Issue 3 (203)/2025

ALSE and ACS Style
Ameso, V.C.; Oduro-Kwarteng, S.; Onwuegbunam, D.O.; Vivan, E.L.; Ali, A.Y.; Mande, T.T. Evaluation of pollutant removal kinetics for greywater treatment in horizontal free surface flow constructed wetland. Journal of Applied Life Sciences and Environment 2025, 58 (3), 513-534.
https://doi.org/10.46909/alse-583189

AMA Style
Ameso VC, Oduro-Kwarteng S, Onwuegbunam DO, Vivan EL, Ali AY, Mande TT. Evaluation of pollutant removal kinetics for greywater treatment in horizontal free surface flow constructed wetland. Journal of Applied Life Sciences and Environment. 2025; 58 (3): 513-534.
https://doi.org/10.46909/alse-583189

Chicago/Turabian Style
Ameso, Vivien Chikogu, Sampson Oduro-Kwarteng,Donatus Obiajulu Onwuegbunam, Ezra Lekwot Vivan, Andesikuteb Yakubu Ali, and Timothy Terna Mande. 2025. “Evaluation of pollutant removal kinetics for greywater treatment in horizontal free surface flow constructed wetland.” Journal of Applied Life Sciences and Environment 58, no. 3: 513-534.
https://doi.org/10.46909/alse-583189

Evaluation of pollutant removal kinetics for greywater treatment in horizontal free surface flow constructed wetland

Vivien Chikogu AMESO¹, Sampson ODURO-KWARTENG², Donatus Obiajulu ONWUEGBUNAM^3*, Ezra Lekwot VIVAN⁴, Andesikuteb Yakubu ALI⁵  and Timothy Terna MANDE⁶

¹Department of Water Resource and Environmental Management, National Water Resource Institute (NWRI), P.M.B. 2309, Mando Road, Kaduna, Kaduna State, Nigeria 1; e-mail: vivienameso@yahoo.com

²Regional Water and Environmental Sanitation Centre, Kwame Nkrumah University of Science and Technology, UPO, Kumasi, Ghana; e-mail: sokwarteng@yahoo.com

³Forestry Research Institute of Nigeria/Federal College of Forestry Mechanization, Afaka, Kaduna, Nigeria

⁴Department of Environmental Management, Faculty of Environmental Sciences, Kaduna State University, Kaduna, Nigeria; e-mail: ezrav540@gmail.com

⁵Department of Environmental Management, Bingham University, Karu, Nigeria; e-mail: andesikutebali@gmail.com

⁶Department of General Studies, National Water Resource, Institute (NWRI), P.M.B. 2309, Mando Road, Kaduna, Kaduna State, Nigeria; e-mail: timomande@gmail.com

*Correspondence: donancy2001@yahoo.com 

Received: Sep. 21, 2025. Revised: Oct. 30, 2025. Accepted: Nov. 07, 2025. Published online: Dec. 04, 2025

ABSTRACT. Amidst a global freshwater shortage, reusing treated greywater is a viable option for supplementing non-potable demands. To ensure effective and sustainable treatment, understanding the kinetics of pollutant removal is essential for optimizing horizontal free surface flow constructed wetlands (HFSF). This study evaluates these kinetics for greywater in a continuous HFSF wetland planted with water hyacinth (Eichhornia crassipes) under hydraulic loading rates (HLRs). A pilot-scale HFSF wetland (12 m × 1 m × 1 m) constructed at the National Water Resources Institute, Kaduna was operated continuously at HLRs of 0.20, 0.25, and 0.30 m day^-1. Greywater samples were collected biweekly and analysed for biochemical oxygen demand (BOD₅), total phosphorus (TP), total suspended solids (TSS), and ammonium nitrogen (NH₄–N). First-order kinetic models (k–C), a modified first-order model with background concentration (k–C*), and a Continuous Stirred Tank Reactor (CSTR) were applied to derive rate constants and assess the model’s performance. First-order rate constants increased with HLR, indicating faster reaction kinetics; however, the overall efficiency of the pollutant removal slightly declined at higher HLRs due to the reduced retention time. TSS removal declined due to resuspension and NH₄–N removal was limited by oxygen deficiency at 0.30 m day^-1. The models demonstrated relatively better predictive agreement for TP and NH₄–N than for BOD₅ and TSS, reflecting non-linear processes. The 0.20 m day^-1 HLR provided the most sustainable performance through longer retention, effective biodegradation, sedimentation, and nitrification. The derived k values fall within global ranges, validating their use in wetland design.

Keywords: constructed wetland; greywater; pollutant removal; kinetics; water hyacinth.

 

INTRODUCTION

All wastewater generated from regular household activities, except that from toilet wastewater, constitutes greywater, which reportedly accounts for about 65% of total household wastewater (Khajvand et al., 2022). Greywater contains key nutrients such as potassium (K), phosphorus (P), and nitrogen (N), which occur in significant proportions, rendering it suitable for reuse after a preliminary treatment (Al-Jayyousi, 2001). With today’s rapid rise in the global population, especially in Nigeria, large amounts of wastewater are being generated within households and improperly disposed of, thus contaminating the environment. Environmental and public health problems such as eutrophication, groundwater pollution, and breeding of disease vectors are associated with untreated greywater discharge in many urban and peri-urban settlements of sub-Saharan Africa. Treating and reusing greywater represents an important approach to reduce the demand on freshwater when used for non-potable applications such as lawn and farm irrigation, especially in water-limited regions. Greywater treatment for reuse promotes sustainable living through the responsible use of water and the protection of both surface water and groundwater resources by reducing pollution discharge into them.

Nigeria has renewable freshwater resources that amount to about 286 billion m³ annually (WRI and CSEA, 2023). However, the corresponding per capita freshwater resources have experienced a steady decline towards water scarcity, which has been attributed largely to rapid population rise and the associated increase in water demand (World Bank, n.d.). This has dropped from about 1,328 to 1,011 m³ year^-1, a 24% decline between 2012 and 2021.

Therefore, reusing treated greywater presents a viable option for supplementing non-potable uses such as irrigation and domestic cleaning. This would reduce the pressure on freshwater resources and help achieve sustainable water management (Khajvand et al., 2022). Despite the evident potential for GWT&R, Nigeria’s institutional framework has remained too weak and fragmented to effectively support decentralized greywater treatment and reuse. This deficiency is exacerbated because low public awareness and negative perceptions limit adoption.

Yet, the economic benefits arising from reduced freshwater demand and lower water bills, alongside environmental gains such as enhanced protection of groundwater resources and reduced eutrophication, provide strong motivation for both institutional commitment and public adoption (Abubakar, 2017). Similar evidence from sub-Saharan Africa highlights the growing relevance of wastewater reuse in enhancing water security and environmental sustainability, and reinforces the need to close the persistent gap between research findings and practical implementation (Qadir et al., 2020).

Natural wetlands (NWs) as simple, cost-effective, and efficient nutrient removal systems perform well in tropical and subtropical climates, with ease of use and requiring little maintenance (Vymazal, 2007, 2011; Gunasekara and Dissanayake, 2022). The functions of NWs can be replicated by horizontal free-water surface flow constructed wetlands (HFWSF systems) by directing wastewater to move laterally through vegetated zones, where pollutants are removed through the combined action of plants, microbial communities, and the filtering capacity of the substrate (Aylan et al., 2023a).

Our limited knowledge of the functional roles of different plants for wastewater treatment makes the selection task very challenging: the choice of plant significantly affects the operation and effectiveness of HFSF systems. Eichhornia crassipes (water hyacinth) has been widely used in water purification because it produces much biomass and its vast root system decomposes into organic materials that harbor microorganisms, which biodegrade organic pollutants, transform nutrients and heavy metals, and form biofilms that enhance overall contaminant removal (Munjeri et al., 2016; Ajibade et al., 2013). While the pollutant removal potential of constructed wetland systems is well-documented, its kinetics under continuous flow treatment conditions in tropical sub-Saharan Africa remain underexplored.

Understanding the treatment kinetics, mechanisms, and pollutant removal is necessary to improve the efficiency and usability of HFSF systems. Much of the focus on water hyacinth in constructed wetlands has been on pollutant removal rates through pilot and batch tests, but the research on pollutant removal dynamics in continuous flow systems is still limited. This stems from the lack of understanding of the breakdown mechanisms of the pollutants during treatment, which impedes the design and optimization of constructed wetlands and their potential for scaling up in tropical subSaharan Africa. GWT&R is increasingly being promoted in water-scarce regions of the world as a way to sustain water management; however, in sub-Saharan Africa, its practical application is limited.

Previous evaluations of these kinetics in constructed wetlands, such as those of Soares et al. (2022) and Tang et al. (2023) confirmed the suitability of first-order models of pollutant removal, though these were mainly in temperate or mixed climates. Comprehensive analyses of the kinetics of continuous horizontal free-surface flow systems in tropical environments remain limited. Hence, this study provides new insights by quantifying the first-order rate constants and model-performance metrics (NOF, ME) across multiple hydraulic loading rates, offering empirical evidence to guide design optimization under tropical sub-Saharan conditions. Building on recent advances in horizontal flow wetland design and greywater treatment optimization (Aylan et al., 2023b), this study is, therefore, significant, with the objective of evaluating the kinetics of pollutant removal of greywater in a continuous HFSF CWL planted with water hyacinth (Eichhornia crassipes). This makes it one of the few efforts to provide experimental evidence for large-scale application in Nigeria, and the study findings would provide insights for design optimization and large-scale applications.

 

MATERIALS AND METHODS

Study area

The study was conducted at the National Water Resources Institute (NWRI), situated in Kaduna, Nigeria, at latitude N10º 34’44.2 and longitude E07º 25’18.2, at an elevation of about 586 m (Alimi et al., 2021). Kaduna is situated within the Northern Guinea savannah ecological zone, and typically experiences tropical weather, with a wet season that lasts from April to October and a dry season from November to March. The annual mean rainfall of Kaduna is 1196 mm (Okafor et al., 2024), with mean temperatures of 19ºC, 26ºC, and 33ºC minimum, average, and maximum scales, respectively (Adamu et al., 2024). Kaduna was chosen as the study area on the basis of its representation of the Northern Guinea savanna climate and the availability of an infrastructure for experiments with a constructed wetland. The location of NWRI Kaduna is shown in Figure 1.

 

 

Kinetic modeling

Model 1: First-order kinetics with a plug-flow assumption (k–C model)

The k–C model establishes a baseline understanding of pollutant removal performance, and was selected to quantify the relationship between influent and effluent pollutant concentrations assuming ideal flow conditions and negligible background concentrations. It is expressed by equations (1) and (2) (Kadlec and Knight, 1996). Equation 1 predicts the effluent concentration from the influent concentration, hydraulic loading rate (HLR), and the first-order rate constant, while Equation 2 provides a means of estimation using observed influent and effluent data.

where C_in is the concentration of the pollutant in the influent (mg L^-1), C_out is the concentration of the pollutant in the effluent (mg L^-1), HLR is the hydraulic loading rate (m day^-1), and K₁ is the first-order area-based removal rate constant (m day^-1).

Model 2: Modified first-order kinetics with a plug-flow assumption (k–C* model)

A k–C* model was applied to account for residual pollutants that persist in constructed wetlands. This model evaluates the removal kinetics under conditions where non-zero background concentrations (C^∗) exist. Such concentrations include residual BOD, TSS, ammonium nitrogen (NH₄–N), and phosphorus (P), which are naturally generated within wetland cells. The expressions for the model are Equation 3 and Equation 4 (Kadlec and Knight, 1996; Kadlec and Wallace, 2009):

where C^* denotes the non-zero background concentration (mg L^-1), C_in is the concentration of the pollutant in the influent (mg L^-1), C_out is the concentration of the pollutant in the effluent (mg L^-1), and K₂ represents the removal rate constant based on the area, following a first-order decay process (m day^-1).

Model 3: CSTR flow assumption with first-order kinetics

Pollutant removal was evaluated by applying the Continuous Stirred Tank Reactor (CSTR) model. A complete mixing within the wetland cell was assumed. Also, the wetland volume is assumed to be constant because of the lined cells and steady inflow–outflow, while pollutant concentrations are assumed to be uniformly distributed throughout the system. The model further assumes first-order kinetics, where removal is directly proportional to the concentration of the pollutant. The relationship is expressed as Equation 5 and Equation 6 as reported by Levenspiel (1972):

These formulas have been applied in modified form to give the first-order area-based rate constant expressed as Equation 7 for wetlands (Kadlec and Wallace, 2009; Rousseau et al., 2004).

where C_in and C_out are influent and effluent concentrations (mg L^-1), Q_v is the volumetric flow rate, HLR is the hydraulic loading rate (m day^-1), and K₃ is the first-order area-based removal rate constant (m day^-1).

Experimental set-up

A horizontal free surface flow (HFSF) constructed wetland was developed at the National Water Resources Institute, Kaduna, Nigeria, to treat greywater generated and collected from bathrooms, kitchens, and laundries of households within the NWRI community. An HFSF wetland was chosen over vertical subsurface flow system because it requires less complex construction, allows direct plant growth on the water surface, and is more adaptable to fluctuating greywater loads in urban communities with limited resources (Alao et al., 2021; Raphael et al., 2023; Mustapha et al., 2018).

The HFSF wetland system shown in Figure 2 was constructed with dimensions 12 m by 1 m by 1 m in length, width, and depth, respectively, in accordance with recommended design ranges for horizontal flow constructed wetlands, which specify depths of 0.3–1.0 m and length-to-width ratios of 10:1 to 20:1 (Kadlec and Wallace, 2009; Vymazal, 2011).

The system components are an inlet, a 1.5-m detention basin, and three treatment cells lined in sequence with impermeable polymer to prevent seepage, all maintained in open-air conditions.

The HFSF was operated at three hydraulic loading rates (HLRs): 0.20, 0.25, and 0.30 m day mg L^-1, which fall within the recommended design and operational ranges of 0.10–0.40 m day^-1 for horizontal flow wetlands in warm climates (Arden and Ma, 2018; Rahman et al., 2023), and selected to represent low, medium, and relatively high flow conditions for evaluating the influence of hydraulic variation on the efficiency of the pollutant removal.

The detention basin serves to promote the settling of coarse solids and to regulate the inflow before distribution into the treatment cells. Greywater first entered the detention basin and was then piped to the wetland cells, where treatment occurred with the aid of wetland vegetation. To achieve different hydraulic loading rates (HLRs) in the wetlands, the flow rates were calculated based on the surface area of the wetland unit. The greywater was distributed to the HSFS wetland cell to achieve targeted HLRs of 0.20, 0.25, and 0.030 (m day^-1). This was achieved by means of a constant head arrangement.

The treatment vegetation was water hyacinth, chosen for its rapid growth, high nutrient uptake efficiency, tolerance to varying pollutant loads, and proven performance in tropical constructed wetlands for greywater treatment. It was then allowed to get established for three months before continuous operation for four months. To account for any potential environmental influence on the performance of the wetland, the ambient temperature and rainfall were recorded throughout the period of operation.

 

 

The treatment’s effectiveness was evaluated by monitoring the parameters of the water quality, which include biochemical oxygen demand (BOD), total phosphorus, and total suspended solids. Sampling was done following the procedures outlined in APHA, AWWA, WEF (2012).

The volumes of influent and effluent were measured volumetrically every two to three days to calculate the average daily discharge for each unit in the system for the purpose of a detailed performance analysis of the constructed wetland under the three HLRs.

Sample collection / laboratory testing

Samples were collected biweekly from the influent and effluent of the HFSF constructed wetland unit operated at each hydraulic loading rate. The collections were done by means of plastic containers that had been sterilized and rinsed with the greywater sample before use. These samples were collected for analysis after three months, to ensure the stability of the operation of the system. The concentrations of biochemical oxygen demand (BOD₅), total phosphate (TP), total suspended solids (TSS), and ammonium nitrogen (NH₄–N) were determined according to the Standard Methods for the Examination of Water and Wastewater (APHA, AWWA and WEF, 2012), corresponding to Methods 5210 B, 4500-P, 2540 D, and 4500-NH₃, respectively.

All analyses were carried out in triplicate (n = 3) to ensure precision of measurements as no replicate treatment units were constructed; the temporal replication was achieved through repeated biweekly sampling during the study period. The influent and effluent wastewater flows were measured for each HFSF unit, enabling the calculation of the daily mean discharge.

The pollutant mass loading, removal efficiency, and first-order kinetic parameters were subsequently estimated using the measured flow and concentration data. A summary of the characteristics of the influent greywater is presented in Table 1.

Data analysis

Estimating the rate constant of a kinetic reaction

The rate constants (k) for biochemical oxygen demand, chemical oxygen demand, total soluble solids, and total phosphorus were estimated by means of a regression model, using the Microsoft Excel Office 2021 data analysis tool. The k–C, k–C*, and CSTR models were selected because they represent the most common first-order approaches for describing pollutant removal in constructed wetlands.

Their mathematical formulations assume steady-state conditions with continuous flow, which correspond to the hydraulic behavior of the horizontal free-surface flow system used in this study. This estimation was performed for three different models at each Hydraulic Loading Rate (HLR).

The statistical analysis employed linear regression as the optimization technique (Babatunde et al., 2011). Biweekly sampling was carried out over the monitoring period to provide sufficient data points for the regression analysis and to minimize random variability.

Comparison of the three kinetic models

The comparison of the performances of the models in terms of the accuracy of estimated values for each greywater parameter was done using a Normalized Objective Function (NOF) (Equation 8 and Equation 9) and the Model Efficiency (ME) (Equation 10) (Gikas et al., 2011). The NOF provides a measure of the differences between predicted and measured values, ranging from 0 to ∞, while ME assess the relative magnitude of the residual variance in comparison to the variance of the measured data.

where, RMSE = root mean square error, NOF = normalized objective function, ME is the model efficiency, m_i = measured (observed) value of parameter at point i, p_i = predicted (modeled) value of parameter at point i, m_mean = the mean of the measured values, and N = the total number of observations.

Assessing the efficiency of the wetland treatment

The impact of the Hydraulic Loading Rate (HLR) on the performance of the wetland treatment was assessed by computing the Mass Loading Rate (MLR) and Mass Removal Rate (MRR) using Equation 11 and Equation 12, respectively.

where C_in is the concentration of the pollutant at the inlet of the constructed wetland technology, and C_out is its concentration at the outlet.

The normality of characteristics of the influent and effluent was assessed using the Microsoft Excel Office 2021 data analysis tool. The significance of treatment differences between wetland systems operated at different HLRs for the removal of ammonium nitrogen, biochemical oxygen demand, total suspended solids, and total phosphate was determined using a regression test at a 95% confidence level (p < 0.05). The statistical inferences were drawn based on repeated biweekly observations.

 

RESULTS AND DISCUSSION

Rate constant of the kinetic reaction (k)

The measured concentrations of the influent and effluent, as presented in Table 1 and Table 2, respectively, served as the empirical basis for deriving the kinetic rate constants. The model-predicted values for the effluent were subsequently computed using the first-order expressions to evaluate the model’s performance and validate the dynamics of the removal.

The estimated first-order rate constants (k₁, k₂, k₃) for BOD₅, TP, TSS, and NH₄-N evaluated across three kinetic models (k–C, k–C*, and CSTR) at hydraulic loading rates (HLRs) of 0.20, 0.25, and 0.30 m/day are presented in Table 3. A one–way analysis of variance (ANOVA) with Tukey’s HSD indicated significant differences (p < 0.05) between the models for all parameters. The differences in rate constants for different HLRs were significant (p < 0.05) only for NH₄–N, whereas variations for BOD₅, TP, and TSS were not statistically significant (p > 0.05), indicating that the kinetics of the removal of the ammonium were more sensitive to hydraulic changes than those of the organic or particulate removal.

Generally, the values of k increased as the HLR increased. The values of R² ranged from 0.93 to 0.99, which shows the robustness of the regression models and predictive fits of the first-order models. The pollutants BOD₅ and TSS exhibited the highest values of k, which reflects a rapid biodegradation and sedimentation of organic and particulate matter; TP showed moderate values, while NH₄–N had the lowest, indicating slower nutrient transformation. The CSTR model consistently produced higher values of k than the k–C and k–C* models, which confirms its superior representation of the continuous-flow conditions typical of horizontal free-surface flow (HFSF) wetlands.

For BOD₅, the rate constants increased progressively across the three HLRs and models, showing that higher organic loading enhances microbial activity and first-order biodegradation. As pointed out by Rahman et al. (2023), this is particularly so under warm and well-aerated conditions. For TP, k also increased consistently with HLR. An implication of this is that adsorption and plant uptake were effective under increased flow contact with media and vegetation. Wang et al. (2023) observed that increase in k with HLR would occur until the sorption sites or uptake capacities begin to saturate. For TSS, the results show a marked increase in k with HLR for Models 1 and 3, but Model 2 produced a lower k (0.2500 m day^-1) at HLR = 0.30 m day^-1 compared to 0.25 m day^-1. This is a system-specific deviation from normal, and may be attributed to particle resuspension and reduced filtration or settling efficiency under higher flow velocities which occurs where hydraulic shear overcomes deposition, reducing apparent removal despite a higher inflow load. This phenomenon has been observed in some constructed wetland performances under varying HLRs (Rahman et al., 2023). For NH₄–N, the values of k increased with HLR for models 1 and 2, while in Model 3, it slightly decreased at HLR = 0.30 compared to 0.25. The result reflects oxygen limitation under higher hydraulic loads, where the increased load surpasses the capacity for oxygen transfer or nitrification, as observed by Lott et al. (2024) in vertical flow wetland studies treating landfill leachate.

Generally, the pollutant removal followed the order TSS > BOD₅ > TP > NH₄–N. This indicates that the HFSF wetland was more efficient at removing organic and suspended solids than nutrients. The observed increase in k with HLR indicates the importance of balancing hydraulic loading and retention time for optimal wetland performance, as well as the applicability of first-order kinetic models, particularly CSTR, for performance evaluation and design optimization of tropical greywater treatment wetlands.

Assessment of the model’s performance

Figure 3 (a – d) presents a comparison between the measured and predicted first-order rate constants (k, m day⁻¹) for BOD₅, TP, TSS, and NH₄–N using the k–C, k–C^*, and CSTR models. In all the cases, the CSTR yielded slightly higher k than the other two, indicating better agreement between the measured and the predicted values.

 

Table 1
Summary of measured influent (greywater) concentrations

Quality Indicator	Mean ± SD	Min	Max	N
BOD₅	41.6 ± 5.5	34.2	52.8	36
TP	2.8 ± 0.15	2.5	3.1	36
TSS	26.0 ± 2.4	22.3	30.5	36
NH₄–N	2.5 ± 0.19	2.1	2.9	36

Units: BOD₅ (mg O₂L^-1); TP (mg L^-1), TSS (mg L^-1), and NH₄–N (mg NL^-1)
SD: standard deviation; Min: minimum value; Max: maximum value; N: number of observations

 

Table 2
Mean measured effluent concentrations at various HLRs

Quality indicator	Effluent at various HLRs
	0.20 m day-1	0.25 day-1	0.30 day-1
BOD5	0.199 ±0.039	0.243 ±0.049	0.280 ±0.03
TP	0.144 ±0.029	0.144 ±0.028	0.21 ±0.05
TSS	0.224 ±0.045	0.231 ±0.046	0.36 ±0.11
NH4–N	0.096 ±0.019	0.109 ±0.01	0.15 ±0.02

Units: BOD₅ (mg O₂L^-1); TP (mg L^-1), TSS (mg L^-1), and NH₄–N (mg NL^-1)

 

Table 3
Estimated rate constants (k₁, k₂, and k₃) of the kinetic models under various hydraulic loading rates (HLRs)

Quality Indicators	HLR (m day-1)	Kinetic reaction rate constants (k) (m/day)			R2
		Model 1 (k–C)	Model 2 (k-C*)	Model 3 (CSTR)
BOD5	0.20	0.1586 ± 0.0012b	0.1944 ± 0.0014a	0.242 ± 0.0036b	0.96–0.98
	0.25	0.1982 ± 0.0009b	0.2420 ± 0.0108a	0.3040 ± 0.0010b
	0.30	0.2179 ± 0.0013b	0.3239 ± 0.0015a	0.3440 ± 0.0010b
TP	0.20	0.1151 ± 0.0006b	0.1211 ± 0.0005a	0.1556 ± 0.0005b	0.97–0.98
	0.25	0.1438 ± 0.0017b	0.1514 ± 0.0008a	0.1944 ± 0.0011b
	0.30	0.1615 ± 0.0005b	0.1697 ± 0.0004a	0.2140 ± 0.0004b
TSS	0.20	0.1794 ± 0.0010b	0.1843 ± 0.0005a	0.2905 ± 0.0003b	0.93–0.95
	0.25	0.2243 ± 0.0036b	0.2297 ± 0.0011a	0.3631 ± 0.0027b
	0.30	0.3495 ± 0.0010b	0.2500 ± 0.0013a	0.3907 ± 0.0010b
NH4–N	0.20	0.0771 ± 0.0008a	0.0771 ± 0.0015a	0.0941 ± 0.0003b	0.94–0.99
	0.25	0.0964 ± 0.0005a	0.0964 ± 0.0006a	0.1176 ± 0.0002b
	0.30	0.1107 ± 0.0002b	0.1357 ± 0.0001a	0.1272 ± 0.0003b

BOD₅: Biochemical oxygen demand; TP: Total phosphorus; TSS: Total suspended solids: NH₄–N: Ammonium nitrogen

 

The close similarity of measured and predicted values across models confirms that the first-order kinetic assumptions adequately describe pollutant removal in the continuous HFSF system. Minor variations of the parameters reflect differences in the characteristics of the substrate, the pollutant’s biodegradability, and flow dynamics within the wetland, consistent with previous findings by Soares et al. (2022).

The predicted values for each model show a close resemblance to the measured concentrations within the range of 0.20–0.30 m/day hydraulic loading rates (HLRs), indicating that the models adequately described pollutant removal within this operational range. Additionally, the values of the NOF and ME provided in Table 4 further validate that the predictions for BOD, TP, TSS, and NH₄–N closely align with the actual measured values. This is consonant with the observations of Soares et al. (2022), who reported a close match between predicted and measured values in constructed wetland systems using first-order kinetics.

The values of the ME for BOD and TSS were 0.00, which indicates that the models only provided a basic fit and did not capture additional variability in the measured data. By contrast, TP (0.16) and NH₄–N (0.12) exhibited ME above the 0.10 threshold, and this suggests a better agreement between predicted and observed values.

This trend is a confirmation of the model’s greater ability to predict phosphorus and ammonium nitrogen dynamics than organic matter (BOD) and suspended solids removal. As widely documented by Kadlec and Wallace (2009), nutrient (N and P) removal processes in free water surface and subsurface wetlands are largely governed by first-order kinetics because microbial transformation and adsorption dominate the dynamics of the system.

 

 

Table 4
Evaluation criteria (NOF and ME) for kinetic model performance

Parameter	Model	Normalized objective function (NOF)	Model efficiency (ME)
BOD5	k1	0.01	0.00
	k2	0.01	0.00
	k3	0.00	0.00
TP	k1	0.01	0.16
	k2	0.01	0.16
	k3	0.01	0.16
TSS	k1	0.00	0.00
	k2	0.00	0.00
	k3	0.00	0.00
NH4–N	k1	0.00	0.12
	k2	0.00	0.12
	k3	0.00	0.12

BOD₅: Biochemical oxygen demand, TP: Total phosphorus, TSS: Total soluble solids, NH₄–N: Ammonium nitrogen

 

The values of the ME obtained in this study imply that the models can adequately describe nutrient (TP and NH₄–N) removal in the studied HLRs, but further calibration would be required for reliable simulation of organic and particulate matter removal. This is because the removal of organic matter and suspended solids often involve non-linear processes such as sedimentation, filtration, clogging, and plant uptake, which cannot be fully captured by simple first-order models (Soares et al., 2022; Ventura et al., 2022). Practically, this implies that confidence in nutrient predictions is higher for this dataset, whereas BOD and TSS predictions may require recalibration of rate constants, testing of alternative kinetic models, or coupling with hydrodynamic residence time distribution (RTD) models to better capture particulate settling and non-ideal flow.

Wetland treatment effectiveness

Greywater characteristics and treatment performances

Table 5 presents the pollutant removal efficiencies achieved under different HLRs in the HFSF constructed wetland for the mean influent and effluent concentrations of BOD₅, TP, TSS, and NH₄–N. The HFSF wetland exhibited varying pollutant removal efficiencies at hydraulic loading rates (HLRs) of 0.2, 0.25, and 0.30 m/day. Influent BOD₅ (41.6 ± 5.528 mg O₂L^-1) was significantly reduced, with the lowest level (0.199 ± 0.039 mg L^-1) at an HLR of 0.2 m day^-1.

However, effluent BOD₅ increased to 0.280 ± 0.03 mg O₂L^-1 at an HLR of 0.30 m day^-1, indicating reduced efficiency at higher flows. More efficient removal at lower HLRs is attributed to longer retention time, enhancing oxygen transfer, microbial activity, and sedimentation (Zou et al., 2022; Zhang et al., 2024).

For TP, the influent level of 2.8 ± 0.146 mg L^-1 dropped to 0.144 ± 0.029 mg L^-1 at 0.2 m day^-1, and remained at 0.144 ± 0.028 mg L^-1 at 0.25 m day^-1, but increased to 0.21 ± 0.05 mg L^-1 at 0.30 m/day. Optimal removal at lower HLRs was mainly due to chemical precipitation, biological uptake, and adsorption onto wetland media under favorable conditions.

Recent studies also show that reactive-media wetlands employing reactive media such as steel slag or iron scrap can achieve phosphorus removal efficiencies above 90% under favorable retention times (Wu et al., 2023; Zhang et al., 2024).

TSS followed a similar pattern, with the influent concentration (26 ± 2.419 mg L^-1) decreasing to 0.224 ± 0.045 mg L^-1 at 0.2 m day^-1 and rising to 0.36 ± 0.11 mg L^-1 at 0.30 m day^-1. The decline in performance at higher HLRs may result from reduced settling time and re-suspension of solids. Higher removal at lower HLRs is connected to effective sedimentation, filtration through substrate, and extended detention time (Tang et al., 2023; Wu et al., 2023). Exceptionally low TSS values were observed at 0.20 and 0.25 m day^-1 HLRs, and this can be attributed to a combination of favorable operating conditions, namely, extended hydraulic retention times (HRT), low influent TSS load (26 ± 2.42 mg L^-1), stable environmental conditions during the experimental period, and an efficient media filtration system.

NH₄–N removal followed a variable pattern. The influent concentration of 2.5 ± 0.189 mg L^-1 was reduced to 0.096 ± 0.019 mg L^-1 at 0.2 m day^-1. The highest effluent concentration (0.109 ± 0.01 mg L^-1) notably occurred at 0.25 m day^-1, whereas 0.15 ± 0.02 mg L^-1 was recorded at 0.30 m day^-1.

As reported by Zou et al. (2022) and Zhang et al. (2024), the observed variations may be linked to fluctuations in nitrification rates, influenced by oxygen availability, microbial adaptation, and the dynamic balance between HRT and organic loading. Effective ammonium nitrogen removal at lower HLRs is supported by improved contact time, which enhances the activity of nitrifying bacteria that leads to better ammonia oxidation (Zou et al., 2022; Zhang et al., 2024).

Overall, the treatment performance of the HFSF wetland system was most effective at an HLR of 0.2 m day^-1, where the lowest effluent concentrations for all measured pollutants were recorded. This confirms a longer retention time as the dominant driver of pollutant reduction, particularly for BOD₅, TP, TSS, and NH₄–N. The decline in efficiency with increasing HLR shows the hydraulic limitation of the system, whereby higher throughputs shorten reaction time and disrupt sedimentation, nitrification, and adsorption.

This underscores the critical role of the hydraulic regime as well as the need for optimal HLRs to enhance greywater treatment.

Mass loading and removal rates

Table 6 provides the average Mass Loading Rates (MLRs), Mass Removal Rates (MRRs), and the associated statistical relationships between these parameters for BOD₅, TP, TSS, and NH₄–N across the three HLRs. The results demonstrate that increasing the HLR leads to a corresponding increase in mass loading for all parameters. This is expected due to the higher volumetric input. It can be observed that the MRRs did not consistently increase with rising HLR. BOD₅, for instance, showed a positive MRR of 4.625 ± 0.362 g m^–² day^-1 at 0.20 m day^-1, which increased to 5.781 ± 0.452 g m^–² day^-1 at 0.25 m day^-1, and further increased to 7.64 ± 0.60 g m^–² day^-1 at 0.30 m day^-1.

This suggests that the system maintained strong removal efficiency despite elevated flow rates. The progressive increase shows that organic degradation and associated microbial activity were not adversely affected by higher loadings within the tested range. As reported by Guo et al. (2024) and Chen et al. (2024), this reflects the robustness of carbon oxidation processes in free water surface wetlands.

For TP, the removal performance showed a consistent improvement with increasing HLR: 0.238 ± 0.01 g m^–² day^-1 at 0.20 m day^-1, 0.297 ± 0.02 g m^–² day^-1 at 0.25 m day^-1, and 0.329 ± 0.00 g m^–² day^-1 at 0.30 m day^-1. An implication of this steady increase is that the treatment efficiency was sustained as the phosphorus removal pathways such as sedimentation, adsorption, and plant uptake were not saturated under the prevailing loading conditions (Zeng et al., 2022; Chen et al., 2024).

TSS and NH₄–N recorded their lowest MRRs at the lowest HLR of 0.20 m/day and increased progressively as the HLRs increased: TSS had an MRR of 0.162 ± 0.106 g m^–² day^-1 at 0.20 m day^-1, which rose to 0.202 ± 0.132 at 0.25 m day^-1 and further to 0.272 ± 0.04 g m^–² day^-1 at 0.30 m day^-1. As observed by Zeng et al. (2022) and Domínguez-Solís et al. (2025), the gradual rise in TSS removal with higher flow rates suggests that settling and filtration processes remained effective within the wetland matrix, while the removal of NH₄–N gained from increased substrate availability for nitrification. This is, however, subject to oxygen limitations.

The correlation between MLR and MRR was generally strong and linear for the lower HLRs (0.20 and 0.25 m day^-1), particularly for BOD₅, TSS, and NH₄–N, with coefficients of determination (R²) ranging 0.95 to 0.99. This suggests that at these lower loading rates, the performance of the wetland system was predictable and efficient. It can be observed that, at an HLR of 0.30 m day^-1, the MRRs did not improve in proportion to the increasing MLRs. This indicates a possible saturation point or reduced treatment efficiency due to hydraulic overloading. Global meta-analysis suggests that HLRs above 0.45 m day^-1 tend to mark thresholds beyond which removal drops significantly (Chen et al., 2024).

While the wetland system demonstrated more effective and stable pollutant removal at HLRs of 0.20 and 0.25 m day^-1, the reduced MRRs and inconsistencies observed at 0.30 m day^-1 emphasize the importance of optimizing the HLR to balance the input loading with the treatment capacity of the system.

Wetland design considerations

The recommended kinetic design parameters across the different hydraulic loading rates for the horizontal free surface flow constructed wetland system are summarized in Table 7. All three models reliably estimated these values for wetland design and performance prediction. As the HLR increased from 0.20 to 0.30 m day^-1, the values of k rose across all pollutants and models. TP increased from 0.1151 to 0.1605 m day^-1 (Model 1), and the trends were the same for BOD₅, TSS, and NH₄–N. The ranges (BOD₅: 0.1586–0.2174; TSS: 0.1794–0.2575; TP: 0.1151–0.1605; NH₄–N: 0.0771–0.1251 m day^-1) fall within the global values, where the values of k for BOD₅ lie between 0.10–0.30 m day^-1, TP between 0.05–0.20 m/day, and NH₄–N around 0.05–0.15 m day^-1 (Ury et al., 2023; Chen et al., 2024).

These findings suggest that the kinetics improve at higher HLRs, although reliability may decline due to hydraulic short-circuiting or reduced contact time. The values of R², of 0.96–0.99, indicate robust fits.

Despite kinetic gains at 0.30 m day^-1, the 0.20–0.25 m day^-1 range proved to be the most sustainable. Model 1 is recommended for TSS and TP, Model 2 for TP and NH₄–N, and Model 3 for NH₄–N optimization. All the models are found to be dependable when site-specific factors are taken into consideration. The differences are a reflection of hydrodynamic controls, with k–C and k–C* approximating plug flow and CSTR capturing mixing (Kadlec and Wallace, 2009; Biswal and Balasubramanian, 2022).

At lower HLRs (0.20–0.25 m day^-1), consistent values of k indicate optimal treatment and transitional behavior between plug flow and CSTR, highlighting the hybrid hydrodynamics of HFSF wetlands.

Limitations and future work

Despite the good model fits, total phosphorus (TP) removal could decrease over time due to substrate saturation and possible legacy soil release, while NH₄–N kinetics remain highly dependent on oxygen transfer and temperature variation.

Although the rate constants (k) increased with the HLR, the slight drop in removal efficiency at 0.30 m day^-1 shows that faster kinetics do not guarantee better treatment when retention time is shortened. The system performed best at moderate flows (0.20–0.25 m day^-1), where hydraulic balance and pollutant removal were optimized.

Future research should:

• Monitor long-term phosphorus binding capacity and potential release from saturated media.
• Incorporate oxygen- and temperature-driven models for better capturing of NH₄–N transformation.
• Use tracer tests to assess non-ideal hydraulic flows and residence time distribution (RTD); and

Evaluate full-scale systems under varying seasonal and loading conditions to validate the model’s applicability for tropical design optimization.

 

Table 5
Mean influent and effluent concentrations with corresponding removal efficiencies under different HLRs

Quality indicator	Influent	Effluent at various HLRs			% Removal
		0.20 m day-1	0.25 day-1	0.30 day-1	0.20 m day-1	0.25 day-1	0.30 day-1
BOD5	41.6 ± 5.528	0.199 ± 0.039	0.243 ± 0.049	0.280 ± 0.03	99.52	99.42	99.33
TP	2.8 ± 0.146	0.144 ± 0.029	0.144 ± 0.028	0.21 ± 0.05	94.67	94.67	92.22
TSS	26 ± 2.419	0.224 ± 0.045	0.231 ± 0.046	0.36 ± 0.11	99.14	99.11	98.62
NH4–N	2.5 ± 0.189	0.096 ± 0.019	0.109 ± 0.01	0.15 ± 0.02	96.16	95.64	94.00

Influent and effluent concentrations: BOD₅ (mg O₂L^-1); TP (mg L^-1), TSS (mg L^-1), and NH₄–N (mg NL^-1)

 

Table 6
Statistical summary of mass loading rates (MLRs) and mass removal rates (MRRs) at varying HLRs

Quality indicator	Rate (g m-2 day-1)	Hydraulic Loading Rate (m day-1)			R2
		0.20	0.25	0.30
BOD5	MLR	3.70 ±1.209	4.625±1.512	5.949 ±1.6	0.99
	MRR	4.625±0.362	5.781±0.452	7.64±0.60	0.98
TP	MLR	0.306±0.089	0.382±0.02	0.416±0.03	0.95
	MRR	0.238±0.01	0.297±0.02	0.329±0.00	0.97
TSS	MLR	16.875±5.190	21.094±6.49	23.37±0.12	0.97
	MRR	0.162±0.106	0.202±0.132	0.272±0.04	0.98
NH4–N	MLR	0.341±0.086	0.426±0.108	0.465±0.00	0.96
	MRR	0.162±0.106	0.202±0.132	0.283±0.01	0.96

 

Table 7
Recommended kinetic design parameters (k, m day^-1) for HFSF wetlands at different HLRs

Parameter	HLR (m day-1)	k–C	k–C*	CSTR	R2 (range)
BOD5	0.20	0.1586	0.1944	0.2420	0.96–0.99
	0.25	0.1983	0.2429	0.3040
	0.30	0.2174	0.2693	0.3460
TP	0.20	0.1151	0.1211	0.1556	0.98–0.99
	0.25	0.1438	0.1514	0.1944
	0.30	0.1605	0.1671	0.2436
TSS	0.20	0.1794	0.1838	0.2905	0.98–0.99
	0.25	0.2243	0.2297	0.3631
	0.30	0.2575	0.2653	0.4087
NH4–N	0.20	0.0771	0.0771	0.0941	0.98–0.99
	0.25	0.0964	0.0964	0.1176
	0.30	0.1251	0.1275	0.1341

HFSF: Horizontal Free Surface Flow wetland; TP: Total phosphorus; TSS: Total suspended solids; NH₄–N: Ammonium nitrogen.

 

CONCLUSIONS

In this study, greywater treatment was evaluated in a horizontal free surface flow wetland at hydraulic loading rates (HLRs) of 0.20, 0.25, and 0.30 m day^-1. The first-order rate constants (k) increased with the HLR for BOD₅, TP, TSS, and NH₄–N, with strong fits (R² = 0.93–0.99). Although higher hydraulic loading enhanced reaction kinetics, the overall pollutant removal efficiencies declined slightly at 0.30 m day⁻¹ due to reduced retention time and oxygen limitation. Higher loading therefore improved the reaction rate for BOD₅ and TP, but not their net removal efficiency. TSS declined under higher flows due to resuspension and reduced settling, while NH₄–N was constrained by oxygen limitation at 0.30 m/day. The models proved to be more reliable for predicting TP and NH₄–N than BOD and TSS. This is attributable to the non-linear and particulate-dominated nature of the latter parameters.

The relation between mass loading and removal remained linear at 0.20–0.25 m day^-1 but weakened at 0.30 m day^-1, indicating hydraulic overloading and reduced treatment stability. An HLR of 0.20 m day^-1 achieved the most sustainable pollutant reductions by extending retention and supporting biodegradation, sedimentation, and nitrification. The derived values of k fall within the global ranges, thus validating their use in wetland design and performance prediction under tropical conditions. Future studies should address long-term phosphorus dynamics, oxygen-sensitive NH₄–N removal, and hydrodynamic validation for system scaling and optimization.

 

Funding: There was no external funding for this study.

Author contributions: Conceptualization: VCA, SOK; Methodology: VCA, SOK, ELV, AYA; Analysis: VCA, DOO, TTM; Investigation: VCA, TTM; Resources: VCA, SOK; Data curation: DOO, VCA; Writing: VCA; Review: DOO, ELV, AYA; Supervision: SOK. All authors declare that they have read and approved the publication of the manuscript in this present form.

Data availability statement: The data presented in this study are available on request from the corresponding author.

Conflicts of interest: The authors declare no conflicts of interest regarding the publication of this paper.

 

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