Abstract
This research evaluated the microbial status and compliance level of wastewater treated through a nature-based phytoremediation system in Rwanda. Physicochemical parameters such as pH, temperature, total suspended solids (TSS), total dissolved solids (TDS), biochemical oxygen demand (BOD), chemical oxygen demand (COD), total nitrogen (TN) and total phosphorus (TP) were measured and analyzed. The microbial contents, such as total heterotrophic bacteria count, fecal coliform bacteria, total coliform bacteria, E. coli, and helminth eggs, were also investigated. Morphological identification and biochemical tests were conducted via standard techniques. After water treatment in different chambers, the physicochemical parameters were analyzed, and the mean values of the microbial indicators were all within the compliant limits of the Rwanda established water quality standards. The results revealed a decrease in the pH, TSS, BOD₅, COD, TP, HE and microbial counts as the wastewater passed through the initial and middle stages. However, there was a statistically significant decrease in the physicochemical parameters and microbial indicators as the water passed through the final stages of water treatment. These relative and logarithmic decreases indicate polishing and pathogen removal efficiency at the end of the treatment. However, the reduction in microbial counts was limited, indicating areas for process improvement. Therefore, the National Police College phytoremediation system is effective at removing both organic pollutants and pathogenic microorganisms.
Keywords: Compliance, Microbial, Phytoremediation, Rwanda, Wastewater
Introduction
Rwanda has made significant strides in terms of environmental protection and sustainable development, with wastewater (ww) management being a critical component of the national environmental agenda. The wastewater generated is discharged into various surfaces and groundwater bodies which present severe threats of water pollution at the local, national and global levels. In many countries, the ww treatment processes required to recover these waters to acceptable quality standards are either nonexistent or inadequate. Water is key to economic growth and development; hence, strict laws in alignment with global protocols for sewage treatment before dumping into water bodies or open environments to ensure the safety of life, the sustainability of the environment, improved water management and enhanced overall ecosystem health have been passed [1].
Sustainable development goal 6 declares the importance of achieving clean water and sanitation for all, and to achieve this goal, the world must reduce freshwater pollution by eliminating dumping and minimizing the release of hazardous chemicals into water bodies [2]. According to the UNICEF report 2023, Rwanda strives to achieve this goal, and only 57% of the population has access to safe drinking water [3]. The growing challenge of water resource management is attributed to the growing population and robust quest for socioeconomic development. Tremendous efforts have been made to launch a Rwandan National Policy (RNP) for the management of the water and sanitation sector, which consists of strategies and programs for the development and rehabilitation of human resources and social and economic infrastructures [4]. Consequently, ww treatment through nature-based solutions (NBSs) or biological processes is a key part of robust policy.
Relentless global effort is evolving through extensive research in search of the best ww treatment techniques, which focus on key issues involving ww purification, reuse, availability and improvement of the quality for human consumption via sustainable NBS. Apart from the global standards of the WHO, the Rwanda Standards Board (RSB) and the Rwanda Environment Management Authority (REMA) have established water quality standards [5] that specify maximum permissible limits for various physicochemical and microbiological parameters in treated ww before discharge into the environment.
Nature-based solution (NBS) systems, particularly phytoremediation (phytoextraction, rhizofiltration, phytodegradation, rhizodegradation and phytostabilization) systems, have gained prominence as eco-friendly alternatives to conventional ww treatment methods. These systems utilize plants and associated microorganisms to remove, degrade, or sequester contaminants from wastewater while providing additional ecosystem services. Sustainable NBS, as an evolved method of ww treatment, employs innovative technologies such as biological treatment, membrane technologies, resource recovery, circular economic approaches (integrated systems that recover water, energy, and nutrients), and smart water management systems essential for conserving water resources and reducing environmental pollution [6] without causing harm to the environment. It is therefore important that feasible techniques for tackling water pollution and protecting the ecosystem from the harmful impacts of pollution in the present-day environment are intelligently developed. The National Police College (NPC) in Rwamagana District represents an institutional facility requiring effective ww treatment solutions that are economically viable and environmentally sustainable.
Novelty and contribution
Previous studies in Rwanda focused on laboratory testing of ww and testing physico-chemical parameters in wastewater samples collected at the influents and effluents of constructed wetland during rainy and dry seasons [7, 8]. By evaluating the role of microbial processes involved in wastewater treatment and compliance levels of wastewater treatment in Rwanda, this research highlights the unique contributions of the current study and emphasizes its significance in addressing urgent environmental challenges in urban wastewater treatment systems. Only a few studies have evaluated microbial reduction along with the physico-chemical parameters during ww treatment in Rwanda. The influence of the microbial activities engaged in this process and the lack of data available limit the ability to optimize and develop this nature-based solution for wider application in Rwanda and similar situations.
The impact of the microbial processes involved in wastewater treatment and environmental water quality, as well as the lack of available data, limit the ability to refine and develop this nature-based approach for wider application in Rwanda and comparable contexts. The authors are certain that this study will offer insightful information and be an important tool for strengthening initiatives to lower water pollution and encourage efficient water reuse techniques in Rwanda’s urban areas.
Materials and methods
The study area
This study was carried out at a domestic facility in Rwamagana District located in the Eastern Province of Rwanda, within the coordinates of 1° 54’ 12. 471’’ S and 30° 25.796 ‘’ E. (latitude − 1.953513, longitude 30.438644.) at the elevation of 1,476.45 meters above sea level. (Fig. 1). This study site is located approximately 50 kilometers east of Kigali, the country’s capital city [6]. The region is characterized by a tropical subhumid climate with two distinct seasons: wet and dry. The monthly temperature ranges from 22°C − 23°C, and the annual rainfall ranges from 1100 mm to approximately 2000 mm during the wet and dry seasons.
Fig. 1.
Map of Rwanda showing the study site area (NPC, Rwamagana)
Ethics approval and consent to participate
Not applicable.
Design of the wastewater (WW) treatment system
The WW treatment system consists of seven (7) chambers/units, which include the influent chamber (Inlet), anaerobic baffled reactor/bioreactor (ABR), first black stone flotation (FBF), shallow aeration basin (SAB), second black stone flotation (SBF), phytoremediation bed (PB), and outlet/shallow maturation basin (SMB). The influent chamber receives the ww directly, and the ABR is built with reinforced concrete and designed to receive ww and accompanying solid waste in volume (Fig. 2). The chamber consists of a series of interconnected compartments within a single reactor designed to regulate the flow of incoming ww and retain sludge efficiently, while the digestate is released in ww. This configuration enhances the separation of bacterial trophic groups and provides high tolerance to both hydraulic and organic shock loads. Physical retention and anaerobic microbial biodegradation produce the digestate within the membrane of the bioreactors. The liquid digestate is then discharged after accumulating to a certain volume through an outlet into the FBF (Fig. 3). The FBF belt in the system is designed to retain flocs and optimize the digestate flow rate while allowing the injection of atmospheric air. It is bedded with black stones of various sizes and shapes in convoluted unit-like structures that increase the ww retention time to enable the absorption of contaminants through the large surface area of black stones. It also enables ww to interface with the multidimensional rough surfaces of black stones, which are suitable habitats for microbes, thereby increasing the ww retention time. The black stones traditionally purify water by absorbing impurities and contaminants in soluble substances within a solution on a proper surface through easing the area available for adsorption.
Fig. 2.
Anaerobic baffled reactor/bioreactor (ABR) chamber
Fig. 3.
First blackstone flotation (FBF)
These SABs are units with dimensions of (4 × 3 × 1.5) m and are built with concrete cement blocks with built-in cells (compartmentalized to facilitate the integration of atmospheric air into the ww) within the structure, which allows for mechanical agitation of the ww while it circulates from one cell to another (Fig. 4). This process promotes flocculation and supports aerobic microbial activity, which is essential for organic matter breakdown. This system allows for oxygen transfer, mixing, biological decomposition and nitrification. Additionally, anaerobic conditions that would otherwise produce hydrogen sulfide and other odorous compounds are prevented. The SBF in the system is designed to retain flocs and optimize the digestate flow rate while allowing the injection of atmospheric air. It is bedded with black stones of various sizes and shapes in convoluted unit-like structures that increase the ww retention time to enable the absorption of contaminants through the large surface area of black stones. It also enables ww to interface with the multidimensional rough surfaces of black stones that are suitable habitats for microbes (Fig. 5), thereby increasing the ww retention time over a large surface area ratio.
Fig. 4.
Shallow aeration basin (SAB)
Fig. 5.
Second blackstone flotation (SBF)
The phytoremediation bed (PB) is the core treatment unit responsible for both nitrification and denitrification processes. The bed features compartments with moderate flow rates that hold ww beneath specially selected plant species, i.e., vetiver (Chrysopogon zizanioides) Source: French & Maynard, 2022).
These grow on a simulated substrate composed of four distinct, juxtaposed layers. Wastewater flows through the treatment bed via vertical or horizontal subsurface pathways or occasionally via surface flow. A combination of surface and subsurface flow systems is referred to as amphibian flow. As shown in Fig. 6, the PB is built with concrete cement blocks of dimensions (8 × 12 × 1.5) m with cells within which plant species grow. This green approach detects, degrades, and removes various types of pollutants from the environment. The plant species take up pollutants from ww and detoxify their toxic effects.
Fig. 6.
Phytoremediation bed (PB)
SMBs (Fig. 7) are shallow, open basins that facilitate natural disinfection through prolonged solar exposure, serving as a form of tertiary treatment. The effluent from the aeration basin may either be discharged into the natural environment or redirected for reuse, such as in landscape irrigation. This is where the treated ww exits the entire system of purification after an extended retention time at the phytoremediation and aeration chambers.
Fig. 7.
Outlet/shallow maturation basin (SMB)
Sampling techniques
To obtain a representative sample, a total of 140 WW samples were collected. For ten months, duplicate wastewater samples were taken once a month from each chamber. The study used the average values (readings) from the analysis of the samples. To reduce impacts on the sample’s physical and chemical integrity, grab sampling was used. At approximately 40–60% dept, the composite sample was collected. In accordance with standard protocols, the grab technique was utilized to directly fill the sample container and systematically collect WW samples from seven chambers/units, beginning at the exit chamber and working backward toward the influent unit [9]. WW samples were collected in two sterile well-labeled sample containers (1000 cm3 bottles) placed in an ice pack (4 °C), to avoid any changes in the targeted parameters. The WW was transported to the laboratory and analyzed within 72 h. Additionally, about 200 cm3 of WW was collected in a 250 cm3 beaker for on-site testing. A HACH HQ40d multimeter measured temperature, pH, and total dissolved solids (TDS) by immersing the probes into the WW samples, and the readings were recorded accordingly. Each monthly sample was collected after the instruments had been recalibrated. (Fig. 8)
Fig. 8.
Flow process of black water treatment at the Gishari police training school
Wastewater analysis
Standard methods were used for data collection and analysis in this research. Physicochemical parameters such as pH, temperature, total suspended solids (TSS), total dissolved solids (TDS), biochemical oxygen demand (BOD), chemical oxygen demand (COD), total nitrogen (TN) and total phosphorus (TP) were measured and analyzed. The microbial contents, such as total heterotrophic bacteria (THB) count, fecal coliform (FC) count, total coliform (TC) count, E. coli count, and Helminth egg (HE) count, were also investigated. The physicochemical parameters and microorganisms detected in the final stage of WW treatment were compared to the Rwanda standards wastewater treatment. Morphological identification and biochemical tests were conducted via standard techniques.
Data analysis
Removal efficiency which refers to the effectiveness of a treatment process in removing contaminants or pollutants from wastewater was determine using Chi-Square(χ²) and expressed as a percentage. Chi-square normalization was used to determine the most statistically significant decrease in the chambers by comparing the percentage (%) reduction i.e. Observed values (O) with the regulatory limit i.e. expected values (E). The statistical assumption is that the Null hypothesis (H0):Percentage reduction occurs in equal proportions (H0: p1 = p2), The Significance levels are (a) for percentage (%) reduction within a chamber degree of freedom (df1) @ 0.05 = 3.841, 0.01 = 6.635, and (b) for the percentage (%) reduction across chambers df6 = 0.05 = 12.592, p 0.01 = 16.812. Regression analysis was used to determine statistically significant reduction with (R² = >0.9).
Results
Physicochemical parameters and compliance limits at various treatment stages (chambers)
Eight (8) physicochemical parameters of the wastewater tested are shown in Table 1 and will be discussed as acidity, temperature, total solids, organic matter and nutrients in terms of wastewater treatment and Rwandan discharge effluent standard (i.e. RS).
Table 1.
Mean results of physicochemical analysis and Rwanda compliance limits
| S/No | Parameter | Chambers/Treatment Units | RS 219:2013 Limit | Compliance Status | ||||||
|---|---|---|---|---|---|---|---|---|---|---|
| Inlet | ABR | FBF | SAB | SBF | PB | SMB RE% | ||||
| 1 | pH | 7.8 ± 0.4 | 7.6 ± 0.3 | 7.4 ± 0.2 | 7.2 ± 0.4 | 7.2 ± 0.1 | 7.1 ± 0.4 | 7.1 ± 0.2 NA | 6.5–8.5 | ✓ Compliant |
| 2 | Temp (°C) | 23.2 ± 2.1 | 22.9 ± 1.9 | 22.7 ± 1.5 | 22.3 ± 1.5 | 22.3 ± 0.4 | 21.3 ± 1.9 | 21.3 ± 1.4 NA | < 30 | ✓ Compliant |
| 3 | TSS (mg/L) | 120 ± 45 | 50 ± 28 | 28 ± 12 | 27 ± 9 | 26 ± 10 | 25 ± 28 | 22 ± 881.6 | 50 | ✓ Compliant |
| 4 | TDS (mg/L) | 1220 ± 28 | 1120 ± 58 | 908 ± 7 | 708 ± 7 | 606 ± 15 | 409 ± 28 | 304 ± 35 75.0 | 500 | ✓ Compliant |
| 5 | BOD₅ (mg/L) | 285 ± 52 | 173 ± 35 | 85 ± 15 | 72 ± 35 | 60.5 ± 42 | 52.5 ± 15 | 32 ± 9 88.8 | 50 | ✓ Compliant |
| 6 | COD (mg/L) | 680 ± 78 | 380 ± 58 | 199 ± 28 | 179 ± 58 | 162 ± 68 | 120 ± 58 | 72 ± 28 89.4 | 100 | ✓ Compliant |
| 7 | TN (mg/L) | 69.5 ± 12 | 57.4 ± 10 | 12.25 ± 7 | 12.18 ± 7 | 12.14 ± 7 | 12.04 ± 7 | 12.01 ± 5 82.7 | 30 | ✓ Compliant |
| 8 | TP (mg/L) | 76.96 ± 3.2 | 64.16 ± 2.1 | 2.33 ± 0.8 | 1.64 ± 3.2 | 2.16 ± 2.1 | 2.08 ± 0.7 | 1.95 ± 0.5 60.7 | 5 | ✓ Compliant |
RS Rwandan standard, NA Not Applicable
Acidity (pH)
The highest mean pH (7.8 ± 0.4) was recorded at the inlet, while the lowest mean value of 7.1 ± 0.2 was recorded at the SMB (the outlet) which was in compliance with Rwanda Standard Limit which ranges from 6.5 to 8.5.
Temperature
The highest temperature results 23.2 ± 2.1 was observed in the inlet chamber, with the most decreased temperature of 21.3 ± 1.4 observed at the SMB (the outlet) chamber and this is compliant with the RS for < 30 °C for wastewater effluents.
Total solids (TDS and TSS)
The TDS results revealed that the amount of TDS decreased from 1,220 mg/L at the inlet chamber to 304 mg/L at the SMB (outlet) chamber with ORE of 75%. The TSS results revealed that the amount of TSS decreased from 120 mg/L at the inlet chamber with a standard deviation of 45 to 22 mg/L with a standard deviation of 8 at the SMB (outlet) chamber with ORE of 81.6%. The TDS and TSS at the SMB chamber were compliant with the RS of 500 mg/L and 50 mg/L respectively.
Organic matter (BOD and COD)
The highest BOD concentration of 285 mg/L with standard deviation of 52 was observed in the inlet chamber while the least BOD concentration of 32 mg/L with standard deviation of 9 was seen in the SMB (outlet) chamber. Similarly, the highest COD concentration of 680 mg/L with standard deviation of 78 was observed in the inlet chamber while the least COD concentration of 72 mg/L with standard deviation of 28 was seen in the SMB (outlet) chamber. Both BOD and COD at the SMB chamber were compliant with the RS of 50 mg/L and 100 mg/L with ORE of 88.8% and 89.4%.
Nutrients (TN and TP)
The total Nitrogen ranged from 69.5 ± 12 in the inlet chamber to 12.01 ± 5 in the SMB chamber. The total phosphorus ranged from 4.96 ± 3.2 in the inlet chamber to 1.95 ± 0.5 in the SMB chamber. Both TN and TP in the SMB chamber were compliant with the RS of 30 mg/L and 5 mg/L with ORE of 82.7% and 60.7%.
Removal efficacy of physicochemical pollutants in different treatment stages/chambers
The wastewater treatment system in this study revealed a progressive, statistically significant reduction in pollutants from Inlet to SMB (Fig. 9). The Early stages (Inlet, ABR) had high pollution loads, and regression analysis revealed very small slopes and low R² values of 0.40 and 0.45 indicating stability with no significant reduction in pH and temperature However, the middle stages (FBF, SAB, SBF) showed a sharp decline, especially in TP and COD and in the final stages (PB, SMB), compliance was achieved with SMB fully meeting regulatory limits. Regression analysis demonstrates that the treatment train is highly effective, with regression slopes and R² values (> 0.9) showing strong, consistent pollutant removal trends.
Fig. 9.
Removal efficacy of physicochemical pollutants in different treatment stages/ chambers
Morphological identification and biochemical tests
Morphological identification and biochemical tests revealed some suspected microbes, including bacteria Escherichia coli, Staphylococcus spp., Enterococcus spp., Klebsiella spp., Pseudomonas spp., Salmonella spp., Streptococcus spp., and Bacillus spp. and protozoans Amoeba spp., Giardia spp., Cryptosporidium spp., Balantidium spp., Ascariasis spp., Euglena spp., Spirogyra spp. and Paramecium spp (Table 2). The bacteria species were consistently present across the seven (7) chambers (Inlet → SMB). The biochemical tests revealed catalase, coagulase, oxidase, indole and motility characteristics.
Table 2.
Microbial analysis summary
| S/No | Unit | Suspected bacteria | Suspected protozoa/parasites | Morphology of the protozoa/parasites |
|---|---|---|---|---|
| 1 | Inlet | Escherichia coli, Staphylococcus spp., Enterococcus spp., Klebsiella spp., Pseudomonas spp., Salmonella spp., Streptococcus spp., Bacillus spp. | Amoeba spp, Giardia spp, Cryptosporidium spp, Balantidium spp | Irregular, oval, ovular, oblong |
| 2 | ABR | Same bacterial set as Inlet (E. coli, Staphylococcus, Enterococcus, Klebsiella, Pseudomonas, Salmonella, Streptococcus, Bacillus) | Amoeba spp, Giardia spp, Cryptosporidium spp, Balantidium spp | Irregular, oval, ovular, oblong |
| 3 | FBF | Same bacterial set as above | Amoeba spp, Giardia spp, Cryptosporidium spp, Balantidium spp | Irregular, oval, ovular, |
| 4 | SAB | Same bacterial set as above | Amoeba spp, Giardia spp, Cryptosporidium spp, Balantidium spp, Paramecium spp (appears here) | Irregular, oval, ovular, oblong, slipper-shaped |
| 5 | SBF | Same bacterial set as above | Amoeba spp, Giardia spp, Cryptosporidium spp, Balantidium spp, Paramecium spp | Irregular, oval, ovular, oblong, slipper-shaped |
| 6 | PB | Same bacterial set as above | Amoeba spp, Giardia spp, Cryptosporidium spp, Balantidium spp, Paramecium spp, Ascariasis spp, Euglena spp, Spirogyra spp | Irregular, oval, ovular, oblong, flagellated, spiral, slipper-shaped, |
| 7 | SMB | Same bacterial set as above | Amoeba spp, Giardia spp, Cryptosporidium spp, Balantidium spp, Paramecium spp | Irregular, oval, ovular, oblong, flagellated, spiral, slipper-shaped, |
Microbial Indicators at various treatment stages
The decrease of the bacterial counts, indicator organism and helminths eggs counts in various treatment chambers (Table 3) is described below.
Table 3.
Microbial indicators at various treatment stages (chambers)
| S/No | Microbial indicator | Chambers/Treatment Units | RS 219:2013 Limit | Compliance Status | ||||||
|---|---|---|---|---|---|---|---|---|---|---|
| Inlet | ABR | FBF | SAB | SBF | PB | SMB | ||||
| 1 | TC (CFU/100 mL) | 3.04 × 107 | 3.48 × 106 | 1.01 × 106 | 3.36 × 105 | 7.20 × 104 | 5.20 × 103 | 6.80 × 102 | < 10,000 | ✓ Compliant |
| 2 | FC (CFU/100 mL) | 1.50 × 107 | 2.32 × 106 | 1.51 × 105 | 1.00 × 105 | 6.50 × 104 | 5.50 × 104 | 2.2 × 10³ | < 5,000 | ✓ Compliant |
| 3 | THB (CFU/mL) | 5.44 × 105 | 6.11 × 104 | 5.64 × 104 | 3.91 × 104 | 2.28 × 104 | 2.x103 | 1.5 × 102 | 500 | ✓ Compliant |
| 4 | E. coli (CFU/100 mL) | 3.84 × 105 | 2.60 × 104 | 1.34 × 104 | 6.10 × 103 | 3.80 × 103 | 1.80 × 103 | 0.23 × 102 | ≤ 126 | ✓ Compliant |
| 5 | HE (eggs/L) | 48 ± 8 | 22 ± 4 | 17 ± 4 | 15 ± 4 | 10 ± 4 | 7 ± 1 | < 1 | < 1 | ✓ Compliant |
Total coliform (TC) counts
The TC counts of 3.04 × 107mL were observed in the inlet chamber while the least TC counts of 6.80 × 102 was recorded in the SMB (outlet chamber), and it was compliant with the Rwandan standard for ww treatment of < 10,000 CFU/100 mL.
Fecal counts (FC)
Fecal count in the inlet chamber was 1.50 × 107 CFU/100 mL while that of the outlet chamber SMB was 2.2 × 10³ in compliance with the RS maximum limit of < 5,000 CFU/100 mL.
Total heterotrophic bacteria (THB) Counts
Total heterotrophic bacteria count of 5.44 × 105 CFU/mL was recorded at the inlet, while THB of 1.5 × 102 CFU/mL was recorded at the SMB (outlet) chamber which agrees with the RS THB limit of 500 CFU/mL.
Indicator organism (E. coli)
In the inlet chamber, 3.84 × 105 CFU/100 mL of the indicator organism, E. coli was reported while 0.23 × 102 CFU/100 mL was recorded at the SMB (outlet) chamber in compliance with the RS limit of ≤ 126 CFU/mL.
Helminths eggs
The helminths eggs in the inlet chamber were 48 eggs/L with a standard deviation of 8. In the SMB (outlet) chamber, no helminths eggs were observed and this in compliance with the RS limit of ≤ 1 eggs/L in effluent of wastewater.
Microbial reduction at various treatment stages (units/chambers)
Table 4 shows the reduction of microbial load in various treatment chambers and is described in terms of total coliform count, fecal count, total heterotrophic bacteria count, the indicator organism, E. coli, and helminths eggs.
Table 4.
Microbial responses to phytoremediation at various treatment stages (units/chambers)
| S/No | Parameter | Chambers/ units |
± error Values |
Differences between units | (%) Reduction of pollutants | (Χ²) value |
Key insights in the treatment unit |
|---|---|---|---|---|---|---|---|
| 1 | TC (cfu/ml | Inlet | 3.04 × 10⁷ | Inlet → ABR Δ = −2.69 × 10⁷ | 88.6 (3.04 × 10⁷ → 3.48 × 10⁶) | 0.94 | Steady decline, with the biggest drop at SBF → PB |
| ABR | 3.48 × 10⁶ | ABR → FBF Δ = −2.47 × 10⁶ | 71.0(3.48 × 10⁶ → 1.01 × 10⁶) | 0.54 | |||
| FBF | 1.01 × 10⁶ | FBF → SAB Δ = −6.74 × 10⁵ | 66.7 (1.01 × 10⁶ → 3.36 × 10⁵) | 0.48 | |||
| SAB | 3.36 × 10⁵ | SAB → SBF Δ = −2.64 × 10⁵ | 78.6(3.36 × 10⁵ → 7.20 × 10⁴) | 0.67 | |||
| SBF | 7.20 × 10⁴ | SBF → PB Δ = −6.68 × 10⁴ | 92.8 (7.20 × 10⁴ → 5.20 × 10⁴) | 1.14 | |||
| PB | 5.20 × 10³ | PB → SMB Δ = −4.52 × 10³ | 87.0(5.20 × 10³ → 6.80 × 10²) | 0.88 | |||
| SMB | 6.80 × 10² | End | ORE = 99.9% | ||||
| 2 | FC (cfu/ml | Inlet | 1.50 × 10⁷ | Inlet → ABR Δ = −1.27 × 10⁷ | 84.5 (1.50 × 10⁷ → 2.32 × 10⁶) | 0.81 | Final SMB stage is decisive for compliance (< 5,000) |
| ABR | 2.32 × 10⁶ | ABR → FBF Δ = −2.17 × 10⁶ | 93.5 (2.32 × 10⁶ → 1.51 × 10⁵) | 1.19 | |||
| FBF | 1.51 × 10⁵ | FBF → SAB Δ = −5.1 × 10⁴ | 33.8 (1.51 × 10⁵ → 1.00 × 10⁵) | 0.18 | |||
| SAB | 1.00 × 10⁵ | SAB → SBF Δ =−3.5 × 10⁴ | 35.0 (1.00 × 10⁵ → 6.50 × 10⁴) | 0.19 | |||
| SBF | 6.50 × 10⁴ | SBF → PB Δ = −1.0 × 10⁴ | 15.4 (6.50 × 10⁴ → 5.50 × 10⁴) | 0.07 | |||
| PB | 5.50 × 10⁴ | PB → SMB Δ =−5.28 × 10⁴ | 96.0 (5.50 × 10⁴ → 2.2 × 10³) | 1.40 | |||
| SMB | 2.20 × 10³ | End | ORE = 99.8% | ||||
| 3 | THB (cfu/ml) | Inlet | 5.44 × 10⁵ | Inlet → ABR Δ = −4.83 × 10⁵ | 88.23(5.44 × 10⁵→ 6.11 × 10⁴) | 0.95 | Final SMB stage is decisive for compliance at 500 |
| ABR | 6.11 × 10⁴ | ABR → FBF Δ = −4.7 × 10³ | 76.92(6.11 × 10⁴ → 5.64 × 10⁴) | 0.04 | |||
| FBF | 5.64 × 10⁴ | FBF → SAB Δ =−1.73 × 10⁴ | 30.67(5.64 × 10⁴ → 3.91 × 10⁴) | 0.16 | |||
| SAB | 3.91 × 10⁴ | SAB → SBF Δ =−1.63 × 10⁴ | 41.68(3.91 × 10⁴ → 2.28 × 10⁴) | 0.23 | |||
| SBF | 2.28 × 10⁴ | SBF → PB Δ = −2.08 × 10⁴ | 91.22 (2.28 × 10⁴ → ~2.00 × 10³) | 1.06 | |||
| PB | ~ 2.00 × 10³ | PB → SMB Δ =−1.85 × 10³ | 92.5(~ 2.00 × 10³ → 1.50 × 10²) | 1.12 | |||
| SMB | 1.50 × 10² | End | ORE = 99.7% | ||||
| 4 | E. coli (cfu/ml) | Inlet | 3.84 × 10⁵ | Inlet → ABR Δ =−3.58 × 10⁵ | 93.2 (3.84 × 10⁵ → 2.60 × 10⁴) | 1.17 | SMB ensures compliance (≤ 126) |
| ABR | 2.60 × 10⁴ | ABR → FBF Δ = −1.26 × 10⁴ | 48.5 (2.60 × 10⁴ → 1.34 × 10⁴) | 0.29 | |||
| FBF | 1.34 × 10⁴ | FBF → SAB Δ =−7.3 × 10³ | 54.5 (1.34 × 10⁴ → 6.10 × 10³) | 0.34 | |||
| SAB | 6.10 × 10³ | SAB → SBF Δ =−2.3 × 10³ | 37.7 (6.10 × 10³ → 3.80 × 10³) | 0.21 | |||
| SBF | 3.80 × 10³ | SBF → PB Δ = −2.0 × 10³ | 52.6 (3.80 × 10³ → 1.80 × 10³) | 0.32 | |||
| PB | 1.80 × 10³ | PB → SMB Δ =−1.78 × 10³ | 98.7 (1.80 × 10³ → 23) | 1.89 | |||
| SMB | 2.30 × 10¹ | End | ORE = 99.9% | ||||
| 5 | HE (eggs/L) | Inlet | 48 ± 8 | Inlet → ABR Δ =−26 | 54.2 (48 → 22) | 8.45 | Gradual decline, with SMB achieving full compliance (< 1 egg/L) |
| ABR | 22 ± 4 | ABR → FBF Δ = −5 | 22.7 (22 → 17) | 0.78 | |||
| FBF | 17 ± 4 | FBF → SAB Δ =−2 | 11.8 (17 → 15) | 0.13 | |||
| SAB | 15 ± 4 | SAB → SBF Δ =−5 | 33.3 (15 → 10) | 0.78 | |||
| SBF | 10 ± 4 | SBF → PB Δ = −3 | 30.0 (10 → 7) | 0.53 | |||
| PB | 7 ± 1 | PB → SMB Δ =−6 | > 85 (7 → <1) | 18.0 | |||
| SMB | < 1 | End | ORE = 97.9% |
Total coliform count
Table 4 reveals that the largest log reduction occurred between SBF → PB (≈ 1.14 log units), and the rate of decrease revealed that the TC decreased dramatically from 3.04 × 10⁷ → 3.48 × 10⁶ in the first step (Inlet → ABR), and a steady reduction continued across units, with the most pronounced microbial removal occurring between SBF → PB. The position of the greatest decrease was between Inlet → ABR (6.80 × 102 CFU/100 mL), and the relative/log decrease was at SBF → PB (≈ 1.14 log reduction with an overall reduction efficiency (ORE) of 99.9%.
Fecal count
The largest raw decrease was inlet → ABR (− 1.27 × 10⁷ CFU/100 mL), and the largest log reduction was PB → SMB (≈ 1.40 log units). There was an initial high rate of decrease from Inlet → ABR (− 1.27 × 10⁷ CFU/100 mL), followed by steady reductions, with smaller steps in the middle, and the final stage (PB → SMB) showed the strongest relative removal. The greatest relative/logarithmic decrease occurred between PB and SMB, which presented an ORE of 99.8% at the outlet.
The THB count (cfu/ml)
Table 4, the largest log reduction was PB → SMB (≈ 1.12 log units), closely followed by SBF → PB (≈ 1.06 log units). The rate of decrease showed a large initial decrease between Inlet and ABR (− 4.83 × 10⁵ CFU/mL), with smaller decreases in the middle stages, and strong microbial removal occurred again in the final stages (SBF → PB → SMB). The highest decrease (raw decrease) was between Inlet → ABR, and the relative/logarithmic decrease was PB → SMB (≈ 1.12 log units).
It can therefore be inferred that the largest raw decrease in THB occurred between Inlet and ABR, whereas the highest relative/logarithmic decrease occurred between PB and SMB, with the strongest microbial removal efficiency at the final stage and an ORE of 99.7%.
Indicator organism (E. coli)
The largest raw decrease was Inlet → ABR (− 3.58 × 10⁵ CFU/100 mL), and the largest log reduction was PB → SMB (≈ 1.89 log units). The rate of decrease showed a large initial decrease between Inlet → ABR (− 3.58 × 10⁵ CFU/100 mL) and moderate decreases in the middle stages (− 1.26 × 10⁴ to − 2.0 × 10³), and the final stage (PB → SMB) presented the strongest relative removal. The position of highest decrease (raw decrease) was between the Inlet → ABR, whereas the relative/logarithmic decrease was between PB → SMB. It can therefore be inferred that the largest decrease in E. coli raw matter occurred between Inlet and ABR, whereas the highest relative/logarithmic decrease occurred between PB and SMB, with the strongest microbial removal efficiency at the final stage and an ORE of 99.9%.
Helminthes eggs
The helminths eggs in the inlet chamber were 48 eggs/L with a standard deviation of 8. The greatest decrease in raw material occurred at Inlet → ABR (− 26 eggs/L), and the initial decrease from Inlet → ABR (− 26 eggs/L) was strong; moreover, moderate decreases in raw material content occurred at the middle stages (− 2 to − 5 eggs/L), and the final stage (PB → SMB) presented another strong decrease ( ~ − 6 eggs/L). The chi-square normalized decrease was between PB → SMB (χ² ≈ 18.0), indicating the most statistically significant removal relative to uncertainty where no helminths eggs were observed in the outlet chamber in compliance with the RS maximum limit of ≤ 1 eggs/L and an ORE of 97.9%.
Discussion
The NPC phytoremediation system demonstrated the microbial analysis and compliance levels of wastewater treatment using a nature-based solution which is comparable to reports from other constructed wetland systems across Sub-Saharan Africa (SSA) [10, 11].
The pH an abbreviation of the potential of hydrogen refers to the measure of hydrogen ion (H+) and hydroxyl ions (OH−) concentration in water, and it provides a concise snapshot of acidity or alkalinity. In aquatic environments, pH influences determine the availability and solubility of essential nutrients, controls the toxicity of metals, and affects the integrity of biological membranes and enzyme activities. The results of the reduction in pH indicate a decrease in the acidity of the ww across the different treatment chambers and suggest the optimum functionality of the ww treatment. This continuous pH decrease was also observed in a similar study reported by [12].
Water temperature is a key ecological and metabolic factor and wastewater generates and discharge excess heat with significant impact such as on increasing the metabolism of communities, promoting eutrophication and intensifying the effects of nutrients and toxic pollutants in receiving rivers [13, 14]. In this study, a continuous temperature decrease was observed from the inlet chamber to the outlet chamber. The reduction in treated wastewater temperature is positive for the biological community of the receiving water.
Total dissolved solids (TDS) are the total amount of salts or mobile charged ions dissolved in the water, and it is one of the important chemical parameters in water quality monitoring. A high TDS level in water impacts both health and the aquatic environment [15]. The ORE of 75% for TDS in this study indicates reduction of total solids in ww treatment. A significant reduction in total dissolved solids (TDS), was observed between the subsurface biofilter (SBF) and the polishing bed (PB). This finding mirrors observations by [16] who reported that subsurface flow units and polishing stages are particularly effective at reducing salinity and dissolved solids, primarily through mechanisms such as filtration, ion exchange with the substrate, and plant uptake. The stepwise reductions in TDS observed in the NPC system are consistent with the gradual polishing effects documented in similar multistage systems [17].
TSS comprises both organic and inorganic matter and is considered a waterborne pollutant. High levels of total suspended solids increase water temperature and decrease dissolved oxygen levels. Over time, TSS results to the siltation and sedimentation of the receiving water body [18]. The TSS ORE of 81.6% was reported which is similar to the reports of [19] who reported ORE of 81.05% in wastewater treatment.
In terms of organic matter, 88.8% ORE in BOD₅ was recorded and this reaffirms the robustness of phytoremediation approaches in reducing organic matter in wastewater. This decrease can be attributed to mechanical agitation in the SAB chamber which promotes flocculation and supports aerobic microbial activity, biological decomposition and nitrification which results reduction in BOD. The findings of this study can be compared with report from several other nature-based treatment solutions in SSA. Similar studies in constructed wetlands reported BOD reduction efficiency of 85–92% in Kenya, and 87% to 90% in Uganda, 85% and 90% in Zambia, 89%, in Zimbabwe, respectively [10, 11, 20, 21]. These results place the NPC system’s performance within the upper range of reported efficiencies for phytoremediation-based treatment in sub-Saharan Africa. The ORE of 75% and 81.6% for TDS and TSS in this study indicates reduction of total solids in ww treatment at the final stage (SMB).
Nitrogen and phosphorus, as essential nutrients, play a crucial role in the dynamics of aquatic ecosystems. Recently, excessive concentrations in wastewater have become a global environmental problem as excessive supply of these nutrients can cause eutrophication of receptors, algal proliferation, red tides and endanger biodiversity of aquatic ecosystems [22–24]. The ORE of TN and TP can be attributed to the phytoremediation properties of Vetiver grass (Chrysopogon zizanioides) which posses a large root system capable of deep penetration and its distinct ability to withstand high concentrations of nitrogen, phosphorus, heavy metals, etc [25, 26]. The ORE of TN (82.7%) and TP (60.7%) recorded in this study was greater that of [27] which demonstrated overall removal efficiencies of 60.5, and 40.8% nitrogen, and phosphate, respectively.
Regression analysis demonstrated that the treatment train is highly effective in the reduction of physicochemical pollutants with regression slopes and R² values (> 0.9). The system’s performance across BOD, COD, TN, TDS, TSS, and TP reductions aligns with results established in other research carried out on decentralized, nature-based wastewater treatment technologies, reinforcing its value in sustainable wastewater management for institutional settings.
The suspected microorganisms detected in the treatment chambers (Table 2) remained the same, suggesting a suitable ecological environment to thrive. Aerobic bacteria such as Escherichia coli, Staphylococcus spp. and Bacillus spp uses available oxygen in ww to break down contaminants before converting the energy to use for reproduction and growth [28]. The authors recognize that microbial identification based solely on morphological and biochemical methods is insufficient; therefore, molecular confirmation in future research is recommended.
In terms of microbial indicators, NPC system demonstrated a fecal coliform log reduction of 3.5, meeting the RS and the World Health Organization (WHO) guidelines for restricted irrigation reuse [29]. A similar study in East Africa, reported fecal coliform log reductions in free-water surface constructed wetlands in Tanzania [30]. The decrease of total heterotrophic bacteria count across the treatment chambers in this study was similar to the report of [31] who observed varied decrease in THB counts from different wastewater treatment plants in Hungary.
The NPC phytoremediation system’s multi-stage design ensures that each unit targets specific pollutants, contributing to the overall effectiveness of the system. In the early stages of the system (Inlet → ABR), there were substantial reductions in TC, FC counts and E. coli. The anaerobic baffled reactors (ABRs) can achieve significant early reductions in microbial loads due to prolonged retention time, anaerobic digestion and enhanced sedimentation. At the midstream stages (ABR → FBF → SAB → SBF), there were moderate levels of polishing and gradual decreases in microbial loads. Intermediate stages in multi-stage wetland systems often contribute incremental reductions in microbial loads due to the combined effects of filtration, predation by protozoa, and natural die-off. For example, SBF contributes to additional microbial polishing by providing finer filtration and improved microbial interactions, leading to gradual decreases in microbial indicators like TC, FC, and E. coli. The PB stage was particularly critical for achieving major reductions in total coliforms. In their study, polishing beds reduced coliform counts by up to 99%, reinforcing the importance of this stage in microbial load reduction. However, the SMB chamber was the final decisive polishing stage that ensured full compliance for FC, E. coli, and helminth eggs. The SMB’s role in achieving regulatory compliance is due to enhanced microbial degradation and longer hydraulic retention times. The gradual step-by-step decrease in microbial loads across the treatment train underscores the cumulative effect of each unit. However, SMB is the essential finishing stage that guarantees compliance with regulatory standards.
The microbial indicators TC, FC, THB, E. coli and Helminths eggs in this study were greatly abated from the inlet to the outlet chamber in compliance with the RS. Although ORE ranging from 97.9% to 99.9% was observed, these microbes were still detected in the outlet chamber which suggests that the treatment process reduced microbial load but could not ensure the complete elimination of microbiological hazards. This may be due to a high amount of pollution of domestic wastewater from the source before being introduced into the NPC phytoremediation system. Biological, chemical and other environmental factors may have promoted microbial replication These findings possess as a public health concern hence the authors suggest pretreatment before discharge into the receiving water bodies.
Conclusion
In conclusion, the NPC phytoremediation system is a well-organized, multi-stage process that effectively reduces both physicochemical and microbial pollutants. This makes it a valuable tool in the range of sustainable wastewater treatment technologies, especially in institutional settings in sub-Saharan Africa and other areas with limited resources. Each stage of the system plays a key role in progressively removing pollutants, but the SMB is crucial in ensuring that the treated water meets all regulatory requirements, which supports its use as a sustainable wastewater management solution, particularly in institutional environments. This study underscores the need to assess the performance of wastewater treatment systems in terms of both microbial and physicochemical factors before releasing the treated water into receiving water bodies to prevent possible risks for the environment, animal and human health.
Acknowledgements
Not applicable.
Author contributions
Author JN designed the study. Authors JI, KT and LYA performed the statistical analysis, wrote the protocol, wrote the first draft of the manuscript and managed literature searches. Authors KH, FH and IA managed the analyses of the study and literature searches. All authors read and approved of the final manuscript.
Funding
No Funding was received for this research.
Data availability
The datasets generated and/or analyzed during the current study are not publicly available as the authors may wish to use data in future as a foundation (baseline studies) for further studies/investigations and therefore would not like to release the data to the public domain but data are available from the corresponding author on reasonable request.
Declarations
Ethics approval and consent to participate
Not applicable.
Consent for publication
Not applicable.
Competing interests
The authors declare no competing interests.
Abbreviations
Not applicable.
Footnotes
Publisher’s note
Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
References
- 1.United Nations. The Sustainable Development Goals Report 2022. New York: United Nations Statistics Division. United Nations Publications; 2022. pp. 38-39. https://unstats.un.org/sdgs/report/2022/The-Sustainable-Development-Goals-Report-2022.pdf.
- 2.UNICEF. Blueprint for acceleration. Sustainable Development Goal 6 synthesis Report on Water and Sanitation. 2023. pp. 32-33. https://www.unwater.org/sites/default/files/2023-08/UN-Water_SDG6_SynthesisReport_2023.pdf.
- 3.Mbateye F, Nhapi I, Wali U, Banadda N. Assessment of wastewater management practices in Kigali City, Rwanda. Open Env Bio Mont J. 2010;3:21–8. [Google Scholar]
- 4.Rwanda Standards Board. RS 219:2013 - Water Quality Standards. Rwanda: Kigali; 2013. [Google Scholar]
- 5.Ulusoy A, Atılgan A, Rolbiecki R, Jagosz B, Rolbiecki S. Innovative Approaches for Sustainable Wastewater Resource Management. Agriculture. 2024;14:2111. [Google Scholar]
- 6.Trent R. Wastewater Sampling Operating Procedure LSASDPROC-306-R7. UN Environmental Protection Agency. Athens: Laboratory Services & Applied Science Division; 2026.
- 7.Nhapi I, Twagirayezu B, Kimwaga R, Banadda N. (2013). Performance evaluation of a hybrid natural wastewater treatment pond system in Kigali, Rwanda. BIOINFO Environ. Pollut. 2013;3(1),023–028.
- 8.Nsanzabaganwa J, Chen X, Liu T, Mupenzi C, Hakorimana E, Mind’je R, Mujawayezu ML, Gasirabo A, Umugwaneza A, Malayika F, Niyonsenga S. Impact analysis of constructed wetland for wastewater management in Rwanda. Front Environ Sci. 2025;13:1559624. [Google Scholar]
- 9.Clesceri L, Greenberg A, Eaton A. Standard methods for the examination of water and wastewater. 20th ed. American Public Health Association, American Water Works Association; Water Environment Federation; 1999. pp. 82-84.
- 10.Onyango J, Omondi P, Otieno F. BOD and nutrient removal efficiencies of constructed wetlands in Kenya receiving domestic wastewater. Envt Mont Asses. 2019;191:654. [Google Scholar]
- 11.Kansiime F, Nalubega M. Wastewater treatment by a pilot-scale constructed wetland in Uganda. Water Res. 2020;35:428–38. [Google Scholar]
- 12.Ali H, Min Y, Yu X, Kooch Y, Marnn P, Ahmed S. Composition of the microbial community in surface flow-constructed wetlands for wastewater treatment. Front Microbiol. 2024;15:1-15. [DOI] [PMC free article] [PubMed]
- 13.Zhang M, Chadwick M. Influences of Elevated Nutrients and Water Temperature from Wastewater Effluent on River Ecosystem Metabolism. Environ Process. 2022;9:43. [Google Scholar]
- 14.Santiago M, García de Jalón D. Heat Recovery as a Tool for Reducing the Thermal Impact of Effluents from Wastewater Treatment Plants. Sustainability. 2026;18(8):3879. [Google Scholar]
- 15.Pushpalatha N, Sreeja V, Karthik R, Saravanan G. Total Dissolved Solids and Their Removal Techniques. Int J Envt Sust Protect. 2022;(2):13–30.
- 16.Kadlec R, Wallace S. Treatment Wetlands. 2nd ed. CRC. 2009. pp. 203-216.
- 17.Wu S, Wallace S, Brix H, Kuschk P, Kirui W, Masi F, Dong R. Treatment of industrial effluents in constructed wetlands: Challenges, operational strategies and overall performance. J Environ Pollut. 2014;192:245–62. [DOI] [PubMed] [Google Scholar]
- 18.Dufatanye I, Lee Y, Kim H, Lee S. Industrial Wastewater Discharge and Compliance Investigation for Environmentally Resilient Rwanda. Water. 2022;14(19):3100. [Google Scholar]
- 19.Yotova G, Lazarova S, Kudłak B, Zlateva B, Mihaylova V, Wieczerzak M. Assessment of the Bulgarian wastewater treatment plants’ impact on the receiving water bodies. Mol. 2019;24(12):2274. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 20.Simate G, Ndlovu S, Matinde E. Performance of pilot-scale constructed wetlands in removing organic pollutants from municipal wastewater in Zambia. JEM. 2021;295:113086. [Google Scholar]
- 21.Nhapi I, Hoko Z. Performance of hybrid constructed wetlands for wastewater management in Zimbabwe. Phys Chem Earth. 2018;108:1–7. [Google Scholar]
- 22.Fernández FJ, Martínez A, Alvarez-Vázquez LJ. Controlling eutrophication by means of water recirculation: An optimal control perspective. J Comput Appl Math. 2023;421:114886. [Google Scholar]
- 23.Irimia O, Gaspar E, Stanciu M, Moșneguțu E, Bârsan N. Optimizing Nitrogen and Phosphorus Removal from Wastewater in the Context of a Sustainable Economy. Water. 2024;16(11):1585. [Google Scholar]
- 24.Wu X, Quan W, Chen Q, Gong W, Wang A. Efficient Adsorption of Nitrogen and Phosphorus in Wastewater by Biochar. Mol. 2024;29(5):1005. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 25.Yan A, Wang Y, Tan S, Mohd Y, Ghosh S, Chen Z, Phytoremediation. A promising approach for revegetation of heavy metal-polluted land. Front Plant Sci. 2020;11:359. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 26.Ketaubon P, Ritthikasem N, Tanheng P, Prapagdee B. Enhancing heavy metal phytoremediation in landfill soil by Chrysopogon zizanioides (L.) roberty through the application of bacterial-biochar pellets. Environ Technol Innov. 2024;35:103738. [Google Scholar]
- 27.Tesfa G, Terefe A. Evaluating the efficiency of vetiver grass (Vetiveria zizanoides) for municipal wastewater treatment in Bahir Dar City, Ethiopia. Sci Rep. 2025;15(1):38700. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 28.Rachel R. Microbial Technology in Wastewater Management. J Microb Biochem Technol. 2022;14:500. [Google Scholar]
- 29.World Health Organization. Guidelines for the Safe Use of Wastewater, Excreta and Greywater. Volume 2.16 Wastewater Use in Agriculture. 2018.
- 30.Kayombo S, Mbwette T, Mayo A, Katima J, Jorgensen S. Performance of a horizontal subsurface flow constructed wetland in the removal of fecal coliforms in Tanzania. Water Sci Tech. 2017;40:109–16. [Google Scholar]
- 31.Aib H, Czegeny I, Benhizia R, Czédli H. Evaluating the Efficiency of Wastewater Treatment Plants in the Northern Hungarian Plains Using Physicochemical and Microbiological Parameters. Water. 2024;16:3590. [Google Scholar]
Associated Data
This section collects any data citations, data availability statements, or supplementary materials included in this article.
Data Availability Statement
The datasets generated and/or analyzed during the current study are not publicly available as the authors may wish to use data in future as a foundation (baseline studies) for further studies/investigations and therefore would not like to release the data to the public domain but data are available from the corresponding author on reasonable request.