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Article

Assessment of Acute Toxicity of Acid Mine Drainage via Toxicity Identification Evaluation (TIE) Using Daphnia magna and Chlorella vulgaris

by
Carol Burgos
1,
Soledad Chamorro
1,
Naomi Monsalves
1,2,
Gloria Gómez
1,2 and
Gladys Vidal
1,2,*
1
Environmental Engineering & Biotechnology Group (GIBA-UDEC), Environmental Science Faculty, Universidad de Concepción, Concepción 4030000, Chile
2
Water Research Center for Agriculture and Mining (CRHIAM), ANID Fondap Center, Victoria 1295, Concepción 4070386, Chile
*
Author to whom correspondence should be addressed.
Water 2025, 17(9), 1313; https://doi.org/10.3390/w17091313
Submission received: 31 March 2025 / Revised: 21 April 2025 / Accepted: 26 April 2025 / Published: 28 April 2025
(This article belongs to the Section Water Quality and Contamination)
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Abstract

:
Acid mine drainage (AMD) is one of the main environmental problems in mining operations. The objective of this study was to assess AMD obtained from a copper mine via toxicity identification evaluation (TIE) using Daphnia magna and Chlorella vulgaris as indicator organisms. AMD was fractionated via filtration and aeration at pH 3 and 11, activated carbon, cation resin, anion resin, and ethylenediaminetetraacetic acid (EDTA). The results showed that unfractionated AMD has a low organic matter content (total chemical organic demand, CODT-183.05 mg/L), low pH (3.9), and high sulfates concentrations (2900 mg/L) and metal ions in solution (0.2–418.9 mg/L), producing high toxicity to Daphnia magna (0.00016% v/v) and no observable acute toxicity to Chlorella vulgaris (72 h-RFU 64.9%). For Daphnia magna, TIE fractionations with the greatest reduction in acute toxicity (LC50) were filtration/pH11 (non-toxic) and anion resin (LC50 = 0.43% v/v), with toxicity reduction percentages of 100% and 99%, respectively. Because of this, Cu was determined to be the main cause of acute toxicity to Daphnia magna. For Chlorella vulgaris, the activated carbon fraction stands out, increasing the % relative fluorescence units by 4% from 48 h to 72 h, demonstrating tolerance to AMD. The TIE technique is presented as an effective strategy to identify toxic compounds in complex samples and evaluate their effect on environmentally relevant organisms. Therefore, this study allows the analysis of the ecological risk in aquatic environments affected by mining activities, which supports environmental decision-making and the design of efficient treatment strategies.

1. Introduction

The mining industry is the main cause of a significant imbalance in the natural ecosystem due to the generation of waste such as mine water, waste rock, and mine tailings [1]. This last item is solid waste resulting from mineral processing that, due to the oxidation of sulfide-type minerals (pyrite, chalcopyrite, arsenopyrite), can generate acid mine drainage (AMD) [2]. AMD presents a pH below 4, low salinity, high solubility, and corrosivity. Among its components are high concentrations of sulfates and very high concentrations of dissolved metals [3,4]. In addition, the acid generated can cause the dissolution of other mineral phases that contain potentially toxic elements such as As, Cd, Pb, Cu, and Zn [5,6]. These compounds in both active and abandoned mines are released continuously into the environment over decades and millennia [7], contaminating both nearby and distant bodies of water and affecting them at chemical, physical, biological, and ecological levels [4].
Acute toxicity tests are necessary to complement chemical measurements, as they are useful for assessing the biological effects of chemical products in wastewater; therefore, it is essential to evaluate the ecotoxicity of wastewater to organisms exposed to it [8]. Toxicity identification evaluation (TIE) is a toxicological technique that allows compounds causing acute toxicity in a complex mixture to be detected, identified, and confirmed [9,10]. High metal concentrations can affect freshwater species such as microalgae, microcrustaceans, and fish [7]. The toxicity of AMD to diverse indicator organisms such as Zebrafish (LC50 < 0.08%), Daphnia sp. (LC50 < 1%), diatoms, and Tilapia sp. has previously been reported [11].
Daphnia magna is a microcrustacean used as an indicator of river health since it serves as food for invertebrates and predatory fish [12]. In addition, it presents advantages such as simplicity of culturing, a short life cycle, ease of managing, and a low maintenance cost [13]. It has been reported that acute exposure of D. magna to concentrations over 0.2 mg/L of Cu has a high influence on its viability due to accumulation in its gut and appendix [14,15]. Chlorella vulgaris, meanwhile, is a photosynthetic microalga used to indicate the stability of aquatic ecosystems [16], as it plays an important role in energy transport and material cycling (phosphorous and nitrogen absorption) and acts as food for primary consumers [17]. This species meets three basic requirements: it is a single cell that does not form aggregates under culture and assay conditions, it is easy to maintain under laboratory conditions, and it is very sensitive to contaminants [18]. The toxicity of AMD to C. vulgaris has not been reported, but its ability to absorb large quantities of metals, associated with its use in heavy metal detoxification, has been reported [19].
Likewise, as of the publication of this study, no scientific publications on the use of the TIE technique to fractionate and assess AMD have been reported. The novelty of this study is that AMD toxicity is assessed using freshwater organisms to understand the impact that these large expanses of land occupied by mine tailings have on surrounding surface ecosystems. Under climate change, events such as extreme rainfall are becoming more frequent and can carry acidic drainage to surrounding populations. Therefore, the objective of this study is to determine the acute toxicity of AMD to D. magna and C. vulgaris via the TIE technique, as well as to assess the effectiveness of this technique in detecting the toxic compounds present in AMD. The authors hypothesize that the defined indicators D. marga and C. vulgaris are sensitive to the compounds contained in AMD.

2. Materials and Methods

2.1. Acid Mine Drainage Acquisition

The acid mine drainage (AMD) was collected from an active copper mine located in the north of Chile. The samples were collected from the influent of a high-density sludge plant in 20 L plastic drums (previously rinsed with AMD) and stored at 4 °C ± 0.1 °C in the laboratory. The samples were not filtered or acidified.

2.2. Toxicity Identification Evaluation (TIE)

Six AMD fractionations were carried out via the following tests: pH adjustment/filtration, pH adjustment/aeration, chelation, ion (anion and cation) exchange, and activated carbon. Via pH adjustment/filtration, compounds at extreme pH were removed through precipitation resulting from pH adjustment (pH 3 and pH 11) and subsequent filtration. To adjust the pH, HCl and NaOH were added (0.1, 1.0, and 2.0 N, p.a. Merck Analysis, Darmstadt, Germany), and the adjusted samples were filtered through a 35 × 2.5 cm glass column with 0.45 μm hydrophobic wool (Diprolab MR, Concepción, Chile). pH adjustment/aeration fractionation evaluates the toxicity of volatile compounds. To this end, the pH of the AMD sample was adjusted (pH 3 and pH 11), and then the sample was aerated for 1 h. Chelation fractioning was performed to assess the degree of toxicity caused by cationic metals via the addition of ethylenediaminetetraacetic acid (EDTA) (ethyl enediaminetetraacetic acid) (Titriplex III, p.a. Merck, Darmstadt, Germany). For the ion exchange fractioning, 20 g of H+ cation exchange resin (Amberlite IR120 H, Merck, Darmstadt, Germany) and 20 g OH− anion exchange resin (Amberjet 4400 OH, Lenntech, Delfgauw, The Netherlands) were added to the glass columns to retain cationic and anionic compounds, respectively. Finally, the test with activated carbon was used to assess heavy metal toxicity, for which the sample passed through a column with 15 g of activated carbon (Merck, Darmstadt, Germany). All the TIE fractionations were adjusted to pH values between 6 and 8 to avoid interference with the actual toxicity of the assessed compounds, except for tests that included pH adjustment [20].

2.3. Toxicity Assays with Daphnia magna

The D. magna organisms were obtained from cultures from the Bioassay Laboratory, School of Environmental Science and EULA-Chile, Universidad de Concepción, Concepción, Chile. The cultures were prepared following the procedure stipulated in the Chilean standard at 20 ± 2 °C with a photoperiod of 16 h of light and 8 h of darkness [21].
The bioassays were performed by depositing 5 D. magna neonates (<24 h old) in borosilicate containers [22] and exposing them to different conditions: AMD concentrations (0.00001%, 0.0001%, 0.001%, 0.01%, 0.1%, 1%, 10% v/v), previously obtained TIE fractions, and a control with culture water. At the end of each exposure, the concentration that resulted in the mortality of 50% (LC50) of the D. magna population after 48 h was determined. For all the conditions, the LC50 was converted into toxic units (TUs) (Equation (1)), and the values were compared with the reference toxicity test (TU reference).
TU = (1/LC50) × 100
The toxicity reduction percentage (%RT) was calculated using Equation (2) [9], allowing the toxic compounds obtained from the fractionations to be identified.
%RT = (1 − ((TU Fraction)/(TU Reference))) × 100

2.4. Chlorella vulgaris Toxicity

The C. vulgaris strains were obtained from the microalga library of the Universidad de Concepción Department of Botany, Concepción, Chile. For the C. vulgaris culture, 104 cells/mL were inoculated and incubated at 23 ± 2 °C under white-spectrum light with a photoperiod of 16 h of light and 8 h of darkness [23].
The bioassays were performed in tubes for 24–72 h, with different conditions evaluated: AMD concentrations (0.00001%, 0.0001%, 0.001%, 0.01%, 0.1%, 1%, 10% v/v), TIE fractions, and a control. To this end, 4 mL of each AMD concentration and TIE fraction were added every 24 h until 72 h had elapsed to subsequently measure fluorescence emission (FE) by chlorophyll in a fluorometer at 685 nm (Fluorometer 10 AU). The values were expressed in relative fluorescence units (%RFUs), as shown in Equation (3).
%RFU = (100 − ((FE × 100)/(FE control)))

2.5. Analytical Methods

The fractionated and unfractionated AMD samples were analyzed following the protocol described in the standard method [24]. Meanwhile, total chemical oxygen demand (CODT) and soluble chemical oxygen demand (CODS) were analyzed via a colorimetric method, 5220-D [24]. pH and electrical conductivity (EC) were measured using an OAKTON-PC650 multiparameter meter (Eutech Instruments; Singapore). Sulfate (SO42−) levels were measured photometrically using a cuvette test (100617, Merck Millipore, Darmstadt, Germany). The Al2+, Cu2+, Fe3+, Mn2+, and Zn2+ concentrations in the TIE fractions were determined via absorption spectroscopy in a certified laboratory under NCh-ISO 17025:2005 [25].

2.6. Statistical Analyses

Non-parametric analysis of variance (Kruskal–Wallis) was used when the transformed values did not meet the distribution assumptions (normality and homogeneity of variance, evaluated by Shapiro–Wilk and Fligner–Killeen, respectively), which was used to evaluate whether there are significant differences between the different TIE fractions in terms of physicochemical parameters, such as CODT, CODs, and SO42−. The software packages used were Toxstat (version 2.1) for mortality/immobility analysis, EPA-Probit (version 1.5) to analyze the bioassays over time, and Spearman–Karber (version 1.5) to determine the median lethal dose. The critical p-value for all the experiments was 0.05. The statistical analyses were performed with Rstudio version 1.2.1335.

3. Results and Discussion

3.1. Physicochemical and Ecotoxicological Characterization of AMD

Table 1 shows the results obtained from the physicochemical characterization of AMD. Regarding the in situ parameters, the AMD presents a pH of 3.9 and EC of 3.7 mS/cm, values similar to those reported by Pino et al. [26] in a copper mine: pH of 3.4 and EC of 5.51 mS/cm. Organic matter content measured as CODT and CODS were 183.06 mg/L and 150.97 mg/L, respectively, while SO42− content was 2900 mg/L. These SO42− concentrations in AMD have been reported previously, as the formation results from the oxidation of sulfide minerals [27].
Regarding the metal concentrations, Cu presented the greatest concentration, with 418.9 mg/L, followed by Mn with 108.8 mg/L, Al with 85.09 mg/L, Zn with 43.96 mg/L, and Fe with 0.205 mg/L, the lowest concentration. The greater Cu concentration relative to the other metals could be explained by the nature of the mine from which the AMD samples were extracted. The concentrations of the rest of the evaluated metals may vary with respect to those reported in the bibliography due to factors such as local geology and climate and microorganism groups present [28,29].
Regarding acute toxicity to D. magna, AMD produced an LC50 of 0.00016% v/v. Radić et al. [30] observed an LC50 of 0.21% v/v at 24 h, which decreased at 48 h to an LC50 value of 0.06% v/v, demonstrating an increase in toxicity. Likewise, Chamorro et al. [11] reported an LC50 < 1% v/v 48 h after exposure to AMD. These values can be explained by the pH of the sample, as it is lower than that tolerated by D. magna (5.5–10). In addition, the solubility of the metals increases, which, in turn, increases their toxicity [31,32].
Evaluation of the effects of unfractionated AMD on C. vulgaris showed a %RFU of 101.61% at 24 h, 75.04% at 48 h, and, finally, 64.88% at 72 h. These results show that AMD was not toxic to the microalga, as although over the course of the study, the %RFU decreased by approximately 37%, the value did not fall below 50%. Authors such as Brar et al. [19], Chen et al. [5], and Kim et al. [33] point to C. vulgaris and microalgae in general as organisms that can live amid high metal concentrations, as they have adaptation mechanisms to tolerate extreme environmental stress (bioaccumulation, alkalinization, biotransformation). Through the secretion of extracellular polymeric substances (EPS) and alkalinization, they can even reduce the accumulation of metals in solution, which explains the obtained results.

3.2. Phase I: Characterization of TIE Fractions

Table 2 summarizes the physicochemical characteristics of each of the obtained TIE fractions. Regarding organic matter (CODT and CODS), no significant variation (p > 0.05) with respect to the influent was observed in the evaluated fractions, except for the fractionation with EDTA (p < 0.05), which increased the concentrations of CODT and CODS by 56.3% and 52.5%, respectively.
Evaluation of SO42− concentrations showed that only the ion exchange fractions were effective at reducing them. Fractionating AMD through cation resins and anion resins reduced SO42− from 2900 mg/L to 302.5 mg/L and <5 mg/L, respectively. These results can be explained by the nature of the resins used. The anion exchange resins reduce the presence of anions in solution through exchange with OH− ions [34]; therefore, sulfate ions are embedded in the resin. Meanwhile, cation resins exchange H+ ions with the cations present, releasing H+, which decreases its pH to 1.1. This can give rise to the formation of molecules such as H2SO4, reducing SO42− concentrations. No significant differences between the activated carbon, EDTA, pH adjustment, or aeration fractions relative to the influent were observed to be statistically significant at the 0.05 level of confidence.
Table 3 shows the concentrations of the main metals in the fractions obtained via fractionation with activated carbon, EDTA, anion resins, and cation resins. The fractions obtained with cation and anion resins and EDTA were able to separate a greater quantity of metals.
The anion resins stand out, reducing the concentrations of all the evaluated metals compared to the influent, from 85 mg/L to 0.79 mg/L of Al2+, 418 mg/L to 0.02 mg/L of Cu2+, 0.21 mg/L to <0.001 mg/L of Fe3+, 108 mg/L to 0.01 mg/L of Mn2+, and 43 mg/L to <0.0002 mg/L of Zn2+. This result is understood to be due to the release of OH− ions that increase the pH of the effluent to 14, which causes precipitation of the metals and retention in the resin. Likewise, the fractionation with EDTA reduced the concentrations of Al2+, Cu2+, and Fe3+ from 85 mg/L to 0.17 mg/L, 418 mg/L to 95.88 mg/L, and 0.21 mg/L to <0.01 mg/L, respectively. Meanwhile, in the cation resins, there were reductions of Mn2+ and Zn2+ to concentrations of 11.50 mg/L and 20 mg/L, respectively.
The fact that the fractioning with anion resins reduces sulfate, as well as all the cationic metals, indicates that the methodology chosen for the TIE technique was not the most appropriate, as it does not allow these compounds to be separated in an optimal manner to evaluate their toxicity separately. The same complication was observed in the fractioning performed with cation resins, which does not allow optimal separation of sulfate ions from cationic metals. In addition, the fact that this fractionation does not reduce metal concentrations as it should indicates that the column is overloaded, causing elution of the metals. The use of other forms of resin is recommended to avoid complications due to OH− and H+ ions, respectively.

3.3. Phase II: Reduction of AMD Toxicity to Bioindicators

3.3.1. Daphnia magna

Figure 1 shows the %RT of each of the fractions. Filtration/pH adjustment to 11 achieves a 100% reduction in toxicity, similar to anion resin, which reduces toxicity by approximately 99%. TIE fraction toxicity to D. magna at 48 h decreases in the following order: aeration/pH adjustment to 3 (20%) > activated carbon (60%) > EDTA (60%) > aeration/pH adjustment to 11 (80%) > cation resin (80%) > filtration/pH adjustment to 3 (82%) > anion resin (99%) > filtration/pH adjustment to 11 (100%).
Table 4, meanwhile, summarizes the ecotoxicological characteristics (LC50 and TU) of the obtained TIE fractions with respect to D. magna exposure. It can be observed that the LC50 and TU results show the same tendency. The fraction that allowed a total removal (NT) of toxicity to D. magna was filtration/pH adjustment to 11. As the pH increases, the concentrations of metal ions in solution decrease through precipitation [35]. Therefore, it can be inferred that AMD toxicity to D. magna is determined by the high concentration of metals in solution. Similarly, the fractionation with anion resin reduced the toxicity, expressed in an increase in the LC50 from 0.0016 to 0.4300% v/v and a decrease in TU values from 62,500 to 232, demonstrating that metals are the causes of toxicity, as Table 3 shows a reduction in the metal concentration of 99%.
By contrast, the effluents that maintained an elevated toxicity after fractionation were aeration/pH adjustment to 3 and activated carbon. Aeration/pH adjustment to 3 resulted in an LC50 of 0.0020% v/v and 50,000 TU, while the values for activated carbon were 0.0037% v/v and 27,027 TU, respectively. Yuan et al. [36] reported an LC50 of 0.0085 mg/L of Cu to D. magna, while Okamoto et al. [37] demonstrated that Cu is highly toxic, with an LC50 < 0.1 mg/L. Considering that the toxicity of the fractions to D. magna decreases to the same extent as Cu2+ concentrations, it can be inferred that this is the main cause of acute toxicity to D. magna. It also explains the persistent toxicity of the effluents treated by activated carbon, EDTA, and cation resin, the Cu2+ concentrations of which were 362.7 mg/L, 95.9 mg/L, and 39.8 mg/L, respectively (Table 3).

3.3.2. Chlorella vulgaris

Although Table 1 shows the lack of AMD toxicity to C. vulgaris, a TIE analysis was conducted to analyze both the behavior of the microalga over time and the effectiveness of the technique. The results of the TIE analysis of C. vulgaris at 24 h, 48 h, and 72 h are presented in Figure 2, expressed as relative fluorescence units (%RFUs).
During the first 24 h analysis, there was greater variation in %RFU, which can be interpreted as an acclimatization behavior on the part of C. vulgaris. The presence of unfractionated AMD generated a lower %RFU for C. vulgaris compared to the other fractions, with the value decreasing by 37% after 72 h. This reduction (24 h to 72 h) was also observed in the fractions: filtration/pH adjustment to 3 (20%), cation resin (29%), and EDTA (22%). In addition, it was observed that at 48 h, the %RFU decreased before increasing again at 72 h, as occurs in the fractions: aeration/pH adjustment to 11 (2%), filtration/pH adjustment to 11 (10%), anion resin (5%), and activated carbon (4%). Freitas et al. [38], studying AMD obtained from coal mines, reported Fe, Al, Zn, Mn, and Cu absorption in the biomass of algal species. Likewise, Brar et al. [19], using C. vulgaris to treat AMD obtained from gold mines, observed sulfate and metal (Fe, Al, Mn) removal efficiencies of 99.9% and 96.8%, respectively. Therefore, it is expected that the greater the contact time of C. vulgaris with the TIE fractions, the more the microalga will recover its initial %RFU due to the reduction in the concentrations of the metals present, although more studies on this matter are needed. Considering that C. vulgaris increases its %RFU after 72 h in contact with the fraction obtained by activated carbon, whose concentrations of SO42− (Table 2) and metals in solution (Table 3) were greater than those of the rest of the obtained fractions, the tolerance of C. vulgaris to the AMD compounds is demonstrated, as presented in Table 1.

4. Conclusions

Considering the results of this study, the following can be concluded:
AMD from a copper mine contains low concentrations of organic matter, measured as CODT (183.05 mg/L), low pH (3.9), and high concentrations of sulfates (2900 mg/L) and metal ions in solution (0.21–418.9 mg/L), producing high toxicity to D. magna (0.00016% v/v). For C. vulgaris, these conditions did not produce observable acute toxicity (72 h RFU 64.9%).
Of the fractionations obtained via TIE, those that generated the greatest reduction in toxicity to D. magna were filtration/pH adjustment to 11 and anion resin, increasing the 48 h LC50 from 0.00016% v/v to NT and 0.43% v/v, respectively, and reducing toxicity by 100% and 99%, respectively, allowing metals, specifically Cu2+, to be defined as the main cause of AMD toxicity to D. magna.
With respect to C. vulgaris, all the TIE fractions assessed produced a %RFU over 50%. A reduction in %RFU from 24 h to 72 h was observed in the fractions: filtration/pH adjustment to 3, cation resin, and EDTA of 20%, 29%, and 22%, respectively. Meanwhile, the aeration/pH adjustment to 11, filtration/pH adjustment to 11, anion resin, and activated carbon fractions presented increases of 2%, 10%, 5%, and 4%, respectively, from 48 to 72 h. This last fraction, due to its concentration of SO42− (2700 mg/L) and metals in solution (41.1–162.7 mg/L), demonstrates the tolerance of C. vulgaris to AMD.
The bioindicators D. magna and C. vulgaris were sensitive indicators of AMD toxicity and TIE tests.
The TIE technique is presented as an effective strategy to identify toxic compounds in complex samples and evaluate their effect on environmentally relevant organisms. Therefore, this study allows the analysis of the ecological risk in aquatic environments affected by mining activities, which supports environmental decision-making and the design of efficient treatment strategies.

Author Contributions

Conceptualization, G.V. and S.C.; methodology, C.B.; software, C.B.; validation, N.M., G.G. and G.V.; formal analysis, C.B.; investigation, C.B. and N.M.; resources, G.V.; data curation, N.M.; writing—original draft preparation, N.M.; writing—review and editing, S.C., G.G. and G.V.; visualization, C.B.; supervision, G.V.; project administration, G.V.; funding acquisition, G.V. All authors have read and agreed to the published version of the manuscript.

Funding

This research was funded by the ANID/FONDAP/1523A0001 grant.

Data Availability Statement

Data have been included in the present paper.

Acknowledgments

This work was supported by ANID/FONDAP/1523A0001.

Conflicts of Interest

The authors declare no conflicts of interest.

References

  1. Bwapwa, J.K.; Jaiyeola, A.T.; Chetty, R. Bioremediation of acid mine drainage using algae strains: A review. S. Afr. J. Chem. 2017, 24, 62–70. [Google Scholar] [CrossRef]
  2. Ruiz-Sanchez, A.; Tapia, J.C.; Lapidus, G.T. Evaluation of acid mine drainage (AMD) from tailings and their valorization by copper recovery. Miner. Eng. 2023, 191, 107979. [Google Scholar] [CrossRef]
  3. Pat-Espadas, A.M.; Loredo, R.; Amabilis-Sosa, L.E.; Gómez, G.; Vidal, G. Review on constructed wetlands for acid mine drainage treatment. Water 2018, 10, 1685. [Google Scholar] [CrossRef]
  4. Jiao, Y.; Zhang, C.; Su, P.; Tang, Y.; Huang, Z.; Ma, T. A review of acid mine drainage: Formation mechanism, treatment technology, typical engineering cases and resource utilization. Process Saf. Environ. Prot. 2023, 170, 1240–1260. [Google Scholar] [CrossRef]
  5. Chen, D.; Wang, G.; Chen, C.; Feng, Z.; Jiang, Y.; Yu, H.; Li, M.; Chao, Y.; Tang, Y.; Wang, S.; et al. The interplay between microalgae and toxic metalloids: Mechanisms and implications in AMD phycoremediation coupled with Fe/Mn mineralization. J. Hazard. Mater. 2023, 454, 131498. [Google Scholar] [CrossRef]
  6. Nwaila, G.T.; Ghorbani, Y.; Zhang, S.E.; Tolmay, L.C.K.; Rose, D.H.; Nwaila, P.C.; Bourdeau, J.E.; Frimmel, H.E. Valorisation of mine waste—Part II: Resource evaluation for consolidated and mineralized mine waste using the Central African Copperbelt as an example. J. Environ. Manag. 2021, 299, 113553. [Google Scholar] [CrossRef]
  7. Ighalo, J.O.; Kurniawan, S.B.; Iwuozor, K.O.; Aniagor, C.O.; Ajala, O.J.; Oba, S.N.; Iwuchukwu, F.U.; Ahmadi, S.; Igwegbe, C.A. A review of treatment technologies for the mitigation of the toxic environmental effects of acid mine drainage (AMD). Process Saf. Environ. Prot. 2022, 157, 37–58. [Google Scholar] [CrossRef]
  8. Liu, M.; Li, X.; He, Y.; Li, H. Aquatic toxicity of heavy metal-containing wastewater effluent treated using vertical flow constructed wetlands. Sci. Total Environ. 2020, 727, 138616. [Google Scholar] [CrossRef]
  9. Villamar, C.; Silva, J.; Bay-Schmit, E.; Vidal, G. Toxicity identification evaluation of anaerobically treated wine slurry: A comparison between Daphnia magna and Raphanus sativus. J. Environ. Sci. Health Part. B-Pestic. Contam. Agric. Wastes 2014, 49, 880–888. [Google Scholar] [CrossRef]
  10. US Environmental Protection Agency (USEPA). Methods for Aquatic Toxicity Identification Evaluations: Phase I Toxicity Characterization Procedures, 2nd ed.; EPA-600-6-91-003; Office of Research and Development: Duluth, MN, USA, 1991. [Google Scholar]
  11. Chamorro, S.; Barata, C.; Piña, B.; Casado, M.; Schwarz, A.; Sáez, K.; Vidal, G. Toxicological analysis of acid mine drainage by water quality and land use bioassays. Mine Water Environ. 2018, 37, 88–97. [Google Scholar] [CrossRef]
  12. Tkaczyk, A.; Bownik, A.; Dudka, J.; Kowal, K.; Slaska, B. Daphnia magna model in the toxicity assessment of pharmaceuticals: A review. Sci. Total Environ. 2021, 763, 143038. [Google Scholar] [CrossRef]
  13. Peng, W.; Liu, Y.; Lin, M.; Liu, Y.; Zhu, C.; Sun, L.; Gui, H. Toxicity of coal fly ash and coal gangue leachate to Daphnia magna: Focusing on typical heavy metals. J. Clean. Prod. 2022, 330, 129946. [Google Scholar] [CrossRef]
  14. Santos-Rasera, J.R.; Neto, A.S.; Rosim-Monteiro, R.T.; van Gestel, C.A.M.; Pereira de Carvalho, H.W. Toxicity, bioaccumulation and biotransformation of Cu oxide nanoparticles in Daphnia magna. Environ. Sci.-Nano 2019, 6, 2897. [Google Scholar] [CrossRef]
  15. García-Valero, A.; Martínez-Martínez, S.; Faz, A.; Rivera, J.; Acosta, J.A. Environmentally sustainable acid mine drainage remediation: Use of natural alkaline material. J. Water Process Eng. 2020, 33, 101064. [Google Scholar] [CrossRef]
  16. Su, Y.; Cheng, Z.; Hou, Y.; Lin, S.; Gao, L.; Wang, Z.; Bao, R.; Peng, L. Biodegradable and conventional microplastics posed similar toxicity to marine algae Chlorella vulgaris. Aquat. Toxicol. 2022, 244, 106097. [Google Scholar] [CrossRef]
  17. Hanachi, P.; Khoshnamvand, M.; Walker, T.R.; Hamidian, A.H. Nano-sized polystyrene plastics toxicity to microalgae Chlorella vulgaris: Toxicity mitigation using humic acid. Aquat. Toxicol. 2022, 245, 106123. [Google Scholar] [CrossRef]
  18. Expósito, N.; Carafa, R.; Kumar, V.; Sierra, J.; Schuhmacher, M.; Papiol, G.G. Performance of Chlorella vulgaris exposed to heavy metal mixtures: Linking measured endpoints and mechanisms. Int. J. Environ. Res. Public Health 2021, 18, 1037. [Google Scholar] [CrossRef]
  19. Brar, K.K.; Etteieb, S.; Magdouli, S.; Calugaru, L.; Brar, S.K. Novel approach for the management of acid mine drainage (AMD) for the recovery of heavy metals along with lipid production by Chlorella vulgaris. J. Environ. Manag. 2022, 308, 114507. [Google Scholar] [CrossRef]
  20. Villamar, C.; Cañuta, T.; Belmonte, M.; Vidal, G. Characterization of swine wastewater by toxicity identification evaluation methodology (TIE). Water Air Soil. Pollut. 2012, 223, 363–369. [Google Scholar] [CrossRef]
  21. NCh2083:1999; Acute Toxicity Bioassays by Determining Inhibition of Mobility of Daphnia magna or Daphnia pulex (Crustacea, Cladocera). National Institute of Standardization: Santiago, Chile, 1999. Available online: https://ecommerce.inn.cl/nch2083199941614 (accessed on 30 March 2025).
  22. Xavier, C.; Chamorro, S.; Vidal, G. Chronic effects of Kraft mill effluents and endocrine active chemical on Daphnia magna. Bull. Environ. Contam. Toxicol. 2005, 75, 670–676. [Google Scholar] [CrossRef]
  23. Guevara, M.; Arredondo-Vega, B.; Palacios, Y.; Saéz, K.; Gómez, P. Comparison of growth and biochemical parameters of two strains of Rhodomonas salina (Cryptophyceae) cultivated under different combinations of irradiance, temperature, and nutrients. J. Appl. Phycol. 2016, 28, 2651–2660. [Google Scholar] [CrossRef]
  24. APHA/AWWA/WEF. Standard Methods for the Examination of Water and Wastewater, 21st ed.; American Public Health Association: Washington, DC, USA, 2005. [Google Scholar]
  25. NCh-ISO 17025:2005; Testing and Calibration Laboratory Analysis and Implementation. National Institute of Normalization of Chile: Santiago, Chile, 2005. Available online: https://www.inn.cl/nch-iso-170252005-laboratorio-de-ensayo-y-calibracion-analisis-e-implementacion (accessed on 30 March 2025).
  26. Pino, L.; Beltran, E.; Schwarz, A.; Ruiz, M.C.; Borquez, R. Optimization of nanofiltration for treatment of acid mine drainage and copper recovery by solvent extraction. Hydrometallurgy 2020, 195, 105361. [Google Scholar] [CrossRef]
  27. López, J.; Reig, M.; Vecino, X.; Cortina, J.L. Arsenic impact on the valorisation schemes of acidic mine waters of the Iberian Pyrite belt: Integration of selective precipitation and spiral-wound nanofiltration processes. J. Hazard. Mater. 2021, 403, 123886. [Google Scholar] [CrossRef] [PubMed]
  28. Acharya, B.S.; Kharel, G. Acid mine drainage from coal mining in the United States—An overview. J. Hydrol. 2020, 588, 125061. [Google Scholar] [CrossRef]
  29. Rambabu, K.; Banat, F.; Pham, Q.M.; Ho, S.H.; Ren, N.Q.; Show, P.L. Biological remediation of acid mine drainage: Review of past trends and current outlook. Environ. Sci. Echotechol. 2020, 2, 100024. [Google Scholar] [CrossRef]
  30. Radić, S.; Vujčić, V.; Cvetković, Ž.; Cvjetko, P.; Oreščanin, V. The efficiency of combined CaO/electrochemical treatment in removal of acid mine drainage induced toxicity and genotoxicity. Sci. Total Environ. 2014, 466–467, 84–89. [Google Scholar] [CrossRef]
  31. Sivula, L.; Vehniainen, E.R.; Karjalainen, A.K.; Kukkonen, J.V.K. Toxicity of biomining effluents to Daphnia magna: Acute toxicity and transcriptomic biomarkers. Chemosphere 2018, 210, 304–311. [Google Scholar] [CrossRef]
  32. Ryskie, S.; Bélanger, E.; Neculita, C.M.; Couture, P.; Rosa, E. Influence of ozone microbubble enhanced oxidation on mine effluent mixes and Daphnia magna toxicity. Chemosphere 2023, 329, 138559. [Google Scholar] [CrossRef]
  33. Kim, D.; Chae, Y.; Kim, M.; An, Y.J. Effects of EDTA and boron toxicity to the green algae Chlamydomonas reinhardtii, Chlorella sorokiniana, and Chlorella vulgaris. J. Water Process Eng. 2023, 53, 103823. [Google Scholar] [CrossRef]
  34. Dixit, F.; Barbeau, B.; Mostafavi, S.G.; Mohseni, M. PFOA and PFOS removal by ion exchange for water reuse and drinking applications: Role of organic matter characteristics. Environ. Sci.-Water Res. Technol. 2019, 5, 1782–1795. [Google Scholar] [CrossRef]
  35. Petronijevic, N.; Radovanovic, D.; Stulovic, M.; Sokic, M.; Jovanovic, G.; Kamberovic, Z.; Stankovic, S.; Stopic, S.; Onjia, A. Analysis of the mechanism of acid mine drainage neutralization using fly ash as an alternative material: A case study of the extremely acidic lake Robule in Eastern Serbia. Water 2022, 14, 3244. [Google Scholar] [CrossRef]
  36. Yuan, W.; Zhou, Y.; Chen, Y.; Liu, X.; Wang, J. Toxicological effects of microplastics and heavy metals on the Daphnia magna. Sci. Total Environ. 2020, 746, 141254. [Google Scholar] [CrossRef] [PubMed]
  37. Okamoto, A.; Yamamuro, M.; Tatarazako, N. Acute toxicity of 50 metals to Daphnia magna. J. Appl. Toxicol. 2014, 35, 824–830. [Google Scholar] [CrossRef]
  38. Freitas, A.P.P.; Schneider, I.A.H.; Schwartzbold, A. Biosorption of heavy metals by algal communities in water streams affected by acid mine drainage in the coal-mining region of Santa Catarina state, Brazil. Miner. Eng. 2011, 24, 1215–1218. [Google Scholar] [CrossRef]
Water 17 01313 g001
Figure 1. Daphnia magna toxicity reduction (%RT) after TIE fractionation.
Figure 1. Daphnia magna toxicity reduction (%RT) after TIE fractionation.
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Figure 2. Observed acute toxicity of fractionated AMD to Chlorella vulgaris expressed as relative fluorescence units (%RFUs) at 24 h, 48 h, and 72 h. (a) Unfractionated AMD; (b) filtration/adjustment pH 11; (c) filtration/adjustment pH 3; (d) aeration/adjustment pH 11; (e) aeration/adjustment pH 3; (f) anion resin; (g) cation resin; (h) EDTA; (i) activated carbon.
Figure 2. Observed acute toxicity of fractionated AMD to Chlorella vulgaris expressed as relative fluorescence units (%RFUs) at 24 h, 48 h, and 72 h. (a) Unfractionated AMD; (b) filtration/adjustment pH 11; (c) filtration/adjustment pH 3; (d) aeration/adjustment pH 11; (e) aeration/adjustment pH 3; (f) anion resin; (g) cation resin; (h) EDTA; (i) activated carbon.
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Table 1. Physicochemical and toxicological characterization (Daphnia magna and Chlorella vulgaris) of AMD.
Table 1. Physicochemical and toxicological characterization (Daphnia magna and Chlorella vulgaris) of AMD.
Metal/ParameterUnitAverage ± SD *
pH-3.9 ± 0.0
EC *mS/cm3.67 ± 0.00
CODT *mg/L183.05 ± 12.16
CODS *mg/L150.97 ± 0.32
SO42−mg/L2900.0 ± 0.0
Cumg/L418.9 ± 0.01
Mnmg/L108.80 ± 0.01
Almg/L85.09 ± 0.01
Znmg/L43.96 ± 0.01
Femg/L0.21 ± 0.01
48 h—LC50 *%0.00016
24 h—RFU *%101.61
48 h—RFU%75.04
72 h—RFU%64.88
Note(s): * EC: electric conductivity; CODT: total chemical oxygen demand; CODS: soluble chemical oxygen demand; 48 h-LC50: median lethal concentration at 48 h; RFU: relative fluorescence unit; SD: standard deviation.
Table 2. In situ and physicochemical characterization of AMD TIE fractions.
Table 2. In situ and physicochemical characterization of AMD TIE fractions.
Fraction* CODT* CODSSO42−* EC
(mS/cm)
(Average ± SD *) (mg/L)
Filtration pH 3180.98 ± 3.11142.62 ± 20.052925.0 ± 106.14.5
Filtration pH 1197.55 ± 10.5783.77 ± 3.582560.0 ± 247.55.4
Aeration pH 3154.13 ± 2.89148.39 ± 18.063275.0 ± 35.34.9
Aeration pH 11153.29 ± 7.2973.23 ± 22.872650.0 ± 141.46.1
EDTA *324.94 ± 14.33287.29 ± 14.362625.0 ± 35.34.9
Cation resin180.22 ± 14.32142.12 ± 63.63302.5 ± 106.118.3
Anion resin148.53 ± 8.97122.49 ± 14.56< 5 ± 0.03.6
Activated carbon174.95 ± 14.01153.29 ± 15.312700.0 ± 0.03.9
Note(s): * CODT: total chemical oxygen demand; CODS: soluble chemical oxygen demand; EC: electric conductivity; SD: standard deviation; EDTA: ethylenediaminetetraacetate.
Table 3. Concentration of metals present in AMD TIE fractions.
Table 3. Concentration of metals present in AMD TIE fractions.
FractionAl2+Cu2+Fe3+Mn2+Zn2+
(mg/L)
Cation resin13.6339.80.27011.5020.0
Anion resin0.790.02<0.0010.01<0.0002
Activated carbon65.20362.70.090108.0041.1
EDTA *0.1795.9<0.00196.3031.5
Note(s): * EDTA: ethylenediaminetetraacetate; TIE: toxicity identification evaluation.
Table 4. Acute toxicity of AMD fractionated by TIE to Daphnia magna measured as median lethal concentration (LC50) and toxicity units (TUs).
Table 4. Acute toxicity of AMD fractionated by TIE to Daphnia magna measured as median lethal concentration (LC50) and toxicity units (TUs).
FractionLC50 * (%v/v) *TU *
AMD *0.001662,500
Filtration pH 30.009610,416
Filtration pH 11NT *NT
Aeration pH 30.002050,000
Aeration pH 110.007613,157
EDTA *0.004025,000
Cation resin0.007313,698
Anion resin0.4300232
Activated carbon0.003727,027
Note(s): * LC50: median lethal concentration at 48 h; TU: toxicity unit; AMD: unfractionated acid mine drainage; EDTA: ethylenediaminetetraacetate; NT: no observed toxicity; %v/v: % volume/volume
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Burgos, C.; Chamorro, S.; Monsalves, N.; Gómez, G.; Vidal, G. Assessment of Acute Toxicity of Acid Mine Drainage via Toxicity Identification Evaluation (TIE) Using Daphnia magna and Chlorella vulgaris. Water 2025, 17, 1313. https://doi.org/10.3390/w17091313

AMA Style

Burgos C, Chamorro S, Monsalves N, Gómez G, Vidal G. Assessment of Acute Toxicity of Acid Mine Drainage via Toxicity Identification Evaluation (TIE) Using Daphnia magna and Chlorella vulgaris. Water. 2025; 17(9):1313. https://doi.org/10.3390/w17091313

Chicago/Turabian Style

Burgos, Carol, Soledad Chamorro, Naomi Monsalves, Gloria Gómez, and Gladys Vidal. 2025. "Assessment of Acute Toxicity of Acid Mine Drainage via Toxicity Identification Evaluation (TIE) Using Daphnia magna and Chlorella vulgaris" Water 17, no. 9: 1313. https://doi.org/10.3390/w17091313

APA Style

Burgos, C., Chamorro, S., Monsalves, N., Gómez, G., & Vidal, G. (2025). Assessment of Acute Toxicity of Acid Mine Drainage via Toxicity Identification Evaluation (TIE) Using Daphnia magna and Chlorella vulgaris. Water, 17(9), 1313. https://doi.org/10.3390/w17091313

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