Next Article in Journal
Effects of Combined High Temperature and Waterlogging Stress at Booting Stage on Root Anatomy of Rice (Oryza sativa L.)
Next Article in Special Issue
Ecological and Health Risk of Soils, Sediments, and Water Contamination
Previous Article in Journal
The Prediction of Oceanic Mesoscale Eddy Properties and Propagation Trajectories Based on Machine Learning
Previous Article in Special Issue
Biodegradation of Amoxicillin, Tetracyclines and Sulfonamides in Wastewater Sludge
 
 
Search for Articles:
Title / Keyword
Author / Affiliation / Email
Journal
Article Type
 
 
Advanced Search
 
Section
Special Issue
Volume
Issue
Number
Page
 
Journals
Water
Volume 12
Issue 9
10.3390/w12092523
water-logo
Submit to this Journal Review for this Journal Propose a Special Issue
► Article Menu

Article Menu

share Share announcement Help format_quote Cite question_answer Discuss in SciProfiles thumb_up
...
Endorse textsms
...
Comment
first_page
settings
Order Article Reprints
Font Type:
Arial Georgia Verdana
Font Size:
Aa Aa Aa
Line Spacing:
Column Width:
Background:
Article

Evaluation of the Effect of Gold Mining on the Water Quality in Monterrey, Bolívar (Colombia)

by
Alison Martín
1,2,
Juliana Arias
1,
Jennifer López
1,
Lorena Santos
1,
Camilo Venegas
1,
Marcela Duarte
3,
Andrés Ortíz-Ardila
4,
Nubia de Parra
3,
Claudia Campos
1 and
Crispín Celis Zambrano
2,*
1
Department of Microbiology, Laboratorio de Indicadores de Calidad de Agua y Lodos (LIAL), Pontificia Universidad Javeriana, Carrera 7 No. 43–82, Bogotá 110231, Colombia
2
Department of Chemistry, Pontificia Universidad Javeriana, Carrera 7 No. 43–82, Bogotá 110231, Colombia
3
Independient Investigator, Bogotá 110111, Colombia
4
Hydraulic and Environmental Engineering Department, Pontificia Universidad Católica de Chile, Av. Vicuña Mackenna 4860, Macul, Santiago 7820436, Chile
*
Author to whom correspondence should be addressed.
Water 2020, 12(9), 2523; https://doi.org/10.3390/w12092523
Submission received: 7 August 2020 / Revised: 3 September 2020 / Accepted: 4 September 2020 / Published: 10 September 2020
(This article belongs to the Special Issue Ecological and Health Risk of Soils, Sediments, and Water Contamination)
Browse Figure
Review Reports Versions Notes

Abstract

:
Gold mining uses chemicals that are discharged into rivers without any control when there are no good mining practices, generating environmental and public health problems, especially for downstream inhabitants who use the water for consumption, as is the case in Monterrey township, where the Boque River water is consumed. In this study, we evaluate Boque River water quality analyzing some physicochemical parameters such as pH, heavy metals, Hg, and cyanide; bioassays (Lactuca sativa, Hydra attenuata, and Daphnia magna), mutagenicity (Ames test), and microbiological assays. The results show that some physicochemical parameters exceed permitted concentrations (Hg, Cd, and cyanide). D. magna showed sensitivity and L. sativa showed inhibition and excessive growth in the analyzed water. Mutagenic values were obtained for all of the sample stations. The presence of bacteria and somatic coliphages in the water show a health risk to inhabitants. In conclusion, the presence of Cd, Hg, and cyanide in the waters for domestic consumption was evidenced in concentrations that can affect the environment and the health of the Monterrey inhabitants. The mutagenic index indicates the possibility of mutations in the population that consumes this type of water. Bioassays stand out as an alert system when concentrations of chemical contaminants cannot be analytically detected.

1. Introduction

Gold mining in developing countries is the main source of income for 30 million miners globally. About 12% of global gold production is through illegal mining that provides a significant economic benefit to miners but also proves hazardous/harmful for the environment by causing impacts such as water source sedimentation, land cover degradation, deforestation, soil degradation, and chemical contamination with mercury, cyanide, nitric acid, and zinc [1,2,3]. In Colombia, despite the various alternatives to avoid the use of Hg in gold extraction, the use of the elemental Hg–Au amalgamation method in small-scale artisanal mining areas is extensive [4,5].
Within the gold mining protocols, mercury and cyanide play an important role. These materials are easy to use, available at a low-cost, and easily accessible. However, there is little awareness among the users or villagers about the use risk of cyanide and mercury in the gold extraction process [1,2]. This activity has led to serious pollution of terrestrial and aquatic ecosystems in emerging countries, impacting mining and fishing communities, and also these polluting elements can reach human beings [4,5,6,7].
According to the records of the Colombian Mining Association (ACM), gold production increased in 2020, going from 8.9 tons in 2019 to 9.5 tons in the first quarter of 2020, this represents a growth of 7% [8]. On the other hand, for gold extraction, 86% is considered illegal, taking place without a recognized mining title or without being registered. Medium-scale mining constitutes up to 26% and large-scale mining only takes up 2% of the total [9,10]. The population of the Bolívar department is 2,195,811 inhabitants, according to DANE’s (National Statistics Administrative Department) projection for 2019 [11]. According to Carranza-Lopez et al. [4] the gold-mining districts (GMDs) at the department of Bolívar have extensive Hg contamination, and this situation requires special attention to reduce environmental and human health problems.
Municipalities of Montecristo, Santa Rosa del Sur, San Martín de Loba, Morales, San Pablo, Barranco de Loba, and Simití that are in Bolívar are where gold mining mainly takes place. Simití is known as the municipality that has the largest gold mining activity within the Bolívar department. It has an estimated population of 10,360 inhabitants in an area of 1345 km2, the mining activity occurs in the Boque River, which flows in Simití. It starts on Serranía San Lucas, passes through Monterrey district, and flows into Magdalena River [12,13,14] (Figure 1).
Gold mining in Middle Magdalena has been carried out through artisanal practices, without considering the implications in the community and ecosystems due to the practice of non-regulated techniques affecting the environment, natural resources as well as health conditions and welfare of the population. Gold mining severely affects water resources, biodiversity, animals, flora, and fauna in its geographical area. In addition, the presence of certain types of mining settlements bring to pass certain types of domestic wastewater discharges without treatment to the Boque River, affecting the quality of the water and the inhabitants downstream [15,16,17,18,19]. The discharge of wastewater into a water body involves a large number and diversity of heavy toxic chemicals, many of which are unknown. These chemicals may react with each other, which can increase the toxicity level, which creates a negative impact on the structure and functioning of the natural ecosystem [4,20].
To determine the effect of gold extraction in the region, the evaluation of physicochemical parameters of the water is required. Nevertheless, the illegal settlements do not have sanitation systems, so microbiological contamination becomes an additional problem. However, even if in some of the above-mentioned situations the parameters could be between the legal requirements, it should be considered that trace heavy elements might have an impact on the population and the ecosystem after long periods of exposure. Thus, it is necessary to test different representatives of the trophic chain to identify the impact of the pollutants through bioassays tests [20,21,22,23].
Bioassays are described as alert mechanisms for long-term periods of exposure to chemical pollutants. These are used as indicators of substances that are harmful to living cells and tissues, useful even in the cases where physicochemical parameters fulfill the requirements of water quality [24]. Likewise, this possible bioaccumulation of chemical elements in the trophic chains can generate mutagenicity or toxicity, which is why it is important to be able to establish whether a complex system such as a water sample from a mining region has these undesirable characteristics, which can be detected by the Ames test or bioassays [25,26,27]. Some Latin American countries have made progress in the application of toxicity tests, while for Colombia, toxicity tests in natural environments are scarce compared to the evaluation of hazardous waste and industrial dumping [28,29]. On the other hand, the Ames test has proven to be effective for the identification of potentially carcinogenic or mutagenic chemicals, achieving its immediate adoption and its requirement by regulatory authorities around the world [30]. In the Ames test, Salmonella typhimurium (S. typhimurium) is used as an indicator of bacterial mutagenesis as a consequence of exposure to chemical contaminants [25,26].
Taking into consideration that the water of the Boque River is used in human consumption without treatment and it collects chemical pollutants from the mining activity, such as mercury and cyanide, the use of the Ames test in the evaluation of this water will permit the evaluation of its possible carcinogenic or mutagenic effect, making it a relevant issue for the inhabitants of Simití. For this reason, it is necessary to have data on bioassays and Ames test indicators in environmental samples, especially in mining, which has become one of the most important fonts of economic resources in Colombia and at the same time of damage not sufficiently evaluated to date. In order to have a complete evaluation of the water quality in relation to the possible presence of bacteria, viruses, and parasites and the risk to the inhabitants, it is necessary to use indicators of fecal contamination, with the most used indicators being total coliforms and Escherichia coli as bacterial indicators and somatic phages as viral indicators, which allow indication of the presence of pathogenic microorganisms in the water.
The aim of this research is to evaluate the impact generated by the exploitation of bad mining practices such as the use of dangerous chemical compounds in gold mining, which are drained into surface waters such as the Boque River in the South of Bolívar, Colombia, as well as the waste generated in the mining settlements. The assessment of the impact on the environment, living organisms, and human health will be done through the detection of heavy metals, microbiological indicators, and bioassays, which through a joint assessment will provide important aspects to protect the health of the inhabitants of Monterrey.

2. Materials and Methods

2.1. Study Area

The Boque River has an approximate area of 876 km2 and merges into the Magdalena River. The Monterrey district belongs to the Municipality of Simití, Department of Bolívar (Colombia). The inhabitants who live within the Monterey township collect and use the water from the Boque River for different activities, this being the main source of water supply (Figure 1) [27].

2.2. Water Physicochemical Analysis, Heavy Metals, and Cyanide Detection

Some physicochemical parameters were analyzed such as pH (pH/T tester pHep®4, Hanna Instruments, RI, USA) [31], chemical oxygen demand (COD photometer Hanna Instruments, New England, RI, USA) [32], and total solids by the gravimetric method [33]. The detection of heavy metals was performed using a Varian SpectrAA 220 G Atomic Absorption Spectrometer(Varian-Agilent Inst., Palo Alto, San Francisco, CA, USA), following previous publications: cadmium, chromium, zinc, and nickel [34]; mercury in a direct mercury analyzer (DMA-80, Milestone Inc., Sorisole, Italy) [35]; and cyanide in a portable photometer (Hanna Instruments, RI, USA) [36]. All reactive, analytical standards and reference materials were purchased from Merck (Merck KGaA, Darmstadt, Germany). The results obtained in the samples from Village Gato, Village Tigui, and the water catchment of the Boque River were compared with normative 0631/2015 [37], which establishes the parameters to be monitored and maximum permissible limits in the specific discharges of non-domestic wastewater (precious minerals and gold). While for houses and deep-well underground sites, they were evaluated in compliance with normative 2115/2007 [38], which regulates water for human consumption.

2.3. Bioassays

In the bioassays, Lactuca sativa (L. sativa) [39] and Hydra attenuata (H. attenuata) [40] were used as a biological indicators of water quality. After the follow-up of the results of the two first collections of water samples, a modification of the protocol was performed replacing Daphnia magna (D. magna) [41] instead of H. attenuata due to no evidence of sensitivity against the possible harmful substances that might be present in the water samples by H. attenuata. The effects on organisms can be inhibition, sublethality, and lethality volume/volume (v/v). The water samples were diluted in four different concentrations 25%, 50%, 75%, and 100% (v/v); reconstituted hard water (160–180 mg/L CaCO3) was used as diluent for the D. magna and H. attenuata; while for L. sativa, distilled water was used. The response of H. attenuata was read using a binocular stereoscope (Leica). Before taking the readings, the containers were shaken in a circular way to reactivate the movement of D. magna and confirm their state. In the case of L. sativa, graph paper was used to measure the length of the radicle.

2.3.1. Endpoint and Toxic Response Model

L. sativa, half-maximal inhibitory concentration (IC50): root growth reduction or inhibitory effects on lettuce seed germination and root growth after 5 days. D. magna, lethal concentration (LC50): number dead/total number or lethal effects of water were observed after 48 h of exposure, and H. attenuata, median effective concentration (EC50): density reduction or lethality test, produced by irreversible morphological changes after 96 h of exposure.

2.3.2. Toxicity

To calculate the lethal concentration (LC50), the half-maximal inhibitory concentration (IC50), and median effective concentration (EC50), the method used was Environmental Protection Agency (EPA) Probit analysis model [42,43,44]. When results in EC50/LC50/IC50 cannot be reported by the statistical program, they are reported as the percentage of effect (%) in the lowest concentration at which the event is still present on the evaluated population [20].

2.4. Ames Test

The method was applied according to Ames [45] using Salmonella typhimurium (S. typhimurium) TA98 and TA100 strains to evaluate possible mutagenicity. The cultures were grown in Oxoid nutrient broth No. 2. The samples of water were diluted in four different concentrations 25%, 50%, 75%, and 100% (v/v). The mutagenic effect was evaluated from the number of revertant colonies per plate. The plates were prepared in triplicate for every test sample, and the result presented was the mean of triplicate observation. The mutagenic activity was detected after 120 h of exposure at 37 (±2) °C. The revertant colonies’ readings were counted using an automatic colony counter (Industrial Scientific). For accuracy of the results, mutagenic index (MI) values greater than or equal to two (≥2) were considered mutagenic [46].

2.5. Statistic Analysis

To establish whether there is a relationship between evaluated physicochemical parameters and heavy metals with results of bioassays, a one-way analysis of variance (ANOVA) was performed with a significance level of p < 0.05.

2.6. Microbiological Analysis

The determination of total coliforms and E. coli as indicators of bacterial fecal contamination was performed according to the ISO 9308-1 standard method [47]. Cellulose acetate membranes of 0.45 µm × 47 mm (Sartorius) were used for the filtration. Dark blue/purple colonies on Chromocult agar (Merck) were presumed to be E. coli. The detection and quantification of somatic coliphages as indicators of viral fecal contamination was performed according to the ISO 10705-2 standard procedure and modified Scholten’s agar (MSA) (OXOID) was used for the detection of coliphages [48].
The results obtained in the samples from Village Gato, Village Tigui, and the water catchment of the Boque River were compared with normative 1594/1984 [49], which regulates waters that can be treated by conventional systems for human consumption. While for houses and deep-well underground sites, they were evaluated in compliance with normative 2115/2007 [38], which regulates water for human consumption. Normative 2115/2007 only beholds the microbiological quality concerning total coliforms and E. coli. Although coliphage concentrations are not regulated within Colombian normatives, their detection is relevant since they confirm contamination of fecal origin and the possible presence of pathogenic viruses, both in drinking water and in water for human consumption.

3. Results

3.1. Physicochemical Parameters

Parameters such as COD, total solids, and pH did not exceed the limits of Colombian normative 0631/2015 [37], in the first three sample stations. However, the level of cadmium was excessive in the Village Gato station in the first sampling with a concentration of 0.05 mg/L. Chromium did surpass the limit in the first sampling in Village Tigui. Likewise, mercury in Village Gato exceeded the limit in the third sampling (0.0029 mg/L). Moreover, in the Village Tigui station, the measurements in the second sampling exceeded 0.0025 mg/L and those in the water catchment of the Boque River in the first sampling were also excessive with 0.0022 mg/L. Furthermore, the permitted concentration of cyanides in the first and second sampling with a concentration of 1.02 and 1.32 mg/L, respectively, was excessive at the Village Tigui sampling station. While in the water catchment of the Boque River station, the prescribed cyanide level was exceeded in the second sampling with a concentration of 1.57 mg/L (Appendix A—Table A1).
The values of heavy metals analyzed in the last two sampling stations were compared with normative 2115/2007 [38] based on waters for human consumption. On one hand, the level of cadmium exceeded the limits established by the regulations for the house station in the second and third sampling with concentrations of 0.03 and 0.01 mg/L, respectively. While the cyanide concentration was exceeded only in the second sampling (1.11 mg/L). On the other hand, the established values of cadmium exceeded only in the second sampling in deep-well underground, presenting a concentration of 0.01 mg/L. Mercury was detected in each of the samples for both the house and deep-well underground stations, but the concentrations did not exceed the limits established in normative 2115 of 2007 [38]. The other metals evaluated (Zn, Ni, and Cr) were not detected in any of the samples analyzed (Appendix A—Table A2).

3.2. Bioassays

Table 1 shows the different percentages of growth inhibition of L. sativa in three samples for five evaluated stations. As the results show, there was root inhibition in some sampling stations and overgrowth in others. In Village Gato, in the third sampling, there was excess growth at a concentration of 25%. Likewise, in Village Tigui, the greatest inhibitions registered were observed at a concentration of 25%. In general, among all the sampled stations where the greatest inhibition was observed the highest was in Village Tigui, followed by house, deep-well underground, Village Gato, and the smallest recorded in the water catchment of the Boque River.
In Table 2, it is observed that the D. magna indicator has different mortality percentages since the same four concentrations of the sample are evaluated as in the L. sativa bioassay. The highest was 23% mortality at a concentration of 50% at the water catchment of the Boque River station and 17% mortality at 75% at the Village Tigui sampling station, followed by the house and deep-well underground stations. Finally, the lowest concentration of mortality was obtained in the Village Gato station with 33% mortality at 100%. For H. attenuata, it was not possible to determine the EC50 and LC50 values because there were no morphological changes, indicating lethality or sublethality, in the three samplings carried out, reporting 0% sublethality at 100% (v/v) and 0% lethality at 100% (v/v).

3.3. Ames Test

The results obtained with the Ames test using S. typhimurium TA98 and TA100 strains are presented in Table 3, where the mutagenic index (MI) is shown for each condition used in the assay. According to Table 3, for the second sampling of the house station, mutagenic values were observed for both strain TA98 and TA100 in each of the concentrations evaluated. While for Village Gato, with strain TA100, a value of 2.4 was observed in the 100% concentration (Table 3). For the other sampling sites, there was no mutagenic index.

3.4. Statistical Analysis

The statistical analysis performed to determine a possible relationship between the results of the physicochemical parameters against the toxicity indicators showed that there is a relationship between the inhibition of L. sativa concerning to mercury with a significance of p < 0.05.
However, due to the low number of samples analyzed for H. attenuata (three samples) versus the number of samples for D. magna (15 samples), it was not possible to establish whether there was a correlation with the concentration of metals or with the results of L. sativa.

3.5. Microbiological Analysis

Table 4 shows the results of the concentration of fecal contamination indicators (total coliforms, E. coli, and somatic coliphages) for the different types of water of the five sampling stations. Table 4 shows that concentrations between 103 and 105 colony forming unit (CFU)/100 mL for total coliforms were obtained at the different stations. While in the case of E. coli, concentrations between 103 and 104 CFU/100 mL were obtained. Somatic coliphages were detected in samples taken at Village Gato and house stations. Colombia does not have regulations for the presence of this indicator, although this is necessary since the presence of somatic coliphages represents a risk to the health of the community.
While, for the water catchment of the Boque River, Village Tigui, and deep-well underground stations, the presence of phages in some samples was not detected (<1.0 × 103). The results were compared with decree 1594/1984 [49], which establishes the concentration of total coliforms (2.0 × 104/100 mL) allowed in waters that will be treated by conventional systems: while normative 2115/2007 [38], establishes that the concentrations for total coliforms and E. coli for drinking water is 0 CFU/100 mL.

4. Discussion

4.1. Bioassays

4.1.1. Hydra attenuata and Daphnia magna

By applying the H. attenuata toxicity test, it was not possible to determine lethality or sub-lethality since there were no morphological changes in the three samples taken. An important factor that could influence why H. attenuata was not sensitive to contaminants present in this water, is that the toxicity of metals is modified by abiotic factors such as hardness, pH, and water temperature [50]. For example, if water hardness is high, the formation of metal complexes tends to increase, which in turn lowers the effect of toxic divalent metals [50,51].
H. attenuata has a higher sensitivity to toxic substances at acidic pH, compared to that at alkaline or neutral pH [52]. The pH value of the water sample from the Boque River is about 7 (Appendix A—Table A1 and Table A2), which could influence H. attenuata not presenting sensitivity when heavy metals, cyanides, or other toxic substances are in the water.
Due to the results obtained with H. attenuata in the first two samples, D. magna was used in the last sampling, to find an animal indicator that presented a greater sensitivity to these types of contaminants. Table 2 shows different mortality percentages that were found, demonstrating the sensitivity of this organism to the contaminants present in the water of the Boque River that is consumed by the Monterrey population. Studies conducted by Forget et al. [53] with D. magna, show percentages of toxicity up to 70% against heavy metals. Castro-Català et al. [54] evaluated the toxicity of sediments and water in rivers with the presence of pesticides and heavy metals using D. magna as an animal indicator, showing that it can be sensitive to these types of samples, due to its high metabolic rate [55]. Likewise, Lattuada et al. [56], in southern Brazil, used D. magna as an indicator of toxicity in waters affected by coal mining, in which heavy metals such as Fe, Mn, Zn, Ni, Cd, and Pb were found. The results showed sensitivity by this indicator in this type of water and suggest the evaluation of toxicity in waters from gold mining. Moreover, studies conducted in China by Wu et al. [57] demonstrated that the most frequently encountered heavy metals in a region affected by gold mining were mercury and cadmium, as observed in the results found in the drinking water of the population of Monterrey (Appendix A—Table A1 and Table A2).

4.1.2. Lactuca Sativa

The differences observed between chemical parameters and toxicity may be related to the fact that the samples were not collected simultaneously and that it is not the same water because along the river route and on the different sampling days, diverse factors can alter its quality. Likewise, dilution effects due to rain, sedimentation, the introduction of new pollutants, among others, can have an influence. Additionally, the water entering the treatment plant can be more contaminated, taking into account that it travels through tanks that are not in operation or comes into contact with sludge that might have a higher concentration of contaminants, which may return to the column of water.
The increase in germination, compared to the positive control (overgrowth), is related to the presence of organic matter because they are essential nutrients for L. sativa seed germination, and if they are available in high concentrations, they will stimulate growth. On the other hand, mercury and cyanide at the Village Tigui station (Appendix A—Table A1 and Table A2) had higher concentrations. The inhibition rates of 24% and 44% for samples 1 and 2 at the concentration of 25%, affect the growth of the seed as the higher concentration of pollutants results in greater inhibition. Castillo et al. [24] found inhibition in the germination of seeds in waters contaminated with mercury and argue that it can occur due to the harmful effects caused by mercury at the cellular level in the seed. These results coincide with other studies where L. sativa has been proposed as a useful tool to evaluate and compare the toxicity of industrial effluents that present heavy metal contamination [58].
Likewise, the level of cadmium (Appendix A—Table A1 and Table A2), also exceeded the minimum values established by the regulations for water for human consumption; studies have been reported where the exposure of L. sativa to this metal causes toxic and harmful effects that decrease its growth as the concentration of Cd, and thereby its adsorption, increases [59,60,61]. Just as the presence of heavy metals and cyanide has toxic implications in the plant and animal model, in the same way, it will affect the health of the human being [62,63].
Cd is one of the most toxic elements to which man is exposed since the accumulation of this metal in the body is gradual and increases with age due to its long half-life, greater than 20 years [64]. This is why eating food or drinking water with very high levels of cadmium causes severe stomach irritation, which causes vomiting, diarrhea, and sometimes death [64]. Moreover, cyanide exceeded the allowed limits (0.05 mg/L) in one of the samples analyzed in one of the houses (1.11 mg/L). The guide values of the World Health Organization [65] establish that the concentration of cyanide toxic to humans is 0.07 mg/L. Exposure to this concentration or higher may cause inhibition of cell growth, thereby affecting the breathing process and the metabolism of nitrogen and phosphate. It also inhibits the activity of some metalloproteins, joining cofactors such as the heme group of hemoglobin [66].
Finally, cyanide has acute effects on human health such as irritation of the eyes, nose, and throat. High exposure causes intoxication with headache, weakness, nausea, strong heartbeat, coma, and even death. As for chronic effects, it causes nosebleeds and nose lesions and can cause enlargement of the thyroid gland, which can interfere with its regular function [67].

4.2. Ames Test

In some cases, there was a decrease in reverts with increasing doses, which may be due to the presence of toxic substances that prevent the growth of bacteria [68]. However, in most of the sampling stations, a direct relationship was observed between the number of revertants and the increase in the concentration of heavy metals. This demonstrates the high probability of the presence of substances such as heavy metals and organic compounds in the Boque River that cause base-pair mutations and changes in the DNA reading frame of bacteria.
When observing the reversion of the strains, it was evidenced that they exceed 2–40 times the value of the negative control for the TA98 strain in the second sample in one of the houses, and from 2.0 to 2.5 for the TA100 strain in the third sample for the house and underground well. According to Orozco and Zuleta [69], some samples can exceed 100 times the negative control and these results are related to the quality of the water.
Likewise, Meléndez et al. [70] investigated the mutagenic activity of drinking water before and after chlorination at the Villa Hermosa plant, Medellín, Colombia, finding that contamination and chlorination influence mutagenicity. They used the Ames test with strains TA100 and TA98. Sierra et al. [71] evaluated the mutagenic activity of the Cauca River water with the same strains with and without the enzyme activator S9, finding that the highest rate of mutagenicity was observed with strain TA98 without enzyme activator. However, the TA100 strain is characterized by presenting the hisG46 mutation and has specific markers that give it greater sensitivity to the test; within these are the uvr mutation, the uvrB mutation, and the plasmid pKM101 [26,68].
Mesquidaz et al. [72] reported alarming figures in the mercury concentrations used in the gold extraction process in a mine in northern Colombia, which ranges from 50 to 100 tons in 2007. Furthermore, it is reported that, thanks to this pollutant present in water, the health of the population has been affected, since Hg was found in human hair at a concentration of 12.8 µg/g, a figure that is well above international standards. It has been shown that inhabitants of different municipalities in southern Bolívar where gold mining takes place have high levels of Hg contamination, and this situation requires special attention to reduce environmental and human health problems [4]. Mercury contamination has been linked to health problems, as direct absorption of mercury vapor released by incinerators in gold mining, or ingestion of mercury-containing wastes, causes hydrargyrism and poisoning. Mercury (Hg) is one of the heavy metals of greatest concern to populations that consume fish. This pollutant can be released from many sources and has various toxic effects in humans [73].
Some of the health problems caused are excessive salivation, shortness of breath and fatigue, bronchitis, tremors and irritability, personality changes (due to brain damage), a sensation of floating teeth and pain in them, kidney and respiratory damage that can lead to death from problems in the lungs and other organs of the body [74,75,76]. While breathing polluted air, elemental mercury can reach the brain, affecting nerve cells and the olfactory system. The main organs in which mercury accumulates are the brain and the kidney [77,78].

4.3. Statistical Analysis

The statistical analysis showed a relationship between the inhibition of L. sativa concerning mercury with a significance of p < 0.05; this inhibition in the germination of L. sativa with this metal was also reported in Chile, where the exposure of the seeds to Hg inhibited their growth [19]. The toxicity caused multiple harmful effects in the seed at the cellular level such as a change in permeability in the cell membrane and the affinity to react with phosphate groups and the sulfhydryl group (SH). When mercury interacts with the SH groups to form the S–Hg–S bonds, it disrupts the stability of the group can affect seed germination and seedling growth whose tissues are rich in SH groups [79].
On the other hand, it was not possible to establish a correlation between the vegetal and the animal model due to the number of samples collected. When comparing the results of the bioassays associating for D. magna and L. sativa, it was observed that the variability due to the sampling was not simultaneous for every sample and it could be possibly affected by a new spill in the river. Additionally, these are different organisms with different sensitivity to the contaminants present in the Boque River water and there exist other factors that can influence this response. For example, some bacteria can naturally modify mercury (Hg2+) by ion methylation forming CH3–Hg+, which is more toxic and is incorporated into trophic chains, affecting the animal model more than the vegetable model [80].

4.4. Total Coliforms, Escherichia Coli, and Somatic Coliphages

The microbiological results confirm the high fecal contamination in all the sampling stations (Table 4). Total coliform concentrations exceeded the limits for Colombian regulations [49]. In the case of drinking water for human consumption (deep-well underground and house), total coliforms and E. coli were well above levels required by regulation for drinking water [38]. Likewise, in the case of drinking water for human consumption by the treatment system (Village Gato, Tigui, and water catchment of the Boque River), the concentrations allowed for total coliforms were exceeded [49].
Campos-Pinilla et al. [81] and Sánchez-Alfonso et al. [82] in studies carried out in the Bogotá River found a total coliform concentration between 103 and 106 CFU/100 mL and for E. coli between 103 and 105/100 mL. This coincides with the values found in this study, which range between 103 and 105 CFU/100 mL of total coliforms and for E. coli between 103 and 104 CFU/100 mL (Table 4). Likewise, studies conducted by Lucena et al. [83] and Sánchez-Alfonso et al. [82] in rivers show average concentrations of somatic coliphages between 102 and 104 plaque forming unit (PFU)/100 mL, similar to those found in this study with ranges from 1 and 103 PFU/100 mL. The concentration of microorganisms in river water varies depending on climatic factors, geographical area, and the amount of organic matter present in water bodies [84,85]. The mine exploitation site is a settlement space for the population that works in this activity legally or illegally, which generates a high level of household waste in the river causing contamination by the discharge of fecal matter and organic matter, which explains the concentration of indicators of fecal contamination. It is related to the absence of treatment systems and improper installation of septic tanks.
The detected concentrations of total coliforms and E. coli in all the drinking water samples and the detection of somatic coliphages in some samples of water used for human consumption confirm the fecal contamination and the possible presence of pathogenic viruses in the drinking water (Table 4). These concentrations of indicators are similar to those detected in river samples as reported by Lucena et al. [83], Campos-Pinilla et al. [81], and Sánchez-Alfonso et al. [82], which could increase the risk for residents.

5. Conclusions

The results obtained with the three toxicity indicators reveal that H. attenuata does not present sensitivity to toxic substances present in this type of water, so its use for this purpose is not recommended. On the other hand, D. magna showed sensitivity even in diluted samples as well as L. sativa, which showed growth inhibition and excessive growth in different concentrations of the analyzed water, inclusive of waters with pollutant concentrations below the detection level. The Ames test shows an increase in the revertants indicating the possibility of mutations in the population that consumes this type of water, which is correlated with the results of the mutagenicity test that showed a mutagenic effect in the five stations evaluated with both strains used in the study. The highest mutagenic index was found in the water sample taken from the house sampling station. The concentration of bacteria in the water exceeded the limits allowed by Colombian regulations, creating a health risk, also with an alert call to the presence of possible pathogenic viruses, and the risk that they imply for the inhabitants of Monterrey due to somatic coliphage levels determined.
This research recognizes the potential use of bioassays to evaluate the toxic effects generated by chemical wastes produced by gold mining and discharged into surface waters. The use of animal and plant models is recommended to evaluate said effects on the environment and public health and infer the damages that until now have not been sufficiently evaluated having as correlation factors physicochemical and microbiological parameters.
Finally, this research generated data that contribute to the knowledge of the effects caused to the environmental and public health by illegal and legal mining carried out with bad practices in emerging countries with inefficient controls of this type of activity. These assays used can help sanitation organizations in different countries to take preventive actions on this issue

Author Contributions

All authors contributed to all features of the paper. A.M., J.A., J.L., L.S., C.V., A.O.-A., and M.D. were involved in the sampling and analysis of bacteria, coliphages, bioassays, and physicochemical determinations. C.C. and C.C.Z. conceived the idea for the research and contributed to the development of the project by obtaining economic resources. C.C., N.d.P., and C.C.Z. provided consultation and interpretation of the results and contributed to writing the manuscript. C.V., A.M., and J.L. edited the manuscript. All authors have read and agreed to the published version of the manuscript.

Funding

This research and article publication was funded by Pontificia Universidad Javeriana, Bogotá, Colombia. Grant number 0005746 and 0008469.

Acknowledgments

The authors would like to acknowledgment the residents of Monterrey Sur de Bolívar, Colombia, and Programa de Desarrollo y Paz del Magdalena Medio by the logistical support in sampling.

Conflicts of Interest

The authors declare no conflict of interest.

Appendix A

Table
Table A1. Results of physicochemical parameter analysis compared with the normative 0631/2015.
Table A1. Results of physicochemical parameter analysis compared with the normative 0631/2015.
Physicochemical Parameters
(n = 9)		Village GatoVillage TiguiWater Catchment of the Boque RiverLimit of the Regulations
Number of SamplingS1S2S3S1S2S3S1S2S3Normative 0631/2015 [37]
pH7.367.497.337.556.056.577.617.567.636.0–9.0
COD (mg/L)32.67<0.0015.5222.46<0.00124.1729.6340.724.82150
Total solids (g/10 mL)0.00240.001650.00.00070.00580.00290.00010.003160.000550
Cyanide (mg/L)<0.025<0.0250.0251.021.32<0.025<0.0251.57<0.0251.0
Cadmium (Cd) (mg/L)0.050.030.02<1.0 × 10−20.020.02<1.0 × 10−20.020.010.05
Chrome (Cr) (mg/L)<1.0 × 10−6<1.0 × 10−6<1.0 × 10−60.06<1.0 × 10−60.04<1.0 × 10−6<1.0 × 10−6<1.0 × 10−60.5
Mercury (Hg) (mg/L)0.00080.00290.00030.0010.00250.00080.00220.0020.00080.002
Nickel (Ni) (mg/L)<1.0 × 10−3<1.0 × 10−3<1.0 × 10−3<1.0 × 10−3<1.0 × 10−3<1.0 × 10−3<1.0 × 10−3<1.0 × 10−3<1.0 × 10−30.5
Zinc (Zn) (mg/L)<1.0 × 10−3<1.0 × 10−3<1.0 × 10−3<1.0 × 10−3<1.0 × 10−3<1.0 × 10−3<1.0 × 10−3<1.0 × 10−3<1.0 × 10−33.0
mg/L: milligram per liter; S: sampling, the numbers 1S, 2S, and 3S correspond to the month of July, September, and December in which the sample was taken; <: less than the limit of quantification; n: is the number of samples; COD: chemical oxygen demand.
Table
Table A2. Results of physicochemical parameters analysis compared with the normative 2115 of 2007.
Table A2. Results of physicochemical parameters analysis compared with the normative 2115 of 2007.
Physicochemical Parameters
(n = 6)		HouseDeep-Well UndergroundLimit of the Regulations
Number of samplingS1S2S3S1S2S3Normative 2115/2007 [38]
pH7.67.537.446.956.796.616.5–9.0
Cyanide (mg/L)<0.0251.11<0.025<0.025<0.025<0.0250.05
Cadmium (Cd) (mg/L)<1.0 × 10−20.030.03<1.0 × 10−20.01<1.0 × 10−20.003
Chrome (Cr) (mg/L)0.02<1.0 × 10−6<1 × 10−6<1.0 × 10−6<1.0 × 10−6<1.0 × 10−60.05
Mercury (Hg) (mg/L)0.00040.00050.00030.00070.00030.00070.001
Nickel (Ni) (mg/L)<1.0 × 10−3<1.0 × 10−3<1.0 × 10−3<1.0 × 10−3<1.0 × 10−3<1.0 × 10−30.2
Zinc (Zn) (mg/L)<1.0 × 10−3<1.0 × 10−3<1.0 × 10−3<1.0 × 10−3<1.0 × 10−3<1.0 × 10−33.0
mg/L: milligram per liter; S: sampling, the numbers 1S, 2S, and 3S correspond to the month of July, September, and December in which the sample was taken; <: less than the limit of quantification; n: is the number of samples.

References

  1. UNIDO Green Industry Initiative for Sustainable Industrial Development 2011. Available online: https://www.greengrowthknowledge.org/sites/default/files/downloads/resource/Green_Industry_Initiative_for_Sustainable_Development_UNIDO.pdf (accessed on 12 February 2020).
  2. Ogola, J.S.; Mitullah, W.V.; Omulo, M.A. Impact of gold mining on the environment and human health: A case study in the Migori Gold Belt, Kenya. Environ. Geochem. Health 2002, 24, 141–157. [Google Scholar] [CrossRef]
  3. Gafur, N.A.; Sakakibara, M.; Sano, S.; Sera, K. A case study of heavy metal pollution in water of Bone River by artisanal small-scale gold mine activities in eastern part of Gorontalo, Indonesia. Water 2018, 10, 1507. [Google Scholar] [CrossRef] [Green Version]
  4. Carranza-Lopez, L.; Caballero-Gallardo, K.; Cervantes-Ceballos, L.; Turizo-Tapia, A.; Olivero-Verbel, J. Multicompartment mercury contamination in major gold mining districts at the department of Bolivar, Colombia. Arch. Environ. Contam. Toxicol. 2019, 76, 640–649. [Google Scholar] [CrossRef] [PubMed]
  5. Pinedo-Hernández, J.; Marrugo-Negrete, J.; Díez, S. Speciation and bioavailability of mercury in sediments impacted by gold mining in Colombia. Chemosphere 2015, 119, 1289–1295. [Google Scholar] [CrossRef] [PubMed]
  6. Von Behren, J.; Liu, R.; Sellen, J.; Duffy, C.N.; Gajek, R.; Choe, K.-Y.; DeGuzman, J.; Janes, M.K.; Hild, J.; Reynolds, P. Heavy metals in California women living in a gold mining-impacted community. Int. J. Environ. Res. Public Health 2019, 16, 2252. [Google Scholar] [CrossRef] [Green Version]
  7. Ouboter, P.E.; Landburg, G.; Satnarain, G.U.; Starke, S.Y.; Nanden, I.; Simon-Friedt, B.; Hawkins, W.B.; Taylor, R.; Lichtveld, M.Y.; Harville, E.; et al. Mercury levels in women and children from interior villages in Suriname, South America. Int. J. Environ. Res. Public Health 2018, 15, 1007. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  8. Producción de oro en Colombia Creció 7% en el Primer Trimestre de 2020. Available online: https://www.elespectador.com/economia/produccion-de-oro-en-colombia-crecio-7-en-el-primer-trimestre-de-2020-articulo-920587/ (accessed on 22 May 2020).
  9. Robles Mengoa, M.E.; Urán, A. Colombia: Legal loopholes behind illegal gold trade. In Global Gold Production Touching Ground, 1st ed.; Springer International Publishing: New York, NY, USA, 2020; pp. 151–161. [Google Scholar]
  10. Güiza, L. Small scale mining in Colombia: Not such a small activity. DYNA 2013, 80, 109–117. [Google Scholar]
  11. DANE Proyecciones de Población Departamentales Por Área 2015–2020. Available online: https://www.dane.gov.co/files/investigaciones/poblacion/proyepobla06_20/7Proyecciones_poblacion.pdf (accessed on 22 February 2020).
  12. Ministerio de Minas y Energía Censo Minero Departamental 2010–2011. Available online: https://www.minenergia.gov.co/documents/10180/698204/CensoMinero.pdf/093cec57-05e8-416b-8e0c-5e4f7c1d6820 (accessed on 8 February 2020).
  13. De la Hoz, V.J. Economía y conflicto en el Cono Sur del Departamento de Bolívar. Banco de la República 2009, 110, 1–109. [Google Scholar]
  14. Alcaldía de Simití-Bolívar Plan de Desarrollo ¡Simití Pata Todos! 2016–2019. Available online: https://simitibolivar.micolombiadigital.gov.co/sites/simitibolivar/content/files/000132/6580_plan-de-desarrollo-municipal-20162019.pdf (accessed on 22 July 2020).
  15. Grajales, A.K. El Río Grande la Magdalena Como Eje Estructurante del Desarrollo territorial. Estudio de Caso: Magdalena Medio 1950–2010; Empresas Publicas de Medellin (EPM): Medellin, Colombia, 2012; pp. 1–65. [Google Scholar]
  16. Donato, D.B.; Nichols, O.; Possingham, H.; Moore, M.; Ricci, P.F.; Noller, B.N. A critical review of the effects of gold cyanide-bearing tailings solutions on wildlife. Environ. Int. 2007, 33, 974–984. [Google Scholar] [CrossRef]
  17. Hilson, G. Abatement of mercury pollution in the small-scale gold mining industry: Restructuring the policy and research agendas. Sci. Total Environ. 2006, 362, 1–14. [Google Scholar] [CrossRef]
  18. Hilson, G.; Murck, B. Progress toward pollution prevention and waste minimization in the North American gold mining industry. J. Clean Prod. 2001, 9, 405–415. [Google Scholar] [CrossRef]
  19. Cordy, P.; Veiga, M.M.; Salih, I.; Al-Saadi, S.; Console, S.; Garcia, O.; Mesa, L.A.; Velásquez-López, P.C.; Roeser, M. Mercury contamination from artisanal gold mining in Antioquia, Colombia: The world’s highest per capita mercury pollution. Sci. Total Environ. 2011, 410, 154–160. [Google Scholar] [CrossRef] [PubMed]
  20. Bohórquez-Echeverry, P.; Duarte-Castañeda, M.; León-López, N.; Caicedo-Carrascal, F.; Vásquez-Vásquez, M.; Campos-Pinilla, C. Selection of a bioassay battery to assess toxicity in the affluents and effluents of three water-treatment plants. Univ. Sci. 2012, 17, 152–166. [Google Scholar] [CrossRef] [Green Version]
  21. Keddy, C.J.; Greene, J.C.; Bonnell, M.A. Review of whole-organism bioassays: Soil, freshwater sediment, and freshwater assessment in Canada. Ecotoxicol. Environ. Saf. 1995, 30, 221–251. [Google Scholar] [CrossRef]
  22. Miller, W.E.; Peterson, S.A.; Greene, J.C.; Callahan, C.A. Comparative toxicology of laboratory organisms for assessing Hazardous Waste Sites. J. Environ. Qual. 1985, 14, 569–574. [Google Scholar] [CrossRef]
  23. Férard, J.F.; Burga Pérez, K.F.; Blaise, C.; Péry, A.; Sutthivaiyakit, P.; Gagné, F. Microscale ecotoxicity testing of Moselle river watershed (Lorraine Province, France) sediments. J. Xenobiot. 2015, 5, 1–7. [Google Scholar] [CrossRef]
  24. Castillo, G.C.; Vila, I.C.; Ella, N. Ecotoxicity assessment of metals and wastewater using multitrophic assays. Environ. Toxicol. 2000, 15, 370–375. [Google Scholar] [CrossRef]
  25. MacGregor, J.T.; Casciano, D.; Müller, L. Strategies and testing methods for identifying mutagenic risks. Mutat. Res. 2000, 455, 3–20. [Google Scholar] [CrossRef]
  26. Maron, D.M.; Ames, B.N. Revised methods for the Salmonella mutagenicity test. Mutat. Res. 1983, 113, 173–215. [Google Scholar] [CrossRef]
  27. González Scancella, T. Evaluación del Sistema de Abastecimiento de Agua Potable y Disposición de Excretas de la Población del Corregimiento de Monterrey, Municipio de Simití, Departamento de Bolívar, Proponiendo Soluciones Integrales al Mejoramiento de Los Sistemas y la Salud de la Comunidad; Ecology College Degree, Pontificia Universidad Javeriana: Bogotá, Colombia, 2013. [Google Scholar]
  28. Barrera, J.A.; Espinosa, A.J.; Álvarez, J.P. Contaminación en el Lago de Tota, Colombia: Toxicidad aguda en Daphnia magna (Cladocera: Daphniidae) e Hydra attenuata (Hydroida: Hydridae). Rev. biol. Trop. 2019, 67, 11–23. [Google Scholar] [CrossRef]
  29. Espinosa-Ramírez, A.J. El Agua, un Reto Para la Salud Pública. La Calidad del Agua y las Oportunidades Para la Vigilancia en Salud Ambiental. Ph.D. Thesis, Universidad Nacional de Colombia, Bogotá, Colombia, 2018. [Google Scholar]
  30. Zeiger, E. The test that changed the world: The Ames test and the regulation of chemicals. Mutat. Res. 2019, 841, 43–48. [Google Scholar] [CrossRef] [PubMed]
  31. American Public Health Association 2310 B. Titration method. In Standard Methods for the Examination of Water and Wastewater; American Public Health Association: Washington, DC, USA, 2012; p. 1946. [Google Scholar]
  32. American Public Health Association 5220 D. Closed reflux, colorimetric method. In Standard Methods for the Examination of Water and Wastewater; American Public Health Association: Washington, DC, USA, 2012; p. 1946. [Google Scholar]
  33. American Public Health Association 2540 B. Total solids dried at 103–105 °C. In Standard Methods for the Examination of Water and Wastewater; American Public Health Association: Washington, DC, USA, 2012; p. 1946. [Google Scholar]
  34. American Public Health Association 3111. Metals by flame atomic absorption spectrometry. In Standard Methods for the Examination of Water and Wastewater; American Public Health Association: Washington, DC, USA, 2012; p. 1946. [Google Scholar]
  35. American Public Health Association 3112B. Metals by cold-vapor atomic absorption spectrometry. In Standard Methods for the Examination of Water and Wastewater; American Public Health Association: Washington, DC, USA, 2012; p. 1946. [Google Scholar]
  36. American Public Health Association 4500-CN-E. Colorimetric method. In Standard Methods for the Examination of Water and Wastewater; American Public Health Association: Washington, DC, USA, 2012; p. 1946. [Google Scholar]
  37. Ministerio de Ambiente y Desarrollo Sostenible Resolución 0631 de 2015, Parámetros y los Valores Límites Máximos Permisibles en los Vertimientos Puntuales a Cuerpos de Aguas Superficiales y a Los Sistemas de al Cantarillado Público y se Dictan Otras Disposiciones. Available online: https://www.minambiente.gov.co/images/normativa/app/resoluciones/d1-res_631_marz_2015.pdf (accessed on 21 March 2020).
  38. Ministerio de Protección Social, Ministerio de Ambiente, Vivienda y Desarrollo Territorial Resolución 2115 de 2007, Características, Instrumentos Básicos y Frecuencias del Sistema de Control y Vigilancia Para la Calidad del Agua Para Consumo Humano. Available online: https://www.minambiente.gov.co/images/GestionIntegraldelRecursoHidrico/pdf/Legislaci%C3%B3n_del_agua/Resoluci%C3%B3n_2115.pdf (accessed on 21 March 2020).
  39. Dutka, B. Short-term root elongation toxicity bioassay. In Methods for Toxicological Analysis of Waters, Wastewaters and Sediments, Rivers Research Branch; Canada Centre for Inland Waters, National Water Research Institute: Burlington, ON, Canada, 1989; pp. 120–122. [Google Scholar]
  40. Trottier, S.; Biaise, C.; Kusui, T.; Johnson, E.M. Acute toxicity assessment of aqueous samples using a microplate-based hydra attenuata assay. Environ. Toxicol. Water Qual. 1997, 12, 265–271. [Google Scholar] [CrossRef]
  41. Dutka, B. Daphnia magna 48 hours static bioassay method for acute toxicity in environmental samples. In Methods for Toxicological Analysis of Waters, Wastewaters and Sediments; Rivers Research Branch; Canada Centre for Inland Waters, National Water Research Institute: Burlington, ON, Canada, 1989; pp. 55–59. [Google Scholar]
  42. EPA. Method for Measuring the Acute Toxicity of Effluents to Freshwater and Marine Organism, 3rd ed.; Environmental Monitoring Systems Laboratory, Office of Research and Development Environmental Protection Agency: Washington, DC, USA, 1985; p. 231.
  43. Finney, D.J. Probit Analysis, 2nd ed.; Cambridge University Press: New York, NY, USA, 1952; p. 318. [Google Scholar]
  44. Hamilton, M.A.; Russo, R.C.; Thurston, R.V. Trimmed spearman-karber method for estimating median lethal concentrations in toxicity bioassays. Environ. Sci. Technol. 1977, 11, 714–719. [Google Scholar] [CrossRef]
  45. Williams, L.; Preston, J.E. Interim Procedures for Conducting the Salmonella/Microsomal Mutagenicity Assay (Ames Test); Environmental Protection Agency: Las Vegas, NV, USA, 1983; p. 40.
  46. Ames, B.N.; Kammen, H.O.; Yamasaki, E. Hair Dyes are mutagenic: Identification of a variety of mutagenic ingredients. Proc. Natl. Acad. Sci. USA 1975, 72, 2423–2427. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  47. International Organization for Standardization. ISO 9308-1: Water Quality—Enumeration of Escherichia coli and Coliform Bacteria-Part 1: Membrane Filtration Method for Waters with Low Bacterial Background Flora, 3rd ed.; International Organization for Standardization: Geneva, Switzerland, 2014. [Google Scholar]
  48. International Organization for Standardization. ISO 10705-2: Water Quality. Detection and Enumeration of Bacteriophages-Part 2: Enumeration of Somatic Coliphages, 1st ed.; International Organization for Standardization: Geneva, Switzerland, 2000. [Google Scholar]
  49. de Ministerio, A. Decreto 1594 de 1984, Por el cual se Reglamenta Parcialmente el del Decreto Ley 2811 de 1974 en Cuanto a Usos del Agua y Residuos Líquidos. Available online: https://www.minambiente.gov.co/images/GestionIntegraldelRecursoHidrico/pdf/normativa/Decreto_1594_de_1984.pdf (accessed on 6 February 2020).
  50. Holdway, D.A.; Lok, K.; Semaan, M. The acute and chronic toxicity of cadmium and zinc to two hydra species. Environ. Toxicol. 2001, 16, 557–565. [Google Scholar] [CrossRef]
  51. Riethmuller, N.; Markich, S.J.; Van Dam, R.A.; Parry, D. Effects of water hardness and alkalinity on the toxicity of uranium to a tropical freshwater hydra (hydra viridissima). Biomarkers 2001, 6, 45–51. [Google Scholar] [CrossRef]
  52. Sundaram, R.; Smith, B.W.; Clark, T.M. pH-dependent toxicity of serotonin selective reuptake inhibitors in taxonomically diverse freshwater invertebrate species. Mar. Freshw. Res. 2015, 66, 518–525. [Google Scholar] [CrossRef]
  53. Forget, G.; Gagnon, P.; Sanchez, W.A.; Dutka, B.J. Overview of methods and results of the eight country International Development Research Centre (IDRC) WaterTox project. Environ. Toxicol. 2000, 15, 264–276. [Google Scholar] [CrossRef]
  54. de Castro-Català, N.; Kuzmanovic, M.; Roig, N.; Sierra, J.; Ginebreda, A.; Barceló, D.; Pérez, S.; Petrovic, M.; Picó, Y.; Schuhmacher, M.; et al. Ecotoxicity of sediments in rivers: Invertebrate community, toxicity bioassays and the toxic unit approach as complementary assessment tools. Sci. Total Environ. 2016, 540, 297–306. [Google Scholar] [CrossRef] [Green Version]
  55. Yuan, N.; Pei, Y.; Bao, A.; Wang, C. The Physiological and Biochemical Responses of Daphnia magna to Dewatered Drinking Water Treatment Residue. Int. J. Environ. Res. Public Health 2020, 17, 5863. [Google Scholar] [CrossRef]
  56. Lattuada, R.M.; Menezes, C.T.B.; Pavei, P.T.; Peralba, M.C.R.; Dos Santos, J.H.Z. Determination of metals by total reflection X-ray fluorescence and evaluation of toxicity of a river impacted by coal mining in the south of Brazil. J. Hazard. Mater. 2009, 163, 531–537. [Google Scholar] [CrossRef] [PubMed]
  57. Wu, Y.G.; Xu, Y.N.; Zhang, J.H.; Hu, S.H. Evaluation of ecological risk and primary empirical research on heavy metals in polluted soil over Xiaoqinling gold mining region, Shaanxi, China. Trans. Nonferrous Met. Soc. China 2010, 20, 688–694. [Google Scholar] [CrossRef]
  58. Charles, J.; Sancey, B.; Morin-Crini, N.; Badot, P.M.; Degiorgi, F.; Trunfio, G.; Crini, G. Evaluation of the phytotoxicity of polycontaminated industrial effluents using the lettuce plant (Lactuca sativa) as a bioindicator. Ecotoxicol Environ. Saf. 2011, 74, 2057–2064. [Google Scholar] [CrossRef]
  59. Cornu, J.Y.; Denaix, L.; Schneider, A.; Pellerin, S. Temporal variability of solution Cd2+ concentration in metal-contaminated soils as affected by soil temperature: Consequences on lettuce (Lactuca sativa L.) exposure. Plant. Soil 2008, 307, 51–65. [Google Scholar] [CrossRef]
  60. Tang, X.; Pang, Y.; Ji, P.; Gao, P.; Nguyen, T.H.; Tong, Y. Cadmium uptake in above-ground parts of lettuce (Lactuca sativa L.). Ecotoxicol. Environ. Saf. 2016, 125, 102–106. [Google Scholar] [CrossRef] [PubMed]
  61. Retamal-Salgado, J.; Hirzel, J.; Walter, I.; Matus, I. Bioabsorption and Bioaccumulation of Cadmium in the Straw and Grain of Maize (Zea mays L.) in Growing Soils Contaminated with Cadmium in Different Environment. Int. J. Environ. Res. Public Health 2017, 14, 1399. [Google Scholar] [CrossRef] [Green Version]
  62. Duri, L.; Visconti, D.; Fiorentino, N.; Adamo, P.; Fagnano, M.; Caporale, A. Health risk assessment in agricultural soil potentially contaminated by Geogenic Thallium: Influence of plant species on metal mobility in soil-plant system. Agronomy 2020, 10, 890. [Google Scholar] [CrossRef]
  63. Mercado-Garcia, D.; Beeckman, E.; Van Butsel, J.; Arroyo, N.D.; Peña, M.S.; Van Buggendhoudt, C.; Saeyer, N.D.; Forio, M.A.E.; Schamphelaere, K.A.C.D.; Wyseure, G.; et al. Assessing the freshwater quality of a large-scale miningwatershed: The need for integrated approaches. Water 2019, 11, 1797. [Google Scholar] [CrossRef] [Green Version]
  64. Atsdr, E.P.A. Agency for toxic substances and disease registry case studies in environmental medicine (CSEM). Cadmium 2011, 1, 1–63. [Google Scholar]
  65. Guidelines for Drinking-Water Quality. Available online: https://www.paho.org/en/documents/guidelines-drinking-water-quality-4o-ed-2011 (accessed on 19 March 2020).
  66. Castillo Rodriguez, F. Biotecnología Ambiental; Editorial Tebar Flores: Madrid, Spain, 2005; p. 592. [Google Scholar]
  67. New Jersey Department of Health and Senior Services Hazardous Substance Fact Sheet 2007. Available online: http://www.nj.gov/health/eoh/rtkweb/documents/fs/0027.pdf (accessed on 22 March 2020).
  68. Ames, B.N.; Lee, F.D.; Durston, W.E. An improved bacterial test system for the detection and classification of Mutagens and Carcinogens. Proc. Natl. Acad. Sci. USA 1973, 70, 782–786. [Google Scholar] [CrossRef] [Green Version]
  69. Orozco, L.Y.; Zuleta, M. Detección de mutacarcinógenos en aguas del Río Pantanillo y efecto genotóxico de esta agua en el DNA nuclear y mitocondrial de células eucarióticas. Iatreia 2000, 13, 94. [Google Scholar]
  70. Meléndez, I.; Zuleta, M.; Marín, I.; Calle, J.; Salazar, D. Actividad mutagénica de aguas de consumo humano antes y después de clorar en la planta de Villa Hermosa, Medellín. Iatreia 2001, 14, 167–175. [Google Scholar]
  71. Sierra, J.; Benitez, N.; Bravo, E.; Larmat, F.; Soto, A. Evaluation of the mutagenic activity of waters collected from the Cauca River in the city Cali, Colombia by using the Salmonella/Microsome Assay. Revista de Ciencias 2012, 16, 131. [Google Scholar]
  72. Mesquidaz, E.D.; Negrete, J.M.; Hernández, J.P. Exposición a mercurio en trabajadores de una mina de oro en el norte de Colombia. Salud Uninorte 2013, 29, 534–541. [Google Scholar]
  73. Manjarres-Suarez, A.; Olivero-Verbel, J. Hematological parameters and hair mercury levels in adolescents from the Colombian Caribbean. Environ. Sci. Pollut. Res. 2020, 27, 14216–14227. [Google Scholar] [CrossRef]
  74. Zahir, F.; Rizwi, S.J.; Haq, S.K.; Khan, R.H. Low dose mercury toxicity and human health. Environ. Toxicol Pharmacol. 2005, 20, 351–360. [Google Scholar] [CrossRef]
  75. Næss, S.; Kjellevold, M.; Dahl, L.; Nerhus, I.; Midtbø, L.K.; Bank, M.S.; Rasinger, J.D.; Markhus, M.W. Effects of seafood consumption on mercury exposure in Norwegian pregnant women: A randomized controlled trial. Environ. Int. 2020, 141, 105759. [Google Scholar] [CrossRef]
  76. Pateda, S.; Sakakibara, M.; Sera, K. Lung function assessment as an early biomonitor of mercury-induced health disorders in artisanal and small-scale gold mining areas in Indonesia. Int. J. Environ. Res. Public Health 2018, 15, 2480. [Google Scholar] [CrossRef] [Green Version]
  77. Park, J.-D.; Zheng, W. Human exposure and health effects of inorganic and elemental mercury. J. Prev. Med. Public Health 2012, 34445, 344–352. [Google Scholar] [CrossRef]
  78. Gyamfi, O.; Sorenson, P.B.; Darko, G.; Ansah, E.; Bak, J.L. Human health risk assessment of exposure to indoor mercury vapour in a Ghanaian artisanal small-scale gold mining community. Chemosphere 2020, 241, 125014. [Google Scholar] [CrossRef]
  79. Patra, M.; Bhowmik, N.; Bandopadhyay, B.; Sharma, A. Comparison of mercury, lead and arsenic with respect to genotoxic effects on plant systems and the development of genetic tolerance. Environ. Exp. Bot. 2004, 52, 199–223. [Google Scholar] [CrossRef]
  80. Clarkson, T.W.; Magos, L. The toxicology of mercury and its chemical compounds. Crit. Rev. Toxicol. 2006, 36, 609–662. [Google Scholar] [CrossRef] [PubMed]
  81. Campos-Pinilla, C.; Cárdenas-Guzmán, M.; Guerrero-Cañizares, A. Comportamiento de los indicadores de contaminación fecal en diferente tipo de aguas de la sabana de Bogotá (Colombia). Univ. Sci. 2008, 13, 103–108. [Google Scholar]
  82. Sánchez-Alfonso, A.C.; Venegas, C.; Díez, H.; Méndez, J.; Blanch, A.R.; Jofre, J.; Campos, C. Microbial indicators and molecular markers used to differentiate the source of faecal pollution in the Bogotá River (Colombia). Int. J. Hyg. Environ. Health 2020, 225, 113450. [Google Scholar] [CrossRef] [PubMed]
  83. Lucena, F.; Méndez, X.; Morón, A.; Calderón, E.; Campos, C.; Guerrero, A.; Cárdenas, M.; Gantzer, C.; Shwartzbrood, L.; Skraber, S.; et al. Occurrence and densities of bacteriophages proposed as indicators and bacterial indicators in river waters from Europe and South America. J. Appl. Microbiol. 2003, 94, 808–815. [Google Scholar] [CrossRef]
  84. Augustyn, Ł.; Babula, A.M.; Joniec, J.; Stanek-Tarkowska, J.; Hajduk, E.; Kaniuczak, J. Microbiological indicators of the quality of river water, used for drinking water supply. Pol. J. Environ. Stud. 2016, 25, 511–519. [Google Scholar] [CrossRef] [Green Version]
  85. Jofre, J.; Lucena, F.; Blanch, A.R.; Muniesa, M. Coliphages as model organisms in the characterization and management of water resources. Water 2016, 8, 199. [Google Scholar] [CrossRef] [Green Version]
Water 12 02523 g001 550
Figure 1. Location of sampling stations in Monterrey, Simití-Bolívar, Colombia. Source: authors.
Figure 1. Location of sampling stations in Monterrey, Simití-Bolívar, Colombia. Source: authors.
Water 12 02523 g001
Table
Table 1. Bioassays results with Lactuca sativa.
Table 1. Bioassays results with Lactuca sativa.
Sampling Station
(n = 15)		1S
% (v/v) Effect		2S
% (v/v) Effect		3S
% (v/v) Effect
Village Gato33% Inhibition to 75%27% Inhibition to 100%133% Growth to 25%
Village Tigui44% Inhibition to 25%24% Inhibition to 25%4% Inhibition to 50%
Water catchment of the Boque River0% Inhibition to 100%27% Inhibition to 100%110% Growth to 100%
House34% Inhibition to 25%19% Inhibition to 75%6% Inhibition to 50%
Deep-well underground35% Inhibition to 50%36% Inhibition to 75%6% Inhibition to 75%
S: sampling, the numbers 1S, 2S, and 3S correspond to the months of July, September, and December in which the sample was taken; n: is the number of samples.
Table
Table 2. Results of bioassay with Daphnia magna.
Table 2. Results of bioassay with Daphnia magna.
Sampling Station3S
% (v/v) Effect
(n = 15)
Village Tigui17% mortality to 75%
Village Gato33% mortality to 100%
Water catchment of the Boque River23% mortality to 50%
House47% mortality to 100%
Deep-well underground43% mortality to 100%
S: sampling, the number 3S corresponds to the month of December in which the sample was taken; n: is the number of samples.
Table
Table 3. Mutagenic index, for each concentration analyzed in the five sampling stations with strain Salmonella typhimurium TA98 and S. typhimurium TA100.
Table 3. Mutagenic index, for each concentration analyzed in the five sampling stations with strain Salmonella typhimurium TA98 and S. typhimurium TA100.
Sampling Stations
(n = 15)		Concentration v/v (%)TA98TA100
(MI)(MI)
S1S2S3S1S2S3
Village Gato250.771.070.000.970.461.00
500.860.870.201.090.681.20
751.061.490.601.270.771.70
1001.121.931.001.511.142.40
Village Tigui250.970.700.001.370.200.60
500.950.740.001.390.340.90
751.121.140.101.480.331.00
1001.211.820.401.810.561.20
Water catchment of the Boque River251.170.390.300.940.270.60
501.390.630.501.000.240.70
751.410.470.601.210.351.10
1001.500.590.901.710.441.30
House250.6841.780.401.0111.050.60
501.0048.490.601.1712.391.00
751.0656.620.801.3613.752.00
1001.2158.311.101.7015.092.50
Deep-well underground2588.00.390.201.020.370.80
500.880.500.501.161.211.20
751.000.500.801.230.421.70
1000.550.640.901.280.642.00
S: sampling, the numbers 1S, 2S, and 3S correspond to the month of July, September, and December in which the sample was taken; n: is the number of samples; MI: mutagenic index.
Table
Table 4. Results of total coliforms, Escherichia coli, and somatic coliphages in waters of the Boque River and drinking waters.
Table 4. Results of total coliforms, Escherichia coli, and somatic coliphages in waters of the Boque River and drinking waters.
Sampling Stations
(n = 15)		Microbiological Indicators
Total Coliforms
CFU/100 mL		E. coli
CFU/100 mL		Somatic Coliphages
PFU/100 mL
1S2S3S1S2S3S1S2S3S
Village Gato7.0 × 1031.1 × 1054.1 × 1051.0 × 1034.0 × 1038.0 × 1041.4 × 1031.0 × 1024.5
Village Tigui1.3 × 1053.2 × 1042.2 × 1052.0 × 1032.0 × 1033.0 × 1044.9 × 1033.0 × 102<1.0 × 103
Water catchment of the Boque River2.4 × 1041.7 × 1044.0 × 1051.0 × 1031.0 × 1031.0 × 104<1.0 × 102<1.0 × 1031.9
House4.0 × 1041.4 × 1052.8 × 1051.0 × 1033.0 × 1043.0 × 1041.0 × 1022.0 × 1041.0 × 102
Deep-well underground3.2 × 1046.0 × 1043.8 × 1051.0 × 1034.0 × 1044.0 × 1042.0 × 102<1.0 × 1031.0
CFU/100 mL: colony forming units in 100 mL of analyzed water; PFU/100 mL: plaque forming units in 100 mL of analyzed water; n: number of samples analyzed. S: sampling, the numbers 1S, 2S, and 3S correspond to the month of July, September, and December in which the sample was taken; <: less than the limit of quantification; n: is the number of samples.

Share and Cite

MDPI and ACS Style

Martín, A.; Arias, J.; López, J.; Santos, L.; Venegas, C.; Duarte, M.; Ortíz-Ardila, A.; de Parra, N.; Campos, C.; Zambrano, C.C. Evaluation of the Effect of Gold Mining on the Water Quality in Monterrey, Bolívar (Colombia). Water 2020, 12, 2523. https://doi.org/10.3390/w12092523

AMA Style

Martín A, Arias J, López J, Santos L, Venegas C, Duarte M, Ortíz-Ardila A, de Parra N, Campos C, Zambrano CC. Evaluation of the Effect of Gold Mining on the Water Quality in Monterrey, Bolívar (Colombia). Water. 2020; 12(9):2523. https://doi.org/10.3390/w12092523

Chicago/Turabian Style

Martín, Alison, Juliana Arias, Jennifer López, Lorena Santos, Camilo Venegas, Marcela Duarte, Andrés Ortíz-Ardila, Nubia de Parra, Claudia Campos, and Crispín Celis Zambrano. 2020. "Evaluation of the Effect of Gold Mining on the Water Quality in Monterrey, Bolívar (Colombia)" Water 12, no. 9: 2523. https://doi.org/10.3390/w12092523

Note that from the first issue of 2016, this journal uses article numbers instead of page numbers. See further details here.

Article Metrics

Back to TopTop