J Masbou

Jérôme Viers

Jose Antonio Grande

R Freydier

Cyril Zouiten

Patrick Seyler

O S S Pokrovsky

Philippe Behra

Brigitte Dubreuil

M L De

R Zouiten

La Torre

Ph.D Jerôme Viers

Strong temporal and spatial variation of dissolved Cu isotope composition in acid mine drainage under contrasted hydrological conditions

Keywords: copper, isotopes, Acid Mine Drainage (AMD), river, flood

de niveau recherche, publiés ou non, émanant des établissements d'enseignement et de recherche français ou étrangers, des laboratoires publics ou privés.

Introduction

The Iberian Pyrite Belt (South-west Spain), which is among the largest metallogenic provinces in the world, presents serious problems of Acid Mine Drainage (AMD) [START_REF] Almodovar | Geology of the Riotinto Ore Deposits, Geology and VMS deposits of the Iberian Pyrite Belt[END_REF][START_REF] Leblanc | 4,500-year-old mining pollution in southwestern Spain: long-term implications for modern mining pollution[END_REF][START_REF] Grande | Overall hydrochemical characterization of the Iberian Pyrite Belt. Main acid mine drainage-generating sources (Huelva, Spain)[END_REF][START_REF] Grande | Characterisation of AMD pollution in the reservoirs of the Iberian Pyrite Belt[END_REF][START_REF] Olias | Causes and impacts of a mine water spill from an acidic pit lake (Iberian Pyrite Belt)[END_REF] due to the intense mining activity that occurred during different periods ofhistory including the present time. In particular, during the most active period, from the mid-XIX th to the XX th centuries, large amounts of abandoned waste have been left over the whole region [START_REF] Pérez Ostalé | Caracterización ambiental de estructuras mineras en la Faja Pirítica Ibérica como soporte metodológico de gestión territorial[END_REF].

Induced AMD phenomenon leads to surface waters with low pH, and a high metal and sulphate load that strongly affect both inland and marine ecosystems since the two largest AMD affected watersheds of the region, the Odiel and Tinto Rivers, deliver their waters to the estuary of Huelva [START_REF] Achterberg | Metal behaviour in an estuary polluted by acid mine drainage: the role of particulate matter[END_REF][START_REF] Sainz | Characterisation of heavy metal discharge into the Ria of Huelva[END_REF][START_REF] Nieto | Acid mine drainage pollution in the Tinto and Odiel rivers (Iberian Pyrite Belt, SW Spain) and bioavailability of the transported metals to the Huelva Estuary[END_REF][START_REF] Grande | Map of impact by acid mine drainage in the river network of The Iberian Pyrite Belt (Sw Spain)[END_REF]. Due to scarcity of water in this region of the South-West of Europe, the AMD can strongly impact the aquatic ecosystems and surface and groundwater quality (see www.fao.org). Despite the numerous studies dealing with the AMD processes origins and consequences on waters, soils and biota (e.g., [START_REF] Elbaz-Poulichet | Metal biogeochemistry in the Tinto-Odiel Rivers (Southern Spain) and in the Gulf of Cadiz: a synthesis of the results of TOROS project[END_REF] the metal distribution, reactivity and transport mechanisms in the rivers still remain poorly known.

In addition to dissolved and particulate metals concentrations monitoring in surface waters, the stable isotopes of metals (Cu, Fe, Zn…) are now routinely used to trace the source of metals in the environment and to reveal the biotic and abiotic mechanisms controlling elements transfer within a watershed (see [START_REF] Teng | Non-traditional stable isotopes: retrospective and prospective[END_REF] for a review). As most of the mines in the Iberian Pyrite Belt were mined for copper (Saez et al., 1999), we looked at the potential contribution of copper isotopes to better understand this metal behaviour in such areas. A number of works addressed Cu isotopes in the AMD context [START_REF] Mathur | Cu isotopic fractionation in the supergene environment with and without bacteria[END_REF][START_REF] Balistrieri | Fractionation of Cu and Zn isotopes during adsorption onto amorphous Fe (III) oxyhydroxide: experimental mixing of acid rock drainage and ambient river water[END_REF][START_REF] Borrok | Isotopic variations of dissolved copper and zinc in stream waters affected by historical mining[END_REF][START_REF] Fernandez | Fractionation of Cu, Fe, and Zn isotopes during the oxidative weathering of sulfide-rich rocks[END_REF][START_REF] Kimball | Copper isotope fractionation in acid mine drainage[END_REF][START_REF] Mathur | Exploration potential of Cu isotope fractionation in porphyry copper deposits[END_REF]Pérez Rodríguez et al., 2013;[START_REF] Mathur | Tracing low-temperature aqueous metal migration in mineralized watersheds with Cu isotope fractionation[END_REF][START_REF] Song | Fingerprinting two metal contaminants in streams with Cu isotopes near the Dexing Mine[END_REF][START_REF] Dótor-Almazán | Geochemical behavior of Cu and sulfur isotopes in the tropical mining region of Taxco, Guerrero (southern Mexico)[END_REF][START_REF] Viers | Are Cu isotopes a useful tool to trace metal sources and processes in acid mine drainage (AMD) context?[END_REF][START_REF] Roebbert | Fractionation of Fe and Cu isotopes in acid mine tailings: Modification and application of s sequential extraction method[END_REF]. Carried out during steady hydrological conditions, these studies showed that sulfide mineral dissolution in oxygenic conditions essentially controls the Cu isotopes distribution in surface and ground waters. Extensive natural observations and experimental works evidenced strong enrichment in heavy Cu isotopes of aqueous solution interacting with primary sulfide minerals. Moreover, in contrast to relatively narrow range of isotopic signature (δ 65 Cu) in these primary minerals, the secondary mineral products exhibit a δ 65 Cu variability as high as from -17 to + 10 ‰, see [START_REF] Mathur | Exploration potential of Cu isotope fractionation in porphyry copper deposits[END_REF]. The speciation of Cu in sulfide mine environments is extremely complex because Cu is present in numerous secondary minerals whose proportions strongly depend on the hydrological regime (wetting and drying) [START_REF] Valente | Mineralogy and environmental relevance of AMD-precipitates from the Tharsis mines, Iberian Pyrite Belt (SW, Spain)[END_REF]. Moreover, the formation of these minerals in mine-impacted surface waters is controlled by key parameters such as pH, temperature, redox conditions, saturation state and biological activity [START_REF] Sanchez Espana | The natural attenuation of two acidic effluents in Tharsis and La Zarza-Perrunal mines (Iberian Pyrite Belt, Huelva, Spain)[END_REF], 2011;Sarmiento et al., 2009a,b). High sensitivity to fractionation of copper isotopes in supergene environments makes copper isotopes a good potential tracer for metal transfer within the continuum mine -river -lake encountered in the Iberian Pyrite Belt.

To better understand the environmental factors controlling Cu concentration and isotopes fractionation in AMD aquatic settings, our initial objective was to study the evolution of chemical and isotopic fractionation during a diel cycle (24h) in an AMD impacted river. Indeed, several parameters and processes that are often interrelated (T°, dissolved O2, water discharge, pH…) may influence the concentration of the chemical species during a diel cycle in the water [START_REF] Nimick | Diel biogeochemical processes and their effect on the aqueous chemistry of streams: A review[END_REF]. To address this issue within the AMD context, we used a representative scenario of strongly contaminated Meca River (Huelva, SW Spain) of the Iberian Pyrite Belt. This river drains the abandoned copper mine of Tharsis -one of the largest in the area -and delivers its waters to the Sancho Lake. Taking the advantage of an extremely strong rainy event that occurred during the sampling period, we primarily focused on studying the response of a mining system to variable hydrological stage. Further, in order to quantify the spatial variability of Cu isotope composition in the AMD-affected Meca River, we performed measurements in two points, one at the outlet of the mining district and one 20 km downstream, three hours each during 24 hours. We expected that by examining the variation of Cu isotopic composition in time and space, we can better understand the transfer and origin of Cu and other metals within the mining area and reveal the mechanisms of Cu isotopes fractionation in these environmentally important riverine systems.

Site description

Geology of the Iberian Pyrite Belt

The study area belongs to the Iberian Pyrite Belt (IPB), located in the south-west of the Iberian Peninsula.This IPB is approximately 240 km long and 50 km wide and is one of the largest stocks of massive sulfides of volcanogenic origin in the world. It includes more than 90 mines (Saez et al., 1999). Pyrite (FeS2) is the main ore mineral but one finds a procession of other metallic sulfides such as sphalerite (ZnS), galena (PbS), chalcopyrite (CuFeS2), arsenopyrite (FeAsS) and there is a large variety of other metal sulfides containing minor quantities of Cd, Sn, Ag, Au, Co, Hg. Today, the majority of these mines are abandoned even though some remain in operation. Details about the geology of this area can be found in [START_REF] Tornos | Formation of the Tharsis massive sulfide deposit, Iberian Pyrite Belt: geological, lithologeochemical, and stable isotope evidence for deposition in a brine pool[END_REF] and [START_REF] Conde | Análisis de elementos traza por la LA-ICPMS en pirita de los sulfuros masivos de Tharsis (FPI)[END_REF].

Hydroclimatic conditions

The study area, located in the Huelva province, has a Mediterranean climate, which can be classified as semi-arid. Annual precipitation is about 630 mm/year, being mostly concentrated in the wet season from October to May, and the average annual temperature is 17.1 ºC (http://www.aemet.es).

Our study took place in the watershed of the Meca River, a tributary of the Odiel River.

The Odiel River joins the Tinto River at the city of Huelva. The average water discharge of the Odiel River is around 10 m 3 .s -1 at Gibraleon, a town close to the river mouth (see ConfederacionHidrografica del Guadiana; https://www.chguadiana.es). The Odiel watershed with a surface of 2300 km 2 and a length of 140 km accounts for about 80% of the continental water reaching the estuary of Huelva [START_REF] Fernandez | Incidencia de procesos AMD en la hidroquimica de embalses afectados en la faja piritica ibérica[END_REF]. The whole river network is impacted by acid mine drainage [START_REF] Grande | Map of impact by acid mine drainage in the river network of The Iberian Pyrite Belt (Sw Spain)[END_REF]. This is especially correct for the Meca River due to the presence of the Tharsis mine, in the upstream part of its catchment. Although it is now abandoned, Tharsis is one of the largest mining districts with almost 100 Mt of estimated resources [START_REF] Conde | Análisis de elementos traza por la LA-ICPMS en pirita de los sulfuros masivos de Tharsis (FPI)[END_REF]. Further details of the Tharsis mine can be found in Perez Ostale (2014) and [START_REF] Valente | Mineralogy and environmental relevance of AMD-precipitates from the Tharsis mines, Iberian Pyrite Belt (SW, Spain)[END_REF].

The weather was particularly rainy during the field sampling (11 to 12-May-2016). It rained 58 mm the preceding three days (8 to 10-May-2016) to our sampling (Alosno station) and 24 mm on the 11-May-2016. Unfortunately, we do not have the whole dataset for rain water because the weather station was destroyed during this storm event; As the Meca River water discharge is not monitored continuously, we performed a measurement of the water discharge using the "bucket method" when it was possible. Using previous work done by [START_REF] Galvan | Aplication of the SWAT model to an AMD-affected River (Meca River, SW Spain). Estimation of transported pollutant load[END_REF] within the Meca River catchment, sulphate concentrations could be used in the first order to account for the relative variation in water discharge. Indeed, these authors proposed the following relation between sulphate concentration (SO4) and water discharge (Q) : ([SO4] = 362.1*Q -0.30 ).No relation was proposed by these authors between Cu concentration and Q due to the lack of reproducibility.

Materials and methods

Sampling protocol

Sampling strategy aimed to study the geochemical processes along the Meca River during a complete diel cycle (24 h). Geographical gradient was investigated by collecting water samples simultaneously by two different teams in two sampling sites (Fig. 1): i) the Tharsis Mine outlet located upstream of the watershed called 'upstream' and ii) a point located 20 km downstream (called 'downstream'). Sampling was achieved in a similar timeframe of 24h for the two sites, between 11-May-2016 4:00 p.m. and 12-May-2016 5:00 p.m. with a time step of 3 hours. In addition, one sample of the main Meca tributary (between the two points) was also collected (Tributary stream, Fig. 1). In addition to water samples, a bedload sediment sample from the Meca River was collected at the upstream point.

At each sampling point, the values of pH, dissolved O2, temperature, and specific conductivity were measured in-situ using a portable multi-parameter instrument (WTW®,340i). Protocols for the measurement of these parameters and the sampling method are reported in [START_REF] Viers | Are Cu isotopes a useful tool to trace metal sources and processes in acid mine drainage (AMD) context?[END_REF]. Among the collected samples, the 0.22 µm membrane of four selected samples were conserved to recover suspended sediments and perform chemical analyses. In addition to 0.22 μm filtration, an ultrafiltration at 1,000 Da were carried out on four selected samples collected upstream (11-May-2016 4:00 p.m., 11-May-2016 10:00 p.m., 12-May-2016 4:00 a.m., 12-May-2016 10:00 a.m.) using a 50 mL Amicon ® ultrafiltration cell. Details of ultrafiltration procedure, analyses of possible artifacts and yields are given elsewhere [START_REF] Viers | Chemical weathering in the drainage basin of a tropical watershed (Nsimi-Zoétélé site, Cameroon): comparison between organic-poor and organic rich waters[END_REF][START_REF] Dupré | Major and trace elements associated with colloids in organic-rich river waters: Ultrafiltration of natural and spiked solutions[END_REF][START_REF] Vasyukova | Trace elements in organic-and iron-rich surficial fluids of the boreal zone : Assessong colloidal forms via dialysis and ultrafiltration[END_REF].

Mineralogical characterization

Two suspended sediments collected at the upstream point (ME-A 11-May-2016 10 p.m. and ME-A 12-May-2016 4 p.m. samples) were characterised by SEM-EDX (form, chemical composition) at the Centre de MicroCaractérisationRaimondCastaing (Toulouse) and by X-Ray Diffraction at the GET laboratory (Toulouse). All the details about the methods are reported in [START_REF] Blondet | Atmospheric dust characterisation in the mining district of Cartagena-La Unión, Spain: Air quality and health risks assessment[END_REF] and [START_REF] Blotevogel | The fate of Cu pesticides in vineyard soils: A case study using δ 65 Cu isotope ratios and EPR analysis[END_REF].

The Raman spectra of the ME-A 11-May-2016 10 p.m. sample was obtained at room temperature by the confocal microscope Raman spectrometer (Horiba Scientific Labram HR evolution spectrometer) equipped with charge coupled device (CCD) as detector at the LCA laboratory of the Ensiacet (INPT). We used the 532 nm laser as excitation source and a dry objective MPLN x100 (NA: 0.90 µm). Measurement conditions were: laser power of 2.5 mW during 1 second and 2 accumulations; pinhole: 100 µm; spectral range: 100 to 2400 cm -1 scanned with a high-resolution grating with 1800 gr/mm; Raman spectra: recorded directly from powder. Raman spectral libraries from Bio-Rad and KnowltAll® ID ExpertTM spectroscopy software were used for the identification.

Elemental content determination (major and Trace Elements (TE))

Major and trace element concentrations were measured using ICP-MS (iCAP Q, Thermo Scientific-Kinetic Energy Discrimination mode using He) at the AETE-ISO platform (OSU OREME/Université de Montpellier). Concentrations were determined with external calibration using (Be, Sc, Ge, Rh, Ir) as internal standards to correct potential sensitivity drifts. The quality of the analysis was checked by analyzing international certified reference waters (CNRC SLRS-6). The accuracy was better than 5% relative to the certified values and the analytical error (relative standard deviation) was better than 5% for concentrations ten times higher than the detection limits. Anions concentrations were determined by ionic chromatography at the GET laboratory.

In addition to total measurements, Fe speciation (Fe 2+ and Fe 3+ ) was determined by spectrophotometry and on-site using ferrozine method [START_REF] Viollier | The ferrozine method revisited : Fe(II)/Fe(III) determination in natural waters[END_REF]. These measurements were performed on the dissolved fraction (<0.22 µm) immediately after sampling for the upstream samples.

Before analysis, sediments were digested at the GET laboratory. For each sample, 100 mg of sediment were precisely weighed in Teflon vessels. 1 mL of H2O2 and 0.5 mL of bidistilled HNO3 were added to the samples and left at room temperature for 24 hours. Then, 1 mL of HNO3 is added and the solutions were warmed at 80°C for 24 h. The solution is then evaporated on a plate at 80°C. 1.2 ml of HF and 1.2 ml of bidistilled HNO3 are then added for a new warming step at 80°C. After evaporation, 20 drops of bidistilled HCL and 10 drops of bidistilled HNO3 are added. The acid solution was warmed at 115°C for 24 h and finally evaporated at 80°C. After complete evaporation, the remaining solid residue for each sample was dissolved in 10 mL of a 10% HNO3 solution. Acid blanks and certified reference material samples (LKSD-03, lake sediment samples) were also used to ensure the quality of the measures and their traceability.

Cu isotopes determination

Water sample aliquots containing approximately 1000 ng of Cu were purified using anion exchange chromatography on AG-MP1 resin (BIORAD) following an adapted protocol from [START_REF] Borrok | Isotopic variations of dissolved copper and zinc in stream waters affected by historical mining[END_REF]. The protocol was repeated twice in order to ensure a complete separation of Cu from the matrix. The total procedure blank was negligible in comparison with the amount of Cu in the samples (<1%). Column yields and remaining elements such as (Na, Mg, Ca, Ti, Cr) that can interfere with Cu and Zn isotopes [START_REF] Petit | Development of Cu and Zn Isotope MC-ICP-MS Measurements: Application to Suspended Particulate Matter and Sediments from the Scheldt Estuary[END_REF] were checked for each samples using Q-ICP-MS iCAP Q (Thermo Scientific). The yield was 100 ± 5% and no interfering elements were found in the solutions. Cu isotopic analyses were performed on a multiple-collector inductively coupled plasma mass spectrometer (MC-ICP-MS) Neptune Plus (Thermo Scientific®), using SIS (Stable introduction System) nebulization chamber and PFA self-aspiration nebulizer (50 µl.min -1 , Elemental Scientific®) at Plateforme AETE-ISO (OSU OREME-Université de Montpellier, France). Each sample was analyzed three times and was bracketed with the SRM NIST 976 copper solution. Cu isotopes ( 63 Cu, 65 Cu), Zn isotopes ( 64 Zn, 66 Zn, 67 Zn, 68 Zn), and Ni isotope ( 62 Ni) were monitored simultaneously.

Measurements of 62 Ni signal allowed correcting the possible isobaric interference of 64 Ni on 64 Zn. A Zn solution JMC 3e0749-L from Lyon was added to the samples in order to correct instrumental mass bias using the 66 Zn/ 64 Zn ratio (exponential law) and the method of samplestandard bracketing was used to determine the δ 65 Cu [START_REF] Marechal | Precise analysis of copper and zinc isotopic compositions by plasma-source mass spectrometry[END_REF]. The 2σ variation obtained on the 3 independent δ 65 Cu measurements was 0.01-0.06 ‰.

δ 65 Cu (in units of ‰) is the Cu isotopic deviation relative to a standard, the SRM NIST-976:

=

-1 × 1000

Thermodynamic calculations

Thermodynamic analysis including calculations of the speciation and the saturation indexes have been performed for the Meca River (upstream and downstream points) with respect to the common minerals of mining environments and specifically those described for the Tharsis mine by previous studies [START_REF] Sanchez Espana | The natural attenuation of two acidic effluents in Tharsis and La Zarza-Perrunal mines (Iberian Pyrite Belt, Huelva, Spain)[END_REF][START_REF] Valente | Mineralogy and environmental relevance of AMD-precipitates from the Tharsis mines, Iberian Pyrite Belt (SW, Spain)[END_REF].

Following these studies, we considered that goethite, ferrihydrite, jarosite, gibbsite, schwertmannite, (hydro)basaluminite, and gypsum may precipitate from aqueous solution.

Modelling calculations were done using Visual MINTEQ ver. 3.0. In the case of the minerals schwertmannite and hydrobasaluminitethe solubility product constants (log Ksp) were taken from Sanchez-Espana et al. ( 2011) and the calculations were done manually using the element activities given by Visual Minteq 3.0. It is visible that their value for schwertmannite (log Ksp = 18.8 ± 3.5; pH range = 2.6 -5.2) is very similar to that proposed by [START_REF] Bigham | Schwertmannite and the chemical modeling of iron in acid sulfate waters[END_REF] (log Ksp = 18.0 ± 2.5; pH range = 2.8 -3.2). The results of speciation and saturation indexes are reported in the supplementary information (Table S1 A and B).

Results

Variation of the water conductivity and pH in the Meca River

In the upstream point, conductivity varies from 2.8 to 11.4 mS/cm and pH varies between 2.43 and 2.82 (Table 1). At the downstream point, conductivity is much lower (from 0.31 to 0.54 mS/cm) and pH is higher with values ranging between 3.61 and 5.68. The Meca tributary exhibits intermediate values with a pH of 3.85 and a conductivity of 0.51 mS/cm.

Element concentrations in the river water are reported in Table 1. At the upstream point, the anionic load is dominated by SO4 2-(> 99%) and the cationic load is dominated by Fe (> 50%), Mg 2+ (> 20%), Al 3+ (> 15%), Zn 2+ and Ca 2+ (> 4%) and Cu 2+ (~1%). At the downstream point, the anionic load is dominated by SO4 2-(> 60%) and Cl -(> 30%) while the cationic load is dominated by Mg 2+ (> 35%), Na + (> 30%), Ca 2+ (> 20%), and Fe (> 6%).

Copper accounts for less than 0.5% of the cationic load at the downstream point. In the Meca tributary, the anionic load is dominated by SO4 2-(70%), followed by Cl -and NO3 -(15%). The cationic load is dominated by Mg 2+ (40%), Ca 2+ (30%) and Na + (20%). Elemental concentrations are generally much lower in the downstream sampling point (e.g., 80 times for Cu) because of dilution process. However, we note that Cl, NO3 and K concentrations are higher in the downstream sampling point while Na concentration is rather similar in the two sampling points.

Copper concentration and isotope composition of Meca River

Upstream, dissolved Cu concentrations range from ∼17 mg/L to ∼120 mg/L and insignificant differences have been detected between concentrations in the < 0.22 µm fraction and in the < 1,000 Da fraction (see Table 1), revealing the absence of Cu in the colloidal phase (1 kDa -0.22 µm). Copper concentrations obtained during this campaign are in good agreement with those measured previously in the Odiel watershed and its sub-watersheds (e.g., Sanchez [START_REF] Sanchez Espana | The natural attenuation of two acidic effluents in Tharsis and La Zarza-Perrunal mines (Iberian Pyrite Belt, Huelva, Spain)[END_REF]Sarmiento et al., 2009a,b;[START_REF] Grande | Overall hydrochemical characterization of the Iberian Pyrite Belt. Main acid mine drainage-generating sources (Huelva, Spain)[END_REF][START_REF] Moreno-Gonzalez | Seasonal variability of extremely metal rich acid mine drainages from the Tharsis mine (SW Spain)[END_REF]. Dissolved Cu concentrations decrease to 0.29 -1.65 mg/L in the downstream point. In both sampling points, dissolved Cu is highly correlated with SO4 (R 2 =0.99 between Cu and SO4), Fe concentrations (Fig. 2 and3) and other elements. To illustrate the link between these elements, we reported the relationship obtained between Cu and Ni concentrations for both upstream and downstream points (Figure SI-1). In order to explore multiple correlations between parameters (time, concentrations….), a Partial Least Square Analysis method was necessary since we have more variables than individuals [START_REF] Wold | Partial Least Squares[END_REF][START_REF] Abdi | Partial least squares regression and projection on latent structure regression (PLS Regression)[END_REF] Copper isotope compositions range from -0.47 to -0.08 ‰ (n = 9) and -0.63 to -0.31(n = 7)

‰ at upstream and downstream point, respectively (Table 1). These values are coherent but more variable than those previously obtained in a similar context (-0.75 ± 0.13 ‰ in the Odiel River, [START_REF] Borrok | Isotopic variations of dissolved copper and zinc in stream waters affected by historical mining[END_REF]. Cu isotope composition of the Meca River suspended matter collected on 12-May-2016 at 4:00 p.m. (δ 65 Cususpended-matter= -0.41 ± 0.03 ‰) is the same as that of filtered water (δ 65 CuDissolved = -0.42 ± 0.01 ‰, Table 2). On the contrary, the top layers of bed sediments of the Meca River revealed more negative δ 65 Cusediment of -1.92 ± 0.04 ‰.

Copper dissolved concentration and δ 65 Cu values showed significant variation over a 24-h period (Fig. 4). The upstream δ 65 Cu values fluctuate between -0.47 ± 0.01‰ (2σ) and -0.08 ± 0.02 ‰ (2σ). During high rainfall periods (high discharge regime), lower Cu concentrations (≈ 17 mg/L) and δ 65 Cu values (≈ -0.4 ‰) associated with higher pH (> 2.80) are observed.

During low water discharge period, we observe higher Cu concentrations (up to 120 mg/L), lower pH (pH < 2.5) and higher δ 65 Cu values (close to 0 ‰). In the downstream point, where

Cu concentrations are much lower, from 0.29 to 1.65 mg/L, the δ 65 Cu is between -0.31 and -0.63‰: Thus we observe similar tendency as in the upstream point with concomitant lower δ 65 Cu and Cu content.

Discussion

Discharge-related variations of Cu concentration and isotopic composition at upstream sampling point of the Meca River

During the rain-free period and steady-state conditions, the low water discharge(< 0.5 m 3 /s, field measurement using the "bucket" method) is associated with low pH and high copper (>100 mg/L) and other metals and sulphate concentrations in the dissolved phase (i.e., <0.22 µm) of the Meca River. An opposite tendency is observed during high rain and runoff. This behavior is consistent with the streamflow -sulphate concentration relationship defined by [START_REF] Galvan | Aplication of the SWAT model to an AMD-affected River (Meca River, SW Spain). Estimation of transported pollutant load[END_REF] (see chapter 2.2) and the fact that we observe in the present study a close relationship between Cu and sulphate concentrations (see Fig. 2). The upstream δ 65 Cu values fluctuate significantly between -0.47 ‰ during high rainfall and -0.08 ‰ during low rainfall (see Fig. 4). For the low water discharge period, we assume that the Meca River is mainly fed by emptying lakes and galleries (groundwater) from the Tharsis mining district since the upstream point is the integrative water collection point of the whole mining district (Perez-Ostale, 2014). The close to zero values obtained during low water period therefore represent the isotopic composition of water in direct contact with the sulfide-rich parent materials and their host rocks.

The lower Cu concentrations (and other metals) obtained during the high water discharge cannot be explained by a single dilution process by meteoric waters since Cu isotopic composition drastically changed with time (Fig. 4). This implies that (an)other(s) source(s)

and/or process(s) contribute(s) to the flux of metals in the Meca River. We hypothesizsed that the large amount of abandoned wastes presents within the Tharsis mining district of the Meca River watershed could be a significant contributor during flood events. Indeed, Perez-Ostale (2014) reported that more than 80 ha of wastes are present within the Tharsis mining district without any remediation measures and thus represent a major source of elements (metals and metalloids) during flood event. In the Lagunazo mine area (Iberian Pyrite Belt), negative δ 65 Cu value (-0.70 ± 0.04 ‰) has been reported for waters percolating through pyrite-rich wastes [START_REF] Viers | Are Cu isotopes a useful tool to trace metal sources and processes in acid mine drainage (AMD) context?[END_REF]. The Lagunazo mine, mined for copper, is constituted by a massive sulfide deposit located North-West of the Tharsis deposit. If we consider this negative signature as a first approximation of the average isotopic composition of waters percolating through the abandoned wastes of the Tharsis mine plant, the leaching of waste during periods of intense precipitation can induce a lower isotopic composition in the Meca River since this river is the outlet of this mining area. In the event of rainfall and after prolonged dry period, rain water quickly dissolves highly soluble sulphates or other secondary minerals that have been deposited during the dry period within the wastes and in the major bed of the river [START_REF] Sanchez Espana | The natural attenuation of two acidic effluents in Tharsis and La Zarza-Perrunal mines (Iberian Pyrite Belt, Huelva, Spain)[END_REF][START_REF] Valente | Mineralogy and environmental relevance of AMD-precipitates from the Tharsis mines, Iberian Pyrite Belt (SW, Spain)[END_REF]. The mineralogical study revealed the presence of secondary minerals with characteristics of mine wastes (copiapite or jarosite type minerals) but also the predominance of a muscovite type minerals suggesting also the contribution of surrounding soils (see section 4.3).

We performed a mass-balance modelling to check if the isotopic composition of the Meca River at the upstream point could be explained by a mixing of waters originating from these two supposed main sources, lakes/galleries and leaching of abandoned wastes (Fig. 5). In this modelling, the isotopic compositions of waters percolating through the wastes varied from -0.45 to -1.95‰ with a Cu concentration set at 10 mg/L while the concentration and isotopic composition of Cu in galleries and lakes were set at 150 mg/L and -0.05 (δ 65 Cu, in ‰), respectively. The isotopic signature used to characterise the "waste" pool was chosen to Another process that could interfere in the resulting isotopic composition of the Meca River at the upstream point is precipitation of secondary minerals within the main stem.

Indeed, the upstream waters are slightly oversaturated with respect to jarosite (KFe3(SO4)2(OH)6), goethite (FeOOH), and a cupric ferrite type mineral (CuFe2O4) (see Fig. 6). It has been previously shown that goethite, jarosite and schwertmannite could precipitate at the pH of 2 to 3 in the river water [START_REF] Sanchez Espana | The natural attenuation of two acidic effluents in Tharsis and La Zarza-Perrunal mines (Iberian Pyrite Belt, Huelva, Spain)[END_REF].As the suspended matter and bed load sediment were enriched in lighter isotopes (δ 65 Cususpended-matter= -0.41 ± 0.03 ‰;

δ 65 Cusediment = -1.92 ± 0.04 ‰), the minerals precipitation can exert strong effect on the isotopic composition of the river water. For example, precipitation of isotopically-light solid phases will enrich the river water in heavier isotopes via mass balance effect. Copper exhibited heavier isotopic composition during low flow period but the effect cannot be quantitatively assessed. However, the absence of copper in the form of small colloids (see section 4.2) would suggest a source change rather than a process within the water column to explain the variation in isotopic composition. Indeed, the precipitation of secondary minerals should take place via precursors and in particular the presence of colloidal particles.

Overall, based on diel cycle under contrasting hydrological regime in the upstream point, Cu isotopes allowed us to detect two distinct sources of Cu in the river, which are: i) lake water under dry conditions, and ii) a mix of lake and soil/waste deposit runoff sources under flood conditions. A multi-parametric statistical treatment suggests that the data structure is governed by one single factor that could be related to the water discharge. With the exception of Na and K, all elements exhibit a temporal pattern which is similar to that of Cu.

Variations of Cu concentration and isotopic composition at the downstream sampling point of the Meca River

Located 20 km down from the upstream sampling point, the downstream point exhibits much lower dissolved Cu concentrations ( ∼0.28 mg/L to ∼1.6 mg/L).With δ 65 Cu values ranging from -0.63 ± 0.03‰ (2σ) to -0.29 ± 0.02‰ (2σ), downstream sampling point exhibits both narrower and negative values compared to upstream during the same sampling period (Fig. 4A and4B).

Because of the lack of hydrological data for both Meca River and tributaries it was impossible for us to physically constrain the mixing processes. Consequently, we will discuss qualitatively the processes that may affect the isotopic composition between the upstream and the downstream points.

A dilution of mine waters by tributaries and lateral input through soils of the watershed are primarily responsible for Cu isotope evolution over the Meca River watercourse. The lighter isotopic composition of the downstream point could result from direct contribution of the Meca tributaries through a dilution process. We sampled only one of these tributaries which exhibited low Cu concentration (0.3 mg/L) and light isotopic composition (δ 65 Cutributary = -2.72 ± 0.03 ‰). As this Meca tributary is draining non mining plant zone, we suggest our sampling to be representative of the soil catchment contribution between the mine district and the downstream sampling point. A small fraction of this Cu could be natural Cu originating from the chemical weathering of the parental rocks that have an average value of 55 mg/kg [START_REF] Chopin | Distribution and mobility of trace elements in soils and vegetation around the mining and smelting areas of Tharsis, Riotinto and Huelva, Iberian Pyrite Belt, SW Spain[END_REF]. A more significant fraction of Cu present in the surrounding soils may originate from the mine after deposition of atmospheric particles on these soils.

Indeed, smelting activity was conducted on the Tharsis site for many years (Valente et a., 2013) and [START_REF] Chopin | Distribution and mobility of trace elements in soils and vegetation around the mining and smelting areas of Tharsis, Riotinto and Huelva, Iberian Pyrite Belt, SW Spain[END_REF] have revealed that in the case of Tharsis, the soils appear to be contaminated significantly in the vicinity of the mine (2 to 3 km around). As copper presents a strong affinity for organic matter, organic (O) soil horizons are generally enriched in copper with respect to deepest soil horizons [START_REF] Bigalke | Stable Cu istope fractionation in soils during oxic weathering and podzolization[END_REF], what was observed by [START_REF] Chopin | Distribution and mobility of trace elements in soils and vegetation around the mining and smelting areas of Tharsis, Riotinto and Huelva, Iberian Pyrite Belt, SW Spain[END_REF]. Based on a mass balance calculation, In this case, it seems that only inputs of tributaries with exogenous Cu would be able to affect δ 65 Cu downstream values.

Furthermore, during the water flow between the mine/upstream and downstream point, various in-stream processes could control Cu concentration and isotopic composition in the fluid. These are: i) precipitations of secondary Cu-bearing minerals; ii) Cu sorption onto major mineral phases of river bed sediments; iii) Cu uptake by aquatic microorganisms. These processes are likely to be mostly pronounced in the downstream point, given that highly acidic upstream waters (pH = 2.4 to 2.8) are not favourable for adsorption and biota development. At the downstream point, speciation calculations show that the fluid is largely oversaturated with respect to schwertmannite (Fe8O8(SO4)x(OH)y,nH2O), a cuprite type mineral (CuFe2O4) and at a lesser extent jarosite (KFe3(SO4)2(OH)6), goethite (FeOOH) and ferrihydrite (Fe2O3,0.5H2O) (see Fig. 6). Within the AMD context, it is known that the heavier Cu isotopic composition of the solution with respect to that of bulk chalcopyrite could be due to the precipitation of an isotopically light Cu-rich solid phase [START_REF] Kimball | Copper isotope fractionation in acid mine drainage[END_REF].

More recent work suggested that the progressive enrichment of Cu heavier isotope along the Cobica River, draining the Lagunazo copper mine, could be due to the precipitation of some secondary minerals enriched in light isotopes [START_REF] Viers | Are Cu isotopes a useful tool to trace metal sources and processes in acid mine drainage (AMD) context?[END_REF]. The values obtained for suspended and bed sediments of the Meca River (δ 65 Cususp-sed = -0.41 ± 0.03 ‰ and δ 65 Cusediment = -1.92 ± 0.04 ‰) seem to support this assumption since the secondary products are enriched in light isotopes. However, given that the isotopic composition at the downstream point (-0.29 to -0.63‰) is globally lower than that at the upstream point (-0.08 to -0.47‰), we suggest that secondary mineral precipitation cannot be sole process controlling Cu isotope fractionation, and other mechanisms should be considered.

The higher pH measured at the downstream point (3.61 to 5.68) compared to the upstream point (2.41 to 2.82) implies a possibility of metals sorption onto the surface of suspended sediments in the course of the water flow, as it is known for other mine water-affected environments [START_REF] Lee | Removal of trace metals by coprecipitation with Fe, Al and Mn from natural waters contaminated with acid mine drainage in the Ducktown Mining District, Tennessee[END_REF][START_REF] Smith | Metal sorption on mineral surfaces: an overview with examples relating to mineral deposits. The environmental geochemistry of mineral deposits[END_REF]. We identified the presence of Fe oxides and other (hydr)oxide minerals in the suspended matter of the Meca River (see section 4.3) that can offer substantial surfaces for Cu sorption. [START_REF] Balistrieri | Fractionation of Cu and Zn isotopes during adsorption onto amorphous Fe (III) oxyhydroxide: experimental mixing of acid rock drainage and ambient river water[END_REF] and [START_REF] Pokrovsky | Copper isotope fractionation during its interaction with soil and aquatic microorganisms and metal oxy(hydr)oxides: possible structural control[END_REF] have shown that Cu sorption onto common mineral and organic surfaces favors the heavy isotope leaving isotopically light Cu in the aqueous solution. The effect of the sorption process could not be quantified but is consistent with a lower isotopic composition in the downstream point.

Finally, third mechanism affecting Cu isotope composition in the river water is Cu interaction with aquatic microorganisms. During our sampling period, the temperature was low (13.6 -17.1°C, upstream) and we did not detect any algal bloom that could have affected the dissolved Cu. Moreover, the uptake of Cu by bacteria, peryphytic biofilm or algae favors the light Cu isotope into the biomass (Navarette et al. 2011;[START_REF] Coutaud | Small changes in Cu redox state and speciation generate large isotope fractionation during adsorption and incorporation of Cu by a phototrophic biofilm[END_REF]. This process would enrich the river water in heavy isotope, which is not consistent with our observations.

Conclusions

This study presented both Cu concentration and isotopic composition of the Meca River draining one of the largest abandoned mine of the Iberian Pyrite Belt during a flood event.

Based on observations over the diel cycle under changing water regime conditions, Cu isotopes are useful to understand the hydrochemical functioning of a complex mining zone. In response to a change in the hydrological conditions, the system appears to react quickly since Cu isotopic composition changes following the amount of precipitation/water discharge in the mining area. In the case of the Tharsis mine, copper isotopes allowed us to detect two distinct metal sources in the headwater catchment under constrained hydrological regime. A major contribution was provided by lake/gallery source under dry conditions, whereas during the flood, a mix of lake/gallery and soil/waste deposit contributed to lateral surface runoff. These findings could be useful for mine remediation measures and monitoring practices. Twenty km downstream the mine, the Cu isotopic composition is essentially controlled by a dilution and mixing process of headwater catchment by lateral surface runoff within soils brought by tributaries. It is not strongly modified by in-stream environmental processes such as precipitation of Cu secondary bearing minerals, sorption on mineral surfaces or uptake by aquatic organisms.

  (see Fig. SI-2). The inertia graph reveals that only one single factor is interpretable (Fig. SI-2A). The two sites are clearly distinguished by their chemical composition and by the evolution of concentrations through time (see Fig. SI-2C). In the upstream point Cu and other element concentrations vary simultaneously as a function of time (and water discharge variation) while concentrations are much more stable at the downstream point.

3. 3 .

 3 The suspended sediment of the Meca River: mineralogical characterization and chemical analysis Two suspended matter samples from the Meca River upstream point (ME-A 11-May-2016 10:00 p.m.; ME-A 12-May-2016 4:00 p.m.,) were studied using SEM-EDS and X-ray diffraction while Raman spectroscopy has been performed on the ME-A 11-May-2016 10:00 p.m. sample. The SEM observations of both samples revealed homogeneous composition of suspended material. We note the predominance of a muscovite type mineral (see Fig. SI-3 supplementary information) in both samples and the presence of quartz, Fe oxides, rutile (TiO2) and grains containing S + Fe + As + Pb or S + Fe + Pb or S + Fe associations. Based on results of the Xray diffraction (see Fig. SI-4), the mineral containing S + Fe + Pb + As appears to be a beudantite type mineral, the mineral containing S + Fe is a copiapite type mineral and the mineral containing S + Fe + Pb is a (plumbo)jarosite type mineral. Pyrite, Ti oxides, and Fe oxides grains have been also observed in the ME-A 11-May-2016 10:00 p.m. sample. The EDS system of the SEM did not allow detecting Cu in the investigated minerals. Raman spectroscopy revealed the presence of Fe oxydes, Tioxydes, jarosite, plumbojarosite and wavellite (hydrated aluminous phosphate) confirming the X-ray diffraction data (Fig. SI-5).Collected sediments were mainly composed of Fe, Al, K and Pb (between 1 and 10%) and contained Mg, Ti, As, Na, Zn, Sb and Cu as minor elements with concentrations between 0.1 and 1%. Due to our analytical protocol, Si and S were not analysed in the solids. All the concentrations have been normalised to the upper crust composition(Taylor and McLennan, 1995) (see supplementary materials Fig.SI-6). Compare to the upper crust reference, the suspended and bed load sediments are enriched in several elements in the order Sb >Pb>>> Cu, Sn, Zn, Cd >> Co, Fe, Cr, V. Compare to the bed load sediment, the suspended sediments present a significant enrichment in Cd >> Sn, Sb, Zn, Pb, > Co.

  encompass the value obtained by[START_REF] Viers | Are Cu isotopes a useful tool to trace metal sources and processes in acid mine drainage (AMD) context?[END_REF] (-0.70 ± 0.04 ‰) for waters percolating through pyrite-rich wastes. Additional theoretical curve with δ 65 Cu of -1.95% was required to encompass the upstream points at intermediate concentrations of dissolved Cu (Fig.5). It can be seen that, while open mine lakes are the major source of riverine Cu during dry periods, their role becomes minor during flood.

(δ 65

 65 Cu x [Cu])downstream = (δ 65 Cu x [Cu])tribute_stream + (δ 65 Cu x [Cu])upstream where [Cu] stands for Cu concentration, we estimated that 87 % of the downstream Cu comes from the upstream point, and only 13% from the tributary streams.

Fig. 1 :

 1 Fig. 1: Upstream, tributary stream and downstream

Figure 2 :Figure 3 :

 23 Figure 2: Dissolved Cu concentration as a function of SO 4 2-concentrations for upstream (black symbols) and downstream (gray symbols) sampling

Figure 4 :Figure 5 :

 45 Figure 4: Diel variation in δ 65 Cu (left axis, black circle) and dissolved Cu concentrations (right axis, gray

Figure 6 :

 6 Figure 6: Saturation indexes calculated using Visual MINTEQ

Figure 6 :

 6 Figure 6: (to be continued)

Table 1 :

 1 Physical

			ME-A	ME-A	ME-A	ME-A	ME-A	ME-A	ME-A	ME-A	ME-A	ME-A	ME-A	ME-A	ME-A		ME-B	ME-B	ME-B	ME-B	ME-B	ME-B	ME-B	ME-B
	Sampling		4:00	4:00	7:00	10:00	10:00	1:00	4:00	4:00	7:00	10:00	10:00	1:00	4:00	ME-A	5:00	8:00	11:00	5:00	8:00	11:00	2:00	5:00
	name		PM	PM	PM	PM	PM	AM	AM	AM	AM	AM	AM	PM	PM	AFL	PM	PM	PM	AM	AM	AM	PM	PM
	Filtration		<0,22	<1000	<0,22	<0,22	<1000	<0,22	<0,22	<1000	<0,22	<0,22	<1000	<0,22	<0,22	<0,22	<0,22	<0,22	<0,22	<0,22	<0,22	<0,22	<0,22	<0,22
	size		µm	da	µm	µm	da	µm	µm	Da	µm	µm	Da	µm	µm	µm	µm	µm	µm	µm	µm	µm	µm	µm
		Unit
	Temperature
	(°C)	°C	16,6	-	17,1	15,4	-	14,3	14,3	-	13,8	15,0	-	13,6	17,0	15,7	16,6	19,7	16,2	14,4	14,4	15,6	16,7	21,0
	pH		2,60	-	2,52	2,57	-	2,56	2,50	-	2,43	2,41	-	2,64	2,82	3,85	4,12	5,68	4,27	4,52	4,34	4,09	3,69	3,61
		mS/cm
		(at
	Conductivity	25°C)	5,48	-	6,44	6,12	-	8,02	9,76	-	11,39	11,6	-	6,22	2,81	0,51	0,43	0,31	0,31	0,31	0,38	0,39	0,54	0,50
	O2	mg/L	6,46	-	6,30	6,61	-	6,64	6,45	-	6,54	6,48	-	8,4	7,65	6,94	-	-	-	-	-	-	-	-
	DOC	mg/L	7,348	-	16,43	7,384	-	13,58	12,7	-	5,676	5,468	-	10,22	9,917	35,93	-	-	-	-	-	-	-	-
	Cl	mg/L	10,67	-	11,61	11,12	-	11,98	12,85	-	13,80	14,07	-	8,85	8,28	21,84	25,03	29,11	26,29	30,19	26,89	26,76	27,69	17,32
	NO3	mg/L	1,07	-	0,95	1,09	-	1,19	1,08	-	1,01	0,84	-	0,80	1,25	34,74	1,93	1,88	2,12	2,26	1,65	1,74	1,89	3,09
	SO4	mg/L	4964	-	6407	5657	-	8251	10784	-	13163	14241	-	5746	1886	144	233	72	81	91	101	132	177	201
			-0,21		-0,36 (	-0,39		-0,08	-0,13		-0,09 (	-0,08 (		-0,10	-0,47	-2,72	-0,38	-0,31	-0,63	-0,48	-0,45	-0,45		-0,35
			(±		±	( ±		( ±	( ±		±	±		( ±	( ±	( ±	( ±	( ±	( ±	( ±	( ±	( ±		( ±
	δ 65 Cu (‰)		0.00)	-	0.02)	0.02)	-	0.03)	0.16)	-	0.02)	0.17)	-	0.02)	0.02)	0.03)	0.02)	0.01)	0.03)	0.02)	0.01)	0.01)		0.01)
	Cu	mg/L	43,55	44,60	57,76	51,07	49,79	72,58	91,79	92,84	113,38	119,88 116,80	51,97	16,92	0,32	1,65	0,29	0,48	0,44	0,64	0,86	1,18	1,46
	Na (mg/L)	mg/L	12,24	8,06	18,61	8,63	8,61	8,72	10,90	9,41	10,34	10,02	9,22	7,41	6,80	17,11	14,18	16,22	14,28	15,43	15,06	14,97	15,42	10,85
	Mg (mg/L)	mg/L	267	256	334	282	283	419	530	549	672	723	693	313	91	16	17	10	9	10	11	12	14	14
	Al (mg/L)	mg/L	298	283	358	317	319	468	602	628	775	826	799	360	101	3	12	1	3	2	4	6	8	10
	Si (mg/L)	mg/L	16,04		20,12	18,12		22,56	25,06		27,63	29,33		14,33	8,54	5,29	4,95	4,12	4,03	4,31	4,77	-	5,19	5,51
	K (mg/L)	mg/L	1,22	1,11	2,71	0,54	1,31	0,67	0,97	1,02	0,92	0,88	1,11	1,27	1,11	3,38	2,05	2,38	2,20	1,87	1,73	1,72	1,66	1,84
	Ca (mg/L)	mg/L	54,10	47,81	100,17	54,25	51,10	70,70	85,65	86,89	106,17	112,66 108,95	50,72	19,05	21,92	10,49	9,81	8,56	8,96	8,90	9,34	10,04	9,48
	Mn (mg/L)	mg/L	34,01	33,16	42,28	36,49	35,05	51,94	65,61	65,34	80,08	84,27	82,53	37,43	11,93	1,67	1,56	0,73	0,72	0,62	0,80	1,01	1,27	1,53
	Fe (total)	mg/L	1023	1029	1355	1214	1157	1793	2337	2338	2872	3007	2924	1295	392	1	21	2	4	4	6	9	14	19
	Fe 2+	mg/L	623	n.m.	826	604	n.m.	1648	1881	n.m.	1779	1456	n.m.	791	245	n.m.	n.m.	n.m.	n.m.	n.m.	n.m.	n.m.	n.m.	n.m.
	Fe 3+	mg/L	400	n.m.	528	610	n.m.	145	456	n.m.	1093	1551	n.m.	504	147	n.m.	n.m.	n.m.	n.m.	n.m.	n.m.	n.m.	n.m.	n.m.
	Co	mg/L	3,07	3,14	3,99	3,43	3,35	4,97	6,31	6,36	7,82	8,17	7,99	3,58	1,09	0,05	0,12	0,03	0,04	0,04	0,05	0,07	0,09	0,11
	Ni	mg/L	1,06	1,10	1,39	1,16	1,15	1,71	2,16	2,19	2,70	2,88	2,81	1,23	0,39	0,02	0,05	0,02	0,02	0,02	0,02	0,03	0,04	0,04
	Zn	mg/L	122,7	122,7	158,1	138,2	132,7	202,7	265,7	268,9	333,8	354,0	344,4	153,2	43,9	0,5	4,8	1,0	1,3	1,3	1,8	2,5	3,5	4,3
	V	µg/L	220	225	290	270	255	388	512	519	629	649	629	272	87	0,33	0,10	0,06	0,05	0,07	0,05	0,04	0,04	0,05
	Cr	µg/L	184	181	247	217	207	314	411	408	505	538	531	229	66	1,36	5,54	0,39	0,80	0,98	1,33	2,34	3,70	5,05
	Cd	µg/L	264	254	328	280	272	422	543	551	682	734	719	315	88	0,66	10,77	2,63	3,20	2,97	4,21	5,65	7,75	9,49

parameters (measured in situ), elemental concentrations and Cu isotopic composition for the upstream and downstream sampling points of the Meca River and for the Meca tributary. All concentrations and isotopic were measured in the dissolved fraction (i.e., <0.22 µm). n.m. indicates not measured.

Table 2 :

 2 Elemental concentrations and Cu isotopic composition for the suspended and bed sediments from the Meca River.

Acknowledgments

This work was supported by the EC2CO program of the INSU/CNRS institution and by the European Union for co-funding SOIL TAKE CARE SOE1/P4/F0023 through the European Regional Development Fund (ERDF), under the Interreg SUDOE Program. This work was also partly supported by the EQUIPEX CRITEX programme (grant no. ANR-11-EQPX-0011, Pls. J. Gaillardet and L. Longuevergne). We deeply thank Ludovic Menjot and Priscia Oliva for their technical and scientific help in XRD data acquisition and interpretation, Manuel Henry for his help in the clean room, and Stéphanie Mounic for anions concentrations measurements at the GET laboratory. We want to also express our gratitude to our Stéphane Le Blond du Plouy from the Centre de MicroCaractérisation Raimond Castaing for his technical support in SEM-EDX characterisation. We would also like to thank the staff of the management department without which nothing could be achieved. The reviewers should be deeply thanked for their work.