Abstract
More than 60% of the population of Pakistan has no access to safe drinking water. Industrial zones near populated areas make conditions more severe due to continuous contamination. The aim of this study was to use statistical tools for correlation and source identification and health risk assessment of contamination due to Sundar Industrial Estate (SIE), Lahore, Pakistan. Drinking and wastewater samples were collected from SIE and analyzed for physical, chemical, microbial, and heavy metals analysis. Results showed that heavy metals and microbial contamination were beyond the National Drinking Water Quality Standards of Pakistan while high values of chemical oxygen demand (COD) and biochemical oxygen demand (BOD) wastewater were responsible for contamination of drinking water through seepage. There was a medium to strong correlation among parameters of all samples as indicated by Pearson correlation and analysis of variance. Principal component analysis and cluster analysis indicated sources of contamination, i.e., refuse leachate and untreated effluent discharges as main source of pollutants for drinking water. Health risk assessment showed a high intake of heavy metals through drinking water. Hazard quotient and hazard index indicated high probability of non-carcinogenic risk while cancer risk assessment suggested that out of every 100 of the population 93 people may suffer carcinogenic effects.
HIGHLIGHTS
Samples showed high bacterial and heavy metals contamination due to untreated effluent.
Statistical modeling showed strong correlation and seepage as the main source of pollution.
The hazard quotient and hazard index (for non-carcinogenic risk) values are >1.
Risk assessment showed 93 people out of 100 of population may suffer from cancer.
Graphical Abstract
INTRODUCTION
Water is an essential element for life. A small proportion (0.01%) of fresh water is available for human use (Azizullah et al. 2011). Unfortunately, even this small proportion is continuously contaminated by various anthropogenic sources including urbanization/industrialization (Rehman et al. 2008; Valipour 2016). Like other developing countries, Pakistan is also facing a problem of contamination in drinking water due to anthropogenic sources. A recent study showed drinking water in Pakistan (4,218 samples) was contaminated by bacteria (69%), chemicals (19%), and heavy metals (24%) (Saiqa et al. 2016). Drinking water can be contaminated by natural or anthropogenic sources. Various studies have indicated that natural sources like the flood (in Pakistan) of 2010 and earthquakes of 2005 and 2008 contaminated the groundwater with microbes (pathogens) (Baig et al. 2012a, 2012b; Khan et al. 2014; Saeed & Attaullah 2014). The main sources of anthropogenic activities are industries and untreated wastewater discharge in rivers and canals (Azizullah et al. 2011). Such anthropogenic activities can be divided into point sources and non-point (diffused) sources (Rehman et al. 2008; Azizullah et al. 2011; Raza et al. 2017). Industrial and domestic effluents are categorized as point sources while runoff of agriculture and hard surfaces are non-point sources (Raza et al. 2017; Valipour 2017).
In Pakistan, out of 6,634 registered industries, 1,228 were considered highly polluted point sources for the environment (Raza et al. 2017). These industries are named as Small Industries-II, Gujranwala City; Industrial Estate Peshawar, Peshawar City; Industrial Estate Hattar; Quid-E-Azam Industrial Estate, Lahore City; Sundar Industrial Estate, Lahore City, etc. Like every developing city, Lahore is also facing problems of safe drinking water due to these point sources. People are drinking this polluted water and facing severe health issues leading to cancer. This study aimed to check the quality and drinking water and pollutant correlation along with health risk assessment due to drinking contaminated water. Sundar Industrial Estate of Lahore, Pakistan was selected, and sampling of drinking water and wastewater was performed. Statistical tools like descriptive statistics, ANOVA, PCA, CA, etc. were used to calculate correlation and identify the sources of pollutants present in the study area. Health risk assessment as hazard quotient (HQ) and cancer risk assessment (CR) was also determined.
MATERIALS AND METHODS
Sundar Industrial Estate (SIE) is in Lahore City, with an area of 1,800 acres (Figure 1). SIE was established in 2007, and currently, more than 550 industrial units are working. The main industries are given in Table 1. The Environmental Impact Assessment (EIA) report of SIE (PIEDMC 2006) indicated a total of 140,600 m3/day wastewater will be produced which needs installation of a wastewater treatment plant with a capacity of 150,000 m3/day (PIEDMC 2006). Unfortunately, this treatment facility was never built. This abundant untreated wastewater contaminates the drinking water of SIE and has resulted in poor health conditions for the population living near SIE.
List of industries which are contributing various pollutants in wastewater and groundwater of SIE
Sr. . | Type of industry . | No. . | Pollutant . |
---|---|---|---|
1. | Aluminum products | 6 | Metals |
2. | Auto parts | 8 | Metals |
3. | Beverage | 4 | Organics |
4. | Chemical manufacturing | 6 | Organics and metals |
5. | Cold storage | 2 | – |
6. | Drugs and pharmaceuticals | 4 | Organics and metals |
7. | Electric goods | 6 | Organics and metals |
8. | Fiber glass industry | 4 | – |
9. | Flour mills | 4 | Organics |
10. | Food products | 2 | Organics |
11. | Glass and glass products | 2 | – |
12. | Knitted textile | 2 | Dyes and organics |
13. | Leather footwears | 2 | Metals, acids |
14. | Light engineering | 12 | Organics and metals |
15. | Marble industry | 2 | Solids |
16. | Packages | 6 | – |
17. | Paints and varnishes | 6 | Organics |
18. | Paper and paper board | 2 | Lignin |
19. | Plastic products | 10 | Solids |
20. | Readymade garments | 14 | – |
21. | Textile processing | 8 | Organics |
Sr. . | Type of industry . | No. . | Pollutant . |
---|---|---|---|
1. | Aluminum products | 6 | Metals |
2. | Auto parts | 8 | Metals |
3. | Beverage | 4 | Organics |
4. | Chemical manufacturing | 6 | Organics and metals |
5. | Cold storage | 2 | – |
6. | Drugs and pharmaceuticals | 4 | Organics and metals |
7. | Electric goods | 6 | Organics and metals |
8. | Fiber glass industry | 4 | – |
9. | Flour mills | 4 | Organics |
10. | Food products | 2 | Organics |
11. | Glass and glass products | 2 | – |
12. | Knitted textile | 2 | Dyes and organics |
13. | Leather footwears | 2 | Metals, acids |
14. | Light engineering | 12 | Organics and metals |
15. | Marble industry | 2 | Solids |
16. | Packages | 6 | – |
17. | Paints and varnishes | 6 | Organics |
18. | Paper and paper board | 2 | Lignin |
19. | Plastic products | 10 | Solids |
20. | Readymade garments | 14 | – |
21. | Textile processing | 8 | Organics |
Sampling and analysis
The wastewater samples were collected from the main drain of SIE (Figure 1) and drinking water samples were collected from taps (home) near the wastewater sample locations. Four locations were selected for wastewater and drinking water sampling. Five samples from each wastewater and drinking water location were collected at an interval of 2 days. Water sampler (WS700) was used for the collection of composite sampling (APHA 2005). The sampler was adjusted to take 1 L of wastewater sample after every 30 min. A total of 20 L wastewater samples was collected from each location and was repeated after every 2 days' interval. For drinking water sampling, the tap water was collected. The water taps were left running for 10–15 min and, after that, a 1 L sample was collected after every 30 min. The same was repeated at every drinking water location with a 2-day interval of time. Samples were collected in sterilized dark glass bottles to avoid any degradation and bacterial contamination. Afterwards collection samples were transferred to the laboratory for analysis (APHA 2005). Samples were analyzed as per instructions given by Standard methods for examination of water and wastewater (APHA 2005). Blank samples were run after every ten samples and spiking of metals was performed as a quality check on an atomic absorption spectrometer (Analyst 800, Perkin Elmer). Samples were run in triplicate and average values were used for statistical analysis. Samples were also sent to the Institute of Chemistry, Punjab University and Pakistan Council for Scientific and Industrial (PCSIR) Laboratories Lahore to reduce the analysis error. An overall ±2.62% error was found.
RESULTS AND DISCUSSION
Drinking and wastewater samples were analyzed, and mean values were used for different statistical tools, i.e., descriptive analysis, Pearson's correlation coefficient, analysis of variance (ANOVA), principal component analysis (PCA), and cluster analysis (CA). These statistical tools were applied for correlation and source of contamination.
Statistical modeling
Descriptive analysis
Descriptive statistics has been computed (Chakrabarty & Sarma 2011). The results of descriptive analysis of all drinking and wastewater samples are shown in Table 2. The mean values of drinking water were also compared with National Drinking Water Quality Standards of Pakistan (NDWQS). The mean value drinking water samples, i.e., pH, turbidity, Ni, Zn, and Cd were within the NDWQS. Bacterial contamination was indicated in drinking water (Table 2), which suggested contamination of drinking water with wastewater. Heavy metals, i.e., Cr, Pb, chlorides, and TDS were beyond the guideline values (Table 2). High concentration of Zn and chloride may be due to fertilizer runoff (Delin & Landon 2002; Valipour 2016). Variations in standard deviation indicated that samples were more representative of the overall study area. Most values of skewness were high, which indicated non-symmetrical distribution of samples (Table 2).
Descriptive statistics of parameters analyzed for drinking water and wastewater from Sundar Industrial Estate (SIE), Lahore, Pakistan
Parameter . | Min . | Max . | Mean . | Std. deviation . | Skewness . | Guideline values . |
---|---|---|---|---|---|---|
Drinking water | ||||||
pH | 7.46 | 8.1 | 7.715 | 0.286 | 1.0 | 6.5–8.5 |
Temp (°C) | 22 | 25 | 23 | 1.258 | −1.129 | – |
Turbidity (NTU) | 2.25 | 5.12 | 3.49 | 1.19 | 0.936 | <5 |
Coliform (MPN/100 mL) | 32 | 1,602 | 1,209.5 | 785 | −2.0 | Nil |
Fecal coliform (MPN/100 mL) | 2 | 123 | 47 | 52.896 | 1.510 | Nil |
Total hardness (mg/L CaCO3) | 1,480 | 1,600 | 1,520 | 56.569 | 1.414 | <500 |
Ca+2 hardness (mg/L CaCO3) | 1,124.8 | 1,337.6 | 1,216.2 | 96.475 | 0.61 | – |
Mg+2 hardness (mg/L CaCO3) | 182.4 | 355.2 | 303.8 | 82.013 | −1.850 | – |
Alkalinity (mg/L CaCO3) | 50 | 662.5 | 310 | 256.035 | 1.031 | – |
TS (mg/L) | 1,708 | 2,907 | 2,490 | 544.287 | −1.544 | – |
TDS (mg/L) | 1,024 | 1,744 | 1,492 | 326 | −1.53 | 1,000 |
TSeS (mg/L) | 689 | 1,263 | 987.75 | 234.73 | −0.299 | – |
Chlorides (mg/L) | 225 | 512 | 349 | 119.563 | 0.936 | <250 |
Nickel (ppm) | 0.012 | 0.024 | 0.019 | 0.005 | −1.056 | <0.02 |
Zinc (ppm) | 0.013 | 0.280 | 0.088 | 0.128 | 1.968 | 5 |
Cadmium (ppm) | 0.001 | 0.003 | 0.002 | 0.000 | −0.060 | 0.01 |
Chromium (ppm) | 2.117 | 3.981 | 3.106 | 0.944 | −0.110 | 0.05 |
Lead (ppm) | 0.645 | 1.804 | 1.206 | 0.534 | 0.119 | 0.05 |
Wastewater | ||||||
pH | 6.66 | 8.89 | 8.01 | 1.0 | −1.013 | 6–9 |
Temp (°C) | 12 | 27 | 16 | 7.35 | 2.0 | 40 ± 3 |
BOD (mg/L) | 1,619 | 2,489 | 2,082 | 359 | −0.4557 | 80 |
COD (mg/L) | 3,200 | 5,240 | 3,830 | 946.784 | 1.9124 | 150 |
TKN (mg/L) | 0.2 | 173.2 | 48.2 | 83.4785 | 1.9791 | – |
Total hardness (mg/L CaCO3) | 3,120 | 6,520 | 4,210 | 1,557 | 1.861 | – |
Ca+2 hardness (mg/L CaCO3) | 2,464 | 3,912 | 2,908 | 682 | 1.7865 | – |
Mg+2 hardness (mg/L CaCO3) | 624 | 2,608 | 1,302 | 889.1494 | 1.7500 | – |
Alkalinity (mg/L CaCO3) | 150 | 700 | 468.75 | 232.18 | −1.0378 | – |
TS (mg/L) | 223 | 3,311 | 2,291 | 1,410 | −1.7455 | – |
TDS (mg/L) | 91 | 1,329 | 918 | 564 | −1.7303 | 3,500 |
TSeS (mg/L) | 133.8 | 1,984 | 1,373 | 845 | −1.7470 | – |
Chlorides (mg/L) | 0.0 | 3.5 | 1.05 | 1.6422 | 1.9348 | 1,000 |
Nickel (ppm) | 0.0 | 5.84 | 1.46 | 2.92 | 2.0 | 1 |
Zinc (ppm) | 0.01 | 0.05 | 0.042 | 0.01 | 0.01 | 5 |
Cadmium (ppm) | 0.4316 | 0.788 | 0.5651 | 0.1594 | 1.2957 | 0.1 |
Chromium (ppm) | 103 | 111 | 108 | 3.8469 | −0.6718 | 1 |
Lead (ppm) | 97.36 | 143.16 | 118.23 | 19.673 | 0.5082 | 0.5 |
Parameter . | Min . | Max . | Mean . | Std. deviation . | Skewness . | Guideline values . |
---|---|---|---|---|---|---|
Drinking water | ||||||
pH | 7.46 | 8.1 | 7.715 | 0.286 | 1.0 | 6.5–8.5 |
Temp (°C) | 22 | 25 | 23 | 1.258 | −1.129 | – |
Turbidity (NTU) | 2.25 | 5.12 | 3.49 | 1.19 | 0.936 | <5 |
Coliform (MPN/100 mL) | 32 | 1,602 | 1,209.5 | 785 | −2.0 | Nil |
Fecal coliform (MPN/100 mL) | 2 | 123 | 47 | 52.896 | 1.510 | Nil |
Total hardness (mg/L CaCO3) | 1,480 | 1,600 | 1,520 | 56.569 | 1.414 | <500 |
Ca+2 hardness (mg/L CaCO3) | 1,124.8 | 1,337.6 | 1,216.2 | 96.475 | 0.61 | – |
Mg+2 hardness (mg/L CaCO3) | 182.4 | 355.2 | 303.8 | 82.013 | −1.850 | – |
Alkalinity (mg/L CaCO3) | 50 | 662.5 | 310 | 256.035 | 1.031 | – |
TS (mg/L) | 1,708 | 2,907 | 2,490 | 544.287 | −1.544 | – |
TDS (mg/L) | 1,024 | 1,744 | 1,492 | 326 | −1.53 | 1,000 |
TSeS (mg/L) | 689 | 1,263 | 987.75 | 234.73 | −0.299 | – |
Chlorides (mg/L) | 225 | 512 | 349 | 119.563 | 0.936 | <250 |
Nickel (ppm) | 0.012 | 0.024 | 0.019 | 0.005 | −1.056 | <0.02 |
Zinc (ppm) | 0.013 | 0.280 | 0.088 | 0.128 | 1.968 | 5 |
Cadmium (ppm) | 0.001 | 0.003 | 0.002 | 0.000 | −0.060 | 0.01 |
Chromium (ppm) | 2.117 | 3.981 | 3.106 | 0.944 | −0.110 | 0.05 |
Lead (ppm) | 0.645 | 1.804 | 1.206 | 0.534 | 0.119 | 0.05 |
Wastewater | ||||||
pH | 6.66 | 8.89 | 8.01 | 1.0 | −1.013 | 6–9 |
Temp (°C) | 12 | 27 | 16 | 7.35 | 2.0 | 40 ± 3 |
BOD (mg/L) | 1,619 | 2,489 | 2,082 | 359 | −0.4557 | 80 |
COD (mg/L) | 3,200 | 5,240 | 3,830 | 946.784 | 1.9124 | 150 |
TKN (mg/L) | 0.2 | 173.2 | 48.2 | 83.4785 | 1.9791 | – |
Total hardness (mg/L CaCO3) | 3,120 | 6,520 | 4,210 | 1,557 | 1.861 | – |
Ca+2 hardness (mg/L CaCO3) | 2,464 | 3,912 | 2,908 | 682 | 1.7865 | – |
Mg+2 hardness (mg/L CaCO3) | 624 | 2,608 | 1,302 | 889.1494 | 1.7500 | – |
Alkalinity (mg/L CaCO3) | 150 | 700 | 468.75 | 232.18 | −1.0378 | – |
TS (mg/L) | 223 | 3,311 | 2,291 | 1,410 | −1.7455 | – |
TDS (mg/L) | 91 | 1,329 | 918 | 564 | −1.7303 | 3,500 |
TSeS (mg/L) | 133.8 | 1,984 | 1,373 | 845 | −1.7470 | – |
Chlorides (mg/L) | 0.0 | 3.5 | 1.05 | 1.6422 | 1.9348 | 1,000 |
Nickel (ppm) | 0.0 | 5.84 | 1.46 | 2.92 | 2.0 | 1 |
Zinc (ppm) | 0.01 | 0.05 | 0.042 | 0.01 | 0.01 | 5 |
Cadmium (ppm) | 0.4316 | 0.788 | 0.5651 | 0.1594 | 1.2957 | 0.1 |
Chromium (ppm) | 103 | 111 | 108 | 3.8469 | −0.6718 | 1 |
Lead (ppm) | 97.36 | 143.16 | 118.23 | 19.673 | 0.5082 | 0.5 |
Wastewater samples indicated a very severe picture. Only pH, TDS, chlorides, and Zn were within the limits of National Effluent Quality (NEQ) standards of Pakistan while all other parameters were beyond the limits (Table 2). High values of BOD and COD indicated that the effluents were discharged without any treatment. Skewness has values greater than 1.0 which indicated that the samples were not normal distributed, rather non-symmetrical.
Analysis of variance (ANOVA)
ANOVA was performed to establish a hypothesis that the parameters (both for drinking and wastewater) have no correlation with each other (null hypothesis). To verify, one-way ANOVA was performed, and results are given in Table 3. For drinking and wastewater sample, Fcrit is 1.82 and 1.8, respectively, which is smaller than F (36.6 and 18.2) value obtained by ANOVA. This suggested that parameters have some correlation.
Analysis of variance (ANOVA) for drinking water and wastewater
Source of variation . | SS . | Df . | MS . | F . | Fcrit . |
---|---|---|---|---|---|
Drinking water | |||||
Between groups | 36,739,526 | 17 | 2,161,149 | 32.68 | 1.82 |
Within groups | 3,571,452 | 54 | 66,138 | ||
Wastewater | |||||
Between groups | 134,312,814 | 17 | 7,900,754 | 18.25 | 1.82 |
Within groups | 23,377,023 | 54 | 432,907.8 |
Source of variation . | SS . | Df . | MS . | F . | Fcrit . |
---|---|---|---|---|---|
Drinking water | |||||
Between groups | 36,739,526 | 17 | 2,161,149 | 32.68 | 1.82 |
Within groups | 3,571,452 | 54 | 66,138 | ||
Wastewater | |||||
Between groups | 134,312,814 | 17 | 7,900,754 | 18.25 | 1.82 |
Within groups | 23,377,023 | 54 | 432,907.8 |
The null hypothesis and alternative hypothesis were formulated and evaluated using ANOVA.
Pearson correlation coefficient
Pearson correlation coefficient was performed for drinking and wastewater to identify the extent of correlation among parameters. The results of Pearson correlation coefficient are given in Table 4. In the case of drinking water, pH showed strong correlation with temperature, total solids, total dissolved solids, total hardness, alkalinity, and zinc. Temperature and turbidity showed strong correlation with coliform and fecal coliform, which indicated that wastewater is contaminating the drinking water. Heavy metals showed moderate to strong correlation (0.3–0.9) among drinking water samples. In the case of wastewater samples, pH showed moderate to strong correlation (0.3–0.7) with BOD and COD, respectively (Table 4). BOD and COD both showed moderate to strong correlation with heavy metals, which suggested that heavy metals were contributed from industrial effluents of SIE (Table 4). Heavy metals showed strong correlation among them, which indicated the same source of these metals. Chlorides showed strong correlation (0.7–0.9) with heavy metals, which suggested that the salts of metals were present in industrial effluents. The common industrial salts are nitrates, chlorides, and sulphate of metals.
Pearson correlation coefficient analysis for drinking and wastewater parameters to find extent of correlation among parameters
. | pH . | Temp . | Turb. . | Coli form . | Fecal form . | Total hardness . | Ca hardness . | Mg hardness . | Alk . | TS . | TDS . | TSeS . | Cl− . | Ni . | Zn . | Cd . | Cr . | Pb . |
---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
Drinking water parameters | ||||||||||||||||||
pH | 1.000 | |||||||||||||||||
Temp | − 0.671 | 1.000 | ||||||||||||||||
Turbidity | − 0.020 | − 0.020 | 1.000 | |||||||||||||||
Coliform | − 0.897 | 0.927 | 0.056 | 1.000 | ||||||||||||||
Fecal form | − 0.652 | 0.336 | 0.764 | 0.567 | 1.000 | |||||||||||||
Total hardness | 0.988* | − 0.749 | − 0.116 | − 0.943 | − 0.704 | 1.000 | ||||||||||||
Ca+2 hardness | 0.597 | 0.159 | − 0.320 | − 0.220 | − 0.697 | 0.530 | 1.000 | |||||||||||
Mg+2 Hardness | − 0.021 | − 0.704 | 0.296 | − 0.392 | 0.335 | 0.067 | − 0.811 | 1.000 | ||||||||||
Alkalinity | 0.890 | − 0.760 | − 0.406 | − 0.918 | − 0.847 | 0.946 | 0.475 | 0.094 | 1.000 | |||||||||
TS | − 0.795 | 0.964* | − 0.185 | 0.958* | 0.308 | − 0.835 | 0.011 | − 0.590 | − 0.766 | 1.000 | ||||||||
TDS | − 0.793 | 0.964* | − 0.189 | 0.956* | 0.304 | − 0.833 | 0.015 | − 0.592 | − 0.763 | 1.000** | 1.000 | |||||||
TSeS | − 0.534 | 0.985* | − 0.049 | 0.848 | 0.216 | − 0.624 | 0.325 | − 0.812 | − 0.653 | 0.919 | 0.920 | 1.000 | ||||||
Chlorides | − 0.020 | − 0.020 | 1.000** | 0.056 | 0.764 | − 0.116 | − 0.320 | 0.296 | − 0.406 | − 0.185 | − 0.189 | − 0.049 | 1.000 | |||||
Ni | 0.507 | 0.052 | − 0.714 | − 0.261 | − 0.911 | 0.508 | 0.888 | − 0.694 | 0.606 | 0.023 | 0.028 | 0.191 | − 0.714 | 1.000 | ||||
Zn | 0.918 | − 0.901 | − 0.102 | − 0.997 | − 0.621 | 0.962* | 0.285 | 0.327 | 0.942 | − 0.935 | − 0.933 | − 0.813 | − 0.102 | 0.331 | 1.000 | |||
Cd | − 0.352 | 0.774 | 0.566 | 0.668 | 0.572 | − 0.493 | 0.173 | − 0.544 | − 0.709 | 0.598 | 0.596 | 0.788 | 0.566 | − 0.199 | − 0.662 | 1.000 | ||
Cr | − 0.095 | 0.595 | 0.660 | 0.440 | 0.479 | − 0.248 | 0.294 | − 0.517 | − 0.518 | 0.371 | 0.370 | 0.642 | 0.660 | − 0.140 | − 0.433 | 0.962* | 1.000 | |
Pb | 0.527 | − 0.752 | − 0.644 | − 0.747 | − 0.761 | 0.651 | 0.090 | 0.343 | 0.850 | − 0.617 | − 0.614 | − 0.722 | − 0.644 | 0.431 | 0.757 | − 0.965 | − 0.890 | 1.000 |
Wastewater parameters | ||||||||||||||||||
pH | Temp | BOD | COD | TKN | Total hardness | Ca hardness | Mg hardness | Alkalinity | TS | TDS | TSeS | Chloride | Ni | Cd | Cr | Pb | ||
pH | 1.0000 | |||||||||||||||||
Temp | − 0.8758 | 1.0000 | ||||||||||||||||
BOD | − 0.3878 | 0.7808 | 1.0000 | |||||||||||||||
COD | 0.6668 | − 0.3852 | 0.0433 | 1.0000 | ||||||||||||||
TKN | 0.5340 | − 0.2255 | 0.1697 | 0.985* | 1.0000 | |||||||||||||
Total hardness | − 0.9234 | 0.989* | 0.6883 | − 0.4060 | − 0.2444 | 1.0000 | ||||||||||||
Ca+2 hardness | − 0.965* | 0.972* | 0.6138 | − 0.5367 | − 0.3851 | 0.989* | 1.0000 | |||||||||||
Mg+2 hardness | − 0.8772 | 0.987* | 0.7350 | − 0.2994 | − 0.1327 | 0.993** | .965* | 1.0000 | ||||||||||
Alkalinity | − 0.7736 | 0.6154 | 0.2569 | − 0.954* | − 0.8999 | 0.6103 | 0.7139 | 0.5215 | 1.0000 | |||||||||
TS | 0.0567 | 0.3700 | 0.8314 | 0.0909 | 0.1322 | 0.2278 | 0.1738 | 0.2658 | 0.1491 | 1.0000 | ||||||||
TDS | 0.0530 | 0.3719 | 0.8310 | 0.0840 | 0.1253 | 0.2297 | 0.1767 | 0.2669 | 0.1555 | 1.000** | 1.0000 | |||||||
TSeS | 0.0558 | 0.3710 | 0.8321 | 0.0909 | 0.1324 | 0.2288 | 0.1748 | 0.2668 | 0.1493 | 1.000** | 1.000** | 1.0000 | ||||||
Chlorides | − 0.9141 | 0.986* | 0.7212 | − 0.5313 | − 0.3830 | 0.976* | 0.983* | 0.955* | 0.7377 | 0.3456 | 0.3486 | 0.3465 | 1.0000 | |||||
Ni | − 0.8969 | 0.998** | 0.7552 | − 0.4436 | − 0.2875 | 0.989* | 0.981* | 0.979* | 0.6640 | 0.3530 | 0.3553 | 0.3540 | 0.995** | 1.0000 | ||||
Cd | − 0.996** | 0.9132 | 0.4678 | − 0.6487 | − 0.5107 | 0.9484 | 0.983* | 0.9071 | 0.7791 | 0.0331 | 0.0367 | 0.0340 | 0.9472 | 0.9320 | 1.0000 | |||
Cr | 0.986* | − 0.8221 | − 0.2867 | 0.6057 | 0.4740 | − 0.8912 | − 0.9290 | − 0.8485 | − 0.6866 | 0.2000 | 0.1969 | 0.1991 | − 0.8503 | − 0.8405 | − 0.970* | 1.0000 | ||
Pb | 0.9215 | − 0.6643 | − 0.1174 | 0.8927 | 0.8118 | − 0.7178 | − 0.8123 | − 0.6343 | − 0.9072 | 0.1855 | 0.1799 | 0.1849 | − 0.7612 | − 0.7072 | − 0.9005 | 0.8988 | 1.0000 |
. | pH . | Temp . | Turb. . | Coli form . | Fecal form . | Total hardness . | Ca hardness . | Mg hardness . | Alk . | TS . | TDS . | TSeS . | Cl− . | Ni . | Zn . | Cd . | Cr . | Pb . |
---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
Drinking water parameters | ||||||||||||||||||
pH | 1.000 | |||||||||||||||||
Temp | − 0.671 | 1.000 | ||||||||||||||||
Turbidity | − 0.020 | − 0.020 | 1.000 | |||||||||||||||
Coliform | − 0.897 | 0.927 | 0.056 | 1.000 | ||||||||||||||
Fecal form | − 0.652 | 0.336 | 0.764 | 0.567 | 1.000 | |||||||||||||
Total hardness | 0.988* | − 0.749 | − 0.116 | − 0.943 | − 0.704 | 1.000 | ||||||||||||
Ca+2 hardness | 0.597 | 0.159 | − 0.320 | − 0.220 | − 0.697 | 0.530 | 1.000 | |||||||||||
Mg+2 Hardness | − 0.021 | − 0.704 | 0.296 | − 0.392 | 0.335 | 0.067 | − 0.811 | 1.000 | ||||||||||
Alkalinity | 0.890 | − 0.760 | − 0.406 | − 0.918 | − 0.847 | 0.946 | 0.475 | 0.094 | 1.000 | |||||||||
TS | − 0.795 | 0.964* | − 0.185 | 0.958* | 0.308 | − 0.835 | 0.011 | − 0.590 | − 0.766 | 1.000 | ||||||||
TDS | − 0.793 | 0.964* | − 0.189 | 0.956* | 0.304 | − 0.833 | 0.015 | − 0.592 | − 0.763 | 1.000** | 1.000 | |||||||
TSeS | − 0.534 | 0.985* | − 0.049 | 0.848 | 0.216 | − 0.624 | 0.325 | − 0.812 | − 0.653 | 0.919 | 0.920 | 1.000 | ||||||
Chlorides | − 0.020 | − 0.020 | 1.000** | 0.056 | 0.764 | − 0.116 | − 0.320 | 0.296 | − 0.406 | − 0.185 | − 0.189 | − 0.049 | 1.000 | |||||
Ni | 0.507 | 0.052 | − 0.714 | − 0.261 | − 0.911 | 0.508 | 0.888 | − 0.694 | 0.606 | 0.023 | 0.028 | 0.191 | − 0.714 | 1.000 | ||||
Zn | 0.918 | − 0.901 | − 0.102 | − 0.997 | − 0.621 | 0.962* | 0.285 | 0.327 | 0.942 | − 0.935 | − 0.933 | − 0.813 | − 0.102 | 0.331 | 1.000 | |||
Cd | − 0.352 | 0.774 | 0.566 | 0.668 | 0.572 | − 0.493 | 0.173 | − 0.544 | − 0.709 | 0.598 | 0.596 | 0.788 | 0.566 | − 0.199 | − 0.662 | 1.000 | ||
Cr | − 0.095 | 0.595 | 0.660 | 0.440 | 0.479 | − 0.248 | 0.294 | − 0.517 | − 0.518 | 0.371 | 0.370 | 0.642 | 0.660 | − 0.140 | − 0.433 | 0.962* | 1.000 | |
Pb | 0.527 | − 0.752 | − 0.644 | − 0.747 | − 0.761 | 0.651 | 0.090 | 0.343 | 0.850 | − 0.617 | − 0.614 | − 0.722 | − 0.644 | 0.431 | 0.757 | − 0.965 | − 0.890 | 1.000 |
Wastewater parameters | ||||||||||||||||||
pH | Temp | BOD | COD | TKN | Total hardness | Ca hardness | Mg hardness | Alkalinity | TS | TDS | TSeS | Chloride | Ni | Cd | Cr | Pb | ||
pH | 1.0000 | |||||||||||||||||
Temp | − 0.8758 | 1.0000 | ||||||||||||||||
BOD | − 0.3878 | 0.7808 | 1.0000 | |||||||||||||||
COD | 0.6668 | − 0.3852 | 0.0433 | 1.0000 | ||||||||||||||
TKN | 0.5340 | − 0.2255 | 0.1697 | 0.985* | 1.0000 | |||||||||||||
Total hardness | − 0.9234 | 0.989* | 0.6883 | − 0.4060 | − 0.2444 | 1.0000 | ||||||||||||
Ca+2 hardness | − 0.965* | 0.972* | 0.6138 | − 0.5367 | − 0.3851 | 0.989* | 1.0000 | |||||||||||
Mg+2 hardness | − 0.8772 | 0.987* | 0.7350 | − 0.2994 | − 0.1327 | 0.993** | .965* | 1.0000 | ||||||||||
Alkalinity | − 0.7736 | 0.6154 | 0.2569 | − 0.954* | − 0.8999 | 0.6103 | 0.7139 | 0.5215 | 1.0000 | |||||||||
TS | 0.0567 | 0.3700 | 0.8314 | 0.0909 | 0.1322 | 0.2278 | 0.1738 | 0.2658 | 0.1491 | 1.0000 | ||||||||
TDS | 0.0530 | 0.3719 | 0.8310 | 0.0840 | 0.1253 | 0.2297 | 0.1767 | 0.2669 | 0.1555 | 1.000** | 1.0000 | |||||||
TSeS | 0.0558 | 0.3710 | 0.8321 | 0.0909 | 0.1324 | 0.2288 | 0.1748 | 0.2668 | 0.1493 | 1.000** | 1.000** | 1.0000 | ||||||
Chlorides | − 0.9141 | 0.986* | 0.7212 | − 0.5313 | − 0.3830 | 0.976* | 0.983* | 0.955* | 0.7377 | 0.3456 | 0.3486 | 0.3465 | 1.0000 | |||||
Ni | − 0.8969 | 0.998** | 0.7552 | − 0.4436 | − 0.2875 | 0.989* | 0.981* | 0.979* | 0.6640 | 0.3530 | 0.3553 | 0.3540 | 0.995** | 1.0000 | ||||
Cd | − 0.996** | 0.9132 | 0.4678 | − 0.6487 | − 0.5107 | 0.9484 | 0.983* | 0.9071 | 0.7791 | 0.0331 | 0.0367 | 0.0340 | 0.9472 | 0.9320 | 1.0000 | |||
Cr | 0.986* | − 0.8221 | − 0.2867 | 0.6057 | 0.4740 | − 0.8912 | − 0.9290 | − 0.8485 | − 0.6866 | 0.2000 | 0.1969 | 0.1991 | − 0.8503 | − 0.8405 | − 0.970* | 1.0000 | ||
Pb | 0.9215 | − 0.6643 | − 0.1174 | 0.8927 | 0.8118 | − 0.7178 | − 0.8123 | − 0.6343 | − 0.9072 | 0.1855 | 0.1799 | 0.1849 | − 0.7612 | − 0.7072 | − 0.9005 | 0.8988 | 1.0000 |
Principal component analysis (PCA)
The principal component analysis (PCA) is a tool which is based on an imaginary Eigen value. In the present study, all Eigen values which were less than 1 were ignored. The components having Eigen value >1 are grouped based on the same source (Jalees et al. 2016). PCA using the rotation method of varimax and Kaiser normalization was performed on drinking water and wastewater samples and the results are shown in Table 5. The PCA for drinking water gave three components, named as PC 1, PC 2, and PC 3, which explained a total of >98% of total variance. PC 1 explained 56.69% of the total variance, PC 2 explained 26.5% while PC 3 explained 16.78% (Table 5). PC 1 expressed highest loading for pH, temperature, coliform, total hardness, alkalinity, TS, TDS, TSeS, and zinc. This high loading reflected seepage to groundwater aquifer from sewage effluent discharges, urban runoff, industrial waste discharges, and contamination from refuse leachate to the ultimate problem (WHO 1984; Jalees et al. 2016). SIE has various industries which contribute these pollutants (Table 1). Moreover, dissolution of salt deposits in the aquifer can increase heavy metal levels, and waters in the areas of Paleozoic and Mesozoic sedimentary rock have higher TDS levels, ranging from as little as 195 to 1,100 mg/L (WHO 1984). PC 2 showed the highest loading for turbidity, Cl−1, Cd, Cr, and Pb which indicated dissolution of rocks and minerals in the aquifer or anthropogenic activities (WHO 1984). PC 3 showed maximum loading for calcium hardness and Ni reflected contamination from the seepage of industrial emissions and tanneries' wastewater (Table 5) (WHO 1984; Jalees et al. 2016).
Principal component analysis (PCA) for source identification
. | 1 . | 2 . | 3 . |
---|---|---|---|
Drinking water | |||
Total variance (%) | 56.69 | 26.52 | 16.78 |
pH | −0.8869 | 0.0266 | 0.4612 |
Temp | 0.9235 | 0.2283 | 0.3082 |
Turbidity | −0.1329 | 0.9263 | −0.3526 |
Coliform | 0.9822 | 0.1763 | −0.0653 |
Fecal coliform | 0.4198 | 0.6402 | −0.6434 |
Total hardness | −0.9146 | −0.1085 | 0.3897 |
Ca+2 hardness | −0.1594 | 0.0075 | 0.9872 |
Mg+2 hardness | −0.4432 | −0.0836 | −0.8925 |
Alkalinity | −0.8350 | −0.4251 | 0.3495 |
TS | 0.9853 | 0.0071 | 0.1707 |
TDS | 0.9847 | 0.0040 | 0.1744 |
TSeS | 0.8506 | 0.2463 | 0.4646 |
Chlorides | −0.1329 | 0.9263 | −0.3526 |
Ni | −0.1262 | −0.4530 | 0.8825 |
Zn | −0.9709 | −0.1987 | 0.1338 |
Cd | 0.5560 | 0.7896 | 0.2596 |
Cr | 0.3112 | 0.8870 | 0.3411 |
Pb | −0.6197 | −0.7848 | −0.0027 |
Wastewater | |||
Total variance (%) | 63.76 | 25.32 | 10.9 |
pH | −0.899 | 0.104 | 0.426 |
Temp | 0.938 | 0.312 | −0.154 |
BOD | 0.596 | 0.788 | 0.155 |
COD | −0.280 | 0.078 | 0.957 |
TKN | −0.114 | 0.107 | 0.988 |
Total hardness | 0.974 | 0.167 | −0.153 |
Ca+2 hardness | 0.949 | 0.119 | −0.293 |
Mg+2 hardness | 0.979 | 0.201 | −0.043 |
Alkalinity | 0.464 | 0.147 | −0.874 |
TS | 0.069 | 0.997 | 0.034 |
TDS | 0.069 | 0.997 | 0.027 |
TSeS | 0.070 | 0.997 | 0.034 |
Chlorides | 0.902 | 0.295 | −0.316 |
Ni | 0.930 | 0.297 | −0.216 |
Cd | 0.912 | −0.016 | −0.410 |
Cr | −0.903 | 0.251 | 0.349 |
Pb | −0.658 | 0.207 | 0.724 |
. | 1 . | 2 . | 3 . |
---|---|---|---|
Drinking water | |||
Total variance (%) | 56.69 | 26.52 | 16.78 |
pH | −0.8869 | 0.0266 | 0.4612 |
Temp | 0.9235 | 0.2283 | 0.3082 |
Turbidity | −0.1329 | 0.9263 | −0.3526 |
Coliform | 0.9822 | 0.1763 | −0.0653 |
Fecal coliform | 0.4198 | 0.6402 | −0.6434 |
Total hardness | −0.9146 | −0.1085 | 0.3897 |
Ca+2 hardness | −0.1594 | 0.0075 | 0.9872 |
Mg+2 hardness | −0.4432 | −0.0836 | −0.8925 |
Alkalinity | −0.8350 | −0.4251 | 0.3495 |
TS | 0.9853 | 0.0071 | 0.1707 |
TDS | 0.9847 | 0.0040 | 0.1744 |
TSeS | 0.8506 | 0.2463 | 0.4646 |
Chlorides | −0.1329 | 0.9263 | −0.3526 |
Ni | −0.1262 | −0.4530 | 0.8825 |
Zn | −0.9709 | −0.1987 | 0.1338 |
Cd | 0.5560 | 0.7896 | 0.2596 |
Cr | 0.3112 | 0.8870 | 0.3411 |
Pb | −0.6197 | −0.7848 | −0.0027 |
Wastewater | |||
Total variance (%) | 63.76 | 25.32 | 10.9 |
pH | −0.899 | 0.104 | 0.426 |
Temp | 0.938 | 0.312 | −0.154 |
BOD | 0.596 | 0.788 | 0.155 |
COD | −0.280 | 0.078 | 0.957 |
TKN | −0.114 | 0.107 | 0.988 |
Total hardness | 0.974 | 0.167 | −0.153 |
Ca+2 hardness | 0.949 | 0.119 | −0.293 |
Mg+2 hardness | 0.979 | 0.201 | −0.043 |
Alkalinity | 0.464 | 0.147 | −0.874 |
TS | 0.069 | 0.997 | 0.034 |
TDS | 0.069 | 0.997 | 0.027 |
TSeS | 0.070 | 0.997 | 0.034 |
Chlorides | 0.902 | 0.295 | −0.316 |
Ni | 0.930 | 0.297 | −0.216 |
Cd | 0.912 | −0.016 | −0.410 |
Cr | −0.903 | 0.251 | 0.349 |
Pb | −0.658 | 0.207 | 0.724 |
For wastewater, three components were identified as PC 1, PC 2, and PC 3 with a combined total of variance of >98%. PC 1 explained 63.76%, PC 2 explained 25.32, and PC 3 explained 10.9% of variance. PC 1 gave maximum loading for pH, temperature, hardness, and heavy metals which indicated metal precipitation due to pH. PC 2 indicated that BOD and solids had high loading values which suggested that solids in untreated wastewater were responsible for high BOD contents (Jalees et al. 2016). PC 3 gave high loading for COD, TKN, and alkalinity, which suggested that these contaminations originated from the same source.
Cluster analysis (CA)
A tree diagram, which shows the agglomerative hierarchical clustering algorithms available in the data, is called a dendrogram (Hintze 1995). This diagram is used for the extent of correlation among the parameters. The CA dendrogram (single linkage) was performed on average parameter values of drinking water and wastewater samples from all locations, as shown in Figure 2. For drinking water, the elucidation distance of turbidity, chlorides, and hardness comprises group G1; elucidation distance of Ni, Zn, Pb, Cr, pH, temperature, and fecal coliform comprises G2 while elucidation distance of solids and hardness comprises G3 (third group). All these groups have strong correlation within groups as indicated by the small elucidation distance (Figure 2), but among the groups, these parameters showed long elucidation distance which indicated the different sources of these pollutants in the drinking water (Jalees et al. 2016). In the wastewater sample, the elucidation distance of heavy metals, i.e., Ni, Cd, Cr, Pb along with chlorides, pH, temperature, TKN showed a similar origin and all fall under one group with strong correlation among group members. Other than these, all wastewater parameters have a long elucidation distance which indicated the multiple sources of pollutants present in the wastewater (Jalees et al. 2016).
Risk assessment
Lifetime average daily dose (LADD)
The values for LADD for heavy metals, i.e., Ni, Pb, Cr, Cd, and Zn, were calculated using Equation (3) (EPA 2004). The Environmental Protection Agency of United States (US EPA) developed this relation in 2004. In locations where drinking water is contaminated, the potential may exist for uptake via ingestion (drinking). This may result in exposure of toxic pollutants among local populations in the contaminated area. Receptors could include families living nearby or societies. Exposure via intake/drinking of contaminated water depends upon the concentration of pollutant intake but also the rate at which the water is used, and the frequency and duration of exposure.
The calculated values in drinking water are given in Table 6. The values of Ni were in the range of 1.6 × 10−4 to 2.1 × 10−4; for Pb, values ranged from 7.6 × 10−3 to 1.3 × 10−2; for Cr, the values were 1.8 × 10−3 to 3.4 × 10−3; for Cd, the values were 6.9 × 10−7 to 3.4 × 10−6; and for Zn, values were 2.1 × 10−4 to 3.1 × 10−4 (Table 6). Based on the average LADD values, the metals showed the following trend Cr > Pb > Zn > Ni > Cd.
Risk assessment calculation showing lifetime average daily dose (LADD), hazard quotient (HQ) and cancer risk for heavy metals present in drinking water of SIE
. | Ni . | Pb . | Cr . | Cd . | Zn . |
---|---|---|---|---|---|
LADD | |||||
Location 1 | 2.1 × 10−4 | 7.6 × 10−3 | 3.4 × 10−2 | 3.4 × 10−6 | 3.1 × 10−4 |
Location 2 | 1.6 × 10−4 | 13 × 10−3 | 1.8 × 10−2 | 1.1 × 10−6 | 2.1 × 10−4 |
Location 3 | 1.8 × 10−4 | 8.6 × 10−3 | 2.1 × 10−2 | 0.69 × 10−6 | 24 × 10−4 |
Location 4 | 2.1 × 10−4 | 7.6 × 10−3 | 3.4 × 10−2 | 3.4 × 10−6 | 3.1 × 10−4 |
RfD | 0.02 | 0.004 | 1.5 | 0.001 | 0.3 |
Hazard quotient | |||||
Location 1 | 5.1 × 10−3 | 1.4 | 2.2 × 10−2 | 3.3 × 10−3 | 3.7 × 10−4 |
Location 2 | 10 × 10−3 | 1.9 | 2.3 × 10−2 | 3.4 × 10−3 | 10 × 10−4 |
Location 3 | 8.2 × 10−3 | 3.2 | 1.2 × 10−2 | 1.1 × 10−3 | 6.9 × 10−4 |
Location 4 | 9.0 × 10−3 | 2.1 | 1.4 × 10−2 | 6.9 × 10−3 | 80 × 10−4 |
HI | 33 × 10−3 | 8.6 | 7.1 × 10−2 | 8.5 × 10−3 | 100 × 10−4 |
Total hazard index (HI) | 8.7 | ||||
Cancer risk | |||||
Location 1 | 9.4 × 10−5 | 4.7 × 0−5 | 1.6 × 10−2 | 4.9 × 10−6 | – |
Location 2 | 19 × 10−5 | 6.5 × 10−5 | 1.7 × 10−2 | 5.2 × 10−6 | – |
Location 3 | 15 × 10−5 | 11 × 10−5 | 91 × 10−2 | 1.7 × 10−6 | – |
Location 4 | 16 × 10−5 | 7.3 × 10−5 | 1.1 × 10−2 | 1.0 × 10−6 | – |
Slope factor | 0.91 | 0.0085 | 0.5 | 1.5 | – |
Sum | 59 × 10−5 | 29 × 10−5 | 93 × 10−2 | 13 × 10−6 | – |
Total cancer risk | 93 × 10−2 |
. | Ni . | Pb . | Cr . | Cd . | Zn . |
---|---|---|---|---|---|
LADD | |||||
Location 1 | 2.1 × 10−4 | 7.6 × 10−3 | 3.4 × 10−2 | 3.4 × 10−6 | 3.1 × 10−4 |
Location 2 | 1.6 × 10−4 | 13 × 10−3 | 1.8 × 10−2 | 1.1 × 10−6 | 2.1 × 10−4 |
Location 3 | 1.8 × 10−4 | 8.6 × 10−3 | 2.1 × 10−2 | 0.69 × 10−6 | 24 × 10−4 |
Location 4 | 2.1 × 10−4 | 7.6 × 10−3 | 3.4 × 10−2 | 3.4 × 10−6 | 3.1 × 10−4 |
RfD | 0.02 | 0.004 | 1.5 | 0.001 | 0.3 |
Hazard quotient | |||||
Location 1 | 5.1 × 10−3 | 1.4 | 2.2 × 10−2 | 3.3 × 10−3 | 3.7 × 10−4 |
Location 2 | 10 × 10−3 | 1.9 | 2.3 × 10−2 | 3.4 × 10−3 | 10 × 10−4 |
Location 3 | 8.2 × 10−3 | 3.2 | 1.2 × 10−2 | 1.1 × 10−3 | 6.9 × 10−4 |
Location 4 | 9.0 × 10−3 | 2.1 | 1.4 × 10−2 | 6.9 × 10−3 | 80 × 10−4 |
HI | 33 × 10−3 | 8.6 | 7.1 × 10−2 | 8.5 × 10−3 | 100 × 10−4 |
Total hazard index (HI) | 8.7 | ||||
Cancer risk | |||||
Location 1 | 9.4 × 10−5 | 4.7 × 0−5 | 1.6 × 10−2 | 4.9 × 10−6 | – |
Location 2 | 19 × 10−5 | 6.5 × 10−5 | 1.7 × 10−2 | 5.2 × 10−6 | – |
Location 3 | 15 × 10−5 | 11 × 10−5 | 91 × 10−2 | 1.7 × 10−6 | – |
Location 4 | 16 × 10−5 | 7.3 × 10−5 | 1.1 × 10−2 | 1.0 × 10−6 | – |
Slope factor | 0.91 | 0.0085 | 0.5 | 1.5 | – |
Sum | 59 × 10−5 | 29 × 10−5 | 93 × 10−2 | 13 × 10−6 | – |
Total cancer risk | 93 × 10−2 |
Non-carcinogenic assessment
The value of HI (Table 6) is 8.7 which clearly indicates that there is a probability of non-carcinogenic hazard among people in the study area due to consumption of contaminated drinking water.
Cancer risk assessment
CONCLUSIONS
In this study, drinking water and wastewater samples were collected from Sundar Industrial Estate for source, correlation, and health risk assessment. The analysis of drinking water indicated high bacterial and heavy metals' contamination which is beyond the NDWQS of Pakistan. High BOD and COD values of wastewater indicated the presence of untreated effluent discharge. Descriptive statistics indicated non-symmetrical distribution of parameters except in the case of heavy metals for both drinking and wastewater. ANOVA and Pearson correlation indicated moderate to strong correlation among physical and chemical parameters of drinking and wastewater analysis. PCA and CA indicated the seepage of wastewater, contamination from refuse leachate, and untreated effluent discharges as the main sources of contamination for drinking water. Lifetime average daily dose (LADD) for heavy metals is in the order of Cr > Pb > Zn > Ni > Cd. The HQ and HI indicated the probability of non-carcinogenic risk as values are greater than 1. Cancer risk assessment and total risk assessment showed that 93 people from every 100 of population may suffer from cancer due to drinking water contaminated by industrial and anthropogenic activities. Based on the results of the current study, it is recommended that the government should implement the regulation of wastewater treatment strictly. In addition to this, a detailed study of other industrial estates situated in different cities of Pakistan should also be undertaken with reference to health risk assessment so that an overall country picture can be seen, and proper remedies can be implemented.
ACKNOWLEDGEMENTS
The authors are grateful to Institute of Chemistry, Punjab University, Lahore and Pakistan Council of Scientific and Industrial Research Laboratories, Lahore for providing analytical facilities.
DATA AVAILABILITY STATEMENT
All relevant data are included in the paper or its Supplementary Information.