Waste Water Treatment Plant

2.3.3.1 Wastewater Treatment Plants as a Point of Control

WWTPs are a significant point source for AMRDs and antimicrobials. WWTPs are relatively nutrient-rich, heavily contaminated environments that receive waste from a variety of AMRD-loaded environments, including hospitals, industrial and agricultural sites and release both solid and liquid by-products that can disseminate AMRDs. Influent can be contaminated with a variety of pollutants, including antimicrobial agents, pharmaceuticals, personal care products, and heavy metals, which can accumulate within WWTPs. Many microbial and chemical contaminants in wastewater cannot be degraded by the treatment process or inactivated through disinfection of the effluent. For those contaminants that can be degraded, the resulting metabolites may still have antimicrobial or selective activity. WWTP effluent and solid waste products not only have a high prevalence of AMRDs but also release selective agents into the receiving environments (Jury et al., 2011).

The nature of biological treatment can also encourage the dissemination of AMRD into the environment and within the wastewater microbiome. Microorganisms are found in a variety of states in WWTP including in planktonic form, flocs suspended in the wastewater, and biofilms attached to solid surfaces (Sustaric, 2009; Sheng et al., 2010). The presence of microorganisms in flocs and in biofilms may be significant in establishing the basis of why WWTPs are considered both hot spots for gene transfer and possible reservoirs for AMRD.

Andersen (1993) found that microbial community composition in a WWTP affected AMR coliforms. Additionally, different WWTPs have different efficiencies for the removal of AMRO. Both operational conditions and design can influence the fate of AMRDs in WWTPs (McKinney et al., 2010; Novo and Manaia, 2010; Chen and Zhang, 2013). There have been numerous studies to determine which treatment systems and operational conditions impact AMRDs. For instance, Kim et al. (2007) found that both organic loading and growth rate resulted in the amplification of tetracycline resistance in WWTPs using biological treatment processes. Christgen et al. (2015) used metagenomic approaches to compare the fate of AMRDs in anaerobic, aerobic, and anaerobic-aerobic sequence bioreactors (AASs). AASs and aerobic reactors were superior to anaerobic reactors in reducing AMRD abundance, particularly aminoglycoside, tetracycline, and beta-lactam determinants. Sulfonamide and chloramphenicol AMRD levels were unaffected by treatment, and a shift from target-specific AMRDs to AMRDs associated with multidrug resistance was seen in influents and effluents from all WWTP. The AASs used 32% less energy than aerobic reactors and favorably reduced AMRD abundance. The chemical properties of the wastewater, including chemical oxygen demand (COD), ammonia (NH₃–N), suspended solids (SS), dissolved oxygen, and temperature, can impact the fate of different AMRDs. For instance, Du et al. (2014) found that the COD was highly correlated with the fate of tetW, intI1, and sul1. Yuan et al. (2014) indicated that most AMROs and AMRDs were positively related to COD and SS of raw sewage and negatively correlated to the corresponding variables in the effluent.

Similarly, the choice of disinfection method can impact the fate of AMRDs in WWTPs. Disinfection may not reduce the abundance of AMRDs and AMROs in the effluent as Munir et al. (2011) observed when studying the presence of tetracycline and sulfonamide and their resistance determinants within five WWTPs in Michigan. The use of chlorination and UV radiation for disinfection is common, and the effectiveness of these strategies for removing AMRD varies as a result of multiple factors. For instance, Zhang et al. (2015) compared the inactivation of AMRDs in municipal wastewater effluent by chlorination, UV radiation, and sequential UV/chlorination. They found that chlorination was more effective than UV radiation in removing AMRDs from WWTP effluent and that its efficiency was affected by NH₃–N concentration. The presence of high NH₃–N in wastewater corresponds to a decline in AMRD removal (Zhang et al., 2015). Free chlorine was also more effective than combined chlorine, and a combination treatment of UV irradiation followed by chlorination showed higher AMRD removal efficiency than UV or chlorination alone.

The methods of evaluation of AMRDs in WWTPs can make the comparison of studies difficult. In some studies, a culture-dependent step is crucial and the focus is mainly on the detection and fate of AMROs (Reinthaler et al., 2003; Schwartz et al., 2003; Garcia-Armisen et al., 2011; Slekovec et al., 2012), whereas others use a combination of culture-dependent and -independent techniques and have shifted the focus to MGE (Tennstedt et al., 2003; Ma et al., 2013). Studies that use a combination of culture-dependent and -independent techniques provide more comprehensive information than studies that use only one technique or the other. Culture-dependent studies provide valuable information about the expression of AMRDs but neglect the impact of extracellular and unexpressed AMRDs (Matthews et al., 2010), whereas culture-independent methods may not account for the function of those genes.

The complexity of the engineered system can obscure the influence of antimicrobials on the spread and prevalence of AMR both within the WWTP and in their effluent. This can make elucidating the factors and mechanisms responsible for the increased prevalence of AMRDs more difficult and determining their relative importance is a constantly evolving area of research. The high degree of gene transfer that can occur in WWTPs and the high prevalence of AMR in microorganisms isolated from wastewater would suggest that WWTPs are a point source for AMR-related environmental contamination. An engineered system, like a WWTP, may be ideal for environmental public health monitoring, and surveillance efforts and management strategies could be developed that are targeted at reducing the release of AMRDs into water and soil environments.

7.9.3.4.3.2 δ¹⁸O of WWTP phosphate

WWTP effluent is a significant source of phosphate to many different aquatic systems. Comparison of the WWTP effluent data from Young et al. (2009) with data collected from other WWTPs in different parts of the United States and France (Colman, 2002; Gruau et al., 2005) shows that ${\delta }^{18}{\mathrm{O}}_{{\mathrm{PO}}_4}$ values within the effluent from a single plant can vary by at least 3.9‰ for samples collected 3 months apart, and samples from different plants span a range of at least + 8.4‰ to + 18‰, with some samples at the expected equilibrium value and others up to 4‰ away from expected equilibrium value. These results show that ${\delta }^{18}{\mathrm{O}}_{{\mathrm{PO}}_4}$ values of individual WWTPs must be measured for each study location and that δ¹⁸O of phosphate in WWTP effluent may be distinct from other PO₄ sources depending upon the specific study location. Breaker (2009) measured a ${\delta }^{18}{\mathrm{O}}_{{\mathrm{PO}}_4}$ value of + 25.2‰ for WWTP effluent in the Illinois River watershed (USA), higher than the values measured in the same study for four other potential PO₄ sources consisting of poultry litter, runoff from a litter amended pasture, inorganic fertilizer, and septic leachate (range of + 10.6‰ to + 20.0‰). Breaker (2009) found some evidence that WWTP input resulted in a minor increase in downstream ${\delta }^{18}{\mathrm{O}}_{{\mathrm{PO}}_4}$ values, although much of the signal was erased by biological cycling within the river. Colman (2002) analyzed ${\delta }^{18}{\mathrm{O}}_{{\mathrm{PO}}_4}$ in the effluent of a WWTP discharging to the Connecticut River (Connecticut, USA), and found that the PO₄ in the effluent was approximately 2‰ higher than the expected equilibrium value. The δ¹⁸O signal from the effluent was retained downstream in the Connecticut River without significant overprinting from biological cycling.

14.1.2 Wastewater treatment plants

Wastewater treatment plants (WWTPs) are one of the most important receptors and sources of environmental AMR. The importance of surveillance of WWTPs to mitigate the dissemination of AMR is already evident (Waseem et al., 2018). The high-throughput data generated by HT-qPCR will be useful for global surveillances of AMR in wastewaters.

There are many reported studies where the AMR status of WWTPs is being investigated by employing HT-qPCR technology. For example, a trans-European AMR surveillance study has recently investigated the AMR status of the influent and effluent of the WWTPs distributed among seven European countries (Pärnänen et al., 2019). A total of 229 ARGs and 25 MGEs were detected and analyzed in a total of 168 collected samples during the study. Societal and environmental factors such as antibiotic consumption, size of the WWTP, and environmental temperatures were found to be critical for the perseverance and spread of AMR. Strong correlations in the patterns/trends between clinical and environmental AMR were also observed. Another study has also reported the use of HT-qPCR technology for deciphering the seasonal variations of AMR in a WWTP with tertiary treatment in Helsinki, Finland (Karkman et al., 2016b). A total of 296 primers targeting transposase (11 primer sets) and ARGs (285 primer sets) were used. All the transposase primers and 175 ARG primer sets were detected. The study concluded that raw sewage entering the WWTPs could be a rich source of ARGs and transposases. Additionally, it was speculated, based on the results, that a WWTP with a tertiary treatment system can effectively control AMR dissemination into the environment.

There are many instances where, apart from antibiotics, presence of chemicals or heavy metals can coselect bacterial antibiotic resistance (Lin et al., 2016; Pal et al., 2017). HT-qPCR technology has also been employed in attempts to decipher the intricate coselection mechanisms in wastewater treatment plants. In one such effort, the abundance and distribution of ARGs was investigated in different types of wastewaters (dyed and domestic) by using HT-qPCR and RNA sequencing technology (Jiao et al., 2017). The study revealed that the presence of dyeing chemicals in WWTPs could influence the HGT of ARGs. In another study, HT-qPCR technology was used to assess 39 ARGs, five metal resistance genes, and three integron genes in samples collected from nontreated and treated UWWTPs (Sandberg et al., 2018). The established HT-qPCR technology was successfully able to quantify antimicrobial resistance and other genes in environmental samples. In yet another study, the effect of chlorination on the resistance status of WWTPs was evaluated (Lin et al., 2016). A total of 296 primers (285 ARGs and 10 MGEs) were targeted in secondary effluents of a WWTP after chlorination. Surprisingly, the study concluded that, except for a small negligible percentage of ARGs (4.8%), all the detected ARGs were decreased after chlorination. Apart from conventional wastewater treatment plants, HT-qPCR technology has also been extensively utilized to explore the AMR in drinking water treatment systems and hospital wastewaters (Buelow et al., 2018; Tang et al., 2017; Wang et al., 2018c; Xu et al., 2016).

As WWTPs are scarce in developing countries, so the effects of other small-scale AMR treatment technologies have also been evaluated to gauge their impact on ARGs removal. We know that the primary purpose of bioreactors is managing wastes and producing energy and not the removal of AMR. Therefore, aerobic-denitrifying downflow hanging sponge bioreactors were cooptimized for total nitrogen and ARGs removal (Jong et al., 2018). HT-qPCR technology was used to assess the removal of ARGs and MGEs in bioreactors as a function of four different percent bypasses by volume, i.e., 0%, 10%, 20%, and 30%. A total of 296 primer sets were used during the study, out of which 59 ARGs and 7 MGEs were detected in all the assessed samples. All the systems were able to remove more than 90% of the ARGs, but the removal rates of total nitrogen and ARGs were varied in different bypasses. The cooptimal reductions of both the parameters were achieved at 20% bypass.

10.4.1 Microplastics in Wastewater Treatment Processes

Wastewater treatment plants are designed to have distinct water treatment process combinations with varied water treatment facilities depending on the influent's water quality and the effluent discharge standard. Conventional wastewater treatment includes pretreatment, primary treatment, and secondary treatment. A series of treatment processes, for example, bar screening, degreasing, air flotation, primary sedimentation, biofilm process/activated sludge process, and secondary sedimentation, are applied. To further improve the effluent quality, tertiary treatment with (sand) filtration, advanced oxidation process, and membrane filtration are used. So far, no treatment method is specially designed to remove MPs, and only a few studies have investigated the detailed removal efficiencies of MPs at different stages of WWTPs.

Dris et al. (2015a) conducted the first investigation about the fate of MPs in a WWTP through the analysis of wastewater influent and effluent. The WWTP applied screening and grit and oil removal as primary treatment, which was then followed by a primary settling tank and biological treatment. Biofilters were used in the tertiary stage, where the total removal rate of MPs into the sludge reached ~ 90%. In the influent, 1000–5000 μm MPs contributed to 45% of the total amount, which were completely removed after tertiary treatment. On the other hand, only small MPs (100–1000 μm) were found in the final effluent. It should be noted that fibers, but not fragments, were the predominant MPs in this WWTP. One shortcoming of this study was that there was no detailed investigation of MP morphology.

Around the same time, Talvitie et al. (2015) also studied a WWTP in Helsinki, Finland, which applied a conventional tertiary treatment procedure. Influent of this WWTP contained approximately 180 textile fibers and 430 synthetic particles per liter. Microplastic fibers were mostly removed by primary sedimentation, while MP particles were mostly settled in secondary sedimentation. Biological filtration in tertiary treatment further improved the removal efficiency of MPs. After the treatment process, an average of 4.9 (± 1.4) fibers and 8.6 (± 2.5) particles per liter were found in final effluent. Artificial textile fibers and synthetic plastic particles were identified as the dominating MPs following a similar pattern in the WWTP effluent and receiving sea water, verifying the role of WWTP as a route for MPs entering the sea.

Carr et al. (2016) investigated the transport of MPs in a tertiary wastewater reclamation plant, but only limited information was provided in regard to the concentration of MPs. The study also confirmed that pretreatment and primary treatment were effective for removing MPs. The majority of MPs in this WWTP had a profile (color, shape, and size) similar to the blue polyethylene particles in toothpaste formulations, implying that the additives in cosmetic and personal care products were the main sources of MPs in WWTPs. It should be noted that the concentration of MPs in return activated sludge reached ~ 50 particles L^− 1, indicating a transport of MPs from wastewater to activated sludge during biological treatment.

Murphy et al. (2016) investigated a WWTP in England serving 6.5 × 10⁵ populations, which used secondary treatment facilities with average treatment capacity of 2.6 × 10⁶ m³ day^− 1. Only grab sampling was applied, and microscope combined with FTIR was used for determining the concentration and composition of MPs. The WWTP influent contained on average 15.70 (± 5.20) particles L^− 1, which was reduced to 0.25 (± 0.04) particles L^− 1 in the final effluent (removal rate reached 98.4%). Approximately 45% of MPs were removed by pretreatment with coarse screening. Subsequent fine screening, grit sedimentation, degreasing, and primary sedimentation removed an additional ~ 34%. The secondary treatment stage handled the other ~ 20% MPs, implying that traditional biological treatment followed by a second sedimentation is also effective for MP elimination. Despite the high removal rate, it was calculated that 65 million pieces of MPs are still discharged into receiving water every day from this WWTP. This suggests that modern WWTPs transport a huge amount of MPs, especially small-size particles, into ambient waters.

In addition, this study also investigated MPs in grit and grease samples and in the sludge cake from sludge treatment. The grease sample contained an average of 19.67 (± 4.51) particles per 2.5 g, which was significantly higher than the grit and sludge cake samples. The study also found that polyethylene microbeads from cosmetic and personal care products were dominant in grease samples. Fortunately, because of their lightweight nature and hydrophobicity, polyethylene microbeads are buoyant on the surface of wastewater and can therefore be easily skimmed off during the degreasing treatment. The final effluent of this WWTP contained no intact microbeads, which may be destructed into some smaller fragments with irregular shapes after the treatment processes.

Two full-scale WWTPs, which employed traditional secondary treatment and tertiary treatment, were examined by Michielssen et al. (2016). Removal efficiency of MPs in a novel pilot-scale WWTP with a microfiltration membrane bioreactor system was also evaluated. A mesh sieve stack was used for sampling, but only stereomicroscope was employed for MP identification. The total removal efficiency reached 95.6% and 97.2%, respectively, after the secondary treatment and tertiary treatment. The membrane bioreactor system removed 99.4% MPs, discharging 0.5 particles L^− 1 MPs. Fibers but not microbeads were identified as the major part in the effluent from two full-scale WWTPs.

More recently, Ziajahromi et al. (2017) compared the removal efficiencies of MPs in three WWTPs. Grab sampling was performed using a customized separating devices (Fig. 10.1), and FTIR was used for the identification of MP particles. After primary treatment and secondary treatment, the concentration of MPs decreased to 1.44–2.20 and 0.48 particles L^− 1, respectively, while the tertiary treatment only yielded a slight improvement. Ziajahromi et al. (2017) investigated the size distribution of MPs in effluent from different stages, and results demonstrated that large particles (≥ 190 μm) were removed in mechanical primary treatment. However, smaller MPs (25–190 μm) were still abundant in the secondary and tertiary effluent. It should be noted that fibers from domestic laundry discharges were dominant in the effluent of all three WWTPs.

In modern WWTPs, primary treatments and secondary treatments have a high removal efficiency of MPs, especially for large particles with low density, which is transported into inorganic sludge (from primary sedimentation or flotation) and organic sludge (from biological treatments), implying that WWTPs are not the final ends of most MPs in wastewater (see Section 11.4.2). Surprisingly, advanced methods in the tertiary stage only slightly improve the ability to intercept smaller residual MPs. For example, effluent of reverse osmosis (Ziajahromi et al., 2017) or microfiltration (Michielssen et al., 2016) still contained MP particles (0.21 and 0.50 particles L^− 1, respectively), indicating that most of the existing treatment methods are inefficient for completely removing MPs from wastewater. MPs of small sizes (< 0.5 mm) in the shape of fiber and microbeads are ubiquitous in the final effluent. The concentrations of MPs in the final effluent of most WWTPs are relatively low (< 1 particles L^− 1), but the discharge volume of normal WWTPs generally reaches 10⁸ L day^− 1 level. This means that a large amount of MPs can enter the receiving water on a daily basis.

1 Introduction

Wastewater treatment plants (WWTPs) are complex systems characterized by intercorrelated physical, chemical, and biological processes and reactions (Nasr, Moustafa, Seif, & El-Kobrosy, 2014; Ugwu & Enweremadu, 2020). These reactions are difficult to model using simple and linear mathematical regression methods (Nasr & Zahran, 2014; Ulucan-Altuntas & Kuzu, 2019). Moreover, WWTPs suffer from hourly, daily, and seasonal variability in discharge quantities and wastewater influent characteristics (Wang, Kvaal, & Ratnaweera, 2019). Despite the high variations of organic and nutrient loads and operational conditions, WWTPs have to maintain high performance with allowable effluent discharges (Nasr, 2018). Mathematical modeling is an adequate approach employed to simulate the WWTP operation for the purposes of optimization, prediction, soft sensing, and control (Karri, Damaraju, & Chimmiri, 2009; Sulthana et al., 2014; Wu, Yang, Wu, Mao, & Zhou, 2016). Artificial neural network (ANN), fuzzy logic (FL), genetic programming, model trees, and hybrid intelligent techniques have found practical applications to model various processes in water and wastewater treatment (Hawari et al., 2017; Karri, T., & C., 2010; Zhang & Qiao, 2020). These black-box modeling techniques have also been applied to reduce costs and improve WWTPs operations (Nadiri, Shokri, Tsai, & Moghaddam, 2018), as well as to overcome the lack of reliable automation instruments (Ruan, Chen, Huang, & Zhang, 2017; Wang et al., 2019). Multivariate methods such as principal component analysis (PCA), independent component analysis (ICA), and clustering have also been employed for data management to monitor, assess, and understand the important features of WWTPs (Jaiswal, Hussain, Gupta, Nasr, & Nema, 2019). Among these mathematical methods, artificial intelligence (AI) has been widely used to model and simulate the WWTPs, even in cases where data are insufficient (Nasr, 2019). Moreover, the AI models can help operators to understand and improve the performance of wastewater treatment facilities (Fawzy, Nasr, Adel, Nagy, & Helmi, 2016a; Yetilmezsoy et al., 2020). However, still more efforts are essential to ensure the applicability and validity of AI models for the management and control of WWTPs, as well as for improving the consistency of decisions.

Hence, this chapter represents the AI techniques that have been recently used to handle the issues of complexity and dynamicity regarding the process of control and automation in WWTPs. The AI technique is selected in this chapter due to its ease and simplicity of application and reasonable prediction accuracy, with no requirement to understand the detailed physical, chemical, and biological reactions in the system. The application of this powerful and practical modeling tool in the field of wastewater treatment has been reviewed to cover the recent publications executed in the SCOPUS database during 2010–19. Case studies and real-world examples that cover the application of AI modeling to solve nonlinear, and complex wastewater treatment issues are also given.

Abstract

Wastewater treatment plants (WWTP) play a crucial role on environmental preservation. The use of appropriate technologies, along with well-established operational strategies, may enable the removal of several pollutants from wastewaters, such as organic matter, nitrogen and phosphorus, avoiding their adverse impacts on the environment. Despite the benefits of implementing the WWTP, their operations can also cause polluting effects, mainly associated with the emission of greenhouse gases (GHG), among which carbon dioxide (CO₂), methane (CH₄), and nitrous oxide (N₂O). While contributions to CO₂ generation are mainly related to energy consumption within the WWTP boundaries, CH₄ and N₂O emissions are associated with biological carbon and nitrogen conversion processes, such as methanogenesis, nitrification and denitrification. In this chapter, the role of different processes in GHG production is assessed. Besides, operational strategies to minimize GHG emissions from WWTP are also addressed, including the control of several variables within the plants facilities, such as dissolved oxygen concentration, applied load, temperature, pH, hydraulic and solids retention time. Treatment approaches for GHG streams that are inevitably produced and innovative processes, such as Anammox, Coupled Aerobic-Anoxic Nitrous Decomposition Operation and cocultures of bacteria and microalgae, capable of generating less GHG and allowing better use of wastewater resources, are also described. Finally, the effects of climate change and its associated consequences (e.g., increased rainfall intensity and temperature), on the performance and operation of current wastewater treatment systems are presented.

11.2 Pharmaceutical contamination of water worldwide

Wastewater Treatment Processes

1 Introduction

Wastewater treatment plants (WWTPs) were set up for the removal of different contaminants present in wastewater before its discharge into nearby water bodies. These WWTPs generate a lot of a residual waste, known as waste sludge, a by-product of the different processes involved (coagulation, filtration, disinfection, etc.). About 100,000 tn/yr of sludge is produced worldwide with estimated average daily production of more than 1000 tons (Babatunde and Zhao, 2007). Studies estimate a total annual production of 240 million tons of sludge in developed countries (i.e., Europe, USA, and China) only from the WWTPs (Pritchard et al., 2010), while specifically in Europe it will reach up to 13 million tons in 2020 (Gendebien et al., 2010). This sludge is of great environmental concern as it is treated as a waste and, in India, it is discharged into the nearby water bodies or nearby open lands (Kamyotra and Bhardwaj, 2011).

As it is generated from the treatment of wastewater, sludge is an active mixture of water (90%–98%), organic matter (50% of total dry weight) (Martinez-Toledo et al., 2012), dead and alive microorganisms both beneficial as well as pathogenic (Viau et al., 2011), and harmful inorganic (heavy metals such as Cd, Hg, Pb, etc.) and organic contaminants (PAHs, pesticides, etc.) (Gonzalez-Martinez et al., 2016; Rodríguez et al., 2015; Saunders et al., 2016). The actual biological, chemical, and physical composition of sludge varies according to the treatment methods used at the WWTPs (Sales et al., 2011). Sludge is mainly used for landfilling and as a fertilizer in agriculture (Gorazda et al., 2017), while a quantity is utilized for thermal processing. The main constraint on sludge use as a resource rather than as waste is the presence of heavy metals and pathogens. This problem is related to the proper treatment procedures to reduce hazardous levels to non-hazardous levels.

In developing countries like India, the problem is more severe since WWTPs dispose the waste directly in nearby drainage without proper and required treatment. Direct discharge from industries results in bioaccumulation of harmful compounds in aquatic life and presents a great threat to the environment (Mandal et al., 2019). Thus, the proper pretreatment of sludge should be legally mandatory before its discharge since zero waste production is not possible. However, the waste production should be minimized by applying the circular economy principles or use of the “3Rs,” i.e., reduce, reuse, and recycle.

20.3.1 Wastewater treatment plants

Wastewater treatment plants (WWTPs) are an important aspect of modern urban life, consisting of different processes for the degradation of organic waste, removal of phosphorus and nitrogen, and reduction of pathogen burden before the release of used water into the surrounding environment. The used water management systems gather and then treat different waste materials (Pruden, 2013). In the last century, WWTP's fundamental structure was improved and enhanced the water and sanitation management system that was not intentionally designed for AMR management. The interpretation of the destiny of antibiotic resistant bacteria (ABR) and ARGs via the water sanitation and cleanliness practices now has become severe for the rehabilitation of used water for irrigation and drinking purposes (Pruden et al., 2012).