Development of Mathematical Models and Application of the Modified Gompertz Model for Designing Batch Biogas Reactors Chukwutem Newton Etuwe, Yusuf Omodia Lucky Momoh & Elijah Tamuno Iyagba Waste and Biomass Valorization ISSN 1877-2641 Waste Biomass Valor DOI 10.1007/s12649-016-9482-8
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Author's personal copy Waste Biomass Valor DOI 10.1007/s12649-016-9482-8
ORIGINAL PAPER
Development of Mathematical Models and Application of the Modified Gompertz Model for Designing Batch Biogas Reactors Chukwutem Newton Etuwe1 • Yusuf Omodia Lucky Momoh1 • Elijah Tamuno Iyagba2
Received: 17 May 2015 / Accepted: 19 January 2016 Ó Springer Science+Business Media Dordrecht 2016
Abstract Biogas is a combustible gas produced by the anaerobic digestion of organic matter (biomass) in the absence of oxygen. In this study, mathematical models for the design of batch anaerobic biogas reactors for digesting cattle dungs at ambient temperatures (30 ± 3 °C) were developed. Biogas productions from five (5) reactors with varying mass of total solids were monitored for a period of 42 days. It was observed that optimal biogas yield (yt) occurred at volatile solids concentration in the range of 60.0–80.0 g VS/L, which corresponds to 8.0–10.0 % total solids. Optimum biogas yield rates were between 1.44 and 1.64 ml/g VS/day. The modified Gompertz model was used in predicting maximum biogas yield (ym), maximum biogas yield rate (Rm), the minimum time taken to produce biogas (k), and these were found respectively to be between 68 and 86 ml/g VSloaded, 2.50–2.97 ml/g VSloaded/day and 9.7–12.0 days with goodness of fit ranging from 0.996 to 0.999. A relationship between maximum biogas yield potential and volatile substrate concentration was established to be ym = -0.0266[VS]2 ? 4.8396[VS] ? 129.1. An appropriate application of the developed models would lead to an optimal design of a biogas plant digesting cattle/ livestock dungs with biogas and organic fertilizers production for farmers and gardeners alike.
& Chukwutem Newton Etuwe
[email protected] 1
Department of Environmental Engineering, Faculty of Engineering, University of Port Harcourt, P.M.B. 5323, Port Harcourt, Nigeria
2
Department of Chemical Engineering, Faculty of Engineering, University of Port Harcourt, P.M.B. 5323, Port Harcourt, Nigeria
Keywords Cattle dung Abattoir Batch reactor Biogas production/yield Renewable energy
Introduction The need for biofuels is steadily increasing because of the problems associated with fossil fuel consumption, energy security and formulation of policies favouring the development of renewable energy technology. One means of achieving this is through the bioconversion of organic based materials in a system known as a biorefinery. Biorefineries have the potentials of improving the sustainability of biofuels through the production of bioenergy (biogas) and further recovery of valuable by-products (e.g. biofertilizers) [1]. Several organic matters commonly known as substrates or feedstock e.g. animal dungs (cattle, goat, sheep, pig, poultry, horse, etc.), plant/agricultural byproducts (waste paper, rice husks, straws, corn, sugarcane, water hyacinth, etc.), wastewater and solid waste have been shown to be viable for biogas production [2–8]. In this study, cattle dungs collected from an abattoir were used as feedstock in batch bioreactors. Abattoirs also known as slaughter houses are places where animals (e.g. cattle, horse, sheep, goat, pig, poultry, etc.) are slaughtered and processed for sales to neighbouring communities on a regular basis. Preliminary survey and elementary reconnaissance on several abattoirs within the Port Harcourt metropolis of Rivers State, Nigeria revealed that the capacities (sizes) of abattoirs vary considerably depending on the location and the population they serve. Some abattoirs hold as little as 5 cattle per day while others could hold as much as 180 cattle per day. Furthermore, it was also gathered that cattle dungs were washed and discharged directly into adjoining water
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bodies. The outcome of this indecent act is a multidimensional environmental problem due to pollution and contamination of the immediate and extended environment. Cattle dung contains pathogens that can be infectious to humans when ingested from drinking polluted water [6]. It is also known to be rich in nutrients such as nitrate and phosphate that may lead to eutrophication of slow flowing surface waters. Additionally, a large quantity of wood is being burnt while processing the slaughtered animals, giving rise to deforestation and air pollution. In recent times, several researches supported the application of anaerobic digestion of organic matter as an appropriate technology for potential renewable energy (e.g. biogas) and nutrient rich fertilizer recovery, sustainable waste management and pathogen destruction [9– 12]. Anaerobic digestion produces lesser pollutants and greenhouse gases than some other waste treatment techniques such as incineration [13], composting [14], and landfilling [15]. It is mainly used for stabilization (treatment) of organic wastes and production of energy in the form of biogas [10, 11, 16]. In an oxygen free environment through the process of hydrolysis, acidogenesis, acetogenesis and methanogenesis, anaerobic microbes such as fermentative bacteria, acetogenic bacteria and methanogenic bacteria, digest biodegradable organic matter into high energy biogas with methane (50–70 %) as potential energy content, carbon dioxide (30–40 %) and other gases such as H2, N2, H2S and O2 in small amount [3, 11, 13, 15, 18]. Anaerobic digestion process for biogas production could be carried out in batch, plug flow and complete mix reactors, with each having its benefits over the other. Batch reactors are gaining widespread application probably because they are easy and cheap to construct, operate and maintain [3, 19–23]. Therefore, its choice in design model development cannot be overemphasised. The aim of this study was to develop optimized mathematical models, which when applied in conjunction with the modified Gompertz model, would be used as an alternative method for the design and development of batch reactors for biogas production from cattle/livestock dungs in abattoirs.
these cattle per day and the moisture contents of the dung, must first be determined. This could be obtained by estimating the number of cattle an abattoir receives on a daily basis and the amount of dung produced per cattle per day. Usually, an adult cow as often transported to a city or metropolitan abattoirs produces a certain amount of dung daily [20, 24]. Thus, the mass of total solid (TS) in it could be estimated according to Eq. (1). MTS ¼ ð1 wÞMDung ;
MTS ¼ ð1 wÞnMDung
ð2Þ
Hence, the total amount of dry matter/cow dung obtainable from an animal barn becomes; MTS ¼ ð1 wÞnNMDung
ð3Þ
where N represents the number of days of cow dung accumulation before digestion. Therefore, the mass of volatile solid (VS) obtainable in a typical abattoir holding/barn becomes: MVS ¼ fVS MTS
ð4aÞ
MVS ¼ ð1 wÞnNfVS MDung
ð4bÞ
where fVS represents the fraction of VS in a mass of cow dung. Sizing the Biodigester Let qTS and x be the dry density and % (w/w) of total solid (TS) in the digester respectively; Then, VTS ¼
MTS qTS
ð5Þ
where (VTS) represents the volume of total solid in the digester; and (noting that 1 ml of water weighs 1 g), x MTS ¼ 100 MTS þ Vw For which,
Total and Volatile Solids Estimation for a Typical Abattoir
Vw ¼
123
ð1Þ
where w (w/w), represents the moisture content (expressed as a fraction of water) in the sample, MDung represents the mass of dung produced per cow per day and MTS represents the amount of dry matter (total solids, TS) in the dung. For an abattoir receiving n number of cattle per day
Mathematical Methods/Model Development
In order to effectively design biogas reactors for digesting cattle/livestock dungs in abattoirs, the amount of volatile solid (VS) which is a function of the number of cattle received by an abattoir, the quantity of dungs excreted by
w\ 1
MTS ð100 xÞ x
ð6Þ
ð7Þ
where Vw is the volume of water in the digester. Note that Vw consists of two components: (1) the volume of water/moisture (Vm) in the dung, and (2) the volume of water required (VwR) to dilute the substrate to the required concentration.
Author's personal copy Waste Biomass Valor
Therefore, wMTS qTS
Vm ¼ wVTS ¼
ð8aÞ
and VwR ¼ Vw Vm
ð8bÞ
Substituting Eqs. (7) and (8a) into Eq. (8b) and simplifying further, one obtains, 100 x w VwR ¼ MTS ð9Þ x qTS Therefore, the working volume of digester VD becomes, VD ¼ VTS þ Vw
ð10Þ
Substituting Eqs. (5) and (7) into Eq. (10) and collecting like terms 100 x 1 þ VD ¼ MTS ð11Þ x qTS By dividing Eq. (9) by Eq. (11), VwR ¼ VD
100x x 100x x
þ
w qTS 1 qTS
¼ Rv
ð12Þ
where Rv is a dimensionless ratio, which also represents the fraction of dilution water in the digester. In the anaerobic digestion of organic feedstock, one of the most important parameters to look out for is the volatile solid concentration. Mathematically, the concentration of volatile solid [VS] in the digester can be represented by, ½VS ¼
MVS VD
fVS þ q1
ð14Þ
TS
Sizing the Gas Chamber: An Application of the Modified Gompertz Model Biogas yield (yt) is defined as the ratio of the volume of gas produced to the mass of volatile solid loaded. Mathematically, Volume of gas produced VG ¼ mass of volatile solid loaded MVS
ð15Þ
Therefore, VG ¼ yt MVS
It is pertinent to note that Eq. (18) represents the cumulative volume of gas produced after time t (say at the end of a production day). The daily volume of gas produced is obtained by subtracting the volume of gas produced at t-1 from that produced after time t, i.e. VG ¼ VGðtÞ VGðt1Þ ðLÞ:
ð19Þ
where VG represents the daily gas production. The maximum value of Eq. (19), VG(max) represents the maximum volume of gas produced daily and it is the key parameter in designing the gas chamber.
Materials and Methods
100x x
yt ¼
where yt represents the experimental/predicted biogas yield (L/kg VS) obtainable after time t, ym represents the maximum biogas yield potential (L/kg VS), Rm represents the maximum biogas production rate (L/kg VS/day), k represents the lag phase or minimum time taken to produce biogas (days), and e = 2.718281828. The unknown variables ym, Rm and k could be determined by non-linear regression analysis. Substituting Eq. (17) into Eq. (16), Rm e VGðtÞ ¼ ym MVS EXP EXP ðk t Þ þ 1 ð18Þ ym
ð13Þ
Substituting Eqs. (4a) and (11) into Eq. (13) and further simplifying yields, ½VS ¼
where VG represent the volume of gas produced and MVS represents the mass of volatile solid loaded. The modified Gompertz kinetic model (Eq. 17) has been widely used in prediction biogas production from the anaerobic digestion of dung slurry [21, 23, 25–27]. Rm e yt ¼ ym EXP EXP ðk t Þ þ 1 ð17Þ ym
ð16Þ
Substrate Collection and Preparation The substrate collection was in accordance with the methods applied by [3, 11, 23]. About 5 kg of fresh cow dung was collected from an abattoir is Choba community in Port Harcourt, Rivers State, Nigeria. The dung was air-dried for 21 days to preserve its microbial population. The stomach chambers of ruminant animals such as cattle, goat, sheep, horse, etc. are known to contain microbes that are required for digestion of their dung under anaerobic conditions [6]. As such, no addition of inoculum was required. The dried dung was then crushed with mortar and pestle to ensure homogeneity and subsequently analysed for moisture, volatile solid, carbon and nitrogen contents according to [28] using an English made muffle furnace-Carbolite model LMF 4. The respective moisture, volatile solid, carbon and nitrogen contents were found to be 14.2, 70.40, 7.14 and 0.28 % per
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mass of TS. Thus, the carbon to nitrogen ration was calculated to be about 25.50. Experimental Procedures Biogas production from cow dung was studied in five (5) anaerobic digesters labelled OP1–OP5 at ambient temperatures and in accordance with the methods described by [3, 17, 23]. An electronic weighing balance Mettler model PN163, manufactured in Switzerland with specification range between 0.10 mg and 500 g was used in weighing the dried dung. Thereafter, the dung was mixed with 250 ml of water inside a 500 ml Buckner flask and corked to exclude air, thereby creating the anaerobic condition required for biomethenation of biomass. The total solid concentration ranged from 8 to 10 % at 0.5 increments as suggested by [29] for low solid loading. The set up was monitored for forty-two (42) days at an ambient temperature with a mean value of 30 ± 3 °C. Within Port Harcourt metropolis the mean annual temperature ranges from 22.54 to 31.03 °C [30]. The procedure was stopped when gas production reduced significantly and in some cases when it stopped completely. The reactors were agitated once daily and biogas production was measured by brine displacement method [11, 12]. Figure 1 shows the cumulative biogas yield from the five (5) digesters.
Results and Discussion Effects of Total Solid on Biogas Yield In this study, it was observed that biogas production (yield) tend to follow the general sigmoid function (S-curve) as
shown in Fig. 1. A similar pattern was observed by [6, 10, 11, 17, 21, 22, 26]. This arises from the specific growth rate pattern of methanogenic bacteria in batch reactors. Gas production was delayed at the beginning due to the slow growth (lag phase) of methanogenic bacteria. After about 2–4 days, gas production began rapidly due to the exponential growth of microorganisms in the reactor. However, gas production started declining after about 28–32 days. At this stage, microbial growth could be predicted to be in the stationary phase (i.e. death rate is in equilibrium with growth rate). At about 42 days of incubation, biogas production dropped significantly and stopped completely is some reactors. This could be attributed to the decline in the population of methanogens because of the decline or complete exhaustion of the limiting nutrient. In all five reactors, biogas yields were observed to increase with increasing total solid (TS) concentrations. The minimum cumulative biogas yield was recorded in digester OP1 containing 8.0 % TS while the maximum value was measured in digester OP5 containing 10.0 % TS (Fig. 1). This is in agreement with the work of [6]. Model Calibration and Accuracy The modified Gompertz model was calibrated using experimental data. The parameters: ym, Rm and k we estimated using the non-linear regression approach made possible by the Solver ToolPak of Microsoft Excel 2013. The modified Gompertz model fitted/predicted the experimental data with over 99 % accuracy (R2 = 99.6–99.9 %). Similar levels of accuracy were observed in the works of [22, 26]. Kinetic Study of Anaerobic Degradation Process
Cumulative biogas yield (ml/g VS)
80
OP1 (8.0%)
70
OP2 (8.5%) OP3 (9.0%)
60
OP4 (9.5%) 50
OP5 (10.0%)
40 30 20 10 0 0
10
20
30
40
50
Hydrualic retention time (days)
Fig. 1 Comparative plot of cumulative biogas yield from digesters OP1–OP5
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Experimental biogas yield (yt-exp) from the five digesters ranged from 60.45 to 66.82 ml/gVS averaging at about 64.71 ± 1.61 ml/g VSloaded. The predicted biogas yield (yt-pred) based on the modified Gompertz model ranged from 63.26 to 70.98 ml/g VS with an average of 67.24 ± 1.71 ml/g VSloaded. Also, the maximum biogas yield potentials (ym) were found to be between 68.51 and 86.78 ml/g VSgVSloaded and the average value was 78.02 ± 3.58 ml/g VSloaded. As for the maximum biogas yield rate (Rm), the values ranged from 2.50 to 2.97 ml/g VSloaded/day with an average value of 2.73 ± 0.09 ml/g VSloaded/day. Finally, the lag phase (i.e. the time between experimental setup and actually biogas production) was between 9.73 and 12.01 days with an average value of about 10.93 ± 0.43 days. In all five digesters, the coefficient of determination (goodness of fit), R2 of the modified Gompertz model ranged from 99.6 to 99.9 %, with an average value of 0.9971 ± 0.0005. It was observed that
Author's personal copy Waste Biomass Valor Fig. 2 Relationship between volatile solid concentration and maximum biogas yield potential
100
ym = -0.0266[VS]2+ 4.8396[VS} -129.1 R2 = 0.9168
Max. biogas yield potential, ym (ml/g VSloaded)
90 80 70
ym 60 50 40 30 20 10 0 55
60
65
70
75
80
Volatile solid Conc. (g/L)
Fig. 3 Relationship between TS, %TS and working volume of digester
7.0% TS
7.5% TS
8.0% TS
8.5% TS
9.0% TS
9.5% TS
10.0% TS
10.5% TS
11.0% TS
11.5% TS
16000
Decreasing %TS @ 0.5
Working volume of digester , VD (ml)
15000 14000 13000 12000 11000 10000 9000 8000 7000 6000 5000 4000 3000 2000 1000 0
0
100
200
300
400
500
600
700
800
900
1000
Mass of total soild (g)
amongst all five digesters the highest experimental biogas yield of 68.82 ml/g VSloaded was recorded in digester OP5 which contained 10.0 % TS, while the highest predicted biogas yield of 70.98 ml/g VSloaded was recorded in digester OP4, which contained 9.5 % TS. The highest value of maximum biogas yield potential of 86.78 ml/g VSloaded was recorded in digester OP5 and the highest
maximum biogas production rate of 2.87 ml/g VSloaded was observed in digester OP4. Finally, the maximum lag of 11.57 days was recorded in digester OP5. In all five digesters, the modified Gompertz model best fitted the biogas data of digester OP5. Through the methods of nonlinear regression analysis (executed with Microsoft Excel 2013 Trendline Function), the maximum biogas yield
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Author's personal copy Waste Biomass Valor Fig. 4 Relationship between moisture content (%), %TS and RV. Volume of water required Rv ¼ Working volume of digester
7.0% TS
7.5% TS
8.0% TS
8.5% TS
9.0% TS
9.5% TS
10.0% TS
10.5% TS
11.0% TS
11.5% TS
0.925 0.900 0.875
Decreasing %TS @ 0.5
Rv =VwR/ VD
0.850 0.825 0.800 0.775 0.750 0.725
0
5
10 15 20 25 30 35 40 45 50 55 60 65 70 75 80 85 90 95 100
Moisture content (%)
potential (ym) was found to be related to the volatile solid concentration according to Eq. (20) with a goodness of fit (R2) of 0.9168 (Fig. 2). ð22Þ
Model Limitations and Application Equations (1)–(3) and (4b) are strictly for estimating the amount of dungs accumulated from cattle/livestock in an abattoir over time. These are basic for the determination of the mass of total solids (MTS). It is pertinent to note that before embarking on the design of reactors, experimental procedures should be carried out with dung samples from a typical abattoir/specific livestock species for the purpose of determining ym, Rm and k according to Eq. (18). In this way, misleading results that might arise from generalisation/estimation of design parameters could be eliminated. For design purpose, a family of curves have been produced from Eqs. (10), (13), and (14) see Figs. 3, 4 and 5 respectively. Theses curves, when combined with Eqs. (18)– (20), would lead to the design of an optimal biogas plant consisting of a bioreactor and a gas holder. Design of Biogas Plant for Abattoirs The choice of the design adapted here is that in which the gas hold is separated from the biogas digester. Authors
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8.0% TS
8.5% TS
9.0% TS
10.0% TS
10.5% TS
11.0% TS
11.5% TS Decreasing %TS @ 0.5
ym ¼ 0:0266½VS þ4:8396½VS 129:1
7.5% TS
9.5% TS
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Volale solid conc. [VS], g/L
2
7.0% TS
100 80 60 40 20 0
0
10
20
30
40
50
60
70
80
90
100
Volale solid, fvs (%) Fig. 5 Relationship between x (%TS), fVS and volatile solid concentration
[20] and [24] reported that the average amount of dung produced by a head of cow on a daily basis ranges from 9 to 15 kg, while the average density of the dried cow dung was found to be about 680 kg/m3. The dung in the form of slurry would be fed into the reactor with pumps if the plant is built above the surface of the ground. Otherwise, gravity flow should be employed when the system is built below ground surface.
Author's personal copy Waste Biomass Valor Table 1 Summary of design parameters
Parameters
Value
Units
Assumptions No. of cattle in abattoir per day, n
12
Mass of cattle manure, MDung
10
kg/cow/day
Density of dry dung, qTS
550
kg/m3
Moisture content of fresh cattle manure, w
80
%
Manure accumulation time, N
42
days
Fraction of volatile solid in manure, fvs
70
%
Total solid content of substrate, x
9
%
Factor of safety, FS
10
%
Mass of total solid, MTS
1008.00
kg
Volume of total Solid, VTS
1832.73
L
Mass of volatile solid, MVS
705.60
kg
Total volume of water, Vw
10,192.00
L
Volume of slurry Working volume of reactor, VD
12,024.73 13,227.20
L L
VD
13.23
m3
Concentration of VS
69.22
g VS/L (kg VS/m3)
Max. biogas production potential, ym
78.44
L/kg VS (m3/kg VS)
Max. daily biogas production, VG
1925.57
L/day
VG
1.926
m3/day
Dimensions of gas chamber
D:h = 1:3
0.93:2.80 m
Design estimates from developed design models
D/h ratio
Choosing digester dimensions Base diameter D (m)
Tank height h (m)
1.0 1.5
2.56 2.93
2.56 1.96
2.0
3.23
1.61
2.5
3.48
1.39
3.0
3.70
1.23
Design Parameters
Volume of biogas produced (L)
2250
Assumptions Let MDung = 10 kg/cow/day, n = 12 cows, N = 42 days, fVS = 70 % = 0.7 and w = 80 % = 0.8. Table 1 shows a summary of the biogas tank design. Figure 6 is a plot of daily biogas production from a plant designed with the parameters of Table 1. The maximum daily biogas production was found to be 1925.57 L.
Daily biogass production
2000 1750 1500 1250 1000
Conclusions
750 500 250 0 0
10
20
30
40
50
60
Time (days)
Fig. 6 Daily biogas productions from a single unit biogas plant
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Anaerobic digestion offers a clean and cheap technology for the production of biogas from organic substrates such as cow dungs. The quantity of dungs accumulated in abattoirs due to the amount of cattle they receive is large enough for the development of biogas reactors in situ. The ambient temperatures within Port Harcourt and other cities in Nigeria are appropriate for the anaerobic digestion of cattle dungs as a
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means of waste management with gas production. This could supplement or completely meet the daily energy requirements for abattoirs. Furthermore, the applicability of the modified Gompertz model in the design of batch biogas reactor has been revealed in the study. Most importantly, the appropriate application of the developed models would lead to an optimal design of a biogas plant digesting cattle/livestock dungs with biogas and organic fertilizers production for farmers and gardeners alike.
References 1. Boldrin, A., Balzan, A., Astrup, T.: Energy and environmental analysis of a rapeseed biorefinery conversion process. Biomass Convers. Biorefinery. 3(2), 127–141 (2013) 2. Ramachandra, T.V.: Geographical information system approach for regional biogas potential assessment. Res. J. Environ. Sci. 2(3), 170–184 (2008) 3. Momoh, O.L.Y., Nwaogazie, I.L.: The effect of waste paper on the kinetics of biogas yield from the co-digestion of cow dung and water hyacinth. Biomass Bioenergy. 35, 1345–1351 (2011) 4. Umeghalu, C.E., Chukwuma, E.C., Okonkwo, I.F., Umeh, S.O.: Potentials for biogas production in Anambra State of Nigeria using cow dung and poultry droppings. Int. J. Vet. Sci. 1(1), 26–30 (2012) 5. Kunatsa, T., Madiye, L., Chikuku, T., Shonhiwa, C., Musademba, D.: Feasibility study of biogas production from water hyacinth: a case of lake Chivero-Harare, Zimbabwe. Int. J. Eng. Technol. 3(2), 119–128 (2013) 6. Momoh, Y.O.L., Anyata, B.: Application of simplified anaerobic digestion models (SADM’s) for studying the biodegradability and kinetics of cow manure at ambient temperature. Leonardo Electron. J. Pract. Technol. 23, 23–36 (2014) 7. Kiran, E.U., Trzcinski, A.P., Ng, W.J., Liu, Y.: Enzyme production from food wastes using a biorefinery concept. Waste Biomass Valorization. 5(6), 903–917 (2014). doi:10.1007/ s12649-014-9311-x 8. Diener, S., Solano, N.M.S., Gutierrez, F.R., Zurbrugg, C., Tockner, K.: Biological treatment of municipal organic waste using black soldier fly larvae. Waste Biomass Valorization. 2, 357–363 (2011). doi:10.1007/s12649-011-9079-1 9. McCarty, P.L.: The development of anaerobic treatment and its future. Water Sci. Technol. 44, 149–156 (2001) 10. Mahnert, R., Linke, B.: Kinetic study of biogas production from energy crops and animal waste slurry: effect of organic loading rate and reactor size. Environ. Technol. 30(1), 93–99 (2008) 11. Li, J., Jha, A.K., He, J., Ban, Q., Chang, S., Wang, P.: Assessment of the effects of dry anaerobic co-digestion of cow dung with waste water sludge on biogas yield and biodegradability. Int. J. Phys. Sci. 6(15), 3679–3688 (2011) 12. Surendra, K.C., Takara, D., Jasinski, J., Khanal, S.K.: Household anaerobic digester for bioenergy production in developing countries: opportunities and challenges. Environ. Technol. 34(13–14), 1671–1689 (2013)
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13. Oliveira, L.B., Rosa, L.P.: Brazilian waste potential: energy, environmental, social and economic benefits. Energy Policy. 31, 1481–1491 (2003) 14. Walker, L., Charles, W., Cord-Ruwisch, R.: Comparison of static, in-vessel composting of MSW with thermophilic anaerobic digestion and combinations of the two processes. Bioresour. Technol. 100(16), 3799–3807 (2009) 15. Lou, X.F., Nair, J.: The impact of landfilling and composting on greenhouse gas emissions—a review. Bioresour. Technol. 100(16), 3792–3798 (2009) 16. Lema, J.M., Omil, F.: Anaerobic treatment: a key technology for a sustainable management of wastes in Europe. Water Sci. Technol. 44, 133–140 (2001) 17. Iyagba, E.T., Mangibo, I.A., Mohammad, Y.S.: The study of cow dung as co-substrate with rice husk in biogas production. Sci. Res. Essay. 4(9), 861–866 (2009) 18. Kharpude, S., Sharma, D.: A computer based approach for economic analysis of Deenbandhu biogas plant based on co-digestion of Agri-wastes. Eco. Environ. Cons. 19(2), 503–508 (2013) 19. Igoni, A.H., Ayotamuno, M.J., Eze, C.L., Ogaji, S.O.T., Probert, S.D.: Designs of anaerobic digesters for producing biogas from municipal solid-waste. Appl. Energy. 85, 430–438 (2008) 20. Widodo, T.W., Ahmad, A., Ana, N., Elita, R.: Design and development of biogas reactor for farmer group scale. Indones. J. Agric. 2(2), 121–128 (2009) 21. Budiyono, Widiasa, I.N., Johari, S., Sunarso, : The kinetic of biogas production rate from cattle dung in batch mode. Int. J. Chem. Biol. Eng. 3(1), 39–44 (2010) 22. Budiyono, Syichurrozi, I., Sumardiono, S.: Biogas production kinetic from vinasse waste in batch mode anaerobic digestion. World Appl. Sci. J. 26(11), 1464–1472 (2013) 23. Momoh, O.L.Y., Anyata, B.U., Saroj, D.P.: Development of simplified anaerobic digestion models (SADM’S) for studying anaerobic biodegradability and kinetics of complex biomass. Biochem. Eng. 79, 84–93 (2013) 24. Itodo, N.I., Agyo, G.E., Yusuf, P.: Performance evaluation of a biogas stove for cooking in Nigeria. J. Energy S. Afr. 18(3), 14–18 (2007) 25. Shin, J.D., Han, S.S., Eom, K.D., Sung, S., Park, S.W., Kim, H.: Predicting methane production potential of anaerobic co-digestion of swine dung and food waste. Korean society of environmental engineers. Environ. Eng. Res. 13(2), 93–97 (2008) 26. Yusuf, M.O.L., Debora, A., Ogheneruona, D.E.: Ambient temperature kinetic assessment of biogas production from co-digestion of horse and cow dung. Res. Agric. Eng. 57(3), 97–104 (2011) 27. Bakhov, Z.K., Korazbekova, K.U., Lakhanova, K.M.: Kinetics of methane production from co-digestion of cattle dung. Pak. J. Bio. Sci. (2014). doi:10.3923/pjbs.2014 28. APHA, AWWA, WPCE: Standard Methods for the Examination of Water and Wastewater, 16th ed., APHA, Washington DC (1985) 29. Tchobanoglous, G., Theisen, H., Vigil, S.: Integrated Solid Waste Management Engineering Principles and Management Issues. McGraw Hill Inc., New York (1993) 30. Uko, E.D., Tamunorbereton-Ari, I.: Variability of climate parameters in Port Harcourt, Nigeria. J. Emerg. Trend Eng. Appl. Sci. 4(5), 727–730 (2013)