Nothing Special   »   [go: up one dir, main page]
Next Article in Journal
Removal of Dyes from Water Using Aluminum-Based Water Treatment Sludge as a Low-Cost Coagulant: Use of Response Surface Methodology
Next Article in Special Issue
Biomonitoring of Waters and Tambacu (Colossoma macropomum × Piaractus mesopotamicus) from the Amazônia Legal, Brazil
Previous Article in Journal
Modeling Forest Snow Using Relative Canopy Structure Metrics
Previous Article in Special Issue
Organic Micropollutants in the Agricultural Chain of Production of Strawberries by Irrigation with Treated Wastewater and Assessment of Human Health Implications
You seem to have javascript disabled. Please note that many of the page functionalities won't work as expected without javascript enabled.
 
 
Search for Articles:
Title / Keyword
Author / Affiliation / Email
Journal
Article Type
 
 
Advanced Search
 
Section
Special Issue
Volume
Issue
Number
Page
 
Journals
Water
Volume 16
Issue 10
10.3390/w16101399
water-logo
Submit to this Journal Review for this Journal Propose a Special Issue
► Article Menu

Article Menu

share Share announcement Help format_quote Cite question_answer Discuss in SciProfiles thumb_up
...
Endorse textsms
...
Comment
first_page
settings
Order Article Reprints
Font Type:
Arial Georgia Verdana
Font Size:
Aa Aa Aa
Line Spacing:
Column Width:
Background:
Article

Wastewater Treatment Plants Performance for Reuse: Evaluation of Bacterial and Viral Risks

by
Ileana Federigi
1,*,
Roberto Salvadori
2,
Giulia Lauretani
1,
Anna Leone
2,
Simone Lippi
2,
Francesca Marvulli
2,
Alessandra Pagani
1,
Marco Verani
1 and
Annalaura Carducci
1
1
Laboratory of Hygiene and Environmental Virology, Department of Biology, University of Pisa, Via S. Zeno 35/39, 56127 Pisa, Italy
2
Acque S.p.A., Via A. Bellatalla 1, 56121 Pisa, Italy
*
Author to whom correspondence should be addressed.
Water 2024, 16(10), 1399; https://doi.org/10.3390/w16101399
Submission received: 8 April 2024 / Revised: 4 May 2024 / Accepted: 11 May 2024 / Published: 14 May 2024
(This article belongs to the Special Issue Integrated Water Cycle: Impact of Treated Wastewater on Water Quality and Human Health Risks)
Browse Figures
Figure 1
<p>Scheme of the sampling strategy along the wastewater treatment stages.</p> "> Figure 2
<p>Interaction plot showing Log<sub>10</sub> <span class="html-italic">E. coli</span> data in the exit effluents under different weather conditions (dry, wet) and chlorination treatment (yes, no), separately for each WWTP: (<b>a</b>) WWTP1, (<b>b</b>) WWTP2. Error bars represent mean ± standard deviation of data distribution for each group.</p> "> Figure 3
<p>Spearman correlation matrix for <span class="html-italic">E. coli</span>, COD, BOD<sub>5</sub>, and TSS in the chlorinated effluents, separately for each WWTP: (<b>a</b>) WWTP1 (66 data for each variable) and (<b>b</b>) WWTP2 (56 data for each variable). Asterisk represents the statistical significance (<span class="html-italic">p</span>) at 0.05 level.</p> "> Figure 4
<p>Relationship between index pathogens and microbial indicators in the exit samples: (<b>a</b>) <span class="html-italic">Salmonella</span> and <span class="html-italic">E. coli</span>, (<b>b</b>) Human Adenovirus (HAdV) and somatic coliphages.</p> ">
Versions Notes

Abstract

:
Reusing reclaimed water is of paramount importance to achieve the 2030 Agenda for Sustainable Development Goals 6 and 13. In Europe, a recent Regulation set minimum requirements for water reuse in agriculture. However, some challenges remain considering microbial risks and their prevention. In this study, two urban wastewater treatment plants (WWTPs) were investigated from the perspective of reuse. A five-year investigation was performed on routine monitoring parameters collected under different weather conditions (wet/dry) and treatments (chlorination/non-chlorination) in inlet and outlet samples. Moreover, a three-month investigation focused on microbial parameters, including indicators, index pathogens (Human Adenovirus—HAdV, Salmonella spp.), and other viral pathogens (norovirus, enterovirus, and SARS-CoV-2). The long-term study revealed the compliance of both WWTPs for chemical parameters (organic substances and solids) in more than 90% of samples, whereas for Escherichia coli, the compliance ranged from 96.1% with chlorination under dry weather to 16.7% without chlorination in wet days. E. coli was positively associated with chemical oxygen demand (COD), which could be a promising and online measurable proxy of E. coli. The study on microbial performance demonstrated sound reliability in detecting E. coli as a suitable surrogate for Salmonella in chlorinated effluents, but neither bacterial nor viral indicators are able to represent HAdV. Although chlorination was able to remove most of the pathogens considered, the compliance with microbial indicators seems insufficient to represent viral water safety.

1. Introduction

Water resources are under pressure as a result of increasing water demand for the irrigation of crops, various water uses, and industrial processes, as well as climate change, which is responsible for persistent droughts that exacerbate water shortages. Such pressure on water causes a deterioration of the quality and quantity of freshwater resources, as a result of pollution, eutrophication and over-exploitation, or drought. In fact, the United Nations reports that half of the world’s population is already experiencing severe water scarcity at least one month a year [1]. In Europe, it was estimated that water stress affected at least 30% of the population on average every year, while up to 70% of the European territory experiences seasonal water stress, mainly during the summer months. In the Mediterranean region and densely populated cities across the EU, water stress is a permanent, year-round issue [2]. Given the global dimension of water issues, they are addressed by the 2030 Agenda, in particular Sustainable Development Goal (SDG) number 6 “Clean water and sanitation”, which is aimed at ensuring the availability and sustainable management of water and sanitation for all [3]. Specifically, water reuse practices are mentioned in Target 6.3 [4], because they are sustainable, affordable, and scalable solutions to fight climate change by reducing the pressure on water resources and increasing water security and resilience [5]. Water reuse also produces benefits from economic and social points of view, reducing energy consumption, supplying water with nutrients for agriculture, and increasing employment [6,7,8]. In recent years, the growing relevance of the integrated use of waste has increased scientific interest worldwide in the assessment of quality and performance of wastewater treatment plants (WWTPs), specifically focused on the potential reuse of treated wastewater, e.g., [9,10,11].
On the other hand, in Europe, only a fraction (2–3%) of treated wastewater is really reused due to various types of barriers: economic regarding the high cost of treatment, regulatory regarding the different requirements among countries, technical regarding the difficulties in reaching the required depuration efficacy, and social, due to the low acceptability of reused water consumption [12]. The same problems have also been experienced by water-scarce countries across North Africa and the Middle East (e.g., Syrian Arab Republic, Egypt, and Israel), although the percentage of reused sewage effluents is higher (up to 70%) compared to Europe due to tackling extreme drought conditions [13]. Among these barriers, the health risks related to reused water contamination are considered prominent and have been assessed through epidemiological and risk assessment studies indicating microbial risks as the most evident ones, in particular for agricultural uses. In the city of Colorado Springs (CO, USA), urban reuse revealed a slight increase in gastrointestinal symptoms among people frequenting public parks irrigated with reused water compared to the use of a conventional water source [14]. Moreover, risk assessment studies reported an increase in gastrointestinal risk from the consumption of vegetables irrigated with treated sewage attributable to enteric viruses, i.e., human adenoviruses and noroviruses [15,16,17], and respiratory risk from the inhalation of Legionellae [18]. In fact, untreated sewage can contain human pathogens (viruses, bacteria, protozoa, and helminth eggs) in very high concentrations, i.e., in the order of 108–1010 per liter [19] and pathogen elimination is highly variable, depending on the treatment scheme and the resistance of the microbes. The WWTPs with conventional processes (e.g., settlement and activated sludge systems) are able to eliminate 20% to 80% of pathogenic enteric viruses [20,21,22,23], with even lower reduction efficiency in the case of (oo)cysts of pathogenic protozoa [24].
In recent years, Europe has been tackling reclaimed water reuse in the agricultural irrigation of crops (EU Regulation 2020/741 [25]) in order to overcome past regulatory issues regarding water quality standards that were too restrictive or inconsistent. The new regulation follows a fit-to-purpose approach; thus, the quality of reclaimed waters can be adjusted to the type of crop: (i) food crops consumed raw, (ii) processed food crops (i.e., cooked or industrially processed), and (iii) non-food crops (e.g., pastures and forage, fiber, ornamental, seeds, and energy). Specifically, reclaimed waters are divided into four water quality classes (A, B, C, and D) on the basis of Escherichia coli, biochemical oxygen demand (BOD5), total suspended solids (TSSs), and turbidity (only for class A); then, other health-relevant monitoring parameters can be added after a risk assessment [26,27]. Although this approach represents an improvement compared to the previous European regulation, some concerns still remain regarding the choice of routine monitoring parameters for the verification (and surveillance) of reclaimed water compliance for reuse applications. Firstly, the removal efficiency of the parameters is considered only for validation monitoring (and only for class A uses), namely, when a system is initially constructed or rehabilitated; however, it can also provide useful insights into the causes of thresholds exceeding in the effluents, such as plant failures (e.g., low dosage of disinfectant) or fluctuation in quality and quantity of the entering sewages, attributable to precipitation (especially in WWTPs served by combined sewer networks) or variations in served populations (e.g., tourism) [28]. Secondly, the microbial requirements are based on E. coli, of which the determination relies on growth-based enumeration methods and does not provide a timely indication of performance; thus, a readily measured chemical proxy of the microbial levels could be useful for the monitoring of treatment efficacy and operational adjustments. Moreover, E. coli is traditionally used as an indicator of bacterial pathogens (e.g., Salmonella spp.), but its reliability regarding the destruction of human viral pathogens is limited because viruses can be more resistant to treatment processes compared to indicators [24]. From a health perspective, the viral contamination of reclaimed waters is relevant since viruses exhibit low infectious doses and can persist in the external environment longer than other pathogens [29,30]. The great variety of pathogens present in wastewater does not allow us to consider all of them in a microbial risk assessment, and thus international guidelines recommend selecting appropriate reference pathogens (also frequently referred to as index pathogens), on the basis of their relevance to the exposure pathway, the representativeness of the likely pathogens from each microbial group (bacteria, protozoa, and viruses), and the availability of the dose–response relationship [31].
In this study, routine monitoring parameters and microbiological parameters including viral and bacterial pathogens were collected from two WWTPs with the aim of (i) understanding the role of external factors (weather conditions) and treatment (chlorination) on WWTP performance; (ii) evaluating the compliance of the current treatments with EU regulations for reuse, specifically looking for a readily measurable proxy to optimize the control of the treatment process; and (iii) investigating the suitability of traditional indicators of index pathogens and pathogenic viruses.

2. Materials and Methods

2.1. Selection of the WWTPs

Two medium-size urban WWTPs located in the Tuscany region coastal area (Italy) were selected for reuse purposes, given the availability of developing an adequate supportive infrastructural framework for water reuse (e.g., accumulation basins to store reclaimed water during periods in which it is not needed and distribution networks to transport them from the WWTP to the point of use). Both WWTPs receive household sewage through separate sewer network structures that are occasionally interested by the intrusion of parasitic rainwaters. Specifically, WWTP1 (approximately 50.000 population equivalent, P.E.) treats wastewater generated by the urban area of the city with a small portion originating from a hospital, whereas WWTP2 (approximately 35.000 P.E.) serves the coastal area of the same Municipality.
The treatment scheme in both WWTPs is based on activated sludge processes for carbon and nitrogen removal and the last stage of chlorine disinfection with sodium hypochlorite (NaClO) at 15% solution strength but with some differences in the concentration and dosage conditions. In WWTP1, the NaClO concentration was set at approximately 15–20 mL/m3, considering a fixed flowrate, whereas in WWTP2, the NaClO concentration was set at 17 mL/m3 and the dosage was adjusted based on the flow of wastewater to the plant. During the study period, chlorine disinfection was periodically applied as illustrated in Figures S1 and S2, separately for each WWTP.

2.2. Monitoring Scheme and Parameters

The WWTPs were studied using two levels of investigation (Figure 1):
(i)
Long-term investigation on routinely collected parameters: routine parameters monitored by the sewage company for compliance with Italian Law on WWTP discharges [32] were gathered from a private sewage company database from 2018 to 2023 on a monthly basis. In particular, biochemical oxygen demand (BOD5), chemical oxygen demand (COD), and total suspended solids (TSSs) were determined at the entrance and exit of the WWTPs, while E. coli was determined only in the exit samples.
(ii)
Specific short-term investigation on microbial parameters: parameters mentioned in the regulation for water reuse [25] were determined during a dedicated monitoring campaign, with weekly samples collected from July to September 2023 (hereafter fieldwork sampling). In particular, grab samples were collected at different stages of the sewage treatment process from each WWTP: at the entrance—untreated samples (16 samples, 2.5 L each); at the inlet of the chlorination units, after biological treatment—secondary effluents (16 samples, 2.5 L each); and after chlorination—tertiary samples (16 samples, 7.5 L each). They included E. coli and intestinal enterococci as indicators for bacteria, somatic coliphages for viruses, and spores of sulfite-reducing clostridia for protozoa (Annex 1, Section 2, Reg. 2020/741). Moreover, Salmonella and Human Adenovirus (HAdV) were selected as index pathogens [33,34,35], and enterovirus, norovirus, and SARS-CoV-2 were also monitored.

2.3. Routinely Collected Parameters

BOD5 (mg/L) and TSS (mg/L) were determined according to the accredited internal methods of the Acque SpA laboratory: BOD5 was measured through chemiluminescence (MI-001 Rev2 2022) and TSS was determined using a gravimetric method with sediment collection via filtration on a 0.45 μm membrane filter (MI-002 Rev. 3 2021). COD (mg/L) was determined by photometric detection at 600 nm following the ISO 15705:2002 [36] protocol. E. coli (MPN/100 mL) were enumerated by UNI EN ISO 9308-2:2014 [37] as detailed in Section 2.4.2. A total of 579 and 297 pairs of entrance–exit samples were collected for WWTP1 and WWTP2, respectively, while E. coli concentrations were determined on a limited number of samples at the exit of the WWTPs (77 for WWTP1 and 123 for WWTP2), considering either chlorinated or non-chlorinated effluents (Figure 1).
Removal efficiencies were calculated for organic compounds and solids using Equation (1) [38].
R e m o v a l   e f f i c i e n c y   ( % ) = ( C i − C e ) × 100 C i
where Ci is the concentration at the inlet of the WWTP (sewage entrance) and Ce is the concentration at the exit of the WWTP (final effluent).

2.4. Microbiological Parameters during Fieldwork

After collection, samples were transferred to the laboratory and kept refrigerated at 4 °C until the analysis within 24 h for bacteria and spores and 48 h for viruses [39].

2.4.1. Somatic Coliphages

Somatic coliphages were enumerated using Bluephage® Enumeration of Somatic Coliphages Easy Kit for 1–10 mL. Briefly, the sample was diluted to 1:1000 (untreated sewage) in sterile deionized water or undiluted (secondary and tertiary effluents), and then 1 mL was analyzed according to the UNI EN ISO 10705-2:2001 [40] procedure (double agar-layer method) on E. coli strain WG5, and the results were expressed as Plaque-Forming Units per liter (PFU/L).

2.4.2. Bacterial Indicators

Bacterial indicators were detected using IDEXX Defined Substrate Technology® for total coliform/E. coli (Colilert-18, UNI EN ISO 9308-2:2014 [37]) and for intestinal enterococci (Enterolert-E, AFNOR IDX 33/04-02/15 [41]), using the Quanti-Tray enumeration procedure. Briefly, the sample was diluted to 1:100,000 (untreated sewages) in sterile deionized water or undiluted (secondary and tertiary effluents), and then 1 mL was analyzed according to the manufacturer’s instructions, and the results were expressed as Most Probable Number per 100 mL (MPN/100 mL).

2.4.3. Spores of Sulfite-Reducing Clostridia

Spores of sulfite-reducing clostridia were determined using the standardized culture-based method using the membrane filtration approach, following the procedure described in the Italian Standard APAT-IRSA/CNR 7060:2003 [42]. Briefly, the sample was heat-treated in a water bath (75 °C for 15 min), diluted to 1:100 in sterile deionized water, and 100 mL was filtered through a 0.45 μm membrane filter (Frisenette Aps, Energivej, Denmark) and the filter was placed onto a Sulphite Polymyxin Sulphadiazine (SPS) solid agar medium, which had been covered with molten SPS to create anaerobic conditions. After incubation in an anaerobic jar at 36 °C for 48 h, black colonies were visually counted, and the results were expressed as colony-forming units per liter (CFU/L).

2.4.4. Salmonella spp.

Salmonella spp. was determined using a qualitative, culture-based assay following the procedure described in the Italian Standard APAT-IRSA/CNR 7080:2003 [43]. Briefly, a 1 L sample was concentrated via membrane filtration on a 0.45 μm filter, which was then placed in Buffered Peptone Water for pre-enrichment (36 °C for 24 h). Then, further enrichment was performed in Rappaport Vassiliadis broth (42 °C for 24 + 24 h). Finally, a loopful of the 24 h (and 48 h) broth culture was subcultured onto xylose lysine desoxycholate agar. After incubation at 36 °C for 24 h, black colonies were confirmed for Salmonella using a carbohydrate fermentation assay onto Kliger Iron Agar (and Lysine Iron Agar) and serologically tested using latex agglutination. The results were expressed as presence/absence in a liter.

2.4.5. Human Viruses

Sample preparation and concentration. Wastewater samples (1 L for untreated samples and secondary effluents, 5 L for tertiary effluents) were passed through 142 mm diameter cellulose nitrate membrane filters with an 8 µm pore size (Sartorius, Goettingen, Germany) with a peristaltic pump to remove solid debris. The membrane was thereafter eluted utilizing 30 mL of 3% beef extract at pH 9, and the supernatant was added to the prefiltered sample. Then, the sample was concentrated via ultrafiltration with polyethersulfone (PES) membranes with a 10 kDa molecular cutoff using two Vivaflow200® cassettes (Sartorius, Stenehouse, UK) in parallel to obtain an active filtration membrane area of 400 cm2. At the end of the process, the final volume of the sample was 50 mL [44].
Biomolecular analysis. The nucleic acids were extracted from 200 μL (for DNA) and 140 μL (for RNA) of the eluant fluids using QIAmp Viral DNA and RNA kits (Qiagen, Hilden, Germany), respectively, according to the manufacturer’s protocols. Then, the extracted genome was purified using the OneStep PCR Inhibitor Removal Kit (Zymo Research, Irvine, CA, USA). The samples were tested for HAdV, norovirus ggII (NoV ggII), enterovirus, and SARS-CoV-2, using primers, probes, and the thermal protocol listed in Table S1. Reactions were performed in duplicate using the Taq Man Universal Master Mix (Applied Biosystems—Thermo Fisher Scientific, Warrington, UK) and AgPath-ID™ One-Step RT-PCR Reagents (Applied Biosystems—Thermo Fisher Scientific, Austin, TX, US) for HAdV and RNA viruses, respectively, and the CFX Opus 96 Real-Time PCR System (Bio-Rad Laboratories, Inc., Singapore). For viral quantification, standard curves were developed for each viral target via serial dilution of a synthetic dsDNA (from 101 GC/µL to 105 GC/µL) and they were considered acceptable when they had a slope between −3.1 and −3.6 and an R2 equal to or greater than 0.98 [45,46]. The (RT)-qPCR data were adjusted according to the volume used in each step of the process (i.e., concentration, extraction), and the results were expressed as GC/L.

2.5. Meteorological Data

Meteorological data were extracted in the same study period from the public database of the Regional Hydrological Service (SIR; https://www.sir.toscana.it/, accessed on 12 January 2024), using site-specific monitoring stations for each WWTP (TOS01000544 for WWTP1 and TOS01005251 for WWTP2). For this study, wet weather is defined as total precipitation greater than 1 mm in the previous 24 h and dry weather is defined as a non-wet day (Copernicus Climate Change Service; https://climate.copernicus.eu/ESOTC, accessed on 12 January 2024). Based on these criteria, wet weather represented 22.5% (130/579) and 18.2% (54/297) of the study period for WWTP1 and WWTP2, respectively. During fieldwork, only one sampling date was performed during wet weather (29 August 2023).

2.6. Statistical Analysis

The water quality of the final effluent was categorized according to the European regulation, which classifies reclaimed water into 4 classes from A to D in descending order of water quality [25]. In the present paper, we considered BOD5, TSS, and E. coli with the threshold values (named minimum requirements [25]) reported in Table 1.
E. coli data have been dichotomized according to the threshold value for the class D minimum requirement, and the chi-square statistic was used to understand if the frequency of compliant samples was influenced by chlorination.
For the purpose of further statistical analysis, the data distributions of E. coli, COD, BOD5, and TSS in the outlet samples, as well as the removal efficiency of the above-mentioned physico-chemical parameters, were checked for normality using the Shapiro–Wilk normality test and the Skewness statistic, separately for each WWTP. Such a normality test revealed departures from normality (Section 3.1) for all the tested data distributions. Thus, the effect of Log10-transformation of E. coli data was also examined and was able to achieve similarity to a normal distribution, thus supporting the use of the parametric analytical methods [47] described below.
A Two-way Analysis of Variance (ANOVA) was performed to understand the influence of weather conditions (dry/wet) and chlorination (yes/no) on Log10E. coli in the exit samples, separately for each WWTP (the usage of a parametric test was consistent with the normal distribution of this variable, Section 3.1). The results are graphically illustrated using interaction plots (R software, package ggpubr).
For chemical parameters, removal efficiencies were calculated as reported in Equation (1) (Section 2.3) and were expressed as average values, and the variability of the data was reported as the 10th and 90th percentiles of the distribution of the data [38]. The Mann–Whitney U test was performed to understand the differences in removal efficiency of physico-chemical parameters (COD, BOD5, and TSS) according to weather conditions, i.e., dry or wet days.
The Spearman correlation coefficient (ρ) was used to investigate the association between E. coli at the exit of each WWTP and the values of the chemical parameters (COD, BOD5, and TSS) in the same samples. The values of the Spearman coefficient were represented by a correlation matrix (R software, package corrplot).
In the fieldwork, the removal of each microbial parameter was expressed as a logarithmic reduction, considering the microbial concentrations of water entering the WWTP (untreated sewage) and those at discharge (secondary or tertiary effluents), following a well-established approach for evaluating waterborne microorganism reductions using common water treatment technologies [48]. Such an approach is also adopted by the Regulation on reuse for assessing performance targets for the entire treatment chain during the microbial validation monitoring of the WWTP producing class A waters (Annex I, Section 2 of the EU Regulation [25]). The log-reduction data were examined using general descriptive statistics, namely the median and interquartile range (IQR), considering the first and third quartiles. The Fisher exact statistic was used to investigate the association between index pathogens and indicators in the exit samples: for bacteria, Salmonella presence/absence was tested with E. coli dichotomized according to the threshold value for class D, while for viruses, HAdV presence/absence was tested with somatic coliphages data, which were dichotomized according to their median value (owing to the lack of a regulatory threshold).
All statistical analyses and graphical representations were performed using R v. 4.3.2.

3. Results

3.1. Long-Term WWTP Performance According to the EU Regulation 2020/741

Normality tests revealed that the data distribution of E. coli, COD, BOD5, and TSS in the final effluents and the removal efficiency of the physico-chemical parameters were not normally distributed, with p < 0.05 for Shapiro–Wilk tests and skewness statistic less than −1 (ranging from −11.50 to −2.41) or greater than +1 (ranging from +2.18 to +7.58). On the other hand, Log10E. coli concentrations in the final effluents showed similarity to a normal distribution, with skewness statistics of −1.05 and −0.45 for WWTP1 and WWTP2, respectively.
The frequency of exit samples compliant with requirements for all water quality classes was high for physico-chemical parameters, e.g., more than 97% of samples were compliant for BOD5 and TSS classes B, C, and D requirements, regardless of the chlorination treatment (Table 2 and Table 3 for WWTP1 and WWTP2, respectively). On the other hand, as expected, compliance with E. coli requirements differed markedly between chlorinated and non-chlorinated effluents: WWTP1 met the threshold value for class D in 36.4% of disinfected effluents and 18.2% of non-disinfected ones, and this difference was greater and statistically significant in WWTP2, with 94.6% (53/56) compliance in chlorinated versus 20.9% (14/67) in not chlorinated (chi-square, p < 0.0001). Similar results were also obtained for class C (85.7%, 48/56 of compliance in chlorinated samples), class B (71.4%, 40/56), and class A (46.4%, 26/56), while non-chlorinated effluents exhibited compliance of less than 5% (3/67). Regarding the role of weather on compliance, in both WWTPs, exceedances of E. coli thresholds for reuse occurred mainly in wet conditions, either in chlorinated or non-chlorinated effluents. As an example, the class D requirement was met in 42.3% of chlorinated samples and 22.2% of non-chlorinated samples in dry weather conditions in WWTP1, but these percentages were reduced to 21.4% and 0% in wet weather. Similarly, in WWTP2, chlorinated and non-chlorinated effluents were compliant in 96.1% and 21.9% of samples, respectively, in dry conditions, which decreased to 80.0% and 16.7% during wet weather (Table 2 and Table 3).
Figure 2 shows the effects of chlorination and meteorological variables on E. coli levels in the outlet samples: the concentrations of E. coli in chlorinated effluents were significantly lower than in non-chlorinated ones, especially in dry conditions, in both WWTPs (see Table S2 for the results of the two-way ANOVA).
The long-term analysis of the removal efficiency of organic substances and solids parameters showed high performances for both WWTPs, with average values greater than 90%, and the influence of weather conditions. In fact, removal efficiency values were lower during wet weather than in dry conditions, and this was statistically significant for WWTP1 (Table 4).
The correlation matrix for E. coli and physico-chemical parameters (COD, BOD5, and TSS) in the chlorinated effluents is reported separately for each WWTP in Figure 3. In WWTP1, the E. coli concentration was positively correlated with the COD level (ρ = 0.48, p = 0.18), while the associations with the other parameters were negligible. In WWTPs, positive associations were observed between E. coli and all the other parameters, namely COD (ρ = 0.37, p = 0.13), BOD5 (ρ = 0.40, p < 0.05), and TSS (ρ = 0.45, p = 0.12). Interestingly, the association between E. coli and COD was maintained in both WWTPs.

3.2. Specific Short-Term Investigation on Microbiological Performance

3.2.1. Microbial Indicators

Microbial removal at different stages of the treatment process is reported separately for each WWTP in Table 4 (details on descriptive statistics of microbial concentrations at the entrance and secondary and tertiary effluents are provided in Table S3, separately for each microbial parameter and WWTP).
Bacterial indicator levels at the entrance were slightly higher in WWTP2 compared to WWTP1. In fact, median E. coli concentrations were 1.43 × 108 MPN/L (IQR = 1.12 × 108 MPN/L − 1.73 × 108 MPN/L) in WWTP2 and 6.68 × 107 MPN/L (IQR = 5.47 × 107 MPN/L − 6.87 × 107 MPN/L), and the values observed for enterococci were 1.53 × 107 MPN/L (IQR = 1.38 × 107 MPN/L − 1.77 × 107 MPN/L) and 1.16 × 107 MPN/L (IQR = 8.17 × 106 MPN/L − 1.31 × 107 MPN/L), respectively. Overall, the median log-removal of bacterial indicators attributable to the entire treatment process ranged from 3.42 to 4.13 (Table 5).
Somatic coliphages at the entrance of WWTP2 (1.05 × 107 PFU/L, IQR = 7.00 × 106 PFU/L − 1.35 × 107 PFU/L) were similar to those observed for WWTP1 (9.00 × 106 PFU/L, IQR = 5.73 × 106 PFU/L − 1.60 × 107 PFU/L), and the removal attributable to the entire treatment process was around 3.5 log in both WWTPs (Table 5).
Both WWTPs also showed similar entrance concentrations for spores of sulfite-reducing clostridia: 9.25 × 104 CFU/L (IQR = 4.55 × 104 CFU/L − 1.24 × 105 CFU/L) for WWTP2 and 1.10 × 105 CFU/L (IQR = 7.00 × 104 CFU/L − 1.80 × 105 CFU/L) for WWTP1; nevertheless, the median removal was markedly different between WWTPs, and WWTP1 was more efficient (Table 5).
Considering microbial reduction, log-removal was mostly attributable to the secondary treatment for all the analyzed microbial parameters, whereas disinfection was able to reduce the microbial concentrations by no more than 1 log (Table 5).
Interestingly, in both WWTPs, lower removal values were observed on the only sampling date with wet weather (29 August 2023); as an example, WWTP1 showed 0.69, 0.91, and 0.62 log-removal for E. coli, intestinal enterococci, and somatic coliphages, respectively.

3.2.2. Relationship between Index Pathogens and Microbial Indicators

The relationship between index pathogens and their microbial indicators is depicted in Figure 4, separately for Salmonella and E. coli (Figure 4a) and HAdV and somatic coliphages (Figure 4b). Regarding bacteria, E. coli values at the exit were dichotomized according to water quality for class D reuse (1.0 × 104 MPN/100mL) and they were related to Salmonella presence in the same samples, showing a significant association between Salmonella absence at the exit and E. coli compliance for class D (Fisher exact test, p < 0.01). Regarding viruses, somatic coliphages were dichotomized according to the median values of the distribution data at the exit of the WWTPs (4.9 × 103 PFU/L), given the lack of threshold requirements for viral indicators. In this case, the association between HAdV absence and coliphages compliance was not significant (Fisher exact test, p = 0.4).

3.2.3. Pathogens

The HAdV genome was present in 100% of the entrance samples and at the exit in 100% of samples for WWTP1 and in 62.5% of samples for WWTP2. In fact, HAdV removal was higher in WWTP2 with a median log-reduction of 2.3 (IQR = 1.72–3.6), compared to WWTP1 (1.3, IQR = 1.02–1.5). In contrast to what was observed for microbial indicators, most of the HAdV abatement was attributable to the disinfection process: 1.5 (IQR = 0.8–2.7) in WWTP2 and 1.0 (IQR = 0.7–1.4) in WWTP1. Considering WWTPs data as a whole, the other pathogens were present at the entrance with different frequencies: 75.0% (12/16) for Salmonella, 93.8% (15/16) for enterovirus and NoV ggII, and 68.8% (11/16) for SARS-CoV-2. Their frequencies after the secondary treatment were 62.5% (10/16) for Salmonella, 19% (3/16) for enterovirus and NoV ggII, and 0% for SARS-CoV-2. After chlorination, only Salmonella (38%, 6/16) and NoV ggII (6%, 1/16) were present, especially during the wet weather event.

4. Discussion

Using recycled wastewater for urban and irrigational purposes represents a valuable strategy to tackle the quality and quantity deterioration of fresh and groundwater resources, as specifically committed by the 2030 Agenda for Sustainable Development in SDG 6. Water reuse is a long-established practice in states suffering from water scarcity: experiences of potable or irrigational reuse date back to 1968 in Namibia (Windhoeck) and the 1950s in Israel, respectively [49,50]. However, in Europe, changes in climatic conditions such as increases in seasonal rainfall or severe drought events are also contributing significantly to the strain on the availability of surface and groundwater bodies [26]. For this reason, Europe recently applied, in June 2023, a water reuse Regulation that set uniform minimum water quality requirements for the safe reuse of treated urban sewages in agricultural irrigation; this will also possibly be extended to other purposes, including industrial, recreational, and environmental applications, during the next evaluation scheduled in June 2028 [25]. However, reuse practices can pose a threat to human health if the effectiveness of the treatment process is not adequately controlled. In particular, microbial pathogens in reclaimed water could be responsible for water-borne disease outbreaks (e.g., gastroenteritis) and other acute effects; nevertheless, microbial parameters are not suitable for operational monitoring because their determination is time-consuming, thus hampering the application of corrective actions in a timely manner [51].
In our long-term investigation, we observed that WWTPs were efficient at removing chemical targets; in fact, considering pooled data, the threshold values of BOD5 and TSS for class A were met in 90% or more of the samples, as requested by the EU Regulation for reuse [25]. However, when data were considered separately according to weather conditions, the compliance under wet conditions with the chemical requirements was reduced as a consequence of a general worsening of the treatment process. Similarly, the WWTPs experienced occasional failure in E. coli compliance especially during rainfall events. For such microbial parameters, the number of wet days was limited (<20 observations for each WWTP), but the same trend has been observed in both WWTPs, thus suggesting the reliability of the results. In fact, this phenomenon may be attributable to parasitic rainwater in sewer network structures, which could be responsible for an increase in the levels of microbial contamination in the entering waters as well as an increase in the flowrate, which can reduce the retention time and, consequently, the effectiveness of the treatments [52,53,54]. Moreover, E. coli levels in the outlet samples were also influenced by chlorine disinfection, which was more efficient in WWTP2 compared to WWTP1. This aspect can be justified by different dosage conditions: in WWTP2, the dosage was adjusted by flowrate, making the disinfection process more efficient and prone to fluctuating influent wastewater volume in a certain period of time, as in the case of precipitation.
Since such variation in water quality can happen rapidly, an easy-to-measure proxy for the occurrence of microbial parameters would be useful to control the treatment process, such as the chemical disinfectant dosage. As an example, Bonetta et al. (2022) [11] reported that various bacterial indicators, including E. coli, were positively associated with BOD5, COD, and TSS considering sewage at various stages of the treatment process. Similarly, Foschi et al. (2021) [55] found positive associations between E. coli and COD, turbidity, and TSS at the inlet of the disinfection unit, and Rocher et al. (2021) [56] found that E. coli and intestinal enterococci after disinfection correlated with the initial bacterial concentration but also with TSS and COD in the disinfected effluents. Our results partially confirm these findings; in fact, we found that E. coli in the chlorinated samples was positively correlated with COD in both WWTPs under investigation, and the association was also significant regarding TSS and BOD5 in the outlet samples for WWTP2. These results indicate that E. coli levels correlate with the degradation of water quality parameters in terms of both organic substances (COD and BOD5) and suspended solids (TSS); however, only COD was associated with E. coli in both WWTPs, thus suggesting such a chemical parameter as a promising proxy, given the short analysis time. This aspect deserves further investigation and a dedicated site-specific data collection campaign to increase the sample size in order to develop a predictive model to estimate E. coli concentrations using chemical proxies.
The short-term investigation revealed the validity of E. coli as a monitoring parameter for bacterial pathogens in the outlet (and chlorinated) samples. In particular, we identified a significant association between the presence of Salmonella and the exceeding of the E. coli threshold for class D water quality, thus confirming a robust relationship between the loss of bacterial pathogens and E. coli removal and inactivation during treatment. Nevertheless, such an association was not revealed when HAdV was considered as an index pathogen, not even considering somatic coliphages as viral indicators of HAdV; thus, the compliance with microbial indicators is not enough to represent the viral safety of reclaimed waters [57].
However, chlorination allowed the removal of most of the enteric pathogens (Salmonella, norovirus, and enterovirus), reduced HAdV from 1.0 to 1.5 log, and produced log-removal values for microbial indicators in line with those reported in the international literature, namely 2.0–6.0 for E. coli, 1.0–2.0 for C. perfringes, and 0.0–2.5 for bacteriophages [58]. Nevertheless, as in the long-term study, a rainfall event was also responsible during this investigation for the loss of control of both WWTPs, resulting in the exceeding of E. coli values for the class D threshold and the detection of Salmonella, NoV, and HAdV in the outlet samples. However, the results of the microbiological investigation, especially those regarding the viral risk, need to be confirmed by increasing the monitoring frequency so as to cover different environmental and meteorological conditions, as the small sample size of this fieldwork represents a limitation of the short-term investigation.

5. Conclusions

In this study, we performed a two-level investigation on urban WWTPs from the perspective of reusing their effluents in order to consider both routine monitoring parameters and microbial parameters, including indicators and pathogens. In fact, a complete characterization of the performance of WWTPs is fundamental for potential reuse practices, especially to identify the hazards and situations that could be responsible for the loss of control of the water reuse system, such as rainfall events. A multi-barrier approach that includes chlorine-based disinfection was needed to obtain at least water quality class D according to EU regulations for E. coli and achieve the removal of most of the enteric pathogens. Nevertheless, the compliance with microbial indicators was not high enough to exclude the presence of viral contamination; in fact, although the treatments reduced somatic coliphages, a similar reduction was not evident for HAdV.

Supplementary Materials

The following supporting information can be downloaded at: https://www.mdpi.com/article/10.3390/w16101399/s1, Table S1: Oligonucleotide primers and probes used for the viral detection by (RT)qPCR. Target regions are also reported for each viral parameter. References are reported in the footnotes; Table S2: Effect of two independent variables, water treatment and weather conditions, on E. coli levels in the exit samples (dependent variable), separately for each WWTP. E. coli concentrations are reported as geometric mean ± standard deviation; Table S3: Bacterial and viral indicator concentrations at different stages of the treatment process. Results are reported as median and interquartile range (first and third quartiles) and refer to eight sampling dates; Figure S1: Compliance of WWTP1 with EU minimum requirements for BOD5, TSS, and E. coli (data of E. coli have been Log10-transformed). Information on rainfall and chlorination is also reported for the entire monitoring period in the bottom box. Precipitation corresponds to accumulated rainfall (mm) in the 24 prior to the sampling dates, according to Copernicus definition of wet days (https://climate.copernicus.eu/ESOTC; accessed on 12 January 2024); Figure S2: Compliance of WWTP2 with EU minimum requirements for BOD5, TSS, and E. coli (data of E. coli have been Log10-transformed). Information on rainfall and chlorination is also reported for the entire monitoring period in the bottom box. Precipitation corresponds to accumulated rainfall (mm) in the 24 h prior to the sampling dates, according to Copernicus definition of wet days (https://climate.copernicus.eu/ESOTC; accessed on 12 January 2024).

Author Contributions

Conceptualization, A.C. and I.F.; methodology, A.C. and I.F.; formal analysis, A.C. and I.F.; investigation, I.F., G.L., A.P., A.L., R.S., S.L. and F.M.; writing—original draft preparation, A.C. and I.F.; writing—review and editing, A.C., I.F., G.L., A.P., A.L., R.S., S.L., F.M. and M.V.; supervision, A.C.; project administration, A.C. and S.L.; funding acquisition, A.C. All authors have read and agreed to the published version of the manuscript.

Funding

This work was also supported by the Ministry of University and Research (MUR) as part of the FSE REACT-EU–PON 2014–2020 “Research and Innovation” resources—Green Action—DM MUR 1062/2021–Title of the Research: “Risk analysis for the human health derived from sewage management: perspectives for the reuse”.

Data Availability Statement

Meteorological data are available from publicly archived datasets of the Regional Hydrological Service of the Tuscany Region (SIR; https://www.sir.toscana.it/, accessed on 12 January 2024). Data on wastewater treatment plants are available upon request due to privacy restrictions.

Acknowledgments

We wish to thank Marino Croppi (Croppi Lottini company) for technical support in testing ultrafiltration modules.

Conflicts of Interest

R.S., A.L., F.M., and S.L. are employees of the sewerage company (Acque S.p.A.) involved in the project research. I.F., G.L., A.P., M.V., and A.C. declare no conflicts of interest.

References

  1. United Nations (UN). Sustainable Development Goals. 2023. Available online: https://www.un.org/sustainabledevelopment/news/communications-material/ (accessed on 22 March 2024).
  2. European Environment Agency (EEA). Water Resources across Europe—Confronting Water Stress: An Updated Assessment. 2021, EEA Report No 12/2021. Available online: https://www.eea.europa.eu/publications/water-resources-across-europe-confronting (accessed on 12 January 2024).
  3. United Nation Development Programme (UNDP). What Are the Sustainable Development Goals? 2024. Available online: https://www.undp.org/sustainable-development-goals (accessed on 22 March 2024).
  4. United Nations Development Programme (UNDP). Goal 6: Clean Water and Sanitation. 2024. Available online: https://www.undp.org/sustainable-development-goals/clean-water-and-sanitation (accessed on 22 March 2024).
  5. European Commission (EC); European Environment Agency (EEA). The European Climate Adaptation Platform, Climate-ADAPT. Available online: https://climate-adapt.eea.europa.eu/en/about (accessed on 22 March 2024).
  6. United Nations. The United Nations World Water Development Report 2024: Water for Prosperity and Peace; United Nations Educational, Scientific and Cultural Organization (UNESCO): Paris, France, 2024. [Google Scholar]
  7. Rodriguez, D.J.; Serrano, H.A.; Delgado, A.; Nolasco, D.; Saltiel, G. From Waste to Resource: Shifting Paradigms for Smarter Wastewater Interventions in Latin America and the Caribbean; World Bank: Washington, DC, USA, 2020. [Google Scholar] [CrossRef]
  8. Pistocchi, A.; Aloe, A.; Dorati, C.; Alcalde Sanz, L.; Bouraoui, F.; Gawlik, B.; Grizzetti, B.; Pastori, M.; Vigiak, O. The Potential of Water Reuse for Agricultural Irrigation in the EU: A Hydro-Economic Analysis; EUR 28980 EN; Publications Office of the European Union: Luxembourg, 2018; JRC109870; ISBN 978-92-79-77210-8. [Google Scholar] [CrossRef]
  9. Dimane, F.; El Hammoudani, Y. Assessment of quality and potential reuse of wastewater treated with conventional activated sludge. Mater. Today Proc. 2021, 45, 7742–7746. [Google Scholar] [CrossRef]
  10. Ramos, M.D.N.; Gomes, T.M.; Aquino, S.F.; Aguiar, A. Sewage treatment in cities of the state of Minas Gerais, Brazil, that use the UASB reactor as the only biological treatment: A case study. J. Water Process Eng. 2023, 56, 104509. [Google Scholar] [CrossRef]
  11. Bonetta, S.; Pignata, C.; Gasparro, E.; Richiardi, L.; Bonetta, S.; Carraro, E. Impact of wastewater treatment plants on microbiological contamination for evaluating the risks of wastewater reuse. Environ. Sci. Eur. 2022, 34, 20. [Google Scholar] [CrossRef]
  12. European Commission (EC). Water Reuse—Background and Policy Context. 2024. Available online: https://environment.ec.europa.eu/topics/water/water-reuse_en (accessed on 22 March 2024).
  13. United Nations Environment Programme (UNEP). Options for Decoupling Economic Growth from Water Use and Water Pollution. Summary for Policy Makers. 2015. Available online: https://wedocs.unep.org/handle/20.500.11822/7539 (accessed on 12 January 2024).
  14. National Academy of Science (NAS), National Research Council. Water Reuse: Potential for Expanding the Nation’s Water Supply through Reuse of Municipal Wastewater; The National Academies Press: Washington, DC, USA, 2012. [Google Scholar] [CrossRef]
  15. Mok, H.F.; Barker, S.F.; Hamilton, A.J. A probabilistic quantitative microbial risk assessment model of norovirus disease burden from wastewater irrigation of vegetables in Shepparton, Australia. Water Res. 2014, 54, 347–362. [Google Scholar] [CrossRef]
  16. Gonzales-Gustavson, E.; Rusiñol, M.; Medema, G.; Calvo, M.; Girones, R. Quantitative risk assessment of norovirus and adenovirus for the use of reclaimed water to irrigate lettuce in Catalonia. Water Res. 2019, 153, 91–99. [Google Scholar] [CrossRef]
  17. Gholipour, S.; Hosseini, M.; Nikaeen, M.; Hadi, M.; Sarmadi, M.; Saderi, H.; Hassanzadeh, A. Quantification of human adenovirus in irrigation water-soil-crop continuum: Are consumers of wastewater-irrigated vegetables at risk? Environ. Sci. Pollut. Res. Int. 2022, 29, 54561–54570. [Google Scholar] [CrossRef]
  18. Hamilton, K.A.; Hamilton, M.T.; Johnson, W.; Jjemba, P.; Bukhari, Z.; LeChevallier, M.; Haas, C.N. Health risks from exposure to Legionella in reclaimed water aerosols: Toilet flushing, spray irrigation, and cooling towers. Water Res. 2018, 134, 261–279. [Google Scholar] [CrossRef]
  19. World Health Organization (WHO). Potable Reuse: Guidance for Producing Safe Drinking-Water; World Health Organization: Geneva, Switzerland, 2017; ISBN 978-92-4-151277-0. [Google Scholar]
  20. Carducci, A.; Verani, M.; Battistini, R.; Pizzi, F.; Rovini, E.; Andreoli, E.; Casini, B. Epidemiological surveillance of human enteric viruses by monitoring of different environmental matrices. Water Sci. Technol. 2006, 54, 239–244. [Google Scholar] [CrossRef]
  21. Carducci, A.; Morici, P.; Pizzi, F.; Battistini, R.; Rovini, E.; Verani, M. Study of the viral removal efficiency in a urban wastewater treatment plant. Water Sci. Technol. 2008, 58, 893–897. [Google Scholar] [CrossRef]
  22. Carducci, A.; Verani, M. Effects of bacterial, chemical, physical and meteorological variables on virus removal by a Wastewater Treatment Plant. Food Environ. Virol. 2013, 5, 69–76. [Google Scholar] [CrossRef]
  23. La Rosa, G.; Fratini, M.; della Libera, S.; Iaconelli, M.; Muscillo, M. Emerging and potentially emerging viruses in water environments. Ann. Ist. Super. Sanita 2012, 48, 397–406. [Google Scholar] [CrossRef]
  24. Momba, M.; Edbon, J.; Kamika, I.; Verbyla, M. Using indicators to assess microbial treatment and disinfection efficacy. In Water and Sanitation for the 21st Century: Health and Microbiological Aspects of Excreta and Wastewater Management (Global Water Pathogen Project); Rose, J.B., Jiménez-Cisneros, B., Eds.; (A. Farnleitner, and A. Blanch (eds), Part 2: Indicators and Microbial Source Tracking Markers), Michigan State University, E. Lansing, MI, UNESCO; 2019; Available online: https://www.waterpathogens.org/book/using-indicators-assess-microbial-treatment-and-disinfection-efficacy (accessed on 12 January 2024).
  25. European Union (EU), Regulation (EU) 2020/741 of the European Parliament and of the Council of 25 May 2020 on Minimum Requirements for Water Reuse, Official Journal of the European Union (L 177/3). Available online: https://eur-lex.europa.eu/eli/reg/2020/741/oj (accessed on 12 January 2024).
  26. European Commission (EC). Commission Notice—Guidelines to Support the Application of Regulation 2020/741 on Minimum Requirements for Water Reuse (2022/C 298/01). Information from European Union Institutions, Bodies, Offices and Agencies. Official Journal of the European Union (C 298/1). Available online: https://eur-lex.europa.eu/legal-content/EN/ALL/?uri=CELEX:52022XC0805(01) (accessed on 12 January 2024).
  27. Maffettone, R.; Gawlik, B.M. Technical Guidance—Water Reuse Risk Management for Agricultural Irrigation Schemes in Europe; Publications Office of the European Union: Luxembourg, 2022. [Google Scholar] [CrossRef]
  28. Carducci, A.; Federigi, I.; Lauretani, G.; Muzio, S.; Pagani, A.; Atomsa, N.T.; Verani, M. Critical Needs for Integrated Surveillance: Wastewater-Based and Clinical Epidemiology in Evolving Scenarios with Lessons Learned from SARS-CoV-2. Food Environ. Virol. 2024, 16, 38–49. [Google Scholar] [CrossRef]
  29. Takuissu, G.R.; Kenmoe, S.; Ebogo-Belobo, J.T.; Kengne-Ndé, C.; Mbaga, D.S.; Bowo-Ngandji, A.; Ondigui Ndzie, J.L.; Kenfack-Momo, R.; Tchatchouang, S.; Kenfack-Zanguim, J.; et al. Exploring adenovirus in water environments: A systematic review and meta-analysis. Int. J. Environ. Health Res. 2023, 34, 2504–2516. [Google Scholar] [CrossRef]
  30. Allard, A.; Vantarakis, A. Adenoviruses. In Water and Sanitation for the 21st Century: Health and Microbiological Aspects of Excreta and Wastewater Management (Global Water Pathogen Project); Rose, J.B., Jiménez-Cisneros, B., Eds.; (J.S Meschke, and R. Girones (eds), Part 3: Specific Excreted Pathogens: Environmental and Epidemiology Aspects-Section 1: Viruses), Michigan State University, E. Lansing, MI, UNESCO; 2017; Available online: https://www.waterpathogens.org/book/adenoviruses (accessed on 12 January 2024).
  31. World Health Organization (WHO). Quantitative Microbial Risk Assessment; Application for Water Safety Management: Geneva, Switzerland, 2016; ISBN 978 92 4 156537 0. [Google Scholar]
  32. Legislative Decree no. 152/2006, Environmental Regulation of the Italian Government (GU Serie Generale n.88 del 14-04-2006—Suppl. Ordinario n. 96). Available only in Italian language. Available online: https://www.normattiva.it/uri-res/N2Ls?urn:nir:stato:decreto.legislativo:2006-04-03;152 (accessed on 12 January 2024).
  33. Verani, M.; Federigi, I.; Donzelli, G.; Cioni, L.; Carducci, A. Human adenoviruses as waterborne index pathogens and their use for quantitative microbial risk assessment. Sci. Total Environ. 2019, 651, 1469–1475. [Google Scholar] [CrossRef]
  34. Federigi, I.; Bonadonna, L.; Bonanno Ferraro, G.; Briancesco, R.; Cioni, L.; Coccia, A.M.; Della Libera, S.; Ferretti, E.; Gramaccioni, L.; Iaconelli, M.; et al. Quantitative Microbial Risk Assessment as support for bathing water profiling. Mar. Pollut. Bull. 2020, 157, 111318. [Google Scholar] [CrossRef]
  35. Lopez-Galvez, F.; Allende, A.; Pedrero-Salcedo, F.; Alarcon, J.J.; Gil, M.I. Safety assessment of greenhouse hydroponic tomatoes irrigated with reclaimed and surface water. Int. J. Food Microbiol. 2014, 191, 97–102. [Google Scholar] [CrossRef]
  36. ISO 15705:2002; Water Quality—Determination of the Chemical Oxygen Demand Index (ST-COD)—Small-Scale Sealed-Tube Method. International Organization for Standardization: Geneva, Switzerland, 2002.
  37. UNI EN ISO 9308-2:2014; Water Quality. Enumeration of Escherichia Coli and Coliform Bacteria. Part 2: Most Probable Number Method. International Organization for Standardization: Geneva, Switzerland, 2014.
  38. Le, T.M.T.; Truong, T.N.S.; Nguyen, P.D.; Le, Q.D.T.; Tran, Q.V.; Le, T.T.; Nguyen, Q.H.; Kieu-Le, T.C.; Strady, E. Evaluation of microplastic removal efficiency of wastewater-treatment plants in a developing country, Vietnam. Environ. Technol. Innov. 2023, 29, 102994. [Google Scholar] [CrossRef]
  39. ISO 19458:2006; Water Quality—Sampling for Microbiological Analysis. International Organization for Standardization: Geneva, Switzerland, 2006.
  40. UNI EN ISO 10705-2:2001; Water Quality. Detection and Enumeration of Bacteriophages Part 2: Enumeration of Somatic Coliphages. International Organization for Standardization: Geneva, Switzerland, 2001.
  41. NF VALIDATION—Validation of analysis methods: Application to water microbiology. Validation protocol for an alternative commercial method as compared with a reference method. Revision 2 (May 2013). Reference method: NF EN ISO 7899-2 (August 2000): Water quality. Detection and enumeration of intestinal enterococci—Part 2: Membrane filtration method.
  42. APAT-IRSA-CNR 7060:2003. Spores of sulfite-reducing clostridia. In APAT-IRSA-CNR, Analytical Method for Waters, Vol. 3, Section 7000—Determination of Microorganisms; Manual and Guidelines 29/2003; Agenzia per la protezione dell’Ambiente e dei Servizi Tecnici (APAT), Istituto di Ricerca sulle Acque del Consiglio Nazionale delle Ricerche (IRSA-CNR): Rome, Italy, (available only in Italian language); Available online: https://www.irsa.cnr.it/wp/?page_id=5435 (accessed on 12 January 2024).
  43. APAT-IRSA-CNR 7080:2003. Salmonella spp. In APAT-IRSA-CNR, Analytical Method for Waters, Vol. 3, Section 7000—Determination of Microorganisms; Manual and Guidelines 29/2003; Agenzia per la protezione dell’Ambiente e dei Servizi Tecnici (APAT), Istituto di Ricerca sulle Acque del Consiglio Nazionale delle Ricerche (IRSA-CNR): Rome, Italy, (available only in Italian language); Available online: https://www.irsa.cnr.it/wp/?page_id=5435 (accessed on 12 January 2024).
  44. Carducci, A.; Federigi, I.; Balestri, E.; Lardicci, C.; Castelli, A.; Maltagliati, F.; Zhao, H.; Menicagli, V.; Valente, R.; De Battisti, D.; et al. Virus contamination and infectivity in beach environment: Focus on sand and stranded material. Mar. Pollut. Bull. 2022, 185, 114342. [Google Scholar] [CrossRef]
  45. Bustin, S.A.; Benes, V.; Garson, J.A.; Hellemans, J.; Huggett, J.; Kubista, M.; Mueller, R.; Nolan, T.; Pfaffl, M.W.; Shipley, G.L.; et al. The MIQE guidelines: Minimum information for publication of quantitative real-time PCR experiments. Clin. Chem. 2009, 55, 611–622. [Google Scholar] [CrossRef]
  46. La Rosa, G.; Brandtner, D.; Bonanno Ferraro, G.; Veneri, C.; Mancini, P.; Iaconelli, M.; Lucentini, L.; Del Giudice, C.; Orlandi, L.; SARI network. Wastewater surveillance of SARS-CoV-2 variants in October-November 2022 in Italy: Detection of XBB.1, BA.2.75 and rapid spread of the BQ.1 lineage. Sci. Total Environ. 2023, 873, 162339. [Google Scholar] [CrossRef]
  47. Sokal, R.R.; Rohlf, F.J. Biometry: The Principles Practice of Statistics in Biological Research, 3rd ed.; W.H. Freeman and Co.: New York, NY, USA, 1995. [Google Scholar]
  48. Hijnen, W.A.M.; Medema, G.J. Elimination of Micro-Organisms by Drinking Water Treatment Processes: A Review; IWA Publishing: London, UK, 2010. [Google Scholar]
  49. Lazarova, V.; Asano, T.; Bahri, A.; Anderson, J. Milestones in Water Reuse—The Best Success Stories; IWA Publishing Alliance: London, UK, 2013. [Google Scholar]
  50. Tal, A. Seeking Sustainability: Israel’s evolving water management strategy. Science 2006, 313, 1081–1084. [Google Scholar] [CrossRef] [PubMed]
  51. World Health Organization (WHO). Guidelines for Drinking-Water Quality: Fourth Edition Incorporating the First and Second Addenda; World Health Organization: Geneva, Switzerland, 2022; ISBN 978-92-4-004506-4. [Google Scholar]
  52. Chhetri, R.K.; Bonnerup, A.; Andersen, H.R. Combined sewer overflow pretreatment with chemical coagulation and a particle settler for improved peracetic acid disinfection. J. Ind. Eng. Chem. 2016, 37, 372–379. [Google Scholar] [CrossRef]
  53. Federigi, I.; Verani, M.; Carducci, A. Sources of bathing water pollution in northern Tuscany (Italy): Effects of meteorological variables. Mar. Pollut. Bull. 2017, 114, 843–848. [Google Scholar] [CrossRef] [PubMed]
  54. Carducci, A.; Federigi, I.; Cioni, L.; Landucci, A.; Donzelli, G.; Iannelli, R.; Pretti, C.; Tardelli, F.; Casu, V.; Verani, M. Approach to a water safety plan for recreational waters: Disinfection of a drainage pumping station as an unconventional point source of fecal contamination. H2Open J. 2020, 3, 1–9. [Google Scholar] [CrossRef]
  55. Foschi, J.; Turolla, A.; Antonelli, M. Soft sensor predictor of E. coli concentration based on conventional monitoring parameters for wastewater disinfection control. Water Res. 2021, 191, 116806. [Google Scholar] [CrossRef] [PubMed]
  56. Rocher, V.; Azimi, S.; Mailler, R.; Guérin, S.; Meche, P.; Pichon, S.; Goffin, A.; Bernier, J.; Roy, J.; Varrault, G.; et al. Effectiveness of Disinfecting Wastewater Treatment Plant Discharges: Case of Chemical Disinfection Using Performic Acid; IWA Publishing: London, UK, 2021. [Google Scholar]
  57. Cuevas-Ferrando, E.; Pérez-Cataluña, A.; Falcó, I.; Randazzo, W.; Sánchez, G. Monitoring Human Viral Pathogens Reveals Potential Hazard for Treated Wastewater Discharge or Reuse. Front. Microbiol. 2022, 13, 836193. [Google Scholar] [CrossRef]
  58. NRMMC–EPHC–AHMC (Natural Resource Management Ministerial Council, Environment Protection and Heritage Council, Australian Health Ministers’ Conference). Australian Guidelines for Water Recycling: Managing Health and Environmental Risks (Phase 1); National Water Quality Management Strategy: Canberra, Australia, 2006.
Water 16 01399 g001
Figure 1. Scheme of the sampling strategy along the wastewater treatment stages.
Figure 1. Scheme of the sampling strategy along the wastewater treatment stages.
Water 16 01399 g001
Water 16 01399 g002
Figure 2. Interaction plot showing Log10 E. coli data in the exit effluents under different weather conditions (dry, wet) and chlorination treatment (yes, no), separately for each WWTP: (a) WWTP1, (b) WWTP2. Error bars represent mean ± standard deviation of data distribution for each group.
Figure 2. Interaction plot showing Log10 E. coli data in the exit effluents under different weather conditions (dry, wet) and chlorination treatment (yes, no), separately for each WWTP: (a) WWTP1, (b) WWTP2. Error bars represent mean ± standard deviation of data distribution for each group.
Water 16 01399 g002
Water 16 01399 g003
Figure 3. Spearman correlation matrix for E. coli, COD, BOD5, and TSS in the chlorinated effluents, separately for each WWTP: (a) WWTP1 (66 data for each variable) and (b) WWTP2 (56 data for each variable). Asterisk represents the statistical significance (p) at 0.05 level.
Figure 3. Spearman correlation matrix for E. coli, COD, BOD5, and TSS in the chlorinated effluents, separately for each WWTP: (a) WWTP1 (66 data for each variable) and (b) WWTP2 (56 data for each variable). Asterisk represents the statistical significance (p) at 0.05 level.
Water 16 01399 g003
Water 16 01399 g004
Figure 4. Relationship between index pathogens and microbial indicators in the exit samples: (a) Salmonella and E. coli, (b) Human Adenovirus (HAdV) and somatic coliphages.
Figure 4. Relationship between index pathogens and microbial indicators in the exit samples: (a) Salmonella and E. coli, (b) Human Adenovirus (HAdV) and somatic coliphages.
Water 16 01399 g004
Table 1. Threshold values used in this paper for minimum requirements for water quality, according to EU regulation [25].
Table 1. Threshold values used in this paper for minimum requirements for water quality, according to EU regulation [25].
ParametersWater Quality Classes
ABCD
BOD5 (mg/L)1025
TSS (mg/L)1035
E. coli (MPN/100 mL)10100100010,000
Table 2. Compliance with minimum requirements for WWTP1. The results are expressed as percentages and refer to the values in the exit samples.
Table 2. Compliance with minimum requirements for WWTP1. The results are expressed as percentages and refer to the values in the exit samples.
ParameterEffluent TreatmentWeather Conditionn. obs (n)Compliance with Minimum Requirements (%)
Class AClass BClass CClass D
BOD5ChlorinatedDry10492.3100
Wet3488.297.1
Total13891.399.3
Not chlorinatedDry34592.599.7
Wet9692.7100
Total44192.599.8
TSSChlorinatedDry10489.497.1
Wet3482.497.1
Total13887.797.1
Not chlorinatedDry34592.299.4
Wet9691.7100
Total44192.199.5
E. coliChlorinatedDry521.99.615.442.3
Wet140.00.00.021.4
Total661.57.612.136.4
Not chlorinatedDry90.00.00.022.2
Wet20.00.00.00.0
Total110.00.00.018.2
Table 3. Compliance with minimum requirements for WWTP2. The results are expressed as percentages and refer to the values in the exit samples.
Table 3. Compliance with minimum requirements for WWTP2. The results are expressed as percentages and refer to the values in the exit samples.
ParameterEffluent TreatmentWeather Conditionn. obs (n)Compliance with Minimum Requirements (%)
Class AClass BClass CClass D
BOD5ChlorinatedDry6498.4100
Wet9100100
Total7398.6100
Not chlorinatedDry17995.099.4
Wet4597.8100
Total22495.599.6
TSSChlorinatedDry6487.5100
Wet977.8100
Total7386.3100
Not chlorinatedDry17988.899.4
Wet4597.8100
Total22490.699.5
E. coliChlorinatedDry5147.170.686.396.1
Wet540.080.080.080.0
Total5646.471.485.794.6
Not chlorinatedDry553.63.65.521.9
Wet120.00.00.016.7
Total673.03.04.520.9
Table 4. Removal efficiency for physico-chemical parameters, according to WWTP and weather conditions. p-values refers to Mann–Whitney U test between dry and wet conditions (significant p-values are in bold).
Table 4. Removal efficiency for physico-chemical parameters, according to WWTP and weather conditions. p-values refers to Mann–Whitney U test between dry and wet conditions (significant p-values are in bold).
ParameterWWTP TypeWeather Conditionn. obsRemoval Efficiency %
Average (10th–90th)		Mann-Whitney U (p-Value)
CODWWTP1Dry44993.1 (88.2–98.6)<0.0001
Wet13087.8 (77.7–100)
Total57991.9 (85.5–98.7)-
WWTP2Dry24393.3 (86.0–100)0.9185
Wet5392.6 (84.7–100)
Total29693.2 (85.6–100)-
BOD5WWTP1Dry44997.7 (93.5–100)<0.01
Wet13094.6 (85.2–100)
Total57997.0 (92.3–100)-
WWTP2Dry24398.3 (94.4–100)0.9451
Wet5396.2 (92.6–100)
Total29697.9 (94.2–100)-
TSSWWTP1Dry44896.6 (90.2–100)<0.01
Wet13092.6 (79.9–100)
Total57895.7 (88.6–100)-
WWTP2Dry24296.3 (88.7–100)0.9596
Wet5396.8 (91.2–100)
Total29596.4 (89.2–100)-
Table 5. Bacterial and viral indicators removal at different stages of the treatment process. Results are expressed as median and interquartile range of the logarithmic removal efficiency (log-removal) of eight sampling dates.
Table 5. Bacterial and viral indicators removal at different stages of the treatment process. Results are expressed as median and interquartile range of the logarithmic removal efficiency (log-removal) of eight sampling dates.
Microbial ParameterWWTP TypeLog-Removal between Entrance and Secondary TreatmentLog-Removal between Secondary and Tertiary TreatmentLog-Removal of the Entire Treatment Process (Entrance Sewage–Tertiary Effluent)
E. coliWWTP12.49 (2.33–2.89)0.30 (0.05–1.45)3.46 (2.54–4.86)
WWTP22.84 (2.50–3.08)0.97 (0.20–2.34)4.13 (3.30–5.31)
Intestinal enterococci WWTP12.63 (2.32–2.82)0.70 (0.02–0.99)3.54 (3.06–3.82)
WWTP22.58 (2.32–2.95)0.56 (0.1–1.56)3.42 (2.93–4.40)
Somatic coliphages WWTP12.43 (1.86–3.09)0.84 (0.36–0.99)3.50 (2.64–4.01)
WWTP22.51 (1.88–2.90)0.99 (0.36–1.47)3.24 (2.30–4.19)
Clostridia spores WWTP12.49 (2.04–2.76)0.51 (0.23–0.97)3.09 (2.71–3.58)
WWTP20.96 (0.79–1.16)0.27 (0.12–0.59)1.24 (1.03–1.46)
Disclaimer/Publisher’s Note: The statements, opinions and data contained in all publications are solely those of the individual author(s) and contributor(s) and not of MDPI and/or the editor(s). MDPI and/or the editor(s) disclaim responsibility for any injury to people or property resulting from any ideas, methods, instructions or products referred to in the content.

Share and Cite

MDPI and ACS Style

Federigi, I.; Salvadori, R.; Lauretani, G.; Leone, A.; Lippi, S.; Marvulli, F.; Pagani, A.; Verani, M.; Carducci, A. Wastewater Treatment Plants Performance for Reuse: Evaluation of Bacterial and Viral Risks. Water 2024, 16, 1399. https://doi.org/10.3390/w16101399

AMA Style

Federigi I, Salvadori R, Lauretani G, Leone A, Lippi S, Marvulli F, Pagani A, Verani M, Carducci A. Wastewater Treatment Plants Performance for Reuse: Evaluation of Bacterial and Viral Risks. Water. 2024; 16(10):1399. https://doi.org/10.3390/w16101399

Chicago/Turabian Style

Federigi, Ileana, Roberto Salvadori, Giulia Lauretani, Anna Leone, Simone Lippi, Francesca Marvulli, Alessandra Pagani, Marco Verani, and Annalaura Carducci. 2024. "Wastewater Treatment Plants Performance for Reuse: Evaluation of Bacterial and Viral Risks" Water 16, no. 10: 1399. https://doi.org/10.3390/w16101399

APA Style

Federigi, I., Salvadori, R., Lauretani, G., Leone, A., Lippi, S., Marvulli, F., Pagani, A., Verani, M., & Carducci, A. (2024). Wastewater Treatment Plants Performance for Reuse: Evaluation of Bacterial and Viral Risks. Water, 16(10), 1399. https://doi.org/10.3390/w16101399

Note that from the first issue of 2016, this journal uses article numbers instead of page numbers. See further details here.

Article Metrics

Back to TopTop