Sustainable treatment of palm oil mill effluent and repurposing of sludge as a micronutrient resource

2.1 Characterization of palm oil mill effluent

The effluent was sampled from a palm oil mill in Selangor, Malaysia. The initial pH, turbidity, TSS, color, and COD of POME were ≈8, 470 ± 106.2 nephelometric turbidity unit (NTU), 2680 ± 204.6 mg/L, 10 313 ± 441 American Dye Manufacturers Institute (ADMI), and 2880 ± 22.3 mg/L, respectively. The effluent was stored in a plastic bottle and kept in a cold room at 4°C to prevent microbial activity.

2.2 Preparation of coagulant stock solutions

Neem leaves used in this study were obtained from Bangi, Selangor, Malaysia, then washed, oven-dried (BS100, Protech, Malaysia) at 40 °C for three days, and ground into a fine powder by using a blender (Panasonic, Malaysia). Sieves with 200-500 μm meshes were used to sieve the ground leaves, and then, the Neem powder was stored in tight containers for the following application. Then, 5 g of the dried plant powder was dissolved in 500 mL of 1 M sodium chloride solution to prepare Neem extract with a dose of 10,000 mg/L. Sodium chloride solution is capable of enhancing the salting-in mechanism effect, thus increasing the protein solubility (Yin, 2010; Mutar et al., 2025). The solution was consistently stirred at 60 rpm for 1 h using a magnetic stirrer for complete dissolution, then centrifuged (5810, Eppendorf, Germany) and filtered using a 0.45 μm filter paper (Whatman, Germany). The coagulant extract was freshly prepared before each experiment to prevent degradation or characteristic change due to storage.

2.3 Coagulation-flocculation experimental runs using neem extract

The ability of Neem extract to coagulate or flocculate suspended solids in POME was conducted using a jar test set-up (VELP, Malaysia). The coagulant dose and pH value were optimized at constant operation parameters (200 rpm and 1 min for rapid mixing, 15 rpm and 30 min for slow mixing, and 30 min for settling time) employing one-variable-at-a-time (OVAT) technique. POME was poured into each 500 mL beaker with a volume of 300 mL to examine the effect of coagulant dose. Subsequently, the Neem extract doses were varied from 0 to 100 mg/L. The coagulant dose was varied at the POME original pH value (≈pH 8). The optimal coagulant dose, preidentified in the dose test, was added to POME by varying pH values from pH 4 to pH 9 to quantify the influence of pH on the coagulation of POME. The pH of POME was amended through the usage of 0.1 M hydrochloric acid or 0.1 M sodium hydroxide. Finally, the supernatant and settled sludge were sampled for further analysis.

2.4 Water quality analysis

The treated POME was analyzed for the content of turbidity, TSS, COD, and color to evaluate the effectiveness of the plant-extracted coagulant. A turbidimeter device (2100AN, HACH, China) was used to measure the turbidity of the treated POME. A DR3900 spectrophotometer (HACH Company, USA) was employed to determine TSS and color. COD levels were quantified in accordance with Lanan et al. (2022) by employing a digital reactor block (DRB 200, HACH Company, the USA) and a DR3900 spectrophotometer. The percentage removal of turbidity was determined in accordance with Eq. (1) from our previous study (Mutar et al., 2023):

with $T_i$ and $T_f$ represent the respective initial and final measurements of POME turbidity, TSS, COD, and color.

2.5 Kinetic determination

Brownian motion controls the aggregation rate of particles during coagulation. The kinetics of coagulation affect the rate of turbidity removal and are determined by the subsequent general differential equation (Varsani et al., 2024):

with C, t, k, and n denote the turbidity, time, rate constant, and reaction order, respectively. The negative sign in Eq. (2) indicates a decrease in turbidity with time (t).

During the coagulation process, the rate of turbidity decrement is crucially proportional to the initial turbidity and weight of the added coagulant. Therefore, by integrating Eq. (2), the first-order rate equation (n=1) for a coagulation process (Varsani et al., 2024) becomes:

with C₀ and C represent the respective initial and final turbidity levels of an effluent (NTU) at time (t), and k₁ is the first-order rate constant in $\frac{1}{\text{min}}$.

Sometimes, the kinetics of coagulation can match the second-order rate (n=2) when the straight line resulting from the plot $\ln \left(\frac{C_0}{C}\right)$ of versus t does not go through the origin but instead passes through another y-intercept. Eq. (2) is then rewritten (Varsani et al., 2024) as:

Subsequently, the integrated equation of the second-order rate (n=2) for the coagulation process is written as:

with k₂ is the second-order rate constant in $\frac{1}{\text{NTU}.\text{min}}$.

2.6 Analysis of surface morphology and elemental distribution of the settled sludge

The coagulated sludge at the bottom of beakers was sampled, filtered, and dried for testing as a soil biofertilizer. A SEM coupled with EDX was utilized to analyze the surface morphology and its elemental distribution of the recovered sludge.

2.7 Determination of GI

The GI was measured as previously described by Zahrim et al. (2017) with modifications to evaluate the phytotoxicity of the recovered POME sludge. The GI test was conducted by using polypropylene seedling trays with individual square cells with a 5 cm dimension. Okra seeds were sown in five cells containing POME sludge mixed with a commercial sandy soil in a 2:8 sludge-to-soil ratio (by mass). Okra was also sown in a control set of five cells, which contained 100% commercial sandy soil. After 14 days, the germinated seeds were counted, and root lengths were measured and compared. GI results were calculated as follows (Zahrim et al., 2017):

2.8 Statistical data analysis

Statistical analysis of the findings was conducted using Statistical Package for the Social Sciences (SPSS) Software (Version 21, IBM, USA) at a confidence level of 95%. The statistically significant effects of coagulant dose and pH on coagulation performance through turbidity, TSS, COD, and color reduction rates (Mutar et al., 2022) were analyzed through one-way ANOVA followed by a post hoc test (Turkey HSD).

3.1 Effect of coagulant dose

The removal rates for the turbidity, TSS, COD, and color of POME showed a clear response with the variation in coagulant dose, reflecting its crucial role, as depicted in Fig. 1. The results revealed two distinct trends: an increasing removal phase at doses of 0 mg/L to 60 mg/L followed by a remarkably stable removal phase at doses of 60 mg/L and above. In the first phase (0-60 mg/L), turbidity, TSS, and COD removal rates steadily and significantly increased (p < 0.05), reaching 79.51%, 93.32% and 87.61%, respectively. The first phase of POME color removal extended from 0 mg/L to 40 mg/L, with the removal efficiency reaching 65.99%. These results are in line with the findings reported by Nigussie and Habtu (2023), who found that in the treatment of drinking water, increasing the doses of moringa, aloe vera and cactus from 50 mg/L to 150 mg/L significantly increased the turbidity removal rate from 68.22% to 98.82%, 61.72% to 98.205% and 45.55% to 69.395%, respectively. Lanan et al. (2022) reported that the turbidity and COD removal rates for POME improved in conjunction with the increase in the dose of a fenugreek coagulant. Under the assumption that charge neutralization and bridging are dominant mechanisms, increasing the biocoagulant dose leads to a direct increase in proteins as the active ingredient, inducing an increase in the collision rate and protein-colloid bridging, thus resulting in the increased neutralization of negatively charged colloids to the isoelectric point (Lek et al., 2018; Nigussie and Habtu, 2023).

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Fig. 1.

Final concentrations and removal rates of (a) turbidity, (b) TSS, (c) COD, and (d) color obtained by the Neem coagulant at various doses and pH≈8 [Letters a–d refer to significantly different removal (p<0.05)].

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In the second phase and with the further increase in coagulant dose (>60 mg/L), the turbidity, TSS, COD, and color removal rates stabilized (p>0.05), reaching 84.14%, 93.71%, 85.90%, and 73.10%, respectively. The optimal dose varied depending on the plant type and wastewater characteristics. While applying a low dose is ineffective, applying a high dose generates excess sludge and introduces other contaminants (Lwasa et al., 2024). Flores et al. (2024) indicated the importance of the optimal biocoagulant dose, emphasizing that exceeding the optimal dose negatively affects treatment. The optimal dose of a coagulant based on prickly pear peel waste was 100 mg/L, reducing the turbidity of domestic wastewater by 76.1%. However, turbidity removal decreased to 51.7% when the coagulant was used at a dose of 250 mg/L. Coagulant dose remarkably affects the effectiveness of coagulation-flocculation because adding a coagulant at its optimal dose contributes to achieving the optimal performance, hence saving costs and reducing sludge formation (Alnawajha et al., 2024). In the current study, 60 mg/L was fixed as the optimal dose to be applied in experiments on identifying the optimal pH value.

3.2 Effect of pH

The Neem extract was examined at a dose of 60 mg/L and various pH values (pH 4-9), as illustrated in Fig. 2, to investigate the pH effect. The POME turbidity, TSS, and color removal rates under acidic conditions (92.01%, 95.89%, and 79.73%, respectively) were higher but in approximate agreement with those under alkaline conditions (85.97%, 94.21% and 73.82%, respectively). Statistically significant differences were found between these results. COD removal showed the opposite trend, increasing under alkaline conditions (pH 9) to 87.84% but decreasing under acidic conditions (pH 4) to 56.25%. Oladoja et al. (2017) previously reported a limited role for pH, given that the turbidity removal performance of the coagulant based on fresh seeds of Matricaria discoidea stabilized with the change in the pH of synthetic turbid water.

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Fig. 2.

Final concentrations and removal percentage of (a) turbidity, (b) TSS, (c) COD, and (d) color obtained by the Neem coagulant at various pH levels and 60 mg/L for the coagulant dose [Letters a–d refer to significantly different removal (p<0.05)].

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Indeed, the role of pH has a complicated double influence on coagulation because it influences the coagulant surface charges and suspension stabilization (Saritha et al., 2017). Shak and Wu (2014) reported that strongly acidic conditions (≈pH 3) were the optimal conditions for the POME treatment using a coagulant based on Cassia obtusifolia seed gum. However, they found that the performance of the coagulant markedly decreased when the pH exceeded 4 because colloidal particles tend to be negatively charged at high pH but maintain their cationic forms under strongly acidic conditions. Contradictory results were reported by other researchers. For example, Saritha et al. (2017) reported that the highest reduction in the turbidity of surface water was achieved by sago coagulant in a medium with neutral pH (pH 6-7). Shah et al. (2023) also confirmed that greater TSS and turbidity removal rates were achieved by plant-extracted coagulants at a pH of 7 than at the original pH of 3.4. Lek et al. (2018) proposed that the protein solubility of a chickpea-extracted coagulant improved at pH levels exceeding 4, accounting for the enhancement in POME treatment at high pH.

3.3 Performance of the neem coagulant

This study addressed the potential of POME treatment using a Neem-based coagulant. The coagulant achieved considerable reductions of more than 92%, 95%, 87% and 79% in the turbidity, TSS, COD, and color of POME, respectively. Researchers have addressed POME treatment using various types of plant-based coagulants, including M. oleifera seed (dose of 6 g/L and pH of 5), and achieved TSS and COD removal rates of approximately 95% and 52%, respectively (Bhatia et al., 2007). They also applied Cassia obtusifolia seed gum (dose of 0.98 g/L and of pH 2.9) as a coagulant and obtained reductions of 61% and 93% in COD and TSS, respectively (Shak and Wu, 2014). Neem leaves are preferred to several other components that have been proposed for POME treatment because they are nonessential components of the food chain. Lek et al (2018) reported that a chickpea coagulant (dose of 2.6 g/L, pH 6.69, and rapid mixing at 140 rpm) reduced the turbidity, COD, and TSS of POME by 86%, 56% and 87%, respectively. Chung et al. (2018) investigated the use of peanut and wheat germ as coagulants in combination with okra as a flocculant (coagulant dose of 1000-1170 mg/L, flocculant dose of 100-135.5 mg/L, and pH of 11.6-12) for the treatment of POME. The authors reported turbidity, TSS, and COD removal rates in the range of 86.6-92.5%, 86.6-87.5%, and 34.8-43.6%, respectively. In the same context, Lanan et al. (2022) stated that the combination of fenugreek as a coagulant and okra as a flocculant (coagulant dose of 4.09 mg/L, flocculant dose of 57.69 mg/L, pH 3.17, and rapid mixing at 97.39 rpm) reduced turbidity, TSS, and COD by 94.9%, 92.70%, and 63.11%, respectively. Zahrim et al. (2017) reported that the inorganic coagulant ferric chloride hexahydrate (dose of 8000 mg/L and pH of 10.0) resulted in 90% POME color removal.

The turbidity data obtained in jar test experiments were fitted with Equations (2) and (4) to evaluate the treatment effectiveness, as demonstrated in Fig. 3. The data on the Neem coagulant were well fitted to both first- and second-order kinetic rates. Nevertheless, Fig. 3 shows that the determination coefficient (R²) for the Neem coagulant favored the first-order kinetic rate (R²=0.9918) (Fig. 3a) compared to the second-order kinetic model (R²=0.9816) (Fig. 3b). High R² values refer to a statistically significant relationship for both kinetic rates, confirming their fittingness (Fard et al., 2021). The rate constants for the first- and second-order kinetics were 0.0679 per min and 0.0005 1/NTU.min, respectively. Higher rate constants are directly associated with the appropriate coagulant type and optimal dose required to achieve effective turbidity removal (Al-Sameraiy, 2017).

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Fig. 3.

Kinetic plots for the (a) first- and (b) second-order processes of the Neem coagulant (coagulant dose = 60 mg/L; pH ≈ 8).

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3.4 Characterization of sludge and its potential use as a soil amendment

The distribution of elements for the settled sludge cake were determined through surface morphological analysis by using SEM with EDX and compared with those of sandy soil, as illustrated in Fig. 4. The results show that sludge mainly consisted of oxygen (42.19%) and carbon (31.75%), in addition to macronutrients, specifically phosphorus (2.96%) and potassium (2.56%), and completely lacked nitrogen. Importantly, the sludge cake was rich with various micronutrients, including calcium (6.68%), silicon (4.57%), sulfur (0.63%), magnesium (4.84%), aluminum (1.24%), chloride (0.32%), and iron (2.27%). By contrast, sandy soil mainly contained varying weights of oxygen (48.57%), silicon (42.73%), carbon (6.59%), and aluminum (2.11%).

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Fig. 4.

SEM microphotographs with EDX elemental maps of (a) the settled sludge cake recovered from the treated POME using Neem coagulant and (b) sandy soil.

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A set of okra seeds was planted in the recovered sludge, and another set was planted in sandy soil as a control. Fig. 5 displays the images of okra seedlings after two weeks of germination. The plants grown on the sludge mixture and control soil had similar average stem lengths of 13.16 ± 1.08 and 12.5 ± 0.87 cm, respectively. However, the okra grown on the modified soil mixture exhibited remarkable signs of healthy growth, including improved root density, straight stems, higher leaf number (four under treatment with the sludge mixture vs three under treatment with the control) and larger leaves than the control plants, which exhibited stem curvature and leaf atrophy. As a result, the GI of the plants grown on the modified soil mixture increased by 43% to 115% relative to that of the plants grown on the control soil (Fig. 5b). Karim et al. (2022) reported remarkable improvements in soil physicochemical characteristics and maize (Zea mays) growth performance when treated POME sludge and fortified vermicompost were used as amendments. Nizar et al. (2020) confirmed that the application of POME sludge contributed to the improvement in the growth of Pennisetum setaceum and Digitaria setivalva and the development of root density that directly led to an increase in soil shear strength. Sanches et al. (2024) compared the abundance of Proteobacteria (48.1%) and Firmicutes (9.0%) in POME-fertilized soil with that in control soil. Mahmod et al. (2023) reported that POME is a resource rich in nitrogen, phosphorus, and potassium that contains low amounts of heavy metal elements and high amounts of micronutrients, including iron, potassium, calcium, magnesium, and phosphorus. Treated POME sludge could be securely utilized as a low-cost biofertilizer replacing chemical fertilizers (Mahmod et al., 2023).

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Fig. 5.

Image of okra seedlings after two weeks of growth on (a) sand and (b) the sludge mixture. (c) Comparison of shoot and root lengths, leaf numbers, and GIs of okra grown on the prepared soil and sandy control soil.

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The impaired growth and development of plants cultivated on sandy soil were expected and consistent with the findings reported by Cavalcante et al. (2019), who confirmed that these symptoms are a result of nutrient deficiency. A previous study concluded that due to nitrogen deficiency, sludge is inappropriate as a soil fertilizer and should instead be used as an energy source. Lek et al. (2018) considered excluding POME sludge as a soil fertilizer due to its nitrogen deficiency and instead suggested its use as an ideal source of energy due to its high carbon ratio. Fortunately, enhancing nitrogen deficiency is possible through mixing POME sludge with rich-nitrogen biochar or composts such as nitrogen-enriched biochar co-compost, which was previously reported by Nain et al. (2022); this would fully increase the potential of POME sludge as a complete fertilizer.

Generally, the use of sludge, including sewage sludge, for agricultural purposes is a common practice; however, to alleviate associated risks, it is necessary to ensure suitable treatment of sludge prior to its application (Pérez-García et al., 2025). Rastetter et al. (2017) reported that triple super phosphate fertilizer was more toxic than thermally treated phosphate fertilizer recovered from sewage sludge. Lee et al. (2023) emphasized that adding an industrial sludge with high levels of toxic substances, such as heavy metals or chemical contaminants, rather than organic matter and essential nutrients, negatively affects seed germination.