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Article

Microbiological Characterization and Pathogen Control in Drying Bed-Processed Sewage Sludge

1
Environmental Research Center (CRE), Avenue BOUGHAZI SAID, Sidi Amar, Annaba 23001, Algeria
2
Biotechnology Research Center (C.R.Bt), Constantine 25016, Algeria
3
Faculty of Natural and Life Sciences and Earth and Universe Sciences, Department of Biology, University of 8 Mai 1945 Guelma, P.O. Box 401, Guelma 24000, Algeria
4
Univ Rennes, National School of Chemistry of Rennes, CNRS, ISCR (Institute of Chemical Sciences of Rennes)—UMR 6226, F-35000 Rennes, France
5
Department of Chemistry, College of Science, King Saud University, Riyadh 11451, Saudi Arabia
6
Institut Européen des Membranes, IEM, UMR-5635, University Montpellier, ENSCM, CNRS, Place Eugene Bataillon, 34090 Montpellier, France
7
Functional Materials Group, Gulf University for Science and Technology (GUST), Mubarak Al-Abdullah 32093, Kuwait
8
NanoStruc Research Group, Chemistry Department, Faculty of Science, Helwan University, Cairo 11795, Egypt
*
Authors to whom correspondence should be addressed.
Water 2024, 16(22), 3276; https://doi.org/10.3390/w16223276
Submission received: 3 September 2024 / Revised: 9 November 2024 / Accepted: 10 November 2024 / Published: 14 November 2024
(This article belongs to the Special Issue Resource Use of Sewage Sludge for Soil Application)

Abstract

:
This study investigated the microbiological and parasitic quality of sewage sludge treated in drying beds in Algeria, aiming to contribute to a better understanding of the factors influencing sludge safety for potential agricultural applications in the Algerian context. The research focused on various sludge types (liquid, semi-solid, and solid) and their behavior across different seasons. Standard microbiological methods were employed to quantify total coliforms, fecal streptococci, E. coli, and Clostridium. Controls were implemented to ensure accuracy, with positive controls validating detection methods using known quantities of microorganisms and parasites, while negative controls confirmed the absence of contamination in the testing environment. Parasitic contamination was assessed through microscopic examination for protozoa and helminths. Results revealed substantial variation in microbial concentrations across sludge types and seasons. Liquid sludge, particularly during summer, exhibited the highest levels of total coliforms (up to 7.021 log10) and E. coli (up to 6.049 log10), while solid sludge showed lower counts. Seasonal trends indicated increased microbial levels during warmer months. Parasitic contamination was prevalent in 81% of samples, with protozoan cysts (e.g., Giardia intestinalis and Endolimax nanus) and helminth eggs detected. Despite reducing microbial loads, drying processes alone were insufficient, leaving significant contamination. Enhanced protocols are needed, such as longer drying periods, chemical disinfectants, or advanced technologies like anaerobic digestion or composting. This highlights the need for locally adapted treatment strategies. Furthermore, this research provides specific recommendations for improving sewage sludge management practices in Algeria, taking into account the unique environmental and agricultural context of the country.

1. Introduction

Water is a vital resource for life, and its purity is closely linked to both environmental protection and human health. With industrialization and urbanization on the rise, the volume of wastewater generated worldwide has increased substantially, creating a pressing need for effective management [1]. On average, an individual uses between 150 and 200 L of water daily, much of which is transformed into wastewater that must be treated to remove contaminants before being safely discharged into the environment. Wastewater treatment plants (WWTPs) play a critical role in this process by filtering pollutants and safeguarding water quality. However, wastewater treatment also produces sewage sludge, a by-product rich in organic matter, nutrients (such as nitrogen and phosphorus), microorganisms, and contaminants like heavy metals and persistent organic pollutants [2]. The composition of sewage sludge varies widely depending on the wastewater source and treatment processes, presenting a challenge for its safe management. Globally, the production of sewage sludge is projected to reach nearly 13 million dry tons annually by 2025, underscoring the need for innovative solutions for its treatment, disposal, and potential reuse in agriculture and energy recovery. This increasing volume of sludge necessitates a transition toward a circular economy approach, where sludge is viewed as a resource rather than a waste product. As highlighted by Capodaglio and Callegari [3], sludge contains significant quantities of recoverable materials, including energy, nutrients, and raw materials, that can be valorized through various processes such as enhanced anaerobic digestion, thermochemical technologies, and biorefinery approaches. These strategies offer opportunities for greater energy self-sufficiency, reduced greenhouse gas emissions, soil fertilization, and the substitution of raw materials for various industries, contributing to a more sustainable and resource-efficient wastewater treatment cycle.
Escalating production of sewage sludge in Algeria presents a critical environmental management challenge, with the National Sanitation Office estimating a daily output of 539 tons, underscoring the urgent need for sustainable treatment and disposal solutions [4]. Improper management of this waste poses substantial risks to public health and the environment due to pollutants such as heavy metals, persistent organic pollutants, and pathogens, including bacteria, viruses, and parasites [5,6]. Key challenges include inadequate treatment infrastructure, high technology costs, limited awareness of health risks, and the absence of a comprehensive regulatory framework for sludge reuse, particularly in agriculture [7]. Drying beds, a commonly employed method for treating sewage sludge, rely on natural evaporation and percolation to reduce water content and microbial load. While well-suited to hot, dry climates, drying beds may be less effective in cooler or more humid regions, where alternative methods like solar greenhouses may offer more controlled environments and enhanced efficiency. Studies, including those by Boguniewicz-Zablocka et al., demonstrate the advantages of solar greenhouse drying, such as reduced land requirements, lower energy consumption, and significantly higher evaporation rates compared to conventional drying beds [8]. The effectiveness of drying beds is heavily influenced by climatic factors like temperature and humidity, which impact pathogen inactivation rates [9,10]. Sewage sludge, increasingly used as a soil amendment in agriculture due to its nutrient-rich content, requires careful management to mitigate risks posed by pathogens, heavy metals, and organic pollutants, necessitating strict adherence to treatment guidelines and heavy metal limits [11,12]. Research into the performance of drying beds under diverse environmental conditions will enhance our understanding of the factors influencing pathogen reduction, particularly in the Algerian context, where untreated sewage sludge has been shown to harbor a range of pathogens, including Salmonella, Clostridium, and helminth eggs, posing significant health risks if not adequately treated [13].
A thorough evaluation of the microbiological quality of sewage sludge and the effectiveness of different treatment methods is necessary, particularly considering Algeria’s diverse climatic conditions and agricultural practices. Additionally, the potential presence of emerging contaminants, such as triclosan, and their environmental impact [14] necessitates further investigation. Regular monitoring of sewage sludge for fecal indicator bacteria and pathogens, especially before land application, is crucial for ensuring its safety [15]. Monitoring protocols should be tailored to local climatic conditions, as significant seasonal variations in bacterial communities and antibiotic resistance genes have been observed in wastewater treatment systems [16,17,18,19,20,21,22]. Optimizing drying bed performance based on local climate factors, such as temperature and humidity [23], and exploring additional treatment processes like composting or anaerobic digestion, especially in cooler or wetter climates [24], are also essential considerations. Guidelines should recommend appropriate soil types and crop selections for sludge application, considering the risk of pathogen persistence in soils and potential human exposure through the consumption of crops [25,26,27]. Developing region-specific standards for sewage sludge application in Algeria, in line with international best practices and local conditions, is crucial for long-term sustainability, as Capodaglio and Callegari [2] emphasize. Sustainable management of sludge requires a holistic approach, including energy and resource recovery tailored to regional contexts and aligned with circular economy principles. This includes adapting treatment technologies and reuse strategies to local conditions and considering the varying nature of sludge and market demands. Establishing such standards in Algeria will not only ensure safe and efficient sludge management but also contribute to the development of a more sustainable and resilient agricultural sector. The prevalence of parasites in sewage sludge [28,29,30] highlights the need for enhanced disinfection practices and robust regulatory measures. Future research should address the evaluation of various disinfection methods [13], as well as the long-term effects of sludge application on soil health and crop quality [31]. The microbiological quality of sewage sludge is paramount for safe utilization, particularly in agriculture, as pathogens in sludge can contaminate soil, crops, and groundwater, threatening human and animal health [32]. Therefore, a rigorous assessment of microbial and parasitic contamination is essential for protecting environmental and public health.
This study characterizes the microbial and parasitic communities in sewage sludge from five wastewater treatment plants (WWTPs) located in eastern Algeria. It also evaluates the efficacy of drying beds as a treatment method, aiming to explore the impact of sludge age, season, and treatment plant location on microbial populations to inform best management practices. The study has three primary objectives: (1) to characterize the microbial and parasitic communities in sewage sludge from five WWTPs in northeastern Algeria, (2) to evaluate the effectiveness of drying beds in reducing sludge pathogens, and (3) to analyze seasonal variations in microbial and parasitic loads. Liquid (LS), semi-solid (BS1), and solid (BS2) sludge samples were systematically collected from the five WWTPs across four seasons. Standard microbiological techniques were employed to quantify fecal contamination indicators such as total coliforms, Escherichia coli, and fecal streptococci. Microscopic examination was used to assess parasitic contamination, identifying and quantifying protozoa and helminths. This paper is structured as follows: Section 2 details the study sites and methodology; Section 3 presents the microbiological and parasitological analysis results; Section 4 discusses the implications of our findings for Algerian sludge management, proposing future research directions; and Section 5 concludes the paper, summarizing the key results and highlighting their significance for sustainable sludge management.

2. Experimental

2.1. Study Sites

This study focused on five major wastewater treatment facilities in Algeria’s northeastern region, chosen for their significant role in reducing the environmental impacts of wastewater. Alongside treating wastewater, these facilities generate substantial amounts of sewage sludge, which requires safe management to mitigate health and environmental risks.
  • Bourdj Bou Ariridj (BBA) WWTP (S1): Located in the southern part of Bourdj Bou Ariridj city, this plant covers an area of 42,750 m2 and processes a daily flow of 30,000 m3. It serves 150,000 equivalent residents using a low-load activated sludge process. The treated water is released into the Oued K’sob river, which supports irrigation downstream. In October 2013, the plant produced approximately 180 m3 of sludge.
  • Sidi Marouane WWTP (S2): Positioned 12 km northwest of the Mila wilaya seat, this facility processes wastewater from multiple localities, aiming to reduce pollution in the Beni Haroun dam. It has a capacity for 137,711 equivalent people. In November 2013, the facility produced around 24,386 m3 of sludge.
  • Ibn Ziad WWTP (S3): Situated 12 km northeast of Constantine, this plant spans 12 hectares and serves 450,000 equivalent people. It treats a portion of the city’s low-load wastewater.
  • El Rabta WWTP (S4): Located 2 km west of Jijel’s wilaya seat, this plant covers 5.9 hectares and serves 150,000 people (with future expansion to 225,000). It has been operational since June 2008. The plant generated 224 m3 of sludge in October 2013.
  • Guelma WWTP (S5): Found north of Guelma city, along national road No. 21, this plant has been operational since 18 February 2008. It spans eight hectares, treats wastewater for 200,000 equivalent residents, and processes a daily flow of 43,388 m3. The facility produced 9288 m3 of sludge in October 2013.

2.2. Sampling

Sampling was conducted from the drying beds of the five WWTPs. Three types of sludge were sampled:
  • Liquid Sludge (LS): Collected directly from the drying beds on day zero.
  • Semi-Dry Sludge (BS1): Collected after 1 to 2 months of drying.
  • Fully Dry Sludge (BS2): Collected after more than six months of drying.
Four sampling campaigns were carried out for each station, one per season. Samples were collected following stringent hygienic procedures, immediately placed in sterile plastic bags, labeled, and stored in a refrigerated chamber (1–4 °C) to ensure analysis within a maximum of eight hours.

2.3. General Dilution Technique

The general dilution technique was utilized to count bacteria in the sludge samples. A 10 g sample was mixed for 20 min with 100 mL of sterile distilled water to create a master suspension. This suspension was then diluted in decimal increments up to 1/1000 (10−3) for further analysis [33].

2.4. Bacterial Enumeration

Bacterial enumeration in sludge samples was conducted using selective and differential culture techniques to quantify and identify various bacterial groups commonly associated with fecal contamination and anaerobic environments. These methods allowed for a comprehensive analysis of bacterial indicators in the sludge.
To enumerate total coliforms, bromocresol purple lactose broth (BCPL) with Durham tubes was used as an indicator of coliform presence. Each sludge sample was added to BCPL tubes, which were then incubated at 37 °C ± 2 °C for 24 to 48 h. Following incubation, results were evaluated using the most probable number (MPN) method, referencing the Mac Grady table [34,35]. This approach allowed for an estimation of coliform levels based on a change in color within the broth, confirming the presence of coliform bacteria in the samples.
Escherichia coli (E. coli), a key indicator of fecal contamination in sewage sludge, was specifically targeted due to its association with potential health risks. E. coli can signal the likelihood of pathogens in the sludge, which is of particular concern for its agricultural applications. To detect E. coli, Schubert medium (Bio-Rad) was prepared as per the manufacturer’s guidelines, with a loopful of bacterial culture from a positive BCPL tube added to 10 mL of Schubert medium containing mannitol. These tubes were incubated at 44 °C for 48 ± 2 h, after which gas production from mannitol fermentation was observed. The presence of a red ring after adding 5 drops of Kovac’s reagent confirmed E. coli. This methodology aligns with previous protocols for E. coli detection and quantification in wastewater and sludge [36].
For fecal streptococci enumeration, Rothe medium (Oxoid) was prepared according to the manufacturer’s instructions for fecal streptococci enumeration. A 1 mL sample of sludge was added to 9 mL of Rothe medium and incubated at 37 °C for 48 ± 2 h. Following initial incubation, a loopful of culture from a positive Rothe tube—indicated by turbidity—was streaked onto an Eva Litsky agar plate. These plates were subsequently incubated at 37 °C for another 48 ± 2 h. The appearance of pinpoint, smooth, gray colonies with a dark red halo confirmed the presence of fecal streptococci [37]. This method provided specific confirmation of fecal streptococci, adding another layer of microbial analysis to assess contamination levels.
The presence of Clostridium species, particularly anaerobic sulfite-reducing bacteria, was also investigated due to the health risks associated with pathogens like Clostridium perfringens. These bacteria can form highly resistant endospores, which highlight the necessity for thorough sludge treatment. To detect these organisms, samples were cultured on deep agar containing sodium sulfite and incubated anaerobically at 36 °C ± 2 °C for 24 to 48 h. Positive results were indicated by the appearance of white colonies with a black halo, which occurs due to the reduction of sodium sulfite to iron sulfide. This detection of sulfite-reducing Clostridium species served as a crucial indicator of anaerobic conditions within the sludge and thus the need for effective disinfection practices [38].

2.5. Parasitological Examination

Parasitological examination of the sludge involved various concentration and enrichment techniques to identify and quantify protozoa and helminth eggs. Three different concentration procedures were employed, followed by two flotation methods using potassium iodomercurate (d = 1.44). This method, known as the flotation-concentration technique, is commonly used for recovering helminth eggs and protozoa from various samples.
Specifically, the following methods were used.
  • Concentration methods: The three concentration procedures included sedimentation, filtration, and centrifugation. Sedimentation allows heavier particles, including parasites, to settle at the bottom of the sample. Filtration removes large debris using a fine-mesh filter. Centrifugation uses centrifugal force to separate parasites from the surrounding medium.
  • Flotation methods: The two flotation methods employed flotation with potassium iodomercurate and flotation with sodium dichromate. These techniques utilize the density difference between parasites and the surrounding medium to concentrate the parasites.
Furthermore, specific techniques were used for specific parasites, as follows.
  • Giardia spp. cysts: Giardia spp. cysts were concentrated using the Teleman-Rivas two-phase method, modified by Bailenger [39], which incorporates ether and an acetoacetic buffer. This technique is particularly effective for separating and concentrating Giardia cysts from other materials in the sludge.
  • Helminth eggs: For detecting helminth eggs, the Dada and Lindquist technique from [40], employing sodium dichromate (d = 1.2), was utilized. This method is widely used for recovering helminth eggs for microscopic analysis [41].

2.6. Data Analysis

Data were analyzed using analysis of variance (ANOVA), and comparisons between groups were conducted using the HSD and Tukey tests. Statistical analyses were performed with XL Stat 2016 and Graph Pad Prism 7.
Significant differences between groups were indicated using the following symbols:
ns: non-significant;
*: significant (p < 0.05); **: highly significant (p < 0.01); ***: very highly significant (p < 0.001); This thorough approach ensured a comprehensive evaluation of the microbiological and parasitological safety of the sludge from the selected WWTPs.

3. Results

The results of this study provide a comprehensive analysis of the microbial and parasitic content of sewage sludge from various treatment plants in Algeria. This section presents detailed findings on the concentrations of total coliforms, E. coli, and fecal streptococci across different types of sludge (liquid, semi-solid, and solid) and seasonal variations. Additionally, it highlights the presence and distribution of various parasitic organisms, including protozoa and helminths, within sludge samples. These results are crucial for understanding the efficacy of different sludge treatment methods and the potential health risks associated with sludge use in agriculture.

3.1. Seasonal Variations in Bacterial Counts in the BS1 Sludge

The study’s data (Table 1, Figure 1) reveal pronounced seasonal variations in the bacterial counts of total coliforms, E. coli, and fecal streptococci in BS1 sludge across five wastewater treatment plants. A notable increase in total coliforms and E. coli was observed during the summer, particularly at stations S1 and S2. Total coliform counts surged significantly, reaching values of 8.15 log CFU/g at both stations, with lower values in winter (5.82 log CFU/g in S1 and 5.02 log CFU/g in S2). Similarly, E. coli counts peaked during summer, with concentrations as high as 7.8 log CFU/g in S1 and 7.4 log CFU/g in S2, with winter counts of 4.86 log CFU/g in S1 and 4.30 log CFU/g in S2. These trends can be attributed to the effect of temperature on microbial growth, with warmer conditions in summer fostering rapid bacterial proliferation. Studies by Pallares-Vega et al. [21] and Ji et al. [23] support these findings, indicating that higher temperatures above 20 °C significantly boost the multiplication of fecal indicator bacteria such as E. coli and total coliforms.
Interestingly, the counts of fecal streptococci displayed less pronounced seasonal variation, with only minor fluctuations across stations. For instance, in S2, the fecal streptococci count increased slightly to 5.0 log CFU/g during summer, but remained relatively stable at other times, such as 4.30 log CFU/g in winter (Table 1). This stability in fecal streptococci counts could be due to their resilience to environmental stressors. Heckman and Soto [42] suggest that fecal streptococci, unlike coliforms and E. coli, can survive under a broader range of conditions due to their ability to form biofilms and their enhanced resistance to temperature fluctuations.
The significant summer spike in total coliforms and E. coli counts highlights the role of temperature in shaping microbial dynamics in sludge (Figure 1). Warmer temperatures enhance microbial metabolism, leading to higher bacterial counts, a trend widely supported by the literature. Al-Gheethi et al. [24] noted that increased water consumption and agricultural runoff during summer could introduce higher levels of organic and fecal matter into treatment plants, further contributing to the elevated bacterial loads observed. Conversely, during winter and autumn, microbial counts decreased, with total coliforms and E. coli showing reductions to around 5.82 log and 4.86 login S1, respectively (Figure 1). These lower counts can be explained by cooler temperatures and decreased microbial activity during these seasons, as also reported by Miguel et al. [15], who found that reduced temperatures and moisture levels hinder bacterial growth in sludge.

3.2. Seasonal Variations in Bacterial Counts in the BS2 Sludge

The data presented in Table 2 and Figure 2 demonstrate distinct seasonal variations in the bacterial counts of total coliforms (TC), E. coli, and fecal streptococci (SF) in the solid sewage sludge (BS2) across five wastewater treatment plants. These variations reveal trends similar to those seen in liquid sludge (BS1), but with different magnitudes and seasonal responses.
The total coliform (TC) counts in BS2 showed notable increases during the autumn season across multiple stations, with a peak of 8.15 log CFU/g in S1, which is consistent with similar high readings in other stations like S2 (7.18 log CFU/g) and S3 (6.978 log CFU/g) during the same season. These findings suggest that autumn, likely due to favorable environmental conditions such as moderate temperatures and increased organic matter in sludge, encourages the growth of coliforms. This observation aligns with research by Zhang et al. [20], which showedthat organic matter in sludge combined with moderate post-summer temperatures can result in higher bacterial activity. Interestingly, summer did not exhibit the same level of increase in total coliforms across all stations. While S1 recorded a moderate increase to 5.40 log CFU/g, stations like S4 and S5 showed smaller variations, with S5 registering only a slight increase from 4.653 log CFU/g in summer to 4.398 log CFU/g in autumn. This lower response to summer temperatures could be due to solid sludge’s reduced moisture content, which may inhibit bacterial growth compared to more hydrated sludge types like BS1.
In the case of E. coli, the counts showed significant fluctuations between seasons, with peaks occurring in both summer and autumn. For instance, in S3, E. coli counts rose to 6.875 log CFU/g during summer, before slightly decreasing to 6.398 log CFU/g in autumn. Similarly, S1 exhibited a rise to 6.30 log CFU/g in autumn, significantly higher than winter counts (4.23 log CFU/g). The enhanced growth of E. coli during summer can be attributed to the warmer temperatures that promote rapid bacterial multiplication, as supported by Schages et al. [22], who found that higher temperatures fostered E. coli proliferation in sludge. However, the trends also reveal some variability across stations. For example, S5 displayed a smaller variation, with E. coli counts only slightly rising from 3.041 log CFU/g in winter to 3.602 log CFU/g in autumn. The relatively modest increase could be attributed to local environmental conditions, such as lower moisture content or differences in sludge composition, which may inhibit the growth of E. coli. Xu et al. [19] and Wei et al. [18] suggest that variations in sludge composition and moisture can affect the seasonal growth patterns of bacteria in sewage sludge.
The fecal streptococci (SF) count in BS2 showed much smaller seasonal variations compared to total coliforms and E. coli. For instance, S1 demonstrated consistent counts across the seasons, fluctuating between 3.01 log CFU/g in winter and 4.65 log CFU/g in autumn. This minimal variation aligns with the findings of López et al. [43], who suggest that fecal streptococci, due to their resilience to environmental changes, exhibit less pronounced seasonal variations compared to other bacterial indicators like E. coli. Station S5, however, experienced a decline in fecal streptococci counts during autumn, from 3.398 log CFU/g in summer to 2.398 log CFU/g in autumn. This decline may be linked to environmental factors such as changes in pH or nutrient availability that could limit the survival of fecal streptococci in solid sludge during colder seasons. Stiborova et al. [31] further support this observation, suggesting that nutrient depletion in more compact, solidified sludge can impact the long-term viability of fecal bacteria.
The trends in BS2 sludge mirror those seen in BS1 sludge, but with differences in the magnitude of seasonal fluctuations. The lower water content and more compact nature of solid sludge seem to moderate the seasonal increases in bacterial counts. This is particularly evident in the less pronounced summer peaks for both total coliforms and E. coli in BS2 compared to BS1. This finding is consistent with Wang et al. [14], who suggest that drier conditions in sludge lead to reduced microbial activity.

3.3. Seasonal Variations in Bacterial Counts in the LS Sludge

The data presented in Table 3 and Figure 3 reveal distinct seasonal trends in the bacterial counts of total coliforms (TC), E. coli, and fecal streptococci (FS) in liquid sewage sludge (LS) across five wastewater treatment plants. These seasonal variations reflect the influence of environmental conditions, particularly temperature and moisture, on microbial proliferation in liquid sludge.
The total coliform (TC) counts in liquid sludge exhibited substantial increases during the warmer seasons, particularly in summer and autumn. For example, in S1, TC counts reached a peak of 8.15 log CFU/g during autumn, after rising steadily from 6.15 log CFU/g in spring and 6.40 log CFU/g in summer. Similar patterns were observed in other stations, such as S2 and S3, where TC counts also peaked in summer and autumn, with S3 showing a maximum of 8.146 log CFU/g in summer. The consistent increase in TC during warmer seasons can be attributed to higher temperatures that accelerate bacterial growth, as supported by Szyłak-Szydłowski and Miaśkiewicz-Pęs [17], who found that elevated temperatures promoted the multiplication of coliform bacteria in wastewater environments. However, the results also suggest that the effects of temperature on bacterial proliferation in liquid sludge can vary depending on station-specific conditions. For instance, S5 showed relatively lower TC counts compared to other stations, with a peak of only 4.398 log CFU/g in summer. This could be due to differences in treatment processes, moisture content, or organic matter composition across the stations, as highlighted by Stiborová et al. [44], who noted that variations in sludge composition can significantly impact bacterial growth patterns.
Similarly to total coliforms, E. coli counts in liquid sludge also exhibited clear seasonal trends, with notable peaks in the warmer months. For instance, in S1, E. coli counts increased from 4.00 log CFU/g in winter to 7.40 log CFU/g in autumn, mirroring the TC trend. S3 displayed a comparable pattern, with E. coli counts rising from 2.954 log CFU/g in winter to 7.653 log CFU/g in summer. The higher counts in summer and autumn can be attributed to the same temperature-driven acceleration of bacterial growth observed for total coliforms. These seasonal fluctuations are in line with the findings of Pallares-Vega et al. [21], who demonstrated that E. coli levels in sludge tend to increase during warmer periods due to enhanced microbial activity. Moreover, the high moisture content of liquid sludge likely facilitates bacterial proliferation during these periods, as moisture provides a conducive environment for bacterial survival and growth. Interestingly, while E. coli counts followed a similar seasonal pattern across most stations, some stations exhibited less pronounced seasonal variations. For example, in S4, E. coli counts remained relatively stable across the seasons, with a peak of 7.699 log CFU/g in spring and slightly lower counts in other seasons. This suggests that while temperature plays a significant role, other factors such as nutrient availability and sludge processing methods also influence E. coli proliferation in liquid sludge.
The fecal streptococci (FS) count in liquid sludge was less affected by seasonal variations compared to total coliforms and E. coli. For example, in S1, FS counts varied only slightly across the seasons, ranging from 3.33 log CFU/g in winter to 4.95 log CFU/g in autumn. Similar trends were observed in other stations, where FS counts exhibited only modest fluctuations throughout the year. This relative stability in FS counts aligns with the findings of Fonti et al. [45], who noted that fecal streptococci are more resistant to environmental changes than other bacterial indicators. Their resilience to temperature fluctuations and varying environmental conditions may explain why their counts did not exhibit the same dramatic increases as total coliforms and E. coli during the warmer seasons. The data indicate that temperature and seasonality have a significant impact on the microbial content of liquid sludge, particularly for total coliforms and E. coli. Warmer temperatures in summer and autumn consistently resulted in higher bacterial counts, suggesting that these seasons require more rigorous sludge treatment protocols to mitigate the risks associated with microbial contamination. This observation is consistent with Jiao et al. [16], who emphasized the need for seasonal adjustments in wastewater treatment processes to account for increased bacterial growth during warmer periods. Fecal streptococci, on the other hand, exhibited greater stability across the seasons, likely due to their higher resistance to environmental stressors. This suggests that fecal streptococci may be a less reliable indicator of seasonal variations in sludge quality compared to total coliforms and E. coli.

3.4. Analysis of Bacterial Loads Across Different Sludge Types

The drying beds used in this study were open-air beds with a typical surface area exceeding 60 square meters. No specific controls were applied to the drying process; sludge was naturally dried under ambient temperature and sunlight. The average temperature during the study period ranged from −2 °C to 35 °C, with variations depending on the season and the geographical location of the treatment plant. Similarly, humidity varied from 35% to 80% depending on the season and location. The drying time for the sludge varied from 20 days up to 30–60 days, depending primarily on the season and the specific geographical location. This is consistent with the findings of Masmoudi et al. [46], who reported varying drying times for sewage sludge depending on the drying technique and season.
Analysis of Table 4 and Figure 1, Figure 2 and Figure 3 reveals key trends in bacterial loads across different sludge types (BS1, BS2, and LS), stations (S1 to S5), and seasons. Middle-aged sludge (BS1) consistently showed higher bacterial populations compared to fresh sludge (LS) and dry sludge (BS2). For instance, at station S1 during summer, BS1 showed a significant increase in total coliforms (CT) and E. coli, with values marked as CF↑ and CT↑. This trend aligns with findings by Luo et al. [47] and Søberg et al. [48], who noted that sludge aged one month or more harbored greater bacterial loads due to favorable temperature and humidity conditions. Conversely, bacterial populations in BS2 were significantly lower than in BS1 and LS, likely due to dehydration and reduced microbial activity. At station S2, E. coli counts in BS2 during winter were markedly reduced, noted as ns (non-significant), supporting the effectiveness of drying in pathogen reduction.
Seasonal variations also played a crucial role, with bacterial loads generally increasing in the warmer months. For example, at station S3, fecal streptococci (SF) in LS rose during the summer, while CT levels similarly increased in BS1 during autumn across various stations. This demonstrates how warmer temperatures and higher humidity facilitate bacterial growth. However, in winter, bacterial populations declined notably across all sludge types, particularly in BS2. At station S4, winter CT and E. coli counts in BS2 were significantly lower, indicated as ns and *, reflecting the suppressive effect of colder temperatures on microbial growth.
Station-specific trends highlight varying bacterial dynamics. Station S1 showed consistently higher CT and E. coli levels, especially in fresh sludge (LS) during summer (*CF↑, CT↑), while station S2 experienced peak CT populations in autumn and increased E. coli in summer. Station S3 was distinguished by the highest SF counts during summer, while station S5 consistently reported lower bacterial loads across all sludge types and seasons. These combined observations underscore the significant influence of sludge age, seasonal environmental factors, and station-specific conditions on bacterial populations.

3.5. Total Coliform (TC) Enumeration

Table 5 shows substantial variability in total coliform (TC) counts across different sludge types and stations. The highest TC count in dry sludge (BS2) was recorded at station S1 in autumn, with a value of 8.15 log10. In contrast, the lowest TC count in fresh sludge (LS) was observed at station S5 during spring, with a value of 3.29 log10. Dry sludge (BS2) consistently had lower TC concentrations compared to semi-solid sludge (BS1), with a notable reduction rate of up to 99.77% in summer and an average reduction of 56% at station S1. Statistical analysis (HDS, TUKY test) revealed significant differences in TC loads for middle-aged sludge (BS1) at station S1 during autumn and summer. For example, TC levels in BS1 during summer were 7.215 log10, while in winter, they were lower. Similarly, in fresh sludge (LS), TC counts varied significantly across seasons, with spring and summer exhibiting higher values. At station S2, TC counts increased significantly in summer and autumn for all sludge types. Station S3 also showed notable variations across seasons, with autumn exhibiting higher TC levels. At station S4, significant TC loading differences were observed in spring, summer, and autumn, whereas station S5 showed minimal variation in TC levels.

3.6. E. coli Enumeration

Table 5 indicates that middle-aged sludge (BS1) had the highest E. coli concentrations, particularly in summer at station S2, where the maximum value reached 7.55 log10 MPN/gTS. In fresh sludge (LS) at the same station, the highest E. coli concentration was 7.65 log10 MPN/gTS. Conversely, the lowest E. coli values were recorded in dry sludge (BS2) at station S5 during summer, at 2.68 log10 MPN/gTS. The average E. coli load across sludge types was 5.23 log10 MPN/gTS, which is notably higher than the 2 to 2.2 log10 MPN/gTS reported by López et al. [49]. Compared to semi-solid sludge (BS1), E. coli levels in dry sludge (BS2) decreased by an average of 65%, with a maximum reduction of 99.15% observed at station S1 during summer.

3.7. Fecal Streptococci (SF) Enumeration

Table 5 shows that semi-solid sludge (BS1) consistently had higher fecal streptococci (SF) concentrations compared to fresh (LS) or dry sludge (BS2). The highest SF concentration of 6.84 log10 MPN/gTS was recorded in summer at station S3. In contrast, the lowest SF concentration of 1.90 log10 MPN/gTS was found in dry sludge (BS2) at station S2 during spring. The average reduction in SF concentration in dry sludge (BS2) was 56%, with a maximum reduction of 96% observed during warmer periods. Statistical analysis (two-way ANOVA) indicated significant associations between SF and other bacterial species across all stations except S1 and S5. For instance, summer SF levels in semi-solid sludge (BS1) at station S3 were 4.186 log10 MPN/gTS, significantly higher compared to spring values. Conversely, in fresh sludge (LS) and dry sludge (BS2) at station S2, significant reductions in SF concentrations were observed during spring.

3.8. Clostridium Enumeration

Analysis revealed remarkably high concentrations of anaerobic sulfite-reducing bacteria (ASR) in all sludge samples, irrespective of sludge type, season, or treatment plant. In all cases, colony counts were too numerous to quantify, indicating a substantial presence of these microorganisms. This contrasts with the findings of Houari et al. [50], who reported that sulfate-reducing prokaryotes constituted only 5% of the total microbial community in anaerobic digesters treating municipal sewage sludge in Marrakech, Morocco. While their study focused on the role of these bacteria in sulfide production, our findings suggest that the abundance of ASR in drying beds may be significantly higher.
Furthermore, Huang et al. [51] found that shorter sludge retention times (SRTs) promoted the enrichment of diverse sulfate-reducing bacteria (SRB) in anaerobic digesters. Although our study did not specifically investigate the effect of SRTs, the consistently high ASR counts observed across all sludge ages imply that drying beds may provide favorable conditions for the proliferation of these bacteria, regardless of retention time. It is important to note that while these studies used molecular techniques to characterize microbial communities, our study relied on culture-dependent methods, which may explain some of the observed differences. Further research employing molecular approaches is needed to confirm the abundance and diversity of ASR in drying beds and explore their potential implications for sludge treatment and valorization.

3.9. Search for Parasites

Table 6 provides a detailed overview of the parasitic contamination found in sewage sludge samples from various treatment stations in Algeria. The investigation revealed a significant presence of parasites, with 81% of samples examined and 50% containing protozoa or helminth eggs. Identified parasites include Giardia intestinalis cysts, Endolimax nanus cysts, Chilomastixmesnili vegetative forms, and protozoan flagella. For instance, Giardia intestinalis cysts were detected at stations S1 and S3 during summer, while Endolimaxnanus cysts were found at stations S2 and S4. Additionally, strongyloid larvae, nematode eggs, and Blastocystis spp. were observed, highlighting a predominance of nematode larvae, which is consistent with the findings of Sabbahi et al. [52], who conducted a parasitological assessment of sewage sludge in Tunisia. They also reported a low concentration of helminth eggs, with a mean value of less than 1 egg/100 g DM, aligning with our observations. The diversity of parasites across different stations and seasons indicates complex contamination patterns.
Similar to the study by Benito et al. [28] who investigated the presence of intestinal protozoa and nematodes in wastewater treatment plants in Spain, our findings demonstrate the widespread occurrence of these parasites in sewage sludge. They also highlighted the challenges of removing these resistant organisms during wastewater treatment. Similarly, Zahedi et al. [29] used 18S rRNA next-generation sequencing to identify eukaryotic microorganisms in wastewater treatment plants in Western Australia. They detected various protozoan parasites, including Endolimax spp., Entamoeba spp., and Blastocystis spp., but emphasized the need for more targeted sequencing approaches for specific pathogen detection.
At Sidi Marouane, nematode larvae and Blastocystis spp. were found in spring liquid sludge, with solid sludge showing Entamoeba coli cysts and nematode eggs. Jijel’s samples presented protozoan flagella and Endolimax nanus cysts, while BBA showed Giardia intestinalis cysts and Enteromonas spp. in liquid sludge and flagellate protozoa and yeasts in solid sludge. Our results align with those of Zdybel et al. [30], who found a high prevalence of Ascaris spp., Toxocara spp., and Trichuris spp. eggs in dehydrated municipal sewage sludge in Poland. Their study emphasized the potential for environmental contamination and health risks associated with the land application of untreated sludge.

4. Discussion

Differences in microbial loads observed in the sewage sludge samples can be attributed to several factors, most notably the age of sludge and the treatment methods employed. The data indicate that middle-aged sludge (BS1, 1–3 months old) consistently harbors higher microbial densities compared to both fresh liquid sludge (LS) and dry sludge (BS2, older than six months). This phenomenon was likely due to the optimal conditions for bacterial growth provided by BS1, which included adequate moisture, high organic content, and a favorable temperature range of 35–37 °C [53,54]. In contrast, dry sludge (BS2) exhibited significantly lower microbial loads, a result supported by the substantial decrease in bacterial counts (CT, E. coli, SF) observed, often exceeding a 99% reduction compared to BS1.
In accordance with Guzman et al. [55] and López et al. [43], microbial densities in raw sewage sludge were considerably high, with concentrations frequently surpassing 106, except for bacteriophages infecting Bact. fragilis, which had an average concentration of 5.7 × 105 per 10 g dry matter. This aligns with findings from Erkan, and Saninansi [56] and Kaetzl et al. [57], who noted that sewage treatment plants using belt filters typically have higher indicator bacteria levels compared to those utilizing centrifugal dewatering. The substantial reduction in microbial load observed in dry sludge can be attributed to the dehydration process, which significantly curtails microbial survival and activity.
Seasonal temperature variations also play a critical role in microbial dynamics. Summertime temperatures particularly favored the proliferation of coliforms and thermotolerant fecal coliforms (E. coli), as high temperatures and abundant organic matter enhanced the load of total coliforms, E. coli, streptococci, and other pathogens [58,59,60]. This seasonal influence underscores the necessity of adjusting treatment strategies to mitigate microbial risks effectively.
Extended sludge storage presents an alternative method for pathogen reduction, though its efficacy can vary. Li et al. [13] describes strategic storage as a moderately effective treatment for pathogen reduction, but it can still support bacterial growth under certain conditions. This explains the lower bacterial loads observed in dry sludge compared to liquid and middle-aged sludges. While drying beds offer a simple and cost-effective method for reducing pathogens in sewage sludge, their effectiveness can be influenced by factors such as sludge type, weather conditions, and the drying technique used, as shown by Masmoudi et al. [46], who compared drying beds with draining greenhouses under natural and forced convection. Their results indicated that draining greenhouses with forced convection achieved faster drying compared to traditional drying beds, especially during winter. This suggests that alternative drying methods, particularly those with enhanced evaporation through controlled conditions, might improve the efficiency of sludge treatment.
It is important to consider their potential integration with or use as a standalone alternative to other treatment methods such as anaerobic digestion and composting. Anaerobic digestion can effectively reduce organic load and pathogens while producing biogas, a valuable renewable energy source [61,62]. Composting, on the other hand, transforms sludge into a stable, nutrient-rich product ideal for soil amendment [63,64,65]. These methods are not mutually exclusive and can be combined to achieve synergistic benefits. For instance, drying beds can be used to pretreat sludge before anaerobic digestion, reducing the volume and improving the digester’s efficiency. Similarly, composted sludge can be further dried on beds to reduce moisture content and enhance its stability. The choice of a treatment strategy, whether standalone or combined, should consider local factors such as climate, available resources, treatment objectives (e.g., pathogen reduction, resource recovery), and the intended use of the treated sludge. Economic considerations, including the costs of implementation, operation, and maintenance for each method, should also be factored into the decision-making process.
The impact of sewage sludge on agricultural soils and crop quality is substantial. Similar to the findings of Boudjabi and Chenchouni [26], who showed that mulching with sludge improves soil properties and crop yields, Douaer et al. [66] found that applying sewage sludge, especially when combined with mineral fertilizers, enhances various physicochemical and biological properties of agricultural soil. Their study emphasized the positive impact of sludge on soil organic matter, structure, water retention, and nutrient availability, alongside increased microbial activity (bacteria, fungi, and azotobacter), consistent with our observations of beneficial microorganisms in treated sludge. However, they also stressed the need to assess sludge toxicity before application and to adapt treatments based on soil and crop needs. This reinforces the importance of considering the integrated effects of sludge application on soil health and crop production.
While our study focused primarily on the microbiological and parasitological characterization of sewage sludge treated in drying beds, our findings have important implications for its potential agricultural use in Algeria. The significant reduction in microbial loads observed after drying, especially during warmer months, suggests that drying beds can be an effective treatment method for reducing pathogen risks associated with land application. However, the persistence of certain bacteria, such as anaerobic sulfite-reducing bacteria (ASR), and the prevalence of parasites highlight the need for complementary treatment or disinfection strategies to ensure sludge safety. Additionally, the observed variability in microbial loads across different treatment plants underscores the need for site-specific monitoring and treatment protocols. It is important to acknowledge that this study focused solely on the microbiological and parasitological aspects of sewage sludge. Further research is needed to assess the potential impacts of sludge application on soil properties, such as salinity and permeability, as well as the long-term accumulation of pollutants, including heavy metals, pharmaceuticals, and microplastics, in agricultural soils. This aligns with the concerns raised by Merdas et al. [67] regarding the potential for large-scale biotic homogenization in arid Mediterranean steppe rangelands due to livestock grazing, suggesting that careful management of grazing practices in areas receiving sludge applications is essential for preserving biodiversity.
Our study offers crucial insights into the microbiological and parasitological quality of sewage sludge treated in drying beds in northeastern Algeria. Our findings underscore the critical need to consider sludge age, seasonal variations, and individual treatment plant characteristics when assessing the potential for agricultural reuse. The significant presence of fecal indicator bacteria and parasites in some samples emphasizes the need for optimizing sludge treatment and minimizing land application risks. Specifically, our findings indicate that drying bed effectiveness varies seasonally, with reduced pathogen reduction observed during colder months. Furthermore, microbial loads differ significantly across treatment plants, highlighting the need for site-specific monitoring and tailored treatment strategies. Moreover, parasites persist even after the drying process, necessitating additional disinfection methods to ensure safe agricultural use. The local climate also significantly influences drying bed performance, often requiring adjustments in drying periods or the implementation of alternative methods in less arid regions. Additionally, standardized quality criteria for sewage sludge incorporating microbial and parasitic parameters are essential in Algeria.
Finally, training and awareness programs are crucial for promoting effective and safe sludge management practices. These findings have important implications for developing context-specific guidelines for safe sludge utilization in Algeria, especially considering the potential risks associated with pathogens, heavy metals, and emerging contaminants like triclosan [14]. Prioritizing regular monitoring of fecal indicator bacteria and pathogens, adapting monitoring protocols to local climate variations [15,16,17,18,19,20,21,22], optimizing drying bed parameters according to local climate factors [23], and exploring additional treatment options like composting or anaerobic digestion [24] are all crucial. Furthermore, careful consideration of soil types and crop selections for sludge application [25,26,27] and the development of region-specific standards, as advocated by Capodaglio and Callegari [2] in their holistic analysis of sludge management strategies, is essential, along with the implementation of enhanced disinfection practices, for ensuring the safe and sustainable use of sewage sludge. Capodaglio and Callegari [2] highlight the importance of adapting sludge treatment and resource recovery processes to the specific characteristics of the sludge, local conditions, and market demands. This localized approach, combined with effective disinfection practices, is crucial for maximizing the benefits of sludge reuse while minimizing potential risks to public health and the environment. Future research should focus on evaluating various disinfection methods [13] and the long-term impacts of sludge application on soil health and crop quality [31], particularly within the Algerian context.
Future research should prioritize several key areas. Firstly, evaluating various dis-infection methods for sewage sludge is crucial for ensuring its safe use. Secondly, investigating the long-term impacts of sludge application on soil and crop health, including heavy metal accumulation and potential transfer to the food chain, is essential for sustainable agricultural practices. Thirdly, optimizing drying bed parameters, such as depth, retention time, and turning frequency, can enhance pathogen reduction and improve odor control. Furthermore, assessing the feasibility of anaerobic digestion for biogas production and its economic viability in the Algerian context should be explored. Additionally, exploring alternative sludge valorization pathways, including biochar production, its use in construction materials, and soil remediation, could offer sustainable solutions. Moreover, conducting life cycle assessments of different sludge management options is crucial for minimizing environmental impacts. Finally, developing specific regulations and guidelines for sewage sludge utilization in Algeria, aligned with international best practices while considering local conditions, is essential for responsible and effective sludge management.

5. Conclusions

This study provides a detailed evaluation of microbial and parasitic content in sewage sludge from various treatment plants in Algeria, revealing the influence of sludge age, treatment methods, and seasonal variations. Our data demonstrate that middle-aged sludge (BS1, 1–3 months old) generally exhibits the highest microbial densities. For instance, total coliform counts in BS1 reached 7.215 log10 (S3) and E. coli concentrations were as high as 6.126 log10 (S3). This high microbial load can be attributed to the optimal conditions for bacterial growth, including sufficient moisture, rich organic matter, and elevated temperatures. In contrast, dry sludge (BS2, older than six months) showed significantly reduced microbial loads. For example, total coliform counts in BS2 at S5 were as low as 4.114 log10 and E. coli counts were reduced to 4.043 log10. This reduction reflects the effectiveness of the drying process in diminishing microbial presence, with a decrease rate of over 99% for coliforms and a substantial drop in E. coli concentrations compared to BS1. Seasonal variations also play a crucial role in microbial populations. During summer, high temperatures were conducive to increased coliform and E. coli counts, as observed with total coliform counts reaching 7.021 log10 (S3) and E. coli reaching 6.049 log10 (S3) in liquid sludge. These findings are consistent with studies indicating that elevated temperatures and high organic matter levels enhance microbial proliferation. The parasitic content in the sludge further underscores the need for rigorous treatment. Our investigation revealed the presence of various parasites, including Giardia intestinalis cysts, Endolimax nanus cysts, and nematode eggs. For example, Giardia intestinalis cysts were detected at several stations, including Sidi Marouane in spring and Guelma in summer. These findings align with previous research and highlight the potential health risks associated with untreated or inadequately treated sludge. The significant variation in parasitic presence across different seasons and sludge types emphasizes the need for comprehensive treatment protocols to mitigate these risks.

Author Contributions

Conceptualization, L.B., N.C., H.N., K.D., N.G., Y.D., A.A. and A.B.; data curation, L.B., N.C., H.N., K.D., N.G., Y.D., A.A., H.A., D.C. and M.B.; formal analysis, L.B., N.C., H.N., K.D., N.G., Y.D., A.A. and H.A.; funding acquisition, H.A., D.C., M.B. and A.B.; investigation, L.B., N.C., H.N., K.D., N.G., Y.D., A.A., H.A., D.C., M.B. and A.B.; methodology, L.B., N.C., H.N., K.D., N.G., Y.D., A.A. and A.B.; project administration, H.A., D.C., M.B. and A.B.; resources, L.B., N.C., H.N., K.D., N.G., Y.D., A.A., H.A., D.C. and M.B.; software, L.B., N.C., H.N., K.D., N.G., Y.D. and A.A.; supervision, H.A., D.C., M.B. and A.B.; validation, L.B., N.C., H.N., K.D., N.G., Y.D. and A.A.; visualization, L.B., H.A., D.C., M.B. and A.B.; writing—original draft, L.B., N.C., H.N., K.D., N.G., Y.D., A.A., D.C., M.B. and A.B.; writing—review and editing, L.B., H.N., K.D., A.A., H.A., M.B. and A.B. All authors have read and agreed to the published version of the manuscript.

Funding

This research received funding from the Researchers Supporting Project (RSPD2024R604), King Saud University, Riyadh, Saudi Arabia.

Data Availability Statement

The original contributions presented in the study are included in the article. Further inquiries can be directed to the corresponding author.

Acknowledgments

First and foremost, we would like to express our deep gratitude to DGRSDT for providing both material and moral support for this project. We also extend our sincere appreciation to the CRBt management, as well as all the engineers, technicians, and researchers in the laboratory for their invaluable contributions. Our profound thanks go to L’EpicEdevco Constantine and all individuals who played a role in the successful execution of this study. We are also grateful to the ONA, the government, and the staff and workers of the wastewater treatment facilities in Bordj Bou Arreridj, Guelma, Constantine, Mila, and Jijel for their assistance and cooperation. Additionally, we would like to acknowledge the support provided by the Researchers Supporting Project (RSPD2024R604), King Saud University, Riyadh, Saudi Arabia.

Conflicts of Interest

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest. The authors declare that they were editorial board members of Frontiers at the time of submission. This had no impact on the peer review process or final decision.

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Figure 1. Seasonal variations in total coliforms (TC), E. coli, and fecal streptococci (SF) in sewage sludge (BS1) across five wastewater treatment plants.
Figure 1. Seasonal variations in total coliforms (TC), E. coli, and fecal streptococci (SF) in sewage sludge (BS1) across five wastewater treatment plants.
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Figure 2. Seasonal variations in total coliforms (TC), E. coli, and fecal streptococci (SF) in solid sewage sludge (BS2) across five wastewater treatment plants.
Figure 2. Seasonal variations in total coliforms (TC), E. coli, and fecal streptococci (SF) in solid sewage sludge (BS2) across five wastewater treatment plants.
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Figure 3. Seasonal variations in total coliforms (TC), E. coli, and fecal streptococci (SF) counts in liquid sewage sludge (LS) across five wastewater treatment stations.
Figure 3. Seasonal variations in total coliforms (TC), E. coli, and fecal streptococci (SF) counts in liquid sewage sludge (LS) across five wastewater treatment stations.
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Table 1. Tabular representation of seasonal variations in total coliforms (TC), E. coli, and fecal streptococci (SF) in sewage sludge (BS1) from five different wastewater treatment plants.
Table 1. Tabular representation of seasonal variations in total coliforms (TC), E. coli, and fecal streptococci (SF) in sewage sludge (BS1) from five different wastewater treatment plants.
SeasonStationSludgeTC1 log 10TC2TC3E.coli1E.coli2E.coli3SF1SF2SF3
WintS1BS15.8205.550 4.8603.950 3.3514.190
Spr6.4005.401 4.9804.400 4.1804.300
Sum8.150 ***8.150 *** 6.880 **6.401 ** 4.1824.540
Aut8.150 ***8.15 *** 6.850 **7.300 ** 4.6505.180
WintS25.0205.145 4.3004.492 3.4013.944
Spr5.1805.176 3.9503.845 2.4012.263
Sum8.150 ***8.041 *** 7.401 **7.667 ** 4.4024.699
Aut8.150 ***8.146 *** 7.180 **6.890 ** 3.4053.875
WintS35.0415.146 3.3983.954 3.1763.301
Spr7.398 **7.978 ** 6.398 **5.978 ** 2.9543.653
Sum8.146 ***8.041 *** 7.398 **6.954 ** 5.176 *7.146 *
Aut8.041 ***7.653 ** 7.398 **7.123 ** 3.3983.041
WintS45.1465.146 4.8754.602 4.4774.398
Spr7.954 **8.146 *** 7.201 **7.398 ** 4.4774.398
Sum7.146 **7.146 ** 6.398 *6.301 * 4.3984.875
Aut7.146 **7.146 ** 6.301 *6.398 * 3.8753.653
WintS54.3814.3984.3984.1924.3984.1763.8363.8453.810
Spr4.1463.9543.3984.3983.9544.0012.9782.1762.978
Sum4.875 *4.568 *4.3394.3984.5443.8042.3982.6533.702
Aut4.6534.1764.3234.3013.0223.8502.6532.2042.813
Notes: ns: not significant, *: significant (p < 0.050), **: highly significant (p < 0.010), ***: very highly significant (p < 0.001).
Table 2. Detailed tabular data of seasonal variations in bacterial counts, including total coliforms (TC), E. coli, and fecal streptococci (SF), in solid sewage sludge (BS2) from five wastewater treatment plants.
Table 2. Detailed tabular data of seasonal variations in bacterial counts, including total coliforms (TC), E. coli, and fecal streptococci (SF), in solid sewage sludge (BS2) from five wastewater treatment plants.
SeasonStationSludgeTC1TC2TC3E.coli1E.coli2E.coli3SF1SF2SF3
WintS1BS25.3405.320 4.2303.850 3.1703.010
Spr5.4004.980 3.6013.950 3.3013.480
Sum5.4015.601 4.6014.650 3.4013.300
Aut8.150 ***8.15 *** 4.9506.301 3.4004.650
WintS24.8305.026 4.3004.399 3.3403.395
Spr4.8804.954 3.6003.653 1.4002.130
Sum6.850 *7.386 ** 6.600 *6.802 * 3.6503.807
Aut7.180 **7.365 ** 6.400 *6.921 * 2.9502.987
WintS34.9784.041 2.9542.477 2.9543.041
Spr6.978 *6.653 * 5.9546.398 3.3983.398
Sum7.602 **7.176 * 6.875 *6.602 * 5.041 *6.653 *
Aut6.978 *6.759 * 6.3986.659 3.1762.954
WintS44.9784.845 3.6994.398 3.9543.653
Spr7.477 **7.845 *** 6.813 *6.602 * 3.9543.653
Sum6.845 *7.041 * 6.1765.978 3.8133.653
Aut7.041 *6.653 * 4.9784.602 3.6533.398
WintS54.1724.1764.3014.0233.0413.9542.5112.3982.114
Spr3.1463.3983.4773.0412.6022.6532.6021.9541.954
Sum4.6534.6534.3182.6022.3012.9233.3983.1762.898
Aut4.3984.1854.3073.6023.8973.8342.3982.2412.793
Notes: ns: not significant, *: significant (p < 0.050), **: highly significant (p < 0.010), ***: very highly significant (p < 0.001).
Table 3. Tabular representation of seasonal fluctuations in total coliforms (TC), E. coli, and fecal streptococci (SF) concentrations in liquid sewage sludge (LS) across five wastewater treatment stations.
Table 3. Tabular representation of seasonal fluctuations in total coliforms (TC), E. coli, and fecal streptococci (SF) concentrations in liquid sewage sludge (LS) across five wastewater treatment stations.
SeasonStationSludgeTC1TC2TC3E.coli1E.coli2E.coli3FS1FS2FS3
WintS1BL4.1904.220 4.0053.403 3.3303.220
Spr6.150 **5.650 * 4.8504.180 3.1803.401
Sum6.401 **6.950 ** 4.4074.950 3.1503.402
Aut8.150 ***8.150 *** 6.400 **5.98 ** 4.950 *4.650 *
WintS24.9025.359 4.9804.463 3.2603.492
Spr4.6005.653 3.8804.176 1.4012.134
Sum8.150 ***7.452 ** 7.401 **7.807 ** 3.4023.913
Aut8.150 ***8.041 *** 7.401 **6.532 ** 3.4013.988
WintS34.9784.653 2.9542.398 2.3982.653
Spr7.653 ***7.653 *** 7.176 **6.653 * 3.3983.041
Sum8.146 ***7.477 ** 7.653 **6.978 ** 3.8873.653
Aut7.398 **7.818 *** 6.653 *7.204 ** 2.9783.398
WintS44.9545.146 4.0414.398 3.3983.653
Spr8.146 ***8.146 *** 7.699 **7.398 ** 2.8162.653
Sum7.146 **6.954 ** 6.398 *5.602 3.8753.653
Aut5.9547.041 * 4.6024.398 2.6533.176
WintS53.2673.6533.3983.0273.0412.3982.9773.0003.081
Spr3.1463.3983.3013.3012.9543.9542.9782.6022.978
Sum4.398 *4.653 *4.3514.1764.3983.9103.6023.9543.882
Aut4.0414.2874.3803.3982.4713.8052.1762.1932.796
Notes: ns: not significant, *: significant (p < 0.050), **: highly significant (p < 0.010), ***: very highly significant (p < 0.001).
Table 4. Significant differences in the bacterial loads found in the various sludges.
Table 4. Significant differences in the bacterial loads found in the various sludges.
Station
Season
Sludge TypeWinterSpringSummerAutumn
S1BS1nsCF↑, CT↑CF↑, CT↑ns
BS2nsns*CF↑, CT↑ns
LSnsCT↑, CF↑nsCF↑, CT↑
S2BS1nsCF↑, CT↑CF↑, CT↑ns
BS2SF↓CF↑, CT↑CF↑, CT↑ns
LSSF↓***CF↑, CT↑*CF↑, CT↑ns
S3BS1CF↑, CT↑CF↑, CT↑, SF↑CF↑, CT↑ns
BS2CF↑, CT↑, SF↑CF↑, CT↑, SF↑CF↑, CT↑ns
LSCF↑, CT↑CF↑, CT↑CF↑, CT↑ns
S4BS1CF↑, CT↑*CF↑, CT↑*CF↑, CT↑ns
BS2CF↑, CT↑***CF↑, CT↑CT↑ns
LS*CF↑, CT↑**CF↑, CT↑**CF↑, CT↑ns
S5BS1ns**ns
BS2ns**ns
LSns**ns
Notes: ns: not significant; *CF↑: significant increase in coliforms; **CF↑: highly significant increase in coliforms; ***CF↑, CT↑: very highly significant increase in coliforms and total coliforms; SF↓: decrease in fecal streptococci; SF↑: increase in fecal streptococci; ↑: increase; ↓: decrease.
Table 5. Estimated average bacterial counts in liquid, semi-solid, and solid sludges across different stations.
Table 5. Estimated average bacterial counts in liquid, semi-solid, and solid sludges across different stations.
Liquid Sludge (LS)
Station/SpeciesTC log10E. coli log10FS log10p
S16.270 ± 0.1374.855 ± 0.0343.675 ± 0.017p < 0.001 significant
S26.650 ± 0.1445.911 ± 0.1063.203 ± 0.056
S37.021 ± 0.0656.049 ± 0.0843.205 ± 0.133
S46.761 ± 0.0775.626 ± 0.0583.232 ± 0.133
S53.877 ± 0.0883.547 ± 0.1193.059 ± 0.108
Semi-Solid Sludge (BS1)
Station/SpeciesTCE. coliFSp
S17.035 ± 0.0815.804 ± 0.0254.394 ± 0.013p < 0.00 significant
S26.627 ± 0.0955.730 ± 0.0913.590 ± 0.079
S37.215 ± 0.0366.126 ± 0.1374.186 ± 0.034
S46.875 ± 0.1096.068 ± 0.0474.339 ± 0.062
S54.351 ± 0.0553.433 ± 0.0742.494 ± 0.113
Solid Sludge (BS2)
Station/SpeciesTCE. coliFSp
S16.06 ± 0.0684.635 ± 0.0783.555 ± 0.025p < 0.001, significant
S26.083 ± 0.0665.357 ± 0.0432.995 ± 0.075
S36.473 ± 0.0325.579 ± 0.1023.968 ± 0.088
S46.615 ± 0.0545.503 ± 0.0783.714 ± 0.056
S54.114 ± 0.0694.043 ± 0.0973.199 ± 0.049
Table 6. Summary of parasite detection in sewage sludge across different seasons and stations.
Table 6. Summary of parasite detection in sewage sludge across different seasons and stations.
StationSludgeWinterSpringSummerAutumn
GuelmaLiquid
-
Endolimax nanus cysts
-
Giardia intestinalis cysts
-
Chilomastixmesnili vegetative forms
-
Flagellate and ciliated protozoan (n. id.)
-
Protozoan flagella (n. id.)
-
Arthrosporous mycelial filaments
-
Nematode eggs
-
Protozoan flagella (n. id.)
-
Endolimaxnanus cysts
-
Arthrosporous mycelial filaments
-
No Treatment Reported (NTR)
Solid
-
Strongyloides larvae
-
Flagellate protozoa (n. id.)
-
Blastocystis spp.
-
Protozoan flagella (n. id.)
-
Arthrosporous mycelial filaments
-
Nematode eggs
-
Filaments mycéliensarthrosporés
-
Protozoan flagella (n. id.)
-
No Treatment Reported (NTR)
Sidi MarouaneLiquid
-
Nematode larvae
-
Giardia intestinalis cysts
-
Vegetative forms and amoeba cysts
-
Protozoan flagella (n. id.)
-
Endolimax nanus cysts
-
Blastocystis spp.
-
No Treatment Reported (NP)
-
No Treatment Reported (NTR)
Solid
-
Nematode larvae
-
Entamoeba coli cysts
-
Mycelial filaments
-
Nematode eggs
-
Alternaria spp.
-
Rabdithoid larvae of nematodes
-
Endolimax nanus cysts
-
Blastocystis spp.
-
Mycelial filaments
-
Nematode larvae
-
Alternaria spp.
-
No Treatment Reported (NTR)
-
No Treatment Reported (NTR)
JijelLiquid
-
No Treatment Reported (NP)
-
Arthrosporous mycelial filaments
-
Protozoan flagella (n. id.)
-
Endolimax nanus cysts
-
No Treatment Reported (NTR)
-
No Treatment Reported (NTR)
Solid
-
No Treatment Reported (NP)
-
Arthrosporous mycelial filaments
-
Vegetative forms and amoeba cysts
-
Endolimax nanus cysts
-
Protozoan flagella (n. id.)
-
Mycelial filaments
-
Endolimaxnanus cysts
-
Protozoan flagella (n. id.)
-
No Treatment Reported (NP)
BBALiquid
-
Giardia intestinalis cysts
-
Enteromonas spp.
-
Trichomonas spp.
-
Yeasts
-
Protozoan flagella (n. id.)
-
Amoeba cysts
-
Nematode larvae
-
Mycelial filaments
-
Yeasts
-
Protozoan flagella (n. id.)
-
Vegetative forms of ciliates
-
Endolimax nanus cysts
-
No Treatment Reported (NP)
Solid
-
Flagellate protozoa (n. id.)
-
Yeasts
-
Mycelial filaments
-
Nematode larvae
-
No Treatment Reported (NTR)
-
No Treatment Reported (NTR)
-
No Treatment Reported (NTR)
ConstantineLiquid
-
No Treatment Reported (NP)
-
Protozoan flagella (n. id.)
-
Endolimax nanus cysts
-
Blastocystis spp.
-
Endolimax nanus cysts
-
Vegetative forms of Endolimax nanus
-
Pseudolimaxbutshliicysts
-
Vegetative forms and amoeba cysts
-
Coccidia oocysts
-
No Treatment Reported (NTR)
Solid
-
No Treatment Reported (NP)
-
Protozoan flagella (n. id.)
-
No Treatment Reported (NTR)
-
No Treatment Reported (NTR)
Notes: NP: not performed; NTR: nothing to report; n. id.: not identified.
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Bouchaala, L.; Grara, N.; Charchar, N.; Nourine, H.; Dahdah, K.; Driouche, Y.; Amrane, A.; Alsaeedi, H.; Cornu, D.; Bechelany, M.; et al. Microbiological Characterization and Pathogen Control in Drying Bed-Processed Sewage Sludge. Water 2024, 16, 3276. https://doi.org/10.3390/w16223276

AMA Style

Bouchaala L, Grara N, Charchar N, Nourine H, Dahdah K, Driouche Y, Amrane A, Alsaeedi H, Cornu D, Bechelany M, et al. Microbiological Characterization and Pathogen Control in Drying Bed-Processed Sewage Sludge. Water. 2024; 16(22):3276. https://doi.org/10.3390/w16223276

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Bouchaala, Laid, Nedjoud Grara, Nabil Charchar, Heidar Nourine, Kamal Dahdah, Youssouf Driouche, Abdeltif Amrane, Huda Alsaeedi, David Cornu, Mikhael Bechelany, and et al. 2024. "Microbiological Characterization and Pathogen Control in Drying Bed-Processed Sewage Sludge" Water 16, no. 22: 3276. https://doi.org/10.3390/w16223276

APA Style

Bouchaala, L., Grara, N., Charchar, N., Nourine, H., Dahdah, K., Driouche, Y., Amrane, A., Alsaeedi, H., Cornu, D., Bechelany, M., & Barhoum, A. (2024). Microbiological Characterization and Pathogen Control in Drying Bed-Processed Sewage Sludge. Water, 16(22), 3276. https://doi.org/10.3390/w16223276

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