Biodegradation of Emerging Organic Micropollutants in Nonconventional Biological Wastewater Treatment: A Critical Review

Abstract

Biodegradation is the predominant removal mechanism for emerging organic micropollutants (EOMs) in wastewater and a promising approach to fully degrade these compounds during wastewater treatment (WWT). This review aims to deliver an up-to-date scientific and technical overview of EOM biological removal during WWTs with a focus on nonconventional biological treatment to include: hybrid activated sludge and membrane bioreactor systems; immobilized, packed-bed, and granular systems; and electro-biochemical treatment. Individual microorganisms that have proven effective in degradation of EOMs commonly found in municipal wastewaters (pesticides, industrial chemicals, disinfectants, and some pharmaceuticals) are included, and elucidated metabolic pathways involved are discussed. Factors that influence biological removal of EOMs in complex wastewater matrices during nonconventional WWTs are assessed based on 25 studies, which provide data on the removal of 151 EOMs and 398 different treatment conditions. Furthermore, in silico tools are discussed, highlighting how they could be used as time-saving approaches to further EOM biodegradation research. Links among these sets of studies are used to identify trends and limitations, to propose future cutting edge research directions to improve biological EOM removal during WWT. Overall, bioremediation has the hallmark of an effective means for removal of EOMs, provided that a well-directed and systemic approach is found to study and implement these complex mechanisms in existing or new WWTs.

Introduction

In water and wastewater, emerging organic pollutants, or emerging organic micropollutants (EOMs) if their concentrations are below parts per million (ppm), is an umbrella term that includes a wide range of chemicals: pharmaceutical and personal care products (PPCPs), pesticides, mycotoxins, fragrances, detergents, illicit drugs, disinfection by-products, and other wastewater treatment (WWT) by-products (Masoner et al., 2014). As EOMs, these contaminants have begun to be addressed in water/wastewater regulations in certain countries (European Parliament, Council of the European Union, 2013; Metz, 2017). Due to the awareness of these pollutants and interest in their removal, since the year 2000 there has been an exponential growth in the number of publications on EOM biodegradation during WWTs (Source, Web of Science^™; Supplementary Fig. S1 in the Supplementary Data).

EOMs are emitted from point and nonpoint sources. Wastewater treatment plant (WWTP) effluents, sewage overflows, and final landfill leachates are point sources. Agricultural, stormwater, and urban runoffs and other contaminated environmental media can be nonpoint sources (Lapworth et al., 2012; Furlong et al., 2014; Masoner et al., 2014). WWTPs are considered the main point sources of EOMs and are the focus of most EOM removal studies (Fairbairn et al., 2016). In a WWTP, EOMs are removed and emitted at different processing stages. The amount and type of EOMs in WWTPs' influents and effluents depend on multiple factors, including sewage contributors (hospitals, manufacturing facilities, households, etc.), treatment technologies, degradation patterns, as well as seasonal, temporal, and population variability.

The aim of this article is to provide an up-to-date scientific review of biological removal of EOMs commonly found in wastewater (e.g., pesticides, industrial chemicals, disinfectants, and PPCPs) with emphasis on nonconventional biological treatments (specifically: hybrid activated sludge and membrane bioreactor (MBR) systems; immobilized, packed-bed and granular systems; and electro-biochemical treatments). Possible effects of EOMs on the environment and human health are presented, and general microbial biodegradation concepts are introduced (Section “Effect and biodegradation of EOMs”). Next, two sets of studies are presented with increasing levels of EOM biodegradation complexity. The first set of studies focuses on the biodegradation of a specific EOM by a specific microbial strain, or a defined microbial community (Section “Biodegradation Mechanisms by Specific Microbial Strains”). The second set showcases more complex biodegradation scenarios of nonconventional WWTs for municipal wastewater effluents, with microbial consortia degrading highly heterogeneous mixtures of EOMs (Section “Biodegradation in Engineered Systems”). Finally, we discuss in silico approaches that can aid in the study of EOM biodegradation during WWTs (Section “In Silico Approaches”). Main trends, limitations, and possible future developments in the mentioned studies are discussed regarding their application to nonconventional WWTs. Connections between these sets of studies are drawn (Supplementary Fig. S2, as Supplementary Data) to better contextualize and illustrate the complexity of EOM biodegradation in novel treatments. Due to the large and rapidly evolving body of work on the various aspects of EOM biodegradation during nonconventional WWTs, the list of references included cannot be complete, but is a personal selection that allows us to illustrate a given issue.

Effect and Biodegradation of EOMs

Effects of EOMs

By definition, EOMs are present at low concentrations. Thus, their effects are typically a result of chronic rather than of acute exposure. In the environment, EOMs can be taken up by plant and animal tissues (Dolliver et al., 2007; Kinney et al., 2008; Fair et al., 2009; Ericson et al., 2010; Schultz et al., 2010; Mita et al., 2011), and their effects include behavioral, physical, and metabolic changes in microorganisms and higher organisms (Morthorst et al., 2010; Underwood et al., 2011; Jonsson et al., 2014). In humans, chronic exposure to low doses of pesticides and pharmaceuticals may lead to the development of diseases like cancer, infertility, and alterations to the immune, endocrine, and neural systems (Möckel, 2015; Kaushik et al., 2016). In Rajamani et al. (2017), chronic exposure (12 days) to individual EOMs (perfluorooctanoic acid at 1.0 ppm; tributyltin at 2.9 parts per billion [ppb]; and butylhydroxytoluene at 2.2 ppb) led to perturbations in early endocrine system development cells, which may contribute to metabolic diseases at later stages. Kaushik et al. (2016) also found that a mixture of psychoactive pharmaceuticals (mix: fluoxetine 10 μg/L; venlafaxine 50 μg/L; carbamazepine 100 μg/L, and valproic acid: 4.9 mg/L) altered the gene expression of neuronal systems in vitro. These gene expressions are associated with neuronal growth, development, and regulation, and their alteration may result in neurological disorders. It is noteworthy that these EOMs are commonly found in wastewater (Yu et al., 2009; Zareitalabad et al., 2013; Kaushik et al., 2016). Determining long-term effects of EOMs in the water environment is an evolving field with several important unexplored areas such as understanding the effects of (i) complex EOM mixtures and their bioaccumulation and (ii) exposure of EOMs at different developmental stages in vivo (Vasquez et al., 2014; Aguirre-Martínez et al., 2015; Rajamani et al., 2017).

Biodegradation overview

Following the precautionary principle as a guideline for environmental and public health issues, the complete degradation of EOMs or their transformation to innocuous compounds is highly sought after during WWTs. EOM removal in WWTPs generally includes physicochemical, chemical, and biological approaches. Physicochemical technologies include: (i) hydrophobic sorption (adsorption) onto surfaces, (ii) absorption into porous materials, and (iii) selective permeation in tangential flow filtration membranes. After the adsorption step, EOMs can be degraded biologically during the secondary treatment or chemically during the tertiary treatment. Chemical treatments, such as advanced oxidation processes (AOPs; involving the generation of hydroxyl radicals [•OH]), have received increasing attention for EOM removal. However, few AOP treatments fully degrade EOMs and tend to be energy intensive (Ganzenko et al., 2014). Thus, complete removal of EOMs by biodegradation promises to be a worthwhile field of investigation to be applied to WWTs.

Biodegradation is the predominant removal mechanism of some EOMs, specifically for PPCPs, endocrine disruptive compounds, plasticizers, and surfactants in municipal wastewaters (De Wever et al., 2004; Batt et al., 2007; Chen et al., 2008; Abegglen et al., 2009; Stasinakis et al., 2010; Estrada-Arriaga and Mijaylova, 2011; Salgado et al., 2012; Alvarino et al., 2014; Ba et al., 2014; Rattier et al., 2014; Belhaj et al., 2015; Zhang et al., 2016). Microbial biodegradation processes include diverse and often complementary mechanisms, from adsorption of pollutants onto biomass or biofilm, to mineralization where final degradation products are inorganic compounds (e.g., CO₂ and H₂O) and biomass. In addition, partial degradation (biotransformation or detoxification) could occur, where initial transformation of an EOM could result in lower toxicity metabolites (through the metabolism of a microorganism or a group of them). However, biotransformation could also produce daughter compounds of a much higher toxicity or persistence than the initial compound (Tran et al., 2013).

Biodegradation of EOMs may be carried out by cometabolism processes, where the degrading microorganisms utilize one compound as the carbon source and another as energy (Fischer and Majewsky, 2014; Huntscha et al., 2014; Fukuoka et al., 2015; Mazioti et al., 2015b). This mechanism is of interest, since EOMs may not be present in sufficient amounts to serve as growth substrates (Fischer and Majewsky, 2014; Huntscha et al., 2014; Tran et al., 2014). A review of the metabolic and cometabolic activities of autotrophic and heterotrophic microorganisms in the biodegradation of EOMs in frequently used WWTs has been carried (Tran et al., 2013). Overall, understanding EOM biodegradation pathways and mechanisms is key to optimizing biological WWT operations. However, accurately determining biodegradation pathways is not straightforward since these may include multiple reactions in parallel or in sequence, such as complex redox reactions.

Biodegradation Mechanisms by Specific Microbial Strains

This section briefly surveys literature from the past 10 years that covers biodegradation of individual EOMs by specific microbial species or communities, carried out under controlled conditions at laboratory scale. The review of these studies is not meant to be exhaustive, only indicative of future research opportunities. The works in this section are the least complex biodegradation scenarios reviewed, and the chosen EOMs are case studies for contaminants commonly found and studied in municipal wastewaters: pesticides, industrial chemicals, disinfectants, and PPCPs. The summarized studies of Section “Bacterial degradation of EOMs” can be found in Table 1 and the EOM physicochemical characteristics (International Union of Pure and Applied Chemistry name, molecular formula, structure, molecular mass, class, and certain computed chemical properties, such as hydrogen bond donor count; hydrogen bond acceptor count; and rotatable bond count and complexity) in Supplementary Table S1 (Supplementary Data). The observed limitations and opportunities are described below.

Table 1.

Degradation of Emerging Organic Micropollutant by Pure Strains and Specified Mixed Cultures

Contaminant	Microorganism	Biodegradation efficiency	Observations	References
2,6 Dichlorobenzamide (BAM; metabolite of pesticide dichlobenil)	Aminobacter sp. strain MSH1	96% (2.7 μg/L) in 1.1 h	• Insignificant formation of degradation products.	Albers et al. (2014)
			• Optimal conditions and/or better contact between cell and compound are required.
			• BAM quantification limit: ∼0.1 μg/L.
	Aminobacter sp. strain MSH1	65–85% (0.9–734 μg/L) in 600 h	• Aminobacter sp. strain MSH1 uses micropollutant 2,6-dichlorobenzamide (BAM) as a C source.	Horemans et al. (2017)
			• The bacterium showed a high frequency of loss of its BAM-mineralizing phenotype under nonselective conditions, which could be due to the loss of genes that convert 2,6-DCBA to Krebs cycle intermediates.
			• The BAM quantification limit is not reported.
Mecoprop 2-(4-chloro-2-methylphenoxy) propanoic acid (R and S enantiomer mixture)	Mixed consortium (as biofilm)	50–83% (10–100 μg/L) in 200 h	• Significant removal preference toward (S)-mecoprop (the enantiomer with no herbicidal activity).	Casas et al. (2017)
			• Carbon supplementation with methanol improved biodegradation.
			• Mecoprop was only removed in the presence of biofilms; the same consortia did not remove the contaminants when it was in suspension.
			• Mecoprop quantification limit: 0.01 ng/mL; enantioselectivity quantification limit: 0.2 ng/mL.
Nonylphenol	Sphingomonas sp. strain TTNP3	93% (2.51 mg/L) (MBR) in 120 h	• Bioaugmentation of MBR and CAS systems• MBR formed only one metabolite.	Cirja et al. (2009)
		50% (2.51 mg/L) (CAS) in 120 h
			• Complex mixtures of structurally similar metabolites in the control reactor.
			• Bioaugmentation had a positive effect on the formation of extractable and nonextractable residues in comparison to the control reactor.
			• The nonylphenol quantification limit is not reported.
	Facultative microbial consortium NP-M2	75–90% (1,000 mg/L) in 48–192 h	• Final consortium included mainly members of the Sphingomonas, Pseudomonas, Alicycliphilus, and Acidovorax genera.	Bai et al. (2017)
			• Carbon supplementation using yeast extract was more effective than using glucose.
			• Secreted surface-active compounds may aid nonylphenol bioavailability and its biodegradation.
			• The nonylphenol quantification limit is not reported.
Bisphenol A (BPA)	Proteobacteria, Bacteroidetes, Chloroflexi, Firmicutes, Gemmatimonadetes, and Actinobacteria	>89% (50 mg/kg) from 960 to 2,880 h	• River sediments were studied under nitrate- or sulfate-reducing conditions.	Yang et al. (2015)
			• Bacterial diversity increased in nitrate-reducing sediment microcosm.
			• Bacterial diversity decreased slightly in sulfate-reducing sediment microcosm.
			• BPA quantification limit: 0.05 mg/kg sediment.
Bisphenol A (BPA)	Ammonia-oxidizing bacteria consortia	87.1–92.9% in (2.5–10.0 mg/L) 1.5 h	• Nitrification efficiency was not related to BPA removal; therefore, the participation of nitrifying bacteria was limited.	Zielinska et al. (2014)
			• Initiation of biodegradation required the adaptation of the microorganisms.
			• Prolonged exposure to BPA or its by-products could have caused damage to cells or inactivation of ammonium oxidation.
			• The BPA quantification limit is not reported.
	Heterotrophic nitrifying microorganisms	80–100% (0.12–1.6 mg/L) after 48 h	• BPA degradation was observed only in the absence of allylthiourea (an inhibitor for ammonia monooxygenase, AMO)	Roh et al. (2009)
			• AMO might be responsible for triclosan and BPA degradation
			• BPA quantification limit: 0.005 mg/L
	Nitrosomonas europaea	80% (0.12–1.6 mg/L) after 10 h	• BPA was cometabolized with triclosan	Roh et al. (2009)
			• More studies are needed to identify and understand the active EOM-degraders, other than ammonia oxidizers, in various CAS systems.
			• BPA quantification limit: 0.005 mg/L
	Sphingobium sp. BiD32	60% removal (1.5 mg/L) after 7 h	• Upregulated proteins in the presence of BPA were characterized as dehydrogenases, a dioxygenase, a hydratase, a hydroxylase, and a cycloisomerase.	Zhou et al. (2015)
			• Novel BPA transformation pathway identified based on the metabolite BPA-M (1,2-Bis(4-hydroxyphenyl)-2-propanol) and the increased abundance in the protocatechuate transformation genes.
			• The BPA quantification limit is not reported.
Triclosan and BPA	Heterotrophic nitrifying microorganisms	100% Triclosan (0.5–2 mg/L), BPA (0.12–1.6 mg/L) after 120 h	• Ammonia-oxidizing bacteria cometabolized triclosan and BPA, offering another potential removal treatment.	Roh et al. (2009)
			• Triclosan quantification limit: 0.005 mg/L.
Triclosan	Nitrosomonas europaea	70% (0.5–2 mg/L) after 10 h	• Triclosan removal was carried out in the absence of allylthiourea and with ammonia-oxidizing bacteria and heterotrophic microorganisms from nitrifying CAS.	Roh et al. (2009)
			• Triclosan quantification limit: 0.005 mg/L.
	Sphingomonas sp. PH-07	75% (1–10,000 μg/L) after 8 h	• Both aromatic rings of the compound dihydroxylated during bioremediation.	Kim et al. (2011)
			• The triclosan quantification limit is not reported.
	Sphingomonas sp. RD1	Not reported	• First step of triclosan biodegradation included adding a hydroxyl group to triclosan to form hydroxy triclosan, which then underwent spontaneous fission to yield 2,4-dichlorophenol and 4-chlorocatechol.	Kagle et al. (2015)
			• Results suggested that triclosan degradation gene clusters have been acquired through horizontal gene transfer
			• The triclosan quantification limit is not reported.
3-Methylindole	Cupriavidus sp. strain KK10	100% (100 mg/L) after 48 h	• 3-Methylindole (at 100 mg/L in glycerol) was biodegraded in 24 h as the sole source of carbon and energy.	Fukuoka et al. (2015)
			• Waste glycerol was utilized as a cosubstrate to mitigate multiple pollution/disposal challenges.
			• The 3-methylindole quantification limit is not reported.
Cefdinir	Ustilago sp. SMN03	81% (100 mg/L) after 144 h	• Biodegradation took place under aerobic conditions following pseudo-first order kinetics.	Selvi et al. (2014)
			• Isolate yeast utilized cefdinir as carbon and energy source.
			• Functional groups such as carboxyl, hydroxyl, lactam, and carbonyl were biodegraded to simpler intermediates.
			• The cefdinir quantification limit is not reported.
Naproxen	Stenotrophomonas maltophilia KB2	78% and 40% (6 mg/L) after 480 h	• Naproxen was cometabolized with glucose or phenol.	Wojcieszynska et al. (2014)
			• Cometabolic systems provided higher biodegradation efficiency with a simultaneous increase of bacterial growth.
.			• The naproxen quantification limit is not reported.
Ibuprofen	Heterotrophic nitrifying microorganisms	100% (0.4 mg/L) after 48 h	• Degradation was not directly linked to a specific microbial strain.	Roh et al. (2009)
			• Results strongly suggested that nonammonia-oxidizing bacteria are important for ibuprofen removal in wastewater.
			• Ibuprofen quantification limit: 0.005 mg/L.
	Microbial consortium from the hyporheic zone (HZ) of rivers downstream of wastewater treatment plants	100% (5, 40, 200, and 400 μM) after 264–384 h	• Ibuprofen treatment resulted in an increase in the abundance of Proteobacteria, Acidobacteria, Actinobacteria, and Firmicutes.• Consortium was able to remove ibuprofen within 24 h (adaptation time to ibuprofen).	Njeru et al. (2017)
			• The ibuprofen quantification limit is not reported.
	Patulibacter sp. strain I11	62–92% (50 μg/L) after 90 h	• Cytochrome b and c, dehydrogenases, and oxidoreductases were considered as possible proteins involved in the ibuprofen biodegradation pathway.	Almeida et al. (2013)
			• Differences between the proteomic data and the qPCR (genomic) data did not allow to determine the ibuprofen biodegradation pathway(s).
			• The ibuprofen quantification limit is not reported.

Physicochemical and other properties of EOM are listed in Supplementary Table S1 in Supplementary Data.

EOM, emerging organic micropollutant; qPCR, quantitative PCR; 2,6-DCBA, 2,6-dichlorobenzoic acid; MBR, membrane bioreactor; CAS, conventional activated sludge.

Bacterial degradation of EOMs

Pesticides

Albers et al. (2014) investigated the biodegradation of 2,6 dichlorobenzamide (BAM), a metabolite of the pesticide dichlobenil, by Aminobacter sp. MSH1 in biologically active sand filters. The inoculated filters removed up to 96% of BAM (starting concentration: 2.7 μg/L BAM) with a 1.1 h residence time (Table 1). Compared to other reviewed contaminants, this compound has a short treatment time possibly due to its high solubility in water. BAM's biodegradation by Aminobacter sp. MSH1 is carried out by two plasmids: (i) the IncP-1 plasmid pBAM1 with the bbdA gene which transforms BAM to 2,6-dichlorobenzoic acid (2,6-DCBA) and (ii) the repABC family plasmid pBAM2 with two gene clusters that degrade 2,6-DCBA to Krebs cycle intermediates (Horemans et al., 2017). In this study, the mentioned catabolic ability was observed to be unstable (i.e., catabolic-gene loss) if the EOM was no longer present. Other works have reported the instability of organic-xenobiotic-catabolic genes in organic-xenobiotic-degrading bacteria, which can be a result of intramolecular gene rearrangements or complete plasmid loss (Horemans et al., 2017).

Casas et al. (2017) studied the biodegradation of the herbicide mecoprop, or 2-(4-chloro-2-methylphenoxy) propanoic acid (a mixture of two enantiomers, where the (R)-enantiomer has the herbicidal activity). A consortium of immobilized microorganisms was grown as a biofilm on carriers in low-nutrient wastewater with spiked mecoprop (10–100 μg/L). Biofilms biodegraded 50–83% of mecoprop after ∼200 h with significant preference toward (S)-mecoprop (the enantiomer without herbicidal activity), while there was insignificant biodegradation if the bacteria did not form biofilms. This consortium's bacterial composition was characterized, and the main genera found were Sphingobium, Rhodospirillales, Parvibaculum, Kaistia, Bradyrhizobium, Roseomonas, and Variovorax. The metagenomic assembly from the sequenced pooled DNA was screened for known phenoxy herbicide catabolic genes. A new metabolite (4-chloro-2-methylphenol sulfate) was identified that may be related to sulfation and glucuronidation pathways in the metabolism of aromatic hydrocarbons by fungi. However, the fungal biomass, which made up 3% of the metagenome, and its genetic potential for the biodegradation of phenoxypropionic acid herbicides were unexplored.

Industrial chemicals

Nonylphenol is a persistent degradation product of nonionic surfactants and reported to be an endocrine disrupter (Masoner et al., 2014). Nonylphenol degradation efficiencies higher than 89% have been obtained by pure cultures and identified consortia with a range of treatment times from 1.5 to 2,880 h (Cirja et al., 2009; Bai et al., 2017). Bai et al. (2017) hypothesized that biodegradation is initiated by oxidizing the benzene ring, followed by stepwise side-chain biodegradation. It was also observed that surfactants (excreted by Sphingomonas sp.) can aid in nonylphenol biodegradation. Furthermore, Kolvenbach and Corvini (2012) surveyed current literature on the biodegradation of alkylphenols by Sphingomonas sp. strain TTNP3, including nonylphenol isomers and bisphenol A (BPA). They concluded that this bacterium biodegrades alkylphenols by a type II ipso-substitution mechanism and that the catabolic biodegradation pathway to degrade alkylphenols and downstream products (i.e., hydroquinone [HQ]) is conferred by a patchwork of genes, opdA genes and the hqd gene cluster (genes for HQ degradation). Based on the location of these genes and the catabolic capabilities of other Sphingomonas strains, several studies reviewed in this work suggested that these genes might have been acquired by transposition events.

Degradation of BPA, a plastic intermediate, has been also extensively studied. A mixed consortium of immobilized microorganisms with high nitrification activity was examined, obtaining removal efficiencies from 87–93% (Zielinska et al., 2014). A strong negative correlation between removal efficiency and nitrification efficiency was observed, indicating a possible competitive inhibition between the target compound and ammonia. That is, the ability of degrading BPA or nitrifying ammonia by these bacteria appears to weaken because the other process dominates. Other researchers have found that BPA can be degraded by ammonia-oxidizing bacteria and heterotrophic microorganisms from nitrifying activated sludge (Roh et al., 2009). More specifically, BPA degradation has been carried out with Nitrosomonas europaea in the absence of allylthiourea, an inhibitor of ammonia monooxygenase. Considering that BPA was not degraded by N. europaea when allylthiourea was present, the researchers in this study suggested that ammonia monooxygenase might be responsible for the degradation (Roh et al., 2009). BPA can also be removed by anaerobic treatment under nitrate- or sulfate-reducing conditions (Yang et al., 2015). Even though the removal rates were >89%, the treatment times were 960–2,880 h long. Furthermore, genomic analysis indicated that Proteobacteria, Bacteroidetes, Chloroflexi, Firmicutes, Gemmatimonadetes, and Actinobacteria were the major bacterial groups in BPA-degrading anaerobic sediments.

Zhou et al., (2015) thoroughly studied the biodegradation of BPA by Sphingobium sp. BiD32, a documented BPA-degrading culture, by a combination of genomics, proteomics, and metabolite analysis to identify enzymes responsible for BPA degradation. The upregulated proteins in the presence of BPA were characterized as dehydrogenases, a dioxygenase, a hydratase, a hydroxylase, and a cycloisomerase, and were related functionally to the degradation of aromatic contaminants. Some of these proteins were homologous to the genes proC, proB, proA, and proJ, which are part of a proposed protocatechuate degradation pathway for BPA. Based on these observations, a novel BPA transformation pathway was identified. This work presented different enzymes involved in the BPA transformation than previously seen (Sasaki et al., 2005a, 2005b; Kolvenbach et al., 2007; Roh et al., 2009; Telke et al., 2009), which may suggest that the mechanisms responsible for BPA degradation differ between microorganisms.

Disinfectants

Triclosan (2,4,4′-trichloro-2′-hydroxyphenyl ether), an antibacterial and antifungal agent, has been degraded with a range of bacteria obtaining an average biodegradation efficiency of 82% in an average treatment time of 48 h (Roh et al., 2009; Kim et al., 2011; Margot et al., 2013). The microorganisms studied include N. europaea, ammonia-oxidizing bacteria, and heterotrophic microorganisms from a nitrifying activated sludge and Sphingomonas sp. PH-07 (Roh et al., 2009; Kim et al., 2011). As in the case of BPA, the oxidation of aromatic functional groups gives rise to triclosan degradation. In addition, it has been reported that triclosan biodegradation starts by dihydroxylation of both aromatic rings of the compound (Kim et al., 2011; Margot et al., 2013). Apart from their enzymatic capabilities, some bacteria may also be effective at triclosan removal through the excretion of biosurfactants, enhancing the compound's bioavailability, as in the case of Sphingomonas sp. (Bai et al., 2017).

Kagle et al. (2015) studied the genetics of triclosan aerobic degradation by Sphingomonas sp. RD1 (RD1). The study results suggested that the first step of triclosan catabolism in RD1 is to add a hydroxyl group to triclosan to form hydroxy triclosan, catalyzed by an inducible class IA aromatic dioxygenase. Once formed, hydroxy triclosan undergoes spontaneous fission to yield 2,4-dichlorophenol and 4-chlorocatechol. Although the mechanism behind this fission remains unknown, the relatedness of RD1's tcsA and tcsB to genes encoding angular dioxygenases and the identified degradation products are both consistent with angular dioxygenation. In RD1, the triclosan gene clusters are adjacent to tRNA genes on the chromosome, which are common insertion sites for phages and other mobile genetic elements. Thus, this study suggested that the triclosan gene clusters have been acquired through horizontal gene transfer since they are absent from the genome sequences of other closely related species, neither of which have homologs of tcsA or tcsB, nor neither of which can degrade triclosan. It is important to underscore that in this work, RD1 did not grow on triclosan as a sole source of carbon, and it had to be grown in a coculture with Pseudomonas sp. SPD in minimal salt medium with 500 μg/mL triclosan.

Fragrances

The biodegradation of 3-methylindole, a heteroaromatic compound used as fragrance and fixative in perfumes, has been assessed. As in the previous chemicals, the elimination of aromaticity in the molecule is a key step to its biodegradation. This EOM has been biodegraded through cometabolism with glycerol using different pathways (carbocyclic aromatic ring fission of 3-methylindole to single-ring pyrrole carboxylic acids). Cupriavidus sp. strain KK10 biotransforms 3-methylindole under aerobic metabolism, and after 48 h, the EOM was no longer detected, and there did not appear to be significant accumulations of low-molar mass biotransformation products (Fukuoka et al., 2015).

Pharmaceuticals

The degradation of the antibiotic cefdinir is initiated by the removal of a hydroxyl group and lateral methylene group, followed by the major step of opening of the β-lactam ring. It has been observed that the yeast strain Ustilago sp. SMN03 can utilize cefdinir as a sole carbon source (Selvi et al., 2014).

Naproxen, a nonsteroidal anti-inflammatory drug (NSAID), has been transformed by Stenotrophomonas maltophilia KB2 under cometabolic conditions with glucose or phenol with moderate biodegradation efficiency (78% and 40%, respectively) within 480 h of treatment (Wojcieszynska et al., 2014). The presence of naproxen phenol monooxygenase, naphthalene dioxygenase, hydroxyquinol 1,2-dioxygenase, and gentisate 1,2-dioxygenase could suggest that degradation of naproxen occurs by its hydroxylation. Regardless of the identification of these biodegradation enzymes, they could be better directed since naproxen has a low biodegradability compared to other EOMs in this section.

Ibuprofen, another NSAID, has been removed completely in 48 h (initial concentration: 0.4 mg/L) by heterotrophic microorganisms in a conventional activated sludge (CAS) (Roh et al., 2009). In this study, the degradation was not directly linked to a specific microbial strain. However, it was concluded that nonammonia-oxidizing microorganisms were likely to be responsible for ibuprofen's elimination. Recently, Njeru et al. (2017) studied the removal of ibuprofen (cometabolism with acetate) in a microbial consortium from the hyporheic zone of rivers downstream of WWTPs. Proteobacteria, Acidobacteria, Actinobacteria, and Firmicutes populations were enriched during the ibuprofen treatment, with α-, β-, and δ-proteobacteria becoming the most active strains as indicated by RNA-based analyses. In addition, quantitative PCR (qPCR) analysis revealed no significant differences in copy numbers of 16S rRNA gene or transcripts between consortia in the presence and absence of ibuprofen.

The work by Almeida et al. (2013) investigated ibuprofen degradation by Patulibacter sp. strain I11 (I11), a bacterial strain isolated from activated sludge, using quantitative proteomics and whole genome sequencing. I11 reduced 62–92% of ibuprofen with a starting concentration of 50 μg/L in mineral medium after 90 h. Proteins that may be involved in the ibuprofen catalytic processes, represented as upregulated proteins during the treatment, include cytochrome b and c, several dehydrogenases, and oxidoreductases. However, many of these proteins were classified as putative uncharacterized proteins. There were also differences observed between the proteomic data and the qPCR (i.e., genomic) data; thus, the details of I11's ibuprofen biodegradation pathway(s) and how they are regulated in situ remain largely unknown.

Fungal degradation of EOMs

The use of ligninolytic fungi as decontaminating agents has been intensively studied at laboratory scale and could be an important and effective alternative for EOM bioremediation that has been scarcely applied in WWTPs (Margot et al., 2013; Yang et al., 2013; Badia-Fabregat et al., 2014). For example, the white rot fungus Trametes versicolor has demonstrated the ability to eliminate a wide range of EOMs from sewage sludge. In the work by Rodriguez-Rodriguez et al. (2011) T. versicolor completely removed the following pharmaceuticals: phenazone, bezafibrate, fenofibrate, cimetidine, clarithromycin, and atenolol. Tran et al. (2010) also studied the degradation of 10 pharmaceutically active compounds by a 7-day-old liquid fungal culture from T. versicolor. After 48 h of incubation, diclofenac, naproxen, indomethacin, ibuprofen, and fenoprofen were completely removed; ketoprofen was eliminated by >95%; and clofibric acid, gemfibrozil, propyphenazone, and carbamazepine were removed by 68–81%.

In these works, the degrading capabilities of white rot fungi have been linked to their unspecific oxidative enzymes (Cabana et al., 2011; Rodriguez-Rodriguez et al., 2011; Margot et al., 2013; Huntscha et al., 2014), such as laccase. Due to this, Margot et al. (2013) examined the use of laccase from T. versicolor for the removal of diclofenac, mefenamic, triclosan, and BPA, achieving removal rates of 96–100% in 3–4 h. Furthermore, the removal of these four compounds in mixtures was studied under conditions common in municipal wastewater (pH 7–8, 10–25°C). Although the pH and temperature conditions were outside the optimal range for the laccase, removal above 85% was possible for the four compounds tested with sufficient enzyme concentration and reaction time.

Limitations and future research needs

The reviewed studies in this section provide insight into the degradation of a specific EOM by a specific strain or defined consortium and showcase molecular biology tools that may be used in understanding the catabolism of EOMs. However, there are some limitations when applying this information to complex biodegradation systems, such as WWTPs (highly heterogeneous mixtures of EOMs and diverse microbial consortia). These shortcomings include: impractical treatment conditions for full-scale applications; biodegradation pathways only for the parent compounds (pathways for metabolites and EOM mixtures are not included in most studies); biodegradation pathways of one microorganism not easily extrapolated to biodegradation capabilities of microbial consortia; missing enzymatic kinetics (production and disappearance of metabolites, CO₂, and biomass during EOM biodegradation); and limited work on nonbacterial biodegradation capabilities.

In general, the treatment conditions in this section are difficult to apply in large-scale WWTs. For example, in this set of studies the treatment times range from 1.1 to 2,880 h (Table 1), while in the set of studies of engineering systems reviewed (see section “Biodegradation in Engineered Systems”) the range is from 0.95 to 288 h. In addition, pure cultures are unlikely to be maintained in real WWTs, and transient conditions in WWTPs will shift the defined microbial consortia throughout time. Future research for these types of studies could focus on designing treatment conditions that when scaled up could maintain its effectiveness while keeping operating costs, energy consumptions, and infrastructure footprints at a minimum.

Furthermore, these studies determined the removal efficiencies and degradation mechanisms with parent chemicals as the initial substrate. However, EOM metabolites tend to be already present along with the parent chemical in raw sewage. For example, in the case of diclofenac, ∼65% of the dosage is excreted through urine in which six metabolites have been identified, while the actual number of metabolites in the feces is still not clear (Zhang et al., 2008). Furthermore, at least two of the metabolites in urine are discharged at higher rates than the unchanged diclofenac. Ideally, biodegradation of EOMs in the presence of their main metabolites should be investigated. In a similar vein, the synergistic effect of different EOMs should also be studied in determining the biodegradation capabilities of microorganisms.

In the studies where biodegradation pathways were examined using genomic, proteomic, and metabolomic analysis, there are some deficiencies in the integration of these different types of information. For example, in Almeida et al. (2013) there seemed to be discrepancies between the genomic and proteomic results. In addition, Njeru et al. (2017) did not observe differences in gene expressions between microorganisms that were in the presence and absence of ibuprofen. Considering that these types of protocol shortcomings have been seen elsewhere (Collado et al., 2013), future studies could focus on improving genomic, proteomic, and metabolomic protocols for EOM biodegradation in sewage/WWTP samples. Even if sufficient information was cross-referenced among the omics datasets (genes, proteins, and metabolites), the resulting knowledge may not be directly applicable to real-life scenarios. For instance, the deciphered pathways appeared to be strain specific. In addition, in some studies, the location of the genes encoding catabolic pathways for organic xenobiotic degradation seems to suggest that they may be transferred horizontally or that they may be unstable (Kolvenbach and Corvini, 2012; Kagle et al., 2015; Horemans et al., 2017). These scenarios have important implications for full-scale WWTPs, where there are complex microbial consortia. In these diverse biological systems, biodegradation capabilities may be more robust than the single-cell ones, as not only could different microorganisms have the same catabolic pathways but also within the consortia there might be different pathways that can degrade the same EOM. In these heterogeneous biological systems, there may also be cooperative or competitive relationships, even among close relatives (Hu et al., 2017), which could foster or hinder the degradation of EOMs.

While the basic science behind biodegradation pathways for a specific strain is key in establishing the optimum treatment conditions (i.e., pH range, carbon supplementation, retention time, and so on), there can be great diversity among pathways for one and the same EOM between different microorganisms. Hence, this knowledge does not translate easily into understanding the biodegradation pathways that can be carried out by an entire microbial consortium. Future research could focus on determining the active metabolic pathways of consortia involved in the degradation of EOMs, through the application of systems biology's top-down and bottom-up approaches (Raes and Bork, 2008).

Moreover, while the biodegradation enzymes for EOMs were identified, they were not described in terms of their kinetics regarding the complete removal of a given EOM or the competitive inhibition they face in the presence of other substrates. Hence, approaches were not proposed to reduce the long treatment times or how to outcompete or develop synergistic approaches with non-EOM substrates. Once the competing or complementary substrates and active pathways have been identified, it may be useful if kinetics were established in future works and applied for optimum EOM biodegradation during WWTs.

Most literature focus on bacteria even though there seem to be limits on removing some recalcitrant organic pollutants using only bacterial strains. Subsequent studies could also focus on the application of nonbacterial microorganisms for EOM removal, such as white rot fungi. While this type of biotechnology is still in its infancy for real WWT applications, fungi have shown great potential in degrading a wide range of persistent organic contaminants (on their own and in mixtures) and can carry out biodegradation in standard bioreactors in continuous mode (these operations being simple to scale up). The biodegradation of organic contaminants by filamentous fungi in bioreactors under nonsterile conditions has recently been reviewed (Svobodová and Novotný, 2018).

All the compounds that were showcased in this section, except for BAM, 3-methylindole, and cefdinir, are also assessed in the following section. However, in Section “Biodegradation in Engineered Systems,” these contaminants are degraded in complex matrices, such as raw wastewater or in EOM mixtures, through microbial consortia in nonconventional secondary treatment technologies. The differences between these two types of studies are discussed in Section “Trends, limitations, and future research needs”.

Biodegradation in Engineered Systems

WWTPs are complex biologically engineered systems with highly heterogeneous mixtures of pollutants. EOMs are removed and emitted at different treatment stages during most commonly used WWTs; however, they are generally not completely mineralized. CAS and MBRs are commonly applied WWTs and are briefly discussed as benchmarks for the nonconventional biological WWTs (Section “CAS and MBR systems”). However, they appear to be unable to completely biodegrade some EOMs and seem to be approaching their technological limitations regarding persistent EOMs (Carballa et al., 2017). Thus, developing nonconventional biological WWTs is of increasing interest, and their biodegradation abilities are reviewed in this study. Findings from the past 10 years on nonconventional biotechnologies aimed at EOM removal in WWTPs, including modified CAS treatments, modified MBR systems, hybrid systems, and other alternative treatments, are described (Section “Nonconventional biological treatments”). Finally, analysis of the findings is discussed to point out trends, limitations, and possible future research directions (Section “Trends, limitations, and future research needs”).

CAS and MBR systems

There are numerous review articles that discuss the effectiveness of CAS and MBR treatments in eliminating EOMs. The ability of different MBR and CAS treatments to remove EOMs at laboratory, pilot plant and full scale, is presented in Supplementary Data (Supplementary Table S2).

In general, CAS treatments have low removals of recalcitrant EOMs in pilot- and full-scale treatments, and biosorption has been reported as the main removal mechanism for some pharmaceuticals (e.g., carbamazepine and sulfamethizole), hormones (e.g., 17 α-ethinyl estradiol and 17β-estradiol), and some endocrine disrupters (e.g., nonylphenol and related compounds and BPA) (Clara et al., 2005; Radjenovic et al., 2009; Galan et al., 2012; Stasinakis et al., 2013).

MBR technology also has adsorption as one of its main mechanisms for pollutant removal. Compared with CAS, the MBR's high biomass concentrations, solids' retention time, and sludge ages may lead to microbial communities better suited to low-bioavailability EOMs (Sipma et al., 2010; Tran and Gin, 2017). In addition, reduction of the lag phases, better adaptation to variable influent concentrations, higher volume loadings compared to CAS, and improved biodegradation of some compounds have been observed in MBRs (De Wever et al., 2007; Chen et al., 2008; Prado et al., 2009; Tadkaew et al., 2011; Tran et al., 2016). Nonetheless, several authors report that membrane treatments may not be superior treatments for compounds that are already extensively degraded in CAS treatments (such as hydrophilic compounds) nor for recalcitrant compounds that are not susceptible to biodegradation (Reemtsma et al., 2002; Clara et al., 2005; De Wever et al., 2007; Chen et al., 2008; Weiss and Reemtsma, 2008; Radjenovic et al., 2009; Cartagena et al., 2013; Tran and Gin, 2017). MBR's niche advantage would appear to be the biodegradation of hydrophobic compounds by promoting their sorption and increasing their retention time.

To improve bioremediation capabilities of both CAS and MBR systems, several modified CAS and MBR treatments have been proposed (Table 2). These hybrid treatments combine CAS or MBR systems with other technologies such as biofilm carriers, suspended/attached growth systems, or cross-linked enzyme aggregates, etc. Grandclément et al. (2017) have looked at general aspects of EOM removal in CAS, MBR, and hybrid systems; however, they mainly studied the operating conditions' effects on the overall EOM removal efficiency.

Table 2.

Nonconventional Engineering Systems for Biological Removal of Emerging Organic Micropollutant at Laboratory- and Pilot Plant Scale

Treatment technology	Contaminants removed ^a	Operation conditions	Biodegradation efficiency	Observations	References
Laboratory-scale
Oxic/anoxic hybrid biofilm-CAS system 10 L	19 EOMs^a	pH 8HRT 12 hT: 16 ± 1°CMLSS 2.4–3.2 g/L[C]_i = 1 μg/L	65% Mefenamic acid20% Diclofenac, atenolol	• Carbamazepine was recalcitrant in all treatments.• Degradation rate of EOM was substance specific and dependent on the redox conditions and the composition of the biomass.• Significantly higher removal rates with the carrier biofilm compared to the sludge in the reactor, as well as for other CAS systems.• Some EOMs were only removed under oxic conditions, while others were removed under both oxic and anoxic conditions.	Falås et al. (2013)
CAS system under different oxic/anaerobic conditions 0.5 and 12 L	29 EOMs^a	pH 7.7HRT 12–288 hT: 20 ± 2°CMLSS 2–5.5 g/L[C]_i = 1–5 μg/L2–10 μg/L	Oxic postreatment:23–55% 2-OH-carbamazepine, terbutryn, carbendazim, metoprolol63–96%, DHH-carbamazepine, diclofenac, benzotriazole, iopromide, diuron, codeine, benzophenone, clarithromycin, climbazole, bezafibrate, acesulfame, trimethoprim>98 Acyclovir, atenolol, acetaminophenAnoxic post-treatment:26–64% Terbutryn, diclofenac, metoprolol, benzotriazole, DHH-carbamazepine, tramadol, iopromide71–98% Climbazole, venlafaxine, acesulfame, bezafibrate, benzophenone, codeine, diatrizoate, trimethoprim, clarithromycin, atenolol, acyclovir, acetaminophen	• Certain improvements in biological removal can be achieved by combining aerobic and anaerobic conditions.• Some EOMs persisted in all biological systems tested (i.e., carbamazepine and 3-OH-carbamazepine).	Falås et al. (2016)
Oxic/anoxic CAS 1 L	Benzotriazoles and hydroxybenzothiazole^a	pH 7.2–8.2HRT —T: 22 ± 0.5°CMLSS 3 ± 0.2 g/L[C]_i = 30 μg/L	66–87% Benzotriazole83–88% 5-Chlorobenzotriazole88–94% Xylytriazole20–38% 5-Methy-1H-lbenzotriazole89–94% 2-Hydroxybenzothiazole	• Aerobic biodegradation was the main mechanism.• Addition of cosubstrate in some cases accelerated EOM biodegradation.• 4-Methyl-1H benzotriazole was recalcitrant.	Mazioti et al. (2015a)
Anoxic-MBR aerobic-MBR 14 L	Carbamazepine and sulfamethoxazole	pH 7.8 ± 0.1HRT 24 hT: 22 ± 2°CMLSS 10.5 g/L[C]i = 750 μg/L	Aerobic conditions:12% Carbamazepine and 66% sulfamethoxazoleAnoxic conditions:68% Carbamazepine and 66% sulfamethoxazole	• Near-anoxic conditions favored biodegradation of carbamazepine.• Sulfamethoxazole biodegradation was obtained in aerobic or anoxic conditions.	Hai et al. (2011a)
Oxic MBR thermophilic 14 L	22 EOMs^a	pH 7.8 ± 0.1HRT 24 hT: 10–45°CMLSS 6–12 g/L^b[C]_i = 1.2–4.7 μg/L	At 20°C:23–39% Fenoprop, carbamazepine, diclofenac metronidazole, acetaminophen, primidone51–93% Ketoprofen, naproxen, pentachlorophenol, estriol, 17-α-ethinylestradiol, nonylphenol, ibuprofen, and salicylic acid96–98% Triclosan, gemfibrozil, 4-tert-butylphenol, estrone, bisphenol A, 17-β-estradiol-17-acetate, 4-tert-octylphenol, and 17-β-estradiol	• The EOM with high removal efficiencies (>96%) remained stable in a range of 10–35°C.• Operation at 45°C clearly exerted detrimental effects on the removal efficiency.• Only acetaminophen and fenoprop biodegradation were enhanced at 45°C from 20% to 60% and from 40% to 70% compared to operation at 20°C.	Hai et al. (2011b)
Anaerobic-MBR 80 L	15 EOMs^a	pH 8–8.4HRT 288 hT: —MLSS 10.1 g/L^b[C]_i = 0.0001–0.595 μg/L	77–99% Organochlorine pesticides68–99% Polycyclic aromatic hydrocarbons77% Nonylphenol	• Combined anaerobic sludge-MBR.• The removal of 4-nonylphenol was mainly established in the MBR process.• Pesticides and polycyclic aromatic hydrocarbons were mainly removed in the anaerobic sludge process.• Some polycyclic aromatic hydrocarbons were not biodegraded.	Xu et al. (2008)
Anaerobic-MBR 30 L	Galaxolide, tonalide, phantolide, traseolide, cashmeran	pH 7 ± 0.1HRT 96 hT: 35 ± 0.1°CMLSS 10 g/L[C]_i = 2 μg/L	83% Galaxolide95% Tonalide97% Phantolide94% Traseolide96% Cashmeran	• Biotransformation and sorption onto the biosolids.• Biotransformation was the dominant removal mechanism.	Wang et al. (2014)
Integrated anoxic–aerobic MBR 25 L	30 EOMs^a	pH 7.25 ± 0.75HRT 24 hT: —MLSS 3.78–5.12 g/L[C]_i = 5 μg/L	15–49% Naproxen, gemfibrozil, primidone, pentachlorophenol, and ketoprofen78–90% Octocrylene, oxybenzone, 17-β-estradiol-17-acetate, 17-β-estradiol, and salicylic acid.	• Simultaneous nitrification/denitrification processes.• 21 of the 30 EOMs were removed.• Biodegradation was the main mechanism of removal.• No biodegradation of diclofenac, carbamazepine, and atrazine was observed with or without recirculation.	Phan et al. (2014)
MBR and activated carbon 14 L	SulfamethoxazoleCarbamazepine	pH 7.8 ± 0.1HRT 24 hT: 22 ± 2°CMLSS 11 g/L[C]_i = 100 μg/L; 750 μg/L	64–82% SulfamethoxazoleND–92% Carbamazepine	• Adsorption process increased the degradation of the EOMs.• Degradation depended on EOM hydrophobicity and loading and dosage of activated carbon.	Li et al. (2011)
MBR-granular activated carbon 5.5–0.017L	22 EOMs^a	pH 7.2–7.5HRT 24 hT: 22 ± 0.1°CMLSS 5 g/L[C]_i = 5 μg/L	MBR:15–67% Diclofenac, carbamazepine, metronidazole, naproxen, acetaminophen, pentachlorophenol, and ketoprofen in MBR–CAS >95% for all EOMs	• Fenoprop, ketoprofen, naproxen, diclofenac, and carbamazepine were Compounds that were poorly removed by MBR treatment.• Granular activated carbon as a post-treatment could significantly improve the removal of those EOMs.	Nguyen et al. (2013)
MBR-functionalized membranes 1 L	Acetaminophen, mefenamic acid, carbamazepine	pH 7.5HRT 0.95 hT: 20°CMLSS —[C]_i = 100 μg/L	99% Acetaminophen99% Mefenamic acid94% Carbamazepine	• Hybrid bioreactor of cross-linked enzyme aggregates of laccase and membrane.• Synergistic effects of the biocatalyst and the membrane.	Ba et al. (2014)
Membrane distillation-thermophilic MBR 5 L	25 EOMs^a	pH 7.6HRT 230 hT: 40 ± 0.1°CMLSS 5.3 g/L[C]_i = 5 μg/L	10–28% Carbamazepine, atrazine, diclofenac64–88% Fenoprop, gemfibrozil, clofibric acid, primidone, benzophenone, pentachlorophenol, triclosan, ametryn, and propoxur>94% Salicylic acid, octocrylene, ketoprofen, 4-tert-Butylphenol, naproxen, estriol, amitriptyline, oxybenzone, estrone, 17-α Ethinylestradiol, 17-β-Estradiol, 17-β-estradiol-17-acetate	• Most EOMs were removed by the thermophilic bioreactor.• EOMs containing electron withdrawing functional groups were recalcitrant.• In combined system, all compounds were highly removed.	Wijekoon et al. (2014)
MBR with biogenic manganese oxides and bio-palladium 0.3 L	29 EOMs^a	pH 6.5HRT 5–24 hT: —MLSS —^b[C]_i = 0.01–6 μg/L	52–75% Sulfamethoxazole, iomeprol, iopromide, iohexol, and clarithromycin78–88% Triclosan, diclofenac, and mecoprop>89% Chlorophene, codeine, diuron, N-acetyl-sulfamethoxazole, ibuprofen, and naproxen	• Main mechanisms were chemical oxidation by biogenic manganese oxides, biological degradation, and adsorption.• Successful removal of the iodinated X-ray contrast media iomeprol, iopromide, iohexol, and diatrizoate was demonstrated in a bio-palladium system.• No biodegradation of diazepam, nordiazepam, axazepan, hydrocodone, morphine, tramadol, methadone, carbamazepine and its metabolites, primidone, trimethoprim, erythromycin, and diatrizoate.	Forrez et al. (2011)
Microbial fuel cells. Single-chamber air cathode and double-chamber air cathode 0.110 and 0.240 L	26 EOMs^a	pH 7.55 ± 0.28HRT —T: roomMLSS —[C]_i = 0.5 μg/L	Single chamber:65.9–97.6% (EOMs positively charged)5.0–27.4% (EOMs negatively charged)Double chamber:34.1–98.0% (EOMs positively charged in cathode chamber)44.0–95.3% (EOMs positively charged in anode chamber)6.1–45.6% (EOMs negatively charged in cathode chamber)4.6–40.3% (EOMs negatively charged in anode chamber)	• The removal mechanisms include sorption (electrical and physical–chemical) and biodegradation.• The factors such as the properties of EOMs (biodegradability, charge state, and hydrophobicity), biological and electrochemical activities of microbes, pH and dissolved oxygen of the solution, and the interactions with the electrodes and other surfaces as sorbents affected the removal.	Wang et al. (2015)
Packed-bed reactor (immobilized enzymes) 0.050 L	1,2,3-trichloropropane (TCP)	pH 8.2HRT —T: 37 ± 0.1°CMLSS —[C]_i = 200,250 μg/L709,330 μg/L	78% (to glycerol)97% (to intermediates)	• Use of haloalkane dehalogenase, haloalcohol dehalogenase, and epoxide hydrolase from two engineered microorganisms.• Conversion of EOM to glycerol.	Dvorak et al. (2014)
Anaerobic granular sludge sequential batch reactor 2.5 L	Fluoxetine	pH 7 ± 0.8HRT —T: —MLSS 10.2–18.2 g/L[C]_i = 1,823 μg/L	8–24%	• Adsorption/desorption of the compound to the aerobic granules.• Main mechanism was sorption to the aerobic granules.	Moreira et al. (2015)
MBR/nanofiltration MBR/reverse osmosis 9 L	40 EOMs^a	pH 8HRT —T: 20 ± 0.1°CMLSS 8–10 g/L[C]_i = 2 μg/L	2–39% Dilantin, atrazine, DEET, trimethoprim, meprobamate, primidone, carbamazepine, diclofenac, linuron, triamterene, and naproxen37–70% Caffeine, simvastatin-hydroxy acid, omeprazole, and ketoprofen87–97% Hydroxyzine, sulfamethoxazole, triclosan, clozapine, bisphenol A, 17-α-ethinylestradiol, verapamil, ibuprofen, 4-octylphenol, atenolol, enalapril, estrone, acetaminophen, nonylphenol, gemfibrozil, 17-β-estradiol, amitriptyline, androstenedione, estriol, testosterone, etiocholanolone, androsterone, triclocarban, risperidone, and simvastatin	• The adsorption of the hydrophobic EOMs onto the MBR mixed.• Mixed liquor suspended solids (MLSS) lead to an extended retention time in the biological reactor, thereby enhancing their biodegradation	Alturki et al. (2010)
Osmotic MBR 5 L	50 EOMs^a	pH 7.4HRT 80 hT: 22.5 ± 0.1°CMLSS 3.4 g/L[C]_i = 0.75 μg/L	21–75% Atrazine, diuron, DEET, carbamazepine, diclofenac, trimethoprim, meprobamate, triamterene, dilantin, primidone, caffeine, linuron, gemfibrozil, salicylic acid, and nonylphenol78–98% Sulfamethoxazole, pentachlorophenol, naproxen, ketoprofen, risperidone, omeprazole, phenylphenol, 4-octylphenol, triclosan, methotrexate, propylparaben, estriol, triclocarban, chlorpyrifos99% Acetaminophen, ibuprofen, atenolol, estrone, 17-β-estradiol, 17-α-estradiol, amitriptyline, androstenedione, testosterone, etiocholanolone, androsterone, 17-α-ethinylestradiol, diazinon, fluoxetine (Prozac), clozapine, hydroxyzine, enalapril, simvastatin, verapamil, simvastatin-hydroxy acid, and simazine	• The complete removal, including physical effect of the membrane.• The partial degradation was attributed to biodegradability.• Salinity build-up in the reactor.• 100% biodegradation of compounds with MW >266 g/mol.• 25–100% of biodegradation compounds with MW >266 g/L.	Alturki et al. (2012)
Sponge-based moving bed bioreactor 15 L	22 EOMs^a	pH 7HRT 24 hT: —MLSS 0.13 g/L[C]_i = 5 μg/L	9–50% Fenoprop, carbamazepine, diclofenac, metronidazole, and ketoprofen66–87% Primidone, 4-tert-Butylphenol, gemfibrozil, 17-α-Ethinylestradiol, 4-tert-octylphenol, acetaminophen, pentachlorophenol, bisphenol A, and naproxen93–97% Triclosan, estriol, salicylic acid, ibuprofen, nonylphenol, estrone, 17-β-Estradiol, and17-β-estradiol-17-acetate	• Biodegradation served as a major removal pathway for most compounds.• Sorption to sludge phase was notable removal mechanism of some persistent EOMs.• Removal was comparable with those of CAS and MBR systems.	Luo et al. (2014)
Moving bed biofilm reactor 4.5 L	5 Benzotriazoles and hydroxybenzothiazole^a	pH 6.8–7.4HRT 10.8–26.4 hT: 22 ± 0.5°CMLSS0.124–0.195 g/L[C]_i = 20 μg/L	43–76% Benzotriazole8–69% 4-Methyl-1H-benzotriazole0–53% 5-Methy-1H-lbenzotriazole42–49% 5-Chlorobenzotriazole40–43% Xylytriazole80–97% 2-Hydroxybenzothiazol	• Attached biomass had higher biodegradation potential for target compounds comparing to suspended biomass.• EOM biodegradation by both types of biomass is cometabolic.	Mazioti et al. (2015b)
Pilot plant
Two-stage MBR1,250 L anoxic reactor; 1,000 L MBR	10 EOMs^a	pH 7.5 ± 0.2HRT 12 hT: 22 ± 1°CMLSS 1 g/L^b[C]_i = 8–10,750 μg/L	74–96% Anthracene, naphthalene, benzyl butyl phthalate, dimethyl phthalate, diethyl phthalate, dioctyl phthalate, 4-methyl-2,6-di-tert-butylphenol, dibutyl phthalate, bisphenol A, and bis(2-ethylhexyl)phthalate	• Biodegradation was the main mechanism for BPA and 4-methyl-2,6-di-tert-butylphenol.• Adsorption on biomass was the main mechanisms for Bis(2-ethylhexyl)phthalate.	Boonyaroj et al. (2012)
Two-stage MBR 1,250 L anoxic reactor; 1,000 L MBR	Bisphenol A (BPA); 2,6-di-tert-butylphenol; 2,6-di-tert-butyl-4methylphenol; di-ethyl phthalate; di-butyl phthalate; and bis (2-ethylhexyl) phthalate	pH 7.6 ± 1.3HRT 24 hT: —MLSS 7–9 g/L^b[C]_i = 146–384 μg/L	45% Bis (2-ethylhexyl)phthalate64% 2,6-Di-tert-4methyl-butylphenol69% 2,6-Di-tert-butylphenol71% Dibutyl phthalate79% Bisphenol A81% Diethyl phthalate	• Treatment was applied to municipal solid waste landfill leachate.• EOM removals were predominant under aerobic conditions. Anoxic (first stage) 13–37%. MBR (second stage) 95–99%.• The main mechanism responsible for those removals was biodegradation.	Boonnorat et al. (2014)
MBR/ nanofiltration MBR/reverse osmosis 11,000 L	Acetaminophen, Ibuprofen, caffeine, nicotine, carbamazepine, diclofenac, triclosan, 4-octylphenol, 4-tert-octylphenol, bisphenol A	pH 7.01–7.63HRT —T: 22 ± 2°CMLSS 8 ± 0.5 g/L^b[C]_i = 0.12–59.5 μg/L	>98% Acetaminophen, ibuprofen, caffeine, nicotine, and 4-tert-Octylphenol4–93% Carbamazepine70–95% Diclofenac82–84% Triclosan78–84% 4-Octylphenol0–96% Bisphenol A	• The type of membrane (flat sheet or hollow fiber) is not influenced efficiency of degradation.• Carbamazepine and BPA were recalcitrant under some treatments.	Cartagena et al. (2013)
Anaerobic reactor and a flow constructed wetland 295 L	Ibuprofen, naproxen, diclofenac, tonalide, and bisphenol A	pH 7–7.6HRT 3.5 hT: 22 ± 0.6°CMLSS —^b[C]_i = 1.5–132 μg/L	98–99% for all EOM	• Anaerobic reactor followed by two wetlands working in parallel and connected to another wetland operating in series.• Aerobic conditions enhance the ibuprofen biodegradation.• Other EOMs were preferentially degraded under anaerobic conditions.• Biodegradation BPA was main removal pathway under aerobic conditions.	Avila et al. (2010)
System: CAS, two hybrid (biofilm-CAS), and moving bed biofilm reactors 3 L–3 L–3 L–3 L	16 EOMs^a	pH 7.3–7.8HRT 3 hT: 15–18°CMLSS —^b[C]_i = 14 μg/L; 200 μg/L	In moving bed biofilm reactor 70% citalopram, 58% propranolol, and 40% tramadol>20% Acetyl-sulfadiazine, atenolol, carbamazepine, clindamycin, erythromycin, iohexol, iomeprol, metoprolol, sulfadiazine, sulfamethizole, sulfamethoxazole, trimethoprim, and venlafaxine	• The train of treatment consisted of one CAS reactor, two hybrid biofilm-CAS modules, and a moving bed biofilm reactor.• Biofilm reactor had the most effective performance in removing pharmaceuticals.	Casas et al. (2015)

Complete list of compounds and their physiochemical properties are presented in Supplementary Table S1, while complementary data on the treatments are presented in Supplementary Tables S3 and S4, in Supplementary Data.

Initial concentration of each EOM is detailed in Supplementary Table S4 in Supplementary Data.

—, not provided; HRT, hydraulic retention time; MLSS, mixed liquor suspended solids; DEET, N,N-Diethyl-3-methylbenzamide; DHH, 10,11-Dihydroxy-10,11-dihydrocarbamazepine; MW, molecular weight; ND, non-detected.

Nonconventional biological treatments

Novel treatments to enhance biodegradation levels include modifications of biological operational conditions (e.g., oxic or anoxic environments), CAS or MBR hybrid systems, and non CAS- or MBR-based treatments. In this section, we have reviewed 25 studies of these nonconventional treatments from the past 10 years, which include 398 different treatment conditions for removal of 151 EOMs in WWTPs. Main findings are summarized in Table 2 in terms of laboratory and pilot-scale studies. Supplementary Tables S3 and S4, in Supplementary Data, present the specific information on the 1,056 data points regarding the biodegradation of each of the 398 treatment conditions.

Modified and hybrid CAS-based systems

Different compounds are preferentially biodegraded under aerobic, oxic, or anaerobic conditions. The evaluation of different configurations of combined aerobic and anaerobic systems for the elimination of 29 EOMs has been reported by Falås et al. (2016). These include (i) aerobic CAS stir reactors; (ii) CAS followed by an oxic post-treatment (one anoxic and two oxic compartments); sequencing anaerobic reactors (six); and (iii) CAS reactors with anaerobic post-treatments. The results indicate that biological removal can be enhanced by combining aerobic and anaerobic conditions (Table 2). However, some EOMs persisted in all biological systems tested (i.e., carbamazepine and 3-OH-carbamazepine). While certain biotic transformations can be the main degradation mechanisms for some EOMs, biodegradation may not be completely understood nor likely be related to a single process parameter (Falås et al., 2016).

A laboratory-scale biofilm-CAS system was tested under oxic and anoxic conditions to obtain considerably higher EOM removal (Table 2 and Supplementary Table S4) rates compared to the CAS (Falås et al., 2013). In these systems, the biofilm was responsible for the overall EOM removal, which may be a physical removal mechanism rather than biological. A pilot-scale train of treatment, which consisted of one CAS, two hybrid biofilms, and one moving bed membrane reactor, has been tested for the removal of pharmaceuticals in a hospital WWTP, including X-ray contrast media, β-blockers, analgesics, and antibiotics, with satisfactory removal results (20–70%; Table 2 and Supplementary Table S4) (Casas et al., 2015). The individual performance of each module for each compound is shown in Supplementary Table S4; the moving bed membrane reactor had the most effective performance in removing pharmaceuticals. Oxic/anoxic conditions, in moving bed biofilm reactor, were also used to treat benzotriazole, 5-chlorobenzotriazole, and xylytriazole (degradation 66–94%); 5-methyl-1H-benzotriazole (20–38%); and 2-hydroxybenzothiazole (89–94%), while 4-methyl-1H-benzotriazole was recalcitrant (Mazioti et al., 2015a).

Other CAS modifications include the addition of adsorption and coprecipitation agents (e.g., FeCl₃ and granular activated carbon), coupled with membrane or other treatments. For example, this approach was used to treat carbamazepine to 40%, diclofenac to 85%, and even obtain a complete elimination of other compounds (Serrano et al., 2010; Li et al., 2011; Sahar et al., 2011; Nguyen et al., 2013). However, in these systems the main elimination mechanisms reported were adsorption, absorption, and biosorption, not the true degradation of EOMs.

Modified and hybrid MBR-based systems

Applying oxic and anaerobic conditions have also been proposed to improve EOM biodegradation in MBRs. Hai et al. (2011a) operated an MBR anaerobically observing that carbamazepine biodegradation was favored near anoxic conditions (68%) compared to aerobic conditions (12%). In addition, a combined anaerobic sludge-MBR system developed by Xu et al. (2008) achieved removal efficiencies in landfill leachate of 77–99% of organochlorine pesticides, 68–99% of polycyclic aromatic hydrocarbons (PAH), and 77% of technical grade nonylphenol. The removal of 4-nonylphenol mainly occurred in the aerobic MBR process, while the removal of pesticides and PAH was mainly achieved under anaerobic conditions. Evaluation of another anaerobic MBR system by Wang et al. (2014), demonstrated that the high removal of polycyclic musks (>83%) was reached because both biotransformation and sorption were present. In addition, an anoxic-aerobic MBR with simultaneous nitrification/denitrification processes for EOM removal found moderate (>50%) to high (>90%) removal rates for PPCPs, steroid hormones, UV filters, and other compounds (Phan et al., 2014).

The effect of temperature (10–45°C) on EOM biodegradation in a MBR under oxic conditions was studied by Hai et al. (2011b). EOM removal efficiencies remained stable at >96% between 10°C and 35°C for triclosan, gemfibrozil, 4-tert-butylphenol, estrone, BPA, 17-β-estradiol-17-acetate, 4-tert-octylphenol, and 17-β-estradiol. However, treatment at 45°C clearly exerted detrimental effects on removal efficiencies. Only acetaminophen and fenoprop biodegradation levels were enhanced at 45°C compared to treatments conducted at 20°C, within an increase from 20% to 60% and from 40% to 70%, respectively.

MBR membranes have also been functionalized for the removal of EOMs. A hybrid bioreactor of cross-linked enzyme aggregates of T. versicolor laccase and polysulfone hollow fiber membrane demonstrated synergistic degradation of aromatic pharmaceuticals. The presence of the enzymatic system allowed for increased degradation of the pollutants compared with the physical system alone (from 50–90% to 85–100%), highlighting the importance of enhancing biological processes (Ba et al., 2014).

A membrane distillation–thermophilic bioreactor system has been designed achieving elimination efficiencies >94% for 12 of the 25 EOMs evaluated (Wijekoon et al., 2014; Table 2). These researchers concluded that biodegradation, sludge adsorption, and rejection by membrane distillation contributed to the removal rates obtained, with EOM biotransformation as the dominant removal mechanism.

A two-stage MBR pilot setup was operated to evaluate the degradation of 2,6-di-tert-butylphenol, 2,6-ditert-butyl-4methylphenol, di-ethyl phthalate, di-butyl phthalate, bis (2-ethylhexyl) phthalate, carbamazepine, and BPA; in this setup, the biodegradation removal efficiencies ranged from 45% to >96% for all but carbamazepine and BPA. For carbamazepine and BPA, there was a wide range in their biodegradation during different treatments, from no or low removal to >93% (Boonyaroj et al., 2012; Boonnorat et al., 2014). In batch experiments, it was found that biodegradation was the main mechanism of their removal, and the microbial activities were enhanced under a sludge age of 500 days (Boonnorat et al., 2014).

The addition of redox agents as biostimulants to MBR systems has also been explored. The laboratory-scale MBR used biogenic manganese oxides and bio-palladium systems as oxidative and reductive agents, respectively, for EOM degradation (Forrez et al., 2011). This approach removed the following 14 of the 29 EOMs identified in the sewage treatment plant effluent: ibuprofen (>95%), naproxen (>95%), diuron (>94%), codeine (>93%), N-acetyl-sulfa-methoxazole (92%), chlorophene (>89%), diclofenac (86%), mecoprop (81%), triclosan (>78%), clarithromycin, (75%), iohexol (72%), iopromide (68%), iomeprol (63%), and sulfamethoxazole (52%). The associated removal mechanisms were chemical oxidation by biogenic metal manganese oxides and biological removal by Pseudomonas putida and associated bacteria in the enriched biofilm.

Other membrane-based modifications proposed for EOM removal include MBR-nanofiltration (NF) and reverse osmosis (RO) systems (Alturki et al., 2010; Cartagena et al., 2013) and developing a novel osmotic MBR (Alturki et al., 2012). The MBR-NF/RO treatment improved the retention of EOMs, but did not exhibit significant improvement in its biodegradation capability compared to the MBR-only system. The combined MBR treatment with forward osmosis membrane separation can effectively retain small particles and EOMs in the biological reactor, thus significantly prolonging their retention time and subsequently facilitating their biodegradation (Alturki et al., 2012). In these systems, it was concluded that increasing salinity leads to severe membrane fouling due to salinity stress and possibly reducing the bioavailability of EOMs. Those observations agree with other studies where MBRs were used for EOM elimination (Wijekoon et al., 2014; Luo et al., 2015).

Other alternative biological treatments

Adding treatment steps in hybrid treatments may achieve relatively higher EOM removal rates than CAS or MBR treatments on their own. However, the technical and cost-benefit competitiveness of hybrid treatments is still unclear since additional treatment steps generally lead to overall reductions in process efficiency (Grandclément et al., 2017). Thus, biological WWTs with different approaches to CAS and MBR are described below. These approaches include immobilized biological systems, such as packed-bed reactors and granular technology, as well as electrochemical–biological proposals.

Considering that high sludge retention times tend to favor biodegradation rates, enzymatic or biomass immobilized systems have been studied. Dvorak et al. (2014) immobilized a three-enzyme system in a packed-bed reactor at laboratory scale; the enzymes were selected to create a synthetic pathway for the biodegradation of 1,2,3-trichloropropane achieving a biodegradation efficiency range of 78–97%. However, not all fixed biomass systems have obtained high biodegradation rates. The aerobic granular sludge sequential batch proposed by Moreira et al. (2015) eliminated fluoxetine only by 8–24%. The low removal rates were attributed to the observed adsorption/desorption of EOMs to the aerobic granules.

Carrier-based immobilization strategies have also been explored. A sponge-based moving bed bioreactor was proposed to eliminate carbamazepine (25.9%) and β-estradiol 17-acetate (97%) (Luo et al., 2014). In addition, a moving bed biofilm reactor has been tested for the biodegradation of benzotriazoles (40–76%) and hydroxybenzothiazole (80–97%) (Mazioti et al., 2015b).

Laboratory-scale microbial fuel cells (MFCs) were studied for the removal of 26 EOMs with broad physicochemical properties using both a single- and double-chamber air cathode. The study showed that EOM removal in this system involved both sorption and biodegradation processes. For neutral compounds, the removal efficiency was affected primarily by the biodegradability and hydrophobicity of the compounds. Electrostatic interactions played an additional role in the systems as the removal rates were generally higher for positively charged compounds than for negatively charged ones (Wang et al., 2015).

Anaerobic conditions have also been investigated in alternative systems. A pilot system composed of an anaerobic reactor and a constructed wetland was evaluated for the elimination of ibuprofen, naproxen, diclofenac, tonalide, and BPA. The system had removal efficiencies >97%. The major removal mechanism was due to hydrophobic sorption of EOMs onto the particulate matter (Avila et al., 2010).

Trends, limitations, and future research needs

Factors influencing the biological removal of EOMs in complex water matrices during nonconventional WWTs were analyzed with the compiled data of 25 studies (1,056 data points; Supplementary Table S3). Overall, the studies in this section indicate that biodegradation of multiple EOMs by complex microbial communities as part of nonconventional WWTs can remove up to 90% of certain EOMs, yet complete elimination of EOMs is still rare (Table 2).

The effect of a compound's chemical complexity on its biodegradation was investigated. The 153 compounds were first grouped with respect to five classes as follows: (i) pharmaceutically active compounds and metabolites; (ii) personal care products; (iii) industrial chemicals; (iv) pesticides; and (v) contrast media. Supplementary Figure S3 (Supplementary Data) illustrates the relationship between the average biodegradation and the chemical complexity for each class of compounds. For a more robust observation, the 29 most studied EOMs (contaminants that appeared in ≥4 articles and have between 11 and 42 degradation values) were plotted together (average biodegradation vs. chemical complexity; Fig. 1). Both Fig. 1 and Supplementary Fig. S3 show that the chemical complexity of a molecule is not directly related to its biodegradation during nonconventional WWTs. For example, the average biodegradation efficiency reported for benzotriazole, the EOM with a low chemical complexity value (92.5), was 64 ± 18% (initial concentration range: 1–30 μg/L), while 17-β-estradiol-17-acetate with the highest chemical complexity (476) has a 94 ± 6% average biodegradation (initial concentration range: 2.7–5 μg/L). In the studies included in this review, the trends from Supplementary Fig. S3 imply that the biodegradation of EOMs may be closely linked to the biotechnology being used and operating conditions. It may be possible that a compound's chemical complexity is not directly related to its biological toxicity, while physicochemical properties, such as solubility and partitioning coefficients, could play a key role in the bioavailability of a compound and, thus, its biodegradation (Tran et al., 2013). Furthermore, Hu et al. (2017) observed that substrate specialization is a key adaptation strategy within a diverse microbial community of hydrocarbon degraders, and thus, the chemical complexity may be overcome in heterogeneous consortia.

FIG. 1.

Average biodegradation and chemical complexity of frequently studied EOMs in nonconventional biological treatments where 4 ≤ number of studies per EOM ≤15. For each EOM, the average biodegradation was calculated using all sets of treatment conditions (n, where 12 ≤ n ≤ 42). EOM, emerging organic micropollutant.

This observation could contrast with previous works where it was observed that EOMs are less biodegradable as their chemical complexity increases (i.e., higher molecular weight, branching, and number and type of functional groups) (Jaworska et al., 2003; Bertelkamp et al., 2014; Wijekoon et al., 2014). However, the trends in Fig. 1 and Supplementary Fig. S3 may also indicate that additional experiments are needed to properly identify the association between molecular characteristics of EOMs, their removal efficiencies, and their transformation pathways (Tran and Gin, 2017).

To identify effective biotechnologies that can biodegrade EOMs, carbamazepine (15 studies with 42 biodegradation values) and diclofenac (12 studies with 35 biodegradation values) were assessed since these compounds were the most studied in this review and are well-known recalcitrant EOMs (Tran and Gin, 2017). In their corresponding studies, carbamazepine and diclofenac were treated under 42 and 35 different sets of conditions, respectively.

Figures 2 and 3 showcase the reported biodegradation (%) values in the studies where carbamazepine and diclofenac were treated, respectively. The average removal for carbamazepine is 31.5% (with a standard deviation of 35.4%; Fig. 2) with initial concentrations between 1 and 100 μg/L. Treatment setups that report having >67% biodegradation (the average removal value plus a standard deviation) include the following: MBR with activated carbon (97–98%, Nguyen et al., 2013; 92%, Li et al., 2011); fungal laccase-functionalized membranes (94%, Ba et al., 2014); MBR-NF and MBR-RO membrane systems (92–93%, Cartagena et al., 2013); double-chamber air-cathode MFC at 1,000 Ω (73%, Wang et al., 2015); and oxic/anoxic MBR (68%, Hai et al., 2011a). The treatments that were unable to biodegrade carbamazepine are as follows: anoxic/aerobic MBR (with and without recirculation) (Phan et al., 2014); CAS systems with oxic post-treatment, with anaerobic post-treatment and anaerobic reactor (Fålas et al., 2016); MBR with biogenic manganese oxides and bio-palladium (Forrez et al., 2011); and a moving bed bioreactor with activated sludge (Casas et al., 2015).

FIG. 2.

Biodegradation values for carbamazepine in nonconventional biological treatments (15 studies, 37 sets of treatment conditions). Compiled average biodegradation value as dotted line and ±standard deviation (±42%) as gray area. CAS OX/AN (Falås et al., 2016); CAS-FILM-MBBR (Casas et al., 2015); MBBR (Luo et al., 2014); MBR OX/THERM (Hai et al., 2011b); MBR OX/AN (Hai et al., 2011a; Phan et al., 2014); MBR REDOX (Forrez et al., 2011); MBR FUNCT (Ba et al., 2014; Wijekoon et al., 2014); MBR AC (Li et al., 2011; Nguyen et al., 2013); MBR NF/RO (Alturki et al., 2010; Cartagena et al., 2013); MBR OSM (Alturki et al., 2012); MFC (Wang et al., 2015). MBR, membrane bioreactor; CAS, conventional activated sludge; OX, oxic; AN, anoxic; FILM, biofilm reactor; THERM, thermophilic; MBBR, moving bed biofilm reactor; FUNCT, functionalized; AC, activated carbon; NF, nanofiltration; RO, reverse osmosis; MFC, microbial fuel cell.

FIG. 3.

Biodegradation values for diclofenac in nonconventional biological treatments (13 studies, 35 treatment condition sets). Compiled average biodegradation value as dotted line and ±standard deviation (±35%) as gray area. CAS OX/AN (Falås et al., 2016); MBR OX/THERM (Hai et al., 2011b); MBR OX/AN (Phan et al., 2014); MFC (Wang et al., 2015); MBR OSM (Alturki et al., 2010, 2012); MBBR (Luo et al., 2014); MBR NF/RO (Cartagena et al., 2013); AN CONST WETLAND, (Avila et al., 2010); MBR AC (Nguyen et al., 2013); MBR FUNCT (Wijekoon et al., 2014); MBR REDOX (Forrez et al., 2011). AN CONST WETLAND, anaerobic constructed wetland.

The average removal for diclofenac is 43.0% (with a standard deviation of 34.9%; Fig. 3) with initial concentrations from 1 to 5 μg/L. Treatments that reach >78% biodegradation include the following: MBR with activated carbon (99–96%, Nguyen et al., 2013); anaerobic reactor + constructed wetland system (99%, Avila et al., 2010); MBR-NF and MBR-RO membrane systems (95–98%, Cartagena et al., 2013); and MBR/biogenic manganese oxides and bio-palladium (86%, Forrez et al., 2011). The treatments that biodegraded <8% of diclofenac are as follows: anoxic/aerobic MBR (with and without recirculation) (0%, Phan et al., 2014); CAS systems with oxic post-treatment and with anaerobic post-treatment (2–6%, Falås et al., 2016); and single- and double-chamber MFCs at 167 Ω (73%, 5–9%, Wang et al., 2015).

Better-performing treatments for carbamazepine and diclofenac include fungal catabolism and biological/chemical removal, as well as physical removal mechanisms (activated carbon, membrane filtration, biofilms, and hydrophobic sorption in wetland sands). The laccase-functionalized membrane study (Ba et al., 2014) reported a synergistic action between the membrane and laccase in the elimination of carbamazepine. Other elimination mechanisms reported for most of these treatments were adsorption, absorption, and biosorption, which may or may not lead to higher biological degradation levels. Future studies on nonconventional treatments could take a closer look at the relationship between physical, chemical, and biological removal mechanisms, to determine if they complement or inhibit each other or if there is a synergistic effect between them. In addition, as mentioned in Section “Fungal degradation of EOMs”, future studies could focus on using fungal catabolic capabilities in the removal of recalcitrant EOMs in municipal wastewaters.

Treatments that did not sufficiently remove carbamazepine and diclofenac used mainly biological (bacterial) or chemical mechanisms. However, these treatments were effective in biodegrading other pollutants, for example, the anoxic/aerobic MBR treatment removed almost 89.5% of 17-β-estradiol-17 (Phan et al., 2014). This may indicate that in general, for recalcitrant EOMs like carbamazepine and diclofenac, a physical–biological approach is more effective than a biological–chemical one. As previously mentioned, closely studying the interactions among physical, chemical, and biological removing mechanisms will help to accurately establish the biodegradation capabilities of a given WWT for recalcitrant EOMs. For instance, Batt et al. (2007) concluded that 100% EOM removal could not be achieved by bioremediation alone in four large-scale WWTPs (0.3–113 mL/day), requiring a combination of biological and physicochemical treatment processes.

Research on coupling processes (biological, physicochemical, and chemical), versus adding sequential treatment steps, could also make up for treatment limitations from a technological perspective. An extensive review of coupling electrochemical AOPs with bioremediation technologies has been performed by Ganzenko et al. (2014). It is also important to highlight that all novel treatments revised in this study, as with Ganzenko et al. (2014), have been studied only at laboratory- and pilot scales. Therefore, it is hard to assess the applicability of these results in real-world conditions. Future studies could focus on determining if scale-up has an impact on the benefits of new technologies.

The effect of complex aqueous EOM mixtures may also be a factor in the treatment of recalcitrant EOMs. For both carbamazepine and diclofenac, poor-performing WWTs were treating on average more complex mixtures of EOMs than the more successful WWTs, 24 and 14 compounds, respectively. Understanding how EOMs behave in complex mixtures can help develop more effective treatment schemes, since EOMs could form micromicelles or change each other's bioavailability. The effect of metabolites in EOM bioavailability and biodegradation pathways also needs to be inquired and taken into consideration.

Aside from carbamazepine and diclofenac, the other eight most studied EOMs in this review include the following: ibuprofen (11 studies with 29 biodegradation values), primidone (11 studies with 31 biodegradation values), naproxen (10 studies with 23 biodegradation values), acetaminophen (9 studies with 31 biodegradation values), triclosan (9 studies with 24 biodegradation values), BPA (9 studies with 26 biodegradation values), gemfibrozil (8 studies with 21 biodegradation values), and 17-β-estradiol (7 studies with 17 biodegradation values) (Supplementary Table S3). These EOMs were studied in a similar manner to carbamazepine and diclofenac (Supplementary Fig. S4, in Supplementary Data).

Considering the 10 most studied EOMs mentioned, the nonconventional treatments that can remove ≥4 of the 10 contaminants are as follows: MBR with activated carbon (Nguyen et al., 2013); MBR-NF and MBR-RO systems (Cartagena et al., 2013); and the anaerobic reactor + constructed wetland system (Avila et al., 2010). As observed with carbamazepine and diclofenac studies, the removal in these three treatments also includes physical mechanisms. The WWTs that were unable to biodegrade significant levels of most of the 10 EOMs are as follows: anoxic/aerobic MBR (with and without recirculation) (Phan et al., 2014) and MFCs (Wang et al., 2015).

Future investigations could focus on gaining a better understanding of biotransformation processes and phenomena under anaerobic or anoxic conditions. While no clear operational trends can be identified, the findings suggest that different bioremediation technologies may have niche applications. Research could then be geared toward specializing technologies, taking advantage of their biodegradation strengths with respect to specific EOMs and operating conditions. Furthermore, as in the case of the biodegradation studies using specific microbial strains, there is also the need to identify biotransformation products in engineered systems for anaerobic/anoxic processes (Helbling et al., 2010; Stasinakis, 2012; Huntscha et al., 2014). In the case of MFCs, their performance is affected by multiple factors (e.g., microbial consortium, pH, dissolved oxygen, interactions between electrodes, and sorbents). As such, these future studies could include multifactorial experimental designs to identify the optimal operating conditions.

Besides the possible approaches described above, other strategies to optimize EOM removal are more process specific. For example, De Wever et al. (2007) concluded that EOM removal is less sensitive to operating conditions in WWTPs, but in other studies, operating conditions seem to play a significant role in EOM removal. Once the accurate biodegradation mechanisms are established, some of the key operating conditions to further evaluate include hydraulic retention time, sludge retention time, mixed liquor suspended solids, and nitrifying/denitrifying, sulfate-reducing, aerobic and anaerobic conditions (Koh et al., 2009; McAdam et al., 2010; Maeng et al., 2013; Herzog et al., 2014; Guerra et al., 2015).

While operating conditions may aid in the removal of EOMs, little attention is paid to the microbial consortia and biodegradation pathways in most of the hybrid processes studied. Further inspection of WWTs' microbial consortia includes determining the type of interactions among different microorganisms (cooperative, competitive, or neutral) and their combined treatment capabilities. Even in review articles such as Ahmed et al. (2017), Grandclément et al. (2017), and Tran et al. (2013), the synergistic interactions between different degrading microorganisms are obviated. Considering that microbes in WWTPs do not live in isolation and that plasmids may be key in biodegradation capabilities, horizontal gene transfer among species may be a possibility and could be exploited. Moreover, dynamic interactions between microbial communities need to be understood, along with the factors that can either enable or limit them. Finally, as in single-strain studies, future works should focus on determining the active metabolic pathways of the entire microbial community involved in the degradation of EOMs (Raes and Bork, 2008).

As already mentioned, a strategic approach is to investigate complex systems: heterogeneous consortia, complex water matrices (EOM mixtures), and coupled technologies. However, these types of experiments can be time consuming and their analysis will require effective big-data analysis. For this reason, Section “In Silico Approaches” briefly reviews current in silico tools of biodegradation mathematical modeling and molecular biology. These tools have the potential to be time-saving approaches and may help overcome the lack of comprehensive experimental data available (Cheng et al., 2012).

In Silico Approaches

Predictive computational and modern molecular biology analysis may be used strategically to reduce the time and number of tests needed to understand EOM biodegradation. Both approaches have the potential to assist in the systematic understanding of the behavior and effects of EOMs and microorganisms taking place during WWTs. These tools are beginning to play an important role in WWT research, and their application is likely to increase in the future.

Predicting biodegradation products, the estimation of their physicochemical properties, degradation half-lives, and persistence has been explored (Ng et al., 2010). Other useful in silico tools include well-developed mechanistic models of biodegradation processes of single compounds, which include both expert systems and artificial intelligence models. However, these models have yet to be developed to fully understand the biodegradability of highly heterogeneous mixes of EOMs along with their metabolites. The application of these tools in understanding WWTs has recently been discussed elsewhere (Prasse et al., 2015). Moreover, computer-based research tools like phenomenological EOM degradation models (Pomies et al., 2013) and databases (Jaworska et al., 2003) are also available, which compile information to better understand EOM transformations and degradation pathways.

Omics analyses are new and powerful in silico molecular biology tools that need to be developed alongside alternative biotechnological WWTs. These tools can help fast-track the development of novel biological systems and better understand their underlying mechanisms. These next-generation analyses rely on novel mass analyzers and include metaproteomics, when complex mixtures of organisms are analyzed, and proteogenomics, when proteomic information is used to improve gene annotations. Other time- and cost-effective screening strategies could also be applied such as whole proteome thermal profiling, subpopulation proteomics and metabolomics, and novel sequencing technologies (Armengaud, 2016).

Bioinformatics and big-data analyses are not commonly used in the development of WWTs, but they can be important tools to help assess dynamic interactions within microbial consortia. Metapopulation analyses have been applied to microbial consortia in natural and engineered wastewater systems (Püttker et al., 2015; Dam et al., 2016). These studies have shown that these models are robust and able to forecast species abundances over years, in response to environmental perturbations or seasonal changes. The ability to assess these dynamic interactions is essential for WWTPs to understand their evolving biocatalytic capabilities, especially when these plants manage daily peaks, and seasonal changes in operational conditions and usage.

The application of molecular biology tools in environmental samples is not straightforward since genomes of the studied organisms are not always established or the organisms are distantly related to previously characterized organisms. Mixtures of microorganisms are especially challenging since this bioinformatics mostly focus on homology-based methods for the characterization of biological systems. Overcoming these challenges in future studies might lead to contributions for the advancement of both bioinformatics and WWT technologies (Armengaud, 2016).

Conclusions

Overall, biodegradation is a promising mechanism for the complete elimination of organic EOMs during WWTs. However, complete elimination of EOMs is still rare and requires further research. From the critical review of EOM biodegradation studies of the past 10 years, future investigations could increase our understanding by:

• Analyzing and understanding in-depth the biodegradation mechanisms in complex systems: heterogeneous consortia, complex water matrices (EOM mixtures and metabolites), and coupled technologies.

• Determining the active metabolic pathways involved during the degradation of EOMs, by the application of systems biology's top-down and bottom-up approaches, to capture the full picture of the biological systems in question.

• Improving genomic, proteomic, and metabolomic protocols for EOM biodegradation in sewage/WWTP samples.

• Using nonbacterial microorganisms, such as fungi, for EOM removal to overcome the current bacterial limitations that lead to incomplete EOM removal.

• Specializing treatment technologies by taking advantage of their biodegradation strengths with respect to specific EOM mixtures and couple them with other biological WWTs.

• Coupling biological, physical, and chemical treatments with different degradation capabilities, with the proper understanding of each treatment's limitations.

• Investigating the scale-up and implementation of nonconventional systems (modified CAS and MBR systems and others) in the biodegradation of highly heterogeneous EOM mixtures.

• Developing bioremediation processes as an integral part of the secondary treatment of WWTPs.

• Jointly developing environmental bioinformatics, big data analysis, and WWTs for the advancement and enrichment of these fields.

Overall, these points suggest that future investigations need to embrace complexity. Multifactorial experimental designs, omics analysis, and various in silico tools can be used to critically assess and better understand experimental results. This in turn can aid in accurately establishing the biodegradation mechanisms, catabolic kinetics, and operational conditions critically needed to design WWTs with enhanced EOM biodegradation capabilities.

Footnotes

Acknowledgments

The authors thank the support provided by Mexico's National Science and Technology Board (CONACyT) for the CONACYT Researcher-Professor Fellowship of Dr. Garcia-Becerra. The authors also thank their reviewers for providing them guidance and recommendations to substantially improve this review and Dr. Karen Miranda for her help with the figures.

Author Disclosure Statement

No competing financial interests exist.

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