Identification and Quantification of Primary Pollutants Impacting Aquaculture in Mine Surface Plant Areas

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Water samples were collected from four sites near mining operations to analyze key pollutants, including iron, copper, and cobalt, along with water quality parameters such as pH, dissolved oxygen (DO), temperature, and conductivity. Results revealed elevated cobalt levels (up to 60 mg/L at Site 1, far exceeding the recommended 0.01 mg/L), significant copper contamination, and slightly acidic conditions, particularly near the contamination source. Dissolved oxygen levels were lowest at Site 1 (4.5 ± 0.6 mg/L), indicating potential stress on aquatic life. The study demonstrated that proximity to mining activities exacerbates pollution levels, with pollutant concentrations decreasing at sites further away due to natural attenuation. The toxic effects of heavy metals, low DO, and high conductivity on aquatic ecosystems were assessed, highlighting severe risks such as gill damage, bioaccumulation, and osmotic stress, particularly at Site 1. These findings align with related studies on the ecological impacts of mining and emphasize the urgent need for targeted mitigation strategies. Recommendations include implementing advanced pollution control technologies, enhancing monitoring systems, and promoting sustainable mining practices. The study underscores the importance of balancing industrial activities with environmental preservation to safeguard aquatic ecosystems and local livelihoods. Environmental Engineering Heavy metals aquaculture mining pollutants environmental Kalumbila Figures Figure 1 1. Introduction and Background Aquaculture in regions near mining operations faces significant environmental challenges due to the release of various pollutants that can impact water quality and aquatic life. Mining activities, especially those in surface plants, introduce a wide range of contaminants into surrounding water bodies, including heavy metals, chemicals, and other pollutants (Jones & Wang, 2021). These pollutants can have both acute and chronic effects on aquatic ecosystems, impacting fish health, growth rates, and reproductive cycles, ultimately threatening the sustainability of aquaculture operations in these areas. This study focuses on identifying and quantifying the primary pollutants in mine surface plant areas that affect aquaculture, with the goal of providing insights for better environmental management in Kalumbila District. Previous studies have shown that heavy metals such as arsenic, lead, mercury, and cadmium are among the most common contaminants released from mining operations into nearby water systems (Miller et al., 2020). When these metals accumulate in water bodies, they can be toxic to fish even at low concentrations, leading to impaired immune function, reduced growth, and mortality in sensitive species (Smith & Khan, 2019). Additionally, other pollutants like suspended solids, sulfates, and nitrates from mining processes can alter the pH levels and oxygen availability in aquatic environments, further stressing aquatic life and diminishing water quality for aquaculture use (Li et al., 2018). By focusing on pollutants in the surface plant areas of Kalumbila's mines, this study aims to create a baseline of knowledge that could be applied to mitigate adverse effects on aquaculture operations and improve water management practices in mining zones. The increasing demand for fish and aquaculture products has highlighted the importance of sustainable practices that protect the environment while supporting food security (FAO, 2022). In areas affected by mining, understanding the specific pollutants and their impacts on aquatic ecosystems is essential for establishing guidelines and regulations to balance economic activities with environmental conservation. This research employed water sampling and pollutant analysis techniques to identify key contaminants and assess their concentrations. 1.1 Problem statement The rising mining activities in Kalumbila, Zambia, particularly copper production, have led to the discharge of harmful pollutants like heavy metals (arsenic, lead, mercury) into nearby water bodies, exceeding safe limits for aquatic ecosystems. In 2020, Zambia’s mining sector produced approximately 800,000 metric tons of copper (Zambia Chamber of Mines, 2021), and arsenic levels in water bodies near Kalumbila have reached 1.5 µg/L, well above the World Health Organization's recommended limits for aquatic life (WHO, 2017). These contaminants pose significant risks to aquaculture operations, causing fish toxicity, reproductive failure, and mortality (Smith & Khan, 2019), while suspended solids from mining runoff can contribute to turbidity levels exceeding 100 NTU, which hinders light penetration and affects fish respiratory health (Gonzalez et al., 2021 ). Despite the growing concern, there is a lack of comprehensive studies on the full extent of these pollutants and their impact on local aquaculture, which this study aims to address by identifying and quantifying the primary pollutants in mining areas. 1.2 The purpose of the study The purpose of this study is to identify and quantify the primary pollutants originating from mine surface plant areas in Kalumbila District that adversely affect aquaculture, with the aim of understanding their impact on water quality and aquatic life. The study is aimed at contributing to the advancement of sustainable aquaculture practices in mine surface plant areas by providing a comprehensive understanding of the current state of the field, identifying gaps, and guiding future research and development efforts in the domain. 1.3 Research Objectives To identify the primary pollutants present in the mine surface plant areas of Kalumbila District that impact aquaculture water quality. To quantify the concentration levels of key pollutants in water bodies surrounding the mine surface plants. To assess the potential toxic effects of these pollutants on fish species and aquatic ecosystems. 1.4 Scope of the study The scope of this study encompasses the identification and quantification of primary pollutants affecting aquaculture in the mine surface plant areas of Kalumbila District. This research focuses on pollutants commonly associated with mining activities, such as heavy metals (e.g., arsenic, lead, mercury), chemical by-products, and suspended solids, and examines their concentrations in surrounding water bodies. Sampling will be conducted in specific surface water sites near the Kalumbila mines, where pollutant levels will be measured and analyzed for their potential impact on water quality and aquatic life. The study will also evaluate the toxicological effects of these pollutants on fish species to determine their implications for local aquaculture practices. However, the research does not extend to other environmental or socioeconomic impacts of mining, nor does it assess pollutants beyond the designated surface plant areas. 2. Literature review 2.1 Introduction The impact of mining on aquatic ecosystems has been a significant focus in environmental research, particularly due to the release of pollutants that can detrimentally affect aquaculture. Mining activities introduce a range of pollutants into nearby water systems, including heavy metals, suspended solids, sulfates, and chemical by-products, all of which can compromise water quality and pose risks to fish and other aquatic organisms (Jones & Wang, 2021). This review synthesizes findings on the primary pollutants from mining operations, their effects on aquaculture, and the methods used for identifying and quantifying these pollutants in water bodies adjacent to mine surface plants. 2.2 Heavy Metals and Toxicity in Aquatic Systems Heavy metals are among the most well-documented pollutants from mining activities, with elements such as arsenic, lead, mercury, and cadmium commonly found in mine runoff. Research indicates that these metals can accumulate in aquatic systems and become toxic to fish even at low concentrations, disrupting immune function, reproductive health, and overall fish viability (Smith & Khan, 2019). For instance, arsenic exposure has been shown to reduce fish growth rates and impact reproductive success, while lead and mercury are known to impair neurological function and development in aquatic species (Miller et al., 2020). The bioaccumulation of heavy metals in fish tissue not only threatens aquaculture viability but also poses risks to human health through the consumption of contaminated fish (Chen et al., 2021 ). Understanding the concentration and distribution of these heavy metals in mine-affected waters is therefore critical for managing the risks associated with aquaculture in mining regions. 2.2.1 Chemical By-products and Suspended Solids Aside from heavy metals, mining operations often release a variety of chemical by-products and suspended solids that affect water quality. Chemical reagents used in mineral processing, such as cyanide, ammonia, and sulfuric acid, can alter the pH balance and oxygen levels in water, leading to unfavorable conditions for fish and other aquatic organisms (Li et al., 2018). Suspended solids, which may include particles of soil, rock, and metallic compounds, can increase water turbidity, reduce light penetration, and interfere with the respiratory systems of fish (Tan & Mohamad, 2020). Studies have shown that elevated levels of suspended solids can clog fish gills, impair feeding efficiency, and reduce fish growth rates, making it essential to monitor and manage these pollutants in aquaculture-sensitive areas near mining sites (Gonzalez et al., 2021 ). The interaction between suspended solids and chemical contaminants can also compound toxicity, further stressing aquatic environments and potentially causing fish mortality in areas with high pollutant concentrations. 2.2.2 Quantification and Analytical Techniques for Pollutant Assessment The identification and quantification of mining pollutants in water bodies require precise analytical methods to ensure accurate results. Common techniques used to assess heavy metal concentrations include atomic absorption spectroscopy (AAS), inductively coupled plasma mass spectrometry (ICP-MS), and X-ray fluorescence (XRF) (Park et al., 2019). These methods enable researchers to detect trace levels of metals in water samples, providing critical data for evaluating pollutant impacts on aquaculture. For chemical by-products and suspended solids, techniques such as high-performance liquid chromatography (HPLC), spectrophotometry, and turbidity measurements are frequently employed to measure concentration levels and analyze pollutant compositions (Johnson et al., 2022). The combination of these analytical tools allows researchers to create a comprehensive pollution profile, which is essential for understanding the extent of mining-related contamination in aquatic systems and its implications for aquaculture. 2.2.3 Impact on Aquaculture and Ecosystem Health Numerous studies have documented the detrimental effects of mining pollutants on aquaculture viability and ecosystem health in areas surrounding mining operations. Pollutants from mine surface plants can lead to declines in fish populations, reduction in species diversity, and disruption of aquatic food chains, ultimately threatening aquaculture sustainability in these regions (Singh et al., 2017). Aquaculture operations in proximity to mining activities often struggle with reduced fish yields, slower growth rates, and increased mortality due to the cumulative impact of pollutants on water quality and fish health (FAO, 2022). These effects underscore the importance of pollutant identification and quantification as essential steps in mitigating the ecological impact of mining on aquaculture and maintaining sustainable fish production in affected regions. 2.3 Mining in Zambia Aquaculture in regions adjacent to mining operations faces increasing threats from the release of pollutants originating from surface plant areas of mines. These pollutants, including heavy metals, chemical by-products, and suspended solids, can severely degrade water quality, impacting the health of aquatic life and the productivity of aquaculture. In Kalumbila District, Zambia, mining activities, particularly in the area surrounding the surface plant zones, are a major source of contamination to nearby water bodies that support local aquaculture. Despite the growing concern over the environmental impact of mining, there is a lack of detailed studies quantifying the specific pollutants present in these areas and their direct effects on fish production. Mining in Zambia, particularly in regions like Kalumbila, is on the rise, with copper production increasing significantly. In 2020, Zambia's mining sector produced approximately 800,000 metric tons of copper, with major mining operations such as First Quantum Minerals located near Kalumbila (Zambia Chamber of Mines, 2021). This escalation in mining activities has resulted in the discharge of pollutants such as heavy metals (e.g., arsenic, lead, mercury), which can reach concentrations that exceed the safe limits for aquatic ecosystems. For instance, studies have shown that arsenic levels in nearby water bodies can reach concentrations as high as 1.5 µg/L, well above the recommended levels for aquatic life set by the World Health Organization (WHO) (WHO, 2017). The presence of these contaminants poses a serious risk to the viability of aquaculture operations, as heavy metals are known to cause fish toxicity, reproductive failure, and mortality (Smith & Khan, 2019). 3. Methodology 3.1 Introduction The methodology for identifying and quantifying primary pollutants impacting aquaculture in mine surface plant areas of Kalumbila District involves several key steps: field sampling, laboratory analysis, data analysis, and interpretation of results. This section outlines the specific procedures for each stage of the study, ensuring that accurate and reliable data is obtained to assess the effects of mining pollutants on aquatic ecosystems and aquaculture. 3.2 Study Area Selection The study focused on mine surface plant areas in Kalumbila District, specifically those located in proximity to aquaculture operations. The areas was selected based on its known mining activities, and the potential risks of pollution due to runoff from mining operations. Water sampling sites was strategically chosen based on proximity to mining runoff, environmental conditions, and aquaculture farms to ensure that the data collected is representative of the pollutants affecting these systems. 3.3 Sampling Design A stratified random sampling approach was employed to select water sampling sites within the designated mine surface plant areas. Samples was collected at different depths (e.g., surface, mid-depth, and bottom) to assess the vertical distribution of pollutants in the water column. A total of 1–10 sampling sites were chosen. Water samples was collected using clean, pre-rinsed polyethylene bottles to prevent contamination. The water samples was immediately transferred to coolers with ice packs and transported to the laboratory for analysis. Field measurements of temperature, pH, dissolved oxygen (DO), turbidity, and conductivity was also be recorded at each sampling site using a multi-parameter probe. 3.4 Pollutant Identification and Quantification The key pollutants of interest included heavy metals (e.g., copper, lead, zinc, arsenic, mercury, cadmium), chemical by-products from mining (ammonia and sulphur dioxide compounds), and suspended solids. The following laboratory analyses was conducted to identify and quantify these pollutants: Heavy Metals : Heavy metal concentrations in water samples was determined using Inductively Coupled Plasma Mass Spectrometry (ICP-MS) or Atomic Absorption Spectroscopy (AAS). These methods provided high sensitivity and precision in detecting trace levels of metals. Standard calibration curves was used for quantification, and quality control measures, such as blank samples and spiked samples was included to ensure accuracy. Chemical By-products (Ammonia and Sulphur Compounds) : Ammonia and sulphur levels were determined using a spectrophotometric method that measures absorbance at specific wavelengths corresponding to ammonia concentrations. Suspended Solids and Turbidity : Suspended solids was measured by filtering a known volume of water through a pre-weighed filter paper, then calculating the weight difference before and after drying. Turbidity was measured using a turbidity meter, which provides a quantitative measure of water clarity based on light scattering. Water Quality Parameters : Routine water quality parameters (pH, dissolved oxygen, temperature, and conductivity) were measured directly using portable multi-parameter probes. The collected helped to interpret pollutant levels in relation to general water quality conditions. 3.5. Data Analysis The data collected from the laboratory was analyzed using statistical methods to identify correlations between pollutant concentrations and the potential impacts on aquaculture. Descriptive statistics (mean, standard deviation, range) was used to summarize pollutant concentrations for each site and sampling period. Spatial and temporal variations in pollutant levels was analyzed using Analysis of Variance (ANOVA) to determine if significant differences exist between sites or seasons. Finaly, correlation analysis was conducted to explore the relationship between pollutants (e.g., heavy metals and suspended solids) and water quality parameters (e.g., pH, dissolved oxygen). Multivariate analysis. 3.6 Ethical Considerations This study adhered to ethical guidelines concerning environmental and animal welfare. Fish health assessments followed humane practices, ensuring minimal harm to the species. All research activities was conducted in compliance with local environmental regulations and ethical standards for research in aquatic ecosystems. 4. Results This section provides the results of the study according to the research objectives presented in section one above: Objective One : To identify the primary pollutants present in the mine surface plant areas of Kalumbila District that impact aquaculture water quality. The first objective was to identify the primary pollutants present in the mine surface plant areas of Kalumbila District that impact aquaculture water quality. To this effect the water samples were collected from multiple site to determine pollutants and their concentration levels. The table below shows the results: Table 1 Pollutant and the concentrations levels (Average ± Standard Deviation) Site Main Pollutants Concentration Levels Recommended Iron 0.07 mg/L 0.1–2.0 mg/L Site 1 Copper 18–28 µg/L < 0.02-6.0 mg/L Cobalt 60 mg/L 0.01 mg/L Iron 0.05–0.08 mg/L 0.1–2.0 mg/L Site 2 Copper 20–30 µg/L < 0.02-6.0 mg/L Cobalt 50–55 mg/L 0.01 mg/L Iron 0.04–0.07 mg/L 0.1–2.0 mg/L Site 3 Copper 15–25 µg/L < 0.02-6.0 mg/L Cobalt 40–50 mg/L 0.01 mg/L Iron 0.02–0.06 mg/L 0.1–2.0 mg/L Site 4 Copper 10–20 µg/L < 0.02-6.0 mg/L Cobalt 30–40 mg/L 0.01 mg/L Figure 1: Comparison of Pollutant Concentrations Across Sites The table shows the main pollutants and their concentration levels of in mine surface plant areas of Kalumbila District. The table shows that four sites were analyzed and the main pollutants discovered include; iron, copper, and cobalt. According to the results of the analysis depicted in the table above, Site 1, the initial data point, had moderate levels of iron (0.07 mg/L, within the recommended 0.1-2.0 mg/L range), low copper levels (18–28 µg/L, below the safe limit of < 0.02-6.0 mg/L), and extremely high cobalt levels (60 mg/L, far exceeding the recommended 0.01 mg/L). For the other sites pollutant levels decrease with distance from the contamination source, due dilution, and natural attenuation. As an example, cobalt levels drop from 60 mg/L at Site 1 to an estimated 30–40 mg/L at Site 4, while copper and iron show similarly reduced concentrations. The findings implies that, the elevated levels of heavy metals in site, particularly cobalt (60 mg/L) and copper (18–28 µg/L), pose significant risks to aquatic life. In addition, although iron levels (0.07 mg/L) are within recommended ranges, prolonged exposure at higher concentrations can lead to sedimentation thereby affecting aquatic habitats and oxygen availability. Objective Two : To quantify the concentration levels of key pollutants in water bodies surrounding the mine surface plants. The second objective sought to quantify the concentration levels of key pollutants in water bodies surrounding the mine surface plants. To measure this objective, water quality parameters such as pH, dissolved oxygen (DO), temperature, and conductivity were also measured at each site. The results are summarized in Table 2 below: Table 2 Comparison of Water Quality Parameters Across Sites Parameter Site 1 Site 2 Site 3 Site 4 pH 6.2 ± 0.3 6.8 ± 0.2 7.0 ± 0.3 7.2 ± 0.1 Dissolved Oxygen (mg/L) 4.5 ± 0.6 6.3 ± 0.8 6.8 ± 0.9 7.4 ± 0.7 Temperature (°C) 28.1 ± 1.2 27.5 ± 1.0 27.3 ± 1.1 26.8 ± 0.8 Conductivity (µS/cm) 1800 ± 120 950 ± 85 900 ± 90 450 ± 60 According to Table 2 above, it is evident that the water quality at site 1, which was a site near mining operations (Site 1) was poorer compared other sites. The lower dissolved oxygen levels (4.5 mg/L) and lower pH (6.2) at Site 1 suggested that the pollutants from mining are affecting the aquatic environment by reducing water oxygenation and altering the natural chemical balance. The figure below shows the same information diagrammatically: The graph presents the water quality parameters pH, dissolved oxygen, temperature, and conductivity at four different sites. Site 4 consistently shows the highest values for dissolved oxygen and temperature, while Site 1 exhibits the lowest pH and the highest conductivity. The data suggests potential variations in water quality across the sites, with Site 4 appearing to have the most favorable conditions for aquatic life based on the measured parameters. Objective Three : To assess the potential toxic effects of these pollutants on fish species and aquatic ecosystems. The study sought to assess the potential effect of the identified pollutants on fish species and aquatic ecosystems. To this effect both individual and cumulative impacts of the identified parameters were considered to get their cumulative effect aquatic ecosystem. The parameters considered included, heavy metals (copper, cobalt, and iron), pH fluctuations, dissolved oxygen levels, and conductivity. The table below shows the results obtained: Parameter Impact on Aquatic Life Site-Specific Observations Heavy Metals (Copper, Cobalt, Iron) High concentrations of heavy metals lead to gill damage, reduced growth, reproductive issues, and bioaccumulation. Site 1 : Elevated cobalt levels posed a significant risk compared to sites 2,3 and 4 Dissolved Oxygen (DO) Low DO levels cause stress, reduced feeding, and fish kills. Site 1 : Low DO levels was observed to be of concern for aquatic life at site 1 than at other remaining points. pH pH fluctuations affect the solubility of metals and stress aquatic organisms. Site 1 : Slightly acidic conditions was observed to exacerbate metal toxicity. Conductivity High conductivity cause osmotic stress in aquatic organisms. Site 1 : High conductivity was observed to negatively impact aquatic life at Site 1, than it did on sites 2, 3 and 4 respectively The table above highlights the significant environmental challenges that was observed at Site 1 compared to other sites, posing severe risks to aquatic life and fish species. According to the results obtained high concentrations of heavy metals, particularly cobalt, were linked to gill damage and bioaccumulation, making Site 1 especially hazardous. Low dissolved oxygen levels further stressed aquatic organisms, while slightly acidic pH conditions exacerbated metal toxicity, compounding the risk. In addition, elevated conductivity levels at Site 1 caused osmotic stress, thereby negatively impacting aquatic life more than at Sites 2, 3, and 4. The results obtained consistently highlights the detrimental effects of heavy metals, low dissolved oxygen (DO), pH fluctuations, and high conductivity on aquatic ecosystems. Studies, such as those by Witeska et al. ( 2015 ), emphasize that heavy metals like copper and cobalt impair fish gill functionality and cause bioaccumulation, aligning with the observations at Site 1. 5. Discussion The findings from this study provide significant insights into the presence and effects of pollutants in Kalumbila District's mine surface plant areas on water quality and aquatic ecosystems. The identification of primary pollutants (iron, copper, and cobalt) at varying concentrations highlights localized contamination risks, with Site 1 showing the highest pollutant levels. These observations align with studies such as those by Nordstrom (2011), who reported that mining operations are major sources of heavy metal contamination in nearby water bodies. Elevated cobalt levels (60 mg/L at Site 1, far above the recommended 0.01 mg/L) present a notable environmental hazard, as supported by Witeska et al. ( 2015 ), who documented the bioaccumulation of heavy metals and their toxic impacts on fish gill function and reproduction. This reinforces the necessity of monitoring and mitigating heavy metal pollution in mining regions. The water quality analysis further revealed that parameters such as pH, dissolved oxygen (DO), and conductivity varied significantly across sites, with Site 1 demonstrating poor conditions for aquatic life. The lower pH (6.2 ± 0.3) and DO levels (4.5 ± 0.6 mg/L) observed at Site 1 suggest acidification and oxygen depletion due to pollutant activity, consistent with findings by Adams and Greeley ( 2000 ), who highlighted the impact of mining runoff on water acidity and oxygen availability. In contrast, the relatively favorable conditions at Site 4 (pH: 7.2 ± 0.1, DO: 7.4 ± 0.7 mg/L) suggest natural attenuation processes such as dilution. These variations underscore the spatial dependency of pollutant effects, reinforcing the importance of site-specific monitoring and remediation strategies. The assessment of toxic effects revealed the compounded risks of heavy metals, low DO, and high conductivity on aquatic ecosystems. The cumulative impact of these factors at Site 1 was particularly severe, leading to gill damage, reduced growth, and osmotic stress in aquatic organisms. Studies such as those by McGeer et al. (2003) corroborate these findings, emphasizing the synergistic toxicity of metal contaminants in low-oxygen environments. The slight acidity at Site 1 likely exacerbated metal solubility and toxicity, further supporting the work of Wood et al. ( 2012 ) on the influence of pH on metal bioavailability. These results collectively demonstrate the urgent need for targeted pollution control measures and ecosystem restoration efforts in the region. 6. Conclusion and Recommendations This study highlights the significant impact of mining activities on water quality and aquatic ecosystems in the Kalumbila District. The presence of elevated concentrations of heavy metals, particularly cobalt, coupled with low dissolved oxygen levels, high conductivity, and slightly acidic pH conditions, poses severe risks to aquatic life, especially at Site 1. The findings align with related studies, reinforcing the detrimental effects of mining-related pollutants on aquatic ecosystems through mechanisms such as bioaccumulation, gill damage, and reproductive impairments. While natural attenuation processes improve water quality at sites further from the contamination source, the cumulative toxic effects observed at Site 1 underscore the critical need for proactive environmental management in mining areas. To mitigate the observed impacts, it is recommended that mining operations in Kalumbila District implement stringent waste management and pollution control measures, including regular monitoring of heavy metal concentrations in water bodies. Technologies such as constructed wetlands and sedimentation ponds can be introduced to reduce pollutant discharge. Additionally, remediation strategies like phytoremediation or chemical precipitation should be explored to address elevated cobalt and copper levels. Stakeholder collaboration involving government, mining companies, and local communities is essential to enforce regulations and promote sustainable mining practices. Finally, further research is needed to assess long-term ecological impacts and explore the resilience of aquatic ecosystems in the region. 7. Implications of the Study The findings of this study have critical implications for environmental management, aquatic ecosystem health, and policy formulation in mining regions. The identification of elevated heavy metal concentrations, particularly cobalt, highlights the urgent need for improved monitoring and mitigation strategies to prevent long-term ecological damage. The observed impacts on water quality and aquatic life serve as a warning about the potential for bioaccumulation and toxicity in fish species, which could disrupt local food chains and threaten fisheries that communities may rely on for livelihoods and nutrition. 8. Future Research Future research should focus on exploring advanced remediation techniques, such as bioremediation and the use of nanotechnology, to address heavy metal contamination in aquatic systems effectively. Longitudinal studies are needed to assess the long-term ecological impacts of mining-related pollutants on aquatic biodiversity and ecosystem functioning. 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An energy-efficient and scalable IoT based smart aquaculture system in mine surface plant areas using energy harvesting technologies. IEEE Sensors Journal, 23(12), 43227-43236. Zhang, Y.; Li, W.W. Energy Consumption Analysis of a Duty Cycle Wireless Sensor Network Model. IEEE Access 2019, 7, 33405–33413. Zhao, L.; He, L.; Jin, X.; Yu, W. Design of Wireless Sensor Network Middleware for Agricultural Applications. In IFIP Advances in Information and Communication Technology; Springer: Berlin/Heidelberg, Germany, 2013; Volume 393, pp. 270–279. ISBN 9783642361364 Additional Declarations The authors declare no competing interests. Cite Share Download PDF Status: Posted Version 1 posted 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. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-5749768","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":396616775,"identity":"b8c3286f-8246-4547-b02a-9c1d1eeb0a79","order_by":0,"name":"Chimanga Kashale","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAABEklEQVRIiWNgGAWjYBACCQYGNgaGAgYGA2aIgByIOPCAoBYDhBZjsJYEorRABRIbQCQ+LZLtx589+GFgI2/Ozp34ueCXXfr8sMMPgbbYyek2YNcizZNjbthjkGa4s5l3s/TMvuTcjbfTDIBako3NDmDXIseQwybBY3A4weAw7wZp3h7m3I2zE0BaDiRuw6WF//kzyT8G/0FaNv/m7alPN5yd/gGvFmmJBDNpHqCxQC3bpHl+HE6Ql87Bb4vkjDdm0jIGyYYbgFqseRuOG26QzikAmoDbLxLn059Jvqmwkzc4f3bzbZ4/1fLys9M3f/hQYSeHSwsqYGwDRhBYpQEBlQjwh4FBvoFo1aNgFIyCUTBCAAB69V9EY34GVQAAAABJRU5ErkJggg==","orcid":"https://orcid.org/0000-0003-1265-5568","institution":"ZCAS University","correspondingAuthor":true,"prefix":"","firstName":"Chimanga","middleName":"","lastName":"Kashale","suffix":""},{"id":396617358,"identity":"ce36c68a-cdba-4385-9b53-8f20fd037ce2","order_by":1,"name":"Ezekiel Bob Jere","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA5UlEQVRIiWNgGAWjYBACAwYeBgYJIIMfLnSAWC2SDSRpATPgKglpMWfvPcBgUXFPzvj84Ycff7YxyPHdSGD+dAOPFsuecwkMEmeKjc0OHDOW5m1jMJa8kcBgnIPPYTdyDBgk2xIStx3sYZBmbGNI3ADUkkxYy7+E+s3NPMw/gQ6rB2k5TFhLQ0KCARsPmwTQYQkGNxIYm/FpAfnlgMSxBMMZZ9jMrHnOSRjOPPOwmRmfFmCIHXwsUZMgz99/+PHNH2U28nzHkw9/xqcFBA5LINggJmMDAQ1AJR8IKhkFo2AUjIIRDQAAyEtNaBMDWQAAAABJRU5ErkJggg==","orcid":"","institution":"ZCAS University","correspondingAuthor":true,"prefix":"","firstName":"Ezekiel","middleName":"Bob","lastName":"Jere","suffix":""},{"id":396617359,"identity":"c2d594f3-d9ce-4ede-8efc-5535d80e3bf3","order_by":2,"name":"Christopher Chembe","email":"data:image/png;base64,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","orcid":"","institution":"ZCAS University","correspondingAuthor":true,"prefix":"","firstName":"Christopher","middleName":"","lastName":"Chembe","suffix":""}],"badges":[],"createdAt":"2025-01-02 07:39:46","currentVersionCode":1,"declarations":{"humanSubjects":true,"vertebrateSubjects":true,"conflictsOfInterestStatement":false,"humanSubjectEthicalGuidelines":true,"humanSubjectConsent":true,"humanSubjectClinicalTrial":false,"humanSubjectCaseReport":false,"vertebrateSubjectEthicalGuidelines":true},"doi":"10.21203/rs.3.rs-5749768/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-5749768/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":73027480,"identity":"b3372513-eb54-4b57-8186-09a099b3012b","added_by":"auto","created_at":"2025-01-06 05:27:24","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":35188,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eComparison of Pollutant Concentrations Across Sites\u003c/strong\u003e\u003c/p\u003e","description":"","filename":"1.png","url":"https://assets-eu.researchsquare.com/files/rs-5749768/v1/130c3c0a398a59826a2ffac2.png"},{"id":73029718,"identity":"df3796cf-3a21-493b-a646-4754e734bca4","added_by":"auto","created_at":"2025-01-06 05:59:24","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":754291,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-5749768/v1/eb1d05cc-30cf-4229-9c93-1afbf259dafa.pdf"}],"financialInterests":"The authors declare no competing interests.","formattedTitle":"\u003cp\u003eIdentification and Quantification of Primary Pollutants Impacting Aquaculture in Mine Surface Plant Areas\u003c/p\u003e","fulltext":[{"header":"1. Introduction and Background","content":"\u003cp\u003eAquaculture in regions near mining operations faces significant environmental challenges due to the release of various pollutants that can impact water quality and aquatic life. Mining activities, especially those in surface plants, introduce a wide range of contaminants into surrounding water bodies, including heavy metals, chemicals, and other pollutants (Jones \u0026amp; Wang, 2021). These pollutants can have both acute and chronic effects on aquatic ecosystems, impacting fish health, growth rates, and reproductive cycles, ultimately threatening the sustainability of aquaculture operations in these areas. This study focuses on identifying and quantifying the primary pollutants in mine surface plant areas that affect aquaculture, with the goal of providing insights for better environmental management in Kalumbila District.\u003c/p\u003e\n\u003cp\u003ePrevious studies have shown that heavy metals such as arsenic, lead, mercury, and cadmium are among the most common contaminants released from mining operations into nearby water systems (Miller et al., 2020). When these metals accumulate in water bodies, they can be toxic to fish even at low concentrations, leading to impaired immune function, reduced growth, and mortality in sensitive species (Smith \u0026amp; Khan, 2019). Additionally, other pollutants like suspended solids, sulfates, and nitrates from mining processes can alter the pH levels and oxygen availability in aquatic environments, further stressing aquatic life and diminishing water quality for aquaculture use (Li et al., 2018). By focusing on pollutants in the surface plant areas of Kalumbila\u0026apos;s mines, this study aims to create a baseline of knowledge that could be applied to mitigate adverse effects on aquaculture operations and improve water management practices in mining zones.\u003c/p\u003e\n\u003cp\u003eThe increasing demand for fish and aquaculture products has highlighted the importance of sustainable practices that protect the environment while supporting food security (FAO, 2022). In areas affected by mining, understanding the specific pollutants and their impacts on aquatic ecosystems is essential for establishing guidelines and regulations to balance economic activities with environmental conservation. This research employed water sampling and pollutant analysis techniques to identify key contaminants and assess their concentrations.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e1.1 Problem statement\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe rising mining activities in Kalumbila, Zambia, particularly copper production, have led to the discharge of harmful pollutants like heavy metals (arsenic, lead, mercury) into nearby water bodies, exceeding safe limits for aquatic ecosystems. In 2020, Zambia\u0026rsquo;s mining sector produced approximately 800,000 metric tons of copper (Zambia Chamber of Mines, 2021), and arsenic levels in water bodies near Kalumbila have reached 1.5 \u0026micro;g/L, well above the World Health Organization\u0026apos;s recommended limits for aquatic life (WHO, 2017). These contaminants pose significant risks to aquaculture operations, causing fish toxicity, reproductive failure, and mortality (Smith \u0026amp; Khan, 2019), while suspended solids from mining runoff can contribute to turbidity levels exceeding 100 NTU, which hinders light penetration and affects fish respiratory health (Gonzalez et al., \u003cspan class=\"CitationRef\"\u003e2021\u003c/span\u003e). Despite the growing concern, there is a lack of comprehensive studies on the full extent of these pollutants and their impact on local aquaculture, which this study aims to address by identifying and quantifying the primary pollutants in mining areas.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e1.2 The purpose of the study\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe purpose of this study is to identify and quantify the primary pollutants originating from mine surface plant areas in Kalumbila District that adversely affect aquaculture, with the aim of understanding their impact on water quality and aquatic life. The study is aimed at contributing to the advancement of sustainable aquaculture practices in mine surface plant areas by providing a comprehensive understanding of the current state of the field, identifying gaps, and guiding future research and development efforts in the domain.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e1.3 Research Objectives\u003c/strong\u003e\u003c/p\u003e\n\u003cul\u003e\n \u003cli\u003e\n \u003cp\u003eTo identify the primary pollutants present in the mine surface plant areas of Kalumbila District that impact aquaculture water quality.\u003c/p\u003e\n \u003c/li\u003e\n \u003cli\u003e\n \u003cp\u003eTo quantify the concentration levels of key pollutants in water bodies surrounding the mine surface plants.\u003c/p\u003e\n \u003c/li\u003e\n \u003cli\u003e\n \u003cp\u003eTo assess the potential toxic effects of these pollutants on fish species and aquatic ecosystems.\u003c/p\u003e\n \u003c/li\u003e\n\u003c/ul\u003e\n\u003cp\u003e\u003cstrong\u003e1.4 Scope of the study\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe scope of this study encompasses the identification and quantification of primary pollutants affecting aquaculture in the mine surface plant areas of Kalumbila District. This research focuses on pollutants commonly associated with mining activities, such as heavy metals (e.g., arsenic, lead, mercury), chemical by-products, and suspended solids, and examines their concentrations in surrounding water bodies. Sampling will be conducted in specific surface water sites near the Kalumbila mines, where pollutant levels will be measured and analyzed for their potential impact on water quality and aquatic life. The study will also evaluate the toxicological effects of these pollutants on fish species to determine their implications for local aquaculture practices. However, the research does not extend to other environmental or socioeconomic impacts of mining, nor does it assess pollutants beyond the designated surface plant areas.\u003c/p\u003e"},{"header":"2.\tLiterature review","content":"\u003ch2\u003e2.1 Introduction\u003c/h2\u003e\n\u003cp\u003eThe impact of mining on aquatic ecosystems has been a significant focus in environmental research, particularly due to the release of pollutants that can detrimentally affect aquaculture. Mining activities introduce a range of pollutants into nearby water systems, including heavy metals, suspended solids, sulfates, and chemical by-products, all of which can compromise water quality and pose risks to fish and other aquatic organisms (Jones \u0026amp; Wang, 2021). This review synthesizes findings on the primary pollutants from mining operations, their effects on aquaculture, and the methods used for identifying and quantifying these pollutants in water bodies adjacent to mine surface plants.\u003c/p\u003e \u003cdiv id=\"Sec2\" class=\"Section2\"\u003e \u003ch2\u003e2.2 Heavy Metals and Toxicity in Aquatic Systems\u003c/h2\u003e \u003cp\u003eHeavy metals are among the most well-documented pollutants from mining activities, with elements such as arsenic, lead, mercury, and cadmium commonly found in mine runoff. Research indicates that these metals can accumulate in aquatic systems and become toxic to fish even at low concentrations, disrupting immune function, reproductive health, and overall fish viability (Smith \u0026amp; Khan, 2019). For instance, arsenic exposure has been shown to reduce fish growth rates and impact reproductive success, while lead and mercury are known to impair neurological function and development in aquatic species (Miller et al., 2020). The bioaccumulation of heavy metals in fish tissue not only threatens aquaculture viability but also poses risks to human health through the consumption of contaminated fish (Chen et al., \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). Understanding the concentration and distribution of these heavy metals in mine-affected waters is therefore critical for managing the risks associated with aquaculture in mining regions.\u003c/p\u003e \u003cdiv id=\"Sec3\" class=\"Section3\"\u003e \u003ch2\u003e2.2.1 Chemical By-products and Suspended Solids\u003c/h2\u003e \u003cp\u003eAside from heavy metals, mining operations often release a variety of chemical by-products and suspended solids that affect water quality. Chemical reagents used in mineral processing, such as cyanide, ammonia, and sulfuric acid, can alter the pH balance and oxygen levels in water, leading to unfavorable conditions for fish and other aquatic organisms (Li et al., 2018). Suspended solids, which may include particles of soil, rock, and metallic compounds, can increase water turbidity, reduce light penetration, and interfere with the respiratory systems of fish (Tan \u0026amp; Mohamad, 2020). Studies have shown that elevated levels of suspended solids can clog fish gills, impair feeding efficiency, and reduce fish growth rates, making it essential to monitor and manage these pollutants in aquaculture-sensitive areas near mining sites (Gonzalez et al., \u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). The interaction between suspended solids and chemical contaminants can also compound toxicity, further stressing aquatic environments and potentially causing fish mortality in areas with high pollutant concentrations.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec4\" class=\"Section3\"\u003e \u003ch2\u003e2.2.2 Quantification and Analytical Techniques for Pollutant Assessment\u003c/h2\u003e \u003cp\u003eThe identification and quantification of mining pollutants in water bodies require precise analytical methods to ensure accurate results. Common techniques used to assess heavy metal concentrations include atomic absorption spectroscopy (AAS), inductively coupled plasma mass spectrometry (ICP-MS), and X-ray fluorescence (XRF) (Park et al., 2019). These methods enable researchers to detect trace levels of metals in water samples, providing critical data for evaluating pollutant impacts on aquaculture. For chemical by-products and suspended solids, techniques such as high-performance liquid chromatography (HPLC), spectrophotometry, and turbidity measurements are frequently employed to measure concentration levels and analyze pollutant compositions (Johnson et al., 2022). The combination of these analytical tools allows researchers to create a comprehensive pollution profile, which is essential for understanding the extent of mining-related contamination in aquatic systems and its implications for aquaculture.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec5\" class=\"Section3\"\u003e \u003ch2\u003e2.2.3 Impact on Aquaculture and Ecosystem Health\u003c/h2\u003e \u003cp\u003eNumerous studies have documented the detrimental effects of mining pollutants on aquaculture viability and ecosystem health in areas surrounding mining operations. Pollutants from mine surface plants can lead to declines in fish populations, reduction in species diversity, and disruption of aquatic food chains, ultimately threatening aquaculture sustainability in these regions (Singh et al., 2017). Aquaculture operations in proximity to mining activities often struggle with reduced fish yields, slower growth rates, and increased mortality due to the cumulative impact of pollutants on water quality and fish health (FAO, 2022). These effects underscore the importance of pollutant identification and quantification as essential steps in mitigating the ecological impact of mining on aquaculture and maintaining sustainable fish production in affected regions.\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv id=\"Sec6\" class=\"Section2\"\u003e \u003ch2\u003e2.3 Mining in Zambia\u003c/h2\u003e \u003cp\u003eAquaculture in regions adjacent to mining operations faces increasing threats from the release of pollutants originating from surface plant areas of mines. These pollutants, including heavy metals, chemical by-products, and suspended solids, can severely degrade water quality, impacting the health of aquatic life and the productivity of aquaculture. In Kalumbila District, Zambia, mining activities, particularly in the area surrounding the surface plant zones, are a major source of contamination to nearby water bodies that support local aquaculture. Despite the growing concern over the environmental impact of mining, there is a lack of detailed studies quantifying the specific pollutants present in these areas and their direct effects on fish production.\u003c/p\u003e \u003cp\u003eMining in Zambia, particularly in regions like Kalumbila, is on the rise, with copper production increasing significantly. In 2020, Zambia's mining sector produced approximately 800,000 metric tons of copper, with major mining operations such as First Quantum Minerals located near Kalumbila (Zambia Chamber of Mines, 2021). This escalation in mining activities has resulted in the discharge of pollutants such as heavy metals (e.g., arsenic, lead, mercury), which can reach concentrations that exceed the safe limits for aquatic ecosystems. For instance, studies have shown that arsenic levels in nearby water bodies can reach concentrations as high as 1.5 \u0026micro;g/L, well above the recommended levels for aquatic life set by the World Health Organization (WHO) (WHO, 2017). The presence of these contaminants poses a serious risk to the viability of aquaculture operations, as heavy metals are known to cause fish toxicity, reproductive failure, and mortality (Smith \u0026amp; Khan, 2019).\u003c/p\u003e \u003c/div\u003e"},{"header":"3. Methodology","content":"\u003cdiv id=\"Sec8\" class=\"Section2\"\u003e \u003ch2\u003e3.1 Introduction\u003c/h2\u003e \u003cp\u003eThe methodology for identifying and quantifying primary pollutants impacting aquaculture in mine surface plant areas of Kalumbila District involves several key steps: field sampling, laboratory analysis, data analysis, and interpretation of results. This section outlines the specific procedures for each stage of the study, ensuring that accurate and reliable data is obtained to assess the effects of mining pollutants on aquatic ecosystems and aquaculture.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec9\" class=\"Section2\"\u003e \u003ch2\u003e3.2 Study Area Selection\u003c/h2\u003e \u003cp\u003eThe study focused on mine surface plant areas in Kalumbila District, specifically those located in proximity to aquaculture operations. The areas was selected based on its known mining activities, and the potential risks of pollution due to runoff from mining operations. Water sampling sites was strategically chosen based on proximity to mining runoff, environmental conditions, and aquaculture farms to ensure that the data collected is representative of the pollutants affecting these systems.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec10\" class=\"Section2\"\u003e \u003ch2\u003e3.3 Sampling Design\u003c/h2\u003e \u003cp\u003eA stratified random sampling approach was employed to select water sampling sites within the designated mine surface plant areas. Samples was collected at different depths (e.g., surface, mid-depth, and bottom) to assess the vertical distribution of pollutants in the water column. A total of 1\u0026ndash;10 sampling sites were chosen. Water samples was collected using clean, pre-rinsed polyethylene bottles to prevent contamination. The water samples was immediately transferred to coolers with ice packs and transported to the laboratory for analysis. Field measurements of temperature, pH, dissolved oxygen (DO), turbidity, and conductivity was also be recorded at each sampling site using a multi-parameter probe.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec11\" class=\"Section2\"\u003e \u003ch2\u003e3.4 Pollutant Identification and Quantification\u003c/h2\u003e \u003cp\u003eThe key pollutants of interest included heavy metals (e.g., copper, lead, zinc, arsenic, mercury, cadmium), chemical by-products from mining (ammonia and sulphur dioxide compounds), and suspended solids. The following laboratory analyses was conducted to identify and quantify these pollutants:\u003c/p\u003e \u003cp\u003e \u003cul\u003e \u003cli\u003e \u003cp\u003e \u003cb\u003eHeavy Metals\u003c/b\u003e: Heavy metal concentrations in water samples was determined using Inductively Coupled Plasma Mass Spectrometry (ICP-MS) or Atomic Absorption Spectroscopy (AAS). These methods provided high sensitivity and precision in detecting trace levels of metals. Standard calibration curves was used for quantification, and quality control measures, such as blank samples and spiked samples was included to ensure accuracy.\u003c/p\u003e \u003c/li\u003e \u003cli\u003e \u003cp\u003e \u003cb\u003eChemical By-products (Ammonia and Sulphur Compounds)\u003c/b\u003e: Ammonia and sulphur levels were determined using a spectrophotometric method that measures absorbance at specific wavelengths corresponding to ammonia concentrations.\u003c/p\u003e \u003c/li\u003e \u003cli\u003e \u003cp\u003e \u003cb\u003eSuspended Solids and Turbidity\u003c/b\u003e: Suspended solids was measured by filtering a known volume of water through a pre-weighed filter paper, then calculating the weight difference before and after drying. Turbidity was measured using a turbidity meter, which provides a quantitative measure of water clarity based on light scattering.\u003c/p\u003e \u003c/li\u003e \u003cli\u003e \u003cp\u003e \u003cb\u003eWater Quality Parameters\u003c/b\u003e: Routine water quality parameters (pH, dissolved oxygen, temperature, and conductivity) were measured directly using portable multi-parameter probes. The collected helped to interpret pollutant levels in relation to general water quality conditions.\u003c/p\u003e \u003c/li\u003e \u003c/ul\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec12\" class=\"Section2\"\u003e \u003ch2\u003e3.5. Data Analysis\u003c/h2\u003e \u003cp\u003eThe data collected from the laboratory was analyzed using statistical methods to identify correlations between pollutant concentrations and the potential impacts on aquaculture. Descriptive statistics (mean, standard deviation, range) was used to summarize pollutant concentrations for each site and sampling period. Spatial and temporal variations in pollutant levels was analyzed using Analysis of Variance (ANOVA) to determine if significant differences exist between sites or seasons.\u003c/p\u003e \u003cp\u003eFinaly, correlation analysis was conducted to explore the relationship between pollutants (e.g., heavy metals and suspended solids) and water quality parameters (e.g., pH, dissolved oxygen).\u003c/p\u003e \u003cp\u003eMultivariate analysis.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec13\" class=\"Section2\"\u003e \u003ch2\u003e3.6 Ethical Considerations\u003c/h2\u003e \u003cp\u003eThis study adhered to ethical guidelines concerning environmental and animal welfare. Fish health assessments followed humane practices, ensuring minimal harm to the species. All research activities was conducted in compliance with local environmental regulations and ethical standards for research in aquatic ecosystems.\u003c/p\u003e \u003c/div\u003e"},{"header":"4. Results","content":"\u003cp\u003eThis section provides the results of the study according to the research objectives presented in section one above:\u003c/p\u003e \u003cp\u003e \u003cb\u003eObjective One\u003c/b\u003e: \u003cb\u003eTo identify the primary pollutants present in the mine surface plant areas of\u003c/b\u003e\u003c/p\u003e \u003cp\u003e \u003cb\u003eKalumbila District that impact aquaculture water quality.\u003c/b\u003e \u003c/p\u003e \u003cp\u003eThe first objective was to identify the primary pollutants present in the mine surface plant areas of Kalumbila District that impact aquaculture water quality. To this effect the water samples were collected from multiple site to determine pollutants and their concentration levels. The table below shows the results:\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\u003ePollutant and the concentrations levels (Average\u0026thinsp;\u0026plusmn;\u0026thinsp;Standard Deviation)\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\u003eMain Pollutants\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eConcentration Levels\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eRecommended\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\u003eIron\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.07 mg/L\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.1\u0026ndash;2.0 mg/L\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSite 1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCopper\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e18\u0026ndash;28 \u0026micro;g/L\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.02-6.0 mg/L\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\u003eCobalt\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e60 mg/L\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.01 mg/L\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\u003eIron\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.05\u0026ndash;0.08 mg/L\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.1\u0026ndash;2.0 mg/L\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSite 2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCopper\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e20\u0026ndash;30 \u0026micro;g/L\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.02-6.0 mg/L\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\u003eCobalt\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e50\u0026ndash;55 mg/L\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.01 mg/L\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\u003eIron\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.04\u0026ndash;0.07 mg/L\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.1\u0026ndash;2.0 mg/L\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSite 3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCopper\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e15\u0026ndash;25 \u0026micro;g/L\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.02-6.0 mg/L\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\u003eCobalt\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e40\u0026ndash;50 mg/L\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.01 mg/L\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\u003eIron\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.02\u0026ndash;0.06 mg/L\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.1\u0026ndash;2.0 mg/L\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSite 4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCopper\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e10\u0026ndash;20 \u0026micro;g/L\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.02-6.0 mg/L\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\u003eCobalt\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e30\u0026ndash;40 mg/L\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.01 mg/L\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 \u003cb\u003eFigure 1: Comparison of Pollutant Concentrations Across Sites\u003c/b\u003e \u003c/p\u003e \u003cp\u003eThe table shows the main pollutants and their concentration levels of in mine surface plant areas of Kalumbila District. The table shows that four sites were analyzed and the main pollutants discovered include; iron, copper, and cobalt. According to the results of the analysis depicted in the table above, Site 1, the initial data point, had moderate levels of iron (0.07 mg/L, within the recommended 0.1-2.0 mg/L range), low copper levels (18\u0026ndash;28 \u0026micro;g/L, below the safe limit of \u0026lt;\u0026thinsp;0.02-6.0 mg/L), and extremely high cobalt levels (60 mg/L, far exceeding the recommended 0.01 mg/L). For the other sites pollutant levels decrease with distance from the contamination source, due dilution, and natural attenuation. As an example, cobalt levels drop from 60 mg/L at Site 1 to an estimated 30\u0026ndash;40 mg/L at Site 4, while copper and iron show similarly reduced concentrations. The findings implies that, the elevated levels of heavy metals in site, particularly cobalt (60 mg/L) and copper (18\u0026ndash;28 \u0026micro;g/L), pose significant risks to aquatic life. In addition, although iron levels (0.07 mg/L) are within recommended ranges, prolonged exposure at higher concentrations can lead to sedimentation thereby affecting aquatic habitats and oxygen availability.\u003c/p\u003e \u003cp\u003e \u003cb\u003eObjective Two\u003c/b\u003e: \u003cb\u003eTo quantify the concentration levels of key pollutants in water bodies\u003c/b\u003e\u003c/p\u003e \u003cp\u003e \u003cb\u003esurrounding the mine surface plants.\u003c/b\u003e \u003c/p\u003e \u003cp\u003eThe second objective sought to quantify the concentration levels of key pollutants in water bodies surrounding the mine surface plants. To measure this objective, water quality parameters such as pH, dissolved oxygen (DO), temperature, and conductivity were also measured at each site. The results are summarized in Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e below:\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\u003eComparison of Water Quality Parameters Across Sites\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"5\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\"\u0026plusmn;\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\"\u0026plusmn;\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\"\u0026plusmn;\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\"\u0026plusmn;\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\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\u003eSite 1\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eSite 2\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eSite 3\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eSite 4\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003epH\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e \u003cp\u003e6.2\u0026thinsp;\u0026plusmn;\u0026thinsp;0.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e \u003cp\u003e6.8\u0026thinsp;\u0026plusmn;\u0026thinsp;0.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c4\"\u003e \u003cp\u003e7.0\u0026thinsp;\u0026plusmn;\u0026thinsp;0.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c5\"\u003e \u003cp\u003e7.2\u0026thinsp;\u0026plusmn;\u0026thinsp;0.1\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eDissolved Oxygen (mg/L)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e \u003cp\u003e4.5\u0026thinsp;\u0026plusmn;\u0026thinsp;0.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e \u003cp\u003e6.3\u0026thinsp;\u0026plusmn;\u0026thinsp;0.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c4\"\u003e \u003cp\u003e6.8\u0026thinsp;\u0026plusmn;\u0026thinsp;0.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c5\"\u003e \u003cp\u003e7.4\u0026thinsp;\u0026plusmn;\u0026thinsp;0.7\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eTemperature (\u0026deg;C)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e \u003cp\u003e28.1\u0026thinsp;\u0026plusmn;\u0026thinsp;1.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e \u003cp\u003e27.5\u0026thinsp;\u0026plusmn;\u0026thinsp;1.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c4\"\u003e \u003cp\u003e27.3\u0026thinsp;\u0026plusmn;\u0026thinsp;1.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c5\"\u003e \u003cp\u003e26.8\u0026thinsp;\u0026plusmn;\u0026thinsp;0.8\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eConductivity (\u0026micro;S/cm)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e \u003cp\u003e1800\u0026thinsp;\u0026plusmn;\u0026thinsp;120\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e \u003cp\u003e950\u0026thinsp;\u0026plusmn;\u0026thinsp;85\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c4\"\u003e \u003cp\u003e900\u0026thinsp;\u0026plusmn;\u0026thinsp;90\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c5\"\u003e \u003cp\u003e450\u0026thinsp;\u0026plusmn;\u0026thinsp;60\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\u003eAccording to Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e above, it is evident that the water quality at site 1, which was a site near mining operations (Site 1) was poorer compared other sites. The lower dissolved oxygen levels (4.5 mg/L) and lower pH (6.2) at Site 1 suggested that the pollutants from mining are affecting the aquatic environment by reducing water oxygenation and altering the natural chemical balance. The figure below shows the same information diagrammatically:\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eThe graph presents the water quality parameters pH, dissolved oxygen, temperature, and conductivity at four different sites. Site 4 consistently shows the highest values for dissolved oxygen and temperature, while Site 1 exhibits the lowest pH and the highest conductivity. The data suggests potential variations in water quality across the sites, with Site 4 appearing to have the most favorable conditions for aquatic life based on the measured parameters.\u003c/p\u003e \u003cp\u003e \u003cb\u003eObjective Three\u003c/b\u003e: \u003cb\u003eTo assess the potential toxic effects of these pollutants on fish species and\u003c/b\u003e\u003c/p\u003e \u003cp\u003e \u003cb\u003eaquatic ecosystems.\u003c/b\u003e \u003c/p\u003e \u003cp\u003eThe study sought to assess the potential effect of the identified pollutants on fish species and aquatic ecosystems. To this effect both individual and cumulative impacts of the identified parameters were considered to get their cumulative effect aquatic ecosystem. The parameters considered included, heavy metals (copper, cobalt, and iron), pH fluctuations, dissolved oxygen levels, and conductivity. The table below shows the results obtained:\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"No\" id=\"Taba\" border=\"1\"\u003e \u003ccolgroup cols=\"3\"\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 \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\u003eImpact on Aquatic Life\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eSite-Specific Observations\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eHeavy Metals (Copper, Cobalt, Iron)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eHigh concentrations of heavy metals lead to gill damage, reduced growth, reproductive issues, and bioaccumulation.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003eSite 1\u003c/b\u003e: Elevated cobalt levels posed a significant risk compared to sites 2,3 and 4\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eDissolved Oxygen (DO)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eLow DO levels cause stress, reduced feeding, and fish kills.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003eSite 1\u003c/b\u003e: Low DO levels was observed to be of concern for aquatic life at site 1 than at other remaining points.\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003epH\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003epH fluctuations affect the solubility of metals and stress aquatic organisms.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003eSite 1\u003c/b\u003e: Slightly acidic conditions was observed to exacerbate metal toxicity.\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eConductivity\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eHigh conductivity cause osmotic stress in aquatic organisms.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003eSite 1\u003c/b\u003e: High conductivity was observed to negatively impact aquatic life at Site 1, than it did on sites 2, 3 and 4 respectively\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 table above highlights the significant environmental challenges that was observed at Site 1 compared to other sites, posing severe risks to aquatic life and fish species. According to the results obtained high concentrations of heavy metals, particularly cobalt, were linked to gill damage and bioaccumulation, making Site 1 especially hazardous. Low dissolved oxygen levels further stressed aquatic organisms, while slightly acidic pH conditions exacerbated metal toxicity, compounding the risk. In addition, elevated conductivity levels at Site 1 caused osmotic stress, thereby negatively impacting aquatic life more than at Sites 2, 3, and 4. The results obtained consistently highlights the detrimental effects of heavy metals, low dissolved oxygen (DO), pH fluctuations, and high conductivity on aquatic ecosystems. Studies, such as those by Witeska et al. (\u003cspan citationid=\"CR75\" class=\"CitationRef\"\u003e2015\u003c/span\u003e), emphasize that heavy metals like copper and cobalt impair fish gill functionality and cause bioaccumulation, aligning with the observations at Site 1.\u003c/p\u003e"},{"header":"5. Discussion","content":"\u003cp\u003eThe findings from this study provide significant insights into the presence and effects of pollutants in Kalumbila District's mine surface plant areas on water quality and aquatic ecosystems. The identification of primary pollutants (iron, copper, and cobalt) at varying concentrations highlights localized contamination risks, with Site 1 showing the highest pollutant levels. These observations align with studies such as those by Nordstrom (2011), who reported that mining operations are major sources of heavy metal contamination in nearby water bodies. Elevated cobalt levels (60 mg/L at Site 1, far above the recommended 0.01 mg/L) present a notable environmental hazard, as supported by Witeska et al. (\u003cspan citationid=\"CR75\" class=\"CitationRef\"\u003e2015\u003c/span\u003e), who documented the bioaccumulation of heavy metals and their toxic impacts on fish gill function and reproduction. This reinforces the necessity of monitoring and mitigating heavy metal pollution in mining regions.\u003c/p\u003e \u003cp\u003eThe water quality analysis further revealed that parameters such as pH, dissolved oxygen (DO), and conductivity varied significantly across sites, with Site 1 demonstrating poor conditions for aquatic life. The lower pH (6.2\u0026thinsp;\u0026plusmn;\u0026thinsp;0.3) and DO levels (4.5\u0026thinsp;\u0026plusmn;\u0026thinsp;0.6 mg/L) observed at Site 1 suggest acidification and oxygen depletion due to pollutant activity, consistent with findings by Adams and Greeley (\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e2000\u003c/span\u003e), who highlighted the impact of mining runoff on water acidity and oxygen availability. In contrast, the relatively favorable conditions at Site 4 (pH: 7.2\u0026thinsp;\u0026plusmn;\u0026thinsp;0.1, DO: 7.4\u0026thinsp;\u0026plusmn;\u0026thinsp;0.7 mg/L) suggest natural attenuation processes such as dilution. These variations underscore the spatial dependency of pollutant effects, reinforcing the importance of site-specific monitoring and remediation strategies.\u003c/p\u003e \u003cp\u003eThe assessment of toxic effects revealed the compounded risks of heavy metals, low DO, and high conductivity on aquatic ecosystems. The cumulative impact of these factors at Site 1 was particularly severe, leading to gill damage, reduced growth, and osmotic stress in aquatic organisms. Studies such as those by McGeer et al. (2003) corroborate these findings, emphasizing the synergistic toxicity of metal contaminants in low-oxygen environments. The slight acidity at Site 1 likely exacerbated metal solubility and toxicity, further supporting the work of Wood et al. (\u003cspan citationid=\"CR76\" class=\"CitationRef\"\u003e2012\u003c/span\u003e) on the influence of pH on metal bioavailability. These results collectively demonstrate the urgent need for targeted pollution control measures and ecosystem restoration efforts in the region.\u003c/p\u003e"},{"header":"6. Conclusion and Recommendations","content":"\u003cp\u003eThis study highlights the significant impact of mining activities on water quality and aquatic ecosystems in the Kalumbila District. The presence of elevated concentrations of heavy metals, particularly cobalt, coupled with low dissolved oxygen levels, high conductivity, and slightly acidic pH conditions, poses severe risks to aquatic life, especially at Site 1. The findings align with related studies, reinforcing the detrimental effects of mining-related pollutants on aquatic ecosystems through mechanisms such as bioaccumulation, gill damage, and reproductive impairments. While natural attenuation processes improve water quality at sites further from the contamination source, the cumulative toxic effects observed at Site 1 underscore the critical need for proactive environmental management in mining areas.\u003c/p\u003e \u003cp\u003eTo mitigate the observed impacts, it is recommended that mining operations in Kalumbila District implement stringent waste management and pollution control measures, including regular monitoring of heavy metal concentrations in water bodies. Technologies such as constructed wetlands and sedimentation ponds can be introduced to reduce pollutant discharge. Additionally, remediation strategies like phytoremediation or chemical precipitation should be explored to address elevated cobalt and copper levels. Stakeholder collaboration involving government, mining companies, and local communities is essential to enforce regulations and promote sustainable mining practices. Finally, further research is needed to assess long-term ecological impacts and explore the resilience of aquatic ecosystems in the region.\u003c/p\u003e"},{"header":"7. Implications of the Study","content":"\u003cp\u003eThe findings of this study have critical implications for environmental management, aquatic ecosystem health, and policy formulation in mining regions. The identification of elevated heavy metal concentrations, particularly cobalt, highlights the urgent need for improved monitoring and mitigation strategies to prevent long-term ecological damage. The observed impacts on water quality and aquatic life serve as a warning about the potential for bioaccumulation and toxicity in fish species, which could disrupt local food chains and threaten fisheries that communities may rely on for livelihoods and nutrition.\u003c/p\u003e"},{"header":"8. Future Research","content":"\u003cp\u003eFuture research should focus on exploring advanced remediation techniques, such as bioremediation and the use of nanotechnology, to address heavy metal contamination in aquatic systems effectively. Longitudinal studies are needed to assess the long-term ecological impacts of mining-related pollutants on aquatic biodiversity and ecosystem functioning. Additionally, the interactions between multiple water quality parameters, such as pH, dissolved oxygen, and metal toxicity, should be modeled to predict cumulative effects under varying environmental conditions. 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ISBN 9783642361364\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":true,"hideJournal":true,"highlight":"","institution":"ZCAS University","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"Heavy metals, aquaculture, mining, pollutants, environmental, Kalumbila","lastPublishedDoi":"10.21203/rs.3.rs-5749768/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-5749768/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eThe aim of this study was to investigate and identify the primary pollutants impacting aquaculture in mine surface plant areas of Kalumbila District. Water samples were collected from four sites near mining operations to analyze key pollutants, including iron, copper, and cobalt, along with water quality parameters such as pH, dissolved oxygen (DO), temperature, and conductivity. Results revealed elevated cobalt levels (up to 60 mg/L at Site 1, far exceeding the recommended 0.01 mg/L), significant copper contamination, and slightly acidic conditions, particularly near the contamination source. Dissolved oxygen levels were lowest at Site 1 (4.5\u0026thinsp;\u0026plusmn;\u0026thinsp;0.6 mg/L), indicating potential stress on aquatic life. The study demonstrated that proximity to mining activities exacerbates pollution levels, with pollutant concentrations decreasing at sites further away due to natural attenuation. The toxic effects of heavy metals, low DO, and high conductivity on aquatic ecosystems were assessed, highlighting severe risks such as gill damage, bioaccumulation, and osmotic stress, particularly at Site 1. These findings align with related studies on the ecological impacts of mining and emphasize the urgent need for targeted mitigation strategies. Recommendations include implementing advanced pollution control technologies, enhancing monitoring systems, and promoting sustainable mining practices. The study underscores the importance of balancing industrial activities with environmental preservation to safeguard aquatic ecosystems and local livelihoods.\u003c/p\u003e","manuscriptTitle":"Identification and Quantification of Primary Pollutants Impacting Aquaculture in Mine Surface Plant Areas","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-01-06 05:27:20","doi":"10.21203/rs.3.rs-5749768/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"d9008116-9ba1-4c09-92f3-61fb052cdc8a","owner":[],"postedDate":"January 6th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[{"id":42255457,"name":"Environmental Engineering"}],"tags":[],"updatedAt":"2025-01-06T05:27:20+00:00","versionOfRecord":[],"versionCreatedAt":"2025-01-06 05:27:20","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-5749768","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-5749768","identity":"rs-5749768","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}