Observation of biogas production by sugarcane bagasse and food waste in different composition combinations

Energy 185 (2019) 1100e1105

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Observation of biogas production by sugarcane bagasse and food waste in different composition combinations Neelam Vats, Abid Ali Khan*, Kafeel Ahmad Department of Civil Engineering, Jamia Millia Islamia (A Central University), New Delhi, India

a r t i c l e i n f o

a b s t r a c t

Article history: Received 23 March 2019 Received in revised form 11 July 2019 Accepted 13 July 2019 Available online 18 July 2019

This paper present the results of a batch study on thermal-acid pre-treated sugarcane bagasse (SB) and food waste (FW) as the substrate with waste activated sludge (WAS) as inoculum. Experiments were conducted in six different batch reactors under ambient condition. Each batch reactor was fed with varied substrate ratio (mixture of SBþFW) maintaining inoculum constant (225 mL) to investigate the highest methane generation. The thermal acid pre-treated sugarcane bagasse (SB) with food waste at mixture ratio (SB: FW~ 35:65) had resulted the maximum biogas production of 7338 mL followed by (SB: FW ~ 50:50) - 6747 mL and (SB: FW ~ 100:0) - 4040 mL. The maximum reduction in Total Solids (TS) concentration was achieved 57% at mixture ratio of [SB: FW ~ 65:35] followed by 44%from [SB: FW ~ 85:15] and 41% from [SB: FW~100:0]. Thermal acid pre-treated sugarcane bagasse produced 81% higher biogas generation at mixture ratio of [SB: FW ~ 100:0], 63% at [SB: FW ~ 50:50] and 22% at [SB: FW ~ 35:65] and results obtained for biogas generation were modelled using Gompertz and logistic model and fitted well. © 2019 Elsevier Ltd. All rights reserved.

Keywords: Anaerobic digestion Biogas Sugarcane bagasse Thermal-acid pre-treatment

1. Introduction Sugarcane bagasse (SB) is found in abundance which is obtained from sugar industry after extraction of juice and it is almost 25% of the total processed sugarcane [15]. Sugarcane bagasse is considered a lignocellulosic biomass contains lignin, cellulose and hemicellulose. Recently, its demand increases in paper and pulp industries, fermentation products, animal feeds, ethanol production and biogas production etc. [13]. Since, SB residue contains sugar, lignin, cellulose and other products; it could be used as an enhanced alternative/additive for production for biogas generation using anaerobic digestion [16]. Biogas production from anaerobic digestion of various kind of organic fraction of wastes like food waste, fruit waste, poultry waste is a conventional technique and same can be applied to produce biogas using SB. Starch is easily biodegradable by the enzymes but lignin and cellulose are hardly biodegradable. The hardly biodegradable materials that are rich in lignin and cellulose content can be used for anaerobic digestion either pre-treating it or co-digestion with other organic waste. Different pre-treatment options physical, chemical, thermal and biological

* Corresponding author. E-mail addresses: [email protected], [email protected] (A.A. Khan). https://doi.org/10.1016/j.energy.2019.07.080 0360-5442/© 2019 Elsevier Ltd. All rights reserved.

can disrupt the lignin cell wall to activate the anaerobic microbes during anaerobic digestion [7, 8,16]. Acid pre-treatment helps in removal of lignin and cellulose from the substrates. Harun [10] observed acid pre-treatment method is mostly used for the substrates which have excess of carbohydrates. Rafique [14] reported disadvantages of acid pre-treatment due to generation of toxic compounds, unrecyclable reagents, and high energy demand. Various chemicals like sulphuric, hydrochloric, phosphoric, nitric, or maleic acids have been used in the acid pretreatment process. Reduction in lignin, cellulose and hemicellulose have been reported at molecular level in acid hydrolysis of SB. Reduction up to 92.78% was observed in hemicellulose content with improvement in efficiency of the process with sulphuric acid pre-treatment [2]. Thermal acid pre-treatment causes significant change in the structure and helps in improving the reactor performance [10]. The Food Waste (FW) is quite attracting and highly potential that can be used for co-digestion with SB for biogas production using anaerobic digestion [11]. It is generated from agricultural source, homes, canteen, and food processing industries, hotel and many other sources [9,10]. Present study investigates the effect of different composition combination on biogas generation using thermal acid pre-treated sugarcane bagasse with food waste.

N. Vats et al. / Energy 185 (2019) 1100e1105

2. Materials and methods 2.1. Collection and pre-treatment of samples The sugarcane bagasse was collected from sugarcane juice shops in plastic polybags. The food waste was brought from the home and college canteen and segregated for bones. The collected wastes were blended with a kitchen blender and stored in the refrigerator at 4  C till further process. The inoculum used in the present study was Waste Activated Sludge (WAS) collected from a Sewage Treatment Plant (STP) e 132 MLD capacity, New Delhi. Since the FW is rich in easily degradable organic matter and desirable for improving buffering capacity, balancing pH of the treatment system and SB is having higher contents of lignocellulosic substances that could greatly hinder the digestibility, the composition combinations were randomly prepared for better co-digestion of mixed substrates for biogas production and consequently for improved carbon and nutrient balance during anaerobic digestion [6,17]. Thermally acid pre-treatment was applied to the sugarcane bagasse with dilution before feeding into the reactors for batch study. Pre-treatment of the samples were done with the help of H2SO4 to bring down the SB slurry pH to 2.0 and after that it was kept overnight to neutralise the pH effect or to obtain a stable pH of the samples. After that the acidified samples were autoclaved for an hour at 120  C and 15 psi for thermal treatment. Samples were taken before and after the pre-treatment of sugarcane bagasse to evaluate the pH, volatile fatty acids (VFA), Carbon, Total solids (TS), Volatile solids (VS), Ammonia, Total COD, alkalinity. The food waste was also analysed for all these parameters.

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point titration method [5] and carbon as per the method given by Ref. [3]. All measurements were done in triplicate. Lignin, cellulose and hemicellulose were measured by the method described in Ref. [4]. The biogas was measured by water displacement method and temperature by using digital thermometer. Batch anaerobic tests and sample analysis were conducted in triplicate. 2.4. Statistical analysis procedure Statistical analysis was performed using one-way analysis of variance (ANOVA). Gompertz model (GM) and Logistic model (LM) were selected for the prediction of biogas [5,8]. GM and LM equations are shown below as (1) and (2) respectively. Both models were analysed with IBM SPSS statistics 22 and ANOVA was performed in Excel 2010. The kinetic coefficients Y, Rm and l parameters were estimated by the SPSS software.

   Rm  e ðl  tÞ þ 1 YðtÞ ¼ Y  exp  exp Y YðtÞ

(1)

Y   1 þ exp 4:RmðYltÞ þ 2

(2)

where, Y(t) ¼ cumulative biogas production in mL, Rm - maximum biogas production rate (mL d1), e-exp (2.718), l-lag phase time (d), Y- ultimate biogas production potential (mL). 3. Results and discussion

2.2. Digester design

3.1. Substrate and inoculum characteristics

Experiments were carried out in batch reactors of 500 mL capacity glass bottles with 450 mL effective volume. Six batch reactors were named as TAC0, TAC1, TAC2, TAC3, TAC4, and TAC5. The composition combination was summarized in Table 1. Different composition combination of thermal acid pre-treated SB and untreated FW were TAC0 (100:0), TAC1 (85:15), TAC2 (65:35), TAC3 (50:50), TAC4 (35:65), and TAC5 (15:85) respectively. The batch reactors were kept under ambient conditions for further study. Each batch reactor was initially inoculated with Waste Activated Sludge (WAS). All the batch reactors were placed in triplicate. The volume of biogas produced was measured by water displacement method. 2.3. Analytical methods All the substrates were analysed for their physical and chemical properties. pH, chemical oxygen demand (COD), volatile solids (VS), ammonia, Total solids (TS), and alkalinity were analysed as per procedure described in Standard Methods for the Examination of Water and Wastewater [1]. The VFA was measured according to 3-

The characteristics of sugarcane bagasse, food waste and waste activated sludge was shown in Table 2. The lignin, cellulose and hemicellulose obtained for SB were 18, 33 and 25% respectively. The highest TS and VS concentration were obtained in SB followed by FW and WAS. The carbon and COD were found maximum in FW and COD decreased subsequently in WAS and SB while carbon reduces accordingly in SB and WAS. The maximum VFA content can be observed in sugarcane bagasse (545 ppm) and FW (450 ppm). Table 3 shows the initial characteristics of substrates at different composition combinations/or mixture ratio for batch reactors TAC0, TAC1, TAC2, TAC3, TAC4 and TAC5. The pH for different substrates were ranged 6.73 ± 0.28 to 7.78 ± 0.11, however, and initial pH was in optimum range. Li [12] also reported similar results. The TS and VS concentration ranged from 5.37 to 8.45%, and 1e5.86%, respectively. The reported values are averages of triplicate analysis. The highest ammonia levels were observed in TAC3 (673.00 ± 44.31 mg/L) and lowest ammonia levels were observed in TAC0 (13.61 ± 7.02 mg/L). The results of the analysis showed that different composition combination of thermal acid pretreated substrates would serve as a good source of feedstock material for

Table 1 Composition of SB, FW and inoculum in batch reactors. Batch Reactor Codes

Substrate/Mixture Ratio (SB:FW)

Reactor Working Volume (mL)

Sugarcane Bagasse (mL) based on % Fraction

Food Waste (mL)

No. of Replications

TAC0 TAC1 TAC2 TAC3 TAC4 TAC5

100:0 85:15 65:35 50:50 35:65 15:85

450 450 450 450 450 450

225 191.25 146.25 112.50 78.75 33.75

0 33.75 78.75 112.50 146.25 191.25

3 3 3 3 3 3

*Inoculum was maintained constant (225 mL) in each batch reactor.

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Table 2 Characteristics of sugarcane bagasse, food waste and waste activated sludge. Parameters

pH

COD (g/kg)

Alkalinity (g/kg)

TS (%)

VS (% TS)

Carbon (%)

Organic Matter (%)

Nitrogen (%)

VFA (ppm)

FW WAS SB

4.74 7.23 6.02

127 78 18

1.120 0.647 6.500

7.72 4.56 8.68

3.58 3.18 6.82

50.56 22.39 34.03

88.07 39 59.22

2.78 2.32 1.01

450 ND 545

Table 3 Initial characteristics of substrates at different composition combinations. Parameters/Reactors

TAC0

TAC1

TAC2

TAC3

TAC4

TAC5

pH COD (g/kg) TS (%) VS (%) Ammonia (mg/L) Carbon

7.02 ± 0.02 59.33 ± 4.16 5.80 ± 0.43 2.41 ± 0.11 13.61 ± 7.02 1.24 ± 0.16

7.54 ± 0.05 100.00 ± 4 7.89 ± 0.56 3.49 ± 0.01 116.22 ± 3.37 1.51 ± 0.21

7.12 ± 0.06 114.00 ± 5.29 7.47 ± 0.44 4.05 ± 0.23 260.31 ± 26.65 2.89 ± 0.36

6.73 ± 0.28 205.33 ± 4.62 6.77 ± 0.51 1.07 ± 0.07 673.00 ± 44.31 3.11 ± 0.32

7.64 ± 0.17 13.50 ± 2.18 6.38 ± 0.36 3.46 ± 0.08 508.26 ± 53.70 1.33 ± 0.27

7.78 ± 0.11 195.00 ± 5.00 7.30 ± 0.31 5.56 ± 0.30 137.00 ± 15.34 11.40 ± 1.13

anaerobic digestion. 3.2. Effect of thermal acid pre-treated sugarcane bagasse and food waste on TS, VS and COD reduction at different composition combinations Fig. 1(aec) shows the pattern of reduction in TS (%), VS (%) and COD (mg/L) over the study period. Results indicate that the maximum reduction in TS was achieved 57% with composition combination of SB: FW~ 65:35 and subsequently decrease in TS (%) reduction was observed in all reactors with composition combinations as SB; FW ~ 85; 15 - TAC1 (44%), 100:0 e TAC0 (41%),50:50 TAC3 (34%), 35: 65 - TAC4 (28%) and 15: 85 - TAC5 (27%) respectively (Fig. 1-a). Fig. 1 (b) shows the VS reduction pattern. The VS is considered an important parameter to know the fate of anaerobic digestion of a system which indicates the degree of biodegradation and metabolic status. Results of this study show that the lowest VS removal of 34% was observed in reactor (TAC4) having composition combination of

SB: FW ~35:65. The characteristics of the composition might be the reason of poor biodegradability, however, a significant reduction was found in other batch composition combinations of SB: FW ~100: 0 - TAC0 (55%), SB: FW ~85:15 - TAC1 (55%), SB: FW ~65: 35 TAC2 (40%), SB: FW ~50:50 - TAC3 (37%), SB: FW ~35:65 - TAC4 (34%) and SB: FW ~15:85 - TAC5 (42%). Fig. 1 (c) shows the reduction of COD pattern. Maximum initial COD was obtained in TAC3 followed by TAC5. Results indicate that the maximum reduction in COD was achieved in TAC2 (64%) with composition combination of SB: FW ~ 65:35 and a subsequent reduction in COD was observed in reactors filled with composition combination, SB: FW ~ 85: 15 - TAC1 (63%), 100:0 e TAC0 (62%), 50:50 - TAC3 (50%), 35: 65 - TAC4 (10%) and 15: 85 - TAC5 (7%) respectively. Results inferred that the TS and COD were reduced linearly in all batch reactors, however, a different trend for biogas generation was observed. The highest biogas generation was achieved at composition combination SB: FW ~35: 65 (TAC4) irrespective of highest TS and COD reduction with SB: FW ~ 65: 35 (TAC2).

Fig. 1. (aec) Initial and final TS (%) and VS (%) and COD (mg/L) changes.

N. Vats et al. / Energy 185 (2019) 1100e1105

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Fig. 2. (aec) pH, carbon and ammonia yield.

3.3. Effect of thermal acid pre-treated sugarcane bagasse and food waste on pH, ammonia and carbon at different composition combinations Fig. 2 (a) shows the variation of pH throughout the anaerobic digestion for a period of 30d. Results revealed that the pH required for stable anaerobic digestion dropped to lower than 6.8 from initial value 7.02 for SB: FW ~100:0 composition combination on 10th day of digestion and it regain until the end of digestion. For all batch reactors TAC1, TAC2, TAC4 and TAC5, the pH value was observed in desired range for anaerobic digestion with zig zag pattern except for the reactor with composition combination of SB: FW ~50:50 (TAC3), pH values measured 6.55 on 3rd day of digestion but it rises

Table 4 One-way anova results for different parameters. Parameters

p value

F value

pH Carbon Ammonia Daily Biogas Yield Cumulative Biogas Yield

<0.05 <0.05 <0.05 <0.05 <0.05

14.21 10.22 13.31 17.03 7.45

to desired range (pH > 7) until experiments terminated. The drop in pH might be the production of VFA during thermal treatment. The variation of ammonia concentration was shown in Fig. 2 (b). The ammonia levels in reactors TAC1, TAC0 and TAC2 were lower than 1000 mg/L. Results referred that a continuous decrease in ammonia level was observed for composition combination SB: FW ~65:35 (TAC2). For composition combination SB:FW ~50:50 for reactor TAC3, ammonia increased drastically to 2261 mg/L on 15th day but a dip was observed after it and reduced till the end of experiments. For reactors TAC3, TAC4 and TAC5, there was significant increase in the ammonia levels till the end of digestion leading to ammonification in the reactors and may slow/or inhibit the methanogenesis activity. Previous studies have shown that the biogas production do not ceased even at ammonia concentration up to 4000 mg/L [18,19]. Results of the present study indicate the stable digestion up to 2200 mg/L until experiments terminated. As long as the ammonia concentration was in suitable range, no adverse affect on methanogenesis was observed. The error bars in figures showed the standard deviation for triplicate sample results. Fig. 2(c) shows the results for carbon pattern in reactors TAC0, TAC1, TAC2, TAC3, TAC4 and TAC5. The highest carbon (%) was observed in reactor TAC5 with composition combination SW: FW ~ 15:85. The carbon content increases with an increase in food

Fig. 3. (aeb) Daily and cumulative biogas production (mL/g VSinitial) at different composition combination.

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3.4. Effect of thermal acid pre-treated sugarcane bagasse and food waste on biogas production at different composition combinations

Table 5 Kinetic coefficients estimated from Gompertz model and Logistic model. Gompertz Model

Logistic Model

Reactors

Y (mL)

l (d)

Rm (mL)

Y (mL)

l (d)

Rm (mL)

TAC0 TAC1 TAC2 TAC3 TAC4 TAC5

448.37 195.84 103.88 1494.06 594.68 161.1

2.57 4.91 3.75 6.20 4.59 5.29

22.33 5.20 5.90 86.40 21.70 8.09

1151.3 432.07 292.98 4169.71 1496.1 439.07

23.49 25.61 16.67 18.66 21.81 19.11

73.04 17.24 18.61 281.2 73.82 26.82

waste fraction in composition combination in different batch reactors. The higher carbon content proliferate the biodegradability in the reactors. The regression coefficient was greater than 0.80 for all the reactors. The error bars in graphs represents the standard deviation for triplicate samples. The ANOVA results for pH, ammonia and carbon are shown in Table 4.

Fig. 3(a and b) represents the daily and cumulative biogas production for six batch reactors at different composition combinations. The highest biogas production was achieved at composition combinations SB: FW ~35:65 (TAC4 - 7338 mL) followed by SB: FW ~ 50:50 (TAC3 - 6747 mL), SB: FW ~ 100:0 (TAC0 - 4040 mL), SB: FW ~ 15:85 (TAC5 - 3710 mL), SB: FW ~ 100:0 (TAC1 - 2070 mL) and SB: FW ~ 65:35 (TAC2 - 1906 mL). Results indicate that the reactor TAC0 with SB:FW ~100:0 (sugarcane bagasse alone) produced biogas of 4040 mL which is quite higher in amount with respect to the biogas obtained from untreated sugarcane bagasse. In TAC0, TAC2, TAC3 and TAC1 biogas production did not started till 6th, 3rd, 3rd and 2nd day of anaerobic digestion due to non-availability of readily biodegradable organic material and after that it continually started increasing with a zig zag pattern. Maximum daily biogas production between 12 and 19th d of digestion in all batch reactors indicates maximum anaerobic activity during this period. Daily maximum biogas observed for TAC0 (320 mL), TAC1 (140 mL), TAC2

Fig. 4. (aef): Comparison of experimental biogas production with predicted from Gompertz (GM) and Logistic Model (LM).

N. Vats et al. / Energy 185 (2019) 1100e1105

(180 mL), TAC3 (520 mL), TAC4 (560 mL) and TAC5 (270 mL) on 16th, 19th, 12th, 17th, 16th and 16th day respectively. Higher biogas yield in TAC4 could be attributed due to thermal acid pre-treated sugarcane bagasse and illustrate the possibility of improving biogas yield from SB with addition of 65% FW. Cumulative biogas in terms of mL/g VS initial (1404) was highest in reactor TAC3 followed by (470.7) TAC4, (373) TAC0, (148.4) TAC5, (131.9) TAC1 and (104.7) TAC2 respectively. The reactor TAC3 with highest ammonia levels shows that ammonia was not affecting the process and helped to attain stability in the system. The regression co-efficient was calculated greater than 0.8 for all the biogas experimental data. 3.5. Model fitting and regression analysis GM and LM models were applied on the experimental results of biogas production to predict and estimate the kinetic coefficients for anaerobic digestion of SB with co-substrates. The experimental data and predicted values of the kinetic coefficient estimated using both models (GM and LM) were reported in Table 5. Fig. 4(aef) shows the plot of the experimental and modelled values of the biogas produced using GM and LM models. Results indicate that the biogas produced experimentally were well supported using Gompertz and Logistic Model as insignificant deviation observed in experimental and modelled values. The predicted biogas from both models shows a higher correlation coefficient (R2 > 0.92), indicate goodness of experimental data with both models (see Table 5). 4. Conclusions The present study investigates the biogas production using thermal acid pre-treated SB and untreated FW with WAS as an inoculum under different composition combinations. Results inferred that the carbon (%) increased upon increasing the proportion of food waste in various composition combinations in batch reactors. The pH was achieved in the desired levels in all reactors except for composition combination SB: FW ~100:0 - TAC0 where levels dropped to lower than 6.8. The increased ammonia levels did not interrupt biogas production under any composition combination Maximum biogas generation was obtained for composition combination SB: FW ~35:65 TAC4 (7338 mL) followed by TAC3 (6747 mL) and TAC0 (4040 mL). Results of this study were statistically significant for pH, ammonia, carbon and biogas production with p < 0.05 and has high correlation co-efficient of 0.80. Experimental results were well supported using Gompertz and Logistic models for cumulative biogas generation since no deviation observed in modelled and experimental values. Conflict of interest All authors agree to submit the manuscript in the Journal Energy and allowed Dr Abid Khan as a corresponding author.

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