https://orcid.org/0000-0002-8527-8284
Figures
Abstract
This study evaluated the impact of palm oil mill effluents (POME) on the water quality of the Agbogbo stream by analysing physicochemical parameters and calculating the Water Quality Index (WQI) across five sampling stations (A–E), including upstream, discharge, and downstream points, over a twenty-month period. Parameters such as temperature, pH, turbidity, total dissolved solids (TDS), total suspended solids (TSS), nitrate, sulphate, and conductivity were measured using standard methods. Results showed that the WQI values ranged from 60.1 to 65.5, with the lowest observed at the effluent discharge point, and an overall average WQI of 64.04, indicating poor water quality unsuitable for potable use. The consistent degradation in water quality across all sites highlights the adverse impact of untreated POME on aquatic ecosystems and community health. Practical implications include the urgent need for effective wastewater treatment prior to discharge, stricter enforcement of environmental regulations for palm oil mills, and continuous water quality monitoring. Future efforts should involve treating of the palm oil mill effluents before discharging it into the nearby waterbody, stakeholder engagement and sustainable practices in palm oil processing to safeguard water resources.
Citation: Ajadi FA, Adewole HA, Obayemi OE, Odetola OO, Olaleye VF, Ayodeji O (2025) Assessment of water quality index in an afro-tropical stream impacted by palm oil mill effluents. PLOS Water 4(10): e0000441. https://doi.org/10.1371/journal.pwat.0000441
Editor: Gaurav Saxena, Mandsaur University, INDIA
Received: November 25, 2024; Accepted: September 12, 2025; Published: October 7, 2025
Copyright: © 2025 Ajadi et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
Data Availability: All the data generated during this study are included in this published article (and its Supporting information files).
Funding: The authors received no specific funding for this work.
Competing interests: The authors have declared that no competing interests exist.
Abbrevations: WHO, World Health Organization; NESREA, National Environmental Standards and Regulations Enforcement Agency; mg/L, Milligrams per litre; °C, Degrees Celsius; NTU, Nephelometric Turbidity Unit; Pt-Co, Platinum-Cobalt scale; µs/cm, Microsiemens per centimetre; CaCO3 mg/L, Milligrams per liter of calcium carbonate
Introduction
Water is a vital natural resource essential for life, yet it is increasingly threatened by pollution from human activities and natural events [1,2]. Industrialization, urbanization, and poor waste management contribute significantly to environmental pollution, affecting both human and animal health [3,4]. The discharge of untreated wastewater into rivers leads to water quality deterioration and impacts aquatic ecosystems [5,6]. Many communities rely on surface water sources for domestic, agricultural, and industrial use, even though these sources often receive wastewater from agro-industrial processes [7]. Palm oil mill effluent (POME), a by-product of palm oil production, is rich in organic matter, suspended solids, and oxygen-demanding substances, posing serious environmental risks when improperly treated [8,9]. While traditional treatment methods like ponding remain common, they are inefficient and contribute to greenhouse gas emissions [10]. The effluent, characterized by its brown, viscous nature and high oxygen-draining capacity, can severely degrade nearby water bodies if not properly managed [11]. Assessing water quality involves evaluating its physical, chemical, and biological characteristics, which reflect both natural conditions and human impacts [12]. The Water Quality Index (WQI) simplifies this assessment by integrating multiple parameters into a single value that indicates the suitability of water for various uses [13,14]. Poor WQI values highlight threats to both aquatic life and human health, especially when values exceed safe limits [15]. WQI can also be used to track changes in water quality due to anthropogenic influences, such as traffic or pandemics, as seen in studies from Egypt [16]. This study is unique because it offers a long-term, site-specific assessment of palm oil mill effluent (POME) impact on stream water quality using both physicochemical parameters and the Water Quality Index (WQI), a composite tool that simplifies complex water data into a single value for practical interpretation. Unlike many short-term or generalized assessments, this study spans a twenty-month period and captures spatial variation across upstream, discharge, and downstream locations, offering a clear picture of POME’s localized and cumulative effects. The WQI provides a holistic impression of the stream’s integrity by integrating multiple key parameters—such as turbidity, TDS, TSS, nitrate, and conductivity—into a single score that reflects overall irrigation suitability. In this study, thirteen (13) parameters—including BOD, DO, temperature, pH, phosphate, nitrate, turbidity, conductivity, and total solids—were used to compute the WQI, with assigned weights reflecting their relative impact on water quality [17]. The study aim to determine whether palm oil mill effluent affects the water quality of an afrotropical stream and its related index. The aim of this study was to:
- a) Characterise the palm oil mill effluent of the Agbogbo community;
- b) ascertain the physical and chemical properties of the Agbogbo stream at the point source and upstream and downstream of the effluent discharge; and
- c) determine the water quality index via multivariate analysis
Methodology
Study area
The research was conducted in Agbogbo Village, Obafemi Awolowo University, Ile-Ife, Nigeria. The village is a rural settlement located at Latitude 7° 32’N North of the equator and Longitude 4° 31’ East of the equator within the estate of Obafemi Awolowo University, Ile-Ife (Fig 1).
The study area is a typical rural setting in which farming is the primary activity. Subsistence farming is the dominant farming system in the area, with a few cash crops, such as cocoa, kola nut, oil palm, and plantain, growing. Bush burning (an ancient farming method) is still common in the area. The palm oil and palm kernel business is the predominant business in this area [18]. The stream, which supplies potable water to the entire village of Agbogbo, also supplies raw water for agricultural processes in the area. The stream generates a perennial source of water for the palm oil processing industry, which is located randomly around Agbogbo village. The study area has two distinct climates, with a pronounced that there is a wet season from April to October and a dry season from November to March.
Selection and description of the sampling stations
Agbogbo village and the stream were located after an initial reconnaissance and survey. Five (5) sampling stations along the stream were subsequently established for the study via a global positioning system (GPS). The station samples were identified as A, B, C, D, and E stations. Station A is located at the upstream portion of the stream, which is one (1) kilometer away from where palm oil is being processed and is selected to serve as the control site. Station B, which was selected, was 500 m long before the palm oil mill effluent was discharged straight into the stream. The wastewater from the palm oil factory was released into the stream at Station C. The distance between Station D and the effluent discharge point was 500 meters. At this point, the stream is also being used for other domestic activities apart from palm oil processing. The distance between Station E and the discharge site was one kilometre of palm oil effluent where there is little or no domestic or farming activity (Table 1).
Palm oil mill effluent sample
Samples of raw palm oil mill effluent were obtained from the palm oil mill processing unit onsite. Raw palm oil mill effluent samples were effluent processing unit. The palm oil mill effluent samples were stored in bottles and delivered in an ice box to the lab. The physicochemical parameters of the samples were determined via techniques established by the Association for American Public Health [19]. Conductivity, pH, and temperature were evaluated as physicochemical properties of palm oil mill effluent, whereas organic matter (OM), The laboratory examined the levels of dissolved oxygen (DO), biological oxygen demand (BOD), and chemical oxygen demand (COD).
Water sample collection
Subsurface water samples were obtained from each sampling point once every two months for twenty months. A mercury-in-glass thermometer was used to measure the water’s temperature on-site, and the pH was determined via pH meters (PCE-PHD I pH meter). The conductivity was determined in the laboratory via a Jenway 4071 conductivity meter. The turbidometric method was used to determine the turbidity via a colorimeter (Jenway 6051). DO and BOD were determined via Winkler’s methods [19]. The chemical oxygen demand, total dissolved solids, total suspended solids, total acidity, total alkalinity, and total organic carbon, Cl-, SO42-, NO3-, and TSS levels in water samples was determined gravimetrically. Total acidity was determined by titration of water sample against standard sodium carbonate (0.02N) Na2CO3 titrant solution with phenolphthalein used as indicator. The level of Cl- was determined by titrating the 100 ml of water sample against 0.014N standardized mercury nitrate (Hg(NO3)2) using 5 drops of 10% diphenylcarbozone and 0.2 M nitric acid (HNO3) as indicator solution, by Mohr- titration method. Turbidometric method was used to determine the sulphate concentration while NO3 - was determined using brucine method. Wet- oxidation digestion method was used for determination of TOC and OM. The contents were identified via standard protocols [19]. These are the list of specific methods used namely; Temperature – Mercury-in-glass thermometer (on-site measurement), pH – pH meter (PCE-PHD I pH meter), Electrical Conductivity – Jenway 4071 conductivity meter, Turbidity – Turbidometric method using a colorimeter (Jenway 6051), Dissolved Oxygen (DO) – Winkler’s method [19], Biochemical Oxygen Demand (BOD) – Winkler’s method after 5-day incubation [19], Chemical Oxygen Demand (COD) – Gravimetric method [19]. Others are Total Dissolved Solids (TDS) – Gravimetric method, Total Suspended Solids (TSS) – Gravimetric method, Total Acidity – Titration against 0.02N sodium carbonate (Na₂CO₃) with phenolphthalein indicator, Total Alkalinity – Gravimetric method [19], Chloride (Cl⁻) – Mohr titration method using 0.014N standardized mercury nitrate [Hg(NO₃)₂] with diphenylcarbazone–HNO₃ indicator, Sulphate (SO₄²⁻) – Turbidometric method, Nitrate (NO₃⁻) – Brucine method, Total Organic Carbon (TOC) – Wet oxidation digestion method [19] andOrganic Matter (OM) – Wet oxidation digestion method [19].
Water quality index
The calculation of the index of water quality in this study is an attempt to analyse the quality of water from a stream impacted by palm oil effluent. Thirteen (13) water quality parameters analysed for this study were examined in terms of their appropriateness for human consumption. The selected parameters were pH, dissolved oxygen, conductivity, total hardness, alkalinity, biological oxygen required, nitrate, chloride, total suspended solids, sulphate and total dissolved solids. The importance of various parameters selected for water quality index calculation depends on the intended use of water.
The weighted arithmetic index approach was used to determine the water quality index (WQI) [20]. The following formula was then used to get each parameter’s quality rating scale (qn):
‘qn’ = quality rating (nth parameter which reflects the relative value of the parameter in polluted water with respect to the standard permissible value.
Vn = Observed value of the nth parameter at a water sample station
Sn =Standard permissible value (nth parameter)
Vi = ideal value of the nth parameter in pure water
For all other parameters, Vi = 0, except for the parameters pH, dissolved oxygen and biological oxygen demand, for which the Vi values are 7.0 and 14.6 mg/L, respectively [21]. The unit weights of several water quality parameters showed inversely proportional to the recommended standards for those parameters.
where Wn = the unit weight for the nth parameter.
Sn = Standard permissible value for the nth parameter
K = proportionality constant
The following formula was used to determine the total water quality index equation.
The drinking water quality index was classified as follows: 0–25 (excellent), 26–50 (good), 51–75 (poor), 76–100 (very poor), and >100 (not fit for drinking) [22]. Using ArcGIS 10.8, we created spatial maps that represented the water quality indexes’ dispersion. The GIS map url was https://services.arcgisonline.com/ArcGIS/rest/services/World_Imagery/MapServer.
Statistical analysis of data
The physicochemical data collected in this study were subjected to several statistical analysis, including descriptive statistics, were performed on the data gathered for this study. Analyses such as analysis of variance, principal component analysis-biplot, cluster analysis and Pearson correlation were used to determine the relationships among different water quality parameters. The level of significance in the Seasonal variation in the factors of water quality was set at p < 0.05. The software packages used for the analysis were PAST (version 4.06b) and SPSS (IBM 26.0). A PCA biplot is a graphical representation that simultaneously displays two critical elements from PCA (PC1 and PC2), serving as a versatile and insightful tool for data analysis by offering a compact way to explore multivariate relationships. Cluster analysis is an unsupervised method that groups similar objects into clusters by preparing and standardizing data, choosing a distance measure and algorithm (like hierarchical or k-means), determining the number of clusters, and validating the results to reveal natural patterns.
Formal ethical approval was not required for this study as the authors explained the study’s purpose and methods which demonstrates respect for local customs and in a Nigerian rural setting where traditional leaders govern communal resources like the stream. Thus, the village head grants the approval for the field site access.
Results
Water quality parameters and characteristics of the palm oil mill effluent of the impacted stream
The raw palm oil mill effluent collected in this study was thick, viscous, brownish, and oily with a foul odour (S1 Table). Table 2 summarizes water quality data from the Agbogbo stream across five stations: the point of discharge, 0.5 km upstream (US), 0.5 km downstream (DS), 1 km US, and 1 km DS. Water temperature increased from 24.7 ± 2.16°C at the discharge point to 26 ± 1.79°C at 1 km DS, indicating downstream heat dispersion that could stress temperature-sensitive aquatic life. Turbidity peaked at the discharge point (86.16 ± 71.92 NTU), reflecting high suspended solids from the effluent, then decreased downstream, likely due to settling or dilution.
Conductivity (730 ± 551.94 μS/cm) and TDS (571.33 ± 347.21 mg/L) peaked at the discharge point, then decreased downstream but remained high. TSS was highest at 0.5 km DS (667.5 ± 516.25 mg/L), likely from resuspension or inputs, while lowest at 1 km US (67.67 ± 24.65 mg/L). DO was highest at discharge (7.88 ± 2.46 mg/L) and lowest at 1 km DS (4.08 ± 1.63 mg/L), indicating downstream oxygen depletion. BOD ranged from 2.42 ± 1.70 to 4.3 ± 2.17 mg/L), showing moderate organic pollution. Water hardness (104.38 ± 77.39 mg/L), alkalinity (137 ± 85.24 mg/L), and acidity (32.67 ± 12.7 mg/L) were highest at the discharge point, reflecting chemical enrichment.
Supplementary 1: The physico-chemical characteristics and the ionic composition of POME collected at the point of discharge during the period of study
Chloride was highest at the discharge point (42.05 ± 26.59 mg/L) and lowest upstream (11.86 ± 8.16 mg/L), indicating pollutant dispersion. Sulphate (11.52 ± 4.13 mg/L) and nitrate (6.45 ± 3.22 mg/L) peaked at 1 km DS, suggesting downstream nutrient buildup and eutrophication risk. Phosphate (0.48 ± 0.12 mg/L), COD (38.37 ± 10.41 mg/L), organic matter (23.41 ± 15.45 mg/L), and TOC (12.77 ± 6.86 mg/L) were highest at the discharge point, reflecting heavy organic pollution. Thus, the discharge point is a pollution hotspot, while downstream areas show oxygen depletion and nutrient shifts, threatening aquatic life and ecosystem health. Comparison with WHO standards showed most parameters at the discharge point were within limits, except for EC, TDS, DO, and alkalinity. Only water temperature, acidity, chloride, sulphate, and nitrate showed significant seasonal variation (Table 3).
Multivariate analysis of the water quality parameters of the impacted stream
Pearson correlation and cluster analysis (Table 4) revealed strong spatial and parameter interrelationships across stations. Water temperature and pH were highly correlated (0.942), suggesting temperature-driven pH shifts affecting aquatic life. TSS strongly correlated with alkalinity (0.987), acidity (0.891), chloride (0.988), and nitrate (0.995), indicating co-variation with suspended pollutants. BOD showed high correlations with acidity (0.964) and sulphate (0.988), reflecting organic pollution and microbial activity. COD was strongly linked to organic matter (0.902) and TOC (0.933), highlighting a clear organic pollution signature from effluent discharge.
The cluster analysis dendrogram (Fig 2) revealed three distinct groups. The clustering of 1 km upstream and downstream suggests similar water quality due to mixing or dilution. The grouping of 0.5 km upstream and downstream reflects moderate impact near the discharge point, while the point of discharge formed a separate cluster, indicating a unique, effluent-dominated profile. This highlights the discharge point as the main pollution source, with downstream and upstream stations showing dilution or baseline conditions.
Principal Component Analysis (PCA) biplots (Figs 3,4) revealed clear seasonal variations in water quality across stations. In the rainy season, PCA 1 and 2 explained 99.1% of the variance, with water quality parameters clustering around 1 km DS, 0.5 km DS, and 1 km US—indicating similar influences from runoff or dilution. The point of discharge was strongly associated with TDS and conductivity, reflecting high effluent input, while 0.5 km US aligned with TSS, likely from upstream sediment. In the dry season, PCA 1 and 2 accounted for 99.2% of the variance, with more variance concentrated in PCA 1 due to reduced flow and pollutant concentration. Stations at 1 km US and DS showed consistent water quality, while 0.5 km DS slightly separated, possibly due to localized effects. The point of discharge showed weaker associations with TDS and conductivity, suggesting dilution or reduced effluent strength. These findings indicate that rainy season conditions promote wider pollutant dispersion, while the dry season increases localized impact near the discharge point, highlighting the need for season-specific water quality management strategies.
Water quality index of the impacted stream
The Water Quality Index (WQI), based on mathematical comparison of 13 key physicochemical parameters, was used to assess pollution across stations and seasons. WQI values ranged from 58.6 at the discharge point to 65.5 at 1 km DS, indicating improving water quality downstream due to dilution. Upstream stations (1 km and 0.5 km US) showed consistent conditions, suggesting minimal discharge impact. Seasonally, the rainy season had wider variation (52.9–65.7), reflecting stronger effluent influence and downstream recovery, while the dry season showed narrower values (63.9–66.6), indicating more stable but concentrated pollution. Although all stations rated poorly for drinking, “naturalness of impact” classified 1 km US and DS in the dry season as “fair” and in need of protection (Tables 5–7).
Geospatial maps (Figs 5–7) confirm spatial WQI trends, with the point of discharge showing consistently poor water quality that improves downstream. During the rainy season (Fig 6), WQI ranged from 52.9 at the discharge point to 65.7 at 1 km DS, highlighting midstream pollution accumulation and downstream recovery. In the dry season (Fig 7), WQI values ranged from 63.9 to 66.6, with the poorest quality near the discharge point and 0.5 km DS, while 1 km US showed fair quality, likely due to minimal rainfall dilution.
(URL: https://services.arcgisonline.com/ArcGIS/rest/services/World_Imagery/MapServer).
(URL: https://services.arcgisonline.com/ArcGIS/rest/services/World_Imagery/MapServer).
(URL: https://services.arcgisonline.com/ArcGIS/rest/services/World_Imagery/MapServer).
Fig 8 shows overall WQI distribution across the stream, ranging from 58.6 (dark green) at the discharge point to 65.5 (lemon) at 1 km DS. The poorest water quality was at the discharge point, indicating heavy pollution, while the best was downstream, likely due to natural dilution or reduced pollutant input.
Globally, the study’s WQI (58.6–65.5) is higher than Turkey’s Korucuköy (34.5–55.6) and India’s Makdhoomyari (48.9), but lower than Nigeria’s Uyo streams (80.4) and South Korea’s agricultural streams (78.9), indicating moderate pollution. Although less affected than streams contaminated by sewage and dumpsites, the Agbogbo Stream’s poor water quality still indicates significant effluent influence and highlights the need for better waste management to restore ecological and human usability.
Discussion
This study analysed raw wastewater from palm oil mills, which appeared as a dense, brown, colloidal suspension that was oily, viscous, and strongly odorous. The oil and grease levels in the palm oil mill effluent were higher than those reported by [28] and [29], but lower than the values documented by [30]. Differences in these concentrations among studies may result from variations in palm kernel species, processing techniques, and water volumes used during palm oil milling. Water contaminated by palm oil effluent has been reported to show high turbidity, altered odour, and taste [31]. Additionally, physicochemical parameters like chemical oxygen demand, dissolved oxygen, total dissolved solids, and biological oxygen demand exceeded the limits [32]. It is known that palm oil mill effluent can negatively affect aquatic ecosystems due to its high physicochemical content and nutrients [33]. Water temperature plays a crucial role in the dynamics of aquatic environments and the biology of aquatic organisms [34]. The slight temperature rise at the discharge point was likely due to the high effluent temperature during sampling [35]. Colloidal materials in the effluent probably contributed to increased turbidity. The average pH of water from the Agbogbo stream remained neutral during sampling. Since pH influences the survival of aquatic life by affecting metabolic processes [36]. The relatively high mean pH upstream of the discharge point may be caused by acidic waste inputs from catchment areas. The electrical conductivity (EC) at the discharge point was consistent with the findings by [37], while other station findings were similar with the results of [14]. The highest mean conductivity, 730 ± 551.94 µS/cm, was recorded at the wastewater discharged point, likely reflecting the nutrient-rich effluents from the palm oil processing plant. Elevated conductivity due to soluble salts in palm oil mill effluents has been noted previously [38]. Throughout the study, conductivity values at all sampling points were within limits set by [39,32].
Water with total dissolved solids (TDS) mainly consists of organic, inorganic substances, and salts [40]. The highest mean TDS (229.60 mg/L) was at wastewater discharge point, while the lowest (52.40 mg/L) was 1 km downstream. High TDS from effluent discharge can harm aquatic life and water quality [41]. All recorded total suspended solids (TSS) exceeded the WHO limit of ≤ 5 mg/L and were higher during the rainy season, likely due to palm oil mill effluents and nutrient runoff. Also, the mean alkalinity values was consistent with those reported in tropical regions [42, 43]. Across all sampling points on the Agbogbo stream, water samples showed mean alkalinity from 37.67 ± 19.03 mg/L CaCO3–137 ± 85.24 mg/L CaCO3 at 0.5 km upstream and discharge points.
The dissolved oxygen (DO) pattern indicates water quality stress from both upstream and effluent-related pollution. DO drops from 7.25 mg/L at 1 km upstream to 4.38 mg/L at 0.5 km upstream, likely due to the impacts of agricultural runoff [44]. The peak at the point of discharge (7.88 mg/L) may result from the untreated effluent thereby increasing oxygen solubility, but DO declines downstream to 4.08 mg/L at 1 km, reflecting microbial decomposition of organic matter from the effluent [45, 46]. DO below 5 mg/L can impair aquatic life and indicates ecological stress [47]. DO was lower during the rainy season, likely due to temperature effects that inversely affect DO [48]. Variations in BOD5 could be linked to differences in deoxygenation rates and organic matter [49].
Despite the impact of palm oil mill effluent, mean BOD₅ levels upstream and downstream indicated relatively low organic pollution [50]. Total hardness, ranging from 8.88 ± 5.22 to 104.38 ± 77.39 mg/L CaCO₃, reflected moderate hardness due to dissolved calcium and magnesium salts [51]. In this study, COD values exceeded the 10.00 mg/L limit [39], particularly downstream, indicating pollution by organic and inorganic matter [52]. Elevated chloride levels at the discharge point, especially in the wet season, suggest effluent and runoff contamination, making the water unsuitable for aquatic life and drinking [53].
Nitrate levels in Agbogbo Stream were within the WHO limit (50 mg/L) and were higher during the rainy season, likely due to fertilizer and waste leaching from the surrounding environment [54, 55]. Phosphate ranged from 0.32 ± 0.04 to 0.48 ± 0.12 mg/L, with higher values in the dry season from runoff and effluents [56]. Sulphate increased during rains but was below the 250 mg/L WHO limit. Organic matter and Total organic carbon levels (6.54–12.77 mg/L and 11.26–23.41 mg/L) indicated moderate pollution yet sustained productivity [57].
WQI values in this study were better at the upstream/downstream but poor at discharge points due to effluent, with DO, BOD, chloride, TSS, and alkalinity as key contributors [17]. Seasonal WQI analysis of Agbogbo Stream showed lower values during the rainy season, likely due to dilution from precipitation [58]. The lowest WQI occurred at the discharge point, highlighting the negative impact of palm oil effluent. In the dry season, WQI at the discharge point improved slightly, with the highest value recorded 1 km upstream. Variations in WQI may also result from other human activities beyond effluent discharge [59].
The Water Quality Index (WQI) values (58.6–65.5) indicate moderate impairment in the stream. Comparing these with global studies highlights differences mainly due to human stressors and environmental conditions. The WQI was lower than in Nigerian streams near waste dumpsites (80.4) [23], while South Korea’s agriculturally affected streams (78.9) had higher WQI scores (Kim et al., 2020) [24]. This suggests less severe pollution in this study, possibly from lower pollutant loads or different effluents than dumpsites or agriculture. Higher WQI values in Nigeria streams near waste dumpsites and South Korea stream may reflect better dilution or natural attenuation, contrasting with this study (WQI: 58.6–65.5) indicating “poor” but threatened water quality. The WQI was also lower in the less disturbed Little Weikert stream, USA [27], likely due to fewer human impacts and natural filtration. Proximity to effluent discharge causes measurable degradation despite moderate pollution levels.
The WQI of this current Agbogbo stream is higher than Turkey’s Korucuköy stream (34.5–55.6) [25] and India’s Makdhoomyari stream (48.9) [26], indicating it experiences fewer or less intense stressors than streams heavily impacted by agricultural runoff and domestic sewage. In Turkey and India, combined discharges likely raise nutrient levels, turbidity, and organic matter, resulting in poorer WQI values. The poor WQI could probably due to the effluent composition, which might lack the broad pollutants from agricultural and domestic sources, and the stream hydrology, such as higher flow or dilution during the rainy season. Seasonal variation shows lower WQI at discharge (52.9) during the rainy season compared to stability in the dry season, as rainfall dilutes pollutants but can also mobilize contaminants, unlike the low-impact forested Little Weikert stream or the more stressed Turkish and Indian streams.
This study also shows that palm oil mill wastewater is polluting Agbogbo Stream, degrading water quality and affecting aquatic life. The effluent increases the levels of BOD, COD, and conductivity while reducing DO. Although some parameters were within the acceptable standards, the water remains poor and unsafe for drinking without treatment. Regular monitoring and better wastewater management are recommended to protect the stream and local communities. Agricultural runoff and domestic sewage discharge significantly impair water quality by introducing excess nitrogen, phosphorus, organic pollutants, and pathogens, which lead to eutrophication, oxygen depletion, and ecosystem degradation, while also posing public health risks due to increased biological oxygen demand [60]. It has been observed that fertilizers and pesticides can trigger algal blooms and hypoxia [61], while domestic sewage increases BOD, disease risk, and introduces emerging contaminants, contributing to 1.8 million waterborne deaths annually [62,63].
Variations in the Water Quality Index (WQI) across the Agbogbo Stream are driven by spatial and seasonal changes in physicochemical parameters, reflecting pollution levels at each station. At discharge points, the WQI was lowest (58.6), indicating poor water quality mainly due to high turbidity, TDS, TSS, conductivity, BOD, COD, organic matter, and TOC [38]. These values show heavy organic and chemical pollution from raw palm oil mill effluents (POME), which carry high solid loads and degradable organic content. Despite high dissolved oxygen (7.88 mg/L) at the point of discharged, the pollution from effluents influence the physico-chemical parameters thereby increasing the WQI values [64].
At downstream, WQI values gradually improved which could be attributed to natural dilution, sediment settling, and reduced effluent, as indicated by lower TDS, conductivity, turbidity, and organic matter [65]. However, sulphate and nitrate peaked at 1 km DS, likely from nutrient buildup during transport which often leads to eutrophication [66]. Upstream stations (1 km and 0.5 km US) showed less poor WQI, reflecting less contamination and limited effluent influence [67].
This study observed that seasonal variation significantly affected WQI. In the rainy season, increased runoff and effluent dispersion caused fluctuations in sulphate, nitrate, chloride, acidity, and temperature. Higher turbidity and nutrients during raining season degraded midstream waterbody but helped disperse pollutants downstream [68]. In the dry season, reduced water flow concentrated pollutants near discharge points, thus resulting in poor WQI values (63.9–66.6) and pollution was more localized with minimal dilution.
Parameters such as alkalinity, hardness, phosphate, COD, and TOC, which were highest at the discharge point, had strong influences on WQI, especially in the absence of significant dilution. The correlation and PCA analyses confirmed that TSS, acidity, BOD, and sulphate are major contributors to pollution, shaping the WQI trend. Therefore, WQI variation across spatial and seasons in this study reflects the combined influence of effluent concentration, hydrological conditions and pollutant transport with the discharge point serving as the primary pollution hotspot and downstream areas showing variable recovery driven by natural processes [69].
The study found that palm oil mill effluents have significantly degraded Agbogbo Stream’s water quality, with an average Water Quality Index (WQI) of 64.04, indicating moderate pollution. To address this, it is recommended that policymakers enforce strict effluent discharge regulations with penalties for non-compliance, mandate the installation of treatment systems such as anaerobic digesters and sedimentation tanks, and implement real-time monitoring of key parameters. Industry stakeholders should adopt effluent recycling for irrigation or biogas production and invest in cleaner production technologies, while local communities and environmental groups are encouraged to establish vegetative buffer zones along stream banks, promote environmental education, and strengthen community oversight to ensure sustainable water management.
Limitations of the study
This study has several limitations. First, its focus on a single stream (Agbogbo Stream) which limits the generalizability of the findings to other water bodies with different hydrological and pollution characteristics. Second, the assessment was restricted to selected physicochemical parameters, excluding key indicators such as microbial contaminants and heavy metals, thereby limiting the comprehensiveness of the water quality evaluation. Additionally, external environmental factors, including weather conditions and nearby pollution sources, may have influenced the results. The temporal scope of sampling may also not reflect seasonal or long-term variations, and the absence of biological or ecological assessments further constrains the overall interpretation of stream health.
Future study should include multiple streams to enhance comparability and generalizability across different flow regimes and pollution sources. Studies should assess microbial contaminants and heavy metals alongside physicochemical parameters for a more comprehensive evaluation. Incorporating seasonal monitoring and spatial analysis will help capture temporal changes and pollution patterns. Ecotoxicological assessments are also recommended to better understand the ecological risks of effluent discharge.
Supporting information
S1 Table. The physico-chemical characteristics and the ionic composition of POME collected at the point of discharge during the period of study.
https://doi.org/10.1371/journal.pwat.0000441.s001
(DOCX)
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