Introduction

Tanning industry makes a significant contribution to global economic development by providing raw materials essential for the footwear, upholstery, and fashion sectors1,2. Despite a vital role they play in terms of economic benefits, industry has significantly affected the natural balance of ecosystems through the discharge of large volumes of effluents containing hazardous substances, such as heavy metals, sulfides, organic pollutants, and microbial contaminants3,4. Release of untreated wastewater from tannery industries, especially in aquatic environments, has resulted in serious water pollution and ecological degradation, which in turn led to biodiversity loss, depletion of oxygen, and chronic toxicity5,6. These practices are widespread in most developing nations, where adequate wastewater treatment facilities are lacking and environmental standards are not consistently enforced, thereby putting both ecosystem stability and public health at greater risk7,8,9. Untreated tannery effluents severely degrade aquatic ecosystems by elevating BOD, COD, and toxic metal concentration, contributing to oxygen deficiency, loss of biodiversity, and eutrophication10. Heavy metals such as chromium can accumulate in organisms and sediments, resulting in long-term ecological damage. For humans, microbial pathogens and toxic metal exposure from polluted water and crops lead to waterborne diseases, organ impairment, developmental abnormalities, and cancer. Neighboring communities around tannery areas may experience skin and respiratory health issues as a result of long-term environmental exposure11,12. Even though scholars have studied similar cases13,14,15 and most of such research were centered on contamination indicators such as Biochemical Oxygen Demand (BOD), Chemical Oxygen Demand (COD), and Total Suspended Solids (TSS), but have failed to explain complex interactions and cumulative risks posed by multiple pollutants. The reason behind could be the void of advanced statistical tools and so the ability to effectively identify major contaminants, their sources, and to develop evidence-based remediation strategies were hindered16,17. To overcome with the shortcomings of previous research on effluent pollution from tanneries, this study employed a thorough, data–based, multifaceted, and data-driven methodology. To comprehensively evaluate an extent and severity of contamination on both ecosystem and human health, the present research used a set of pollution assessment indices, including Pollution Index (PI), Contamination Index (CI), Geo-Accumulation Index (I_geo), Environmental Hazard Index (EHI), and Health Risk Index (HRI). These indices were applied to measure pollution intensity, determine anthropogenic effluences, assess ecological risks, and estimate potential health risks to the exposed populations. Additionally, this study widens its scope to cover critical areas that most of the past studies didn’t consider, such as sediment contamination, bioaccumulation potentials, and long-term ecological risk, which enables the outcome to be easily used in environmental regulation and policy formulation18,19. Additionally, the use of Principal Component Analysis (PCA) and correlational matrix, which function as efficient model for an identification of prominent contaminants and pollution patterns through statistical modeling, is the research’s most notable aspect. Policymakers and environmental managers can better understand the data when PCA analysis and correlational visualizations are included. The research offers a comprehensive framework to evaluate contamination risk, to differentiate between anthropogenic and natural pollution sources, and to pinpoint high-risk locations for focused intervention by utilizing an integrated collection of pollution indices and statistical methods. The results of this study might advance environmental sustainability, protect public health, and fortify the governance of industrial wastewater management through this all-encompassing and policy-oriented approach.

Materials and Methods

Study Area

Figure: 1
Figure: 1
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Study area and sampling points at the river Dalimi in Naraguta. All Maps of Figure 1 were created using QGIS Version 3.28.10 “Firenze” (https://qgis.org), a free geographic information system available on GitHub through the efforts of the QGIS Development Team (QGIS, 2023). Base layers were taken from OpenStreetMap, SRTM, and FAO- GAUL. All layers were projected using a spatial reference system WGS 84 (EPSG:4326) to guarantee global positional accuracy and compatibility.

Naraguta Village, Jos North LGA, Plateau State, is located in the North Central region of Nigeria (Fig. 1). The Naraguta Village comprises a population of over 400,000. The climate is temperate due to elevated altitude (~ 1,200 m asl), and the area experiences a clear rainy (April-October) and dry (November–March) season. The region experiences 1,100–1,500 mm rainfall, and temperatures in the range 13 °C to 30 °C. The landscape is gently undulating with soils of lateritic-loamy types and are good for subsistence agriculture. Farming (maize, potatoes, and vegetables), animal husbandry, and artisanal mining are the common economic activities. Industrially, the area is suitable for accommodating small to medium-scale enterprises, including tannery operations processing raw hides into leather, enabling significant employment and contribution to the leather industry in Nigeria. These tanneries, however, dispose of untreated effluents with high contents of heavy metals and organic matter into surrounding water bodies, and the consequences on the environment and public health are negative. This highlights the requirement for the integrated management of wastes and environmental risk assessment for sustainable development in a way that preserves ecological and human health.

Sampling and Analytical Techniques

Sample Collection

84 surface water samples were collected over one year to assess the spatial and temporal extent of pollutants in tannery wastewater-polluted environments. Seven samples were collected monthly from seven systematically geo-referenced stations labeled A to G (Fig. 1), spaced 20 m apart, starting at the outlet of the tannery effluent discharge (station A) and continuing 180 m downstream (station G). Sampling points are named as AB, BC, CD, GE, EF, and GO for easier identification. This spatial arrangement was intended to capture the pollutant dispersion gradients from the point source. At each sampling station, three replicate samples were collected to ensure analytical accuracy, and their mean values were recorded for interpretation. Samplings were done in pre-sterilized 1-liter borosilicate glass bottles, as recommended by APHA Standard Methods20 to prevent contamination and guarantee sample integrity for physicochemical, microbial, and heavy metals analysis. All samples were kept in ice during transport and analyzed within 24 to 48 h of sampling. A systematic fixed-interval approach, enhanced by a stratified spatial coverage method was used. Stratified spatial coverage is a method well suited for assessing contamination patterns surrounding a point-source discharge, as advocated by United States Environmental Protection Agency (USEPA)21 and additionally validated by22 for water quality monitoring in river systems. This strategy enables the identification of pollution gradients, enhances reproducibility, and is widely applied in environmental impact assessments for industrial effluents. Monthly samples were taken to reflect seasonality and temporal fluctuations in effluent composition as a result of operational or climatic influences23. This study used the American Public Health Association24 Standard Methods for the examination of water and wastewater. This method is internationally recognized for water quality monitoring. The method provides standard validated procedures for the collection of samples, their preservation, and guidelines to analyse physicochemical, biological, and heavy metal parameters in water. The current study also follows the WHO23 requirements of water safety and quality guidelines24. Standard procedures were employed for the measurement of the parameters like pH, EC, BOD5, COD, TDS, TSS, nutrients. Microbial Indicators, and Atomic Absorption Spectrophotometry (AAS) were utilized for heavy metal determination. The used procedures maintained accuracy, reliability, and comparability of results relative to regulatory and scientific standards.

Sample Analysis

Monthly, a total of 7 samples were taken and analyzed. Parameters measured were pH, electrical conductivity (EC), total dissolved solids (TDS), total suspended solids (TSS), total solids (TS), biochemical oxygen demand (BOD5), and chemical oxygen demand (COD). The measurement of various parameters was done by following standard protocols given by APHA25, WHO26 and also by following procedures given in the literatures27,28. BOD5 was analyzed with the OxiTop® respirometric system, while COD and solids (TDS, TSS, TS) were determined by colorimetric and gravimetric methods, respectively. Concentrations of heavy metals, namely iron (Fe) and chromium (Cr), were measured by atomic absorption spectrophotometry (AAS) after calibration of the instrument with certified standards. Heavy metals (Fe and Cr) were determined by Flame Atomic Absorption Spectrophotometry (AAS) by APHA Standard Method 3111 B, and sample digestion according to EPA Method 3050B. The calibration was made with certified standard solutions (1000 mg/L stock) diluted to 0.5–10 mg/L, with a blank (matched acidity deionized water) for instrument zeroing. A linear calibration curve (R² > 0.995) was maintained in compliance with Beer–Lambert Law for analytical accuracy. Reference standards were APHA, EPA Method 7000B, and ISO 15586:2003. The concentrations of nutrients, total nitrogen (TN), nitrate (NO₃⁻), sulfate (SO₄²⁻), and chloride (Cl⁻), were analyzed by UV–Vis spectrophotometric and titrimetric procedures through standard operating procedures29. Microbiological examination involved the count of Escherichia coli and identification of helminth eggs (Ascaris lumbricoides, Hookworm, Trichuris trichiura, Strongyloides stercoralis) through the multiple-tube fermentation method and concentration methods of parasitology. Other biochemical tests Triple Sugar Iron (TSI), Methyl Red-Voges Proskauer (MR-VP), citrate, and urease tests, were utilized to validate the presence of E. coli and other coliform bacteria26.

Pollution Assessment

To quantify and describe the extent and risk of tannery effluent discharge contamination, the current research employed a multi-index pollution assessment model. The indices employed include the Pollution Load Index (PLI), Contamination Factor (CF), Contamination Index (CI), and Geo-Accumulation Index (I_geo). These indices facilitated a comprehensive assessment of pollutant intensity compared against the NESREA and WHO regulatory guidelines.

Pollution Load Index (PLI) and Contamination Factor (CF)

The PLI offered an overall composite measure of pollution burden at the sampling stations. Dividing the measured concentration of a particular contaminant in the sample environment by its equivalent natural background or baseline value, the CF is used to assess the level of pollution. This index aids in quantifying the level of contamination as well as the risk of individual pollutants for the environment30.

$${\text{CF} = {\text{C}}_{\text{Water Pollution}}}/{\text{C}}_{\text{Background}}$$
(1)

where, CF is the extent to which the water is polluted. CWater Pollution is the total pollution concentration and CBackground value represents the average background value of the element in water. The contamination levels are generally divided into four major classes31,32,33 as: very high contamination (CF ≥ 6), high contamination (3 ≤ CF ≤ 6), moderate contamination (1 ≤ CF ≤ 3), and low contamination (CF < 1). While assessing the long-term accumulation of heavy metals in soils and determining potential remediation sites, CF values are especially helpful. Pollution Load Index (PLI) provides an overall estimate of the extent of contamination in soil or water. The index provides more comprehensive view of environmental quality and is especially handy when comparing pollution levels.

$${\text{PLI}} = ({\text{CF1}}~\times~{\text{CF2}}~\times~{\text{CF3}}~\times~{\dots}.~\times~{\text{CF}}_{\text{n}})1/{\text{n}}$$
(2)
where, n is the types of pollutants present in the sample, CF1 and CF2 are the contamination factor of the sample 1 and 2 respectively Geo-accumulation Index

Geo-Accumulation Index (I_geo) is a numerical index used to assess the level of anthropogenic pollution in aquatic ecosystems, particularly concerning heavy metal contamination in sediments or water. Developed by34 Geo-Accumulation Index (I_geo) was utilized to quantify the extent of man-induced pollution. The formula below is used to calculate it.

$$\:{\text{I}}_{\text{geo}}=\:{Log}_{2}\:\left(\frac{{C}_{n}}{1.5Bn}\right)$$
(3)

Where: Cn represents the measured concentration of the contaminant, and Bn refers to the local geochemical background level of that element, as established by35. To account for natural variability in background values, a correction factor of 1.5 was incorporated into the calculation.

Health Risk Assessment

The Health Risk Assessment is a numerical index that can be employed to measure the potential ecological hazard of contaminants in environmental media like water, soil, or sediment. The EHI is a conservative ratio that relates the measured concentration of a pollutant to its accepted threshold or guideline value and assists in establishing whether the contaminant is a hazard to aquatic ecosystems or biota. To analyze the potential environmental risk from these pollutants, the Environmental Hazard Index (EHI) was calculated as:

$$\:EHI=\:\sum\:\left(\:\frac{{C}_{i}}{{S}_{I}}\right)$$
(4)

Where:

  • \(\:{C}_{i}\)= Measured Concentration of a Parameter. \(\:{S}_{i}\) = Standard Permissible Limit of the Parameter obtained from NESREA or WHO guidelines.

An EHI value greater than 1 indicates a potential risk to the ecosystem (Fig. 3). The parameters used in the current investigation, namely sulphate (S), chromium (Cr), BOD, and COD, presented values ranging 100 to 200 times beyond the fixed limits of safety, reflecting severe contaminations. Likewise, biological contaminants, i.e., eggs of helminths (Ascaris lumbricoides and Trichuris trichiura), also reported EHI values much higher than acceptable limits, notably at downstream areas (sites E, F, and G). The results reflect serious deficiencies in biological treatment and effluent holding systems, chemical toxicity, as well as microbiological pollution. The high EHI values reflect the serious environmental damage inflicted on aquatic environments and water quality by untreated industrial effluents.

The Health Risk Index (HRI) was used to evaluate possible health effects, particularly chronic risks to adults through ingestion exposure. The following formula is used to determine this index:

$$\:HRI=\:\frac{DIM}{RfD}$$
(5)
$${\text{CDI}} = {\text{C}}~\times~{\text{IR}}~\times~{\text{EF}}~\times~{\text{ED}}/{\text{BW}}~\times~{\text{AT}}$$
(6)

Where,

  • CDI = Chronic Daily Intake (mg/kg-day)

  • C = Contaminant Concentration (mg/L)

  • IR = Ingestion Rate (L/day)

  • EF = Exposure Frequency (days/year)

  • ED = Exposure Duration (Years)

  • BW = Body Weight (kg)

  • AT = Average Time (days)

  • RfD = Reference Dose for the contaminant (mg/kg-day), as recommended by USEPA or WHO.

  • Futher, RfD was calculated by using below formula

  • RfD = NOAEL or LOAEL or BMDL/UF * MF

where,

  • NOAEL = No Observed Adverse Effect Level (highest dose with no observe adverse effects in humans)

  • LOAEL = Lowest Observed Adverse Effect Level (lowestet dose at which effects are obseve, used when NOAEL is not available)

  • BMDL = Benchmark Dose Lower Confidence Limit (statistically derived safe dose)

  • UF = Uncertainty Factor(s)

  • MF = MOdifying Factor

The Pollution Load Index (PLI) serves as an important mechanism for measuring the total environmental impact of multiple pollutants relative to pre-established thresholds. In this case, PLI was used to measure the relationship between inputs from open defecation, including microbial contaminants and nutrients, into a single value representative of overall stream health. It can help to identify pollution hotspots and seasonal patterns of pollution, allow communication with stakeholders, and inform environmental policy. PLI has been applied broadly in similar research efforts globally36,37,38 and offers an evidence-based mechanism for determining public health interventions and water management issues.

Principal Component Analysis

One of the widely used multivariate statistical techniques for data dimension reduction without sacrificing the most significant variations of a data set is Principal Component Analysis (PCA). PCA is a helpful tool to explain complex data in the field of environmental pollution. To identify the significant causes of pollution, PCA was applied in this study. PCA facilitates discrimination between tannery effluent pollution and natural water quality variation by projecting large sets of collinear variables into a small number of independent principal components (PCs). Research by39 of Bangladesh and40 of Tunisia, utilized PCA to distinguish chemical and organic pollutants in tannery wastewater and have demonstrated that this methodology is effective. The equations used in PCA is as follows:

$$\:{Z}_{ij}=\frac{{X}_{ij}-{\mu\:}_{j}}{{\delta\:}_{j}}$$
(7)

where,

\(\:{Z}_{ij}\) = Standardized value of parameter j in sample i

\(\:{X}_{ij}\)= Original data value

\(\:{\mu\:}_{j}\)= Mean of parameter j

\(\:{\delta\:}_{j}\)= Standard deviation of j

Covariance or Correlation Matrix

$$R = \frac{{Z^{T} \times Z}}{{n - 1}}$$
(8)

where,

R = Correction matrix

\(\:{Z}^{T}\)= Transpose of standardized data

 n = Number of samples

Eigenvalue & Eigenvector Formula (For PCA Loadings)

$$\left| {R - ~\lambda I} \right| = 0$$
(9)

where,

\(\:{\Lambda\:}\)= Eigenvalue (Variance explained by each principal component)

I = Identify matrix R = h

Principal Components (linear combination)

$${\text{PC}}_{{\text{1}}} {\text{ = ~a}}_{{{\text{11}}}} {\text{Z}}_{{\text{1}}} {\text{ + ~Z}}_{{\text{2}}} {\text{ + ~a}}_{{{\text{13}}}} {\text{Z}}_{{\text{3}}} {\text{ + ~}}....{\text{ + a1pZ}}_{{\text{p}}}$$
(10)

where,

aip = Loading of parameters p on component \({PC}_{i}\)

Variance Ratio : Variance Ratio was applied, and was calculated to determine whether there were significant difference in pollutant concentration across the sites. This helped to identify which pollutants contribute most to the observed variation.  

$$Variance{\text{ }}Explained{\text{ }}byPCi = \frac{{\lambda i}}{{\varepsilon x}}$$
(11)
$$Variance{\text{ }}Explained{\text{ }}byPCi = {{\lambda i}}/{{\sum^{\text{p}}}}_{\text{j = i}} {{\lambda i}}$$
(12)

where,

λi = eigenvalue of the ith principal components

Σpj =1 λj = sum of all eigenvalue

p = total number of original variables

Quality Assurance (QA)

To provide analytical consistency and data integrity, this research strictly adhered to QA procedures according to Good Laboratory Practice (GLP) and APHA and WHO recommendations. Analytical-grade chemicals and calibrated equipments were utilized throughout the study. Reagent blanks, duplicate samples (≥ 10%), and calibration against certified standards were utilized in monitoring contamination, precision, and instrument accuracy. Field parameters (temperature, EC and pH) were determined in the field, whereas for the measurement of other parameters, samples were taken from the field, stored at temperature around 4 ± 2 °C and analyzed within 24-48 h. Repetition analyses revealed insignificant variability, with Relative Standard Deviation (RSD) ranging from 1.2 to 4.7% for major parameters like BOD5, COD, and heavy metals. Reagent blanks validated insignificant background contamination, corroborating the integrity of the analytical findings.

Results and Discussion

Analysis of Tannery Effluent from Naraguta, Jos

Physical Characteristics of Tannery Effluent

The physical parameters evaluation of the effluent released by the Naraguta tannery in Jos, Nigeria, revealed extreme departures from the standards established by the NESREA (Table 1), as well as from values reported in analogous international research8, 10. The color concentration of the effluent ranged from 210 to 370 Pt-Co units, significantly higher than the NESREA standard of 40 Pt-Co units. The increased concentration level is traceable to the makeup of organic dyes, chromium-containing substances, and other chemical substances commonly used in the tanning process. Similar results were obtained for tannery effluent studies in India and Pakistan, both in terms of color content in the range 250 to 400 Pt-Co units 41,42 respectively. The result is a testimonial to the global problem of color pollution caused by tannery activities worldwide.

Table 1 Physical analysis of tannery effluent from naraguta, Jos
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The analysis indicated that Naraguta, Jos, tannery effluents had electrical conductivity (EC) values of between 1,220 and 2,200 µS/cm, surpassing NESREA-recommended values of 400–1,000 µS/cm. This implies a high concentration of dissolved ions from tanning agents. The total dissolved solids (TDS) were also vastly inconsistent, with some concentrations above the NESREA limit of 2,000 mg/L (refer Table 1). These high concentrations imply inefficiency in effluent treatment and dilution effects. The same trends have been reported from the studies done in the identified in other nations like Bangladesh, Ethiopia, and Pakistan, indicating that the pollution profile aligns with the characteristics of global tannery waste43,44. Total suspended solids (TSS) in the samples ranged within NESREA’s acceptable limit (1.35–2.30 mg/L), but total solids (TS), which is the collective of both suspended and dissolved phases, ranged between 5.00 and 9.10 mg/L. It is a hazard to aquatic biota in an environment that contains high TS levels, meaning that there is cumulative pollutant loading. The study emphasizes that, although TSS values are low, total pollution load is high due to high TDS and TS levels. This mixture of pollutants can ruin the physical and chemical balance of the receiving water bodies. Turbidity levels were very high, ranging from 61 to 155 NTU, which is way above the recommended NESREA standard of 5–10 NTU. The high turbidity indicates a lot of organic waste, chemical by-products, and suspended particles, consistent with previous studies in China and other regions of Africa2,45. Generally, the physical characteristics of the effluent show extreme pollution, signifying poor wastewater treatment in the tannery sector. The research emphasizes the necessity for efficient treatment technologies and vigorous enforcement of environmental policies to protect ecosystems and public health.

Chemical Parameters of the Tannery Effluent

Major environmental problems in line with global trends in tannery wastewater pollution are indicated by the chemical composition of Naraguta Tannery effluent, including parameters such as pH, BOD, COD, total nitrogen (TN), nitrogen (N), sulphur (S), chloride (Cl⁻), total iron (Fe), and total chromium (Cr) (Table 2). All samples ranged between 7.0 and 7.6, reflecting slightly alkaline to neutral conditions. These values are similar to effluent pH levels as reported in other comparable research studies, for example29, in India and45 in Sudan, where pH levels usually ranged from 7.0 to 8.5. The tannery waste from Naraguta has elevated pollutant concentrations such as BOD (210–300 mg/L), COD (570–720 mg/L), and total nitrogen (38–55 mg/L), which all exceed the NESREA thresholds, indicating a large amount of biodegradable and non-biodegradable organic matter. These values are consistent with similar studies in Ethiopia, Pakistan, Bangladesh, and India, where practices for removing waste produced elevated pollutant concentrations31, 41, 46, 47.

Table 2 Chemical Analysis of Naraguta Tannery Effluent
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The application of salt-based preserving methods during hide processing is likely the reason for the range of chloride (Cl⁻) concentrations in the effluent, which varied from 165 to 199 mg/L. This compares to levels observed in Egyptian tanneries48 which were between 150 and 300 mg/L. Apart from contributing to the salinization of soils in surrounding environments, elevated chloride levels are likely to be harmful to aquatic life. Another salient observation of the effluent samples was the occurrence of heavy metals. The level of total iron (Fe) and total chromium (Cr) ranged from 2.1 to 2.8 mg/L and 2.8 to 3.4 mg/L, respectively. There is an acute environmental threat since the concentration of chromium is significantly higher than the permissible 0.5 mg/L NESREA limit. These findings are in agreement with similar studies in Turkey49,50 and India30 whereby the widespread practice of chrome-based tanning procedures have been responsible for high chromium concentrations. Other environmental issues arise from the variable total sulfur (S) concentration, ranging from 75 to 90 mg/L. These levels are consistent with findings by51 in Iran, unpleasant smells and the production of dangerous sulphide gases have been connected to high Sulphur content in tannery effluents. The complex chemical burden linked to untreated tannery wastewater is highlighted by the presence of sulfur in conjunction with high concentrations of heavy metals and chlorides.

Biological Parameters of Tannery Effluent

Severe microbial and parasitic pollution was established when biological parameters of tannery effluent samples collected from Naraguta (Sites A to G) were analyzed (Table 3, & Fig. 3). The potential of the effluent as a significant public health risk is emphasized by the presence of helminth eggs, Escherichia coli (E. coli), and some parasitic species, including Ascaris lumbricoides, hookworm, Trichuris trichiura, and Strongyloides stercoralis. E. coli levels ranged from 10 to 23 MPN/100 mL, representing contamination levels commonly associated with inadequate effluent treatment. These findings are in agreement with studies conducted in other low- and middle-income countries. For instance, in Kano, Nigeria, tannery wastewater had levels of E. coli that varied between 12 and 26 MPN/100 mL, reported by52 which they attributed to unhygienic conditions at tannery factories. Microbial contamination of inadequately treated tannery effluents was also verified globally by53 as the levels of E. coli in the effluent from tanneries in Dhaka, Bangladesh, ranged from 15 to 30 MPN/100 mL.

Table 3 Biological Parameters Analysis of tannery effluent from Naraguta
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The finding of the Helminth eggs in the range of 12 to 23 eggs/L agrees with studies conducted in India and Pakistan, where tannery effluents are often discharged in open drainage channels without any treatment. Helminth egg levels in Punjab (India), Pakistani tannery wastewater, for example, were found to range from 5 to 15 eggs/L54. Detection of Ascaris Lumbricoides (5-12 eggs/L), Hook Wworm (2-6 eggs/L), Trichuris Trichiura (2-4 eggs/L), and Strongyloides Stercoralis (1-4 eggs/L) in Naraguta effluent samples were close to the finding of 55, who found similar levels of parasitic pollution in Ethiopian tannery wastewaters. A prominent reason we observe high levels of biological pollutants, including Helminth eggs and E. coli in tannery wastewaters in developing countries like Nigeria is that these countries may not utilize even basic wastewater treatment technologies. The tannery wastewaters in Naraguta contain pathogens that exceed the strict “zero tolerance limit” established by NESREA under Nigeria’s National Environmental Sanitation Policy. The discovery of contaminants implies that the tannery lacks a biological treatment phase. Individuals consuming water for irrigation, washing, and domestic purposes are at high risk of contracting parasitic infections and gastrointestinal diseases. Our findings are align with the observations of the World Health Organization56 that untreated tannery effluents contribute to global trends of waterborne diseases in low-income and low-resource settings.

Biological Parameters Contamination Index

The Biological Contamination Index (BCI) is used to measure microbial pollution in environmental media such as wastewater, soil, or water. The important parameters are Escherichia coli (E. coli), Total Coliform Count (TCC), and Fecal Coliform Count (FCC). In Nigerian effluents from tanneries these parameters were far higher than NESREA standards (TCC: 1.4 MPN/100 mL compared to 0; FCC: 9.2 MPN/100 mL compared to 0; E. coli: 7.3 MPN/100 mL compared to 0) (Table 3, & Fig. 4). The Pollution Load Index (PLI) value for FCC and E. coli was infinite, reflecting high pathogen contamination. The same was reported for other developing countries such as India and Egypt, where poor wastewater treatment resulted in elevated microbial counts41,57. Developed nations such as Spain and Italy had undetectable levels of coliform due to proper regulations and innovative treatment technologies58,59. E. coli and FCC are severe public health hazards, underscoring the imperative need for effective and sustainable wastewater management and upgraded treatment plants.

Physical Parameters Contamination Index

Physical pollution indicators of tannery effluents are color, electrical conductivity (EC), total dissolved solids (TDS), total suspended solids (TSS), and turbidity. In tannery under study, color values were within or marginally above NESREA standards (PI: 0.93–1.04), pointing to controlled discharges of dyes27. EC (PI: 1.04–1.21) indicated moderate ionic contamination, whereas TDS (PI: 0.00175–0.00198) and TSS (PI: 0.0417–0.0467) exhibited minimal organic and inorganic contamination, pointing to efficient treatment or minimized salt consumption (Table 4; Fig. 2). Nevertheless, turbidity was high (PI: 14.40–15.20), reflecting low water clarity from colloidal matter60. Comparisons with Ghana, India, and Kenya studies reflected more severe pollution levels13,61,62 reflecting the importance of improved filtration and sedimentation practices. Overall, the tannery exhibited effective color, TDS, and TSS management, but needed to be improved for EC and turbidity.

Fig. 2
Fig. 2
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Pollution Index Physical Parameters

Chemical Parameters Contamination Index

Chemical pollution indicators presented high organic and heavy metal pollution. Biological Oxygen Demand (BOD: 4.20-5.60 mg/L) and Chemical Oxygen Demand (COD: 2.28-2.88) were above limits, which was an index of high organic pollution. Nutrient parameters such as Total Nitrogen (TN: PI 1.2-1.8) presented eutrophication hazards. Heavy metals, including iron (Fe: 2.1-2.8 mg/L) and chromium (Cr: 5.6-6.8 mg/L), were way above NESREA limits (Fe: 0.3 mg/L; Cr: 0.05 mg/L), showing extreme environmental threats. In contrast, sodium (Na⁺) and zinc (Zn²⁺) contents were within tolerable limits (Table 2; Fig. 3). Results from various international researchare calling for improved treatment technologies as well as effective regulations to prevent pollution from tannery effluents.

Table 4 Naraguta effluent pollution index of chemical parameters
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Environmental Hazard and Health Risk Indices

The analysis revealed that physical parameters such as colour and turbidity exhibited very high \(\:{I}_{geo}\) values (≥ 3), categorizing them as “strongly to extremely polluted". This suggests a substantial input of dye residues, suspended organic particles, and colloidal materials originating from tannery operations (Fig. 3). In contrast, most chemical parameters, including TDS, TS, chloride, and total nitrogen, were found within the “unpolluted” classification (Fig. 4). However, chromium (Cr) was a notable exception, with I_geo value reaching as high as 5.059 in sample G, indicating a “very strongly polluted” condition (Fig. 3).

Fig. 3
Fig. 3
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Biplot of physical, chemical, and biological geo accumulation.

Among various biological parameters analyzed, Helminth eggs had the highest value of I_geo at 3.0, followed by Ascaris lumbricoides and Hook Worm, which showed signs of moderate levels of anthropogenic impacts (Figs. 2 and 3). This indicates a high concentration of pollutants, primarily heavy metals and pathogenic organisms in the aquatic environment.

Human Health Risk from Iron and Chromium Exposure in Naraguta Effluent

The calculated Chronic Daily Intake (CDI) of iron (Fe) and chromium (Cr) at seven stations (A–G) (Table 5) shows definitive spatial trends in exposure. For adult reference, Fe-CDI ranged from 0.0600 to 0.0800 mg/kg/day, while Cr-CDI varied between 0.0800 and 0.0971 mg/kg/day. In kids values were much greater because of their lighter body weight and physiological sensitivity with Fe-CDI varying between 0.1400 and 0.1867 mg/kg/day, and Cr-CDI from 0.1867 to 0.2267 mg/kg/day. These values were above concern thresholds especially for Cr. These values agree with or are greater than those reported in industrially affected areas. For example46, recorded levels of 0.045–0.082 mg/kg/day of Cr-CDI in a leather tannery area in Bangladesh, which shows that the level of Cr exposure in Naraguta is higher compared to most of South Asia. Parallel to the present findings63, noted Fe-CDI values of 0.05–0.07 mg/kg/day in the vicinity of textile dye effluent points in Pakistan, which are marginally lower than the values in most stations in this study, supporting the high iron burden in the study area.

Table 5 Chronic Daily Intake (CDI) for Fe and Cr in Naraguta for adults and children
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The high Cr-CDI values, particularly at stations E, F, and G are highly alarming considering USEPA’s reference dose (RfD) for Cr (VI) which was merely below 0.003 mg/kg/day. The measured levels of CDI in Naraguta were 26 to 32 times higher than the safe limit for an adult and 60 times that for a child. These levels may cause long-term damage, such as carcinogen and mutagen effects, particularly for hexavalent chromium (Cr⁶⁺), a severe toxic compound of the element. Comparing the results of this study with other studies like 64, maximum Cr HRI value of 12.5 in children who were exposed to tannery effluent to this study registers higher indices (up to 75.56), highlighting a more severe risk situation. Further, chronic exposure to Fe above dietary levels, though less harmful than Cr. The higher exposure of Fe may linked to oxidative stress, hemochromatosis, and gastrointestinal upset, particularly in vulnerable populations23.

Toxicological Thresholds and Risk Significance of Key Parameters

Reference Dose (RfD) is an important guideline in environmental health. The highest daily intake of any substance should not cause harm to any life. For nitrate (NO₃⁻) RfD of 1.6 mg/kg/day has been set by WHO and USEPA to avoid the development of conditions such as methemoglobinemia, especially in infants. High nitrate concentrations in polluted wastewater regions, particularly those with protein-rich tannery effluent can be extremely hazardous to communities that depend on untreated surface water, as reported by65. Likewise, sulfate (SO₄²⁻), with RfD of 1.5 mg/kg/day, although not acutely toxic, may produce laxative effects and electrolyte disturbance, particularly among children. Health ailments related to exposure to sulfates in tannery-contaminated regions have been documented in India by66. Chloride (Cl⁻), while necessary as an electrolyte, does not have an official USEPA RfD but does have a literature-based estimate of 0.1 mg/kg/day to maintain palatability and infrastructure.

Table 6 Reference Dose of contaminants
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Although not extremely toxic, increased chloride has been associated with hypertension and degraded water quality, especially when in combination with other sodium salts. Research such as67 validates the impairment of drinking water quality because of excessive chloride levels within industrial areas. Few research (like68)  findings support the necessity of context-dependent exposure assessments within effluent-affected zones. For heavy metals, there is a provisional RfD for iron (Fe) of 0.7 mg/kg/day. While physiologically required, a chronic excess of iron may lead to oxidative stress and hemochromatosis, especially in susceptible populations like children68. Excessive Fe consumption from tannery effluent in Nigeria was linked to tissue injury and micronutrient malabsorption69. Chromium (Cr), especially in its hexavalent state (Cr⁶⁺), is a greater risk with RfD of only 0.003 mg/kg/day because it has carcinogenic and mutagenic effects69. Exposure measurements from Naraguta (Table 6) concur with Bangladesh findings done by 69 and70. According to these studies, Cr exposures were 50 times higher than RfD and correlated to respiratory, dermatological, and cancer-related health effects, particularly among children. Such comparisons demonstrate the relevance of RfD-based health risk assessment in research on industrial wastewater.

Principal Component Analysis

The Principal Component Analysis (PCA) of Naraguta tannery effluent indicates that the first principal component (PC1) accounts for a tremendous 89.82% of the variance and implies that it captures the overall burden of pollution (Fig. 4). PC1 has strong correlations with different organic and inorganic contaminants like BOD, COD, TN, ammonia nitrogen, sulphate, chloride, iron, chromium, and zinc. This indicates that the increase in these pollutants increases the PC1 score, making PC1 a broad marker of pollution intensity. PC2, which explains 7.41% of the variance, separates sources of pollution and emphasizing differences between organic waste and inorganic pollutants such as pH and zinc concentrations.

Fig. 4
Fig. 4
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Biplot for PCA

PC3, accounting for 1.78% of the variance, concerns metal contamination, specifically zinc. It has a reverse relationship between zinc and factors such as pH and iron. This component indicates localized metal contamination patterns that differ from general organic pollutant effects. While PC4 and PC5 explain small variance (0.66% and 0.29%, respectively) and offer information on site-specific pollution patterns, particularly chromium and iron variations. Physical parameter analysis indicates that PC1 explains 92.87% of the variance, with strong negative correlations with all physical pollutants measured, such as color, EC, TDS, TSS, TS, turbidity, and pH. This suggested that PC1 can be used as a comprehensive index of physical pollution. PC2 and PC3 (explaining 3.70% and 2.44% variance, respectively) provide additional discrimination, especially between dissolved and suspended solid matter at different sites. The low variance explained by PC4 and PC5 indicates that they are representative of more subtle, location-specific pollution characteristics. These PCA results are consistent with evidence-based policies for targeted pollution control and regulation.

Conclusion

This research offers a holistic assessment of the pollution and health hazards presented by untreated tannery effluent in Naraguta, Nigeria. Results indicated critically elevated levels of major pollutants such as chromium, sulphur, biochemical oxygen demand (BOD), and helminth eggs well above both national and international water quality standards, especially at downstream points (Stations E, F, and G). Using the Environmental Hazard Index (EHI), Geo-Accumulation Index (\(\:{I}_{geo}\)), Health Risk Index (HRI), and Principal Component Analysis (PCA), contamination was traced in the research to various sources, such as improper waste management practices and lack of regulation of industrial effluents. These findings underscore the synergistic risk of chemical and biological contaminants to human health, the integrity of the ecosystem, and the realization of sustainable development goals. In addition to academic relevance, the research provides pragmatic implications for environmental management and policy. It highlights the importance of having real-time monitoring systems for pollution at industrial point sources to help maintain regulatory standards and identify potential environmental threats at an early stage. Enhancing the technical capability of local laboratories and environmental authorities is essential for effective enforcement and evidence-based decision-making. The study recommends the implementation of low-cost, environmentally benign treatment technologies like bioremediation with microbial consortia, constructed wetlands, and biochar-based adsorption systems, which are ideal for resource-constrained environments. Furthermore, the reuse of treated wastewater for irrigation and valuable element recovery, such as chromium, is also circular economy-compatible, providing both environmental and economic advantages. The research also encourages the adoption of zero-liquid discharge (ZLD) technologies to reduce water loss and pollution. Also, encouraging partnerships between academia, the regulatory environment, and industry can enable knowledge transfer, encourage cleaner production technologies, and hasten the shift to sustainable wastewater management in the tannery industry. Generally, the results highlight the importance of coordinated regulatory, technical, and economic measures to protect water resources and public health in developing regions.