An Overview of Quality Assessment Methods for Water and Soil in Mining Regions ^†

Abstract

Mining activities are a form of severe anthropogenic stress and result in water and soil contamination in mining sites. A decline in the quality of water affects humans directly through water consumption or indirectly through contaminated food consumption. Soil pollution has an immediate consequence on farming products and soil fertility and may affect water resources. Monitoring environmental conditions and changes is essential for mining industries and local authorities. The aim of this paper is to review different methods, their purpose, and adequacy, for the environmental management of mining areas.

1. Introduction

Overall, mining activities have significant effects on the extensive ecosystem of mining sites, with the most common and severe being acid mine drainage (AMD). Potentially toxic elements (PTEs) that originate from AMD are hazardous to the ecosystem as they end up in water streams and on agricultural land [1]. Even in abandoned mines, ecosystems can be affected by fluoride and PTE contamination or by the salinization of water bodies due to long-term mining [2].

Monitoring water and soil is crucial when environmental pressure of a high risk is present. Using biodiversity or a biological community as a monitoring system can be the key to assessing contaminants’ impacts and the extent of pollution [3]. Bioindicators are organisms whose changes are observed when exposed to unusual natural conditions [3]. Such organisms should be highly available in areas of interest with an adequate spatio-temporal distribution, easy to collect and cost-effective [3]. As for their nature, they should be sensitive to changes but tolerant of extreme conditions. For example, planktons are a great bioindicator of water quality, especially in lakes, due to their abundance, fast reproduction, and rapid reaction to environmental changes [4].

In order to determine the quality of water and soil, their physical, chemical and biological properties should be examined. This paper provides quality evaluation methods often used in mining sites, and examines their suitability, as determined via the following parameters:

• Their purpose: What information can the method provide and which property does it regard (chemical, physical, or biological)? In which cases should it be utilized?
• Their adequacy: Is the method sufficient to determine the degree of pollution?

2. Materials & Methods

2.1. Water Resources

Quality indices (or chemical indices) are a direct and economical way to assess the quality of water. Statistical methods are an efficient tool with which to support the results of indices and are mainly used for the analysis of spatio-temporal changes [5].

Quality indices are valuable tools with which to evaluate the degree of pollution by converting the concentrations of selected parameters into classes concerning their quality [5]. Although they are developed to be applied in regions with specific conditions (specific indices), there are indices that can be of use to policymakers in estimating the overall quality of water and determining optimal water management methods (public and planning indices) [6].

Most of the properties taken into consideration in quality indices are chemical or physical, and their purpose is to quantify the degree of pollution. However, the impact of contamination on the ecosystem can be examined through studying organisms that inhabit the area. Thus, indices that concern biological factors, such as biotic indices and the trophic state index (TSI), are of great significance [7].

The general steps of the development of a quality index are as follows:

• Distinguish the key parameters;
• Create sub-indices (classes based on the type of water use and the nature of the property);
• Assign weights to each parameter;
• Apply a suitable function to calculate the WQI [5].

The most frequently used parameters of each property are the following:

• Physical: temperature, turbidity, color, taste, and odor;
• Chemical: pH, alkalinity, DO, BOD, chlorine (Cl), inorganic toxic substances, fluoride (F⁻), iron (Fe), manganese (Mn), copper (Cu), nitrogen (N₂), and zinc (Zn);
• Biological: total viable count, coliforms, protozoa, and algae;

An overview of the most frequently used and valuable indices and statistical methods for evaluating the quality of water is presented below (Table 1).

Table 1. Methods and indices for water quality assessment.

Method/Index	Formula	Summary
Heavy Metal Pollution Index (HPI)	$HPI=\frac{{\sum }_{i=1}^n{W}_i{Q}_i}{{\sum }_{i=1}^n{W}_i}$ Sub-Index: $Q_i={\displaystyle \sum _{i=1}^n}\frac{|M_i-I_i|}{S_i-I_i}100$	Indicates the combined effect of individual PTEs on the quality of water by assigning weights depending on the significance of each potentially toxic element.	[8]
Heavy Metal Evaluation Index (HEI)	$HEI={\displaystyle \sum _{i=1}^n}\frac{H_c}{H_{mac}}$	Presents the overall water quality with respect to the presence of PTEs.	[8]
Degree of Contamination (Cd)	$C_d={\displaystyle \sum _{i=1}^n}{Cf}_i$ Contamination Factor: ${Cf}_i=\frac{M_i}{{MAC}_i}-1$	Indicates the collective impact of PTEs on water resources.	[8]
Principal Component Analysis (PCA)	$z_{ij}=a_{i1}{x}_{1j}+a_{i2}{x}_{2j}+\cdots +a_{im}{x}_{mj}$	PCA is a multivariate statistical technique that extracts linear relations among a set of variables and converts them into a smaller number of principal components.	[9]
Factor Analysis (FA)	$z_{ji}=a_{f1}{f}_{1i}+a_{f2}{f}_{2i}+\cdots +a_{fm}{f}_{mi}+e_{fi}$	FA is a multivariate statistical technique that follows PCA, but reduces the contribution of less significant variables, simplifying the outcome.	[9]
Biotic Indices	Factors: - Species richness (number of species in each sample) - Total abundance (number of individuals in each sample)	Present a numeric figure regarding the health and diversity of a species, by assigning a weight based on a taxon’s tolerance of and sensitivity to pollutants.	[10]
Family Biotic Index (FBI)	$IBF=\frac{1}{N(ni\ast ti)}$	A tolerance value is assigned to each species.	[10]
Shannon Index	$H=-\sum P_{i}ln{P}_i$	Indicates the diversity of an aquatic ecosystem.	[11]
Biological Monitoring Working Party Index (BMWP)	-	A score is assigned to each microbial community and the final BMWP score is represented by the sum. The outcome is classified based on disturbance in ecology.	[10]
Trophic State Index (TSI)	$TSI=10(6-{log}_{2}SD)$	Defines and estimates the trophic status of a lake (oligotrophic, mesotrophic, and eutrophic) considering measures of biomass and production.	[7]
Bayesian Mixed Model	$X_{ij}={\displaystyle \sum _{K=1}^K}{P}_k\left(S_{jk}+C_{jk}\right)+{\epsilon }_{jk}$	Estimates the contribution of different pollutant sources to a specific mixture.	[12]
δ18O and δD Isotopic Ratio	$\delta D=8\ast {\delta }^{18}O+10$	Determines the dynamics and mixing of water without exchanges with geological formations. In general, the analysis of stable isotopes provides information about the origin and evolution of specific pollutants in water.	[12,13]

2.2. Soil Environment

PTE soil contamination can be evaluated using the most common geochemical indices, which are presented in Table 2.

The physicochemical properties of soil that affect the geochemical indices are as follows: pH, organic matter content, soil particle grain size (grain size in mm classified in sand > silt > clay) [14], electrical conductivity, and total organic carbon [15]. Other significant properties include phosphorus, potassium, and nitrogen content, the maximum possible accumulated volume of water as well as of the positive ions in the soil mass, and the moisture of the soil environment [16].

In some cases, soil characteristics affect microbial indicators, rendering them incapable of detecting PTE contamination. This is the case for soil biomass ratios that can complimentary assess soil quality, when PTE concentrations are low (when C_PTE increases → C_mic/N_mic reacts positively, but the microbial quotient C_mic/C_org and metabolic quotient react negatively) [14]. Low soil microbial mass is a sign of resistant microorganisms that have altered genotypes in order to adapt and thus can be utilized for remediation [17]. Earthworm Eisenia Fetida (E. fetida) is characterized as an ideal toxicity indicator by the Organization of Economic and Cooperation Development due to its reaction to various chemicals, resistance in lab environments, and omnipresence [16].

Poor soil quality is defined by the presence of PTEs, and the mortality and descending reproduction rate of E. fetida. Biomarkers such as anti-oxidant defensive systems and lysosomal membrane stability are used for the quantitative analysis and identification of PTEs collectively with physicochemical analysis [18]. A decrease in lysosomal membrane stability and an increase in metallothionein content indicate Cu, Mn, Zn, and Cd metal accumulation in soil environments [18]. The structural index of the nematode community is another PTE soil contamination assessment tool that is usually used in combination with biomarkers such as phytochelatin. For instance, when the plant Zeamays L. is exposed to Cu, Zn, and Cadmium (Cd), an increase in phytochelatin in the part of the plant where PTEs are accumulated takes place in a matter of minutes [19].

Table 2. Methods and geochemical indices for soil quality assessment.

Method/Index	Formula	Summary
Contamination Factor (CF)	$CF=\frac{C_{metal}}{C_{background}}$	The CF is a quotient of the PTE concentration of a sample (Cmetal) and the background PTE concentration (Cbackground).	[20]
Pollution Load Index (PLI)	$PLI=\sqrt[n]{{CF}_1\ast {CF}_2\ast {CF}_3\ast {CF}_n}$	The PLI combines CMs that result from PTE measures from multiple places and timings and evaluates the PTE pollution extent of the sites.	[20]
Enrichment Factor (EF)	$EF=\frac{{\left(\frac{C_s}{C_{ref}}\right)}_{sample}}{{\left(\frac{C_s}{C_{ref}}\right)}_{shale}}$	The EF reflects the concentration fluctuation of an element in soil and identifies if it is anthropogenic or a natural-source pollutant, and it results from the fraction where a sample’s PTE concentration is the numerator and the average shale PTE concentration is the denominator. Cref represents the concentration of a chosen element (such as Al and Fe) that normally exists in the soil and has only horizontal mobility or can be a soil property such as grain size and TOC, and it acts as a comparison factor.	[21]
Ecological Risk (Ei)	$E_i=T_i\ast {CF}_i$	Ei describes the level of toxicity of PTEs, taking into consideration the CF and the toxic response of the measured PTEs, with each element’s toxic response being significantly different, with As = 10, Cd = 30, Cr = 2, Cu = 5, Mn = 1, Ni = 5, Pb = 5, and Zn = 1.	[22]
Potential Ecological Risk (RI)	$RI={\displaystyle \sum _{i=1}^n}{E}_i$	The RI evaluates the level of toxicity of multiple PTEs and the biological community’s responsiveness to them as it combines the Ei of the PTEs of interest while taking into consideration the different toxicity levels of each one.	[22]
Geoaccumulation Index (Igeo)	$I_{geo}={log}_2\left(\frac{C_n}{1.5\ast B_n}\right)$	The Igeo estimates PTE concentrations and identifies the anthropogenic sourced pollutants by combining the sample’s PTE concentration and the PTEs’ geochemical average shale concentrations, setting 1.5 as the average shale matrix correlation factor that shows variations based on the anthropogenic acts of a chosen substance.	[23]
Nemerow Pollution Index (NIPI)	$NIPI=\sqrt{\frac{{\left(P_{iave}\right)}^2+{\left(P_{imax}\right)}^2}{2}}$	The NIPI describes the possibility of pollution, the risk amount of the indicated pollution and it is also able to measure the reach of PTE pollution to the surface soil level, taking into account the risks of all referenced PTEs.	[24]
Risk Assessment Code (RAC)	$RAC=\%F_1+\%F_2$	The RAC acts as a PTE tracer as it describes their solubility properties and other properties that are connected to their mobility in a soil environment.	[25]
Individual Contamination Factor (ICF)	$ICF=\frac{F_1+F_2+F_3+F_4}{F_5}$	The ΙCF assesses a PTE’s environmental pollution risk as it differentiates this depending on the PTE and also the soil type.	[25]
Degree of Contamination (Cdeg)	$C_{deg}={\displaystyle \sum _{i=1}^n}C{F}_i$	The Cdeg is a multimetal assessment tool of the level of contamination of soil samples.	[26]

Table 2. Methods and geochemical indices for soil quality assessment.

Method/Index	Formula	Summary
Contamination Factor (CF)	$CF=\frac{C_{metal}}{C_{background}}$	The CF is a quotient of the PTE concentration of a sample (Cmetal) and the background PTE concentration (Cbackground).	[20]
Pollution Load Index (PLI)	$PLI=\sqrt[n]{{CF}_1\ast {CF}_2\ast {CF}_3\ast {CF}_n}$	The PLI combines CMs that result from PTE measures from multiple places and timings and evaluates the PTE pollution extent of the sites.	[20]
Enrichment Factor (EF)	$EF=\frac{{\left(\frac{C_s}{C_{ref}}\right)}_{sample}}{{\left(\frac{C_s}{C_{ref}}\right)}_{shale}}$	The EF reflects the concentration fluctuation of an element in soil and identifies if it is anthropogenic or a natural-source pollutant, and it results from the fraction where a sample’s PTE concentration is the numerator and the average shale PTE concentration is the denominator. Cref represents the concentration of a chosen element (such as Al and Fe) that normally exists in the soil and has only horizontal mobility or can be a soil property such as grain size and TOC, and it acts as a comparison factor.	[21]
Ecological Risk (Ei)	$E_i=T_i\ast {CF}_i$	Ei describes the level of toxicity of PTEs, taking into consideration the CF and the toxic response of the measured PTEs, with each element’s toxic response being significantly different, with As = 10, Cd = 30, Cr = 2, Cu = 5, Mn = 1, Ni = 5, Pb = 5, and Zn = 1.	[22]
Potential Ecological Risk (RI)	$RI={\displaystyle \sum _{i=1}^n}{E}_i$	The RI evaluates the level of toxicity of multiple PTEs and the biological community’s responsiveness to them as it combines the Ei of the PTEs of interest while taking into consideration the different toxicity levels of each one.	[22]
Geoaccumulation Index (Igeo)	$I_{geo}={log}_2\left(\frac{C_n}{1.5\ast B_n}\right)$	The Igeo estimates PTE concentrations and identifies the anthropogenic sourced pollutants by combining the sample’s PTE concentration and the PTEs’ geochemical average shale concentrations, setting 1.5 as the average shale matrix correlation factor that shows variations based on the anthropogenic acts of a chosen substance.	[23]
Nemerow Pollution Index (NIPI)	$NIPI=\sqrt{\frac{{\left(P_{iave}\right)}^2+{\left(P_{imax}\right)}^2}{2}}$	The NIPI describes the possibility of pollution, the risk amount of the indicated pollution and it is also able to measure the reach of PTE pollution to the surface soil level, taking into account the risks of all referenced PTEs.	[24]
Risk Assessment Code (RAC)	$RAC=\%F_1+\%F_2$	The RAC acts as a PTE tracer as it describes their solubility properties and other properties that are connected to their mobility in a soil environment.	[25]
Individual Contamination Factor (ICF)	$ICF=\frac{F_1+F_2+F_3+F_4}{F_5}$	The ΙCF assesses a PTE’s environmental pollution risk as it differentiates this depending on the PTE and also the soil type.	[25]
Degree of Contamination (Cdeg)	$C_{deg}={\displaystyle \sum _{i=1}^n}C{F}_i$	The Cdeg is a multimetal assessment tool of the level of contamination of soil samples.	[26]

3. Results and Discussion

3.1. Water Resources

Methods used for water quality assessment can be categorized into three groups: chemical indices, statistical methods, and biological indices.

Chemical indices (HPI, HEI, and C_d) estimate the overall degree of contamination based on a custom scale whereas statistical Methods (the Bayesian mixed model, FA, PCA, δ¹⁸O, and the δD isotopic ratio) provide valuable information about the source of contaminants and identify relations between parameters. Biological indices (biotic indices, the TSI, the Shannon index, the BMWP, and the FBI) examine the impact of pollution in an ecosystem through organisms.

3.2. Soil Environment

Similarly to those used for water quality assessments, the methods used for soil quality assessment can be categorized into three groups: chemical (geochemical) indices, physiochemical analysis tools, and biochemical Indicators with their suitable biomarkers.

Geochemical indices (I_geo, EF, CF, PLI, RI, NIPI, RAC, ICF, E_i, and C_deg) have broader utility in soil compared to water, as they are trustworthy multivariable assessment methods with consistent results for contaminants’ source, quantity, range, toxicity, fluctuation, mobility, and biological response. Biological indicators (Eisenia Fetida; Zeamays L.) and biomarkers (anti-oxidant defensive systems, lysosomal membrane stability, metallothionein content, the structural index of a nematode community, and phytochelatin), add to the mobility and biological response the results of the Geochemical indices, but are more complicated to use as they are not versatile due to their specific use and sensitivity to environment changes. Finally, physiochemical analysis (of soil particle grain size organic matter content, pH, total organic carbon, potassium content, phosphorus content, nitrogen content, electrical conductivity, and soil moisture) acts as the primary contamination indicator and specifies the conditions of soil in order to select the most suitable bioindicator for monitoring.

To support the utility of the methods, case studies are provided in Table 3 and Table 4.

Table 3. Case studies regarding methods and indices mentioned for the quality assessment of water in mining regions.

Method/Index	Assessment	Process	Result	Mining Site
HPI, PCA and Isotopic Ratio	Impact of acid mine drainage on the quality of water, with 30 samples from 5 sites, including AMD-polluted and AMD-unpolluted water, from July to December 2019.	The HPI was used to determine overall quality whereas PCA was applied to 21 PTEs, 3 anions, and 3 quality parameters (pH, Eh, and TDS).	PCA results showed that the concentration of soluble metals in the area is related to SO42−, caused by the oxidation of sulfur-containing minerals. HPI results showed that in AMD-polluted water, the maximum value was 133,380.7, whereas the isotopic composition indicated that the pyrite mine interacts with groundwater, confirming the high HPI values.	South China (pyrite mine)	[13]
HPI	Groundwater quality regarding pollution from PTEs using 20 samples during May, August, and December 2011.	Fe, Mn, Zn, and Cu: smaller Wi Cd, Cr, and Pd: bigger Wi.	The calculated HPI value was 6.8860, which is within the acceptable limit (<100).	Dhanbad, India (coal mine)	[27]
Biotic Indices, BMWP, and FBI	Influence of mining activities on the aquatic ecosystem, studying macroinvertebrates from 12 sampling sites in October 2011.	Using the BMWP and FBI, the rivers were classified based on ecology disturbances on a scale from strongly disturbed to undisturbed, with the latter being the site with the highest abundance and richness.	Results revealed severe mining pollution, highlighting the need for the protection of water resources and the implementation of a biomonitoring program documenting human activities. Macroinvertebrates were proven useful for the development of biotic indices.	Northen Chile (mining activities and acid–sulfate-type hydrothermal systems)	[10]
Shannon Index	Investigation of microbial community structure, diversity, and activity in AMD-polluted water resources from 3 sites with different contamination levels.	Diversity was mirrored in all 3 sample sites depending on the AMD contamination level (uncontaminated water, moderately contaminated water, and heavily contaminated water).	Results showed that AMD pollution changed the bacterial community structure, and decreased microbial activity and diversity, but enhanced specific bacterial populations.	Guryong Mine, South Korea (copper mine)	[11]

Table 4. Case studies regarding methods and indices mentioned for the quality assessment of soil in mining regions.

Method/Index	Assessment	Purpose	Mining Site
Igeo	Anthropogenic-source pollutants were the main PTE accumulation factor in mining sites, taking up 65.4% of possible sources with Cd and Zn from smelting sources, Pb from transportation and mining activities, As and Cu from PTE flow mobility, and the rest, Cr, Ni, and Sb, being naturally sources.	Source and quantity determination	China (Lead–Zinc)	[28]
CF, PLI	CF values calculated the level of contamination in a copper mine area showing the difference between direct soil (Cu > As > Zn > Pb > Fe > Cr > Ni) and tailings of the same area (As > Cu > Zn > Fe > Pb > Ni > Cr).	Quantity determination	Algeria (Copper)	[29]
EF	Compared to non-exploited sites in the area of Breccia Pipe Uranium deposits, U was the most enriched of all other elements (S, As, Mo, and Cu).	Fluctuation and source determination	USA (Uranium)	[21]
Ei, NIPI	Ci > Cs → PTEs exceeded the standard. Ci > Cb → PTEs in soil have positive accumulation trends. Ci < Cs and Ci < Cb → PTEs do not exceed the standard and have negative accumulative trends.	Toxicity and range determination	China (Molybdeneum)	[30]
RI	Cr, Cu, Co, As, Ni, and Zn were way over the standard values after being compared to the median values, and pointed out specific areas with PTE accumulation.	Toxicity and biological response determination	Egypt (Iron)	[31]
Cdeg	The Cdeg values are differentiated depending on the background value, which is based on the average shale and the crustal average, and the results must be contrasted to the World Health Organism’s Soil Health Guidelines and the Dutch List.	Quantity determination	Algeria (Copper)	[29]
RAC and ICF	RAC used in lead–zinc mine site classified the risk levels as high/very high for Cu, Pb, Cd, and Zn, and low/medium for Cr, whilst with ICF, PTE risk levels were low despite the high concentration of Cd.	Mobility and toxicity determination	Vietnam (Lead–Zinc)	[25]

4. Conclusions

In conclusion, all aforementioned methods are valuable for environmental evaluation in a region impacted by PTEs from mining activities. However, some are distinguished based on their representative results and broad applications in mining areas.

Regarding water quality assessments, the combination of a chemical index and a statistical method is adequate to detect an early-stage contamination that has yet to severely impact the environment. Concerning the impact on the ecosystem, the Shannon index depicts diversity, thus indicating the loss of sensitive microorganisms due to the presence of PTEs, while biotic indices reveal information about a species’ ability to colonize and reproduce in the presence of PTEs.

Regarding soil quality assessments, the geoaccumulation index (I_geo) is a commonly used geochemical index for the source identification and quantity assessment of contaminant sources, due to its versatility and multivariability. As for bioindicators, earthworm Eisenia Fetida is frequently used for the toxicity characterization of a mining site’s contaminants. Finally, grain size, a physicochemical analysis property, is integrated in multiple mulitivariable formulas for soil quality assessment.