Optimized Coagulation Flocculation of Drinking Water Using Pine cone-Based Bio-Coagulants: A Comparative Study of Different Extracts

Abstract

High turbidity in raw water poses a major challenge to drinking water quality and requires effective, sustainable treatment solutions. This work investigates the reduction in turbidity in raw water and the enhancement of overall drinking water quality through the coagulation–flocculation process. The performance of Pine cone extract as a bio-coagulant was evaluated using four different solvent-based extractions (PC-H₂O, PC-HCl, PC-NaCl, and PC-NaOH). The effects of key operational parameters were analyzed, and jar tests were carried out to enhance the coagulation–flocculation process by identifying the optimal conditions. Experimental design was further refined using RSM based on a BBD, incorporating three factors: initial pH, coagulant dosage, and settling time, with turbidity removal efficiency as the response variable. Statistical analysis confirmed that initial pH, coagulant dosage, and settling time significantly influenced turbidity reduction at a confidence level of p-value < 0.05 for all four solvents. Among the extracts tested, PC-HCl demonstrated the highest turbidity removal efficiency. The optimal conditions achieving 78.57% turbidity reduction were a pH of 8.5, a coagulant dosage of 100 mL/L, and a settling time of 120 min. These findings highlight the significant potential of Pine cone extract as an effective, sustainable, and eco-friendly organic coagulant for raw water treatment.

1. Introduction

Drinking water is vital for human survival and having access to clean and safe water is a basic human right, regardless of nationality, religion, race, or socio-economic status. Polluted water and poor sanitation are major contributors to the spread of diseases such as cholera, diarrhea, dysentery, and polio, highlighting the significant impact of water quality on public health [1,2]. The treatment of surface or groundwater to produce potable water typically involves multiple steps to remove harmful substances. When surface water is used as the raw source, turbidity removal is often a critical part of the process. To ensure that clean water is accessible to as many people as possible, affordable, simple, and efficient treatment methods are required [3,4].

Various treatment technologies are employed to process raw water into potable water and to treat water and wastewater before it is released into natural water sources [5]. The coagulation–flocculation process is an integral stage in most water and wastewater treatment processes. These methods are widely used for their efficiency in eliminating suspended particles, organic matter, color, and turbidity from water [5,6,7]. The coagulation process uses inorganic coagulants to destabilize dispersed organic matter by forming microflocs, which then aggregate into larger flocs and settle out of the water by gravity [8,9]. However, the use of chemical coagulants presents several drawbacks, including high operational costs, reduced efficiency in cold water, the generation of large sludge volumes, significant impacts on the pH of treated water, and potential health risks, such as a link to Alzheimer’s disease [10,11]. In contrast, the use of natural, plant-based coagulants, such as fruit peels, seeds, and other agricultural by-products, provides a sustainable and eco-friendly alternative, decreasing reliance on chemical coagulants and lessening the environmental impact associated with chemically produced sludge disposal [8,12,13,14].

Recent research has increasingly focused on sustainable and environmentally eco-friendly natural coagulants as alternatives to chemical and synthetic coagulants for drinking water treatment [15,16,17]. Various bio-coagulants have been investigated, including aloe vera, as studied by Benalia et al. [18], as well as Moringa oleifera, Strychnos potatorum, Phaseolus vulgaris [19], chitosan [20,21], and Acorn leaves have also been explored for their coagulation properties [22]. However, to the best of our knowledge, no previous study has investigated the potential use of Pine cone-based coagulants for drinking water treatment, despite their richness in bioactive compounds such as polyphenols, polysaccharides, lignin, and proteins [6,23,24], which are known to play key roles in coagulation mechanisms like charge neutralization, adsorption, and bridging flocculation.

This study investigates the use of Pine cone extract, specifically from Pinus nigra, a species abundant in the Mediterranean region, as a novel and renewable bio-coagulant for drinking water treatment. To enhance the extraction of active compounds, four solvents were selected based on their extraction efficiency and suitability for simple extraction methods. Distilled water was used as a neutral and accessible medium to extract water-soluble compounds. Salt extraction using NaCl is known to effectively isolate proteins that can act as polyelectrolytes during the coagulation process [25]. Alkaline extraction with NaOH was applied to solubilize lignin and polysaccharides [26], while acidic extraction with HCl was employed to release polyphenols and bound carbohydrates [13]. These solvents offer the advantage of being low-cost, low-toxicity, and suitable for low-energy processes. The performance of the resulting extracts, namely PC-H₂O, PC-NaCl, PC-NaOH, and PC-HCl, was evaluated based on their ability to reduce turbidity in raw water collected from the Oued El Athmania drinking water treatment plant. A Response Surface Methodology (RSM) using the Box–Behnken Design (BBD) was applied to optimize key operational parameters, namely pH, coagulant dosage, and settling time, with turbidity removal as the main response variable. The performance of the four extracts was then compared based on their turbidity removal efficiency. This work aims to provide a scientific basis for the valorization of Pine cones as an accessible, cost-effective, and sustainable resource for water treatment.

2. Materials and Methods

2.1. Raw Water Collection and Analysis

The raw water for this study was sourced from the Oued El Athmania drinking water treatment plant in Algeria (coordinates: 36°49′34.89″ N, 6°31′11.81″ E). The physicochemical properties of the raw water, along with the regulatory quality limits set by Algerian water standards, are summarized in

Table 1. Raw water characterization.

Parameters	Raw Water		Algerian Standard [27]
	Unit	Value
Temperature	°C	21	25
pH	/	7.57	6.5–9
Turbidity	NTU	32.5	5
TSS	mg. L−1	16.2	/
TA	meq. L−1	0	/
TAC	°F	16.5	50
TH	°F	18.4	20
Salinity	g. L−1	0.9	/
Conductivity	µs. cm−1	1724	2800
Solid content	mg. L−1	1924.1	1500 mg/L
UV254	Cm−1	0.714	/

.

2.2. Analytical Methods

Turbidity was assessed with a turbidimeter (Turbidimeter HI 98713-02-ISO 7027-Hanna instruments, Cluj-Napoca, Romania). Total hardness and alkalinity were determined using standard titrimetric methods. Measurements of pH, temperature, electrical conductivity, and salinity were carried out with a multi-parameter instrument (Jenway Model 3540, Camlab, Cambridge, UK). Total suspended solids (TSSs) in the effluent were measured by filtration using Whatman filter paper, followed by drying at 105 °C for 2 h. The solid content was determined by measuring the difference between the sludge initial weight and its dry weight after drying in an oven at 105 °C for 24 h. Aromatic organic matter was identified by UV–vis spectrophotometry (SHIMADZU UV 1201 model, Kyoto, Japan), with absorbance measured at 254 nm (UV₂₅₄). All reagents were of high-purity grade.

2.3. Bio-Coagulant Preparation

Pine cones were sourced from fields in Mila, Algeria. The preparation process for Pine cone powder (PCP) is outlined in Figure 1a. Initially, the cones were manually selected and peeled to remove unwanted materials. They were then dried in an oven at 50 °C ± 1 °C for 24 h to reduce moisture content. Once dried, the cones were finely ground using a domestic grinder and subsequently sieved through a 250 μm laboratory sieve to obtain a uniform powder.

The extraction was performed according to the steps shown in Figure 1b. A total of 5 g of prepared PCP was stirred with 1000 mL of each solvent: distilled water, NaCl (0.5 M), NaOH (0.05 M), and HCl (0.05 M), to obtain the corresponding aqueous extracts. The mixtures were stirred at 400 rpm for 20 min, followed by 30 min of maceration. The resulting suspensions were then filtered through standard filter paper with a porosity of less than 8 µm [23,24]. The resulting clear filtrates, stored at 4 °C, were labeled as PC-H₂O, PC-NaCl, PC-NaOH, and PC-HCl based on the solvent used.

For this investigation, sodium chloride (NaCl), sodium hydroxide (NaOH), and hydrochloric acid (HCl) were obtained from Sigma-Aldrich Chemical Company (St. Louis, MO, USA).

2.4. FTIR Analysis

Fourier Transform Infrared (FTIR) spectroscopy is a method used to analyze molecular structures by identifying functional groups and chemical bonds. It enables the identification of key functional groups that play a significant role in coagulation activities. The analysis of the absorption spectrum of Pine cone powder and extracts were obtained by using FTIR (Shimadzu, IRAffinity-1S, Kyoto, Japan).

2.5. Design of Experiment

A BBD was implemented using Minitab 21.0 software (Minitab, LLC, State College, PA, USA) as part of the RSM approach to optimize water treatment efficiency, focusing on turbidity removal and the reduction in physicochemical parameters that deviate from drinking water standards. Three key factors were selected to evaluate their impact on treatment performance: coagulant dose (X₁), initial pH (X₂), and settling time (X₃) (see

Table 2. The coded and actual levels of variables in BBD.

Coded Values	Factor	Coded level
		−1	0	1
X1	Coagulant dosage (mL/L)	10	55	100
X2	pH	6.5	7.5	8.5
X3	Settling time (min)	30	75	120

). The dependent variable, representing the response, was turbidity removal efficiency. These parameters were used to calculate removal efficiencies after each trial. Using RSM, a quadratic polynomial equation was developed to predict the response (treatment efficiency) based on the independent variables and their interactions (Equation (1)). The experimental design included 15 trials: 12 main trials and three replicates at the central point of the design.

$$Y_i=B_0+{\sum }_{i=1}^k{B}_i{X}_i+{\sum }_{i=1}^k{B}_{ii}{X}_i^2+{\sum }_{\begin{array}{c}i=1\\ j=2\\ i\ne j\end{array}}^k{B}_{ij}\ast X_i\ast X_j$$

(1)

In this model, Yi represents the response (turbidity removal); K denotes the number of factors (K = 4); β0 is a constant term; while βi, βii, and βij correspond to the regression coefficients; and Xi represents the investigated parameters [6,28,29].

2.6. Experiments (Jar Test Assays)

Jar test experiments (Jar test Selecta-Flucomatica, Barcelona, Spain) were employed to evaluate the performance of the coagulation–flocculation process. Experiments were performed with a six-position stirrer and six beakers, each containing 500 mL of raw water samples. The pH was modified to the required level (Table 2) by adding 1 M hydrochloric acid or sodium hydroxide solutions. After adding the respective coagulant doses for the four extracts studied (PC-H₂O, PC-HCl, PC-NaOH, PC-NaCl) as indicated in Table 2, the mixtures were agitated at 160 rpm for a duration of 3 min. The stirring speed was then reduced to 30 rpm for 20 min [30], followed by a settling period, the duration of which varied according to Table 2. The supernatant was collected from 2 cm below the surface [31] and analyzed to measure turbidity. The turbidity removal efficiency was then determined using Equation (2) [6].

$$\mathbf{T}\mathbf{R}\mathbf{E} (\mathbf{\%})={\displaystyle \frac{\left(\mathbf{I}\mathbf{T}-\mathbf{R}\mathbf{T}\right)\times \mathbf{100}}{\mathbf{I}\mathbf{T}}}$$

(2)

where TRE is the turbidity removal efficiency (%), IT is the initial turbidity (NTU), and RT is the residual turbidity (NTU).

After determining the optimal conditions for each bio-coagulant (PC-H₂O, PC-HCl, PC-NaOH, PC-NaCl), the treated water was analyzed for key parameters, including turbidity, pH, conductivity, salinity, total alkalinity (TAC), total hardness (TH), UV₂₅₄, and total dissolved solids (TSSs).

2.7. Statistical Analysis

To assess the quality of the quadratic polynomial models, the R² and adjusted R², statistical tests (F and p-values), and normality plots were analyzed. A high F-value suggests that the regression model explains the response variability, while a p-value below 0.05 confirms the model’s statistical significance. R² and adjusted R² closer to 1 demonstrate better model fit [32,33,34]. The significance of regression coefficients was assessed using F and P-tests at a 95% confidence level [33,35,36].

3. Results and Discussion

3.1. Fourier Transform Infrared (FTIR) Spectroscopy

FTIR analysis was conducted to identify the functional groups in raw Pine cone powder and to evaluate their presence in the different extracts (PC-H₂O, PC-NaCl, PC-NaOH, and PC-HCl). This comparison aimed to confirm the extraction of key bioactive compounds such as proteins, polyphenols, and polysaccharides by detecting characteristic absorption bands of hydroxyl, carboxyl, and amide groups, which are linked to their coagulating activity.

Figure 2a shows the FTIR spectrum of the Pine cone powder. An intense absorption band is observed at 3331 cm⁻¹, corresponding to the stretching vibrations of O-H functional groups (carboxylic acids, alcohols, or phenols) or associated with amine groups (NH) [37,38,39]. The CH group is detected at 2928 cm⁻¹ [40]. The peak at 1637 cm⁻¹ is most likely associated with carboxyl (C=O) functional groups [41]. The band at 1273 cm⁻¹ indicates the presence of a COO stretching vibration, confirming the presence of functional groups such as carboxyl, alcohol, ether, or ester [23,41]. Additionally, the FTIR spectrum of the raw Pine cone confirms the probable presence of an ester (CO) functional group, as indicated by the pronounced peak at 1030 cm⁻¹ [31].

Figure 2b presents the FTIR spectrum of the four Pine cone extracts (PC-H₂O, PC-NaCl, PC-NaOH, and PC-HCl). The spectra reveal similar absorption bands with varying intensities, indicating the presence of distinct molecules such as proteins, polyphenols, and polysaccharides extracted from the Pine cone. The figure presents a diverse range of broad infrared absorption bands positioned within the following spectral regions: 3039–3645 cm⁻¹, 2792–3024 cm⁻¹, and 906–1770 cm⁻¹. A wide band centered at 3286 cm⁻¹ corresponds to the stretching of O-H groups, commonly found in fatty acids, proteins, and polysaccharides within the different extracts [39,42]. The involvement of N-H stretching from amide groups is also observed in this region, primarily in the PC-NaCl extract, with lower intensity in PC-HCl, and its absence in the PC-NaOH and PC-H₂O extracts. The peaks at 2924 cm⁻¹ and 2850 cm⁻¹ are associated with the symmetric and asymmetric stretching of C-H groups from CH₂, which are characteristic of fatty acids [43]. In the region between 1485 and 1770 cm⁻¹, two intense bands are attributed to the stretching of the C=O bond, characteristic of carbonyl functions (primary amides). In this case, the spectra reveal a band at 1633 cm⁻¹ associated with fatty acids, aromatic groups, phenol groups, and polysaccharides [31]. In the spectrum of the PC-NaCl extract, a band at 1536 cm⁻¹ is observed, associated with the amide group of proteins and the aromatic groups of polyphenols. Three weak peaks are noted in the PC-NaCl extract: a peak at 1396 cm⁻¹ attributed to the C-N group of aromatic primary amines, a peak at 1242 cm⁻¹ corresponding to the stretching of the carboxylic acid COO bond, confirming the presence of ether, carboxyl, ester or alcohol functional groups, and finally, a weak peak at 1065 cm⁻¹, which could be attributed to an ester CO group [31,39,44].

In summary, comparing the FTIR spectra of the raw Pine cone powder with those of the extracts clearly shows that the extraction process managed to recover the main bioactive functional groups. The presence of hydroxyl, carboxyl, and amide groups in the extracts confirms that important compounds like proteins, polysaccharides, and polyphenols originally found in the raw material were successfully extracted. These groups are essential because they provide active sites that help destabilize colloidal particles, which is a key step in removing pollutants during the coagulation–flocculation process [45].

3.2. Optimization and Modeling of the Turbidity of Drinking Water

Table 3. Results of the RSM methodology in terms of turbidity removal efficiency for the extracts: PC-H₂O, PC-NaCl, PC-NaOH, and PC-HCl.

Factor				Turbidity Removal (%)
	X1	X2	X3	PC-H2O		PC-NaCl		PC-NaOH		PC-HCl
Standard Run	Coagulant Dosage (mL/L)	pH	Settling Time (min)	Experimental	Predicted	Experimental	Predicted	Experimental	Predicted	Experimental	Predicted
1	10	6.5	75	70.36	69.61	38.12	37.07	41.8	34.94	68.357	68.923
2	100	6.5	75	70.06	69.23	33.43	34.57	5.35	10.11	68.260	69.198
3	10	8.5	75	60.86	61.7	29.77	28.63	32.77	28.01	68.227	67.290
4	100	8.5	75	59.19	59.94	33.11	34.15	−0.66	6.18	72.615	72.050
5	10	7.5	30	60.86	60.78	25.4	27.38	20.06	23.45	64.551	64.351
6	100	7.5	30	68.22	68.22	26.42	26.21	12.04	3.8	62.207	61.635
7	10	7.5	120	66.85	66.86	36.78	36.99	64.88	73.11	70.665	71.237
8	100	7.5	120	57.19	57.28	43.15	41.17	49.49	46.11	78.789	78.989
9	55	6.5	30	65.54	66.38	39.79	38.87	8.69	12.16	64.551	64.186
10	55	8.5	30	57.86	57.11	33.11	32.27	0.00	1.37	63.872	65.010
11	55	6.5	120	62.53	63.28	48.15	48.99	54.18	52.8	77.658	76.521
12	55	8.5	120	56.19	55.35	45.8	46.73	56.18	52.71	76.551	76.916
13	55	7.5	75	58.2	58.19	37.78	37.34	43.81	49.05	69.829	69.763
14	55	7.5	75	58.18	58.19	37.12	37.34	54.84	49.05	69.672	69.763
15	55	7.5	75	58.2	58.19	37.12	37.34	48.49	49.05	69.789	69.763

presents the results of the 15 analyses conducted according to the experimental plan defined by the Minitab software. The table shows the levels assigned to each studied variable, as well as the predicted and experimental values obtained for the turbidity reduction rate.

According to the data presented in Table 3, it is observed that PC-H₂O demonstrated remarkable turbidity removal efficiency, achieving 70.36%. These results were obtained under optimal conditions: a coagulant dose of 10 mL/L, a pH of 6.5, and a sedimentation time of 75 min. Using a concentration of 55 mL/L of PC-NaCl, with a pH of 6.5 and a sedimentation time of 120 min, a maximum turbidity reduction of 48.15% was observed. For PC-NaOH, the highest turbidity removal was 64.88%, with an optimal dose of 55 mL/L, an optimal pH of 7.5, and a sedimentation time of 120 min. Regarding PC-HCl, a maximum turbidity removal of 78.78% was achieved, with a dose of 100 mL/L, a pH of 7.5 and a sedimentation time of 120 min. These results indicate that PC-HCl proved to be the most effective in turbidity removal among the extracts tested.

The complete quadratic regression models for coagulation, using the four extracts PC-H₂O, PC-NaCl, PC-NaOH, and PC-HCl, are presented in coded form in Equations (3)–(6), respectively.

Turbidity removal (PC-H₂O (%)) = 58.195 − 0.534 X₁ − 4.298 X₂ − 1.216X₃ + 4.84X₁²
+ 2.089 X₂² + 0.251X₃² − 0.344X₁X₂ − 4.256 X₁X₃ + 0.334 X₂X₃.

(3)

Turbidity removal (PC-NaCl (%)) = 37.35 + 0.753 X₁ − 2.214 X₂ + 6.145X₃ − 6.256X₁²
+ 2.522 X₂² + 1.852X₃² + 2.007X₁X₂ + 1.337 X₁X₃ + 1.084 X₂X₃.

(4)

Turbidity removal (PC-NaOH (%)) = 49.05 − 11.66 X₁ − 2.72 X₂ + 22.99X₃ − 11.19X₁²
− 18.05 X₂² − 1.24X₃² + 0.75X₁X₂ − 1.84 X₁X₃ +2.68 X₂X₃.

(5)

Turbidity removal (PC-HCl (%)) = 69.764 + 1.259 X₁ + 0.305
X₂ + 6.06X₃ − 1.002X₁² + 0.604 X₂² + 0.292X₃² + 1.121X₁X₂ + 2.617 X₁X₃ − 0.107 X₂X₃.

(6)

The negative sign in Equations (2)–(5) denotes an antagonistic effect, whereas the positive sign represents a synergistic effect. It is clear from these equations that the individual operating variable, namely the coagulant dosage for the H₂O and NaOH extracts, has a negative effect on turbidity removal, while for the NaCl and HCl extracts, the coagulant dosage has a net positive effect. Regarding the individual variable of pH, a negative effect on turbidity removal is observed for the H₂O, NaOH, and NaCl extracts. In contrast, for the HCl extract, pH has a positive effect. As for the sedimentation time, a positive effect is noted for all extracts except for the H₂O extract. Variability is observed for quadratic and interactive effects.

3.3. Analysis of Variance (ANOVA Test)

An ANOVA analysis was performed on the regression model in Equations (3)–(6) and the significance of each term is presented in

Table 4. Analysis of variance (ANOVA) of the fitted models developed for the turbidity removal of the extracts: PC-H₂O, PC-NaCl, PC-NaOH, and PC-HCl.

		PC-H2O			PC-NaCl			PC-NaOH			PC-HCl
Source	DF	MS	F-Value	p-Value	MS	F-Value	p-Value	MS	F-Value	p-Value	MS	F-Value	p-Value
Model	9	36.994	36.37	0.000	63.167	19.67	0.002	775.94	10.02	0.010	38.390	32.00	0.001
Linear	3	53.975	53.06	0.000	115.263	35.90	0.001	1792.3	23.14	0.002	102.409	85.35	0.000
X1	1	2.284	2.25	0.194	4.535	1.41	0.288	1088.3	14.05	0.013	12.676	10.57	0.023
X2	1	147.81	145.32	0.000	39.201	12.21	0.017	59.07	0.76	0.422	0.743	0.62	0.467
X3	1	11.824	11.62	0.019	302.054	94.07	0.000	4229.5	54.60	0.001	293.808	244.88	0.000
Square	3	32.551	32.00	0.001	64.917	20.22	0.003	520.67	6.72	0.033	1.936	1.61	0.298
X12	1	86.485	85.03	0.000	144.488	45.00	0.001	462.34	5.97	0.058	3.706	3.09	0.139
X22	1	16.112	15.84	0.011	23.485	7.31	0.043	1202.4	15.52	0.011	1.345	1.12	0.338
X23	1	0.233	0.23	0.653	12.668	3.95	0.104	5.68	0.07	0.797	0.314	0.26	0.631
Interaction	3	24.457	24.04	0.002	9.320	2.90	0.141	14.81	0.19	0.898	10.823	9.02	0.018
X1 X2	1	0.475	0.47	0.525	116.107	5.02	0.075	2.27	0.03	0.871	5.029	4.19	0.096
X1 X3	1	72.449	71.23	0.000	7.150	2.23	0.196	13.53	0.17	0.693	27.396	22.83	0.005
X2X3	1	0.447	0.44	0.537	4.704	1.46	0.280	28.64	0.37	0.570	0.046	0.04	0.853
Error	5	1.017			3.211			77.46			1.200
Lack of fit	3	1.695	18,186.28	0.000	5.256	36.70	0.027	108.64	3.54	0.228	1.995	299.12	0.003
Pure error	2	0.000			0.143	0.757		30.69			0.007
Total	14
R2%		98.50			97.25			94.75			98.29
R2 adj%		95.79			92.31			85.29			95.22

.

From Table 4, it can be observed that all regression models are statistically significant (p ≤ 0.05) for each of the four extracts analyzed, as well as for all the dependent variables investigated.

The models’ calculated F-values are greater than the critical tabulated F-values (3.4817), confirming their significance [46,47]. Furthermore, elevated mean square (MS) values across all models suggest their statistical significance and suitability for accurate prediction.

A well-fitted regression model is expected to have a computed F value that is at least four times greater than the tabulated F value [48,49]. The four regression models analyzed in this study all demonstrate this relationship.

The models describe the proportion of variation in the response as 98.50%, 97.25%, 94.75%, and 98.29% for PC-H₂O, PC-NaCl, PC-NaOH, and PC-HCl, respectively, these are the values of the determination coefficients (R²). The adjusted coefficient of determination values (adjusted R²) for turbidity removal were 95.79%, 92.31%, 85.29%, and 95.22% for PC-H₂O, PC-NaCl, PC-NaOH, and PC-HCl, respectively. The adjusted R² represents the proportion of variation in the response explained by the model, considering the number of predictors in relation to the total observations. As stated by Sabeti et al. [50], a difference of less than 20.0% between R² and adjusted R² is considered ideal for assessing the model’s fit, and this is the case in our study.

3.4. Evaluation Models

The models’ robustness further validates their predictive capability, as shown by the close clustering of points along the diagonal line, indicating a strong correlation between observed and predicted values [51,52,53]. This correlation is demonstrated in Figure 3. These figures illustrate the relationship between the actual and predicted values of turbidity removal from simulated drinking water using the four Pine cone extracts: PC-H₂O, PC-NaCl, PC-NaOH, and PC-HCl. The observed values represent the original turbidity removal measurement in solution, obtained experimentally, while the predicted values were generated using Equations (3)–(6).

3.5. Effect of the Factors on Turbidity Reduction

The most important parameters influencing the effectiveness of turbidity removal by the coagulation/flocculation process, and which have been studied, are the coagulant dosage, pH, and settling time. The main effect graphs of each parameter for turbidity reduction by different Pine cone extracts are presented in Figure 4.

As illustrated in Figure 4, both the optimal dosage and the turbidity removal efficiency vary considerably depending on the type of Pine cone extract used, highlighting clear differences in their bioactive compounds. The PC-H₂O and PC-NaOH extracts showed their best performance at a relatively low dose of 10 mL/L, achieving removal efficiencies of about 65% and 40%, respectively. In contrast, the PC-HCl extract reached its highest efficiency around 71% but at a much higher dose of 100 mL/L. Similarly, the PC-NaCl extract required 55 mL/L to reach an efficiency of about 40%. These variations are consistent with the findings of FTIR analysis, which confirmed the presence of functional groups associated with bioactive compounds responsible for coagulation. The higher turbidity removal at lower doses of PC-H₂O is likely due to the presence of functional groups (C=O, C–O, –CH) identified by FTIR, which serve as active sites for adsorption. At low coagulant concentrations, these sites remain sufficiently available to interact with colloidal particles, favoring an adsorption–bridging mechanism that enables the formation of stable flocs without complete charge neutralization. This suggests that PC-H₂O acts primarily through surface interactions and bridging, rather than relying on charge neutralization, which typically requires higher dosages [54,55]. The high turbidity removal observed with the PC-HCl extract at higher doses may be attributed to the presence of functional groups such as hydroxyl (–OH) and carboxyl (–COOH) in proteins, polyphenols and carbohydrates, whose protonation under acidic conditions enhances coagulation through charge neutralization, adsorption, and bridging mechanisms [56]. In the case of PC-NaCl, higher turbidity removal was observed at medium doses. FTIR spectra revealed amide and N–H bands, indicating the presence of proteins responsible for the coagulation activity. However, the lower efficiency at other doses may be due to a reduced concentration or activity of these proteins, which affects their ability to neutralize charges and form effective inter-particle bridges [56]. This observation, according to Naim et al., [57] supports the finding that an increased number of amino groups enhances aggregation and floc formation. However, at excessively high doses, repulsion between amino groups causes floc destabilization and decreases turbidity removal. As for PC-NaOH, the highest turbidity removal was observed at lower doses. FTIR analysis revealed strong O–H and C–O bands, indicating a high polysaccharide content. Under alkaline conditions, these biomolecules may experience structural changes that reduce their effectiveness at higher concentrations. Several studies, including that by Bahrodin et al., have shown that polysaccharide-based coagulants are more effective at lower doses, as higher concentrations can lead to active site saturation and conformational changes. In general, a higher polysaccharide content improves performance by reducing the coagulant dose required to achieve optimal turbidity removal [26]. Overall, the study revealed that the optimal coagulant dose varied for each extract of bio coagulant, and increasing the dosage did not necessarily result in enhanced coagulation activity. This implies that the coagulation process is strongly influenced by factors such as the concentration and functionality of active groups, as well as the nature of their interactions with suspended particles [56]. Moreover, using a dose that is either too high or too low compared to the optimal value can reduce efficiency, potentially increasing turbidity by destabilizing flocs or restabilizing suspended particles [58].

According to Figure 4a–d, the optimal pH for coagulation varies depending on the type of bio-coagulant extract used. The PC-H₂O and PC-NaCl extracts exhibited their highest turbidity removal efficiencies at a slightly acidic pH of 6.5, reaching 67% and 40%, respectively. In contrast, the PC-HCl extract showed improved performance at a more alkaline pH of 8.5, achieving 71% removal. The PC-NaOH extract reached its maximum efficiency of 42% at a near-neutral pH of 7.5.

The higher turbidity removal observed under mildly acidic conditions for the PC-H₂O and PC-NaCl extracts may be attributed to the protonation of hydroxyl and carboxyl groups present in the proteins and carbohydrates within the bio-coagulant extracts, which enhances their interaction with colloidal particles [56]. In contrast, the PC-HCl extract exhibits optimal performance at pH 8.5, likely due to the presence of acid-extracted polyphenols. Upon deprotonation, these compounds become more reactive, facilitating particle aggregation through bridging mechanisms, which leads to increased turbidity removal. Conversely, alkaline extraction solubilizes organic compounds rich in ionizable functional groups [59], as confirmed by FTIR analysis. However, these compounds can hinder floc formation at higher pH levels. Additionally, the increased negative surface charge of polysaccharides under strongly alkaline conditions may lead to electrostatic repulsion between the bio-coagulant and the negatively charged colloids, thereby reducing overall coagulation–flocculation efficiency [6].

These findings confirm that pH critically influences the surface charge, solubility, and functionality of the active biomolecules extracted from Pine cone. Similar to observations in studies on Opuntia ficus-indica [60] and Aloe vera [18], our results demonstrate that acidic to neutral conditions generally favor adsorption and bridging mechanisms. However, in some cases, alkaline pH can enhance removal efficiency depending on the specific composition of the extract, although it may also induce electrostatic repulsion that reduces coagulation efficiency.

The settling time also has a significant and measurable effect on coagulation efficiency. As shown in Figure 4, maximum turbidity removal was achieved for PC-NaCl, PC-HCl, and PC-NaOH extracts after 120 min (Figure 4b–d). This can be explained by the fact that, after 120 min of treatment, the maximum amount of active coagulant agents is available in the aqueous solution, enhancing coagulation activity. In contrast, for the PC-H₂O extract, removal efficiency decreases significantly after 30 min of settling (Figure 4a). This is due to the reduced concentration of remaining suspended solid particles responsible for turbidity and the active coagulant agents in the extract. Therefore, more time is required for the active coagulant components to bind effectively to these suspended particles [58].

3.6. Response Surface

In the turbidity removal process, experimental factors such as coagulant dosage, settling time, and pH play a crucial role [61]. In Figure 5, Figure 6, Figure 7 and Figure 8, the 2D contour plots and 3D surface plots of the model illustrate the three experimental variables. They are plotted based on two factors while keeping the other factor at a fixed level. These plots can be used to explore the relationships between the variables.

3.6.1. Effect of PC-H₂O Dosage, pH, and Settling Time

According to Figure 5a,b, the contour plots (2D) and surface plots (3D) show that turbidity removal efficiency increases as the pH decreases from 8.5 to 6.5. The coagulant dosage takes a moderate value in the center, with a positive quadratic effect of both coagulant dosage and pH (Table 4). As indicated in Figure 5c,d, effective turbidity removal efficiency was observed within a settling time range of 30–120 min, with coagulant doses at minimum (10) and maximum (100) values, showing a positive linear effect of settling time, a positive quadratic effect of coagulant dosage, and a positive interactive effect between these two parameters (Table 4) in terms of p-values. Figure 5e,f shows that the best turbidity removal efficiency was achieved with a settling time between 30 and 90 min and a water pH of 6.5, with a positive linear effect of both pH and settling time (Table 4).

From these figures, a maximum turbidity reduction rate of approximately 67% was obtained under the following conditions: coagulant dosage between 10- and 20-mL L⁻¹, pH between 6.5 and 6.75, and settling time between 30 and 90 min.

3.6.2. Effect of PC-NaCl Dosage, pH, and Settling Time

It is clear from Figure 6a,b that turbidity removal efficiency increases as the pH varies from 6.5 to 6.75, with the coagulant dosage maintaining an average value of 50 mL/L. The influence of these factors on turbidity removal is primarily characterized by their positive quadratic effect.

The increase in settling time also leads to an increase in turbidity reduction efficiency, as shown in Figure 6c,d. With a coagulant dosage of 50 mL/L, the positive quadratic effect of coagulant dosage is observed. Similarly, Figure 6e,f shows that maximum turbidity removal is achieved with maximum settling time and minimum pH values, indicating a positive linear and quadratic effect of pH.

From these figures, a maximum turbidity reduction rate of approximately 40% to 45% was obtained under the following conditions: coagulant dosage between 30 and 70 mL/L, pH between 6.5 and 6.75, and settling time of 120 min.

3.6.3. Effect of PC-NaOH Dosage, pH, and Settling Time

According to Figure 7a,b, increasing the added coagulant dosage and moving away from the neutral pH range significantly reduces turbidity removal efficiency. Therefore, maximum turbidity removal is observed at minimal coagulant doses with a neutral pH between 7 and 7.5, indicating a positive quadratic effect of both coagulant dosage and pH (Table 4).

As shown in Figure 7c,d, significant turbidity removal efficiency is observed with coagulant doses between 10 and 50 mL/L and a maximum settling time of 120 min, showing a positive quadratic effect of coagulant dosage and a positive linear effect of settling time. For the interactions between pH and settling time, Figure 7e,f shows that turbidity removal efficiency is maximal when pH is in the neutral range and with a maximum settling time of 120 min, indicating a positive linear effect of these parameters as well as a positive quadratic effect of pH.

3.6.4. Effect of PC-HCl Dosage, pH, and Settling Time

Figure 8a,b shows that turbidity removal efficiency is maximal when the coagulant dosage is between 70 and 100 mL/L and the pH is between 8 and 8.5, indicating a positive linear effect of coagulant dosage. According to Figure 8c,d, it is clear that maximization of turbidity removal occurs at the maximum intervals of the coagulant dosage and pH operating range, which is confirmed by the positive linear effect of these two parameters as well as a positive interaction between them. Regarding Figure 8e,f, maximum turbidity removal is observed across the entire pH range studied, with maximum settling time values, showing a positive linear effect of settling time.

3.7. Optimization of Experimental Conditions and Validation of Polynomial Models

The determination of the optimal coagulant dosage, pH, and settling time for turbidity removal was carried out using the response surface optimization tool and the desirability function. For each extract used, the optimal point was identified (Figure 9).

For PC-H₂O, the best combination was obtained with a coagulant dosage of 100 mL/L at a pH of 6.50 and a settling time of 30 min. Under these conditions, the turbidity removal predicted by the fitted regression model was 75.28%, with a desirability of 1.000.

For PC-NaCl, the optimal combination was found with a coagulant dosage of 55.45 mL/L at a pH of 6.5 and a settling time of 120 min. Under these conditions, the predicted turbidity removal was 48.99%, with a desirability of 1.000.

For PC-NaOH, the best combination was found with a coagulant dosage of 28.18 mL/L at a pH of 7.48 and a settling time of 120 min. Under these conditions, the predicted turbidity removal was 74.88%, with a desirability of 1.000.

For PC-HCl, the optimal combination was obtained with a coagulant dosage of 100 mL/L at a pH of 8.5 and a settling time of 120 min. Under these conditions, the predicted turbidity removal was 80.66%, with a desirability of 1.000.

These results show that the optimal conditions vary depending on the pine cone extracts used as bio-coagulants. The PC-HCl extract demonstrated the best turbidity removal rate of 80.66%. This result is similar to that found by Benalia et al. [62], who reported that the HCl solvent was the best for reducing turbidity by 85.15% when treating drinking water with Aloe vera, compared to NaCl and NaOH.

The desirability of 1.000 for all optimal combinations indicates that the predictive models used are perfectly suited to estimate the efficiency of turbidity removal under the defined experimental conditions.

Once the optimal coagulation point was determined for the four extracts used, the regression models were validated through tests conducted under conditions corresponding to the optimal coagulant dose, pH, and settling time. The values predicted by the model were compared to those obtained experimentally, and the relative error was calculated.

Table 5. Validation of polynomial models.

Results Obtained	PC-H2O		PC-NaCl		PC-NaOH		PC-HCl
	Tu (NTU)	Turbidity Removal (%)	Tu (NTU)	Turbidity Removal (%)	Tu (NTU)	Turbidity Removal (%)	Tu (NTU)	Turbidity Removal (%)
Observed	8.8	73.25	16.88	48.69	9.58	70.88	7.05	78.57
Predicted		75.28		48.99		74/88		80.66
Relative error (%)		2.6		0.61		5.3		2.59

presents the results obtained for turbidity removal for the four extracts studied.

According to Table 5, it can be observed that the mathematical models developed are capable of satisfactorily predicting the turbidity removal from raw water. The relative error between the predicted values and the values obtained during experimentation for the PC-H₂O, PC-NaCl, PC-NaOH, and PC-HCl extracts were 2.6%, 0.61%, 5.3%, and 2.59%, respectively. It is noteworthy that all of these values are below 5%, which validates and confirms the reliability of the generated mathematical models.

3.8. Characterization of Treated Water Quality Under Optimal Conditions

Several water parameters were measured under the previously determined optimal conditions, including total hardness, total alkalinity, total suspended solids (SSs), UV₂₅₄, dry residue, salinity, and conductivity. These results are summarized in

Table 6. The physico-chemical parameters of water treated with PC-H₂O, PC-NaCl, PC-NaOH, and PC-HCl.

Parameters	Unit	Raw Water	PC-H2O		PC-NaCl		PC-NaOH		PC-HCl
		Value	Value	%	Value	%	Value	%	Value	%
Turbidity	NTU	32.5	8.8	73.25	16.88	48.69	9.58	70.88	7.05	78.57
Salinity	g L−1	0.9	0.7	/	1.2	/	0.7	/	0.6	/
Conductivity	µs cm−1	1724	722	/	2411	/	845	/	1128	/
UV254	cm−1	0.714	0.262	63.30	0.547	23.38	0.309	56.72	0.237	66.80
Total alkalinity	F°	16.5	8.6	/	8.8	/	19	/	0	/
Total hardness	F°	18.4	8.6	/	8.8	/	34.4	/	31	/
TSS	mg L−1	16.2	6.1	62.34	14.4	11.11	9.3	42.59	2.3	85.8
dry residue	mg L−1	1924.1	950.7	50.58	1910.4	0.71	915	52.44	921	52.13

.

According to Table 6, a variability in the effectiveness of Pine cone extracts used as bio-coagulants is observed. The PC-HCl extract demonstrates the best performance, reducing turbidity, total suspended solids (TSSs), and UV₂₅₄ by 78.57%, 85.8%, and 66.80%, respectively. This efficiency is attributed to the presence of long protein chains, total sugars, and polyphenols in the extract. These molecules promote pollutant aggregation and floc formation, enabling their removal through sedimentation or filtration [45].

Regarding alkalinity, the results in Table 6 show a decrease during treatment with PC-H₂O and PC-NaCl extracts (8 °F). This can be explained by the reaction between the released H+ ions and the alkaline ions (HCO₃⁻, CO₃²⁻, OH⁻) present in the water. Treatment with PC-HCl shows an alkalinity of 0 °F, which is due to the complete neutralization of alkaline ions by the H⁺ ions released by hydrochloric acid (HCl). Conversely, treatment with PC-NaOH increases alkalinity to 19 °F, attributed to the rise in hydroxyl ion (OH⁻) concentration, which reduces the concentration of hydrogen ions (H⁺), thereby increasing the water’s alkalinity.

For the effect of Pine cone extracts on total hardness, an increase in hardness (34.4 °F and 31 °F) is observed after treatment with PC-NaOH and PC-HCl extracts, respectively. This increase is explained by the rise in hydroxyl ions (OH⁻) released during the pH adjustment to 7.48 for PC-NaOH and 8 for PC-HCl. In contrast, using PC-H₂O and PC-NaCl extracts at an optimal pH of 6.5 results in a decrease in hardness to 8.6 °F and 8.8 °F. This reduction is linked to the reaction between H+ ions released by HCl used for pH adjustment and the HCO₃⁻, OH⁻, CO₃²⁻, Ca²⁺, and Mg²⁺ ions present in the water.

The results regarding dry residue indicate a nearly identical reduction for treatments with PC-H₂O, PC-NaCl, and PC-HCl extracts. This suggests that these treatments effectively removed a significant amount of solid matter (organic and/or mineral) from the water. Thus, a high dry residue content may indeed be attributed to the presence of mineral salts, heavy metals, or other undesirable substances, which are eliminated during treatment with these extracts.

3.9. Techno-Economic and Environmental Feasibility

Beyond evaluating the turbidity removal efficiency of Pine cone extract, this study also explores the economic and environmental potential of its large-scale use in water treatment. Pine cones, particularly from Pinus nigra, are abundant, renewable, and often considered forestry waste, making them an appealing, low-cost raw material.

The four extraction methods used in this work (PC-H₂O, PC-NaCl, PC-NaOH, and PC-HCl) rely on relatively simple, low-energy processes and affordable solvents, which supports their potential for cost-effective application. From a techno-economic standpoint, this approach benefits from the absence of high-temperature processing, minimal chemical use (especially for PC-H₂O and PC-NaCl), and the ease with which it could be scaled up for decentralized or small-scale treatment systems. Moreover, since the raw water used in the study came from an actual drinking water treatment plant, the process conditions and results reflect realistic, real-world scenarios.

From a life cycle perspective, the environmental impact of this bio-coagulant system is likely lower than that of traditional chemical coagulants. In particular, PC-H₂O and PC-NaCl extracts use non-toxic, biodegradable solvents and natural biomass, suggesting a favorable environmental profile. While PC-HCl and PC-NaOH involve more reactive chemicals, their environmental impacts could potentially be reduced through optimized usage and strategies such as solvent recovery or neutralization.

Overall, the findings not only confirm the technical effectiveness of Pine cone extracts for turbidity removal (with PC-HCl achieving up to 78.57% reduction), but also highlight their promise as sustainable and economically viable alternatives to synthetic coagulants. These results encourage further investigation through comprehensive techno-economic and life cycle assessments in future studies.

3.10. Comparative Study of Natural Coagulants for Water Treatment Applications

To assess Pine cone efficacy in turbidity removal, its performance was benchmarked against other natural coagulants documented in the literature, with the comparative results detailed in

Table 7. Comparison of turbidity removal efficiency of Pine cone extract and other bio-coagulants from the literature.

Bio-Coagulant	Optimal Dosage	pH	Settling Time (min)	Rapid Mixing Speed and Time (rpm/min)	Slow Mixing Speed and Time (rpm/min)	Turbidity Removal Efficiency (%)	References
Moringa peregrina seed	100 mg/L extract with 0.5 NaCl			200 rpm/1 min	35 rpm/30 min	88	[12]
Acanthus sennii C.	0.98 g L−1 extract prepared in distilled water	8.76		76.67	21.69	97.52	[63]
Moringa stenopetala B	0.82 g L−1 extract prepared in distilled water	8.6		73.68	28.00	98.37	[63]
Aloe vera L	1.65 g L−1 extract prepared in distilled water	8.94		70.96	32.64	96.74	[63]
Rice starch	4 g L−1 extract prepared in distilled water		15	50 rpm/2 min	30 rpm/15 min	72	[33]
Chitosan	18.25 mg L−1	7	18.1			94 ± 0.61	[64]
L. leucocephala seeds	120 mg L−1 extract prepared in distilled water	6.5	30	260 rpm/11 min	30 rpm/15 min	93.05	[65]
Albizia lebbeck	8.5 mL L−1, prepared with 10 g of 0.5 mm seeds at 4% NaCl			200 rpm/3 min	60 rpm/30 min		[66]
Sorghum	40 mg L−1 extract prepared in distilled water	2		200 rpm/2 min	30 rpm/25 min	87.73	[67]
Cassia fistula	160 mgL−1 extract prepared in distilled water		60	100 rpm/1 min	40 rpm/30 min	62.18	[68]
Aloe vera	0.5 mL L−1 extract prepared in HCl (0.05)	8	30	120 rpm/1 min	30 rpm/10 min	96.99	[69]
	0.5 mL L−1 extract prepared in distilled water	8	30			91.76	[69]
Watermelon rinds	200 mg L−1 powder, 100 μm granulation	7	60	300 rpm/2 min	60 rpm/20 min	99.21	[70]
Leucaena leucocephala	Distilled water With KCl (2 M) With KNO3 (1 M)		60	150 rpm/5 min	30 rpm/30 min	3.78 86.52 86	[71]
Avocado seed	300 mg L−1 powder, 63 μm granulation	8	/	/	/	99.64	[72]
Crab shell	17.5 mL L−1 extract prepared in distilled water	11.3	/	/	/	98.91	[73]
Maerua Decumbent	1 kg m−3 Powder with 0.4 mm granulation	5.56	52.31 min	180 rpm/3 min	30 rpm/20 min	99.2	[74]
Banana trunk peduncles	50 mg L−1 extract with 2.5M of sodium hydroxide (NaOH)	7	30	200 rpm/2 min	40 rpm/20 min	90.2	[75]
Guazuma ulmifolia	775.8 mg L−1 powder with 0.3 mm granulation	5		200 rpm/1 min	30 rpm/15 min	95.8	[48]
Pine cone	100 mL L−1 extract prepared in distilled water 55.45 mL L−1 extract prepared in NaCl (0.5M) 28.18 mL L−1 extract prepared in NaOH (0.05M) 100 mL L−1 extract prepared in HCl (0.5M)	6.5 6.5 7.48 8.5	30 120 120 120	160 rpm/3 min	30 rpm/20 min	73.25 48.69 70.88 78.57	This study

.

4. Conclusions

This study highlights the suitability of Pine cone extract as a sustainable bio-coagulant for turbidity reduction in raw water. Based on the experimental design, the key factors influencing turbidity removal are coagulant dosage, settling time, and pH. The models showed excellent fit, as indicated by the high coefficients of determination: R² = 0.985 and adj R² = 0.9579 for PC-H₂O, R² = 0.9725 and adj R² = 0.9231 for PC-NaCl, R² = 0.9475 and adj R² = 0.8529 for PC-NaOH and R² = 0.9829 and adj R² = 0.9522 for PC-HCl. Among the extracts studied, the HCl extract was the most effective for turbidity reduction. For the optimal turbidity removal efficiency of 78.57%, the ideal operating conditions are a coagulant dosage of 100 mL/L, pH 8.5, and a settling time of 120 min. These results highlight the importance of adjusting the pH, coagulant dosage, and settling time to achieve maximum efficiency. Furthermore, selecting the appropriate solvent for extracting the active molecules responsible for coagulation plays a critical role in raw water treatment. The findings from this research provide valuable insights for designing pilot or full-scale treatment plants, aiming to address raw water pollution. While Pine cone extract proved effective for turbidity removal, the results indicate that additional technologies, such as adsorption and filtration, are necessary to meet potable water standards and conform to environmental regulations. Moreover, future studies should evaluate the reusability of Pine cone extracts to determine their long-term applicability and operational sustainability.