Bioresource Technology 170 (2014) 1019Contents lists available at ScienceDirect

Bioresource Technology

journal homepage: www.elsevier .com/locate /bior techEnhanced removal of COD and color from landfill leachate in a sequentialbioreactorhttp://dx.doi.org/10.1016/j.biortech.2014.07.0790960-8524/ 2014 Elsevier Ltd. All rights reserved.

Corresponding author. Tel.: +91 011 26704321 (O); fax: +91 011 26717586.E-mail addresses: pooja.ghosh9@gmail.com (P. Ghosh), isthakur@hotmail.com

(I.S. Thakur).Pooja Ghosh, Swati, Indu Shekhar Thakur School of Environmental Sciences, Jawaharlal Nehru University, New Delhi 110067, India

h i g h l i g h t s

Leachate was treated by a sequential process involving bacterial and fungal sp. The process was optimized by BoxBehnken design and response surface methodology. Optimized conditions showed enhanced removal of COD (76.9%) and color (45.4%). Sequential treatment by the strains led to significant reduction in genotoxicity.a r t i c l e i n f o

Article history:Received 25 June 2014Received in revised form 21 July 2014Accepted 22 July 2014Available online 30 July 2014

Keywords:Leachate treatmentBioreactorResponse surface methodologyCODToxicity reductiona b s t r a c t

In the present study, a sequential treatment process was carried out using a fungal sp. (Phanerochaete sp.)followed by a bacterial sp. (Pseudomonas sp.) for the degradation and detoxification of contaminants inlandfill leachate. The process was optimized using BoxBehnken design (BBD) and response surfacemethodology (RSM) for three variables (C source, N source and duration), while monitoring tworesponses (% COD and color removal). After treatment in a bioreactor under optimized conditions,enhanced removal of COD (76.9%) and color (45.4%) was observed. Further, GCMS analysis of metabo-lites detected at different stages of treatment showed formation of degradation products of lignin andpolycyclic aromatic compounds. Treatment efficiency was finally evaluated by the alkaline comet assayin HepG2 human hepato-carcinoma cells. The results indicated no statistically significant DNA damage atthe end of the treatment, making the effluent suitable to be discharged conforming to the safetystandards.

2014 Elsevier Ltd. All rights reserved.1. Introduction

Sanitary landfilling is the most common disposal method formunicipal solid wastes (MSW). Approximately 8000 tonnes dailyof MSW is disposed in the three landfill sites of Delhi (Talyanet al., 2008). However, this method of disposal results in theformation of leachate, a high strength wastewater containing highconcentrations of organic contaminants, inorganic salts and heavymetals. Though present in trace amounts, the organic micropollu-tants, such as polycyclic aromatic hydrocarbons (PAHs), polychlo-rinated biphenyls (PCBs), pesticides, phenols and phthalate estersfound in the leachate are highly toxic, carcinogenic and estrogenic(Matejczyk et al., 2011). Several studies have confirmed adverseeffects of landfill leachate using plant bioassays (Sang et al.,2010), aquatic bioassays (Deguchi et al., 2007) and mammalian cellline based bioassays (Ghosh et al., 2014). If not treated and dis-posed safely, landfill leachate could be a major source of groundand surface water contamination. Therefore, it is important to finda sustainable option to treat leachate effectively before beingdischarged into the environment.

Various physico-chemical methods such as ion-exchange,chemical precipitation, adsorption and coagulation-flocculationhave been applied for landfill leachate treatment (Kurniawanet al., 2006). But these methods have the limitation of high operat-ing cost and limited versatility. Use of microbes like fungi and bac-teria is an environment-friendly and cost effective alternativecompared to these physico-chemical methods. The extracellularlignin modifying enzymes (LME) of white-rot fungi, consisting oflignin peroxidase (LiP), manganese peroxidase (MnP) and laccaseare relatively non-specific and provide white rot fungi the uniqueability to degrade a broad array of environmental pollutants suchas dioxins, PCBs and PAHs commonly found in leachate(Pointing, 2001). Growth by hyphal extension further gives thema competitive advantage over single cells such as bacteria,

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P. Ghosh et al. / Bioresource Technology 170 (2014) 1019 11especially with respect to the colonization of insoluble substrates(Baldrian, 2008). However, studies utilizing white- rot fungi forlandfill leachate treatment have been limited (Tigini et al., 2013).Bacteria particularly Burkholderia sp., Pseudomonas sp. andSphingomonas sp. which have been reported to degrade PAHs, PCBs,pesticides and other persistent organic pollutants are also promis-ing candidates for treatment of landfill leachate (Kanaly andHarayama, 2000). Also, it has been shown that when both fungiand bacteria are used in a stepwise manner for treating wastewa-ter, higher reduction in color, COD level and recalcitrant organiccompounds occurs as fungi are more effective in removing the col-ored components and lignin, whereas bacteria is more potent inremoval of recalcitrant organic compounds (Kaushik et al., 2010).In spite of their great potential, studies on application of fungiand bacteria in a sequential manner for leachate treatment arelacking.

Determining the optimum conditions for the growth of micro-organisms is important to accelerate the removal of COD, colorand other contaminants present. Traditional approach of optimiz-ing one-factor at a time for a multivariable system is not onlytime and labor intensive but often results in missing out the inter-active effects between the components (Bandaru et al., 2006).Response surface methodology is a suitable multivariate statisticaltechnique to evaluate the effects of combination of factors andinteractions among them and search for the optimum conditionsfor desirable response function (Lee et al., 2003). Comparing BBDwith other response surface designs has revealed that it is moreefficient than the central composite and full factorial designs(Ferreira et al., 2007). It has been effectively applied for the optimi-zation of various processes such as dye decolorization and degra-dation, biosorption, enzyme and drug production (Gurme et al.,2014; Jadhav et al., 2013).

The present study investigates the suitability of fungal (Phan-erochaete sp. ISTL01) and bacterial (Pseudomonas sp. ISTDF1)strains for landfill leachate treatment. BoxBehnken design andresponse surface methodology were used to design the experi-ments, build models and determine the optimum conditions forimproving the simultaneous removal of COD and color. The statis-tical design was based on three factors (C source, N source andduration) and two responses (% COD and color removal). In ourprevious study (Ghosh et al., 2014), the efficiency of the strainPseudomonas sp. ISTDF1 for bioremediation and detoxification oflandfill leachate has been shown. In this paper, an improvementin the treatment process is being reported by sequential action ofthe two strains under optimized conditions in a bioreactor.2. Methods

2.1. Okhla landfill leachate characterization

Okhla landfill site is located in South Delhi (283004800N,77170400E), India. It is an unengineered landfill site receiving1500 tonnes of MSW daily. Sampling of leachate was done fromthree sites within the landfill and the samples collected were com-bined to obtain a homogeneous sample. The leachate from thislandfill is characterized as a dark-colored liquid having 8120 color-ing units (CU), pH of 8.3 and high COD value of 29,020 (Ghosh et al.,2014).2.2. Microorganisms and inoculum preparation

The white rot fungus Phanerochaete sp. ISTL01 (gene bankaccession number KC862287) used in the study was grown onpotato dextrose agar (PDA) plates until sporulation (6 days) at30 C and kept at 4 C till further use. For inoculums preparation,the spores were scratched from freshly grown PDA plate, dispersedinto sterilized water and filtered through glass wool. The concen-tration was adjusted to 2 105 spores/mL, corresponding to anabsorbance of 0.5 at 650 nm. The inoculums ratio used was 10%v/v in MSM. The bacterial strain Pseudomonas sp. ISTDF1 (genebank accession number EU834943) was maintained in LB agarplate at 4 C. It was initially grown in LB followed by MSM. Inocu-lums size in MSM was kept 5 104 CFU/ mL (absorbance mea-sured at 600 nm).2.3. Culture conditions, COD removal and decolorization of leachate

Phanerochaete sp. ISTL01 and Pseudomonas sp. ISTDF1 wereassessed for their decolorization and COD removal potential.MSM-effluent i.e., MSM containing (g/L), Na2HPO42H2O, 7.8; KH2PO4, 6.8; MgSO4, 0.2; NaNO3, 0.085; Ca(NO3)24H2O, 0.05 with pH4 for fungi and 8 for bacteria was used. 20% v/v landfill leachatewas added in Erlenmeyer flasks with individual fungal and bacte-rial isolates and incubated at 30 C on a rotary shaker (rpm 150)for 10 days. Color and COD were estimated at an interval of 0, 1,5 and 10 days. On the basis of percentage reduction in both theparameters studied by the individual isolates, these organismswere used for scale up studies after optimization of nutritionalsupplements and duration.2.4. Optimization of process parameters experimental design,analysis and validation

Studies were performed with individual isolates (fungal andbacterial strains) in Erlenmeyer flasks to screen suitable C (sucrose,dextrose, sodium citrate and sodium acetate) and N (tryptone,yeast extract, sodium nitrate and ammonium nitrate) sources.After selection of the most appropriate C and N sources for bothfungi and bacteria, the concentration of selected C and N sourcesalong with duration was optimized for maximum reduction inCOD and color using BoxBehnken design and response surfacemethodology (RSM) with the help of Design Expert 9.0.2.0 software(Stat-Ease Inc., Minneapolis, USA).

A total of 17 experiments each for bacteria and fungi were car-ried out to evaluate the effects of the three variables (C source, Nsource and duration), each with three levels (low, medium andhigh) on two responses (% COD and color removal) as shown inTable 1. 20% v/v leachate-MSM, temperature of 30 C, 150 rpm,pH 4 for fungi and 8 for bacteria and inoculums size (as mentionedin Section 2.2) was used throughout the experiments. One uninoc-ulated flask with 20% v/v leachate and one with fungal/bacterialculture without leachate were kept as controls. The experimentaldesign matrix derived from the BoxBehnken model is also shownin Table 1. Percent COD and color removal by fungal and bacterialstrains individually has also been included in the same table. Thequadratic equation obtained from BoxBehnken model for predict-ing the optimal conditions can be expressed in the form of follow-ing equation:

Y b0 X

bixi X

bijxixj X

biix2ii 1

where b0, bi, bij are regression coefficients for the intercept, linearand interactions among factors, respectively; Y is the predictedresponse; xi and xj are independent factors in coded units and e isthe error term (Chattoraj et al., 2014). The data was subjected toanalysis of variance (ANOVA) and the coefficient of regression (R2)was calculated to find out the goodness of fit of the model. Threedimensional plots were obtained for both the strains to visualizethe individual and interactive effects of factors on the response asshown in Figs. 1 and 2.

Table 1The BoxBehnken design matrix for experimental design, observed and predicted values of responses-% COD and color removal using Pseudomonas sp. ISTDF1 and Phanerochaetesp. ISTL01.

RunNo.

Experimental design Pseudomonas sp. ISTDF1 Phanerochaete sp. ISTL01Responses (removal (%)) Responses (removal (%))

Carbon sourcea

(code)Nitrogensourcea (code)

Durationb

(code)CODobserved(R1)

CODpredicted(R1)

Colorobserved(R2)

Colorpredicted(R2)

CODobserved(R1)

CODpredicted(R1)

Colorobserved(R2)

Colorpredicted(R2)

1 1 (0) 0.5 (+1) 240 (+1) 33.41 33.63 21.52 22.26 49.6 49.72 18.49 18.152 0.5 (1) 0.1 (1) 120 (0) 27.32 27.82 15.95 16.42 42.46 42.68 28.41 27.493 1.5 (+1) 0.25 (0) 240 (+1) 42.62 42.61 24.12 23.59 49.7 49.84 29.69 29.074 0.5 (1) 0.25 (0) 240 (+1) 36.53 35.87 24.72 24.14 45.19 45.57 27.32 27.575 1 (0) 0.1 (1) 240 (+1) 32.96 33.41 16.91 17.28 47.31 46.67 31.72 32.16 1 (0) 0.25 (0) 120 (0) 35.43 36.21 20.43 21.2 52.1 51.84 29.3 28.777 1.5 (+1) 0.5 (+1) 120 (0) 42.29 42.01 25.69 25.23 44.62 44.32 20.14 20.888 1 (0) 0.25 (0) 120 (0) 35.11 36.21 21.96 21.2 51.66 51.84 28.64 28.779 1 (0) 0.25 (0) 120 (0) 36.32 36.21 20.52 21.2 53.41 51.84 28.61 28.77

10 1.5 (+1) 0.25 (0) 48 (1) 35.65 36.53 16.01 16.6 29.61 29.16 23.31 22.8811 1 (0) 0.25 (0) 120 (0) 37.21 36.21 20.94 21.2 51.32 51.84 29.4 28.7712 1 (0) 0.1 (1) 48 (1) 23.11 22.74 9.98 8.74 30.22 30.02 21.64 22.2113 1 (0) 0.5 (+1) 48 (1) 27.69 27.38 14.63 14.76 28.48 29.19 17.32 16.7114 0.5 (1) 0.5 (+1) 120 (0) 27.24 27.61 13.37 12.96 43.96 43.43 18.69 18.915 1.5 (+1) 0.1 (1) 120 (0) 36.42 35.84 10.11 10.51 43.21 43.82 29.68 29.6416 0.5 (1) 0.25 (0) 48 (1) 24.12 23.92 14.31 14.83 30.11 30.05 20.19 20.6517 1 (0) 0.25 (0) 120 (0) 36.96 36.21 22.13 21.2 50.69 51.84 27.91 28.77

a Unit of dosage: g/L.b Unit of dosage: h.

12 P. Ghosh et al. / Bioresource Technology 170 (2014) 1019Optimization using the desirability function (numerical optimi-zation) was employed to optimize the level of each factor for max-imum response. Finally, confirmatory experiments wereperformed in duplicate using the optimized conditions obtainedfrom numerical optimization for validation of model. The averagevalues of the experiments were compared with the predicted val-ues by the model in order to find out the accuracy and suitabilityof the model.

2.5. Stepwise treatment of landfill leachate under optimized conditions

After optimizing the culture conditions for both the strains,treatment of landfill leachate was carried out in a sequential man-ner, using the fungus followed by bacteria and vice versa to maxi-mize the COD and color removal. To determine the best sequence,treatments were carried out in flask culture with 20% v/v leachate-MSM. The sequence, which led to maximum reduction in COD andcolor of leachate, was used in scale up studies in the bioreactor. A15 L bioreactor with an effective volume of 10 L was used. Processparameters such as temperature, rpm, inoculums size, pH alongwith the optimized nutritional supplements were maintained forboth the strains. A schematic diagram of a two stage bioreactoris shown in Fig. 3. The samples (300 mL) were withdrawn at theend of each stage of treatment. All the samples denoted as UT(untreated), FT (fungal treated) and FBT (fungal and bacterial trea-ted) were centrifuged at 7000 rpm for 10 min to remove microbialbiomass and the supernatants were processed for COD, lignin andcolor measurement, GCMS analysis and in vitro genotoxicityassay.

2.6. Analytical methods

2.6.1. Measurement of COD, lignin and colorAll tests were conducted in accordance with the standard meth-

ods for the examination of water and wastewater. COD was mea-sured by open reflux method and color by platinum-cobaltmethod (APHA 2005). Lignin content was measured according toPearl and Benson (1940). For this, the pH of the supernatant wasadjusted to 7.0 with 2 M NaOH. 50 mL of sample or water (forblank) was mixed with 1 mL CH3COOH (10%) and 1 mL NaNO2(10%) and incubated for 15 min. This was followed by addition of2 mL of NH4OH and incubation for 5 min. Absorbance was mea-sured at 430 nm. The absorbance value was transformed into lignincontent (ppm) using the following formula:

Lignin ppm Absorbance=0:0002472.6.2. Gas chromatography-mass spectroscopy analysisThe untreated and treated leachate samples from each stage of

bioreactor were processed prior to GCMS analysis according toDas et al. (2012). Separatory funnel extraction was carried outusing 100 mL 1:1 v/v dichloromethane (DCM) and acetone addedto 250 mL sample. Extraction process was repeated thrice. Theextracted organic fraction was filtered through Whatman No. 54filter paper and then evaporated to dryness at room temperatureusing a vacuum rotator evaporator. After evaporation, it was dis-solved in 2 mL DCM (Crude organic extracts) for GCMS analysis.The analysis was done using a Shimadzu GCMS-QP 2010 Plusequipped with a capillary column Rtx-5 (dimensions: 0.25-lm filmthickness, 0.25 mm internal diameter, 30 m in length). One micro-liter of extract was analyzed by GC at conditions: splitless modewith a split ratio of 10.0; initial temperature 60 C for 1.0 min;temperature increased from 60320 C at a rate of 22 C min1).Data were compared with the inbuilt standard mass spectra librarysystem (NIST-05 and Wiley-8) of GCMS.

2.6.3. Alkaline single-cell gel electrophoresis (Comet assay)The effect of the bacterial and fungal treatments on the geno-

toxicity of the leachate was evaluated by Comet assay using HepG2cell line. The test samples for toxicity assay was prepared from thetreated leachate samples after removal of bacterial/fungal biomassby centrifugation followed by filter sterilization using 0.22 lm syr-inge filter. Comet assay was done according to Zegura and Filipic(2004) with slight modification (15 min electrophoresis at 25 V).HepG2 cells were treated with 0.5% v/v Milli-Q (negative control),50 lM Benzo (a) pyrene (positive control) and with 20% v/v testsamples for 24 h. The slides were stained with ethidium bromide(2 lg/mL, 100 lL per slide). The comets were visualized withfluorescent microscope at excitation and emission setting of518/605 nm. The percentage of DNA in tail, tail moment and olive

(A)

(B)

(C)

(i) (ii)

(i) (ii)

(i) (ii)

Fig. 1. 3-D surface plot showing the interaction of (A) dextrose (g/L) and tryptone (g/L) on (i) % COD removal and (ii) % color removal; (B) dextrose (g/L) and duration (h) on(i) % COD removal and (ii) % color removal; (C) tryptone (g/L) and duration (h) on (i) % COD removal and (ii) % color removal by Pseudomonas sp. ISTDF1.

P. Ghosh et al. / Bioresource Technology 170 (2014) 1019 13tail moment (OTM) of 40 randomly selected cells were analyzedfrom each slide by using Cometscore Freeware Software(www.tritekcorp. com). The comets were divided into five classeson the basis of DNA in the tail; Class I, less than 1% DNA in tail(intact nucleus); Class II, 120% DNA in tail; Class III, 2050%DNA in tail; Class IV, 5075% DNA in tail and Class V, more than75% DNA in tail. Statistical differences between the control andtreated cells were examined with the aid of ANOVA followed bymultiple comparisons (Dunnetts Method) in sigma plot 11 statis-tical package (Systat Software, San Jose, CA). A value of P < 0.05was used to determine significance in statistical analyses.3. Results and discussion

3.1. Screening of the nutrient supplements

20% v/v leachate-MSM was used throughout the experimentshaving 6120 mg/L COD, initial color 2360 CU and 3608.6 ppm oflignin. Among sucrose, dextrose, sodium citrate and sodium ace-tate analyzed at 1% w/v concentration, dextrose was found to bethe best C source for both the strains, causing 32.12% reductionin COD and 16.62% reduction in color by Pseudomonas sp. ISTDF1and 49.1% reduction in COD and 23.83% reduction in color by Phan-erochaete sp. ISTL01 after 240 h of treatment. Among tryptone,yeast extract, sodium nitrate and ammonium nitrate analyzed at0.25% w/v, tryptone was found to be the most suitable N sourcefor Pseudomonas sp. ISTDF1 accounting for 31.96% reduction inCOD and 15.96% reduction in color. Similarly for Phanerochaetesp. ISTL01, yeast extract was most suitable with 43.2% reductionin COD and 21.63% reduction in color after 240 h of treatment.

The nutrient requirements for optimum pollutant removal varygreatly with the microorganism used and the nature of the efflu-ent. Previous studies have reported that C and N sources regulatethe production of lignolytic enzymes in several bacteria andwood-rotting fungi (Galhaup et al., 2002; Mishra and Thakur,2010). Kaushik et al. (2010) reported the importance of dextroseand sodium nitrate as media supplements for removal of COD

http://www.tritekcorp.%20com

(i) (ii)

(C) (i) (ii)

(i) (ii)

(A)

(B)

Fig. 2. 3-D surface plot showing the interaction of (A) dextrose (g/L) and yeast extract (g/L) on (i) % COD removal and (ii) % color removal; (B) dextrose (g/L) and duration (h)on (i) % COD removal and (ii) % color removal; (C) yeast extract (g/L) and duration (h) on (i) % COD removal and (ii) % color removal by Phanerochaete sp. ISTL01.

14 P. Ghosh et al. / Bioresource Technology 170 (2014) 1019and color from distillery effluent. However, in another study,sodium nitrate was found to have a negative impact on decoloriza-tion of pulp and paper mill effluent (Mishra and Thakur, 2010).Also, there are reports where maximum decolorization is achievedin the absence of additional C and N sources using soil as inocu-lums (Adikane et al., 2006). The type of carbon and nitrogen(organic or inorganic) utilized by the microorganism also varies.Thus, screening of the nutrient supplements for maximal responseis important. Based on maximal removal of COD and color, dex-trose as a C source for both the strains and tryptone and yeastextract as N sources for Pseudomonas sp. ISTDF1 and Phanerochaetesp. ISTL01 respectively were used for further optimization by theBoxBehnken design.

3.2. Regression models and statistical testing

The relationship between independent factors and responsewas drawn by second-order polynomial equations. The regressionequation coefficients were calculated and the data was fitted tosecond-order polynomial equation for removal of COD and colorby the two strains. The coded equations obtained from BoxBehnken design for percentage removal of COD and color byPseudomonas sp. ISTDF1 as suggested by software is given below:

Removalof COD38:195:24A1:21B4:23C1:60AB1:47AC1:11BC1:24A24:80B24:10C2 2

Removalof color23:381:44A2:75B4:01C4:55AB0:58AC0:26BC0:45A25:51B22:11C2 3

Following coded equations were obtained for percentage removal ofCOD and color by Phanerochaete sp. ISTL01 by the software:

Removalof COD55:260:83A0:55B9:29C0:06AB1:29AC0:97BC4:23A24:39B211:96C2 4

Removalof color28:801:01A4:87B2:83C0:04AB0:09AC2:11BC0:92A22:71B23:80C2 5

Fig. 3. Schematic diagram of two stage bioreactor for treatment of landfill leachate.

P. Ghosh et al. / Bioresource Technology 170 (2014) 1019 15where A = carbon source (g/L), B = nitrogen source (g/L) andC = duration (h)

By comparing the factor coefficients in the coded equations, therole of individual factors or their double interactions on theresponse is revealed. Negative coefficient values indicate that indi-vidual or double interaction factors negatively affect the response,whereas the positive coefficient values indicate that the factorsincrease the response in the tested range. The coefficient valuesin Eqs. (2) and (3) reveal that the percentage of COD and colorremoval by Pseudomonas sp. ISTDF1 increase with factors dex-trose concentration, tryptone concentration and duration of treat-ment. Similar is the case with Phanerochaete sp. ISTL01where allthe factors dextrose concentration, yeast extract concentrationand duration positively affect the percentage of COD removal asshown in Eq. (4). However, Eq. (5) reveals that with increase inyeast extract concentration there is a decrease in percentage ofcolor removal.

The adequacy of the model was justified by the analysis ofvariance (ANOVA). The ANOVA of COD and color removal byPseudomonas sp. ISTDF1 and Phanerochaete sp. ISTL01 is given inTable 2. The Model F-value of 68.65 for COD removal and 43.47for color removal by Pseudomonas sp. ISTDF1 implies that themodel is significant. Similar was the case with Phanerochaete sp.ISTL01 where the model F-value was found to be 150.09 and66.18 for COD and color removal respectively implying significanceof the model. There is only a 0.01% chance that an F-value this largecould occur due to noise in both the cases. The Lack of Fit F valueof 1.0004 and 2.2018 in case of Pseudomonas sp. ISTDF1 and 0.6843and 2.6876 in case of Phanerochaete sp. ISTL01 implies that Lack offit is not significant relative to the pure error. There is a 47.88% and23.04% chance respectively for COD and color removal by Pseudo-monas sp. ISTDF1 and 60.67% and 18.17% chance respectively forCOD and color removal by Phanerochaete sp. ISTL01 that a Lackof Fit F-value this large could occur due to noise. The R2 coefficientgives the proportion of the total variation in the response predictedby the model, ensuring a satisfactory adjustment of the quadraticmodel to the experimental data. A high R2 value close to 1 isdesirable and a reasonable agreement with adjusted R2 is neces-sary (Nordin et al., 2004). The coefficient of variance (CV) is theratio of standard error of estimate to the mean value of theresponse and defines the reproducibility of the model. A modelnormally can be considered reproducible if its CV is not greaterthan 10% (Beg et al., 2003). As shown in Table 2, the values of CVare less than 10% in all the cases confirming the reproducibilityof the model. The adequate precision (AP) value is a measure ofthe signal to noise ratio and was found to be 28.12 for CODremoval and 21.81 for color removal by Pseudomonas sp. ISTDF1.For Phanerochaete sp. ISTL01, the AP values were found to be31.19 and 25.31 for COD and color removal respectively. AP valueshigher than four are desirable and confirm that the predictedmodels can be used to navigate the space defined by BBD.3.3. Interactive effects of factors on removal of COD and color

Three-dimensional graphical responses were generated on thebasis of the model equations to visualize the interactive effects ofthe factors on removal of COD and color from leachate. Theresponse surface plots for Pseudomonas sp. ISTDF1 and Phanerocha-ete sp. ISTL01 are shown in Figs. 1 and 2 respectively. These plotsillustrate the relative effects of any two factors by keeping the thirdfactor constant. In case of Pseudomonas sp. ISTDF1, COD removalefficiency was found to increase with increasing concentration ofdextrose, but for tryptone, it increased up to intermediate concen-trations after which there was a decline (Fig. 1A(i)). However, forremoval of color, decreasing the concentration of dextrose margin-ally along with intermediate concentrations of tryptone led tomaximal removal (Fig. 1A(ii)). Increasing the duration of treatmentalong with the dextrose concentration had a positive influence onremoval of both the responses (Fig. 1B). Fig. 1C shows the interac-tive effects of duration and tryptone concentration and suggeststhat intermediate tryptone concentration along with high durationtime results in increased removal of COD and color. Thus, theseplots suggest that the excessive supplement of nitrogen source

Table 2Analysis of variance for RSM variables fitted to quadratic model.

Micro-organism Response Source Sum of squares Degree of freedom (d.f.) Mean square F-value P-value Prob > F

Pseudomonas sp. ISTDF1 % COD removal Model 524.16 9 58.24003 68.6465

P. Ghosh et al. / Bioresource Technology 170 (2014) 1019 17conditions were dextrose = 1.13 g/L, yeast extract = 0.21 g/L andduration = 184.38 h leading to 55.76% COD and 31.59% colorremoval. Verification experiments carried out at optimum condi-tions confirmed the accuracy of the predicted model as the exper-imental values (Fig. S2) were found to be close to the predictedones with COD and color removal efficiencies of 44.11% and26.92% respectively for Pseudomonas sp. ISTDF1. In case of Phanero-chaete sp. ISTL01, COD and color removal efficiencies of 54.69% and30.65% respectively were observed. Without optimization of theprocess parameters, the removal of COD and color was 31.12%and 15.2% respectively for Pseudomonas sp. ISTDF1 and 40.71%COD and 27.98% color removal by Phanerochaete sp. ISTL01 after240 h of treatment. Thus, these results clearly indicate the impor-tance of process optimization via statistical experimental designfor enhanced removal of COD and color from landfill leachate.3.5. Sequential treatment of leachate in bioreactor

Leachate treatment in a sequential manner was first carried outat flask level to determine the best sequence for treatment. Resultsof the study indicated that maximum reduction in COD (71.32%)and color (41.12%) was obtained when the leachate was first trea-ted with Phanerochaete sp. ISTL01 followed by treatment withPseudomonas sp. ISTDF1. This sequence was finally used in scaleup studies. In the sequential bioreactor, reduction in COD and colorwas further increased to 76.9% and 45.4% respectively. A 35.6%reduction in lignin content was also observed. Similar studies havebeen carried out where the use of two or more micro-organisms in(A)

Treatment conditions

BaP 50 M UT FT FBT

Tail

Mom

ent

0

200

400

600

800

(B)

Fig. 4. Genotoxicity assessment of the contaminants prior and after treatment at differeagainst different samples. Tail moments of 40 randomly selected comets are presented asa solid line in the box represents the median value while dotted line represents meanoutlying points beyond 5th and 95th percentiles. Olive tail moments of the same 40 cdifferent classes of comets seen under fluorescent microscope after ethidium bromide sa sequential manner has been beneficial for the treatment ofeffluent as one could carry out the initial catabolic reactions andother could efficiently mineralize the organic compounds com-pletely (Kaushik et al., 2010; Singh and Thakur, 2006).3.6. Degradation analysis by GCMS

The chromatograms of the crude organic extracts UT, FT andFBT are shown in Figs. S3S5 respectively. The compounds presentin the extracts were identified on the basis of standard GCMSdatabase of the authentic compounds documented in NIST-05andWiley-8 libraries (Table 3). Results of the study clearly indicatethe degradation of organic contaminants like alpha-limonene diep-oxide (RT = 9.068), brominated dioxin-2-one (RT = 10.10), bisphe-nol-A (RT = 13.155) and nitromusk (RT = 12.217) and lignin foundin the UT sample. With the ongoing degradation, formation oflow molecular weight compounds like ethanediol (RT = 4.714), lac-tic acid (RT = 6.138), phenol (RT = 8.166) in the FT sample andhexadecanoic acid (RT = 10.494), acetophenone (RT = 11.617),octadecanoic acid (RT = 12.235) in the FBT sample clearly suggestlignin degradation by the strains (Shi et al., 2013). Along with theintermediates reported in lignin degradation, formation of phthalicacid (RT = 10.06) in both FT and FBT samples suggest degradationof other aromatic compounds present in the sample as well(Arias et al., 2008; Lpez et al., 2006). Presence of brominated com-pound (RT = 12.042) in the FT sample but not in FBT sample showsthe dehalogenation capability of the bacterial strain as previouslyreported by Das et al. (2012).MQ 0.5%

Oliv

e Ta

il M

omen

t

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50

100

150

200

250

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Tail MomentOlive Tail Moment

nt stages of the bioreactor. (A) The tail moment and the olive tail moment plottedquantile box plots. The edges of the box represent the 25th and the 75th percentiles;value. Error bars indicate 90th and 10th percentiles and the black circles indicateomets are shown as the mean standard deviation. (B) Representative images oftaining.

18 P. Ghosh et al. / Bioresource Technology 170 (2014) 10193.7. Genotoxicity analysis

Results of the comet assay for untreated (UT) and treatedleachate (FT and FBT) samples are shown in Fig. 4A and B. Basedon % DNA in tail, the comets were placed into different classes.HepG2 cells treated with the untreated (UT) leachate resulted in37.5% and 62.5% comets that fell under classes IV and V respec-tively. In the fungal treated (FT) leachate, the percentage of cometsfalling in class V was drastically reduced to 15%. More number ofcomets were found to belong to classes III (55%) and IV (30%). Afterthe sequential treatment by fungi and bacteria, a significant reduc-tion in genotoxicity was observed as the sample (FBT) resulted incomets belonging to classes I (20%) and II (80%). The comets withlower tail moments (1.3616 3.5982) were found to be morehomogeneous in the FBT sample as compared to the FT (165.4212 151.9378) and UT sample (417.111 195.2496) as shown by thequantile box plot in Fig. 4A. Compared to the negative control(0.5% v/v Milli-Q), all the samples except the FBT sample showedstatistically significant DNA damage (Dunnetts method p < 0.05)showing that the sequential treatment was efficient in genotoxicityreduction. The olive tail moment data was also found to decreasewith each step of sequential treatment and resulted in a 22-foldand 36-fold decrease in DNA migration (OTM = 4.0536 3.2548)in the FBT sample compared to the FT sample (88.4242 68.2753)and UT sample (OTM = 147.6991 66.41559) respectively. In ourprevious study (Ghosh et al., 2014), only a 7-fold decrease wasobserved after bacterial treatment under un-optimized conditionsshowing that both optimization of the nutrient media and sequen-tial treatment were extremely effective in genotoxicity removal.Higher values of % tail DNA, tail moment and OTM of the untreatedsample can be attributed to the additive action of various organiccontaminants like bisphenol-A, phthalate esters, dioxin-2-one andothers which accounted for high COD of untreated leachate. Forma-tion of toxic intermediary metabolites or increased bioavailabilityof native toxins over the course of bioremediation often leads tosubstantial increase in toxicity as documented by Lundstedt et al.(2003). However, in this case concomitant reduction in genotoxicitywas observed with the formation of low molecular weight com-pounds, removal of COD, color and lignin in each stage of bioreactorshowing the detoxification potential of the strains when used in asequential manner.4. Conclusions

Treatment of landfill leachate in a sequential bioreactor usingfungi and bacteria was an efficient and economic process capableof not only removing high percentage of COD (76.9%) and color(45.4%), but also genotoxicity of the effluent. Response surfacemethodology was successfully applied to optimize the nutritionalsupplements and duration of treatment to maximize the removalof COD and color. Further, the study ascertained that combiningchemical analyses with toxicological assay was helpful in deter-mining the efficiency of the treatment process for safe disposal oftreated leachate.Acknowledgements

Wewould like to express our sincere thanks to Council of Scien-tific and Industrial Research, Government of India, New Delhi, forproviding SRF (Ghosh P. and Swati). We also thank Dr. Ajai Kumar(Advanced Instrumentation Research Facility AIRF, JNU, NewDelhi) for GCMS analysis. We would also like to extend our sin-cere thanks to Dr. Mihir Tanay Das and Mr. Subhanjan Senguptafor their excellent technical assistance in preparing themanuscript.Appendix A. Supplementary data

Supplementary data associated with this article can be found, inthe online version, at http://dx.doi.org/10.1016/j.biortech.2014.07.079.

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Enhanced removal of COD and color from landfill leachate in a sequential bioreactor1 Introduction2 Methods2.1 Okhla landfill leachate characterization2.2 Microorganisms and inoculum preparation2.3 Culture conditions, COD removal and decolorization of leachate2.4 Optimization of process parameters experimental design, analysis and validation2.5 Stepwise treatment of landfill leachate under optimized conditions2.6 Analytical methods2.6.1 Measurement of COD, lignin and color2.6.2 Gas chromatography-mass spectroscopy analysis2.6.3 Alkaline single-cell gel electrophoresis (Comet assay)

3 Results and discussion3.1 Screening of the nutrient supplements3.2 Regression models and statistical testing3.3 Interactive effects of factors on removal of COD and color3.4 Validation of the model3.5 Sequential treatment of leachate in bioreactor3.6 Degradation analysis by GCMS3.7 Genotoxicity analysis

4 ConclusionsAcknowledgementsAppendix A Supplementary dataReferences