Removal of Metal(oids) from Acid Mine Drainage Using Manganese Oxide Wastes from a Mining-Metallurgical Process

doi:10.21203/rs.3.rs-3718074/v1

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Removal of Metal(oids) from Acid Mine Drainage Using Manganese Oxide Wastes from a Mining-Metallurgical Process

https://doi.org/10.21203/rs.3.rs-3718074/v1

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The study addresses Acid Mine Drainage (AMD) in Central Mexico from iron-sulfur ore mine which poses environmental risks. The initial passive treatment using alkaline minerals improved pH and reduced metal concentrations but exceeded permissible limits (MLP) for Zn2 + and Cd2+, set by Mexican regulations (Zn = 10 and Cd = 0.2 mg/L). This study aimed to improve the original process by utilizing waste materials from a manganese mine (Mn-wastes). These materials contain carbonates (R3) and oxides and clays (R6) with a high sorption capacity to reduce Zn²⁺ and Cd²⁺ concentrations below the permissible level (MPL) or to directly treat the AMD without using other alkaline materials. The original pH of the AMD was 2.99, with the following contents: Al (445 mg/L), Fe (263 mg/L), Mn (364 mg/L), Cd (2.82 mg/L), and Zn (4,830 mg/L). After the pre-treatment at pH 6.31, concentrations in mg/L were found to be below the limits of detection (LODs) for Al and Fe, while Mn = 279, Cd = 0.39, and Zn = 1,110 mg/L. The results indicated that using R3 and R6, with or without the alkaline pre-treatment, allows compliance with the MPL, but the technical-economic viability is greater with the pre-treatment. Waste R6 is more efficient than R3. The addition of R6 (Mn-waste) to pre-treated AMD in a ratio of 0.75 (R6/AMD) with 30 hours of contact or with a ratio of 0.2 and 60 hours, resulted in Cd²⁺ and Zn²⁺ soluble concentrations decreasing below their MPL. The Zeta Potential of both wastes after contact with AMD increased to positive values, indicating that sorption occurred during the removal of metal(oids).

AMD treatment

sorption capacity

AMD management

manganese waste reuse

sustainable mining

metal concentration

Acid drainage is the result of sulfur-bearing minerals being exposed to air, water, and acidophilic iron-oxidizing bacteria, leading to the formation of sulfuric acid (Iatan, 2021). Acid mine drainage (AMD) primarily develops in active and abandoned mines from the oxidation of polymetallic sulfide deposits containing low amounts of acid-neutralizing minerals (Masindi et al., 2022). This acidic solution with a pH of 4 has elevated levels of dissolved metal(oids) and sulfates, including ions of well-known toxic elements such as Pb, Cd, As, and, in some cases, rare-earth elements and radionuclides.

Consequently, the development of AMD poses a potential environmental risk (NOM-157-SEMARNAT-2009, Akcil & Koldas, 2006) with significant ecotoxicological and socioeconomic impacts. Two AMD management strategies have recently drawn attention: prevention techniques and mine waste recycling. However, these alternatives are still pending despite their potential benefits (Park et al., 2019). The current control of AMD is carried out by applying other treatments, classified as active or passive, and can be biotic or abiotic. Active treatments require chemicals to raise pH under aerobic conditions, promoting the precipitation of metal(oid) ions. These methods are quick and selective, but require machinery and careful control of the process.

As a result, the cost is high and their use is not suitable for places where the generation of acid drainage is constant (RoyChowdhury et al., 2015). The chemicals used to treat different sites depend on properties and cost. The most commonly used materials are limestone, hydrated lime, pebble quicklime, soda ash, caustic soda, ammonia, and steel slag. The process using limestone is effective when the drainage is not very acidic, and the concentration of metal(oids) is low. When the flow and acidity are higher, other reagents, such as hydrated lime, can be more effective.

In contrast to the active methods mentioned above, passive methods rely on biological, geochemical, and physical processes. Biological passive treatments generally involve sulfate-reducing bacteria to transform sulfates into sulfides, generating alkalinity and the removal of dissolved contaminants, mainly by precipitation as insoluble metal sulfides. Organic matter may be used to stimulate microbial activity. Bacteria can work in aerobic and/or anaerobic environments (Zipper & Skousen, 2014). Examples include constructed wetlands, vertical flow wetlands, and bioreactors.

Passive treatments are as effective as active systems and are less expensive because they do not consume electrical energy, chemical reagents, or mechanical equipment. They also do not require facilities, daily operations, or frequent maintenance. Additionally, these techniques are more environmentally friendly as they can support plants and wildlife (Ford, 2003). Nevertheless, remediation times are longer compared to active processes and typically require periodic inspection and some maintenance (Ford, 2003).

In the study area, Taxco de Alarcon Guerrero, Mexico, a non-operational historic mine, produces acid mine drainage (AMD, pH 2.2–2.9). Oxidation mainly occurs in underground tunnels where minerals and rocks are exposed to oxygen and water. According to Romero et al., (2011), the acid effluent (pH 2.2–2.9) produces high concentrations (in mg/L) of the following species: sulfates (SO₄²⁻, 1,470–5,454), zinc (3.0–859), iron (5.5–504), copper (0.7–16.3), cadmium (0.3–6.7), lead (0.05–1.8), and arsenic (0.002–0.6).

On this site, a passive treatment was developed to control AMD, utilizing the area's natural conditions. The system consists of ten ground-installed drains. The initial six steps comprise drains containing indigenous calcareous shales, aimed at neutralizing acidity and promoting the precipitation and sorption of As and heavy metals, as described by Romero et al., (2011). Subsequently, the process involves the adsorption and precipitation of soluble elements in drains 7 to 8 using a mixture of phosphoric rocks, gravel, and clays. Finally, the operation concludes with two biotic drains, as described by Rico (2018).

The aforementioned passive process reduced all the Pollutant Elements of Concern (PETs) to levels compliant with Mexican environmental legislation, except for Zn²⁺ (10 mg/L) and Cd²⁺ (0.2 mg/L), which remained elevated (according to NOM-001-SEMARNAT-2021). This could be attributed to the fact that Zn removal typically requires a pH higher than 8.0, as indicated by Pérez-Corrales (2014) and Romero et al., (2011). However, the maximum pH achieved in this study was lower.

Consequently, there was a need to improve the process to enhance the efficiency of AMD element removal. The selected method was developed by adding materials with greater sorption capacities, such as waste materials, from a manganese mine-metallurgical unit located in the province of Molango, Hidalgo, Mexico, where one of the most significant global deposits of Mn is found (Molina & Piñon, 2019). Currently, two mines are in operation: one is an open pit containing MnCO₃, and the other is an underground MnO₂ mine. The metallurgical process converts MnCO₃ into MnO in a rotary nodulization furnace. The mineral from the underground mine undergoes purification within the same complex to yield MnO₂, which will be utilized in various industries including ceramics, fertilizer, and food. Additionally, MnO₂ is sold as a raw material for the manufacturing of alkaline batteries.

One of the waste materials contains fine particles from the rotary furnace, the size of which are unsuitable for the nodulization process. These particles are stored outdoors, where atmospheric and hydrologic erosion are able to disperse them, potentially affecting the quality of air and water bodies. Under extreme conditions, respirable particles from the air can pose a potential health risk to the chronically exposed human population. These particles can be inhaled and may gain access to the body through direct uptake into the central nervous system (CNS). The extent of health damage may vary depending on the absorbed concentration and duration of exposure (Roth, 2006; O'Neal & Zheng, 2015).

Several studies have reported that Mn-oxides and Mn-carbonates have proven to be effective scavengers of contaminants (McKenzie, 1972; Xiong et al., 2017; Islam et al., 2018; Zhang et al., 2020). They have a high specific surface area (SSA), as well as surface charge, a polymorphic nature, and natural availability. Some studies have reported high cation and anion sorption capacities of manganese carbonates, such as fluoride, Cu, Cd, Pb, and Zn (Della et al., 2013; Zhang & Jia, 2018). Other studies have demonstrated the efficiency of Mn_xO_y in treating matrices polluted with organic substances. Therefore, Mn wastes can be effective in treating a wide range of inorganic and organic contaminants in water and soils (Chowdhury et al., 2009; Remulcan & Ginder-Vogel, 2014; Zhou et al., 2015); and certainly, the use of these wastes to treat AMD can be effective and “environmentally friendly” (Feng et al., 2007; Qin et al., 2011; Demirkiran, 2015; Islam et al., 2018).

This study aims to evaluate the use of two Mn wastes rich in carbonates and/or oxides to reduce Zn²⁺ and Cd²⁺ concentrations in pre-treated AMD from the old mine in Taxco to levels below Mexican regulatory guidelines. It also explores whether the wastes can remove all the metal(oids) from the AMD without the need for other alkaline materials. The improved AMD treatment process aims to set an example of a circular economy solution proposal to protect the environment and transform our throwaway culture into one in which wastes are valorized.

2.1 Sampling and preparation

In the mining area of Taxco, ten liquid samples of AMD were collected from ten drains of the passive treatment (P0 to P9). Two liters from each drain were transferred into high-density Nalgene bottles (500 mL each) with airtight lids, stored at 4 °C, and transported to the laboratory for analysis and experiments.

Additionally, samples of two wastes from the mining and nodulization processes of a mining-metallurgical complex were collected: dust from the cooling system (R3) containing MnCO₃ from the open-pit mine, and the other from the final step of the nodulization furnace composed of particles <1/4" inches (R6) with MnO.

Two composite samples were prepared from independent samples (n=10). Approximately one kg of each solid sample was collected using steel scoops, transferred into hermetically sealed plastic bags, and meticulously labeled for transportation to the laboratory. They were dried at 45 °C for 48 hours, ground, sieved to pass through a #100 (0.149 mm) mesh, and homogenized by quartering (Hesse, 1971).

Aliquots of 100 g were prepared and combined to create 1 kg of composite samples for each waste. Aliquots (100 g) for chemical analysis were milled, sieved (#200 mesh < 0.074 mm), and dried at 96°C. The samples were stored in airtight containers at room temperature (15-20°C) until analysis.

2.2 Analytical determinations

The analyses were conducted by the LABQA laboratory (No. R-0593-031/14, accredited by the "Accreditation Body in Mexico") at the Faculty of Chemistry, National Autonomous University of Mexico (UNAM). Sampling and analytical reproducibility were assessed following the QA/QC analytical procedure, which included preparing blanks and duplicates using spike samples and certified international reference material (NIST 2710a), ultrapure deionized water, and analytical-grade or high-purity reagents.

The pH was measured using the EPA 9045D method (EPA, 2004) with a Thermo-720 potentiometer at 25°C. Electrical conductivity (EC) was determined in accordance with the EPA-120.1 method (EPA, 1982) using Corning-441 equipment.

For elemental determination, AMD samples were digested by mixing 7 mL with 3 mL of concentrated nitric acid and heating them in an Ethos Easy Milestone microwave, following the EPA 3015A method (EPA, 2007). Mineral solid samples were digested following the general conditions described in the EPA-3052 method (EPA, 1996). Portions of 0.2 (± 0.0001) g of each solid sample were placed in an open digestion system using 3 mL of concentrated nitric acid, 2 mL of concentrated hydrochloric acid, and 5 mL of concentrated hydrofluoric acid (analytical grade). The mixture was heated to 120°C until complete digestion and then filtered using Whatman No. 42 filter paper (2.5 mm). The resulting samples were stored in airtight Nalgene bottles at 4°C.

Aluminum (Al), Mn, As, Fe, Cd, and Zn were quantified using Inductively Coupled Plasma-optical Emission Spectrometry (ICP-OES) equipment (Agilent Technologies AG-5100) following the EPA-6010C method (EPA, 2000). Additionally, the elemental composition of the solid samples was determined using XRF equipment (Olympus modelo DP-6000).

SEM-EDS analysis was performed using a HITACHI TM1000 tabletop scanning electron microscope equipped with an energy-dispersive spectroscopy module. The geochemical crystalline composition was determined by XRD using an EMPYREAN instrument equipped with a Ni-filter, fine-focus copper tube, and PIXcel3D detector. The measurements were conducted in the angular interval 2θ from 4° to 80° using a "step scan" of 0.003° (2 Theta) and an integration time of 40 s per step. Quantification was performed using the Rietveld method, which was implemented in the HIGHScore v4.5 software, and utilizing the ICDD (International Center for Diffraction DATA) and ICSD (Inorganic Crystal Structure Database).

Zeta potential (ZP) was measured using the ZETA-METER 3.0+ equipment within a pH range of 3 to 9 at various concentrations of ZnSO₄.H₂O.

2.3 Preliminary experiment

A preliminary factorial experiment was conducted to approximate Mn-wastes' capacity for removing metal(oids) from AMD. The samples of the treated acid solution from the passive treatment that were tested included initial (P0), intermediate (P5), and final (P9) drains. The R3 sample was selected and tested due to its high carbonate content, which facilitates rapid AMD neutralization and removal through sorption and/or precipitation. R3 was mixed with the three AMD samples (P0, P5, and P9) at three solid/liquid (s/l) ratios (1.5 g/25mL, 2.5 g/25mL, and 3 g/25mL). Three solid-liquid contact times were proposed: 20 and 60 minutes with axial agitation, and 1,080 minutes without stirring. Duplicates were conducted for the 27 tests, and the identified metal(oids) in the AMD were monitored. The factorial experiment conditions are presented in Table S1 (in Supplementary Data).

2.4 Experiment designed by Minitab

In this experiment, waste materials R3 and R6 were added to 15 mL of AMD from the P0, P5, and P9 drains. The optimal conditions for reducing Zn²⁺ and Cd²⁺ concentrations below their Mexican Permissible levels (MPLs) were determined using the statistical software Minitab. This software generates an algorithm to construct scenarios by extrapolating data with 95% confidence.

The optimized variables included contact time (ranging from 24 to 120 hours) and solid/liquid ratios (ranging from 0.5 g/15 mL to 2 g/15 mL). These ranges were selected based on the results of the initial experiment. The Minitab software adjusted the conditions for solid/liquid ratios and contact time for each waste and AMD sample, as shown in Table S2 (in Supplementary Data).

A total of fifty-four trials, including repetitions, were performed, considering various conditions as shown in Table 2. These conditions included: a) contact time (hours) with values T1=4.12, T2=24, T3=72, T4=120, and T5=139.88; b) solid/solution ratio (g/mL) with values C1=0.189/15, C2=0.5/15, C3=1.25/15, C4=2/15, and C5=2.31/15. The software evaluated the influence of each variable and their combined effects.

2.5 Zeta Potential

Zeta Potential (ZP) measures the surface charge of the solids and their interaction with the ions in the solution, indicating whether sorption has occurred. In this phenomenon, “the oppositely charged surface (counter-ions) are attracted, while similar charge (co-ions) particles are repelled" (Bauddh et al., 2019). The ZP was assessed as follows:

• First test. One gram of each waste was mixed with 500 mL of deionized water. From the stock solution, eight aliquots were prepared, and their pH was adjusted to different values between 3 and 10, shaking until equilibrium was reached. pH adjustment was achieved using HCl and NaOH.

• Second test: Four trials were conducted to measure the ZP of R3 and R6 samples in contact with AMD from P9 drain at pH around 7, under the following conditions: a) C2T4, b) C3T1, c) C3T5, and d) C4T2 (Table S2). Under these conditions, the first experiment achieved the highest Zn removal.

• Third test: The ZP of the R3 and R6 wastes was determined at different Zn²⁺ concentrations around neutrality under the following conditions: a) original concentration of AMD, b) AMD + 1,000 mg Zn²⁺/L, c) AMD + 2,000 mg Zn²⁺/L, and d) AMD + 5,000 mg Zn²⁺/L. The suspensions were filtered using syringes with membranes with a pore size of 0.05 μm, and the solutions were acid-digested. Zn²⁺ concentrations were quantified by ICP-OES following the EPA-6010C method (EPA, 2000).

3.1 Characterization of AMD

Table 1 displays the pH, EC, and total elemental concentrations of Al, As, Cd, Fe, Mn, Pb, and Zn in AMD.

The pH of the AMD increased significantly with the addition of local alkaline materials throughout the successive steps of the passive treatment. The pH ranged from 2.99 in the P0 drain (non-treated AMD) to 4.83 in the intermediate drain (P5) and reached 6.31 in the final treatment (P9) (Table 1).

The decrease in EC was insignificant, with a change from 3.03 to 2.36, suggesting the presence of soluble ions throughout the entire treatment.

The primary components of the AMD were Al, Fe, Zn, and Mn, and their concentrations decreased as the pH increased. The elements with higher removal rates were Al (reduced from 445 to <0.2 mg/L) and Fe (reduced from 263 to <0.1 mg/L). Starting from the P7 drain, the concentrations of these two elements fell below their LODs (Table 1).

After reaching P9 in the final stage of the alkaline treatment, the Zn concentration dropped from 4,830 to 1,110 mg/L, representing a significant reduction but, as mentioned earlier, still exceeding the MPL for treated water discharged into rivers (Zn = 10 mg/L, monthly average).

The Cd²⁺ concentration changed from 2.82 mg/L in the P0 drain to 2.47 mg/L in P5 and 0.39 mg/L in P9, representing a notable decrease but still exceeding its MPL (0.2 mg/L, monthly average) (Table 3).

The concentrations of Pb and As were below the LODs (0.02 and 0.1 mg/L) and the MPL in the AMD from P9 (non-treated) (Table S1). The concentrations of Al and Fe in the AMD at the initial step of the passive treatment were lower than expected. It is likely that under acidic conditions, Al and Fe ions form solid oxi-hydroxides and hydroxy sulfates, such as jarosite or goethite-bearing Fe (III) (Webster et al., 1998; Ryu & Kim, 2022). These compounds could retain Pb and As, thereby lowering their concentrations in non-treated AMD. However, it's possible that Pb could also partially precipitate as PbSO₄ (Kumpiene, 2010). The decrease in Mn concentration in the AMD during the neutralization process is relatively low (Table 1). However, it is an unregulated element in river water. This may be due to the pH becoming a natural controlling factor as equilibrium is approached. According to Laxen et al., (1984), at pH 5.48 in unfiltered samples, soluble Mn was drastically depleted, and above pH 7.0, this element is practically removed from the solution regardless of filtration.

3.2 Characterization of mining-metallurgical waste

R3 is a waste rich in MnCO3 from the open-pit mine, while R6 is a waste from the nodulization furnace stored in an open-air deposit (Table S3 In Supplementary Data). Both Mn wastes have a basic pH and contain significant total concentrations of metal(oids).

Mn: R3= 31% and R6=33.5%, Fe: 4% and 5.6%, and Al: 0.31% and 0.17%. The concentrations of other elements in these wastes vary: Pb: R3=55 and R6= <0.2 mg/kg, Zn: 89.4 and 204 mg/kg, and As: <0.3 and 49.8 mg/kg. The soluble concentrations of these metals recovered with meteoric water are lower than the detection limits (data not presented), suggesting that their original compounds have low solubility under environmental conditions. Based on the results, it can be assumed that R3 and R6 are not significant sources of soluble or total toxic elements. Both wastes are available in any required volume for AMD treatment.

R3 reacted strongly with HCl, resulting in a high pH (10.55) due to the presence of rhodochrosite. Its EC value was low (Table S4 In Supplementary Data).

Sample R6 reacted less vigorously with HCl, resulting in a basic pH of 8.65, which was lower than that of R3. This difference may be due to R6 having a lower carbonate concentration. Under furnace conditions, carbonates are transformed into oxides. Its EC was higher than that of R3, possibly due to the liberation of Ca from the oxides.

Based on the results of the semi-quantitative XRF analysis (Table S5 in Supplementary Data) and the ICP-OES analysis (Table S3), Al, Pb, Si, and Zn concentrations in R3 are slightly higher than those in R6. Lower concentrations of the remaining detected elements, Ca, As, Fe, Mn, and S, were found in both wastes. The minimal differences observed in the elemental composition of R3 (before the thermic process) and R6 (waste from the thermic process) indicate that most of the elements from R3 are separated from the final product of the furnace (MnO) and concentrated in R6 waste.

The XRD diffractogram of sample R3 indicates the dominant presence of rhodochrosite and minor concentrations of Ca/Mg/Fe carbonates, quartz, pyrite, and magnetite (Figure S1 in Supplementary Data). On the other hand, R6 exhibited signals of gypsum, quartz, Mn-silicates (ribbeite, tephroite), Mn-oxides (manganosite, hausmannite, todorokite, galaxite), Fe-oxides and Fe-silicates (goethite, fayalite, magnetite). The amorphous background partially covered the weak signals. These amorphous materials are abundant in waste from furnaces, especially in Mn ores, where crystals are extremely rare (Figure 1). However, amorphous Mn oxides have been reported as substances with higher sorption capacity than their crystalline counterparts (Dyer et al., 2000; Al-Degs et al., 2001; Zhang et al., 2016; Islam et al., 2018; Wick et al., 2019).

Both R3 and R6 wastes contain approximately 40% Mn, but different sorption behaviors are expected due to their distinct mineral compositions.

The results of the SEM-EDS particle analysis of R3 and R6 were consistent with the elemental composition of the entire sample. As expected, the total concentrations of Mn and other minor elements in the analyzed particles were higher than those in the whole sample (Figure 1).

3.3 Preliminary experiment

The addition of R3 waste to AMD from drain P0 (non-treated) at different solid/liquid ratios (C1, C2, C3) increased the pH value from the shortest contact time and the smallest quantity of waste added. The pH changed to near-neutral values in the AMD of drain P0, ranging from 2.99±0.50 to 6.45-6.65, in P5 from 4.83 to 6.57-6.85, and in P9 from 6.31 to 6.72-7.04 (Table S6 in Supplementary Data).

All trials shown in Table S3 indicate a significant removal of soluble elements (Table S6), primarily Al (P0: 93-95%, P5: 93-98%, P9: 96-99%) and Fe (P0: 93-95%, P5: 93-98%, P9: 96-99%). However, reducing acidity does not sufficiently eliminate Cd and Zn to meet regulatory standards (Balintova & Petrilakova, 2011). Zn²⁺ removal is observed in P0: 93-95% and in P5: 95-98%, while Cd²⁺ removal is observed in P0: 14-80% and in P5: 91%. In drain P9, the final step of AMD pre-treatment, the addition of R3 increased the removal efficiency. The Cd²⁺ concentration dropped below the MPL (0.2 mg/L), but not the Zn²⁺ concentration. When R3 was added at the highest concentration (3g/25mL), both Cd²⁺ and Zn²⁺ concentrations decreased to MPL or lower values regardless of the contact times.

Comparison of preliminary experiment results with the different AMD from drains P0 to P9 indicates that pretreatment with alkaline materials yields favorable results (Table S6). Adding R3 or R6 wastes to AMD from drain P9 reduces the need for acid neutralization, thereby enhancing the sorption capacity of both wastes.

3.4 Experiment designed using Minitab Software

The addition of the two Mn wastes to the three selected drains (P0, P5 and P9) is effective in PTE removal. In all trails, the elements Al, As, Cu, Cr, Fe, Ni, and Pb were below 1 mg/L, and the concentrations of Cd²⁺varied from <LOD to 2.19 mg/L and the Zn²⁺ from <LOD to 241 mg/L (Table 2).

When R3 was used to treat AMD from the P9 drain, the Zn²⁺ and Cd²⁺ concentrations were lower than their MPL (10 mg/L and 0.2 mg/L). However, when R3 was used to treat AMD from P0 and P5, the Cd²⁺ and Zn²⁺ concentrations exceeded their MPLs (Figure 2).

In comparison, when R6 was used to treat AMD from P5 and P9, the final Zn²⁺ and Cd²⁺ concentrations obtained were below the MPL. Nevertheless, when R6 was mixed with AMD from P0 (non-treated), only the concentration of Zn²⁺ was <10 mg/L, considering prolonged contact times and high solid/solution ratios (C4T4 and C5T3). In summary, in 66.66% of the trials using R3 and 88.88% using R6 to treat AMD from drain P9 , the final Zn2+ and Cd2+ concentrations were smaller than their MPLs (Figure 2). These results show the advantages of treating the pretreated AMD (P9) and R6 waste.

The Mn concentration in non-treated AMD is slightly higher than that in the final treated AMD with R3 and R6 wastes. This behavior can be explained by considering the high sorption capacity of Mn wastes. Figure 3 presents the results of the extrapolation using Minitab software. This figure shows the contour plots of R3 and R6 Mn waste/15 mL AMD-P9 ratios versus contact times (hours) with the final concentrations of Zn²⁺ in treated AMD.

The efficiency of Mn wastes in removing this metal is proportional to the solid/liquid ratio and contact time. Blue indicates solid/liquid (s/l) ratios and contact times that reduce the Zn²⁺ concentration below its MPL, changing to green when the concentration increases. Using R3, the MPL of Zn²⁺ is reached at 30 hours with a ratio of 1.5 g waste/15 mL AMD and at a ratio of 0.5 g/15 mL with a time of approximately 120 hours (Figure 3). Conversely, when using R6 waste, the Zn concentration dropped to between 5-7.5 mg/L within 1 hour or less and with a ratio of 1.0/15 mL or slightly lower (Figure 3). At a lower ratio (0.5 g/15 mL), the contact time increases to approximately 45 hours. In conclusion, these results indicate that waste R6 has a better sorption capacity and is more efficient than R3.

3.5 Zeta Potential (ZP)

1) The Zeta potential (ZP) of R3 at pH 8.4 was -64.8 mV and remained practically constant up to pH 6 (-60.0 mV and -55.8 mV). At pH 5.86, the ZP changed to -38.4 mV, and at pH 4.75, the ZP value became positive at +5.64 mV. At pH 3.2, it increased to +21.8 mV. At pH 4.94, the ZP under the experimental conditions reached 0 (isoelectronic point), as shown in Figure 4.

The ZP of R6 remained constant from pH 8.7 to pH 6 (-52.3 mV, -53.8 mV, -54.8 mV). At pH 4.9, it changed to -17.2 mV, and at pH 2.6, the ZP became positive at +16.8 mV. The isoelectric point (ZP0) was found at pH 3.09, as indicated in Figure 4.

2) After adding R3 and R6 to the AMD, the Zeta potential (ZP) increased proportionally with concentration and contact time. Trial R3C3T1 showed the lowest ZP increases, while R6-C3T5 had the highest increases, indicating that both wastes adsorbed Zn²⁺, with R6 showing a higher concentration.

3) In the final experiment, in which several Zn²⁺ concentrations were added to non-treated AMD (NT-AMD), the changes in Zeta potential (ZP) were measured, as shown in Figure 5. The ZP of R3 was -38.9 mV when in contact with NT-AMD, and it increased proportionally with the addition of Zn²⁺. At a concentration of 5,000 mg Zn²⁺/L, the ZP reached its highest value (+24.75 mV) (Figure 5). The R6 waste exhibited only positive ZPs, even without the addition of Zn²⁺, with values ranging from +9.82 with NT-AMD to +41.25 mV with AMD containing 5,000 mg Zn²⁺/L.

4) These results indicate that both wastes have a high sorption capacity. R6, in particular, demonstrated better sorption efficiency, consistent with the findings of the previous experiment. These results highlight that sorption is the controlling process for cation removal. After adding R3 and R6 to the AMD, the Zeta Potential (ZP) increases proportionally with concentration and contact time. Trial R3C3T1 exhibited the smallest ZP increases, while R6-C3T5 showed the highest, suggesting that both wastes adsorbed Zn²⁺, with R6 displaying a higher adsorption capacity.

In the final experiment, where various Zn²⁺ concentrations were added to non-treated AMD (NT-AMD), the ZP variations were measured (Figure 5). The ZP of R3 was -38.9 mV when in contact with NT-AMD, and it increased proportionally with the addition of Zn²⁺. At a Zn²⁺ concentration of 5,000 mg/L, the ZP reached its maximum value of +24.75 mV (Figure 5). Conversely, the R6 waste consistently displayed positive Zeta Potentials (ZPs), even in the absence of Zn²⁺ addition. The ZP values ranged from +9.82 when in contact with NT-AMD to +41.25 mV when exposed to AMD containing 5,000 mg/L Zn²⁺.

These results indicate that both wastes have high sorption capacity, but that R6 provides a better outcome. They also indicate that sorption is the controlling process for cation removal. Similar results have been reported for organic and inorganic pollutant sorption using synthesized Mn_xO_y (Feng et al., 2007; Chowdhury et al., 2009; Della et al., 2013; Zhao et al., 2016). The surfaces of the finest particles in R3 and R6 are rich in Mn carbonates or oxides, creating a basic micro-environment with negative charges that favor adsorption and co-precipitation. Inner complexes may possibly be formed by exchanging Mn²⁺ from the carbonates with Zn²⁺ or Cd²⁺ from the solution, or they might be co-precipitated as hydroxy sulfates (Zhizhaev & Merkulova, 2014) or hydroxy silicates (Kent and Kastner, 1985).

Overall results indicate that Mn wastes are able to absorb cations from AMD with no need for additional materials (pretreatment); however, larger quantities are required. In this case, using a mixture of R3, rich in carbonates, with R6, containing Mn-Fe oxides, is the most convenient approach. The central role of R3 is as a neutralizing agent, while R6 acts as a sorbent material.

However, pretreatment with alkaline materials from the region increased the efficiency of the removal process by reducing acidity and cation concentrations, thereby enhancing the availability of Mn wastes as sorption agents. The addition of R3 and R6 wastes to pretreated AMD, under specific contact times and solid/liquid ratios, resulted in achieving values lower than their Permissible Limits (PL). With longer contact times or higher solid/liquid ratios, the final concentrations fell below their Limits of Detection (LODs). In conclusion, pretreating AMD enhanced the technical and economic viability of the treatment process.

The removal process of Zn²⁺ and Cd²⁺ using Mn wastes primarily involves sorption. Further experiments are required to assess the potential recycling of Mn wastes and the reduction of AMD treatment costs.

A pilot test must be conducted to evaluate the feasibility of the proposed sorption process and identify critical parameters for scaling it up. Using Mn wastes to treat AMD simultaneously addresses two environmental issues. First, it reduces the volume of solid wastes deposited in the open, while neutralizing AMD, thereby decreasing environmental risks. This study, along with other reports, provides evidence of the potential of Mn wastes to effectively remove various pollutants from water due to their positive surface adsorption characteristics.

Conflict 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.

Acknowledgements

The authors are especially grateful to Dr. Francisco Romero and Dr. Gerardo Martinez for their support to collect the samples, to Q.F.B. Reyna Roldan and M. in C. Alfredo Jimenez for their participation in the chemical analysis and to Sonia Helen Ponce Wainer for the grammatical revision.

Akcil A, Koldas S (2006) Acid Mine Drainage (AMD): causes, treatment and case studies. J Clean Prod 14(12–13):1139–1145. https://doi.org/10.1016/j.jclepro.2004.09.006
Al-Degs Y, Khraisheh MAM, Tutunji MF (2001) Sorption of lead ions on diatomite and manganese oxides modified diatomite. Water Res 35(15):3724–3728. https://doi.org/10.1016/S0043-1354(01)00071-9
Balintova M, Petrilakova A (2011) Study of pH influence on selective precipitation of heavy metals from acid mine drainage. Chem Eng Trans 25:1–6. https://doi.org/10.3303/CET1125058
Bauddh K, Korstad J, Sharma P (eds) (2020) Phytorestoration of Abandoned Mining and Oil Drilling Sites. Elsevier. https://doi.org/10.1016/C2019-0-02457-0
Chowdhury AN, Azam MS, Aktaruzzaman M, Rahim A (2009) Oxidative and antibacterial activity of Mn3O4. J Hazard Mater 172(2–3):1229–1235. https://doi.org/10.1016/j.jhazmat.2009.07.129
Della Puppa L, Komárek M, Bordas F, Bollinger JC, Joussein E (2013) Adsorption of copper, cadmium, lead and zinc onto a synthetic manganese oxide. J Colloid Interface Sci 399:99–106. https://doi.org/10.1016/j.jcis.2013.02.029
Demirkiran N (2015) Copper adsorption by natural manganese dioxide. Trans Nonferrous Met Soc China 25(2):647–653. https://doi.org/10.1016/S1003-6326(15)63648-2
Dyer A, Pillinger M, Newton J, Harjula R, Möller T, Amin S (2000) Sorption behavior of radionuclides on crystalline synthetic tunnel manganese oxides. Chem Mater 12(12):3798–3804. https://doi.org/10.1021/cm001142v
Agency EP (1982) Method 120.1: Conductance (Specific Conductance, umhos at 25°C) by Conductivity Meter,
Environmental Protection Agency, Method 3015A (2007) : Microwave assisted acid digestion of aqueous samples and extracts,
Environmental Protection Agency (1996) Method 3052: Microwave assisted acid digestion of siliceous and organically based matrices,
Environmental Protection Agency (November 2000) Method 6010C (SW-846). Inductively Coupled Plasma - Atomic Emission Spectrometry
Environmental P (2004) Agency, Method 9045D: Soil and waste pH. November
Feng XH, Zhai LM, Tan WF, Liu F, He JZ (2007) Adsorption and redox reactions of heavy metals on synthesized Mn oxide minerals. Environ Pollut 147(2):366–373. https://doi.org/10.1016/j.envpol.2006.05.028
Ford KL, "Passive Treatment Systems for Acid Mine Drainage" (2003) U.S. Bureau of Land Management. Papers 19. https://digitalcommons.unl.edu/usblmpub/19
Hesse PR, Hesse PR (1971) A textbook of soil chemical analysis. https://doi.org/10.1017/S0014479700005202
Iatan EL (2021) Gold mining industry influence on the environment and possible phytoremediation applications. In Phytorestoration of abandoned mining and oil drilling sites (pp. 373–408). Elsevier. https://doi.org/10.1016/B978-0-12-821200-4.00007-8
Islam MA, Morton DW, Johnson BB, Mainali B, Angove MJ (2018) Manganese oxides and their application to metal ion and contaminant removal from wastewater. J water process Eng 26:264–280. https://doi.org/10.1016/j.jwpe.2018.10.018
Kumpiene J (2010) Trace element immobilization in soil using amendments. Trace Elem soils 353–379. 10.1002/9781444319477
Laxen DP, Davison W, Woof C (1984) Manganese chemistry in rivers and streams. Geochim Cosmochim Acta 48(10):2107–2111. https://doi.org/10.1016/0016-7037(84)90390-9
Masindi V, Foteinis S, Renforth P, Ndiritu J, Maree JP, Tekere M, Chatzisymeon E (2022) Challenges and avenues for acid mine drainage treatment, beneficiation, and valorisation in circular economy: A review. Ecol Eng 183:106740. https://doi.org/10.1016/j.ecoleng.2022.106740
McKenzie RM (1972) The sorption of some heavy metals by the lower oxides of manganese. Geoderma 8(1):29–35. https://doi.org/10.1016/0016-7061(72)90030-4
Molina-Reyes MA, Piñon-Flores LF (2019) Utilización de un residuo proveniente de una planta nodulizadora de MnCO3 para el manejo de drenaje ácido. Dissertation UNAM, Faculty of Enginnering. Universidad Nacional Autónoma de México. (In Spanish). https://hdl.handle.net/20.500.14330/TES01000790551
NOM-157-SEMARNAT-2009. Norma Oficial Mexicana, que establece los elementos y procedimientos para instrumentar planes de manejo de residuos mineros, publicada en el Diario Oficial de la Federación el 12 de abril de 2010, México (in Spanish)
O’Neal SL, Zheng W (2015) Manganese toxicity upon overexposure: a decade in review. Curr Environ health Rep 2:315–328. https://doi.org/10.1007/s40572-015-0056-x
Park I, Tabelin CB, Jeon S, Li X, Seno K, Ito M, Hiroyoshi N (2019) A review of recent strategies for acid mine drainage prevention and mine tailings recycling. Chemosphere 219:588–606. https://doi.org/10.1016/j.chemosphere.2018.11.053
Pérez-Corrales D (2014) Evaluación de diferentes materiales geológicos para el tratamiento pasivo del drenaje ácido de minas, en Taxco-Guerrero. PhD Thesis, Programa Posgrado en Ciencias de la Tierra. Universidad Nacional Autónoma de México (In spanish). https://hdl.handle.net/20.500.14330/TES01000723805
Qin Q, Wang Q, Fu D, Ma J (2011) An efficient approach for Pb (II) and Cd (II) removal using manganese dioxide formed in situ. Chem Eng J 172(1):68–74. https://doi.org/10.1016/j.cej.2011.05.066
Remucal CK, Ginder-Vogel M (2014) A critical review of the reactivity of manganese oxides with organic contaminants. Environ Science: Processes Impacts 16(6):1247–1266
Rico-Malacara T (2018) Estudio de la movilidad de los elementos potencialmente tóxicos (hierro, aluminio y zinc) provenientes de drenaje ácido de mina en Taxco, Guerrero. Tesis Maestría en Ciencias de la Tierra Dissertation, Universidad Nacional Autónoma de México. (In Spanish). https://hdl.handle.net/20.500.14330/TES01000775123
Romero FM, Núñez L, Gutiérrez ME, Armienta MA, Ceniceros-Gómez AE (2011) Evaluation of the potential of indigenous calcareous shale for neutralization and removal of arsenic and heavy metals from acid mine drainage in the Taxco mining area, Mexico. Arch Environ Contam Toxicol 60(2):191–203. https://doi.org/10.1007/s00244-010-9544-z
Roth JA (2006) Homeostatic and toxic mechanisms regulating manganese uptake, retention, and elimination. Biol Res 39(1):45–57. http://dx.doi.org/10.4067/S0716-97602006000100006
RoyChowdhury A, Sarkar D, Datta R (2015) Remediation of acid mine drainage-impacted water. Curr Pollution Rep 1:131–141. https://doi.org/10.1007/s40726-015-0011-3
Ryu JG, Kim Y (2022) Mineral transformation and dissolution of jarosite coprecipitated with hazardous oxyanions and their mobility changes. J Hazard Mater 427:128283. https://doi.org/10.1016/j.jhazmat.2022.128283
Webster Jenny G, Peter J, Swedlund, Kerry S, Webster (1998) Trace Metal Adsorption onto an Acid Mine Drainage Iron(III) Oxy Hydroxy Sulfate. Environ Sci Technol 32:10, 1361–1368. https://doi.org/10.1021/es9704390
Wick S, Peña J, Voegelin A (2019) Thallium sorption onto manganese oxides. Environ Sci Technol 53(22):13168–13178. https://doi.org/10.1021/acs.est.9b04454
Xiong Y, Tong Q, Shan W, Xing Z, Wang Y, Wen S, Lou Z (2017) Arsenic transformation and adsorption by iron hydroxide/manganese dioxide doped straw activated carbon. Appl Surf Sci 416:618–627. https://doi.org/10.1016/j.apsusc.2017.04.145
Zhang C, Yu Z, Zeng G, Huang B, Dong H, Huang J, Zhang Q (2016) Phase transformation of crystalline iron oxides and their adsorption abilities for Pb and Cd. Chem Eng J 284:247–259. https://doi.org/10.1016/j.cej.2015.08.096
Zhang H, Xu F, Xue J, Chen S, Wang J, Yang Y (2020) Enhanced removal of heavy metal ions from aqueous solution using manganese dioxide-loaded biochar: Behavior and mechanism. Sci Rep 10(1):6067. https://doi.org/10.1038/s41598-020-63000-z
Zhang YX, Jia Y (2018) Fluoride adsorption on manganese carbonate: Ion-exchange based on the surface carbonate-like groups and hydroxyl groups. J Colloid Interface Sci 510:407–417. https://doi.org/10.1016/j.jcis.2017.09.090
Zhao M, Xu Y, Zhang C, Rong H, Zeng G (2016) New trends in removing heavy metals from wastewater. Appl Microbiol Biotechnol 100(15):6509–6518. https://doi.org/10.1007/s00253-016-7646-x
Zhizhaev AM, Merkulova EN (2014) Interaction of copper (II) and zinc (II) in coprecipitation from sulfate solutions with natural calcium carbonate. Russ J Appl Chem 87:16–22. https://doi.org/10.1134/S1070427214010029
Zhou D, Kim DG, Ko SO (2015) Heavy metal adsorption with biogenic manganese oxides generated by Pseudomonas putida strain MnB1. J Ind Eng Chem 24:132–139. https://doi.org/10.1016/j.jiec.2014.09.020
Zipper C, Skousen J (2014) Passive treatment of acid mine drainage. Acid Mine Drainage, Rock Drainage, and Acid Sulfate Soils: Causes, Assessment, Prediction, Prevention, and Remediation, 339–353. https://doi.org/10.1002/9781118749197.ch30

Table 1. pH, EC, and Elemental Total Concentration of metal(oids) in AMD

Code	Concentration of the elements (ICP)
Code	pH	C.E. (mS/cm)	Al (mg/L)	As (mg/L)	Fe (mg/L)	Mn (mg/L)	Cd (mg/L)	Zn (mg/L)	Pb (mg/L)
LOD (mg/L)	pH	C.E. (mS/cm)	0.2	0.1	0.1	0.2	0.1	0.1	0.02
Permissible Level (MPL for Rivers, mg/L) (NOM-001-SEMARNAT-2021)
Monthly Average	6a-9	non controlled	non controlled	0.2	non controlled	non controlled	0.2	10	0.2
Daily Average				0.3			0.3	15	0.3
Instant Value				0.4			0.4	20	0.4
P0	2.99(±) 0.5	3.03	445(±) 31.3	<LOD	263(±) 16.8	364(±) 35.6	2.82(±) 0.22	4,830(±) 322	<LOD
P1	2.8(±) 0.5	3.35	534(±) 37.5	<LOD	277(±) 17.7	417(±) 40.8	2.92(±) 0.23	5,250(±) 350	<LOD
P2	4.49(±) 0.5	2.95	133(±) 9.35	<LOD	0.17(±) 0.01	401(±) 39.2	2.71(±) 0.21	4,650(±) 310	<LOD
P3	4.22(±) 0.5	2.84	210(±) 14.8	<LOD	0.39(±) 0.02	380(±) 37.1	2.74(±) 0.21	4,710(±) 314	<LOD
P4	4.94(±) 0.5	2.75	0.32(±) 0.02	<LOD	<LOD	337(±) 33.0	2.54 (±)0.20	3,640(±) 242	<LOD
P5	4.83(±) 0.5	2.67	4.62(±) 0.33	<LOD	0.19(±) 0.01	347(±) 33.9	2.47(±)0.19	3,600(±) 240	<LOD
P6	5.25(±) 0.5	2.53	0.2(±) 0.02	<LOD	<LOD	324(±)31.7	2.25(±) 0.17	5,680(±) 379	<LOD
P7	5.34(±) 0.5	2.39	<LOD	<LOD	<LOD	312(±) 30.5	2.05(±) 0.16	2,970(±) 198	<LOD
P8	5.89(±) 0.5	2.42	<LOD	<LOD	<LOD	311(±) 30.4	1.37(±) 0.11	2,310(±) 154	<LOD
P9	6.31(±) 0.5	2.36	<LOD	<LOD	<LOD	279(±) 27.3	0.39(±) 0.03	1,110 (±) 74	<LOD

Table 2. Cd²⁺ and Zn²⁺ concentrations (mg/L) in the Minitab experiment

Code	Cd	Zn	Code	Cd	Zn
Detection limits	0.01	0.01	Detection limits	0.01	0.01
P0-R3-C1T3	2.19 ± 0.04	318 ± 3	P0-R6-C1T3	1.77 ± 0.05	241 ± 12.4
P0-R3-C2T2	1.66 ± 0.01	300 ± 7	P0-R6-C2T2	1.48 ± 0.16	214 ± 10.0
P0-R3-C2T4	1.31 ± 0.01	244 ± 4	P0-R6-C2T4	0.82 ± 0.15	117 ± 6.5
P0-R3-C3T1	1.32 ± 0.01	275 ± 5	P0-R6-C3T1	1.27 ± 0.11	182 ± 7.4
P0-R3-C3T3	0.754 ± 0.260	212 ± 12.85	P0-R6-C3T3	0.296 ± 0.33	32.8 ± 4.02
P0-R3-C3T5	0.56 ± 0.02	175 ± 17	P0-R6-C3T5	0.15 ± 0.05	10 ± 0.57
P0-R3-C4T2	0.69 ± 0.36	208 ± 21	P0-R6-C4T2	0.49 ±0.13	55.18 ± 7.9
P0-R3-C4T4	0.29 ± 0.01	137 ± 2	P0-R6-C4T4	0.03 ± 0.02	2.01 ±0.22
P0-R3-C5T3	0.38 ± 0.09	127 ± 5	P0-R6-C5T3	0.08 ± 0.01	6.29 ± 0.62
P5-R3-C1T3	1.19 ± 0.01	204 ± 6.35	P5-R6-C1T3	1.38 ± 0.11	179 ± 18.53
P5-R3-C2T2	0.66 ± 0.01	183 ± 1.0	P5-R6-C2T2	1 ± 0.18	146 ± 8.43
P5-R3-C2T4	0.67 ± 0.07	166 ± 1.27	P5-R6-C2T4	< LOD	0.35 ± 0.06
P5-R3-C3T1	0.71 ± 0.01	182 ± 1.0	P5-R6-C3T1	0.84 ± 0.07	138 ± 13.87
P5-R3-C3T3	0.31 ± 0.07	120 ± 12.9	P5-R6-C3T3	0.14 ± 0.04	12.60 ± 1.65
P5-R3-C3T5	0.27 ± 0.09	108 ± 6.54	P5-R6-C3T5	0.02 ± 0.01	0.73 ± 0.45
P5-R3-C4T2	0.18± 0.02	111 ± 11.5	P5-R6-C4T2	0.14 ± 0.01	16.9 ± 2.23
P5-R3-C4T4	0.17 ± 0.01	82 ± 11.25	P5-R6-C4T4	< LOD	0.40 ±0.11
P5-R3-C5T3	0.13 ± 0.01	72 ± 8.4	P5-R6-C5T3	< LOD	0.75 ± 0.23
P9-R3-C1T3	< LOD	33.9± 2.26	P9-R6-C1T3	< LOD	5.18 ± 0.35
P9-R3-C2T2	< LOD	23.7± 1.58	P9-R6-C2T2	< LOD	10.7 ± 0.71
P9-R3-C2T4	< LOD	4.01± 0.27	P9-R6-C2T4	< LOD	1.36 ± 0.09
P9-R3-C3T1	< LOD	27.5± 1.83	P9-R6-C3T1	< LOD	3.6± 0.24
P9-R3-C3T3	< LOD	2.99± 0.20	P9-R6-C3T3	< LOD	0.58± 0.04
P9-R3-C3T5	< LOD	0.97± 0.06	P9-R6-C3T5	< LOD	<LOD
P9-R3-C4T2	< LOD	4.16± 0.28	P9-R6-C4T2	< LOD	0.75 ± 0.05
P9-R3-C4T4	< LOD	0.63± 0.04	P9-R6-C4T4	< LOD	<LOD
P9-R3-C5T3	< LOD	1.15± 0.08	P9-R6-C5T3	< LOD	<LOD

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Removal of Metal(oids) from Acid Mine Drainage Using Manganese Oxide Wastes from a Mining-Metallurgical Process

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Abstract

Figures

1. Introduction

2. Methodology

3. Results and discussion

3.1 Characterization of AMD

3.2 Characterization of mining-metallurgical waste

3.3 Preliminary experiment

3.4 Experiment designed using Minitab Software

3.5 Zeta Potential (ZP)

4. Conclusions

Declarations

Acknowledgements

References

Tables

Supplementary Files

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