This study investigated groundwater pollution and potential human health risks from arsenic, iron, and manganese in the rural area of Jashore, Bangladesh. Study results show that the mean value of groundwater pH is 7.25 ± 0.31, with a mean conductivity of 633.94 ± 327.41 μs/cm, while about 73, 97, and 91% of groundwater samples exceeded the Bangladesh drinking water standard limits for As, Fe, and Mn, respectively. Groundwater pollution evaluation indices, including the heavy metal pollution index, the heavy metal evaluation index, the degree of contamination, and the Nemerow pollution index, show that approximately 97, 82, 100, and 100% of samples are in the high degree of pollution category, respectively. Spatial distribution exhibited that the study area is highly exposed to As (73%), Fe (82%), and Mn (46%). In the case of non-carcinogenic health risk via oral exposure, about 94% of samples suggest a high category of risk for infants, and 97% of samples are found to be at high risk for children and adults. The carcinogenic risk of arsenic via an oral exposure pathway suggests that approximately 97% of the samples are found to be at high risk for infants, and all of the samples are at high risk for both adults and children.

  • Shallow groundwater samples were collected from the rural area, Jashore, Bangladesh.

  • The study area is highly exposed to As (73%), Fe (82%), and Mn (46%).

  • Pollution evaluation indices exhibit a high degree of pollution.

  • Infants, adults, and children have significant non-carcinogenic and carcinogenic health risks via oral ingestion.

  • Sensitivity analysis revealed that concentration is mainly responsible for carcinogenic risk.

Groundwater is considered a suitable option for drinking purposes in many countries around the world due to its prompt availability, easy to access, and safe from contamination (Bhuiyan et al. 2016). In Bangladesh, about 95% of rural and 70% of urban people depend on groundwater for drinking and domestic purposes (WHO & UNICEF 2017). Much attention has been paid to groundwater quality, availability, and sustainability because it not only regulates the suitability for numerous purposes but also influences human health and other developments. Anthropogenic activities (such as mining, agricultural activities, landfilling, municipal waste, and rapid urbanization and industrialization) have a significant impact on groundwater quality and typically lead to its degradation (Bhuiyan et al. 2016; Wagh et al. 2017). Additionally, groundwater quality is also significantly influenced by geological processes (e.g., weathering of bedrock, dissolution, rock water interaction, and leaching/infiltration from the soil surface) and environmental changes (Xiao et al. 2020). Groundwater quality is varied from place to place or even season to season by the influence of diverse factors such as water sources, types of soils and rocks, pH, oxidation and reduction potential, dissolved organic matter, and ion exchange capacity (Thivya et al. 2014; Rahman & Rahman 2018). Groundwater pollution by metals or metalloids, such as arsenic (As), iron (Fe), and manganese (Mn), is considered a matter of global concern due to their persistence, source availability, abundances, and potential eco-toxic character (Rahman et al. 2017). It acts as a barrier to achieving the water targets of Sustainable Development Goal (SDG goal 6.1) (Ahmed et al. 2019; Bodrud-Doza et al. 2019). Previous studies reporting common contaminants, such as As, Fe, and Mn, are the most common and naturally occurring contaminants in the groundwater of Bangladesh (Islam et al. 2019). For example, Islam et al. (2017a) found elevated levels of As (2.5–150.6 g/L), Fe (30.2–350.6 g/L), and Mn (30.1–450 g/L) in the Chapai-Nawabganj district. Rahman et al. (2017) detect a high concentration of As (5–198 g/L), Fe (0.9–25.2 mg/L), and Mn (0.1–0.48 mg/L) in the Gopalgonj district. High concentrations of As (27.19 ± 32.76 μg/L), Fe (6.82 ± 6.05 mg/L), and Mn (0.28 ± 0.23 mg/L) were also found in the Surma Basin area (Ahmed et al. 2019). According to the NDWQS survey of 2009, 42 and 80% of tube wells (n = 43) in Jashore district contain iron and manganese, respectively, above Bangladesh's drinking water standards (UNICEF Bangladesh 2011). About 53% of tube wells in the Jashore district exceeded the safe arsenic level (0.05 mg/L) (Khan et al. 2016). Through various exposure pathways like dermal contact and drinking water, long-term exposure to elevated levels of As, Fe, and Mn in drinking water might cause diverse adverse health effects such as neurological, cardiovascular, hematological, skin, kidney, and bladder cancer, Alzheimer's, hyperkeratosis, diabetes mellitus, Parkinson's, mental and neurological disorders, loss of weight, and joint pain (Islam et al. 2017b; Bodrud-Doza et al. 2019). Several pollution evaluation indices, such as the heavy metal pollution index (HPI), heavy metal evaluation index (HEI), degree of contamination (Cd), and Nemerow's pollution index (NI), and the Environmental Protection Agency of the United States (USEPA) proposed the health risk assessment (HRA) model, are widely applied to determine the groundwater contamination level and carcinogenic and non-carcinogenic human health risk, respectively (Fallahzadeh et al. 2017; Bodrud-Doza et al. 2019). Nowadays, many researchers use multiple approaches for groundwater-induced human HRA to reduce uncertainties or even under- or over-estimate risk. In this aspect, Monte Carlo simulations are a quantitative risk analysis method to assess the probability distribution of risk (Rajasekhar et al. 2018). Inhabitants, particularly in rural areas, depend on groundwater resources. The quality of this source water is unpredictable and some areas may contain high concentrations of As, Fe, and Mn (Von Brömssem et al. 2014; Rahman et al. 2017; Ghosh et al. 2020), which is most concerning to them. Though a few pieces of work have been done in Bangladesh, unfortunately no work has been conducted in Jhikargachha, Jashore district, Bangladesh, where groundwater is mainly used for drinking, domestic, and agricultural purposes. Bearing in mind all the above concerns, the objectives of this present study are (i) to assess the concentration of As, Fe, and Mn in groundwater and (ii) to determine the groundwater pollution level by As, Fe, and Mn and their possible sources, and (iii) to appraise the human health risks associated with oral ingestion.

Study area, sample collection, and preservation

Jhikargachha Upazila, under Jashore district, is located in the southwestern part of Bangladesh and lies between 89 °00′ to 89 °07′E longitude and 22 °55′55″ to 23 °12′34″N latitude (Figure 1). The geology of this area is characterized by Pleistocene-Modhupur clay, and the thicknesses of underlying fluvial-deltaic sediments are Holocene age that made the main aquifer system (Ahmed et al. 2020). The hydrogeological state of the study area is categorized into three layers (Jakariya et al. 2003). The three lithological indices are designated as topsoil, clay, or silty clay to silt and sand, respectively. The lithological distribution is also indicated in such a way that clay-fine sand-medium sand-porous medium sand (Ahmed et al. 2020). Jhikargachha is rarely flooded and is geo-morphologically more stable, which is mainly underlain by the active Meghna floodplain. The whole of Jhikargachha Upazila is underlain by Holocene-Recent fluvial (river) sediments (GSB 1990). Jhikargachha is likely underlain by the full range of fluvial sediments (gravels, sands, silts, and clays) related to different relict features of fluvial systems such as in-filled oxbow lakes, floodplain, meander belts, and levees (Jakariya 2000). The annual average temperature ranged from 15.4 to 34.6 °C (59.7–94.3 °F) and the annual rainfall is 1,537 mm (60.5 inches) (Jakariya 2000). However, the total area of the Upazila is 308.09 km2, with a population of 271,014, and the main water bodies are the Kobadak and Betna River, while this Upazila consists of 11 unions. Agriculture (65.97%) is the main source of income in the study area. The sources of drinking water for this study area are tube wells (96.18%), tap water (0.57%), pond water (0.18%), and others (3.07%) (Banglapedia 2014).

Figure 1

Map of the study area with sampling points ((a) Bangladesh with Jashore district; (b) Jhikargachha Upazila; and (c) Sampling point in Jhikargachha Upazila).

Figure 1

Map of the study area with sampling points ((a) Bangladesh with Jashore district; (b) Jhikargachha Upazila; and (c) Sampling point in Jhikargachha Upazila).

Close modal

In the study area, tube wells were installed between the 2001 and 2015 years. The depths of the sample collected tube wells ranged between 100 and 220 ft. (30.48–67.05 m) with the median value of 154.8 ft. (47.18 m), which was recorded by the tube-well owners. Geographical locations of the selected tube wells during sampling times were collected by using a global positioning system (GPS) receiver (Kansas, USA). Groundwater samples were collected in 500 mL polystyrene bottles; the sampling bottles were washed with 1:1 HNO3 and rinsed three times with distilled water. Before sampling, the tube wells were pumped for 15–20 min, and then water samples were collected in a pre-cleaned sampling bottle after being three times rinsed with sample water. For the measurement of As, Fe, and Mn in groundwater, samples were filtered (0.45 μm filters, cellulose nitrate, Millipore) into polypropylene tubes using a plastic syringe (BD Plastipak, 100 mL) for dissolved metal concentrations, then samples were acidified with concentrated HNO3 (69%, Sigma-Aldrich, Germany) to make the water (pH < 2), and samples were labeled, kept in a cooler box, shifted to our laboratory, and then kept in a freezer at 4 °C until further analysis (APHA 2012).

Pollution evaluation indices

In this present study, HPI, HEI, Cd, and NI were applied to evaluate the groundwater quality. The HPI is used to evaluate the quality of water corresponding with heavy metals. This indexing is developed based on the weighted arithmetic method, where weights (Wi) are between 0 and 1, indicating the relative significance of every metal, and can be defined as inversely proportional to the recommended standard (Si) for each metal (Mohan et al. 1996). The following Equations (1)–(2) are used to calculate these indexes.
formula
(1)
where Wi and Qi are the unite weight and sub-index value of heavy metal of the ith parameter, respectively, and n is the number of studied heavy metals.
formula
(2)
where Mi, Ii, and Si are the measured, ideal, and standard values of heavy metal in the ith parameter, respectively. The sign (−) indicates the numerical difference of the two values, ignoring the algebraic sign. In this present study, the standard permissible value (Si) and ideal value (Ii) were adopted from the WHO standard (WHO 2011). The HPI critical value for drinking water is 100; above this value, the source water is not suitable for drinking purposes.
HEI is an overall water quality monitoring index, which is developed on the basis of heavy metals concentration (Edet & Offiong 2002) and calculated using the following equation:
formula
(3)
where HC and HMAC are the measured and maximum admissible concentration (MAC) of heavy metal of the ith parameter, respectively. The HEI was categorized into following types: HEI ≤ 10, 10–20, and >20, indicating low, medium, and high pollution, respectively (Edet & Offiong 2002; Bodrud-Doza et al. 2016).
Cd shows the inclusive effects of every pollutant on the source water quality (Backman et al. 1997) and calculated by using the following equations:
formula
(4)
formula
(5)
where Cfi is the contamination factor, and CAi and CNi are the measured and upper permissible limits of heavy metals in the ith parameter, respectively. N denotes the ‘normative value’ and in this study, CNi is taken as MAC. This index is classified into three categories, such as Cd < 1, (1–3), and >3, indicating a low, medium, and high Cd, respectively (Edet & Offiong 2002).
The NI is used to measure how diverse heavy metals pollute groundwater at the sampling points of the study area (Zhong et al. 2015) and is calculated using the following equation:
formula
(6)

The NI is divided into six types such as ≤0.5, 0.5–0.7, 0.7–1.0, 1.0–2.0, 2.0–3.0, and >3.0, indicating no, clean, warm, polluted, medium polluted, and severe polluted, respectively (Zhong et al. 2015).

Human HRA

The HRA was classified as carcinogenic or non-carcinogenic based on the quantification of risk level for metal or metalloid exposure. In this study, the chronic daily intake (CDI), hazard quotient (HQ), hazard index (HI), and carcinogenic risk (CR) were calculated using the USEPA standards to determine the ingestion rate of contaminants in a human body via oral ingestion of drinking water.

Hazard quotient

HQ is used to measure the non-CR due to the exposure of non-carcinogenic contaminants. Based on the USEPA toxicants division, Fe and Mn are considered non-carcinogenic contaminants. HQ is calculated by using the following equation:
formula
(7)
RfD (mg/kg/day) refers to the reference dose (0.7 mg/kg/day for Fe (USEPA 2006), 0.14 mg/kg/day for Mn, and 0.0003 mg/kg/day for As (WHO 1984)). CDI is the chronic daily intake (mg/kg/day) (USEPA 1989) and is calculated by using the following equation:
formula
(8)
where C is the concentration of heavy metals (mg/L); IR is the drinking water ingestion rate in L/day (3.53 L/day for adults (Milton et al. 2006), 1.0 L/day for children (USEPA 1989), and 0.25 L/day for infants (Brindha et al. 2016)); ED is the exposure duration in years (70 years for adults and 6 years for children (USEPA 1989) and 1 year for infants (Brindha et al. 2016)); EF is the exposure frequency in days/year (365 days for adults, children, and infants (USEPA 1989)); BW is the average body weight in kg (50 kg for adults, 15 kg for children, and 6.9 kg for infant (USEPA 1989; NIPORT 2013)); and AT is the averaging time (AT = 365 × ED(d)).

Hazard index

HI is defined as the summation of HQ of studied parameters and calculated by the following equation:
formula
(9)

According to HQ values, HQ < 1 and HQ > 1 indicate no and significant non-carcinogenic health effects, respectively. HI < 1 indicates no or lowers adverse non-cancer health risk and HI > 1 indicates significant adverse non-cancer health risk. The chronic risk (HQ or HI) is divided into following types: negligible (<0.1), low (≥0.1 < 1), medium (≥1 < 4), and high (≥4), respectively (USEPA 1999).

Carcinogenic risk

CR helps to estimate the probability of developing any type of cancer for an individual over the lifetime by exposing to carcinogenic elements (USEPA 1989). CR is estimated by multiplying CDI and slope factor (SF) of cancer created heavy metals, as presented in the following equation:
formula
(10)
where SF is the slope factor of contaminants (mg/kg/day) (1.5 mg/kg/day for As) (USEPA 1989).

CR is categorized into five types: very low (<1E-06); low (>1E-06 to <1E-05); medium (>1E-05 to <1E-04); high (>1E-04 to <1E-03); and very high (>1E-03), respectively (USEPA 1999). This study also used the sensitivity analysis technique to determine which factor is most responsible for cancer risk from the other input factors. This assessment was conducted using the Monte Carlo simulation technique using the software Crystal Ball version 11.1.2.3 created by Oracle Co. (Oracle® Crystal Ball software version 11.1.2.3) (Fallahzadeh et al. 2017). Monte Carlo is a USEPA-proposed methodical HRA process that uses recurrent samples from probability distributions for every exposure parameter. The inputs for the health risk parameters are arsenic concentration (C), body weight (BW), AT, total exposure duration (ED), EF, and ingestion water rate (IR). Exposure duration, risk coefficients, and average time were considered constants. Similar approaches were also carried out by other researchers (Rajasekhar et al. 2018; Ramesh et al. 2021).

Chemical analysis and quality assurance

Collected water samples were subjected to both field (pH, electrical conductivity (EC)) and laboratory analysis (As, Fe, and Mn). The field analyses were measured with calibrated portable instruments. The water sample pH was measured by a pH meter (Model: MARTINI instruments, pH 56 pHWP, USA). EC and total dissolved solids (TDS) were measured by using a Conductivity Meter (HACH Sension-156; multi-parameter, USA). The pH meter was initially calibrated with three buffer solutions at pH 4.0, 7.0, and 10.0, and then the pH meter was verified after measuring three samples. For EC and TDS determination, the multi-meter was calibrated by using 1,000 μS/cm EC and 1,000 mg/L TDS standard solutions and verified after three measurements. For water sample digestion, 50 mL of acid-mixed water sample was taken in a beaker; 10 mL of concentrated HNO3 acid solution was applied and heated to a hot plate for digestion (Rizwan et al. 2021). After cooling, volume was adjusted to the desired level with deionized water (DIW) passing through the Whatman no. 41 filter paper. The concentration of As, Fe, and Mn in the water samples was analyzed by using a Hydride Generator and an air-acetylene flame atomic absorption spectrophotometer (AAS) system (model: AA-7000, Shimadzu, Japan) and equipped with a single-element hollow-cathode lamp as a light source at the wavelength of 193.7, 248.3, and 279.5 nm, respectively. The concentration limit of detection for As was 0.0003 mg/L, while for Fe and Mn, it was 0.01–0.004 mg/L. The instrument calibration was done by using different concentrations of working solution from the standard solution (1,000 ppm), obtained from Sigma-Aldrich, Switzerland. The analysis results of water samples were expressed as mg/L. Deionized ultrapure water was utilized for the whole experimental work. All laboratory equipment and glassware were cleaned (i.e., used 20% HNO3 acid for cleaning purposes and frequently washed with double distilled water and oven-dried) before use. The analytical procedure was checked using a certified reference material (Reference # 7502-a, white rice powder, National Metrology Institute of Japan) and a certified reference material for metals and metalloids (Supplementary Material, Table S1). For quality assurance, every sample was made to run duplicate analyses, including blank and validated. Based on the necessity, water samples were diluted several times, and the relative standard deviations of detected major ions and elements were within ±5–7%.

Statistical analysis

In this study, Pearson's correlation matrix (PCM) and the principal component analysis (PCA) were used to evaluate the analytical data through SPSS (V.20) and Microsoft Excel 2010. The PCA was applied to identify the probable sources of studied parameters based on their concentration (R-mode) and sampling points (Q-mode). The PCA was conducted by the varimax rotation method, which reduced the variable number as well as increased the loading rate of each component; as a result, it facilitated the explanation of the PCA results. The ArcGIS (V.10.5) software was applied to the spatial distribution of As, Fe, and Mn through the inverse distance weighting (IDW) method.

Concentration of physicochemical parameters in groundwater

The concentrations of physicochemical parameters (pH, EC, TDS, As, Fe, and Mn) in groundwater samples are presented in Table 1. The pH values of the groundwater samples ranged from 6.80 to 7.90, with a mean value of 7.25 ± 0.31 (Table 1). The concentration of EC in the water sampled varied from 350.00 to 2,090.00 μs/cm, with an average value of 633.93 ± 327.41 μs/cm. On the other hand, TDS concentration in the study area water samples was 405.72 ± 209.54 mg/L, ranging from 224.00 to 1,337.6 mg/L. According to EC and TDS classification, the majority of the groundwater samples are in the freshwater category. The concentration of As, Fe, and Mn in groundwater samples followed the order Fe > As > Mn, respectively (Table 1).

Table 1

Summary of physicochemical properties of groundwater samples (n = 33)

ParametersMinimumMaximumMean ± SDaWHO (2011) bBDWS (1997) c% sample exceed (WHO 2011)% sample exceed (BDWS 1997)
pH 6.80 7.90 7.25 ± 0.31 6.5–8.5 6.5–8.5 – – 
EC (μs/cm) 350.00 2,090.00 633.94 ± 327.41 750 2,000 21 
TDS (mg/L) 224.00 1,337.6 405.72 ± 209.54 1,000 1,000 
As (mg/L) 0.013 0.501 0.090 ± 0.082 0.01 0.05 97 73 
Fe (mg/L) 0.30 7.81 3.68 ± 1.72 0.3 0.3–1.0 97 97 
Mn (mg/L) 0.02 0.63 0.38 ± 0.19 0.4 0.1 45 91 
ParametersMinimumMaximumMean ± SDaWHO (2011) bBDWS (1997) c% sample exceed (WHO 2011)% sample exceed (BDWS 1997)
pH 6.80 7.90 7.25 ± 0.31 6.5–8.5 6.5–8.5 – – 
EC (μs/cm) 350.00 2,090.00 633.94 ± 327.41 750 2,000 21 
TDS (mg/L) 224.00 1,337.6 405.72 ± 209.54 1,000 1,000 
As (mg/L) 0.013 0.501 0.090 ± 0.082 0.01 0.05 97 73 
Fe (mg/L) 0.30 7.81 3.68 ± 1.72 0.3 0.3–1.0 97 97 
Mn (mg/L) 0.02 0.63 0.38 ± 0.19 0.4 0.1 45 91 

aStandard deviation.

bWorld Health Organization.

cBangladesh Drinking Water Standard.

The measured concentrations of As ranged from 0.013 to 0.501 mg/L, with a mean value of 0.090 ± 0.082 mg/L (Table 1). According to the study results, about 97 and 73% of groundwater samples exceeded the WHO (0.01 mg/L) and Bangladesh Drinking Water Standard (BDWS) (0.05 mg/L) limits, respectively, whereas the mean concentration of As was 9 and 1.8 times higher than the WHO (0.01 mg/L) and BDWS (0.05 mg/L) limits. In the Jashore district, about 53% of surveyed tube-well water contains more than 50 μg/L of arsenic (Khan et al. 2016). The concentrations of Fe in groundwater samples varied from 0.30 to 7.81 mg/L, with an average concentration of 3.68 ± 1.72 mg/L (Table 1). The average value of iron in the study area groundwater was about 12 and 3.68 times higher than the WHO (0.3 mg/L) and the higher limit of BDWS (0.3–1.0 mg/L) limits. About 97% of the groundwater samples exceeded both the BDWS and WHO permissible limits. Tanabe et al. (2001) found elevated levels of iron (3.9–10.5 mg/L) in the small village of Jashore district, Bangladesh. The Mn concentration in groundwater samples ranged from 0.02 to 0.63 mg/L, with an average value of 0.38 ± 0.19 mg/L (Table 1). Approximately 45 and 91% of groundwater samples exceeded the WHO (0.4 mg/L) and BDWS (0.1 mg/L) limits, respectively. The mean value of Mn was 3.8 and 1.3 times higher than the BDWS (0.1 mg/L) and WHO health guidelines (0.4 mg/L), respectively. Elevated level of manganese (0.016–2.108 mg/L) was previously reported from the Jashore district, Bangladesh (Ghosh et al. 2020).

Groundwater pollution evaluation indices

In this study, As, Fe, and Mn concentrations were used to calculate groundwater pollution evaluation indices, and the results are shown in Table 2, where WHO recommended standards were used for all index evaluations. HPI values varied from 18.76 to 1,629.33, with an average value of 683.98 ± 399.32 (Table 2), suggesting that source water except S20 is highly polluted by As, Fe, and Mn.

Table 2

Analysis results of groundwater pollution evaluation indices

Sample IDHPIaCategoryHEIbCategoryCdcCategoryNIdCategory
S1 1,003.84 Polluted 7.35 Low 4.35 High 4.69 Severe 
S2 655.58 Polluted 35.05 High 32.05 High 19.16 Severe 
S3 476.67 Polluted 6.56 Low 3.56 High 3.73 Severe 
S4 428.14 Polluted 40.58 High 37.58 High 21.67 Severe 
S5 1,629.33 Polluted 56.39 High 53.39 High 30.64 Severe 
S6 510.10 Polluted 29.94 High 26.94 High 14.51 Severe 
S7 262.01 Polluted 23.05 High 20.05 High 10.04 Severe 
S8 603.11 Polluted 38.68 High 35.68 High 21.86 Severe 
S9 329.26 Polluted 34.59 High 31.59 High 17.05 Severe 
S10 296.76 Polluted 27.13 High 24.13 High 12.81 Severe 
S11 1,471.78 Polluted 30.27 High 27.27 High 19.42 Severe 
S12 684.24 Polluted 26.40 High 23.40 High 13.53 Severe 
S13 172.67 Polluted 30.26 High 27.26 High 13.46 Severe 
S14 613.12 Polluted 27.65 High 24.65 High 14.52 Severe 
S15 201.11 Polluted 15.53 Medium 12.53 High 7.46 Severe 
S16 384.99 Polluted 26.71 High 23.71 High 12.47 Severe 
S17 1,065.78 Polluted 40.04 High 37.04 High 23.67 Severe 
S18 872.91 Polluted 24.92 High 21.92 High 13.71 Severe 
S19 775.97 Polluted 41.29 High 38.29 High 23.48 Severe 
S20 18.76 Unpolluted 18.77 Medium 15.77 High 9.47 Severe 
S21 1,083.11 Polluted 31.37 High 28.37 High 19.39 Severe 
S22 1,447.11 Polluted 32.28 High 29.28 High 20.75 Severe 
S23 1,077.21 Polluted 28.34 High 25.34 High 17.46 Severe 
S24 916.44 Polluted 26.60 High 23.60 High 15.57 Severe 
S25 1,098.69 Polluted 24.62 High 21.62 High 15.88 Severe 
S26 603.48 Polluted 24.69 High 21.69 High 12.64 Severe 
S27 677.11 Polluted 24.48 High 21.48 High 11.46 Severe 
S28 236.89 Polluted 16.99 Medium 13.99 High 7.86 Severe 
S29 710.17 Polluted 23.42 High 20.42 High 12.32 Severe 
S30 291.97 Polluted 30.42 High 27.42 High 14.36 Severe 
S31 750.69 Polluted 10.74 Medium 7.74 High 5.07 Severe 
S32 322.67 Polluted 32.63 High 29.63 High 14.78 Severe 
S33 899.58 Polluted 32.36 High 29.36 High 18.51 Severe 
Minimum 18.76 Unpolluted 6.56 Low 3.56 High 3.73 Severe 
Maximum 1,629.33 Polluted 56.39 High 53.39 High 30.64 Severe 
Mean ± SD 683.98 ± 399.32 Polluted 27.88 ± 10.04 High 24.88 ± 10.04 High 14.95 ± 5.95 Severe 
Sample IDHPIaCategoryHEIbCategoryCdcCategoryNIdCategory
S1 1,003.84 Polluted 7.35 Low 4.35 High 4.69 Severe 
S2 655.58 Polluted 35.05 High 32.05 High 19.16 Severe 
S3 476.67 Polluted 6.56 Low 3.56 High 3.73 Severe 
S4 428.14 Polluted 40.58 High 37.58 High 21.67 Severe 
S5 1,629.33 Polluted 56.39 High 53.39 High 30.64 Severe 
S6 510.10 Polluted 29.94 High 26.94 High 14.51 Severe 
S7 262.01 Polluted 23.05 High 20.05 High 10.04 Severe 
S8 603.11 Polluted 38.68 High 35.68 High 21.86 Severe 
S9 329.26 Polluted 34.59 High 31.59 High 17.05 Severe 
S10 296.76 Polluted 27.13 High 24.13 High 12.81 Severe 
S11 1,471.78 Polluted 30.27 High 27.27 High 19.42 Severe 
S12 684.24 Polluted 26.40 High 23.40 High 13.53 Severe 
S13 172.67 Polluted 30.26 High 27.26 High 13.46 Severe 
S14 613.12 Polluted 27.65 High 24.65 High 14.52 Severe 
S15 201.11 Polluted 15.53 Medium 12.53 High 7.46 Severe 
S16 384.99 Polluted 26.71 High 23.71 High 12.47 Severe 
S17 1,065.78 Polluted 40.04 High 37.04 High 23.67 Severe 
S18 872.91 Polluted 24.92 High 21.92 High 13.71 Severe 
S19 775.97 Polluted 41.29 High 38.29 High 23.48 Severe 
S20 18.76 Unpolluted 18.77 Medium 15.77 High 9.47 Severe 
S21 1,083.11 Polluted 31.37 High 28.37 High 19.39 Severe 
S22 1,447.11 Polluted 32.28 High 29.28 High 20.75 Severe 
S23 1,077.21 Polluted 28.34 High 25.34 High 17.46 Severe 
S24 916.44 Polluted 26.60 High 23.60 High 15.57 Severe 
S25 1,098.69 Polluted 24.62 High 21.62 High 15.88 Severe 
S26 603.48 Polluted 24.69 High 21.69 High 12.64 Severe 
S27 677.11 Polluted 24.48 High 21.48 High 11.46 Severe 
S28 236.89 Polluted 16.99 Medium 13.99 High 7.86 Severe 
S29 710.17 Polluted 23.42 High 20.42 High 12.32 Severe 
S30 291.97 Polluted 30.42 High 27.42 High 14.36 Severe 
S31 750.69 Polluted 10.74 Medium 7.74 High 5.07 Severe 
S32 322.67 Polluted 32.63 High 29.63 High 14.78 Severe 
S33 899.58 Polluted 32.36 High 29.36 High 18.51 Severe 
Minimum 18.76 Unpolluted 6.56 Low 3.56 High 3.73 Severe 
Maximum 1,629.33 Polluted 56.39 High 53.39 High 30.64 Severe 
Mean ± SD 683.98 ± 399.32 Polluted 27.88 ± 10.04 High 24.88 ± 10.04 High 14.95 ± 5.95 Severe 

aHeavy metal pollution index.

bHeavy metal evaluation index.

cDegree of contamination.

dNemerow's pollution index.

The HEI values ranged from 6.56 to 56.39, with a mean value of 27.88 ± 10.04 (Table 2). According to the HEI classification, about 6, 12, and 83% of samples were in low, medium, and high pollution levels, respectively. However, the Cd was applied to measure the intensity of metal pollution in the sampling sites. The results of Cd varied from 3.56 to 53.39, with a mean value of 24.88 ± 10.04. Based on the categories of Cd, all sampling sites fall into a high Cd category. Furthermore, NI was used to identify how diverse heavy metals contaminate the groundwater (Zhong et al. 2015) in the sampling sites of the study area. The range and mean values of NI were 3.73–30.64 and 14.95 ± 5.95, indicating that all sampling sites exhibited a severe level of contamination. In this study, PCM was performed between the concentration of As, Fe, and Mn and pollution indices (HPI, HEI, Cd, and NI) to determine the key parameters responsible for computing pollution indices. This analysis indicates that As and Fe show a significant correlation with all the indices, suggesting that these metals are the prime contributory metals.

Additionally, HPI, HEI, Cd, and NI values represent similar results for almost all of the sampling points (Table 2), and a significant correlation was also found among the pollution indices (HPI, HEI, Cd, and NI) (Table 3). Furthermore, Ficklin et al. (1992), modified by Caboi et al. (1999), methods were used for assessing water classification. Figure 2 displays the relationship between metal loads computed as (As + Fe + Mn) mg/L and pH for the analyzed water samples. All water samples fall into the field of near-neutral-high metals, suggesting this source of water is not suitable for drinking and domestic purposes.

Table 3

Correlation analysis of physicochemical parameters with pollution evaluation indices

pHECTDSAsFeMnHPIHEICdNI
pH          
EC 0.237         
TDS 0.237        
As −0.029 −0.114 −0.114       
Fe −0.366 −0.323 −0.323 0.501*      
Mn −0.074 −0.002 −0.002 −0.071 −0.016     
HPI −0.126 −0.179 −0.179 0.524* 0.606* 0.779    
HEI −0.343 −0.297 −0.297 0.569* 0.934* 0.312 0.341   
Cd −0.343 −0.297 −0.297 0.569* 0.934* 0.312 0.341 1*  
NI −0.366 −0.289 −0.289 0.543* 0.986* 0.071 0.543* 0.958* 0.958* 
pHECTDSAsFeMnHPIHEICdNI
pH          
EC 0.237         
TDS 0.237        
As −0.029 −0.114 −0.114       
Fe −0.366 −0.323 −0.323 0.501*      
Mn −0.074 −0.002 −0.002 −0.071 −0.016     
HPI −0.126 −0.179 −0.179 0.524* 0.606* 0.779    
HEI −0.343 −0.297 −0.297 0.569* 0.934* 0.312 0.341   
Cd −0.343 −0.297 −0.297 0.569* 0.934* 0.312 0.341 1*  
NI −0.366 −0.289 −0.289 0.543* 0.986* 0.071 0.543* 0.958* 0.958* 

*Correlation is significant at the 0.01 level (two-tailed).

**(Bold values) Correlation is significant at the 0.01 level (2-tailed).

Figure 2

Scatter diagram of the concentrations of the metals vs. pH.

Figure 2

Scatter diagram of the concentrations of the metals vs. pH.

Close modal

Spatial distribution of arsenic, iron, and manganese

Figure 3 presents the spatial distribution of As, Fe, and Mn in the groundwater samples of the study area based on health-related class boundaries adopted by the WHO (2011) and Ghosh et al. (2020). For As, about 73% area of groundwater was covered by ‘high’ level of As (>0.05 mg/L), while 24% of the area was covered by ‘elevated’ level of As (0.01–0.05 mg/L) and only 3% of the study area was covered by ‘minimal’ level of As (<0.01 mg/L).

Figure 3

Spatial distribution of heavy metals in the study area ((a) As, (b) Fe, and (c) Mn).

Figure 3

Spatial distribution of heavy metals in the study area ((a) As, (b) Fe, and (c) Mn).

Close modal

However, a ‘high’ level of Fe (>2.0 mg/L) covered 82% of the groundwater area, while an ‘elevated’ level of Fe (0.3–2.0 mg/L) covered about 15% of the groundwater area and a ‘minimal’ level of Fe (0.3 mg/L) covered only 3% of the groundwater area. On the other hand, a ‘high’ level of Mn (>0.4 mg/L) was distributed over 46% of the groundwater, an ‘elevated’ level of Mn (0.1–0.4 mg/L) was distributed over 45% of the groundwater, and a ‘minimal’ level of manganese (0.1 mg/L) was distributed over only 9% of the groundwater.

Human health risk assessment

Chronic risk

In the study area, groundwater As, Fe, and Mn are the most abundant elements, so it is necessary to measure their probable health risk due to long-term consumption. This study considered only the ingestion pathway for assessing the non-carcinogenic (HQ and HI) and carcinogenic health risks of infants, children, and adults. The summarized results are presented in Supplementary Material, Tables S2–S4 and Table 4, respectively. The HQ values were decreased in the following order: As > Fe > Mn via oral ingestion routes for all groups (infants, children, and adults), respectively. This study showed that HQ values for Fe and Mn were less than one (HQ < 1) for infants, children, and adults, respectively (Supplementary Material, Tables S2–S4), suggesting that these elements could pose no or lower level of toxic impacts on these groups (infants, children, and adults) over a long period of exposure. However, the HQ values of As were larger than one (HQ > 1) in all sampling sites (Supplementary Material, Tables S2–S4), indicating that all groups (infants, children, and adults) have a significant level of health risk from drinking this source of water over a lifetime. In this study, HI was applied to evaluate the non-carcinogenic effects of As, Fe, and Mn jointly. The HI results revealed that all sampling sites (100%) exceeded the USEPA recommended value (HI > 1), owing primarily to the higher HQ value of arsenic, demonstrating that residents in this study area face a significant non-carcinogenic health risk across all age groups (infants, children, and adults) (Supplementary Material, Tables S2–S4). According to the mean values of HI, the descending order of non-carcinogenic health risk for all groups was adults > children > infants. Adults have a 2.17 times higher non-carcinogenic health risk than infants, suggesting that adults are more suspected than infants (Supplementary Material, Tables S2–S4). Due to continuous drinking of this groundwater, inhabitants in that study area might suffer from several non-carcinogenic health hazards, including vomiting, abdominal pain, diarrhea, injury to the skin, gastrointestinal and respiratory tract infections, damage to the liver, cardiovascular, hematopoietic, and nervous system problems, diabetes, reproductive problems, hair loss, and neurological problems. Khan et al. (2016) found that about 1,537 arsenicosis patients were assumed in Jashore district, while 375 arsenicosis patients were detected in Jhikargachha Upazila.

Table 4

Cancer risk of As among the infants, children and adults for oral exposure pathway

Sample IDCancer risk values for As
Chronic risk based on USEPA (1999) 
InfantsChildrenAdultsInfantsChildrenAdults
S1 2.21E-03 4.07E-03 4.31E-03 Very high Very high Very high 
S2 3.72E-03 6.85E-03 7.25E-03 Very high Very high Very high 
S3 7.07E-04 1.30E-03 1.38E-03 High Very high Very high 
S4 2.34E-03 4.30E-03 4.55E-03 Very high Very high Very high 
S5 2.72E-02 5.01E-02 5.31E-02 Very high Very high Very high 
S6 6.09E-03 1.12E-02 1.19E-02 Very high Very high Very high 
S7 2.43E-03 4.47E-03 4.73E-03 Very high Very high Very high 
S8 1.20E-03 2.20E-03 2.33E-03 Very high Very high Very high 
S9 3.67E-03 6.75E-03 7.15E-03 Very high Very high Very high 
S10 2.03E-03 3.74E-03 3.96E-03 Very high Very high Very high 
S11 8.80E-03 1.62E-02 1.72E-02 Very high Very high Very high 
S12 5.42E-03 9.97E-03 1.06E-02 Very high Very high Very high 
S13 4.01E-03 7.37E-03 7.80E-03 Very high Very high Very high 
S14 3.33E-03 6.12E-03 6.48E-03 Very high Very high Very high 
S15 1.85E-03 3.40E-03 3.60E-03 Very high Very high Very high 
S16 4.01E-03 7.37E-03 7.80E-03 Very high Very high Very high 
S17 6.74E-03 1.24E-02 1.31E-02 Very high Very high Very high 
S18 5.37E-03 9.88E-03 1.05E-02 Very high Very high Very high 
S19 4.39E-03 8.08E-03 8.56E-03 Very high Very high Very high 
S20 5.03E-03 9.26E-03 9.81E-03 Very high Very high Very high 
S21 3.75E-03 6.90E-03 7.31E-03 Very high Very high Very high 
S22 8.04E-03 1.48E-02 1.57E-02 Very high Very high Very high 
S23 3.88E-03 7.13E-03 7.55E-03 Very high Very high Very high 
S24 3.51E-03 6.46E-03 6.84E-03 Very high Very high Very high 
S25 2.03E-03 3.74E-03 3.96E-03 Very high Very high Very high 
S26 3.38E-03 6.22E-03 6.59E-03 Very high Very high Very high 
S27 8.32E-03 1.53E-02 1.62E-02 Very high Very high Very high 
S28 5.39E-03 9.91E-03 1.05E-02 Very high Very high Very high 
S29 3.86E-03 7.11E-03 7.53E-03 Very high Very high Very high 
S30 3.48E-03 6.41E-03 6.79E-03 Very high Very high Very high 
S31 2.98E-03 5.48E-03 5.80E-03 Very high Very high Very high 
S32 7.23E-03 1.33E-02 1.41E-02 Very high Very high Very high 
S33 5.10E-03 9.39E-03 9.94E-03 Very high Very high Very high 
Minimum 7.07E-04 1.30E-03 1.38E-03 High Very high Very high 
Maximum 2.72E-02 5.01E-02 5.31E-02 Very high Very high Very high 
Mean ± SD 4.89E-03 ± 4.49E-03 9.01E-03 ± 8.25E-03 9.54E-03 ± 8.74E-03 Very high Very high Very high 
Sample IDCancer risk values for As
Chronic risk based on USEPA (1999) 
InfantsChildrenAdultsInfantsChildrenAdults
S1 2.21E-03 4.07E-03 4.31E-03 Very high Very high Very high 
S2 3.72E-03 6.85E-03 7.25E-03 Very high Very high Very high 
S3 7.07E-04 1.30E-03 1.38E-03 High Very high Very high 
S4 2.34E-03 4.30E-03 4.55E-03 Very high Very high Very high 
S5 2.72E-02 5.01E-02 5.31E-02 Very high Very high Very high 
S6 6.09E-03 1.12E-02 1.19E-02 Very high Very high Very high 
S7 2.43E-03 4.47E-03 4.73E-03 Very high Very high Very high 
S8 1.20E-03 2.20E-03 2.33E-03 Very high Very high Very high 
S9 3.67E-03 6.75E-03 7.15E-03 Very high Very high Very high 
S10 2.03E-03 3.74E-03 3.96E-03 Very high Very high Very high 
S11 8.80E-03 1.62E-02 1.72E-02 Very high Very high Very high 
S12 5.42E-03 9.97E-03 1.06E-02 Very high Very high Very high 
S13 4.01E-03 7.37E-03 7.80E-03 Very high Very high Very high 
S14 3.33E-03 6.12E-03 6.48E-03 Very high Very high Very high 
S15 1.85E-03 3.40E-03 3.60E-03 Very high Very high Very high 
S16 4.01E-03 7.37E-03 7.80E-03 Very high Very high Very high 
S17 6.74E-03 1.24E-02 1.31E-02 Very high Very high Very high 
S18 5.37E-03 9.88E-03 1.05E-02 Very high Very high Very high 
S19 4.39E-03 8.08E-03 8.56E-03 Very high Very high Very high 
S20 5.03E-03 9.26E-03 9.81E-03 Very high Very high Very high 
S21 3.75E-03 6.90E-03 7.31E-03 Very high Very high Very high 
S22 8.04E-03 1.48E-02 1.57E-02 Very high Very high Very high 
S23 3.88E-03 7.13E-03 7.55E-03 Very high Very high Very high 
S24 3.51E-03 6.46E-03 6.84E-03 Very high Very high Very high 
S25 2.03E-03 3.74E-03 3.96E-03 Very high Very high Very high 
S26 3.38E-03 6.22E-03 6.59E-03 Very high Very high Very high 
S27 8.32E-03 1.53E-02 1.62E-02 Very high Very high Very high 
S28 5.39E-03 9.91E-03 1.05E-02 Very high Very high Very high 
S29 3.86E-03 7.11E-03 7.53E-03 Very high Very high Very high 
S30 3.48E-03 6.41E-03 6.79E-03 Very high Very high Very high 
S31 2.98E-03 5.48E-03 5.80E-03 Very high Very high Very high 
S32 7.23E-03 1.33E-02 1.41E-02 Very high Very high Very high 
S33 5.10E-03 9.39E-03 9.94E-03 Very high Very high Very high 
Minimum 7.07E-04 1.30E-03 1.38E-03 High Very high Very high 
Maximum 2.72E-02 5.01E-02 5.31E-02 Very high Very high Very high 
Mean ± SD 4.89E-03 ± 4.49E-03 9.01E-03 ± 8.25E-03 9.54E-03 ± 8.74E-03 Very high Very high Very high 

Carcinogenic risk assessment

The calculated results of CR for all groups (infants, children, and adults) are presented in Table 4. The mean CR values for infants, children, and adults were 4.89, 9.01, and 9.54E-03, indicating that of every 10,000 people in the study area, 4.89, 9.01, and 9.54 people would have cancer risk due to the consumption of drinking water, respectively (Table 4). The descending order of CR among the three groups was adults > children > infants. According to the mean value of CR, the adults were 1.95 times more likely than infants, showing that infants had the lowest cancer risk and adults had the highest cancer risk (Table 4).

However, this study demonstrated that the CR value for all groups (infants, children, and adults) exceeded the USEPA (2001) recommended safe ranges (1E-06 to 1E-04), suggesting that each group (infants, children, and adults) has the possibility of carcinogenicity by the consumption of this arsenic-contaminated groundwater, though this study did not mention any particular types of arsenic-associated cancer in the study area. Several authors mentioned that skin, kidney, and bladder cancers are the general types of cancer due to chronic exposure to arsenic-contaminated drinking water. This study also used the Monte Carlo simulation method to evaluate arsenic-associated cancer risk. Figure 4(a)–4(c) displays the probability of arsenic-associated cancer risk for infants, children, and adults.

Figure 4

Probability results of CR on As in the study area ((a) infants, (b) children, and (c) adults), which are calculated by the Monte Carlo simulation model based on Crystal Ball software.

Figure 4

Probability results of CR on As in the study area ((a) infants, (b) children, and (c) adults), which are calculated by the Monte Carlo simulation model based on Crystal Ball software.

Close modal

The mean probability of CR for infants, children, and adults was 4.89E-03, 9.00E-03, and 9.54E-03 (Figure 4), as well as the risks of 5 and 95%, which were found to be 3.93E-03 and 5.85E-03 for infants, 7.24E-03 and 1.08E-02 for children, and 7.67E-03 and 1.14E-02 for adults (Figure 4), respectively.

On the other hand, in case of 100% risk, it also exceeded the safe risk (1E-06) and the priority risk level (1E-04), suggesting that each group in the study area has high potential health risks from arsenic in drinking water, so special attention is required for this element.

A similar study was conducted by Islam et al. (2019) in Rangpur district, Bangladesh. A sensitivity analysis was also performed to determine the main factor, which is associated with CR evaluation (Fallahzadeh et al. 2017). In the case of infants, C, ED, EF, and IR indicated the positive effects with a percentage of 69.9, 6.6, 6.4, and 6.4%, respectively. For children, C, ED, EF, and IR indicate the positive effects with a percentage of 71.5, 5.0, 6.9, and 6.7%, respectively. Conversely, C (71.4%), ED (6.7%), EF (5.7%), and IR (6.8%) show positive effects on the CR of adults (Figure 5(a)–5(c)). Finally, sensitivity analysis results showed that the concentration of arsenic is mainly responsible for the CR.

Figure 5

Sensitivity analysis results on the CR model for As in the study area ((a) Infants; (b) children; and (c) adults).

Figure 5

Sensitivity analysis results on the CR model for As in the study area ((a) Infants; (b) children; and (c) adults).

Close modal

Sources of groundwater pollution

In the case of the PCA, PC, along with Eigenvalues >1 and loading values >0.40, considerably affects the overall quality of water sources, where positive and negative values indicate that the water quality becomes affected or unaffected by studied parameters. The three PCs were drawn out with 79.198% of cumulative variance. The factor loadings, Eigenvalues (>1), % of Variance, and cumulative % values are presented in Supplementary Material, Table S5. Additionally, R-mode and Q-mode PCA were used to explain the relationship of cluster variables, where the R-mode analysis was aligned with Q-mode (Supplementary Material, Table S5). Additionally, R-mode and Q-mode PCA were used to explain the relationship of cluster variables, where the R-mode analysis was aligned with Q-mode (Supplementary Material, Table S5). PC1 accounts for 34.543% of total variance and is primarily composed of EC and TDS (Supplementary Material, Table S5), which are significantly found in S3, S8, S16, S28, S30, and S33 (Supplementary Material, Table S5) sampling sites, reflecting the physicochemical characteristics of water quality resulting from geogenic processes that lead to salt storage in soils rather than anthropogenic activities such as agricultural practices and fertilizer use (Drever 1997). PC2 shows a total variance of 26.601% and is mostly loaded with As and Fe (Supplementary Material, Table S5). Very high loadings of these elements were found in the sampling sites S5, S11, S17, S19, S22, and S33 (Supplementary Material, Table S5). Arsenic in groundwater release from the Holocene alluvial/deltaic sediments is due to the strongly reducing nature of groundwater in the study area rather than anthropogenic sources (e.g., agrochemicals) (Jakariya et al. 2003). However, Fe is one of the abundant metals released from geogenic sources such as chemical weathering of bedrock, i.e., oxidation reaction (Rahman & Gagnon 2014), which is confirmed by the correlation between As and Fe (0.53) (Table 3). Again, PC3 exhibited 18.456% of the total variance and Mn was the dominating metal (Supplementary Material, Table S5), mostly found in the sampling sites of S11, S12, S15, S21, S22, S23, S27, S31, S32, and S33 (Supplementary Material, Table S5). Mn in groundwater comes from the leaching of parent material from the soil horizon and probably from the chemical weathering of bedrock (ATSDR 2000). Finally, the PCA results showed that geogenic sources (rock weathering and ion exchange) followed by anthropogenic activities (agrochemicals) were the main controlling factors for the groundwater quality of the study area.

This present study investigated a total of 33 groundwater samples to assess the groundwater pollution and potential health risks from arsenic, iron, and manganese in the rural area of Jashore, Bangladesh. The concentrations of As (73%), Fe (97%), and Mn (91%) exceeded Bangladesh's drinking water standard limits. According to the PCA, geogenic origins predominate over anthropogenic sources. Pollution evaluation indices (HPI, HEI, Cd, and NI) show that almost all of the samples fall into a high degree of pollution category. In the case of human health vulnerabilities, about 94% of samples for infants and 97% of samples for children and adults are found to have high non-carcinogenic health risks, whereas all groups (infants, children, and adults) are at very high carcinogenic health risks due to the consumption of arsenic-containing drinking water. Finally, this study concludes that the study area is highly contaminated with arsenic, iron, and manganese and falls into a higher health risk category for both non-carcinogenic chronic and carcinogenic health risks. This study recommends different initiatives such as formulating and implementing low-cost water treatment facilities (e.g., community-based or household level), increasing consciousness among local inhabitants, and allowing the vendor to supply safe water at a low price to overcome the health risk of local inhabitants.

The authors would like to acknowledge the Department of Environmental Science and Technology, Jashore University of Science and Technology for instrumental facility and the Ministry of Science and Technology, Bangladesh, for research grant award.

All relevant data are included in the paper or its Supplementary Information.

The authors declare there is no conflict.

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