Yasaman Tadayon

Delphine Vantelon

Julien Gigault

Aline Dia

Maxime Pattier

Lionel Dutruch

Mélanie Davranche

Validation, Writing -Review Mélanie Davranche Supervision

Rare earth elements interaction with iron-organic matter colloids as a control of the REE environmental dissemination

Keywords: colloids, Organic matter (OM), Iron (Fe), Rare earth elements (REE), heterogenous colloids, pH, adsorption, mobility, aggregation, Fe-OM aggregates Yasaman Tadayon Conceptualization, Methodology, Investigation, Data curation, Formal analysis, Software, Writing -Original Delphine Vantelon Supervision, Investigation, Data curation, Software, Writing -Review

Rare earth elements (REE) are highly sought after for advanced technology, in response concerns about their environmental impact have arisen. The mobility and transport of REEs are influenced by their binding to solid surfaces, particularly colloids. With the widespread occurrence of REEs and their potential increase due to climate change, there is growing interest in understanding colloids composed of organic matter (OM) and iron (Fe). The reactivity of these colloids depends on their structural organization and the availability of Fe phase and OM binding sites. The effect of pH on the binding and mobility of REEs in these colloids in response to structural modification of Fe-OM colloids was investigated. REEs are primarily bind to the OM component of Fe-OM colloids, and their mobility is controlled by the response of OM colloids and molecules to pH conditions. At pH 6, the solubilization of small organic colloids (< 3 kDa) control the REE pattern and subsequent speciation and mobility. In contrast, at pH 4, Fe-OM colloids bind less amount of REE but aggregate to form a large network. While most REEs remain soluble, those bound to Fe-OM colloids are expected to be immobilized through settlement or trapping in soil and sediment pores.

This study supports the idea that colloids control the REE speciation and subsequent dissemination. The findings are particularly relevant for assessing the fate and ecotoxicology of REE in response to changing environmental conditions and increasing REE concentration in natural systems.

Introduction

The development of new green energy technologies is bases on 'novel' strategic chemical elements such as the rare earth elements (REE). This group of elements comprise 15 lanthanides as well as Yttrium (Y) and Scandium (Sc). They have gained significant prominence since they are extensively employed in a wide range of industrial and technological applications, primarily for energy storage purposes to reduce greenhouse gases (wind turbines, hybrid cars, etc.). The upcoming industrial revolution is predicted to be the new green energy transitions [START_REF] Lawrence | Characterising mine wastes as archaeological landscapes[END_REF][START_REF] Bortone | Gaps in Regulation and Policies on the Application of Green Technologies at Household Level in the United Kingdom[END_REF][START_REF] Pitron | The war for rare earth metals-The hidden face of the energy and digital transition[END_REF]. Rare earth elements are used in agriculture as well, and numerous reports have highlighted their absorption by plants [START_REF] Hu | Physiological and biochemical effects of rare earth elements on plants and their agricultural significance: a review[END_REF]. Gadolinium (Gd), is also used in magnetic resonance imaging (MRI) as a contrast enhancer [START_REF] Bau | Anthropogenic gadolinium as a micropollutant in river waters in Pennsylvania and in Lake Erie, northeastern United States[END_REF]. Moreover, as REE are becoming a matter of great economic interest, their significant release into the environment is expected over the next few decades. As green technologies continue to advance and find greater application in agriculture, high tech products, etc., REE are likely to be more and more extracted. Their recycling is increasingly gaining attention, however various challenges exist in technologies and methods for REE recovery [START_REF] Jyothi | Review of rare earth elements recovery from secondary resources for clean energy technologies: Grand opportunities to create wealth from waste[END_REF].

Processes to extract REE from secondary sources are under development, it is not yet clear which will be profitable at scale [START_REF] Gaustad | Rare earth metals from secondary sources: Review of potential supply from waste and byproducts[END_REF] and recycling satay less profitable than extraction for some of recovery processes [START_REF] Dang | Toward the circular economy of Rare Earth Elements: a review of abundance, extraction, applications, and environmental impacts[END_REF]. This increasing extrication results in the disruption of REE biogeochemical cycles. However, knowledge gaps exist regarding the substantial short and long-term release of REEs into the environment. The enduring exposure of REE can inflict harm upon animals, plants, and human health [START_REF] Pagano | Human exposures to rare earth elements: Present knowledge and research prospects[END_REF]. High levels of REEs have been associated with organ-specific toxicity, growth inhibition, pneumoconiosis, and nerve diseases source. Consequently, there is mounting concern about REE in recent years, leading to their consideration as emerging pollutants [START_REF] Kulaksız | Contrasting behaviour of anthropogenic gadolinium and natural rare earth elements in estuaries and the gadolinium input into the North Sea[END_REF][START_REF] Liu | Source, environmental behavior and potential health risk of rare earth elements in Beijing urban park soils[END_REF].

Hence, it becomes crucial to assess their sources, transportat pathways and potential health and environmental hazards.

Environmental nanoparticles are common in natural systems [START_REF] Buffle | Characterization of Aquatic Colloids and Macromolecules. 1. Structure and Behavior of Colloidal Material[END_REF][START_REF] Buffle | Characterization of Aquatic Colloids and Macromolecules. 2. Key Role of Physical Structures on Analytical Results[END_REF][START_REF] Wigginton | Aquatic environmental nanoparticles[END_REF]. They are known to play an important role in the distribution and transportation of chemical elements. Among those nanoparticles, natural iron-organic matter (Fe-OM) aggregates are particularly important because of their abundance in natural systems such as wetlands [START_REF] Guénet | Evidence of organic matter control on As oxidation by iron oxides in riparian wetlands[END_REF][START_REF] Lotfi-Kalahroodi | Iron isotope fractionation in iron-organic matter associations: Experimental evidence using filtration and ultrafiltration[END_REF][START_REF] Ratié | Iron speciation at the riverbank surface in wetland and potential impact on the mobility of trace metals[END_REF], peatlands [START_REF] Pokrovsky | Fe-Al-organic colloids control of trace elements in peat soil solutions: results of ultrafiltration and dialysis[END_REF][START_REF] Thomasarrigo | Iron and arsenic speciation and distribution in organic flocs from streambeds of an arsenic-enriched peatland[END_REF] and permafrost [START_REF] Hirst | Characterisation of Fe-bearing particles and colloids in the Lena River basin, NE Russia[END_REF][START_REF] Pokrovsky | Iron colloids/organic matter associated transport of major and trace elements in small boreal rivers and their estuaries (NW Russia)[END_REF]. They are primarily produced in soil as a result of anthropogenic forcing and geochemical and physical processes such as alteration and erosion, as well as oxidation-reduction variations that occur in response to the soil water-saturation/desaturation alternation [START_REF] Lotfi-Kalahroodi | Iron isotope fractionation in iron-organic matter associations: Experimental evidence using filtration and ultrafiltration[END_REF]. Due to global warming, involving an increase in rainfall frequency, volume, and intensity as well as permafrost thawing, the production of these nano-aggregates or colloids has tended to significantly increase in recent decades.

As recently described, inside Fe-OM aggregates, weakly crystallized Fe oxyhydroxides are embedded in an OM matrix following a fractal organisation [START_REF] Beauvois | How does calcium drive the structural organization of iron-organic matter aggregates? A multiscale investigation[END_REF][START_REF] Gentile | Ferrihydrite Nanoparticle Aggregation Induced by Dissolved Organic Matter[END_REF][START_REF] Guénet | Characterization of iron-organic matter nano-aggregate networks through a combination of SAXS/SANS and XAS analyses: impact on As binding[END_REF][START_REF] Poggenburg | Microbial reduction of ferrihydrite-organic matter coprecipitates by Shewanella putrefaciens and Geobacter metallireducens in comparison to mediated electrochemical reduction[END_REF]. Organic matter as molecules and colloids [START_REF] Beauvois | How does calcium drive the structural organization of iron-organic matter aggregates? A multiscale investigation[END_REF][START_REF] Gentile | Ferrihydrite Nanoparticle Aggregation Induced by Dissolved Organic Matter[END_REF][START_REF] Guénet | Characterization of iron-organic matter nano-aggregate networks through a combination of SAXS/SANS and XAS analyses: impact on As binding[END_REF] limit the growth and crystallinity of the Fe phases [START_REF] Pédrot | How does organic matter constrain the nature, size and availability of Fe nanoparticles for biological reduction?[END_REF][START_REF] Vantelon | Iron speciation in iron-organic matter nanoaggregates: a kinetic approach coupling Quick-EXAFS and MCR-ALS chemometrics[END_REF]. As a result, Fe generates Fe(III) monomers, tiny oligomers, and ferrihydrite-like nanoparticles (Fh-like Nps) linked to the OM via the carboxylic (COOH) and phenolic (PhOH) sites [START_REF] Beauvois | How does calcium drive the structural organization of iron-organic matter aggregates? A multiscale investigation[END_REF][START_REF] Vantelon | Iron speciation in iron-organic matter nanoaggregates: a kinetic approach coupling Quick-EXAFS and MCR-ALS chemometrics[END_REF][START_REF] Chen | Properties of Fe-Organic Matter Associations via Coprecipitation versus Adsorption[END_REF][START_REF] Karlsson | Characterization of Iron(III) in Organic Soils Using Extended X-ray Absorption Fine Structure Spectroscopy[END_REF][START_REF] Karlsson | Complexes with aquatic organic matter suppress hydrolysis and precipitation of Fe(III)[END_REF][START_REF] Karlsson | Coordination chemistry and hydrolysis of Fe(III) in a peat humic acid studied by X-ray absorption spectroscopy[END_REF][START_REF] Kleber | Chapter One -Mineral-Organic Associations: Formation, Properties, and Relevance in Soil Environments[END_REF]. The Fh-like Nps have fractal organization and are made of primary beads (radius 0.8 nm) that combine to generate primary aggregates (radius 4 nm), which aggregate to form secondary aggregates (radius > 100 nm) embedded into larger OM aggregates (radius ~ 700 nm) [START_REF] Beauvois | How does calcium drive the structural organization of iron-organic matter aggregates? A multiscale investigation[END_REF][START_REF] Guénet | Characterization of iron-organic matter nano-aggregate networks through a combination of SAXS/SANS and XAS analyses: impact on As binding[END_REF].

Because of the high affinity of OM and Fe phases for metallic elements, REE are expected to bind to these aggregates [START_REF] Grybos | Is trace metal release in wetland soils controlled by organic matter mobility or Fe-oxyhydroxides reduction?[END_REF][START_REF] Marsac | Effects of Fe competition on REE binding to humic acid: Origin of REE pattern variability in organic waters[END_REF][START_REF] La Force | Solid-phase iron characterization during common selective sequential extractions[END_REF]. Therefore, Fe-OM aggregates physical and chemical properties and stability control the metallic elements mobility through the soil and aqueous system. However, mechanisms controlling the interactions between metallic elements and Fe-OM aggregates are still unclear. For a long time, the sorption capacities of heterogeneous aggregates were assuming to follow an additive rule. However, [START_REF] Guénet | Characterization of iron-organic matter nano-aggregate networks through a combination of SAXS/SANS and XAS analyses: impact on As binding[END_REF] revealed that the sorption capacity of Fe-OM aggregates increases with the increasing Fe/organic carbon (OC) ratio while the specific surface area (SSA) of Fe-NPs remained constant, demonstrating that the SSA is not the sole parameter that governs the reactivity of Fe-OM aggregates. Additionally, Calcium (Ca) can significantly impact the structural organization of the Fe-OM aggregates [START_REF] Beauvois | How does calcium drive the structural organization of iron-organic matter aggregates? A multiscale investigation[END_REF]. High Ca concentrations produce the Fe-OM aggregates structural modifications, transitioning from a colloidal state to a non-colloidal micrometric Ca-branched OM network in which Fh-like Nps remained embedded. This drastic modification is mostly caused by the binding of Ca to the OM COOH sites. According to [START_REF] Beauvois | How does calcium drive the structural organization of iron-organic matter aggregates? A multiscale investigation[END_REF] and Davis and Edwards (2017), under these conditions, two antagonistic effects are anticipated when the interactions between Fe and OM are partially screened. Network formation decreases of SSA, resulting in less adsorption, while colloids branching increases the density of available binding sites, leading to an increase in adsorption. Investigating the REE adsorption mechanisms is thus crucial to comprehend the overall adsorption capability of the Fe-OM aggregates and their subsequent impact on REE mobility and transfer in the environment.

Our objective is to provide a detailed description of the parameters that control the Fe-OM aggregate as regard to REE. Aggregates of Fe-OM-Ca were synthesized with a constant Ca/Fe ratio of 0.5 (mol mol -1 ) and various Fe/OC ratios (ranging from 0.1 to 0.0008 mol mol -1 ).

Adsorption experiments were carried out to investigate the distribution of REE relative to structure of the Fe-OM aggregates in order to evaluate the involved mechanisms and the controlling parameters. For this, experimental datasets were analysed to investigate the REE patterns variation relative to the REE concentrations, Fe/OM ratio, presence of Ca and pH. The surface interactions of REE with the Fe-OM aggregate was investigated by X-ray absorption spectroscopy (XAS), carried out at the Ce K-edge.

Materials and methods

Colloid synthesis

The colloids were synthesized with Leonardite humic acid (HA) (International Humic Substances Society) at Fe/OC ratios = 0.25 (mol mol -1 ) and without or with Ca for Ca/Fe = 0.5 following the protocol of Guénet et al. [START_REF] Guénet | Characterization of iron-organic matter nano-aggregate networks through a combination of SAXS/SANS and XAS analyses: impact on As binding[END_REF] and Beauvois et al. [START_REF] Beauvois | How does calcium drive the structural organization of iron-organic matter aggregates? A multiscale investigation[END_REF][START_REF] Beauvois | How crucial is the impact of calcium on the reactivity of iron-organic matter aggregates? Insights from arsenic[END_REF][START_REF] Beauvois | Aluminum-induced colloidal destabilization of iron-organic matter nanoaggregates[END_REF]. The studied ratio were chosen in coherent with those reported for natural wetland by Dia et al. [START_REF] Dia | The distribution of rare earth elements in groundwaters: assessing the role of source-rock composition, redox changes and colloidal particles[END_REF] and Pourret et al. [START_REF] Pourret | Colloidal Control on the Distribution of Rare Earth Elements in Shallow Groundwaters[END_REF] . Humic acids major elements are C = 63.81%, O = 31.27% as a mass fraction. All aqueous solutions were prepared with ultra-pure water (Milli-Q-Integral, Millipore). The samples were named with specific titles (Caxx-Feyy) and (Fexx-OMyy) according to Fe-OM and Ca-Fe ratios.

By HA titration with Fe(II) and Ca(II) solution for the Ca-containing colloids, the Fe-OM colloids were synthesized. The exact protocol is detailed by Guénet et al. [START_REF] Guénet | Characterization of iron-organic matter nano-aggregate networks through a combination of SAXS/SANS and XAS analyses: impact on As binding[END_REF]. The titration solution was prepared with FeCl 4 .4H 2 O (Sigma Aldrich) at 1000 mg L -1 of Fe(II) and CaCl 2 .2H 2 O (Sigma Aldrich) at 1000 mg L -1 of Ca(II).

The ionic strength (IS) of the titration and HA solutions were fixed at 5 mM with NaCl. The titration solution was added to a HA suspension at 700 mg L -1 at 0.05 mL min -1 using an automated titrator (Titrino 794, Metrohm). The pH was kept constant at 6.5 by adding NaOH 0.1M. (Titrino 794, Metrohm). The pH measurement accuracy was ±0.04 pH unit.

Adsorption Experiments

Adsorption experiments of REE (Lanthanide, from La to Lu stock solution CCS-1, Inorganic Venture) by Fe-OM colloids were carried out at five REE/Fe molar ratios from 0.0008 to 0.1 as measured on natural samples collected from mining areas. The colloids suspensions were diluted 100 times without modifying the Fe/OM ratios. The dilution did not modify the colloids size and stability significantly as showed by DLS measurement (detailed results are provided in supplementary information SI. 1). REE adsorption by colloids was investigated using a common batch equilibrium method. After REE addition to the colloid's suspension, the pH was adjusted at pH 4 and 6 with HNO 3 and/or NaOH (0.1 to 1 mol L -1 ). These pHs were chosen to obtain REE pattern at low and high REE loading (amount of adsorbed REE). The equilibrium time was 48 hours as determined from previous studies [START_REF] Catrouillet | Rare earth elements as tracers of active colloidal organic matter composition[END_REF].

At equilibrium, the suspensions were ultra-filtered at 3 kDa with Polyether sulfone membrane (PES) (Sartorius) and using ultrafiltration cells to separate REE bound to the colloids from the solution. The ultrafiltration cells were washed with 0.05M HNO 3 and 3 times with ultra-pure water to reach a total dissolved organic carbon concentration under 0.2 mg L -1 . After ultrafiltration, all samples were acidified with 0.37 mol L -1 HNO 3 before ICP-MS measurements.

REE complexation with colloids is described using the apparent partition coefficient K d relative to the dissolved organic carbon (DOC), as follow:

= (Eq. 1) 𝐾 𝑑 (𝑙𝑛) [𝑙𝑛 𝑎𝑑𝑠𝑜𝑟𝑏𝑒𝑑 ] 𝜇𝑔 𝐿 -1 𝑔 𝐷𝑂𝐶 [𝑙𝑛 3 + ]𝜇𝑔 𝐿 -1
Where ln = La to Lu

The pattern evolution relative to the experimental conditions was highlighted using the La/Sm ratio that fingerprint the MREE downward concavity modification and the Gd/Yb ratio that fingerprint the LREE increase or decrease. Both were calculated using the log K d (ln).

Chemical analysis

Total organic carbon (TOC) was measured using a TOC-V Shimadzu analyser, the accuracy of measurement was ±5% as determined by using a standard solution of potassium hydrogen phthalate (Sigma Aldrich).

The concentrations of Fe, Ca and REE were measured using a QQQ-ICP-MS instrument (Agilent Technologies-8'900), features two quadrupole mass filters and has greater sensitivity and smaller backgrounds than single quadrupole ICP-MS, which facilitates analysis of particulate pollutants.

Calibration curves were generated and validated with certified reference materials (SLRS-6, National Research Council). A rhodium solution was used as an internal standard to correct for instrumental drift and possible matrix effects. The average limit of quantification of REE was calculated by measuring 10 blank samples. After averaging the standard deviation (SD), the limit of quantification (LOQ) was calculated using the following formula: (Eq. 2) LOQ = 10×SD and was considered to be 0.1 ppt. Since the upper limit of the REE calibration curve was 5 ppb, samples were diluted so that this value was not exceeded.

Dynamic light scattering was used to verify the effects of dilution on colloids (VASCO Flex, Cordouan Technologies), details of the methodology are provided in SI-Table S1.

X-ray absorption spectroscopy

X-Ray Absorption Spectroscopy (XAS), including X-ray Absorption Near Edge Spectroscopy (XANES) and Extended X-ray Absorption Fine Structure (EXAFS), was performed to identify the atomic neighbouring of REE when adsorbed by Fe-OM colloids. Since the adsorption edges of REE are close to each other, it is impossible to record EXAFS when the whole REE group is present. We therefore chose to study only Ce notably because of its potential to be oxidized by Feoxides [START_REF] Bau | Scavenging of dissolved yttrium and rare earths by precipitating iron oxyhydroxide: experimental evidence for Ce oxidation, Y-Ho fractionation, and lanthanide tetrad effect[END_REF][START_REF] Takahashi | Determination of the oxidation state of cerium in rocks by Ce LIII-edge X-ray absorption near-edge structure spectroscopy[END_REF]. Cerium(III) was adsorbed at a Ce/Fe ratio = 0.1 mol mol -1 onto the 0.25 Fe-OM colloids without and with Ca (Ca/Fe ratio = 0.5 ) at pH 7 and IS = 5 mmol L -1 of NaCl. The Ce L3edge XANES and EXAFS spectra (5723 eV) were record at the Synchrotron SOLEIL on the LUCIA beamline (SOLEIL, St Aubin, France) [START_REF] Flank | a microfocus soft XAS beamline[END_REF][START_REF] Vantelon | The LUCIA beamline at SOLEIL[END_REF]. A Si(111) double crystal was used as monochromator. The monochromator was calibrated by setting the initial inflexion point of a Cr metallic foil XANES to 5987 eV, the beam size was 2×2 mm 2 . Measurements were performed in fluorescence mode (using a Bruker 60 mm2 mono-element SDD) and in transmission (using a silicon diode) when possible. The reference compounds (CeO 2 and Ce(SO 4 ) 3 ) were prepared as pellets of finely ground and homogenized powder combined with cellulose. The Ce adsorbed Fe-OM aggregates samples (Ce-Fe-OM, Ce-Fe-OM-Ca), were crushed on indium foil. All the samples were analysed under vacuum at 25 K, using a liquid helium cryostat to prevent any beam-induced redox damages. EXAFS spectra were collected with steps of 3 eV in the pre-edge region (5650-5710 eV), 0.5 eV in the edge region (5711-5790 eV), and 2 eV in the post-edge region (5791-6100 eV), with a counting time of 1 s step -1 . For each sample, the recorded spectra (up to four) were superimposed, demonstrating that no beam damage had occurred as a result of these measurement conditions. XANES and EXAFS spectra were extracted using the Athena software [START_REF] Ravel | HEPHAESTUS: data analysis for X-ray absorption spectroscopy using IFEFFIT[END_REF] including the Autbk algorithm (Rbkb = 1 , K-weight = 3). Normalized spectra were obtained by fitting the pre-edge region with a linear function and the post-edge region with a quadratic polynomial function.

EXAFS spectra were analysed by shell fitting. A theoretical back scattering paths were calculated from the crystal structure of Ce(HCOO) 3 [START_REF] Hennig | Crystal structure and solution species of Ce (III) and Ce (IV) formates: From mononuclear to hexanuclear complexes[END_REF]. Theoretical phase and amplitude functions were calculated using FEFF. The paths were carefully considered and selected for the final fits using the Artemis software [START_REF] Ravel | HEPHAESTUS: data analysis for X-ray absorption spectroscopy using IFEFFIT[END_REF]. The Fourier transform of the k 3 -weighted EXAFS spectra were calculated over a range of 2-9 Å -1 using an Hanning apodization window (window parameter = 1). The shell fits were performed on the 1-5 Å range of the FTs k 3 -weighted spectra. The amplitude reduction factor was set to 0.9. The number of O was fixed to 9 throughout the data fits as performed by Henning et al. 2013.

Results

Rare Earth Elements adsorption patterns

The patterns of the distribution coefficient (Log K d ) of REE bound to colloids with and without Ca were plotted relative to the REE/Fe ratios in figure 1 [START_REF] Marsac | Effects of Fe competition on REE binding to humic acid: Origin of REE pattern variability in organic waters[END_REF][START_REF] Davranche | Adsorption of REE(III)-humate complexes onto MnO2: Experimental evidence for cerium anomaly and lanthanide tetrad effect suppression[END_REF][START_REF] Marsac | Metal loading effect on rare earth element binding to humic acid: Experimental and modelling evidence[END_REF] (Figure 1A). More importantly, at low REE concentration and loading (i.e. REE/Fe ≤ 0.0129), patterns exhibited a non-common enrichment of light REE (LREE) and a depletion of heavy REE (HREE) as illustrated by the increasing La/Sm ratios (Figure 1B). When the REE are adsorbed on the MO, the pattern exhibits an enrichment in LREE at low loading that evolves to a MREE downward concavity at high loading [START_REF] Marsac | Metal loading effect on rare earth element binding to humic acid: Experimental and modelling evidence[END_REF][START_REF] Pourret | Rare earth elements complexation with humic acid[END_REF]. When adsorbed on the surface of Fe oxyhydroxides, a tetrad effect, sometimes a positive Ce anomaly and a strong MREE downward concavity, due to the low La adsorption, are developed [START_REF] Bau | Scavenging of dissolved yttrium and rare earths by precipitating iron oxyhydroxide: experimental evidence for Ce oxidation, Y-Ho fractionation, and lanthanide tetrad effect[END_REF][START_REF] Quinn | Sorption of yttrium and rare earth elements by amorphous ferric hydroxide: Influence of solution complexation with carbonate[END_REF]. An enrichment in LREE is never observed for both phases. Moreover, up to our knowledge, such patterns have never been observed in natural water [START_REF] Hirst | Characterisation of Fe-bearing particles and colloids in the Lena River basin, NE Russia[END_REF][START_REF] Pokrovsky | Iron colloids/organic matter associated transport of major and trace elements in small boreal rivers and their estuaries (NW Russia)[END_REF][START_REF] Gruau | Controls on the distribution of rare earth elements in shallow groundwaters[END_REF][START_REF] Pokrovsky | Organic and organo-mineral colloids in discontinuous permafrost zone[END_REF]. However, at low REE loading, the fraction < 3 kDa exhibited a REE pattern with a MREE downward concavity and an enrichment in HREE (exact inverse of the REE patterns of the > 3 kDa fraction) (SI, Figure S1 A andB) and a DOC concentration at around 0.3 mg L -1 , indicating that small organic colloids have passed through membrane. In presence of OM, this typical REE pattern was previously attributed, for low REE loading, to the binding of REE by OM as multidentate or phenolic complexes [START_REF] Marsac | Metal loading effect on rare earth element binding to humic acid: Experimental and modelling evidence[END_REF]. All these results suggested that, at pH 6, small organic colloids (size < 3 kDa) have preferentially bound REE as strong complexes, imposing an inverse pattern on the solution > 3 kDa. Note, however, that only 0.9 % of REE are released from the Fe-OM colloids with these organic colloids < 3 At pH 4 without Ca, the log K d was lower than those at pH 6 indicating a smaller amount of bound REE (figure 2A). A MREE downward concavity was observed for all REE loadings that decreased with the decreasing REE loading in response to the increasing La adsorption as compared to Sm (Figure 2 A andB). No significant HREE variations were observed (Figures 2 A andB). At pH 4, no small organic colloids pass thus through the 3 kDa membrane. At pH 4, most binding sites are protonated limiting the adsorption of REE and the formation of multidendate complexes.

Complexation with phenolic sites is limited since they are all protonated (pKa -OH 8) [START_REF] Chang | Surface complexation model of rare earth element adsorption onto bacterial surfaces with lanthanide binding tags[END_REF].

Therefore, acidic pH limits the release of REE complexes with small organic colloids and the REE adsorption as strong complex, avoiding a significant variation of the REE pattern with the REE loading. With Ca, the patterns were flatter with a less marked MREE downward concavity and no HREE variations as demonstrated by the very small variation of La/Sm and Gd/Yb ratios (Figure 2C andD).

REE adsorption Isotherms

Lanthanum, Eu and Yb adsorption isotherms are plotted for the 0.25 Fe-OM ratio with and without Ca at pH 6 and 4 in figure 3. At pH 6 without Ca, La, Eu and Yb adsorbed concentrations increased with the increasing free REE concentrations without reaching a plateau. Adsorption isotherms can be divided in two parts. For free La, Eu and Yb < 10 -2 mg L -1 , adsorption increased strongly with the free concentration. Over this value, adsorption increased weakly suggesting a progressive saturation of the surface even if no plateau was reached. Lanthanum was more adsorbed than Eu which is more adsorbed than Yb. At pH 6 with Ca, lower amount of La, Eu and Lu are adsorbed (log K d values are lower with Ca, Figure 2 C andD). The inflection concentration of the isotherm was around 5×10 -3 mg L -1 , namely 2 time smaller than without Ca. Such result indicated a progressive site saturation, reached at lowest concentration than without Ca. Moreover, a pseudo equilibrium seemed to be reached for La (Figure 3 B). All these results suggest an impact of the Ca on the binding mechanism of REE by the Fe-OM colloids. At pH 4 without Ca, La, Eu and Yb adsorbed concentrations were strongly lower than at pH 6 (6 against 16 mg L -1 for La at pH 4 and 6, respectively). This decrease can be explained by the increase of the protonated OM sites as well as the OM aggregation that limit the binding site availability [START_REF] Alvarez-Puebla | Effect of pH on the aggregation of a gray humic acid in colloidal and solid states[END_REF]. The isotherms were also quite different than at pH 6. Without Ca, if Isotherm can be divided in two parts, the first part that corresponded to the strongest adsorption, have a lower slope (0.32) indicating a lowest adsorption than at pH 6. From 5×10 -2 mg L -1 a pseudo plateau seemed to be reached. These results demonstrated that pH 4 strongly limit the REE adsorption onto the Fe-OM colloids and that a site saturation was reached. With Ca, adsorption isotherm exhibited the same slope (0.32) and no plateau seemed to be reached. However, the max of adsorption is the same for experiment with and without pH (ex. for La, adsorbed max was equal to 6.9 mg g -1 without Ca against 6.6 mg g -1 with Ca). Therefore, at pH 4 for this Ca concentration, the presence of Ca seems have no influence on the sorption processes.

X-Ray-Absorption microscopy

The oxidation state of Ce in Ce-Fe-OM samples with and without Ca was determined from XANES spectra collecting at the Ce L III -edge. The spectra of both Ce-Fe-OM colloids with or without Ca and that of the Ce(III) reference are reported in Figure 5. The spectra shapes demonstrated a noticeable difference between trivalent and tetravalent Ce, namely that Ce(III) exhibits a single sharp peak around 5727 eV followed by a broad oscillation around 5760 eV while Ce(IV) exhibits a two-humped peak at 5731 and 5738 eV respectively followed by a broad oscillation at 5770 eV. The white line maximum of the 2 samples at 5726.82eV matched with that of the Ce(III) reference, and is followed by a broad band centred around 5760 eV. These results demonstrated that Ce was present as Ce(III) in both Ce-Fe-OM colloids and that no oxidation seemed to occur in these samples. However, several studies suggested that Fe-oxyhydroxide has the possibility to catalysis the oxidation of Ce(III ) as Ce(IV) [START_REF] Bau | Scavenging of dissolved yttrium and rare earths by precipitating iron oxyhydroxide: experimental evidence for Ce oxidation, Y-Ho fractionation, and lanthanide tetrad effect[END_REF][START_REF] Takahashi | Determination of the oxidation state of cerium in rocks by Ce LIII-edge X-ray absorption near-edge structure spectroscopy[END_REF]. By contrast, from Ce L III -edge XAS analysis of a Ceferrihydrite, [START_REF] Nakada | Isotopic and speciation study on cerium during its solidwater distribution with implication for Ce stable isotope as a paleo-redox proxy[END_REF] and [START_REF] Yu | Cerium sequestration and accumulation in fractured crystalline bedrock: the role of Mn-Fe (hydr-) oxides and clay minerals[END_REF] showed that Ce adsorbed on ferrihydrite exists predominantly as trivalent species, and no oxidation of Ce(III) as Ce(IV) occurred at the ferrihydrite surface under their physico-chemical conditions (pH 5 and 6.4 and Ce/Fe ratio = 0.1). However, [START_REF] Yu | Cerium sequestration and accumulation in fractured crystalline bedrock: the role of Mn-Fe (hydr-) oxides and clay minerals[END_REF], observed a modest shoulder at 5737 eV on their XANES spectra that could correspond to a small amount of Ce(IV). The EXAFS and the corresponding Fourier-Transform (FTs) of the Fe-OM colloids with and without Ca are reported in Figure 5. The EXAFS spectra of both samples were quite similar, monotonously oscillating with a shoulder occurring at 6 Å -1 which has a higher intensity in presence of Ca. Three peaks dominated the FT. The first peak located at 2.2 Å (R+∆R), corresponded to the first shell of neighboring atoms around the Ce. The scattering of the Ce neighbors from the second and third coordination shells led to the formation of the second and third peaks, which were respectively measured at 2.8 and 3.5 Å (R + ∆R). The first intense peak at 2.2Å was well reproduced with the backscattering signal of 9 O first neighbors at 2.51 Å. The peak at 2.8 Å was fitted by adding C as second neighbor at 3.25 Å (Table 1).

Table 1 EXAFS Fit Parameters of Fe-OM-Ce and Fe-Ca-OM-Ce for Ce/Fe ratio = 0.1, Fe-OM 0.25 and Ca/Fe ratio = 0.5 at pH 6 and IS 5 mmol L -1 of NaCl. E0 was set to 5.24 eV, S02 to 0.

a Coordination numbers are taken from the crystallographic data of Ce(COOH)3 [START_REF] Hennig | Crystal structure and solution species of Ce (III) and Ce (IV) formates: From mononuclear to hexanuclear complexes[END_REF] and fixed during the fit procedure. Errors in R distances are ±1%, errors in coordination numbers are ±10% error on sigma ss ±20%.

The present result clearly demonstrated that no oxidation of Ce(III) as Ce(IV) occurred at the surface of the Fe-OM colloids. Moreover, the fitting of the EXAFS data demonstrated that the second neighbour of Ce at the surface of the colloids is C. All these results suggested that Ce and thus REE could not be bound to the Fe nanoparticles or oligomer constitutive of the colloids but rather to their OM part.

The REE patterns at the Fe-OM colloids surface mainly varied with the pH and REE loading (figure 1). X-ray absorption spectroscopy demonstrated that REE were bound to the OM component of the Fe-OM colloids. This result is also supported by the absence of a Ce positive anomaly development on the REE patterns that can be observed relative to the physico-chemical conditions for the pattern of REE adsorbed onto Fe-oxyhydroxides [START_REF] Bau | Scavenging of dissolved yttrium and rare earths by precipitating iron oxyhydroxide: experimental evidence for Ce oxidation, Y-Ho fractionation, and lanthanide tetrad effect[END_REF]. The variation of the REE pattern is therefore only controlled by the OM behavior relative to the pH conditions.

The most important variation was obtained at pH 6 for the lower REE concentrations and loading.

As previously stated, these patterns are controlled by the fractionation of the OM colloids occurring at pH 6 and resulting in the release of small organic colloids from the supramolecular structure of the whole OM [START_REF] Pédrot | Dynamic structure of humic substances: Rare earth elements as a fingerprint[END_REF]. Under our experimental conditions, these small organic colloids with their REE loading were physically separated from the whole OM colloids thanks to the ultrafiltration membrane (fraction < 3 kDa). The amount of REE adsorbed to this small organic colloid was low (0.012 µg L -1 ). As previously explained by [START_REF] Marsac | Metal loading effect on rare earth element binding to humic acid: Experimental and modelling evidence[END_REF], at low REE loading, REE preferentially form strong multidendate or phenolic complexes with OM which result in a REE pattern exhibited a strong HREE enrichment as observed here at pH 6 in the fraction < 3kDa. Because the REE concentration were low, the REE binding as strong complexes to the small colloids (combined with the K d REE calculation effect) control the REE pattern of the fraction > 3kDa. However, when the REE concentration increased, REE were bound not only as strong complexes (multidendate and phenolic) but also as weaker bidentate complexes with the most abundant COOH sites of the OM [START_REF] Marsac | Metal loading effect on rare earth element binding to humic acid: Experimental and modelling evidence[END_REF]. These complexes become progressively dominants with the increasing REE loading. As a result, the HREE enrichment disappeared since masked by the MREE downward concavity produced by the REE binding to the weak but abundant COOH sites of OM.

At pH 4, the MREE downward concavity was observed regardless of the REE concentrations and loadings indicating that the REE-COOH-OM binding dominate for all experimental conditions although the concentration of adsorbed REE was lower than at pH 6. But, by contrast with pH 6 that involved the fractionation of the whole OM colloids, pH 4 promotes its aggregation [START_REF] Buffle | Characterization of Aquatic Colloids and Macromolecules. 1. Structure and Behavior of Colloidal Material[END_REF][START_REF] Buffle | Characterization of Aquatic Colloids and Macromolecules. 2. Key Role of Physical Structures on Analytical Results[END_REF][START_REF] Pédrot | Dynamic structure of humic substances: Rare earth elements as a fingerprint[END_REF], avoiding the release of small colloids and molecules and therefore the pattern control by the strong but less abundant REE multidendate/phenolic complexes.

This different mechanisms at pH 6 and pH 4 explain the difference obtained for the REE adsorption isotherms. At pH 6, isotherm was more curved and can be divided into two parts from 5×10 -2 mol L -1 free REE. This concentration corresponds to the concentration when the REE binding as bidendate complexes with the -COOH sites become dominant, in response to the OM pHfractionation. By contrast, the isotherm at pH 4 is not controlled by the formed complexes (since OM is aggregated and no fractionation occurred) but rather by the total amount of adsorbed REE.

The influence of Ca on the REE adsorption seems to be low and rather insignificant at pH 4. At pH 6, isotherm suggested that Ca may limit the REE adsorption on the OM part of the Fe-OM colloids. [START_REF] Beauvois | How does calcium drive the structural organization of iron-organic matter aggregates? A multiscale investigation[END_REF] demonstrated that when the Fe-OM colloids are synthesized with Ca, Ca was only bound to the OM and not to the iron phases. Calcium is bound to the COOH OM site, connecting the OM molecules and colloids to form a large network at high concentration of Ca [START_REF] Beauvois | How does calcium drive the structural organization of iron-organic matter aggregates? A multiscale investigation[END_REF]. In our experimental conditions, REE and Ca could therefore compete for their binding to the OM of the Fe-OM colloids which results in a slight decrease of the REE adsorbed amount.

Impact of the colloid dynamic on the REE mobility

Understanding how REEs are transported throughout the environment is one of the first steps toward preventing the health hazards associated with them. Here, we demonstrated that since REE are mainly bound to the OM of the Fe-OM colloids, their fate and their subsequent mobility and transfer will be only controlled by the OM behavior and interactions with the Fe phases and other competitive elements. According to previous research, the aggregation of OM is dynamic, especially with reference to pH [START_REF] Pédrot | Dynamic structure of humic substances: Rare earth elements as a fingerprint[END_REF]. At acidic pH, the amount of REE bound to the Fe-OM colloids is low and pH involves OM aggregation and result in an increase of the Fe-OM colloids size [START_REF] Kipton | Solubility and fractionation of humic acid; effect of pH and ionic medium[END_REF][START_REF] Pinheiro | Dynamic properties of humic matter by dynamic light scattering and voltammetry[END_REF] which can limits their mobility and transfer as well as that of adsorbed REE in porous media such as soil and sediment. By contrast, at higher pH, the aggregation is lower. The COOH groups are progressively protonated increasing the repulsion between organic molecules/colloids. However, at pH 4, some H bonding that remained, combined with the Fe phases occurrence, maintain a degree of aggregation that result in the release of a limited quantity of tiny colloids. Kloster et al; (2013) estimated that fractionation of humic substances can occur only down to 60% of aggregation [START_REF] Kloster | Aggregation kinetics of humic acids in the presence of calcium ions[END_REF]. The result is that only 0.9 % of REE are released from the Fe-OM colloids with this tiny organic colloid. This percentage is sufficient to control the log K dREE pattern in our experimental conditions notably due to the log K dREE calculation mode . This fractionation will thus influence the REE mobility only regarding to the amount of this tiny OM colloids that can be produced under the prevailing environmental conditions. At pH 6, the size of the OM and subsequently of the entire Fe-OM colloids decrease while complexing high amount of REE (between 90 to 99 % with the decreasing REE concentration). In such conditions, the mobility/transfer of REE will depend on the ability of the colloids to be water-transferred in the soil porosity or in surface water relative to the physico-chemical conditions.

A last important point is the impact of the major ion that influence the colloid structural organization, and/or compete with REE for their binding by OM. [START_REF] Beauvois | How does calcium drive the structural organization of iron-organic matter aggregates? A multiscale investigation[END_REF] demonstrated that at pH 6.5, the size of OM inside the Fe-OM colloids significantly increases from Ca/OC = 0.026 (mol mol -1 ) until forming an OM micrometric network that finally settled bringing with it the initially bound Fe phases. Before Ca/OC = 0.026, the OM size is around 400 nm and the Fe-OM aggregate behave as colloid, namely are stable in solution. Here Ca/OC = 0.5 (mol mol - 1 ), Fe-OM aggregate was thus stable in solution, and its sole influence is its low competition with REE. In these conditions, this competition is only possible since Ca is present as major ion although REE are as trace elements. Rare earth elements as metallic element and trivalent ion have indeed larger affinity for the carboxylic sites than Ca (log K REE-COOH is in the range of 2.55-2.84 and log K Ca-COOH = 1.18) [START_REF] Martell | Carboxylic Acids[END_REF]. Therefore, the impact Fe-OM aggregates will only significantly influence the REE mobility and transfer for high Ca/OC ratio when Ca can involve the formation of a micrometric network. Beauvois et al. (2023) also studied the impact of Al as major ion on the Fe-OM structural arrangement. They demonstrated that at pH 6.5, Al form monomers/oligomers that polymerized which branch out the OM and Fe aggregates resulting in a large settling network [START_REF] Beauvois | Aluminum-induced colloidal destabilization of iron-organic matter nanoaggregates[END_REF]. In such conditions, Al will have the same impact on the REE mobility/transfer than Ca.

Hence, the most important factors affecting the REE mobility/transfer is the parameter that modify the colloids conformational structure with respect to pH, and major ion concentration. The REE bound to Fe-OM colloids are thus expected to be immobilized by the colloid settlement and in soil and sediment, by the colloids trapping by the porosity. The challenge today is thus how the REE reactivity is controlled by the organo-mineral colloids structural arrangement relative to the prevailing physico-conditions.

Conclusion

Evaluating the mobility/transfer of REE in this environment is crucial to determine their environmental impact and the potential to be transfer between the various environmental compartment (water, soil, biota). The present study focused on the potential of the Fe-OM aggregates to bind and subsequently control the REE mobility and transfer. The choice of Fe-OM aggregate is justified by 1) the high binding affinity of REE for both Fe phases [START_REF] Bau | Scavenging of dissolved yttrium and rare earths by precipitating iron oxyhydroxide: experimental evidence for Ce oxidation, Y-Ho fractionation, and lanthanide tetrad effect[END_REF][START_REF] Quinn | Sorption of yttrium and rare earth elements by amorphous ferric hydroxide: Influence of solution complexation with carbonate[END_REF] and OM [START_REF] Catrouillet | Rare earth elements as tracers of active colloidal organic matter composition[END_REF][START_REF] Pourret | Rare earth elements complexation with humic acid[END_REF][START_REF] Marsac | An improved description of the interactions between rare earth elements and humic acids by modeling: PHREEQC-Model VI coupling[END_REF][START_REF] Tang | Speciation of rare earth elements in natural terrestrial waters: assessing the role of dissolved organic matter from the modeling approach[END_REF], 2) the ubiquity and increasing environmental production of Fe-OM aggregate with the climatic global changing and 3) the well-known structure of such aggregates [START_REF] Beauvois | How does calcium drive the structural organization of iron-organic matter aggregates? A multiscale investigation[END_REF][START_REF] Gentile | Ferrihydrite Nanoparticle Aggregation Induced by Dissolved Organic Matter[END_REF][START_REF] Guénet | Characterization of iron-organic matter nano-aggregate networks through a combination of SAXS/SANS and XAS analyses: impact on As binding[END_REF][START_REF] Beauvois | How crucial is the impact of calcium on the reactivity of iron-organic matter aggregates? Insights from arsenic[END_REF][START_REF] Beauvois | Aluminum-induced colloidal destabilization of iron-organic matter nanoaggregates[END_REF].

Rare earth elements adsorption experiments by Fe-OM aggregate without and with Ca were thus carried out at pH 4 and 6. Rare earth element adsorption pattern combined with Ce-L III edge XAS experiments showed that REE were only bound to the OM component of the Fe-OM aggregates which demonstrate that REE fate is only control by OM in the Fe-OM aggregates. As expected, the amount of the REE adsorbed increased with the increasing pH in response to the OM binding site deprotonation. The pH also controls the aggregation/disaggregation and size of the OM part of the Fe-OM colloids. This control result, at pH 6, in the release of tiny OM colloids (size < 3kDa) in which REE form strong multidendate and/or phenolic complexes. However, they only complex 0.8% of the initial REE concentration. The impact of this tiny colloids on the REE mobility and transfer will thus depend on the quantity that can be produced as regards to the prevailing environmental conditions. But, pH 6 also promote the decrease of the Fe-OM size that will increase their mobility and those of the REE. By contrast, at pH 4, as demonstrated in the literature, the size of the OM colloids increases and potentially limits its mobility/transfer and those of REE.

However, at pH 4, 4 time more REE remain soluble in solution as compared to pH 6 (amount of adsorbed REE 4.4 mg g -1 at pH 4 against 12 mg g -1 ). Therefore, while the Fe-OM size increase, pH will globally promote the REE mobility.

In the studied experimental conditions, the impact of Ca was low and can only be observed at pH 6. The Ca impact only occurred through its competition with REE for its binding to the OM COOH groups and since occurring as major ion. At pH 4, no impact of Ca was notified although its high concentration, Ca was unable to compete with REE for the lower quantity of deprotonated COO-groups. However, as demonstrated in the literature for pH 6.5, for higher concentration Ca as well as other major ions as Al, a micrometric OM network can occur and result in the Fe-OM settlement that will immobilized REE.

Therefore, the mobility and transfer of REE when interacting with Fe-OM aggregates is mainly controlled by the pH that controls 1) the REE adsorbed amount, 2) the size of the aggregate and its subsequent mobility in porous media 3) and indirectly the amount of major ions that are allowed to bind to OM and to polymerize in order to form a micrometric network that result in the Fe-OM aggregates settlement in the porous media or in the water flow.

  kDa. The presence of Ca seems to not modify significantly both the REE adsorbed amount and patterns as shown by comparison of the Fig 1(A) and (C).

Fig. 1 .Fig. 2 .

 12 Fig. 1. Variation of Log K d REE patterns relative to the REE/Fe ratios (0.1, 0.05, 0.0129, 0.004, 0.0008) at Fe/OM 0.25, without (A) and with Ca (C) and evolution of La/Sm and Gd/Yb ratios relative to REE/Fe without (B) and with Ca (D) at pH = 6. Error bars represent triplicates of experiments.

Fig. 3 .

 3 Fig. 3. Adsorption isotherm of La, Eu and Yb at Fe/OM 0.25 ratios and 0.1,0.05,0.0129,0.004 and 0.0008 REE/Fe ratios without (A) and with Ca (B) at pH 6, without (C) and with Ca (D) at pH 4.

Figure 4 .

 4 Figure 4. Ce L III -edge XANES spectra for samples and relevant references

Fig. 5 .

 5 Fig. 5. (A) Cerium L III -edge EXAFS spectra for the Fe-OM-Ca and Fe-OM colloids (B) the magnitude and imaginary part of the associated Fourier Transform, not corrected from phase shift. Solid lines are experimental data and dotted lines are the fit results

  and 2 for Fe/OM 0.25 at pH 6 and 4, respectively. All REE patterns varied with the REE/Fe ratios, namely with the REE concentrations and thus REE loading. At pH 6, for high REE concentration and high loading (i.e. REE/Fe  0.05), REE patterns exhibited a typical middle REE downward concavity, typical of the REE binding to OM as previously reported

Declaration of interests

☒ 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.

☐The authors declare the following financial interests/personal relationships which may be considered as potential competing interests:


Camila ; Diaz-Vanegas

Angélique Desoeuvre

Marina Héry
email: marina.hery@umontpellier.fr

Odile Bruneel

Catherine Joulian

Jérôme Jacob

Fabienne Battaglia-Brunet

Corinne Casiot

Bruneel

Diaz-Vanegas

Desoeuvre

Towards an

Keywords: acid mine water, microbial ecotoxicology, biological arsenic oxidation, biological iron oxidation, bioremediation, aioA gene acid mine water, microbial ecotoxicology, biological arsenic oxidation, biological 29 iron oxidation, bioremediation, aioA gene

The attached communities correspond to the bacterial communities living in the biogenic 131 precipitates accumulated in the biomass carriers. These biogenic precipitates were collected 132 by scrapping the biomass carrier in each bioreactor. In the WP bioreactor, they were sampled 133 only from the wood chips (due to the difficult access to the pozzolana at the bottom of the 134 tank). Samples were collected in Falcon tubes (50 mL) and left some minutes for decantation. 135 The supernatant was discarded and the precipitates were distributed into six cryo-tubes (2 136 mL). The suspended communities correspond to the bacteria living in the aqueous phase and 137 associated with the suspended particulate matter (SPM) recovered from filters (0.22 µm). For 138 each point of water sampling (outlet PS,outlet WP, and inlet water), six replicates of outlet 139 water (300 mL each one) were filtered on sterile 0.22 µm cellulose acetate filters.

140 All the solid samples and filters were flash-frozen in dry ice in the field, transported to the 141 laboratory and stored at -80 °C until DNA and RNA extractions.

143

Geochemistry of the waters and the biogenic precipitates and performance of 144 the two bioreactors 145 The chemical characterization of the inlet water, outlet water and biogenic precipitates of each 146 bioreactor is detailed in our previous study [START_REF] Diaz-Vanegas | Performance of semipassive systems for the biological 768 treatment of high -As acid mine drainage : Results from a year of monitoring at the 769 Carnoulès mine (Southern France)[END_REF]. The data for inlet and 147 outlet waters corresponding to the sampling performed for microbiological analyses are 148 summarized in Table 1 and Table SI 1. These data were used for the correlation analyses. In 149 the inlet water, As concentration varied between 50 and 100 mg L -1 and Fe concentration 150 between 500 and 1000 mg L -1 . The AMD was more concentrated in pollutants during the 151 driest and hottest seasons (periods E, F and G) as described before [START_REF] Egal | An updated 778 insight into the natural attenuation of As concentrations in Reigous Creek (southern 779 France)[END_REF]. The pH 152 of the AMD varied between 3.7 and 4.8, with the highest values during period B. The AMD 153 showed a temperature between 8 and 22°C with the highest value during period E. The 154 coldest temperature was measured during periods B and C, which also correspond to the 155 periods with the lowest concentration of total Fe (449-501 mg L -1 ) and As (49-54 mg L -1 ).

156 The hydraulic retention time (HRT) was slightly different between the two devices, with 157 approximately one hour more in the WP device. Two HRT were tested (~ 9h and ~ 18h), but 158 the difference in the performances (rates of Fe and As oxidation and precipitation) was less 414 Correlations between the microbiology (abundance of the 13 most dominant bacterial taxa 415 developed in the bioreactors) and the physico-chemistry of the AMD were assessed by 416 calculating Spearman's coefficients (significant when the coefficient was ≥ 0.5 or ≤ -0.5).

417 Correlations were also determined between the microbiology and the variables reflecting the 418 performance of the treatment system (kinetic constant value KOFe, Fe precipitation rate, As et al., 2010;[START_REF] Bartsch | Metallibacterium scheffleri: 745 Genomic data reveal a versatile metabolism[END_REF][START_REF] Gavrilov | and in Fe-oxidizing bioreactors[END_REF][START_REF] Li | Insights into the metabolism and evolution of the genus Acidiphilium, a typical 881 acidophile in Acid Mine Drainage[END_REF]. These 486 bacteria were globally poorly represented in the active community. However, oxygenation 487 should be carefully controlled to avoid suitable conditions for ferric iron reduction, which 488 would contribute to As remobilization into the aqueous phase [START_REF] Tufano | Confounding impacts of iron reduction on arsenic retention[END_REF].

489 Arsenic remobilization has indeed been evidenced from river sediments impacted by the 490 Carnoulès AMD during incubation under anoxic conditions [START_REF] Héry | 835 Release of arsenite, arsenate and methyl-arsenic species from streambed sediment 836 affected by acid mine drainage: A microcosm study[END_REF].

492

Influence of the biomass carrier on the bacterial diversity

493 Biomass carriers provide a physical support for bacterial growth, extend their survival rate, 494 and enhance oxygen transfer [START_REF] Tyagi | Bioaugmentation and biostimulation 986 strategies to improve the effectiveness of bioremediation processes[END_REF]. Al-Amshawee et al., (2021) reported that 495 the biomass attached to the carriers can be up to 500 times more resistant than suspended 496 bacteria to sudden changes. In a membrane bioreactor, the surface of a biomass carrier 497 provided a diversified environment, promoting the growth of diverse types of microorganisms 498 [START_REF] Li | Microbial community 884 structure analysis in a hybrid membrane bioreactor via high-throughput sequencing[END_REF]. On the contrary, diversity was higher in suspended than in attached 499 communities in a waste water treatment plant, possibly due to oxygen limitation inside the 500 biofilm [START_REF] Kwon | Bacterial community composition and 866 diversity of a full-scale integrated fixed-film activated sludge system as investigated by 867 pyrosequencing[END_REF]. As recently reported [START_REF] Zhu | Metagenomic insights into the 1009 effects of various biocarriers on moving bed biofilm reactors for municipal wastewater 1010 treatment[END_REF], the type of biomass 501 carrier can also influence the diversity and composition of the bacterial communities 502 developing inside the bioreactors. 511 512 Our first assumption to explain these differences was that organic carbon provided by the 513 wood chips could promote the development of heterotrophic bacteria. The wood chips are 514 often used in bioreactors as biofilm support as well as a source of organic carbon or electron 515 donors (Lopez-Ponnada et al., 2017;Zhao et al., 2019). This concurs with occasional 516 measurements of total organic carbon in the biogenic precipitates, indicating a much higher 517 concentrations in the WP (71 ± 47 g kg -1 ) than in the PS (3 ± 0.7 g kg -1 (dry wt.). However, [START_REF] Michel | Biofilms of 914 As(III)-oxidising bacteria: Formation and activity studies for bioremediation process 915 development[END_REF] showed that As(III) oxidation 597 activity of some Thiomonas strains was higher for the suspended cells than for the attached 598 ones. This is in agreement with our results for the WP bioreactor, but contradictory with the 599 results for the PS bioreactor. Consequently, in the present study, As(III) oxidation by 600 Thiomonas did not seem to be conditioned by their lifestyle. It is also possible that the 601 Thiomonas strains developed in the PS and WP bioreactors were able to switch from attached 602 to suspended mode as reported by [START_REF] Farasin | Comparison of biofilm 787 formation and motility processes in arsenic-resistant Thiomonas spp. strains revealed 788 divergent response to arsenite[END_REF]. There is growing evidence that 603 environmental bacteria are capable of alternating between the free living and the attached 604 fractions [START_REF] Grossart | Ecological consequences of bacterioplankton lifestyles: changes in[END_REF] and that the two fractions are connected [START_REF] Tang | Spatiotemporal dynamics of 977 bacterial community composition in large shallow eutrophic Lake Taihu: High overlap 978 between free-living and particle-attached assemblages[END_REF]. 626 grow in more acidic conditions than Gallionella [START_REF] Ziegler | Oxygen-dependent niche formation of a 1013 pyrite-dependent acidophilic consortium built by archaea and bacteria[END_REF]. Accordingly, Ferrovum 627 showed a negative correlation with pH. All these findings are consistent with previous studies 628 showing that Gallionella is favored at pH > 3 while Ferrovum are favored at pH < 3 ( Jones et 629 al., 2015;[START_REF] Sheng | 970 Bioreactors for low-pH iron(II) oxidation remove considerable amounts of total iron[END_REF]. 630 631 In AMD, dissolved ferrous iron (Fe(II)) is one of the main energy source for bacteria; thus, its 632 concentration may be another important factor determining geochemical niches of FeOB 633 [START_REF] Jones | Geochemical 856 niches of iron-oxidizing acidophiles in acidic coal mine drainage[END_REF]. Here, the relative abundance of Gallionella and Gallionellaceae-related 634 sequences were negatively correlated with Fe(II) concentration as described elsewhere 635 [START_REF] Fleming | Ecological succession among 808 iron-oxidizing bacteria[END_REF]. The abundance of Ferrovum increased during period D and E in both 636 bioreactors concomitantly to the increase of the Fe(II) concentration in the inlet water.

F
637 Assignment of Ferrovum to high Fe concentration was also reported by Jones et al 2015.

638 639 In the PS bioreactor, Acidithiobacillus abundance increased when the highest Fe(II) 640 concentrations (712-1049 mg L -1 ) were measured in the inlet water (periods F and G). This is 641 in contradiction with other study [START_REF] Jones | Geochemical 856 niches of iron-oxidizing acidophiles in acidic coal mine drainage[END_REF] where this genus was restricted to lower 642 Fe(II) concentration (< 224 mg L -1 ). Then, another factor should be responsible for the 643 dynamic of Acidithiobacillus in the PS bioreactor at the end of the monitoring. During periods 644 F and G, oxygen limitation, due to the clogging of the aeration system, could be detrimental 645 to Ferrovum and Leptospirillum [START_REF] Ziegler | Oxygen-dependent niche formation of a 1013 pyrite-dependent acidophilic consortium built by archaea and bacteria[END_REF][START_REF] Johnson | Uncovering a microbial enigma: isolation and 852 characterization of the streamer-generating, iron-oxidizing, acidophilic bacterium 853 "Ferrovum myxofaciens[END_REF]. Conversely, the 646 capacity of Acidithiobacillus to live in microaerophilic conditions has been widely described 647 [START_REF] Dave | Characterization of arsenic resistant and arsenopyrite 762 oxidizing Acidithiobacillus ferrooxidans from Hutti gold leachate and effluents[END_REF]. Thus, the dynamic of Acidithiobacillus in the bioreactors may be 648 attributed to the synergy of the lack of oxygenation, the different biomass carrier used or 649 another undetermined factor. et al., 2013;Johnson et al., 672 2014). The maintenance of their activity even at high As concentration (50 -100 mg L -1 ) is an 673 important point to consider for the treatment of high-As AMD.

674 675 Despite the slight differences observed in the microbiology of the two bioreactors, the general 676 performances (in terms of As and Fe oxidation and removal) were similar. The global stability 677 of the system performances, (including both the temporal stability and the capacity to recover 678 the performances after disturbances) may rely on functional redundancy of the bacterial 679 communities. Indeed, different taxonomic groups sharing similar functions allowed the 680 performance of a system to be maintained even when the community structure changes 681 [START_REF] Allison | Resistance, resilience, and redundancy in microbial communities[END_REF]. Thus, the robustness of the treatment system may rely both on 682 the resilience capacity and the functional redundancy of the bacterial communities. This is in 694 permanent member of the active community, which suggests its contribution to the stable 695 performances. The bioreactor filled with wood and pozzolana (WP) showed a faster recovery 696 of its performances after interruptions that may be attributed to a higher bacterial alpha 697 diversity.

698 Our work provided the first evidence of the expression of the arsenite oxidase gene (aioA) in 699 treatment bioreactors under field-conditions. This is an important function since As oxidation 700 contributes to a more efficient removal of As, mainly under its more stable form (As(V)), 701 which is a clear advantage for future application in bioremediation. More effort is required to 702 optimize the quantification of aioA gene expression to better identify the factors regulating 703 the expression of this key function.

704 The resilience of bacterial communities to operational disruptions and variability of the 705 chemistry of the AMD of on-site treatment is another essential point in the perspective of a 706 large-scale AMD treatment.

707 The validation of our process in real field conditions provided achievement of Technology 2 Solid lines represent the evolution of the kinetic constant value (KOFe) for the WP and PS bioreactors.

3

Dashed lines represent the evolution of the arsenic precipitation rates (mol L -1 s -1 ) calculated for each 4 pilot. The triangles and the squares represent the data from the PS and WP bioreactor respectively 5 (Diaz- [START_REF] Diaz-Vanegas | Performance of semipassive systems for the biological 768 treatment of high -As acid mine drainage : Results from a year of monitoring at the 769 Carnoulès mine (Southern France)[END_REF]. The stars represent the periods with the clogging of the air diffusers. The 6 values used for this graph correspond to the average of the data obtained for each period. 1, supplementary Table S1 andS2

Introduction32

  Acid mine drainages (AMD) are undesired products of the weathering of sulfide minerals 33 present in mining wastes. They contribute to decreasing the pH and releasing metals and 34 metalloids into aquatic environments. Arsenic is associated with more than 200 minerals through the analysis of environmental RNA and distinguished the 95 communities attached to the supports to those in suspension. Bacterial diversity was 96 determined by metabarcoding of the 16S rRNA gene and the presence and the expression of 97 the As(III) oxidase gene quantified by quantitative PCR (qPCR). Then, we related the 98 microbiological parameters to bioreactors performances and discussed the links between the 99 dynamic of the bacterial communities, the variations of the physico-chemistry of the AMD 100 water and the system treatment stability. bacterial community characterization. Sample collection began in period B 127 (due to the time required to form sufficient quantity of precipitates), and was carried out once 128 per period for each bioreactor. 129 130

  . Occasional measurements of dissolved oxygen concentration inside the bioreactors 160 showed dysfunction of the air diffusers in period F. 161 162 Both bioreactors showed similar Fe oxidation and As removal rates, represented respectively 163 by the first-order kinetic constant of Fe oxidation KOFe and the As precipitation rate 164 determined in Diaz-[START_REF] Diaz-Vanegas | Performance of semipassive systems for the biological 768 treatment of high -As acid mine drainage : Results from a year of monitoring at the 769 Carnoulès mine (Southern France)[END_REF]. The highest performances were obtained during 165 period E (Fe oxidation) and F (As precipitation) as shown in Figure1. In the biogenic 166 precipitates, more than 60 % of total As was under the As(V) oxidation state during the entire 167 monitoring (

339340354

  The dynamic of the FeOB populations was different in the two bioreactors (Figure4). In the 341 PS bioreactor, the first two periods B and C (December and February) were dominated by 342 Leptospirillum, Gallionella, and an undetermined genus from Gallionellaceae family, while 343 in the WP bioreactor, Leptospirillum was the only dominant FeOB. Then, the FeOB 344 populations evolved towards a dominance of Ferrovum and Leptospirillum in both 345 bioreactors. At the end of the monitoring(period F and G), the communities of the PS 346 bioreactor were enriched with Acidithiobacillus. Gallionella was mainly present and active 347 during the first stage of the monitoring only in the suspended community of the WP 348 bioreactor, but present in both suspended and attached communities in the PS bioreactor.349 The OTUs affiliated to the Gallionellaceae family were dominant in PS bioreactor in the 350 suspended and attached communities during period B and C, but they relative abundance 351 dramatically decreased from period D. In a lesser extent, the same trend was observed for 352 Acidocella and Granulicella. Thiomonas was the sixth most dominant genus identified in the metabarcoding data (Figure355 4). It was always detected in both the total and active communities, although its distribution 356 showed a different pattern in the two bioreactors. In the WP bioreactor, Thiomonas was more 357 abundant in the suspended community during period E, with a similar trend between total and 358 active communities. On the contrary, in the PS bioreactor, Thiomonas was more represented 359 in the attached community, with a stable abundance over time. Acidiphilium was present in 360 both bioreactors, for most of the monitoring period, but was more represented in the attached 361 community than in the suspended community. Metallibacterium was present in relatively low 362 proportions in both systems, and RNA-based analysis showed that this genus was probably 363 not metabolically active. 364 365 Indicator Species Analysis supported our previous observations about the bacterial genera 366 representative of a particular group; in the attached communities (biogenic precipitates) the 367 representative genera were Acidiphilium, Leptospirillum, Acidibacter, Acidicapsa for both 368 bioreactors, and Acidocella, Acidibrevibacterium and Granulicella for WP only. On the 369 contrary, Ferrovum and Sideroxydans were representative of the suspended community in 370 both bioreactors. Legionella and an undetermined genus of Acidobacteriaceae family were 371 representative of the suspended community only in the WP bioreactor. 372 373 Abundance and expression of 16S rRNA and aioA genes 374 Based on environmental DNA analysis, the 16S rRNA gene copy number varied between 10 2 375 and 10 6 copies mg -1 of biogenic precipitate and between 10 4 to 10 7 copies mL -1 of water in 376 both bioreactors (Figure 5.a and 5.b). The average bacterial biomass of the biogenic 377 precipitates community was similar in the two bioreactors (Figure 5.a). The average biomass 378 of suspended communities in water remained stable between the inlet and the outlet water of 379 the PS and WP bioreactors (Figure 5.b). The biomass varied over time without any clear trend 380 (Figure SI 3).381382 Results based on cDNA showed between 10 3 to 10 6 16S rRNA transcripts mg -1 of biogenic 383 precipitate and between 10 3 to 10 5 16S rRNA transcripts mL -1 of outlet water, without 384 difference between the two bioreactors (Figure5.a and 5.b). DNA analysis, the number of aioA genes in both bioreactors varied between 10 1 and 387 10 5 copies mg -1 of biogenic precipitate and between 10 2 and 10 6 copies mL -1 of water(Fig 5.c 388 and 5.d). The number of genes and the number of transcripts of the arsenite oxidase were 389 similar in both bioreactors (Figure5.c and 5.d), except for the attached community of WP in 390 which aioA transcripts remained below the detection limit (Figure5.c). The expression of the 391 arsenite oxidase gene was evidenced (by detection of aioA transcripts) in 14 of a total of 60 392 samples, and showed up to 150 transcripts mL -1 of water in the WP bioreactor during period E 393 and up to 421 transcripts copies mg -1 of biogenic precipitate in the PS bioreactor in period C 394 (FigureSI3). In the other samples, recovery of aioA transcripts was below the detection limit.395 The results suggest that the As(III)-oxidizing activity might be more expressed during period 396 E and C, compared to other periods. However, technical limitations associated with mRNA 397 extraction yield and cDNA synthesis could have interfered with the analysis.398 For DNA-based analyses, the relative abundance of bacteria carrying aioA gene in the 399 bacterial community and its dynamic in the bioreactors were assessed based on aioA/16S 400 rRNA genes ratio (Figure6). In the WP bioreactor, the suspended bacterial communities 401 sampled at period E was the most enriched in As(III)-oxidizing bacteria (0.6 copies of 402 aioA/16S rRNA ratio). On the contrary, in the PS bioreactor, the attached communities were 403 the most enriched in As(III)-oxidizing bacteria. The highest enrichment was observed for 404 periods C, D and E (average of 0.35 copies of aioA/16S rRNA ratio). 405 406 The relative abundance of aioA gene varied widely according to the period, the bioreactor and 407 the lifestyle, but without any clear trend. For instance, the average of the relative abundances 408 of arsenite oxidase gene was similar in the outlet waters of both bioreactors (0.09  0.15 409 copies of aioA/16S rRNA ratio) and the feed water (Carnoulès AMD) (0.07  0.02 copies of 410 aioA/16S rRNA ratio, data not shown). 411 412 Links between the bacterial communities and the physicochemical 413 characteristics of the AMD or the treatment performances.

448

  rate, As(V) % in the outlet, pH outlet) or the operating condition (HRT) (Figure420 7). 421 422 The relative abundance of sequences related to Ferrovum, Acidithiobacillus and 423 Acidobacteriaceae were positively correlated with dissolved As concentration, temperature 424 and Fe(II) concentration in the inlet water (correlation > 0.5). In a lesser extent, Thiomonas 425 also showed a positive correlation with those parameters. On the contrary, taxa Gallionella 426 and Gallionellaceae-undetermined genus showed a negative correlation with those parameters 427 (correlation -0.5). The relative abundance of As(III)-oxidizing bacteria (aioA/16S rRNA ratio) 428 was positively correlated with the temperature, the total dissolved As concentration and the 429 percentage of As(III) in the inlet water. The rates of Fe precipitation and As precipitation 430 were strongly positively correlated with the relative abundance of Ferrovum (correlation 0.6 431 and 0.7 respectively). The percentage of As(V) in the outlet water was positively correlated 432 with the relative abundance of the As(III)-oxidizing genus Thiomonas (correlation 0.6) and in 433 lesser extent with Acidobacteraceae-undetermined genus and Acidiphilium (correlation 0.5).434 On the contrary, this parameter was negatively correlated with Gallionella and 435 Gallionellaceae-undetermined genus (correlation -0.5). The pH of the outlet water was 436 positively correlated with the abundance of Gallionella and Gallionellaceae-undetermined 437 genus (correlation 0.5) and negatively correlated with Ferrovum (correlation -0.7). 438 439 The relative abundance of the As(III)-oxidizing bacteria (aioA/16S rRNA genes ratio) was 440 strongly positively correlated with Thiomonas (correlation 0.8). Two HRT were applied in 441 both bioreactors (~9h and ~18h). There was a positive correlation between the relative 442 abundance of Acidibrevibacterium, Acidiphilium and Acidobacteriaceae relative sequences 443 and HRT. However, no significant correlation between the FeOB and the HRT Characterization of the total and active bacterial communities 449 Total and active bacterial communities were dominated by Fe-oxidizing bacteria (FeOB) 450 (Leptospirillum, Ferrovum, Acidiothiobacillus, an undetermined genus of Gallionellaceae,

503504

  Bioprecipitates were sampled from the surface of the plastic carriers or from the wood ships 505 (no sampling on pozzolana due to the difficult access to the pozzolana at the bottom of the 506 tank). During the early-stage of the monitoring, bacterial community developed on the PS 507 biomass carrier was dominated by chemoautotrophs (i.e. Galionellla and Leptospirillum), 508 while the one associated with WP carrier was composed by both chemoauthotrophs (i.e. 509 Leptospirillum, Acidiphillum) and chemoheterotrophs (i.e Acidobacteriaceae, Acidocella, 510 Acidiphillum, Acidicapsa, Acidibacter and Acidibrevibacterium).

605606

  Arsenic oxidation led to the enrichment into As(V) in the biogenic precipitates(80 ± 11 %) 607 and in the outlet water (41 ± 26 %, compared with 25 ± 5 % in the inlet water) (Diaz-Vanegas 608 et al., 2022). Because of the higher affinity of As(V) for iron minerals[START_REF] Paikaray | Arsenic geochemistry of acid mine drainage[END_REF], As 609 removal under its oxidized form is more efficient and stable. affected environments, bacterial diversity is under the control of geochemical and 614 environmental parameters[START_REF] Méndez-García | Microbial stratification in low pH 908 oxic and suboxic macroscopic growths along an acid mine drainage[END_REF][START_REF] Paikaray | Arsenic geochemistry of acid mine drainage[END_REF][START_REF] Volant | Diversity and spatiotemporal 990 dynamics of bacterial communities[END_REF]. As 615 supported by Spearman correlations, pH, dissolved Fe(II) and As concentrations as well as 616 water temperature were drivers determining the dynamic of FeOB and As(III) oxidizers the bioreactors. pH has a strong direct and indirect influence on AMD 618 microbial communities due to its relationships with geochemical variables such as minerals 619 solubility. In particular, pH controls dissolved As and Fe concentrations in the AMD(Jones et 620 al., 2015;[START_REF] Méndez-García | Microbial 911 diversity and metabolic networks in acid mine drainage habitats[END_REF]. 621 622 In the present study, Gallionella and Gallionellaceae-related sequences showed a positive 623 correlation with pH of both inlet and outlet waters. The decrease of their relative abundance in 624 the PS bioreactor coincided with the decrease of the pH. From period D, the bacterial 625 communities inside the bioreactors were enriched with Ferrovum, known for its capacity to

  that influence bacterial diversity in the bioreactors were dissolved As 652 concentration and water temperature, as reported by[START_REF] Laroche | Dynamics of bacterial communities mediating the treatment 874 of an As-rich acid mine drainage in a field pilot[END_REF] andTardy et al., 653 (2018). As discussed previously, the present study supports the positive influence of 654 temperature on the raise of the relative abundance of Thiomonas / arsenite-oxidizing bacterial 655 populations. In contrast, Gallionella and Gallionellaceae-related sequences were negatively 656 correlated with As concentration and temperature of the inlet water, as observed byFleming 657 et al., (2014). The positive correlations between Ferrovum abundance and temperature and 658 arsenic concentration in the inlet water (Figure7), have not been described before. They 659 revealed the adaptation of Ferrovum to high As concentrations, which makes it a good 660 candidate for the bioremediation of highly As-rich effluents. On the contrary, the negative 661 correlation of Gallionella and Gallionellaceae-related sequences with As concentration, 662 suggest their possible poor adaptability for the treatment of As rich AMD. analysis of performance indicators (As and Fe precipitation rates and Fe(II) 667 oxidation kinetic constant KOFe) and microbiological variables provides new insights about 668 the relationships between total and active bacterial diversity and treatment efficiency during 669 periods of optimal operation (B-E). The abundance of total and active Leptospirillum and 670 Ferrovum were positively correlated with performance indicators. Both genera are well 671 known for their highly efficient Fe-oxidation activity (Chen

  the uncoupling between the resilience in function and the resilience in bacterial 684 diversity described by Mills et al., bioreactors, FeOB were controlled by pH, dissolved Fe and As concentrations and 689 temperature. The over-representation of Ferrovum in the active community, together with the 690 positive correlation between its abundance and the highest treatment performances, confirmed 691 its central role in the treatment efficiency. Furthermore, based on the positive correlation 692 between its relative abundance and dissolved arsenic concentration, Ferrovum appeared 693 particularly well adapted for the treatment of As rich effluents. Leptospirillum was another

1 Figure 1 .

 11 Evolution of the bioreactor performances (represented by KOFe and As precipitation rate).

7 8Figure 2 .Figure 3 .Figure 4 .

 7234 Diversity indices for the total bacterial communities developed in PS and WP bioreactors; 9 alpha diversity: Chao1 and Shannon (a), beta diversity (Bray-Curtis) (b). ("****" =p-value < 0.0001, 10 "***" p-value <0.001). These analyses include total and active communities. 11 12 NMDS with the main taxa (genus level) explaining the communities' differences (p-value < 13 0.05). When genus identification was not possible, classification was made at the family or at the order 14 level. The symbols represent the structure of the bacterial communities of each sample. The shape of 15 the symbol represents the lifestyle (suspended or attached) and the status of the community (total 16 community based on DNA analysis or active community based on RNA analysis). The colors 17 represent the periods of monitoring (B, C, D, E, F and G). The two ellipses differentiate the samples 18 from each bioreactor (dashed line for the WP samples and solid line for the PS samples)Evolution of the relative abundances of the main bacterial at genus level (relative abundance 22 > 0.05 % of total number of sequences) over the monitoring periods. The results are presented for the 23 PS (plastic biomass carrier) and WP (wood and pozzolana as biomass carrier) bioreactors according to 24 the different lifestyle (attached versus suspended) and to the status of the communities (total or active). 25 When genus identification was not possible, classification was made at the family level ( * ) or at the 26 order level ( * * ).

Figure 5 .

 5 Figure5. Abundance of genes and transcripts in the biogenic precipitates and in the water collected at the inlet and at the outel of the two bioreactors (average of all the periods). 16S rRNA genes and transcripts in the attached community (a), and in the suspended community (b), aioA genes and transcripts in the attached community (c) and in the suspended community (d). Analyses were performed on DNA (presence of the genetic potential) and cDNA (gene expression). Values annotated with the same letter are not significantly different (Tukey's multiple range test with p = 0.05). The quantification of the aioA transcripts from cDNA in the WP biogenic precipitates was below the detection limit.

Figure 6 .

 6 Figure 6. aioA / 16S rRNA genes ratio in the suspended (outlet water) and attached communities (biogenic precipitates) in the two bioreactors (based on DNA analyses only). Data are mean values (n= 3). *** the three asterisks correspond to period F (bioreactor PS and WP) and period G (only bioreactor PS), for which data are missing due to technical limitations.

Figure 7 .(Figure 1 .Figure 2 .Figure 3 .Figure 4 .Figure 5 .Figure 6 Figure 7 .

 71234567 Figure 7. Heat map of the Spearman correlation coefficients between relative abundance of the most dominant taxa (vertical axis) and physicochemical parameters of the inlet water, operational parameters or performances indicators (represented in the horizontal axis). All the parameters used are presented in Error! Reference source not found., supplementary TableS1 and S2; for the performance indicators only the periods with optimal performances B-E were considered. Correlation analyses were performed with the sum of the sequences data from the total and active communities (based on DNA and RNA analyses). The last group corresponds to the relative abundance of the As(III)-oxidizing bacteria (correlation performed only with the abundance of the total communities (based on DNA analyses). When genus identification was not possible, classification was made at the family level ( * ) or at the order level ( * * ).

  Figure7. Heat map of the Spearman correlation coefficients between relative abundance of the most dominant taxa (vertical axis) and physicochemical parameters of the inlet water, operational parameters or performances indicators (represented in the horizontal axis). All the parameters used are presented in Table1, supplementary TableS1 and S2; for the performance indicators only the periods with optimal performances B-E were considered. Correlation analyses were performed with the sum of the sequences data from the total and active communities (based on DNA and RNA analyses). The last group corresponds to the relative abundance of the As(III)-oxidizing bacteria (correlation performed only with the abundance of the total communities (based on DNA analyses). When genus identification was not possible, classification was made at the family level ( * ) or at the order level ( * * ).250x117mm (150 x 150 DPI)

Figure SI 1 .

 1 Figure SI 1. Indices of alpha (a) and beta (b) diversity obtained from the different types of samples (biogenic precipitates and water). ("****" =p-value < 0.0001, "***" p-value < 0.001, "**"= p-value < 0.01, "*"= p-value < 0.05). These analyses include total and active.

Figure SI 2 .

 2 Figure SI 2. Indices of alpha (a) and beta (b) diversity obtained from the DNA and RNA extracts.("****" =p-value < 0.0001, "ns" = p-value > 0.05).

Figure SI 3 .

 3 Figure SI 3. Number of copies of 16S rRNA gene (a) and aioA gene (b) in biogenic precipitates. Number of copies of 16S rRNA gene (c) and aioA gene (d) in water.

of the bacterial community structures in the PS and WP bioreactors

  Table SI 2).225 to keep only non-chimeric OTUs, OTUs with an expected error per nucleotide below 0.0002, 226 OTUs containing more than three reads or seen in at least two samples. The raw data are 227 available under the bioproject (https://www.ebi.ac.uk/ena/data/view/PRJEB63466).

	289 p-value <0.0001) (Figure 2.b). Also, the suspended community showed higher beta diversity 322 Acidibrevibacterium, Granulicella and Tepidsphareales-related sequences were
	290 than the attached communities (Figure SI 1.b; Mann-Whitney; p-value <0.0001). Finally, the 323 representative of samples collected in the WP bioreactor particularly during the first periods B
	291 total bacterial community presented higher beta diversity than the active one (Figure SI 2.b; 324 and C. Acidithiobacillus was representative of samples collected in the PS bioreactor at the
	228 292 Mann-Whitney; p-value <0.0001). 325 end of the monitoring (periods F and G). Thiomonas was representative of the total and the
	229 The OTU table was processed with R 3.5.2 (R Core Team, 2018) for additional filtering steps 293 326 metabolically active bacterial communities in both bioreactors particularly during period E.
	230 and statistical analysis with the packages tidyverse 1.3.0 (Wickham 2017) and vegan 2.5.6 231 (Oksanen et al., 2018). These steps include removing the controls and the samples with less 232 than 1000 reads, and the rarefaction of the remaining samples. 294 327 Dynamic 295 The dynamic of the bacterial communities developed in both bioreactors was represented by 328 Taxonomic
	296 non-metric multidimensional scaling (NMDS) (Figure 3). In complement, an ANOSIM test
	233 297 was used to determine significant differences in the bacterial community composition of aioA and 16S rRNA genes and transcripts quantification
	234 Abundance of the aioA gene (encoding the catalytic subunit of the arsenite oxidase) and of the 298 groups of samples. Groups were defined according to the sampling period, the nature of the
	F F 235 bacterial 16S rRNA genes and their transcripts were quantified by a real-time quantitative F F 299 biomass carrier, the lifestyle (attached versus suspended communities) and the metabolic F
	o r o r 236 PCR (qPCR) from the DNA extracts and from the cDNA, respectively. For 16S, we used 237 universal primers 341F (5'CCTACGGGAGGCAGCAG-3') and 515R o r o r 300 status (total versus active communities). The most important differences were observed 301 between the different periods of monitoring (represented by the different colors in the NMDS) o r
	P P 238 (5'ATTACCGCGGCTGCTGGCA-3'). P P 302 (ANOSIM test, R 0.4463, p-value = 0.001). There were marked variations in the bacterial For aioA, we used primers m4-1F P
	e e r e e r e e r e e r 303 community structure particularly between the first periods of monitoring (B and C), and the 304 next ones (D, E, F and G). These variations were more pronounced for the PS bioreactor than 305 for the WP, reflected by the wider ellipse shown in Figure 3, and in agreement with the higher e e r
	R e v R e v R e v R e v 308 The influence of both lifestyle and biomass carrier was moderate compared to the temporal 306 beta diversity measured in PS (Figure 2.b). 307 R e v
	i e w i e w i e w i e w 309 dynamic (ANOSIM test, R 0.4463, p-value = 0.001). The lifestyle (suspended or attached in 247 310 the biogenic precipitates) was the second criteria driving the bacterial communities (ANOSIM 311 test, R 0.1935, p-value = 0.001) and the third criteria was the biomass carrier (plastic or i e w
	248 312 wood/pozzolana) (ANOSIM test, R 0.1535, p-value = 0.001). Finally, active communities Biostatistical analysis
	313 were relatively distinct from the total ones during the first stage of the monitoring (period B
	249 All statistical analyses were performed with R version 3. Chao1 and Shannon indices were 314 and C). During the other periods, the structure of the active and the total communities
	185 Reverse transcription was immediately performed on DNA-free RNA extracts using the 250 calculated using the vegan and ggplot2 packages for biological diversity statistics in R 315 appeared more similar. Overall, the status (total versus metabolically active) of the bacterial
	186 iScript™ cDNA Synthesis Kit (Biorad). 251 (Wickham 2017; Oksanen et al., 2018). Bray Curtis was used as diversity metric to compare 316 communities was the factor explaining the less the differences between the samples
	187 The quality of the cDNA was confirmed by performing a PCR targeting 16S rRNA gene 252 the bacterial communities from each bioreactor (R packages phyloseq and dplyr (McMurdie 317 (ANOSIM test, R 0.05191, p-value = 0.002).
	188 using 8F and 1489R primers or aioA gene using aoxBM1-2F (5-253 and Holmes 2013; Wickham et al., 2022). 318
	189 CCACTTCTGCATCGTGGGNTGGGNT 254 The analysis of similarity (ANOSYM, 999 permutations) was performed to compare the A-3) and aoxBM3-2R (5-319 Indicators species analysis revealed the bacterial taxa that contributed the most to the shifts in
	255 statistical differences between pre-defined groups. It allowed us to compare the results 320 the bacterial communities. For instance, Gallionella and Gallionellaceae-related sequences
	256 obtained for the structure of the bacterial communities based on the following criteria: 321 dominated the PS bioreactor during periods B and C. Acidicapsa, Acidiphium, Acidibacter,
	8 10 11

168

169 The performance indicators used for the correlations include the KOFe (min -1 ), Fe 170 precipitation rate (mol L -1 s -1 ), As precipitation rate (mol L -1 s -1 ) and percentage of As(V) 171 released in the outlet water (As(V)% outlet). 172 173 Environmental DNA and RNA extraction and cDNA synthesis 174 The molecular characterization of the total and active bacterial communities was based on the 175 analyses of environmental DNA and RNA (cDNA) respectively. For each bioreactor, DNA 176 was extracted from biogenic precipitates and water filters using DNeasy PowerSoil kit and 177 DNeasy PowerWater kit (Qiagen) respectively, according to the manufacturer's 178 recommendations. The RNA extractions were performed from biogenic precipitates and outlet 179 water filters using FastRNA Pro Soil-Direct kit (MP Biomedicals) and RNeasy Power Water 180 Kit (Qiagen) respectively, according to the manufacturer's recommendations. Residual DNA 181 was removed from the extracted RNA with an additional Turbo DNase treatment (Turbo 182 DNA-free kit, Ambion). The absence of DNA was confirmed by the absence of amplification, 183 from RNA extracts, of 16S rRNA gene with 8F (5′-AGAGTTTGATCCTGGCTCAG-3′, Lane 184 1991) and 1489R (5′-TACCTTGT TACGACTTCA-3′, Weisburg et al., 1991) primers. 190 TGTCGTTGCCCCAGATGADNCCYTTYT-3) primers (degenerate primers designed to 191 target mutliple bacterial and archaeal taxa, Quéméneur et al., 2008). DNA and RNA extracts 239 (5'GCCGGCGGGGGNTWYGARRAYA-3') and m2-1R (5'GGAGTTGTAGGCGGGCCK 240 RTTRTGDAT-3) (degenerate primers designed to target multiple bacterial and archaeal taxa, 241 Quéméneur 2008). The qPCR was performed with the CFX Real-Time PCR Detection system 242 (Bio-Rad), using SSO Advanced SYBR® Green Supermix and each primer at 0.4 µM (16S

243 rRNA gene) or 0.3 µM (aioA gene). Calculation of copy numbers was done using a linear 244 calibration curve (r 2 > 0.9) obtained over 7 orders of magnitude, ranging from 10 2 to 10 8 gene 245 copies of a linearized plasmid carrying the target gene (gene copies/mL of water or mg of 246 biogenic precipitates).

composition of the bacterial communities thriving in the two

	329	bioreactors
	330 The most abundant phyla identified in the outlet waters and the biogenic precipitates sampled
	331 in both bioreactors were Proteobacteria (62%) and Nitrospirota (35%). Acidobacteria was
	332 the third more abundant phylum, representing only 1% of the total number of sequences. On
	333 the whole data set, the dominant genera were the iron-oxidizing (FeOB) bacteria
	334 Leptospirillum, Ferrovum, Acidithiobacillus and an undetermined genus of the

335 Gallionellaceae family. Leptospirillum was abundant and active from the beginning to the 336 end of the monitoring, mainly in the biogenic precipitates. Ferrovum was more abundant and 337 active in the suspended community (outlet water), particularly during the D period of the 338 monitoring.

  The highest abundances of aioA genes and aioA transcripts, observed during period E, were 585 concomitant with an increase of Thiomonas-related sequences. Period E was characterized by 586 an increase of temperature by more than 5℃, an increase of the total Fe concentration ( 100 587 mg L -1 ), and total As concentration ( 15 mg L -1 ) (Table1 and Diaz[START_REF] Diaz-Vanegas | Performance of semipassive systems for the biological 768 treatment of high -As acid mine drainage : Results from a year of monitoring at the 769 Carnoulès mine (Southern France)[END_REF]. 588 Similarly,[START_REF] Tardy | Temperature and nutrients as drivers of 981 microbially mediated arsenic oxidation and removal from acid mine drainage[END_REF] showed, in batch experiment, that high temperature stimulated 589 As(III) oxidation associated with an increase of both the abundance of aioA genes and of 590 Thiomonas spp.[START_REF] Quéméneur | Population structure and abundance of arsenite-oxidizing bacteria along an 940 arsenic pollution gradient in waters of the upper isle river basin, France[END_REF] found high aioA gene densities associated with high

	584 591 concentration of As in surface water.
	592
	593 As(III)-oxidizing bacteria distribution was different in the two bioreactors: they were more
	o r F o r 594 represented in the attached community in the PS bioreactor, and in the suspended one in the F 595 WP bioreactor. In opposition to the common idea that the formation of a carrier-attached o r 596 biofilm enhances bacterial activity,
	P P P
	e e r e e r e e r
	R e v R e v R e v
	i e w i e w i e w
	19

  Li JT, Chen YT, Huang L, Hua Z, Hu M, Shu W (2013) Shifts in microbial 759 community composition and function in the acidification of a lead/zinc mine tailings.

	F F F 2229.2010.00179.x. 828 Hedrich S, Johnson DB (2012) A modular continuous flow reactor system for the selective 826 827 860 abandoned underground copper mine. Life 3:189-210. 962 https://doi.org/10.1016/j.scitotenv.2020.137211 963 Rognes T, Flouri T, Nichols B, Quince C, Mahé F (2016) VSEARCH: a versatile open source 964 tool for metagenomics. PeerJ 18;4:e2584. doi: 10.7717/peerj.2584. 965 Sheng Y, Bibby K, Grettenberger C, Kaley B, Macalady J, Wang G, Burgos W (2016) 996 immobilized Acidithiobacillus ferrooxidans and its relevance to acid mine drainage. 997 Hydrometallurgy 125-126:152-156. https://doi.org/10.1016/j.hydromet.2012.06.003 998 Weisburg WG, Barns SM, Pelletier DA, Lane DJ (1991) 16S ribosomal DNA amplification 999 for phylogenetic study. J Bacteriol. 173(2):697-703. doi: 10.1128/jb.173.2.697-703.1991. 1000 Wickham H (2017). tidyverse: Easily Install and Load the 'Tidyverse'. R package version 1001 1.2.1. https://CRAN.R-project.org/package=tidyverse 1002 Wickham H, François R, Henry L, Müller K (2022) dplyr: A Grammar of Data Manipulation, 1003 R package version 1,0,9, https://CRAN,R-project,org/package=dplyr 1004 Zhao Y, Liu D, Huang W, Yang Y, Ji M, Duc Nghiem L, Thang QT, Tran NH (2019) Insights 1005 into biofilm carriers for biological wastewater treatment processes: Current state-of-the-758 Chen LX, F F F F F F F 1006 art, challenges, and opportunities. Bioresour Technol 288:121619.
	o r o r o r o r o r o r o r o r o r o r
	P P P P P P P P P P
	e e r e e r e e r e e r e e r e e r e e r e e r e e r e e r
	R e v R e v R e v R e v R e v R e v R e v R e v R e v R e v
	i e w i e w i e w i e w i e w i e w i e w i e w i e w i e w
	708 Readiness Level 5. This technology, which did not use chemical reagent, could be
	709 competitive with lime treatment, provided that additional treatment step such as sulfate-
	710 reducing bioreactor is used to meet discharge standards.
	711
	712
	713
	714
	25 27 28 30 31 32

Table 1

 1 Inlet and outlet water main characteristics (DO was measured inside the bioreactor)

	HRT (h)	TOC (mg L -1 )	DO (mg L -1 )**

Table SI 1

 SI . Chemical characterization of inlet and outlet waters for the sampling dates where microbioligical analyses were performed

Table SI 2

 SI . Performance indicators for the sampling dates where microbiological analyses were performed

						FEMS Microbiology Ecology			Page 46 of 93
	Date (d.m.y)	Period	Total As (wt%)	Total Fe (wt%)	As/Fe (mol mol-1 )*	%As V (wt%)
			PS	WP	PS	WP	PS	WP	PS	WP
	19.12.19	B	10.7	4.9	37	22	0.39	0.30	81	88
	06.02.20	C	NA	NA	NA	NA	NA	NA	NA	NA
	12.03.20	D	9.1	5.7	36	28	0.34	0.27	69	53
	18.06.20	E	8.6	8.3	36	32	0.32	0.35	77	78
	27.07.20	F	8.3	5.0	31	25	0.36	0.26	83	83
	15.09.20	G	12.2	8.4	33	25	0.49	0.45	92	94
	*Molar ratio
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