Effects of triclosan, diclofenac, and nonylphenol on mesophilic and thermophilic methanogenic activity and on the methanogenic communities

Journal of Hazardous Materials 291 (2015) 45–51

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Effects of triclosan, diclofenac, and nonylphenol on mesophilic and thermophilic methanogenic activity and on the methanogenic communities Evangelos C. Symsaris a , Ioannis A. Fotidis b , Athanasios S. Stasinakis a , Irini Angelidaki b,∗ a b

Department of Environment, Water and Air Quality Laboratory, University of the Aegean, University Hill, Mytilene 81 100, Greece Department of Environmental Engineering, Technical University of Denmark, Building 113, Kongens Lyngby DK-2800 Denmark

h i g h l i g h t s • • • • •

Toxicity assay of xenobiotics (TCS, DCF, and NP) on anaerobic digestion process. Sludge-based inoculum was more resistant to xenobiotics than manure-based. Additional biomass increases DCF’s and decreases TCS’s inhibition effect. Hydrogenotrophic methanogens were more robust to the xenobiotics than aceticlastic. TCS was the most toxic xenobiotic to biomethanation process compared to DCF and NP.

a r t i c l e

i n f o

Article history: Received 16 July 2014 Received in revised form 12 February 2015 Accepted 1 March 2015 Available online 3 March 2015 Keywords: Biomethanation IC50 PPCPs Toxicity Xenobiotics

a b s t r a c t In this study, a toxicity assay using a mesophilic wastewater treatment plant sludge-based (SI) and a thermophilic manure-based inoculum (MI), under different biomass concentrations was performed to define the effects of diclofenac (DCF), triclosan (TCS), and nonylphenol (NP) on anaerobic digestion (AD) process. Additionally, the influence of DCF, TCS, and NP on the relative abundance of the methanogenic populations was investigated. Results obtained demonstrated that, in terms of methane production, SI inoculum was more resistant to the toxicity effect of DCF, TCS, and NP, compared to the MI inoculum. The IC50 values were 546, 35, and 363 mg L−1 for SI inoculum and 481, 32, and 74 mg L−1 for MI inoculum for DCF, TCS, and NP, respectively. For both inocula, higher biomass concentrations reduced the toxic effect of TCS (higher methane production up to 64%), contrary to DCF, where higher biomass loads decreased methane yield up to 31%. Fluorescence in situ hybridization analysis showed that hydrogenotrophic methanogens were more resistant to the inhibitory effect of DCF, TCS, and NP compared to aceticlastic methanogens. © 2015 Elsevier B.V. All rights reserved.

1. Introduction Anaerobic digestion (AD) is a complex biological process mediated by distinct microbial populations (i.e., saccharide and

Abbreviations: AD, anaerobic digestion; SI, wastewater treatment plant sludgebased inoculum; MI, manure-based inoculum; DCF, diclofenac; TCS, triclosan; NP, nonylphenol; FISH, fluorescence in situ hybridization; VFA, volatile fatty acids; TS, total solids; VS, volatile solids; PPCPs, pharmaceuticals and personal care products; IC50 , 50% inhibition. ∗ Corresponding author at: Department of Environmental Engineering, Technical University of Denmark, Bld. 113, 2800 Kongens Lyngby, Denmark. Tel.: +45 4525 1429; fax: +45 4593 2850. E-mail address: [email protected] (I. Angelidaki). http://dx.doi.org/10.1016/j.jhazmat.2015.03.002 0304-3894/© 2015 Elsevier B.V. All rights reserved.

amino acid fermenters, volatile fatty acid (VFA) oxidizers, and methanogenic archaea) that catabolise organic material to produce biogas [1]. Methanogenesis, the final step of AD process, is mediated by methanogenic archaea, which are members of acetoclastic order Methanosarcinales (consist of two families: Methanosarcinaceae spp. a versatile acetoclastic and Methanosaetaceae spp. a strict acetoclastic) and strictly hydrogenotrophic orders Methanomicrobiales spp., Methanobacteriales spp., Methanococcales spp., and Methanopyrales spp. [2,3]. The structure, the relative abundance and the interplay in the methanogenic community are of crucial importance for the biogas reactors efficiency [1,4]. Methanogens are the most vulnerable microorganisms in the AD process and many organic (long chain fatty acids, N-substituted aromatics etc.) and inorganic (e.g., ammonia, heavy metals, etc.) compounds can

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potentially inhibit AD process [5]. Specifically, some organic compounds, due to their hydrophobic nature and their sorption to solid surfaces, can accumulate at high levels in AD systems, while their toxicity can be affected from organics concentration, biomass concentration, exposure time, cell age, feeding pattern, acclimation, and temperature [5]. Pharmaceuticals and personal care products (PPCPs) are considered to be emerging contaminants (micropollutants). These micropollutants have been reported in domestic wastewater, surface and ground water, animal slurry, and soil [6,7]. In wastewater treatment plants (WWTP), most of these micropollutants are partially adsorbed to the suspended solids and removed with the particles contained in the primary and secondary sludge [8]. These sludges are typically used as substrates in anaerobic reactors. Additionally, many of these micropollutants are used in the livestock industry and through the animal slurry they end up in the manurebased anaerobic reactors [9,10]. The adverse impacts of all the micropollutants on the manure-based AD reactors are not clear yet. Three of the most known PPCPs are DCF: (2-[(2,6dichlorophenyl)amino]benzeneacetic acid, monosodium salt), TCS (5-chloro-2-(2,4-dichlorophenoxy)phenol) and NP (4(2,4-dimethylheptan-3-yl)phenol) and have been accused of significant adverse environmental impact [11]. The logarithm of the octanol–water partition coefficient (log Kow ) is 0.7–4.5, 4.8, and 5.76 and solubility in water is 2425, 12, and 7 mg L−1 for DCF, TCS, and NP, respectively [12–14]. Specifically, DCF is a common pharmaceutical considered as a nonsteroidal anti-inflammatory drug [15]. DCF concentration in the wastewater influent, ranges between 0.10 and 4.11 ␮g L−1 [16], while in the wastewater sludge the concentration is up to 380.7 ng g−1 [17]. Fountoulakis et al. [12], tested the specific methanogenic activity using an acetate-based synthetic medium under different DCF concentrations and found an IC50 value of 120 mg L−1 . In the same study, sorption of DCF in the biomass sludge and bacterial cells was correlated with the inhibition effect on methanogenesis. TCS is a hydrophobic antibacterial agent found in the WWTP sludge with concentrations between 0.8 and 80 mg kg−1 of dry matter [8]. TCS is also used in the livestock industry [10] and consequently, it accumulates in the animal slurry which used as substrate in AD reactors. NP is a metabolite of a common detergent, nonylphenol ethoxylates, that does not undergo further transformation [18]. NP is a hydrophobic compound that has been found to interfere with the hormonal system of many organisms, and it has shown effects in aquatic organisms, such as feminization, reduction of male activity and increase of mortality rates of juveniles [19]. Additionally, NP is present in WWTPs’ sludge (150–2200 mg kg−1 of dry matter) and in animal manures (e.g., 120 mg kg−1 of dry matter of swine manure) [8,20]. Many researchers have reported that nonacclimatised AD process has little or no impact on the degradation of DCF, TCS, and NP [18,21,22]. There is scarce knowledge on the influence of DCF, TCS, and NP on AD process and it is not yet clear if the origin of the methanogenic inoculum (i.e., WWTP sludge-based or manure-based) affects the toxicity of these micropollutants. Furthermore, DCF, TCS, and NP have different distribution rates between solid and aqueous phase,

Table 1 Characteristics of inocula. Parameters

SI Inoculuma

MI Inoculumb

pH Temperature (◦ C) Total solids (% w/v) Volatile solids (% w/v) Total VFA (mg HAc L−1 ) Total Kjeldahl nitrogen (g N L−1 ) Total ammonia (g NH4 + –N L−1 )

7.95 37 ± 1 3.36 ± 0.42 1.78 ± 0.20 112.1 ± 2.9 2.18 ± 0.09 1.11 ± 0.05

8.42 52.5 ± 1 3.64 ± 0.84 2.17 ± 0.57 178.7 ± 4.2 2.96 ± 0.06 2.04 ± 0.03

a b

Wastewater treatment plant sludge-based inoculum. Manure-based inoculum.

thus, it is possible that their bioavailability also affects the toxicity on the AD process [23]. Thus, the primary aim of the present study was to elucidate the effect of DCF, TCS, and NP on AD process efficiency and to investigate the impact of biomass concentration and inocula origin on the micropollutants’ toxic effect. Additionally, since it is not yet clear if the above mentioned micropollutants affect the structure of methanogenic populations, a secondary aim of the current study was to investigate the influence of DCF, TCS, and NP on the relative abundance of the methanogenic populations. 2. Materials and methods 2.1. Inocula and media Two methanogenic inocula, derived from centralized biogas plants of Denmark, were used for the experiments: (a) a mesophilic inoculum from the anaerobic digester of the Lundtofte WWTP, which was fed with primary and biological sludge (SI-sludge inoculum), and (b) a thermophilic inoculum from Snertinge biogas plant, which was fed mainly with cattle and pig manure (MI-manure inoculum). The working volumes and the hydraulic retention times for Lundtofte and Snertinge reactors were 5000 and 3000 m3 and 30 and 15 days, respectively. The inocula were transferred to the laboratory within 24 h after sampling and degassed in order to reduce the residual methane production for 5 days [24]. The characteristics of the inocula used in the experiments are shown in the Table 1. To test the influence of the abiotic biomass concentration on the toxicity of micropollutants, 1 L of each inoculum was sterilized at 121 ◦ C and 1.02 atm for 20 min. The sterilized inocula were used as the additional biomass source in order to insure homogeneity and not to introduce additional active methanogenic populations in the batch reactors. The basal anaerobic (BA) medium used in the experiments was prepared as described before [25,26]. The xenobiotics stock solutions were prepared in methanol with final concentrations of 10 g L−1 for each of the three tested compounds (DCF, TCS, and NP). 2.2. Batch experiments setup For batch reactor experiments, 118 mL glass vessels were used with 40 mL working volume. Three different experimental assays were performed for each of the two inocula, which consisted of Assay-I: 8 mL active inoculum and 32 mL of BA medium, Assay-II:

Table 2 Initial concentrations of TS and VS in the three experimental assays for inocula MI and SI. Experimental assays

SI inoculuma −1

TS (g L Assay-I Assay-II Assay-III a b

)

7.72 ± 0.03 14.44 ± 0.06 21.16 ± 0.09

Wastewater treatment plant sludge-based inoculum. Manure-based inoculum.

MI inoculumb −1

VS (g L

)

4.56 ± 0.01 8.12 ± 0.02 11.68 ± 0.02

TS (g L−1 )

VS (g L−1 )

8.28 ± 0.07 15.56 ± 0.13 22.84 ± 0.19

5.34 ± 0.03 9.68 ± 0.05 14.02 ± 0.07

E.C. Symsaris et al. / Journal of Hazardous Materials 291 (2015) 45–51 Table 3 The parallel, nominal tested concentrations of the micropollutants. Micropollutants

Tested concentrations

DCF (mg L−1 ) TCS (mg L−1 ) NP (mg L−1 )

0 0 0

100 20 10

300 80 50

1000 160 100

3000 320 300

47

according to APHA’s standard methods [28]. The pH was measured with PHM99 LAB pH meter (RadiometerTM ). All values are the means of three independent replicates (n = 3) presented with the corresponding standard deviation (SD). 2.4. Fluorescence in situ hybridization analysis

8 mL active inoculum, 8 mL additional sterile biomass, and 24 mL BA medium, and Assay-III: 8 mL active inoculum, 16 mL additional sterile biomass, and 16 mL BA medium. Thus, the corresponding ratios of the active and sterile inocula were 100–0% w/w, 50–50% w/w, and 33–67% w/w for Assays-I–III, respectively. Additionally, to insure that there was available carbon source for the aceticlastic archaea and/or syntrophic acetate oxidising bacteria [1], 1 g L−1 of acetate (in the form of sodium acetate) was added in all the reactors. Acetate constituted just a small fraction of the total organic matter content in the vials and the final concentrations of the total solids (TS) and volatile solids (VS) tested in assays are presented in Table 2. All batch reactor experiments were performed in triplicates (n = 3). Five different nominal concentrations of xenobiotics were tested separately in distinct batch reactors for both inocula (MI and SI) and Assay-I–III (Table 3). The levels of the xenobiotics tested in the current study were based on preliminary screening experiments (data not show) and, where possible, on the available literature data for the solubility of the compounds in water solutions and the expected bioavailability/sorption in the biomass [12–14]. The xenobiotics were spiked in the reactors, dried with gentle N2 flow and then BA medium was added followed by 15 min of sonication for dilution–dispersion purposes. This process was performed to avoid undesirable interactions of the AD with the methanol (methylotrophic methanogenesis) of the stock solutions [1]. After the addition of inocula (Assay-I–III) and additional sterile biomass (Assay-II and III), the headspace of the reactors was flushed with N2 /CO2 (80%/20%) gas mixture, closed with rubber stoppers, sealed with aluminium caps, and stored in the incubators, at the respective temperatures. The first (baseline) concentration without micropollutant addition, was used to determine any statistically significant (p < 0.05) changes in methane yields and growth rates compared to the other tested micropollutants’ nominal concentrations (second–fifth). The overall experimental period was 60 days to allow for the detection of possible prolonged lag phases.

In order to define the influence of DCF, TCS, and NP on the methanogenic populations’ abundance, fluorescence in situ hybridization (FISH) analysis was used, as described before by Fotidis et al. [4]. The samples for FISH analyses were collected at the end of the experimental period, only from the Assay-I (no additional sterile biomass). For each micropollutant and inoculum, three representative samples were chosen using the following criteria: (a) no xenobiotics addition (baseline methanogenic population), (b) first statistically significant inhibition manifestation (p < 0.05) based on the methane yield, and (c) first statistically significant inhibition manifestation (p < 0.05) above the IC50 micropollutant nominal concentration. The FISH probes, used to identify the orders–families of the methanogenic populations, are described in the Table 4. All probes were used at optimal stringency with 0–50% formamide [4]. The hyperthermophilic (optimum 98 ◦ C) methanogenic order Methanopyrales spp. was not stained, because it was not expected to be found [4]. The total cells of the cultures were quantified with the use of 0.35 mg L−1 of 4 ,6 -diamidino-2-phenylindole (DAPI) diluted in filtered Milli-Q water. The visualization of the slides was achieved with an epifluorescence microscope (Olympus BX60; Olympus Corporation of the Americas), equipped with DAPI (blue emission filter), 6-FAM fluorescein amidite (green emission filter), and Cy3 fluorochromes (red emission filter) at 353 nm, 488 nm, and 545 nm wavelength, respectively. Digital microphotographs of the cultures were taken with a Leica DFC 320 camera (Leica Microsystems Imaging Solutions Ltd., United Kingdom). The determination of methanogenic consortium was achieved with the observation of 20 microscope fields using 63 × 1.4 lenses, corresponding 3000–10000 individual cells. Dominance of a specific methanogenic population was defined as a positive response to the group-level probe in range of 30–100% of the individual cells relative to all members of the archaea (identified positive by ARC915 probe). Non-dominant methanogenic populations represented between 1% and 29% of all the ARC915 probe positive archaea cells.

2.3. Analytical methods

2.5. Calculations and statistical analysis

The methane production of the batch reactors was determined three to four times per week by a gas chromatograph (Shimadzu GC-8A, Tokyo, Japan) equipped with a glass column (2 m, 5 mm OD, 2.6 mm ID) packed with Porapak Q 80/100 mesh (Supelco, Bellefonte, PA, USA) and with a flame ionization detector (FID), while hydrogen was the carrier gas [27]. The VFA measurements were performed using gas chromatography (HP 5890 series II) equipped with flame ionization detector and a FFAP fused silica capillary column, 30 m × 0.53 mm ID with film thickness 1.5 ␮m, while the carrier gas was nitrogen [3]. The TS and VS, were measured

Student’s t-test was used for the statistical significance between the reactors performances and the IC50 values in the three Assays. The IC50 values were calculated using the maximum methane yields of the batch reactors for all four different nominal concentrations of each xenobiotic, as the contaminant concentration resulting in 50% reduction of the maximum methane yield observed without presence of contaminants (baseline concentration). The IC50 value and 95% confidence interval were determined from the sigmoidal dose-response curves [32,33]. Differences between the total methane yields of the batch reactors and the comparison of

Table 4 FISH oligonucleotide probes used for identification of the methanogenic groups. Probes

Phylogenetic group

Functional groupa

Probe sequenceb

Reference

ARC915 MSMX860 MG1200 MB1174 MC1109

Archaea Methanosarcinales Methanomicrobiales Methanobacteriales Methanococcales

Mainly methanogens Acetoclastic, hydrogenotrophic Hydrogenotrophic Hydrogenotrophic Hydrogenotrophic

GTGCTCCCCCGCCAATTCCT GGCTCGCTTCACGGC TTCCCT CGGATAATTCGGGGCATGCTG TACCGTCGTCCACTCCTTCCTC GCAACATAGGGCACGGGTCT

Stahl and Amann [29] Raskin et al. [30] Sekiguchi et al. [31] Sekiguchi et al. [31] Raskin et al. [30]

a b

Methanogens. W, A + T mixed base.

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Fig. 1. Methane yield production plotted with nominal xenobiotics concentration for the three different experimental assays for SI (a–c) and MI (d–f) inocula, respectively. Error bars represent the standard deviation (n = 3).

xenobiotics and additional biomass effects were tested using a twoway ANOVA analysis. All the statistical analyses and the IC50 results were obtained using the Graphpad PRISM program (Graphpad Software, Inc., San Diego, California) and all values are the mean of three independent replicates (n = 3) ± standard deviation (SD).

3. Results and discussion 3.1. Effect of DCF, TCS, and NP on anaerobic digestion process The results obtained from the batch experiments showed a correlation between increasing DCF and TCS levels and reduction in methane production yield for both inocula (Fig. 1). For NP a sharp decrease of the methane production was observed for nominal concentrations above 50 mg L−1 . Only concentrations above that level affected the methane production. Increase of the SI volume (Assay-II and III) significantly increased (p < 0.05) the methane production in the majority of the DCF, TCS, and NP nominal concentrations tested compared to Assay-I. Interestingly, in the case of no micropollutant addition for both SI and MI inocula, the methane production of Assay-II and III were significantly (p < 0.05) higher and lower, respectively, compared to Assay-I. Nevertheless, since the characterisation of xenobiotic levels in the inocula was out of the scope of the current experiment, it was not possible to pinpoint the reason for the different yields of the SI and MI inocula.

Complete inhibition of methanogenesis was observed only at the highest DCF nominal concentration tested (3000 mg L−1 ) and for both inocula. For SI inoculum, nominal concentrations of NP below 100 mg L−1 were not enough to inhibit AD process in all assays. On the contrary, at 300 and 100 mg L−1 , methane production yields were significantly (p < 0.05) lower for SI and MI, respectively, compared to control reactors. Therefore, NP does not seem to pose a serious threat for AD process in the concentrations met in real treatment systems (<100 mg L−1 ), such as WWTP and manure-fed biogas plants [20,34]. Comparative analysis of the assays, showed different effects of the additional biomass between the micropollutants reflected on the inhibition of methane production rate (Fig. 2). Specifically, biomass addition did not reduce the inhibitory effect of DCF for either inocula (Fig. 2a and b). An interesting observation was that at 300 mg L−1 of DCF, the methane production in Assay-III (8 mL inoculum and 16 mL additional sterile biomass) was more strongly inhibited relative to the one observed at Assay-I (8 mL inoculum and no additional sterile biomass), i.e., the methane production was inhibited by 38–7% and by 46–16% for SI and MI, respectively. This finding was unexpected, since DCF has high sorption capacity [35]. These discordant results could be attributed to the combined synergistic inhibitory effect of high organic loading and high micropollutant bioavailability [36]. This assumption is also supported by the two-way ANOVA analysis of the interactive effects of DCF nominal concentration and additional biomass concentration

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49

Fig. 2. Effect of the nominal micropollutants’ concentrations on the anaerobic digestion, expressed as the percentage of methane inhibition extent of the spiked digesters to the control digesters, for the SI (a–c) and MI (d–f) inocula, respectively.

on methanogenic efficiency (Tables S1–S4). On the other hand, biomass addition (Assay-II and III) significantly reduced (p < 0.05) the inhibition effect of TCS in both tested inocula compared to the Assay-I (Fig. 2b and e). It seems that sorption capacity from the additional abiotic biomass reduced the TCS bioavailability counteracting the inhibition effect on AD for both inocula tested. The additional biomass had contradictory results on the toxicity of NP for the two different inocula (Fig. 2c and f). For SI inoculum, the methanogenic inhibition showed a small but statistically significant (p < 0.05) increase for Assay-III compared to Assay-I and II, for 100 and/or 300 mg L−1 of NP. For MI inoculum conversely, the inhibition effect significantly (p < 0.05) decreased with the addition of biomass at 100 mg L−1 of NP from 95% in Assay-I to 25% for both Assay-II and III. Finally, SI inoculum had significantly lower (p < 0.05) inhibition effect by NP even at 300 mg L−1 , compared to the MI inoculum (Fig. 2c and f). Thus, it seems that only for MI inoculum the addition of abiotic biomass reduced the inhibitory effect of the NP at the higher tested concentrations (100 and 300 mg NP L−1 ). A possible explanation might be that sludge inoculum was previously exposed to NP and thus, acclimatised to high concentrations of NP, since WWTP sludge can contain even a tenfold higher NP concentrations compared to manures [8,20]. The presence of micropollutant-acclimatized methanogens in WWTP sludge-based reactors, has been reported before [22,37].

3.2. IC50 IC50 results (Fig. 3a) showed that DCF was the least toxic micropollutant in Assay-I with values of 546 and 481 mg L−1 for SI and MI, respectively. These IC50 levels were considerably higher, compared to a previous study testing DCF where IC50 was 120 mg L−1 [12]. The inoculum of the aforementioned study was derived from a lab scale reactor fed with synthetic wastewater without DCF thus, methanogens were not acclimatised to the DCF, resulting to a lower IC50 value [22,37]. Additional biomass (Assay-II and III) led up to 31% drop in IC50 of DCF compared to Assay-I for both tested inocula. TCS was the most toxic micropollutant, compared to DCF and NP, with low IC50 values in Assay-I of 30.0 and 32.1 mg L−1 for SI and MI inocula, respectively (Fig. 3b). The additional biomass (Assay-II and III) decreased the toxicity of TCS, which led to significantly higher (p < 0.05) IC50 values compared to Assay-I, for both inocula. These findings further support the idea suggested before by Halden and Paull [38] for potential biomass sorption of TCS. Thus, the low IC50 caused by the higher biomass concentrations indicates improvement in the biomass sorption capacity for TCS. The IC50 levels of NP in Assay-I were 364.1 and 74.4 mg L−1 for SI and MI inoculum, respectively. As it was explained previously, this profound difference in the IC50 levels between the two inocula was most probably due to prior acclimatization of the SI inoculum to higher NP levels

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Table 5 Dominant and non-dominant methanogenic orders in baseline and in selected, batch reactors of Assay-I. Sample

SI inoculum

(Concentration)

Dominanta

Non-dominantb

Dominant

Non-dominant

Baseline DCF (300 mg L−1 ) DCF (1000 mg L−1 ) TCS (20 mg L−1 ) TCS (80 mg L−1 ) NP (100 mg L−1 ) NP (300 mg L−1 )

MB, MXc MS MG MS MG MB, MX MS, MC

MS, MC, MG MX, MG, MB, MC MS, MX, MB, MC MX, MG, MB, MC MS, MX, MB, MC MS, MC, MG MX, MG, MB

MS, MC MS, MG MS, MB MG, MB MS, MB MG, MB MB

MG, MB MB, MC MG, MC MS, MC MG, MC MS, MC MS, MG, MC

a b c

MI inoculum

Dominant methanogens: between 30% and 100% of the total number of methanogenic cells. Non-dominant methanogens: between 1% and 29% of the total number of methanogenic cells. MS: Methanosarcinaceae spp., MX: Methanosaetaceae spp., MG: Methanomicrobiales spp., MB: Methanobacteriales spp., and MC: Methanococcales spp.

step of Assay-I (no micropollutants addition) was used. It was found that, when no micropollutants were present, Methanobacteriales spp. and Methanosaetaceae spp., were the dominant methanogens in SI inoculum, while Methanosarcinaceae spp. and Methanococcales spp. were the dominant methanogenic species for MI inoculum (Table 5). The microbiological analyses in the spiked samples showed changes in the dominancy of the methanogenic consortia, comparing with the respective baseline samples. The only exception was the SI batch reactor spiked with 100 mg L−1 NP, where the dominant methanogens remained the same as in the baseline samples. This finding supports the assumption that methanogens of SI were acclimatised to NP, thus, the relative abundance of the dominant methanogens and AD efficiency were not affected by 100 mg NP L−1 . A possible explanation of this might be that there was not significant inhibitory pressure at those NP levels, as Fig. 2c indicates. As expected in manure-based methanogenic inocula, in all samples tested, Methanosaetaceae spp. were not identified among the dominant nor the non-dominant methanogenic populations [4]. An interesting finding was that hydrogenotrophic methanogens (Methanomicrobiales spp. and/or Methanobacteriales spp. and/or Methanococcales spp.) were dominant in 10 out of 12 samples for both inocula in Assay-I, spiked with the three micropollutants. There are other studies indicating that hydrogenotrophic methanogens are less sensitive to micropollutants toxicity (e.g., pentachlorophenol) compared to acetoclastic methanogens [39]. However, these results should be interpreted with caution, since the experiments were performed using specific inocula and physicochemical parameters. Thus, further studies focusing on potential mechanisms dictating the abundance of methanogenic populations spiked with DCF, TCS, and NP would be needed to elucidate the inhibition mechanism on methanogens. 4. Conclusions Fig. 3. IC50 for (a) DCF, (b) TCS, and (c) NP of the two tested inocula and the three Assays. The range represents the 95% confidence intervals of the model.

compared to MI inoculum. The IC50 for NP increased significantly (p < 0.05) alongside with the biomass (Assay-II and III) for MI inoculum (Fig. 3c). On the contrary for SI inoculum there was no clear tendency and IC50 levels for Assay-I and III were similar (p > 0.05) and at the same time higher (p < 0.05) compared to IC50 for AssayII. The non-linear (sigmoidal dose-response) regression predicting the IC50 and the goodness of fit are presented in the Supplementary data (Figs. S1 and S2 and Tables S5–S10, respectively).

Results derived from this study demonstrated that, in terms of methane production, the wastewater treatment plant sludgebased inoculum was more resistant to the toxicity effect of DCF, TCS, and NP compared to the manure-based inoculum. Generally, the toxicity of the tested xenobiotics on anaerobic digestion process followed by the following order TCS > NP > DCF for both inocula tested. Higher biomass concentration enhanced AD efficiency in both inocula only when TCS was spiked. Finally, DCF, TCS, and NP presence alternated the dominant methanogenic populations and hydrogenotrophic methanogens seemed to be more robust to the three micropollutants compared to aceticlastic methanogens.

3.3. Effect of DCF, TCS, and NP on relative abundance of methanogenic populations

Acknowledgments

As baseline for methanogenic communities, for the two inocula, the methanogenic communities found in the first concentration

We thank Hector Garcia for technical assistance with the experiment. This research has been co-financed by the European

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