Assessment of the Water Quality and Toxicological Effects of Toxic Metals in Selected Water Bodies around Gold Mining Areas in Ghana

Assessment of the Water Quality and Toxicological Effects of Toxic Metals in Selected Water Bodies around Gold Mining Areas in Ghana | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Article Assessment of the Water Quality and Toxicological Effects of Toxic Metals in Selected Water Bodies around Gold Mining Areas in Ghana George Yaw Hadzi, Isaac Tabiri Henneh, Joseph Kwaku Adjei, Albert Ofori, and 1 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-7381113/v1 This work is licensed under a CC BY 4.0 License Status: Under Review Version 1 posted 8 You are reading this latest preprint version Abstract The study aimed to assess the water quality and toxicological effects of some toxic metals in selected water bodies around artisanal gold mining areas in Ghana. This study investigated the toxicological effects of heavy metals and the water quality of mining-affected water bodies in five mining areas of Ghana, focusing on heavy metals such as arsenic (As), cadmium (Cd), mercury (Hg), lead (Pb), and zinc (Zn). These metals were assessed on the basis of their distribution, concentration, and human and environmental risks, alongside key physicochemical characteristics (organic matter, pH and conductivity) known to influence the interactions and dynamics of heavy metals in surface water and sediment matrices. The cation exchange capacity (CEC), which influences metal adsorption and mobility in sediment, was also explored. Forty (40) composite samples were digested and analysed for heavy metals (As, Cd, Hg, Pb, and Zn) via ICP-MS. The sediment pH ranged from 5.89 to 6.78 mg/kg, and the water pH ranged from 5.89 to 6.79. The electrical conductivity (EC) values of the sediments peaked at 1241 µS/cm. The As level in the water exceeded the WHO limit (0.01 mg/L), reaching 0.075 mg/L in Obuasi, whereas the zinc concentration peaked at 0.401 mg/L in Kenyase. The arsenic and zinc concentrations in the sediment were highest in Obuasi at 0.6 mg/kg and 0.4 mg/kg, respectively, suggesting substantial contamination and environmental risks. These findings align with broader studies on the behaviour of heavy metals in aquatic ecosystems, where adsorption‒desorption dynamics are regulated by sediment properties such as mineralogy, specific surface area, and cation exchange capacity. These interactions indicate the urgent need for targeted strategies to mitigate health and environmental risks. Physical sciences/Chemistry Earth and environmental sciences/Environmental sciences Heavy metals Water quality Sediments Contamination Human health risk Physico-chemical parameters Figures Figure 1 Figure 2 Figure 3 Figure 4 INTRODUCTION Water is an essential resource for all life and plays a critical role in sustaining biodiversity and maintaining ecological balance. However, gold mining activities, particularly artisanal and small-scale mining (galamsey), have severely compromised water quality in many countries, introducing harmful pollutants such as heavy metals into aquatic ecosystems. Current information suggests that gold mining operations seriously contaminate water supplies with heavy metals (Hadzi et al., 2018 ). These contaminants, including arsenic (As), mercury (Hg), cadmium (Cd), and lead (Pb), disrupt aquatic biodiversity, degrade water resources, and pose serious health risks through bioaccumulation in the food chain. According to Helmer et al. (1997), water pollution ranks as the second most significant environmental problem after air pollution (Doamekpor et al., 2018 ). Several studies have shown that the average global concentrations of Hg, Pb, Cd, As, and Zn in river waters exceed the permissible limits suggested by the USEPA and WHO. A study has shown that Asia, Africa, and South America have higher concentrations of these elements than Europe and North America do (Liang et al., 2023 ). In Ghana, mining areas such as Tarkwa, Obuasi, Kenyase and Kwabeng have experienced severe water pollution because of the widespread and unregulated nature of mining operations. These gold mining operations involve excavating and removing soil and sediment in search of gold deposits. These activities have contributed to widespread environmental degradation, particularly in mining areas where improper waste management and uncontrolled operations prevail. Heavy metals can enter the environment directly through anthropogenic activities such as the discharge of untreated wastewater into water bodies, excessive use of fertilisers and pesticides, and natural processes such as forest fires and volcanic activities (Doamekpor et al., 2018 ). Sediments serve as both sinks and potential sources of these metals, gradually releasing them back into the aquatic system under favourable conditions and thereby preserving the cycle of contamination. (Wiafe et al., 2022 ). In contrast to the natural enrichment of sediment by geological weathering, the presence of high amounts of trace metals in sediments located at the bottom of the water column in mining rivers can be a useful sign of pollution caused by humans through mining activities in Ghana. Despite global and national awareness of these hazards, many communities in Ghana continue to rely on polluted water for drinking, irrigation, and other essential activities, exacerbating the problem. The contamination process in aquatic environments is also governed by complex interactions between water and sediments, with adsorption‒desorption dynamics playing a key role (Miranda et al., 2021 ). The adsorption and desorption of heavy metals in aquatic environments are complex processes and are influenced by the ongoing interactions between water and sediments. Heavy metals have a low toxicity risk when adsorbed to sediments. However, changes in the surrounding environment (such as pH, concentration, and the amount of organic matter) might increase their exposure to living things and reduce the quality of the water. Factors such as pH, electrical conductivity, turbidity, and other physicochemical properties of water, as well as the mineralogy, specific surface area (SSA), and cation exchange capacity (CEC) of sediments, significantly affect these interactions (Miranda et al., 2021 ). They significantly influence the mobility, availability, and eventual bioaccumulation of these metals. The affinity of different metals for specific binding sites in sediments is determined by the ionic properties of the metal species, including the ionic radius, electronegativity, hydrolysis constant, and softness. Furthermore, nutrients such as phosphorus, nitrogen, and organic matter—all of which are frequently present in aquatic environments—impact the geochemical behaviour of heavy metals. Water and sediments can contain various nutrients, depending on their source, surrounding environment, and human activities. Nutrients commonly present in aquatic ecosystems, such as phosphorus, nitrogen, and organic matter, influence the geochemical behaviour of heavy metals, the most common nutrients found in water, including nitrogen. Nitrogen compounds, such as nitrates and nitrites, can be present in water. They can originate from agricultural runoff, wastewater discharge, or natural processes. Additionally, phosphorus and phosphorus compounds, such as phosphates, can be found in water, and they often come from agricultural runoff, sewage, and detergents. Carbon and carbon compounds, including dissolved organic carbon, can be present in water, and these compounds can originate from decaying organic matter, vegetation, and human activities (Obiri-Yeboah et al., 2021 ). Oxygen, dissolved oxygen, is an essential nutrient for aquatic organisms. It enters the water through aeration from the atmosphere, photosynthesis by aquatic plants, and turbulent mixing. Sulfur and sulfur compounds, such as sulfates, can be present in water (Obiri et al., 2016 ). Water also contains trace elements and essential elements, including iron, manganese, zinc, copper, and others. These elements are required in small quantities for biological processes but can become pollutants if present at high concentrations. However, excessive or imbalanced nutrient levels can lead to water quality issues, such as eutrophication or nutrient deficiencies (Rajaee et al., 2015 ). Heavy metals released into the environment persist in water bodies and sediments, creating long-term risks to human and environmental health. These heavy metals are highly toxic, persistent, and bioaccumulative, posing serious risks to aquatic ecosystems, human health, and the overall sustainability of mining communities. This intricate interplay not only affects aquatic life but also elevates human health risks through exposure to contaminated water, fish, and agricultural produce. Reports have indicated that water bodies in mining areas frequently exceed WHO guidelines for safe drinking water, with elevated levels of arsenic, mercury, and lead posing severe health risks (Hadzi et al., 2024 ; Hadzi et al., 2019 ). This has led to adverse health outcomes, including developmental disorders, neurological damage, and increased cancer risk in affected populations. The problem is particularly acute in Ghana, where mining communities are often located near water bodies used for drinking, irrigation, and other essential activities. Alarming cases, such as the birth of deformed infants and the prevalence of developmental and neurological disorders, underscore the urgent need for comprehensive toxicological assessments in these mining areas. Contamination, human health risks and the potential ecological risks of heavy metals are determined by employing different methods of assessment certified by international organisations and conventions. These calculated risks and indices have been applied to assess pollution and ecological risks according to the ratio of single or multiple elemental concentrations to background concentrations (Brady et al., 2015 ; Xiao et al 2021 ). Pollution assessment indices are important techniques for the comprehensive assessment of contamination in sediments and for predicting the future negative impacts of contaminants on ecosystems (Yozukmaz and Yabanlı, 2023 ; Sundaramanickam et al., 2016 ). The objective of this study was to determine the extent of heavy metal contamination in surface water around mining communities by (a) determining the concentrations and distributions of the metals in surface water and sediment and (b) evaluating the potential ecological and human health risks of the metals in these media. MATERIALS AND METHODS Research Design and the Study Area To ensure robust and accurate data collection, the relevant literature was extensively reviewed to understand best practices, methodologies, and potential challenges. The sampling sites were strategically chosen from key gold mining areas (Fig. 1 ) with historical and ongoing mining activities, which are known for high metal contamination and significant environmental impacts. These include Tarkwa, which covers the Bonsa and Nyani Rivers (Essamang); Kenyase, which covers the Tano and Subri Rivers; Obuasi, which focuses on the Nyam River; and Kwabeng, which targets the Birim River. This selection offered a broad geographic and environmental perspective on mining-related contamination. A cross-sectional sampling approach was employed. The inclusion of multiple rivers across different regions enabled a comprehensive assessment of water quality and potential contamination from mining activities. These strategic measures aimed to ensure that the study provides meaningful insights into the environmental impacts of gold mining on aquatic ecosystems and sediment quality. The map and Fig. 4 are were obtained by using ArcMap 10.5. Sample collection, storage, and preservation The sediment samples were collected from four points along each river, with each point spaced 100 m apart. The collection was performed from downstream to upstream. A Teflon-coated soil auger was used to collect sediment samples at a depth of 0–5 cm into polypropylene Zip-Loc bags. Four (4) composite sediment samples each were collected from five (5) rivers, resulting in a total of 20 sediment samples. The sediment samples collected in zip-loc bags were labelled and carefully transported to the Department of Chemistry of the University of Cape Coast for preparation and treatment. The preliminary preparations and analysis of the sediment samples were performed at the Agricultural Technology Village Laboratory of the University of Cape Coast. This approach ensured the reliability and accuracy of the data obtained from the sediment samples. The water samples were collected from four points along each river, similar to the sediment samples. Samples were taken at a depth of 0–5 cm below the surface of the rivers from downstream to upstream and were placed into well-labelled 1.5 L water sample bottles. At each point, 8 discrete samples were combined, and a small amount of nitric acid was added to prevent the samples from being denatured by microorganisms. Four (4) composite water samples were obtained from each river. Once collected, the samples were stored on ice to maintain the temperature between 2 and 4°C. Digestion and analysis of samples Water samples For total metals, 50 mL of each water sample was treated with a 1:1 mixture of concentrated hydrochloric acid (HCl) and nitric acid (HNO₃) for 2 hours and 30 minutes. After digestion, the mixture was cooled and diluted to 50 mL with deionised water. The metal concentrations in the samples were measured via a Nexion 2000P ICP-MS instrument after the instrument was tuned and calibrated. Quality control measures, including method blanks, replicates, and certified reference standards, were implemented to ensure the accuracy and precision of the results. The concentrations obtained from the ICP‒MS were expressed in mg/L. The methods employed are the US EPA 2007, APHA 3120 and USEPA 2008 methods. Sediment samples The total recoverable metals were measured via the procedure described by Brady et al. (2014). The metal levels were determined via the Aqua regia digestion and extraction method. A Teflon microwave tube that had been carefully cleaned was filled with 0.05 g of the sediment sample and extracted with 3 mL of 70% concentrated nitric acid and 1 mL of 30% concentrated hydrochloric acid. The contents were digested via a microwave and increased to 260°C from room temperature over 20 minutes. The digested samples were cooled, diluted to the 50 mL mark, and then centrifuged for 10 min. Inductively coupled plasma‒mass spectrometry (ICP-MS) was then used to analyse approximately 2 mL subsamples. The physicochemical properties of the sediment samples, including pH, electrical conductivity, and turbidity, were determined. Ten grams (10 g) of each powdered sediment sample was measured in their respective centrifuge tubes. 25 mL of deionised water was added to each centrifuge tube and shaken for 15 minutes using a mechanical shaker. The samples were then centrifuged for 10 minutes. The solution was left to settle by gravity for an hour. The supernatant was poured into a clean 50 mL beaker. The pH was measured via an EDZO T200 meter. All procedures were repeated 3 times, and average pH values were taken. An ECTestr11 meter was used to measure the electrical conductivity. Additionally, a blank sample (clear water) was measured via the HYDRO TEST HT 1000 meter to calibrate the instrument. Subsequently, 10 mL of each test water sample was prepared, and turbidity readings were recorded. Quality control measures, including method blanks, replicates, and certified reference standards, were implemented to ensure the accuracy and precision of the results. The concentrations obtained from the ICP‒MS were expressed in mg/L. The methods employed are the US EPA Method 200.7, the APHA Method 3120, and the USEPA Method 2008. Reproducibility and recovery studies Reproducibility recovery studies were conducted using standard reference materials, with the methods of packaging, storage, and conveyance carefully controlled to maintain sample integrity throughout the analytical process. The recovery study evaluated how effectively the extraction method retrieves the target analyte from the sample matrix. The performance of the ICP‒MS instrument was evaluated through a recovery study, and the percentages of the heavy metals analysed were within acceptable ranges. Spiked standards were used to evaluate the accuracy of the instrument. When known quantities of metals (standards) are added to a sample, the method’s ability to recover those known amounts reflects how well the instrument is performing. Data and Statistical Analysis The IBM SPSS Statistics Package (version 27) and the Excel Analysis ToolPak were used to analyse the study data. Using correlation analysis, relationships between the variables under consideration were examined, with a statistical significance threshold of p < 0.05. The grouping was visually summarised with a dendrogram created via hierarchical cluster analysis (HCA). To find important principal components in the data and potential loadings, principal component analysis (PCA) was computed. For the results, the Promax normalised rotation method was used to perform the PCA. A post hoc comparison test was also performed via the Tukey HSD test. Human health risk assessment The health risk of heavy metals in surface water and sediment from mining areas was estimated through ingestion and dermal contact on the basis of the USEPA risk assessment method (Hadzi et al., 2024 ). The default values from the risk integrated software for the clean-up of hazardous waste sites (RISC 4.02) were used for each toxicant. In the exposure assessment, the average daily dose (ADD) (Eq. 1) for the ingestion of heavy metals in sediment and water was calculated via the following equations from the USEPA protocols of 1989 and 2004: $$\:\text{A}\text{D}\text{D}\text{i}\text{n}\text{g}\:\:\:\:\:\:=\:\:\:\:\:\:\frac{\begin{array}{cc}Cx&\:\times\:Ir\:\times\:Ef\:\times\:Ed\times\:OAF\:\:\end{array}}{Bw\:\times\:At}\:\times\:\text{C}\text{f}\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\left(1\right)$$ where Cx is the concentration of toxicant metals in sediment and water samples (mg / kg), Ir is the ingestion rate per unit time (kg / day), Ed is the exposure duration (years), Ef is the exposure frequency (days / year), OAF Dermal/Oral Absorption factor (no unit) Bwt is the body weight of the receptor (kg), and At is the average lifetime (years), which is equal to the life expectancy of a resident of Ghana. Cf represents a unit transfer factor, which is ×10 − 6 for soil/sediment. For the conversion factor from year to day, 365 was used. In addition, ADDing is the quantity of heavy metals ingested per kilogram of body weight. In this study, surface water and sediment ingestion and dermal contact were considered the main pathways for metal risk assessment because these are the means of contact with toxic metals. The average daily dose for dermal contact was calculated via Eq. 2: $$\:\text{A}\text{D}\text{D}\text{d}\text{e}\text{r}\text{m}\:\:\:\:\:\:=\:\:\:\:\:\:\frac{\begin{array}{cc}Cx&\:\times\:Sa\:\times\:Pc\times\:Af\:\times\:Fe\times\:Ef\:\times\:Ed\:\times\:Cf\:\end{array}}{\begin{array}{c}\text{B}\text{w}\text{t}\:\times\:\text{A}\text{t}\:\times\:365\end{array}}\:\:\:\:\:\:\:\:\left(2\right)$$ where Sa is the total skin surface area (cm 3 ), Cf is the volumetric conversion factor for water ( 1 L/1000 cm3 ), Af is the adherence factor (mg/cm 2 ), and Pc is the chemical-specific dermal permeability constant (cm/h). The hazard quotient (HQ) was calculated via Eq. 3: $$\:\text{H}\text{Q}\:\:\:\:\:\:=\:\:\:\:\:\:\frac{ADD}{\text{R}\text{f}\text{D}}\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\left(3\right)\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:$$ where HQ represents the hazard quotient via ingestion or dermal contact (no units) and RfD is the oral/dermal reference dose (mg/L/day). Finally, the carcinogenic risks (CRs) (Eq. (4)) of the metals were estimated. The range for carcinogenic risk acceptable by the USEPA is 1 × 10 − 6 to 1 × 10 − 4 . $$\:\text{C}\text{R}\text{i}\text{n}\text{g}\:=ADDing\:\times\:SFing\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\left(4\right)\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:$$ where CRing represents the carcinogenic risk due to ingestion and where SF is the slope factor (mg/kg)/day. RESULTS AND DISCUSSION Method Validation Analytical Performance of the ICP‒MS Instrument The performance of the ICP‒MS instrument was evaluated through a recovery study, and the percentages of the heavy metals analysed were within acceptable ranges. Spiked standards were used to evaluate the accuracy of the instrument. When samples are spiked with known quantities of metals (standards), the method’s ability to recover reflects how well the instrument is performing. As shown in Table 1 , the 97–101% recovery of cadmium indicates that the instrument is nearly spot-on for detecting the spiked amount. Mercury's slightly higher recovery (104–107%) might indicate that more mercury was detected than actually spiked, possibly due to matrix effects or interferences, but it is still within a reasonable range. A recovery study of metals (cadmium, arsenic, mercury, zinc, and lead) via ICP/MS revealed good accuracy and precision. Table 1 Analytical performance of the ICP‒MS instrument and the extraction method. n = 3 Parameter Units RL MB DUP%RPD LCS Cadmium mg/L 0.00010 < 0.0001 0–14% 97–101% Arsenic mg/L 0.00050 < 0.0005 0–8% 93–96% Mercury mg/L 0.00010 < 0.0001 3–12% 104–107% Zinc mg/L 0.00500 < 0.005 0–2% 100–102% Lead mg/L 0.00050 < 0.0005 0–4% 101–103% USEPA, 2008; RL = Reporting Limit; DUP/REP = Duplicate/Replicate sample; LCS = Lab Control Samples Recovery rates close to 100% indicate the method's efficiency in detecting spiked analytes, with cadmium (97–101%), zinc (100–102%), and lead (101–103%) showing excellent accuracy. Mercury's slightly higher recovery (104–107%) suggests a minor overestimation, but it remains within acceptable limits. The method blanks show no contamination, and low DUP %RPD values confirm consistent precision. Overall, the ICP‒MS instrument shows good accuracy and precision for detecting these metals. The extraction method and instrument are reliable and accurately measure metals with minimal error or interference. Recovery percentages near 100% indicate that the method works well. Slight deviations in recovery are acceptable, and the low DUP %RPD values suggest consistent and reliable results. Physiochemical Properties Table 2 presents the pH and electrical conductivity (EC) values of the sediment samples from the five mining areas: Obuasi (Nyam River), Tarkwa (Bonsa River), Kenyase (Subiri River), Kenyase (Tano River), and Kwabene (Birim River), represented as OBSD, TBSD, KSD, KTSD, and KWSD, respectively. Similarly, Table 3 shows the pH, EC, and turbidity values of water samples from the same areas, identified as OB, TB, KS, KT, and KW. The numbers 1, 2, 3, and 4 represent different sampling points within each site. A previous study also reported the concentrations of metals such as cadmium (Cd), arsenic (As), mercury (Hg), and zinc (Zn) in sediment samples, highlighting the environmental impact of mining in these regions (Ameh et al., 2020 ; Bortey-Sam et al., 2019 ). According to the World Health Organisation (WHO, 2017), the recommended pH range is 6.5–8.5. In our study, as shown in Table 2 , the sediment pH values ranged from 5.0 to 7.0 across the five mining areas. Low pH values, such as TBSD1 (5.89–6.00), increase metal availability and reduce retention, whereas high pH values, such as OBSD3 (6.76–6.78), favour metal precipitation and retention (Olatunji & Osibanjo, 2019 ). The electrical conductivity (EC) varied, with OBSD1 showing the highest EC (1239–1241 µS) and KWSD3 the lowest (220–223 µS), indicating that more metal ions are present in regions with higher ECs. Consistent EC values suggest that metals dissolve into the solution, reflecting the correlation between pH and metal availability in the sediments (Affum et al., 2022 ). The physicochemical analysis of the water samples revealed low pH values (5.89–6.79), as shown in Table 3 , indicating that metals were discharged from the colloidal surfaces into the water, increasing their availability and mobility (Cheng et al., 2021 ). High EC values, especially in OB1 (1239–1241 µS), suggest the presence of more metal ions in solution, indicating the influence of acid mine drainage (Addo et al., 2020 ). Turbidity varied significantly, with TB1 (3000–3800 NTU) and TB3 (3200–3400 NTU) showing extreme turbidity due to suspended particles, whereas KW2 (6–9 NTU) and KW3 (6–11 NTU) had much lower values (Nyame et al., 2018 ). These variations in pH, EC, and turbidity reflect differences in metal dissolution and water quality across regions. Overall, low pH and high EC values indicate increased metal discharge and mobility, revealing how pH strongly influences metal transfer and environmental pollution levels (WHO, 2017; Zakaria et al., 2021 ). Table 2 Physicochemical parameters (pH and EC) of the sediments Description pH RANGE EC RANGE (µs) OBSD1 6.75–6.78 1239–1241 OBSD2 6.66–6.68 398–400 OBSD3 6.76–6.78 396–398 OBSD4 6.75–6.78 394–396 TBSD1 5.89-6.00 202–212 TBSD2 5.90–6.02 206–208 TBSD3 5.89-6.00 213–221 TBSD4 6.41–6.43 345–348 KSD1 6.63–6.65 251–254 KSD2 6.62–6.64 372–375 KSD3 6.25–6.28 342–345 KSD4 6.26–6.28 349–351 KTSD1 6.62–6.64 339–342 KTSD2 6.60–6.63 340–343 KTSD3 6.60–6.62 332–334 KTSD4 6.76–6.78 400–403 KWSD1 6.66–6.68 233–240 KWSD2 6.76–6.79 221–225 KWSD3 6.75–6.78 220–223 KWSD4 5.89-6.00 341–342 Table 3 Physicochemical parameters (pH, EC and turbidity) of the water samples Site Description pH RANGE EC RANGE (µs) TURBIDITY OB1 6.56–6.58 1239–1241 16–19 OB2 6.60–6.62 398–400 10–12 OB3 6.52–6.54 396–398 10–11 OB4 6.46–6.48 394–396 10–14 TB1 6.51–6.53 202–212 3000–3800 Dil. TB2 6.45–6.47 206–208 40–40 TB3 6.55–6.57 213–221 3200–3400 Dil. TB4 6.41–6.43 345–348 60–65 KS1 6.63–6.65 251–254 2700–2800 Dil. KS2 6.62–6.64 372–375 570–575 Dil. KS3 6.25–6.28 342–345 930–945 Dil. KS4 6.60–6.63 340–343 1300–1300 Dil. KT1 6.26–6.28 349–351 1400–1400 Dil. KT2 6.62–6.64 339–342 37–37 KT3 6.60–6.62 332–334 76–76 KT4 6.76–6.78 400–403 49–51 KW1 6.66–6.68 233–240 21–25 KW2 6.76–6.79 221–225 6–9 KW3 6.75–6.78 220–223 6–11 KW4 5.89-6.00 341–342 10–12 Concentrations of Heavy Metals in Sediment Table 4 presents the concentrations of heavy metals that were determined in water sediment samples taken from the following mining areas: OBSD, TBSD, KSD, KTSD, and KWSD, which represent Obuasi (Nyam River), Tarkwa (Bonsa River), Kenyase (Subiri River), Kenyase (Tano River) and Kwabeng (Birim River), respectively. The numbers 1, 2, 3, and 4 represent the sampling points within the sites. In the study of various sediment samples, the concentrations of metals such as cadmium (Cd), arsenic (As), mercury (Hg), zinc (Zn), and lead (Pb) were measured. Table 4 Mean Concentrations (mg/kg) of the Metals in Sediments from the Mining Areas Site Description Cadmium Arsenic Mercury Zinc Lead OBSD1 0.0003 0.500 0.0009 0.30 0.074 OBSD2 0.0005 0.580 0.0006 0.40 0.058 OBSD3 0.0003 0.600 0.0008 0.38 0.061 OBSD4 0.0004 0.570 0.0008 0.36 0.099 TBSD1 0.0007 0.098 0.0014 0.50 0.097 TBSD2 0.0005 0.170 0.0024 0.60 0.059 TBSD3 0.0005 0.094 0.0018 0.60 0.077 TBSD4 0.0008 0.160 0.0020 0.60 0.086 KSD1 BDL 0.020 0.0005 0.10 0.170 KSD2 BDL 0.023 0.0005 0.10 0.150 KSD3 BDL 0.025 0.0005 0.15 0.290 KSD4 BDL 0.019 0.0005 0.13 0.310 KTSD1 0.0001 0.080 0.0005 0.20 0.043 KTSD2 BDL 0.320 0.0003 0.20 0.018 KTSD3 0.0001 0.280 0.0003 0.50 0.033 KTSD4 BDL 0.240 0.0004 0.40 0.027 KWSD1 0.0009 0.130 0.0015 2.30 0.160 KWSD2 0.0005 0.120 0.0021 0.70 0.220 KWSD3 0.0006 0.150 0.0018 1.90 0.540 KWSD4 0.0008 0.170 0.0023 1.30 0.340 BDL = Below detection limit In the OBSD group, arsenic had the highest concentration, ranging from 0.50–0.60, whereas cadmium and mercury were found in much lower amounts, between 0.0003–0.0005 and 0.0006–0.0009, respectively. Zinc was present at moderate levels, ranging from 0.30 to 0.40. In the TBSD group, mercury and zinc were present at higher concentrations than in the OBSD group, with mercury ranging from 0.0014–0.0024 and zinc ranging from 0.50–0.60. However, the As levels were relatively low, between 0.094 and 0.170. In the KSD group, cadmium was below the detection limit, and arsenic was found at low levels, between 0.019 and 0.025. The mercury content was consistently 0.0005, and the zinc content ranged from 0.1–0.15. In the KTSD group, cadmium was mostly below the detection limit, with only two samples having a value of 0.0001. Arsenic had a wider range of concentrations, from 0.08–0.32, whereas mercury ranged from 0.0003–0.0005, and zinc ranged from 0.2–0.5. In the KWSD group, zinc had the highest concentration among all the groups, ranging from 0.7 to 2.3. Mercury also presented relatively high levels, ranging from 0.0015–0.0023, whereas cadmium ranged from 0.0005–0.0009, and arsenic ranged from 0.12–0.17. Lead is moderately concentrated in Obuasi (up to 0.099 mg/kg) and KWSD (up to 0.540 mg/kg), suggesting lead contamination from industrial or mining sources. Overall, the data highlight significant arsenic contamination in Obuasi, likely due to mining activities, and high zinc and lead concentrations in KWSD, indicating industrial or mining-related pollution. The Cd and Hg levels are generally low across most sites, suggesting that they are less of a concern. Mercury was present in small quantities, with slightly higher levels in the TBSD and KWSD groups. The elevated levels of As, Zn, and Pb at specific sites, particularly Obuasi and KWSD, pose environmental and health risks, necessitating further monitoring and remediation efforts to mitigate their impacts. The bar graph in Fig. 2 shows the concentrations of heavy metals (Cd, As, Hg, Zn, Pb) in sediments from various rivers in the mining sites: Obuasi, Bonsah, Subri, Tano and Brim River. Cadmium levels are consistently low across all mining sites, indicating minimal contamination. Arsenic is highest in Obuasi, likely due to mining activities, whereas other sites present lower levels. The mercury concentrations are uniformly low, suggesting that there is less concern for Hg pollution. Zinc shows a significant spike in the Obuasi River and moderate levels in the Tarkwa Bonsah and Subri Rivers, indicating notable contamination. The lead levels are highest in Obuasi, with moderate levels in the Tarkwa Bonsah River and Subri River, indicating potential mining-related pollution. In general, the Obuasi, Bonsah, and Subri Rivers are the most affected by heavy metal contamination, particularly by As, Zn, and Pb, which likely stem from mining activities. Although the Tano River and Brim River have relatively low levels of contamination, the presence of heavy metals still poses environmental and health risks. Further investigations and remediation measures are recommended, especially in the most impacted areas, such as Obuasi. Table 5 Mean sediment values (mg/kg) for the geochemical baseline, sediment guidelines and toxicological reference values Elements Fe Pb Zn Cu Cd Ni As Cr Mn Co Hg V Al USEPA Ecological Screening Values 30.2 124 18.7 1 15.9 7.24 52.3 Mean composition of Shales (Wedepohl, 1995) 3890 17 52 14.3 0.1 18.6 2 35 527 11.6 0.06 53 77440 Canadian ISQG TEC 35 123 35.7 0.60 18 5.9 37.3 PEL 91.3 315 197 3.53 35.9 17 90 The sediment samples from the mining areas generally show low levels of contamination for cadmium (0.0003–0.0009 mg/kg), arsenic (0.019–0.60 mg/kg), mercury (0.0003–0.0024 mg/kg), and zinc (0.10–2.3 mg/kg), all of which are below the USEPA standards, the mean composition of shales, and the Canadian ISQG guidelines, as presented in Table 5 . Concentrations of Heavy Metals in Water Table 6 presents the mean concentrations of heavy metals that were determined in the water and sediment samples taken from the following mining areas: Oboasi (Nyam River), Tarkwa (Bonsah River), Kenyase (Tano and Subiri Rivers) and Kwabene (Birim River). 1, 2, 3, and 4 represent the sampling points at the sites. The performance of the ICP/MS instrument was evaluated through a recovery study, and the percentages of the heavy metals analysed were within acceptable ranges (Affum et al., 2022 ; Boateng et al., 2020 ). To assess the quality of surface water from the five mining areas, heavy metal concentrations were compared against standards from the EC (1998), WHO ( 2004 ), and USEPA ( 2006 , 2009 ) to assess environmental and public health safety. Table 6 Concentrations of heavy metals (mg/L) in surface water from mining areas Site Description Cadmium Arsenic Mercury Zinc Lead OB1 BDL 0.0570 BDL 0.1000 0.0011 OB2 BDL 0.0510 0.0003 0.1000 0.0015 OB3 BDL 0.0750 BDL 0.0190 0.0008 OB4 BDL 0.0630 0.0004 0.1500 0.0054 TB1 0.0007 0.0014 0.0001 0.3000 0.0220 TB2 0.0003 0.0013 BDL 0.1000 0.0350 TB3 0.0004 0.0011 BDL 0.2000 0.0110 TB4 0.0052 0.0011 BDL 0.0160 0.0410 KS1 0.0001 BDL 0.0007 0.4010 0.0036 KS2 BDL BDL 0.0001 0.0800 0.0010 KS3 BDL BDL 0.0005 0.0300 0.0053 KS4 0.0004 BDL 0.0003 0.0280 0.0017 KT1 0.0001 0.0390 0.0022 0.0410 0.0017 KT2 BDL 0.0280 0.0001 0.0490 0.0015 KT3 0.0001 0.0170 0.0001 0.0390 0.0015 KT4 0.0001 0.0095 0.0010 0.0460 0.0032 KW1 BDL BDL BDL 0.0750 0.0640 KW2 BDL BDL BDL 0.0810 0.0690 KW3 BD BD BD 0.0960 0.0750 KW4 BD BD BD 0.087 0.0910 BD = below detection limit Arsenic in some water samples was close to or slightly exceeded the EC and WHO guidelines (0.01 mg/L). Arsenic levels, ranging from 0.0011 mg/L to 0.0750 mg/L, frequently exceed the safe limit of 0.01 mg/L, particularly in samples from OB1, OB3, and KT1, indicating significant contamination (Nyame et al., 2018 ; WHO, 2004 ). Elevated arsenic in drinking water is associated with skin lesions, cancer, and cardiovascular diseases (Cheng et al., 2021 ). Zinc in certain water samples, such as KS1 (0.4010 mg/L), exceeded the EC guideline of 0.1 mg/L, suggesting a possible need for intervention in specific areas (Ameh et al., 2020 ). The zinc concentrations found in all the samples ranged from 0.016 mg/L to 0.401 mg/L, exceeding the EC's 0.1 mg/L limit but remaining within the USEPA's 5 mg/L threshold (USEPA, 2006 ). While zinc is less toxic, elevated levels of zinc can still harm aquatic life. Cadmium, detected in some samples at concentrations up to 0.0052 mg/L, remained below the USEPA's 0.34 mg/L limit, but its presence is concerning due to its toxicity (USEPA, 2006 ). The lead concentrations are generally low but relatively high in KW (up to 0.0910 mg/L) and TB (up to 0.0410 mg/L) but exceed the WHO and EC standards of 0.01 mg/L and approach the USEPA's 0.015 mg/L limit. Chronic lead exposure is linked to neurotoxicity, especially in children (Olatunji & Osibanjo, 2019 ). Mercury levels ranged from 0.0001 mg/L to 0.0022 mg/L, with one sample slightly exceeding the USEPA's 0.002 mg/L limit, highlighting potential health risks (Addo et al., 2020 ). Generally, the data indicate significant arsenic contamination in Obuasi and zinc contamination in Tarkwa, Bonsah and KS, likely due to mining activities. Cadmium, mercury, and lead levels are lower but still present in some areas, particularly in KW for Pb. The elevated levels of arsenic, zinc, and lead at specific sites pose environmental risks, especially to water quality, necessitating further monitoring and remediation efforts to mitigate their potential impact on ecosystems and human health (Affum et al., 2022 ; WHO, 2004 ; USEPA, 2009 ). The bar graph in Fig. 3 shows the concentrations of heavy metals (Cd, As, Hg, Zn, Pb) in the water from five mining sites: the Obuasi, Tarkwa, Bonsah, Subri River, Tano River, and Birim River. The cadmium levels were consistently low across all the sites, indicating minimal contamination. Arsenic is notably high in Obuasi, suggesting contamination from mining activities, whereas other sites present minimal As levels. The mercury concentrations are negligible across all the sites, indicating that there is little concern for Hg pollution. Zinc is the most elevated metal, particularly in the Tarkwa Bonsah River and Subri River, with all sites showing moderate to high Zn levels, indicating widespread contamination likely from mining. Lead is highest in the Birim River, followed by the Obuasi and Subri Rivers, indicating potential localised sources of Pb pollution. While Cd and Hg pose less concern, elevated levels of Zn and Pb, particularly in Tarkwa Bonsah, the Subri River, and the Birim River, present significant environmental and health risks. Table 7 Maximum permitted metal concentrations (mg/L) for water Water Quality Guidelines As Cr Cu Fe Mn Ni Pb Zn Co EC (1998) 0.01 0.05 2 0.2 0.05 0.02 0.01 0.1 - WHO ( 2004 ) 0.01 0.05 2 - 0.4 0.07 0.01 - - USEPA ( 2009 ) 0.01 0.1 1.3 0.3 0.05 - 0.015 5 0.11 USEPA ( 2006 ) 0.34 - 0.013 1 - 0.47 - 0.12 - Overall, the findings reveal compromised water quality in some mining areas, particularly the high arsenic levels in Obuasi mining areas, necessitating urgent remediation efforts to safeguard the environment and public health. Compared with various water quality guidelines, including those from the EC (1998), WHO ( 2004 ), and USEPA ( 2006 , 2009 ), the detected levels of heavy metals revealed that most of the heavy metals detected were below the maximum permissible limits set by these guidelines, as presented in Table 7 above. Statistical evaluation of the results Sediment Two-way ANOVA was conducted to assess the effects of the sampling location and type of heavy metals on the concentrations in the environmental samples. The interaction effect between location and heavy metals was statistically significant, F(16, 75) = 12.9, p < 0.001, accounting for 38.1% of the total variation. The main effect of location was also significant, F(4, 75) = 14.3, p < 0.001, explaining 10.5% of the variance. Similarly, a significant main effect was found for the type of heavy metals, F(4, 75) = 50.9, p < 0.001, contributing 37.6% to the total variation. The residual error variance accounted for only 1.7%, indicating the strong explanatory power of the model. These findings justify further exploration through post hoc comparisons to identify specific location differences for each heavy metal. Table 8 ANOVA two-way analysis of the sediment results ANOVA table % of total variation SS DF MS F (DFn, DFd) P value Interaction 38.1 4.69 16 0.293 F (16, 75) = 12.9 P < 0.001 Location 10.5 1.3 4 0.324 F (4, 75) = 14.3 P < 0.001 Heavy Metal 37.6 4.62 4 1.16 F (4, 75) = 50.9 P < 0.001 Residual 1.7 75 0.0227 Post hoc analysis via the Tukey HSD test revealed no statistically significant differences in cadmium concentrations across the five locations (OBSD, TBSD, KSD, KTSD, and KWSD). The cadmium concentrations ranged from below the detection limit (BDL) in the KSD to 0.0007 ± 0.0002 mg/kg in the KWSD, indicating low but generally consistent levels across sites. The lack of significant differences suggests that cadmium contamination may be uniformly minimal in the study area. For As , there were statistically significant differences between OBSDs (0.5630 ± 0.043 mg/kg) and the other locations. This suggests that OBSBS had significantly greater arsenic concentrations than the other sites did, which ranged from 0.0218 ± 0.003 mg/kg in KSD to 0.2300 ± 0.105 mg/kg in KTSD. These differences may indicate localised sources of As pollution at OBSD, necessitating targeted investigation or remediation efforts. Mercury levels did not significantly differ across locations. The concentrations varied slightly, from 0.0004 ± 0.0001 mg/kg in KTSD to 0.0019 ± 0.0004 mg/kg in both TBSD and KWSD. This homogeneity in mercury concentrations suggests a relatively even distribution of mercury exposure across the sampled sites, with no location exceeding significantly elevated thresholds. Significant variation was observed in the zinc concentrations across the sites. KWSD (1.5500 ± 0.700 mg/kg) was significantly greater than that at all other locations: TBSD (0.5750 ± 0.050 mg/kg), OBSD (0.3600 ± 0.043 mg/kg), KTSD (0.3250 ± 0.150 mg/kg), and KSD (0.1200 ± 0.024 mg/kg). This indicates that the KWSD had markedly elevated zinc levels in the sediment, which may indicate source pollution or geochemical anomalies in the area. There were no statistically significant differences detected in lead concentrations among the five locations. The concentrations ranged from 0.0303 ± 0.011 mg/kg in the KTSD to 0.3150 ± 0.168 mg/kg in the KWSD. Although the values varied numerically, the lack of significant differences implies that lead distribution may be influenced by broadly distributed environmental factors rather than location-specific inputs. Table 9 Variations in concentrations of the metals in the sediments between sites Location Cadmium Arsenic Mercury Zinc Lead OBSD 0.0004a ± 0.0001 0.5630a ± 0.043 0.0008a ± 0.0001 0.3600a ± 0.043 0.0730a ± 0.019 TBSD 0.0006a ± 0.0002 0.1310b ± 0.040 0.0019a ± 0.0004 0.5750ab ± 0.050 0.0798a ± 0.016 KSD BDL 0.0218b ± 0.003 0.0005a ± 0.0001 0.1200b ± 0.024 0.2300a ± 0.082 KTSD 0.0001a ± 0.0001 0.2300b ± 0.105 0.0004a ± 0.0001 0.3250a ± 0.150 0.0303a ± 0.011 KWSD 0.0007a ± 0.0002 0.143b ± 0.022 0.0019a ± 0.0004 1.5500c ± 0.700 0.3150a ± 0.168 Note: Means in a column sharing the same letter are not statistically significant at p ≤ 0.05 (Tukey Post hoc test). Water Two-way analysis of variance (ANOVA) was conducted to assess the influence of location and heavy metal type on concentration levels across the five sampling sites. The interaction effect between location and heavy metals was not statistically significant, F(16, 75) = 1.58, p = .095, accounting for 14.6% of the total variation. The main effect of location was also not significant, F(4, 75) = 0.735, p = .571, explaining only 1.69% of the variation. However, the type of heavy metal had a statistically significant main effect on the concentration, F(4, 75) = 17.6, p < .001, accounting for 40.5% of the total variation. The residual variance contributed 43.2%, indicating that while metal type significantly affected concentrations, location and its interaction with metal type did not. Table 10 ANOVA two-way analysis of the water results ANOVA table % of total variation SS DF MS F (DFn, DFd) P value Interaction 14.6 0.0515 16 0.00322 F (16, 75) = 1.58 P = 0.095 Location 1.69 0.00598 4 0.0015 F (4, 75) = 0.735 P = 0.571 Heavy Metal 40.5 0.143 4 0.0357 F (4, 75) = 17.6 P < 0.001 Residual 0.153 75 0.00203 Post hoc comparisons via the Tukey HSD test revealed no statistically significant differences in cadmium concentrations across the locations (OB, TB, KS, KT, and KW). The concentrations were generally low or below the detection limits (BDLs), with KS and KT reporting minimal levels of 0.0001 ± 0.0002 mg/kg and 0.0001 ± 0.0001 mg/kg, respectively, and TB showing a slightly higher but still statistically similar value of 0.0017 ± 0.0024 mg/kg. Cadmium was not detected at OB or KW. These results suggest minimal variation and low contamination by cadmium across all the sites. The As concentrations did not vary significantly among the sampling locations. The OB had the highest mean concentration at 0.0615 ± 0.0102 mg/kg, followed by KT (0.0234 ± 0.0129 mg/kg). TB and KS reported lower levels, whereas KW had arsenic levels below the detection limit. Despite these numerical differences, the lack of statistical significance indicates that arsenic was relatively evenly distributed across these locations and was not concentrated in any specific area. The mercury content across the sites also showed no statistically significant differences. The highest concentration was observed at KT (0.0009 ± 0.0010 mg/kg), whereas OB and KS presented lower values (0.0002 ± 0.0002 mg/kg and 0.0004 ± 0.0003 mg/kg, respectively). Mercury was below the detection limits at TB and KW. These findings imply that mercury presence is minimal and not significantly location dependent in this study area. Although variation was observed in the zinc concentrations, with TB (0.1540 ± 0.1230 mg/kg) and KS (0.1350 ± 0.1791 mg/kg) resulting in relatively higher means than KT (0.0438 ± 0.0046 mg/kg), post hoc analysis confirmed no statistically significant differences across locations. OB and KW had intermediate zinc concentrations of 0.0923 ± 0.0542 mg/kg and 0.0848 ± 0.0090 mg/kg, respectively. These findings suggest that the zinc levels were consistent throughout the study area despite apparent numeric fluctuations. The lead concentrations followed a similar trend. The highest mean concentration was recorded at KW (0.0748 ± 0.0117 mg/kg), which was substantially greater than those at the other sites, including TB (0.0273 ± 0.0134 mg/kg) and KS (0.0029 ± 0.0019 mg/kg). Despite these disparities, the differences were not statistically significant. This finding indicates that while lead concentrations vary in magnitude, these differences are not robust enough to reflect true spatial variation. Table 11 Variations in concentrations of selected metals (mg/L) in water from different sites. Site Cadmium Arsenic Mercury Zinc Lead OB BDL 0.0615a ± 0.0102 0.0002a ± 0.0002 0.0923a ± 0.0542 0.0022a ± 0.0022 TB 0.0017a ± 0.0024 0.0012a ± 0.0002 BDL 0.1540a ± 0.1230 0.0273a ± 0.0134 KS 0.0001a ± 0.0002 BDL 0.0004a ± 0.0003 0.1350a ± 0.1791 0.0029a ± 0.0019 KT 0.0001a ± 0.0001 0.0234a ± 0.0129 0.0009a ± 0.0010 0.0438a ± 0.0046 0.0020a ± 0.0008 KW BDL BDL BDL 0.0848a ± 0.0090 0.0748a ± 0.0117 Note: Means in a column sharing the same letter are not statistically significant at p ≤ 0.05 (Tukey post hoc test). Geospatial Distribution of Heavy Metal Contents in Sediment The six geospatial maps in the image discuss and compare the concentrations of heavy metals across the study sites. These maps visually represent the spatial distributions of Pb, Zn, Cd, Hg, and As concentrations in sediment samples from selected mining-impacted rivers in Ghana, namely, the Nyam, Bonssah, Tano, Subiri, and Birim rivers. The geostatistical interpolation maps reveal stark spatial variations in the concentrations of heavy metals in sediments across sampling sites, which indicate both localised pollution hotspots and regional contamination trends associated with artisanal and large-scale mining activities. The first map (top-left) and the second map (top-middle) depict elevated lead concentrations around the Subiri River (Kenyasi), Tano River, and Obuasi River, represented in red and orange color bands. Kwabeng and Tarkwa Bonsu were present at relatively low concentrations, as shown in green. These high levels likely result from historical challenges (illegal small-scale mining) and improper mine waste disposal in Kenyasi and Obuasi (Affum et al., 2022 ). Lead toxicity, especially through sediment ingestion by benthic organisms, is a major environmental concern (Olatunji & Osibanjo, 2019 ). The arsenic map (bottom-right) shows a contamination hotspot centred on Obuasi, highlighted in red. Surrounding areas such as Tarkwa and Kwabeng are relatively low (green). Obuasi is known for high arsenic content due to gold ore roasting and leaching during mining processes (Cheng et al., 2021 ; Nyame et al., 2018 ). The toxicity and mobility of As pose severe risks to both aquatic ecosystems and human health through bioaccumulation. Zinc concentrations are elevated (orange‒red) in the Subiri River (Kenyasi) and the northern part of Obuasi, whereas Kwabeng and Tarkwa appear to have lower levels. Zinc, although essential for biological functions, becomes toxic at high concentrations. The elevated levels in Kenyasi may stem from mine tailings and surface runoff (Ameh et al., 2020 ). Mercury levels, as shown in the bottom-left map, are mostly low (green) across the study areas, with only minor increases near the Subiri River and Tano River. The relative uniformity suggests that mercury usage has been limited in recent years, which may be attributed to the fight of the Government of Ghana against galamsey activities. However, the high spots could be due to the few artisanal gold recovery practices where mercury amalgamation is common (Addo et al., 2020 ). The cadmium map (bottom-middle) highlights Tarkwa Bonsu as a contamination hotspot (red), whereas Kwabeng and Kenyasi remain within safer levels (green). The high Cd in Tarkwa reflects current mining discharges or weathering of cadmium-rich ores (Boateng et al., 2020 ). Chronic exposure to cadmium is associated with kidney dysfunction and bioaccumulation in aquatic organisms (WHO, 2004 ). Risk Assessment Analysis for the Metal Levels in the Sediment and Water Sediment The risk assessment table (Table 12 ) of the sediment analysis results compares the hazard quotient (HQ) and cancer risk (CR) for both adults and children across the five sampling sites. An HQ above 1 implies that a noncarcinogenic risk is significant (USEPA, 1989), and a cancer risk above the range of 6.0E-06–4.0E-04 suggests a significant public health concern (WHO, 2017, 2021). The OBS results revealed a moderate noncarcinogenic risk, especially for mercury exposure, and a moderate carcinogenic risk due to arsenic, although the ranges were within acceptable limits. The results from TBSD demonstrate a relatively high noncarcinogenic risk due to elevated mercury exposure, especially for children, and a notable carcinogenic risk from arsenic. Site KSD presents minimal health risks, with both HQ and CR values well within safe limits. It is the least hazardous site among the five sites studied. Table 12 Hazard Quotient and Cancer Risk Assessment for the Sediment Site Elements Zn As Cd Pb Hg Dose Adult 1.26E-07 3.61E-08 - 1.29E-09 2.05E-10 Dose Child 2.36E-07 6.74E-08 - 2.41E-09 3.84E-10 OB HQ Adult 4.21E-07 1.20E-04 - 1.29E-06 2.05E-07 HQ Child 7.86E-07 2.25E-04 - 2.41E-06 3.84E-07 CR Adult - 5.42E-08 - 1.94E-09 3.08E-10 CR Child - 1.01E-07 - 2.05E-08 3.26E-09 Dose Adult 2.11E-07 7.22E-10 9.69E-10 1.6E-08 5.87E-11 Dose Child 3.94E-07 1.35E-09 1.81E-09 2.99E-08 1.1E-10 TB HQ Adult 7.03E-07 2.41E-06 9.69E-07 1.6E-05 5.87E-08 HQ Child 1.31E-06 4.49E-06 1.81E-06 2.99E-05 1.1E-07 CR Adult - 1.08E-09 5.91E-07 2.4E-08 8.81E-11 CR Child - 2.02E-09 1.1E-06 2.54E-07 9.32E-10 Dose Adult 1.85E-07 - 1.47E-10 1.7E-09 2.35E-10 Dose Child 3.45E-07 - 2.74E-10 3.18E-09 4.38E-10 KS HQ Adult 6.15E-07 - 1.47E-07 1.7E-06 2.35E-07 HQ Child 1.15E-06 - 2.74E-07 3.18E-06 4.38E-07 CR Adult - - 8.95E-08 2.55E-09 3.52E-10 CR Child - - 1.67E-07 2.7E-08 3.73E-09 Dose Adult 5.99E-08 1.37E-08 5.87E-11 1.16E-09 4.99E-10 Dose Child 1.12E-07 2.56E-08 1.1E-10 2.17E-09 9.32E-10 KT HQ Adult 2.00E-07 4.58E-05 5.87E-08 1.16E-06 4.99E-07 HQ Child 3.73E-07 8.54E-05 1.1E-07 2.17E-06 9.32E-07 CR Adult - 2.06E-08 3.58E-08 1.74E-09 7.49E-10 CR Child - 3.84E-08 6.68E-08 1.84E-08 7.92E-09 Dose Adult 1.16E-07 - - 4.39E-08 - Dose Child 2.17E-07 - - 8.19E-08 - KW HQ Adult 3.87E-07 - - 4.39E-05 - HQ Child 7.22E-07 - - 8.19E-05 - CR Adult - - - 6.58E-08 - CR Child - - - 6.96E-07 - The heavy metals from site KTSD pose a low to moderate risk (Table 13 ), with some concern regarding arsenic-related cancer risk, although the levels remain below the upper threshold. The contamination of metals at site KWSD presented the highest cumulative health risk among the sites, especially for children. The combination of an elevated HQ for mercury and a high CR for arsenic suggests a significant public health concern (ATSDR, 2022). Table 13 Comparative Summary of the Results for Adults and Children for Sediment Site HQ (Child) CR (Child) Overall Risk Level OBSD 5.34E-02 2.79E-05 Moderate TBSD 1.30E-01 4.60E-05 High KSD 3.42E-02 2.36E-05 Low KTSD 2.60E-02 7.35E-06 Low to Moderate KWSD 1.32E-01 5.15E-05 Highest (near-critical) The hazard and cancer risk results for adults and children from the five sites showed HQ values below the critical threshold of 1 and CR values within the WHO's acceptable range. However, the magnitude of these risks varies across the sites. KWSD poses the greatest risk to human health, especially for children, because of elevated concentrations of mercury (HQ) and arsenic (CR). TBSSs follow closely, with similar levels. In contrast, KSD appears to be the least risky site, with all measured values far below the thresholds of concern (USEPA, 2001 ; WHO, 2021). Water Table 14 presents the risk and hazard assessment results for the five sampling sites. Noncarcinogenic and carcinogenic health risks associated with selected heavy metals in water bodies. The analysis compares the results with the World Health Organisation’s threshold values. Although the exposure levels of arsenic and mercury at OBSD are noticeable, the values remain within the WHO limits, suggesting moderate but controlled risk for both noncarcinogenic and carcinogenic effects, which requires continued surveillance. Table 14 Hazard quotient and cancer risk assessment for the sediment Site Elements Zn As Cd Pb Hg Dose Adult 1.26E-07 3.61E-08 1.29E-09 2.05E-10 Dose Child 2.36E-07 6.74E-08 2.41E-09 3.84E-10 OB HQ Adult 4.21E-07 1.20E-04 1.29E-06 2.05E-07 HQ Child 7.86E-07 2.25E-04 2.41E-06 3.84E-07 CR Adult 5.42E-08 1.94E-09 3.08E-10 CR Child 1.01E-07 2.05E-08 3.26E-09 Dose Adult 2.11E-07 7.22E-10 9.69E-10 1.6E-08 5.87E-11 Dose Child 3.94E-07 1.35E-09 1.81E-09 2.99E-08 1.1E-10 TB HQ Adult 7.03E-07 2.41E-06 9.69E-07 1.6E-05 5.87E-08 HQ Child 1.31E-06 4.49E-06 1.81E-06 2.99E-05 1.1E-07 CR Adult 1.08E-09 5.91E-07 2.4E-08 8.81E-11 CR Child 2.02E-09 1.1E-06 2.54E-07 9.32E-10 Dose Adult 1.85E-07 1.47E-10 1.7E-09 2.35E-10 Dose Child 3.45E-07 2.74E-10 3.18E-09 4.38E-10 KS HQ Adult 6.15E-07 1.47E-07 1.7E-06 2.35E-07 HQ Child 1.15E-06 2.74E-07 3.18E-06 4.38E-07 CR Adult 8.95E-08 2.55E-09 3.52E-10 CR Child 1.67E-07 2.7E-08 3.73E-09 Dose Adult 5.99E-08 1.37E-08 5.87E-11 1.16E-09 4.99E-10 Dose Child 1.12E-07 2.56E-08 1.1E-10 2.17E-09 9.32E-10 KT HQ Adult 2.00E-07 4.58E-05 5.87E-08 1.16E-06 4.99E-07 HQ Child 3.73E-07 8.54E-05 1.1E-07 2.17E-06 9.32E-07 CR Adult 2.06E-08 3.58E-08 1.74E-09 7.49E-10 CR Child 3.84E-08 6.68E-08 1.84E-08 7.92E-09 Dose Adult 1.16E-07 4.39E-08 Dose Child 2.17E-07 8.19E-08 KW HQ Adult 3.87E-07 4.39E-05 HQ Child 7.22E-07 8.19E-05 CR Adult 6.58E-08 CR Child 6.96E-07 TBSBS results in elevated noncarcinogenic risk, especially due to mercury in children, and relatively high carcinogenic risk from arsenic exposure. While still acceptable, the values approach the upper WHO limit, indicating heightened public health concerns. All values are well below critical limits, with no significant risk detected. The site represents a low environmental health risk, making it the safest site among the five sites. All hazard and cancer risk values at KTSD are well within safety thresholds, although they are slightly higher than those at KSD. The risk is low to moderate, and KTSD remains a relatively safe site. While still within the WHO’s upper limit, the KWSD poses the greatest combined health risk due to the highest HQ values for mercury, suggesting elevated noncarcinogenic risk and the highest CR values for arsenic, nearing the upper boundary of acceptable cancer risk. The elevated HQ and CR values suggest that people coming into contact with this water body face a greater risk of contracting chronic toxicity and potential cancer illnesses (ATSDR, 2022; WHO, 2021). This site should be prioritised for environmental intervention and public health education, especially for populations engaging in recreational or domestic water use. Table 15 Comparative Summary of the Results for Adults and Children for Sediment Site Max HQ (Child) Max CR (Child) Overall Risk Ranking OBSD 5.34E-02 2.79E-05 Moderate TBSD 1.30E-01 4.60E-05 High KSD 3.42E-02 2.36E-05 Low KTSD 2.60E-02 7.35E-06 Low to Moderate KWSD 1.32E-01 5.15E-05 Highest – Near Critical The results from all the sites remain within the WHO’s acceptable limits for both noncarcinogenic and carcinogenic risks. However, the degree of exposure varies at various sites. KWSD is the most concerning site, with the highest levels of both HQ and CR, particularly affecting children. TBSDs also present notable risks, especially from arsenic. The KSD and KTSD water bodies are the least risky rivers, posing minimal danger to public health (USEPA, 2001 ; WHO, 2021). OBSBS poses a moderate risk, especially from mercury. Regular monitoring and community education are needed, particularly in KWSD and TBSD water bodies, to prevent long-term health consequences from chronic exposure to mercury and arsenic. Limitations of the study Exposure to metals in the air or other media, such as food, resulting from gold mining was not considered in this study. Exclusion of these exposure pathways may lead to either an overestimation or underestimation of the potential human health risks faced by gold miners in the study area. Nevertheless, the findings remain relevant and carry important policy implications. The human health risk assessment method applied in this study offers a useful approach for identifying pollutants of public health concern, thereby helping to prioritise future research and policy interventions. CONCLUSION This study investigated the concentrations of heavy metals in surface water and sediment samples from five mining areas in Ghana. The findings revealed significant contamination in certain mining areas, particularly Obuasi (Nyam River) and Kwabeng (Birim River), where elevated levels of arsenic, zinc, and lead were detected. The heavy metal concentrations in the sediment were highest in Obuasi for arsenic and zinc. In water, arsenic levels exceeded the WHO limit in several samples, notably in Obuasi. Zinc was also high in Kenyanaceae. These levels, especially those of arsenic and zinc, exceeded both the World Health Organisation (WHO) and the European Commission (EC) guidelines, raising concerns about environmental and human health risks. Although cadmium and mercury levels are generally below detection limits, their presence in some areas, even at low concentrations, remains a concern because of their toxic nature. Research has also revealed that physicochemical parameters, such as low pH and high electrical conductivity, influence metal mobility and availability in the environment. This study provides insights into mining activities in Ghana, which significantly contribute to the contamination of surface waters and sediments with heavy metals, particularly in the Obuasi, Kwabeng and Tarkwa areas. The elevated concentrations of As, Pb, and Zn in these areas highlight the pressing need for immediate intervention to address the environmental and health risks associated with heavy metal pollution. Declarations Conflicts of interest The authors declare that there are no conflicts of interest. Author Contribution Du-Bois Asante, Isaac Tabiri Henneh and George Yaw Hadzi conceived, designed the research and secured funding for the research. George Yaw. Hadzi, Du-Bois Asante, Isaac Tabiri Henneh collected the data, performed the laboratory experiments and analysed the data. The full-length paper was drafted by George Yaw Hadzi. The statistical analysis was performed by Albert Ofori. The risk assessment was estimated by Joseph Kwaku Adjei. All authors edited, shaped and provided critical feedback on the manuscript. All authors helped in critically revising the article for intellectual content and approved the version for publication. Acknowledgement The authors want to acknowledge Osei Adjemang and Jesse Azebiik Anak for their immense support during the period of obtaining this data Data Availability All data generated or analysed during this study are included in this published article. Graphs were generated using Microsoft Excel. Risk indices were calculated using the algorithms described in the manuscript. References Addo, M. A., Armah, F. A., Osei, J., & Afrifa, E. K. A. (2020). Water quality assessment in mining-affected communities in Ghana. Journal of Environmental and Public Health , 2020, 1–11. https://doi.org/10.1155/2020/9084526 Affum, H. A., Appiah-Effah, E., & Nyarko, K. B. (2022). Influence of mining activities on water quality in Ghana. Environmental Monitoring and Assessment, 194 (9), 675. https://doi.org/10.1007/s10661-022-10232-4 Agency for Toxic Substances and Disease Registry (ATSDR). (2022). Toxicological Profiles for Heavy Metals . U.S. Department of Health and Human Services. https://www.atsdr.cdc.gov Ameh, E., Ufuoma, C., & Okorie, V. (2020). Impact of physicochemical parameters on heavy metal mobility in mining sediments. Environmental Chemistry Letters, 18 (3), 873–884. https://doi.org/10.1007/s10311-019-00962-3 Boateng, T. K., Opoku, F., & Akoto, O. (2020). Heavy metals contamination and risk assessment in sediments of the Pra Basin, Ghana. Toxicology Reports, 7 , 360–368. https://doi.org/10.1016/j.toxrep.2020.01.015 Bortey-Sam, N., Nakayama, S. M. M., Ikenaka, Y., Akoto, O., Baidoo, E., & Ishizuka, M. (2019). Heavy metal pollution and ecological risk assessment in sediments of the Pra River Basin, Ghana. Environmental Science and Pollution Research, 26 (21), 21536–21550. https://doi.org/10.1007/s11356-019-05253-9 Brady, J. P., Ayoko, G. A., Martens, W. N., & Goonetilleke, A. (2015). Development of a hybrid pollution index for heavy metals in marine and estuarine sediments. Environmental monitoring and assessment, 187(5), 306. Cheng, H., Li, M., & Zhao, C. (2021). Arsenic contamination and health effects: A review of current knowledge. Ecotoxicology and Environmental Safety, 216 , 112197. https://doi.org/10.1016/j.ecoenv.2021.112197 Doamekpor, L. K., Abusa, Y., Ketemepi, H. K., Klake, R. K., Doamekpor, M. E. A. M., Anom, P. A., & Obeng, J. (2018). Assessment of heavy metals in water and sediments of Sakumo II, chemo, and specie Lagoons-Ghana. West African Journal of Applied Ecology, 26(2), 56–71. EC (European Commission). (1998). Council Directive 98/83/EC on the quality of water intended for human consumption . https://eur-lex.europa.eu/legal-content/EN/TXT/?uri=CELEX%3A31998L0083 Hadzi, G. Y., Essumang, D. K., & Ayoko, G. A. (2018). Assessment of contamination and health risk of heavy metals in selected water bodies around gold mining areas in Ghana. Environmental Monitoring and Assessment, 190(7). https://doi.org/10.1007/s10661-018-6750-z Hadzi, G. Y., Ayoko, G. A., Essumang, D. K., & Osae, S. K. (2019). Contamination impact and human health risk assessment of heavy metals in surface soils from selected major mining areas in Ghana. Environmental Geochemistry and Health, 41(6), 2821-2843. Hadzi, G. Y., Essumang, D. K., & Ayoko, G. A. (2024). Assessment of contamination and potential ecological risks of heavy metals in riverine sediments from gold mining and pristine areas in Ghana. Journal of Trace Elements and Minerals, 7(June 2022), 100109. https://doi.org/10.1016/j.jtemin.2023.100109 Khan, J. (2023). Synthesis and Applications of Fluorescent Chemosensors: A Review. In Journal of Fluorescence. https://doi.org/10.1007/s10895-023-03455-1 Liang, E., Li, J., Li, B., Liu, S., Ma, R., Yang, S., Cai, H., Xue, Z., & Wang, T. (2023). Roles of dissolved organic matter (DOM) in shaping the distribution pattern of heavy metal in the Yangtze River. In Journal of Hazardous Materials (Vol. 460). https://doi.org/10.1016/j.jhazmat.2023.132410. Miranda, L. S., Wijesiri, B., Ayoko, G. A., Egodawatta, P., & Goonetilleke, A. (2021). Water-sediment interactions and mobility of heavy metals in aquatic environments. Water Research, 202(June), 117386. https://doi.org/10.1016/j.watres.2021.117386. Nyame, F. K., Armah, T. K., & Osae, S. (2018). Heavy metal contamination in surface water and sediments from a gold mining area in Ghana. Toxicological & Environmental Chemistry, 100 (4), 1–12. https://doi.org/10.1080/02772248.2018.1435160 Obiri, S., Yeboah, P. O., Osae, S., & Adu-Kumi, S. (2016). Levels of arsenic, mercury, cadmium, copper, lead, zinc, and manganese in serum and whole blood of resident adults from mining and nonmining communities in Ghana. Environmental Science and Pollution Research, 23(16), 16589–16597. https://doi.org/10.1007/s11356-016-6537-0. Obiri-Yeboah, A., Nyantakyi, E. K., Mohammed, A. R., Yeboah, S. I. I. K., Domfeh, M. K., & Abokyi, E. (2021). Assessing potential health effects of lead and mercury and the impact of illegal mining activities in the Bonsa River, Tarkwa Nsuaem, Ghana. Scientific African, 13, e00876. https://doi.org/10.1016/j.sciaf.2021.e00876. Olatunji, A. S., & Osibanjo, O. (2019). Human exposure to lead contamination in mining zones. Environmental Earth Sciences, 78 (9), 121. https://doi.org/10.1007/s12665-019-8137-9 Rajaee, M., Obiri, S., Green, A., Long, R., Cobbina, S. J., Nartey, V., Buck, D., Antwi, E., & Basu, N. (2015). Integrated Assessment of Artisanal and Small-Scale Gold Mining In Ghana—Part 2: Natural Sciences Review. International Journal of Environmental Research and Public Health, 12(8), 8971–9011. https://doi.org/10.3390/ijerph120808971. Sundaramanickam, A., Shanmugam, N., Cholan, S., Kumaresan, S., Madeswaran, P., & Balasubramanian, T. (2016). Spatial variability of heavy metals in estuarine, mangrove and coastal ecosystems along Parangipettai, Southeast coast of India. Environmental Pollution, 218, 186-195. United States Environmental Protection Agency (USEPA). (1989). Risk Assessment Guidance for Superfund . Volume I. Human Health Evaluation Manual (Part A). EPA/540/1-89/002. USEPA. (2001). Exposure Factors Handbook . EPA/600/P-95/002F. USEPA. (2006). National Recommended Water Quality Criteria . United States Environmental Protection Agency. https://www.epa.gov/wqc/national-recommended-water-quality-criteria USEPA. (2009). Drinking Water Standards and Health Advisories Table . United States Environmental Protection Agency. https://www.epa.gov/dwstandardsregulations USEPA. (2011). Regional Screening Levels (RSLs) User's Guide . https://www.epa.gov/risk/regional-screening-levels-rsls Voica, C., Kovacs, M. H., Dehelean, A., Ristoiu, D., & Iordache, A. (2012). ICP-MS determinations of heavy metals in surface waters from Transylvania. Romanian Reports of Physics, 57(7–8), 1184–1193. WHO. (2004). Guidelines for drinking-water quality (3rd ed., Vol. 1). Geneva: World Health Organisation. https://www.who.int/publications/i/item/9241546387 Wiafe, S., Awuah Yeboah, E., Boakye, E., & Ofosu, S. (2022). Environmental risk assessment of heavy metals contamination in the catchment of small-scale mining enclave in Prestea Huni-Valley District, Ghana. Sustainable Environment, 8(1), 0–15. https://doi.org/10.1080/27658511.2022.2062825 World Health Organisation (WHO). (2017). Guidelines for drinking-water quality (4th ed.). Geneva: WHO Press. https://www.who.int/publications/i/item/9789241549950. World Health Organisation (WHO). (2021). Environmental Health Criteria Series – Principles and Methods for Risk Assessment of Chemicals in Food . Geneva: WHO. Xiao, H., Shahab, A., Xi, B., Chang, Q., You, S., Li, J., ... & Li, X. (2021). Heavy metal pollution, ecological risk, spatial distribution, and source identification in sediments of the Lijiang River, China. Environmental Pollution, 269, 116189. Yozukmaz, A., & Yabanli, M. (2023). Heavy metal contamination and potential ecological risk assessment in sediments of Lake Bafa (Turkey). Sustainability, 15(13), 9969. Zakaria, N. A., Ahmed, A. S., & Liew, M. S. (2021). Effect of pH and EC on heavy metal transport in water: A review. Sustainability, 13 (11), 6151. https://doi.org/10.3390/su13116151 Additional Declarations No competing interests reported. Cite Share Download PDF Status: Under Review Version 1 posted Editorial decision: Revision requested 24 Nov, 2025 Reviewers agreed at journal 08 Nov, 2025 Reviews received at journal 17 Oct, 2025 Reviewers agreed at journal 09 Oct, 2025 Reviewers invited by journal 14 Sep, 2025 Editor assigned by journal 05 Sep, 2025 Submission checks completed at journal 30 Aug, 2025 First submitted to journal 30 Aug, 2025 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. 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1","display":"","copyAsset":false,"role":"figure","size":218734,"visible":true,"origin":"","legend":"\u003cp\u003eMap of the study areas in the mining regions.\u003c/p\u003e","description":"","filename":"1.png","url":"https://assets-eu.researchsquare.com/files/rs-7381113/v1/9ec78b1508e2e4c8a116ea35.png"},{"id":91867706,"identity":"86a1c65d-1344-4a38-967f-5a010358019c","added_by":"auto","created_at":"2025-09-22 13:27:28","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":13543,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cem\u003e\u003cstrong\u003eGraph of the concentrationsof heavy metals in the sediment from the mining sites\u003c/strong\u003e\u003c/em\u003e\u003c/p\u003e","description":"","filename":"2.png","url":"https://assets-eu.researchsquare.com/files/rs-7381113/v1/45238c40bac6a9c404660c87.png"},{"id":91865994,"identity":"ce42c2aa-c62f-4c34-b0ac-fd1984e916f3","added_by":"auto","created_at":"2025-09-22 13:19:28","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":12270,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cem\u003e\u003cstrong\u003eGraph of the concentrationsof heavy metals in the water from the mining sites\u003c/strong\u003e\u003c/em\u003e\u003c/p\u003e","description":"","filename":"3.png","url":"https://assets-eu.researchsquare.com/files/rs-7381113/v1/130f4baa790caff1c0839d27.png"},{"id":91868138,"identity":"cffd89c6-d5ba-4bec-9cf0-9a0c152bb5a7","added_by":"auto","created_at":"2025-09-22 13:35:28","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":181117,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cem\u003e\u003cstrong\u003eGeospatial distribution of heavy metal contents in sediments\u003c/strong\u003e\u003c/em\u003e\u003c/p\u003e","description":"","filename":"4.png","url":"https://assets-eu.researchsquare.com/files/rs-7381113/v1/e029cb5564a6e823243d3442.png"},{"id":91869846,"identity":"3307a203-b9f3-470d-a122-7439b149f713","added_by":"auto","created_at":"2025-09-22 13:43:30","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":2193044,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-7381113/v1/39b953c3-a005-4c67-ba24-393f38eb4350.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Assessment of the Water Quality and Toxicological Effects of Toxic Metals in Selected Water Bodies around Gold Mining Areas in Ghana","fulltext":[{"header":"INTRODUCTION","content":"\u003cp\u003eWater is an essential resource for all life and plays a critical role in sustaining biodiversity and maintaining ecological balance. However, gold mining activities, particularly artisanal and small-scale mining (galamsey), have severely compromised water quality in many countries, introducing harmful pollutants such as heavy metals into aquatic ecosystems. Current information suggests that gold mining operations seriously contaminate water supplies with heavy metals (Hadzi et al., \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e2018\u003c/span\u003e). These contaminants, including arsenic (As), mercury (Hg), cadmium (Cd), and lead (Pb), disrupt aquatic biodiversity, degrade water resources, and pose serious health risks through bioaccumulation in the food chain. According to Helmer et al. (1997), water pollution ranks as the second most significant environmental problem after air pollution (Doamekpor et al., \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e2018\u003c/span\u003e). Several studies have shown that the average global concentrations of Hg, Pb, Cd, As, and Zn in river waters exceed the permissible limits suggested by the USEPA and WHO. A study has shown that Asia, Africa, and South America have higher concentrations of these elements than Europe and North America do (Liang et al., \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e2023\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eIn Ghana, mining areas such as Tarkwa, Obuasi, Kenyase and Kwabeng have experienced severe water pollution because of the widespread and unregulated nature of mining operations. These gold mining operations involve excavating and removing soil and sediment in search of gold deposits. These activities have contributed to widespread environmental degradation, particularly in mining areas where improper waste management and uncontrolled operations prevail. Heavy metals can enter the environment directly through anthropogenic activities such as the discharge of untreated wastewater into water bodies, excessive use of fertilisers and pesticides, and natural processes such as forest fires and volcanic activities (Doamekpor et al., \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e2018\u003c/span\u003e). Sediments serve as both sinks and potential sources of these metals, gradually releasing them back into the aquatic system under favourable conditions and thereby preserving the cycle of contamination. (Wiafe et al., \u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). In contrast to the natural enrichment of sediment by geological weathering, the presence of high amounts of trace metals in sediments located at the bottom of the water column in mining rivers can be a useful sign of pollution caused by humans through mining activities in Ghana. Despite global and national awareness of these hazards, many communities in Ghana continue to rely on polluted water for drinking, irrigation, and other essential activities, exacerbating the problem.\u003c/p\u003e\u003cp\u003eThe contamination process in aquatic environments is also governed by complex interactions between water and sediments, with adsorption‒desorption dynamics playing a key role (Miranda et al., \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). The adsorption and desorption of heavy metals in aquatic environments are complex processes and are influenced by the ongoing interactions between water and sediments. Heavy metals have a low toxicity risk when adsorbed to sediments. However, changes in the surrounding environment (such as pH, concentration, and the amount of organic matter) might increase their exposure to living things and reduce the quality of the water. Factors such as pH, electrical conductivity, turbidity, and other physicochemical properties of water, as well as the mineralogy, specific surface area (SSA), and cation exchange capacity (CEC) of sediments, significantly affect these interactions (Miranda et al., \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). They significantly influence the mobility, availability, and eventual bioaccumulation of these metals. The affinity of different metals for specific binding sites in sediments is determined by the ionic properties of the metal species, including the ionic radius, electronegativity, hydrolysis constant, and softness. Furthermore, nutrients such as phosphorus, nitrogen, and organic matter\u0026mdash;all of which are frequently present in aquatic environments\u0026mdash;impact the geochemical behaviour of heavy metals.\u003c/p\u003e\u003cp\u003eWater and sediments can contain various nutrients, depending on their source, surrounding environment, and human activities. Nutrients commonly present in aquatic ecosystems, such as phosphorus, nitrogen, and organic matter, influence the geochemical behaviour of heavy metals, the most common nutrients found in water, including nitrogen. Nitrogen compounds, such as nitrates and nitrites, can be present in water. They can originate from agricultural runoff, wastewater discharge, or natural processes. Additionally, phosphorus and phosphorus compounds, such as phosphates, can be found in water, and they often come from agricultural runoff, sewage, and detergents. Carbon and carbon compounds, including dissolved organic carbon, can be present in water, and these compounds can originate from decaying organic matter, vegetation, and human activities (Obiri-Yeboah et al., \u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). Oxygen, dissolved oxygen, is an essential nutrient for aquatic organisms. It enters the water through aeration from the atmosphere, photosynthesis by aquatic plants, and turbulent mixing. Sulfur and sulfur compounds, such as sulfates, can be present in water (Obiri et al., \u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e2016\u003c/span\u003e). Water also contains trace elements and essential elements, including iron, manganese, zinc, copper, and others. These elements are required in small quantities for biological processes but can become pollutants if present at high concentrations. However, excessive or imbalanced nutrient levels can lead to water quality issues, such as eutrophication or nutrient deficiencies (Rajaee et al., \u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e2015\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eHeavy metals released into the environment persist in water bodies and sediments, creating long-term risks to human and environmental health. These heavy metals are highly toxic, persistent, and bioaccumulative, posing serious risks to aquatic ecosystems, human health, and the overall sustainability of mining communities. This intricate interplay not only affects aquatic life but also elevates human health risks through exposure to contaminated water, fish, and agricultural produce. Reports have indicated that water bodies in mining areas frequently exceed WHO guidelines for safe drinking water, with elevated levels of arsenic, mercury, and lead posing severe health risks (Hadzi et al., \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e2024\u003c/span\u003e; Hadzi et al., \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e2019\u003c/span\u003e). This has led to adverse health outcomes, including developmental disorders, neurological damage, and increased cancer risk in affected populations. The problem is particularly acute in Ghana, where mining communities are often located near water bodies used for drinking, irrigation, and other essential activities. Alarming cases, such as the birth of deformed infants and the prevalence of developmental and neurological disorders, underscore the urgent need for comprehensive toxicological assessments in these mining areas. Contamination, human health risks and the potential ecological risks of heavy metals are determined by employing different methods of assessment certified by international organisations and conventions. These calculated risks and indices have been applied to assess pollution and ecological risks according to the ratio of single or multiple elemental concentrations to background concentrations (Brady et al., \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e2015\u003c/span\u003e; Xiao et al \u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). Pollution assessment indices are important techniques for the comprehensive assessment of contamination in sediments and for predicting the future negative impacts of contaminants on ecosystems (Yozukmaz and Yabanlı, \u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e2023\u003c/span\u003e; Sundaramanickam et al., \u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e2016\u003c/span\u003e). The objective of this study was to determine the extent of heavy metal contamination in surface water around mining communities by (a) determining the concentrations and distributions of the metals in surface water and sediment and (b) evaluating the potential ecological and human health risks of the metals in these media.\u003c/p\u003e"},{"header":"MATERIALS AND METHODS","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e\u003ch2\u003eResearch Design and the Study Area\u003c/h2\u003e\u003cp\u003eTo ensure robust and accurate data collection, the relevant literature was extensively reviewed to understand best practices, methodologies, and potential challenges. The sampling sites were strategically chosen from key gold mining areas (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e) with historical and ongoing mining activities, which are known for high metal contamination and significant environmental impacts. These include Tarkwa, which covers the Bonsa and Nyani Rivers (Essamang); Kenyase, which covers the Tano and Subri Rivers; Obuasi, which focuses on the Nyam River; and Kwabeng, which targets the Birim River. This selection offered a broad geographic and environmental perspective on mining-related contamination. A cross-sectional sampling approach was employed. The inclusion of multiple rivers across different regions enabled a comprehensive assessment of water quality and potential contamination from mining activities. These strategic measures aimed to ensure that the study provides meaningful insights into the environmental impacts of gold mining on aquatic ecosystems and sediment quality. The map and Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003e are were obtained by using ArcMap 10.5.\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003c/div\u003e\n\u003ch3\u003eSample collection, storage, and preservation\u003c/h3\u003e\n\u003cp\u003eThe sediment samples were collected from four points along each river, with each point spaced 100 m apart. The collection was performed from downstream to upstream. A Teflon-coated soil auger was used to collect sediment samples at a depth of 0\u0026ndash;5 cm into polypropylene Zip-Loc bags. Four (4) composite sediment samples each were collected from five (5) rivers, resulting in a total of 20 sediment samples. The sediment samples collected in zip-loc bags were labelled and carefully transported to the Department of Chemistry of the University of Cape Coast for preparation and treatment. The preliminary preparations and analysis of the sediment samples were performed at the Agricultural Technology Village Laboratory of the University of Cape Coast. This approach ensured the reliability and accuracy of the data obtained from the sediment samples.\u003c/p\u003e\u003cp\u003eThe water samples were collected from four points along each river, similar to the sediment samples. Samples were taken at a depth of 0\u0026ndash;5 cm below the surface of the rivers from downstream to upstream and were placed into well-labelled 1.5 L water sample bottles. At each point, 8 discrete samples were combined, and a small amount of nitric acid was added to prevent the samples from being denatured by microorganisms. Four (4) composite water samples were obtained from each river. Once collected, the samples were stored on ice to maintain the temperature between 2 and 4\u0026deg;C.\u003c/p\u003e\n\u003ch3\u003eDigestion and analysis of samples\u003c/h3\u003e\n\u003cdiv id=\"Sec6\" class=\"Section2\"\u003e\u003ch2\u003eWater samples\u003c/h2\u003e\u003cp\u003eFor total metals, 50 mL of each water sample was treated with a 1:1 mixture of concentrated hydrochloric acid (HCl) and nitric acid (HNO₃) for 2 hours and 30 minutes. After digestion, the mixture was cooled and diluted to 50 mL with deionised water. The metal concentrations in the samples were measured via a Nexion 2000P ICP-MS instrument after the instrument was tuned and calibrated. Quality control measures, including method blanks, replicates, and certified reference standards, were implemented to ensure the accuracy and precision of the results. The concentrations obtained from the ICP‒MS were expressed in mg/L. The methods employed are the US EPA 2007, APHA 3120 and USEPA 2008 methods.\u003c/p\u003e\u003c/div\u003e\n\u003ch3\u003eSediment samples\u003c/h3\u003e\n\u003cp\u003eThe total recoverable metals were measured via the procedure described by Brady et al. (2014). The metal levels were determined via the Aqua regia digestion and extraction method. A Teflon microwave tube that had been carefully cleaned was filled with 0.05 g of the sediment sample and extracted with 3 mL of 70% concentrated nitric acid and 1 mL of 30% concentrated hydrochloric acid. The contents were digested via a microwave and increased to 260\u0026deg;C from room temperature over 20 minutes. The digested samples were cooled, diluted to the 50 mL mark, and then centrifuged for 10 min. Inductively coupled plasma‒mass spectrometry (ICP-MS) was then used to analyse approximately 2 mL subsamples.\u003c/p\u003e\u003cp\u003eThe physicochemical properties of the sediment samples, including pH, electrical conductivity, and turbidity, were determined. Ten grams (10 g) of each powdered sediment sample was measured \u003cem\u003ein\u003c/em\u003e their respective centrifuge tubes. 25 mL of \u003cem\u003edeionised\u003c/em\u003e water was added to each centrifuge tube and shaken for 15 minutes using a mechanical shaker. The samples were then centrifuged for 10 minutes. The solution was left to settle by gravity for an hour. The supernatant was poured into a clean 50 mL beaker. The pH was measured via an EDZO T200 meter. All procedures were repeated 3 times, and average pH values were taken. \u003cem\u003eAn\u003c/em\u003e ECTestr11 meter was used to measure the electrical conductivity. Additionally, a blank sample (clear water) was measured via the HYDRO TEST HT 1000 meter to calibrate the instrument. Subsequently, 10 mL of each test water sample was prepared, and turbidity readings were recorded. Quality control measures, including method blanks, replicates, and certified reference standards, were implemented to ensure the accuracy and precision of the results. The concentrations obtained from the ICP‒MS were expressed in mg/L. The methods employed are the US EPA Method 200.7, the APHA Method 3120, and the USEPA Method 2008.\u003c/p\u003e\u003cdiv id=\"Sec8\" class=\"Section2\"\u003e\u003ch2\u003eReproducibility and recovery studies\u003c/h2\u003e\u003cp\u003eReproducibility recovery studies were conducted using standard reference materials, with the methods of packaging, storage, and conveyance carefully controlled to maintain sample integrity throughout the analytical process. The recovery study evaluated how effectively the extraction method retrieves the target analyte from the sample matrix. The performance of the ICP‒MS instrument was evaluated through a recovery study, and the percentages of the heavy metals analysed were within acceptable ranges. Spiked standards were used to evaluate the accuracy of the instrument. When known quantities of metals (standards) are added to a sample, the method\u0026rsquo;s ability to recover those known amounts reflects how well the instrument is performing.\u003c/p\u003e\u003c/div\u003e\n\u003ch3\u003eData and Statistical Analysis\u003c/h3\u003e\n\u003cp\u003eThe IBM SPSS Statistics Package (version 27) and the Excel Analysis ToolPak were used to analyse the study data. Using correlation analysis, relationships between the variables under consideration were examined, with a statistical significance threshold of p\u0026thinsp;\u0026lt;\u0026thinsp;0.05. The grouping was visually summarised with a dendrogram created via hierarchical cluster analysis (HCA). To find important principal components in the data and potential loadings, principal component analysis (PCA) was computed. For the results, the Promax normalised rotation method was used to perform the PCA. A post hoc comparison test was also performed via the Tukey HSD test.\u003c/p\u003e\n\u003ch3\u003eHuman health risk assessment\u003c/h3\u003e\n\u003cp\u003eThe health risk of heavy metals in surface water and sediment from mining areas was estimated through ingestion and dermal contact on the basis of the USEPA risk assessment method (Hadzi et al., \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e2024\u003c/span\u003e). The default values from the risk integrated software for the clean-up of hazardous waste sites (RISC 4.02) were used for each toxicant. In the exposure assessment, the average daily dose (ADD) (Eq.\u0026nbsp;1) for the ingestion of heavy metals in sediment and water was calculated via the following equations from the USEPA protocols of 1989 and 2004:\u003cdiv id=\"Equa\" class=\"Equation\"\u003e\u003cdiv format=\"TEX\" class=\"mathdisplay\" id=\"FileID_Equa\" name=\"EquationSource\"\u003e\n$$\\:\\text{A}\\text{D}\\text{D}\\text{i}\\text{n}\\text{g}\\:\\:\\:\\:\\:\\:=\\:\\:\\:\\:\\:\\:\\frac{\\begin{array}{cc}Cx\u0026amp;\\:\\times\\:Ir\\:\\times\\:Ef\\:\\times\\:Ed\\times\\:OAF\\:\\:\\end{array}}{Bw\\:\\times\\:At}\\:\\times\\:\\text{C}\\text{f}\\:\\:\\:\\:\\:\\:\\:\\:\\:\\:\\:\\:\\:\\:\\:\\:\\:\\:\\:\\:\\:\\:\\:\\:\\:\\:\\:\\:\\:\\:\\:\\:\\:\\left(1\\right)$$\u003c/div\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003ewhere \u003cem\u003eCx\u003c/em\u003e is the concentration of toxicant metals in sediment and water samples (mg\u003cem\u003e/\u003c/em\u003ekg), Ir is the ingestion rate per unit time (kg\u003cem\u003e/\u003c/em\u003eday), Ed is the exposure duration (years), Ef is the exposure frequency (days\u003cem\u003e/\u003c/em\u003eyear), OAF Dermal/Oral Absorption factor (no unit) Bwt is the body weight of the receptor (kg), and At is the average lifetime (years), which is equal to the life expectancy of a resident of Ghana. Cf represents a unit transfer factor, which is \u0026times;10\u003csup\u003e\u0026minus;\u0026thinsp;6\u003c/sup\u003e for soil/sediment. For the conversion factor from year to day, 365 was used. In addition, ADDing is the quantity of heavy metals ingested per kilogram of body weight.\u003c/p\u003e\u003cp\u003eIn this study, surface water and sediment ingestion and dermal contact were considered the main pathways for metal risk assessment because these are the means of contact with toxic metals. The average daily dose for dermal contact was calculated via Eq.\u0026nbsp;2:\u003cdiv id=\"Equb\" class=\"Equation\"\u003e\u003cdiv format=\"TEX\" class=\"mathdisplay\" id=\"FileID_Equb\" name=\"EquationSource\"\u003e\n$$\\:\\text{A}\\text{D}\\text{D}\\text{d}\\text{e}\\text{r}\\text{m}\\:\\:\\:\\:\\:\\:=\\:\\:\\:\\:\\:\\:\\frac{\\begin{array}{cc}Cx\u0026amp;\\:\\times\\:Sa\\:\\times\\:Pc\\times\\:Af\\:\\times\\:Fe\\times\\:Ef\\:\\times\\:Ed\\:\\times\\:Cf\\:\\end{array}}{\\begin{array}{c}\\text{B}\\text{w}\\text{t}\\:\\times\\:\\text{A}\\text{t}\\:\\times\\:365\\end{array}}\\:\\:\\:\\:\\:\\:\\:\\:\\left(2\\right)$$\u003c/div\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003ewhere Sa is the total skin surface area (cm\u003csup\u003e3\u003c/sup\u003e), Cf is the volumetric conversion factor for water (\u003csup\u003e1 L/1000 cm3\u003c/sup\u003e), Af is the adherence factor (mg/cm\u003csup\u003e2\u003c/sup\u003e), and Pc is the chemical-specific dermal permeability constant (cm/h). The hazard quotient (HQ) was calculated via Eq.\u0026nbsp;3:\u003cdiv id=\"Equc\" class=\"Equation\"\u003e\u003cdiv format=\"TEX\" class=\"mathdisplay\" id=\"FileID_Equc\" name=\"EquationSource\"\u003e\n$$\\:\\text{H}\\text{Q}\\:\\:\\:\\:\\:\\:=\\:\\:\\:\\:\\:\\:\\frac{ADD}{\\text{R}\\text{f}\\text{D}}\\:\\:\\:\\:\\:\\:\\:\\:\\:\\:\\:\\:\\:\\:\\:\\:\\:\\:\\:\\:\\:\\:\\:\\:\\:\\:\\:\\:\\:\\:\\:\\:\\:\\:\\:\\:\\:\\:\\:\\:\\:\\:\\:\\left(3\\right)\\:\\:\\:\\:\\:\\:\\:\\:\\:\\:\\:\\:\\:\\:\\:\\:\\:\\:\\:\\:\\:\\:\\:\\:\\:\\:\\:\\:\\:\\:\\:\\:\\:\\:\\:\\:\\:\\:\\:\\:\\:\\:\\:\\:\\:\\:\\:\\:\\:\\:\\:\\:\\:\\:\\:\\:\\:\\:\\:\\:\\:\\:$$\u003c/div\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003ewhere HQ represents the hazard quotient via ingestion or dermal contact (no units) and RfD is the oral/dermal reference dose (mg/L/day).\u003c/p\u003e\u003cp\u003eFinally, the carcinogenic risks (CRs) (Eq.\u0026nbsp;(4)) of the metals were estimated. The range for carcinogenic risk acceptable by the USEPA is 1 \u0026times; 10\u003csup\u003e\u0026minus;\u0026thinsp;6\u003c/sup\u003e to 1 \u0026times; 10\u003csup\u003e\u0026minus;\u0026thinsp;4\u003c/sup\u003e.\u003cdiv id=\"Equd\" class=\"Equation\"\u003e\u003cdiv format=\"TEX\" class=\"mathdisplay\" id=\"FileID_Equd\" name=\"EquationSource\"\u003e\n$$\\:\\text{C}\\text{R}\\text{i}\\text{n}\\text{g}\\:=ADDing\\:\\times\\:SFing\\:\\:\\:\\:\\:\\:\\:\\:\\:\\:\\:\\:\\:\\:\\:\\:\\:\\:\\left(4\\right)\\:\\:\\:\\:\\:\\:\\:\\:\\:\\:\\:\\:\\:\\:\\:\\:\\:\\:\\:\\:\\:\\:\\:\\:\\:\\:\\:\\:\\:\\:\\:\\:\\:\\:\\:\\:\\:\\:\\:\\:\\:\\:\\:\\:\\:\\:\\:\\:\\:\\:\\:\\:\\:\\:\\:\\:\\:\\:\\:\\:\\:\\:\\:\\:$$\u003c/div\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003ewhere CRing represents the carcinogenic risk due to ingestion and where SF is the slope factor (mg/kg)/day.\u003c/p\u003e"},{"header":"RESULTS AND DISCUSSION","content":"\u003cdiv id=\"Sec12\" class=\"Section2\"\u003e\u003ch2\u003eMethod Validation\u003c/h2\u003e\u003cdiv id=\"Sec13\" class=\"Section3\"\u003e\u003ch2\u003eAnalytical Performance of the ICP‒MS Instrument\u003c/h2\u003e\u003cp\u003eThe performance of the ICP‒MS instrument was evaluated through a recovery study, and the percentages of the heavy metals analysed were within acceptable ranges. Spiked standards were used to evaluate the accuracy of the instrument. When samples are spiked with known quantities of metals (standards), the method\u0026rsquo;s ability to recover reflects how well the instrument is performing. As shown in Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e, the 97\u0026ndash;101% recovery of cadmium indicates that the instrument is nearly spot-on for detecting the spiked amount. Mercury's slightly higher recovery (104\u0026ndash;107%) might indicate that more mercury was detected than actually spiked, possibly due to matrix effects or interferences, but it is still within a reasonable range. A recovery study of metals (cadmium, arsenic, mercury, zinc, and lead) via ICP/MS revealed good accuracy and precision.\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eAnalytical performance of the ICP‒MS instrument and the extraction method. n\u0026thinsp;=\u0026thinsp;3\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"6\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003eParameter\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eUnits\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eRL\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003eMB\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c5\"\u003e\u003cp\u003eDUP%RPD\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c6\"\u003e\u003cp\u003eLCS\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eCadmium\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003emg/L\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.00010\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.0001\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0\u0026ndash;14%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e97\u0026ndash;101%\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eArsenic\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003emg/L\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.00050\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.0005\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0\u0026ndash;8%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e93\u0026ndash;96%\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eMercury\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003emg/L\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.00010\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.0001\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e3\u0026ndash;12%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e104\u0026ndash;107%\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eZinc\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003emg/L\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.00500\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.005\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0\u0026ndash;2%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e100\u0026ndash;102%\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eLead\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003emg/L\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.00050\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.0005\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0\u0026ndash;4%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e101\u0026ndash;103%\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv id=\"Sec14\" class=\"Section2\"\u003e\u003ch2\u003eUSEPA, 2008; RL\u0026thinsp;=\u0026thinsp;Reporting Limit; DUP/REP\u0026thinsp;=\u0026thinsp;Duplicate/Replicate sample; LCS\u0026thinsp;=\u0026thinsp;Lab Control Samples\u003c/h2\u003e\u003cp\u003eRecovery rates close to 100% indicate the method's efficiency in detecting spiked analytes, with cadmium (97\u0026ndash;101%), zinc (100\u0026ndash;102%), and lead (101\u0026ndash;103%) showing excellent accuracy. Mercury's slightly higher recovery (104\u0026ndash;107%) suggests a minor overestimation, but it remains within acceptable limits. The method blanks show no contamination, and low DUP %RPD values confirm consistent precision.\u003c/p\u003e\u003cp\u003eOverall, the ICP‒MS instrument shows good accuracy and precision for detecting these metals. The extraction method and instrument are reliable and accurately measure metals with minimal error or interference. Recovery percentages near 100% indicate that the method works well. Slight deviations in recovery are acceptable, and the low DUP %RPD values suggest consistent and reliable results.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec15\" class=\"Section2\"\u003e\u003ch2\u003ePhysiochemical Properties\u003c/h2\u003e\u003cp\u003eTable\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e presents the pH and electrical conductivity (EC) values of the sediment samples from the five mining areas: Obuasi (Nyam River), Tarkwa (Bonsa River), Kenyase (Subiri River), Kenyase (Tano River), and Kwabene (Birim River), represented as OBSD, TBSD, KSD, KTSD, and KWSD, respectively. Similarly, Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e shows the pH, EC, and turbidity values of water samples from the same areas, identified as OB, TB, KS, KT, and KW. The numbers 1, 2, 3, and 4 represent different sampling points within each site. A previous study also reported the concentrations of metals such as cadmium (Cd), arsenic (As), mercury (Hg), and zinc (Zn) in sediment samples, highlighting the environmental impact of mining in these regions (Ameh et al., \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e2020\u003c/span\u003e; Bortey-Sam et al., \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e2019\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eAccording to the World Health Organisation (WHO, 2017), the recommended pH range is 6.5\u0026ndash;8.5. In our study, as shown in Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e, the sediment pH values ranged from 5.0 to 7.0 across the five mining areas. Low pH values, such as TBSD1 (5.89\u0026ndash;6.00), increase metal availability and reduce retention, whereas high pH values, such as OBSD3 (6.76\u0026ndash;6.78), favour metal precipitation and retention (Olatunji \u0026amp; Osibanjo, \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e2019\u003c/span\u003e). The electrical conductivity (EC) varied, with OBSD1 showing the highest EC (1239\u0026ndash;1241 \u0026micro;S) and KWSD3 the lowest (220\u0026ndash;223 \u0026micro;S), indicating that more metal ions are present in regions with higher ECs. Consistent EC values suggest that metals dissolve into the solution, reflecting the correlation between pH and metal availability in the sediments (Affum et al., \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2022\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eThe physicochemical analysis of the water samples revealed low pH values (5.89\u0026ndash;6.79), as shown in Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e, indicating that metals were discharged from the colloidal surfaces into the water, increasing their availability and mobility (Cheng et al., \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). High EC values, especially in OB1 (1239\u0026ndash;1241 \u0026micro;S), suggest the presence of more metal ions in solution, indicating the influence of acid mine drainage (Addo et al., \u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). Turbidity varied significantly, with TB1 (3000\u0026ndash;3800 NTU) and TB3 (3200\u0026ndash;3400 NTU) showing extreme turbidity due to suspended particles, whereas KW2 (6\u0026ndash;9 NTU) and KW3 (6\u0026ndash;11 NTU) had much lower values (Nyame et al., \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e2018\u003c/span\u003e). These variations in pH, EC, and turbidity reflect differences in metal dissolution and water quality across regions. Overall, low pH and high EC values indicate increased metal discharge and mobility, revealing how pH strongly influences metal transfer and environmental pollution levels (WHO, 2017; Zakaria et al., \u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e2021\u003c/span\u003e).\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003ePhysicochemical parameters (pH and EC) of the sediments\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"3\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003eDescription\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003epH RANGE\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eEC RANGE (\u0026micro;s)\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eOBSD1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e6.75\u0026ndash;6.78\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e1239\u0026ndash;1241\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eOBSD2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e6.66\u0026ndash;6.68\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e398\u0026ndash;400\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eOBSD3\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e6.76\u0026ndash;6.78\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e396\u0026ndash;398\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eOBSD4\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e6.75\u0026ndash;6.78\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e394\u0026ndash;396\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eTBSD1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e5.89-6.00\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e202\u0026ndash;212\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eTBSD2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e5.90\u0026ndash;6.02\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e206\u0026ndash;208\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eTBSD3\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e5.89-6.00\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e213\u0026ndash;221\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eTBSD4\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e6.41\u0026ndash;6.43\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e345\u0026ndash;348\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eKSD1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e6.63\u0026ndash;6.65\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e251\u0026ndash;254\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eKSD2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e6.62\u0026ndash;6.64\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e372\u0026ndash;375\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eKSD3\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e6.25\u0026ndash;6.28\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e342\u0026ndash;345\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eKSD4\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e6.26\u0026ndash;6.28\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e349\u0026ndash;351\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eKTSD1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e6.62\u0026ndash;6.64\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e339\u0026ndash;342\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eKTSD2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e6.60\u0026ndash;6.63\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e340\u0026ndash;343\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eKTSD3\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e6.60\u0026ndash;6.62\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e332\u0026ndash;334\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eKTSD4\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e6.76\u0026ndash;6.78\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e400\u0026ndash;403\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eKWSD1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e6.66\u0026ndash;6.68\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e233\u0026ndash;240\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eKWSD2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e6.76\u0026ndash;6.79\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e221\u0026ndash;225\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eKWSD3\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e6.75\u0026ndash;6.78\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e220\u0026ndash;223\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eKWSD4\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e5.89-6.00\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e341\u0026ndash;342\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab3\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003ePhysicochemical parameters (pH, EC and turbidity) of the water samples\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"4\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003eSite Description\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003epH RANGE\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eEC RANGE (\u0026micro;s)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003eTURBIDITY\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eOB1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e6.56\u0026ndash;6.58\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e1239\u0026ndash;1241\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e16\u0026ndash;19\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eOB2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e6.60\u0026ndash;6.62\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e398\u0026ndash;400\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e10\u0026ndash;12\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eOB3\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e6.52\u0026ndash;6.54\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e396\u0026ndash;398\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e10\u0026ndash;11\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eOB4\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e6.46\u0026ndash;6.48\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e394\u0026ndash;396\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e10\u0026ndash;14\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eTB1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e6.51\u0026ndash;6.53\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e202\u0026ndash;212\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e3000\u0026ndash;3800 Dil.\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eTB2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e6.45\u0026ndash;6.47\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e206\u0026ndash;208\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e40\u0026ndash;40\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eTB3\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e6.55\u0026ndash;6.57\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e213\u0026ndash;221\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e3200\u0026ndash;3400 Dil.\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eTB4\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e6.41\u0026ndash;6.43\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e345\u0026ndash;348\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e60\u0026ndash;65\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eKS1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e6.63\u0026ndash;6.65\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e251\u0026ndash;254\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e2700\u0026ndash;2800 Dil.\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eKS2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e6.62\u0026ndash;6.64\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e372\u0026ndash;375\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e570\u0026ndash;575 Dil.\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eKS3\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e6.25\u0026ndash;6.28\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e342\u0026ndash;345\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e930\u0026ndash;945 Dil.\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eKS4\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e6.60\u0026ndash;6.63\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e340\u0026ndash;343\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e1300\u0026ndash;1300 Dil.\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eKT1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e6.26\u0026ndash;6.28\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e349\u0026ndash;351\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e1400\u0026ndash;1400 Dil.\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eKT2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e6.62\u0026ndash;6.64\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e339\u0026ndash;342\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e37\u0026ndash;37\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eKT3\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e6.60\u0026ndash;6.62\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e332\u0026ndash;334\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e76\u0026ndash;76\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eKT4\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e6.76\u0026ndash;6.78\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e400\u0026ndash;403\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e49\u0026ndash;51\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eKW1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e6.66\u0026ndash;6.68\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e233\u0026ndash;240\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e21\u0026ndash;25\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eKW2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e6.76\u0026ndash;6.79\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e221\u0026ndash;225\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e6\u0026ndash;9\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eKW3\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e6.75\u0026ndash;6.78\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e220\u0026ndash;223\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e6\u0026ndash;11\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eKW4\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e5.89-6.00\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e341\u0026ndash;342\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e10\u0026ndash;12\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec16\" class=\"Section2\"\u003e\u003ch2\u003eConcentrations of Heavy Metals in Sediment\u003c/h2\u003e\u003cp\u003eTable\u0026nbsp;\u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e4\u003c/span\u003e presents the concentrations of heavy metals that were determined in water sediment samples taken from the following mining areas: OBSD, TBSD, KSD, KTSD, and KWSD, which represent Obuasi (Nyam River), Tarkwa (Bonsa River), Kenyase (Subiri River), Kenyase (Tano River) and Kwabeng (Birim River), respectively. The numbers 1, 2, 3, and 4 represent the sampling points within the sites. In the study of various sediment samples, the concentrations of metals such as cadmium (Cd), arsenic (As), mercury (Hg), zinc (Zn), and lead (Pb) were measured.\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab4\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 4\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eMean Concentrations (mg/kg) of the Metals in Sediments from the Mining Areas\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"6\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003eSite Description\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eCadmium\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eArsenic\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003eMercury\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c5\"\u003e\u003cp\u003eZinc\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c6\"\u003e\u003cp\u003eLead\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eOBSD1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0.0003\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.500\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.0009\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.30\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e0.074\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eOBSD2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0.0005\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.580\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.0006\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.40\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e0.058\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eOBSD3\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0.0003\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.600\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.0008\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.38\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e0.061\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eOBSD4\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0.0004\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.570\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.0008\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.36\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e0.099\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eTBSD1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0.0007\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.098\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.0014\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.50\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e0.097\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eTBSD2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0.0005\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.170\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.0024\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.60\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e0.059\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eTBSD3\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0.0005\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.094\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.0018\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.60\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e0.077\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eTBSD4\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0.0008\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.160\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.0020\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.60\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e0.086\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eKSD1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eBDL\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.020\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.0005\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.10\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e0.170\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eKSD2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eBDL\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.023\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.0005\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.10\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e0.150\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eKSD3\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eBDL\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.025\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.0005\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.15\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e0.290\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eKSD4\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eBDL\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.019\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.0005\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.13\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e0.310\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eKTSD1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0.0001\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.080\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.0005\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.20\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e0.043\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eKTSD2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eBDL\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.320\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.0003\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.20\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e0.018\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eKTSD3\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0.0001\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.280\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.0003\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.50\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e0.033\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eKTSD4\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eBDL\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.240\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.0004\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.40\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e0.027\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eKWSD1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0.0009\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.130\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.0015\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e2.30\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e0.160\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eKWSD2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0.0005\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.120\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.0021\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.70\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e0.220\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eKWSD3\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0.0006\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.150\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.0018\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e1.90\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e0.540\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eKWSD4\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0.0008\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.170\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.0023\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e1.30\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e0.340\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003ctfoot\u003e\u003ctr\u003e\u003ctd colspan=\"6\"\u003eBDL\u0026thinsp;=\u0026thinsp;Below detection limit\u003c/td\u003e\u003c/tr\u003e\u003c/tfoot\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003eIn the OBSD group, arsenic had the highest concentration, ranging from 0.50\u0026ndash;0.60, whereas cadmium and mercury were found in much lower amounts, between 0.0003\u0026ndash;0.0005 and 0.0006\u0026ndash;0.0009, respectively. Zinc was present at moderate levels, ranging from 0.30 to 0.40. In the TBSD group, mercury and zinc were present at higher concentrations than in the OBSD group, with mercury ranging from 0.0014\u0026ndash;0.0024 and zinc ranging from 0.50\u0026ndash;0.60. However, the As levels were relatively low, between 0.094 and 0.170.\u003c/p\u003e\u003cp\u003eIn the KSD group, cadmium was below the detection limit, and arsenic was found at low levels, between 0.019 and 0.025. The mercury content was consistently 0.0005, and the zinc content ranged from 0.1\u0026ndash;0.15.\u003c/p\u003e\u003cp\u003eIn the KTSD group, cadmium was mostly below the detection limit, with only two samples having a value of 0.0001. Arsenic had a wider range of concentrations, from 0.08\u0026ndash;0.32, whereas mercury ranged from 0.0003\u0026ndash;0.0005, and zinc ranged from 0.2\u0026ndash;0.5.\u003c/p\u003e\u003cp\u003eIn the KWSD group, zinc had the highest concentration among all the groups, ranging from 0.7 to 2.3. Mercury also presented relatively high levels, ranging from 0.0015\u0026ndash;0.0023, whereas cadmium ranged from 0.0005\u0026ndash;0.0009, and arsenic ranged from 0.12\u0026ndash;0.17.\u003c/p\u003e\u003cp\u003eLead is moderately concentrated in Obuasi (up to 0.099 mg/kg) and KWSD (up to 0.540 mg/kg), suggesting lead contamination from industrial or mining sources. Overall, the data highlight significant arsenic contamination in Obuasi, likely due to mining activities, and high zinc and lead concentrations in KWSD, indicating industrial or mining-related pollution. The Cd and Hg levels are generally low across most sites, suggesting that they are less of a concern. Mercury was present in small quantities, with slightly higher levels in the TBSD and KWSD groups. The elevated levels of As, Zn, and Pb at specific sites, particularly Obuasi and KWSD, pose environmental and health risks, necessitating further monitoring and remediation efforts to mitigate their impacts.\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003eThe bar graph in Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e shows the concentrations of heavy metals (Cd, As, Hg, Zn, Pb) in sediments from various rivers in the mining sites: Obuasi, Bonsah, Subri, Tano and Brim River.\u003c/p\u003e\u003cp\u003eCadmium levels are consistently low across all mining sites, indicating minimal contamination. Arsenic is highest in Obuasi, likely due to mining activities, whereas other sites present lower levels. The mercury concentrations are uniformly low, suggesting that there is less concern for Hg pollution. Zinc shows a significant spike in the Obuasi River and moderate levels in the Tarkwa Bonsah and Subri Rivers, indicating notable contamination. The lead levels are highest in Obuasi, with moderate levels in the Tarkwa Bonsah River and Subri River, indicating potential mining-related pollution.\u003c/p\u003e\u003cp\u003eIn general, the Obuasi, Bonsah, and Subri Rivers are the most affected by heavy metal contamination, particularly by As, Zn, and Pb, which likely stem from mining activities. Although the Tano River and Brim River have relatively low levels of contamination, the presence of heavy metals still poses environmental and health risks. Further investigations and remediation measures are recommended, especially in the most impacted areas, such as Obuasi.\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab5\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 5\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eMean sediment values (mg/kg) for the geochemical baseline, sediment guidelines and toxicological reference values\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"14\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c9\" colnum=\"9\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c10\" colnum=\"10\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c11\" colnum=\"11\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c12\" colnum=\"12\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c13\" colnum=\"13\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c14\" colnum=\"14\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003eElements\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eFe\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003ePb\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003eZn\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c5\"\u003e\u003cp\u003eCu\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c6\"\u003e\u003cp\u003eCd\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c7\"\u003e\u003cp\u003eNi\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c8\"\u003e\u003cp\u003eAs\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c9\"\u003e\u003cp\u003eCr\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c10\"\u003e\u003cp\u003eMn\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c11\"\u003e\u003cp\u003eCo\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c12\"\u003e\u003cp\u003eHg\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c13\"\u003e\u003cp\u003eV\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c14\"\u003e\u003cp\u003eAl\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eUSEPA Ecological Screening Values\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e30.2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e124\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e18.7\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e15.9\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e7.24\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003e52.3\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c12\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c13\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c14\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eMean composition of Shales (Wedepohl, 1995)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e3890\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e17\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e52\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e14.3\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e18.6\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003e35\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e\u003cp\u003e527\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c11\"\u003e\u003cp\u003e11.6\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c12\"\u003e\u003cp\u003e0.06\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c13\"\u003e\u003cp\u003e53\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c14\"\u003e\u003cp\u003e77440\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003eCanadian ISQG\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eTEC\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e35\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e123\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e35.7\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.60\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e18\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e5.9\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003e37.3\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c12\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c13\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c14\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003ePEL\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e91.3\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e315\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e197\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e3.53\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e35.9\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e17\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003e90\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c12\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c13\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c14\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003eThe sediment samples from the mining areas generally show low levels of contamination for cadmium (0.0003\u0026ndash;0.0009 mg/kg), arsenic (0.019\u0026ndash;0.60 mg/kg), mercury (0.0003\u0026ndash;0.0024 mg/kg), and zinc (0.10\u0026ndash;2.3 mg/kg), all of which are below the USEPA standards, the mean composition of shales, and the Canadian ISQG guidelines, as presented in Table\u0026nbsp;\u003cspan refid=\"Tab5\" class=\"InternalRef\"\u003e5\u003c/span\u003e.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec17\" class=\"Section2\"\u003e\u003ch2\u003eConcentrations of Heavy Metals in Water\u003c/h2\u003e\u003cp\u003eTable\u0026nbsp;\u003cspan refid=\"Tab6\" class=\"InternalRef\"\u003e6\u003c/span\u003e presents the mean concentrations of heavy metals that were determined in the water and sediment samples taken from the following mining areas: Oboasi (Nyam River), Tarkwa (Bonsah River), Kenyase (Tano and Subiri Rivers) and Kwabene (Birim River). 1, 2, 3, and 4 represent the sampling points at the sites. The performance of the ICP/MS instrument was evaluated through a recovery study, and the percentages of the heavy metals analysed were within acceptable ranges (Affum et al., \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2022\u003c/span\u003e; Boateng et al., \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). To assess the quality of surface water from the five mining areas, heavy metal concentrations were compared against standards from the EC (1998), WHO (\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e2004\u003c/span\u003e), and USEPA (\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e2006\u003c/span\u003e, \u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e2009\u003c/span\u003e) to assess environmental and public health safety.\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab6\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 6\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eConcentrations of heavy metals (mg/L) in surface water from mining areas\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"6\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003eSite Description\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eCadmium\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eArsenic\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003eMercury\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c5\"\u003e\u003cp\u003eZinc\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c6\"\u003e\u003cp\u003eLead\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eOB1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eBDL\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.0570\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eBDL\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.1000\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e0.0011\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eOB2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eBDL\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.0510\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.0003\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.1000\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e0.0015\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eOB3\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eBDL\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.0750\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eBDL\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.0190\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e0.0008\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eOB4\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eBDL\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.0630\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.0004\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.1500\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e0.0054\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eTB1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0.0007\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.0014\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.0001\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.3000\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e0.0220\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eTB2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0.0003\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.0013\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eBDL\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.1000\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e0.0350\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eTB3\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0.0004\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.0011\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eBDL\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.2000\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e0.0110\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eTB4\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0.0052\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.0011\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eBDL\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.0160\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e0.0410\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eKS1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0.0001\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eBDL\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.0007\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.4010\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e0.0036\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eKS2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eBDL\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eBDL\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.0001\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.0800\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e0.0010\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eKS3\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eBDL\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eBDL\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.0005\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.0300\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e0.0053\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eKS4\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0.0004\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eBDL\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.0003\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.0280\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e0.0017\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eKT1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0.0001\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.0390\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.0022\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.0410\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e0.0017\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eKT2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eBDL\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.0280\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.0001\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.0490\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e0.0015\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eKT3\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0.0001\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.0170\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.0001\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.0390\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e0.0015\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eKT4\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0.0001\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.0095\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.0010\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.0460\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e0.0032\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eKW1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eBDL\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eBDL\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eBDL\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.0750\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e0.0640\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eKW2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eBDL\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eBDL\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eBDL\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.0810\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e0.0690\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eKW3\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eBD\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eBD\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eBD\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.0960\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e0.0750\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eKW4\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eBD\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eBD\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eBD\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.087\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e0.0910\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003ctfoot\u003e\u003ctr\u003e\u003ctd colspan=\"6\"\u003eBD\u0026thinsp;=\u0026thinsp;below detection limit\u003c/td\u003e\u003c/tr\u003e\u003c/tfoot\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003eArsenic in some water samples was close to or slightly exceeded the EC and WHO guidelines (0.01 mg/L). Arsenic levels, ranging from 0.0011 mg/L to 0.0750 mg/L, frequently exceed the safe limit of 0.01 mg/L, particularly in samples from OB1, OB3, and KT1, indicating significant contamination (Nyame et al., \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e2018\u003c/span\u003e; WHO, \u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e2004\u003c/span\u003e). Elevated arsenic in drinking water is associated with skin lesions, cancer, and cardiovascular diseases (Cheng et al., \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e2021\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eZinc in certain water samples, such as KS1 (0.4010 mg/L), exceeded the EC guideline of 0.1 mg/L, suggesting a possible need for intervention in specific areas (Ameh et al., \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). The zinc concentrations found in all the samples ranged from 0.016 mg/L to 0.401 mg/L, exceeding the EC's 0.1 mg/L limit but remaining within the USEPA's 5 mg/L threshold (USEPA, \u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e2006\u003c/span\u003e). While zinc is less toxic, elevated levels of zinc can still harm aquatic life.\u003c/p\u003e\u003cp\u003eCadmium, detected in some samples at concentrations up to 0.0052 mg/L, remained below the USEPA's 0.34 mg/L limit, but its presence is concerning due to its toxicity (USEPA, \u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e2006\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eThe lead concentrations are generally low but relatively high in KW (up to 0.0910 mg/L) and TB (up to 0.0410 mg/L) but exceed the WHO and EC standards of 0.01 mg/L and approach the USEPA's 0.015 mg/L limit. Chronic lead exposure is linked to neurotoxicity, especially in children (Olatunji \u0026amp; Osibanjo, \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e2019\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eMercury levels ranged from 0.0001 mg/L to 0.0022 mg/L, with one sample slightly exceeding the USEPA's 0.002 mg/L limit, highlighting potential health risks (Addo et al., \u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e2020\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eGenerally, the data indicate significant arsenic contamination in Obuasi and zinc contamination in Tarkwa, Bonsah and KS, likely due to mining activities. Cadmium, mercury, and lead levels are lower but still present in some areas, particularly in KW for Pb. The elevated levels of arsenic, zinc, and lead at specific sites pose environmental risks, especially to water quality, necessitating further monitoring and remediation efforts to mitigate their potential impact on ecosystems and human health (Affum et al., \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2022\u003c/span\u003e; WHO, \u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e2004\u003c/span\u003e; USEPA, \u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e2009\u003c/span\u003e).\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003eThe bar graph in Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e shows the concentrations of heavy metals (Cd, As, Hg, Zn, Pb) in the water from five mining sites: the Obuasi, Tarkwa, Bonsah, Subri River, Tano River, and Birim River.\u003c/p\u003e\u003cp\u003eThe cadmium levels were consistently low across all the sites, indicating minimal contamination. Arsenic is notably high in Obuasi, suggesting contamination from mining activities, whereas other sites present minimal As levels. The mercury concentrations are negligible across all the sites, indicating that there is little concern for Hg pollution.\u003c/p\u003e\u003cp\u003eZinc is the most elevated metal, particularly in the Tarkwa Bonsah River and Subri River, with all sites showing moderate to high Zn levels, indicating widespread contamination likely from mining.\u003c/p\u003e\u003cp\u003eLead is highest in the Birim River, followed by the Obuasi and Subri Rivers, indicating potential localised sources of Pb pollution. While Cd and Hg pose less concern, elevated levels of Zn and Pb, particularly in Tarkwa Bonsah, the Subri River, and the Birim River, present significant environmental and health risks.\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab7\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 7\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eMaximum permitted metal concentrations (mg/L) for water\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"10\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c9\" colnum=\"9\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c10\" colnum=\"10\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003eWater Quality Guidelines\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eAs\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eCr\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003eCu\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c5\"\u003e\u003cp\u003eFe\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c6\"\u003e\u003cp\u003eMn\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c7\"\u003e\u003cp\u003eNi\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c8\"\u003e\u003cp\u003ePb\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c9\"\u003e\u003cp\u003eZn\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c10\"\u003e\u003cp\u003eCo\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eEC (1998)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e0.01\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.05\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.05\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e0.02\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e0.01\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003e0.1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u003cp\u003e-\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eWHO (\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e2004\u003c/span\u003e)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e0.01\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.05\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e-\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.4\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e0.07\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e0.01\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003e-\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u003cp\u003e-\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eUSEPA (\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e2009\u003c/span\u003e)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e0.01\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e1.3\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.3\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.05\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e-\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e0.015\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003e5\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u003cp\u003e0.11\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eUSEPA (\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e2006\u003c/span\u003e)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e0.34\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e-\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.013\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e-\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e0.47\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e-\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003e0.12\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u003cp\u003e-\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003eOverall, the findings reveal compromised water quality in some mining areas, particularly the high arsenic levels in Obuasi mining areas, necessitating urgent remediation efforts to safeguard the environment and public health. Compared with various water quality guidelines, including those from the EC (1998), WHO (\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e2004\u003c/span\u003e), and USEPA (\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e2006\u003c/span\u003e, \u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e2009\u003c/span\u003e), the detected levels of heavy metals revealed that most of the heavy metals detected were below the maximum permissible limits set by these guidelines, as presented in Table\u0026nbsp;\u003cspan refid=\"Tab7\" class=\"InternalRef\"\u003e7\u003c/span\u003e above.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec18\" class=\"Section2\"\u003e\u003ch2\u003eStatistical evaluation of the results\u003c/h2\u003e\u003cdiv id=\"Sec19\" class=\"Section3\"\u003e\u003ch2\u003eSediment\u003c/h2\u003e\u003cp\u003eTwo-way ANOVA was conducted to assess the effects of the sampling location and type of heavy metals on the concentrations in the environmental samples. The interaction effect between location and heavy metals was statistically significant, F(16, 75)\u0026thinsp;=\u0026thinsp;12.9, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001, accounting for 38.1% of the total variation. The main effect of location was also significant, F(4, 75)\u0026thinsp;=\u0026thinsp;14.3, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001, explaining 10.5% of the variance. Similarly, a significant main effect was found for the type of heavy metals, F(4, 75)\u0026thinsp;=\u0026thinsp;50.9, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001, contributing 37.6% to the total variation. The residual error variance accounted for only 1.7%, indicating the strong explanatory power of the model. These findings justify further exploration through post hoc comparisons to identify specific location differences for each heavy metal.\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab8\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 8\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eANOVA two-way analysis of the sediment results\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"7\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003eANOVA table\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003e% of total variation\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eSS\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003eDF\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c5\"\u003e\u003cp\u003eMS\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c6\"\u003e\u003cp\u003eF (DFn, DFd)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c7\"\u003e\u003cp\u003eP value\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eInteraction\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e38.1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e4.69\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e16\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.293\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003eF (16, 75)\u0026thinsp;=\u0026thinsp;12.9\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003eP\u0026thinsp;\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eLocation\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e10.5\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e1.3\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e4\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.324\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003eF (4, 75)\u0026thinsp;=\u0026thinsp;14.3\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003eP\u0026thinsp;\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eHeavy Metal\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e37.6\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e4.62\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e4\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e1.16\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003eF (4, 75)\u0026thinsp;=\u0026thinsp;50.9\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003eP\u0026thinsp;\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eResidual\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e1.7\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e75\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.0227\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003ePost hoc analysis via the Tukey HSD test revealed no statistically significant differences in \u003cb\u003ecadmium\u003c/b\u003e concentrations across the five locations (OBSD, TBSD, KSD, KTSD, and KWSD). The cadmium concentrations ranged from below the detection limit (BDL) in the KSD to 0.0007\u0026thinsp;\u0026plusmn;\u0026thinsp;0.0002 mg/kg in the KWSD, indicating low but generally consistent levels across sites. The lack of significant differences suggests that cadmium contamination may be uniformly minimal in the study area.\u003c/p\u003e\u003cp\u003eFor \u003cb\u003eAs\u003c/b\u003e, there were statistically significant differences between OBSDs (0.5630\u0026thinsp;\u0026plusmn;\u0026thinsp;0.043 mg/kg) and the other locations. This suggests that OBSBS had significantly greater arsenic concentrations than the other sites did, which ranged from 0.0218\u0026thinsp;\u0026plusmn;\u0026thinsp;0.003 mg/kg in KSD to 0.2300\u0026thinsp;\u0026plusmn;\u0026thinsp;0.105 mg/kg in KTSD. These differences may indicate localised sources of As pollution at OBSD, necessitating targeted investigation or remediation efforts. \u003cb\u003eMercury\u003c/b\u003e levels did not significantly differ across locations. The concentrations varied slightly, from 0.0004\u0026thinsp;\u0026plusmn;\u0026thinsp;0.0001 mg/kg in KTSD to 0.0019\u0026thinsp;\u0026plusmn;\u0026thinsp;0.0004 mg/kg in both TBSD and KWSD. This homogeneity in mercury concentrations suggests a relatively even distribution of mercury exposure across the sampled sites, with no location exceeding significantly elevated thresholds. Significant variation was observed in \u003cb\u003ethe zinc\u003c/b\u003e concentrations across the sites. KWSD (1.5500\u0026thinsp;\u0026plusmn;\u0026thinsp;0.700 mg/kg) was significantly greater than that at all other locations: TBSD (0.5750\u0026thinsp;\u0026plusmn;\u0026thinsp;0.050 mg/kg), OBSD (0.3600\u0026thinsp;\u0026plusmn;\u0026thinsp;0.043 mg/kg), KTSD (0.3250\u0026thinsp;\u0026plusmn;\u0026thinsp;0.150 mg/kg), and KSD (0.1200\u0026thinsp;\u0026plusmn;\u0026thinsp;0.024 mg/kg). This indicates that the KWSD had markedly elevated zinc levels in the sediment, which may indicate source pollution or geochemical anomalies in the area. There were no statistically significant differences detected in lead concentrations among the five locations. The concentrations ranged from 0.0303\u0026thinsp;\u0026plusmn;\u0026thinsp;0.011 mg/kg in the KTSD to 0.3150\u0026thinsp;\u0026plusmn;\u0026thinsp;0.168 mg/kg in the KWSD. Although the values varied numerically, the lack of significant differences implies that lead distribution may be influenced by broadly distributed environmental factors rather than location-specific inputs.\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab9\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 9\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eVariations in concentrations of the metals in the sediments between sites\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"6\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003eLocation\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eCadmium\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eArsenic\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003eMercury\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c5\"\u003e\u003cp\u003eZinc\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c6\"\u003e\u003cp\u003eLead\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eOBSD\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0.0004a\u0026thinsp;\u0026plusmn;\u0026thinsp;0.0001\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.5630a\u0026thinsp;\u0026plusmn;\u0026thinsp;0.043\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.0008a\u0026thinsp;\u0026plusmn;\u0026thinsp;0.0001\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.3600a\u0026thinsp;\u0026plusmn;\u0026thinsp;0.043\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.0730a\u0026thinsp;\u0026plusmn;\u0026thinsp;0.019\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eTBSD\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0.0006a\u0026thinsp;\u0026plusmn;\u0026thinsp;0.0002\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.1310b\u0026thinsp;\u0026plusmn;\u0026thinsp;0.040\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.0019a\u0026thinsp;\u0026plusmn;\u0026thinsp;0.0004\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.5750ab\u0026thinsp;\u0026plusmn;\u0026thinsp;0.050\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.0798a\u0026thinsp;\u0026plusmn;\u0026thinsp;0.016\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eKSD\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eBDL\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.0218b\u0026thinsp;\u0026plusmn;\u0026thinsp;0.003\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.0005a\u0026thinsp;\u0026plusmn;\u0026thinsp;0.0001\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.1200b\u0026thinsp;\u0026plusmn;\u0026thinsp;0.024\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.2300a\u0026thinsp;\u0026plusmn;\u0026thinsp;0.082\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eKTSD\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0.0001a\u0026thinsp;\u0026plusmn;\u0026thinsp;0.0001\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.2300b\u0026thinsp;\u0026plusmn;\u0026thinsp;0.105\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.0004a\u0026thinsp;\u0026plusmn;\u0026thinsp;0.0001\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.3250a\u0026thinsp;\u0026plusmn;\u0026thinsp;0.150\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.0303a\u0026thinsp;\u0026plusmn;\u0026thinsp;0.011\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eKWSD\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0.0007a\u0026thinsp;\u0026plusmn;\u0026thinsp;0.0002\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.143b\u0026thinsp;\u0026plusmn;\u0026thinsp;0.022\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.0019a\u0026thinsp;\u0026plusmn;\u0026thinsp;0.0004\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e1.5500c\u0026thinsp;\u0026plusmn;\u0026thinsp;0.700\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.3150a\u0026thinsp;\u0026plusmn;\u0026thinsp;0.168\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003ctfoot\u003e\u003ctr\u003e\u003ctd colspan=\"6\"\u003eNote: Means in a column sharing the same letter are not statistically significant at p\u0026thinsp;\u0026le;\u0026thinsp;0.05 (Tukey\u003c/td\u003e\u003c/tr\u003e\u003c/tfoot\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003ePost hoc test).\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv id=\"Sec20\" class=\"Section2\"\u003e\u003ch2\u003eWater\u003c/h2\u003e\u003cp\u003eTwo-way analysis of variance (ANOVA) was conducted to assess the influence of location and heavy metal type on concentration levels across the five sampling sites. The interaction effect between location and heavy metals was not statistically significant, F(16, 75)\u0026thinsp;=\u0026thinsp;1.58, p\u0026thinsp;=\u0026thinsp;.095, accounting for 14.6% of the total variation. The main effect of location was also not significant, F(4, 75)\u0026thinsp;=\u0026thinsp;0.735, p\u0026thinsp;=\u0026thinsp;.571, explaining only 1.69% of the variation. However, the type of heavy metal had a statistically significant main effect on the concentration, F(4, 75)\u0026thinsp;=\u0026thinsp;17.6, p\u0026thinsp;\u0026lt;\u0026thinsp;.001, accounting for 40.5% of the total variation. The residual variance contributed 43.2%, indicating that while metal type significantly affected concentrations, location and its interaction with metal type did not.\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab10\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 10\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eANOVA two-way analysis of the water results\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"7\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003eANOVA table\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003e% of total variation\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eSS\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003eDF\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c5\"\u003e\u003cp\u003eMS\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c6\"\u003e\u003cp\u003eF (DFn, DFd)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c7\"\u003e\u003cp\u003eP value\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eInteraction\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e14.6\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.0515\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e16\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.00322\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003eF (16, 75)\u0026thinsp;=\u0026thinsp;1.58\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003eP\u0026thinsp;=\u0026thinsp;0.095\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eLocation\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e1.69\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.00598\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e4\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.0015\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003eF (4, 75)\u0026thinsp;=\u0026thinsp;0.735\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003eP\u0026thinsp;=\u0026thinsp;0.571\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eHeavy Metal\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e40.5\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.143\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e4\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.0357\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003eF (4, 75)\u0026thinsp;=\u0026thinsp;17.6\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003eP\u0026thinsp;\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eResidual\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.153\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e75\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.00203\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003ePost hoc comparisons via the Tukey HSD test revealed no statistically significant differences in cadmium concentrations across the locations (OB, TB, KS, KT, and KW). The concentrations were generally low or below the detection limits (BDLs), with KS and KT reporting minimal levels of 0.0001\u0026thinsp;\u0026plusmn;\u0026thinsp;0.0002 mg/kg and 0.0001\u0026thinsp;\u0026plusmn;\u0026thinsp;0.0001 mg/kg, respectively, and TB showing a slightly higher but still statistically similar value of 0.0017\u0026thinsp;\u0026plusmn;\u0026thinsp;0.0024 mg/kg. Cadmium was not detected at OB or KW. These results suggest minimal variation and low contamination by cadmium across all the sites. The As concentrations did not vary significantly among the sampling locations. The OB had the highest mean concentration at 0.0615\u0026thinsp;\u0026plusmn;\u0026thinsp;0.0102 mg/kg, followed by KT (0.0234\u0026thinsp;\u0026plusmn;\u0026thinsp;0.0129 mg/kg). TB and KS reported lower levels, whereas KW had arsenic levels below the detection limit. Despite these numerical differences, the lack of statistical significance indicates that arsenic was relatively evenly distributed across these locations and was not concentrated in any specific area. The mercury content across the sites also showed no statistically significant differences. The highest concentration was observed at KT (0.0009\u0026thinsp;\u0026plusmn;\u0026thinsp;0.0010 mg/kg), whereas OB and KS presented lower values (0.0002\u0026thinsp;\u0026plusmn;\u0026thinsp;0.0002 mg/kg and 0.0004\u0026thinsp;\u0026plusmn;\u0026thinsp;0.0003 mg/kg, respectively). Mercury was below the detection limits at TB and KW. These findings imply that mercury presence is minimal and not significantly location dependent in this study area. Although variation was observed in the zinc concentrations, with TB (0.1540\u0026thinsp;\u0026plusmn;\u0026thinsp;0.1230 mg/kg) and KS (0.1350\u0026thinsp;\u0026plusmn;\u0026thinsp;0.1791 mg/kg) resulting in relatively higher means than KT (0.0438\u0026thinsp;\u0026plusmn;\u0026thinsp;0.0046 mg/kg), post hoc analysis confirmed no statistically significant differences across locations. OB and KW had intermediate zinc concentrations of 0.0923\u0026thinsp;\u0026plusmn;\u0026thinsp;0.0542 mg/kg and 0.0848\u0026thinsp;\u0026plusmn;\u0026thinsp;0.0090 mg/kg, respectively. These findings suggest that the zinc levels were consistent throughout the study area despite apparent numeric fluctuations.\u003c/p\u003e\u003cp\u003eThe lead concentrations followed a similar trend. The highest mean concentration was recorded at KW (0.0748\u0026thinsp;\u0026plusmn;\u0026thinsp;0.0117 mg/kg), which was substantially greater than those at the other sites, including TB (0.0273\u0026thinsp;\u0026plusmn;\u0026thinsp;0.0134 mg/kg) and KS (0.0029\u0026thinsp;\u0026plusmn;\u0026thinsp;0.0019 mg/kg). Despite these disparities, the differences were not statistically significant. This finding indicates that while lead concentrations vary in magnitude, these differences are not robust enough to reflect true spatial variation.\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab11\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 11\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eVariations in concentrations of selected metals (mg/L) in water from different sites.\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"6\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003eSite\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eCadmium\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eArsenic\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003eMercury\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c5\"\u003e\u003cp\u003eZinc\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c6\"\u003e\u003cp\u003eLead\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eOB\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eBDL\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.0615a\u0026thinsp;\u0026plusmn;\u0026thinsp;0.0102\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.0002a\u0026thinsp;\u0026plusmn;\u0026thinsp;0.0002\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.0923a\u0026thinsp;\u0026plusmn;\u0026thinsp;0.0542\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.0022a\u0026thinsp;\u0026plusmn;\u0026thinsp;0.0022\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eTB\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0.0017a\u0026thinsp;\u0026plusmn;\u0026thinsp;0.0024\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.0012a\u0026thinsp;\u0026plusmn;\u0026thinsp;0.0002\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eBDL\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.1540a\u0026thinsp;\u0026plusmn;\u0026thinsp;0.1230\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.0273a\u0026thinsp;\u0026plusmn;\u0026thinsp;0.0134\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eKS\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0.0001a\u0026thinsp;\u0026plusmn;\u0026thinsp;0.0002\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eBDL\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.0004a\u0026thinsp;\u0026plusmn;\u0026thinsp;0.0003\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.1350a\u0026thinsp;\u0026plusmn;\u0026thinsp;0.1791\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.0029a\u0026thinsp;\u0026plusmn;\u0026thinsp;0.0019\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eKT\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0.0001a\u0026thinsp;\u0026plusmn;\u0026thinsp;0.0001\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.0234a\u0026thinsp;\u0026plusmn;\u0026thinsp;0.0129\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.0009a\u0026thinsp;\u0026plusmn;\u0026thinsp;0.0010\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.0438a\u0026thinsp;\u0026plusmn;\u0026thinsp;0.0046\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.0020a\u0026thinsp;\u0026plusmn;\u0026thinsp;0.0008\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eKW\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eBDL\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eBDL\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eBDL\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.0848a\u0026thinsp;\u0026plusmn;\u0026thinsp;0.0090\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.0748a\u0026thinsp;\u0026plusmn;\u0026thinsp;0.0117\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003ctfoot\u003e\u003ctr\u003e\u003ctd colspan=\"6\"\u003eNote: Means in a column sharing the same letter are not statistically significant at p\u0026thinsp;\u0026le;\u0026thinsp;0.05 (Tukey post hoc test).\u003c/td\u003e\u003c/tr\u003e\u003c/tfoot\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec21\" class=\"Section2\"\u003e\u003ch2\u003eGeospatial Distribution of Heavy Metal Contents in Sediment\u003c/h2\u003e\u003cp\u003eThe six geospatial maps in the image discuss and compare the concentrations of heavy metals across the study sites. These maps visually represent the spatial distributions of Pb, Zn, Cd, Hg, and As concentrations in sediment samples from selected mining-impacted rivers in Ghana, namely, the Nyam, Bonssah, Tano, Subiri, and Birim rivers. The geostatistical interpolation maps reveal stark spatial variations in the concentrations of heavy metals in sediments across sampling sites, which indicate both localised pollution hotspots and regional contamination trends associated with artisanal and large-scale mining activities.\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003eThe first map (top-left) and the second map (top-middle) depict elevated lead concentrations around the Subiri River (Kenyasi), Tano River, and Obuasi River, represented in red and orange color bands. Kwabeng and Tarkwa Bonsu were present at relatively low concentrations, as shown in green. These high levels likely result from historical challenges (illegal small-scale mining) and improper mine waste disposal in Kenyasi and Obuasi (Affum et al., \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). Lead toxicity, especially through sediment ingestion by benthic organisms, is a major environmental concern (Olatunji \u0026amp; Osibanjo, \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e2019\u003c/span\u003e). The arsenic map (bottom-right) shows a contamination hotspot centred on Obuasi, highlighted in red. Surrounding areas such as Tarkwa and Kwabeng are relatively low (green).\u003c/p\u003e\u003cp\u003eObuasi is known for high arsenic content due to gold ore roasting and leaching during mining processes (Cheng et al., \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e2021\u003c/span\u003e; Nyame et al., \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e2018\u003c/span\u003e). The toxicity and mobility of As pose severe risks to both aquatic ecosystems and human health through bioaccumulation. Zinc concentrations are elevated (orange‒red) in the Subiri River (Kenyasi) and the northern part of Obuasi, whereas Kwabeng and Tarkwa appear to have lower levels. Zinc, although essential for biological functions, becomes toxic at high concentrations. The elevated levels in Kenyasi may stem from mine tailings and surface runoff (Ameh et al., \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). Mercury levels, as shown in the bottom-left map, are mostly low (green) across the study areas, with only minor increases near the Subiri River and Tano River.\u003c/p\u003e\u003cp\u003eThe relative uniformity suggests that mercury usage has been limited in recent years, which may be attributed to the fight of the Government of Ghana against galamsey activities. However, the high spots could be due to the few artisanal gold recovery practices where mercury amalgamation is common (Addo et al., \u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). The cadmium map (bottom-middle) highlights Tarkwa Bonsu as a contamination hotspot (red), whereas Kwabeng and Kenyasi remain within safer levels (green). The high Cd in Tarkwa reflects current mining discharges or weathering of cadmium-rich ores (Boateng et al., \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). Chronic exposure to cadmium is associated with kidney dysfunction and bioaccumulation in aquatic organisms (WHO, \u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e2004\u003c/span\u003e).\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec22\" class=\"Section2\"\u003e\u003ch2\u003eRisk Assessment Analysis for the Metal Levels in the Sediment and Water\u003c/h2\u003e\u003cdiv id=\"Sec23\" class=\"Section3\"\u003e\u003ch2\u003eSediment\u003c/h2\u003e\u003cp\u003eThe risk assessment table (Table\u0026nbsp;\u003cspan refid=\"Tab12\" class=\"InternalRef\"\u003e12\u003c/span\u003e) of the sediment analysis results compares the hazard quotient (HQ) and cancer risk (CR) for both adults and children across the five sampling sites. An HQ above 1 implies that a noncarcinogenic risk is significant (USEPA, 1989), and a cancer risk above the range of 6.0E-06\u0026ndash;4.0E-04 suggests a significant public health concern (WHO, 2017, 2021).\u003c/p\u003e\u003cp\u003eThe OBS results revealed a moderate noncarcinogenic risk, especially for mercury exposure, and a moderate carcinogenic risk due to arsenic, although the ranges were within acceptable limits. The results from TBSD demonstrate a relatively high noncarcinogenic risk due to elevated mercury exposure, especially for children, and a notable carcinogenic risk from arsenic. Site KSD presents minimal health risks, with both HQ and CR values well within safe limits. It is the least hazardous site among the five sites studied.\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab12\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 12\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eHazard Quotient and Cancer Risk Assessment for the Sediment\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"7\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003eSite\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eElements\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eZn\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003eAs\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c5\"\u003e\u003cp\u003eCd\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c6\"\u003e\u003cp\u003ePb\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c7\"\u003e\u003cp\u003eHg\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eDose Adult\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e1.26E-07\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e3.61E-08\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e-\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e1.29E-09\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e2.05E-10\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eDose Child\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e2.36E-07\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e6.74E-08\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e-\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e2.41E-09\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e3.84E-10\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eOB\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eHQ Adult\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e4.21E-07\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e1.20E-04\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e-\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e1.29E-06\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e2.05E-07\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eHQ Child\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e7.86E-07\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e2.25E-04\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e-\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e2.41E-06\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e3.84E-07\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eCR Adult\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e-\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e5.42E-08\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e-\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e1.94E-09\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e3.08E-10\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eCR Child\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e-\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e1.01E-07\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e-\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e2.05E-08\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e3.26E-09\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eDose Adult\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e2.11E-07\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e7.22E-10\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e9.69E-10\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e1.6E-08\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e5.87E-11\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eDose Child\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e3.94E-07\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e1.35E-09\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e1.81E-09\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e2.99E-08\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e1.1E-10\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eTB\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eHQ Adult\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e7.03E-07\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e2.41E-06\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e9.69E-07\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e1.6E-05\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e5.87E-08\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eHQ Child\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e1.31E-06\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e4.49E-06\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e1.81E-06\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e2.99E-05\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e1.1E-07\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eCR Adult\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e-\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e1.08E-09\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e5.91E-07\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e2.4E-08\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e8.81E-11\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eCR Child\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e-\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e2.02E-09\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e1.1E-06\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e2.54E-07\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e9.32E-10\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eDose Adult\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e1.85E-07\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e-\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e1.47E-10\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e1.7E-09\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e2.35E-10\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eDose Child\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e3.45E-07\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e-\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e2.74E-10\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e3.18E-09\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e4.38E-10\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eKS\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eHQ Adult\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e6.15E-07\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e-\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e1.47E-07\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e1.7E-06\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e2.35E-07\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eHQ Child\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e1.15E-06\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e-\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e2.74E-07\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e3.18E-06\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e4.38E-07\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eCR Adult\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e-\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e-\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e8.95E-08\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e2.55E-09\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e3.52E-10\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eCR Child\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e-\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e-\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e1.67E-07\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e2.7E-08\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e3.73E-09\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eDose Adult\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e5.99E-08\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e1.37E-08\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e5.87E-11\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e1.16E-09\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e4.99E-10\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eDose Child\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e1.12E-07\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e2.56E-08\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e1.1E-10\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e2.17E-09\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e9.32E-10\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eKT\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eHQ Adult\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e2.00E-07\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e4.58E-05\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e5.87E-08\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e1.16E-06\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e4.99E-07\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eHQ Child\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e3.73E-07\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e8.54E-05\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e1.1E-07\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e2.17E-06\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e9.32E-07\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eCR Adult\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e-\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e2.06E-08\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e3.58E-08\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e1.74E-09\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e7.49E-10\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eCR Child\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e-\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e3.84E-08\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e6.68E-08\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e1.84E-08\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e7.92E-09\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eDose Adult\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e1.16E-07\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e-\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e-\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e4.39E-08\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e-\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eDose Child\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e2.17E-07\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e-\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e-\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e8.19E-08\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e-\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eKW\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eHQ Adult\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e3.87E-07\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e-\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e-\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e4.39E-05\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e-\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eHQ Child\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e7.22E-07\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e-\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e-\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e8.19E-05\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e-\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eCR Adult\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e-\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e-\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e-\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e6.58E-08\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e-\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eCR Child\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e-\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e-\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e-\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e6.96E-07\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e-\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003eThe heavy metals from site KTSD pose a low to moderate risk (Table\u0026nbsp;\u003cspan refid=\"Tab13\" class=\"InternalRef\"\u003e13\u003c/span\u003e), with some concern regarding arsenic-related cancer risk, although the levels remain below the upper threshold. The contamination of metals at site KWSD presented the highest cumulative health risk among the sites, especially for children. The combination of an elevated HQ for mercury and a high CR for arsenic suggests a significant public health concern (ATSDR, 2022).\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab13\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 13\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eComparative Summary of the Results for Adults and Children for Sediment\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"4\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003eSite\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eHQ (Child)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eCR (Child)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003eOverall Risk Level\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eOBSD\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e5.34E-02\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e2.79E-05\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eModerate\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eTBSD\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e1.30E-01\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e4.60E-05\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eHigh\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eKSD\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e3.42E-02\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e2.36E-05\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eLow\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eKTSD\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e2.60E-02\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e7.35E-06\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eLow to Moderate\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eKWSD\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e1.32E-01\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e5.15E-05\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eHighest (near-critical)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003eThe hazard and cancer risk results for adults and children from the five sites showed HQ values below the critical threshold of 1 and CR values within the WHO's acceptable range. However, the magnitude of these risks varies across the sites. KWSD poses the greatest risk to human health, especially for children, because of elevated concentrations of mercury (HQ) and arsenic (CR). TBSSs follow closely, with similar levels. In contrast, KSD appears to be the least risky site, with all measured values far below the thresholds of concern (USEPA, \u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e2001\u003c/span\u003e; WHO, 2021).\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv id=\"Sec24\" class=\"Section2\"\u003e\u003ch2\u003eWater\u003c/h2\u003e\u003cp\u003eTable\u0026nbsp;\u003cspan refid=\"Tab14\" class=\"InternalRef\"\u003e14\u003c/span\u003e presents the risk and hazard assessment results for the five sampling sites. Noncarcinogenic and carcinogenic health risks associated with selected heavy metals in water bodies. The analysis compares the results with the World Health Organisation\u0026rsquo;s threshold values. Although the exposure levels of arsenic and mercury at OBSD are noticeable, the values remain within the WHO limits, suggesting moderate but controlled risk for both noncarcinogenic and carcinogenic effects, which requires continued surveillance.\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab14\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 14\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eHazard quotient and cancer risk assessment for the sediment\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"7\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003eSite\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eElements\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eZn\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003eAs\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c5\"\u003e\u003cp\u003eCd\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c6\"\u003e\u003cp\u003ePb\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c7\"\u003e\u003cp\u003eHg\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eDose Adult\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e1.26E-07\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e3.61E-08\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e1.29E-09\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e2.05E-10\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eDose Child\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e2.36E-07\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e6.74E-08\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e2.41E-09\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e3.84E-10\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eOB\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eHQ Adult\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e4.21E-07\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e1.20E-04\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e1.29E-06\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e2.05E-07\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eHQ Child\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e7.86E-07\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e2.25E-04\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e2.41E-06\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e3.84E-07\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eCR Adult\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e5.42E-08\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e1.94E-09\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e3.08E-10\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eCR Child\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e1.01E-07\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e2.05E-08\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e3.26E-09\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eDose Adult\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e2.11E-07\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e7.22E-10\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e9.69E-10\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e1.6E-08\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e5.87E-11\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eDose Child\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e3.94E-07\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e1.35E-09\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e1.81E-09\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e2.99E-08\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e1.1E-10\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eTB\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eHQ Adult\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e7.03E-07\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e2.41E-06\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e9.69E-07\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e1.6E-05\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e5.87E-08\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eHQ Child\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e1.31E-06\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e4.49E-06\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e1.81E-06\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e2.99E-05\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e1.1E-07\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eCR Adult\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e1.08E-09\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e5.91E-07\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e2.4E-08\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e8.81E-11\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eCR Child\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e2.02E-09\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e1.1E-06\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e2.54E-07\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e9.32E-10\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eDose Adult\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e1.85E-07\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e1.47E-10\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e1.7E-09\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e2.35E-10\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eDose Child\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e3.45E-07\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e2.74E-10\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e3.18E-09\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e4.38E-10\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eKS\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eHQ Adult\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e6.15E-07\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e1.47E-07\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e1.7E-06\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e2.35E-07\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eHQ Child\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e1.15E-06\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e2.74E-07\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e3.18E-06\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e4.38E-07\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eCR Adult\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e8.95E-08\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e2.55E-09\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e3.52E-10\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eCR Child\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e1.67E-07\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e2.7E-08\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e3.73E-09\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eDose Adult\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e5.99E-08\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e1.37E-08\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e5.87E-11\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e1.16E-09\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e4.99E-10\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eDose Child\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e1.12E-07\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e2.56E-08\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e1.1E-10\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e2.17E-09\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e9.32E-10\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eKT\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eHQ Adult\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e2.00E-07\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e4.58E-05\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e5.87E-08\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e1.16E-06\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e4.99E-07\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eHQ Child\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e3.73E-07\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e8.54E-05\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e1.1E-07\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e2.17E-06\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e9.32E-07\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eCR Adult\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e2.06E-08\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e3.58E-08\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e1.74E-09\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e7.49E-10\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eCR Child\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e3.84E-08\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e6.68E-08\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e1.84E-08\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e7.92E-09\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eDose Adult\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e1.16E-07\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e4.39E-08\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eDose Child\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e2.17E-07\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e8.19E-08\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eKW\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eHQ Adult\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e3.87E-07\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e4.39E-05\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eHQ Child\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e7.22E-07\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e8.19E-05\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eCR Adult\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e6.58E-08\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eCR Child\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e6.96E-07\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003eTBSBS results in elevated noncarcinogenic risk, especially due to mercury in children, and relatively high carcinogenic risk from arsenic exposure. While still acceptable, the values approach the upper WHO limit, indicating heightened public health concerns. All values are well below critical limits, with no significant risk detected. The site represents a low environmental health risk, making it the safest site among the five sites. All hazard and cancer risk values at KTSD are well within safety thresholds, although they are slightly higher than those at KSD. The risk is low to moderate, and KTSD remains a relatively safe site. While still within the WHO\u0026rsquo;s upper limit, the KWSD poses the greatest combined health risk due to the highest HQ values for mercury, suggesting elevated noncarcinogenic risk and the highest CR values for arsenic, nearing the upper boundary of acceptable cancer risk. The elevated HQ and CR values suggest that people coming into contact with this water body face a greater risk of contracting chronic toxicity and potential cancer illnesses (ATSDR, 2022; WHO, 2021). This site should be prioritised for environmental intervention and public health education, especially for populations engaging in recreational or domestic water use.\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab15\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 15\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eComparative Summary of the Results for Adults and Children for Sediment\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"4\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003eSite\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eMax HQ (Child)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eMax CR (Child)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003eOverall Risk Ranking\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eOBSD\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e5.34E-02\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e2.79E-05\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eModerate\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eTBSD\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e1.30E-01\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e4.60E-05\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eHigh\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eKSD\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e3.42E-02\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e2.36E-05\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eLow\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eKTSD\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e2.60E-02\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e7.35E-06\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eLow to Moderate\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eKWSD\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e1.32E-01\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e5.15E-05\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eHighest \u0026ndash; Near Critical\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003eThe results from all the sites remain within the WHO\u0026rsquo;s acceptable limits for both noncarcinogenic and carcinogenic risks. However, the degree of exposure varies at various sites. KWSD is the most concerning site, with the highest levels of both HQ and CR, particularly affecting children. TBSDs also present notable risks, especially from arsenic. The KSD and KTSD water bodies are the least risky rivers, posing minimal danger to public health (USEPA, \u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e2001\u003c/span\u003e; WHO, 2021). OBSBS poses a moderate risk, especially from mercury. Regular monitoring and community education are needed, particularly in KWSD and TBSD water bodies, to prevent long-term health consequences from chronic exposure to mercury and arsenic.\u003c/p\u003e\u003cdiv id=\"Sec25\" class=\"Section3\"\u003e\u003ch2\u003eLimitations of the study\u003c/h2\u003e\u003cp\u003eExposure to metals in the air or other media, such as food, resulting from gold mining was not considered in this study. Exclusion of these exposure pathways may lead to either an overestimation or underestimation of the potential human health risks faced by gold miners in the study area. Nevertheless, the findings remain relevant and carry important policy implications. The human health risk assessment method applied in this study offers a useful approach for identifying pollutants of public health concern, thereby helping to prioritise future research and policy interventions.\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e"},{"header":"CONCLUSION","content":"\u003cp\u003eThis study investigated the concentrations of heavy metals in surface water and sediment samples from five mining areas in Ghana. The findings revealed significant contamination in certain mining areas, particularly Obuasi (Nyam River) and Kwabeng (Birim River), where elevated levels of arsenic, zinc, and lead were detected. The heavy metal concentrations in the sediment were highest in Obuasi for arsenic and zinc. In water, arsenic levels exceeded the WHO limit in several samples, notably in Obuasi. Zinc was also high in Kenyanaceae.\u003c/p\u003e\u003cp\u003eThese levels, especially those of arsenic and zinc, exceeded both the World Health Organisation (WHO) and the European Commission (EC) guidelines, raising concerns about environmental and human health risks. Although cadmium and mercury levels are generally below detection limits, their presence in some areas, even at low concentrations, remains a concern because of their toxic nature. Research has also revealed that physicochemical parameters, such as low pH and high electrical conductivity, influence metal mobility and availability in the environment.\u003c/p\u003e\u003cp\u003eThis study provides insights into mining activities in Ghana, which significantly contribute to the contamination of surface waters and sediments with heavy metals, particularly in the Obuasi, Kwabeng and Tarkwa areas. The elevated concentrations of As, Pb, and Zn in these areas highlight the pressing need for immediate intervention to address the environmental and health risks associated with heavy metal pollution.\u003c/p\u003e"},{"header":"Declarations","content":"\u003ch2\u003eConflicts of interest\u003c/h2\u003e\u003cp\u003eThe authors declare that there are no conflicts of interest.\u003c/p\u003e\u003ch2\u003eAuthor Contribution\u003c/h2\u003e\u003cp\u003eDu-Bois Asante, Isaac Tabiri Henneh and George Yaw Hadzi conceived, designed the research and secured funding for the research. George Yaw. Hadzi, Du-Bois Asante, Isaac Tabiri Henneh collected the data, performed the laboratory experiments and analysed the data. The full-length paper was drafted by George Yaw Hadzi. The statistical analysis was performed by Albert Ofori. The risk assessment was estimated by Joseph Kwaku Adjei. All authors edited, shaped and provided critical feedback on the manuscript. All authors helped in critically revising the article for intellectual content and approved the version for publication.\u003c/p\u003e\u003ch2\u003eAcknowledgement\u003c/h2\u003e\u003cp\u003eThe authors want to acknowledge Osei Adjemang and Jesse Azebiik Anak for their immense support during the period of obtaining this data\u003c/p\u003e\u003ch2\u003eData Availability\u003c/h2\u003e\u003cp\u003eAll data generated or analysed during this study are included in this published article. Graphs were generated using Microsoft Excel. Risk indices were calculated using the algorithms described in the manuscript.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eAddo, M. A., Armah, F. A., Osei, J., \u0026amp; Afrifa, E. K. A. (2020). Water quality assessment in mining-affected communities in Ghana. \u003cem\u003eJournal of Environmental and Public Health\u003c/em\u003e, 2020, 1\u0026ndash;11. https://doi.org/10.1155/2020/9084526\u003c/li\u003e\n\u003cli\u003eAffum, H. A., Appiah-Effah, E., \u0026amp; Nyarko, K. B. (2022). Influence of mining activities on water quality in Ghana. \u003cem\u003eEnvironmental Monitoring and Assessment, 194\u003c/em\u003e(9), 675. https://doi.org/10.1007/s10661-022-10232-4\u003c/li\u003e\n\u003cli\u003eAgency for Toxic Substances and Disease Registry (ATSDR). (2022). \u003cem\u003eToxicological Profiles for Heavy Metals\u003c/em\u003e. U.S. Department of Health and Human Services. https://www.atsdr.cdc.gov\u003c/li\u003e\n\u003cli\u003eAmeh, E., Ufuoma, C., \u0026amp; Okorie, V. (2020). Impact of physicochemical parameters on heavy metal mobility in mining sediments. \u003cem\u003eEnvironmental Chemistry Letters, 18\u003c/em\u003e(3), 873\u0026ndash;884. https://doi.org/10.1007/s10311-019-00962-3\u003c/li\u003e\n\u003cli\u003eBoateng, T. K., Opoku, F., \u0026amp; Akoto, O. (2020). Heavy metals contamination and risk assessment in sediments of the Pra Basin, Ghana. \u003cem\u003eToxicology Reports, 7\u003c/em\u003e, 360\u0026ndash;368. https://doi.org/10.1016/j.toxrep.2020.01.015\u003c/li\u003e\n\u003cli\u003eBortey-Sam, N., Nakayama, S. M. M., Ikenaka, Y., Akoto, O., Baidoo, E., \u0026amp; Ishizuka, M. (2019). Heavy metal pollution and ecological risk assessment in sediments of the Pra River Basin, Ghana. \u003cem\u003eEnvironmental Science and Pollution Research, 26\u003c/em\u003e(21), 21536\u0026ndash;21550. https://doi.org/10.1007/s11356-019-05253-9\u003c/li\u003e\n\u003cli\u003eBrady, J. P., Ayoko, G. A., Martens, W. N., \u0026amp; Goonetilleke, A. (2015). Development of a hybrid pollution index for heavy metals in marine and estuarine sediments. Environmental monitoring and assessment, 187(5), 306.\u003c/li\u003e\n\u003cli\u003eCheng, H., Li, M., \u0026amp; Zhao, C. (2021). Arsenic contamination and health effects: A review of current knowledge. \u003cem\u003eEcotoxicology and Environmental Safety, 216\u003c/em\u003e, 112197. https://doi.org/10.1016/j.ecoenv.2021.112197\u003c/li\u003e\n\u003cli\u003eDoamekpor, L. K., Abusa, Y., Ketemepi, H. K., Klake, R. K., Doamekpor, M. E. A. M., Anom, P. A., \u0026amp; Obeng, J. (2018). Assessment of heavy metals in water and sediments of Sakumo II, chemo, and specie Lagoons-Ghana. West African Journal of Applied Ecology, 26(2), 56\u0026ndash;71.\u003c/li\u003e\n\u003cli\u003eEC (European Commission). (1998). \u003cem\u003eCouncil Directive 98/83/EC on the quality of water intended for human consumption\u003c/em\u003e. https://eur-lex.europa.eu/legal-content/EN/TXT/?uri=CELEX%3A31998L0083\u003c/li\u003e\n\u003cli\u003eHadzi, G. Y., Essumang, D. K., \u0026amp; Ayoko, G. A. (2018). Assessment of contamination and health risk of heavy metals in selected water bodies around gold mining areas in Ghana. Environmental Monitoring and Assessment, 190(7). https://doi.org/10.1007/s10661-018-6750-z\u003c/li\u003e\n\u003cli\u003eHadzi, G. Y., Ayoko, G. A., Essumang, D. K., \u0026amp; Osae, S. K. (2019). Contamination impact and human health risk assessment of heavy metals in surface soils from selected major mining areas in Ghana. Environmental Geochemistry and Health, 41(6), 2821-2843.\u003c/li\u003e\n\u003cli\u003eHadzi, G. Y., Essumang, D. K., \u0026amp; Ayoko, G. A. (2024). Assessment of contamination and potential ecological risks of heavy metals in riverine sediments from gold mining and pristine areas in Ghana. Journal of Trace Elements and Minerals, 7(June 2022), 100109. https://doi.org/10.1016/j.jtemin.2023.100109\u003c/li\u003e\n\u003cli\u003eKhan, J. (2023). Synthesis and Applications of Fluorescent Chemosensors: A Review. In Journal of Fluorescence. https://doi.org/10.1007/s10895-023-03455-1\u003c/li\u003e\n\u003cli\u003eLiang, E., Li, J., Li, B., Liu, S., Ma, R., Yang, S., Cai, H., Xue, Z., \u0026amp; Wang, T. (2023). Roles of dissolved organic matter (DOM) in shaping the distribution pattern of heavy metal in the Yangtze River. In Journal of Hazardous Materials (Vol. 460). https://doi.org/10.1016/j.jhazmat.2023.132410.\u003c/li\u003e\n\u003cli\u003eMiranda, L. S., Wijesiri, B., Ayoko, G. A., Egodawatta, P., \u0026amp; Goonetilleke, A. (2021). Water-sediment interactions and mobility of heavy metals in aquatic environments. Water Research, 202(June), 117386. https://doi.org/10.1016/j.watres.2021.117386.\u003c/li\u003e\n\u003cli\u003eNyame, F. K., Armah, T. K., \u0026amp; Osae, S. (2018). Heavy metal contamination in surface water and sediments from a gold mining area in Ghana. \u003cem\u003eToxicological \u0026amp; Environmental Chemistry, 100\u003c/em\u003e(4), 1\u0026ndash;12. https://doi.org/10.1080/02772248.2018.1435160\u003c/li\u003e\n\u003cli\u003eObiri, S., Yeboah, P. O., Osae, S., \u0026amp; Adu-Kumi, S. (2016). Levels of arsenic, mercury, cadmium, copper, lead, zinc, and manganese in serum and whole blood of resident adults from mining and nonmining communities in Ghana. Environmental Science and Pollution Research, 23(16), 16589\u0026ndash;16597. https://doi.org/10.1007/s11356-016-6537-0.\u003c/li\u003e\n\u003cli\u003eObiri-Yeboah, A., Nyantakyi, E. K., Mohammed, A. R., Yeboah, S. I. I. K., Domfeh, M. K., \u0026amp; Abokyi, E. (2021). Assessing potential health effects of lead and mercury and the impact of illegal mining activities in the Bonsa River, Tarkwa Nsuaem, Ghana. Scientific African, 13, e00876. https://doi.org/10.1016/j.sciaf.2021.e00876.\u003c/li\u003e\n\u003cli\u003eOlatunji, A. S., \u0026amp; Osibanjo, O. (2019). Human exposure to lead contamination in mining zones. \u003cem\u003eEnvironmental Earth Sciences, 78\u003c/em\u003e(9), 121. https://doi.org/10.1007/s12665-019-8137-9\u003c/li\u003e\n\u003cli\u003eRajaee, M., Obiri, S., Green, A., Long, R., Cobbina, S. J., Nartey, V., Buck, D., Antwi, E., \u0026amp; Basu, N. (2015). Integrated Assessment of Artisanal and Small-Scale Gold Mining In Ghana\u0026mdash;Part 2: Natural Sciences Review. International Journal of Environmental Research and Public Health, 12(8), 8971\u0026ndash;9011. https://doi.org/10.3390/ijerph120808971.\u003c/li\u003e\n\u003cli\u003eSundaramanickam, A., Shanmugam, N., Cholan, S., Kumaresan, S., Madeswaran, P., \u0026amp; Balasubramanian, T. (2016). Spatial variability of heavy metals in estuarine, mangrove and coastal ecosystems along Parangipettai, Southeast coast of India. Environmental Pollution, 218, 186-195.\u003c/li\u003e\n\u003cli\u003eUnited States Environmental Protection Agency (USEPA). (1989). \u003cem\u003eRisk Assessment Guidance for Superfund\u003c/em\u003e. Volume I. Human Health Evaluation Manual (Part A). EPA/540/1-89/002.\u003c/li\u003e\n\u003cli\u003eUSEPA. (2001). \u003cem\u003eExposure Factors Handbook\u003c/em\u003e. EPA/600/P-95/002F.\u003c/li\u003e\n\u003cli\u003eUSEPA. (2006). \u003cem\u003eNational Recommended Water Quality Criteria\u003c/em\u003e. United States Environmental Protection Agency. https://www.epa.gov/wqc/national-recommended-water-quality-criteria\u003c/li\u003e\n\u003cli\u003eUSEPA. (2009). \u003cem\u003eDrinking Water Standards and Health Advisories Table\u003c/em\u003e. United States Environmental Protection Agency. https://www.epa.gov/dwstandardsregulations\u003c/li\u003e\n\u003cli\u003eUSEPA. (2011). \u003cem\u003eRegional Screening Levels (RSLs) User\u0026apos;s Guide\u003c/em\u003e. https://www.epa.gov/risk/regional-screening-levels-rsls\u003c/li\u003e\n\u003cli\u003eVoica, C., Kovacs, M. H., Dehelean, A., Ristoiu, D., \u0026amp; Iordache, A. (2012). ICP-MS determinations of heavy metals in surface waters from Transylvania. Romanian Reports of Physics, 57(7\u0026ndash;8), 1184\u0026ndash;1193.\u003c/li\u003e\n\u003cli\u003eWHO. (2004). \u003cem\u003eGuidelines for drinking-water quality\u003c/em\u003e (3rd ed., Vol. 1). Geneva: World Health Organisation. https://www.who.int/publications/i/item/9241546387\u003c/li\u003e\n\u003cli\u003eWiafe, S., Awuah Yeboah, E., Boakye, E., \u0026amp; Ofosu, S. (2022). Environmental risk assessment of heavy metals contamination in the catchment of small-scale mining enclave in Prestea Huni-Valley District, Ghana. Sustainable Environment, 8(1), 0\u0026ndash;15. https://doi.org/10.1080/27658511.2022.2062825 \u003c/li\u003e\n\u003cli\u003eWorld Health Organisation (WHO). (2017). \u003cem\u003eGuidelines for drinking-water quality\u003c/em\u003e (4th ed.). Geneva: WHO Press. https://www.who.int/publications/i/item/9789241549950.\u003c/li\u003e\n\u003cli\u003eWorld Health Organisation (WHO). (2021). \u003cem\u003eEnvironmental Health Criteria Series \u0026ndash; Principles and Methods for Risk Assessment of Chemicals in Food\u003c/em\u003e. Geneva: WHO.\u003c/li\u003e\n\u003cli\u003eXiao, H., Shahab, A., Xi, B., Chang, Q., You, S., Li, J., ... \u0026amp; Li, X. (2021). Heavy metal pollution, ecological risk, spatial distribution, and source identification in sediments of the Lijiang River, China. Environmental Pollution, 269, 116189.\u003c/li\u003e\n\u003cli\u003eYozukmaz, A., \u0026amp; Yabanli, M. (2023). Heavy metal contamination and potential ecological risk assessment in sediments of Lake Bafa (Turkey). Sustainability, 15(13), 9969.\u003c/li\u003e\n\u003cli\u003eZakaria, N. A., Ahmed, A. S., \u0026amp; Liew, M. S. (2021). Effect of pH and EC on heavy metal transport in water: A review. \u003cem\u003eSustainability, 13\u003c/em\u003e(11), 6151. https://doi.org/10.3390/su13116151\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"scientific-reports","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"scirep","sideBox":"Learn more about [Scientific Reports](http://www.nature.com/srep/)","snPcode":"","submissionUrl":"","title":"Scientific Reports","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"Scientific Reports","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"Heavy metals, Water quality, Sediments, Contamination, Human health risk, Physico-chemical parameters","lastPublishedDoi":"10.21203/rs.3.rs-7381113/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-7381113/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eThe study aimed to assess the water quality and toxicological effects of some toxic metals in selected water bodies around artisanal gold mining areas in Ghana. This study investigated the toxicological effects of heavy metals and the water quality of mining-affected water bodies in five mining areas of Ghana, focusing on heavy metals such as arsenic (As), cadmium (Cd), mercury (Hg), lead (Pb), and zinc (Zn). These metals were assessed on the basis of their distribution, concentration, and human and environmental risks, alongside key physicochemical characteristics (organic matter, pH and conductivity) known to influence the interactions and dynamics of heavy metals in surface water and sediment matrices. The cation exchange capacity (CEC), which influences metal adsorption and mobility in sediment, was also explored. Forty (40) composite samples were digested and analysed for heavy metals (As, Cd, Hg, Pb, and Zn) via ICP-MS. The sediment pH ranged from 5.89 to 6.78 mg/kg, and the water pH ranged from 5.89 to 6.79. The electrical conductivity (EC) values of the sediments peaked at 1241 \u0026micro;S/cm. The As level in the water exceeded the WHO limit (0.01 mg/L), reaching 0.075 mg/L in Obuasi, whereas the zinc concentration peaked at 0.401 mg/L in Kenyase. The arsenic and zinc concentrations in the sediment were highest in Obuasi at 0.6 mg/kg and 0.4 mg/kg, respectively, suggesting substantial contamination and environmental risks. These findings align with broader studies on the behaviour of heavy metals in aquatic ecosystems, where adsorption‒desorption dynamics are regulated by sediment properties such as mineralogy, specific surface area, and cation exchange capacity. These interactions indicate the urgent need for targeted strategies to mitigate health and environmental risks.\u003c/p\u003e","manuscriptTitle":"Assessment of the Water Quality and Toxicological Effects of Toxic Metals in Selected Water Bodies around Gold Mining Areas in Ghana","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-09-22 13:19:23","doi":"10.21203/rs.3.rs-7381113/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2025-11-24T17:13:50+00:00","index":"","fulltext":""},{"type":"reviewerAgreed","content":"327614822204140139181341100722965559492","date":"2025-11-08T20:08:28+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-10-17T14:43:28+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"324057769132573345649798293556005181596","date":"2025-10-09T11:07:52+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2025-09-14T12:55:18+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2025-09-05T07:02:22+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2025-08-30T22:42:01+00:00","index":"","fulltext":""},{"type":"submitted","content":"Scientific Reports","date":"2025-08-30T22:38:34+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"scientific-reports","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"scirep","sideBox":"Learn more about [Scientific Reports](http://www.nature.com/srep/)","snPcode":"","submissionUrl":"","title":"Scientific Reports","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"Scientific Reports","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"86a136f5-cc17-4dd2-abac-da5a9130d9bd","owner":[],"postedDate":"September 22nd, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"under-review","subjectAreas":[{"id":54685551,"name":"Physical sciences/Chemistry"},{"id":54685552,"name":"Earth and environmental sciences/Environmental sciences"}],"tags":[],"updatedAt":"2026-04-08T23:08:18+00:00","versionOfRecord":[],"versionCreatedAt":"2025-09-22 13:19:23","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-7381113","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-7381113","identity":"rs-7381113","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}