1. Introduction
The large coal deposits scattered across Pakistan are known to have about 185,175 million tons [
1]. These coal reserves are of different ranks, among which, 97% are of lignite rank [
2]. The types of coal from different regions of Pakistan vary from low rank lignite coal to high rank volatile bituminous coal [
3]. Thus, looking at the vast coal resources, policy makers in Pakistan have realized the importance of coal by explaining the government’s plans to meet about 20% of its energy demand in the near future. Coal mines play a very significant role in amplifying Pakistan’s economic wealth. There are a large number of coalfields in Balochistan. However, the main coalfields are Deragi, Sor-Range, Chamalang, Duki, Harnai, Khost, Sharagh, Mach, and Ziarat. The present research covered coal mine fields in Chamalang, Duki, Harnai, Sharagh, and Khost: the four districts of the province. The total coal reserves of the province reach to about 217 million tons. The coal of Balochistan is found to be classified into two types according to its ranks—i.e., sub-bituminous to bituminous—with a considerable heating value that ranges from 9637 to 15,499 Btu/lb.
Coal mining areas are currently being overexploited due to coal excavation; the improper handling of waste disposal results in groundwater contamination [
4]. The coal seam that is being excavated is generally lower than the level of the water table [
5]. When exposed to water or air, these mineral rocks produce acid that continuously leach the sulphide. This causes the contamination and acidification of the underground water resources and is undoubtedly considered as one of the most significant water quality problems related to coal mining [
6]. In the semi-arid regions of Balochistan, groundwater is the only source of water. The decline in the water quality and quantity and the increasing demand due to overpopulation has a profound effect on the existing freshwater resource, resulting in water shortage in the major part of the country [
7,
8]. In a certain area of the Balochistan and Sindh province of Pakistan, many people already have no means to access the safe drinking water and are forced to use brackish water for daily consumption [
9]. In Balochistan, the water table is annually dropping by 3.5 m and, soon, this source will be completely exhausted [
10,
11].
Contamination due to heavy metals in groundwater occurs due to the natural weathering process of mineral rocks that bear minerals. Anthropogenic activities, such as coal mining, mineral excavation, industrial effluent, and fertilizers, significantly contribute to the heavy metal pollution of groundwater [
4]. In the current study, heavy metal analysis data were integrated with geographic data to model the spatial distribution of heavy metal in the groundwater. The global information system is an effective tool for loading a huge volume of data to correlate and use further for spatial analysis [
11]. GIS technology has been recommended and proposed by many scientists all over the world [
12,
13,
14,
15,
16,
17] to determine the spatial distribution of heavy metal and identify the source of pollution. The present research aims to understand the quality of groundwater based on heavy metal concentration and is depicted by means of an interpolation technique [
18].
In the mid-twentieth century (1965), Horton initially started the categorization of water quality [
19]. Furthermore, in 1970, the Brown group introduced a water quality index (WQI) similar to Horton’s index. However, various modifications have been considered by scientists and experts for the water quality index (WQI) concept [
20]. Basically, a water quality index (WQI) is a significant tool that is either developed for irrigation water or for drinking water. It is a water rating scale based on a single number-like grade that is derived through the testing of different parameters of water, which depicts the overall water quality [
21]. The major advantages of these indices are to provide significant information of water quality to policy makers, the public, and concerned authorities in a very precise and effective manner [
22]. Similarly, a statistical approach—i.e., principle component analysis (PCA)—is widely applied and used by many scientists all over the world [
23,
24,
25,
26]. As such, it offers a statistical approach for the interpretation of large and complex water quality data, the ease of understanding the ecological status, and the factors involved in demeriting the overall water system [
27]. In the current study, the level of heavy metal contamination in the groundwater of the five selected coal mining fields scattered across four districts of Balochistan was assessed by a principal component analysis (PCA). Throughout the world, contamination due to coal mining activities is a major concern. Many studies have been conducted globally to significantly explain the consequences of large-scale coal excavation. The current research was conducted in a coal mining area of Balochistan that has not been explored and investigated before to check the current state of water for drinking purposes.
2. Materials and Methods
2.1. Study Area
Pakistan’s largest province, Balochistan, covers an area of 347,190 km
2 and is the driest province among all provinces. It is geographically bounded by 24°, 53′ and 32°, 06′ North latitudes and 60°, 52′ and 70°, 17 East longitudes [
28]. The terrain of the district consists of East–West aligned mountains ranging in ground elevation from 924 to 3136 meters above the mean sea level (MSL). The climate of the province is semi-arid continental and varies dramatically from very cold winters to hot summers [
17]. It has diversified rainfall, recording between 200 and 350 mm per year. The temperature varies greatly with the location and elevation from sea level, from between −3 to 38 Celsius, but the daily maximum, mean, and minimum temperatures recorded are 27, 31, and 16 Celsius, respectively [
29]. Balochistan is present in the Triassic strata, which are characterized by different tectonic metallic and sedimentary basins, such as Sulaiman, Indus suture, Kirthar, and Balochistan basin. The rocks of the study site are mainly composed of igneous, ultra-mafic, and sedimentary types [
30]. Balochistan is the custodian of a large reservoir of natural gas and barite. Besides these resources, large deposits of silica, magnesite, and sulphur are also present. The study area hosts large deposits of coal of different types—mainly bituminous to sub-bituminous [
3].
The main coalfields of Balochistan are Deragi, Sor-Range, Chamalang, Duki, Harnai, Khost, Sharagh, Mach, and Ziarat (
Figure 1). The thickness of the coal seams ranges from 0.3 to 2.3 meters. Among these coal mining fields, five coal mining locations were selected, which are scattered across four districts of the province: i.e., Chamalang (Dist. Loralai), Duki (Dist. Duki), Harnai (Dist. Harnai), Sharagh (Dist. Ziarat), and Khost (Dist. Ziarat).
2.2. Water Sampling and Analysis
Water sampling was carried out in two seasons (2017–2018). The first sampling was done during the summer season in July, 2017, and the second was during winter in January, 2018. A total of 100 groundwater samples were collected, with fifty (50) samples in one season from all the possible water resources. Duplicates of 10 water samples were collected from each coal field. In the coal mining fields, the surface water resources were limited and the only sources of drinking water were karazes, springs, dug and Persian wells, and freshwater aquifers. During field sampling, some samples were collected directly from the bore holes and some were collected from the water tanks consumed by the mine workers. The depth of the groundwater throughout the study ranged from 250 to 300 ft deep.
Sedimentary rocks are extensively exposed in all the hydrologic basins of the region and mainly consist of calcareous and arenaceous. The Cenozoic and Mesozoic rocks are mainly composed of limestone, sandstone, and shale, which are widely exposed in all the river basins. This formation and distribution of sedimentary rocks represent different hydrogeological characteristics at different depths and levels. In all the hydrologic basins of Balochistan Province, such types of formations are widely exposed [
31].
For the current research, physicochemical parameters (i.e., pH, total dissolved solid (TDS), and electrical conductivity (EC)), anions (i.e., Cl- and HCO3-), various heavy metals (i.e., Cd, Cu, Co, Cr, Hg, Zn, Pb, Ni, Fe, and Mn), and several light metals (i.e., Ca2+ and Mg2+) were tested for each groundwater sample. Analyses were performed by following the standard protocols of American Public Health Association (APHA, 1992, 1998). The pH, EC, and TDS were measured with a multi-meter. Na+ and K+ were analyzed by using a flame photometer. Cl- and HCO3- were measured by following the titration method (APHA, standard protocol, 1992). A flame atomic absorption spectrophotometer (220 spectra AA, Varian) was used to detect mercury (Hg), whereas the remaining heavy metals were analyzed via an atomic absorption spectrophotometer (AA-7000 Shimadzu).
2.3. Spatial Distribution of Heavy Metals
During the field sampling of both seasons, each sampling point was located by means of a handheld portable GPS device. Excel sheets were prepared with sample coordinates and analyzed data. Prepared excel sheets were incorporated into ArcGIS 10.2 system software, and a raster interpolation technique, known as inverse distance weighted (IDW), was used to delineate the spatial distribution of water pollutants: i.e., heavy and light metals.
2.4. WQI
More than 50% of the world’s population depends upon groundwater as a source of drinking water [
32]. The chemistry of groundwater is used as a tool to investigate the status of water for drinking or for irrigation purposes [
18]. For the current study, the water quality index was computed for a total of one hundred (100) groundwater samples taken from the selected coal mining fields across the four districts during two seasons (i.e., summer and winter). The WQI was calculated in order to assess the suitability of groundwater for drinking purposes around the coal mines. The grading system followed by Ketata-Rokbani [
33] was used to classify drinking groundwater, as shown in
Table 1.
For computing the WQI, relative weight (Wi) was assigned for the selected parameters based on their significance and adverse effects on human health. The WHO permissible standards (2011) and relative weight (Wi) for each variable is shown in
Table 2. Each tested parameter in the current research was assigned a weight (
wi) from 1 to 5, as represented in
Table 2 [
22]. Five numbers represented the minimum (1) and maximum (5) weight of the selected pollutant due to their importance and ability to deteriorate the status of water. The key variables considered in the current study were pH, EC, TDS, HCO
3-, Na
+, Ca
2+, Mg
2+, K
+, Cl
-, Cd, Cr, Pb, Cu, Mn, Fe, Zn, Ni, and Hg.
Relative weight (Wi) was calculated as:
where Wi is the relative weight, wi is the weight assigned to each of the individual variables, and
n is the number of variables.
The second step involved the development of the rating scale—i.e., (qi)—by dividing the recorded concentration of the individual parameter (Ci) by the WHO standard (Si); the obtained value is then multiplied by 100.
where Ci is the recorded concentration of the individual parameter and Si is the WHO standard for each parameter.
In the third and final step, SI was calculated for each water quality variable by multiplying Wi with qi. The sum of SI was equal to the water quality index (WQI).
SI was calculated for each water quality variable and the summation of SI was equal to the water quality index (WQI), as formulated in Equation (4).
2.5. Principal Component Analysis
The principal component analysis is a powerful method that attempts to elucidate the variance of a large data set with inter-correlated variables [
34]. It determines the connotation between different parameters, resulting in the summarization of data set dimensionality. From the original parameter’s covariance matrix, the PCA uses the eigen vectors and eigen scores. Basically, eigen values of the principal components are the degree of their related variance; the contribution of original variables in the principal components is specified by loadings and the individual modified observations are called scores [
34]. In the current study, a PCA was used to find the pattern of variance using XL STAT (2019).
4. Discussion
Groundwater quality is considered as a function of natural—as well as anthropogenic—activities [
49]. Documentation of groundwater quality in a region where it is the only source of drinking water is of utmost importance. The results from the current study suggested that the deterioration of drinking water is influenced by natural—as well anthropogenic—activities around the coal mines of Balochistan. Coal resources are, economically, the cheapest source of energy in the region, and this has led to the overexploitation of coal resources. The overall results of the current study were in line with a similar study reported in the Thar coalfield of Pakistan [
50]. The slight increase of pH during the summer season in the groundwater might be due to the calcareous nature of the underlaying aquifers of the study area. This can be attributed to the discharge of a large quantity of electrolytes and minerals from coal mining waste and the interaction of water with the bed rocks [
51]. The higher value of EC in the underground water samples might be due to the dissolution of minerals and interaction of water with the bed rocks. Water EC provides an important indication of the amount of nutrients dissolved in water solution. However, a higher EC level can lead to salt toxicity. The higher concentration of TDS in the water samples was mainly because of the dissolved inorganic salts and the small amount of organic substances. TDS levels in the groundwater can also be a measure of salinity level. Lowering the TDS concentration will lower the salinity, and a higher conc. of TDS (>1000) could indicate a very high salinity level [
52]. However, the measured TDS values showed a reduced water quality, with significant health issues for mineworkers.
This varied distribution of HCO
3- and Cl
- in groundwater of the study area might be due to the dissolution of minerals from the sedimentary rocks and the weathering of calcite in the parental mineral rock most commonly found in local geology [
53]. The results of the current study for HCO
3- and Cl
- are in line with other similar studies conducted in other parts of the country [
54]. High HCO
3- levels in water can lead to an increase in the pH level. Elevated levels of Ca
2+ and Mg
2+ in some of the sampled groundwater may be due to the cationic exchange with sodium. Calcium is naturally present in drinking water as calcium carbonate or calcium chloride. The results of the current study are in line with other similar studies conducted in other parts of the country [
54,
55]. While the source of magnesium is dolomite and magnetite rocks, metals are released and distributed in the aquatic ecosystem from different natural sources (e.g., volcanic activity, ore deposits, bed rocks erosion, and weathering) and anthropogenic sources (e.g., mining, agricultural activities, smelting, industrial influx, etc.) [
56]. This can be attributed to the release of acid mine draining directly into the water resource. The acid drainage from coal mines or coal disposal piles contain a significant amount of metals [
57]. The presences of these elements are because of the leaching of minerals, such as silicates and sulfides. These minerals are directly associated with layers of coal body and parent rocks—i.e., siltstones, shales, limestones, and sandstones [
58]. Similar research on quantifying these metals and apportioning the source of their distribution in the groundwater can be seen in various parts of the world [
59,
60,
61]. The elevated concentrations of the majority of the selected parameters during the winter season can be attributed to the high rainfall that triggers the phenomenon of leaching in higher rates than before. The previous studies conducted globally indicated that untreated mine waste is the main source of heavy metals and can leach the underground water resource while the surface water is polluted by the surface runoff during the wet season [
62,
63,
64,
65].
From the analysis, many principal components were generated. According to the results, the maximum (4) components were responsible for contributing to about 66.5% of the total variance. The very first component of PCA revealed that it was responsible for about 25.9% variance, with the eigenvalue of 5.18. The most important parameters comprised by the first component that governed and controlled the whole groundwater chemistry were pH (0.78), Mg (–0.73), K (–0.71), Cr (–0.64), Ni (0.83), and Zn (–0.79). The second component of PCA was comprised of about 18.8% variance with an eigenvalue of 3.8. Strong positive and negative loadings for EC (0.60), Na (0.78), and Ca (–0.77) and Hg (–0.61) were accounted for by factor 2, respectively. The third component of PCA was comprised of about 11.9% variance with an eigenvalue of 2.37. Unlike other components, the third component of PCA was only dominated by positive loadings: i.e., carbonates (0.62) and Cu (0.62). Similarly, the fourth component of PCA was comprised of about 10.1% with an eigenvalue of 2.01, having one positive loading for Cd (0.69) and one negative loading for Fe (–0.61).
In the current study, the correlation matrix showed positive as well as slightly negative correlations among various heavy and light metals. As clearly shown in
Table 7, micronutrients, such as Cd, Cr, Co, and Cu, had a very strong positive correlation among themselves, and a positive association towards Hg and Zn was also observed [
63]. This positive association among these heavy and light metals was because of the same origin or source [
22]. These heavy metals abundantly originated from solid waste, such as lead batteries, steel scarps, cans, and tins [
40]. Coal mining sites can be considered as the point source for the release of these metals into the groundwater system. During coal mining, heavy machinery for excavation is used, so it might be suggested that coal mines and coal mining activities are a source of release for these metals and, thus, deteriorate the water system. In the study area, waste from the underground coal mines was dumped just outside the mines contaminating the soil surface. Interaction of this waste with rainwater can lead to the leaching of these heavy metals, resulting in the accumulation of the majority of pollutants in groundwater, which, in turn, can pollute the whole water system. Similarly, trends of correlation between heavy metals that cause pollution in the water resources have also been spotted in various other studies [
66,
67,
68].
5. Conclusions
A successful evaluation for groundwater quality in the five selected coal mining sites scattered across the four districts of Balochistan was accomplished through the analysis of physicochemical parameters in two seasons. An analysis of these parameters indicated that many parameters were beyond their permissible limits according to the WHO standards (2011) except for a few variables. Results computed from the WQI were high for all the selected sites, which indicated the deteriorated status of drinking water quality around coal mines. In the current study, a correlation between physicochemical variables and heavy metals revealed that during both the seasons, natural as well as manmade sources (i.e., coal mining activities) were the main source of pollution of these metals in the groundwater reservoirs. Therefore, the results suggested that the deterioration of drinking water is influenced by natural as well anthropogenic activities around the coal mines of Balochistan. Looking at the economic value of coal, these coal mines are functional almost 24 hours a day, so the continuous activity can lead to even more deterioration of the water system. Different scientifically proven methods should be adopted prior to the dumping of mine waste. This research can provide baseline data for concerned authorities, as well as the public, for contaminant prevention, remediation, planning management strategies, and for future environmental monitoring.