# Biomonitoring of elements airborne pollution in European Mediterranean region by two Tillandsia species

Alexandre Gonzalez, Zohra Benfodda, David Bénimélis, Damien Bourgeois, Jean-Xavier Fontaine, Roland Molinié, Patrick Meffre

► To cite this version:

Alexandre Gonzalez, Zohra Benfodda, David Bénimélis, Damien Bourgeois, Jean-Xavier Fontaine, et al.. Biomonitoring of elements airborne pollution in European Mediterranean region by two Tillandsia species. Atmospheric Pollution Research, 2025, 16 (8), pp.102576. 10.1016/j.apr.2025.102576. hal-05075353

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# Biomonitoring of elements airborne pollution in European Mediterranean region by two *Tillandsia* species

Alexandre Gonzalez<sup>a</sup>, Zohra Benfodda<sup>a</sup>, David Bénimélis<sup>a</sup>, Damien Bourgeois<sup>b</sup>,
Jean-Xavier Fontaine<sup>c, d</sup>, Roland Molinié<sup>c, d</sup>, Patrick Meffre<sup>a, *, d</sup>

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

## ARTICLE INFO

**Keywords:**

*Tillandsia*

Biomonitoring

Elements

Atmospheric pollution

## ABSTRACT

*Tillandsia* genus belongs to the Bromeliaceae family plants and some species display active or passive bio-
monitoring capacities in their natural habitat as it has been described mostly in the American continent.
However, *Tillandsia aeranthos* (Loisiel.) Desf. and *Tillandsia bergeri* Mez have never been studied for their metal
air pollution biomonitor potential. A recent study conducted in our laboratory brought to light the maximum
capacity of elements bioconcentration into these two species leaves. The aim of the present study is to determine
if *T. aeranthos* and *T. bergeri* acclimated to Southern/European region are good biomonitors for airborne elements
pollution. Twelve elements were chosen to evaluate the biomonitoring potential (As, Ba, Co, Cr, Cu, Fe, Mn, Ni,
Pb, Sn, Ti and Zn). After sampling, the content of the twelve elements in leaves was measured by Inductively
Coupled Plasma-Optical Emission Spectrometry and Inductively Coupled Plasma-Mass Spectrometry. Data sets
were treated according to sampling sites by box plots over time and Principal Component Analysis. The results
showed differences between the two species, with *T. bergeri* possessing a higher capacity in accumulating ele-
ments than *T. aeranthos*. Fe, Zn and Co showed a higher contribution in the accumulation process in the two
*Tillandsia* species leading to the hypothesis of a good affinity of the two species with these elements. Values
obtained for five elements (As, Cr, Ni, Pb and Zn) were compared with values recorded by a monitoring station
close to sampling sites showing the efficiency of these two *Tillandsia* species as biomonitors. High Co accumu-
lation rates obtained in both *Tillandsia* species were particularly intriguing but could not be rationalized as this
metal is not currently monitored by air pollution station in this region. *T. aeranthos* and *T. bergeri* proved their
efficiency for the biomonitoring of elements air pollution, especially for Co, Fe and Zn.

## 1. Introduction

Air pollution has become a real concern since the beginning of the
20th century with the rapid growth of industry. It is nowadays a major
public health issue with the increase of respiratory diseases due e.g. to
intense vehicular traffic (Han and Naeher, 2006; Mateos et al., 2018).
According to the World Health Organization (WHO), it was responsible
for the premature death of 6.7 million people worldwide in 2022 against
2 million in 2002. Elements pollution is one of the main sources of air
pollution due to metallurgic activity, energy combustion and road
transport (Vianna et al., 2011; World Health Organization, 2002, 2022).

Metals pollution is one of the main sources of air pollution due to met-
allurgic activity, energy combustion and road transport (Adamiec, 2017;
Manisalidis et al., 2020; Wilk et al., 2017). Metals cannot be degraded in
the environment, several are highly toxic and their elimination requires
human intervention (Lasat, 2002; Pescott et al., 2015). Consequently,
the monitoring of trace metal elements in air is of great interest due to
the constant increase of emissions (Rodriguez et al., 2011).

Biomonitoring is the continuous observation of a potential polluted
area using living organisms such as plants, able to give us information on
the air, water or soil constituents (Vianna et al., 2011). It can be both
active (plants transplanted from their natural unpolluted habitat to a

<footnote><sup>a</sup> UPR CHROME, Université de Nîmes, CEDEX 1, 30021, Nîmes, France</footnote>

<footnote><sup>b</sup> ICSM, CEA, CNRS, ENCSM, Université de Montpellier, Marcoule, France</footnote>

<footnote><sup>c</sup> UMR INRAE 1158 Transfrontalière BioEcoAgro, BIOlogie des Plantes et Innovation (BIOPI), UPJV, UFR de Pharmacie, 80037, Amiens, France</footnote>

<footnote>* Corresponding author.</footnote>

<footnote>E-mail addresses: alexandre.gonzalez@unimes.fr (A. Gonzalez), zohra.benfodda@unimes.fr (Z. Benfodda), david.benimelis@unimes.fr (D. Bénimélis), damien.bourgeois@umontpellier.fr (D. Bourgeois), jean-xavier fontaine@u-picardie.fr (J.-X. Fontaine), roland.molinie@u-picardie.fr (R. Molinié), patrick.meffre@unimes.fr (P. Meffre).</footnote>
polluted area to study the bioconcentration in their tissues) or passive (plants studied in their growing natural habitats and kept there to study this area) whether for water, soil or air (da Costa et al., 2016; Schmidt et al., 1999; Silva et al., 2023; Urošević et al., 2022; Wegener et al., 1992). Air pollution monitoring using air quality control stations is a very expensive way to collect information about the air content in specifically identified pollutants (De la Cruz et al., 2020). Thus, bio-monitoring has been more and more developed around the world as it is a low-cost air quality control technique to provide air composition information. Moreover, it allows prolonged studies considering every effect of the environment such as air pollution, weather conditions and the possibility of monitoring air pollution in many sites simultaneously (Nangeilil et al., 2022). Some plants can be good biomonitors for various metals and elements.

Tillandsia species from the Bromeliaceae family are colloquially called “air plants” and are originally located in America, from the south of the United States to the south of Argentina (Belmonte et al., 2022; Bernal et al., 2005; Garth, 2015; Miranda et al., 2020; Sáyago et al., 2018). For most of them they are epiphytic plants, which means that they are completely independent from the soil and grow by up taking nutrients from the air and the rainwater (Eggli and Gouda, 2020; Estrella-Parra et al., 2019; Gouda, 2020). Consequently, their tissue composition is widely representative of the atmosphere and its air pollution status (Contreras et al., 2022). Their foliar structure and anatomy of the trichomes are adapted to the absorption of nutrients from the air or ambient humidity (Belmonte et al., 2022; de Oliveira et al., 2021). Tillandsia have already been studied in their home region for their pollution biomonitoring potential (Bermudez et al., 2009; Brighigna et al., 1997; Sánchez-Chardi, 2016; Wannaz and Pignata, 2006). First of all, it has been shown that in their natural habitats, Tillandsia species such as *Tillandsia recurvata* (L.) L. and *Tillandsia usneoides* (L.) L. are very good biomonitors for various metals air pollution (Beringui et al., 2021; Cardoso-Gustavson et al., 2016; Figueiredo et al., 2004; Mendoza-Ramos et al., 2021; Nangeilil et al., 2022; Piazzetta et al., 2019; Salas-Luévano et al., 2017). Species such as *Tillandsia capillaris* Ruiz & Pav. or *Tillandsia brachycaulos* Schltdl. taken from their natural habitats or from greenhouses and placed in polluted areas revealed a good adaptation and bioconcentration of metals (De la Cruz et al., 2020; Zheng et al., 2020). The *Tillandsia* genus has proven its efficiency in bioaccumulating various metals or elements whether it is passive or active biomonitoring (Li et al., 2021; Sun et al., 2021). Few studies were conducted in Europe and none of them with acclimated *Tillandsia* species (only from tropical greenhouses) (Pellegrini et al., 2014; Schreck et al., 2020).

Herein, in the Southern/Mediterranean Europe region, some *Tillandsia* species from *Tillandsia* PROD nursery (Le Cailar, Gard, France) are well acclimated to the local climate: *Tillandsia aeranthos* (Loisiel.) Desf. and *Tillandsia bergeri* Mez (Roguenand, 2002; Roguenand et al., 2016; Róth, 1991). With the aim of getting more information about the air quality of our cities, a study of the ability of these two *Tillandsia* species to bioaccumulate various elements in their tissues over time is of great interest. A recent study conducted in our laboratory proved that both *Tillandsia* species could be used as biomonitors of elements air pollution as their bioconcentration potential and maximum capacity were determined and showed promising results for biomonitoring studies (Gonzalez et al., 2024). In this study, both active and passive biomonitoring were set up since the nursery where there are cultivated was a sampling point of the study with four other sampling points where the two *Tillandsia* species were transplanted. *T. aeranthos* and *T. bergeri* samples were collected every 15 days and the content in twelve elements was determined using Inductively Coupled Plasma-Optical Emission Spectrometry (ICP-OES) and Inductively Coupled Plasma-Mass Spectrometry (ICP-MS). The main objective of this study is to determine the biomonitoring capacity of these two *Tillandsia* species and their ability to be used in polluted areas to biomonitor element airborne pollution.

## 2. Material and methods

### 2.1. Plant material and chemicals

All the *Tillandsia* species used for this study were provided from the *Tillandsia* PROD plant nursery located in Le Cailar (Occitanie, France, 43°41'31.98" N, 4°14'34.85" E) and were harvested in January 2022 with similar size. Two species were used: *T. aeranthos*, *T. bergeri*. All plants of each species were analogues since they grew and came from the same location of the plant nursery. The chemicals used for the plant digestion were ordered from the Carlo Erba Reagents company (Val de Reuil, France): Nitric acid 67–69 % (RPE quality), Hydrochloric acid 35–37 % (RPE quality) and Hydrogen peroxide solution 30 % (RPE quality). The chemicals used for ICP-OES and ICP-MS analysis were ordered from the Carlo Erba Reagents company (Val de Reuil, France): Nitric acid 67–69 % (RS quality) and Hydrochloric acid 34–37 % (RS quality) both super pure for trace analysis. The standard solutions at 1000 mg.L⁻¹ were ordered from SCP Sciences (Quebec, Canada). A mix of standards of the twelve studied elements at 100 mg.L⁻¹ of each element was custom-made from these mono-element standards: As (99.9 %), Ba (99.9 %), Co (99.9 %), Cr (99.6 %), Cu (99.3 %), Fe (99.6 %), Mn (99.7 %), Ni (100 %), Pb (99.4 %), Sn (99.0 %), Ti (99.5 %) and Zn (99.9 %). These percentages represent the purity of each mono-element standards.

### 2.2. Sampling area

Fig. 1 presents the 5 sampling points located in Le Cailar (Site A, nursery, 2418 inhabitants) with one sampling point, Lunel-Viel (Sites B and C, 4367 inhabitants) with two sampling points and Nîmes (Sites D and E, 148 561 inhabitants) with two sampling points in the Occitanie province in France. The elevation above sea level is between 21 and 39 m in the sampling areas. The mean annual temperature in the sampling area is 14.9 °C with a pluviometry about 735 mm per year. Site A (*Tillandsia* PROD plant nursery) is 300m from departmental road D6572, which is a main road to go from Nîmes to seaside resorts (La Grande-Motte, Le Grau-du-Roi, Aigues-Mortes), beaches and industrial sites with high car and truck traffic. Sites B and C are located in Lunel-Viel along a high traffic road (national road N113, 25000 vehicles/day) and a waste incineration plant. This road is also parallel to the heavy traffic highway A9 (>80000 vehicles/day in this part, 1600m from the two sites). Many trucks use this road with many industries closeby such as Perrier, Royal Canin for instance. Sites D and E are urban areas located in the city of Nîmes. Site D is situated close to the A9 highway (300m, 40–60000 vehicles/day in this part) on one side and to the Nîmes ring road (200m) on the other side. Site E is in the city center with dense vehicular traffic.

For each sampling point, 15 specimens of *T. aeranthos* and 15 specimens of *T. bergeri* were set, providing leaves from one different plant for every sampling date. *T. aeranthos* and *T. bergeri* were placed outdoors in the sampling areas on January 27th 2022, and samples were collected on every sampling area every fifteen days from the 24th of February until the 7th of July. For the sampling, three pools of leaves were sampled from the two *Tillandsia* species for each sampling sites at each sampling date. To do so, leaves were cut from the specimen using Teflon coating scissors and tweezers.

### 2.3. Sample preparation

*T. aeranthos* and *T. bergeri* collected leaves were rinsed through immersion in 150 mL of ultrapure miliQ water for 15 min under stirring. Rinsing water was filtered through a 0.2 µm cellulose acetate membrane, then acidified with 2 % of concentrated HNO₃ and analyzed. Content of the twelve elements in rinsing water was always found below detection limit. Rinsed *Tillandsia* leaves were dried in an oven (Mementert, UF55) at 50 °C until constant weight. They were then grinded using a spex planetary ball mill apparatus, with a tungsten grinding bowl
<figure><img src="image_4.png" /><figcaption>Fig. 1. Sampling sites location. © IGN 2023.</figcaption></figure>

and three tungsten balls for 2 × 1 minute. Then, dried and grinded *Tillandsia* samples were digested using a high-performance microwave digestion system (Ethos one, Milestone) with Teflon reactors. About exactly 60 mg of dried and grinded sample were weighed in a Teflon reactor, 8.1 mL of HNO₃ 67–69 % (RPE quality), 1.6 mL of H₂O₂ 30 % (RPE quality) and 0.3 mL of HCl 35–37 % (RPE quality) were added to the Teflon reactor which was then sealed. Reactors were placed in the microwave assisted device and temperature was brought to 200 °C under autogenic pressure within 15 min at a 12 °C/min temperature increase rate, then the temperature was maintained at 200 °C for 15 min and finally the reactors were left until room temperature was reached. The digested samples were diluted in 50 mL volumetric flasks, then filtered using 0.2 µm cellulose acetate syringe filters. 5 mL were poured in polypropylene tubes and kept at 4 °C until analysis using Inductively Coupled Plasma-Optical Emission Spectroscopy (IPC-OES). The remaining 45 mL were diluted to be analyzed using Inductively Coupled Plasma-Mass Spectrometry (ICP-MS). 1.5 mL were poured in a polypropylene tube and 3 mL of a HNO₃ 1 % (RS quality)/HCl 0.5 % (RS quality) solution were added. The diluted samples were then kept at 4 °C until analysis using ICP-MS.

## 2.4. Elemental analysis of *T. aeranthos* and *T. bergeri* leaves

The concentrations of the twelve elements (As, Ba, Co, Cr, Cu, Fe, Mn, Ni, Pb, Sn, Ti and Zn) into rinsed, dried and grinded *Tillandsia* leaves (60 mg) were determined using both Inductively Coupled Plasma-Optical Emission Spectroscopy (ICP-OES, Thermoscientific, iCAP PRO series with a CETAC Technologies ASX-560 autosampler) and Inductively Coupled Plasma-Mass Spectrometry (ICP-MS, Thermoscientific, iCAP RQ with an Elemental Scientific 4DX autosampler). Each batch of samples included a blank ultrapure water, a blank acid and replicates. Limits of detection (LOD) and limits of quantification (LOQ) were determined in each analyzed phase for each element from the dilution factor applied and the background equivalent concentration automatically calculated by the spectrometer. The standard solution of the twelve

targeted elements at 100 mg.L⁻¹ each was diluted to make a six-points calibration curve. Concentration of the twelve elements was quantified applying a blank correction. The given concentrations were calculated as the average of three replicates at different wavelengths for each replicate, for the twelve elements. The selected spectral lines and m/z to assay elements were free from interferences.

## 2.5. Data analysis

Pd and Pt values were removed from the results for data analysis as there were always below the LOD in all samples.

Statistical analysis was carried out using R software (version 4.2.3). To study the influence of exposure sites, a univariate analysis can be performed. Variance analysis (ANOVA) is a statistical test that can be used to show the difference between the means of several conditions (more than two). The normal distribution of the data (verified by a Shapiro test: 'shapiro.test', function of the 'stats' package (version 4.2.3)) and the homoscedasticity (verified by a Leven test: 'levenTest', function of the 'carData' package (version 3.0-5)) of the results were not respected to perform a parametric test like ANOVA. A similar non-parametric Kruskal-Wallis test was therefore used to compare the effect of the exposure sites, for both varieties of *Tillandsia* and for every elements. The analysis was performed using 'kruskal.test' function of the 'stats' package (version 4.2.3). The significance of the test was established for a p-value less than 0.01. When the Kruskal-Wallis test was significant, a post-hoc test (Dunn's test) was performed using the 'kwAllPairsDunnTest' function of the 'PMCMRplus' package (version 1.9.7) with an adjustment of the p-value according to the Bonferroni method. If the post-hoc test was not significant (p-value less than 0.01), the effect of collection site was not considered.

PCA was used to find underlying correlations in our data set (twelve metals content and one hundred samples). It was performed in molar unit (mol⁻¹ DW) and not in weight unit (g⁻¹ DW). Advantage here of using molar unit allows us to see the correlations of accumulation of metals in quantity independently of their molecular mass. A metal with a
higher molecular mass will contribute more in the construction of the axes of the PCA compared to a metal with a lower molecular mass. The molar unit allows us to have an identical scale of accumulation common for all considered metals. The 'FactoMineR' package (version 2.8) was used for the principal component analysis (PCA) using the 'PCA' function with scale.unit = FALSE option. Pareto and univariate scaling were done before PCA analysis. The Pareto scale, by its construction, allows us to highlight the most accumulated and correlated metals, while the univariate scale allows us to highlight the correlations between metals, whatever their level of accumulation.

## 3. Results

In this study, *T. aeranthos* and *T. bergeri* were transplanted from the *Tillandsia* PROD nursery to four sampling sites in order to evaluate, over time, the accumulation of the twelve studied elements into the leaves. These elements were chosen as there were the most studied ones in the literature due to their potential toxicity for human health and their high emission ratios by human and industrial activities. Sites B and C are located in Lunel-Viel close to a high vehicular traffic road and a waste incineration plant. These two exposure sites are very close to an air quality control station for which data on several metals were collected in ATMO website for the discussion. Sites D and E are urban areas located in Nîmes. Site D is close to the highway and site E was in the city center with dense vehicular traffic. Leaves were sampled every fifteen days on the five sampling points to see the evolution of the bioconcentration of the twelve studied elements. Reference values were determined before starting the exposure experiment by sampling *T. aeranthos* and *T. bergeri* leaves in the first sampling point: the *Tillandsia* PROD nursery (Site A). The results show the evolution over six months.

### 3.1. Determination of the sampling sites influence for metal accumulation

First of all, Pd and Pt were not detected in any of the analyzed samples. Although these precious metals are systematically used in catalytic converters and are regularly dissipated in the environment within exhaust gas, either their content in the atmosphere is very low, insufficient to observe bioconcentration over the duration of the experiment, or they are not accumulated by the plants. Thus, all following discussion is dealing with the 12 other elements (As, Ba, Co, Cr, Cu, Fe, Mn, Ni, Pb, Sn, Ti and Zn). The test presented in Figs. 2–3 is a Kruskal-Wallis test and concerned the study of the exposure sites influence. For Ba, Cu and Zn, the Kruskal-Wallis test showed a *p* value < 0.01 which means there is a significant influence of the sampling sites. However, after a post hoc analysis, the *p* value was adjusted with the Bonferroni correction method and for most elements, the sampling sites showed no more significant influence: sampling site influence remained

significant for Ba only. Consequently, since there was no significant influence of the sampling sites for eleven elements (As, Co, Cr, Cu, Fe, Mn, Ni, Pb, Sn, Ti and Zn), the accumulation evolution in the two *Tillandsia* species leaves was considered as a mean of all sampling sites. These allowed the increase of the studied individuals from five to fifteen for each sampling date. In Figs. 2–3, Ba and Cr are presented as representative examples, results regarding other metals are available in supplementary data (Figs. S1–S10). Concerning Ba, the Kruskal-Wallis test followed by the post hoc analysis revealed the need to represent the results with two different sampling sites groups: Sites group 1 (Sites A, B and E) and Sites group 2 (Sites C and D) as described in Fig. 2.

In Fig. 3, it is possible to see that for Cr, the five boxplots have the same overall shape (i.e. the dispersion of values is similar), which explains the non-significant influence of exposure sites while in Fig. 2, for Ba, the boxplots of sites C and D are different from the three other ones which explains the influence of the exposure sites for Ba. However, it was hard to explain why two sites were significantly different concerning Ba accumulation by *Tillandsia* leaves.

### 3.2. Evaluation of the element accumulation in tillandsia leaves over time

This part concerned the evolution of the element content in the leaves of *T. aeranthos* and *T. bergeri* over time. In Fig. 4, the boxplots present the accumulation of four metals (Zn, Sn, Fe and Co) from the 45th day to the 180th day of exposure. The boxplots for the eight other elements (As, Ba, Cr, Cu, Mn, Ni, Pb, and Ti) are available in supplementary data (Figs. S11–S19). As explained before, except for Ba, the eleven other elements showed no significant influence of the exposure site as shown by the boxplots in Fig. 2. Thus, the boxplots in Fig. 4 are presented as the mean of all sampling sites.

Examining the boxplots, the eleven studied elements (without Ba) could be divided into different groups corresponding of the observed accumulation patterns. As, Co, Cr and Ni have a similar accumulation pattern which is characterized by an increase followed by a decrease. Cu, Fe, Mn, Pb, Ti and Zn remained constant over the exposure period. And Finally, Sn had an opposite trend to the first group with a slight decrease in the first exposure period followed by a slight increase in the second exposure period. Moreover, *T. bergeri* has higher concentrations value for all elements than *T. aeranthos*. Only Sn was constant over time and with similar value in both *Tillandsia* species.

In Table 1, the accumulation values of the twelve studied elements with the first exposure day (T₀) and the final exposure day (T₁) are presented. For T₀, the mean values are presented and correspond to the reference content in *Tillandsia* leaves. Concerning T₁, mean concentration, median and minimum and maximum values observed for each element are presented. This table allows to confirm that element content in *T. bergeri* is higher than in *T. aeranthos* for all studied elements except

<figure><img src="image_5.png" /><figcaption>**Fig. 2.** Boxplot of Ba concentration in Tillandsia aeranthos and Tillandsia bergeri leaves representing the exposure sites influence test.</figcaption></figure>
<figure><img src="image_6.png" /><figcaption>Fig. 3. Boxplot of Cr concentration in Tillandsia aeranthos and Tillandsia bergeri leaves representing the exposure sites influence test.</figcaption></figure>

for Sn which rates are similar between the two *Tillandsia* species. Moreover, Co, Fe and Zn presented the highest maximum values in both *Tillandsia* species.

### 3.3. Comparison of the twelve elements contribution in *T. aeranthos* and *T. bergeri* leaves

In order to help with the comprehension of the data obtained in this exposure experiment, a first principal component analysis (PCA) was performed with a Pareto scale applied to reduce the importance of the more intense values while maintaining the intensities obtained with the results (van den Berg et al., 2006). PCA can be defined as an unsupervised learning algorithm. It is a dimensionality reduction method used to find underlying correlations in samples and variables that potentially exist in a large set of data without direct supervision of human. It is very useful for uncovering hidden data patterns. The joint observation of the score plot and the loading plot allows us to highlight specific behaviour between the two species of *Tillandsia*. This PCA allows to identify differences between *T. aeranthos* and *T. bergeri* and which metals are determining factors to the accumulation in leaves. In Fig. 5 the first principal component (PC1) contributes to 53.62 % and the second principal component (PC2) contributes to 38.11 % of the total variance in the element concentration in *Tillandsia* leaves. By looking at the score plot in Fig. 5a, PC1 allowed to confirm that there was an accumulation of elements concentration over time. However, the two species were not well separated on PC1. The loading plot in Fig. 5b confirmed that on PC1 with Co being the most influent metal on accumulation in *Tillandsia* leaves over time. Indeed, Co is completely on the right side of the PCA in PC1 which means it has more intense concentration values in leaves than other metals and it increases in the middle of the exposure time and decreases in PC1. In the score plot of Fig. 5a, the two *Tillandsia* species were well separated on PC2. In the loading plot of Fig. 5b, Fe and Zn are separated from other metals in PC2 and show a high contribution on the PCA profile. These two metals are more present in *T. bergeri* than *T. aeranthos* which explains the separation between *T. aeranthos* and *T. bergeri* in PC2 on the score plot.

Despite the Pareto scale application, the contribution of Co, Fe and Zn is too strong to allow the separation of the other elements. Consequently, in order to observe behavior of elements in the accumulation process, another PCA analysis was performed. A univariate scale was applied (autoscaling) which means that all variables have the same contribution. High accumulation on the smallest variables has the same contribution as high accumulation on the strongest variables. In Fig. 6 the first principal component (PC1) contributes to 41.72 % and the second principal component (PC2) contributes to 22.2 % of the total variance in the element concentration in *Tillandsia* leaves. With this PCA analysis, it is possible to see that Co and Ni have similar accumulation

patterns with an increase followed by a decrease at the end of the exposure. In the same way, Cr and As have also a similar pattern together and also with Co and Ni but with lower concentrations values. On the contrary, Sn is in the opposite of the PCA from Co and Ni and its profile is also the opposite with a slight decrease first, followed by an increase until the end of the exposure. Concerning Mn, it is constant over time and in both *Tillandsia* species. Finally, Ba, Cu, Fe, Pb, Ti and Zn are relatively constant over time during the whole exposure. Their concentration is more important in *T. bergeri* leaves than in *T. aeranthos* ones which is explained by their presence on the top right corner of the loading plot in Fig. 6b. Indeed, *T. bergeri* and *T. aeranthos* are separated in PC2 on the score plot in Fig. 6a. Essential and potential toxic elements could not be discriminated on their behavior in *Tillandsia* leaves which means all studied elements (except Mn) might have been provided by anthropogenic sources such as vehicular traffic or industrial emissions.

## 4. Discussion

In the present study, *T. aeranthos* and *T. bergeri* plants acclimated to Southern/Mediterranean Europe were placed in various sites for 6 months in order to evaluate the biomonitoring capacity of these two species for element airborne pollution. twelve elements (As, Ba, Co, Cr, Cu, Fe, Mn, Ni, Pb, Sn, Ti and Zn) were biomonitored during this study. As presented before, *T. aeranthos* and *T. bergeri* proved their efficiency on bioaccumulating elements in their tissues (Gonzalez et al., 2024). On every exposure site, *T. aeranthos* and *T. bergeri* were sampled every fifteen days during six months to determine the accumulation of these elements into the leaves.

Except for Ba, all exposure sites revealed no statistically significant difference, and results were presented as a mean of all sampling sites. For all elements, the accumulation was higher in *T. bergeri* leaves than in *T. aeranthos* leaves, except for Sn all along the experiment. This conclusion was also observed in the previous study concerning the determination of the maximum bioconcentration capacity of these two *Tillandsia* species (Gonzalez et al., 2024). These two *Tillandsia* species seem to excrete elements after one hundred exposure days approximately. The concentration of these elements into the leaves might be toxic for which could explain the excretion of some elements (Ahmad and Ashraf, 2011; Hunter and Vergano, 1952; Kolberg et al., 2022). It has been observed that Fe, Zn and Co are the three metals with the highest content in both *Tillandsia* species leaves. Indeed, Co rate in *Tillandsia* leaves starts quite low and strongly increases in the middle of the experiment to finally decrease at the end. This can be explained because Co is an essential metal for plant growth whether it can be toxic in high concentrations. Moreover, it has been studied that Co might be emitted by vehicular traffic, industrial activities such as incinerators or mining activities (Bej and Chattaraj, 2023; Chen et al., 2023; Simonsen
<figure><img src="image_7.png" /><figcaption>**Fig. 4.** Evolution of the concentrations of some representative elements in Tillandsia aeranthos and Tillandsia bergeri leaves over time. (a) Evolution of the Sn concentration (b) Evolution of the Zn concentration. (c) Evolution of the Fe concentration. (d) Evolution of the Co concentration.</figcaption></figure>
<caption>**Table 1**</caption>

Evolution of the accumulation values of the twelve elements in *Tillandsia aeranthos* and *Tillandsia bergeri* leaves over time. Mean concentration, median and min-max values in nmol.g⁻¹ of dry weight of *Tillandsia*.

<table><thead><tr><th rowspan="3"></th><th colspan="4">Tillandsia aeranthos</th><th colspan="4">Tillandsia bergeri</th></tr><tr><th colspan="4">nmol.g<sup>-1</sup></th><th colspan="4">nmol.g<sup>-1</sup></th></tr><tr><th>T<sub>0</sub> (0 day)</th><th colspan="3">T<sub>1</sub> (180 days)</th><th>T<sub>0</sub> (0 day)</th><th colspan="3">T<sub>1</sub> (180 days)</th></tr><tr><th></th><th>Mean</th><th>Mean</th><th>Median</th><th>Min-Max</th><th>Mean</th><th>Mean</th><th>Median</th><th>Min-Max</th></tr></thead><tbody><tr><td>As</td><td>0.3</td><td>0.2</td><td>0.2</td><td>0.09-0.3</td><td>0.6</td><td>0.3</td><td>0.2</td><td>0.2-0.5</td></tr><tr><td>Ba</td><td>3</td><td>8</td><td>5</td><td>2-19</td><td>8</td><td>11</td><td>8</td><td>4-23</td></tr><tr><td>Co</td><td>7</td><td>530</td><td>190</td><td>110-1300</td><td>8</td><td>650</td><td>240</td><td>84-2000</td></tr><tr><td>Cr</td><td>8</td><td>4</td><td>4</td><td>3-5</td><td>9</td><td>6</td><td>5</td><td>4-9</td></tr><tr><td>Cu</td><td>8</td><td>8</td><td>7</td><td>5-10</td><td>10</td><td>9</td><td>9</td><td>6-11</td></tr><tr><td>Fe</td><td>190</td><td>300</td><td>230</td><td>190-450</td><td>580</td><td>650</td><td>700</td><td>400-750</td></tr><tr><td>Mn</td><td>22</td><td>14</td><td>13</td><td>9-19</td><td>100</td><td>55</td><td>48</td><td>27-110</td></tr><tr><td>Ni</td><td>9</td><td>3</td><td>2</td><td>1-4</td><td>13</td><td>4</td><td>3</td><td>2-7</td></tr><tr><td>Pb</td><td>0.5</td><td>0.6</td><td>0.4</td><td>0.3-0.9</td><td>2</td><td>0.9</td><td>0.8</td><td>0.5-6</td></tr><tr><td>Sn</td><td>110</td><td>110</td><td>110</td><td>100-110</td><td>100</td><td>100</td><td>110</td><td>100-110</td></tr><tr><td>Ti</td><td>9</td><td>5</td><td>4</td><td>2-10</td><td>34</td><td>14</td><td>15</td><td>10-18</td></tr><tr><td>Zn</td><td>23</td><td>180</td><td>140</td><td>35-360</td><td>270</td><td>350</td><td>400</td><td>180-520</td></tr></tbody></table>

<figure><img src="image_8.png" /><figcaption>**Fig. 5.** PCA based on the 12 elements (As, Ba, Co, Cr, Cu, Fe, Mn, Ni, Pb, Sn, Ti and Zn) accumulated by *Tillandsia aeranthos* and *Tillandsia bergeri* leaves over six months with a pareto scale applied. (a) score plot of PC1 scores versus PC2 scores. (b) loading plot of PC1 and PC2 contributing to accumulation rates of elements in *Tillandsia* leaves.</figcaption></figure>

et al., 2012). Thus, *T. aeranthos* and *T. bergeri* might have excreted Co for plant health or Co receptors in the plant were filled (Jayakumar and Jaleel, 2009; Nakos et al., 2017; Palit et al., 1994). All sampling sites were concerned with vehicular traffic emissions, including the nursery (Site A). Consequently, it could be interesting in a future experiment, to expose *Tillandsia* specimens in a complete rural area to evaluated Co content in rural air. Concerning Fe and Zn, their rates in *Tillandsia* leaves are higher than other elements and are higher in *T. bergeri* than in *T. aeranthos* as it was also demonstrated in the previous study (Gonzalez et al., 2024). These are also two essential metals for plant growth and are widely present in our atmosphere and environment which can explain the higher values compared to other elements (Ferraz et al., 2012; Hewitt, 1948; Kolberg et al., 2022). Concerning other metals such as Sn, Cr, Pb or Cu, they stay constant all along the experiment. Except for Cu, these three metals are non-essential or even toxic for plants. This might explain the fact that *Tillandsia* species almost do not accumulate these metals. In the same way, Ti decreases over time as it is also a toxic element for plant health (Finnegan and Chen, 2012; Larue et al., 2011; Llugany et al., 2000; Suwa et al., 2008). The potential selectivity of an

element from another could be explained by their role in plant health and growth as the three more contributing metals (Fe, Co and Zn) are essential metals for plants. Pb levels in both *Tillandsia* species were low. These rates could be explained because the use of Pb has significantly decreased in the past years with lead-free paints and gasoline. The rates of most elements in this study were low which might be due to the presence of many trichomes on *Tillandsia* leaves similar to scales. It has been shown that these trichomes are mainly phenolic compounds (Cardoso-Gustavson et al., 2016; Sakihama et al., 2002; Tangahu et al., 2011). Indeed, these phenolic compounds might be able to chelate metals and protect inner tissues of the leaves by reducing penetration of these metals through leaves.

To our knowledge, *T. aeranthos* and *T. bergeri* have only been studied once concerning their bioconcentration potential of metals in laboratory biomonitoring (Gonzalez et al., 2024). *T. bergeri* was studied once concerning its potential of bioindication of pesticides (Silva-Barni et al., 2019). Other studies were conducted on other species of the *Tillandsia* genus concerning the bioindication of metal air pollution in different areas. Most of these studies were conducted in countries where the
<figure><img src="image_9.png" /><figcaption>**Fig. 6.** PCA based on the 12 elements (As, Ba, Co, Cr, Cu, Fe, Mn, Ni, Pb, Sn, Ti and Zn) accumulated by Tillandsia aeranthos and Tillandsia bergeri leaves over six months with a univariate scale (autoscaling) applied. (a) score plot of PC1 scores versus PC2 scores. (b) loading plot of PC1 and PC2 contributing to accumulation rates of elements in Tillandsia leaves.</figcaption></figure>

atmosphere is usually more polluted than in this location study. Consequently, it can be hard to compare the efficiency of *T. aeranthos* and *T. bergeri* with other studied *Tillandsia* species as biomonitors. A study conducted in China on *T. brachycaulos* included the twelve elements studied in the present study. Rates of Co and Sn were lower in the study on *T. brachycaulos* while other elements were present inside the leaves in higher rates (Zheng et al., 2020). *T. recurvata* is another *Tillandsia* species widely studied in this context. A study in Chile showed Co rates way lower than in our study and similar rates of Zn. On the contrary, the other common studied metals (Cu, Cr, Mn ...) were higher in the Chilean study (Cortés, 2004). Finally, Bermudez et al. conducted a study in Argentina over nine months on three *Tillandsia* species, *T. capillaris*, *T. recurvata* and *T. tricholepsis* (Bermudez et al., 2009). In this study for the three species, Zn rates were similar to the ones obtained in the present study. For Mn and Fe, rates were higher in the Argentinian study. However, the same evolution over time was observed with an increase in the first part of the exposure followed by a decrease at the end of the exposure.

In the location of the study, an air quality control station is installed (close to Sites B and C). Five elements were monitored in this station are common with our present study (As, Cr, Ni, Pb and Zn). Consequently, it is possible to compare the rates of these five elements in the two *Tillandsia* species leaves with the content in the air around the air control station (ATMO, 2020, 2022).

As it can be seen in Table 2, the rates of these five elements are way

<caption>**Table 2**</caption>

Comparison between Tillandsia aeranthos and Tillandsia bergeri samples from the 95th day as biomonitors and air control station for five common elements, and ratios determined as C<sub>station</sub>/C<sub>Tillandsia</sub>.

<table><thead><tr><th></th><th>Tillandsia<br>aeranthos</th><th>Tillandsia<br>bergeri</th><th>Air control<br>station<br>(2022)</th><th>Ratios for<br>T. bergeri</th><th>Ratios for<br>T. aeranthos</th></tr><tr><td></td><td colspan="2">nmol.g<sup>-1</sup> DW of Tillandsia<br>after 95 exposure days</td><td>nmol.L<sup>-1</sup> of<br>air</td><td>µg.L<sup>-1</sup></td><td>µg.L<sup>-1</sup></td></tr></thead><tbody><tr><td>As</td><td>0.4</td><td>0.7</td><td>6.7x10<sup>-6</sup></td><td>10</td><td>17</td></tr><tr><td>Pb</td><td>0.5</td><td>2</td><td>8.7x10<sup>-6</sup></td><td>5</td><td>17</td></tr><tr><td>Cr</td><td>7</td><td>10</td><td>4.0x10<sup>-5</sup></td><td>4</td><td>6</td></tr><tr><td>Ni</td><td>12</td><td>17</td><td>1.0x10<sup>-5</sup></td><td>0.6</td><td>0.8</td></tr><tr><td>Zn</td><td>86</td><td>420</td><td>9.6x10<sup>-5</sup></td><td>0.2</td><td>1</td></tr></tbody></table>

higher in 1 g of both *Tillandsia* species leaves than in 1 L of air from the air quality control station. Ratios were calculated for each *Tillandsia* species between the rates found in the air control station and in the *Tillandsia* leaves (C<sub>station</sub>/C<sub>Tillandsia</sub>). The highest concentrations obtained from the quality control station were the same as the ones from both *Tillandsia* species. The concentrations of elements in *Tillandsia* leaves were taken halfway through the experiment. In *Tillandsia* species as in the filters of air control station, essential metals (Ni and Zn) for plant were the most accumulated in both *Tillandsia* species. Co has been showed to be an essential metal for plants and content of Co in *T. aeranthos* and *T. bergeri* was particularly high. It would be interesting to monitor Co in the air control station in order to have correlation factors for Co. This would give the opportunity to determine if Co is highly present in the air or if *Tillandsia* species greatly accumulate it. Moreover, further experiments could allow the identification of potential Co emission sources to better understand these high levels detected in *Tillandsia* leaves (Jayakumar and Jaleel, 2009; Simonsen et al., 2012). This may lead to the conclusion that, considering the basal concentration of some elements into *Tillandsia* leaves, *T. aeranthos* and *T. bergeri* might be better biomonitors than air quality control station or might possess a higher affinity for some elements.

## 5. Conclusion

This study allowed the evaluation of the biomonitoring potential of *T. aeranthos* and *T. bergeri* regarding airborne elements pollution. twelve elements (As, Ba, Co, Cr, Cu, Fe, Mn, Ni, Pb, Sn, Ti and Zn) were studied on 5 sampling points during 6 months with sampling every 15 days. This study allowed to conclude that *T. bergeri* is a better bioaccumulator than *T. aeranthos*. Furthermore, it is possible to conclude there were no significant differences between the five sampling points, all located in urban areas close to heavy road traffic. The accumulation of the elements in *T. aeranthos* and *T. bergeri* leaves was similar in the five sampling points. The PCA analysis allowed us to determine that Fe, Zn and Co were the three metals contributing the most in the accumulation process. Co showed the highest rate with a strong increase from the beginning to the halfway experiment followed by a decrease at the end of the experiment. Fe and Zn were constant over time. Other elements were for most of them constant and showed low accumulation over time. The application of a univariate scale on the second PCA allowed to
conclude that Sn had a singular profile on the opposite of Co, Ni, Cr and As. Indeed, Sn decreased a little in the halfway experiment while the last-mentioned elements increased. Most of the elements decreased at the end of the exposure period. These two *Tillandsia* species were never studied before concerning their biomonitoring potential of elements and this study allows us to conclude that *T. aeranthos* and *T. bergeri* acci- mated to Southern/Mediterranean Europe could be used as biomonitors for airborne elements pollution, but some adjustments should be done. For instance, the exposure period should be optimized in order to reduce the excretion risks. Co showed a particularly high accumulation poten- tial in these two *Tillandsia* species and further studies will concentrate on this metal in order to understand better its accumulation mechanism through the leaves of *Tillandsia*.

## CRediT authorship contribution statement

**Alexandre Gonzalez:** Writing – original draft, Visualization, Validation, Software, Methodology, Formal analysis. **Zohra Benfodda:** Writing – review & editing, Supervision. **David Bénimélis:** Resources. **Damien Bourgeois:** Writing – review & editing, Supervision. **Jean-Xavier Fontaine:** Writing – review & editing, Visualization, Software, Formal analysis. **Roland Molinié:** Writing – review & editing, Visualization, Validation, Supervision, Software, Methodology, Formal analysis. **Patrick Meffre:** Writing – review & editing, Validation, Supervision, Project administration, Funding acquisition, Conceptualization.

## Data availability statement

The data presented in this study are available within the article and the supplementary data.

## Funding

This work was funded by La Région Occitanie, Université de Nîmes and *Tillandsia* PROD plant nursery (28 chemin du Cailar F-30740 Le Cailar, France, contact@tillandsia-prod.com), which provided all the plants that were necessary for the study (in kind contribution). We gratefully thank the French Ministère de l'Enseignement Supérieur, de la Recherche et de l'Innovation (MESRI).

## Declaration of competing interest

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

## Acknowledgments

We gratefully acknowledge *Tillandsia* PROD (28 chemin du Cailar 30740 Le Cailar, France, contact@tillandsia-prod.com) plant nursery (Pierre Kerrand, Daniel Thomin) for providing us the *Tillandsia* plants used in this study and for helpful discussions and interest in the project. We also gratefully acknowledge the ICSM, CEA (Damien Bourgeois, Béatrice Baus-Lagarde) for their collaboration and ICP-OES, ICP-MS provision for analysis. Finally, we gratefully acknowledge the Syndicat mixte Pic et Etang (825 route de Valergues 34400 Lunel-Viel, France, contact@picetang.fr) for collaborating to the exposure sites choices (Johanne Lecomte and Fabrice Fenoy).

## Appendix A. Supplementary data

Supplementary data to this article can be found online at https://doi.org/10.1016/j.apr.2025.102576.

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