Assessment of Physicochemical and Metal Characteristics of Effluent in Ebonyi State, Nigeria in Comparison with WHO Guidelines, Implications for Aquatic Ecosystem Health and Food Security

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F Mbonu, Prof. O. N Omaka, Dr. D. O. Igwe This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-8977341/v1 This work is licensed under a CC BY 4.0 License Status: Under Review Version 1 posted 11 You are reading this latest preprint version Abstract Industrial and domestic effluent discharges contribute significantly to surface and ground water pollution. Industrialisation in rapidly urbanizing regions of Sub-Saharan Africa often impacts our environment, leading to severe aquatic degradation. This study presents a comprehensive physicochemical, metal and toxicological characterization of industrial effluents within the Abakaliki metropolis, Ebonyi State, Nigeria. Twenty-nine representative samples were collected from strategic discharge points, including Royal Salt processing area which doubles as lead and zinc mining region, Abattoirs, Building material market area, Iyiudele River and Municipal drainage canals. Analysis was conducted following APHA and ASTM standard protocols for eighteen parameters, including heavy metal speciation through spectrophotometry. Results indicated a critical state of pollution, with several parameters significantly exceeding WHO ( 2023 ) and SON permissible limits. Notably, Arsenate (As) and Lead (Pb) exhibited mean concentrations of 0.07 mg/L and 0.105 mg/L respectively, representing a high percentage exceedance of safety thresholds. Organic loading was equally severe, with Biochemical Oxygen Demand (BOD₅) averaging 88.5 mg/L (CF = 2.95) and Dissolved Oxygen (DO) levels dropping to a hypoxic mean of 1.85 mg/L. Furthermore, extreme nutrient enrichment was observed, with Total Phosphate (5.29 mg/L) exceeding the limit by over ten-fold, signaling a high risk for irreversible eutrophication in receiving water bodies like the Iyiokwu River. Statistical analysis (ANOVA, p < 0.05) confirmed significant spatial variation in contaminant plumes, specifically linking Royal salt processing to metal toxicity and abattoir discharge to organic hypoxia. The study concludes that the uncontrolled discharge of these untreated effluents poses an immediate threat to the regional "One Health" framework, necessitating urgent bio-remediation strategies—such as phytoremediation and low-cost adsorption treatment methods alongside stricter enforcement of NESREA discharge permits. These findings provide a baseline for future longitudinal studies on the biomagnification of neurotoxic metals within the local food chain. Water Quality Effluent Physicochemical Aquatic WHO Standards Water Pollution Figures Figure 1 Figure 2 Figure 3 1. Introduction Rapid industrialization in developing economies like Nigeria has led to a proportional increase in the volume of untreated effluents discharged into the environment. In Ebonyi State, particularly the Abakaliki metropolis, various industrial activities ranging from salt processing, minning, agricultural activities to building material production discharge biological and chemical wastes into local canals and stream networks. (WHO 2023 ) said, these effluents are major drivers of surface and groundwater degradation. Elevated levels of Biochemical Oxygen Demand (BOD) and Chemical Oxygen Demand (COD) in wastewater indicate a high organic load, which depletes dissolved oxygen (DO), leading to anaerobic conditions that threaten aquatic life. (USEPA 2012). Furthermore, the presence of excess nutrients like nitrates and phosphates triggers eutrophication. Heavy metal contamination, such as arsenate, poses long-term carcinogenic risks to populations relying on these water bodies for domestic use. This study aims to provide a comprehensive assessment of industrial effluents in Ebonyi State to quantify the extent of pollution relative to international health standards. (Dasgupta, M & Yildiz, Y., 2016 ). 2. Materials and Methods 2.1 Study Area and Sampling The study was conducted in Abakaliki, the capital of Ebonyi State, Southeastern Nigeria (latitude 6°20'N and longitude 8°06'E). The region is characterized by significant industrial activities including paint production, quarrying, rice milling, salt processing, and chemical marketing. A total of twenty-nine (29) representative effluent samples were collected using a stratified grab sampling technique from multiple discharge outlets, including Iyiokwu, Iyiudele, Hatchery canal, Nnodo canal, Afikpo Rd, Abattoir, Royal Salt and lead mining, Ikwo, and Building Material streams. Figure 2 . A map showing sampling sites, indicating industrial, mining, agricultural, abattoir and municipal areas of waste disposal around Abakaliki, Ebonyi state, Nigeria. Urban Drainage/Canals : Iyiokwu, Iyiudele, and Nnodo. Industrial/Commercial Zones : Hatchery, Afikpo Road, and Building Material canals. Processing Units : Abattoir, Ogoja rd. Mining zone : Royal Salt, Ikwo. These sites were selected based on their proximity to human settlements and their roles as primary conduits for waste into larger surface water bodies. 2.2 Sample Collection and Preservation Samples were collected in pre-sterilized 2-liter polyethylene (HDPE) bottles that were acid cleaned following a standard procedure (Worsfold, et al., 2005 ; Omaka et al., 2007 ) and preserved at 4 o C, and transported to the laboratory for analysis within 24 hours. In-situ measurements for temperature, pH, and Electrical Conductivity (EC) were performed using a multi-parameter water quality meter, to preserve the integrity of the samples. Sampling was conducted following the protocols described by APHA ( 2017 ) . At each discharge point, grab samples were collected into pre-rinsed 2-liter high-density polyethylene (HDPE) bottles. For BOD₅ and COD analysis, samples were collected in amber glass bottles to prevent photo-degradation of organic constituents. Samples intended for heavy metal analysis (Arsenate) were acidified with HNO3​ to a pH < 2.0 to minimize adsorption of metals to the container walls. All samples were labeled, stored in ice chests at approximately 4 o C, and transported to the laboratory for analysis within 24 hours to ensure sample integrity (ASTM 2018 ). 2.3 Physicochemical Analysis A multi-parameter approach was employed to characterize the effluents: On-Site (In-situ) Measurements : Temperature, pH, Electrical Conductivity (EC), and Total Dissolved Solids (TDS) were measured at the point of collection using a calibrated portable multi-parameter water quality meter (Model: HI-98129, Hanna Instruments). Gravimetric & Titrimetric Methods Turbidity was determined using the nephelometric method (APHA 2130B). Total hardness, calcium, and magnesium components were analyzed via EDTA complexometric titration (APHA 2017 ). Chloride was determined by the Mohr argentometric method (APHA 2023 ). Organic Load Analysis: Dissolved Oxygen (DO) and Biochemical Oxygen Demand (BOD₅) were determined using the Winkler titration method with a 5-day incubation period at 20 o C (APHA 2017 ). Chemical Oxygen Demand (COD) was determined using the open reflux dichromate digestion method (APHA 2023 ). 2.4 Analytical Procedures Chemical analysis followed the Standard Methods for the Examination of Water and Wastewater (APHA 2017 ). A UV-Visible Spectrophotometer (Model: Spectrumlab 752s). Titration was used to determine Total Acidity was determined using (Duruibe et al. , 2007), total alkalinity was by acid titration using methyl-orange indicator (Arain et al. , 2008), Biological Oxygen Demand by Winkler’s method, while Chemical Oxygen Demand was by dichromate method (Duruibe et al. , 2007). Nitrate and phosphate were determined spectrophotometrically at 410 and 820 nm respectively (Jenkins and Medsken, 1964; Omaka et al., 2007 ; Valderrama, 1981). We adopted the method of formation of 12-molybdophosphoric acid from phosphate and molybdate in acid solution and subsequent reduction to a blue heteropoly compound for the determination of Phosphate, For Nitrates, the reaction of nitrate ion with brucine sulphate in a 13N H 2 SO 4 solution at 100°C Sulphate was determined spectrophotometrically usng, (Anthoney, 2019 ) method by reacting it with barium chloride in an acidic medium to form a barium sulphate suspension, and measuring the resulting turbidity (light scattering) at 420 nm or 525 nm. Arsenate (As): Was analysed using the Silver Diethyldithiocarbamate method, where the intensity of the red complex formed was measured at 535nm (APHA 3500-As B) BOD₅ was determined using the 5-day incubation method, while COD was analyzed using the open reflux dichromate method. The determination of heavy metal concentrations was performed using Atomic Absorption Spectrometry (AAS) (Model: buck scientific 210GP), a standard technique for trace metal analysis in aqueous matrices. APHA ( 2023 ) was used and Calibration of Standard working solutions for each metal were prepared by serial dilution of 1000 mg/L certified stock standards (Sigma-Aldrich). Calibration curves were constructed with a correlation coefficient (R2) ≥ 0.999. 2.5 Quality Assurance and Data Analysis Analytical quality was ensured through the use of reagent blanks, triplicate analysis (n = 3), and calibration of instruments with standard solutions. Data were summarized using descriptive statistics and compared against the WHO ( 2023 ) permissible limits for wastewater discharge. All reagents used were of analytical grade (Sigma-Aldrich). To ensure data reliability, the laboratory adhered to ISO/IEC 17025 standards, incorporating reagent blanks, duplicate analyses, and matrix spikes. A recovery study was performed for Arsenate, yielding a recovery rate of 96.5 ± 2.0%. Descriptive statistics (Mean, Standard Deviation, and Ranges) were computed using SPSS version 26.0. Significant differences between the observed values and the WHO ( 2023 ) and NESREA (Nigeria) standards were evaluated using one-way ANOVA at a 95% confidence interval (p < 0.05). 3. Results The physicochemical profile of the industrial effluents is summarized in table below. Due to the varying units (NTU, mg/L, µS/cm and mg/L) and magnitudes, logarithmic scale was used to ensure that parameters with smaller values like Phosphate… are visible alongside larger values like EC. 4. Discussion The results in fig1, indicate a critical level of contamination across the majority of sampling sites. The high Turbidity (up to 78 NTU) is likely due to the presence of suspended solids and colloidal matter from industrial wash-offs. The pH values as low as 4.7 indicate acidic discharge in some canals, which can increase the solubility and toxicity of heavy metals. The disparity in BOD 5 and COD relative to WHO limits is the most alarming finding. BOD 5 levels were nearly 3 times the limit, while COD was over 3 times the limit. This indicates a high concentration of chemically oxidisable organic matter, which is corroborated by the extremely low Dissolved Oxygen (0.5mg/L). Such levels are insufficient to support aerobic aquatic organisms. Furthermore, Phosphate and Nitrate levels suggest a high risk of eutrophication in the receiving water bodies. The Arsenate concentration (up to 3.6 mg/L) is over 300 times the WHO permissible limit. This suggests that the "Building Material" and "Royal Salt" canals may be leaching toxic elements into the local water table, necessitating immediate remediation. The generated graph presents the Contamination Factor (CF) for each physicochemical parameter, calculated as the ratio of the observed mean concentration to the WHO (2023) permissible limit. 4.1 Research Findings 1. Organic Waste Load (BOD₅, COD, and DO) BOD₅ (CF=2.95): The Biological Oxygen Demand is nearly triple the permissible limit, indicating a high concentration of biodegradable organic waste requiring significant oxygen for decomposition. Dissolved Oxygen (DO): The failure factor (CF=1.43 calculated as Limit/Observed) shows that oxygen levels are critically low. The mean of 2.1mg/L is insufficient to support aerobic aquatic organisms, creating "dead zones" in the receiving water bodies. COD (CF=0.95): While the mean Chemical Oxygen Demand is slightly below the 250mg/L limit provided in the table, the high maximum value (324mg/L) suggests that many individual samples are heavily polluted with non-biodegradable chemicals. 2. Mineral and Anion Profile (Sulphate and Nitrate) Sulphate (CF=1.30): Sulphate levels surpass the limit, contributing to mineralization and potentially causing laxative effects if consumed. Nitrate (CF=1.05): Nitrates are just above the threshold, further compounding the eutrophication risks noted with phosphates. 3. The metal analysis result in fig.2. reveals a high level of toxicity, specifically regarding neurotoxic and carcinogenic elements. i. Lead (Pb) and Arsenate Contamination: Lead (Mean: 0.105 mg/L vs. WHO: 0.01 mg/L): Lead levels are 10 times higher than the safe limit. Lead is a non-essential, highly toxic metal that accumulates in the bones and soft tissues. In water chemistry, such high levels are usually associated with industrial discharge or lead-based mining and can cause neurological damage, especially in children; Abakaliki is a serious lead mining region of Nigeria, which accounts for the presence of high lead. Arsenate (Mean: 0.07 mg/L vs. WHO/SON: 0.01 mg/L): Arsenate is 7 times higher than the limit. Its 100% exceedance rate across samples suggests a systemic industrial pollution issue. Arsenic is a known human carcinogen. Analysis revealed detectable levels of Arsenate across the industrial discharge points, with significant concentrations recorded at the Royal Salt Ikwo discharge site and the Building Material canal. Observed values ranged from 0.02mg/L to 0.45mg/L, frequently exceeding the WHO and SON permissible limit of 0.01mg/L. The elevated Arsenate levels in the salt mining and industrial zones are likely due to the oxidation of As-rich pyrite and arsenopyrite minerals associated with the geological formations of the Asu River Group (Omaka et al ., 2024). Chemically, at the recorded pH levels (7.1–8.2), arsenic predominantly exists as Arsenate (As(V)), which is less mobile but highly persistent in sediment. However, the presence of organic matter in the canals can trigger reductive dissolution, potentially converting As(V) to the more toxic Arsenite (As(III)). ii. Cadmium (Cd) and Chromium (Cr) Cadmium (Mean: 0.026 mg/L vs. WHO: 0.003 mg/L): Cadmium is nearly 9 times higher than the permissible limit. Chronic exposure to cadmium via contaminated water is linked to kidney damage and "Itai-itai" disease (bone softening). Chromium (Mean: 0.095 mg/L vs. WHO: 0.05 mg/L): While less extreme than Lead or Cadmium, Chromium still exceeds the safe threshold. Hexavalent chromium, often found in industrial waste, is highly toxic and skin-permeable. iii. Zinc (Zn) and Copper (Cu): Zinc (5.04 mg/L) and Copper (1.41 mg/L): Both parameters are currently within the WHO/SON limits. Zinc and Copper are considered "essential" trace elements; they only become toxic at much higher concentrations than those observed here. Their 0% exceedance rate indicates they do not pose an immediate health threat in this specific study area. iv. Compliant Parameters Parameters such as TDS, EC, Temperature, Total Hardness, and pH (mean) currently fall within the WHO and SON acceptable ranges. However, the extreme exceedances in toxic and organic parameters categorize these effluents as untreated and hazardous, necessitating immediate regulatory intervention and the implementation of advanced wastewater treatment protocols in Ebonyi State 4. Nutrient Enrichment and Eutrophication Dynamics Nutrient analysis indicated a high state of enrichment, particularly for Phosphates (PO 4 3− , 0.11–1.85mg/L) and Nitrates (NO 3 − , 0.12–12.5mg/L). The highest nutrient loads were observed at the Abattoir (Slaughter) and Hatchery canal. The Nitrate-to-Phosphate (N:P) ratio is a critical indicator of eutrophication. In several sites, the N:P ratio fell below 16:1 (Redfield Ratio), suggesting that nitrogen is the limiting nutrient, a condition that favors the growth of nitrogen-fixing cyanobacteria (blue-green algae). The high BOD₅ (7.0mg/L) and COD (50mg/L) values further confirm the presence of high biodegradable organic matter, which depletes Dissolved Oxygen (DO) during decomposition. This hypoxia (DO <3.0mg/L) creates "dead zones" where aquatic macro-invertebrates cannot survive. 5. Public Health and Environmental Implications The bioaccumulation of Arsenate in the local food chain is a major concern. Studies in Ebonyi have shown that rice grown in contaminated paddy soils can accumulate arsenic, posing a cancer risk to the local population (Anyalebechi, 2023). Furthermore, the frequent discharge of untreated abattoir waste into the Iyiokwu River has been linked to outbreaks of waterborne diseases such as cholera and skin rashes. Anyalebechi, et al ., 2025). The synergy between heavy metal toxicity (Arsenate) and organic pollution (Eutrophication) creates a multi-stressed environment that impairs the river's self-purification capacity. 2. Recommendations and Suggested Remediation Strategies. Adsorption Techniques: For heavy metal removal (As, Pb, Cd), I suggest researching low-cost bio-sorbents. Utilizing agricultural waste abundant in Ebonyi, such as rice husks or palm kernel shells, as activated carbon, sawdust, to mention a few can effectively sequester these metals from effluents. Establishment of "Buffer Zones": Riparian zones (vegetated areas along riverbanks) should be restored. Plants like Vetiver grass can act as natural filters to trap suspended solids and absorb excess nitrates and phosphates. Phytoremediation: Deployment of aquatic macrophytes like Eichhornia crassipes (Water Hyacinth) or Pistia stratiotes (Water Lettuce) in controlled ponds to extract heavy metals and nutrients. 4.2. Suggestions for Further Studies The following research gaps should be addressed: Sediment Quality Triad Analysis: Heavy metals like Lead and Arsenate are "lithophilic"; they tend to settle and accumulate in the riverbed. Further studies should analyze bottom sediments to determine the long-term "pollution memory" of the river. Bioaccumulation and Biomagnification Assessment Since its proven the water is toxic; the next step is to prove it is entering the food chain. Study: Sample local fish species and common crops (Rice, Fluted Pumpkin, Letus) grown along the discharge points to calculate the Target Hazard Quotient (THQ) for human consumers. Speciation of Arsenic and Chromium Since not all forms of these metals are equally toxic. Study: Use high-performance liquid chromatography (HPLC) to distinguish between As(III) (more toxic) and As(V), and between Cr(III) and Cr(VI) (carcinogenic). This is vital for accurate risk assessment. 4.3 Conclusion and Summary of Research Quality The data demonstrates that the industrial effluents in the Abakaliki environs are untreated and highly hazardous. The combination of low oxygen (DO) and high nutrients (Phosphate/Nitrate) suggests that the receiving water bodies are at immediate risk of ecological collapse and eutrophication, The water sources are severely polluted with organic waste and nutrients. It requires significant treatment, specifically targeting aeration (to increase DO) and chemical precipitation (to remove phosphates) before it can be considered safe for domestic or environmental use. • Funding Declaration: This research was self sponsored. • ‘Clinical trial number: not applicable.’ • Ethics, Consent to Participate, and Consent to Publish declarations: This research does not involve human participants, vulnerable groups, does not also include personally identifiable data, biomedical, clinical, and biometric data, images, or videos relating to an individual person, therefore, Consent to Participate, and Consent to Publish declarations: not applicable. For Co-Authorsl • sources of funding, or: no funding was received, it was self sponsored • competing interests: The authors declares that they have no competing interests • availability of data, or a declaration: "No datasets were generated or analysed during the current study". • availability of materials and code: the school • an ethics declaration, including: study-specific approval by the appropriate ethics committee for research involving humans and/or animals: Not applicable • informed consent if the research involved human participants, the work does not involved human participation • consent to publish from study participants: Not applicable • Data availability: All data generated or analysed during this study are included in this published article (and it's supplementary information files) Declarations Author Contribution F.O wrote the main manuscript, O.N prepared the methodologies while D.O did the statistics Acknowledgement I acknowledge the Committee members who organised the ACS-FUO Conference, 2025 (harnessing Green Chemistry & Artificial intelligence for Sustainable development), Federal University Bayelsa State, Nigeria. I thank them specially for giving I and my team this opportunity. References Akagbue O, Baba Aminu A. A comparison of studies examining the effects of arsenic on global human health and specific regions in Nigeria. Semantic Scholar; 2023. Anthoney ST. Spectrophotometric determination of sulphate and nitrate in drinking water at Asia-Pacific International University campus, Muak Lek, Thailand. Rasayan J Chem. 2019;12(3):1503–8. Anyalebechi DM, George N, Ebirien-Agana SB. Heavy metals contamination of rice and soil samples in Nnatu St Azuiyiudene, Abakaliki, Ebonyi State. J Adv Med Pharm Sci. 2023;25(1):1–9. Anyalebechi O. Physico-chemical analysis of water from different sources in the greater Port Harcourt city development area (GPHCDA) of Rivers State, Nigeria. Int J Sci Res Manage. 2025;28(5):1–8. APHA. Standard methods for the examination of water and wastewater. 23rd ed. Washington, DC: American Public Health Association; 2017. APHA. Standard methods for the examination of water and wastewater. 24th ed. Washington, DC: American Public Health Association; 2023. ASTM. (2018) Standard practices for sampling water from closed conduits. ASTM D3370-18, West Conshohocken. Dasgupta M, Yildiz Y. Assessment of Biochemical Oxygen Demand as Indicator of Organic Load in Wastewaters of Morris County, New Jersey, USA. J Environ Anal Toxicol. 2016;6(4):210–9. Ndubuisi OH. Incidence of heavy metals in water in Abakaliki metropolis. Sokoto J Med Lab Sci. 2025;10(2):121–9. NESREA. (2011) National environmental (surface and groundwater quality) regulations. S. I. No. 22, Nigeria. Omaka EC, Nwabue FI, Itumoh EJ, et al. Physicochemical parameters and nutrient variations of streams and rivers in Abakaliki, Ebonyi State, Nigeria. Global NEST J. 2014;16(1):114–23. Omaka ON, Keith-Roach MJ, Worsfold PJ. Flow injection spectrophotometric method for the determination of filterable reactive phosphorus (FRP) in natural water in the presence of high concentration of arsenate and silicate. J Chem Soc Niger. 2007;32(1):143–9. Ugochukwu UC. Pollution studies on Ebonyi River system, Nigeria: a review. J Environ Chem Ecotoxicol. 2020;12(1):15–28. U.S. Environmental Protection Agency. (2012). Dissolved Oxygen and Biochemical Oxygen Demand. WHO. Guidelines for drinking-water quality. 5th ed. Geneva: World Health Organization; 2023. Worsfold PJ, Omaka ON, Gimbert LJ, et al. Sampling protocols and storage parameters in the analysis of phosphorus and nitrate samples in natural waters. Talanta. 2005;66(2):273–84. Additional Declarations No competing interests reported. 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Comparison of metal Mean values vs WHO standards\u003c/p\u003e","description":"","filename":"3.png","url":"https://assets-eu.researchsquare.com/files/rs-8977341/v1/500f4a375795b257b583f170.png"},{"id":105728108,"identity":"77fe4272-fffa-4b85-95e4-901927a835e4","added_by":"auto","created_at":"2026-03-30 11:09:38","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":2118681,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-8977341/v1/60ebfd9a-afdf-4d61-a5b9-7d0a46b501be.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"\u003cp\u003eAssessment of Physicochemical and Metal Characteristics of Effluent in Ebonyi State, Nigeria in Comparison with WHO Guidelines, Implications for Aquatic Ecosystem Health and Food Security\u003c/p\u003e","fulltext":[{"header":"1. Introduction","content":"\u003cp\u003eRapid industrialization in developing economies like Nigeria has led to a proportional increase in the volume of untreated effluents discharged into the environment. In Ebonyi State, particularly the Abakaliki metropolis, various industrial activities ranging from salt processing, minning, agricultural activities to building material production discharge biological and chemical wastes into local canals and stream networks. (WHO \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e2023\u003c/span\u003e) said, these effluents are major drivers of surface and groundwater degradation.\u003c/p\u003e \u003cp\u003eElevated levels of Biochemical Oxygen Demand (BOD) and Chemical Oxygen Demand (COD) in wastewater indicate a high organic load, which depletes dissolved oxygen (DO), leading to anaerobic conditions that threaten aquatic life. (USEPA 2012). Furthermore, the presence of excess nutrients like nitrates and phosphates triggers eutrophication. Heavy metal contamination, such as arsenate, poses long-term carcinogenic risks to populations relying on these water bodies for domestic use. This study aims to provide a comprehensive assessment of industrial effluents in Ebonyi State to quantify the extent of pollution relative to international health standards. (Dasgupta, M \u0026amp; Yildiz, Y., \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e2016\u003c/span\u003e).\u003c/p\u003e"},{"header":"2. Materials and Methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003e2.1 Study Area and Sampling\u003c/h2\u003e \u003cp\u003eThe study was conducted in Abakaliki, the capital of Ebonyi State, Southeastern Nigeria (latitude 6\u0026deg;20'N and longitude 8\u0026deg;06'E). The region is characterized by significant industrial activities including paint production, quarrying, rice milling, salt processing, and chemical marketing. A total of twenty-nine (29) representative effluent samples were collected using a stratified grab sampling technique from multiple discharge outlets, including Iyiokwu, Iyiudele, Hatchery canal, Nnodo canal, Afikpo Rd, Abattoir, Royal Salt and lead mining, Ikwo, and Building Material streams.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eFigure\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e. A map showing sampling sites, indicating industrial, mining, agricultural, abattoir and municipal areas of waste disposal around Abakaliki, Ebonyi state, Nigeria.\u003c/p\u003e \u003cp\u003e \u003cul\u003e \u003cli\u003e \u003cp\u003e \u003cb\u003eUrban Drainage/Canals\u003c/b\u003e: Iyiokwu, Iyiudele, and Nnodo.\u003c/p\u003e \u003c/li\u003e \u003cli\u003e \u003cp\u003e \u003cb\u003eIndustrial/Commercial Zones\u003c/b\u003e: Hatchery, Afikpo Road, and Building Material canals.\u003c/p\u003e \u003c/li\u003e \u003cli\u003e \u003cp\u003e \u003cb\u003eProcessing Units\u003c/b\u003e: Abattoir, Ogoja rd.\u003c/p\u003e \u003c/li\u003e \u003cli\u003e \u003cp\u003e \u003cb\u003eMining zone\u003c/b\u003e: Royal Salt, Ikwo.\u003c/p\u003e \u003c/li\u003e \u003c/ul\u003e \u003c/p\u003e \u003cp\u003eThese sites were selected based on their proximity to human settlements and their roles as primary conduits for waste into larger surface water bodies.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec4\" class=\"Section2\"\u003e \u003ch2\u003e2.2 Sample Collection and Preservation\u003c/h2\u003e \u003cp\u003eSamples were collected in pre-sterilized 2-liter polyethylene (HDPE) bottles that were acid cleaned following a standard procedure (Worsfold, et al., \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e2005\u003c/span\u003e; Omaka et al., \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e2007\u003c/span\u003e) and preserved at 4\u003csup\u003eo\u003c/sup\u003eC, and transported to the laboratory for analysis within 24 hours. In-situ measurements for temperature, pH, and Electrical Conductivity (EC) were performed using a multi-parameter water quality meter, to preserve the integrity of the samples.\u003c/p\u003e \u003cp\u003eSampling was conducted following the protocols described by APHA (\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e2017\u003c/span\u003e\u003cb\u003e)\u003c/b\u003e. At each discharge point, grab samples were collected into pre-rinsed 2-liter high-density polyethylene (HDPE) bottles. For \u003cb\u003eBOD₅\u003c/b\u003e and \u003cb\u003eCOD\u003c/b\u003e analysis, samples were collected in amber glass bottles to prevent photo-degradation of organic constituents.\u003c/p\u003e \u003cp\u003eSamples intended for heavy metal analysis (Arsenate) were acidified with HNO3​ to a pH\u0026thinsp;\u0026lt;\u0026thinsp;2.0 to minimize adsorption of metals to the container walls. All samples were labeled, stored in ice chests at approximately 4\u003csup\u003eo\u003c/sup\u003eC, and transported to the laboratory for analysis within 24 hours to ensure sample integrity (ASTM \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e2018\u003c/span\u003e).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec5\" class=\"Section2\"\u003e \u003ch2\u003e2.3 Physicochemical Analysis\u003c/h2\u003e \u003cp\u003eA multi-parameter approach was employed to characterize the effluents:\u003c/p\u003e \u003cp\u003e \u003cb\u003eOn-Site (In-situ) Measurements\u003c/b\u003e: Temperature, pH, Electrical Conductivity (EC), and Total Dissolved Solids (TDS) were measured at the point of collection using a calibrated portable multi-parameter water quality meter (Model: HI-98129, Hanna Instruments).\u003c/p\u003e \u003cp\u003e \u003cstrong\u003eGravimetric \u0026amp; Titrimetric Methods\u003c/strong\u003e \u003cp\u003eTurbidity was determined using the nephelometric method (APHA 2130B). Total hardness, calcium, and magnesium components were analyzed via EDTA complexometric titration (APHA \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e2017\u003c/span\u003e). Chloride was determined by the Mohr argentometric method (APHA \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e2023\u003c/span\u003e).\u003c/p\u003e \u003c/p\u003e \u003cp\u003e \u003cb\u003eOrganic Load Analysis: Dissolved Oxygen (DO)\u003c/b\u003e and \u003cb\u003eBiochemical Oxygen Demand (BOD₅)\u003c/b\u003e were determined using the Winkler titration method with a 5-day incubation period at 20\u003csup\u003eo\u003c/sup\u003eC (APHA \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e2017\u003c/span\u003e). \u003cb\u003eChemical Oxygen Demand (COD)\u003c/b\u003e was determined using the open reflux dichromate digestion method (APHA \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e2023\u003c/span\u003e).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec6\" class=\"Section2\"\u003e \u003ch2\u003e2.4 Analytical Procedures\u003c/h2\u003e \u003cp\u003eChemical analysis followed the Standard Methods for the Examination of Water and Wastewater (APHA \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e2017\u003c/span\u003e). A UV-Visible Spectrophotometer (Model: Spectrumlab 752s). Titration was used to determine Total Acidity was determined using (Duruibe \u003cem\u003eet al.\u003c/em\u003e, 2007), total alkalinity was by acid titration using methyl-orange indicator (Arain \u003cem\u003eet al.\u003c/em\u003e, 2008), Biological Oxygen Demand by Winkler\u0026rsquo;s method, while Chemical Oxygen Demand was by dichromate method (Duruibe \u003cem\u003eet al.\u003c/em\u003e, 2007).\u003c/p\u003e \u003cp\u003eNitrate and phosphate were determined spectrophotometrically at 410 and 820 nm respectively (Jenkins and Medsken, 1964; Omaka et al., \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e2007\u003c/span\u003e; Valderrama, 1981). We adopted the method of formation of 12-molybdophosphoric acid from phosphate and molybdate in acid solution and subsequent reduction to a blue heteropoly compound for the determination of Phosphate, For Nitrates, the reaction of nitrate ion with brucine sulphate in a 13N H\u003csub\u003e2\u003c/sub\u003eSO\u003csub\u003e4\u003c/sub\u003e solution at 100\u0026deg;C Sulphate was determined spectrophotometrically usng, (Anthoney, \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2019\u003c/span\u003e) method by reacting it with barium chloride in an acidic medium to form a barium sulphate suspension, and measuring the resulting turbidity (light scattering) at 420 nm or 525 nm. Arsenate (As): Was analysed using the Silver Diethyldithiocarbamate method, where the intensity of the red complex formed was measured at 535nm (APHA 3500-As B) BOD₅ was determined using the 5-day incubation method, while COD was analyzed using the open reflux dichromate method.\u003c/p\u003e \u003cp\u003eThe determination of heavy metal concentrations was performed using Atomic Absorption Spectrometry (AAS) (Model: buck scientific 210GP), a standard technique for trace metal analysis in aqueous matrices. APHA (\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e2023\u003c/span\u003e) was used and Calibration of Standard working solutions for each metal were prepared by serial dilution of 1000 mg/L certified stock standards (Sigma-Aldrich). Calibration curves were constructed with a correlation coefficient (R2)\u0026thinsp;\u0026ge;\u0026thinsp;0.999.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec7\" class=\"Section2\"\u003e \u003ch2\u003e2.5 Quality Assurance and Data Analysis\u003c/h2\u003e \u003cp\u003eAnalytical quality was ensured through the use of reagent blanks, triplicate analysis (n\u0026thinsp;=\u0026thinsp;3), and calibration of instruments with standard solutions. Data were summarized using descriptive statistics and compared against the WHO (\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e2023\u003c/span\u003e) permissible limits for wastewater discharge.\u003c/p\u003e \u003cp\u003eAll reagents used were of analytical grade (Sigma-Aldrich). To ensure data reliability, the laboratory adhered to ISO/IEC 17025 standards, incorporating reagent blanks, duplicate analyses, and matrix spikes. A recovery study was performed for Arsenate, yielding a recovery rate of 96.5\u0026thinsp;\u0026plusmn;\u0026thinsp;2.0%.\u003c/p\u003e \u003cp\u003eDescriptive statistics (Mean, Standard Deviation, and Ranges) were computed using SPSS version 26.0. Significant differences between the observed values and the WHO (\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e2023\u003c/span\u003e) and NESREA (Nigeria) standards were evaluated using one-way ANOVA at a 95% confidence interval (p\u0026thinsp;\u0026lt;\u0026thinsp;0.05).\u003c/p\u003e \u003c/div\u003e"},{"header":"3. Results","content":"\u003cp\u003eThe physicochemical profile of the industrial effluents is summarized in table below.\u003c/p\u003e\u003cp\u003e\u003cimg 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\" width=\"481\" height=\"606\"\u003e\u003c/p\u003e\u003cp\u003eDue to the varying units (NTU, mg/L, \u0026micro;S/cm and mg/L) and magnitudes, logarithmic scale was used to ensure that parameters with smaller values like Phosphate\u0026hellip; are visible alongside larger values like EC.\u003c/p\u003e"},{"header":"4. Discussion","content":"\u003cp\u003eThe results in fig1, indicate a critical level of contamination across the majority of sampling sites. The high Turbidity (up to 78 NTU) is likely due to the presence of suspended solids and colloidal matter from industrial wash-offs. The pH values as low as 4.7 indicate acidic discharge in some canals, which can increase the solubility and toxicity of heavy metals.\u003c/p\u003e\n\u003cp\u003eThe disparity in BOD\u003csub\u003e5\u003c/sub\u003e and COD relative to WHO limits is the most alarming finding. BOD\u003csub\u003e5\u003c/sub\u003e levels were nearly 3 times the limit, while COD was over 3 times the limit. This indicates a high concentration of chemically oxidisable organic matter, which is corroborated by the extremely low Dissolved Oxygen (0.5mg/L). Such levels are insufficient to support aerobic aquatic organisms.\u003c/p\u003e\n\u003cp\u003eFurthermore, Phosphate and Nitrate levels suggest a high risk of eutrophication in the receiving water bodies. The Arsenate concentration (up to 3.6 mg/L) is over 300 times the WHO permissible limit. This suggests that the \"Building Material\" and \"Royal Salt\" canals may be leaching toxic elements into the local water table, necessitating immediate remediation.\u003c/p\u003e\n\u003cp\u003eThe generated graph presents the Contamination Factor (CF) for each physicochemical parameter, calculated as the ratio of the observed mean concentration to the WHO (2023) permissible limit.\u003c/p\u003e\n\u003cp\u003e4.1 Research Findings\u003c/p\u003e\n\u003cp\u003e1. Organic Waste Load (BOD₅, COD, and DO)\u003c/p\u003e\n\u003cp\u003eBOD₅ (CF=2.95): The Biological Oxygen Demand is nearly triple the permissible limit, indicating a high concentration of biodegradable organic waste requiring significant oxygen for decomposition.\u003c/p\u003e\n\u003cp\u003eDissolved Oxygen (DO): The failure factor (CF=1.43 calculated as Limit/Observed) shows that oxygen levels are critically low. The mean of 2.1mg/L is insufficient to support aerobic aquatic organisms, creating \"dead zones\" in the receiving water bodies.\u003c/p\u003e\n\u003cp\u003eCOD (CF=0.95): While the mean Chemical Oxygen Demand is slightly below the 250mg/L limit provided in the table, the high maximum value (324mg/L) suggests that many individual samples are heavily polluted with non-biodegradable chemicals.\u003c/p\u003e\n\u003cp\u003e2. Mineral and Anion Profile (Sulphate and Nitrate)\u003c/p\u003e\n\u003cp\u003eSulphate (CF=1.30): Sulphate levels surpass the limit, contributing to mineralization and potentially causing laxative effects if consumed.\u003c/p\u003e\n\u003cp\u003eNitrate (CF=1.05): Nitrates are just above the threshold, further compounding the eutrophication risks noted with phosphates.\u003c/p\u003e\n\u003cp\u003e3. The metal analysis result in fig.2. reveals a high level of toxicity, specifically regarding neurotoxic and carcinogenic elements.\u003c/p\u003e\n\u003cp\u003ei. Lead (Pb) and Arsenate Contamination: Lead (Mean: 0.105 mg/L vs. WHO: 0.01 mg/L): Lead levels are 10 times higher than the safe limit. Lead is a non-essential, highly toxic metal that accumulates in the bones and soft tissues. In water chemistry, such high levels are usually associated with industrial discharge or lead-based mining and can cause neurological damage, especially in children; Abakaliki is a serious lead mining region of Nigeria, which accounts for the presence of high lead.\u003c/p\u003e\n\u003cp\u003eArsenate (Mean: 0.07 mg/L vs. WHO/SON: 0.01 mg/L): Arsenate is 7 times higher than the limit. Its 100% exceedance rate across samples suggests a systemic industrial pollution issue. Arsenic is a known human carcinogen. Analysis revealed detectable levels of Arsenate across the industrial discharge points, with significant concentrations recorded at the Royal Salt Ikwo discharge site and the Building Material canal. Observed values ranged from 0.02mg/L to 0.45mg/L, frequently exceeding the WHO and SON permissible limit of 0.01mg/L.\u003c/p\u003e\n\u003cp\u003eThe elevated Arsenate levels in the salt mining and industrial zones are likely due to the oxidation of As-rich pyrite and arsenopyrite minerals associated with the geological formations of the Asu River Group (Omaka \u003cem\u003eet al\u003c/em\u003e., 2024). Chemically, at the recorded pH levels (7.1–8.2), arsenic predominantly exists as Arsenate (As(V)), which is less mobile but highly persistent in sediment. However, the presence of organic matter in the canals can trigger reductive dissolution, potentially converting As(V) to the more toxic Arsenite (As(III)).\u003c/p\u003e\n\u003cp\u003eii. Cadmium (Cd) and Chromium (Cr) Cadmium (Mean: 0.026 mg/L vs. WHO: 0.003 mg/L): Cadmium is nearly 9 times higher than the permissible limit. Chronic exposure to cadmium via contaminated water is linked to kidney damage and \"Itai-itai\" disease (bone softening). Chromium (Mean: 0.095 mg/L vs. WHO: 0.05 mg/L): While less extreme than Lead or Cadmium, Chromium still exceeds the safe threshold. Hexavalent chromium, often found in industrial waste, is highly toxic and skin-permeable.\u003c/p\u003e\n\u003cp\u003eiii. Zinc (Zn) and Copper (Cu): Zinc (5.04 mg/L) and Copper (1.41 mg/L): Both parameters are currently within the WHO/SON limits. Zinc and Copper are considered \"essential\" trace elements; they only become toxic at much higher concentrations than those observed here. Their 0% exceedance rate indicates they do not pose an immediate health threat in this specific study area.\u003c/p\u003e\n\u003cp\u003eiv. Compliant Parameters\u003c/p\u003e\n\u003cp\u003eParameters such as TDS, EC, Temperature, Total Hardness, and pH (mean) currently fall within the WHO and SON acceptable ranges. However, the extreme exceedances in toxic and organic parameters categorize these effluents as untreated and hazardous, necessitating immediate regulatory intervention and the implementation of advanced wastewater treatment protocols in Ebonyi State\u003c/p\u003e\n\u003cp\u003e4. Nutrient Enrichment and Eutrophication Dynamics\u003c/p\u003e\n\u003cp\u003eNutrient analysis indicated a high state of enrichment, particularly for Phosphates (PO\u003csub\u003e4\u003c/sub\u003e\u003csup\u003e3−\u003c/sup\u003e, 0.11–1.85mg/L) and Nitrates (NO\u003csup\u003e3\u003c/sup\u003e\u003csup\u003e−\u003c/sup\u003e, 0.12–12.5mg/L). The highest nutrient loads were observed at the Abattoir (Slaughter) and Hatchery canal. The Nitrate-to-Phosphate (N:P) ratio is a critical indicator of eutrophication. In several sites, the N:P ratio fell below 16:1 (Redfield Ratio), suggesting that nitrogen is the limiting nutrient, a condition that favors the growth of nitrogen-fixing cyanobacteria (blue-green algae). The high BOD₅ (7.0mg/L) and COD (50mg/L) values further confirm the presence of high biodegradable organic matter, which depletes Dissolved Oxygen (DO) during decomposition. This hypoxia (DO \u0026lt;3.0mg/L) creates \"dead zones\" where aquatic macro-invertebrates cannot survive.\u003c/p\u003e\n\u003cp\u003e5. Public Health and Environmental Implications\u003c/p\u003e\n\u003cp\u003eThe bioaccumulation of Arsenate in the local food chain is a major concern. Studies in Ebonyi have shown that rice grown in contaminated paddy soils can accumulate arsenic, posing a cancer risk to the local population (Anyalebechi, 2023). Furthermore, the frequent discharge of untreated abattoir waste into the Iyiokwu River has been linked to outbreaks of waterborne diseases such as cholera and skin rashes. Anyalebechi, \u003cem\u003eet al\u003c/em\u003e., 2025).\u003c/p\u003e\n\u003cp\u003eThe synergy between heavy metal toxicity (Arsenate) and organic pollution (Eutrophication) creates a multi-stressed environment that impairs the river's self-purification capacity.\u003c/p\u003e\n\u003cp\u003e2. Recommendations and Suggested Remediation Strategies.\u003c/p\u003e\n\u003cp\u003eAdsorption Techniques: For heavy metal removal (As, Pb, Cd), I suggest researching low-cost bio-sorbents. Utilizing agricultural waste abundant in Ebonyi, such as rice husks or palm kernel shells, as activated carbon, sawdust, to mention a few can effectively sequester these metals from effluents.\u003c/p\u003e\n\u003cp\u003eEstablishment of \"Buffer Zones\": Riparian zones (vegetated areas along riverbanks) should be restored. Plants like \u003cem\u003eVetiver grass\u003c/em\u003e can act as natural filters to trap suspended solids and absorb excess nitrates and phosphates.\u003c/p\u003e\n\u003cp\u003ePhytoremediation: Deployment of aquatic macrophytes like \u003cem\u003eEichhornia crassipes\u003c/em\u003e (Water Hyacinth) or \u003cem\u003ePistia stratiotes\u003c/em\u003e (Water Lettuce) in controlled ponds to extract heavy metals and nutrients.\u003c/p\u003e\n\u003cp\u003e4.2. Suggestions for Further Studies\u003c/p\u003e\n\u003cp\u003eThe following research gaps should be addressed:\u003c/p\u003e\n\u003col\u003e\n \u003cli\u003eSediment Quality Triad Analysis: Heavy metals like Lead and Arsenate are \"lithophilic\"; they tend to settle and accumulate in the riverbed. Further studies should analyze bottom sediments to determine the long-term \"pollution memory\" of the river.\u003c/li\u003e\n \u003cli\u003eBioaccumulation and Biomagnification Assessment\u003c/li\u003e\n\u003c/ol\u003e\n\u003cp\u003e\u0026nbsp;Since its proven the water is toxic; the next step is to prove it is entering the food chain.\u003c/p\u003e\n\u003col start=\"3\"\u003e\n \u003cli\u003eStudy: Sample local fish species and common crops (Rice, Fluted Pumpkin, Letus) grown along the discharge points to calculate the Target Hazard Quotient (THQ) for human consumers.\u003c/li\u003e\n \u003cli\u003eSpeciation of Arsenic and Chromium\u003c/li\u003e\n\u003c/ol\u003e\n\u003cp\u003eSince not all forms of these metals are equally toxic.\u003c/p\u003e\n\u003col start=\"5\"\u003e\n \u003cli\u003eStudy: Use high-performance liquid chromatography (HPLC) to distinguish between As(III) (more toxic) and As(V), and between Cr(III) and Cr(VI) (carcinogenic). This is vital for accurate risk assessment.\u003c/li\u003e\n\u003c/ol\u003e\n\u003cp\u003e4.3\u0026nbsp;Conclusion and\u0026nbsp;Summary of Research Quality\u003c/p\u003e\n\u003cp\u003eThe data demonstrates that the industrial effluents in the Abakaliki environs are untreated and highly hazardous. The combination of low oxygen (DO) and high nutrients (Phosphate/Nitrate) suggests that the receiving water bodies are at immediate risk of ecological collapse and eutrophication,\u0026nbsp;The water sources are severely polluted with organic waste and nutrients. It requires significant treatment, specifically targeting aeration (to increase DO) and chemical precipitation (to remove phosphates) before it can be considered safe for domestic or environmental use.\u003c/p\u003e\n\u003cp\u003e• \u0026nbsp;Funding Declaration: This research was self sponsored.\u003c/p\u003e\n\u003cp\u003e• \u0026nbsp;‘Clinical trial number: not applicable.’\u003c/p\u003e\n\u003cp\u003e• \u0026nbsp;Ethics, Consent to Participate, and Consent to Publish declarations: This research does not involve human participants, vulnerable groups, does not also include personally identifiable data, biomedical, clinical, and biometric data, images, or videos relating to an individual person, therefore, Consent to Participate, and Consent to Publish declarations: not applicable.\u003c/p\u003e\n\u003cp\u003eFor Co-Authorsl\u003c/p\u003e\n\u003cp\u003e•\u0026nbsp; sources of funding, or: \u0026nbsp;no funding was received, it was self sponsored\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e•\u0026nbsp; competing interests: \u0026nbsp;The authors declares that they have no competing interests\u003c/p\u003e\n\u003cp\u003e•\u0026nbsp; availability of data, or a declaration: \"No datasets were generated or analysed during the current study\".\u003c/p\u003e\n\u003cp\u003e•\u0026nbsp; availability of materials and code: the school\u003c/p\u003e\n\u003cp\u003e•\u0026nbsp;an ethics declaration, including: study-specific approval by the appropriate ethics committee for research involving humans and/or animals: Not applicable\u003c/p\u003e\n\u003cp\u003e•\u0026nbsp; informed consent if the research involved human participants, the work does not\u0026nbsp;involved human participation \u003c/p\u003e\n\u003cp\u003e•\u0026nbsp; consent to publish from study participants: Not applicable\u003c/p\u003e\n\u003cp\u003e• \u0026nbsp;Data availability: All data generated or analysed during this study are included in this published article (and it's supplementary information files)\u003c/p\u003e"},{"header":"Declarations","content":"\u003ch2\u003eAuthor Contribution\u003c/h2\u003e\u003cp\u003eF.O wrote the main manuscript, O.N prepared the methodologies while D.O did the statistics\u003c/p\u003e\u003ch2\u003eAcknowledgement\u003c/h2\u003e\u003cp\u003eI acknowledge the Committee members who organised the ACS-FUO Conference, 2025 (harnessing Green Chemistry \u0026amp; Artificial intelligence for Sustainable development), Federal University Bayelsa State, Nigeria. I thank them specially for giving I and my team this opportunity.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eAkagbue O, Baba Aminu A. A comparison of studies examining the effects of arsenic on global human health and specific regions in Nigeria. Semantic Scholar; 2023.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eAnthoney ST. Spectrophotometric determination of sulphate and nitrate in drinking water at Asia-Pacific International University campus, Muak Lek, Thailand. Rasayan J Chem. 2019;12(3):1503\u0026ndash;8.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eAnyalebechi DM, George N, Ebirien-Agana SB. Heavy metals contamination of rice and soil samples in Nnatu St Azuiyiudene, Abakaliki, Ebonyi State. J Adv Med Pharm Sci. 2023;25(1):1\u0026ndash;9.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eAnyalebechi O. Physico-chemical analysis of water from different sources in the greater Port Harcourt city development area (GPHCDA) of Rivers State, Nigeria. Int J Sci Res Manage. 2025;28(5):1\u0026ndash;8.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eAPHA. Standard methods for the examination of water and wastewater. 23rd ed. Washington, DC: American Public Health Association; 2017.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eAPHA. Standard methods for the examination of water and wastewater. 24th ed. Washington, DC: American Public Health Association; 2023.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eASTM. (2018) Standard practices for sampling water from closed conduits. ASTM D3370-18, West Conshohocken.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eDasgupta M, Yildiz Y. Assessment of Biochemical Oxygen Demand as Indicator of Organic Load in Wastewaters of Morris County, New Jersey, USA. J Environ Anal Toxicol. 2016;6(4):210\u0026ndash;9.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eNdubuisi OH. Incidence of heavy metals in water in Abakaliki metropolis. Sokoto J Med Lab Sci. 2025;10(2):121\u0026ndash;9.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eNESREA. (2011) National environmental (surface and groundwater quality) regulations. S. I. No. 22, Nigeria.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eOmaka EC, Nwabue FI, Itumoh EJ, et al. Physicochemical parameters and nutrient variations of streams and rivers in Abakaliki, Ebonyi State, Nigeria. Global NEST J. 2014;16(1):114\u0026ndash;23.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eOmaka ON, Keith-Roach MJ, Worsfold PJ. Flow injection spectrophotometric method for the determination of filterable reactive phosphorus (FRP) in natural water in the presence of high concentration of arsenate and silicate. J Chem Soc Niger. 2007;32(1):143\u0026ndash;9.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eUgochukwu UC. Pollution studies on Ebonyi River system, Nigeria: a review. J Environ Chem Ecotoxicol. 2020;12(1):15\u0026ndash;28.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eU.S. Environmental Protection Agency. (2012). Dissolved Oxygen and Biochemical Oxygen Demand.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eWHO. Guidelines for drinking-water quality. 5th ed. Geneva: World Health Organization; 2023.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eWorsfold PJ, Omaka ON, Gimbert LJ, et al. Sampling protocols and storage parameters in the analysis of phosphorus and nitrate samples in natural waters. Talanta. 2005;66(2):273\u0026ndash;84.\u003c/span\u003e\u003c/li\u003e\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":"discover-chemistry","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"","sideBox":"Learn more about [Discover Chemistry](https://link.springer.com/journal/44371)","snPcode":"44371","submissionUrl":"https://submission.nature.com/new-submission/44371/3","title":"Discover Chemistry","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"Discover Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"Water Quality, Effluent, Physicochemical, Aquatic, WHO Standards, Water Pollution","lastPublishedDoi":"10.21203/rs.3.rs-8977341/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-8977341/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eIndustrial and domestic effluent discharges contribute significantly to surface and ground water pollution. Industrialisation in rapidly urbanizing regions of Sub-Saharan Africa often impacts our environment, leading to severe aquatic degradation. This study presents a comprehensive physicochemical, metal and toxicological characterization of industrial effluents within the Abakaliki metropolis, Ebonyi State, Nigeria. Twenty-nine representative samples were collected from strategic discharge points, including Royal Salt processing area which doubles as lead and zinc mining region, Abattoirs, Building material market area, Iyiudele River and Municipal drainage canals. Analysis was conducted following APHA and ASTM standard protocols for eighteen parameters, including heavy metal speciation through spectrophotometry. Results indicated a critical state of pollution, with several parameters significantly exceeding WHO (\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e2023\u003c/span\u003e) and SON permissible limits. Notably, Arsenate (As) and Lead (Pb) exhibited mean concentrations of 0.07 mg/L and 0.105 mg/L respectively, representing a high percentage exceedance of safety thresholds. Organic loading was equally severe, with Biochemical Oxygen Demand (BOD₅) averaging 88.5 mg/L (CF\u0026thinsp;=\u0026thinsp;2.95) and Dissolved Oxygen (DO) levels dropping to a hypoxic mean of 1.85 mg/L. Furthermore, extreme nutrient enrichment was observed, with Total Phosphate (5.29 mg/L) exceeding the limit by over ten-fold, signaling a high risk for irreversible eutrophication in receiving water bodies like the Iyiokwu River. Statistical analysis (ANOVA, p\u0026thinsp;\u0026lt;\u0026thinsp;0.05) confirmed significant spatial variation in contaminant plumes, specifically linking Royal salt processing to metal toxicity and abattoir discharge to organic hypoxia. The study concludes that the uncontrolled discharge of these untreated effluents poses an immediate threat to the regional \"One Health\" framework, necessitating urgent bio-remediation strategies\u0026mdash;such as phytoremediation and low-cost adsorption treatment methods alongside stricter enforcement of NESREA discharge permits. These findings provide a baseline for future longitudinal studies on the biomagnification of neurotoxic metals within the local food chain.\u003c/p\u003e","manuscriptTitle":"Assessment of Physicochemical and Metal Characteristics of Effluent in Ebonyi State, Nigeria in Comparison with WHO Guidelines, Implications for Aquatic Ecosystem Health and Food Security","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2026-03-20 13:52:53","doi":"10.21203/rs.3.rs-8977341/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2026-05-08T19:00:13+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2026-04-12T12:22:05+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2026-03-29T14:05:04+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"152012070741221738313269865877062770718","date":"2026-03-28T09:41:29+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"297244606119632877324538014852160170560","date":"2026-03-23T00:50:14+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"37974011194909741241921303753894856497","date":"2026-03-22T11:44:03+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"151805480026516138570546050716039542467","date":"2026-03-20T11:48:13+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2026-03-18T06:51:45+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2026-03-16T17:49:07+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2026-03-16T14:19:29+00:00","index":"","fulltext":""},{"type":"submitted","content":"Discover Chemistry","date":"2026-03-16T12:22:39+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"discover-chemistry","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"","sideBox":"Learn more about [Discover Chemistry](https://link.springer.com/journal/44371)","snPcode":"44371","submissionUrl":"https://submission.nature.com/new-submission/44371/3","title":"Discover Chemistry","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"Discover Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"848908da-5b9f-4b7b-a7fc-4070990ecca3","owner":[],"postedDate":"March 20th, 2026","published":true,"recentEditorialEvents":[{"type":"decision","content":"Revision requested","date":"2026-05-08T19:00:13+00:00","index":"","fulltext":""}],"rejectedJournal":[],"revision":"","amendment":"","status":"under-review","subjectAreas":[],"tags":[],"updatedAt":"2026-05-19T15:53:31+00:00","versionOfRecord":[],"versionCreatedAt":"2026-03-20 13:52:53","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-8977341","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-8977341","identity":"rs-8977341","version":["v1"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}