Evaluation of physical, chemical, and microbiological characteristics of waste stabilization ponds, Giza, Egypt

Abstract

Wastewater treatment plants (WWTPs) contain a diverse array of microbes, underscoring the need for regular monitoring to ensure treatment efficacy and protect health. However, detailed studies on waste stabilization ponds (WSPs) are scarce. This study evaluates a full-scale WSP, located in Giza Governorate, Egypt, including anaerobic, facultative, and maturation ponds, examining an array of parameters such as enteric viruses, microeukaryotes (protozoa and algae), bacterial indicators, bacterial pathogens, and physicochemical characteristics. Utilizing multivariate statistical models, we identified significant distinctions in physicochemical parameters and microbial communities, primarily driven by treatment stages rather than temporal variations. In addition, seven viruses (human rotavirus, adenovirus, norovirus, astrovirus, hepatitis A virus, polyomavirus, and papillomavirus) were detected during the different stages (inlet, anaerobic, facultative, and outlet) of the WSP, except norovirus and papillomavirus were absent in the outlet stage. The viral log means reductions ranged from 1.24 to 5.94, depending on the stage and virus type. The removal efficiency of bacterial pathogens was more than 99%. High throughput 18S rRNA gene amplicon sequencing indicated the dominance of animal parasitic Apicomplexa species and Vermamoeba spp. in the WSP. Network analysis indicated significant roles for Ciliophora in virus reduction. Notably, the maturation pond's outlet was dominated by Spirulina maxima, whose mat-forming tendencies may inhibit pathogen removal by providing protective shelters. Although the WSP effectively reduced pathogen levels, the high initial loads resulted in considerable concentrations in the final effluent, posing ongoing public health concerns. This study highlights the imperative of including pathogen standards in national regulations for wastewater reuse.

Introduction

Wastewater treatment occupies a critical intersection of environmental stewardship and public health, addressing the urgent challenge of water scarcity and furthering sustainability in a rapidly changing global landscape. The effective removal of contaminants from wastewater not only allows for its reuse in agriculture, industrial activities, and even as a potential source of drinking water, but also mitigates the intensifying pressures of water scarcity. These pressures are compounded by climate change, population growth, and heightened demands from various sectors, necessitating the adoption of advanced treatment systems and practices. Such systems are crucial for preserving water quality, maintaining ecosystem health, and promoting a sustainable, cyclical approach to water management [1,2,3]. Therefore, continuous monitoring and assessment of these systems are essential for safeguarding human and environmental health.

In developing countries, the complexities of wastewater management are intensified by factors, such as rapid population growth, urbanization, industrialization, financial limitations, and a scarcity of specialized knowledge [4, 5]. Often, the increase in wastewater production surpasses the expansion capabilities of existing treatment infrastructures, resulting in environmental degradation and adverse health impacts. This situation highlights the critical need for effective wastewater treatment strategies to protect environmental and human health [5, 6].

Complications arising from poorly treated wastewater include the proliferation of pathogenic microorganisms and an excess of nutrients, notably phosphates, and nitrates. These nutrients, while essential for plant life, can induce eutrophication when present in high concentrations, leading to algal blooms that deplete aquatic dissolved oxygen levels, degrade water quality, and disrupt biodiversity [7,8,9]. The myriad of pathogens found in wastewater, such as viruses, bacteria, and protozoa, presents significant health risks and environmental concerns [10, 11]. Despite technological advancements in water treatment, waterborne diseases remain a formidable public health threat worldwide [12]. Notably, the persistence of human enteric viruses in wastewater systems, attributable to their resilience to environmental factors and extended shedding from infected individuals, has implications for community health, with some viruses remaining infectious post-treatment [13,14,15]. In addition, free-living amoebae (FLA), which thrive in diverse environments, can act both as independent pathogens and vectors for various pathogens, highlighting their significance in environmental and public health contexts [16, 17].

In Egypt, more than 372 WWTPs exist for the treatment of municipal wastewater. Numerous treatment technologies are applied, such as the activated sludge, trickling filter, up flow-anaerobic sludge blanket, constructed wetlands, and waste stabilization pond systems [10, 18]. Waste stabilization ponds (WSPs) offer a cost-effective, viable alternative to conventional wastewater treatment facilities, particularly in developing countries. These biological treatment systems, characterized by simple operation and low technical and financial requirements, undergo a three-stage process involving anaerobic, facultative, and maturation phases to degrade organic matter, pathogens, and nutrients effectively. Despite their benefits, WSPs face challenges, such as extensive land use and potential as mosquito breeding sites [19, 20].

The interaction between microalgal and bacterial communities in WSPs has attracted significant scientific attention due to its impact on the efficacy of these systems. Optimal conditions, such as minimal water turbidity and abundant sunlight, facilitate the aerobic breakdown of organic matter by bacteria, which in turn supports algal growth. This symbiotic relationship significantly boosts the overall performance of WSPs by promoting efficient organic matter decomposition and nutrient recycling [21, 22]. Microalgae, which are photosynthetic microorganisms, exhibit considerable diversity in their physical and biochemical attributes [23]. The utilization of microalgae in wastewater treatment not only presents an eco-friendly solution for biomass production but also stands out as a highly sustainable and cost-effective approach [24]. This synergy provides numerous benefits; microalgae can rapidly proliferate, absorbing inorganic nitrogen and phosphorus, and in the process, supply dissolved oxygen (DO) essential for bacterial functions aimed at reducing biological oxygen demands (BOD) and chemical oxygen demands (COD) [25, 26].

WSPs are an effective and natural technology for wastewater treatment, heavily influenced by various physicochemical parameters that dictate the system's efficiency. Key parameters include pH, temperature, DO, BOD, COD, nutrient levels (nitrogen and phosphorus), and turbidity. Each of these parameters plays a vital role in the metabolic activities of the microbial communities within WSPs, thus impacting the overall treatment performance. For example, pH level in WSPs affects the solubility and availability of nutrients, as well as the microbial processes. Microalgae typically prefer slightly alkaline conditions, which enhance their photosynthetic activity and growth. This, in turn, increases the DO levels essential for aerobic bacteria that degrade organic matter. DO is a critical parameter that reflects the oxygenation status of the pond. Adequate DO levels, sustained by the photosynthetic activity of microalgae, support aerobic bacterial processes crucial for reducing BOD and COD. Temperature also plays a crucial role; higher temperatures generally accelerate microbial metabolic rates, improving the breakdown of organic pollutants and nutrient uptake by microalgae. However, extremely high temperatures can inhibit microbial activity, reducing treatment efficiency [27, 28]. Nutrient levels, particularly nitrogen and phosphorus, are essential for microalgal growth but can cause eutrophication if not adequately removed. Microalgae uptake these nutrients, converting them into biomass and thereby reducing their concentrations in the effluent [29].

Research on WSPs, both globally [19, 30, 31] and in Egypt [10, 18], has been limited, particularly regarding the interactions between biotic–biotic and biotic–abiotic factors within these treatment systems. This study aims to address this knowledge gap by examining a comprehensive range of factors including seven enteric viruses, 18S rRNA–microeukaryotes, protozoa, bacterial indicators, bacterial pathogens, algae, and physicochemical characteristics. Specifically, our objectives are to (1) evaluate the efficiency of the WSP in reducing pathogen loads, emphasizing the roles of different treatment stages, (2) assess the performance efficiency of the WSP concerning the physicochemical parameters, in compliance with the Egyptian Code of Practice (ECP 501/2015) for the use of treated wastewater for agricultural purposes, (3) investigate the interaction between pathogens and other microorganisms, such as Ciliophora, to understand their roles in pathogen reduction and overall system efficacy, and (4) examine the specific role of algal species in the wastewater treatment process. This study will enhance our understanding of the roles of various biological entities, ultimately leading to better operational strategies and improved efficiency of WSPs.

Materials and methods

WSP description and sample collection

A total of 24 samples were collected from various stages of the wastewater treatment plant (29 °27′32.6"N 31 °14′37.0"E) located in Atfih city, Giza Governorate, Egypt. These stages included the inlet, anaerobic, facultative, and the outlet (after maturation pond) as shown in Additional file 1: Fig. S1. The Atfih WSPs are designed with a capacity to treat 45000 m³/day, although the actual processing capacity ranges from 5000 to 7000 m³/day. The system comprises three treatment stages anaerobic pond, facultative pond, and maturation pond constructed to comply with the Egyptian code for the use of treated municipal wastewater for agricultural purposes [32]. The total retention time at the station is 35–38 days, with the treated effluent being utilized for the irrigation of trees. Between August 2022 and January 2023, a series of 24 samples were meticulously gathered. Six sampling events were conducted over these 6 months, with each event comprising samples from four different stages of the treatment process (inlet, anaerobic pond, facultative pond, and maturation pond). The samples were collected in sterile containers, immediately chilled with ice for preservation, and transported for analysis at the National Research Centre laboratories, ensuring a maximum interval of 5 h from collection to analysis. The sample volumes were tailored to the specific requirements of each analytical procedure: 1 l for viruses, 1 l for microeukaryotic community analysis, 1 l for protozoa, and 1 l dedicated to the assessment of bacterial indicators and bacterial pathogens. In addition, a 3-l volume was allocated for the comprehensive evaluation of physicochemical parameters and algal community in each sample.

Physicochemical analysis

Wastewater samples were subjected to physicochemical analysis in accordance with the standard methods for the examination of water and wastewater [33]. In situ measurements for temperature, dissolved oxygen (DO), and DO saturation were performed using an AD 360 DO meter provided by Adwa Instruments, Inc., Europe. The pH levels were determined using a Jenway model 3510 bench pH meter. In addition, electric conductivity (EC) and total dissolved solids (TDS) were determined using a Jenway 4510 conductivity meter. Laboratory assessments were conducted to analyze various parameters, including chemical oxygen demand (COD), biochemical oxygen demand (BOD), ammonium nitrogen (NH₄–N), total phosphorus (TP), nitrate nitrogen (NO₃–N), total Kjeldahl nitrogen (TKN), nitrite nitrogen (NO₂–N), and total nitrogen (TN).

Viral Analyses

Virus concentration by polyethylene glycol precipitation.

To concentrate viruses from wastewater samples, a modified polyethylene glycol (PEG) precipitation method was employed for 250 ml samples [34, 35], with some modifications. Initially, the samples were agitated at 4 °C at a speed of 100 rpm for 30 min to facilitate the transfer of viruses into the aqueous phase. Subsequent to this, bacterial debris and large particles were eliminated through centrifugation at 11.000 rpm for 60 min at 4 °C. The clear supernatant was adjusted to pH from 7 to 7.5, and then treated with 10% w/v PEG 8000 and 1.8% w/v 0.2 M NaCl, mixed by shaking stirrer for 20 min. The viruses were subsequently precipitated by further centrifugation at 11.000 rpm for 150 min at 4 °C. The supernatant was discarded, and the viral pellets were resuspended in 1 mL of phosphate-buffered saline and stored at −20 °C for future analysis.

Viral RNA extraction

Viral RNA/DNA was extracted from 300 μl of the concentrated samples using the QIAamp Viral RNA Isolation Kit by Qiagen, Hilden, Germany, following the protocol provided by the manufacturer. To assess potential PCR inhibition, a representative sample from the concentrated wastewater was spiked with 4.7 X 10⁸ GC/mL murine norovirus (MNV-1), previously confirmed as MNV-1 negative, and analyzed via quantitative PCR (qPCR) to confirm the absence of inhibitory effects [36].

Real time PCR (RV, AdV, HAV, NoVs, AstV, HPyV, PapiV)

Quantitative PCR analysis were conducted to detect human adenovirus (HAdV) using the Rotor-Gene Probe PCR Kit from Qiagen, Germany [37]. Similarly, astrovirus (AstV), hepatitis A virus (HAV), human polyomavirus (HPyV), rotavirus A (RVA), and norovirus (NoV) were quantified using the Rotor-Gene Probe RT-PCR Kit, employing methodologies detailed in previous studies [38,39,40,41,42]. Papillomavirus (PapiV) detection was performed using an SYBR green qPCR assay with GP5 + /GP6 + primers targeting a segment of the L1 gene [43]. All PCR amplifications were conducted in duplicate on the Rotor-Gene system (Qiagen, Germany). Positive controls for each virus were established by cloning respective PCR amplicons into plasmids, with concentrations determined using a Nano Drop spectrophotometer (Denovix, USA). A tenfold serial dilution of these plasmids created standard curves for quantification. Serial dilution was also applied to the nucleic acids to minimize inhibitors and enhance PCR efficiency. Each 25 μL real-time PCR mixture comprised 5 μL of DNA or RNA extract, 12.5 μL of PCR master mix, 400 nM of each primer, 250 nM of TaqMan probe, and was completed to volume with nuclease-free water. PBS served as the negative control in both nucleic acid extraction and qPCR assays, with fluorescence data recorded at the end of the annealing phase. Sequence of the primers and probes used in this study are listed in Additional file 1: Table S1

Bacteriological analyses

Enumeration of bacterial indicator

Bacterial indicators, including total coliforms (TC) (APHA Method 9221), fecal coliforms (FC) (APHA Method 9222), Escherichia coli (EC) (APHA Method 9221), and fecal streptococci (FS) (APHA Method 9230), were quantified using the most probable number (MPN) technique as outlined by APHA (2023) [33].

Enumeration of bacterial pathogens

The assessment of potential bacterial pathogens was conducted using culture-dependent methods on specific agar media according to APHA (2023) [33]. A 100 μL sample of serially diluted water was plated on HiCrome Improved Salmonella Agar for Salmonella species detection, with incubation at 37 °C for 24–48 h. Characteristic colonies appeared light pink to red (APHA Method 9260 B). Pseudomonas aeruginosa was identified on HiFluoro^™ Pseudomonas Agar enhanced with 10 mL glycerol, incubated at 37 °C for 24 h, with typical colonies exhibiting fluorescence under UV light (APHA Method 9213 F). Staphylococcus aureus was cultured on HiCrome Staph Selective Agar, where colonies developed a green color after 24–48 h at 37 °C (APHA Method 9213 B). Listeria spp. was enumerated on HiCrome Listeria Agar Base modified with HiCrome Listeria Selective Supplement, with typical colonies turning bluish-green after 24–48 h of incubation at 37 °C. Pathogen counts were expressed as colony-forming units per 100 mL (CFU/100 mL). All specific media were provided by HiMedia Co., India. Pathogenic isolates were confirmed using Biolog GEN III as described by El-Liethy et al. [44].

Protozoological analysis

For the analysis of FLA, wastewater samples were concentrated through a nitrocellulose membrane with a pore size of 0.45 µm and a diameter of 47 mm, and then cultured on non-nutrient agar seeded with heat-killed E. coli at a temperature of 30 °C [45]. DNA was extracted from morphologically identified FLA-positive samples using the DNeasy PowerLyzer PowerSoil Kit from QIAGEN, USA, in accordance with manufacturer’s protocols [46]. The DNA samples were then subjected to PCR testing using primers JDP1 and JDP2 for Acanthamoeba species detection [47], and HART-F and HART-R for Vermamoeba Vermiformis identification [48] (Additional file 1: Table S1). PCR reactions were executed in a total volume of 25 µL, which included 12.5 µL of 2X master mix from Promega, USA, 3 µL of template DNA, 1 µL of each primer, and the remaining volume filled with nuclease-free water. The amplification process consisted of an initial denaturation at 95 °C for 5 min, followed by 35 cycles of denaturation at 94 °C for 30 s, annealing at 55 °C for 40 s, extension at 72 °C for 40 s, and a final extension at 72 °C for 10 min [49].

18S rRNA high-throughput amplicon sequencing analysis

Six wastewater samples, comprising three inlet and three outlet samples, were filtered using a 0.2 µm-pore polycarbonate membrane (47 mm diameter, Millipore, Billerica, MA, USA). The membranes were stored at −20 °C until DNA extraction. Prior to DNA extraction, three replicates of each sample were thoroughly mixed. DNA was directly extracted from these membranes using the DNeasy PowerLyzer PowerSoil Kit (QIAGEN, USA). Amplification of the eukaryotic 18S rRNA genes’ hypervariable V4 region was conducted using primer pairs A-528F and B-706R [50]. The PCR cycle included an initial denaturation at 95 °C for 5 min, followed by 25 cycles of denaturation at 95 °C for 30 s, annealing at 50 °C for 30 s, and extension at 72 °C for 60 s, with a final extension at 72 °C for 10 min. The resulting PCR products were purified, pooled in equal amounts, and sequenced using an Illumina platform (Illumina Inc., San Diego, CA, USA).

Sequence analysis

Raw paired-end reads were processed using DADA2 v1.16.0 to denoise and assemble the sequences (https://benjjneb.github.io/dada2/tutorial.html) [51]. Amplicon sequence variants (ASVs) were generated at 100% sequence identity from high-quality reads. Taxonomic classification was performed using the RDP classifier and the Protist Ribosomal Reference (PR2) database (version 4.7.2) [52]. The data set included a minimum of 120,722 reads and a maximum of 135,722 reads per sample. To normalize sequencing depth, samples were randomly subsampled to 120,000 sequences each, retaining a total of 3224 microeukaryotic ASVs in the final data set for further analysis.

Microalgal consortium analysis

For microscopic identification of microalgae, samples were placed into sterile glass containers and fixed with Legol’s solution [53]. A volume of 0.2 ml of this solution was spread onto glass slides for examination. Identification of dominant genera was conducted on five slides per sample, with each slide being examined twice using an Olympus X3 microscope (Olympus Corporation, Tokyo, Japan), following the key to freshwater algae [53].

Statistical analysis

Principal Component Analysis (PCA), utilizing Euclidean distance metrics, was employed to elucidate the distribution patterns of physicochemical parameters across various WSPs. Significant disparities in physicochemical and microbiological parameters among the ponds were evaluated using Permutational Multivariate Analysis of Variance (PERMANOVA) and Analysis of Similarity (ANOSIM). Non-metric Multidimensional Scaling (nMDS) facilitated the exploration of viral and bacterial community patterns, employing Bray–Curtis distance calculations to assess dissimilarities. Similarly, Principal Coordinate Analysis (PCoA) was utilized to delineate the distribution patterns of microeukaryotic communities. Network analysis was applied to delineate and visualize the interrelationships between pathogenic and non-pathogenic microorganisms. All statistical analyses and visualizations were conducted using PRIMER v.7.0.21 (Quest Research Limited, Auckland, New Zealand) and R v4.1.0 (https://www.r-project.org/).

Results

Physicochemical characteristics of wastewater

PCA effectively delineated the physicochemical parameter profiles of wastewater at different treatment stages, particularly highlighting clear distinctions between the influent/anaerobic stages and the outlet, which were more pronounced than temporal variations. This suggests a substantial influence of the treatment processes on these parameters (Fig. 1). These observations were statistically supported by significant results in PERMANOVA and ANOSIM analyses (p < 0.05) (Table 1). Detailed physicochemical profiles of wastewater in the WSPs are depicted in Fig. 2. Analysis of the influent revealed the presence of substantial organic content, with COD ranging from 110 to 365 mgO₂/L and BOD between 48 and 209 mgO₂/L. The biodegradability index, calculated as the ratio of BOD to COD, was noted as 0.50. pH values of the influent varied from 6.9 to 8.11. DO, EC, and TDS in the influent were recorded in the ranges of 0.3–2.7 mg/L, 1196–1538 µs/cm, and 720–923 mg/L, respectively. Nitrogenous compounds showed considerable fluctuations, with TN, TKN, NH₄–N, NO₂–N, and NO₃–N concentrations ranging extensively from 10.32 to 45.54 mg/L, 10.1 to 45.4 mg/L, 29.2 to 40.23 mg/L, 0.011 to 0.048 mg/L, and 0.097 to 0.617 mg/L, respectively. TP concentrations varied from 4.5 to 12.55 mg/L, with an average of 6.08 mg/L.

Fig. 1

Principal component analysis (PCA) for mapping the physicochemical parameters in different stages of Atfih WSPs during 6 months

Table 1 PERMANOVA and ANOSIM to test the significance of the differences in bacteria, viruses, algae, protozoa, and physicochemical parameters between the treatment stages

Fig. 2

Minimum, maximum and averages of some physicochemical parameters in different treatment stages of Atfih WSPs. DO dissolved oxygen, DO% DO saturation, EC electric conductivity, TDS total dissolved solids, COD chemical oxygen demand, BOD biochemical oxygen demand, NH₄–N ammonium nitrogen, TP total phosphorus, NO₃–N nitrate nitrogen, TKN total Kjeldahl nitrogen, NO₂–N nitrite nitrogen, TN total nitrogen, Temp temperature

In the anaerobic pond, an initial degradation process resulted in average removal efficiencies of 36.39% for COD, 42.48% for BOD, 20.71% for TP, and 8.51% for NO₃–N. There was a marked increase in the concentrations of various nitrogenous compounds in samples of the anaerobic pond, specifically NH₄–N, NO₃–N, NO₂–N, TKN, and TN, with concentrations ranging from 28.5 to 29.2 mg/L for NH₄–N, 0.177 to 0.28 mg/L for NO₃–N, 0.04 to 0.072 mg/L for NO₂–N, 9 to 73 mg/L for TKN, and 9.23 to 73.30 mg/L for TN. Furthermore, pH of the effluent from this pond slightly increased, ranging from 6.95 to 8.35. Transitioning to the facultative pond, there was a noticeable elevation in pH levels, ranging from 7.77 to 9.9, and a reduction in odor was observed. Here, the concentrations of NO₃–N and NO₂–N rose markedly from 0.23 mg/L to 2.6 mg/L and from 0.033 mg/L to 0.45 mg/L, respectively. Despite these changes, the quality of effluent from the facultative pond deteriorated, evidenced by COD levels between 73 and 630 mgO₂/L and BOD levels from 15 to 292 mgO₂/L.

Finally, in the maturation pond, further refinement of the effluent was achieved. The pH of the final effluent elevated to a range of 8.1–9.29 (Fig. 2). Notably, residual concentrations of NO₂–N and NO₃–N averaged at 0.756 mg/L and 0.652 mg/L, respectively. The outlet also exhibited an EC of 1353 µS/cm and TDS of 816 mg/L. Variability in COD and BOD was reduced to between 78 and 150 mgO₂/L and 31 and 85 mgO₂/L, respectively, yielding average removal efficiencies of 51.15% for COD and 56.78% for BOD. Nutrient reduction efficiencies were recorded at 16.18% for TP, 93.63% for NH₄–N, 42.04% for TKN, and 36.92% for TN. The outlet parameters of the Atfih WWTP met the Egyptian legislation (the Egyptian Code 501/2015, category D) for the irrigation of trees (Table 2).

Table 2 Physicochemical characteristics (average ± standard deviation) of the inlet and outlet of Atfih WSP

qPCR specificity, sensitivity, and detection limits

Each set of real-time primers and probes utilized in this investigation was assessed for specificity. The adenovirus, rotavirus, asrovirus, HAV, polyomavirus, papillomavirus, and rotavirus plasmid DNA standards (10⁵ copies each) were subjected to examination using each of the seven real-time PCR techniques. When plasmid DNA standards were utilized as a template, no cross-reactivity between primer and probes was observed. Regarding to the detection limit for each virus, the highest dilution at which virus quantification was possible was used to determine the qPCR detection limit (the detection limits for HAdV, RVA, HAV, and AstV were 2 × 10¹ genome copies/L of sample, while the detection limits for NoV, HPyV, and PapiV were 3 × 10¹ genome copies/L of sample). The investigation resulted in standard curves that showed linear regression values: the slope ranged from 3.45 to 3.50, the reaction efficiency ranged from 96% to 97.5%, and the coefficient of determination (R²) ranged from 0.958 to 0.965.

Prevalence of viruses in wastewater

A total of seven types of viruses were assessed, including four RNA viruses (RV, HAV, GI NoV, GII NoV, and AstV) and three DNA viruses (AdV, HPyVs, and PapiV), across various stages of wastewater treatment using (RT) qPCR. Significant alterations in viral community structures due to treatment processes were evident (PERMANOVA: p = 0.0001), in contrast to temporal variations, which showed no significant impact on viral composition (p > 0.05), as illustrated in Fig. 3. Notable differences were observed between the inlet stage and the subsequent anaerobic, facultative, and outlet stages (PERMANOVA: p = 0.002), detailed further in Table 1. All viruses were detected across all treatment stages, except for HPyVs in the facultative samples and both NoV and PapiV in the outlet samples (Fig. 4). RV was the most prevalent, detected at rates of 100% in the inlet, 66.7% in both anaerobic and facultative stages, and 16.7% in the outlet, with concentrations ranging from 1.5 × 10 to 1.12 × 10⁶ GC/mL, averaging 5.49 × 10⁵ GC/mL.

Fig. 3 

Non-metric multidimensional scaling (nMDS) plot to characterize the pattern of viruses and bacteria based on dissimilarities calculated using the Bray–Curtis distance

Fig. 4

Concentrations of viruses at different wastewater treatment stages. Zero virus concentration are not depicted in this figure. RV Human rotavirus, AdV adenovirus, NoV norovirus, AstV astrovirus, HAV hepatitis A virus, HPyV polyomavirus, and PapiV papillomavirus

Detection ratios for HAdV and HAV were consistent across stages: 83.3% in the inlet and 50% in both the anaerobic and outlet stages, with a slight decrease to 33.3% in the facultative stage. HAdV concentrations varied from 3.48 × 10² to 9.54 × 10⁵ GC/mL, averaging 3.24 × 10⁵ GC/mL, while HAV concentrations ranged from 6.2 × 10 to 2.53 × 10⁵ GC/mL, averaging 4.32 × 10⁴ GC/mL. NoV GI and GII showed variable detection rates and were completely absent in the outlet stage. NoV concentrations varied from 7.4 × 10¹ to 2.3 × 10³ GC/mL with a mean concentration of 1.4 × 10² GC/mL for GI and from 2.3 × 10² to 7.42 × 10³ GC/mL with a mean concentration of 6 × 10² GC/ml for NoV GII (Fig. 4).

AstV concentrations ranged from 9.4 × 10¹ to 3.45 × 10⁵ GC/ml, averaging 2.15 × 10⁴ GC/ml. HPyV DNA was detected in 83.3% (5/6), 33.3% (2/6), 0% (0/6), 16.7% (1/6) of inlet, anaerobic, facultative, and outlet samples, respectively. HPyV and PapiV exhibited lower detection frequencies in the latter stages of treatment, with HPyV not detected in facultative samples and PapiV absent in outlet samples. Concentrations for these viruses varied, with HPyV DNA ranged from 1.54 × 10² to 4.26 × 10⁵ GC/mL, and PapiV ranged from 1.24 × 10² to 7.89 × 10³ GC/mL (Fig. 4).

Virus removal during wastewater treatment processes

The efficiency of viral load reduction was quantified using log mean reductions from qPCR-positive samples. The anaerobic stage showed removal efficiencies ranging from 1.24 Log₁₀ for NoV to 3.19 Log₁₀ for HPyVs. In the facultative stage, reductions ranged from 1.06 Log₁₀ for PapiV to 5.07 Log₁₀ for HPyVs, and in the final treated effluent (outlet stage), they ranged from 2.08 Log₁₀ for HPyVs to 5.94 Log₁₀ for RV. RV exhibited the highest reduction rate, decreasing from 6.34 Log₁₀ in raw sewage to 0.4 Log₁₀ in treated effluent, achieving an average removal efficiency of 5.94 Log₁₀. This was followed by HAdV, with a decrease from 6.1 Log₁₀ to 2.49 Log₁₀, averaging a removal of 3.61 Log₁₀. HAV RNA concentrations averaged 5.23 Log₁₀ in raw sewage, reducing to 2.22 Log₁₀ in the final effluent, equating to a removal efficiency of 3.01 Log₁₀. AstV RNA presented an average initial concentration of 4.95 Log₁₀, which diminished to 1.42 Log₁₀ post-treatment, reflecting a mean reduction of 3.53 Log₁₀. HPyVs DNA showed an average decrease from 5.07 Log₁₀ in untreated sewage to 2.99 Log₁₀ in the effluent, resulting in a removal efficiency of 2.08 Log₁₀. Notably, the genomes of NoV GI and GII, along with PapiV, initially measured at relatively lower concentrations of 3.13 Log₁₀ and 3.21 Log₁₀, respectively, in raw sewage samples, were found to be effectively eliminated in the treated effluent, as illustrated in Fig. 5.

Fig. 5

Efficiency of virus removal in sewage treatment plants which was calculated as viral titers in influent compared to treated effluent. RV Human rotavirus, AdV adenovirus, NoV norovirus, AstV astrovirus, HAV hepatitis A virus, HPyV polyomavirus, and PapiV papillomavirus

Pearson correlation analysis revealed a strong negative association (Pearson`s-r = −0.99, p = 0.005) between virus prevalence and temperature, as depicted in Fig. 6. This suggests that higher temperatures may contribute to the inactivation of viruses within the WSPs. Furthermore, network analysis demonstrated a negative correlation between viruses and Ciliophora, a group of predatory microorganisms, indicating their role in naturally reducing virus levels (Additional file 1: Fig. S2). In addition, a positive correlation was observed between rotavirus (RV) and several bacterial indicators (FC, FS, TC, and EC) as well as bacterial pathogens (S. aureus and Salmonella spp.) (Additional file 1: Fig. S3). This implies that the presence of these bacterial indicators/pathogens may serve as reliable proxies for detecting RV in wastewater.

Fig. 6

Pearson analysis shows the correlation between the physicochemical parameters and pathogenic/non-pathogenic microorganisms. DO dissolved oxygen, DO% DO saturation, EC electric conductivity, TDS total dissolved solids, COD chemical oxygen demand, BOD biochemical oxygen demand, NH₄–N ammonium nitrogen, TP total phosphorus, NO₃–N nitrate nitrogen, TKN total Kjeldahl nitrogen, NO₂–N nitrite nitrogen, TN total nitrogen, Temp temperature

Variations in bacterial indicators and pathogens across different WSPs

The composition of bacteria indicators and pathogens were markedly influenced by the treatment processes, showing significant statistical differences (PERMANOVA: p = 0.0001). In contrast, temporal variations had no substantial impact on these microbial populations (p > 0.05), as depicted in Fig. 3. Bacteria, including fecal bacterial indicators and pathogens, demonstrated a strong correlation with DO, DO% and NH₄–N (Additional file 1: Fig. S4). At the inlet stage, the highest concentrations for TC, FC, EC and FS were 6.4 × 10⁹, 2.1 × 10⁹, 2.1 × 10⁹ and 1.1 × 10⁹ MPN/100 mL, respectively. Concurrently, the highest counts of Salmonella spp., P. aeruginosa, S. aureus and Listeria spp. values were 5.1 × 10⁶, 7.8 × 10⁵, 1.3 × 10⁶ and 6.5 × 1 0⁶ CFU/100 mL, respectively (Fig. 7).

Fig. 7

Counts of bacterial indicators and bacterial pathogens (Salmonella spp., P. aeruginosa, S. aureus and Listeria spp.) in different stages of the WWTP during 6 months extended from August 2022 to January 2023. TC Total coliforms, FC Fecal coliforms, EC Escherichia coli, FC Fecal streptococci

Post-anaerobic stage, the counts for TC, FC, EC and FS dropped to 3.9 × 10⁸, 1.0 × 10⁸, 6.4 × 10⁷ and 7.0 × 10⁸ MPN/100 mL, respectively. After anaerobic stage, the average removal efficiency for FBI was 94.2, 94.6, 95 and 74.4% for TC, FC, EC and FS, respectively. The removal efficiency for bacterial pathogens was 86.9, 73.8, 95.2 and 97.4% for Salmonella spp., P. aeruginosa, S. aureus and Listeria spp., respectively (Fig. 7).

Following the facultative stage, the highest values recorded for TC, FC, EC and FS were 1.5 × 10⁷, 4.6 × 10⁶, 4.6 × 10⁶ and 5.3 × 10⁶ MPN/100 mL, respectively. The average removal efficiency for FBI dramatically increased to 99.8, 99.9, 99.8 and 99.8%, respectively. Similarly, the highest counts for Salmonella spp., P. aeruginosa, S. aureus, and Listeria spp. decreased to 1.0 × 10⁵, 8.2 × 10⁴, 1.9 × 10⁴, and 1.5 × 10⁴ CFU/100 mL, respectively, with respective average removal efficiencies of 98, 91.1, 98.6, and 99.6% (Fig. 7).

In the outlet samples, the counts for TC, FC, EC and FS values were 2.1 × 10³, 9.3 × 10³, 7.0 × 10³ and 9.3 × 10³ MPN/100 mL, respectively, achieving a removal efficiency of 99.99% for FBI. The counts for bacterial pathogens were consistent with those after the facultative stage, showing removal efficiencies of 99.93%, 99.83%, 99.97%, and 99.7% for Salmonella spp., P. aeruginosa, S. aureus, and Listeria spp., respectively (Fig. 7).

Microeukaryotic communities’ structure in inlet and outlet of the WSPs

PCoA revealed distinct dissimilarities in microeukaryotic community compositions between the inlet and outlet samples (Additional file 1: Fig. S5). These differences were statistically confirmed by Analysis of Similarity (ANOSIM) with an R value of 0.815 and a p value of 0.001, indicating significant variation. Notable fluctuations were observed in the outlet samples over time, suggesting variations in water quality at this stage. A Venn diagram highlighted the presence of 1399 shared microeukaryotic ASVs, compared to 1188 unique ASVs at the inlet and 637 at the outlet (Additional file 1: Fig. S6).

Distribution of protozoa in WSPs

The heatmap illustrates the relative abundance of the top 30 microeukaryotic taxa, predominantly associated with groups such as Opisthokonta, Alveolata, Chlorophyta, and Stramenopiles (Additional file 1: Fig. S7). Notably, the heatmap does not show protozoan taxa (Apicomplexa and amoebae), indicating that they are rare within the data set. Statistical analysis (ANOSIM: R = 0.171, p = 0.024) revealed significant variations in protozoa structure throughout the wastewater treatment process (Table 1), with a particularly marked reduction in species such as Acanthamoeba during the anaerobic treatment stage (Table 3). Vermamoeba vermiformis demonstrated higher prevalence compared to Acanthamoeba in the anaerobic and facultative stages, suggesting it possesses greater resistance to the specific conditions or treatments employed at these stages.

Table 3 Prevalence of Acanthamoeba and Vermamoeba vermiformis in each treatment stages. The presented results by microscope and confirmed by PCR

Both organisms showed some degree of removals (25% for Acanthamoeba and 50% for Vermamoeba vermiformis), as indicated by their intermittent absence in the outlet samples, but their occasional presence at the outlet also suggests potential shortcomings in the treatment process or the resilience of these organisms. These results were supported by 18S rRNA amplicon sequencing as depicted in Table 4. Specifically, at least one ASV of Vermamoeba vermiformis was detected in each outlet sample (Table 4). Naegleria australiensis and Vahlkampfia avara were exclusively found in the inlet samples, while Naegleria gruberi was identified in both inlet and outlet samples, highlighting different survival or removal dynamics. More details are available in Table 4. The predominance of Apicomplexa species, known to be associated with animal parasites, aligns with the wastewater treatment plant’s role in servicing areas with extensive domestic animal husbandry (Additional file 1: Table S2). It is evident that the WWTP effectively reduces a significant portion of Apicomplexa parasites, underscoring its efficiency in managing apicomplexan parasites (Additional file 1: Table S2).

Table 4 Amoebae species (ASVs) in inlet samples (Atins03, Atins04, Atins05) and outlet samples (Atms03, Atms04, Atms05) generated from high throughput amplicon 18S rRNA sequencing

Shifts in microalgal communities across wastewater treatment stages

The structure of the microalgal consortium displayed significant changes attributable to the treatment processes. Notably, substantial alterations in the algal community structures were observed between the inlet stage and the subsequent anaerobic, facultative, and outlet stages, as statistically validated by (PERMANOVA: P = 0.002), with additional details provided in Table 1. Similar to bacteria, the algal community exhibited a strong correlation with DO, DO%, and NH₄–N, as illustrated in Additional file 1: Fig. S4. A comprehensive survey identified a total of 13 phytoplankton species distributed across four major taxa groups. Chlorophyta was the most diverse, with eight species, dominated by Chlamydomonas sp. Cyanophyta, represented by four species, was most notably characterized by Spirulina maxima. Euglenophyta was represented by a single species, Euglena sp., as shown in Fig. 8.

Fig. 8

Heatmap of the algal community in different treatment stages. Z-scores demonstrating all samples were represented by the median-centered Z-scores as the relative abundance levels

Analysis of the heatmap presented in Fig. 8 indicates that the inlet and anaerobic stages were predominantly characterized by cyanophyta, specifically Oscillatoria limntica, Oscillatoria chlorina, and Merismopedia elegans. In contrast, the facultative pond stage displayed a markedly diverse microalgal community, including diatom species such as Cyclotella comta and Nitzschia linearis (Additional file 1: Fig. S8). In addition, multiple Chlorophyta species were detected, including Scenedesmus obliquus, Scenedesmus quadricauda, Chlorella vulgaris, Oocystis lacustris, Ankistrodesmus falcatus, Aktinastrum sp., and Crucigenia quadrata. Transitioning to the outlet stage, Spirulina maxima emerged as the most dominant species, aligning with a significant increase in algal counts observed in both the facultative and outlet stages, indicative of the wastewater treatment process’s efficacy. This surge in algal proliferation coincided with increases in pH and DO levels, underscoring the environmental shifts that favor algal growth (Fig. 8).

Discussion

Efficiency of waste stabilization ponds in treating wastewater

WSPs are designed to biologically treat a variety of constituents including organic matter, suspended solids, viruses, pathogens, and nutrients. The ratio of BOD to COD effectively indicates that the domestic wastewater is well-suited for this type of biological degradation [22, 30]. At the first stage of treatment, wastewater enters the anaerobic pond, primarily targeting the reduction of BOD. This stage typically yields effluent with moderate removal efficiencies for organic matters, total phosphorus, and nitrate. Notably, a slight increase in effluent pH might result from the hydrolysis of organic nitrogen into ammonia, where anaerobic microorganisms further convert organic matter into CO2 and methane [54]. This finding aligns with the results of Aziz et al., they observed similar removal efficiencies for COD and BOD in anaerobic ponds treating slaughterhouse wastewater [55].

Following anaerobic treatment, the effluent settles into the facultative pond, where increased pH levels are typically observed due to heightened algal activity [30]. Algae play a crucial role in nitrogen absorption, leading to ammonia stripping and pH elevation. Moreover, nitrification processes primarily conducted by ammonia oxidizing bacteria (AOB) and nitrite oxidizing bacteria (NOB) lead to increased concentrations of nitrate and nitrite. The facultative pond supports a complex microbial ecosystem across its upper aerobic, lower anaerobic, and intermediate zones, facilitating various nitrogen removal mechanisms including assimilation, volatilization, sedimentation, nitrification, and denitrification [56, 57]. However, the resultant effluent quality often deteriorates due to the significant algal biomass, which increases the organic load, although pathogen die-off is facilitated by high pH and solar radiation [58].

The maturation pond at Atfih WSPs receives effluent from the facultative pond, aimed at further improving the quality of the final effluent to make it suitable for irrigating both wooden and oil-producing trees. The recorded moderate efficiencies in COD and could be attributed to potential deficiencies in maintenance, operation, or the design of the Atfih WSP. Although the hydraulic retention time (HRT) at Atfih WSP ranges from 35 to 38 days, this extended duration did not influence the reduction of chemical oxygen demand (COD), consistent with observations by Mahaparta et al. [59]. Other factors may contribute to the efficiency of WWTP, such as the location of the pond, weather conditions, temperature, and pond depth [31].

Overall, the Atfih WSP represents a sustainable, straightforward, and energy-efficient method for treating domestic wastewater. The quality of the final effluent generally meets the ECP 501 guidelines for irrigation purposes, except for one sample. This deviation may be attributed to the decay and die-off of certain algae, which elevate the BOD concentration in the final effluent [60]. To enhance system performance, routine maintenance, pond de-sludging, recirculation, and optimization of operational conditions are essential. In addition, managing algal blooms, particularly the dominance of filamentous forms like Spirulina maxima, which obstructs light penetration (Fig. 8), is crucial for improving the efficiency of the Atfih WSP.

Viral prevalence, removal efficiency, and public health implications

Prior to this study, viral gastroenteritis was not monitored at this wastewater treatment plant. Analyzing untreated wastewater has emerged as a viable alternative to fecal specimen testing, serving as an effective tool for identifying circulating enteric viruses within the population. Sewage systems aggregate microbial pathogens excreted by humans over a wide area, facilitating their transport to wastewater treatment plants for processing. Studies have shown correlations between the types and concentrations of enteric microorganisms in wastewater and the incidence of disease in the population [61].

In this study, monitoring confirmed the presence of all seven viruses in Atfih WSPs. Notably, the prevalence of rotavirus (RV) in untreated wastewater was 100%, mirroring findings from Beijing, where RV was detected in all untreated wastewater samples [62]. The prevalence rates of HAdV, HAV, and HpyV in untreated sewage were similar (83.3%), which were higher than NoV GI (33.3%), NoV GII (66.7%), AstV (66.7%), and PapiV (50%). HAV prevalence in this study, determined through reverse transcription (RT), was 83.3%, lower than the prevalence observed by Villar et al. in Brazil [63], but higher than that in sewage samples from India [64]. The detection rate of PapiV in this study was higher in raw sewage than those reported in pervious from Egypt (33.3%) and Uruguay (34%) [65, 66]. The detection rate of NoV GI was lower than NoV GII in this study, which is consistent with our previous study that NoV GII is commonly detected in the aquatic environment [15], suggesting that NoV GII may be more resistance to the environmental conditions than NoV GI.

The mean concentrations of RV and HAdV were lower than those reported in our previous studies and others [67, 68], where concentrations reached 10⁸ in urban sewage. The concentration of HAV in raw sewage (2.53 × 10⁵ GC/L) was higher than those detected in another study, where HAV titers did not exceed 8.9 × 10² GC/ml of raw sewage [63]. Despite HPyV and PapiV not being traditionally considered enteric viruses, their widespread occurrence in the human population and their presence in urine suggest their utility as indicators of human fecal pollution [69]. In our study, HPyV concentrations in raw wastewater reached 4.26 × 10⁵ GC/ml and were lower than concentrations detected in other wastewater studies from different countries and Egypt [63, 65, 69].

The mean log₁₀ viral removal rates in treated effluent ranged from 1.83 for adenovirus (AdV) to 5.94 for rotavirus (RV), indicating variability in viral stability and treatment efficacy. The maturation ponds, responsible for virus removal, demonstrated complex performance dependent on the interactions among chemical factors (e.g., pH), physical factors (e.g., sunlight), and the microbial community, as well as the efficiency of virus adsorption to solids [70,71,72,73]. This study also found that higher temperatures may enhance virus reduction (Fig. 6). However, the limited sample size and the moderate temperature range observed during our study could lead to bias in this observation. Our network analysis revealed a significant negative correlation between ciliates (Ciliophora) and both viruses and bacterial pathogens, suggesting predation as a mechanism for pathogen removal. In addition, associations between parasitic protists such as Dientamoeba, Entamoeba, and Giardia and their potential predators (ciliates and rotifers) indicate a complex ecosystem facilitating pathogen control within the ponds, as evidenced in a previous study [74].

The data from the present study showed positive correlation between rotavirus and bacterial indicators as well as bacterial pathogens (Additional file 1: Fig. S3). This is consistent with a previous study by Pisharody et al. [75] but contrasts with others [76, 77], which show negative correlations between rotavirus and bacterial indictors. In general, correlations between enteric viruses and bacterial indicators depend on number of factors, including geographical location, natural environment and survivability, size of sample, positive percent detection rate, concentration loads of pathogens in samples, and anthropogenic activities [78].

We attempted to find viruses that meet the necessary criteria for viral indicators based on high abundance in raw sewage and low viral removal in treated effluent where it may be used for routine monitoring. One of the most significant results of this research is that HAdV and HPyVs may be a good viral indicator in the aquatic environments. This is because they were detected in both raw and treated effluent with a relatively high concentrations and lower log reduction during the entire wastewater treatment, suggesting their high persistence during wastewater treatment process. Consistent with the pervious study, HAdV, HPyV have been proposed as useful viral indicator of human fecal contamination due to their high occurrence in sewage contaminated water [79]. One limitation of our study is the absence of infectivity assay or even applying PMA pretreatment for the samples prior to qPCR test as a possible way to differentiate between inactivated virus and viable virus [80].

Protozoa taxa profiling in wastewater stabilization ponds

This study represents the inaugural profiling of protozoa taxa in WSPs. We identified several species within the Amoebozoa and Apicomplexa groups, as detailed in Tables 4 and S2. Notably, our findings highlight the presence of apicomplexan parasites, predominantly those associated with animal hosts such as Babesia and Theileria. These parasites have been documented in wastewater in prior studies [7, 81]. Importantly, we observed a significant reduction in these apicomplexan parasites in the outlet samples of the WSPs, indicating effective removal processes. The detection of Acanthamoeba and Vermamoeba species in the Atfih wastewater stabilization ponds (WSP) may be attributed to deficiencies in the operational upkeep and the pressing need for comprehensive equipment overhauls, alongside repairs to the structural integrity of the pond systems. In our pervious study, the M.K. WSP failed to remove the parasitic nematode ova to reach the acceptable limit for the Egyptian regulations [10]. It was observed that the M.K. WSP suffered from improper maintenance and required renovations to almost all the equipment and repairs to the pond structure [10]. Pathogen elimination can be considerably reduced by malfunctions caused by inadequate maintenance [82]. Several studies have reported a high level of human enteric parasites, bacteria, protozoa, and viruses in treated wastewater [7, 10, 83]. Pathogens removal is attributed to the adsorption onto the settleable solids and sedimentation process [58].

Role of microalgal consortium in wastewater treatment

Microalgal consortium have been identified as excellent indicators of environmental conditions and aquatic health within ponds, corroborated by prior research [84]. These organisms are particularly sensitive to changes in biomass and density [85], as evidenced in our study (Fig. 8, S4). This sensitivity primarily arises from their varied tolerance to environmental conditions [86]. Consistent with previous findings [84], the dominant species within these consortia in our study belong to the phyla Chlorophyta, Bacillariophyta, and Cyanophyta, which are adept at thriving in diverse and challenging environmental conditions. Specifically, Cyanophyta, or blue–green algae, are particularly well-adapted to environments characterized by low oxygen levels and high organic loads, conditions commonly encountered during the early stages of wastewater treatment [87].

These algae possess adaptive traits that enable them to endure harsh conditions and outcompete other organisms. Their dominance in the inlet and anaerobic stages of treatment is attributed to their robust adaptability. Notably, many cyanophyta, such as Spirulina maxima, exhibit a filamentous growth form that facilitates the formation of dense mats or colonies. This structural adaptation not only allows efficient capture of light and nutrients but also provides a protective barrier against predation, enhancing their competitive edge [29]. However, the filamentous structure also harbors a downside as it can shield pathogens, demonstrated by a positive correlation observed between algae and bacterial pathogens in our network analysis (Additional file 1: Fig. S2). The interaction between filamentous microalgae and bacteria in oxidation ponds is complex, with the dense algal mats providing a conducive microenvironment for bacterial colonization. These mats not only offer protection but also nutrients and attachment sites for bacteria, which in turn contribute to the degradation of organic matter. However, excessive filamentous microalgal growth can lead to imbalances in the microbial community, favoring certain bacterial species that are associated with the filaments. These bacteria can produce extracellular polymeric substances (EPS) that contribute to the formation of the dense mats. To maintain the proper functioning of oxidation ponds, it is important to monitor and manage filamentous microalgal blooms. Strategies such as controlling nutrient inputs, maintaining appropriate hydraulic conditions, and implementing mechanical or biological methods for filament removal can help mitigate the negative impacts of filamentous microalgae and promote effective wastewater treatment [88].

Conclusions

This comprehensive study elucidated the crucial efficacy of the investigated WSP, showcasing substantial reductions in microbial and viral loads across various treatment stages. The application of multivariate statistical approaches has distinctly outlined shifts in physicochemical and microbial parameters, which are predominantly influenced by treatment processes rather than temporal variations. Notably, there has been a significant removal of enteric viruses, parasites, and bacterial pathogens observed at the outlet. In addition, the role of Ciliophora as consumers may have significantly contributed to the reduction of viral loads. Furthermore, the dominance of Spirulina maxima in the maturation pond, with its mat-forming capabilities, suggests potential interference with optimal pathogen removal processes, meriting further investigation into pond management practices to mitigate this effect. Despite the high efficiency of pathogen removal, substantial initial microbial loads can result in considerable concentrations in the final effluent. These findings underpin the necessity for rigorous pathogen standards in national wastewater reuse regulations to safeguard public health and safety.