Holistic approach to assess human health risks, integrating physicochemical quality attributes and heavy metal levels in tap water

Abstract

Heavy metal contamination is a serious concern affecting the safety of tap water sources. Hence, this study evaluated physicochemical quality indices, carcinogenic and non-carcinogenic health hazard derived from the level of toxic metals in tap water in Gondar city, Ethiopia. The results revealed that except dissolved oxygen, salinity and nitrite, all quality attributes were below the allowable quality standards. The average concentrations for iron (Fe), copper (Cu), lead (Pb), chromium (Cr) and cadmium (Cd) were ranged from 0.003 mg/L to 5 mg/L, 0.475 mg/L to 0.752 mg/L, 0.14 mg/L to 0.703 mg/L, 0.261 mg/L to 2.182 mg/L, and 0.035 mg/L to 4.286 mg/L, respectively. The mean levels of metals in different areas decreased in the order: AR > AZ1 > PS1 > AZ3 > PS2 > MR > PS3 > SHD > AZ2 > CL. Except for Cu, the concentration of Fe, Pb, Cr, and Cd exceeded the safe limits described by WHO/FAO. According to principal component analysis and cluster analysis, anthropogenic activities were found to be the major source of metals. Chronic daily intake (CDI), target hazard quotient (THQ), hazard index (HI), and incremental lifetime cancer risk assessment (ILCR) were employed to evaluate human health risks. Except for Pb in AZ1, PS3, and AR, the values of THQ for both ingestion and dermal pathways from the analysed metals for adults were within the safety limits (THQ $<$1). However, the distribution pattern of HI values were presented in the decreasing order: PS1 > PS2 > AZ3 > MR > PS3 > AR > AZ2 > AZ1 > SHD > CL. Except, the HI values in CL, all values were greater than one (HI > 1), indicating that tap water in these areas may pose non-carcinogenic health risk. The analysis of carcinogenic health risks indicated that the lifetime cancer risk (ingestion and dermal exposure pathways) of heavy metals were in accordance with the acceptable range for tap water (10^–6 – 10^–4). This finding provides valuable input for the development of precise action plans aimed at elevating water quality standards in the studied areas.

Graphical Abstract

Highlights

• •Most of the physicochemical quality parameters of tap water in Gondar city were within safe limits.
• •The heavy metal levels determined in tap water indicated that all areas need immediate attention.
• •The health risk assessment results indicated that there will be non-carcinogenic risk, but not carcinogenic risks.
• •Principal component analysis (PCA) indicates, six principal components can describe the influence of parameters for tap water.

1. Introduction

Access to safe tap water is critical to human health and development because it is necessary for proper functioning of the body [1], [2]. Contamination of tap water constitute a major burden on human health (WHO 2017), and the evaluation of the quality of tap water is one of the high priorities to avoid any health problems [3], [4], [6], [5]. The deterioration of tap water can be due to changes in physical parameters (turbidity, total dissolved solids, alkalinity), chemical parameters (undesirable increase in toxic heavy metal levels), and bacteriological parameters [7], [8]. Drinking polluted tap water has been a global challenge, that’s why it deserves special attention since it is very impaired and seriously threatened by human activities [9]. Monitoring of the physicochemical water quality parameters plays a vital role in assessing the tap water environment, ecosystem, hydrochemistry, and ecology, and restoring tap water quality [10], [11]. The evaluation of physicochemical parameters including electrical conductivity (EC), pH, alkalinity, temperature, dissolved oxygen (DO), salinity, total dissolved solid (TDS), turbidity, sulfate, sulfite, phosphate, nitrate, and nitrite are generally considered to set guidelines and categorize the physicochemical tap water quality [12], [2].

Climate change, industry, urbanization, population growth, and chemical pollution can cause tap water problems worldwide [13]. Most ecological problems are multifaceted because large amounts of waste water discharged into rivers are incompletely treated, which is a particular problem in watersheds in Ethiopia [14]. Prolonged exposure of tap water to heavy metals has brought about negative long-term effects. Heavy metals are amongst the most pollutants threatening human well-being [15]. Heavy metal pollutants could be chemical and biological processes in nature with a potential impact on human health and environmental welfare. Heavy metals are extremely soluble in the aquatic environments and therefore they can be absorbed easily by living organisms [17], [18], [16]. Some heavy metals including Cu, Zn, and Fe are essential for living organisms, however, others such as Pb, Cd, and Cr are toxic triggering severe impairment to metabolic, physiological, and structural systems of organisms [19], [20], [21]. The adverse effect of heavy metals may manifest in various kinds of disorders like retardation of growth, morbidity, formation of tumors, symptoms of chronic diseases, and pathological changes [17], [22], [23]. The assessment of current tap water sources is important due to their possible health risks. The health risk assessment is a method for evaluating the link between the environment and human health in terms of hazard degree. Currently, health risk assessment models are applied to evaluate whether exposure to potentially toxic metals could increase the incidence of adverse effect on human health [25], [26], [24].

Different reports showed that Fe, Cu, Cd, Cr, and Pb in rivers and tap water sources from various region of Ethiopia are beyond the WHO maximum permissible limit. Moreover, researchers recommended that the ground water sources in many parts of Ethiopia are polluted due to unsuccessful monitoring of liquid and solid waste that are discharged to surface water and then the polluted surface water infiltrate to ground water [27]. Based on the current literature available, it can be observed that there is lack of comprehensive studies on tap water in Gondar city in context with toxic metals occurrence, physicochemical quality characteristics and potential health risks related with heavy metal levels. Therefore, the objectives of this study were to (1) examine the physicochemical quality parameters and the levels of heavy metals such as Fe, Cu, Cd, Cr, and Pb in tap water (2) assess the human health risks (carcinogenic and non-carcinogenic) for the residents exposed to heavy metals through ingestion and dermal contact with tap water.

2. Materials and method

2.1. Study area description

The study area is situated in the urban parts of Gondar city, North Gondar zone of Amhara region of Ethiopia. Gondar city is north of Lake Tana on the Lesser Angereb River and southwest of the Simien Mountains. Gondar is the largest city in the region, located at 12°3’N latitude and 37°28’E longitude. Gondar is located 727 km from Addis Ababa the capital city of the Federal government of Ethiopia and 120 km from Bahir Dar the capital city of Amhara Region. The major sources of tap water for Gondar city is groundwater obtained from tube wells, hand pumps, and open wells. The sites for collection of tap water samples are shown in the map of the study area (Fig. 1). There is no satisfactory tap water treatment system for the community water supply in Gondar city, except the removal of pathogenic organisms by the addition of chlorine and particulate matter. Study areas were deliberately selected taking the level of anthropogenic activities into consideration.

Fig. 1.

Map of study areas for water samples.

2.2. Chemical and instrumentation

All chemicals used for this study were HNO₃ (69 %, spectrosol, BDH, England), H₂O₂ (30 %, RAN chemicals and RSA Industries) and multi-element standard solutions (1000 mg/L) for Fe, Cu, Cr, Cd, and Pb from Perkin Elmer (BUCK SCIENTIFIC GRAPH ICTM, East Norwalk, USA) were used to prepare a series of working standards and digestion of samples. The equipments and instruments used for this finding were refrigerator (Hitachi, Tokyo, japan), digital balance (ABT220–4M, Germany), flame atomic absorption spectrophotometer (BUCK Scientific model 210 VGP, East Norwalk, USA), and InoLab IDS multi 9310 device equipped with a pH metric electrode IDT Sen Tix®940 and a conductometric sensor Tetra Con 925 IDS (WTW, Poland) to examine the level of metals and physicochemical quality parameters. All glassware and plastic materials were purified by prior overnight soaking using 5 % HNO₃ in distiled water.

2.3. Sample collection and preparation

Tap Water samples were collected from ten sampling sites for a period of one month during May 2022. A total of 30 tap water samples were collected from the study sites. The samples were collected on the same day for each sample at the same time from tap water of Azezo subcity (AZ1, AZ2, AZ3), Piazza subcity (PS1, PS2, PS3), Arada (AR), Shiwadabo (SHD), Maraki subcity (MR), and College (CL) in 1 liter polyethylene terephthalate bottles that were washed with deionized water and 5 % nitric acid [28]. After sampling, each tap water was acidified with 5 mL of (10 %) HNO₃ and filtered through a Millipore cellulose membrane (0.45 μm) for metal analysis [29]. To obtain clear and colorless sample solutions, different water digestion procedures were optimized using HNO₃ and H₂O₂ mixtures. The samples were digested by adding the acid mixture of 3 mL of HNO₃ (69 %) and 2 mL of H₂O₂ (30 %) allowing these to heat up 225 $℃$ for 1:40 h. All samples were filtered with Whatman no. 42 filter paper, and diluted to 50 mL distilled water. Similarly, blank solutions were prepared for analysis and repeated more than five times to ensure accuracy and the standard mean errors were kept to barest minimum [30], [26], [31].

2.3.1. Determination of physicochemical parameters and nutrient values

Eight physicochemical attributes and five nutrient values were estimated for water quality analysis. The water quality indicators such as pH, turbidity, temperature, electrical conductivity, salinity and dissolved oxygen (DO) concentration were measured in situ using pH meter, turbidity meter, thermometer, conductivity meter and with DO meter with luminescent DO calibrated portable multiparameter probe, respectively [14], [11]. A filtered tap water of 60 mL was oven dried at 105 $℃$in the beaker and the dried content was used to estimate the level of total dissolved solids (TDS) [32], [33]. Total alkalinity was evaluated using phenolphthalein and methyl orange indicator method. In this method, 50 mL of tap water was used and 3 drops from each indicator were added and titrated against 0.2 N H₂SO₄ until orange color appeared [34]. The assessment of various nutrient concentrations such as sulfate, sulfite, nitrate, nitrite and phosphate were carried out using Ultra Violet-visible spectrophotometer described by the method [35], [36] with minor modifications.

2.3.2. Validation of the method and trace metal analysis

For quantitative assessment of the instrument’s stability, the blank, standard and samples were run in triplicates for each analytical course. For the systematic procedure in the metal analysis, calibration curves were prepared at the range of (0.05–10) ppm for Fe, Cr, Cd, Pb and (0.75–10) ppm for Cu. According to the instrument operation to attain its better sensitivity, the working standards were aspirated one after the other into the flame atomic absorption spectrometer and its absorbance was recorded. The recovery rates of the targeted trace metals were detected as Fe (96 %), Cu (93 %), Pb (88.3 %), Cr (101.6 %), and Cd (86.2 %) Table 1. The values of limit of detection (LOD) and limit of quantification (LOQ) were found in the range 0.03–0.59 mg/L and 0.9–2.0 mg/L, respectively. A very good linearity was found for all tested metals with correlation coefficients (R²) $>$ 0.996 (Table 1) [37], [30].

Table 1.

Standards concentration (mg/L), correlation coefficient, limit of detection (mg/L), limit of quantification (mg/L), and recovery rate of metals in water samples.

Metal	Standards	R2	LOD	LOQ	Unspiked sample	Amount added	Spiked sample	Recovery (%)
Fe	0.05, 1, 2.5, 5, 7.5, 10	0.999	0.03	0.9	2 ± 0.103	2.0	3.92 ± 0.24	96
Cu	0.75, 1, 2.5, 5, 7.5, 10	0.997	0.59	2.0	0.575 ± 0.08	0.575	1.11 ± 0.38	93
Pb	0.05, 1, 2.5, 5, 7.5, 10	0.999	0.38	1.3	0.162 ± 0.006	0.162	0.305 ± 0.004	88.3
Cr	0.05, 1, 2.5, 5, 7.5, 10	0.996	0.27	0.9	1.273 ± 0.014	1.273	2.566 ± 0.273	101.6
Cd	0.05, 1, 2.5, 5, 7.5, 10	0.998	0.35	1.2	8.571 ± 0.298	8.571	15.96 ± 0.44	86.2

2.3.3. Assessment of carcinogenic and non-carcinogenic health risks

The health risk of heavy metals from long-term tap water consumption by humans can be assessed in terms of their carcinogenic and non-carcinogenic effects. To evaluate the human health risk of toxic heavy metals, it was essential to determine the value of human exposure to that metal by outlining the route of exposure of pollutants to the human body [39], [38]. The target hazard quotient (THQ), hazard index (HI), and incremental lifetime cancer risk (ILCR) were employed to assess carcinogenic and non-carcinogenic risks from metal levels of tap water in the examined areas. There are multiple sources of exposure to potentially toxic metals in human including ingestion and dermal absorption [40]. The United States environmental protection agency (US EPA) states that the exposure of toxic metals in tap water was characterized by the chronic daily intake (CDI, mg/kg/day). The CDI in the two exposure pathways can be computed using the following (1), (2), (3) [41], [42].

$${\mathrm{CDI}}_{\mathrm{ing}}=\frac{C_i\times \mathit{IR}\times {\mathit{ABS}}_g\times \mathit{EF}\times \mathit{ED}}{\mathit{BW}\times \mathit{AT}}$$ (1)

$${\mathrm{CDI}}_{\mathrm{der}}=\frac{C_i\times \mathit{SA}\times K_p\times {\mathit{ABS}}_d\times \mathit{ET}\times \mathit{EF}\times \mathit{ED}\times \mathit{CF}}{\mathit{BW}\times \mathit{AT}}$$ (2)

CDI_total = CDI_ing + CDI_der (3)

Where the CDI_ing and CDI_der are the exposure rates from ingestion and dermal absorption mg/kg/day respectively, and C_i - is the mean level of n^th heavy metals in tap water (mg/L). More explanations, values, and the units for other parameters are shown in Table 2. The gastrointestinal absorption factors were 0.014 for Fe, 0.3 for Cu, 0.025 for Cr, 0.05 for Cd, and 0.3 for Pb [43], [42].

Table 2.

Parameters description for health risk assessment in tap water samples.

Parameter	Description	Value for adult	Unit	References
Ci	Metal concentration		mg/L
IR	Ingestion rate	1.92	L/day	Qu et al. [42]
EF	Exposure frequency	365	days/year	Emmanuel et al. [26]
ED	Exposure duration	70	years	Korea et al. [40]
SA	Exposure skin area	16,000	cm2	Qu et al. [42]
BW	Body weight	70	kg	Emmanuel et al. [26]
AT	Average time	25,550	day	Korea et al. [40]
Kp	Permeability coefficient	0.001	cm/h	Qu et al. [42]
ET	Exposure Time	0.273	h/day	Qu et al. [42]
ABSd	Dermal absorption factor	0.001		Qu et al. [42]
CF	Conversion Factor	0.001	L/cm3	Eziz et al. [41]
ABSg	Gastrointestinal absorption factor

Human health risk was categorized into carcinogenic and non-carcinogenic risks by the International Agency for Research on Cancer (IARC) through hazard Quotients (HQ) and carcinogenic risk (CR), respectively [41], [42]. Target hazard quotient (THQ) helps to assess the health risk values from heavy metals in tap water. It is the ratio of chronic daily dose of metals and the oral reference dose of each metal. The non-carcinogenic health risk from heavy metals calculated using the following Eqs. (4) and (5) [44], [45], [42].

$${\mathrm{THQ}}_{\mathrm{in}}=\frac{{\mathit{CDI}}_{\mathit{in}}}{{\mathit{RfD}}_{\mathit{in}}}$$ (4)

$${\mathrm{THQ}}_{\mathrm{der}}=\frac{{\mathit{CDI}}_{\mathit{der}}}{{\mathit{RfD}}_{\mathit{der}}}$$ (5)

Where THQ–target hazard quotient, CDI–chronic daily intake (mg/kg/day) and RfD-oral reference dose of each metal (mg/kg/day). The oral reference doses for Fe, Cu, Pb, Cr, and Cd were 7 × 10^–1, 4 × 10^–2, 3.5 × 10^–3, 3 × 10^–3, and 1 × 10^–3 mg/kg/day; and the dermal reference doses were 4.5 × 10^–2, 1.2 × 10^–2, 5.25 × 10^–4, 6 × 10^–5, and 5 × 10^–6 mg/kg/day, respectively [41], [31], [45], [42].

Non-carcinogenic potential risk to human health through exposure to a multiple of potential toxic metal was assessed by hazard index (HI). To estimate the potential human health risk through more than one heavy metal, a hazard index has been developed. The hazard index is expressed as the sum of the hazard quotients as described using the following formula [46], [44], [31], [45].

$$\mathrm{HI}={\sum }_{i=1}^{5}THQ,{\mathrm{THQ}}_{\mathrm{Fe}}+{\mathrm{THQ}}_{\mathrm{Cu}}+{\mathrm{THQ}}_{\mathrm{Pb}}+{\mathrm{THQ}}_{\mathrm{Cr}}+{\mathrm{THQ}}_{\mathrm{Cd}}$$ (6)

HI_total = THQ_ing + THQ_der (7)

When HI < 1, the exposed individual will not have the non-carcinogenic health risks from heavy metals in tap water. On the contrary, HI > 1 indicates a potential non-carcinogenic health risks [47], [41], [44], [31].

Cancer risk was described in terms of incremental lifetime cancer risk (ILCR), which is the probability that one may develop cancer over 70 year lifetime due to a 24 h exposure to a potential carcinogen [26]. The carcinogenic health risk from the potential toxic heavy metals in tap water was calculated in terms of incremental lifetime cancer risk (ILCR) using Eq. (8) [46].

ILCR = CDI x CSF (8)

Where CDI-is chronic daily intake (mg/kg/day), CSF-is cancer slope factor of hazardous substance. The CSF values (per mg/kg/day) of Cr, Pb and Cd were 0.5, 0.0085, and 0.38, respectively [46], [48]. The cumulative cancer risk, as a result of exposure to multiple carcinogenic potentially toxic trace metals, due to drinking of tap water can be calculated from Eq. (9).

$$\mathrm{TILCR}={\sum }_1^3\mathit{ILCR},{\mathrm{ILCR}}_{\mathrm{Cr}}+{\mathrm{ILCR}}_{\mathrm{Cd}}+{\mathrm{ILCR}}_{\mathrm{Pb}}$$ (9)

The acceptable cancer risk values for the regulatory purpose is assumed to be in the range between 1 × 10^–6 – 1 × 10^–4 [46], [31].

3. Statistical analysis

The average levels of metals and quality attributes in tap water were calculated and expressed as (mean$\pm$SD). The measured values of all data were statistically evaluated using one-way ANOVA (SPSS, version 26 software). Statistical analysis was employed to test significant differences existed between samples at level of significance (p $<$ 0.05) for physicochemical quality parameters and the level of heavy metals in tap water. Pearson correlation was used to identify the inter-relationship between quality parameters and metal levels. Multivariate statistical technique including principal component analysis (PCA) and hierarchical cluster analysis (HCA) were used to analyze the variation of the dataset between sample components.

4. Results and discussions

4.1. Analysis of physicochemical quality parameters

The physicochemical properties of tap water were presented in Table 3. The average values of pH were ranged from 7.8–8.28 which confirmed that the tap water in the studied areas were slightly alkaline. The normal range of pH for tap water is 6.5–8.5 [11]. According to the results (Table 3), the mean pH values was within the permissible limit. The highest pH value was recoreded in the AZ3 (8.27) whereas the lowest value was estimated in the AZ1 (7.8). Rahman et al. [11] recorded similar pH value of surface water in the range (7.48–8.09) with this study, but slightly lower values of pH was calculated in Ethiopia by [14] (6.8–7.33). The average electrical conductivities (EC) of the studied tap water samples were arranged in decreasing order AZ3 > AZ2 > CL > PS3 > PS1 > SHD > MR > AR > AZ1 > PS2. The highest electrical conductivity was calculated in AZ3 (481 μs/cm) whereas the lowest value was found in PS2 (280 μs/cm). Rahman et al. [11] in Bangladesh reported the highest mean EC values in the range from (973–1335.74) μs/cm than this study. Fikadu [14] Conducted EC values in the range (253.18–793.5) μs/cm, which was in agreement with this study. The EC values were within the range of acceptable limits reported by [11] in tap water (700 ms/cm).

Table 3.

Mean values of physicochemical parameters in tap water (mean±SD, n = 3).

Sample	DO (mg/L)	Salinity (mg/L)	pH	EC (μs/cm)	TDS (mg/L)	T (℃)	Turbidity (NTU)	Alkalinity (mg/L)
AZ1	8.68 ± 0.22a	0.28 ± 0.06a	7.8 ± 0.1a	314 ± 0.8a	270 ± 5a	25.4 ± 0.3a	8 ± 1.74a	245 ± 6a
AZ2	14.01 ± 0.65b	0.23 ± 0.06b	8.08 ± 0.18b	465 ± 6b	232 ± 5b	26.1 ± 0.3b	7 ± 1b	240 ± 16b
AZ3	14.39 ± 0.16c	0.23 ± 0.03b	8.27 ± 0.16c	481c	240.2 ± 4.6c	25.4 ± 0.1a	8 ± 2a	240 ± 2b
PS1	14.01 ± 0.65b	0.18 ± 0.06c	8.10 ± 0.2d	366d	183.1 ± 0.6d	25.2 ± 0.1c	ND	210 ± 3c
PS2	28.69 ± 0.37d	0.16 ± 0.04d	8.0 ± 0.21e	280 ± 5e	118 ± 1e	24.6 ± 0.5d	ND	220 ± 5d
PS3	34.98 ± 0.78e	0.18 ± 0.05c	8.2 ± 0.3 f	366 ± 0.5 f	182.7 ± 0.6 f	24e	ND	215 ± 5e
AR	8.69 ± 0.21a	0.17 ± 0.05e	8.3 ± 0.1 g	345 ± 2 g	173.2 ± 0.3 g	27.1 ± 0.5 f	6 ± 1c	175 ± 5 f
SHD	19.43 ± 0.68 f	0.17 ± 0.01e	8.2 ± 0.4 f	361 ± 0.06 h	180.5 ± 0.1 h	25.2 ± 0.05c	ND	195 ± 7 g
MR	11.85 ± 1.75 g	0.16 ± 0.01d	7.8 ± 0.3 g	356 ± 1i	177.3 ± 1.1i	26.67 ± 0.16 g	ND	198 ± 6 h
CL	8.09 ± 0.02i	0.21 ± 0.05e	7.83 ± 0.13a	438 ± 0.63j	219 ± 2j	24.28 ± 0.29 h	ND	200 ± 9i
Sample		Sulfite (mg/L)	Sulfate (mg/L)	Phosphate (mg/L)	Nitrate (mg/L)	Nitrite (mg/L)
AZ1		10 ± 1a	3.167 ± 1.102a	0.04 ± 0.02a	0.06 ± 0.01a	5.633 ± 1.896a
AZ2		9 ± 1b	2.033 ± 0.757b	0.043 ± 0.058b	0.05 ± 0.001b	5.16 ± 1.47b
AZ3		9.2 ± 0.5c	3.1 ± 1.0a	0.048 ± 0.003c	0.06 ± 0.01a	5.153 ± 3.238c
PS1		9.433 ± 1.447d	1.107 ± 0.287c	0.033 ± 0.017d	0.05 ± 0.01b	4.787 ± 1.662d
PS2		10.367 ± 1.686e	1.26 ± 0.07d	0.031 ± 0.009d	0.05 ± 0.02b	4.903 ± 0.580e
PS3		9.567 ± 1.762 f	1.083 ± 0.294c	0.033 ± 0.012d	0.04 ± 0.02c	5.32 ± 1.77 f
AR		7.9 ± 0.8 g	2.05 ± 0.33b	0.063 ± 0.019e	0.06 ± 0.01a	6.01 ± 1.68 g
SHD		9.067 ± 1.387 h	2.233 ± 0.569e	0.021 ± 0.009 f	0.05 ± 0.03b	5.34 ± 1.76 h
MR		9.467 ± 1.601d	2.107 ± 0.655 f	0.04 ± 0.01a	0.05 ± 0.02b	6.03 ± 2.35 g
CL		8.073 ± 0.403i	2.153 ± 0.501 g	0.024 ± 0.014 g	0.05 ± 0.02b	5.92 ± 0.72i

The mean values with different superscript letters in the same column indicates significant difference (p $<$ 0.05). EC= electrical conductivity, TDS = total dissolved solid, T = temperature, AZ1 = Azezo1, AZ2 = Azezo2, AZ3 = Azezo3, PS1 = Piazza1, PS2 = Piazza2, PS3 = Piazza3, AR = Arada, SHD = Shewa Dabo, MR = Maraki and CL= College.

The values of dissolved oxygen (DO, mg/L) in tap water were AZ1 (8.68), AZ2 (14.01), AZ3 (14.39), PS1 (14.01), PS2 (28.69), PS3 (34.98), AR (8.69), SHD (19.43), MR (11.85), and CL (8.09). It was found that value in PS3 contained the highest DO level (34.98 mg/L), while the lowest value was found in CL (8.09) Table 3. The maximum limit for DO prescribed by (WHO, 2017a, 2017b; DOE, 1997; DPHE, 2019) was 6 mg/L, which is suitable for drinking [34], [11]. Ashraful Flura et al. [34], [11] in Bangladesh reported lower level of DO than this study. The mean temperature of tap water in the studied areas were found between (24–27.8) $℃$ (Table 3). According to the standards of the Department of Environment (DOE, 1997), the Department of Public Health Engineering (DPHE, 2019), (WHO, 2017a), and the (USEPA, 2012) for values (20–30$℃)$, these values were acceptable for aquatic life and household activities [11]. Therefore, this study values were with the acceptable range and safe for drinking and other purposes.

Table 4.

The concentration of potentially toxic heavy metals in drinking water in Gondar subcity.

	Level of metals (mean±SD, mg/L)
Samples	Fe	Cu	Pb	Cr	Cd
AZ1	4 ± 0.306a	0.619 ± 0.009a	0.432 ± 0.011a	0.364 ± 0.026a	0.035 ± 0.01a
AZ2	0.107 ± 0.015b	0.575 ± 0.068b	0.162 ± 0.019b	1.273 ± 0.078b	0.633 ± 0.081b
AZ3	0.644 ± 0.04c	0.708 ± 0.069c	0.15 ± 0.01c	1.212 ± 0.032c	2.857 ± 0.174c
PS1	2 ± 0.076d	0.752 ± 0.051d	0.401 ± 0.03d	0.306 ± 0.032d	4.286 ± 0.065d
PS2	0.077 ± 0.009e	0.525 ± 0.033e	0.140 ± 0.018e	0.364 ± 0.032a	4.286 ± 0.043d
PS3	1.00 ± 0.032 f	0.575 ± 0.012b	0.703 ± 0.022 f	0.261 ± 0.004e	0.093 ± 0.006e
AR	5 ± 0.051 g	0.664 ± 0.009 f	0.42 ± 0.006 g	2.182 ± 0.086 f	0.07 ± 0.013 f
SHD	0.144 ± 0.028 h	0.475 ± 0.01 g	0.411 ± 0.011d	1.243 ± 0.016 g	ND
MR	0.087 ± 0.011e	0.609 ± 0.006 h	0.155 ± 0.01c	1.261 ± 0.017 g	1.429 ± 0.05 g
CL	0.03 ± 0.004i	0.504 ± 0.028i	0.160 ± 0.005b	0.354 ± 0.01 h	0.113 ± 0.016 h

Values with different superscript letters in the same column are significant at p < 0.05 level (Tukey multiple comparison test). ND = not detected.

The mean turbidity values of tap water studied in different areas of Gondar city found in AZ1, AZ2, AZ3, and AR, were 8, 7, 8, and 6 NTU, respectively. The turbidity values were below the acceptable limits (10 NTU) prescribed by (DOE 1997), (DPHE 2019), and (USEPA 2012) Table 3 [11]. The previous reports in Ethiopia [14] (0.03–21.02 NTU) and in Pakistan [49] (3.68–10.5 NTU) were in agreement with this findings. However, the reported values in Bangladesh was higher than this study (28.19–37.83) NTU by [11]. For this study, the TDS values were ranged from 118 mg/L–270 mg/L which were within WHO standards (600 mg/L) [11] (Table 3). Comparatively, the outcome was in accordance with values in Bangladesh [34], but lower than in Nigeria [32] and Pakistan [49]. The alkalinity and salinity values in this study were observed in the range (175–245) mg/L and (0.16–0.28) mg/L, respectively. The alkalinity in tap water were in agreement with the prescribed limits (20–200) mg/L, and the reports in Cameroon [50] and Nigeria [32]. The mean salinity values were highly greater than the recommended safe limits in tap water 1 × 10 ^{– 7} mg/L and the over concentration of salinity is equivalent with the report by [32].

The levels of sulfate, nitrate, nitrite, phosphate and sulfite in tap water (mg/L) were calculated in the range 1.07–30.167, 0.04–0.07, 4.787–6.44, 0.021–0.069, and 7.9–10.367, respectively. The highest levels of phosphate, sulfite, sulfate, nitrate and nitrite were examined in AR (0.063 mg/L), PS2 (10.367 mg/L), AZ1 (3.167 mg/L), AZ1, AZ3 and AR (0.06 mg/L) and MR (6.03 mg/L) while the lowest levels were determined in SHD (0.021 mg/L), AR (7.9 mg/L), PS3 (1.083 mg/L), PS3 (0.04 mg/L), and PS1 (4.787), respectively. The concentration of sulfate was found within the maximum permissible limit of WHO (250 mg/L) [34]. The effects of nitrate and nitrite in human are very complex and WHO recommended maximum health based guideline of 50 mg/L for nitrates and 3 mg/L for nitrite [51]. Therefore, the level of nitrate were below the limit whereas nitrites was above the maximum limit.

4.2. Concentration of metals in tap water

The mean level of metals in tap water samples were displayed in Table 4. The heavy metal contents were considerably varied for studied locations except between PS2–MR for Fe, AZ2–PS3 for Cu, PS1–SHD, AZ3–MR and AZ2–CL for Pb, AZ1–PS2 and SHD–MR for Cr, and PS1– PS2 for Cd (P > 0.05). The highest content of metals in tap water recorded in AR (5 mg/L), AZ1 (4 mg/L), and PS1(2 mg/L) for Fe, PS1 (4.286 mg/L), PS2 (4.286 mg/L), and AZ3 (2.857 mg/L) for Cd, whereas the lowest average level of metals examined were observed in CL (0.03 mg/L) for Fe, AZ1 (0.035 mg/L), AR (0.07 mg/L), PS3 (0.093 mg/L) for Cd. The overall concentrations of heavy metals in Gondar city tap water were in the decreasing order: AR $>$ PS1 > PS2 > AZ1 > AZ3 > MR > AZ2 > SHD > PS3 > CL. The distribution pattern of metals were described in the order: Cd > Fe > Cr > Cu > Pb.

The primary anthropogenic sources of Fe pollutions are urban wasts/sewage [46]. In different water sources containing Fe, the concentrations ranged from (0.03–5) mg/L, in which most of the values were greater than the permissible WHO limit (0.3 mg/L) [52]. In particular, the level of Fe in AR (5 mg/L), and AZ1 (4 mg/L) were recorded the highest among all studied sample locations. According to the findings (Table 4), the average concentration of Fe in Gondar city were lower than the reported values for tap water from Ethiopia [53], [46], Albania (A. [54]) and Nigeria [52]. The presence of excess Fe in the body causes aesthetic and health effects, hemochromatosis and liver cirrhosis [46].

The concentrations of Cu in tap water were found in the range (0.575–0.752) mg/L and 2–3 times lower than the reports in Kenya [21], 17–27 times greater than in China [41], 2–27 times greater than in South Africa [36], but equivalent with other study in Pakistan [31]. In this study, the level of Cu was below the maximum permissible limit (2 mg/L) prescribed by WHO [21], which indicates safe for drinking containing Cu in Gondar city. Comparatively, the mean level of Cu in tap water follows the order: PS1 > AZ3 > AR > AZ1 > MR > AZ2 = PS3 > PS2 > CL > SHD.

The level of Pb in tap water showed slight variations from (0.162–0.703) mg/L in different areas of Gondar city. For the present study, Pb in water sample were above the WHO recommended limits of 0.01 mg/L [36]. The findings of our study for Pb levels in water were greater than in China [42], Albania (A. [54]), Ethiopia [46], Kenya [21], South Africa [36], but in agreement with Ethiopia conducted by [53]. According to the earlier studies, one of the main sources of Pb in tap water is typically from the leaded pipes inclosing Pb [36]. Due to high toxicity and non-essential properties, there is the possibility of adverse health effects by Pb for consumers of the studied tap water.

For this finding, the amount of Cr (mg/L) from all areas were AZ1 (0.364), AZ2 (1.273), AZ3 (1.212), PS1 (0.306), PS2 (0.364), PS3 (0.261), AR (2.182), SHD (1.243), MR (1.261) and CL (0.354). The highest value was in AR (2.182 mg/L), while the lowest level was recorded in PS3 (0.261 mg/L). In comparison with (WHO, 2017) standards, the levels of Cr in tap water in Gondar city exceeds the maximum safe limits (0.05 mg/L) for drinking [42]. Different studies suggested that the presence of Cr in tap water may either be from natural or anthropogenic sources and the main pollution sources can be paints, construction remnants, deposition of household and municipal wastes, and construction activities [37], [46], [36]. Comparative study with the preceding reports showed that the values of Cr in Albania [54], and India [45] were lower than the present study, but in accordance with the studies in Ethiopia [37], [30]. The levels of Cr from other study in Ethiopia [55] was greater than this study.

The contents of Cd in studied tap water samples were greater than the maximum allowable levels (MAL) provided by WHO and USEPA which had been set at 0.005 mg/L [17]. The average values of Cd analyzed in Gondar sub cities were ranged from 0.035–4.286 mg/L Table 4, which demonstrated highly greater than the recommended limits (WHO and USEPA). The average level of Cd detected in PS1 (4.286 mg/L) and PS2 (4.286 mg/L) were the highest followed by AZ3 (2.857 mg/L) and MR (1.429 mg/L). Cadmium’s mobility in tap water depends on several factors including the pH and the availability of organic matter [56]. The detected concentration of Cd in the present study were found highly greater than the previous studies reported by [37], [30], [26], [41], but in agreement with results reported by [42]. The levels and distributions of trace metals in tap water were potentially influenced by the physicochemical properties, such as DO, EC, pH, salinity and turbidity [37]. One of the limitation of our study was lack of comprehensive analysis including mercury (Hg) and arsenic (As) because this metals are highly toxic to induce threats to human health through chronic exposure.

4.3. Human health risk assessment in tap water

4.3.1. Non-carcinogenic risk evaluation

The chronic daily intake (CDI) values for the studied metals were displayed in Table 5. For this finding, except for Pb in PS3, and Cd in PS1, PS2 and MR, the chronic daily intake in ingestion and dermal contact of studied metals in all examined tap water were less than the recommended dietary allowance (RDA) for adults, indicating that consumption of the analyzed metals in the examined tap water in Gondar subcity may not result non-carcinogenic health implications to human. As the results depicted in Table 5, the values of CDI (mg/kg/day) for Fe, Cu, Pb, Cr and Cd were found in the range 1 × 10^–5 – 1.9 × 10^–3, 3.9 × 10^–3 – 6.1 × 10^–3, 1.2 × 10^–3 – 5.7 × 10^–3, 1.4 × 10^–4 – 1.4 × 10^–3, 4.8 × 10^–5 – 5.8 × 10^–3 for ingestion, 1.8 × 10^–9 – 3.1 × 10^–7, 2.9 × 10^–8 – 4.6 × 10^–8, 9.3 × 10^–9 – 1 × 10^–8, 1.3 × 10^–8 – 1.3 × 10^–7, and 2.1 × 10^–9 – 2.6 × 10^–7 for dermal absorption, respectively. According to the results in Table 5, the average CDI of trace elements for adults were ranked as follows: Cu > Pb > Cd > Cr > Fe for ingestion, and Cd > Cu > Cr > Pb > Fe for dermal contact. The highest chronic daily intake (mg/kg/day) for Fe, Cu, Pb, Cr, and Cd were found in AR1 (1.9 × 10^–1), PS1 (6.1 × 10^–3), PS3 (5.7 ×10^–3), AR1 (1.4 × 10^–3), and PS2 (5.8 × 10^–3) for ingestion, and AR1 (3.1 × 10^–7), PS1 (4.6 × 10^–8), AZ1 and AR1 (2.6 × 10^–8), AR1 (1.3 × 10^–7), and PS1 and PS2 (2.6 × 10^–7) for dermal absorptions, respectively.

Table 5.

Chronic daily intake of metals in tap water samples studied in Gondar sub cities.

	Chronic daily intake (mg/kg/day)
Sample	Parameter	Fe	Cu	Pb	Cr	Cd
AZ1	CDIing	1.5 × 10–3	5 × 10–3	3.5 × 10–3	2.4 × 10–4	4.8 × 10–5
	CDIder	2.4 × 10–7	3.8 × 10–8	2.6 × 10–8	2.2 × 10–8	2.1 × 10–9
AZ2	CDIing	4.1 × 10–5	4.7 × 10–3	1.3 × 10–3	8.7 × 10–4	8.6 × 10–4
	CDIder	6.6 × 10–9	3.5 × 10–8	1 × 10–8	7.9 × 10–8	3.9 × 10–8
AZ3	CDIing	2.4 × 10–4	5.8 × 10–3	1.2 × 10–3	1.4 × 10–4	3.9 × 10–3
	CDIder	4 × 10–8	4.4 × 10–8	9.3 × 10–9	1.3 × 10–8	1.7 × 10–7
PS1	CDIing	7.6 × 10–4	6.1 × 10–3	3.2 × 10–3	2 × 10–4	5.8 × 10–3
	CDIder	1.2 × 10–7	4.6 × 10–8	2.5 × 10–8	1.9 × 10–8	2.6 × 10–7
PS2	CDIing	2.9 × 10–5	4.3 × 10–3	1.3 × 10–3	2.4 × 10–4	5.8 × 10–3
	CDIder	4.8 × 10–9	3.2 × 10–8	1 × 10–8	2.2 × 10–8	2.6 × 10–7
PS3	CDIing	3.8 × 10–4	4.7 × 10–3	5.7 × 10–3	1.7 × 10–4	1.2 × 0–4
	CDIder	6.2 × 10–8	3.5 × 10–8	4.3 × 110–3	1.6 × 10–8	5.8 × 10–9
AR1	CDIing	1.9 × 10–3	5.4 × 10–3	3.5 × 10–3	1.4 × 10–3	9.6 × 10–5
	CDIder	3.1 × 10–7	4.1 × 10–8	2.6 × 10–8	1.3 × 10–7	4.3 × 10–9
SHD	CDIing	5.5 × 10–5	3.9 × 10–3	3.3 × 10–3	1.6 × 10–4	ND
	CDIder	8.9 × 10–9	2.9 × 10–8	2.5 × 10–8	1.5 × 10–8	ND
MR	CDIing	3.3 × 10–5	5 × 10–3	1.2 × 10–3	1.7 × 10–4	1.9 × 10–3
	CDIder	5.4 × 10–9	3.8 × 10–8	9.6 × 10–9	1.6 × 10–8	8.9 × 10–8
CL	CDIing	1 × 10–5	4.1 × 10–3	1.3 × 10–3	2.4 × 10–4	1.5 × 10–4
	CDIder	1.8 × 10–9	3.1 × 10–8	9.9 × 10–9	2.2 × 10–8	7 × 10–9

As shown in Table 6, the values of THQ for the exposure routs via ingestion was greater than the skin contact, indicated that the ingestion is a predominant route of trace metals exposure affecting human health. The calculated value of THQ for Fe, Cu, Pb, Cr, and Cd consumption through ingestion and dermal absorption were ranged from 1.6 × 10^–5 (CL) to 2.7 × 10^–3 (AR), 9.7 × 10^–2 (SHD) to 1.4 × 10^–1 (AZ3), 3.5 × 10^–1 (AZ3) to 1.6 (PS3), 4.8 × 10^–2 (AZ3) to 4.9 × 10^–1 (AR), 4.8 × 10^–2 (AZ1) to 5.8 (PS1 and PS2) for ingestion, 4 × 10^–8 (CL) to 6.9 × 10^–6 (AR), 2.4 × 10^–6 (SHD) to 3.9 × 10^–6 (PS1), 1.7 × 10^–5 (AZ3) to 8.3 × 10^–5 (PS3), 2.2 × 10^–4 (AZ3) to 1.3 × 10^–3 (AZ2), and 4.3 × 10^–4 (AZ1) to 5.3 × 10^–2 (PS2) for dermal contact, respectively. The average most THQ values of heavy metals from the consumption of tap water were less than the acceptable limit (1), but the values of THQ in AZ1, PS3, and AR for Pb, AZ3, PS1, PS2, and MR for Cd were $>$ 1, revealed that it may pose a non-carcinogenic health risk to the population in these areas. The HI values in different areas were arranged in descending order: PS1 > PS2 > AZ3 > MR > PS3 > AR > AZ2 > AZ1 > SHD > CL. Except the value in CL, the HI values of heavy metals in the present study were greater than the maximum recommended limit (1) for adults. Non-carcinogenic risk related to HI values was classified as negligible (HI < 0.1), low risk (0.1$\le$ HI < 1), medium (1 ≤ HI < 4) and high (HI $\ge$ 4) [57], [8]. According to the results Table 6 for adults, HI values were categorized as low risk for CL sample, medium for AZ1, AZ2, PS3, AR, SHD and MR samples while high risk was observed in samples from AZ3, PS1, and PS2. Therefore, a diet containing these metals can affect human health through the combined influence and special attention must be paid to this metals.

Table 6.

Target hazard quotient (THQ) and hazard index (HI) of drinking water samples.

	Target hazard quotient (THQ)						HI
Sample	Parameter	Fe	Cu	Pb	Cr	Cd
AZ1	THQing	2.1 × 10–3	1.2 × 10–1	1	8.3 × 10–2	4.8 × 10–2	1.25
	THQder	5.5 × 10–6	3.2 × 10–6	5.1 × 10–5	3.7 × 10–4	4.3 × 10–4
AZ2	THQing	5.8 × 10–5	1.1 × 10–1	3.8 × 10–1	2.9 × 10–1	8.6 × 10–1	1.64
	THQder	1.4 × 10–7	2.9 × 10–6	1.9 × 10–5	1.3 × 10–3	7.8 × 10–3
AZ3	THQing	3.5 × 10–4	1.4 × 10–1	3.5 × 10–1	4.8 × 10–2	3.9	4.47
	THQder	8.9 × 10–7	3.6 × 10–6	1.7 × 10–5	2.2 × 10–4	3.5 × 10–2
PS1	THQing	1 × 10–3	1.5 × 10–1	9.4 × 10–1	6.9 × 10–2	5.8	7.01
	THQder	2.7 × 10–6	3.9 × 10–6	4.7 × 10–5	3.1 × 10–4	5.3 × 10–2
PS2	THQing	4.2 × 10–5	1 × 10–1	3.8 × 10–1	8.3 × 10–2	5.8	6.42
	THQder	1 × 10–7	2.7 × 10–6	1.9 × 10–5	3.7 × 10–4	5.3 × 10–2
PS3	THQing	5.4 × 10–4	1.1 × 10–1	1.6	5.9 × 10–2	1.2 × 10–1	1.8
	THQder	1.3 × 10–6	2.9 × 10–6	8.3 × 10–5	2.7 × 10–4	1.1 × 10–3
AR	THQing	2.7 × 10–3	1.3 × 10–1	1	4.9 × 10–1	9.6 × 10–2	1.71
	THQder	6.9 × 10–6	3.4 × 10–6	5.1 × 10–5	2.2 × 10–3	8.7 × 10–4
SHD	THQing	7.8 × 10–5	9.7 × 10–2	9.6 × 10–1	5.5 × 10–2	ND	1.11
	THQder	1.9 × 10–7	2.4 × 10–6	4.8 × 10–5	2.5 × 10–4	ND
MR	THQing	4.7 × 10–5	1.2 × 10–1	3.6 × 10–1	5.9 × 10–2	1.9	2.45
	THQder	1.2 × 10–7	3.1 × 10–6	1.8 × 10–5	2.7 × 10–4	1.7 × 10–2
CL	THQing	1.6 × 10–5	1 × 10–1	3.7 × 10–1	8 × 10–2	1.5 × 10–1	0.7
	THQder	4 × 10–8	2.6 × 10–6	1.9 × 10–5	3.6 × 10– 4	4 × 10–3

4.3.2. Carcinogenic risk assessment

The incremental lifetime cancer risk due to Pb, Cr, and Cd levels in tap water in both routs (ingestion and dermal absorption) for adults were calculated in this study. According to the finding in Table 7, the values of ILCR for Pb, Cr, and Cd intake for adults were displayed in the range between 1 × 10^–5 – 8.5 × 10^–5, 7 × 10^–5 – 7 × 10^–4, and 5.7 × 10^–5 – 2.2 × 10^–3, respectively, as well as the summation of ILCR were described between 1 × 10^–4 – 2.3 × 10^–3. According to New York State Department of Health (NYSDOH, 2007) the TCR categories are described as, if TCR ≤ 10⁻⁶ = very Low; 10^–6 – 10^–4 = low, 10^–4 – 10⁻³ moderate; 10⁻³ – 10⁻¹ = high; ≥ 10⁻¹ = very high [48], [58]. The present study indicated that ILCR and TILCR values of Pb, Cr, and most values of Cd in tap water were found between 10^–6 – 10^–4 which was described as low and be negligible for carcinogenic risks (Table 7). However, the values of ILCR and TILCR in AZ3, PS1, and PS2 for Cd were estimated in the range 10^–4 – 10^–3, categorized as moderate for carcinogenic risks. The finding of the present study confirmed that no significant carcinogenic health risks for adults via ingestion and skin contact exposure pathways in Gondar city, Ethiopia.

Table 7.

Carcinogenic health risk of tap water in different locations.

	ILCR			TILCR	Acceptable limit
Sample	Pb	Cr	Cd		(10–6 – 10–4)
AZ1	2.9 × 10–5	1.2 × 10–4	1.8 × 10–5	1.67 × 10–4	≤ 10–6 – 10–4
AZ2	1.1 × 10–5	4.3 × 10–4	3.2 × 10–4	7.61 × 10–4	≤ 10–6 – 10–4
AZ3	1 × 10–5	7 × 10–5	1.4 × 10–3	1.48 × 10–3	> 10–6 – 10–4
PS1	2.7 × 10–5	1 × 10–4	2.2 × 10–3	2.3 × 10–3	> 10–6 – 10–4
PS2	1.1 × 10–5	1.2 × 10–4	2.2 × 10–3	2.3 × 10–3	> 10–6 – 10–4
PS3	8.5 × 10–5	8.5 × 10–5	4.5 × 10–5	2.1 × 10–4	≤ 10–6 – 10–4
AR	2.9 × 10–5	7 × 10–4	3.6 × 210–5	7.65 × 10–4	≤ 10–6 – 10–4
SHD	2.8 × 10–5	8 × 10–5	ND	1 × 10–4	≤ 10–6 – 10–4
MR	1 × 10–5	8.5 × 10–5	7.2 × 10–4	8.1 × 10–4	≤ 10–6 – 10–4
CL	1.1 × 10–5	1.2 × 10–4	5.7 × 10–5	1.8 × 10–4	≤ 10–6 – 10–4

4.4. Multivariate statistical analysis

4.4.1. Correlation analysis

Correlation analysis is a statistical technique employed in water quality study, contributing valuable insights into how various parameters interact and impact the chemical constituents of tap water. The correlation matrix represents the relationship among several parameters. It is developed based on the correlation coefficient, which ranges from – 1–1 [59], [60]. For this study, the data sets were subjected to correlation analysis in order to describe the relationship within trace metals and physicochemical quality parameters in the form of a mathematical language to understand the origin of the chosen quality testing and heavy metals. Table 8, showed the correlations for the selected physicochemical attributes and heavy metal levels in water samples in Gondar subcity. According to [61], strong, moderate, and weak correlations are considered as those with correlation coefficients of r > 0.7, 0.5 < r < 0.7 and r < 0.5, respectively. Significantly strong positive correlations were observed between salinity with TDS (r = 0.92), turbidity (r = 0.74), alkalinity (r = 0.75), sulfate (r = 0.71), TDS with sulfate (r = 0.75), temperature with phosphate (r = 0.73), Cr (r = 0.83), turbidity with sulfate (r = 0.71), phosphate (r = 0.7), nitrate (r = 0.75), and sulfate with nitrate (r = 0.76). Comparatively, moderate positive correlations were found between DO with sulfite (r = 0.53), EC with TDS (r = 0.55), TDS with turbidity (r = 0.69), alkalinity (r = 0.58), temperature with nitrate (r = 0.58), alkalinity with sulfite (r = 0.58), phosphate with nitrate (r = 0.62), Fe (r = 0.64), Cu (r = 0.61), Cr (r = 0.68), and nitrate with Fe (r = 0.59). These strong and moderate positive correlation indicated that the results of the correlation matrix for metals, physicochemical parameters, and relevant ions found in the tap water of Gondar city resultant from the same source most likely human activities [59].

Table 8.

Pearson correlation matrix of physicochemical and trace metal levels in tap water.

	DO	SLT	pH	EC	TDS	T°	TBT	AKT	Sulfite	Sulfate	PPH	Nitrate	Nitrite	Fe	Cu	Pb	Cr	Cd
DO	1
Salinity	−0.42	1
pH	−0.09	0.29	1
EC	−0.29	0.35	0.48	1
TDS	−0.54	0.92	0.28	0.55	1
T°	−0.59	−0.07	0.23	0.02	0.07	1
Turbidity	−0.45	0.74	0.38	0.34	0.69	0.44	1
Alkalinity	0.097	0.75	0.40	0.27	0.58	−0.27	0.53	1
Sulfite	0.53	0.08	−0.09	−0.49	−0.16	−0.31	−0.12	0.58	1
Sulfate	−0.62	0.71	0.02	0.32	0.75	0.32	0.71	0.36	−0.14	1
Phosphate	−0.36	0.14	0.16	0.10	0.17	0.73	0.70	−0.03	−0.29	0.29	1
Nitrate	−0.7	0.47	−0.11	0.05	0.43	0.58	0.75	0.13	−0.20	0.76	0.62	1
Nitrite	−0.52	0.013	−0.21	−0.02	0.18	0.43	0.07	−0.49	−0.55	0.38	0.28	0.24	1
Fe	−0.38	0.25	−0.23	−0.36	0.21	0.42	0.49	−0.16	−0.20	0.21	0.64	0.59	0.29	1
Cu	−0.3	0.16	−0.10	0.15	0.22	0.38	0.39	0.15	0.04	0.07	0.61	0.42	−0.19	0.49	1
Pb	0.4	−0.06	−0.28	−0.34	−0.02	−0.24	−0.12	−0.18	0.05	−0.29	−0.02	−0.30	−0.02	0.47	0.09	1
Cr	−0.39	−0.19	0.21	0.20	−0.03	0.83	0.41	−0.41	−0.56	0.32	0.68	0.47	0.42	0.28	0.15	−0.17	1
Cd	0.21	−0.27	−0.15	−0.14	−0.42	−0.13	−0.19	0.21	0.49	−0.35	−0.06	0.01	−0.69	−0.23	0.44	−0.37	−0.29	1

SLT = Salinity, TBT = Turbidity, AKT = Alkalinity, PPH = Phosphate, DO = Dissolved oxygen, EC = Electrical conductivity, TDS = Total dissolved solids, and T° = Temperature.

4.4.2. Principal component analysis (PCA)

Principal component analysis (PCA) is the most important multivariate analysis method which controls the dynamics of several parameters observed for a system having aimed to reduce the dimensionality of the data by providing the useful information in small components. PCs with high eigenvalues were considered to capture the most significant variations amongst diverse heavy metals and physicochemical parameters [62], [60]. The PCA results of tap water samples were illustrated in Fig. 2, Fig. 3 using scree plot and Biplot, respectively. The scree plot shown in Fig. 2 is the way of identifying a number of useful factors, wherein, a sharp break in sizes of eigenvalues which results in a change in the slope of the plot from steep to shallow could be observed. The slope of the plot changes from steep to shallow after the six factors. The eigenvalues also drop below 1, when we move factor 7 to factor 10. This suggests that a six component solution could be the right choice which includes the total variance of 92.88 %.

Fig. 2.

A Scree plot showing the number of extracted principal components in water quality parameters.

Fig. 3.

Principal component of Biplot for metal levels and physicochemical quality parameters. PS1, PS2, AZ1 and AR in the Biplot indicated the occurrence of outlier’s in these areas.

The PCA extracted six principal components with eigenvalues describing 92.88 % of the total variance (Table 9). The first principal component (PC1) comprised of high loadings for sulfate, phosphate, nitrate, and turbidity with 33.9 % of total variance. The second principal component (PC2) were characterized by salinity, TDS, and alkalinity with 19.9 % of total variance, the third principal component (PC3) categorized by the loadings of Cu and Cd with 13.7 % total variance, the forth Principal component (PC4) governs with the metals including Pb and Fe with total variance of 11.6 %, the fifth principal component (PC5) accounted for 7.9 % of the total variance with positive loading of only pH, and the sixth principal component (PC6) captures 5.88 % of the total variance, indicating positive loading of only sulfite (Table 9). It was observed that turbidity, alkalinity, Cu, Pb, pH and sulfite has major influence for PC1, PC2, PC3, PC4, PC5, and PC6, respectively. High positive loadings in all PCs indicated that these metals and physicochemical parameters are likely influenced by factors such as natural composition of the earth’s crust, industrial emissions, phosphorus fertilizers, presence of uncontrolled landfills contribute to the leaching of these metals and other parameters into the tap water bodies. The overuse of chemical fertilizers, improper waste disposal, and manure can introduce Cu into the soil, which consequently polluting the tap water [63], [60]. According to the finding (Table 9 and Fig. 3), it can be recognized that the stronger positive loadings in each PCs for tap water quality parameters and heavy metals reflecting their contamination origin might be from the same source.

Table 9.

Principal component analysis of physicochemical quality parameters and trace metal levels in tap water.

Parameter	PC1	PC2	PC3	PC4	PC5	PC6
DO	−0.319	0.068	0.087	0.057	0.306	0.21
Salinity	0.246	0.473	−0.055	0.225	−0.012	0.005
pH	0.096	0.184	−0.188	−0.332	0.467	0.273
EC	0.154	0.181	−0.308	−0.296	0.195	−0.449
TDS	0.281	0.394	−0.163	0.196	0.033	−0.176
Temperature	0.268	−0.257	0.123	−0.228	0.043	0.254
Turbidity	0.56	0.174	0.117	0.011	0.168	0.163
Alkalinity	0.067	0.51	0.099	−0.004	0.065	0.168
Sulfite	−0.179	0.275	0.315	0.073	−0.119	0.417
Sulfate	0.391	0.142	−0.109	0.107	−0.311	0.138
Phosphate	0.489	−0.153	0.271	−0.1	0.257	0.07
Nitrate	0.436	−0.008	0.207	0.005	−0.304	0.051
Nitrite	0.181	−0.298	−0.277	0.201	−0.187	0.084
Fe	0.219	−0.174	0.313	0.358	0.126	−0.035
Cu	0.165	0.017	0.448	−0.085	0.123	−0.476
Pb	−0.084	−0.096	0.104	0.514	0.449	−0.121
Cr	0.242	−0.306	−0.03	−0.249	0.16	0.208
Cd	−0.143	0.12	0.424	−0.357	−0.227	−0.188
Eigenvalue	6.105	3.589	2.458	2.08	1.417	1.058
Variance (%)	33.9	19.9	13.7	11.6	7.9	5.88
Cumulative (%)	33.9	53.8	67.5	79.1	87	92.88

4.4.3. Hierarchical cluster analysis (HCA)

The main purpose of hierarchical cluster analysis is to identify groups of similar sample points and group them together. When applied to a set of variables, cluster analysis orders and categorizes the variables into groups that are as identical as possible based on their correlations [43]. To validate the PCA analysis, HCA was applied to group quality indices and metals into correlated classes within a variable space. For this study, samples were classified using hierarchical clustering of average linkages (between groups), a dendrogram of six clusters for physicochemical parameters and metals concentrations were drawn. According to the results (Fig. 4), cluster one (C1) contained Cd and subclusters of (DO and sulfite), C2 accounted only Pb, C3 comprising alkalinity and further linked with subclusters of (salinity, and TDS), turbidity further conjugated with subclusters of (sulfate and nitrate), C4 characterized by EC and pH, C5 contained subclusters of Fe and Cu and further connected with phosphate, Cr and temperature, and C6 characterized only by nitrite. It was perceived that C3 and C5 were the largest subgroup containing most of the physicochemical parameters. The results indicated that the physicochemical parameters and metal levels found in tap water in Gondar city are highly ordinated with each other (Fig. 4). For this study, joined clusters relatively implying a likely common source of pollution while the long distance cluster showed that this grouping might have a different or separate sources. HCA is therefore a good approach for identification of pollution distribution among different groups [64]. The linkage of Cu and Fe with Cr and phosphate depicted that these metals might be co-mobilized through agricultural runoff, industrial discharges, improper waste disposal and landfill leachate.

Fig. 4.

Dendrogram of hierarchical cluster analysis for metal concentrations and physicochemical quality parameters.

5. Conclusion

In the present study, physicochemical quality attributes, the pollution status of heavy metals, carcinogenic and non-carcinogenic human health risks were evaluated for inhabitants of Gondar city, Ehtiopia. The findings of this study indicated that the physicochemical properties of tap water in the studied areas were varied and most quality indices revealed a good fit for drinking. The average concentration of heavy metals in the studied areas decreased in the order AR $>$ AZ1 > PS1 > AZ3 > PS2 > MR > PS3 > SHD > AZ2 > CL. By comparing the results of this study with WHO/FAO, the levels of heavy metals were above the allowable limits for tap water except for Cu. Although the values of THQ $<$ 1 for most metals, the non-carcinogenic risk (HI) of metals fell above the recommended limit (1), signifying that it may pose non-carcinogenic risk from these heavy metals in tap water. The carcinogenic risk assessment values indicated there is no significant health hazards for adults through ingestion and skin contact exposure. This finding offers the status of pollution of tap water in Gondar city in terms of quality characteristics and toxic metal levels, which provides the decision makers and policy designers to improve future policies with respect to adjust and applied the water resources in Gondar city, Ethiopia.

CRediT authorship contribution statement

Molla Tefera: Investigation, Formal analysis, Writing – review & editing, Validation. Habtamu Aderajew: Methodology, Validation, Formal analysis, Data curation. Dessie Ezez: Methodology, Conceptualization, Formal analysis, Writing – original draft. Mamo Dikamu: Methodology, Validation, Resources. Worku Lakew: Supervision, Formal analysis, Validation.

Funding

This research did not receive any specific grant from funding agencies in the public, commercial, or not-for-profit sectors.

Declaration of Competing Interest

The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

Handling Editor: L.H. Lash

Data availability

Data will be made available on request.