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Article

Revalorisation of Fine Recycled Concrete in Acid Mine Water Treatment: A Challenge to a Circular Economy

by
Cinta Barba-Brioso
,
Domingo Martín
,
Antonio Romero-Baena
,
Paloma Campos
and
Joaquín Delgado
*
Department of Crystallography, Mineralogy and Agricultural Chemistry, University of Seville, 41071 Seville, Spain
*
Author to whom correspondence should be addressed.
Minerals 2023, 13(8), 1028; https://doi.org/10.3390/min13081028
Submission received: 13 June 2023 / Revised: 27 July 2023 / Accepted: 28 July 2023 / Published: 31 July 2023
(This article belongs to the Special Issue Mobility of Potentially Toxic Elements: Environmental Hazards)
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Abstract

:
Currently, only 50% of concrete produced from construction and demolition waste is being recycled in Europe. This falls short of the European Union’s target of 70% by 2020. Moreover, this figure only considers coarse fractions (>4 mm), as technical issues arise when using fine fractions. In pursuit of a complete circular life for recycled concrete, this investigation explores the potential use of fine fractions to enhance the physicochemical conditions and reduce the element concentration of acid mine drainage. Two trickling sets were prepared using a filter holder, with acidic waters passing through a layer of recycled concrete aggregates. Results revealed an immediate increase in water pH to neutral levels, a reduction in solution oxidation, and the complete, or near-complete retention, of potentially toxic elements by the substrate (with retention percentages of over 99.9% for Al and Fe, between 43.1% and 61.1% for S, over 91.1% for Zn, and over 99.1% for Cu). The experiment also showed a significant increase in Ca levels (tripling the initial value) and some Mg in the water, which could promote the subsequent precipitation of carbonates and the retention of trace metals. In summary, this study demonstrates the effectiveness of using recycled concrete aggregates in a laboratory setting. Further investigation is necessary to evaluate the feasibility of implementing this technique at the pilot scale.

1. Introduction

The environmental damage caused by mining activities extend far beyond the mining spaces themselves and the large volumes of waste scattered in their surroundings. The problem of mining-related environmental pollution has been an issue of global relevance for more than a century, regardless of the products obtained from mining [1,2,3,4].
When exposed to atmospheric conditions, the waste products from coal and metal mining activities generate acid mine drainage (AMD). AMD is composed of leachates that are typically acidic, with generally low pH values, and high redox potential. This gives the solution strong solubility potential, but it also results in high spatial and temporal variability in terms of chemical composition [5,6,7]. The composition of AMD is influenced by the material it drains (soils, sediments, rocks, or even waste material). In most cases, AMD contains a high concentration of dissolved elements, with iron being the main cation, along with other transition metals and metalloids. Moreover, sulphate is the most common anion [5].
When AMD covers the soil around mining districts, it causes a significant change in terms of their reactivity and composition [8,9,10,11]. First, it leads to soil acidification, which mobilises a high proportion of elements by dissolving minerals. Furthermore, the high concentration of dissolved elements in the acidic waters continues to interact with the minerals present in the soils, leading to various reactions that involve the formation and precipitation of new phases on the soil, with varying degrees of crystallinity. In periods of drought, the effects of AMD on the soils can be observed as efflorescence salts, which consist of mineral precipitates that are mainly composed of iron and aluminium sulphates and (oxy)hydroxysulphates such as melanterite, copiapite, and halotrichite. These salts are formed due to oversaturation processes that occur after the soil reacts with the sulphate of the AMD [12].
This is a widely described environmental problem in the Iberian Pyritic Belt (IPB) at the Iberian Peninsula, affecting southwest Spain and southeast Portugal. This mining district has been exploited for 5000 years [13], and it has more than 1500 million tons of polymetallic sulfides [14].
Even though the recent reopening of the IPB mines suggests that they now align with environmental pollution prevention and remediation projects, the numerous tailing dumps distributed throughout the mining district during previous periods of exploitation have not been treated accordingly [15]. As a result, acidic water discharge continues to occur in each new rainy season, leading to continued impacts on the surrounding soils.
AMD generated from the volcanogenic deposit of massive sulfides at the IPB has been extensively studied and described, along with its effects on soils, watercourses, and biota [16,17,18,19,20,21,22]. Its affection includes the discharge of local rivers, mainly the Guadiana, Tinto, and Odiel rivers, into the Gulf of Cadiz in the Atlantic Ocean [23,24,25].
Efforts to rehabilitate areas impacted by mining activities have led to the investigation of low-cost and effective long-term solutions for mitigating the effects of acid mine drainage (AMD) on ecosystems [5,6,26]. Passive treatment systems are currently the focus of most research, with some systems utilizing tanks with reagents or settling ponds to alkalinise the water and to precipitate metallic elements and their companions [27,28,29,30]. In this vein, previous works have introduced concrete waste as a reactant in composed treatments [31].
In recent years, research into soil remediation has explored the use of Technosols, which involves mixing residual materials from various sources (e.g., industrial, agricultural) into the topsoil. This results in the creation of artificial soils that can passively promote the regeneration of environmental functions [32,33,34,35]. In line with this concept, further research should focus on identifying cost-effective residual materials that can enhance the physicochemical conditions of mined soils and improve their resilience against acid water discharge.
Construction and Demolition Wastes (C&DW) accounts for more than a third of all waste generated in the EU [36]. This represents around 461 million ton/year. Although the Waste Framework Directive 2008/98/EC aimed to have 70% of C&DW recycled by 2020, only about 50% is currently being recycled. Of this amount, it has been estimated that 52% is made up of concrete waste. Although new environmental and circular economy policies are achieving a high recycling rate for concrete, regarding the manufacturing of new recycled concrete, this is based on the exclusive use of fractions larger than 4 mm. Thus, the lower fractions (which represent approximately 40% of the concrete waste volume) are downcycled, due to technical barriers during recycling [37].
To address both issues, the use of fine concrete waste is here proposed as an amendment to AMD. In this sense, it could be used for the treatment of AMD while using waste at no cost, thus extending its life cycle as it performs a new function. This could reduce a significant quantity of construction waste, which is the objective of the European Union’s circular economy protocol and guidelines [38], and the Roadmap for the sustainable management of mineral raw materials, as set out by the Spanish Government [39]. In light of this, the specific aims of this investigation were (a) to study the changes in AMD parameters and chemical composition after the ‘trickle down’ occurs, with regard to the C&DW of concrete, via a comparison with the untreated AMD; (b) to establish mineralogical changes produced in the C&DW of concrete after irrigation with AMD to detect possible pollutant retainers; and (c) to detect the presence of the main variables that influence reactivity with AMD compounds by using different recycled concrete aggregates.

2. Materials and Methods

2.1. Materials

A 5L AMD sample was obtained from the Tinto River, via the Cascajal water mill, in the town of Paterna del Campo (Huelva); its coordinates are 37°27′33.8′′ N 6°34′29.8′′ W. The sampling occurred during the wet season, on 29 November 2021.
Two ‘all-in-one’ samples of approximately 10 kg of C&DW were provided by two companies dedicated to waste management and revalorisation: Ecoinertes and Áridos El Soto.

2.2. Methodology

2.2.1. Sample Preparation

The water sample was collected directly by submerging a polyethylene 5 L bottle in the river, and it was immediately carried to a laboratory in a cooler at 4 °C for testing. Once in the laboratory, the bottle was stirred and the water was filtered using an Albet® qualitative filter, grade 604, for the fast filtration and retention of coarse particles (>12 µm) that were present in the collected water. The filtered sample was labelled as AMD-0.
C&DW samples were labelled in laboratory as ECO (Ecoinertes sample) and SOTO (El Soto sample). Both samples of aggregates that were composed of recycled concrete were sieved at 4 mm as that is the is the legal value that distinguishes coarse aggregates from fine aggregates (Article 30.8, Royal Decree 470/2021 [40]). Once sieved, fine concrete samples were labelled EF (from ECO fine, Figure 1a) and SF (SOTO fine, Figure 1b). The granulometric distribution of the fine samples was studied in detail using a sieve tower for fine aggregates (2 mm–1 mm–630 µm–500 µm–355 µm–200 µm–100 µm–63 µm). Weights under 63 µm were labelled as “filler”, which is the term used to refer to very small particles that should be monitored when aggregates are going to be employed as construction materials.

2.2.2. Percolation Experiment

A percolating test was carried out on 150 g of samples (SF and EF) which were arranged into thicknesses of 5 cm, with 117 mm diameters, using the PSF filter holder Thermo-Fisher Scientific model 300–4050 (Figure 1c). The samples were distributed so that they covered the container and slightly compacted into a substrate. Regarding the sample, the connection to the effluent collection system had a filtration system wherein 0.22-micron filters were placed into each drainage episode, so as to isolate the aqueous solution phase. The percolation experiment consisted of 7 episodes, wherein 150 mL of AMD were added to the samples. This allowed it to percolate naturally throughout the system, without using vacuum pumps, thus allowing for the natural percolation of the AMD through the substrates. The experiment lasted for 33 days, with AMD additions on days 1, 2, 7, 27, 28, 29, and 33.

2.2.3. Parameter Determination and Chemical Analysis

An aliquot of 25 mL AMD-0 was taken to measure pH, redox potential, and electrical conductivity (EC). Moreover, recycled aggregates were prepared in a solid/distilled water ratio of 1:2.5. Determining the pH and redox potential was achieved using a portable Crison® instrument 507 equipped with electrode 5200. Electrical conductivity was measured using a portable conductivity meter, Crison® 524.
The analytical characterisation of solutions was conducted using the Microanalysis Service of the Research Services Department of Seville University (CITIUS). Prior to the experiment, the AMD was chemically analysed, and after each percolating process, the resulting leachate from the C&DW samples was determined using an ICP-OES analysis performed on a SpectroBlue TI instrument. The key elements involved in the AMD–C&DW reactions, including S, Ca, Mg, Al, Fe, As, Cd, Cu, Pb, and Zn, were analysed. The limits of detection for the mentioned elements (in ppm) were 0.003 for S, Ca, and Mg; 0.001 for Al, Fe, Cd, Cu, and Zn; 0.004 for As; and 0.01 for Pb.
In addition, samples SF and EF were chemically analysed for major and trace elements before and after the experiment; the experiment used the X-ray Service of the Research Services Department of Seville University (CITIUS). These analyses were carried out in a Panalytical Zetium (XRF) spectrometer to assess X-ray fluorescence. The total concentrations for major elements (Al, Ca, Fe, K, Mg, Na, P, S, Si, and Ti) and trace elements (As, Cr, Cu, Ni, Pb, and Zn) were determined and compared against Panalyitical Wroxi-CRM (for major elements) and Panalytical Protrace standards (trace elements). The limits of detection for the principal major elements (in oxide weight %) were 0.01 for Al2O3 and SO3; 0.02 for MgO; 0.03 for CaO; and 0.04 for Fe2O3. Detection limits for trace elements (in mg kg−1) were 3.1 for As; 0.4 for Cd and Zn; 0.1 for Cu; and 0.7 for Pb.

2.2.4. Mineralogical Study

Mineralogical characterisation was conducted using the X-ray Service of the Research Services department of Seville University (CITIUS). This included the following steps. (1) Identification and quantification of the present minerals in concrete samples before and after the experiment using a Bruker D-8 Advance A25 X-ray diffractometer. The main components of the instrument were as follows: Cu Kα monochromatic radiation operated at 40 kV and 30 mA; a 2 g sample that was milled under 50 µm and randomly deposited on holders, which were scanned from 3° to 70° 2θ, with a step size of 0.03° 2θ, and a counting time of 1 s per step. The diffraction results were interpreted using the software, Diffrac. Eva, by Bruker®. The semi-quantification of minerals was achieved using Match® software and the PDF2 database for mineral standards, in accordance with the intensity parameter I/Ic. (2) Observation via scanning electron microscopy (SEM) on a Dual Beam ZEISS Auriga, coupled with energy dispersive X-ray spectroscopy (EDS), acquired at a 20 kV accelerating voltage, assisted with the identification of accessory minerals of environmental concern.

2.2.5. Geochemical Modelling

PHREEQC software from the U.S. Geological Survey was used to perform the geochemical modelling of waters in the experiment. The PHREEQC program (interactive version 3.3 [41]) was used for calculating the activity and chemical speciation of dissolved species, as well as the saturation index of minerals [SI = log(IAP/KS)], where SI is the saturation index, IAP is the ion activity product, and KS is the solid solubility product in the parent solutions [42]. Zero, negative, and positive SI values indicate that the solutions are saturated, undersaturated, and supersaturated, respectively, with respect to the solid phase. For a state of supersaturation, precipitation of the solid phase is expected.
The thermodynamic database of PHREEQC was enlarged using data from the geochemical code, WATEQ4F [43]. The solubility constants (KS = 1.84) from the literature [44,45] were used for other minerals such as schwertmannite (not included in the software database).

3. Results

3.1. Characterisation of Initial Materials

The granulometry of SF and EF showed different distributions (Table 1). SF had a wider grain distribution among all the fractions comprising fine aggregates (<4 mm); the highest weight was over 2 mm (28.64%). Each one of the other fractions represented more than 5%, except the fraction between 100 and 63 µm, which had the lowest representation (3.78%). Conversely, EF particles were mainly concentrated between 2 and 4 mm (69.91%), with 10.24% particles in a range of 1–2 mm, and the rest of the fractions representing values under 4%. These differences in grain size distribution were an important parameter to study as the reactivity of concrete minerals is dependent on their grain size [46].
The DR-X study of the aggregates, which occurred before the percolation experiment, showed a typical mineralogy of the C&DW that was made of concrete (Table 1). Diffractograms of both samples, SF (Figure 2) and EF (Figure 3), showed that the presence of dolomite (45% and 41%, respectively), quartz (17% and 27%), calcite (19% and 12%), gypsum (<5% and 6%), feldspars (9% and <5%), biotite (<5% and 6%), chlorite (8% and <5%), paragonite (<5%), and cement, results in reaction products like calcium aluminate and calcium silicate (<5%).
The main elements present in SF and EF were (in oxide form, Table 1) CaO (26.85% in SF and 20.64% in EF) and SiO2 (21.99% in SF and 33.75% in EF). The rest of the elements were present in different percentages in each sample, but always below 10%. The chemical composition was consistent, in accordance with the obtained mineralogy, with calcium and magnesium carbonates being the main minerals. Gypsum was also present, and almost all of the remaining minerals were silicates, which explained the high SiO2 content.
The AMD extracted from the Tinto River exhibited a high level of acidity, with a mean pH value of 2.4. Electrical conductivity revealed values of 11.62 mS cm−1, and the redox potential (EH conversed) was 653 mV (AMD-0 in Table 2). These results are consistent with the findings of previous studies [16], which documented the presence of an acidic and oxidative aqueous environment. Although electrical conductivity is a highly variable parameter, the values obtained in this study fall within the mean range of the Tinto River, indicating a high load of dissolved salts in its waters.
In contrast, samples EF and SF exhibited similar pH (mean value of 10.1), electrical conductivity (1046 µS cm−1), and EhH (124 mV) values. These results are promising, as they suggest a high degree of alkalinisation and an antioxidative effect is expected from the concrete aggregates.
The chemical composition of AMD (AMD-0 in Table 2) was consistent with previous studies on mine drainage [16,19]. It contained 2.67 g L−1 S, 1059 mg L−1 Fe, 459 mg L−1 Al, 376 mg L−1 Mg, 258 mg L−1 Ca, 98.6 mg L−1 Zn, and 66.5 mg L−1 Cu. Arsenic, Pb, and Cd fell below the detection limit in the solution.

3.2. AMD Response to Percolation Experiment

During the first day of experiment, AMD drastically changed in terms of its original reaction and composition after percolating through the system. The pH value drastically increased from 2.4 to 7.6 in both cases (AMD-S1 and AMD-E1), reaching neutral conditions (Table 2) which were similar or even better than the results obtained in other experiments, which incurred more costs and encountered more difficulties [30,49]. Indeed, EhH was reduced by more than 350 units in both filter systems, down to 275 mV in AMD-S1, and 269 mV in AMD-E1, thus revealing the losses that occur in strongly oxidizing conditions. Lastly, EC also showed a reduction, with values below 10 (7.57 in AMD-S1 and 9.27 in AMD-E1); the EPA established this as the limit between freshwater streams and industrial wastewater. The chemistry of AMD also changed after crossing the concrete aggregate layers in the first trickling (Figure 4). Aluminium and iron were completely removed from the solution in AMD-S1, and in AMD-S2, the values fell to 0.030 and 0.091 mg L−1. Sulfur was partially removed from the solution, but its concentrations were still very high (1.04 g L−1 in AMD-S1 and 1.02 g L−1 AMD-E1). Conversely, Ca increased in the solution to 801 and 885 mg L−1 (in AMD-S1 and AMD-E1, respectively). Magnesium experienced a slight change (from 376 mg L−1 to 341 mg L−1 in AMD-S1 and to 333 mg L−1 in AMD-E1).
Regarding the minor elements studied, the first percolation almost achieved Cu and Zn removal in solutions AMD-S1 (Figure 4a) and AMD-E1 (Figure 4b), with values of 0.157 and 0.205 for Cu, and 0.096 and 0.136 for Zn.
On the second day of the experiment, a new AMD inundation was carried out with the samples that were still wet from the previous day. Subsequent irrigations were produced on days 7, 27, 28, 29, and 33, with the aim of simultaneous rainfall events. During these episodes, the aggregate response hardly changed with respect to the first rain simulation. These changes were generally marked by a decreasing trend in the salinity of leachates (Table 2). Regarding the concentration of elements, aluminium was detected in AMD-S in very low concentrations, generally under 0.04 mg L−1, except for day 27 (AMD-S-5), when 0.3 mg L−1 were measured in the solution. Leachates in AMD-E presented fewer Al components in the solution, and the maximum value was registered in AMD-E-5 (0.039 mg L−1). Day 27 produced the maximum values for the rest of the major elements, Ca, Mg, and S, indicating that some changes in the system occurred with respect to the rest of episodes. This trend was different than that of Fe; the Fe concentration that dissolved was also very low for both experiments, but it presented its maximum leachate value on day 2 (AMD-S-2 0.195 mg L−1 and AMD-E-2 0.097 mg L−1). The trace elements, Cu and Zn, were different in terms of behaviour. Although Cu was always extracted in very low concentrations, under 0.6 mg L−1, the concentrations of Zn in percolated solutions increased towards the end of the treatment, suggesting a loss in efficiency of the recycled aggregates in terms of retaining zinc over time. Thus, at the end of the experiment, 7.9 mg L−1 Zn was obtained from AMD-S and 12 mg L−1 Zn was obtained from AMD-E. Moreover, concentrations of all the elements of the leachates were below the regulatory limits for wastewaters in Spain; only the E.C. values were over the limit (Table 2).

3.3. Changes in the Mineralogy and Geochemistry of Aggregates after the Experiment

The effect of AMD percolation on the recycled aggregates was evident due to changes in their appearance (Figure 5), which occurred due to slight mineralogical and compositional changes.
Although most of the minerals that were initially in the samples remained after the experiment, changes in their proportions were observed, as was the presence of neoformed traces of jarosite; this was a consequence of the precipitation of substances from AMD (Figure 2). A clear reduction in calcite and dolomite proportions was also detected.
The study of chemical compositions and electron microscopy were completed using XRD observations. Major elements such as aluminum, iron, and sulfur increased their proportions, whereas calcium, magnesium, and silica decreased their proportions (Table 3). In the final samples, the main trace elements related to AMD were also measured, and very high concentrations of copper and zinc were revealed in the aggregates.

4. Discussion

4.1. Parameters Involved in AMD Improvement

The water sample taken from the Tinto River revealed the impact of mine waste drainage along the hydrographic basin. Although it was collected far away from the mine site, along the course of the river, it still showed typical characteristics of AMD, which are also characteristics of the Tinto River: low pH, high redox potential, and electrical conductivity [18,19]. Moreover, the alkalinity of the recycled concrete aggregates, which are mainly composed of carbonates, as well as the reactiveness of their mineralogy, meant that they were good raw materials for the experiment. Previous studies have confirmed the usefulness of other concrete aggregates that are composed only of calcite when neutralizing simulated AMD [46,50,51]. The employed aggregates were mainly composed of dolomite, and they act as sources of Mg which can be applied to solutions for use in passive treatments in recent years, this has occurred to obtain more durable reactions and higher alkalinity than calcite.
The effect of the grain size of aggregates was tested by using two aggregates with different textures. Although the SF sample showed a more continuous granulometry, the EF particles were concentrated between 2 and 4 mm. This parameter influenced the mineralogy as SF contained higher proportions of reactive materials (sum of carbonates: 64%) than EF (sum of carbonates: 53%). This could be of interest in the medium-term, as it affects the effectiveness of the treatment. Previous studies have demonstrated that higher dosages and smaller particle sizes of concrete aggregates result in a better neutralisation performance [46].
Nevertheless, alkalinity was not as high as in the aforementioned study, wherein pHs of 12 were achieved; this was due to differences in experimental conditions. Differences could be found in water pressure influence, as Jones and Cetin [51] compacted the aggregates in pressure columns, or in the use of simulated concrete, as in the experiments conducted by Ho et al. [46]. In the present study, water leached the aggregates via gravity, without any mixing or added pressure, to obtain the most realistic field conditions. The moderately alkaline pH observed in this study could potentially have a positive effect on metal cation precipitations, as mentioned in the works of Jones and Cetin, who reported an increase in the electrical conductivity of AMD, which is typically associated with the dissolution of cations in highly alkaline environments [52].
Trickling promoted the effective retention of AMD contaminants using the aggregates and the partial dissolution of carbonate compounds. This dissolution resulted in an immediate increase in pH, leading to neutralisation, and even slight alkalinisation [51]. These favorable conditions remained stable throughout the experiment, indicating that the aggregates continued to exhibit activity. Additionally, the content of calcium (expressed as CaO) only decreased by 3%, and magnesium (as MgO) decreased by 2% in both samples, despite the repeated addition of highly acidic water (Table 3).
The process of AMD neutralisation also involved a reaction with the aggregates, leading to the precipitation of an ochreous disseminated deck of aluminium and iron oxyhydroxide or hydroxysulphate over the particles of the aggregates which were visible to the naked eye (Figure 5). SEM analysis provided a more detailed image of the nanoprecipitates (Figure 6a) that were formed over the gypsum, carbonate, or silicate particles previously present in the samples. Precipitates appeared as spheroidal and lentil-shaped particles, mainly composed of Fe and Al, with minor amounts of S, and traces of Cu (Figure 6b). Although chemical analyses indicated some retention of Zn by the aggregates, it was not detected by the EDAX analyses at SEM. The reactivity of the experiment mainly occurred in the upper and lower millimeters of the aggregates, and due to the low crystallinity of the minerals forming the precipitated layer, the changes were practically not observable by the DRX.
Nevertheless, a characteristic peak of jarosite was observed by the DRX (Figure 2) from the thin layer precipitated at the top of the SFU (Figure 5). The high contrast between the AMD and alkaline aggregates promoted the formation of a reactive layer due to the fast increase in pH value on the contact surface. This allowed the precipitation of the initial products of the neutralisation process; most products were amorphous Fe compounds, but jarosite compounds were also found at a stable phase at a low pH [53]. Since most of the Fe reacted in this top layer, the Fe in the solution was progressively depleted, thus promoting the presence of phases with progressively more aluminium from the jarosite-alunite group, which were found in the thickness of the aggregates. This group is defined as M(FexAlyCrz)(SO4)2(OH)6, in which “M” may be Na+, K+, NH4+, or H3O+, and x + y + z=3. For x = 3, the formula represents jarosite, whereas for y = 3, it represents alunite [54].
Finally, some scattered crystals of ettringite, typical of concrete samples, were visible on the samples, although they were not detected by DRX (acicular crystals in Figure 6b).

4.2. Hydrochemical Modelling of Aggregate–AMD Interactions

To gain a deeper understanding of the interactions between AMD and recycled aggregates, the leachates obtained over the course of the experiment were subjected to modelling, as minimal changes in mineralogy were observed. This modelling aimed to explain the potential evolution of mineral phases that could form throughout the treatment period, based on the main dissolved species. The predominant species in the solution were Mg+2 (22%), AlSO4+ (17%), Al+3 (10%), SO4−2 (10%), and Ca+2 (9%), followed by various Fe(III) species (Fe+3, FeSO4+, FeOH+2, Fe3OH+5 and Fe2OH2+4) (Figure 7). However, the Fe(II) species were almost absent. This can be attributed to the sampling point of the AMD, which was downstream of the Tinto River, wherein the neutralisation and dilution processes had already commenced.
In accordance with the model in AMD-0, amorphous Fe oxy-hydroxy-sulphates such as ferrihydrite (FeOH3), lepidocrocite [FeOOH], H-jarosite [(H3O)Fe3(SO4)2(OH)6], and schwertmannite [Fe8O8(OH)6(SO4)] (Figure 8) were saturated at acidic pH values (2.4). These phases are likely to be responsible for the remotion of Fe, Al, sulphates, and minor amounts of trace elements in the solution. As the pH increases, the precipitation of aluminium species becomes significant, as they are largely influenced by adsorption–coprecipitation and iron-rich sulphates [52], as explained by Nordstrom and Alpers [12]. Additionally, concentrations of Cu and Zn can be somewhat reduced through coprecipitation processes involving jarosite and schwertmannite [55], as well as ferrihydrite-rich phases [56]. This latter is considered the main initial product of the oxidation and precipitation processes of ferrous iron-bearing solutions under near-neutral pH conditions on the surface [57].
In accordance with previous experiments on AMD treatment [27,58], and supported by the obtained data, the dissolution of dolomite and calcite in an acidic environment promoted increases in pH values to above 6. This increase in pH would have induced the formation of ochreous precipitates, which include low-crystalline hydroxylated and sulphated Fe and Al phases [42,59]. Additionally, when AMD leached the SF aggregate (sample AMD-S-1, Figure 7), there was a significant increase in the presence of divalent species of Ca and Mg in the solution. Under these conditions, an effective neutralisation of acidity occurred.
Based on the literature, the precipitation of aluminium phases, such as alunite or its precursor, basaluminite, is common at pH values ranging from 3.3 to 5.7. However, in the present study, both the hydrochemical model and the diffraction study did not indicate the presence of these minerals. Nevertheless, SEM–EDS analysis revealed chemical compositions within the range of the jarosite–alunite group (Figure 6b), wherein substitutions of Al for Fe are frequent [54]. As the pH increased, the model predicted that the pre-existing dissolved Al and SO42− species played a significant role in the solution, whereas the concentration of Fe decreased over time. The Fe was progressively replaced by low-crystalline Al hydroxides such as diaspore [AlOOH] (sample AMD-S-4, Figure 8), boehmite, and gibbsite [Al(OH)3] (sample AMD-S-7) [27].
Furthermore, Cu sulphates such as brochantite [Cu3(OH)4SO4], antlerite [Cu4(OH)6SO4], and langite [Cu4(OH)6SO4·H2O] were found to be supersaturated (Figure 8), and they were accompanied by a significant reduction in Cu concentration in the solution (Figure 3). These minerals are frequently described as stable phases when high sulphate and Cu concentrations occur in near-neutral conditions [60]. However, mineralogical studies of solid wastes generated from AMD treatment suggest that their presence is difficult to confirm [61]. In the present study, Cu was observed using SEM images associated with Al-Fe oxy-hydroxy-sulphates (jarosite-alunite type); these are likely to be related to coprecipitation processes, as previous studies have demonstrated [55].
Analogous results were obtained regarding the main species present in the solution after trickling the EF aggregate (speciation not plotted). However, slight differences were observed in the saturation index (SI) of minerals, such as the coexistence of Fe and Al mineral phases during the initial stage of treatment in Sample AMD-E-1. This phenomenon could be attributed to a higher infiltration rate of the AMD through the EF aggregate, resulting in a shorter reaction time when reactive Ca and Mg phases were used. This lower initial reactivity rate can be attributed to the disparity in particle size distribution between the aggregates. EF, with over 80% of particles larger than 1 mm, has a lower surface area available for reactions, leading to lower efficiency in the treatment process. The treatment exhibited similar neutralisation conditions to those observed in the SF aggregate. The Fe and Al minerals in the solution were predominantly undersaturated, except for lepidocrocite. The presence of brochantite at this advanced stage also indicated the progress of the treatment.
Based on the hydrochemical conditions and PHREEQC data, a direct relationship between Cu–Zn and sulphates at a near-neutral pH was found. Recent research on AMD passive treatment [27] showed that a higher efficiency regarding Cu and Zn retention is likely determined by Cu/Zn-rich phases such as antlerite and brochantite. In accordance with other studies [52,62], it was generally observed that the most effective retention, regarding divalent metals that used hydroxides, occurs when the pH is between 8 and 10. However, the optimal pH was not achieved in the experiment under consideration. This likely explains the low proportions of Cu and Zn sulphates (Cu/ZnSO4), determined as dissolved species, in the solution (Figure 7).
Finally, the chemical data indicate that the dissolution of Cu and Zn occurred at a later stage (1 month, sample AMD-E-7), coinciding with a slight increase in the concentrations of Fe and Al in the solution. The model supported this observation, suggesting that minerals such as lepidocrocite, ferrihydrite, diaspore, or gibbsite may once again reach positive saturation levels (Figure 8). This phenomenon can be attributed to the intensive and continuous leaching of aggregates over 3 days, which hindered the formation of Fe–Al-rich phases and promoted the re-dissolution of low-crystalline sulphate efflorescence. This effect has been extensively described in AMD sources during the wet season when rainfall occurs [63,64].

5. Conclusions

Recycled fine concrete aggregates exhibit high reactivity and significant neutralizing potential against acidic solutions, primarily due to the presence of Ca and Mg carbonates. The rapid increase in Ca concentration in the solution initiates the neutralisation process, whereas the progressive dissolution of Mg ensures the long-term effectiveness of the treatment. Grain size differences among the samples did not appear to influence the mineralogy of the precipitates over the duration of the treatment. However, smaller particle sizes promoted a reduction in the number of metal species in the solution, indicating a higher retention capacity of the aggregates.
The percolation experiment successfully reduced the pollutant load of the AMD, with retention percentages close to 100% for Al, Fe, and Cu, over 90% for Zn, and slightly lower percentages for S, averaging around 50%.
X-ray diffraction analysis identified traces of ochre minerals such as jarosite, which formed as a result of AMD acidity neutralisation. The combined geochemical study, including electron microscopy observations and the hydrochemical modelling of the leachates generated during the treatment, provided insights into the composition of the newly formed phases that are responsible for metal retention. The neutralisation process was primarily governed by the precipitation of Fe- and Al-oxyhydroxysulphate nanoparticles from the jarosite–alunite group, which exhibited the ability to retain trace elements, particularly Cu.
The results of the laboratory-scale percolation experiment demonstrate that recycled fine aggregates are a promising option for treating AMD, as they can be used without requiring any prior processing, thereby contributing to the sustainable life cycle of a material that was previously considered waste.
This study represents an initial and fundamental step towards understanding the interactions between recycled aggregates and AMD within natural systems. It is important to acknowledge that potential challenges may arise, such as the potential decline in reactivity of the substrate over longer time scales or a potential decrease in efficiency when applied to mined soils. To address these concerns, future research will focus on examining the behaviour of these recycled aggregates within mined soils over an extended time period. This research will also involve studying the performance of different proportions of aggregates to determine the optimal ratio that ensures sustained reactivity and efficiency over time.

Author Contributions

Conceptualization, C.B.-B. and J.D.; Methodology, C.B.-B., D.M., A.R.-B. and P.C.; Validation, J.D.; Formal analysis, J.D.; Investigation, C.B.-B.; Resources, D.M.; Data curation, C.B.-B.; Writing—original draft, C.B.-B.; Writing—review & editing, C.B.-B., D.M., A.R.-B. and J.D.; Supervision, J.D. All authors have read and agreed to the published version of the manuscript.

Funding

This research received no external funding.

Data Availability Statement

Data is contained within the article.

Acknowledgments

The authors acknowledge the supply of recycled aggregates by Ecoinertes S.L. and Áridos El Soto S.L.

Conflicts of Interest

The authors declare no conflict of interest.

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Minerals 13 01028 g001 550
Figure 1. Images showing the components of the experiment. (a) EF aggregate in a 200 mm diameter sieve; (b) SF aggregate in a 200 mm diameter sieve; (c) percolation system.
Figure 1. Images showing the components of the experiment. (a) EF aggregate in a 200 mm diameter sieve; (b) SF aggregate in a 200 mm diameter sieve; (c) percolation system.
Minerals 13 01028 g001
Minerals 13 01028 g002 550
Figure 2. X-ray random powder diffractogram of sample SF (initial recycled aggregate) and SFU (residual aggregate). SFU intensity increased by 800 counts for vertical displacement, with comparative purposes. The abbreviations of the minerals are in accordance with those of the International Mineralogical Association IMA [47].
Figure 2. X-ray random powder diffractogram of sample SF (initial recycled aggregate) and SFU (residual aggregate). SFU intensity increased by 800 counts for vertical displacement, with comparative purposes. The abbreviations of the minerals are in accordance with those of the International Mineralogical Association IMA [47].
Minerals 13 01028 g002
Minerals 13 01028 g003 550
Figure 3. X-ray random powder diffractogram of sample EF (initial recycled aggregate) and EFU (residual aggregate). EFU intensity increased by 800 counts for vertical displacement, with comparative purposes. The abbreviations of the minerals are in accordance with the IMA [47].
Figure 3. X-ray random powder diffractogram of sample EF (initial recycled aggregate) and EFU (residual aggregate). EFU intensity increased by 800 counts for vertical displacement, with comparative purposes. The abbreviations of the minerals are in accordance with the IMA [47].
Minerals 13 01028 g003
Minerals 13 01028 g004 550
Figure 4. Graphs showing the evolution of element concentration in leachates (ppm) throughout the experiment. (a) SF leachates; (b) EF leachates.
Figure 4. Graphs showing the evolution of element concentration in leachates (ppm) throughout the experiment. (a) SF leachates; (b) EF leachates.
Minerals 13 01028 g004
Minerals 13 01028 g005 550
Figure 5. Appearance of the aggregates after the experiment; an ochreous deck is visible to the naked eye across the surfaces of the samples (a) SFU (b) EFU.
Figure 5. Appearance of the aggregates after the experiment; an ochreous deck is visible to the naked eye across the surfaces of the samples (a) SFU (b) EFU.
Minerals 13 01028 g005
Minerals 13 01028 g006 550
Figure 6. SEM images of the aggregates after the percolation experiment. (a) General image showing many gypsum particles. (b) Detail of the precipitates of Fe–Al formed on the reaction surfaces. EDAX punctual analyses are identified using color dots in Figure 6b.
Figure 6. SEM images of the aggregates after the percolation experiment. (a) General image showing many gypsum particles. (b) Detail of the precipitates of Fe–Al formed on the reaction surfaces. EDAX punctual analyses are identified using color dots in Figure 6b.
Minerals 13 01028 g006
Minerals 13 01028 g007 550
Figure 7. Example of the PHREEQC speciation of AMD and leachate solutions 1, 4, and 7, obtained from SF aggregate (species in solution < 1% have not been plotted).
Figure 7. Example of the PHREEQC speciation of AMD and leachate solutions 1, 4, and 7, obtained from SF aggregate (species in solution < 1% have not been plotted).
Minerals 13 01028 g007
Minerals 13 01028 g008 550
Figure 8. Bar chart showing the most relevant mineral saturation indexes (SI) controlling trace element retention. * IS of schwertmannite has been calculated in accordance with Yu et al. [44] Hematite, goethite, and maghemite showed a positive saturation index, but this has not been taken into consideration due to their slow precipitation kinetics and specific formation conditions [45,56].
Figure 8. Bar chart showing the most relevant mineral saturation indexes (SI) controlling trace element retention. * IS of schwertmannite has been calculated in accordance with Yu et al. [44] Hematite, goethite, and maghemite showed a positive saturation index, but this has not been taken into consideration due to their slow precipitation kinetics and specific formation conditions [45,56].
Minerals 13 01028 g008
Table
Table 1. Resumed characterisation of recycled aggregates SF and EF.
Table 1. Resumed characterisation of recycled aggregates SF and EF.
Grain Size DistributionChemical CompositionMineralogy
SFEF SFEF SFEF
Sieve% RetainedElementWeight %MineralWeight % (±5%)
2 mm28.6469.91SiO221.9933.75Dolomite Dol4541
1 mm24.6210.24Al2O34.606.88Quartz Qz1727
630 µm11.203.80Fe2O32.012.67Calcite Cal1912
500 µm4.922.00MnON.C.0.04Gypsum Gptr6
355 µm5.762.11MgO9.077.38Feldspars Fsp9tr
200 µm7.503.06CaO26.8520.64Biotite Bttr6
100 µm6.522.90Na2O0.220.35Chlorite Chl8tr
63 µm3.703.65K2O0.831.13Paragonite Pgtrtr
Filler6.521.81TiO20.230.36Ca-silicatetrtr
Total recovered99.3899.48P2O50.110.09Ca-aluminatetrtr
SO31.033.10
PC32.0423.76
TOTAL99.01100.14
tr trace percentage (less than 5%); PC lost on ignition.
Table
Table 2. Hydrochemical parameters and chemical composition of AMD (AMD-0); leachates obtained with SF (AMD-S-1 to AMD-S-8) and EF (AMD-E-1 to AMD-E-8). RSD calculated using three measures. * RSD without value (result under detection limit). RL Regulatory limit [48]. n.d. no reported data.
Table 2. Hydrochemical parameters and chemical composition of AMD (AMD-0); leachates obtained with SF (AMD-S-1 to AMD-S-8) and EF (AMD-E-1 to AMD-E-8). RSD calculated using three measures. * RSD without value (result under detection limit). RL Regulatory limit [48]. n.d. no reported data.
Sample AMD-0AMD-S-1AMD-S-2AMD-S-4AMD-S-5AMD-S-6AMD-S-7AMD-S-8RL *
Test Day012727282933
pH2.47.67.67.87.87.87.67.66 to 9
Eh (mV)851473480487477487494481n.d.
CE (mS cm−1)11.627.577.588.176.626.065.785.655
Al mg/L459≤0.0010.0280.0050.30.040.0210.01815
RSD2.21*5.498.020.780.710.591.03
Ca mg/L258801736679859723719733n.d.
RSD9.851.11.20.260.620.490.250.48
Fe mg/L1059≤0.0010.195≤0.0010.0990.037≤0.0010.01310
RSD1.81*2.25*0.972.46*9.24
Mg mg/L376341413489679463388482n.d.
RSD0.440.910.980.650.21.021.140.23
S g/L2.671.041.11.211.511.271.191.262
RSD0.310.540.720.440.530.210.890.43
Zn mg/L98.60.0960.0220.0763.833.398.787.9210
RSD2.645.114.40.550.260.480.20.8
Cu mg/L66.50.157≤0.0010.0190.580.1540.1220.1075
RSD8.858.86*9.383.381.322.583.37
SampleAMD-0AMD-E-1AMD-E-2AMD-E-4AMD-E-5AMD-E-6AMD-E-7AMD-E-8RL *
Test Day012727282933
pH2.47.67.77.87.87.57.57.66 to 9
Eh (mV)851467475488476479489477n.d.
CE (mS cm−1)11.629.278.058.526.576.476.035.95
Al mg/L4590.030.023≤0.0010.0390.0170.0150.02815
RSD2.214.871.32*0.330.980.413.4
Ca mg/L258885743733801739725701n.d.
RSD9.850.40.481.450.662.150.490.76
Fe mg/L10590.0910.097≤0.0010.0170.0210.0080.01110
RSD1.811.80.38*2.572.260.681.62
Mg mg/L376333414473666528468534n.d.
RSD0.440.110.360.620.260.510.370.69
S g/L2.671.021.071.291.541.431.291.282
RSD0.310.960.910.390.680.980.550.16
Zn mg/L98.60.1360.0350.7170.3122.826.131210
RSD2.640.621.110.781.820.570.760.21
Cu mg/L66.50.2050.0610.0270.1360.1470.1420.2295
RSD8.851.514.852.792.243.093.133.59
Table
Table 3. Chemical composition of the main and trace elements of aggregates after the lixiviation test.
Table 3. Chemical composition of the main and trace elements of aggregates after the lixiviation test.
Major Elements (%)Trace Elements (mg kg−1)
SiO2Al2O3Fe2O3MnOMgOCaONa2OK2OTiO2P2O5SO3AsCdCoCrCuPbZn
SFU20.947.196.450.086.9323.150.240.780.260.113.9331.28.737.940.2200331.51438
EFU27.218.187.050.086.5417.950.350.960.320.114.4732.06.529.045.3183647.01093
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Barba-Brioso, C.; Martín, D.; Romero-Baena, A.; Campos, P.; Delgado, J. Revalorisation of Fine Recycled Concrete in Acid Mine Water Treatment: A Challenge to a Circular Economy. Minerals 2023, 13, 1028. https://doi.org/10.3390/min13081028

AMA Style

Barba-Brioso C, Martín D, Romero-Baena A, Campos P, Delgado J. Revalorisation of Fine Recycled Concrete in Acid Mine Water Treatment: A Challenge to a Circular Economy. Minerals. 2023; 13(8):1028. https://doi.org/10.3390/min13081028

Chicago/Turabian Style

Barba-Brioso, Cinta, Domingo Martín, Antonio Romero-Baena, Paloma Campos, and Joaquín Delgado. 2023. "Revalorisation of Fine Recycled Concrete in Acid Mine Water Treatment: A Challenge to a Circular Economy" Minerals 13, no. 8: 1028. https://doi.org/10.3390/min13081028

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