Removal of petroleum pollutants and monitoring of bacterial community structure in a membrane bioreactor

Chemosphere 83 (2011) 49–56

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Removal of petroleum pollutants and monitoring of bacterial community structure in a membrane bioreactor Jarosław Wiszniowski a,⇑, Aleksandra Ziembin´ska a, Sławomir Ciesielski b a b

Environmental Biotechnology Department, Silesian University of Technology, Akademicka 2, 44100 Gliwice, Poland Department of Environmental Biotechnology, University of Warmia and Mazury in Olsztyn, Sloneczna 45G, 10-719 Olsztyn, Poland

a r t i c l e

i n f o

Article history: Received 6 October 2010 Received in revised form 28 December 2010 Accepted 29 December 2010 Available online 22 January 2011 Keywords: Membrane bioreactor PAHs Petroleum organics PCR-DGGE 16S rRNA gene sequences

a b s t r a c t The long-term operational stability (159 d) in removal of organics and ammonia from synthetic wastewater was investigated. The experiment was carried out in two identical plug flow membrane bioreactors (MBR) (each with a submerged A4 Kubota membrane) operated under aerobic conditions. The vacuum distillate of a crude oil fraction in the emulsified state, which was used to model the petroleum pollutants, was added into the feed medium. The performance of biological treatment was evaluated by physicochemical analyses such as nitrogen forms, COD, and BOD. Additionally, monitoring of PAHs in the wastewaters was performed using HPLC-diode array detector. Moreover, the community structure of bacteria was analyzed by polymerase chain reaction-denaturing gradient gel electrophoresis. The MBR treatment was very effective with reduction by more than 90% of COD and Total Organic Carbon. Nearly complete removal of petroleum originated non-polar micropollutants was observed. The influence of the highest dosage of petroleum pollutants (1000 lL L1) on the bacterial community was noted. Ó 2011 Published by Elsevier Ltd.

1. Introduction Due to the rapid industrialization and urbanization, significant amounts of fuels as oil and petroleum products are released into the environment. Petroleum and oil pollutants in wastewater originate from a variety of sources such as crude oil production, oil refineries, the petrochemical industry, rinsing baths from metal processing, compressor condensates, lubricant and cooling agents run-off from urban areas (Cheng et al., 2005). Many oil hydrocarbons are believed to be a source of toxicity for aquatic life and create a chronic impact in certain areas (Wake, 2005). The toxicity from dispersed oil appears to be primarily associated with effects of various dissolved-phase PAHs. Certain members of the PAH class possess carcinogenic and/or mutagenic properties (IARC, 1991) and their presence in treated wastewater as well as in sludge has been subjected to legislative control required by US-EPA and the EU (Busetti et al., 2006). The membrane bioreactor (MBR) is becoming an important innovation and a reliable technology for biological wastewater treatment and has a high potential for petroleum and oil pollution abatement. However, only limited research has been carried out to investigate the applicability of the MBR technology for the treatment of wastewater from the petrochemical industry (Qin et al., ⇑ Corresponding author. Tel.: +48 32 237 29 15; fax: +48 32 237 29 46. E-mail addresses: [email protected] (J. Wiszniowski), [email protected] (A. Ziembin´ska), [email protected] (S. Ciesielski). 0045-6535/$ - see front matter Ó 2011 Published by Elsevier Ltd. doi:10.1016/j.chemosphere.2010.12.092

2007; Ravanchia et al., 2009) or oil-contaminated wastewaters (Scholz and Fuchs, 2000; Tri et al., 2006; Alberti et al., 2007; Wiszniowski et al., 2009). The MBR process has been proved to have many advantages in comparison to conventional biological processes such as small footprint size of the treatment unit, reduced sludge production, complete retention of solids and flexibility of operation (Visvanathan et al., 2000). Since the 1990s a spectacular reduction (by 30-fold) in the capital and operating costs of MBR technology has been seen (DiGiano et al., 2004), though the present cost (i.e. energy requirement for aeration, managing of membrane fouling, membrane replacements) of treatment by MBR still remains higher than that of the conventional treatment. Consequently, further reductions with respect to costs and energy requirement in MBR are eagerly awaited. They might be achieved by improvements in process design (efficiency of biological processes), improved operation and maintenance schedules and membrane life (Kennedy and Churchouse, 2005). Free oil is mostly removed from treated wastewaters by gravity oil separator and other equipment such as dissolved air floatation units (Galil et al., 1989). The other components of the oily wastewater, i.e. oil–water emulsion can be inadvertently transported into the biological treatment system and can potentially affect process performance. Tabakin et al. (1978) indicated that the adsorbed oil tends to impair sludge settling characteristics and cause failure of conventional systems. It can be expected that the major threat to the biological process is due to the oil coat causing the microorgan-

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isms to float out of the system, and limit oxygen and food transfer efficiency. On the other hand, the toxicity of a complex mixture of inorganic and organic chemicals (including BTEX, PAHs) present in the water-soluble oil fraction would decrease the activity of activated sludge microorganisms. Bearing in mind that the microbial community is the core component of every biological wastewater treatment system, it is important to elucidate the effect of oil– water contamination on microbial community and stable performance of MBRs. The possibility of examining microorganisms at molecular level, has led to an increased understanding of the composition of microbial communities and their structure in complex biocenosis, such as in activated sludge (Gilbride et al., 2006). However, information on structure, diversity, and stability of bacterial communities in MBRs treating oily wastewater is still sparse. Recently Silva et al. (2010) and Figuerola and Erijman (2010) reported results on monitoring bacterial community dynamics by a molecular approach in MBR treated petroleum refinery wastewaters. The aim of this study was to investigate the operational stability of MBRs used to remove organics (including PAHs) and ammonia from synthetic wastewater contaminated by petroleum compounds. Additionally, it was aimed at determining the effect of petroleum substances on bacterial biodiversity changes in bioreactors. The bacterial structure was monitored using denaturing gradient gel electrophoresis (DGGE) of PCR (Polymerase Chain Reaction)-amplified 16S rRNA gene fragments. 2. Materials and methods 2.1. Membrane bioreactor and operation The MBR was equipped with a submerged A4 Kubota membrane (cartridge type 203), made of chlorinated polyethylene with a nominal pore size of 0.4 lm and an effective surface of 0.3 m2. The experiments were carried out in two reactors (MBRA and MBRB) operated under aerobic conditions (oxygen concentration: 1–4 mg L1). The continuous aeration provided for both MBRs limited membrane fouling. Each MBR was operated at room temperature (22 ± 4 °C) and at a working volume of 10.5 L and at a solids retention time (SRT) of 75 ± 14 d and at a hydraulic retention time (HRT) of 25 ± 3 h. 2.2. Analytical methods For the start-up, both MBRs were filled with activated sludge from the local municipal wastewater treatment plant (WWTP) and fed with synthetic wastewater. The composition of the wastewater was as follows (in mg L1): CH3COONa 700–1300; dry meat extract 80; yeast extract 10; NH4Cl 200–250, K2HPO4 27; KH2PO4 10; MgSO4 7H2O; and Tween80 5–12.5 lL L1. The feed was pumped into the MBR (inlet) and pumped out (permeate) using peristaltic pumps (Zalimp, Poland). Subsequently, the feeding medium of MBRB was supplemented with different doses of petroleum organics (P-30 fraction), while the MBRA was free of petroleum contamination and assumed as the control (reference) system. The P-30 fraction (density at 20 °C is 0.878 g mL1) was a vacuum distillate of crude oil furnished by the oil refinery (in Poland). The following doses of this petroleum substance were used during the experiment: 0, 50, 200, 500 and 1000 lL L1 in acclimation period, period I, period II, period III and period IV, respectively. The period durations were 45, 28, 45, 24, and 16 d, respectively. Emulsified wastewater was prepared by mixing P-30 fraction with an aqueous solution of a surfactant (Tween80) in a blender. The analyses included COD (dichromate method, Merck), BOD (5 d test, Oxi Top WTW system), TOC (Total Organic Carbon) determined with Shimadzu Analyzer TOC-VCSH and petroleum ether

extractable organics by a gravimetric method (Polish Standard Methods PN-86C-04573/01). Ammonia, nitrite and nitrate were determined according to standard Merck methods using the Spectroquant test. The pH values and the dissolved oxygen concentration were analyzed using a pH-meter (WTW 340i) and oxymeter (WTW 340i) respectively. Volatile suspended solids (VSS), mineral suspended solids (MSS) and mixed liquor suspended solids (MLSS) were measured by heating gravimetric method (Polish Standard Methods PN-72/C-04559/03). Most of the parameters were measured twice a week. The quality of the feeding medium and reactor permeate wastewater obtained during the studies is shown in Table 1. 2.3. Sample pre-treatments, chromatographic separation and detection The PAHs were analyzed in the raw and biologically treated wastewater (from 6 to 8 replicates for each period). Solid-phase extraction (SPE) was carried out in a BAKER spe 12-G System using Supelclean Envi-18 (1 g, 6 mL, Supelco) sorbent. An aliquot of aqueous sample (from 150 to 1000 mL depending on dose of petroleum contaminates) was used. The extraction was based on the protocols suggested by Busetti et al. (2006) with some modifications. The standard addition method was applied (ca 50 and 150 lL of 16PAHs mix) to determine PAH concentrations in the samples. The applied analytical standard was OEKANAL (Sigma–Aldrich), of 16PAHs (10 ng each lL1) in acetonitrile. An organic modifier, 2-propanol (12%, v/v), was added to aqueous samples before performing SPE procedures. The SPE stationary phases were conditioned with sequential elutions of acetonitrile (9 mL), 2-propanol (9 mL) and a solution of Milli-Q water: 2-propanol (9 mL; 85:15, v/v) acidified at pH 2.5 with HCl (37%, v/v). The aqueous samples were passed through the cartridges. Interferences were removed from sorbing material by eluting through the cartridges a solution of Milli-Q water and 2-propanol (12 mL; 85:15, v/v) acidified at pH 2.5. The cartridges were dried under vacuum for 15– 20 min. The analytes were subsequently eluted using 12 mL of nhexane (grand, POCH Gliwice, Poland). The extracts were added to 2-propanol (2 mL) and then concentrated to 500 lL under a gentle stream of nitrogen at room temperature. The final extracts were diluted with 2-propanol and stored in 2 mL Teflon-lined screw capped brown-glass vials at 4 °C, prior to chemical analyses. The sample extracts were injected into a Gynkotek HPLC – UVD 340u using a Dionex ASI-100 autosampler. The chromatographic separation of the sixteen PAHs was performed using SUPELCOSIL LC-PAH HPLC Column (250  4.6 mm, 5 lm) and protected column by SUPELCOSIL LC-18 Supelguard (20  4.0 mm, 5 lm) (Supelco) at room temperature. The mobile phase was a mixture of acetonitrile (A)/methanol (B)/water (C) (super-gradient, POCH – Gliwice, Poland) at the flow rate of 1.0 mL min1. The optimized linear gradient for PAH separation (in petroleum pollutants) was as follows:

Table 1 Characteristics of the MBRs influent and effluent. Parameter

COD (mg L1) BOD (mg L1) TOC (mg L1) 1 NHþ 4  N (mg L ) 1 NO  N (mg L ) 2 1 NO 3  N (mg L ) pH

MBRA

MBRB

Influent

Efflunet

Influent

Efflunet

655–1230 460–900 230–495 40–75 0 0 7.1–7.5

50–124 0–8 4–17 0–0.7 (6.0)a 0.1–2.5 39–71 7.5–8.2

655–3290 460–1150 230–990 40–75 0 0 7.1–7.5

50–202 0–14 9–32 0–4.0 (46)a 0.1–2.2 0–71 7.6–8.2

a Average concentration of ammonia in experimental period IV (dose 1000 lL L1).

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the initial composition, A/B/C 50/15/35 v/v%, was held for 5 min and then was changed to A/B/C 62/5/33 v/v% over a period of 40 min, then within 5 min to A/B/C 100/0/0 v/v% and held for 15 min, then it was changed to A/B/C 50/15/35 v/v% within 5 min and finally held over a period of 5 min (A/B/C 50/15/35 v/v%). 2.3.1. LOD, LOQ and recovery experiment The limit of detection (LOD) and the limit of quantification (LOQ) were determined by the method which was based on the standard deviation (SD) of 10 independent samples containing Milli-Q water spiked with the 16PAHs analytical standard (at levels approximating the LOD). The parameters were calculated as follows: LOD = 3 SD, LOQ = 3 LOD (Konieczko and Namiesnik, 2009). Taking into account the maximal concentration factor for the SPE methods (500-folds), LOD equals to 0.023, 0.029, 0.02, 0.02 lg L1 and LOQ = 0.07, 0.09, 0.07, 0.07 lg L1 for naphthalene, fluorene, phenanthrene and anthracene, respectively. The recovery was performed in Milli-Q water (1 L) spiked with 16PAHs standard (200 lL) (n = 4) and using the SPE and HPLC methods described above. The percentage of recoveries was 84 ± 13, 90 ± 6, 98 ± 6 and 93 ± 5 for naphthalene, fluorene, phenanthrene and anthracene, respectively.

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(nMDS) technique. The Dice similarity matrices were calculated with the PAST software. It allowed us to construct planes ordination, by nMDS, to discriminate genetic structure over time and differences between the MBR systems. 2.6. DNA bands purification, cloning and sequencing The dominant bands, present in the PCR-DGGE profiles obtained using 968F-GC/1401R primers pair, were excised and DNA was reamplified using the same conditions as for the first amplification. PCR products were purified using Clean-up kit (A&A Biotechnology, Poland) and cloned using the QIAGEN PCR cloning kit (Qiagen). Plasmid DNA was purified using a Plasmid DNA Kit (A&A Biotechnology, Poland) and sequencing was performed using a Perkin Elmer ABI 373 Automated DNA Sequencer (PE Applied Biosystems, USA). All reactions were run following the manufacturer’s protocols. DNA sequences and their closely related sequences were aligned using the Clustal W software (Thompson et al., 1994). Genetic relationships were determined by the distance method with the mega 2.1 software (Kumar et al., 2001). The nucleotide sequences were deposited in GenBank under accession numbers: HM755954-HM755971 (Table 3).

2.4. DNA isolation and PCR conditions 3. Results and discussion Activated sludge samples (10 mL) were collected from the membrane bioreactor and stored at 20 °C. Total genomic DNA was extracted from 0.2 g of the activated sludge samples using a Fast DNA Spin Kit for Soil (MP Biomedicals LLC) according to the manufacturer’s instructions. The amount of DNA was measured spectrophotometrically using a Biophotometer (Eppendorf) and stored at 20 °C until PCR amplification. The PCR was carried out using 968F-GC/1401R primers as described previously (Evans et al., 2004). The PCR products were evaluated by agarose gel electrophoresis (0.8% w/v agarose, Promega) in 1 TBE buffer (Tris base, boric acid, EDTA, pH = 8.3), gel was stained with ethidium bromide (0.5 lg L1) in Milli-Q water and photographed under UV light. 2.5. DGGE analysis The DGGE of the PCR products obtained with 968F-GC/1401R primers were performed using the Dcode Universal Mutation Detection System (Bio-Rad) Polyacrylamide gel (8%, 37:1 acrylamide-bisacrylamide, Fluka) with 30–60% gradient of denaturant (urea), prepared accordingly to the manufacturer’s instruction. The electrophoresis was run for 9 h at 55 V in a 1 TAE buffer (Tris base, acetic acid, EDTA, pH = 8.0) at a constant temperature of 60 °C. The gel was stained with SYBR Gold (1  10 000, Invitrogen) in Milli-Q water for 30 min and destained in Milli-Q water for 30 min, then visualized under UV light and photographed using a Gel Doc 2000 System (Bio-Rad). 2.5.1. Analysis of DGGE patterns The processing of the DGGE gels was performed using GelCompar software version 6.0 (Applied Maths, Kortrijk, Belgium). The DGGE banding patterns reflecting microbial structure in MBRA and MBRB were examined in two ways: (i) by clustering analysis and (ii) by dimensioning techniques. In the first approach the gels were normalized and the dendrograms of DGGE patterns were constructed using an Unweighted Pair Group Method with an Arithmetic Mean method. The Dice correlation (binary) coefficient matrices were applied. The clustering analysis was performed using GelCompar software. In addition, binary matrix data of DGGE patterns were extracted and used for the second approach in the non-metric multidimensional scaling

3.1. Organics and ammonia removal In the acclimation period, both MBRA and MBRB were operated under the same parameters in order to adapt biomass from WWTP to the synthetic wastewater medium (without any petrochemical contaminants) and to hydrodynamic conditions in the lab-scale reactors. Since the synthetic wastewater consists of readily degradable organics (BOD/COD = 0.7), acclimation proceeded very rapidly, and already after one week of the process more than 93% of COD (Fig. 1a and b), 96% of TOC and almost 100% (99.7%) of BOD were removed. After 45 d of operation, the surfactant oil/water emulsion was added into the feed of MBRB system (50 lL L1), while into MBRA (control), only an identical amount of surfactant was supplied. The lowest dose of petrochemical contaminants (period I) did not influence organics removal (Fig. 1a and b) nor oxidation of ammonia (Table 1) in MBRB. Ammonia oxidation to nitrate with 99% efficiency was achieved in both systems. Next, the MBRB was fed with synthetic wastewater in which the concentration of the pollutants (surfactant oil/water emulsion) was rapidly increased to 200, 500 and 1000 lL L1 for period II, III and IV, respectively. This corresponded to the increase of COD concentration and volumetric loading rates (from 0.71 to 1.17 g COD L1 d1) of MBRB among the periods (Fig. 1b). Meanwhile, the COD concentration in the control reactor (MBRA) remained stable, approximately at the level of 1000 mg L1. The computable percentage of COD corresponding to the increase of petrochemical organics in MBRB was 4, 36, 53 and 70% of COD in the period II, III and IV, respectively. Simultaneously with the increase of COD contents in the influent of MBRB (Fig. 1d), the MLSS concentration increased in the bioreactor. Thus, the calculated organic loading rates (OLR) were at a similar level ranging from 0.28 to 0.35 g COD g MLSS1 d1 (except the period IV when OLR in MBRB was 0.479 g COD g MLSS1 d1) in both reactors. Even though the BOD/COD ratio (known as the biodegradability) in the influent of MBRB was decreasing from 0.7 in the acclimation and period I to 0.6, 0.4 and 0.3 for the periods II, III and IV, the organics removal was at a very high level. Irrespective of

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J. Wiszniowski et al. / Chemosphere 83 (2011) 49–56

the dose of petroleum pollutants in the influent of MBRB the removal of organics of more than 93% of COD, 99% of BOD and 96% of TOC was ensured. Also, in the period IV when the average influent COD concentration was 3250 mg L1, effluent COD value was

Table 2 PAHs concentration in influent and effluent of the MBRB system. PAHs

Influent Naphthalene Fluorene Phenanthrene Anthracene Effluent Naphthalene Fluorene Phenanthrene Anthracene

Period I (lg L1) Mean ± SD

Period II (lg L1) Mean ± SD

Period III (lg L1) Mean ± SD

Period IV (lg L1) Mean ± SD

0.1 ± 0.1 8.2 ± 1.5 43.2 ± 7.0 5.4 ± 1.7

4.0 ± 0.6 48.2 ± 6.1 182.0 ± 20.7 19.9 ± 0.8

4.4 ± 1.0 62.2 ± 10.3 322.2 ± 26.3 35.4 ± 2.6

12.0 ± 3.5 152.7 ± 17.2 672.2 ± 15.3 74.1 ± 1.5



0.1 ± 0.0
0.2 ± 0.1 0.3 ± 0.2 0.4 ± 0.1 0.2 ± 0.1

below 140 mg L1 on average. The significant removal of organics in the MBRB system (despite the decrease of biodegradability i.e. the BOD/COD ratio) can be attributed to the retention of emulsified organics by the MF membrane in the bioreactor. It was also observed that the VSS fraction increased more rapidly in MBRB than in the MBRA system. For instance, the percentage of organic fraction in MLSS rose to 90% in MBRB (period IV) (Fig. 1d). The experiments carried out with the emulsified petroleum fraction (using Tween80 surfactant) in MilliQ showed that from 70 to 85% TOC can be retained by the KUBOTA membrane depending on the initial concentration of petroleum pollutants (data not shown). Thus, it is conceivable that petroleum oily pollutants were accumulated in MBRB increasing the concentration of MLSS. This hypothesis is in agreement with visual observation of activated sludge. In the period IV, white granules (diameter of about 0.5– 3.0 mm) can easily be distinguished in the reactor with only the naked eye (photo not shown). Previously Scholz and Fuchs (2000) investigated the application of the MBR process to treat synthetic wastewater containing either

Table 3 Characteristics of the DNA sequence obtained from excised DGGE bands. Band number

Band name/accesion numbers

Closest relatives/accession numbers

Coverage/identity (%)

1, 3, 4 2 5, 7 6 8 9, 13 10 11, 12 14 15 16 17 19 20 21 22 23, 24 25

P1-1.3.4/HM755954 P1-2/HM755955 P1-5.7/HM755956 P1-6/HM755957 P1-8/HM755958 P1-9.13/HM755959 P1-10/HM755960 P1-11.12/HM755961 P1-14/HM755962 P1-15/HM755963 P1-16/HM755964 P1-17.18/HM755965 P1-19/HM755966 P1-20/HM755967 P1-21/HM755968 P1-22/HM755969 P1-23.24/HM755970 P1-25/HM755971

Uncultured Alphaproteobacteria/CU924477 Uncultured Gammaproteobacteria/CU924388 Uncultured sludge bacterium H9/AF234706 Uncultured Alphaproteobacteria EU12/AY428758 Uncultured verrucomicrobium DEV064/AJ401131 Uncultured bacterium clone A88/FJ660577 Uncultured bacterium clone np13b31/GU250866 Uncultured Gammaproteobacteria/CU926728 Uncultured bacterium/GQ397004 Uncultured bacterium/AB286604 Uncultured bacterium clone 85/FJ623344 Uncultured bacterium clone Gctb_ML_324/FJ353577 Uncultured Gammaproteobacteria/CU926728 Uncultured bacterium clone nbw221c01c1/GQ075444 Uncultured bacterium clone A191/FJ660600 Uncultured bacterium clone CH51i/FJ380174 Bacterium enrichment culture clone 5/GU065725 Alpha proteobacterium EU26/AY428761

100/99 99/99 99/99 99/99 99/99 99/99 99/93 99/99 99/98 9998 99/96 99/100 99/99 99/100 99/94 99/99 99/99 99/99

1500

40

1000

L-1

6

MLSS, g

8

2000

60

1500

40

1000 20

500 Accl.

I

II

III

IV

MSS VSS % VSS

0

100 80 60

4

40

2 0

80

MBRB Influent MBRB effluent Removal, %

20

500

(c)

2500

20 Accl.

I

II

III

IV

0

0

(d)

8

Removal, %

60

COD, mg L-1

2000

0

3000

80

Accl.

I

II

III

IV

0 100

MSS VSS % VSS

80

6

60

4

40

2

20

Percentage of VSS,%

MBRA Influent MBRA effluent Removal, %

100

3500

MLSS, g L-1

2500

Removal, %

COD, mg L-1

3000

(b)

100

3500

Percentage of VSS, %

(a)

0

0 Accl.

I

II

III

IV

Fig. 1. The COD concentrations in raw and treated wastewater (a) MBRA, (b) MBRB and suspended solid concentrations (c) MBRA, (d) MBRB vs. time (periods).

J. Wiszniowski et al. / Chemosphere 83 (2011) 49–56

fuel oil or lubricant oil and wastewater containing oils and surfactants. The authors obtained similar reduction of COD, exceeding 94% COD ranging from 5262 to 7877 mg L1) in the MBR with an external tubular cross flow ultrafiltration unit. More recently, high removal efficiency of both COD and hydrocarbons in a hollow-fibre MBR for wastewater stemming from the washing of mineral oil storage tanks was proved by Alberti et al. (2007). In this case, the COD removal in the reactor ranged from 93 to 96%, for concentrations ranging from 1300 to 7964 mg L1 and HRT from 7.9 to 31.8 d. A few days after the exposition of nitrifying activated sludge in the MBRB to the highest dose of petroleum pollutants (1000 lL1 L1), the process failed and the ammonia concentration increased to about 50 mg L1 in the effluent of reactor (Table 1). 3.2. PAHs and petroleum ether extractable organics removal

Relative absorbancy, a.u.

The mixture of petroleum and crude oil consists of thousands of individual compounds, aliphatic, aromatic and alkyl homologs of aromatic hydrocarbons. In this study, the presence of 16 PAHs was evaluated using HPLC-DAD preceding SPE techniques. The optimized conditions for liner gradient elution allowed the identification and quantification of four PAHs: naphthalene, fluorene, phenanthrene and anthracene (Table 2, Fig. 2). The identification of analytes was based on specific retention times (in comparison to standard 16PAHs mixture), combined with structure confirmation, which was performed by matching the UV analyte spectra. However, due to the complex matrix of petroleum contaminants, the standard addition method had to be applied in order to accurately determine the selected PAHs. The tested PAHs in the influent of the MBRA (control reactor) were on average below the LOQ level. In general, a proportional increase in PAH concentrations with the increase of petroleum contamination dose added to the influent of MBRB was observed. The highest content was noted for phenanthrene (Table 2). The content of four PAHs was reduced by more than 99% during the treatment. Peculiarly, the highest concentrations of naphthalene, phenathrene and anthracene in the effluent were noted in the period II, even though in the period III and IV 2.5-fold and 5-fold higher concentrations of petroleum pollutants, respectively were provided in MBRB. We cannot exclude that, due to acclimation of activated sludge microorganisms to petroleum pollutants, PAHs were more efficiently biodegraded. The improvement in decay of PAHs could be contributed by the presence of surfactants (Li and Chen, 2009). It should be underlined

1 2 3 0

10

20

30

40

50

60

Retention time, min Fig. 2. Chromatograms (at k = 220 nm): 1 – influent (period III), concentration factor = 100, 2 – analytical standard of 16 PAHs (about 2 mg L1 of each PAH), 3 – effluent (period II), concentration factor = 500 (on the left) and, activated sludge with white granules in the period IV (on the right).

53

that the petroleum pollutants (oily fraction) were dispersing (emulsified by Tween80) into the aqueous environment, which can promote the biodegradation of petroleum hydrocarbons in the MBRB system. On the other hand PAHs might undergo volatilization and this can be a phenomenon occurring in our studies. The increase in temperature (by 3–4 °C) in the period III and period IV (in comparison to the period II) most likely resulted in more important losses of 2- and 3-ring PAHs. This assumption may be supported by the findings of Manoli and Samara (1999), who concluded that lower molecular weight PAHs (i.e. naphthalene, acenaphtene, phenanthrene, anthracene, and fluoren) undergo substantial reduction (>40%) in biological systems due to volatilization and degradation. Above all, PAHs due to their lipophilic and hydrophobic properties can easily be adsorbed onto particulate organic matter (including activated sludge) (Busetti et al., 2006), which is the main pathway of PAHs removal in conventional wastewater treatment systems. Fig. 2 shows the chromatograms obtained for the MBRB influent and effluent wastewaters in the period II, when the doses of 500 lL L1 of petroleum contamination were added to the feeding medium. Similar profiles of chromatograms were obtained on different days of the entire period. The analyses clearly indicate that not only the identified PAHs but also oily hydrocarbons originated from petroleum contamination were almost completely removed during the biodegradation/membrane filtration. The removal of oily hydrocarbons was confirmed by the magnitude of the petroleum ether extractable organics. This parameter which represents oil and grease contamination was lowered by more than 90% in the MBRB system irrespective of the doses (Wiszniowski et al., 2009). 3.3. DGGE cluster analysis Using Gelcompar, a software program capable of similarity/dissimilarity calculation and cluster analysis, the DGGE fingerprints of the bacterial community from MBRA and MBRB and for different times were analyzed for percent of similarity (Fig. 3a). Cluster analysis showed that the samples fell into three groups presenting >65% similarity among each group (Fig. 3a). These three clusters represent the samples taken from the period of acclimation (0, 41 d), the periods I and II (56 and 83 d) and from the periods III and IV (131 d and 159 d), respectively. The results suggest that the most important differentiation of the bacterial populations in both reactors appeared among the operational periods. At a given time, the DGGE profiles from MBRA and MBRB showed about 80% similarity in the period of acclimation (0, 7, 41 d) and period I and II (56 and 83 d). In the later period IV (159 d), the bacterial banding patterns from the two reactors became separated into different sub-clusters. However, despite this, >65% of similarity for the bacterial communities in both reactors remained evident. As an alternative to the cluster analysis, the grouping technique: nMDS was used to treat DGGE patterns (Fig. 3b). Generally, the MDS analysis shows that MBRA (control) and MBRB sludge grouping remain together at a given time. This was true from the acclimation period until the later period III (0–143 d). It suggests that the structure of the bacterial communities in both reactors did not vary significantly one from another. However, in the period IV (159 d), after adding the highest experimental concentration of petroleum pollutants (1000 lL1 L1), the samples from MBRA and MBRB diverged. This implies that the petroleum contaminants had influenced bacterial biocenosis. On the other hand, the MDS plot depicts a temporal changeability of bacterial community structure. The most important fluctuations were observed in the acclimation period (0–45 d), when the activated sludge seed from WWTP was adopted to operational conditions in the lab-scale MBRs. The samples withdrawn at 41, 56

(b)

100

90

60

(a)

80

J. Wiszniowski et al. / Chemosphere 83 (2011) 49–56

70

54

Stress = 0.175 159d A

0 seed 83.2 90.0 67.2

7d A 7d B

87.8

131d A

0 seed

41d A 131d B

41d B 54.6

86.7

56d A 56d B

70.2 77.8

7d B

7d A 159d B

83d A 83d B

58.8 77.8 70.4 65.4

56d A

131d A 131d B 159d B 159d A

83d A 56d B

41d B

41d A

83d B

Fig. 3. UPGMA clustering of DGGE bands by pattern similarity (a) nMDS (b) obtained from MBRA and MBRB sludge samples during five months of operation.

and 83 d refer to the period of acclimation, i.e. the middle of periods I and II, respectively. These samples remained grouped in the same area, which suggests that bacterial community did not fluc-

tuate during that time (Fig. 3b). Further temporal evolution in both reactors can be correlated with SRT, i.e. average time the activated sludge solids are in the system.

(a)

(b)

Fig. 4. (a) DGGE analysis of 16S rRNA gene fragment of total bacterial population from MBRA and MBRB. Bands that were sequenced are marked on the gel. Samples were taken in different periods of time from experimental (A) and control (B) reactors, 0 – seed and (b) phylogenetic tree of 16S rDNA sequences derived from the DGGE bands.

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3.4. Phylogenetic analysis The bacterial community composition of activated sludge from two membrane bioreactors – the control and contaminated with petroleum substances were investigated with DGGE fingerprinting using 16S rRNA gene sequences. The 25 dominant bands obtained by amplification using the 968FGC/1401R primer pair were excised from the gel and approximately 400 bp long DNA sequences were obtained (Fig. 4a). The initial analysis revealed that among all 25 obtained sequences, 18 were unique and each of them corresponded to an expected part of the 16S rRNA gene. Nucleotide sequences were compared to the GenBank database using BLASTN, all of them showed a high similarity to previously described DNA sequences obtained from uncultured microorganisms (Table 3). Eleven bands (Nos. 1, 3, 4, 5, 6, 7, 16, 17, 18, 25) were grouped within the class Alfaproteobacteria. The class of Betaproteobacteria was represented by three bands (Nos. 10, 20, 21), whereas eleven bands (Nos. 2, 9, 11, 19, 12, 13, 14, 19, 22, 23, 24) created the cluster of the Gammaproteobacteria class. Only one species (band no. 15) was characterized as a member of the Deltaproteobacteria class, also one species (band no. 8) belonged to Verrumicrobia phylum. These results are consistent with the results obtained by Silva et al. (2010), where the analysis of MBR and conventional sludge dealing with PAH contaminated wastewater was performed. The low abundance of the other bacterial taxa in the system could be explained by small size of the MBRs studied (volume of 10.5 L). Such bioreactors possess a lower number of possible ecological niches than regular WWTP systems, so the biodiversity in these MBRs is generally lower (data not shown). The lack of representatives of other bacterial groups could also be explained, as Schloss and Handelsman (2004) suggested, by PCR bias introduced by the use of bacterial primers designed on the basis of rRNA gene sequences from cultivable organisms. These may lead to the amplification of the environmental sequences similar to those of cultured organisms. This interpretation can be supported by the fact that most of the sequences analyzed in this experiment referred to ‘‘uncultured’’ microorganisms which underlines the statement that most of environmental microorganisms are still not obtained as pure cultures (Kamagata and Kamaki, 2005). During the large part of the experimentation, until the last dosing of PAHs, biocenosis from both bioreactors was similar and drastic changes in the fingerprint were not observed. The difference in bacterial composition in the studied reactors arose mainly from the presence of band nos. 9, 10, 17, and 18 in the MBBR (Fig. 4a). In some cases these DNA sequences were obtained from bands located at different positions (e.g. bands 1, 3, 4; bands 9, 13; and bands 11, 12). Most probably this resulted from the fact that only part of the resolved 16S rRNA gene fragments were sequenced and analyzed. Additionally, bands 2 and 4 are identified as different microorganisms although they are located at the same level in the DGGE gel. This is probably caused by the same melting properties of two different sequences. In order to conduct a precise identification, longer DNA fragments should be used, and thus DGGE-based results should be analyzed cautiously. All of the taxonomic groups present in the analyzed bioreactors are ubiquitous in WWTP systems and they have already been described in the literature (Juretschko et al., 2002; Silva et al., 2010). Details of sequences are given in Table 3. The sequence of Escherichia coli (NC_013353) was used as an outgroup to root the tree. The bootstrap numbers indicate the value of 1000 replicate trees supporting the branching order, only values higher than 50 are given (Fig. 4b). 4. Conclusions The research showed that the elimination of organic pollutants from wastewater proceeded effectively. Irrespective of their dose

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in the influent of MBRB the removal of organics of more than 93% of COD, 99% of BOD and 96% of TOC was observed. The chromatographic analyses confirmed almost complete reduction of oil hydrocarbons present in the synthetic wastewater. The inhibition of nitrification was noted only for a petroleum dose of 1000 lL L1 (period IV). Temporal changes in the structures of bacterial communities were observed in both reactors, although the bacterial structures themselves did not vary significantly between the A and B reactors. Petroleum contaminants at the highest experimental concentration of 1000 lL L1 influenced bacterial biocenosis. The bacterial population from MBRA and MBRB started to diverge in period IV. Acknowledgement The authors gratefully acknowledge the support provided by the Polish Ministry of Science and Higher Education Grant No. 4119/B/T02/2008/35 (2009–2011). References Alberti, F., Bienati, B., Bottino, A., Capannelli, G., Comite, A., Ferrari, F., Firpo, R., 2007. Hydrocarbon removal from industrial wastewater by hollow-fibre membrane bioreactors. Desalination 204, 24–32. Busetti, F., Heitz, A., Cuomo, M., Badoer, S., Traverso, P., 2006. Determination of sixteen polycyclic aromatic hydrocarbons in aqueous and solid samples from an Italian wastewater treatment plant. J. Chromatogr. A 1102, 104–115. Cheng, C., Phipps, D., Alkhaddar, R.M., 2005. Treatment of spent metalworking fluids. Water Res. 17, 4051–4063. DiGiano, F.A., Andreottola, G., Adham, S., Buckley, C., Cornel, P., Daigger, G.T., Fane, A.G., Galil, N., Jacangelo, J., Pollice, A., Rittmann, B.E., Rozzi, A., Stephenson, T. Ujang, Z., 2004. Safe water for everyone: membrane bioreactor technology. Africa’s first on-line science magazine (available at ). Evans, F.F., Rosado, G.V., Sebastian, R., Casella, P., Machado, C., Holmström, S., Jelleberg, , van Elsas, J.D., Seldin, L., 2004. Impact of oil contamination and biostimulation on the diversity of indigenous bacterial communities in soil microcosms. FEMS Microbiol. Ecol. 49, 295–305. Figuerola, E.L.M., Erijman, L., 2010. Diversity of nitrifying bacteria in a full-scale petroleum refinery wastewater treatment plant experiencing unstable nitrification. J. Hazard. Mater. 181, 281–288. Galil, N., Rebhun, M., Brayer, Y., 1989. Disturbances and inhibition in biological treatment of wastewater from an integrated refinery. Water Sci. Technol. 20 (10), 21–29. Gilbride, K.A., Frigon, D., Cesnik, A., Gawat, J., Fulthorpe, R.R., 2006. Effect of chemical and physical parameters on a pulp mill biotreatment bacterial community. Water Res. 40, 775–787. IARC, 1991. International agency for research on cancer, Lyon. Monographs on the Evaluation of Carcinogenic Risks to Humans, vol. 43–53. Juretschko, S., Loy, A., Lehner, A., Wagner, M., 2002. The microbial community composition of a nitrifying-denitrifying activated sludge from an industrial sewage treatment plant analyzed by the full-cycle rRNA approach. Syst. Appl. Microbiol. 25, 84–99. Kamagata, Y., Kamaki, H., 2005. Cultivation of uncultured fastidious microbes. Microbes Environ. 20, 85–91. Kennedy, S., Churchouse, S.J., 2005. Progress in membrane bioreactors: new advances. Proceedings of Water and Wastewater Europe Conference, Milan. Konieczko, P., Namiesnik, J., 2009. Quality Assurance and Quality Control in the Analytical Chemical Laboratory: a Practical Approach (Analytical Chemistry). Boca Raton, FL, pp. 145. Kumar, S., Tamura, K., Jakobsen, I.B., Nei, M., 2001. MEGA2: molecular evolutionary genetics analysis software. Bioinformatics 17, 1244–1245. Li, J.-L., Chen, B.-H., 2009. Surfactant-mediated biodegradation of polycyclic aromatic hydrocarbons. Materials 2, 76–94. Manoli, E., Samara, C., 1999. Occurrence and mass balance of polycyclic aromatic hydrocarbons in the Thessaloniki sewage treatment plant. J. Environ. Qual. 28, 176–187. Qin, J.-J., Oo, M.H., Tao, G., Kekre, K.A., 2007. Feasibility study on petrochemical wastewater treatment and reuse using submerged MBR. J. Membrane Sci. 293, 161–166. Ravanchia, M.T., Tahereh, K., Kargarib, A., 2009. Application of membrane separation processes in petrochemical industry: a review. Desalination 235, 199–244. Scholz, W., Fuchs, W., 2000. Treatment of oil contaminated wastewater in a membrane bioreactor. Water Res. 34, 3621–3629. Schloss, P.D., Handelsman, J., 2004. Status of the microbial census. Microbiol. Mol. Biol. Rev. 68, 686–691. Silva, C.C., Jesus, E.C., Torres, A.P., Sousa, M.P., Santiago, V.M., Oliveira, V.M., 2010. Investigation of bacterial diversity in membrane bioreactor and conventional

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