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Article

Geochemistry and Mineralogy of Precipitates from Passive Treatment of Acid Mine Drainage: Implications for Future Management Strategies

by
Joaquín Delgado
1,*,
Olivia Lozano
1,
Diana Ayala
2,
Domingo Martín
1 and
Cinta Barba-Brioso
1
1
Department of Crystallography, Mineralogy and Agricultural Chemistry, University of Seville, 41071 Seville, Spain
2
Faculty of Engineering and Applied Sciences, University of Las Americas, UDLA Park, Quito 170124, Ecuador
*
Author to whom correspondence should be addressed.
Minerals 2025, 15(1), 15; https://doi.org/10.3390/min15010015
Submission received: 11 November 2024 / Revised: 23 December 2024 / Accepted: 24 December 2024 / Published: 26 December 2024
(This article belongs to the Special Issue Environmental Pollution and Assessment in Mining Areas)
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Abstract

:
Traditional mining activities in Zaruma-Portovelo (SE Ecuador) have led to high concentrations of pollutants in the Puyango River due to acid mine drainage (AMD) from abandoned waste. Dispersed alkaline substrate (DAS) passive treatment systems have shown efficacy in neutralizing acidity and retaining metals and sulfates in acidic waters, achieving near a 100% retention for Fe, Al, and Cu, over 70% for trace elements, and 25% for SO42−. However, significant solid residues are generated, requiring proper geochemical and mineralogical understanding for management. This study investigates the fractionation of elements in AMD precipitates. Results indicate that Fe3+ and Al3+ predominantly precipitate as low-crystallinity oxyhydroxysulfate minerals such as schwertmannite [Fe3+16(OHSO4)12–13O16·10–12H2O] and jarosite [KFe3+3(SO4)2(OH)6], which retain elements like As, Cr, Cu, Pb, and Zn through adsorption and co-precipitation processes. Sulfate removal occurs via salts like coquimbite [AlFe3(SO4)6(H2O)12·6H2O] and gypsum [CaSO4·2H2O]. Divalent metals are primarily removed through carbonate and bicarbonate phases, with minerals such as azurite [Cu(OH)2·2CuCO3], malachite [Cu2(CO3)(OH)2], rhodochrosite [MnCO3], and calcite [CaCO3]. Despite the effectiveness of DAS, leachates from the precipitates exceed regulatory thresholds for aquatic life protection, classifying them as hazardous and posing environmental risks. However, these residues offer opportunities for the recovery of valuable metals.

Graphical Abstract

1. Introduction

Acid mine drainage (AMD) is referred to as a water course with both high acidity and concentrations of metal(loid)s and sulfates [1] generated by the oxidative dissolution of metal sulfides in abandoned mining areas and uncontrolled tailing dumps. It is a major cause of hydrographic basin contamination [2]. AMD poses a worldwide concern in mining, creating extreme environmental impacts to be responsibly managed [3,4]. In this sense, several passive remediation techniques, including dispersed alkaline substrates (DAS) [4,5,6,7], have been designed to reduce their environmental impact. Passive treatments are currently growing for the restoration of abandoned mine areas since they do not require the continuous addition of reagents and need occasional maintenance with little energy consumption [8,9], resulting in an economical option for AMD remediation. These technologies, especially DAS, have been successfully applied in medium- and high-acidity waters with high metal loads, and they are widely developed despite problems of saturation or a decrease in effectiveness of the systems in the medium term [10,11,12,13,14].
While a significant amount of research has been dedicated to the occurrence and treatment of AMD, there has been limited investigation into the assessment and proper management of post-treatment residues of AMD. These treatments generate solid metal-rich residues or sludge (AMDp, acid mine drainage precipitates) that are also qualified as wastes [4,15]. These present high variability in chemical composition and physical properties depending on the AMD treated [16], making it difficult to control and predict their stability and environmental behavior. In fact, they could generate drainage themselves with negative environmental impacts if their storage conditions are non-stabilized. This demonstrates the importance of the proper management of the solid waste generated during the neutralization of AMD-polluted sources [17]. According to the literature, the recommendations to store the residues are very varied, but many authors agree that the residues are unstable and should be stored in a dry environment [15]. According to regulations, any contact with acidic or alkaline water and DAS residues must be avoided.
Standardized leaching tests are commonly used to characterize the potential release of contaminants from treatment wastes, such as the pH control leaching procedure (TCLP) or sequential extraction procedure (SEP), used increasingly by more researchers to understand the main processes in the mine waste environment: sulfide oxidation and the retention of mobilized elements by secondary minerals via sorption and/or coprecipitation processes [18,19,20]. In this sense, effective extractants and detailed studies of environmental conditions have been tested [21,22]. Additionally, according to Jouini et al. [17], metal bonds in Fe-rich AMD have still not been investigated enough in multi-step passive treatment methods, despite their importance in management strategies. These studies could allow the evaluation of various residues such as hazardous waste [15,16,17,18,19,20,21,22,23] as well as the establishment of the potential valorization of such metals from mining residues [12].
In this context, the aims of the present study were the following: (1) to gain a better understanding of trace metal cycles in environmental systems affected by AMD, with this objective being based on the detailed geochemical characterization of trace elements mobilized from the generated solid wastes (AMDp) in a laboratory passive multi-step treatment for Fe-rich AMD; and (2) to investigate mineral transformation and its influence on element fixation as a basis of future studies on waste reutilization and better management strategies for appropriate storage.

2. Study Area

Mining activities in southern Ecuador have impacted the Puyango River basin (Figure 1), a key watershed extending through southern Ecuador into northern Peru before flowing into the Pacific Ocean. The Puyango River flows through the Zaruma-Portovelo gold mining site (ZPMS), located atop the Paleozoic El Oro metamorphic complex and overlaid with Cretaceous volcanic rocks intruded by Cenozoic igneous complexes. Primary ores in the area contain gold and silver in quartz veins, along with sulfides like arsenopyrite [FeAsS], chalcopyrite [CuFeS2], galena [PbS], and sphalerite [ZnS].
In 2008, the Peruvian government raised concerns about contamination in the lower Puyango basin, referencing the 1971 Binational Convention. Since then, Ecuadorian authorities have undertaken remediation efforts, including constructing a community tailings facility. Nevertheless, substantial, unclassified volumes of mineralogically diverse mine waste continue to pose AMD risks, necessitating ongoing mitigation or remediation [24]. Also, approximately 100 small-scale processing plants in the Zaruma-Portovelo site [25] store tailings in dams near rivers or discharge them directly, promoting oxidation and generating potential AMD sources [26]. Several studies have documented the environmental effects of these mining operations on the Amarillo and Calera Rivers within the Puyango basin [27,28,29]. Furthermore, the climatic conditions of the basin (dry mega-thermal), characterized by high temperatures and precipitation variability (24 °C annual average, 500–2000 mm rainfall), promotes the oxidation of unmanaged waste dispersed along the riverbanks.

3. Materials and Methods

3.1. Experimental Design and Sampling

A reactive substrate system (Figure 1) combining calcium and magnesium DAS according to the conceptual model developed by Rötting and others [14,30] was implemented at the National Research Institute of Geology, Mining, and Metallurgy (INIGEMM) laboratories in Quito, Ecuador. AMD sources located in the ZPMS, selected for treatment, exhibited mean pH values of 2.7 and an electrical conductivity of 4.7 mS/cm, both indicative of high acidity (4361 mg/L eq as CaCO3 equivalents) and elevated concentrations of Al, Cd, Cu, Fe, Mn, Pb, Zn, and sulfates. The system operated at both low and high hydraulic flow rates for 8 months, proving high efficiency in increasing water’s pH and achieving approximately an 80% retention of Fe, Al, Mn, and trace elements. A complete description of the design, results, and hydrochemical model can be found in Delgado et al. [2,24].
The dissolution of limestone sand promotes protons’ decline in solution, which increases the pH and induces the formation of an “ochre” horizon in the first few centimeters of the column due to chemical shock, followed by a white horizon that may correspond to Fe and Al precipitates, respectively [2]. DAS-Ca alone is proved to be insufficient to remediate high concentrations of divalent metals such as Zn, Mn, Ni, and Cd derived from hydrochemical conditions [31,32,33]. For this reason, Rötting and collaborators [34] conducted laboratory experiments demonstrating that caustic magnesia [MgO] could be used to remove high concentrations of divalent metals from solution.
To evaluate the effectiveness of the acid water treatment, solids (AMDp) generated in the columns at various depths were sampled after the treatment. Five samples were taken from the DAS-Ca column located at depths of 3.5, 7.5, 8.5, 10, and 15 cm, while four samples were collected from the DAS-Mg column: two samples coinciding with superficial green–white precipitates and the other two at 1 and 12 cm depths (Figure 1).

3.2. Chemical Study

Total element concentrations were determined as the sum of 5 steps of the selected SEP [35]. Sequential extractions are widely used for exploration purposes and to study element speciation in natural environments (i.e., [36,37,38,39]) and gradually more in mine waste’s environments to understand trace metal mobility. In this study, changes were implemented to the ratio of the sample to the extractant volume and to experimental settings for high concentrations of iron oxides and oxyhydroxysulfates. Due to the presumable nature of the samples, this study was performed according to Caraballo et al. [35] and the schematic SE steps are summarized in Table 1.
Major and trace elements were determined in <0.2 μm extracted solutions by inductively coupled plasma–atomic emission spectroscopy (ICP-OES, model Optima 8300, Perkin Elmer, Waltham, MA, USA). The main key elements (Ag, Al, K, Mg, Mn, As, Be, Ca, Cd, Co, Cr, Cu, Mo, Na, Nb, Ni, Pb, Sn, Sr, and Zn) were reported. Calibration and accuracy controls were certified with ICP Multi-Element standard solutions from AccuStandard, SQS-01-1CRM, and SQS-02-R1-1CRM, according to EPA 200.7 and EPA 6010. Certified reference material (No. 1244) and inter-laboratory tests for trace metals (No. 586) (CRM-European Environmental Production) were measured as quality controls. Each step of the SEP was analyzed in triplicate, calculating the relative percentual difference (Equation (1)) among the replicates and the mean values. Most values were below the admissible value (5%), except for Ag, which stood at 10%.
%RPD = (S − D)/((S + D)/2) × 100
where S = the determined value of the samples and D = the value of the duplicates.
The internal recovery of this SEP was assessed by comparing the sum of each metal in the five fractions with its acid-digested concentration, in percentages. The recovery rates for Al, Zn, Cu, Fe, and Mn ranged from 102.2% to 97.3%, 91.6% to 105.8%, 90.8% to 109.0%, 90.0% to 109.0%, and 91.4% to 107.4%, respectively. The recovery percentages for Cu and Zn in the Mg-1 sample were high, probably due to inherent errors in the SEP method, since through acid attack for the extraction of the sorbed and exchangeable fraction (F2), the elements associated with poorly ordered Fe3+ or hydroxide precipitates could also be released, adding excess values to the measurement.

3.3. Mineralogical Characterization

X-ray diffraction (XRD) measurements were performed with a Panalytical Empyrean diffractometer (Malvern Panalytical, Malvern, UK) with Cu-Kα radiation at 40 kV and 20 mA. A step size of 0.008° 2θ was used in the range of 5–80°, and a step time of 0.5 s/step was set. The software used for mineral identification were EVA v16.0 (Bruker-AXS) and Match! v3.15 (Crystal Impact), and the BGMN/Profex v4.8 for Rietveld refinement was employed. Structure models for Rietveld analysis were selected based on the Powder Diffraction File and from the Crystallography Open Database. The crystallinity order of the analyzed samples was calculated using the software Diffract.Eva v4.1 (Bruker-AXS). This crystallinity order represented the proportion of crystalline material in the samples, as indicated by the total integrated areas of the full pattern. In samples with higher crystallinity, the control refinement fit values (such as discrepancy values, χ2, and agreement factors R, Rwp, Rexp and RB) were satisfactory. However, in samples with lower crystallinity and poor-quality data, these values were higher. This was why, due to the low crystallinity of some minerals, the percentages of the mineral phases were semi-quantitative.
Selected samples were studied using a Tescan-MIRA 3 (Kohoutovice, Brno, Czech Republic) scanning electron microscope (SEM) operating with an accelerating voltage of 25 kV. Compositional information was extracted by back-scattered electron (BSE) imaging and energy-dispersive X-ray (EDX) microanalysis (Link ISIS system). The samples were coated with a sputtering Quorum-Q150R ES with gold–platinum.

4. Results and Discussion

4.1. Metal Partition from AMD to Solid Phases

During AMD treatment, the gradual increase in the pH along the DAS-Ca column led to the development of an “ochre horizon” in the upper centimeters of the solid residue, followed by the formation of a “white horizon” (Figure 2a). The chemical conditions developed along the column triggered Fe depletion from the solution, probably forming low-crystalline oxyhydroxides or oxy-hydroxysulfates such as H-jarosite [H3O)Fe3(SO4)2(OH)6], K-jarosite [KFe3(SO4)2(OH)6], schwertmannite [Fe8O8(OH)6(SO4)], ferrihydrite [Fe(OH)3], hematite [α-Fe2O3], goethite [α-FeOOH], lepidocrocite [γ-FeOOH], and maghemite [γ-Fe2O3] [2].
Indeed, the “ochre horizon” (Figure 3a) exhibited the highest concentrations of Fe, with retention rates exceeding 90% (Ca1; 336 g/kg) and 80% (Ca3; 149 g/kg) of the total metal content (Figure 3a; Table 2), as confirmed by the corresponding visual observations.
The SEP data of the surficial sample, Ca1, indicated the presence of high concentrations of Ca (760 mg/kg). In addition, Ca increased at greater depths, so Ca3 was present in 17 g/kg, associated with the labile fraction of the residues (Figure 3b and Figure 3d, respectively). Furthermore, in the exchangeable fraction (F2), the release of low-crystalline iron hydroxide seemed evident, along with weakly adsorbed trace elements onto these compounds, as previously described by other authors [40]. The presence of iron and trace metals in the F2 of sample Ca1 (Figure 3b) endorsed this interpretation.
The movement of trace elements from solution to solid Fe-Al phases involves adsorption and/or coprecipitation mechanisms. Research on ochre-like deposits rich in iron in acidic conditions indicates that jarosite and schwertmannite may have the greatest amounts of As and Cr [41], as well as other metals like Cu, Pb, and Zn [42]. Furthermore, ferrihydrite appears to be related to high concentrations of Pb and relatively high contents of Zn and Ni [43]. In this regard, the main concentration of As was related to the higher concentrations of Fe and K in the Ca1 and Ca3 samples (Figure 3b,d), presumably associated with schwertmannite and jarosite. Contrary to expectations, although significant concentrations of As, Cu, and Pb associated with fractions F3 and F4 (involving Fe(III) oxyhydroxides and oxyhydroxysulfates) were leached, concentrations of up to 2536 mg/kg of As (Ca1 sample) were extracted from F2, the fraction associated with carbonates (Figure 3b). This could be attributed to the dissolution of amorphous or disordered Fe(III) precipitates, along with the release of adsorbed elements such as As, Cu, Mn, and Zn, induced by the exposure to acetic acid at a pH of 4.5 within the F2 fraction. Additionally, excluding the samples from DAS-Mg, the trace metals Cu, Cd, Pb, and Zn showed considerable concentrations associated with this section of the iron profile (up to 105, 38.1, 27.7, and 42.2 mg/kg, respectively), confirming the link between Fe-rich mineral phases and trace elements’ retention.
The deeper ‘white horizon’ likely corresponded to Al precipitates formed when the pH increased, as described by Rötting et al. [14]. This was confirmed by the higher Al concentration throughout the column, with the highest value (56 g/kg) present in sample Ca4 (Table 2). According to Macías et al. [15], aluminum may be trapped as hydroxides or hydroxysulfates in white precipitates, which were mainly concentrated in sample Ca4, as shown in Figure 2a. The high Al concentrations extracted in F3 and F4 confirmed the dissolution of Al-rich sulfate phases such as alunite [KAl3(SO4)2(OH)6], basaluminite [Al4(SO4)(OH)10·5(H2O)], jurbanite [Al(SO4)(OH)·5(H2O)], or Al-hydroxides [Al(OH)3(am), gibbsite Al(OH)3, boehmite γ-AlO(OH), and diaspore AlO(OH)] that would be important as the pH rises above 6 [25,44,45]. Furthermore, the presence of alunite could be elucidated by considering the relative concentration of potassium in this profile section. These precipitates frequently contained gypsum (confirmed by the high concentration of Ca associated with the F1 fraction, Figure 3c,e). Furthermore, based on the hydrochemical model developed by Delgado et al. [2], the dominant aqueous species (AlSO4+, Al(OH)2+, and AlOH2+) and the pH range between 5.8 and 6.4 in these sections of the profile were consistent with the precipitation of Al phases.
Elevated concentrations of Al, Cu, and Ca and low Fe concentrations were measured in sample Ca2 (30 g/kg). This can be attributed to the significant dissolution of the calcium substrate and unexpected local alkaline conditions indicated by the presence of green precipitates in the “ochre horizon” of DAS-Ca (Figure 2c). AMDp are commonly associated with the precipitation of divalent metal hydroxides, as described by Cortina et al. [32], when the pH reaches neutral-to-alkaline conditions. This supports the high concentrations of Al (43 g/kg), Cu (42 g/kg), Mg (1300 mg/kg), Mn (1223 mg/kg), and Zn (3860 mg/kg) at this depth (Ca2) of the profile.
It is noted that the neutral conditions obtained in the final section of the DAS-Ca are typically insufficient for the formation of divalent metal hydroxides [32]. According to Baes and Mesler [46], divalent metals are most effectively retained by hydroxides at a pH between 8 and 10. Based on these premises, the presence of high concentration of Ca in the final section of DAS-Ca (F2 of samples Ca4 and Ca5, Figure 3) added to the addition of alkalinity by the magnesia dissolved in DAS-Mg (supported by the presence of Mg in F1 of Ca5) appear to provide an ideal scenario for divalent metal retention. However, the control over the fractionation of divalent metals appeared to be mainly exerted by carbonate phases [2]. These conditions were obtained towards the end of DAS-Ca (sample Ca5) and were accompanied by significant concentrations of Ca, Mg, Cu, or Fe (until 231, 2.3, 9.4, and 1.7 g/kg, respectively) associated with the exchangeable phase (Figure 3f). Additionally, the fractionation of divalent elements in this zone of the profile seemed to be somehow influenced by the availability of aluminum, with these phases extracted in F3 of the SEP, as previously suggested by Caraballo et al. [35].
The samples Mg1 and Mg2 exhibited the highest concentrations of Cd, Co, Cu, Ni, Pb, and Zn (Table 2 and Figure 3g,h). The DAS-Mg hydrochemical model suggested that primary carbonate species in water quickly disappeared upon entering the DAS-Mg column due to the formation of carbonate minerals like malachite, azurite, and, to a lesser extent, smithsonite [ZnCO3·1H2O] [2]. These findings align with the results observed in the experimental columns, where the highest Cu and Zn retentions (900 and 516 g/kg, respectively) were linked to sample Mg1 (exchangeable fraction, Figure 3g). This was supported by a bluish-green color change in the precipitates at the DAS-Mg surface. Additionally, most Zn partitioning from the solution to the solid phase occurred in the final section of DAS-Mg, with Mg1 (around 40%) and Mg2 (80%) being the most significant (Figure 3a). In calcareous settings with high levels of divalent metals (like the DAS-Mg column), the amount of these metals in water (including Cd and Mn) is typically controlled by the precipitation of solid metal–carbonate compounds [47,48,49]. In fact, Zn and Mn showed a clear association with the carbonate fraction of the AMDp. While Cd showed some association with the water-soluble fraction along with Co (894 and 1360 mg/kg, respectively), its higher concentrations (3558 and 3202 mg/kg) were linked to the F2 fraction (Figure 3h). Other divalent metals, such as Ni and Cr, exhibited similar behavior, showing higher concentrations in the F2 fraction, particularly in the final stage of the treatment (e.g., Ni reached 1878 mg/kg in F2, Figure 3h).

4.2. DAS Mineralogical Assemblages

In the diffraction pattern of the surficial sample of DAS-Ca (Ca1), the presence of amorphous and low-crystalline phases required background subtraction so that the peaks of some minerals became evident (Figure 4a).
In the “iron profile”, the precipitation of the first oxyhydroxysulfates, such as schwertmannite and jarosite, could trap toxic elements like As, Cr, Cu, Pb, and Zn from the solution [41,42]. According to Hudson-Edwards et al. [50], these are the controlling phases at low pH values. Observations by SEM-EDS showed a clear association between S and Al-Fe and the dissemination of As and Pb trapped in this column’s section (Figure 5a). Other sulfate species could play an important role here, depending on the availability of certain elements in the solution. The high proportion of Fe3+ in solution could lead to coquimbite (Fe33+(SO4)3·9H2O) formation, and if the water contained more than 1500 mg/L sulfate, the presence of gypsum was expected due to the dissolution of the reactive calcium across the substrate. Based on phosphate concentrations and the hydrochemical model reported by Delgado et al. [2,26], brushite [Ca(PO3OH)·2H2O] could form in AMD neutralization processes, as suggested by the XRD data (Figure 4a and Table 3). This phase has been described by other authors under similar pH conditions during wetland restoration treatments. Furthermore, the model indicated the possible presence of other Fe (strengite, FePO4) and lanthanide (monazite, La, Ce(PO4)) phases at a low pH that could not be detected with the applied methods.
Sample Ca2 (Figure S1, Supplementary Data) was dominated by amorphous phases but also presented calcite and gypsum, which accounted 54% and 45% of the crystalline phases, respectively (Table 3). This sample corresponded to a zone of the profile where the nature of the alkaline reagent could be observed. However, the relatively high concentration of Cu, Zn (Figure 3c), and gypsum (rhombohedral) in this section seemed to be a consequence of the beginning neutralization processes [51,52], as evidenced by the green–white color of the precipitates. In fact, the SEM images confirmed the presence of some Al-hydroxide amorphous precipitates and discrete Cu carbonated phases. The low presence of Fe associated with S and Al could explain the commonly described substitution of Fe to Al in the jarosite–alunite group [53,54] as the pH increased (Figure 5b,c).
Likewise, in the Ca1 sample, the background of Ca3 (8.5 cm-deep profile) was subtracted to improve the identification of mineral phases. The results, consistent with the modeled hydrochemical data [2], pointed to the presence of schwertmannite (5.8%) and jarosite (6.9%), with presence of plumbojarosite [Pb0.5Fe33+(SO4)2(OH)6] (Figure S2). Although distinguishing among these phases is challenging [41], these results were also checked with the chemical data (Table 2). In this case, a preferential retention of Pb could be observed, supporting the XRD interpretations. Regarding trace elements, the SEP results (F3 and F4 SEP extractant) and potassium distribution among the fractions could indicate a relative affinity between both As–schwertmannite and Cu–jarosite.
Table 3. Semiquantitative results made by Rietveld showing the grade of crystallinity of the samples and chi^-2GOF obtained before analysis. The XRD pattern and identification peak can be seen in the Supplementary Figures S1–S6. Trace percentage in red font (<1%). Mineral symbols are according to IMA–CNMNC [55].
Table 3. Semiquantitative results made by Rietveld showing the grade of crystallinity of the samples and chi^-2GOF obtained before analysis. The XRD pattern and identification peak can be seen in the Supplementary Figures S1–S6. Trace percentage in red font (<1%). Mineral symbols are according to IMA–CNMNC [55].
DAS—CaDAS—MgDrain
Mineral PhasesSAMPLECa1Ca2Ca3Ca4Ca5Mg1Mg2Pindo
Boehmiteγ-AlO(OH) Bhm--3.4-----
BrushiteCa(PO3OH)·2H2O Bsh9.5-5.9-----
CalciteCaCO3 Cal 54.5 51.685.6-59.2-
CoquimbiteAlFe3(SO4)6(H2O)12·6H2O Coq22.1- -----
DiasporeAlO(OH) Dsp - 1.2----
DolomiteCa, Mg(CO3)2 Dol - 3.0-42.9--
GypsumCaSO4 Gp2.445.574.144.213.72.0--
JarositeKFe3+3(SO4)2(OH)6 Jrs14.7-6.9-----
MelanteriteFe2+(H2O)6SO4·H2O Mln -4.0-----
QuartzSiO2 Qtz15.9- -0.71.90.672.0
SchwertmanniteFe3+16(OH,SO4)12-13O16·10-12H2O Swm35.4-5.8-----
AragoniteCaCO3 Arg------34.1-
Aurichalcite(Zn,Cu)5(CO3)2(OH)6 Ach-----11.6--
BruciteMg(OH)2 Brc------1.1-
Azurite/MalachiteCu(OH)2·2(CuCO3) Azu/Cu2(CO3)(OH)2 Mlc-----24.2--
MonohydrocalciteCaCO3·H2O Mhcal-----1.9--
RhodochrositeMnCO3 Rds-----9.12.0-
SideriteFeCO3 Sd-----6.53.1-
AlbiteNa(AlSi3O8) Ab-------8.7
Chlorite(Mg,Fe)3(Si,Al)4O10(OH)2(Mg,Fe)3(OH)6 Chl-------4.0
MagnetiteFe2+Fe3+2O4 Mag-------1.0
MicroclineK(AlSi3O8) Mcc-------1.5
MicaK(Mg,Fe)3AlSi3O10(OH, F)2 Mca-------11.9
OrthoclaseK(AlSi3O8) Or-------1.0
Total100.02100.00100.00100.00100.01100.00100.00100.01
% Crystallinity7.4388.111.689.190.556.378.789.2
chi^218.82.1213.63.274.111.563.971.41
GOF4.341.453.691.812.031.251.991.19
Additionally, other sulfate phases such as melanterite (FeSO4·7H2O; 4%), gypsum (74%), or phosphates like brushite (5.9%) were linked to Fe and Ca reactivity in this section. The hydrochemistry of the water column in Ca3 and deeper strata suggested that Fe di-sulfate species were leading [FeSO4+ (73%) and Fe (SO4)2− (14%)], supporting the formation of melanterite, which would increase the proportion of hydrolyzed species, promoting the precipitation of saturated Fe phases like schwertmannite and jarosite [52].
On the other hand, in this profile position, a low 2θ crest seemed to indicate the presence of Al phases like boehmite (3.4%, Table 3). According to the hydrochemical model and in line with the data described by Sánchez-España et al. [41], at pH values greater than 4 (10 cm depth), the presence of Al oxyhydroxides (alunite and basaluminite, among others) could be expected. As previously outlined, the substitution of Fe by Al became more noticeable in this section of the profile (Figure 5c). In fact, the SEM data allowed the distinction of a common pattern of distribution for Al, S, and Mg (Figure 5d), which could imply the presence of other sulfate phases such as epsomite (MgSO4·7H2O) or pickeringite (MgAl2(SO4)4·22H2O). Although their presence could not be confirmed, the SEP data also supported this argument, as significant concentrations of Mg (280 mg/kg) associated with the labile fraction (F1) could be observed.
The samples at the depths of Ca4 and Ca5 did not show more Al-rich phases, except for the presence of diaspore, but this was in a low proportion (1.15% of the crystalline phases in sample Ca4). Both samples were characterized by the high presence of calcite from the reactive substrate, higher than 50% (Table 3, Figures S3 and S4). Additionally, the Ca4 sample showed representative amounts of gypsum (44%) and dolomite [CaMg(CO3)2; 3%], probably derived from the pH increase that could also promote the precipitation of these carbonate-type divalent metal phases in presence of high Mg concentrations [2]. Calcite and gypsum were the most frequent phases in the final section of DAS-Ca and in the DAS-Mg column (Table 3), due to the large amount of reactive calcium available (evidenced by the high proportion in sample Ca5, Figure 5e). In fact, the SEM study of the surface precipitates in the DAS-Mg column suggested that the white aggregates (Mg-SB) were essentially composed of gypsum (Figure 6a), while the green–blue ones (Mg-SV) also exhibited a nanocrystalline lattice composed of Fe, Cu, and C (Figure 6b). XRD suggested that this grid was composed of metal(II) hydroxide carbonate minerals (rosasite group, including malachite-Cu) and siderite [Fe2+(CO3)].
Under the conditions of the DAS-Mg column with a pH > 6, newly formed carbonate and bicarbonate phases could play an important role in removing divalent metals from the solution [2]. The presence of dolomite in this section was explained by the dissolution of the reactive magnesia in DAS-Mg. Thus, monohydrocalcite [CaCO3·(H2O)], malachite, azurite, siderite, and rhodochrosite [MnCO3] were identified (Table 3). The efficient removal of Cu and Mn within the initial centimeters of DAS-Mg (Mg1, Figure 4b) was evident, so subspherical Cu-C aggregates could be recognized by the SEM (Figure 6c).
Although iron chemistry is typically broad in more acidic environments (e.g., DAS-Ca), small amounts of available Fe were associated with the carbonate group as a divalent metal and precipitated as siderite (Figure 4b and Figure S5; Table 3), representing 6.5% and 3.1% of the crystalline phases in samples Mg1 and Mg2, respectively. The SEP results clearly revealed high concentrations of Cu, Fe, Mn, and Zn in DAS-Mg (Figure 3g,h), associated with the carbonate system (F2). Additionally, based on the hydrochemical data of these environments (high Mn concentrations) and the mineralogical interpretations of the DAS-Mg samples, the presence of rhodochrosite could be confirmed (Figure 4b and Figure S5; 9% and 2% of Mg1 and Mg2, respectively).
According to Cortina et al. [32], metal hydroxides rapidly precipitate in these experiments, while sulfates precipitate more slowly and progressively. Although the literature suggests the presence of brucite [Mg(OH)2], it only appeared in a negligible proportion (1.1% of the total crystalline phases of sample Mg2, Figure S5) in the deepest part of the Mg column. However, the SEM data demonstrated the presence of Na and Mg, associated with the formation of small-sized spherical aggregates (Figure 6d). This was also supported by the concentration of Mg and Na determined in F1 of the DAS-Mg samples (Figure 3g,h), which evidenced that carbonate-type divalent metal phases played an important role in the partition processes between AMD and solids in the final section of the treatment [2].
Moreover, the alkaline conditions facilitated the saturation of carbonated phases, such as calcite or dolomite, which could be recognized as subspherical aggregates of Ca-Mg, displaying the same compositional pattern as C (Figure 6d). These phases could play a role in coprecipitation–sorption processes, influencing the solubility of Zn, Mn, and other trace elements [56]. In fact, higher Zn and Mn concentrations were associated with F2 of the Mg1 and Mg2 samples (516 and 465 g/kg of Zn and 13 and 75 g/kg of Mn, respectively). The data revealed that Zn was the divalent metal whose partition towards the solid phase occurred in the late stages of the treatment (DAS-Mg), but it was depleted by carbonate mineral phases such as aurichalcite [(Zn, Cu+2)5 (CO3)2·(OH)6] (7% in the Mg2 samples). The SEP data showed that 516 g/kg of Zn and 906 g/Kg of Cu were trapped in the carbonated phases (F2) of the Mg1 sample, supporting this assumption.
On the other hand, due to the high availability of sulfate hydroxides, newly formed phases linked to divalent metals such as brochantite [Cu4SO4(OH)6], antlerite [(Cu+2)3SO4(OH)4], goslarite [ZnSO4·7H2O], and anglesite [PbSO4], among others, are frequently described [47]. However, the mineralogical characterization of the samples was consistent with the hydrochemical model (Figure 4b in [2]) that showed the low depletion of aqueous sulphated phases in the final section of the treatment. While hydrated sulfates are frequently described as the main controlling factor in the partitioning process of divalent metals such as Cu, Zn, or even Fe [57], no sulfate phases involving these elements were identified in the samples of the present study.
Finally, the bottom sample of the treatment (“Arenas del Pindo”—sandy drainage; Table 3 and Figure S6) was characterized by the presence of quartz (72%), albite (8.7%), K-feldspar (microcline–orthoclase, 2.5%), and phyllosilicates (mainly biotite, 12%, and chlorite, 4% of the total). This mineralogy explains the presence of crystalline quartz in some samples such as Ca1 or Mg2, which probably accidentally transferred along the samples during the columns’ opening process.

4.3. Possible Environmental Implication of Residues’ Management

The SEP method is commonly used to evaluate the potential mobility of pollutants under various simulated environmental conditions. In this study, an improved SEP [35] was applied to assess the leaching behavior of PTEs from AMDp across different weathering scenarios (Figure 7), and the results were compared with the continuous concentration criterion (CCC) limits established by the European Community’s recommended water quality standards [58]. This value represents a potential negative effect for aquatic life when uncontrolled leachates are generated from the inappropriate disposal of AMDp. The proposed scenarios were as follows. Scenario 1: the contact of the residue with rainwater (emulated by the F1 SEP fraction), which may occur in uncovered disposal facilities and is considered highly dangerous to the environment according to regulations [59]. Scenario 2: Interaction between the residue and weak acidic leachates under reducing conditions (F1 + F2 fraction). These conditions are relevant to scenarios such as underground disposal facilities. Scenario 3: The exposure of residues to weak acidic leachates in oxidizing environments (F1 + F3 + F4 fraction). These conditions aimed to simulate disposal scenarios in surface impoundments or waste piles, as has been previously described by [12].
The data suggest that, although some samples may have occasionally fallen below the CCC limit, when the resulting whole-body residue from any DAS system is disposed of, it could pose danger to aquatic ecosystems and the life associated with them. In scenario 1 (exposure to rainfall), Pb, Zn, Al, and Fe exceeded the proposed values for DAS-Ca, while Cd, Cr, Zn, and Fe behaved similarly for DAS-Mg. For the rest of the more aggressive conditions, scenario 2 (underground disposal) and scenario 3 (surface impoundments or waste piles), the AMD residues generated leachates that surpassed the threshold for most of the elements studied, making them incompatible with aquatic life. In this regard, these metal-rich residues from passive treatments (both laboratory-scale and field-scale), when stored in an oxidizing environment, demonstrated the significant leaching of metals and sulfates [60,61,62]. Several studies have shown that residues from Fe-rich AMD are unstable and have a high risk of leaching. They should be stored underwater or in a neutral-pH environment to prevent contamination release and ensure safe disposal [5,6]. Meanwhile, specific studies on MgO-DAS also recommend storing them in a dry (not mixed with acidic or alkaline water) environment [15]. More recent studies suggest that, in addition to being stored under anoxic conditions in the presence of water to prevent the formation of new AMD, these residues should undergo stabilization/solidification before any storage [8].
In addition, Table 4 presents the regulatory limits for waste acceptance at landfills in the EU [59] in comparison to the concentrations of elements detected in AMDp (DAS-Ca and DAS-Mg) following the F1 leaching fraction. This fraction denotes the metals and metalloids capable of mobilization upon contact with water and those that are considered the leaching limit values to be applied to waste for storage in the three types of landfills proposed by the Royal Decree 646/2020 [63], under the auspices of EU regulation [59].
According to the results obtained, the DAS-Ca residues would be classified as hazardous since the concentration of Zn (104 mg/kg) exceeded the reference value, while Cu (50 mg/kg) and Pb (10 mg/kg) were at the limit value. Meanwhile, the precipitates of the DAS-Mg would pose storage issues in landfills due to the excessive leached concentrations of Cd (901), Cu (164), and Zn (206 mg/kg).
Under these circumstances, the EU regulation [59] recommends additional treatment (such as further neutralization, encapsulation, etc.) before the storage of these materials in any type of regulated landfill. Also, recent directives have established and emphasized, in general terms, the necessity of subjecting waste destined for landfills to appropriate pretreatment [63], considered an essential requirement to ensure that landfill operations are conducted without endangering human health and the environment. Additionally, in accordance with the circularity principle, it is important to note that these treatments generate metal-rich solid residues considered generally hazardous wastes, but they can also present an opportunity for the potential recovery of metals and other critical elements [60,64,65]. In this regard, the European Regional Development Fund (FEDER, 2021–2027) aims to enhance these efforts by fostering the transition to a circular and resource-efficient economy (Raw Materials Initiative) through the generation of added value from waste. This initiative contributes to reducing the amount of waste sent to landfills and conserving natural resources by promoting reuse and recycling.

5. Conclusions

The mineralogy of solid residues from the DAS system experience with Ecuadorian AMD was consistent with the basic principles of metal retention from acidic solutions and helped the interpretation of the geochemical results and modelling. Elements like Fe and Al were retained in the DAS-Ca column, while most divalent metals fractionated towards the solid phase in DAS-Mg.
Among the minerals that retained Fe3+ and Al3+, oxyhydroxysulfates such as schwertmannite and the jarosite–alunite group were primarily responsible for their fractionation towards the solid phase. In this process of mineral formation, other trace elements with diverse charges were retained through adsorption–coprecipitation mechanisms (As, Cr, Cu, Pb, and Zn). Additionally, sulfated efflorescent salts such as coquimbite and gypsum were responsible for removing sulfate from the solution.
The fractionation of divalent metals (Cu, Zn, and Mn) predominantly occurred in the DAS-Mg column, and it was controlled by the formation of carbonated phases (identified through XRD and SEM studies). In the initial stages of DAS-Mg, phases rich in Cu-Zn from the azurite–malachite group were abundantly formed, while other discrete phases such as rhodochrosite (Mn) appeared accompanying neoformed calcite, monohydrocalcite, and dolomite when the Mg supply increased in the column. Hydroxides of divalent metals have frequently been described as the main mechanism for controlling metal loads in passive treatment systems of the DAS type; however, although they were not absent, the results of this study suggest that newly formed carbonate and bicarbonate phases were the most evident neutralization mechanism trapping the metallic charge. This result confirms the initial hypothesis of the metal fractionation processes according to the hydrochemical model proposed by [2], highlighting the key role of carbonates in removing divalent metals from AMD solution.
The leachates from the SEP were analyzed against the limits set by the continuous concentration criterion (CCC) to assess the potential aquatic life exposure to contaminants in various disposal scenarios. In these scenarios (disposal in superficial environmental conditions, in underground facilities, and in surface impoundments or waste piles), the established values were exceeded for PTEs including As, Cd, Cr, Pb, Ni, and Zn (excluding the punctual samples of the profile). According to the regulatory normative, none of the DAS residues could be defined as inert wastes. The DAS-Ca solids could be classified as non-hazardous wastes for most elements (only Zn posed risk). Residues from DAS-Mg exceeded the hazard threshold for Cd, Cu, and Zn, indicating a significant environmental risk for all landfill options, emphasizing the need to prevent waste from directly contacting leaching solutions.
Combining different analytical and management approaches could improve waste management practices and mitigate potential environmental risks by providing a more comprehensive understanding of the composition, behavior, and potential environmental impacts of these residues. Efforts should focus on accurately characterizing waste to promote viable solutions aimed at reducing the volume of waste sent to landfills by using them as a new source of metals and other critical elements.

Supplementary Materials

The following supporting information can be downloaded at https://www.mdpi.com/article/10.3390/min15010015/s1. Figures S1–S6: The XRD pattern of samples in DAS-Ca (S1 (Ca2, 7.5 cm); S2 (Ca3, 8.5 cm); S3 (Ca4, 10 cm); S4 (Ca5, 15 cm)) and DAS-Mg (S5 (Mg2, 12 cm)), as well as S6 (the “Pindo”, sand drain of the bottom columns), showing the main mineral phases identified* and their correlation with the patterns obtained from database by Match. The mineral symbols are according to the IMA–CNMNC. * Semiquantitative results were improved by Rietveld refinement (see also Table 3).

Author Contributions

Conceptualization, J.D.; methodology, O.L. and D.M.; validation, J.D., C.B.-B. and D.A.; investigation, J.D., C.B.-B. and D.M.; resources, D.A.; writing—original draft preparation, O.L.; writing—review and editing, J.D. and C.B.-B.; visualization, J.D. and C.B.-B.; supervision, J.D. and C.B.-B.; project administration, J.D. and D.A.; funding acquisition, J.D. All authors have read and agreed to the published version of the manuscript.

Funding

This work was supported by the PROMETEO Ecuadorian program (Secretary of Superior Education, Science, Technology and Innovation) in the framework of the project “Experiencia Piloto en la Remediación y Mitigación de la Oxidación de Sulfuros y la Generación de AMD en Relaveras del Distrito Minero de Zaruma-Portovelo” by the means of the postdoctoral contract nº 20140411 BP.

Data Availability Statement

Data is contained within the article or Supplementary Materials.

Acknowledgments

The authors acknowledge the material and human resources displayed from the INIGEMM (Ecuadorian National Research Institute of Geology, Mining and Metallurgy) and US (Seville University). Diana Ayala thanks Cumbal for the support in studying the samples using the SEM at the Center for Nanoscience and Nanotechnology (CENCINAT).

Conflicts of Interest

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

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Minerals 15 00015 g001
Figure 1. A geographic map of the Zaruma-Portovelo gold mining site (ZPMS). (a) The location of the AMD creek treated in the experimental columns, (b) details of the Zaruma-Portovelo processing plant, and (c) a photograph showing the wastes of the processing plants around the Amarillo River.
Figure 1. A geographic map of the Zaruma-Portovelo gold mining site (ZPMS). (a) The location of the AMD creek treated in the experimental columns, (b) details of the Zaruma-Portovelo processing plant, and (c) a photograph showing the wastes of the processing plants around the Amarillo River.
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Figure 2. A passive treatment system based on the DAS concept [2]. (a) Photographs of the sampling points in the DAS-Ca column, (b) DAS-Mg column, taken after 8 months of treatment, and (c) detail of the inner Ca2 layer showing green precipitates.
Figure 2. A passive treatment system based on the DAS concept [2]. (a) Photographs of the sampling points in the DAS-Ca column, (b) DAS-Mg column, taken after 8 months of treatment, and (c) detail of the inner Ca2 layer showing green precipitates.
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Figure 3. (a) The total concentration in each sample (% respect to total) of the main elements involved in the AMD neutralization process. (b–h) Sequential extraction data showing the percentage of the total extracted data in each fraction. Where necessary, elements with higher concentrations were suppressed (thin bars) to improve the visualization of trace elements. Concentrations are expressed in mg/kg.
Figure 3. (a) The total concentration in each sample (% respect to total) of the main elements involved in the AMD neutralization process. (b–h) Sequential extraction data showing the percentage of the total extracted data in each fraction. Where necessary, elements with higher concentrations were suppressed (thin bars) to improve the visualization of trace elements. Concentrations are expressed in mg/kg.
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Figure 4. Representative XRD pattern of samples showing main mineral phases identified and their correlation with patterns obtained from database by Match, (a) DAS-Ca (Ca1), and (b) DAS-Mg (Mg1).
Figure 4. Representative XRD pattern of samples showing main mineral phases identified and their correlation with patterns obtained from database by Match, (a) DAS-Ca (Ca1), and (b) DAS-Mg (Mg1).
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Figure 5. SEM images revealing the composition and morphology of mineralogical assemblages from DAS-Ca. The green frame highlights the correlation between the SE image and compositional mapping using Quantax. (a) Sample Ca1, where the relationship of Fe and Al with trace elements such as As and Pb can be observed. Framboidal aggregates of schwertmannite can also be observed. (b) Sample Ca2, showing the rhombohedral Gp and the formation of aluminum hydroxides and copper carbonates in local alkaline conditions and (c) the presence of Fe (microcrystalline aggregates (<10 μm) of Fe-Al-S, attributed to the jarosite–alunite group). The larger-sized spherical aggregates exhibited low concentrations of Fe (alunite–basaluminite). (d) Samples Ca-3, showing the presence of Mg-Al sulfates (identical compositional map) that could imply the formation of epsomite or pickeringite. (e) Microgranular calcite on the reactive substrate over wood shavings in sample Ca5.
Figure 5. SEM images revealing the composition and morphology of mineralogical assemblages from DAS-Ca. The green frame highlights the correlation between the SE image and compositional mapping using Quantax. (a) Sample Ca1, where the relationship of Fe and Al with trace elements such as As and Pb can be observed. Framboidal aggregates of schwertmannite can also be observed. (b) Sample Ca2, showing the rhombohedral Gp and the formation of aluminum hydroxides and copper carbonates in local alkaline conditions and (c) the presence of Fe (microcrystalline aggregates (<10 μm) of Fe-Al-S, attributed to the jarosite–alunite group). The larger-sized spherical aggregates exhibited low concentrations of Fe (alunite–basaluminite). (d) Samples Ca-3, showing the presence of Mg-Al sulfates (identical compositional map) that could imply the formation of epsomite or pickeringite. (e) Microgranular calcite on the reactive substrate over wood shavings in sample Ca5.
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Figure 6. SEM images revealing the composition and morphology of mineralogical assemblages from DAS-Mg. The green frame highlights the correlation between the SE image and compositional mapping using Quantax. (a,b) Both precipitates collected on the surface of the residue from the DAS-Mg column, white (SB) and green (SV), respectively, showing diverse gypsum crystallization forms. Also, (b) presents a nanocrystalline lattice of Cu-Fe carbonate. (c) Sample Mg-1, where the relation of divalent metals and carbonate can be observed. (d) Sample Mg2, showing the presence subspherical aggregates of Ca-Mg (calcite and dolomite) and another spherical particulate with high Na-Mg.
Figure 6. SEM images revealing the composition and morphology of mineralogical assemblages from DAS-Mg. The green frame highlights the correlation between the SE image and compositional mapping using Quantax. (a,b) Both precipitates collected on the surface of the residue from the DAS-Mg column, white (SB) and green (SV), respectively, showing diverse gypsum crystallization forms. Also, (b) presents a nanocrystalline lattice of Cu-Fe carbonate. (c) Sample Mg-1, where the relation of divalent metals and carbonate can be observed. (d) Sample Mg2, showing the presence subspherical aggregates of Ca-Mg (calcite and dolomite) and another spherical particulate with high Na-Mg.
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Figure 7. Charts showing the leached concentrations of As, Cd, Cr, Pb, Ni, Zn, Al, and Fe in the different weathering scenarios from the DAS-Ca (upper) and DAS-Mg (down) residues. The continuous concentration criterion (CCC limit) from the US EPA National Recommended Water Quality Criteria is also shown for comparison purposes. The data are in mg/L.
Figure 7. Charts showing the leached concentrations of As, Cd, Cr, Pb, Ni, Zn, Al, and Fe in the different weathering scenarios from the DAS-Ca (upper) and DAS-Mg (down) residues. The continuous concentration criterion (CCC limit) from the US EPA National Recommended Water Quality Criteria is also shown for comparison purposes. The data are in mg/L.
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Table 1. Five-step sequential extraction procedure scheme. * Mineral phases dissolved in each step according to Caraballo et al. [35].
Table 1. Five-step sequential extraction procedure scheme. * Mineral phases dissolved in each step according to Caraballo et al. [35].
Sequential Extraction Step* Dissolved PhasesElements Released
into Solution		Possible Dissolved PhasesPreferentially
Dissolved Minerals
(1) Water soluble fraction: 200 mg of sample and 20 mL deionizied water, shake for 12 h at room temperature.GypsumCa and SO42−; Fe, K, Mg, Mn, Zn and Cd-CoGypsum, secondary sulfates and other salts, hydroxides.
Fe-amorphous		Secondary sulfates and other salts
(2) Sorbed and exchangeable fraction: 20 mL of 1 M NH-acetate (4.5 pH buffer). shake for 1 h at RT.CalciteCa and adsorbed
elements; Fe and Al- K, As, Cu, Mn, Zn		Metal-divalent carbonate type, including calcite; Fe-amorphous or very poorly ordered Fe(III) precipitatesCalcite and some clay minerals
(3) Poorly ordered Fe(III) oxyhydroxides and oxyhydroxysulfates: 20 mL of 0.2 M NHy-oxalate (3 pH buffer). 30 min shake in darkness and at RT.Schwertmannite, hydrobasaluminite and gibbsiteFe, Al and SO42− and trace associated
Residual Ca		schwertmannite; jarosite-
alunite group		Mainly
schwertmannite and 2-line ferrihydrite
(4) Highly ordered Fe (III) hydroxides and oxides:
20 mL of 0.2 M NH4-oxalate (3 pH buffer), 80 °C water bath for 1h.		GoethiteK, Fe, Al and SO42−;
also As, Cu, Zn, Mn, Mg
Residual Ca		jarosite-alunite group;
residual Ca-Mg-Mn oxides		Goethite, jarosite,
6-line ferrihydrite and hematite
(5) Residue digestion: 3 mL of HNO3 + 7.5 mL of HF + 2.5 mL of HClO4Residue
(wood chips)		Organic elementsWood and residual silicates and clay assimilatedSilicates
Table 2. A summary of the solid wastes’ pseudototal concentration showing the elements frequently associated with AMD environments in the Zaruma-Portovelo mine district. <d.l., below the detection limit.
Table 2. A summary of the solid wastes’ pseudototal concentration showing the elements frequently associated with AMD environments in the Zaruma-Portovelo mine district. <d.l., below the detection limit.
Das—CaDas—Mg
Ca1Ca2Ca3Ca4Ca5Mg1Mg2
Agmg/kg9.7423.2316.3336.15100.7611.8260.0
Femg/kg336,42230,527149,3243096232432,842727
Almg/kg249743,040709156,47482881576162
Asmg/kg6616127121537.611.243.031.1
Camg/kg1085145,27819,878160,770257,35511,060116,385
Cdmg/kg39.60.719.75<d.l.34.753474453
Comg/kg3.49<d.l.2.41<d.l.<d.l.7734565
Crmg/kg11821.428.614.019.220.268.4
Cumg/kg42341,688101546329842909,59911,385
Kmg/kg262612271114167236034023943
Mgmg/kg2901305347133025979168253
Mnmg/kg1071223741024247113,18175,841
Momg/kg<d.l.17.71.2725.324.90.864.87
Namg/kg74555449257911741257460
Nimg/kg4.0112.42.291.49<d.l.4861883
Pbmg/kg39.01.8047.3<d.l.<d.l.88841.2
Sbmg/kg11262.370.268.168.692.3112
Srmg/kg21.157436588113069.81364
Znmg/kg139386086320517517,344465,916
Table 4. A comparison between AMDp and the regulatory criteria for the acceptance of waste at different types of landfills and their classification of hazardousness (Council Decision, 2003/33/EC).
Table 4. A comparison between AMDp and the regulatory criteria for the acceptance of waste at different types of landfills and their classification of hazardousness (Council Decision, 2003/33/EC).
Landfill TypeAsBaCdCrCuNiPbZnSulfate
DAS-Ca<d.l<d.l<d.l0.7504.010104<5000
DAS-Mg<d.l<d.l9019.4164<d.l<d.l206<5000
Inert wastes0.5200.040.52.00.40.54.01000
Non-Hazardous wastes2.01001105010105020,000
Hazardous wastes25300570100505020050,000
<d.l. Below detection limit. Data in mg/kg.
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Delgado, J.; Lozano, O.; Ayala, D.; Martín, D.; Barba-Brioso, C. Geochemistry and Mineralogy of Precipitates from Passive Treatment of Acid Mine Drainage: Implications for Future Management Strategies. Minerals 2025, 15, 15. https://doi.org/10.3390/min15010015

AMA Style

Delgado J, Lozano O, Ayala D, Martín D, Barba-Brioso C. Geochemistry and Mineralogy of Precipitates from Passive Treatment of Acid Mine Drainage: Implications for Future Management Strategies. Minerals. 2025; 15(1):15. https://doi.org/10.3390/min15010015

Chicago/Turabian Style

Delgado, Joaquín, Olivia Lozano, Diana Ayala, Domingo Martín, and Cinta Barba-Brioso. 2025. "Geochemistry and Mineralogy of Precipitates from Passive Treatment of Acid Mine Drainage: Implications for Future Management Strategies" Minerals 15, no. 1: 15. https://doi.org/10.3390/min15010015

APA Style

Delgado, J., Lozano, O., Ayala, D., Martín, D., & Barba-Brioso, C. (2025). Geochemistry and Mineralogy of Precipitates from Passive Treatment of Acid Mine Drainage: Implications for Future Management Strategies. Minerals, 15(1), 15. https://doi.org/10.3390/min15010015

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