Haiyan Liu
email: hy_liu@ecut.edu.cn

Huaming Guo
email: hmguo@cugb.edu.cn

Olivier Pourret
email: olivier.pourret@unilasalle.fr

Zhen Wang

Maohan Liu

Weimin Zhang

Zebing Li

Bai Gao

Zhanxue Sun

Pierre Laine

; Bai Gao

Geochemical signatures of rare earth elements and yttrium exploited by acid solution mining around an ion-adsorption type deposit: Role of source control and potential for recovery

Keywords: Lanthanide, Acid mine drainage, Water-rock interaction, Fractionation, Critical metals

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Introduction

Global demand of rare earth elements and yttrium (REE+Y) to support technology has increased in the past two decades [START_REF] Haxel | Rare earth elements critical resources for high technology[END_REF]Van Gosen et al., 2014), leading to increased production of rare-earth oxides (U.S. Geological [START_REF] Survey | Rare Earth Statistics[END_REF]. China sustains 98% of global REE+Y demand with an ion-exchange processed clay deposit in southern China as a major supplier for middle REE (MREE) and heavy REE (HREE) [START_REF] Alonso | Evaluating rare earth element availability: a case with revolutionary demand from clean technologies[END_REF]). The REE+Y were mainly mined via heap leaching, and this technology produced a large amount of acid mine drainage (AMD) and mine tailings (Liu et al., 2019b). The AMD potentially migrating into subsurface environments imposed severe REE+Y contamination to soils, waters, and crops (Liu et al., 2019a;[START_REF] Liu | Reclamation with organic amendments and plants remodels the diversity and structure of bacterial community in ion-adsorption rare earth element mine tailings[END_REF]. The thus increased REE+Y emissions to the environment have caused worldwide concerns [START_REF] Vaziri Hassas | Effect of various ligands on the selective precipitation of critical and rare earth elements from acid mine drainage[END_REF][START_REF] Ayora | Recovery of rare earth elements and yttrium from passive-remediation systems of acid mine drainage[END_REF].

Acid mine drainage is generated through oxidation of sulfides (e.g., pyrite) contained in target strata upon ADM has acidic pH and contains elevated sulfate and metal(loid)s (Nordstrom and Alpers, 1999;[START_REF] Gimeno | REE speciation in low-temperature acidic waters and the competitive effects of aluminium[END_REF][START_REF] Nordstrom | Hydrogeochemistry and microbiology of mine drainage: an update[END_REF]. The highly polluted AMD has been considered a severe environmental problem posing great risks to the environment near the exploited mine. This issue is of global concern (e.g., in China, Vietnam, Australia, India and Spain) [START_REF] Akcil | Acid Mine Drainage (AMD): causes, treatment and case studies[END_REF]Marquez et al., 2018, and references therein). AMD could be treated by passive natural attenuation like microbial activity, or by active technology requiring external input of energy and material to maintain in continuous operation [START_REF] Johnson | Acid mine drainage remediation options: a review[END_REF]. However, both technologies have drawbacks such as bioclogging and scaling problems resulting from mineral precipitation for the former, and costly and time-consuming processing for the latter [START_REF] Lé On | Mine waters as a secondary source of rare earth elements worldwide: the case of the Iberian Pyrite Belt[END_REF].

Acid mine drainage has also been shown to contain high levels of REE+Y [START_REF] Verplanck | Rare earth element partitioning between hydrous ferric oxides and acid mine water during iron oxidation[END_REF][START_REF] Moraes | The role of iron in the rare earth elements and uranium scavenging by Fe-Al precipitates in acid mine drainage[END_REF]. Owing to their spectroscopic and magnetic properties, the REE+Y have been widely used in clear energy producing, medical diagnosis, and other applications [START_REF] Wall | Rare earth elements[END_REF]Van Gosen et al., 2014). This has resulted in increased demand of REE+Y for the world's market. Therefore, seeking alternative sources of REE+Y (esp. HREEs: Dy, Tb, Eu and Yb) is an important need for development of recovery technology in many countries [START_REF] Binnemans | Recycling of rare earths: a critical review[END_REF].

REE+Y recovery from AMD and its sludges were investigated by a number of studies [START_REF] Stewart | Rare earth element resources in coal mine drainage and treatment precipitates in the Appalachian Basin, USA[END_REF][START_REF] Vass | The occurrence and concentration of rare earth elements in acid mine drainage and treatment by-products: part 1-initial survey of the northern Appalachian coal basin[END_REF][START_REF] Zhang | Process development for the recovery of rare earth elements and critical metals from an acid mine leachate[END_REF]. Previous research at various mine sites showed that the REE+Y concentrations in AMD were several orders of magnitude higher than the median values of near-neutral mine waters [START_REF] Ayora | Recovery of rare earth elements and yttrium from passive-remediation systems of acid mine drainage[END_REF]. The normalized REE+Y patterns were characterized by MREE enrichment over LREE and HREE. Some studies showed LREE- [START_REF] Bozau | Light rare earth elements enrichment in an acidic mine lake (Lusatia, Germany)[END_REF]) and HREE- [START_REF] Medas | Geochemistry of rare earth elements in water and solid materials at abandoned mines in SW Sardinia[END_REF] enriched normalized patterns in AMD as well.

Other studies reported that AMD was depleted in LREE [START_REF] Gammons | Geochemistry of rare earth elements and uranium in the acidic Berkeley Pit Lake, Butte, Montana[END_REF][START_REF] Sharifi | Geochemical behavior and speciation modeling of rare earth elements in acid drainages at sarcheshmeh porphyry copper deposit, Kerman province, Iran[END_REF][START_REF] Migaszewski | The study of rare earth elements in farmer's well waters of the Podwiśniówka acid mine drainage area (south-central Poland)[END_REF].

In spite of the known normalized REE+Y patterns in AMD systems, the underlying mechanism regulating the formation of the patterns is poorly understood.

Considering the extremely low concentrations of REE+Y in rainwater [START_REF] Zhang | Major and rare earth elements in rainwaters from Japan and East China Sea: natural and anthropogenic sources[END_REF][START_REF] Zhu | Rare earth elements concentrations and speciation in rainwater from Guiyang, an acid rain impacted zone of southwest China[END_REF], REE+Y are ultimately sourced from water-rock interactions.

Preferential leaching of REE-bearing solids was proposed for causing the enrichment patterns [START_REF] Sun | Behavior of rare earth elements in acid coal mine drainage in Shanxi province, China[END_REF]Wallrich et al., 2020, and references therein). In this framework, REE+Y-enriched mineral phases should be present in the bulk solid samples. Indeed, sequential extraction of strata rocks showed that the REE content was related to carbonate and aluminosilicate minerals [START_REF] Worrall | Water-rock interaction in an acidic mine discharge as indicated by rare earth element patterns[END_REF].

After being removed by ion-exchange, the rock samples were extracted sequentially with acidic solutions buffered at pH 1.6, 3.6, and 5.5, to simulate the formation process of AMD, showing that the sequential extracts had similar REE patterns to those of AMD [START_REF] Worrall | Water-rock interaction in an acidic mine discharge as indicated by rare earth element patterns[END_REF]. Results of [START_REF] Worrall | Water-rock interaction in an acidic mine discharge as indicated by rare earth element patterns[END_REF] experiments further demonstrated that REE signatures in acidic water were a mixture of leachates of various sedimentary mineral components, suggesting that REE+Y enrichment patterns for AMD were of source-control. Furthermore, the conservative behavior of REE+Y in the acidic solutions had accounted for their long-distance transport [START_REF] Verplanck | Rare earth element partitioning between hydrous ferric oxides and acid mine water during iron oxidation[END_REF]. However, other studies indicated that process-derived reactions such as fractionation by colloidal complexes [START_REF] Åström | Distribution of rare earth elements in anionic, cationic and particulate fractions in boreal humus-rich streams affected by acid sulphate soils[END_REF], adsorption-desorption on surface coatings (Åström, 2001), differences in solutes complexation [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 preferential precipitation of certain REE during formation of secondary minerals [START_REF] Elderfield | The rare earth elements in rivers, estuaries and coastal seas and their significance to the composition of ocean waters[END_REF][START_REF] Leybourne | Rapid development of negative Ce anomalies in surface waters and contrasting ree patterns in groundwaters associated with Zn-Pb massive sulphide deposits[END_REF] were responsible for the deviating REE+Y enrichment patterns. A recent study suggested that the roles of geology in controlling REE+Y distribution and patterns in AMD might be complicated by geochemical, biological and environmental factors (León et al., 2021). The coherent properties and predictable behavior of REE+Y make them ideal tracers of clastic sediment transport (Taylor and McLennan, 1988), water-rock interactions [START_REF] Worrall | Water-rock interaction in an acidic mine discharge as indicated by rare earth element patterns[END_REF], and mixing processes (Liu et al., 2017a). The unique properties of REE+Y constitute therefore an opportunity to study the source, origin, fate and transport of AMD, which is important in addressing the mechanisms of AMD formation and contamination.

The hypotheses for this study were: (i) high REE+Y concentrations occur in AMD where elevated metal, sulfate and ammonium concentrations co-occur, (ii) local lithology in relation to acidification-enhanced desorption and scavenging by secondary minerals controls REE+Y distribution patterns in AMD, and (iii) the REE+Y inventory of AMD is potentially recoverable upon pH neutralization by implementing appropriate treatment options. The objectives of this study were to: (i) investigate the concentrations and distributions of REE+Y in an AMD system (i.e. water, rock, sediment, and sludge), (ii) characterize the geochemical controls of REE+Y sources and fractionation patterns in AMD, and (iii) assess the potential of REE+Y recovery from AMD.

Methods and materials

Regional hydrogeological settings

The mining site (longitude: 114°47′28″, latitude: 24°54′25″) is located in the Jiangxi province, southern China (Fig. 1), and has a subtropical monsoon climate. The temperature ranges from 39°C to -3.1°C (recorded historically), with an annual average of 19.7 °C . Precipitation ranges from 1058 to 2190 mm (annual average 1608 mm), dominating from April to July (accounts for 60%). Annual evaporation is 1497 mm (1349 to 1619 mm), intensely occurring in July and August. The drainage basin has five main rivers that are connected to the tributaries of Dongjiang River running from south to north with an annual average flow rate of 14 m 3 /s. Late Cretaceous to Quaternary strata outcrop in the mine area, of which Cambrian, Devonian and Jurassic strata are exposed in most areas and are distributed primarily in the eastern and southern part of the study area. The mine is hosted in Jurassic to early-Cretaceous igneous rocks, which cover a total area of 360 km 2 . The main rocks are micaceous granite, porphyry granite, monzonitic granite, and diorite [START_REF] Yang | China's ion-adsorption rare earth resources, mining consequences and preservation[END_REF]. The REE+Y are concentrated in two types of micaceous granite, namely muscovitic granite and biotitic granite, where HREE and LREE have distinct distribution patterns in their weathered layers [START_REF] Yang | China's ion-adsorption rare earth resources, mining consequences and preservation[END_REF]. The HREE accounted for 75 to 89 wt.-%, with an average value of HREE/LREE of 4.4 in the weathering regoliths of muscovitic granite. The average HREE proportion was 61%, and the HREE/LREE value was 1.6 for the biotitic granite counterpart. The thickness of the strongly-weathered regolith layer ranges from 5 to 25 m with a corresponding mineral inventory of mainly quartz, feldspar and mica.

Groundwater in the mine area is mainly hosted in the fissure network of medium-grain micaceous granite and largely belongs to the phreatic water type. The hydrochemical facies include Ca-SO4, Ca-SO4-HCO3, Ca-Cl, and Ca-HCO3-Cl type waters with total dissolved solids (TDS) ranging from 17 to 170 mg/L. Heap and pond leaching was used previously as an active mining technology at this mine site. However, it has been banned by Chinese government due to great vegetation damage. In-situ leaching is currently done by injecting acidic ammonium sulfate solution through wells drilled into the sedimentary ore deposit. The acidic leachate solution containing the dissolved metals pumped out poses environmental risks as well. Ammonium has been reported to exceed the threshold recorded in groundwater quality standard (Liu et al., 2019b). The main REE leaching mechanism as shown by Eq. ( 1) is an ion-exchange reaction with ammonium (NH4 + ) from clay minerals in the sedimentary deposit [START_REF] Chi | Prospect and development of weathered crust elution-deposited rare earth ore[END_REF]:

(Al4Si4O10(OH)8)m• nREE 3+ + 3nNH 4+ = (Al4Si4O10(OH)8)m• (NH 4+ )3n + nRE 3+ (1)
Although not AMD in sensu-stricto, the acidic mine waters recovered from this solution mining process are termed AMD as well in the following. A sewage treatment plant (STP) was established at the mine site to process the acid efflux from the mine.

The STP technology mainly consists of three procedures, which are (i) nitrification-denitrification to remove ammonium, (ii) coagulation-precipitation to remove metals, and (iii) dilution of treated water with original mine water. Finally, the mixture is discharged into rivers down-stream.

Sample collection

Sixteen water samples were collected in July 2020. Among them, five were AMD samples (MW1 to 5), six were effluents of STP undergoing nitrification-denitrification treatment procedures (NDT1 to 6), four were effluents going through coagulation-precipitation treatment processes (CPT1 to 4), and one was water sample collected from a local groundwater (GW) well in a village near the mine.

All water samples were filtered with 0.22 μm pore size cellulose acetate membranes.

Samples for cation and trace element analysis were stored in 50 mL high-density polyethylene (HDPE) bottles and were acidified to pH <2 with HNO3. Samples for anion analysis were stored in HDPE bottles without acidification. Samples for DOC analysis were sampled in 30 mL amber glass bottles and acidified to pH <2.0 by admixing 1:9 (v/v) H2SO4. Samples for REE+Y analysis were sampled in 500 mL HDPE bottles following an acidification with HNO3. Sampling locations are shown in Fig. 1.

Two rock samples (R1 and R2) were sampled from the outcrop. Three surface sediment samples (MW1-SS, MW2-SS and MW3-SS) were collected from the locations where mine water samples (MW1, 2, and 3) were taken (Fig. 1). The surface sediment samples were collected down to a depth of about 30 cm below land surface.

Sludge samples (MW4-SG, MW5-SG and CPT1-SG) were taken from the bottom precipitates of the settling pond and creek bed, while NDT2-SG and NDT3-SG were sludge samples collected by using a vacuum hose that was deployed to the bottom of a huge container having a depth of about 6 m. All the rock, sediment and sludge samples were stored in clean plastic bags.

Analytical methods

Physicochemical parameters of the water samples, including temperature, pH, electrical conductivity (EC), and redox potential, were measured with a HI 9828 portable multi-meter (HANNA, Woonsocket, RI, USA). To minimize the influence of atmospheric contact, the monitoring probe was immersed in an in-line flow cell where water was pumped through constantly. Physiochemical data were recorded in the field once stabilized. Alkalinity was titrated immediately in the field by using a Model 16900 digital titrator (HACH, Loveland, USA). Redox sensitive components such as total Fe, Fe(II), NH3-N, NO2-N, and S 2-were quantified using a portable UV/VIS spectrophotometer (HACH, DR2800). This device was calibrated with holmium oxide filter and holmium oxide wavelength standard solution.

Anions were analyzed by a lab-based ion chromatography system (ICS2000, Dionex, Thermo Fisher Scientific, Waltham, USA). Cations and trace elements were determined by using inductively coupled plasma optical emission spectrometry (ICP-OES iCAP6300, Thermo Fisher Scientific, Waltham, USA) and inductively coupled plasma mass spectrometry (ICP-MS 7500C, Agilent Technologies, Santa Clara, USA), respectively. Six standard solutions, diluted from stock standards (AR, Tanmo Quality Inspection Technology, China), were used to calibrate the instrument.

Only the standard curves with correlation coefficient (r 2 ) better than 0.9999 were used for subsequent analysis. The results were verified with replicate samples to ensure an analytical precision better than 5%.

Analysis of REE+Y concentrations were performed by employing two different single-collector inductively coupled plasma sector field mass spectrometry instruments (ICP-SFMS ELEMENT XR and ELEMENT 2, Thermo Fisher Scientific, Bremen, Germany) based on the protocol published by [START_REF] Rodushkin | Application of double-focusing sector field icp-ms for determination of ultratrace constituents in samples characterized by complex composition of the matrix[END_REF]. A cation exchange resin (AG 50W-X8, 200 to 400 dry mesh size, Bio-Rad laboratory AB, Solna, Sweden) was used for the preconcentration of REE+Y. Prior to use, the resins were immersed in 14 mol/L HNO3 overnight and were cleaned with deionized water. A 2 mL low-density polyethylene (LDPE) column was loaded with the prepared resins, and 4 mL 14 mol/L HNO3 (AR, Sinopharm, China), 8 mL deionized water and 4 mL 9.5 mol/L HCl (AR, Sinopharm, China) were loaded sequentially for conditioning. Finally, a 200 mL sample was introduced into the pre-conditioned column and the retained REE+Y were eluted with 4 mL 0.5 mol/L HCl. By this method, a 50-fold preconcentration was achieved. The REE+Y recovery ranged between 90% and 103%. Calibration and quality control samples were prepared in 2% nitric acid with a stock solution. A medium resolution mode (MR, m/Δm approximately 5400) was set up for monitoring the isotopes 146 Nd, 147 Sm, 151 Eu, 163 Dy, 165 Ho, and 172 Yb, and a high resolution mode (HR, m/Δm approximately 12000) was used for monitoring the isotopes 139 La, 140 Ce, 141 Pr, 157 Gd, 159 Tb, 166 Er, 169 Tm, and 175 Lu, as suggested by [START_REF] Wilkin | Rare-earth elements as natural tracers for in situ remediation of groundwater[END_REF]. The detection limits were 0.1 ng/L for Lu, 0.2 ng/L for Eu, and 0.5 ng/L for other REE and Y. One ng/L In solution was used as internal standard to check for the mass bias. Interferences of BaO + on the 151 Eu and 153 Eu isotopes were corrected automatically by setting up a correction measure during analysis. Briefly, we run ~100 μg/L Ba and determine the peak area of the Eu isotope being monitored. During a run of samples, Ba (without calibration) was monitored and the results were applied for a correction. The analytical precision of replicate samples of REE+Y were generally better than 8%.

Bulk composition analysis of sediment and sludge samples were carried out using a LiBO2-LiB4O7 fusion and X-ray fluorescence (XRF ARL Advant X), and after dissolving the glass disks by dilute nitric acid also by ICP-OES and ICP-MS. Mineral compositions in sediment and sludge were determined by X-ray diffraction (XRD D8 advance, Bruker) with a CuKα radiation. Diffraction patterns were scanned at 2θ of 20° to 70° and a step size of 0.02°. Minerals having content greater than 5 wt.-% of the bulk solid were thus identified.

Solid samples and suspended matter filtered out of aqueous solutions were examined additionally by using scanning electron microscopy (SEM) (NovaNanao 450, Fei Czech, Co., Ltd.).

Modelling approach

Speciation calculations were performed using the hydrogeochemical code PHREEQC version 3.4 (Parkhurst and Appelo, 2013) with the Nagra/PSI database [START_REF] Hummel | Nagra/PSI Chemical Thermodynamic Data Base 01/01[END_REF]. Stability constants of REE complexation to major anions (e.g. CO3 2-, SO4 2-, OH -, Cl -, F -, and NO3 -) were incorporated into the database from literature (Table S1) (Supporting Information). For example, constants for REE(CO3)2 -and REECO3 + were taken from [START_REF] Luo | Carbonate complexation of yttrium and the rare earth elements in natural waters[END_REF], and those for REESO4 + were taken from [START_REF] Schijf | Determination of SO4β1 for yttrium and the rare earth elements at I = 0.66 m and T = 25 °C -Implications for YREE solution speciation in sulfate-rich waters[END_REF]. Surface complexations of REE onto iron oxyhydroxides were considered as previously done by Liu et al. (2017b), in which the relevant formation constants and detailed modelling procedures were provided. Statistical tests were performed using Grapher (version 10.0) and IBM SPSS Statistics (version 19.0) programs.

Results

Water chemistry

Major ion concentrations and physicochemical parameters are compiled in Table S2. Results revealed that mine waters (MW1 to 5) had pH values between 3.8 and 4.2.

A slight increase in pH (4.1 to 4.9) was observed for NDT samples (NDT1 to 6). The CPT samples had pH values > 7 (7.4 to 8.7), and the GW sample's pH was 6.5.

Generally, pH values increased from the regions nearest to the mine site to downstream of the STP facility.

All water compositions are shown on a Piper plot for comparison (Fig. 2). The TDS ranged between 95 and 562 mg/L (average 363 mg/L) with the lowest values in GW. Before passing through the STP (i.e., samples MW 1 to 5), cation compositions were predominated by Ca 2+ and Mg 2+ , and NO3 -and SO4 2-were the dominant anions, while Cl -concentrations were < 5 mg/L. Water types thus determined for MW 1 to 5 were Ca/Mg-SO4 and Ca/Mg-HCO3/SO4. Over the CPT pathway (CPT 1 to 4), the major cation composition shifted towards Na + predominance (52 to 104 mg/L), followed by Mg 2+ (23 to 26 mg/L) and Ca 2+ (31 to 48 mg/L), while the dominant anion was HCO3 -(>156 mg/L), hydrochemical type for these samples being Na-Ca/Mg-HCO3. This type of water continued downstream near the village (CPT 4), approximately 1 km downstream from the STP. The NDT samples showed a coherent water type of Mg-Na-Ca-HCO3-SO4. The GW collected from the village was of Na-HCO3 water type.

Total dissolved Fe (FeT) concentration ranged from 0.23 to 0.48 mg/L (average 0.31 mg/L) in MW samples, while it dramatically decreased to a range of 0.05 to 0.20 mg/L (average 0.08 mg/L) after passing through the NDT procedure. A further decease in FeT concentration occurred in water which went through the CPT (0.03 to 0.07 mg/L, average 0.06 mg/L). The lowest FeT concentration was observed in GW (0.006 mg/L, i.e. near detection limit). Ferrous presumably dominated the Fe species in MW and NDT water samples due to the high FeT concentrations. For CPT and GW samples, Fe(ΙΙ) concentrations were below detection limits, with an exception of CPT 4 which had a FeT concentration of 0.02 mg/L (Fig. 3a).

Total dissolved Al (AlT) concentration ranged between 3.04 and 5.64 mg/L (average 4.7 mg/L), and between 1.77 and 2.57 mg/L in MW and NDT samples, respectively. Concentrations of AlT decreased to < 0.3 mg/L in CPT samples. No AlT could be detected in GW. Total dissolved Mn concentrations were generally higher in MW samples ( 2.00 to 5.36 mg/L, average 3.09 mg/L), as compared to those in NDT (2.14 to 2.61 mg/L, average 2.45 mg/L) and CPT (1.14 to 2.12 mg/L, average 1.63 mg/L) samples. Other trace element concentrations, including Pb, Zn, Sr, Rb, and U, all decreased substantially after the CPT procedure (Fig. 3b).

Aqueous REE+Y distribution patterns

Total concentrations of REE+Y (ΣREE+Y) in water samples are presented in Table S3. The ΣREE+Y concentrations ranged from 3.84 to 4.33 mg/L (average 4.11 mg/L), and from 1.67 to 2.97 mg/L (average 2.21 mg/L) in MW and DNT samples, respectively. These values were up to two orders of magnitude higher than the ΣREE+Y concentrations of CPT samples (0.07 to 0.19 mg/L, average 0.12 mg/L), and were more than three orders of magnitude higher than the ΣREE+Y concentrations in GW sample (5.3 μg/L, Fig. 3a).

Upper continental crust normalized REE+Y patterns were characterized by HREE enrichment over LREE and negative Ce (Ce/Ce* = CeUCC/(LaUCC × PrUCC) 0.5 ) (Fig. 4). The average normalized (Yb/Nd)UCC ratio (as a fractionation measure) was higher in CPT samples (10.23) as compared to MW (7.11), NDT (7.76), and GW (5.70) samples. The Ce anomaly was < 0.3 with an exception of GW (Ce/Ce* = 0.37) (Table S3). Positive Y anomaly ((Y/Ho)UCC) was observed in MW (1.14 to 1.53, average 1.29) and NDT (1.21 to 1.36, average 1.33) samples. Value of (Y/Ho)UCC was > 1.70 for CPT samples, and was 1.39 for the GW sample.

Modelling results

Free (REE 3+ ) and sulfate (REESO4 + ) complexes dominated lanthanide species in MW and NDT samples (Figs. 4b andd). The LREE tended more to be associated with SO4 2-, while the HREE were dominantly present as free ions. The average proportion of La occurring as REESO4 + was 48%, and 36% for Lu. Carbonate (REECO3 + and REE(CO3)2 -) and nitrate complexes (REENO3 + ) were < 5% in proportion of all lanthanide species. The lanthanides in CPT samples were calculated mainly in carbonate complex forms of REECO3 + and REE(CO3)2 -that accounted for 73% to 98% for La and 89% to 99% for Lu. Free ions made up 6% for La and < 1% for Lu (Fig. 4f). Lanthanides in the GW sample were predicted to occur as free ions, REECO3 + + REE(CO3)2 -, and REESO4 + . The proportions of these three species were predicted to be 49% to 79%, 5% to 34%, and 7% to 15%, respectively (Fig. 4h).

REENO3 + mostly accounted for < 2% of total lanthanide speciation. The other potential species, including hydroxyl and chloride complexes, were < 1% in the water samples.

Geochemical and mineralogical properties of solids

The rock samples were dominated by SiO2 (66 to 68 wt.-%), while Al2O3 was the second most abundant component (9 to 18 wt.-%), followed by Fe2O3 (4 to 7 wt. %) (Table S4). Composition of surface sediment samples ranged from 61 to 76 wt. % for SiO2, 10 to 3 wt. % for Al2O3, and 2 to 5 wt. % for Fe2O3. Other metal oxides were generally < 6 wt. %. For the sludge samples, SiO2 contents ranged from 60 to 67 wt. %, Al2O3 from 15 to 18 wt. %, and Fe2O3 from 3 to 12 wt. %. Other metal oxides were < 5 wt.%.

Contents of ΣREE+Y in sludge samples ranged between 0.80 mg/kg and 44.74 g/kg (average 19.95 g/kg). Those values were much higher than the ΣREE+Y contents of rock (0.33 to 0.85 g/kg, average 0.66 g/kg) and sediment samples (0.35 to 0.43 g/kg, average 0.39 g/kg) (Table S5). UCC-normalized REE+Y patterns showed that all samples were enriched in HREE relative to LREE and had negative Ce anomaly.

The (Yb/Nd)UCC values ranged from 6.14 to 9.14, from 3.51 to 5.83, and from 1.08 to 2.10 in sludge, sediment and rock samples, respectively (Table S5). Normalized REE+Y patterns of sludge and sediment samples showed an increasing upward trend from La to Sm, and a relatively flat trend from Tb to Lu (Fig. 5). On the other hand, REE+Y patterns for rock samples showed a slightly increasing trend with atomic numbers, indicating that a higher degree of HREE enrichment over LREE occurred for sludge and sediment samples as compared to rock samples. The Ce anomaly ranged from 0.18 to 0.63, and from 0.61 to 0.79, in sludge and sediment samples, respectively. Rock samples showed weakly negative Ce anomalies (Ce/Ce* ~0.98) (Table S5).

SEM imaging of filter residuals showed that the mine waters contained many suspended aggregate particles with diameters larger than 0.22 μm. This was more commonly observed in CPT samples as compared to MW samples (Fig. S1).

Sediment samples contained clastic textures on the surfaces with length <1 μm (Fig. S2). On the surfaces of sludge samples, needle-like and burr-like shapes occurred with shorter length than those observed in sediment samples (Fig. S2).

Results of XRD show that quartz (56% to 68%), muscovite (7% to 11%), kaolinite (8% to 14%), feldspar (both albite (NaAlSi3O8) and microcline (KAlSi3O8), 10% to 14%), schwertmannite (< 5%), and ferrihydrite (< 5%) were present in the sediment samples (Fig. S3). For sludge samples, quartz was determined to account for 27% to 47%, feldspar 10% to 27%, and schwertmannite 15% to 24%. Other minerals mostly showed contents < 5%.

Discussion

Geochemical characteristics

The average values of REE concentrations in the acid mine waters were several orders of magnitude higher than those in natural near-neutral waters [START_REF] Ayora | Recovery of rare earth elements and yttrium from passive-remediation systems of acid mine drainage[END_REF]. Specifically, the average total REE (ΣREE) concentrations in our samples (0.003 to 2.18 mg/L, average 0.94 mg/L) were comparable to the values reported by Liu et al. (2019a) (up to 10.86 mg/L, average 1.14 mg/L) found for the same study area. The MW samples showed higher ΣREE+Y concentrations than NDT, CPT and GW samples. With MW water moving downstream the processing line, ΣREE+Y concentrations decreased (Fig. 3a). Trends of Fe, Al, and Mn concentrations were similar to those of ΣREE+Y concentrations (Fig. 3a), indicating that REE+Y exhibited similar behavior to these metals. Indeed, the Fe, Al and Mn concentrations were positively correlated with ΣREE+Y concentrations, with correlation coefficients (r 2 ) of 0.61 (p < 0.01), 0.86 (p < 0.01), and 0.43 (p < 0.01) (Fig. 6a), respectively, indicating that REE+Y behaved more like Al than Mn or Fe. The positive correlation indicated intense leaching of these cations and a close association of REE+Y with Fe, Mn and Al in particulate phases [START_REF] Zhou | Rare earth element patterns in a Chinese stalagmite controlled by sources and scavenging from karst groundwater[END_REF].

Samples with higher ΣREE+Y concentrations also contained relatively higher SO4 2-and NO3 -concentrations (Table S2 andS3). Although a poor positive correlation was observed between SO4 2-and ΣREE+Y concentrations (r 2 = 0.18, p = 0.1) (Fig. 6a), the predominance of SO4 2-in total anions could be observed in MW samples (Fig. 2). This was largely due to the use of ammonium sulfate as an in-situ extractant for REE+Y mining (Liu et al., 2019b). Similarly, anthropogenic pumping of ammonium sulfate would account for the high NO3 -concentrations, and the relatively constant NO3 -concentrations in CPT samples demonstrated that nitrification reactions occurred under these conditions. It should be noted that, in addition to Fe, Al, Mn, SO4 2-and NO3, high concentrations of NH3-N (mostly >10 mg/L) were found to co-occur with REE+Y in AMD. The ΣREE+Y occurrence was therefore attributed to geochemical characteristics of source deposit as well as anthropogenic alterations.

Origin and mobility of REE+Y

Previous investigations of AMD suggested that REE+Y originated from leaching of acid soils (Åström, 2001). Other studies attributed REE+Y source to dissolution of REE+Y-bearing minerals in host rocks (Pé rez-López et al., 2010;[START_REF] Cá Novas | Release of technology critical metals during sulfide oxidation processes: the case of the Poderosa sulfide mine (south-west Spain)[END_REF][START_REF] Wallrich | Neodymium isotopes track sources of rare earth elements in acidic mine waters[END_REF]. The UCC-normalized REE+Y pattern similarity between acid leachate water and sediment indicates that REE+Y in AMD were derived from sediments directly (Fig. 5). The HREE enrichment in the rock samples suggested that the parent rock acted as the original REE+Y source for the clay-rich sediment layers leached by the acidic waters. Therefore, origin of REE+Y in the AMD highly depended on the REE+Y-bearing mineral phases in the bedrocks, and weathering of bedrocks and desorption from the weathering product minerals were a main pathway mobilizing REE+Y into mine water. The REE+Y would be initially mobilized naturally, when rainwater infiltrated underground [START_REF] Nesbitt | Mobility and fractionation of rare earth elements during weathering of a granodiorite[END_REF]. The acidic water in contact with the host rock led to a preferential dissolution of weathered minerals like feldspars [START_REF] Nordstrom | Hydrogeochemistry and microbiology of mine drainage: an update[END_REF]. Upon REE+Y being mobilized from the rocks, the majority of them were scavenged via ion exchange by clay-rich sediments/soils. A zone of soils/sediments was formed after weathering of rock crust in the study area, where igneous rocks, mainly composed of acidic granites, were exposed in a large area [START_REF] Yang | China's ion-adsorption rare earth resources, mining consequences and preservation[END_REF][START_REF] Chi | Prospect and development of weathered crust elution-deposited rare earth ore[END_REF]. The ion-exchanged REE+Y were readily desorbed from the sediments by acid leaching, where the acid extractant (ammonium sulfate) was injected into the soil/sediment layer. The coherent HREE-enriched patterns in all water samples indicated that the desorbed REE+Y were ultimately discharged into streams/creeks, and were transported in form of sulfate complexes and free ions until solution conditions became neutral or weakly alkaline as discussed below. Consequently, REE+Y compositions were originally derived from the parent rocks and were immobilized by sediments via sorption, and ion exchange might mobilize REE+Y into the aquifer and surface waters.

Control on REE+Y concentrations

Concentrations of REE+Y in the investigated acidic waters were controlled by the bulk solution chemistry and co-precipitation of secondary minerals. A negative correlation (r 2 = -0.72, p < 0.01) was observed between pH values and ΣREE+Y concentrations. The lowest pH occurring in MW favored leaching of REE+Y-containing minerals in sediment [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][START_REF] Worrall | Water-rock interaction in an acidic mine discharge as indicated by rare earth element patterns[END_REF][START_REF] Janssen | Geochemistry of some rare earth elements in groundwater, Vierlingsbeek, The Netherlands[END_REF]. This controlled REE+Y concentrations in the source areas, as reflected by high ΣREE+Y concentrations in MW and NDT samples where pH < 4.9 occurred (Fig. 3a). A decrease in ΣREE+Y concentrations in CPT samples was due to REE+Y scavenging via ion-exchange and/or adsorption by secondary minerals resulting from increased pH values (> 7.4). Similar decreasing trends of Fe, Mn, Al, and SO4 2-concentrations with MW water moving CPT indicated that Fe-, Mn-and Al-bearing minerals were possible secondary phases to scavenge REE+Y in CPT samples (Fig. 3a). Results of XRD supported that clay minerals (i.e. kaolinite), iron oxide (i.e. ferrihydrite), and schwertmannite were the potentially scavenging secondary minerals (Fig. S3). The dominant Fe species shifted from Fe(II) in MW and NDT samples to Fe(III) in CPT (Fig. 3a), suggesting that the formation of ferrihydrite and schwertmannite might occur following Eqs. ( 2) and (3):

4Fe 2+ + O2 + 10H2O = 4Fe(OH)3(s) + 8H + (2) 8FeSO4 + 2O2 + (4 + m)H2O = Fe8O8(OH)mSOn + (8-n)SO4 2-+2(8-n)H + (3)
These minerals have been suggested to be most commonly precipitated from AMD during neutralization processes (Lozano et al., 2020a).

The positive Y/Ho anomaly was a good indicator for the impact of sorption by solids on ΣREE+Y concentrations [START_REF] Tweed | Behavior of rare earth elements in groundwater during flow and mixing in fractured rock aquifers: An example from the Dandenong Ranges, southeast Australia[END_REF], as Y behaves differently from Ho during sorption, with Ho having greater affinities than Y for surface complex formation [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], and thus leads to fractionation between them [START_REF] Nozaki | Rare earth element sorption onto hydrous manganese oxide: A modeling study[END_REF][START_REF] Möller | Rare earth elements, yttrium and H, O, C, Sr, Nd and Pb isotope studies in mineral waters and corresponding rocks from NW-Bohemia, Czech Republic[END_REF]. The prevailing positive Y/Ho anomaly observed in water samples implied that sorption of REE+Y readily occurred during the neutralization processes (Table S3). Higher Y/Ho values found in CPT samples (1.70 to 1.81) as compared to MW (1.14 to 1.53) and NDT (1.21 to 1.36) samples was attributed to intensive sorption or/and co-precipitation of REE+Y in CPT samples. Indeed, ΣREE+Y concentrations were negatively correlated with Y/Ho values (r 2 = 0.66, p < 0.05), showing that low-pH conditions disfavored REE+Y sorption [START_REF] De Carlo | The influence of redox reactions on the uptake of dissolved Ce by suspended Fe and Mn oxide particles[END_REF]Liu et al., 2017b). Scavenging of REE+Y by schwertmannite (Lozano et al., 2020a, b) and Al oxyhydroxides (Ogawa et al., 2019) was recently investigated with different pH ranges. Additionally, changes of REE+Y concentrations might also be coupled to scavenging by Mn oxyhydroxides, with a sorption edge low to pH 4 and a complete REE+Y sorption at pH around 8 (Pourret and Davranche, 2013). However, Mn oxyhydroxides were not detected by XRD in the sludge samples of this study.

Therefore, REE+Y concentrations were mainly determined by acidification-enhanced dissolution/desorption/ion exchange from the sedimentary mine body by the acidic ammonium sulfate solution injected, and scavenging by secondary mineral precipitates upon neutralization treatment.

Control on REE+Y patterns

All water samples showed enrichments in HREE over LREE when normalized to UCC (Figs. 4a, c, e andg). This pattern has been reported also for AMD and AMD-impacted waters in solution mining for in-situ ion-exchange extraction of REE+Y [START_REF] Luo | Effects of colloidal particle size on the geochemical characteristics of REE in the water in southern Jiangxi province, China[END_REF]. As shown in Fig. 6b, REE+Y patterns of this study and other deposits [START_REF] Hao | Evaluation of water quality in surface water and shallow groundwater: a case study of a rare earth mining area in southern Jiangxi Province, China[END_REF][START_REF] Luo | Effects of colloidal particle size on the geochemical characteristics of REE in the water in southern Jiangxi province, China[END_REF] exploited by the acidic ion-exchange process in southern China were characterized by (La/Sm)UCC and

(Gd/Yb)UCC. Results showed that all investigated samples were in the quadrant with (La/Sm)UCC < 1 and (Gd/Yb)UCC <1 , suggesting HREE-enriched patterns (Fig. 6b).

These distribution patterns were thought to be mainly controlled by source sediment in this study. The possible mechanisms were addressed as follow.

The relatively flat UCC-normalized REE+Y pattern of rocks suggested that the host rock was not a direct cause for HREE enrichment in the acid mine waters. The clear resemblance between REE+Y patterns in sediment and those in the acid mine water indicated that the aqueous REE+Y patterns were probably controlled by the characteristics of the REE+Y sources. The pattern remained relatively constant irrespective of precipitation of secondary minerals with water processing. A model could be developed as to the formation of HREE enrichment pattern in the acid mine waters, which was that (i) thick zones of clay rich sediment/soil developed above the granites via weathering; (ii) the REE+Y originally mobilized by weathering were sorbed by the sediment layers, whereby a preferential accumulation of HREE by the sediments led to HREE enrichment (Aström, 2001); and (iii) the desorption of previously sorbed REE+Y into the mining solutions, giving rise to enrichments of HREE relative to LREEs in the acidic mine waters [START_REF] Leybourne | Rapid development of negative Ce anomalies in surface waters and contrasting ree patterns in groundwaters associated with Zn-Pb massive sulphide deposits[END_REF][START_REF] Migaszewski | Rare earth and trace element signatures for assessing an impact of rock mining and processing on the environment: Wiśniówka case study, south-central Poland[END_REF]. The desorption process was not expected to significantly fractionate REE+Y in the acid mine waters. This was because: (i) sulfate complex and free ion were the main solution species as indicated by speciation calculations (Fig. 5b), whereby the association of REE+Y with sulfate would not modify REE+Y patterns in aqueous solutions owing to the relatively constant REE+Y-sulfate formation constants [START_REF] Wilkin | Rare-earth elements as natural tracers for in situ remediation of groundwater[END_REF]; and (ii) REE+Y re-adsorption onto mineral phases was quite limited. This was due to the generally low pH values (<4) in the MW samples, where REE+Y behaved conservatively in spite of Fe and/or Mn oxyhydroxides present [START_REF] Verplanck | Rare earth element partitioning between hydrous ferric oxides and acid mine water during iron oxidation[END_REF]Pourret and Davranche, 2013).

The impact of Fe and Al oxyhydroxide scavenging on HREE enrichment might only be found for the CPT. The low pH values in MW and NDT samples (<4; except for NDT1) disfavor formation of Fe and Al oxyhydroxides (Ogawa et al., 2019). This was why coefficients of distribution of the REE+Y between Al/Fe oxyhydroxide solids and water showed a very weak increase across lanthanide series at pH of 6.3 to 6.8 (Lozano et al., 2020a). This suggested also that HREE fractionation during enrichment by adsorption or/and co-precipitation with Fe/Al oxyhydroxides was insignificant for this study.

Influence of solution complexation on HREE enrichment in CPT and GW samples was insufficient to significantly fractionate REE+Y in the MW and NDT samples. The most plausible ligand responsible for enrichment of HREE in CPT and GW samples would be CO3 2-, due to preferential stabilization of HREE relative to LREE during REE+Y-CO3 2-complexation [START_REF] Guo | Geochemical controls on arsenic and rare earth elements approximately along a groundwater flow path in the shallow aquifer of the Hetao Basin, Inner Mongolia[END_REF][START_REF] Liu | Geochemical behaviors of rare earth elements in groundwater along a flow path in the North China Plain[END_REF].

Although SO4 2-complexes and free ions were the dominating lanthanide species in MW and NDT samples (Fig. 4), SO4 2-was an almost equally strong complexant for all REE+Y [START_REF] Wood | The aqueous geochemistry of the rare-earth elements and yttrium: 2. Theoretical predictions of speciation in hydrothermal solutions to 350°C at saturation water vapor pressure[END_REF]. The possibility of HREE enrichment caused by other ligands including OH -, NO3 -, PO4 3--, F -and Cl -could be excluded either by their low speciation predicted by the model (Fig. 4) or by the preferential complexation of LREE.

Effect of organic matter on HREE enrichment in waters could be ruled out due to preferential complexation of MREE relative to LREE and HREE [START_REF] Wood | The aqueous geochemistry of the rare-earth elements: critical stability constants for complexes with simple carboxylic acids at 25°C and 1 bar and their application to nuclear waste management[END_REF][START_REF] Pourret | Rare earth elements complexation with humic acid[END_REF] and the low DOC concentrations (generally < 3.2 mg/L). The REE+Y were mostly truly dissolved in the acidic mine waters, and the particulates were less important to control the REE+Y fractionation patterns under pH<4 conditions (Olí as et al., 2018).

Cerium anomaly

A narrow range in Ce anomaly values (Ce/Ce*: 0.21 to 0.29) was observed for all water samples (Fig. 6d). regarding the Ce-H2O system showed that MW and NDT samples mostly were located in stability field of Ce(III), while CPT and GW sample in the stability field of CeO2 (Fig. 6c). This indicated that Ce initially occurred as free cation when mobilized from sediments, and it tended to be precipitated in form of CeO2 as pH increased and Eh decreased. In this respect, oxidative scavenging of Ce by Fe oxyhydroxides and/or Mn oxides due to co-precipitation of these secondary minerals might occur in CPT samples (Ohta and Kawabe, 2001;[START_REF] Takahashi | Chemical and structural control of the partitioning of Co, Ce, and Pb in marine ferromanganese oxides[END_REF]. However, this process could not be a dominant control on negative Ce anomaly formation, because the Ce/Ce* values in CPT samples were comparable to those of MW and NDT samples (Table S3), despite that Fe and Mn concentrations decreased substantially with acid mine waters downstream the processing line (Fig. 4a). Therefore, the negative Ce anomaly was suggested to be largely controlled by REE+Y sources in the sedimentary strata. A similar case was reported by [START_REF] Smedley | The geochemistry of rare earth elements in groundwater from the Carnmenellis area, southwest England[END_REF], showing that Ce anomaly in slightly acidic groundwaters (pH 5.0 -6.8) was related to rock aquifer as source. Biochar may server as a potential sorbent as well to immobilize these metals in aqueous solution where pH value is acidic (Pourret and Houben, 2018). To sum up,

the practical examples of REE+Y recovery from AMD render an environmental problem worthwhile as a source of raw materials, considering that alternative sources of REE+Y is warranted due to an ever increasing demand for these critical metals, particularly for the countries without primary deposits.

Conclusions

This study investigated the geochemistry of rare earth element (REE) and

  yttrium (REE+Y) in acid mine drainage from solution mining. Elevated concentrations of REE+Y were observed in the mine water with low pH. A progressive decrease in REE+Y concentrations occurred with MW flowing through nitrification-denitrification (NDT) and coagulating-precipitation treatment procedures (CPT). Negative correlation between REE+Y concentrations and pH values (r 2 = 0.72) indicated that REE+Y were primarily derived from an enhanced acidic desorption and ion exchange from minerals in the source area. The similarity of HREE-enriched patterns exhibited by AMD to those of source sediment indicated a major role of sediments in controlling REE+Y signatures of AMD. A preferential precipitation of LREE over HREE during the plant treatment process provided for a limited contribution to HREE enrichment in AMD, because the degree of HREE enrichment changed slightly and Ce remained relatively constant in MW, NDT, and CPT samples. Results of XRD and SEM examination indicate that clay minerals (i.e. kaolinite), iron oxides (i.e. ferrihydrite), muscovite, and secondary schwertmannite minerals were the main hosts of REE+Y. Therefore, HREE-enrichment patterns in AMD resulted from preferential desorption of HREE from sediment under the conditions of the in-situ leaching process at the mine site. Free ions and sulfate complexes, which dominated REE+Y species in MW and NTD samples, facilitated the transport of REE+Y and preserved REE+Y patterns during AMD flow. Carbonate complexation accounted for HREE enrichment as well in CPT and GW samples. Results of this study demonstrated significant potential for REE+Y recovery from AMD. acknowledge Dr. Michael Kersten for editing the manuscript in English and comments. Dr Wei Xiu is thanked for his suggestions and comments. Anonymous reviewers and Associate Editor Mae Sexauer Gustin are also acknowledged for their helpful comments. marine environment. Earth Planet. Sci. Lett. 148, 329-340. Ogawa, Y., Ishiyama, D., Shikazono, N., Iwane, K., Hoshino, T., Kajiwara, M., Tsuchiya, N., Saini-Eidukat, B. Wood, S. A. 2019. Fractionation of rare earth elements (REEs) and actinides (U and Th) originating from acid thermal water during artificial and natural neutralization processes of surface waters. Geochim. Cosmochim. Acta 249, 247-262. Ohta, A., Kawabe, I. 2001. REE(III) adsorption onto Mn dioxide and Fe oxyhydroxide: Ce(III) oxidation by Mn dioxide. Geochim. Cosmochim. Acta 65, 695-703. Olí as, M., Cá novas, C. R., Basallote, D. B., Lozano, A. 2018. Geochemical behaviour of rare earth elements (REE) along a river reach receiving inputs of acid mine drainage. Chem. Geol. 493, 468-477. Parkhurst, D.L., Appelo, C.A.J. 2013. Description of input and examples for PHREEQC version 3-a computer program for speciation, batch-reaction, one-dimensional transport, and inverse geochemical calculations. US geological survey techniques and methods, 6, 497. Pé rez-López, R., Delgado, J., Nieto J. M., Má rquez-Garcí a, B. 2010. Rare earth element geochemistry of sulphide weathering in the Sã o Domingos mine area (Iberian Pyrite Belt): a proxy for fluid-rock interaction and ancient mining pollution. Chem. Geol. 276: 29-4. Pourret, O., Houben, D. 2018. Characterization of metal binding sites onto biochar using rare earth elements as a fingerprint. Heliyon, 4, e00543.

Figure captions Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Figure 6

 captions123456 Figure captions

Fig. 2

 2 Fig. 2

  Fig. 3

  Fig. 5

Fig. 6

 6 Fig. 6

  The negative Ce anomaly was controlled by sedimentary REE+Y patterns, where negative Ce anomaly was evident (0.61 to 0.79). Oxidation of soluble Ce(III) to insoluble Ce(IV) that is precipitated as CeO2 and/or Ce(OH)4 has been recognized as a mechanism immobilizing Ce and resulting in negative Ce anomaly in aqueous solution. This process might have occurred when REE+Y either were initially weathered from host rock or were secondarily mobilized from sediments. The lower Ce/Ce* values in sediments than rocks supported the former to be a more plausible cause for negative Ce anomaly in the acid mine waters. It was unlikely that redox processes played a dominant role in the development of negative Ce anomalies over acid mine water flow, since Ce anomaly was relatively constant in all acid mine water samples despite variable redox conditions. Indeed, Eh-pH diagram

  It must be noted that the profitability of REE+Y recovery from AMD depends on the amounts in AMD, the cost of separation and extraction, and the proportion of HREE over LREE in the AMD[START_REF] Lé On | Mine waters as a secondary source of rare earth elements worldwide: the case of the Iberian Pyrite Belt[END_REF]. The high proportions of HREE found in AMD of this area renders recovery of REE+Y from the acid mine waters attractive, considering that HREE are more precious compared to LREE, and that they are largely restricted to South China. The availability of recovering REE+Y as well as other critical metals like Cu, Zn, and Ni from acid mine leachate and their neutralization precipitates were documented by[START_REF] Zhang | Process development for the recovery of rare earth elements and critical metals from an acid mine leachate[END_REF].[START_REF] Ayora | Recovery of rare earth elements and yttrium from passive-remediation systems of acid mine drainage[END_REF] studied the recovery of REE+Y from passive remediation systems of AMD

	4.6 Implication for REE+Y recovery from AMD
	Although AMD has been considered as an environmental concern globally due to
	its great hazard to ecosystems, it is a potential secondary source of REE+Y as well as
	coexisting metal elements, which are of economic interest, if appropriate control and
	treatment processes are implemented. Neutralization of mine water acidity constitutes
	a simple but promising option for recovering REE+Y from the acid waters. As shown
	in this study, REE+Y were efficiently sequestrated in CPT samples, where pH values
	were increased to > 7.4. Correspondingly, high levels of REE+Y were found in
	precipitate sludge samples, and their concentrations on the g/kg levels were higher
	than those of source sediments. The yield of REE+Y that were potentially recoverable
	from acid mine waters were calculated by the difference between loads of REE+Y in
	original acid mine waters and effluents of the treated mine waters. The loads of
	REE+Y were obtained by multiplying plant treatment capacity by the REE+Y
	concentrations in studied waters. Results showed that the recoverable ∑LREE and
	∑HREE ranged between 1.11 and 3.37 kg/day, and between 1.29 and 3.76 kg/day,
	contributing nearly equally between 34% and 38%, and between 38% and 42% of the
	total ∑REE+Y, respectively. The recoverable Y ranged between 0.79 and 2.35 kg/day
	(20% to 28%) (Fig. S4). The highest total recoverable value occurred at the location
	of MW5, which was nearest the inlet of the WTP (Fig. 1).

system with two mineral substrate -(schwertmannite and basaluminite) based treatments, showing that AMD remediation process serves as a suitable REE+Y source.

Acknowledgments

This investigation has been funded by National Natural Science Foundation of China (No. 41902243), Natural Science Foundation of Jiangxi province, China (20202BABL211018), and East China University of Technology Research Foundation for Advanced Talents (Nos. DHBK2019094 and SHT201901). We gratefully


domain: spi phys math info

text:
Elise Colin Koeniguer

Alexandre Mayerowitz

Nathan Letheule

Aurélien Plyer

THE DREAM DATABASE: A MULTIMODE DATABASE INCLUDING OPTICS, RADAR, DSM (SRTM) AND OSM LABELS FOR DEEP MACHINE LEARNING PURPOSES

Keywords: deep learning, database, radar, optical

This paper describes a multimodal remote sensing database, called DREAM (Data Rang or EArth Monitoring), developed from open-source data. The method of development of the database is described, as well as its specificity. The database includes radar, optical, rasterized Open Street Map datasets, and DEM data for two types of landscapes: France and the United States. Already used in deep learning multimodal data registration and in style transfer simulation, this database can also be used for classification, speckle filtering, and image quality improvement needs.

INTRODUCTION

Deep learning techniques are booming for many applications in the data processing. Remote sensing is one of the fields where deep learning could be useful, especially since the rise of open access data, for example, distributed by NASA or ESA. However, one of the main difficulties lies in the constitution of data sets, possibly annotated for supervised learning. Besides, access to multi-temporal or even multimodal data is spreading. The processing of this multimodality makes the constitution of databases more tricky: indeed, it is necessary to manage the problems of co-registration of multimodal data, with shared footprints and different tiling.

Within the framework of a project called AI4GEO, France is acquiring an automatic 3D geospatial information production capacity to meet several challenges for many booming sectors of activity, such as economic intelligence or urban planning. The availability of considerable volumes of satellite imagery data, supplemented by airborne or in situ data, now makes it possible to achieve controlled quality levels using new artificial intelligence and Big Data technologies.

In the framework of this project, we have developed a multimodal database. It contains both radar and optical images, OpenStreetMap vectorized data, and DEM data, useful for multiple purposes. The creation of open-access databases is becoming widespread: this approach favors benchmarks and the progression of the fiedl.

It is already in this state of mind that we have proposed the S12Flood [START_REF] Rambour | Flood detection in time series of optical and sar images[END_REF], MiniFrance [START_REF] Castillo-Navarro | Semi-Supervised Semantic Segmentation in Earth Observation: The MiniFrance suite, dataset analysis and multi-task network study[END_REF], and OSCD bases [START_REF] Daudt | Urban change detection for multispectral earth observation using convolutional neural networks[END_REF]. Among these databases, only the first one contains both optical and radar images. But these images are devoted to the specific flood detection application.

Recently, the SEN12MS [?] dataset contains patch triplets of corresponding Sentinel-1 dual-pol SAR data, Sentinel-2 multi-spectral images, and MODIS-derived land cover maps. The patches are distributed across the landmasses of the Earth and spread over all four meteorological seasons. This database is useful for data fusion and classification. In our case, the objective was a bit different, as we wanted to address applications-oriented on image quality improvement, for speckle co-registration or filtering, or on detection, rather than on information extraction. For these reasons, we did not keep the image calibration information. On the other hand, other information sources have been added, such as the Digital Surface Model from the Shuttle Radar Topography Mission (SRTM) or the radar images after speckle temporal filtering, which is not the case in the SEN12MS database.

Because of its particularity, we propose our database 'DREAM' in free access: [?].

In the following section, we present the description of the database, its specificity compared to other current databases. Then in Section 3, we will present a certain number of works that have been initiated on this base, in order to inspire future developments allowed by this database. Finally, we propose other application scenarios that could use this database in training.

DESCRIPTION OF THE DATABASE

Geographical Places

Two main sites have been chosen, with different landscapes: France and the USA. The first database was built in France from Copernicus data mainly, Sentinel 1 and Sentinel 2. The second database in the USA aims at a resolution range twice as high. It contains fully polarimetric L-band UAVSAR data and high-resolution RGB aerial data from the NAIP database. To these data, we have added the Sentinel 1 and Sentinel 2 images also available. We have split all images into different 1024 x 1024 pixel tiles within spread areas. Figure 1 displays the resulting areas in France. The flight paths of the UAVSAR images constrain the different areas for the USA, as shown in

Preparation of data in France

The tools used are the Google Earth Engine platform and the python GDAL package.

The Google Earth Engine (GEE) platform offers the possibility to download the data Sentinel-1 and 2, stored on Google's servers. The interest of this platform for the rapid development of S1 and S2 data is twofold :

-first of all, the platform allows access to S1 data delivered after the Terrain Correction. This Terrain Correction is essential to have the data in a cartographic repository similar to that of the other data. This Terrain Correction procedure based on DEM SRTM data takes a long time to apply to the data.

-The platform also allows the data to be downloaded on subareas without downloading the whole images.

-Finally, the intuitive functions offered also allow the selection of optics images according to their cloud cover.

To build the database, we launched queries to select Sentinel 1 and 2 data with the best possible overlap across France and no clouds in the case of Sentinel 2 data. The selected data are then downloaded only on the intersecting part.

On the other hand, we have chosen to download the temporally averaged S1 images over one year: this temporal filtering strongly reduces the speckle.

Finally, we have resampled the Sentinel-1 and -2 images at the same 10-meter resolution grid. We have added to the base the corresponding SRTM tiles.

rasterized OSM data

To these images have been added data from the Open-StreetMap data source. The database has been rasterized using the python module pyosm. This library aims to provide a way to extract objects from OpenStreetMap and rasterize those to match a given image as input. OpenStreetMap (OSM) is a collaborative project to create a free editable map of the world. OSM is considered a prominent example of volunteered geographic information.

Preparation of data in USA

The second database constituted is a base sampled at a better resolution (5m). The radar images are images from NASA's UAVSAR (Uninhabited Aerial Vehicle Synthetic Aperture Radar) program, which maps different regions using aircraftmounted radars. Optical images are from the National Agriculture Imagery Program (NAIP) of the U.S. Department of Agriculture. Radar data are represented in the polarimetric Pauli database, which to some extent makes it easier to interpret the images, with false colors that can be interpreted as in optics: the sea in blue, vegetation in green, cities in red/pink.

For two of these zones, we have intentionally chosen 3 overlapping passes, in order to have different polarimetric realizations of the same zone, the polarimetric effects varying with the orientation of the sensor heading.

The figure 3 give examples of the different patches for a given tile.

EXAMPLES OF USE CASES

We have initially developed this database to serve deep learning optical and SAR image co-registration algorithms. Then we used it to perform learning transfer between optical and radar images. We illustrate the first results of these applications in this section.

Coregistration

To use remote sensing data as geospatial data, it is necessary to georeference it. To do this, terrain correction for satellite images, and corrections related to trajectory uncertainties for airborne sensors, must be applied. In practice, the georeferencing of the data achieve mostly sufficient registration accuracy between Sentinel 1 and Sentinel 2 data. However, as soon as finer resolutions are addressed, the registration errors sometimes become significant, of the order of several pixels. To counter this problem, we have developed a multimodal resetting algorithm using optical flow.

The underlying idea is to take our Sentinel 1 and Sentinel 2 database, which we assume to be well coregistered, and to apply a synthetic deformation function generated by us to them. This deformation function is the target on which we are trying to teach a deep neuronal architecture. This idea has led to the development of a registration algorithm called PWCnet-mulimodal, which already gives promising results in terms of generalization to high-resolution data, and better than a previous dense coregistration algorithm, GeFolki, in terms of accuracy.

The figure 4 shows examples of optical flows trained on the French database (on the 10mx10m grid), and tested on other images of this same database, or an image of the USA database, with a 5mx5m grid. The diversity of the database's resolutions thus makes it possible to test the generalization capabilities of training models.

Transfer from optics to radar

Large amounts of multi-modal data can be used to learn a style transfer between an image from one modality to an image from another modality: this is the case for GAN-type architectures [START_REF] Fuentes | SAR-to-optical image translation based on conditional generative adversarial networks-Optimization, opportunities and limits[END_REF].

Initial results based on images in France have made it possible to simulate realistic SAR images from optical images.

Work is in progress: it is inspired by a pix2pix [START_REF] Leang | Image-to-image translation using identical-pair adversarial networks[END_REF] architecture: indeed, this "supervised" model fits for cases where two images of the same area are available. An example of first result is given on Fig. 5.

DISCUSSION

The proposed "DREAM" base is unique in terms of number of available modalities: optical, speckle filtered or unfiltered radar, OSM, and SRTM. Although several works have started concerning the exploitation of this base, we believe that many other applications are possible, in particular semantic segmentation based on the exploitation of OSM data, but also image quality improvement, via speckle filtering or the improvement of resolutions. We plan to further enrich the current database with maps of activity or change rates, and better-resolved optical aerial data over France.

Fig. 1 :

 1 Fig. 1: Caption

Fig. 3 :Fig. 4 :

 34 Fig. 3: Caption

Fig. 5 :

 5 Fig. 5: First results obtained by using the pix2pix architecture for generating a SAR-image from an optical one. Left: the optical image. Second : the SAR real one. Right: the generated one