Nu Quant allows the management of the isotopes of interest and separates the particles from the dissolved background. Particle events are separated from the background by setting each element threshold at the mean background plus 3 times the background standard deviation (3sd). A calibration curve (0, 0.1, 0.5, 1, 2, 5, 10, 20 ppb) of target elements (Al, Si, Ti, Cr, Fe, Cu, Zn, Sr, Y, Zr, Nb, Ba, La, Ce, Th) diluted with 1% HNO₃ (v/v) is used to quantify the mass of each element in individual NPs, subsequently transformed in molar fraction. This latter is hereby used as input for the data post-processing step. The method used here was developed by Tharaud et al. (2022) and uses hierarchical agglomerative clustering (HAC) to identify
the populations of NPs in the spICP-ToF-MS signal. The execution of HAC method provides several subsequent information like (1) the multi-elemental composition of the individual clusters, (2) the average mass of each NP clusters and (3) the proportion of each cluster used to observe their abundance in the analyte. To ascertain the reproducibility of the findings (Figure 2 in Supplementary Material 1), two solutions of *Sphagnum* were subjected to a 1:100 dilution from the sampling point number 4. The data underwent analysis using a uniform threshold (see above) for each constituent element. The mean error in number across all cluster approximates 1%, yet discrepancies are evident among NP families. Specifically, multi-elemental NPs exhibit a higher error (24%), whereas mono-elemental clusters demonstrate a lower error rate (2%). Nevertheless, the multi-elemental composition of each cluster is highly similar between both replicates.

Families of NPs obtained from spICP-ToF-MS measurements coupled with HAC are then compared with Secondary Electron Microscopy (SEM) images of particles on the surface of *Ruyschia* and *Philodendron* leaves taken at sample position n°7 and at LCCRW using a Field Emission Gun (FEG) SEM (Auriga 40, Zeiss) at the PARI platform at the Institut de physique du globe de Paris (IPGP), France.

Semi-quantitative chemical analyses were carried out in Energy Dispersive Spectroscopy (EDS) mode using an acceleration voltage of 15 kV and a working distance of 8.5mm.

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## IV – Results

### 4.1 Concentration of recovered nanoparticles and bulk.

The HAC data treatment reveals 6 common NPs families made up of similar major elements (Si, Al, Fe and Ti) on the surface of the *Ruyschia* and *Philodendron* (included the control sample) leaves, the waterlogged *Sphagnum* moss and in the supernatant ash solution. The number concentrations (expressed in NPs.L⁻¹) of major elements-bearing NPs in all plant types and ashes, and the concentrations of trace elements-bearing NPs for *Sphagnum* only, are listed in Tables 2, 3, and 4 in
Supplementary Material 2 before being normalised to the surface area of the leached leaf (cm²). In contrast to the bulk analysis results (Table 5 in Supplementary Material 2), which show a concentration trend for S (the dominant element) in the *Sphagnum* solution with the highest concentration at the sampling position n° 4, no concentration trend is observed based on sampling position for the NP analysis. However, according to Figure 2, *Ruyschia* leaves accumulate a greater quantity of NPs than *Philodendron* leaves, regardless of their composition. It is therefore relevant to investigate the factors that control the rate of accumulation on plant surfaces.

## 4.2 Chemical composition of nanoparticles according to plant species and ashes

The Figure 3 displays the average composition of the different families of NPs containing at least 2 major elements detected for all the plant species and different eruptions of ashes. The 6 families are composed of 3 multi-elemental NPs, one cluster (Clus-AlSi) represents an aluminosilicate group where Si is the most abundant element (less pronounced in the control sample) and Al and Fe are the other two major elements but present in lower amounts. The second cluster (Clus-AlFe) is mainly composed of Al with smaller amount of Fe. The third cluster (Clus-Ti) is dominated by Ti with significant variable amounts of Fe or Al (Figure 3). There are also 3 mono-elemental clusters made up of Al (Clus-Al), Si (Clus-Si), and Fe (Clus-Fe) with very few additional trace elements (not shown here). To ensure an accurate representation of cluster proportions, it is crucial to confirm that mono-elemental clusters do not inadvertently include bi-elemental NPs in which the minority element falls below the detection threshold. For instance, a mono-elemental particles of aluminum (classified as Clus-Al) might correspond to a bi-elemental NPs containing both Al and Fe, as illustrated in Clus-AlFe Figure 3. However, if the Fe content in a NP falls below the quantification limit, the HAC algorithm categorizes it as Clus-Al due to its pure Al composition. To rectify this analytical bias, the average mass ratio (Al/Fe) is computed for Clus-AlFe, and an estimated mass of Fe is determined for each NP within mono-elemental Clus-Al, which primarily consists of the dominant element in Clus-AlFe. If the calculated Fe mass exceeds the quantification limit, the NP is deemed truly mono-elemental; otherwise, it may be bi-elemental. This process is repeated for both bi-elemental and mono-elemental clusters. The limit
271 of detection (in fg) and the proportion of genuine mono-elemental NPs within Clus-Al and Clus-Si is
272 provided in table 6 in Supplementary Material 2. Notably, Clus-Al and Clus-Si are found to comprise
273 approximately 100% of mono-elemental NPs composed exclusively of Al and Si, respectively, across
274 all analysed species.

275 NPs containing trace elements were detected only in undiluted *Sphagnum* extraction solutions. The
276 leaching solutions from *Ruyschia* and *Philodendron* leaves were not sufficiently concentrated in these
277 elements, preventing effective detection. The undiluted *Sphagnum* extraction solutions (Figure 3 in
278 Supplementary Material 1) contained NPs distrusted among 9 mono-elemental clusters (Cr, Cu, Zn, Sr,
279 Y, Zr, Ba, La, Ce), 1 bi-elemental cluster (Ce-La) and 1 tri-elemental cluster (Sr-Ce-La). The proportion
280 of genuine mono-elemental NPs within Clus-Sr and Clus-Ce was also calculated (table 6 in
281 Supplementary Material 2). It seems that Clus-Sr is 100% mono-elemental, but this is not the case for
282 Clus-Ce. One third of the NPs belonging to this cluster have a theoretical quantity of La mole, below
283 the quantification limit, according to the measured Ce/La ratio = 6.46 (Figure 3 in Supplementary
284 material 1).

285 4.3 SEM characterization

286 The morphology and chemistry of those NPs at the surface of the leaves taken at the sample position
287 n°7 were observed (Figure 4 a and b for *Philodendron* leaf and 4 c and d for *Ruyschia* leaf in
288 Supplementary Material 1). To prevent leaf damage caused by the beam, the photographs were
289 captured using a moderate zoom level, thereby restricting the ability to selectively observe ultrafine
290 particles. The size of the particle on the surface of the leaves varies between 300 and 900 nm,
291 appearing as sub-rounded droplets. Based on their chemical composition, particles can be divided into
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293 - Aluminosilicate particles (particles 6, 8, 10 to 12) having Si:Al ratios equal to 3.49, 3.31, 2.44,
294 8.64, 3.24, respectively.

295 - Aluminosilicate particles with Fe (particles 3,5) or K (particle 7) impurity.
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- Iron-bearing particles with impurities of Al, K, Mg (particle 1) or Al and Si impurities (particle 4).

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- Potassium-bearing particles with impurities of Fe and Al (particle 2).

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- Silicate particles (particle 9).

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Regarding the control leaf (Figure 4e in Supplementary Material 1), the observed particles exhibit significantly larger sizes, ranging from 1.80 to 5.55 µm, and possess a more complex chemistry, characterized by higher quantities of Mg, Cl, K, and Ca. These NPs are beyond the range of spICP-ToF-MS measurements due to their relatively large size, which prevents them from passing through the spray chamber. In addition, because of unresolved polyatomic interferences and high dissolved concentration, NPs bearing those elements could not be monitored resulting for instance in particles 13 and 15 categorized as aluminosilicate (Si:Al = 3.59) and silicate, respectively.

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# V – Discussion

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## 5.1 Factors governing the plant's rate of accumulation.

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Different mechanisms are involved in the accumulation of NPs by mosses and leaves. *Sphagnum* moss is advantageous for the detection of nanoparticles (NPs) containing trace elements. This is because sphagnum acts as a pre-concentration tool where NPs accumulate, mainly due to the presence of its pores, whereas other plant species tend to have NPs deposited on their surfaces, which can be washed away by different climatic conditions. Despite the fact that collected leaves are subject to a comparable NP concentration process and climatic conditions, a constant variation in the capacity of plants to accumulate particles on the surface of their leaves was observed between *Philodendron* and *Ruyschia* species on Figure 2 regardless of the composition of the NPs. In the Guadeloupe context, considering both the climatic conditions and the composition and origin of fumaroles, particle accumulation on the two plant types occurs via both wet and dry deposition. Particles deposited on leaf surfaces increase wettability, as many are composed of materials that are either readily wetted or dissolved in water, such as salts (Neinhuis and Barthlott, 1998). Sæbø et al. (2012) noted variations
in atmospheric particulate matter uptake rates among different species. These authors found no significant correlation between particulate matter accumulation and leaf surface roughness or leaf size across the tested species. However, they identify two crucial factors influencing particulate matter accumulation: leaf hair density and the quantity of leaf wax. Paull et al. (2020) also investigated various plant species to ascertain the leaf characteristics strongly influencing particle deposition. However, the diverse characteristics among plant species (such as stiffness, size, and hair density) posed challenges in attributing particle accumulation capacity to specific traits. One species, resembling *Philodendron giganteum*, *Philodendron xanadu* Croat, exhibited notably efficient particle accumulation, although it did not rank among the most efficient accumulators in this study. Previous research has indicated a higher rate of particle deposition on smaller leaves, likely due to their reduced susceptibility to wind-induced resuspension of accumulated particles (Leonard et al. 2016). These findings align with our observations, considering that *Ruyschia* leaves are considerably smaller. Additionally, *philodendron* leaves possess elongated stems compared to *Ruyschia* leaves, resulting in a broader vegetative axis, thereby increasing their exposure to wind.

## 5.2 Origin of major elements from leaf leachates and *Sphagnum* extracted water samples

NPs are collected on the leaf surface (*Ruyschia* and *Philodendron*) and inside the moss (*Sphagnum*). Even if these plants are collected around La Soufrière dome, NPs they captured can have different origins. The island of Guadeloupe is a complex system under the influence of different aerosol origins. It is influenced by marine aerosols enriched in Na, Mg, S, K and Ca, but also by Saharan dust, with a strong contribution between April and September, which enriches the Guadeloupe atmosphere with microparticles containing Al, Si, K, Ca and Fe (Dessert et al. 2020). During March and November (the months of sampling), the island seems to be more affected by sea salt deposits than dust (Xu-Yang et al., 2022). These studies however omit the fact that Guadeloupe's atmosphere is also affected by
volcanic emissions, even more so since the recent increase in fumarole activity (Tamburello et al., 2019).

First of all, bulk analysis (table 5 in Supplementary Material 2) show that the dominant element is S, probably in the form of SO₄²⁻. This represents a distinctive feature commonly observed in hydrothermal systems associated with andesitic volcanoes, specifically within the Lesser Antilles volcanic region, known for emitting sulfuric acid gases (Villemant et al., 2008). This observation supports the possibility that elements of volcanic origin were deposited on the surface of the leaves or released into the atmosphere, then sorbed onto the spongy organisms. Indeed, heavy precipitation promotes atmospheric washing, scavenging particulate matter from the air to the land surface (González and Aristizábal 2012). Contrary to the influence of atmospheric aerosols, our samples exhibit distinct S/Na ratios beyond the range calculated by Xu-Yang et al. (2022) in Figure 4. These ratios closely resemble those of hydrothermal fluids, as reported by Chen et al. 2014 and Villemant et al. 2005, suggesting a volcanic origin for the deposits collected on the leaves. Salaün et al. (2011) demonstrated, in their study of the La Soufrière volcano, that observed hydrothermal alterations, characterized by the presence of smectite, silica polymorphs, and the occurrence of pyrite/jarosite/gypsum, are consistent with features associated with alterations induced by low-temperature acid-sulphate fluids (<150°C). The dissolution of highly soluble sulphur-bearing particles (i.e. CaSO₄) during the leaching of leaves likely contributes to the elevated S/Na ratio, while the lower Ca/Na ratio may be attributed to the influence of sea salt, identified as the sole source of sodium according to Xu-Yang et al. (2022).

NPs are collected in two different ways: on the leaf surface (Ruyschia and Philodendron) and inside the moss (Sphagnum). Discriminating characteristics can be used to determine whether these NPs have a similar origin despite the sampling method i.e. the species. According to Figure 3, the NPs have a similar chemical composition of the main elements and molar ratios, but the similarity does not extend to the control leaves taken at LCCRW, since these NPs have a different Si/Al ratio in the largest
cluster: Clus-AlSi. The composition of Clus-AlFe is similar between all samples, but the proportion of this cluster in the control sample plant is 2 and 10 times higher compared to the plant sampled around the volcano and the volcanic ash, respectively. It can be interpreted that this cluster represents atmospheric background noise, which is diluted in the plant samples collected in the vicinity of the volcano and is not particularly noticeable in the raw product of volcanic ash. The mass of NPs within each cluster can serve as a distinguishing characteristic. While the spICP-ToF-MS technique does not directly measure NP size, it provides a mass distribution that is typically underestimated because elements such as oxygen (O), sulfur (S), and phosphorus (P) are excluded from the calculation. This limitation complicates the determination of the "true mass" and, consequently, the actual NP size, which requires additional assumptions regarding morphology, composition, and density. To improve accuracy, we present both the mean and dispersion of NP mass for each cluster, as shown in Figure 5. This figure displays the mass distribution of NPs collected around the volcano, along with those from the LCCRW. To estimate the corresponding size ranges for these masses, size distributions for NPs containing major and trace elements are provided in Figures 5 and 6 of Supplementary Material 1. NPs containing major elements appear to fall within the colloidal range (100 nm < NP < 1000 nm), while those with trace elements are likely within the NP range (≤ 100 nm). The NPs median mass as well as the dispersion for the three plant species collected around the volcano are consistent for each cluster; with average masses equal to 9.6, 1.4, 0.6, 0.9, 7.7, and 0.6 femtograms (fg) for Clus-Si-Al-Fe, Clus-Al-Fe, Clus-Fe, Clus-Ti, Clus-Si, and Clus-Al clusters, respectively. In leaves (*Philodendron, Ruyschia*), NPs accumulate on the surface, while in peat moss, they are trapped within large hyaline porous cells. However, no significant mass fractionation of atmospheric NPs with major elements is observed based on the plant used as a passive sensor. This aligns with the pore opening size of approximately 15 µm (Weber et al., 2017). For NPs containing trace elements, even if associated with larger major elements as shown by spICP-ToF-MS analysis, fractionation is unlikely since the pore size is drastically larger than the size range studied here (i.e., the colloidal range). However, NPs composed solely of essential trace elements (e.g., Cu, Zn) or low-mass oxides, sulfides, or phosphates may experience some
fractionation. In contrast, NPs from the control plant exhibit systematically higher masses (table 6 in Supplementary Material 2), with values 6, 5, 5, 14, 3, and 6 times higher for the respective clusters despite the slight reduction in the limit of detection for the control plant analysis. This mass shift towards higher mass combine to the different Si/Al ratio for the control sample suggests a different origin for the NPs sampled at LCCRW.

It is also important to consider the detrital origin of particles (originating from the soil), as they can be suspended by heavy rain or wind. In this region, the majority of particles originate from the erosion of weathering profiles. The LCCRW soils, developing under wet conditions, undergo a mineralogical transition from fresh andesite to gibbsite/allophane, and eventually to halloysite/Fe-oxide (Colmet-Daage and Lagache, 1965; Ndayiragije and Delvaux, 2004, 2003). These soils primarily consist of allophane with Si/Al ratios close to 1, which is significantly different from the Si/Al ratio measured in the Clus-Si-Al-Fe (> 2.5) for the plants and statistically close to that for the control sample in Figure 3. In-depth analysis of Si-Al-Fe molar proportions across various samples, including plant, ashes from Montserrat (NPs), eruptive products of La Soufrière eruption, aerosol filters and condensates, fresh basaltic andesite, weathered basaltic andesite, and soil collected in the eastern and western parts, shows that the NPs collected by leaves have a volcanic signature (Figure 6).

The Si, Al, Fe molar proportions in the total of NPs detected in this study (excluding families) are similar to those observed by Inostroza et al., (2023, 2022) and Boudon et al., (2008), as well as to the proportions determined for the NPs sampled in the Montserrat ashes demonstrating a volcanic origin. This is also supported by systematically lower Si/Al molar ratios measured for the control sample, more in line with those of weathered andesite or soils from the eastern part of the island of Guadeloupe (1.3), where its sampling took place (Henriet et al., 2008). The molar proportions of NPs from leaves, collected on the western flank of the volcano, cluster closely with aerosol and ash values, distinctly separated from data points corresponding to soils on the eastern flank, more closely resembling the control sample. Furthermore, these values do not resemble the soil values collected
on the western flank of the volcano, reinforcing the conclusion that the NPs we collected are primarily of volcanic origin, rather than derived from the resuspension of soil particles in the air. The NPs found in volcanic ash and those from fumaroles are likely to have distinct elemental compositions due to differences in their formation processes. Ash particles are primarily composed of silicates (e.g., Si, Al, Fe), resulting from magma fragmentation during eruptions. In contrast, NPs from fumaroles, which are produced by the condensation of magmatic gases, are expected to be enriched in sulfur, chlorine, and metal chlorides or sulfides (e.g., FeCl₂, CuCl) (Inostroza et al., 2024). Additionally, fumarole emissions may lead to NPs with unique chemical signatures depending on the gas composition and the phase of volcanic activity (Mandon et al., 2019). Therefore, we would expect fumarolic NPs to have different elemental fingerprints compared to ash-derived NPs, with variability depending on the eruption type, fumarole activity, and other factors.

### 5.3 Elemental composition of nanoparticles in volcanic aerosols and sphagnum:
comparing trace element enrichment and mineralogical associations.

Due to previously mentioned analytical constraints, Na, Mg, P, S, Cl, K and Ca-bearing NPs could not be identified making it more difficult to interpret the clusters in terms of mineralogical composition. Nevertheless, the elemental ratios measured can be compared with the published mineralogical data for our system

The mono-elemental clusters bearing major elements (Al, Fe and Si) might correspond to alunite ($KAl_3(SO_4)_2(OH)_6$), natrojarosite $NaFe_3(SO_4)_2(OH)_6$ and silica polymorph, respectively as these minerals were identified by Salaün et al., (2011) in hydrothermal weathering products of Guadeloupe's hydrothermal systems. The cluster compositions are consistent with the ICP-Q-MS analyses of aerosol filters collected approximately 10 m from the vent at three different sites (CS, NapN, G56) as reported by (Inostroza et al., 2023). These authors reveal that the plume exhibits an elevated concentration of specific lithophile elements (K, Ti, Si, Al, Mn, and Mg) and siderophile element (Fe), attributed to the leaching of rocks through hydrothermal processes. All the lithophilic and siderophilic elements
identified by (Inostroza et al., 2023) were detected using spICP-ToF-MS, with the exception of Mn not detected and K and Mg, which were not measured by this method. However, the presence of K and Mg was confirmed through ICP-OES and SEM analyses. (Table 5 in Supplementary Material 2 and Figure 4 in Supplementary Material 1). Inostroza et al. (2023) conducted SEM analyses on these aerosol filters, their investigation also encompassed the measurement of significantly larger particles, reaching dimensions of up to 310 µm, exhibiting a subrounded droplet morphology. They categorized particles into three groups: i) sulfur-bearing particles, ii) chloride-bearing fragments, and iii) rock particles abundant in silicon (Si) and other lithophile and siderophile chemical elements (Mg, Ca, K, Ti, Mn, Fe). Notably, solely particles belonging to the third group were identified here with SEM observation on the surface of leaves, with no presence of Cl or S bearing particles, potentially due to their dissolution during rain events.

Concerning trace element-bearing clusters, we cannot rule out the possibility that Ce, La, and Sr could be present as trace elements in minerals such as alunite, natrojarosite, and silica polymorphs. Salaün et al., (2011) identified these minerals as potential carriers of rare earth elements. The range of concentration of those trace elements cannot reveal an association between them and major elements as high dilution factor are needed to correctly quantify and analyse major element-bearing NPs by spICP-ToF-MS. It is however interesting to compare the chemical composition of the trace element-bearing NPs collected through *Sphagnum* extraction followed by spICP-MS analyses performed by Ermolin et al. (2018) on the NP-Colloidal fraction (20,000 Daltons – 1 µm) of ash emitted from two volcanoes with similar volcanism as La Soufrière in Montserrat or Guadeloupe. Ermolin et al. (2018) calculated enrichment factors (EF) for toxic and potentially toxic elements (Ni, Cu, As, Se, Ag, Cd, Sn, Te, Hg, Tl, Pb, Bi). The elements with the highest enrichment factor were: As, Se, Te, Hg and Bi, none of these elements were detected by spICP-ToF-MS at La Soufrière volcano. In contrast, our investigation also unveiled NPs containing trace elements such as Cu, Ce, La, and Y (refer to Table 4 in Supplementary Material 2 for elemental concentrations expressed in NPs.L⁻¹). These NPs were discernible within the undiluted *Sphagnum* extraction solutions. For Ermolin et al. (2018), Cu exhibited
the highest EF, while rare earth elements (REE) and Y were detected across all volcanoes, displaying much smaller EF. In this study, we calculated the EFs for Ce, La, Ba, Cu, and Cr, and compared them to the EF values of the same elements measured by Salaün et al., (2011) in silica polymorphs, smectite, and magnetite, identified as key phases in hydrothermally weathered materials. The EF was calculated using a formula that differs from that of Ermolin et al., (2018):

$$EF = \frac{\frac{m_{X_i-NPs}}{m_{Zr-NPs}}}{\frac{m_{X_i-fresh Andesite}}{m_{Zr-fresh Andesite}}}$$

Where $m_{X_i-NPs}$ is the mass of element X$_i$ in the NPs, $m_{X_i-fresh Andesite}$ is the mass of element X$_i$ in the fresh andesite, $m_{Zr-NPs}$ is the mass of element Zr in the NPs and $m_{Zr-fresh Andesite}$ is the mass of Zr in the fresh andesite. We selected andesite as the normalization rock because it represents the typical composition of volcanic materials in the region, particularly in volcanic arcs where intermediate volcanic rocks like andesite are common.

The average EF for Ce, La, Ba, Cu, and Cr across all seven sampling sites are presented in Figure 7. The similarity of EF values of this study compared to the one reported by Salaün et al., (2011) suggest that some of the Cu and Cr detected as mono-elemental particles may also be present as trace elements in larger NPs corresponding to silica polymorphs and smectite. For instance, a strong correlation is found between the average mass (in fg) of Si-bearing NPs and pure Cr-bearing NPs in sphagnum extraction solutions (Figure 7a in Supplementary Material 1). Additionally, the intermediate EF values for Ce, La, and Ba, shows that magnetite may also act as a carrier for these elements. As the major and trace elements were measured using different dilutions due to the significant differences in the number of NPs, other analyses with longer acquisition times on the more dilute solutions are necessary. This will make it possible to measure the major and trace element simultaneously and to count a higher number of particles in order to improve statistical reliability, which will enable us to confirm these hypotheses. Moreover, Figure 7b in Supplementary Material 1 shows the concentration of bi-elemental Ce-La nanoparticles (NPs) detected in a sphagnum solution together with Ce/La ratios
from NPs in volcanic ash (Ermolin et al., 2018) and fumarolic condensates (Inostroza et al., 2022). The observed Ce-La ratios in *sphagnum* align with those found in volcanic ash and condensates, which contain micron-sized minerals with major and trace elements. This supports the hypothesis that Ce and La are linked to larger particles, whose major elements are "blanked" during spICP-ToF-MS analysis due to overlapping of major element peaks and high average counts preventing to distinguish peaks from background.

502

## Conclusion:

According to the study on the origin of NPs collected by plants, despite the extreme precipitation conditions at the summit of La Soufrière, plants are good passive sensors thanks to a similar chemical composition in major elements of atmospheric NPs. However, their effectiveness as passive sensors vary from one plant species to another. *Philodendron* can be considered the least efficient of the 3 species, but the NP extraction protocol could be improved by trying to recover NPs from plant waxes. *Sphagnum* mosses have proved to be the best passive sensors, capturing NPs from atmospheric washing with an elemental signal (S/Na) that is more affected by volcanic activity.

Thanks to its multi-channel detection and (nearly-)simultaneous acquisition, spICP-ToF-MS is capable of obtaining the multi-elemental composition of a NP. Coupled with HAC, it allows us to determine the multi-elemental composition of NP families carrying major or trace elements. The main limitation is the difficulty in quantifying the total amount of NPs emitted by fumaroles or deposited by ash. For major element-bearing NPs, 6 families were highlighted with 3 multi-elemental (Clus-AlSi, Clus-AlFe, Clus-Ti) and 3 mono-elemental (Clus-Al, Clus-Si, Clus-Fe) clusters. While for trace element-bearing NPs, only detected in undiluted *Sphagnum* solutions, the HAC reveals 1 tri-elemental (Sr-Ce-La), 1 bi-elemental (Ce-La) and 9 mono-elemental (Cr, Cu, Zn, Sr, Y, Zr, Ba, La, Ce) clusters.

The mineralogy of a sample can be deduced by comparing molar fractions. However, the fact that aluminosilicate minerals (i.e., clays) can have varying Al/Si ratios with their structure as main
classification factor, makes interpretation more complicated. In addition, the relatively high quantification limits of spICP-ToF-MS and the presence of interferences, particularly O₂, prevent the detection of elements such as S and Cl, which are common in volcanic environments and crucial for mineral classification. The analysis of undiluted samples to characterize NPs carrying trace elements forces us to ignore certain major element masses due to peak overlapping and high average counts.

To address this, we calculated the average enrichment factors (EFs) for Ce, La, Ba, Cu, and Cr in our NPs and compared them with EF on hydrothermal weathering products. Mono-elemental Cu and Cr particles may exist as trace elements in larger NPs, such as silica polymorphs and smectite, while Ba is likely associated with magnetite or silica polymorphs.

By comparing the average mass of the different NP clusters between the sampling points around the La Soufrière volcano and a leaf control sample from the Capesterre River watershed, and by comparing the composition of the sampled NPs with the composition of NPs from different objects, we were able to determine that the origin of the NPs from this study is mainly volcanic. This work provides new insights into the chemistry of NPs that are released in fumaroles during the periods of volcanic inactivity and in ash during periods of volcanic activity. A study using filters near fumaroles could be useful for monitoring volcanic activity and/or health risks.

## Acknowledgments

Parts of this work were supported by IPGP multidisciplinary program PARI, and by Paris-IdF region SESAME Grant no. 12015908. This study contributes to the IdEx Université de Paris ANR-18-IDEX-0001.

This work could not have been done without logistical support from both INSU-CNRS observatories in Guadeloupe run by the IPGP: the Observatoire de l'Eau et de l'Erosion aux Antilles (OBSERA) and the Observatoire Volcanologique et Sismologique de Guadeloupe (OVSG). We would like first to thank the Parc National de Guadeloupe for allowing us to take plant samples in the protected area (authorization # 2021-21 within the framework of the FEDER IMMERGE project coordinated by C. Dessert). We would like to extend our sincere gratitude to Dr. Alain Rousteau of the University of the Antilles and Guyana
546 for his invaluable assistance in the recognition and selection of plant species. We also wish to express
547 our heartfelt thanks to Professor Jean-Christophe Komorowski of the Institut de Physique du Globe de
548 Paris for generously providing the ash samples from La Soufrière volcano in Montserrat that were
549 deposited on the island of Guadeloupe. Their contributions have been instrumental to the success of
550 this work. A special acknowledgment is due to Dr. Céline Dessert and Jolaine Ajax from the
551 Observatoire de l'Eau et de l'Erosion aux Antilles for their exceptional support and expertise
552 throughout this project. Their contributions have been crucial to our understanding and analysis of La
553 Soufrière de Guadeloupe. We are also grateful to Dr. Julien Bouchez from IPGP for his constructive
554 comments on the manuscript, which significantly enhanced the quality of our work.

555 CRediT author statement

556
557 Gelin, M.: Investigation, Methodology, Writing - Original Draft, Writing - Review & Editing

558 Tharaud M.: Supervision, Software, Writing - Review & Editing.

559 Benedetti MF.: Conceptualization, Funding acquisition, Supervision, Writing - Review & Editing.

560

561 Declaration of competing interest

562 The authors declare that they have no known competing financial interests or personal relationships
563 that could have appeared to influence the work reported in this paper.

564

565 Appendix A. Supplementary data

566 Supplementary Material 1: additional Figures including SEM images

567 Supplementary Material 2: spICP-ToF-MS and ICP-OES Data

568
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<table><tr><td>Figure 1</td><td>Map of La Soufrière volcano. Sampling locations of plant, active fumaroles and thermal springs represented by green leaves, red stars and blue circles, respectively. The control sampling point for plants was taken in Capesterre river watershed, located to the west of the volcanic dome. The map presented in this article was created using QGIS® software from Esri satellite images.</td></tr><tr><td>Figure 2</td><td>Number concentration of NPs (10<sup>5</sup>NPs/cm<sup>2</sup>) on the surface of ruyschia and philodendron leaves. Concentrations were calculated using the number of NPs in leaching solutions for all sampling points around La Soufrière dome.</td></tr><tr><td>Figure 3</td><td>Chemical composition (in mole %) of families of NPs containing at least 2 major elements detected for the leaves (philodendron, ruyschia) and the moss (sphagnum) sampled around La Soufrière volcano, the control (philodendron) and Montserrat's ashes deposited on Guadeloupe. The dilution fold (d.f.) and the number of samples representative of the number of 1min analyses is indicated.</td></tr><tr><td>Figure 4</td><td>Variation in sulfur (S) and calcium (Ca) concentrations, normalized to sodium (Na), in moles of plant leachates and extraction solutions, compared with samples from various sources. Volcanic sources include hydrothermal springs around La Soufrière dome (Chen et al., 2014), condensates from 1976-1977 (Chevrier and Le Guern, 1982), and 2010 fumaroles (Chen et al., 2014) on La Soufrière, Guadeloupe. Detrital sources are represented by river samples (Chen et al., 2014), while atmospheric sources are illustrated by rainwater collected at the volcano's summit (Dessert et al., 2015) and aerosols (Yang et al., 2022).</td></tr><tr><td>Figure 5</td><td>Boxplots representing the median and the dispersion of nanoparticle mass (in femtograms) per cluster for tri or bi-elemental clusters (Si-Al-Fe, Al-Fe, Ti-Fe-Al) and mono-elemental clusters (Al, Si, Fe) across different species (Philodendron, Ruyschia, Sphagnum) located around the Soufrière dome, compared with a control site in Capesterre watershed (Philodendron).</td></tr><tr><td>Figure 6</td><td>Ternary diagram of Si, Al, Fe molar proportions in all the nanoparticles (NPs) analyzed using spICP-ToF-MS (excluding families) and bulk elemental analyses of materials from various sources in the literature. Volcanic, detrital, and mixed volcanic/detrital origins are represented by circles, diamonds, and squares, respectively.</td></tr><tr><td>Figure 7</td><td>Comparison of the enrichment factor (EF) for trace elements measured in undiluted extraction solutions of sphagnum moss versus hydrothermal weathering products (magnetite, smectite, and silicon polymorphs) as characterized by Salaün et al. (2011) at La Soufrière volcano.</td></tr></table>
<figure><img src="image_2.png" /></figure>

Montserrat

Guadeloupe

Dominique
<figure><img src="image_3.png" /></figure>

Species

Ruyschia

Philodendron
Control (no d.f., 2 samples)

<figure><img src="image_4.png" /></figure>

Ahses (50 < d.f. < 250, 6 samples)

<figure><img src="image_5.png" /></figure>

Philodendron (no d.f., 7 samples)

<figure><img src="image_6.png" /></figure>

Ruyschia (d.f.= 5, 4 samples)

<figure><img src="image_7.png" /></figure>

Sphagnum (d.f. = 100, 7 samples)

<figure><img src="image_8.png" /></figure>
<figure><img src="image_9.png" /></figure>

<figure><img src="image_10.png" /></figure>

<figure><img src="image_11.png" /></figure>

<figure><img src="image_12.png" /></figure>

<figure><img src="image_13.png" /></figure>

<figure><img src="image_14.png" /></figure>

<figure><img src="image_15.png" /></figure>

<figure><img src="image_16.png" /></figure>

<figure><img src="image_17.png" /></figure>

Control

Philodendron

Ruyshia

Sphagnum

Fumarolic gas (Chen et al., 2014)

Hydrothermal springs (Chen et al., 2014)

Rivers (Chen et al., 2014 and Chevrier et Guern, 1982)

Atmospheric aerosols (Yang et al., 2022) and rain (Dessert et al., 2015)
<figure><img src="image_18.png" /></figure>

Species

Control

Philodendron

Ruyschia

Sphagnum
<figure><img src="image_19.png" /></figure>

Name, origin

★ Leaves NPs, This study

★ Control Philodendron NPs, This study

★ Ashes NPs, This study

★ Eruptive products of the Soufriere eruption (G. Boudon et al., 2008), Volcanic

★ Aerosol filters and condensates (Inostroza et al.2023, 2022), Volcanic

★ Fresh basaltic andesite (Ma et al. 2012), Volcanic

♦ Altered basaltic andesite (Ma et al. 2012), Volcanic/Detritic

● East soil (Henriet et al., 2008), Detritic

● West soil (Henriet et al., 2008), Detritic
<figure><img src="image_20.png" /></figure>

$$EF = \frac{\left( \frac{m_{X_i - \text{NPs}}}{m_{Zr - \text{NPs}}} \right)}{\left( \frac{m_{X_i - \text{fresh Andesite}}}{m_{Zr - \text{fresh Andesite}}} \right)}$$
Volcanic aerosols captured by plants: a study of nanoparticles and their chemical composition.

Gelin Marine, Tharaud Mickael and Benedetti Marc F.*

Université Paris Cité – Institut de Physique du globe de Paris, CNRS,
F75005 Paris, France

Supplementary Material 1
Supplementary Material 1

<figure><img src="image_21.png" /><figcaption>a) *Sphagnum erythrocalyx*</figcaption></figure>

<figure><img src="image_22.png" /><figcaption>b) *Ruyschia clusiifolia*</figcaption></figure>

<figure><img src="image_23.png" /><figcaption>c) *Philodendron giganteum*</figcaption></figure>

Figure 1: Photographs of the three plant species sampled around the volcanic dome of La Soufrière, Guadeloupe.

<figure><img src="image_24.png" /></figure>

Figure 2: Duplicate analysis (1min) of NPs carrying major elements from two *sphagnum* solutions taken at point 4 and diluted at 1:100.
<figure><img src="image_25.png" /><figcaption>Figure 3 : Chemical composition (in mole %) of families of NPs containing at least 1 trace elements detected for all the *sphagnum* extraction solution non diluted located around the Soufrière dome.</figcaption></figure>

<figure><img src="image_26.png" /></figure>

<table><thead><tr><th>Particle</th><th>1</th><th>2</th></tr><tr><th>Element</th><th>Mole %</th><th>Mole %</th></tr></thead><tbody><tr><td>O K</td><td>30.38</td><td>59.87</td></tr><tr><td>Mg K</td><td>0.22</td><td>0.00</td></tr><tr><td>Al K</td><td>9.46</td><td>2.56</td></tr><tr><td>K K</td><td>8.16</td><td>32.41</td></tr><tr><td>Fe K</td><td>51.79</td><td>5.16</td></tr><tr><td>Totals</td><td>100</td><td>100</td></tr><tr><td>Diameter (nm)</td><td>450</td><td>560</td></tr></tbody></table>

<figure><img src="image_27.png" /></figure>

<table><thead><tr><th>Particle</th><th>3</th><th>4</th><th>5</th></tr><tr><th>Element</th><th>Mole %</th><th>Mole %</th><th>Mole %</th></tr></thead><tbody><tr><td>O K</td><td>68.58</td><td>54.77</td><td>73.61</td></tr><tr><td>Al K</td><td>7.26</td><td>10.11</td><td>1.87</td></tr><tr><td>Si K</td><td>23.97</td><td>8.38</td><td>22.70</td></tr><tr><td>Fe K</td><td>0.19</td><td>26.74</td><td>1.82</td></tr><tr><td>Totals</td><td>100</td><td>100</td><td>100</td></tr><tr><td>Diameter (nm)</td><td>600</td><td>550</td><td>700</td></tr></tbody></table>
<figure><img src="image_28.png" /></figure>

<table><thead><tr><th>Particle</th><th>6</th><th>7</th><th>8</th></tr><tr><th>Element</th><th>Mole %</th><th>Mole %</th><th>Mole %</th></tr></thead><tbody><tr><td>O K</td><td>72.06</td><td>67.62</td><td>70.28</td></tr><tr><td>Al K</td><td>6.23</td><td>5.42</td><td>6.90</td></tr><tr><td>Si K</td><td>21.72</td><td>23.76</td><td>22.82</td></tr><tr><td>K K</td><td>0.00</td><td>3.20</td><td>0.00</td></tr><tr><td>Totals</td><td>100</td><td>100</td><td>100</td></tr><tr><td>Diameter (nm)</td><td>410</td><td>460</td><td>430</td></tr></tbody></table>

<figure><img src="image_29.png" /></figure>

<table><thead><tr><th>Particle</th><th>9</th><th>10</th><th>11</th><th>12</th></tr><tr><th>Element</th><th>Mole %</th><th>Mole %</th><th>Mole %</th><th>Mole %</th></tr></thead><tbody><tr><td>O K</td><td>62.75</td><td>64.77</td><td>67.96</td><td>67.04</td></tr><tr><td>Al K</td><td>0.00</td><td>10.24</td><td>3.32</td><td>7.78</td></tr><tr><td>Si K</td><td>37.25</td><td>25.00</td><td>28.71</td><td>25.18</td></tr><tr><td>Totals</td><td>100</td><td>100</td><td>100</td><td>100</td></tr><tr><td>Diameter (nm)</td><td>730</td><td>860</td><td>770</td><td>650</td></tr></tbody></table>

<figure><img src="image_30.png" /></figure>

<table><caption>Figure 4: Morphology (SEM) and chemistry of particles on the surface of leaves (a,b: *ruyschia*, c,d: *philodendron*) at the position n°7 and at Capesterre (e: *philodendron*).</caption><thead><tr><th>Spectra</th><th>13</th><th>14</th><th>15</th></tr><tr><th></th><th>Mole %</th><th>Mole %</th><th>Mole %</th></tr></thead><tbody><tr><td>O K</td><td>83.79</td><td>63.20</td><td>88.72</td></tr><tr><td>Mg K</td><td>1.17</td><td>4.03</td><td>0.00</td></tr><tr><td>Al K</td><td>2.79</td><td>0.00</td><td>0.00</td></tr><tr><td>Si K</td><td>10.01</td><td>0.00</td><td>2.73</td></tr><tr><td>Cl K</td><td>0.61</td><td>10.21</td><td>2.74</td></tr><tr><td>K K</td><td>0.00</td><td>9.52</td><td>2.52</td></tr><tr><td>Ca K</td><td>1.63</td><td>13.03</td><td>3.28</td></tr><tr><td>Totals</td><td>100</td><td>100</td><td>100</td></tr><tr><td>Diameter (um)</td><td>2.70</td><td>1.80</td><td>5.55</td></tr></tbody></table>

Carbon is ubiquitous in the spectrum during elemental analysis. However, when testing a part of the leaf where no particles were present, carbon and gold (the latter due to the metallisation of the sample) were the only elements detected by elemental analysis. For the purpose of comparison with spICP-ToF-MS analyses, we have excluded carbon and gold from our spectral representations, both elements being considered as background noise.
<figure><img src="image_31.png" /><figcaption>Figure 5: Boxplots representing the median and the dispersion of nanoparticle estimated size (in nm) per cluster for tri or bi-elemental clusters (Si-Al-Fe, Al-Fe, Ti-Fe-Al) and mono-elemental clusters (Al, Si, Fe) across different species (*Philodendron*, *Ruyschia*, *Sphagnum*) located around La Soufrière dome, compared with a control site in Capesterre watershed (*Philodendron*).</figcaption></figure>

The spICP-ToF-MS method cannot be used to obtain directly the size of nanoparticles. However the size can be calculated assuming a spherical geometry of the element and considering the simplest form of oxides (for example SiO2 for Si NPs events) for the density following the equation below:

$$d_{NP} = \left( \frac{6 \cdot m_{NP}}{\rho_{oxide} \cdot \pi \cdot f_a} \right)^{\frac{1}{3}}$$

where $d_{NP}$, $m_{NP}$, $\rho_{oxide}$, $f_a$ are respectively associated with the size of an NP (in nm), the mass of an NP corrected for transport efficiency (in ng), the density of the element in its simple oxidised form (in ng$^3$), the mass fraction in the NP of the analysed element (in %).
<figure><img src="image_32.png" /></figure>

Figure 6 : Boxplots representing the median and the dispersion of nanoparticle estimated size (in nm) per cluster for tri or bi-elemental clusters (Sr-Ce-La, Ce-La) and mono-elemental clusters (Cr, Cu, Zn, Sr, Y, Zr, Ba, La, Ce) for the *sphagnum* moss located around La Soufrière dome. The *sphagnum* is the sole plant species for which NPs bearing trace elements have been identified in the analysis of undiluted extraction solutions.
<figure><img src="image_33.png" /><figcaption>Figure 7 : a) Correlation between the average mass (in fg) of a family of NPs bearing a major element (Si) and a family of NPs bearing a trace element (Cr) for sphagnum extraction solutions. b) Ce moles (fmol) vs La moles (fmol) for each nanoparticles containing both elements. The grey line represents the detection limit, defined as the value for which 95% of measured signals from NPs are considered to be detected for Ce and La. The red and brown lines correspond to the Ce/La ratio of NPs of volcanic ash, separated and quantitatively analyzed by Ermolin et al., (2018) and in fumarolic condensates measured by Inostroza et al., (2022), respectively.</figcaption></figure>
# Volcanic aerosols captured by plants: a study of nanoparticles and their chemical composition.

Gelin Marine, Tharaud Mickael and Benedetti Marc F.*

Université Paris Cité – Institut de Physique du globe de Paris, CNRS,
F75005 Paris, France

## Supplementary Material 2

<table><caption>Table 1 : conditions of analysis with a ICP-ToF-MS in single particle mode from Nu Instruments.</caption><thead><tr><th></th><th>spICP-ToF-MS parameters</th></tr></thead><tbody><tr><td>Uptake rate</td><td>190 µL.min<sup>-1</sup></td></tr><tr><td>RF power</td><td>1300</td></tr><tr><td>Ar cool gas</td><td>13.0 L.min<sup>-1</sup></td></tr><tr><td>Ar auxiliary gas</td><td>2.0 L.min<sup>-1</sup></td></tr><tr><td>Ar nebulization gas</td><td>1.0 L.min<sup>-1</sup></td></tr><tr><td>Collision cell gas</td><td>He : 0.014 L.min<sup>-1</sup> H : 0.007 L.min<sup>-1</sup></td></tr><tr><td>Acquired mass range</td><td>25 to 238 amu (blanked between 29.5 and 41 amu)</td></tr><tr><td>Examined isotopes</td><td><sup>27</sup>Al, <sup>28</sup>Si, <sup>48</sup>Ti, <sup>52</sup>Cr, <sup>56</sup>Fe, <sup>63</sup>Cu, <sup>65</sup>Zn, <sup>88</sup>Sr, <sup>89</sup>Y, <sup>90</sup>Zr, <sup>93</sup>Nb, <sup>138</sup>Ba, <sup>139</sup>La, <sup>140</sup>Ce, <sup>232</sup>Th</td></tr><tr><td>Dwell-time</td><td>80 µs</td></tr></tbody></table>
<table><caption>Table 2 : Concentrations of major element-bearing NPs in extracted *sphagnum* solutions and leaching *philodendron* and *ruyshia* solutions (in 10⁷ NPs.L⁻¹) obtained with spICP-ToF-MS analysis. n.a. not applicable</caption><thead><tr><th>Species</th><th>Position</th><th>Surface (cm²)</th><th>Si-Al-Fe</th><th>Al-Fe</th><th>Al</th><th>Si</th><th>Ti</th><th>Fe</th></tr></thead><tbody><tr><td rowspan="7">Sphagnum</td><td>1</td><td>n.a.</td><td>760.65</td><td>219.13</td><td>468.82</td><td>1381.17</td><td>181.21</td><td>624.74</td></tr><tr><td>2</td><td>n.a.</td><td>1570.81</td><td>261.27</td><td>1206.29</td><td>1317.96</td><td>285.51</td><td>503.59</td></tr><tr><td>3</td><td>n.a.</td><td>1187.33</td><td>343.45</td><td>1558.17</td><td>1580.29</td><td>307.63</td><td>562.58</td></tr><tr><td>4</td><td>n.a.</td><td>884.96</td><td>436.16</td><td>1064.06</td><td>1247.38</td><td>533.08</td><td>1336.93</td></tr><tr><td>5</td><td>n.a.</td><td>1188.38</td><td>32.66</td><td>237.04</td><td>2607.48</td><td>274.97</td><td>399.29</td></tr><tr><td>6</td><td>n.a.</td><td>862.84</td><td>114.83</td><td>648.97</td><td>2728.64</td><td>161.19</td><td>451.96</td></tr><tr><td>7</td><td>n.a.</td><td>293.93</td><td>675.31</td><td>1710.93</td><td>522.55</td><td>521.50</td><td>764.86</td></tr><tr><td rowspan="8">Philodendron</td><td>2</td><td>66</td><td>7.33</td><td>1.03</td><td>3.60</td><td>18.58</td><td>0.62</td><td>4.46</td></tr><tr><td>3</td><td>65.8</td><td>7.16</td><td>0.97</td><td>2.24</td><td>19.88</td><td>1.35</td><td>6.25</td></tr><tr><td>4</td><td>64.3</td><td>13.08</td><td>3.28</td><td>5.09</td><td>16.53</td><td>1.93</td><td>10.17</td></tr><tr><td>5</td><td>76</td><td>10.08</td><td>1.37</td><td>4.01</td><td>13.74</td><td>0.96</td><td>3.89</td></tr><tr><td>6</td><td>71</td><td>6.47</td><td>1.15</td><td>11.80</td><td>14.67</td><td>6.71</td><td>1.91</td></tr><tr><td>7</td><td>92</td><td>13.43</td><td>2.58</td><td>6.95</td><td>15.99</td><td>0.95</td><td>8.61</td></tr><tr><td>8</td><td>92</td><td>19.61</td><td>4.66</td><td>5.24</td><td>21.27</td><td>1.46</td><td>18.88</td></tr><tr><td>LCCRW</td><td>154.8</td><td>14.91</td><td>7.70</td><td>10.81</td><td>16.76</td><td>1.21</td><td>12.32</td></tr><tr><td>LCCRW</td><td>73</td><td>6.22</td><td>1.93</td><td>4.13</td><td>3.83</td><td>0.52</td><td>3.94</td></tr><tr><td rowspan="4">Ruyshia</td><td>3</td><td>41</td><td>30.13</td><td>2.05</td><td>34.98</td><td>50.46</td><td>4.06</td><td>9.01</td></tr><tr><td>4</td><td>54</td><td>99.66</td><td>13.38</td><td>97.45</td><td>57.10</td><td>11.96</td><td>32.40</td></tr><tr><td>6</td><td>58.9</td><td>17.70</td><td>1.79</td><td>20.81</td><td>19.23</td><td>1.58</td><td>6.64</td></tr><tr><td>7</td><td>58</td><td>70.93</td><td>25.60</td><td>83.97</td><td>55.63</td><td>4.85</td><td>74.22</td></tr></tbody></table>
<table><caption>Table 3 : Concentration of major element-bearing NPs found in supernatant solutions from ashes (in $10^8$ NPs.L$^{-1}$) obtained with spICP-ToF-MS analysis. LOD: Limit Of Detection</caption><thead><tr><th>Samples</th><th>Si-Al-Fe</th><th>Al-Fe</th><th>Al</th><th>Si</th><th>Ti</th><th>Fe</th></tr></thead><tbody><tr><td>Mon-G-1001</td><td>918.90</td><td>10.37</td><td>191.70</td><td>242.61</td><td>&lt; LOD</td><td>16.97</td></tr><tr><td>Mon-G-001</td><td>1126.00</td><td>35.83</td><td>179.13</td><td>411.37</td><td>6.91</td><td>48.08</td></tr><tr><td>Mon-G-9601</td><td>647.95</td><td>2.20</td><td>93.90</td><td>340.28</td><td>7.61</td><td>49.72</td></tr><tr><td>Mon 0803</td><td>112.88</td><td>1.89</td><td>11.25</td><td>57.76</td><td>1.38</td><td>1.95</td></tr><tr><td>Mon 16-01-1997</td><td>878.05</td><td>38.65</td><td>160.90</td><td>305.15</td><td>8.49</td><td>43.68</td></tr><tr><td>Soufriere Hills</td><td>262.22</td><td>2.20</td><td>42.05</td><td>227.84</td><td>&lt; LOD</td><td>5.28</td></tr></tbody></table>

<table><caption>Table 4 : Concentration of trace element-bearing NPs in extracted *sphagnum* solutions (in $10^6$ NPs.L$^{-1}$) obtained with spICP-ToF-MS analysis.</caption><thead><tr><th>Position</th><th>Cr</th><th>Cu</th><th>Zn</th><th>Sr</th><th>Y</th><th>Zr</th><th>Ce-La</th><th>Sr-Ce-La</th><th>La</th><th>Ce</th><th>Ba</th></tr></thead><tbody><tr><td>1</td><td>17.70</td><td>93.34</td><td>3.27</td><td>8.11</td><td>14.22</td><td>51.10</td><td>12.43</td><td>8.64</td><td>2.74</td><td>8.43</td><td>1.69</td></tr><tr><td>2</td><td>16.01</td><td>161.51</td><td>1.79</td><td>30.87</td><td>30.45</td><td>151.50</td><td>11.69</td><td>36.45</td><td>20.65</td><td>4.85</td><td>264.22</td></tr><tr><td>3</td><td>10.22</td><td>43.19</td><td>&lt; LOD</td><td>39.61</td><td>31.71</td><td>133.38</td><td>10.43</td><td>23.92</td><td>1.69</td><td>11.17</td><td>38.66</td></tr><tr><td>4</td><td>7.37</td><td>0.32</td><td>0.00</td><td>2.21</td><td>41.30</td><td>50.57</td><td>3.06</td><td>3.48</td><td>1.05</td><td>8.95</td><td>0.32</td></tr><tr><td>5</td><td>14.22</td><td>20.65</td><td>6.32</td><td>34.03</td><td>26.34</td><td>63.95</td><td>4.21</td><td>6.01</td><td>3.16</td><td>2.42</td><td>2.74</td></tr><tr><td>6</td><td>15.49</td><td>12.96</td><td>9.80</td><td>17.49</td><td>16.96</td><td>60.05</td><td>10.85</td><td>12.54</td><td>4.53</td><td>6.01</td><td>0.21</td></tr><tr><td>7</td><td>11.90</td><td>7.37</td><td>16.54</td><td>46.78</td><td>28.45</td><td>117.15</td><td>12.75</td><td>17.80</td><td>3.69</td><td>8.22</td><td>0.74</td></tr></tbody></table>
<table><caption>Table 5 : Total major element concentrations measured in leaf leachate solution (in µmol.L⁻¹). Data was obtained by ICP-OES.</caption><thead><tr><th>Species</th><th>Position</th><th>Na</th><th>Mg</th><th>S</th><th>K</th><th>Ca</th></tr></thead><tbody><tr><td rowspan="7">Sphagnum</td><td>1</td><td>192.4 ± 0.2</td><td>44.7 ± 0.1</td><td>171.4 ± 0.1</td><td>135.9 ± 0.1</td><td>28.1 ± 0.1</td></tr><tr><td>2</td><td>115.2 ± 0.1</td><td>19.5 ± 0.1</td><td>251.1 ± 0.3</td><td>63.9 ± 0.1</td><td>18.5 ± 0.1</td></tr><tr><td>3</td><td>164.8 ± 0.1</td><td>37.2 ± 0.2</td><td>318.4 ± 0.2</td><td>114.9 ± 0.1</td><td>27.7 ± 0.2</td></tr><tr><td>4</td><td>447.2 ± 0.2</td><td>160.4 ± 0.2</td><td>998.7 ± 0.4</td><td>145.5 ± 0.2</td><td>139.6 ± 0.1</td></tr><tr><td>5</td><td>129.9 ± 0.1</td><td>6.1 ± 0.5</td><td>98.4 ± 0.5</td><td>45.7 ± 0.3</td><td>5.5 ± 0.1</td></tr><tr><td>6</td><td>282.8 ± 0.1</td><td>18.2 ± 0.3</td><td>174.9 ± 0.2</td><td>134.2 ± 0.1</td><td>8.6 ± 0.1</td></tr><tr><td>7</td><td>219.8 ± 0.1</td><td>8.8 ± 0.1</td><td>64.5 ± 0.1</td><td>22.6 ± 0.1</td><td>5.9 ± 0.1</td></tr><tr><td rowspan="8">Philodendron</td><td>2</td><td>77.0 ± 0.1</td><td>26.8 ± 0.2</td><td>75.5 ± 0.1</td><td>77.7 ± 0.1</td><td>13.6 ± 0.1</td></tr><tr><td>3</td><td>52.3 ± 0.1</td><td>48.9 ± 0.2</td><td>66.2 ± 0.1</td><td>41.2 ± 0.1</td><td>17.5 ± 0.1</td></tr><tr><td>4</td><td>67.3 ± 0.1</td><td>23.8 ± 0.1</td><td>68.8 ± 0.1</td><td>53.8 ± 0.1</td><td>40.1 ± 0.1</td></tr><tr><td>5</td><td>51.1 ± 0.1</td><td>7.5 ± 0.1</td><td>19.2 ± 0.1</td><td>31.4 ± 0.1</td><td>13.2 ± 0.1</td></tr><tr><td>6</td><td>48.3 ± 0.1</td><td>15.3 ± 0.2</td><td>32.2 ± 0.1</td><td>21.7 ± 0.2</td><td>15.8 ± 0.1</td></tr><tr><td>7</td><td>133.3 ± 0.1</td><td>24.9 ± 0.5</td><td>70.9 ± 0.1</td><td>41.1 ± 0.1</td><td>31.7 ± 0.1</td></tr><tr><td>8</td><td>80.4 ± 0.1</td><td>6.5 ± 0.7</td><td>16.1 ± 0.2</td><td>148.9 ± 0.1</td><td>10.9 ± 0.1</td></tr><tr><td>LCCRW</td><td>35.8 ± 0.6</td><td>6.8 ± 0.1</td><td>21.2 ± 0.2</td><td>83.2 ± 1.4</td><td>13.2 ± 0.1</td></tr><tr><td>LCCRW</td><td>2.4 ± 0.2</td><td>2.2 ± 0.1</td><td>13.7 ± 0.1</td><td>35.9 ± 0.7</td><td>4.6 ± 0.1</td></tr><tr><td rowspan="4">Ruyshia</td><td>3</td><td>14.0 ± 0.2</td><td>&lt; LOD</td><td>14.2 ± 0.1</td><td>8.6 ± 0.1</td><td>6.1 ± 0.1</td></tr><tr><td>4</td><td>22.9 ± 0.1</td><td>20.9 ± 0.1</td><td>32.9 ± 0.1</td><td>12.7 ± 0.2</td><td>87.0 ± 0.1</td></tr><tr><td>6</td><td>88.5 ± 0.1</td><td>5.4 ± 0.1</td><td>11.6 ± 0.1</td><td>33.1 ± 0.1</td><td>6.9 ± 0.1</td></tr><tr><td>7</td><td>26.7 ± 0.1</td><td>4.0 ± 0.2</td><td>2.3 ± 0.1</td><td>18.6 ± 0.2</td><td>5.1 ± 0.1</td></tr></tbody></table>
<table><caption>Table 6 : Calculation of the limit of detection (in fg) of the spICP-ToF-MS data and proportion of real mono-elemental cluster (%). n.r. : not relevant</caption><thead><tr><th>Species</th><th>Position</th><th>Al</th><th>Si</th><th>Ti</th><th>Fe</th></tr></thead><tbody><tr><td rowspan="7">Sphagnum</td><td>1</td><td>0.084</td><td>0.313</td><td>0.017</td><td>0.033</td></tr><tr><td>2</td><td>0.112</td><td>0.375</td><td>0.020</td><td>0.050</td></tr><tr><td>3</td><td>0.125</td><td>0.725</td><td>0.020</td><td>0.063</td></tr><tr><td>4</td><td>0.168</td><td>0.971</td><td>0.025</td><td>0.061</td></tr><tr><td>5</td><td>0.096</td><td>0.296</td><td>0.018</td><td>0.048</td></tr><tr><td>6</td><td>0.077</td><td>0.339</td><td>0.017</td><td>0.036</td></tr><tr><td>7</td><td>0.132</td><td>0.580</td><td>0.020</td><td>0.059</td></tr><tr><td rowspan="8">Philodendron</td><td>2</td><td>0.110</td><td>0.392</td><td>0.089</td><td>0.044</td></tr><tr><td>3</td><td>0.094</td><td>0.276</td><td>0.052</td><td>0.058</td></tr><tr><td>4</td><td>0.125</td><td>0.401</td><td>0.053</td><td>0.068</td></tr><tr><td>5</td><td>0.112</td><td>0.279</td><td>0.050</td><td>0.050</td></tr><tr><td>6</td><td>0.106</td><td>0.374</td><td>0.056</td><td>0.050</td></tr><tr><td>7</td><td>0.126</td><td>0.289</td><td>0.080</td><td>0.053</td></tr><tr><td>8</td><td>0.121</td><td>0.384</td><td>0.042</td><td>0.032</td></tr><tr><td>LCCRW</td><td>0.082</td><td>0.355</td><td>0.042</td><td>0.038</td></tr><tr><td>LCCRW</td><td>0.060</td><td>0.302</td><td>0.024</td><td>0.033</td></tr><tr><td rowspan="4">Ruyshia</td><td>3</td><td>0.057</td><td>0.066</td><td>0.052</td><td>0.090</td></tr><tr><td>4</td><td>0.330</td><td>0.371</td><td>0.225</td><td>0.267</td></tr><tr><td>6</td><td>0.022</td><td>0.033</td><td>0.021</td><td>0.022</td></tr><tr><td>7</td><td>0.026</td><td>0.031</td><td>0.023</td><td>0.035</td></tr></tbody></table>

<table><thead><tr><th>Ashes Samples</th><th>Al</th><th>Si</th><th>Ti</th><th>Fe</th></tr></thead><tbody><tr><td>Mon-G-1001</td><td>0.009</td><td>0.025</td><td>0.002</td><td>0.002</td></tr><tr><td>Mon-G-001</td><td>0.009</td><td>0.026</td><td>0.002</td><td>0.002</td></tr><tr><td>Mon-G-9601</td><td>0.011</td><td>0.032</td><td>0.005</td><td>0.002</td></tr><tr><td>Mon 0803</td><td>0.010</td><td>0.031</td><td>0.003</td><td>0.002</td></tr><tr><td>Mon 16-01-1997</td><td>0.010</td><td>0.025</td><td>0.002</td><td>0.002</td></tr><tr><td>Soufriere Hills</td><td>0.010</td><td>0.032</td><td>0.003</td><td>0.002</td></tr></tbody></table>

<table><thead><tr><th>Sphagnum<br>Position</th><th>Cr</th><th>Cu</th><th>Zn</th><th>Sr</th><th>Y</th><th>Zr</th><th>Ba</th><th>La</th><th>Ce</th></tr></thead><tbody><tr><td>1</td><td>0.022</td><td>0.027</td><td>0.251</td><td>0.092</td><td>0.011</td><td>0.059</td><td>0.240</td><td>0.015</td><td>0.018</td></tr><tr><td>2</td><td>0.033</td><td>0.036</td><td>0.276</td><td>0.056</td><td>0.018</td><td>0.087</td><td>0.301</td><td>0.021</td><td>0.030</td></tr><tr><td>3</td><td>0.028</td><td>0.038</td><td>0.257</td><td>0.053</td><td>0.014</td><td>0.076</td><td>0.183</td><td>0.017</td><td>0.022</td></tr><tr><td>4</td><td>0.023</td><td>0.143</td><td>0.328</td><td>0.070</td><td>0.015</td><td>0.055</td><td>0.090</td><td>0.014</td><td>0.018</td></tr><tr><td>5</td><td>0.026</td><td>0.039</td><td>0.183</td><td>0.026</td><td>0.012</td><td>0.073</td><td>0.118</td><td>0.017</td><td>0.021</td></tr><tr><td>6</td><td>0.023</td><td>0.027</td><td>0.173</td><td>0.044</td><td>0.012</td><td>0.062</td><td>0.260</td><td>0.016</td><td>0.020</td></tr><tr><td>7</td><td>0.033</td><td>0.034</td><td>0.171</td><td>0.041</td><td>0.012</td><td>0.086</td><td>0.172</td><td>0.018</td><td>0.024</td></tr></tbody></table>
The detection limit $S_D (ADC)$ is calculated in equation 1 following (Gundlach-Graham et al. 2018). It represents the value for which 95% of measured signals from NPs are considered to be detected. This new detection criterion is specially developed for detection of NPs with spICP-ToF-MS made of a fast analog-to-digital converter (ADC) in order to avoid the pulse-pileup effects (Harycki and Gundlach-Graham 2023). Additionally, for spICP-TOF-MS measurements, the calculation of the limit of detection has to be calculated with a conservative false-positive rate. They suggest that a 0.1% false-positive rate ($\alpha$ = 0.001) is a reasonable rate. For example, a conservative false positive rate from the background of 0.1% will lead to an increase of 1% of the counting nanoparticles events.

$$S_D (ADC) = \lambda_{bkgd} + (5.24\sqrt{\lambda_{bkgd}} + 5.54)$$

for $\alpha$ = 0.001, $\beta$ = 0.05

<table><thead><tr><th>Species</th><th>Sphagnum</th><th>Philodendron</th><th>Ruyshia</th><th>Control (Philodendron)</th><th>Ashes</th></tr></thead><tbody><tr><td>%mono element NPs in Si cluster</td><td>99</td><td>99</td><td>100</td><td>100</td><td>100</td></tr><tr><td>%mono element NPs in Al cluster</td><td>100</td><td>100</td><td>100</td><td>100</td><td>100</td></tr><tr><td>%mono element NPs in Sr cluster</td><td>100</td><td>n.r.</td><td>n.r.</td><td>n.r.</td><td>n.r.</td></tr><tr><td>%mono element NPs in Ce cluster</td><td>66</td><td>n.r.</td><td>n.r.</td><td>n.r.</td><td>n.r.</td></tr></tbody></table>