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Evaluation of Biogas Yield and Microbial Species from Selected Multi-biomass Feedstocks in Nigeria

London Journal of Research in Science: Natural and Formal
Volume | Issue | Compilation
Authored by Sokan-Adeaga Adewale Allen , Oseji Matthew Ejike, Ana Godson R.E.E
Classification: For Code: 020601, 829802
Keywords: biogas yield, renewable energy, multi-feedstock, anaerobic digestion, anaerobes.
Language: English

Virtually all countries, especially the developing nations, are being confronted with the twin problems of waste management and energy deficit. This development has led to the search for renewable energy sources. Biomass such as pig dung (PD), water hyacinth (WH) and maize cob (MC) are potential feedstocks for anaerobic digestion in Nigeria, however studies utilising their mixtures have not been fully explored. This study was therefore designed to evaluate the biogas yield and microbial species from mixtures of biomass feedstocks. Feedstocks utilized for this study comprised PD, WH, MC, PD:MC (1:1), PD:WH (1:1), and PD:MC:WH (1:1:1). Biogas digester was fabricated from 10 litres keg for feedstock biodegradation. Ratio 1:11 (w/v) slurry was prepared from each feedstock sample to be digested and fed into the corresponding digester, kept for 35 days for anaerobic digestion while samples of the effluent were taken at seven days interval for five weeks for laboratory analyses of their physicochemical and microbial characteristics. Gas generated was estimated based on Archimedes’ Principle. Data were analyzed using descriptive statistics and ANOVA at p ˂ 0.05.

               

Evaluation of Biogas Yield and Microbial Species from Selected Multi-biomass Feedstocks in Nigeria  

Oseji Matthew Ejikeα, Ana Godson R.E.E σ  & Sokan-Adeaga Adewale Allenρ 

____________________________________________

  1. ABSTRACT

Virtually all countries, especially the developing nations, are being confronted with the twin crisis of waste management and energy deficit. This development has led to the search for renewable energy sources. Biomass such as pig dung (PD), water hyacinth (WH) and maize cob (MC) are potential feedstocks for anaerobic digestion in Nigeria, however studies utilising their mixtures have not been fully explored. This study was therefore designed to evaluate the biogas yield and microbial species from mixtures of biomass feedstocks. Feedstocks utilized for this study comprised PD, WH, MC, PD:MC (1:1), PD:WH (1:1), and PD:MC:WH (1:1:1). Biogas digester was fabricated from 10 litres keg for feedstock biodegradation. Ratio 1:11 (w/v) slurry was prepared from each feedstock sample to be digested and fed into the corresponding digester, kept for 35 days for anaerobic digestion while samples of the effluent were taken at seven days interval for five weeks for laboratory analyses of their physicochemical and microbial characteristics. Gas generated was estimated based on Archimedes’ Principle. Data were analyzed using descriptive statistics and ANOVA at p < 0.05. Temperature was within the mesophilic range and pH (5.80±0.0 to 7.85±0.1) for all the slurries respectively. There was a significant difference in percentage nitrogen, phosphorus and potassium of the various slurries. The anaerobic, coliform and fungal counts ranged from 6.80×102 to 1.0×105cfu/g, 4.3×104 to 6.2×106cfu/g, and 9.1×103 to 6.3×106cfu/g respectively throughout the duration of the study. The highest anaerobic count (1.0×105±0.03×105cfu/g) and biogas yield (6067.00±38.2ml) was recorded in PD:WH. There was a significant difference between the mean biogas yields of the various feedstock groups. Co-digestion of pig dung with water hyacinth had the highest number of anaerobes and biogas yield as compared to single feedstocks. Therefore, the use of multi-biomass feedstocks for biogas production as a source of alternative energy production should be fully optimised.

Keywords: biogas yield, renewable energy, multi- feedstock, anaerobic digestion, anaerobes.

Author α σ ρ: Department of Environmental Health Sciences, Faculty of Public Health, College of Medicine, University of Ibadan, Ibadan, Nigeria.

  1. INTRODUCTION   

Wastes generation and improper disposal into the environment posed a great threat to the ecosystem and public health. The need for proper waste management cannot be over emphasized in order to mitigate its, detrimental impact [1]. Although the biogeochemical cycles help to convert biodegradable wastes into harmless, however with the increased in human population and energy consumption these natural processes have become hampered and inefficient to cope with the enormous wastes production. For examples landfill and fossil fuels combustion contributes enormously to the greenhouse gases in the atmosphere and aggravate global warming and its consequential effects [2]. Hence, the need for alternative renewable energy source appear, being biogas a viable option. Biogas technology, is a green energy that utilized cheaply abundant raw materials and its has the dual benefits of serving as a sustainable waste management strategy and cleaner fuel (mitigating greenhouse gas emission). Biogas technology involves the production of biogas by methanogens through a series of reactions controlled by many parameters such as pH, temperature, nutrient etc. by the anaerobic digestion of biomass (materials of plant origin). These substrates include but not limited to forest residues and products, wastewater, municipal, industrial and agro-based wastes [3].    

Nigeria major source of energy is crude oil and 90% of its revenue is gotten from exportation of fossil fuels. Currently the country is face with the twin challenge of fossil fuels depletion and environmental degradation arising from indiscriminate combustion of fossil fuels. However, the country is rich in renewable energy sources such as biomass, solar and wind, yet this has not been fully explored. Many economic substrates for biogas production has been identified by several authors viz agro-residues, domestic, municipal, industrial, animal and human wastes [4 -7]. Although biogas technology is in its infant stage in Nigeria, various researches on the technical and policy aspects of biogas production has been carried out by various researchers in the country. A prominent research is the one that involved a reactor design by some Nigerian scientists that would lead to process optimization in the development of biodigester. For example, a simple biogas plant (with additional gas storage system) that has the capacity to generate 425 L of biogas per day has been designed at Usman Danfodiyo University, Sokoto, Nigeria [8].

In Nigeria, many biomasses have been critically assessed for their possible use in biogas production by Odeyemi [9]. They include agricultural residues, municipal solid wastes, manure and sewage. Sridhar and co-workers [10] generated biogas through the co-digestion of cow dung and water hyacinth, while Ilori et al., [11] researched on the production of biogas from co-digestion of banana and plantain peels in a 10 L laboratory scale anaerobic digester. Several   authors [12 - 17] had also demonstrated the potential of animal dung and kitchen wastes for biogas production. It was concluded that poultry manure generated in domestic homes and from commercial agricultural activities could be economically feasible substrates for biogas production. Ezekoye and Okeke [18] designed and constructed a plastic biodigester that utilised the mixture of spent grains and rice husk to produce biogas, also Fariku and Kidah [19] reported good biogas yield from anaerobic digestion of waste shells of Lophira lanceolata fruit. Seeding of co-digested pig waste and cassava with wood ash was reported to produce a significant increase in biogas yield compared with unseeded mixture of pig waste and cassava peels [20]. Also, Weerasinghe and Naqvi [21] recognized the potential use of local algal biomass for biogas production in Nigeria. Odeyemi [9] compared the biogas production potential of four different substrates, namely Eupatorium odoratum, water lettuce, water hyacinth and cow dung. He observed that Eupatorium odoratum gave the highest biogas yield while cowdung gave the lowest yield. He concluded that E. odoratum was a cheap substrate for biogas production in Nigeria because of its luxuriant and ubiquitous growth. These laboratory studies corroborated the potential of biogas production from various existing agro-waste, industrial, municipal solid wastes and animal waste in Nigeria. These extensive studies confirms that some groundwork for biogas research and development have been initiated in Nigeria.

Several authors have reported the potential of single substrates for biogas generation, but there is no documentation in Nigeria on the potential of multi-substrates using pig dung, maize cob and water hyacinth for biogas generation. There is also no documentation that compared biogas yield of raw samples (wet mass) from two or more biomass materials using equal masses (weight) based on the quantity of dry matter in them. Hence, in our study, we explored the biogas yield and associated microbial species from multi- biomass feedstocks using wet matter.  

  1. MATERIALS AND METHODS 

3.1   Study Design

The study was experimental and laboratory based involving pre-treatment, anaerobic digestion, biochemical tests and microbiological examination. Different types of organic wastes such as pig dung, water hyacinth and maize cob were utilized in the experiment. The experiment was divided into six (6) treatment groups:

Treatment A = Pig dung (PD)

Treatment B = Water Hyacinth (WH)

Treatment C = Maize cob (MC)

Treatment D = 1:1 of Pig dung + Maize cob (PM)

Treatment E = 1:1 of Pig dung + Water hyacinth (PW)

Treatment F = 1:1:1 of Pig dung + Maize cob + Water hyacinth (PMW)

The experiment employed a complete randomized design with three replicate of each of the sample biomass. An evaluation of the biogas yielding capacity and microbial load of the different biomass was carried out. 

3.2   Source Identification

The different organic wastes utilized in this study were collected from the following sources in Ibadan: Pig Dung (PD) and Maize Cob (MC) were obtained from the University of Ibadan Teaching and Research Farm (UITRF) located at the north end of the University campus. It covers approximately a land area of hundred and sixty hectares (160 ha) [400acres] which is used for both livestock husbandry (cattle, pig, poultry and sheep) and crop (maize, cassava etc) production. These Agricultural practices led to large generation of biomass wastes which are disposed indiscriminately in the environment. Water Hyacinth (WH) was obtained from Oba-Dam (OD) which is located in the outskirt of the University of Ibadan (UI) very close to Ibadan Polytechnic (IP). It is about 130m in length, 12.2m wide at the top, about 27.4m wide at the deepest portion and has a maximum depth of about 5.5m. It has a capacity to hold about 227million litres of water.

3.3   Quantification of Biomass Materials

A feasibility study was carried out on the sample collection area to determine the amount of wastes being generated from the parent food materials. The quantity of biomass by-products generated from the crop production was estimated using the method of [22] which utilizes the residue to crop ratio approach. The weight (kg) and volume (m3) of the waste of the sample population was determined using a weighing balance (Top Load & Silvano Weight Balance), and measuring cylinder (Hirschman Model), with the density calculated in kg/m3.

3.4   Sample Collection

A representative sample of each biomass was obtained from the respective sources. From each heap of biomass wastes, a grab sample was collected into a polythene bag ready for physicochemical characterization.

3.5   Experimental Process

The production process for this research is depicted through a flowchart as illustrated in figure 1 below

3.5.1 Construction of the Anaerobic Digesters

As shown in figure 2, each digesting vessel that was used in the various experiments consists of a black 10-litre water dispensing plastic (Keg 1). A plastic tap with open and lock system was connected to the base of the digester (Keg 1) which served as the outlet pipe. A short tube was connected to the top of the keg which served for testing when gas generation started. This tube was properly stoppered with nut, pipe clip and treading tape to avoid gas leakage. Another delivery tube was used to connect keg1 to a 5-litre transparent plastic (keg 2) which served as the gas collection chamber. This keg was filled with water. A third delivery tube was used to connect keg 2 to another 5-litre transparent plastic (keg 3) which served for the collection of water displaced from keg 2 by the gas generated (Archimedes’ Principle). The entire system was made airtight using tongit gum. The above process was repeated for the remaining five different treatments.

Figure 1:  Flow chart showing experimental set up.

Figure 2: Picture of pig dung digester, 1; gas displacement, 2; and water collection chamber, 3

3.5.2  Preparation of Substrates for Biogas Production

Single Substrates

  • Treatment 1 - PD: 1.88 kg of wet pig dung was weighed and 7.12 litres of water was added to form slurry (9 litres).
  • Treatment 2 - WH: 3.64 kg of wet water hyacinth was weighed out and 5.36 litres of water was added to form slurry (9 litres). Treatment 3 - MC: 3.30kg of wet maize cob was weighed out and 5.7 litres of water was added to form slurry (9 litres).

Multi-substrates

  • Treatment 4 - PM: 0.94 kg of wet pig dung and 1.65 kg of wet maize cob were weighed out and 6.41litres of water was added to form slurry (9 litres).
  • Treatment 5 - PW: 0.94kg of wet pig dung and1.82kg of wet water hyacinth was weighed out and 6.24litres of water was added to form slurry (9litres).
  • Treatment 6 - PMW: 0.63kg of wet pig dung, 1.10kg of wet maize cob and 1.22kg of wet water hyacinth were weighed and 6.05 litres of water was added to form slurry (9 litres).

Note: The above weights of each waste used were equivalent to 0.75kg of its dry matter. All mixtures of slurry were poured into their respective digesters and were properly sealed for anaerobic digestion process to begin.

3.5.3  Charging of Digesters  

The operational mode was the batch method using an operational mesophilic temperature. Respective weights were mixed with water at the ratio of 1:3 (w/v) and placed in the digesters. The various variants were charged into the 10L rubber keg digesters as originally weighed out. The wastes were charged up to ¾ of the digester leaving ¼ headspace for collection of gas. The digester contents were stirred adequately and on a daily basis to ensure homogenous dispersion of the constituents of the mixture. The digesters were tightly corked with rubber stopper to create anaerobic condition and connected to a gasometrical chamber. Biogas was monitored and measured daily over a period of 35 days using the gasometrical chamber with the displacement of paraffin wax. The total biogas yields were determined by opening the outlet tap of the anaerobic digester and the inlet tap to the graduated burette. Gas production was measured in dm3/kg of slurry (35kg) was obtained by downward displacement of water by the gas.

3.6   Analyses of Wastes

3.6.1  Physicochemical Characterization of Slurry

The pH and temperature of all slurry mixtures were determined using pH meter and thermometer while 200 ml of each slurry mixture was collected into clean bottle water container and was immediately taken to the laboratory for analysis of the following parameters; Physical characteristics (total solids) and chemical characteristics (TOC, TN, TP, TK, BOD, COD). Samples were also analyzed on days 7, 14, 21, 28 and 35. The AOAC methods [23] were employed in the determination of the Total Organic Carbon (T.O.C), Total Nitrogen (TN), Total Phosphorus (TP) (%), Total Potassium (TK), Biochemical Oxygen Demand (BOD) and Chemical Oxygen Demand (COD). The T.O.C (%) of the sample was determined quantitatively by using the Walkey-Black Method [24]. The TN (%) of the samples was determined by the routine semi-micro kjeldahl technique. This consists of three techniques namely; Digestion, Distillation and Titration [23]. The TP (%) was determined routinely by the vanado-molybdate colorimetric method [23]. The concentration of the phosphorus was obtained by taking the optical density (OD) or absorbance of the solution on a Spectronic-20 spectrophotometer at a wavelength of 470nm. Anhydrous KH2PO4 was used as standard phosphate solution to obtain the calibration curve. The TK was determined by flame photometry at a wavelength of 766.5 nm.

3.6.2 Isolation and Assessment of Microbial Populations

The 6 samples listed above were diluted using the tenfold serial dilution technique to reduce the microbial concentration in the samples step wisely. 1ml of the appropriate dilutions was pipetted (aseptically) into various Petri-dishes and already sterilized molten agar at 45oC were poured on them, swirled gently and allowed to solidify using the method of [25]. The culture media used include: Potato Dextrose agar (PDA) for fungal isolation, MacConkey agar for coliforms, Nutrient Agar for Total Heterotrophic count, and DE Man Sharpe Rogosa (MRS) Agar for anaerobic organisms. Fungal plates were incubated at 30oC for 3 to 5 days, coliforms and aerobic plates were incubated at 30oC for 24-48 hours while anaerobic plates were incubated in an anaerobic jar containing a moistened pack of gas generating kit (Oxoid BR, Basrugstoke, England) at 300C for 72 hours. After the incubation period, colonies of organisms were counted using a colony counter and the total count for each target organism was enumerated by multiplying with the corresponding dilution factor.

3.6.3  Characterization of Isolates

The obtained microorganisms were characterized using macroscopic, microscopic and biochemical methods. The results were compared with the scheme of Bergey’s Manual of Determinative Bacteriology and Cowan and Steel.

  • Gram staining

This was done to classify the isolated organisms into Gram positive or gram negative based on their reaction to the Gram staining technique of Christian Gram.

  • Catalase test

This test was carried out to detect the production of the enzyme, catalase by an organism. The enzyme converts Hydrogen peroxide to Water and Oxygen as shown in the equation:

   2H2O2 ……………………………… 2H2O + O2

  • Oxidase test

The Oxidase test was carried out to detect the presence of Cytochrome C in the organisms under study. The test is very sensitive and of importance in taxonomic and identification studies.

  • Citrate utilization test

This was carried out to differentiate the isolated organisms by their ability to utilize citrate as a sole carbon source.

  • Indole production

This test was carried out to detect the production of indole from tryptophan by the organisms.

  • Sugar fermentation tests

The ability of an organism to ferment several sugars is demonstrated by this test. The sugars utilized may be characteristic of a particular microorganism and hence such organisms can be identified on the basis of the type of sugar they ferment.

3.7  Data Management & Statistical Analysis

Data was recorded at every given step in the process. This was achieved by measurement of weight, volumes, density, pH, temperature, TOC, TN, TP, TK, BOD, COD, microbial (aerobic, anaerobic, coliform and fungal) characteristics and biogas yield. All data was summarized using descriptive statistics such as proportions, means and standard deviation. The results of the physicochemical analysis, microbial analysis and biogas yields from the various slurries were subjected to One-Way Analysis of Variance (ANOVA) at 5% level of Precision (α=5%) to compare their various means. Spearman-rank correlation was used identify any relationship between the biogas yield of the slurries and the mean anaerobic organism count.

  1. RESULTS

4.1  Wastes Characterization

A feasibility study was carried out on the sample collection areas to determine the sample populations and the quantity of agro by-product generated from the parent food materials. The 1acre of pig farm at University of Ibadan (UI) rear 200 to 250 pigs. The 0.65 hectares maize plantation at Abadina Quarters in UI produces 24074 to 40,000 maize cobs per harvest. The Oba-dam at UI occupies a land area of about 1586m2 which is covered with 126880 to 190320 strands of water hyacinth (WH) at the river bank.

Table 1 shows the quantity of biomass wastes generated from the parent source. The 1 acre of pig farm at UI generates pig dung of mean weight ranging from 99.0±9.6 to 123.8±12.1 and a mean volume ranging from 0.14±0.02 to 0.18±0.23m3 per day. The mean density was estimated as 702.67±34.30kg/m3. The 0.65 hectare of maize plantation at Abadina Quarters in UI generates MC with a mean weight ranging from 1163.6±36.8 to 1933.3±61.1kg and a mean volume ranging from 0.1±0.0 to 1.0±0.3 m3 per harvest, while the mean density was estimated as 1641.4±36.2kg/m3. The Oba-dam at UI occupy a land area of about 1586m2 which are covered with WH of mean weight ranging from 3895.2±681.4 to 5842.8± 1022.1 kg and mean volume which ranges from 38.7±6.7 to 58.1±10.0 m3. Its mean density was estimated as 100.6±1.4kg/m3.

Table 1: Estimation of the quantity of agro-based wastes from parent source

Sample

Mean Weight (Kg) Mean ± S.D

Mean Volume (m3) Mean ± S.D

Density (Kg/m3)

Mean ± S.D

Min. Limit

Max. Limit

Min. Limit

Max. Limit

Pig dung

99.0±9.6

123.8±12.1

0.14±0.02

0.18±0.23

702.67±34.30

Water hyacinth

3895.2±681.4

5842.82±1022.1

38.7±6.7

58.05±10.0

100.6±1.4

Maize cob

1163.6±36.8

1933.3±61.1

0.71±0.02

1.02±0.3

1641.5±36.2

4.2  The Physicochemical Characteristics of the Slurry Mixtures

Tables 2-3 shows the mean values obtained from the physicochemical characterization of the different slurry mixtures at weekly interval. The mean ambient and slurry temperatures of all the slurry mixtures were within the mesophilic range of 25.3 ± 0.4oC to 26.3 ± 0.4oC and 25.8 ± 0.4oC to 28.8 ± 0.4oC respectively throughout the duration of study. pH of all the slurries from day 0 to day 35 were within the range of 5.8 ± 0.0 to 7.9 ± 0.1. The Total Solids (TS) obtained from all the slurries ranged from 8.3 ± 0.1 to 20.6 ± 0.2.

The mean T.O.C (%) decreased as the anaerobic digestion progressed and vice versa. Among the biomass, MC recorded the highest T.O.C (%) at different days of anaerobic digestion while the least mean T.O.C (%) was found in PD. The T.O.C of each of the biomass were significantly different from each other (p<0.05). For the Total Nitrogen, TN (%); it was evident that the mean TN (%) increased as the days of anaerobic digestion increased and vice versa. The mean TN (%) was found to be greatest in PD for the whole duration of the study and least for MC. Thus, the mean TN (%) of the various substrates were significantly different from each other (p<0.05). The mean Total Phosphorus, TP (%) increased as the biodegradation process progressed in the anaerobic digester. It was obvious from the Table 2 that PD had the highest TP (%) throughout the course of the experiment while MC recorded the least TP (%). The mean TP of the various substrates were significantly different from each other (p<0.05). Lastly, it was observed that the mean Total Potassium, TK (%) increased as the time of anaerobic digestion increased. Among the biomass, PW recorded the highest TK (%) at different days of anaerobic digestion while the least mean TK (%) was found in MC. The TK (%) of each of the biomass were significantly different from each other at p<0.05.

The mean Biological Oxygen Demand (BOD) and Chemical Oxygen Demand (COD) decreased sharply in the first three (3) weeks [days 0, 7 and 14] of the experiment and slowly for the remaining weeks of the experiment [days 21, 28 and 35]. PD had the highest BOD and COD value compared to the other biomasses (WH, MC, PM, PW, PMW) [p<0.05].

Table 2: Pattern of Physicochemical Properties of the slurry mixtures at weekly interval (days 0-14)

Day

Slurry mixtures

Temperature of slurry

pH

TOC (%)

TN %

C/ N ratio

TP (mg/l)

Potassium (mg/l)

BOD5 (mg/l)

COD (mg/l)

0

PD

25.8±0.4

6.6±0.0

41.7±4.9

2.1±.1

20.1±2.1

208.3±2.9

29.7±.58

2533.3±15.3

4675.0±15.0

WH

25.9±.3

7.9±.06

45.9±1.3

2.0±.1

23.3±.1

191.7±2.9

28.7±.6

2223.3±12.6

3925.0±21.8

MC

26.2±.3

5.8±.0

63.4±1.1

0.7±.0

97.5±3.3

153.3±2.9

23.0±1.0

1456.7±16.1

2630.0±10.0

PD/MC

25.9±.4

6.0±.0

58.0±.6

1.0±.0

57.3±.2

198.3±5.8

29.7±.6

2336.7±15.3

4248.3±20.8

PD/WH

26.1±.2

7.3±.1

56.5±8.1

2.0±.0

28.5±4.2

198.3±2.9

30.7±1.2

2250.0±8.7

4130.0±13.2

PMW

26.1±.2

6.2±.0

56.9±3.8

1.1±.0

49.9±2.9

203.3±2.9

30.3±.6

2448.3±25.7

4653.3±22.6

7

PD

28.0±.5

6.4±0.1

41.7±4.0

2.1±.0

20.0±1.8

225.0±5.0

31.0±1.0

2263.3±15.3

4323.33±12.6

WH

28.2±.4

7.3±.1

44.1±.1

2.0±.0

21.7±.2

205.0±.0

29.0±1.0

2040.0±20.0

3783.3±07.6

MC

28.3±.2

4.0±3.5

60.4±1.4

0.7±.0

90.2±1.4

166.7±2.9

26.0±1.0

1226.7±15.3

2185.0±13.2

PD/MC

28.4±.1

6.1±.0

55.1±1.5

1.1±.0

52.5±2.4

211.7±2.9

31.3±.6

2166.7±41.6

4051.7±2.9

PD/WH

27.9±.1

7.2±.0

56.1±2.3

2.0±.0

27.9±1.1

213.3±2.9

32.3±.6

2098.3±47.5

4005.0±31.2

PMW

28.2±.3

6.2±.0

55.9±1.0

1.2±.0

48.2±1.0

218.3±2.9

32.0±.0

2168.3±38.2

4228.3±17.6

14

PD

28.5±.0

6.5±.1

41.3±3.3

2.1±.0

19.6±1.8

235.0±.0

32.0±.0

2140.0±10.0

4013.3±22.6

WH

28.3±.6

7.3±.1

39.0±2.8

2.1±.0

18.8±1.3

210.0±5.0

29.3±.6

1988.3±18.9

3570.0±00.0

MC

28.0±.0

6.2±.0

55.6±.8

0.7±.0

78.3±.1

176.7±5.8

27.7±.6

1041.7±17.6

1813.3±2.9

PD/MC

28.7±.3

6.2±.0

50.9±.0

1.1±.0

47.6±.0

218.3±2.9

32.3±1.2

2073.3±20.8

3981.7±10.4

PD/WH

28.6±.1

7.3±.0

55.4±3.2

2.1±.0

26.8±1.9

225.0±.0

33.7±.6

1980.0±5.0

3506.7±25.2

PMW

28.0±.5

6.4±.0

54.8±1.3

1.2±.0

46.4±.1

230.0±.0

33.3±.6

2088.3±33.3

3766.7±15.3

Table 3: Pattern of Physicochemical Properties of the slurry mixtures at weekly interval (days 21-35)

Day

Slurry

mixtures

Temperature of slurry

pH

TOC (%)

TN %

C/ N ratio

TP (mg/l)

Potassium (mg/l)

BOD5 (mg/l)

COD (mg/l)

21

PD

28.2±.3

6.4±.1

43.8±3.6

2.2±.0

19.8±1.7

273.3±2.9

33.7±.6

2051.7±12.6

3888.3±67.9

WH

28.5±.3

7.3±.0

33.9±.3

2.1±.0

15.9±.1

231.7±2.9

29.7±.6

1893.3±15.3

3456.7±16.1

MC

28.5±.1

6.1±.1

47.0±1.5

0.8±.0

62.7±1.9

196.7±5.8

28.0±1.0

996.7±12.6

1733.3±36.9

PD/MC

28.4±.2

6.1±.1

44.2±1.2

1.2±.0

38.5±1.4

250.0±5.0

35.0±.0

1996.7±20.8

3875.0±96.6

PD/WH

28.3±.3

7.2±.0

54.5±.0

2.1±.0

26.0±.0

260.0±5.0

36.0±1.0

1913.3±7.6

3485.0±21.8

PMW

28.4±.2

6.3±.0

52.3±2.3

1.2±.0

42.2±1.5

270.0±.0

34.7±1.5

1995.0±25.0

3723.3±12.6

28

PD

28.1±.5

6.6±.1

38.4±2.6

2.3±.0

16.9±1.3

285.0±5.0

34.3±.6

2010.0±10.0

3790.0±10.0

WH

28.6±.2

7.2±.1

31.5±.1

2.2±.0

14.1±.1

238.3±2.9

30.7±.6

1853.3±11.6

3371.7±7.6

MC

28.8±.4

6.2±.0

39.2±.3

.8±.0

51.0±.8

208.3±2.9

29.3±.6

976.7±7.6

1631.7±16.1

PD/MC

27.6±1.8

6.3±.1

35.7±.8

1.2±.0

29.7±.3

258.3±7.6

35.7±.6

1963.3±05.8

3681.7±30.1

PD/WH

28.3±.3

7.0±.0

52.5±4.8

2.1±.0

24.6±2.3

268.3±2.9

36.7±.6

1888.3±2.9

3393.3±30.6

PMW

28.6±.2

6.2±.0

50.9±3.6

1.3±.0

38.8±1.9

276.7±2.9

35.0±1.0

1976.7±10.4

3668.3±16.1

35

PD

28.0±.5

6.5±.0

37.8±2.7

2.3±.0

16.3±1.1

301.7±2.9

35.0±1.0

1995.0±10.0

3698.3±25.7

WH

28.0±.0

7.2±.0

29.1±2.4

2.3±.0

13.0±1.2

251.7±2.9

31.0±1.0

1846.7±2.9

3360.0±13.2

MC

28.2±.3

6.1±.0

37.2±.7

0.8±.0

47.7±1.3

221.7±2.9

29.5±.6

968.3±10.4

1576.7±25.2

PD/MC

28.3±.1

6.1±.1

34.9±2.9

1.2±.0

28.3±2.1

273.3±2.9

36.0±.0

1956.7±7.6

3588.3±28.4

PD/WH

27.9±.2

7.0±.1

52.0±4.2

2.2±.0

24.2±2.0

281.7±2.9

36.7±.6

1870.0±5.0

3355.0±5.0

PMW

28.3±.3

6.2±.1

49.5±3.0

1.3±.0

37.2±2.4

290.0±5.0

35.7±1.0

1961.7±7.6

3526.7±12.6

4.3  Microbial Enumeration and Identification

Figures 3-6 show results of the microbiological examination of slurries obtained from the anaerobic digestion of the various biomass feedstocks. The organisms identified were aerobes (Bacillus spp; Flavobacterium sp; Micrococcus sp; Pseudomonas sp; Staphylococcus sp), coliform groups (E.coli; Enterobacter sp; Aeromonas sp; Proteus sp), anaerobes (Lactobacillus spp; Methanobacterium spp.), and Fungi (Aspergillus sp; Candida spp). The anaerobic, coliform and fungal counts ranged from 6.80×102 to 1.0×105cfu/g, 4.3×104 to 6.2×106cfu/g, and 9.1×103 to 6.3×106cfu/g respectively throughout the duration of the study. The highest anaerobic count (1.0×105 ± 0.03×105cfu/g) was recorded in PW on day 28. Figure 3 show that the mean Total Anaerobic count (TANC) increased steadily from day 0-14 and sharply from day 14-28 before declining from day 28-35. In Figures 4-6, the mean Total Aerobic count (TAC), Total coliform count (TCC) and Total fungal count (TFC) [cfus/g] decreased significantly throughout the duration of the study (p<0.05).

Figure 3: Mean total anaerobes of slurries for the entire degradation phase (Day 0-35).

Figure 4: Mean total coliform count of slurries for the entire degradation phase (Day 0-35).

Figure 5: Mean total aerobic count of slurries for the entire degradation phase (Day 0-35)

Figure 6: Mean total fungal count of slurries for the entire degradation phase (Day 0-35).

4.4  Biogas Yield

Figure 7 shows the daily biogas production obtained from the different slurries of the various biomasses from day 20 to day 33. The initiation time for biogas production was observed on day 20 (PD, PD/MC and PD/WH) and day 22 (WH, MC and PMW). Peak biogas production was observed on day 23 for PD (987.50±3.5ml); day 24 for PW (1095.00 ± 7.1ml), and PM (732.50 ± 17.7ml); day 25 for MC (560.00 ± 7.1ml), day 26 for WH (635.00 ± 7.1ml) and PMW (662.50 ± 10.6ml). Group PW had the highest biogas yield of 6067.00 ±38.2ml throughout the degradation phase of the study. There was a significant difference between the mean biogas yields of the various feedstock groups (p<0.05).

Figure 7: Biogas yield over the entire degradation phase (Day 0-35).

4.5  Relationship between Anaerobic Count and Biogas Yield

Figure 8 shows the relationship between the mean anaerobic count and the sum of biogas yield for the entire degradation phase (Day 0-35). The anaerobic count is directly proportional to the biogas yield that is as the anaerobic count increases, the biogas production also increases for the different substrates.

Figure 8: Relationship between anaerobic count and biogas yield for the different substrates               biomass  

4.6  Projected Yields of Biogas from Parent Source

Developing countries, such as Nigeria are rich in biomass and wastes materials that are suitable precursors for biofuel, yet this has not been fully explored. From this study, it is possible to estimate the biogas yield that will be produced from the parent source. Table 4 shows an estimate of the projected quantity of biogas which will be yielded if all wastes generated is digested anaerobically. The pig farm generates 128.0±16. 0kg of pig dung per day which if digested anaerobically will yield an estimated biogas of 306.69±37.90L. The 1586m2 area of Oba-Dam if completely covered with water hyacinth will produce water hyacinth of mean weight ranging from 3.90±0.68 to 5.84±1.02tons which when put into biogas production will generate mean biogas of 4482.29±769.52 to 6723.43±1154.27L. While the 0.65 hectare maize plantation at Abadina Quarters generates maize cob of mean weight 1.16±0.04 to 1.93±0.06tons per harvest which if totally utilized for biogas production will yield 1177.04±33.42 to 1955.66±55.56L of biogas.

Table 4: Projected mean value of biogas yield of pig dung, water hyacinth and maize cob that will be generated from the parent sources.

Experimental quantity of waste used and its corresponding total biogas yield

Total wastes generated from parent source and its projected total biogas yield

Sample

Waste (kg)

Biogas yield (ml)

Mean weight of waste (tons) Mean ± SD

Mean Biogas yield (L)

Mean ± SD

Wet Weight (WW)

Dry weight (DW)

WW

DW

Min. limit

Max. limit

Min. limit

Max. limit

Min. limit

Max. limit

PD

1.88

0.75

4505.3±35.50

0.10±0.01

0.12±0.01

0.04±0.01

0.05±0.01

237.30±31.30

296.69±37.90

WH

3.64

0.75

4190.0±21.10

3.90±0.68

5.84±1.02

0.80±0.14

1.20±0.21

4482.29±769.52

6723.43±1154.27

MC

3.30

0.75

3338.3±10.60

1.16±0.04

1.93±0.06

0.27±0.008

0.44±0.01

1177.04±33.42

1955.66±55.56

V.   DISCUSSION

The findings from this study revealed that huge quantities of waste are generated from University of Ibadan (U.I.) Teaching and Research Farm and also from Oba-Dam in U.I. A similar study conducted by [26] reported that huge amount of lignocellulosic wastes from agricultural activities are found in Ibadan; these materials do have negative impact on the environment if not properly managed. Their utilization as resource materials for biofuel production is currently being explored.

Anaerobic bacteria, especially the methanogens, are sensitive to the acid concentration within the digester and their growth can be inhibited by acidic conditions. It has been reported [27] that an optimum pH value for AD lies between 5.5 and 8.5.In this study, a pH range of about 5.80 ± 0.0 to 7.85 ± 0.1 was observed which conforms with the reported range. Several authors [28, 29] have also reported that highest biogas yields were observed with digester at pH 8.  

The temperature of the digester in this study remained constant at mesophilic range (25.8 ± 0.4oC to 28.8 ± 0.4oC) throughout the digestion period. Temperature has been observed by most researchers to be quite critical for anaerobic digestion, since methane – producing bacteria operate most efficiently at temperatures 30.0 – 40.0oC or 50.0 – 60.0oC [17]. Temperature does not seem to have any significant effect on the amount of gas produced daily as revealed in this study. Daily gas generations tend not to follow specific temperature pattern and this is indicative by the fact that other parameters apart from temperature could be responsible for the quantity of biogas generated per day [11].

From this study, the mean T.O.C decreased as the duration of anaerobic digestion increased, meaning that the organic bonded carbon in the slurries were oxidized to carbon dioxide (CO2) and other inorganic Carbon (IC) such as carbonate, bicarbonate etc [30]. Among the various substrates, the mean T.O.C was greatest for the MC throughout the duration of the anaerobic digestion while the least mean T.O.C was found in PD, the implication being that MC had a high quantity of organic bonded carbon in its composition than other wastes. Environmentally, this implies that the natural degradation of these wastes contributes a substantial amount of greenhouse gases such as CO2, CH4 etc to the environment. This was in agreement with [30] who also reported that natural degradation of lignocellulosic wastes by anaerobic digestion of methanogenic bacteria; generate about 25 million tons of methane gas annually worldwide.

In this study, it was observed that the total nitrogen content of the slurries increased steadily as the anaerobic digestion progressed daily and this was in agreement with other studies of [31, 32, 33] which have found an increased yield and nitrogen availability with application of anaerobically digested material as compared to non-digested material, possibly due to increased nitrogen content and reduced carbon content, which can result in nitrogen mineralization by microbes. In this study, it was found that the Total Phosphate of all the slurries increased throughout the experiment. Nutrient speciation data collected from previous AD studies suggest that a high percentage of the P can be found in the inorganic form in the AD effluent [34, 35, 36, 37, 37] and colleagues demonstrated a 26% increase of inorganic P (PO43) in digested swine slurry compared to the raw swine slurry (1591 mg/L and 1256.2 of PO43- respectively).

In this study, it was observed that potassium increased steadily in all slurries throughout the duration of the anaerobic digestion. PD had the highest potassium while MC had the least. Tchobanoglous et al., [38] reported that for the proper functioning and continuous reproduction of methanogens in the anaerobic digestion process, there is a need for synthesis of new cellular materials, of which inorganic elements such as potassium play a key role.

The relationship between the amount of carbon and nitrogen present in organic materials is expressed in terms of the Carbon/Nitrogen, C-N ratio. A C-N ratio ranging from 20 to 30 is considered optimum for anaerobic digestion [39, 40 and 41]. Mean C-N ratio of the various slurries decreased from day 0 to day 35 as follows: 20.05 ± 2.1 to 16.27 ± 1.1, 23.28 ± 0.1 to 12.95 ± 1.2, 97.54 ± 3.3 to 47.70 ± 1.3, 57.27 ± 0.2 to 28.34 ± 2.1, 28.52 ± 4.2 to 24.19 ± 2.0 and 49.86 ± 2.9 to 37.24 ± 2.4 for PD, WH, MC, PM, PW, and PWM respectively. In this study, it was observed that the values obtained for the C:N of PM and PW lies within the optimum range while those of the other substrates (PD, WH,MC, and PWM) lies outside the optimum value of C:N for biogas generation from biomass. This high biogas production observed in PM and PW may be attributed to their C:N which lie within the optimum range (20: 1-30:1).

The result of the analysis of the feedstocks during the anaerobic digestion revealed that there is reduction in BOD and COD indicating that anaerobic digestion is a potent way of reducing these parameters from sludge or wastewater. The reduction in BOD observed in this study agrees with [42] that treating human waste by anaerobic digestion is a credibly ethical sanitation technology and removes Biochemical Oxygen Demand (BOD) from sewage, conserves nutrients (especially nitrogen compounds) and most importantly reduces pathogens. From the environmental point of view, anaerobic digestion treatment helps to avert the serious public health risk posed by these wastes, which if discharged directly into water bodies can contribute to algal blooms and cyanobacterial growth thus destroying the aquatic ecosystem. Also, the reduction in BOD and COD is in agreement with [43] who reported a high BOD and COD removal from supernatant of hydrothermally treated municipal sludge by up-flow anaerobic sludge blanket reactor (UASD). In a similar study, [44] reported the recovery of bioenergy from hydrothermally heated cow manure with COD removal rate reaching up to 75.9%.

The groups of bacteria isolated from the digester feedstock include Bacillus, Escherichia, Clostridium, Klebsiella, Proteus and Bacteroides some of which are acid-formers and a methane former Methanococcus species, the correct balance between these two groups of microorganisms determines the successful operation of anaerobic digesters for biogas production. The methane formers however multiply at a slower rate than acid formers and are very sensitive to environmental changes as seen in this research. Fungal isolates includes Aspergillius spp and Candida spp whose source could be the feedstock. [45] reported a similar result when he isolated E. coli, Aspergillius, Clostridium botulinum, C. chavoie and others from water contaminated by human excreta in Malawi. The decreasing trend seen in the aerobic count could be attributed to the increasing anaerobiosis. The acidic nature of the feedstock over the first four weeks of digestion could have supported the growth of acid producing organisms despite the anaerobic condition. Decrease in fungal isolates over the first three weeks even as the digestion becomes more anaerobic is in support of fungal general physiology and metabolism which is known to be purely aerobic. In support of this, [46] in his research, reported that the acidic condition of his digester could be a support for fungi which are known to be acid loving.  

Gas generation commenced on the twentieth (20th) [PD, PD/MC and PD/WH] and twenty second (22nd) [WH, MC and PMW] days, it increased steadily and reached the peak on the 23rd (PD); 24th (PW and PM); 25th (MC), and 26th (WH and PMW) days before dropping. This result agrees with the findings of [43] who reported an increasing trend of biogas production from commencement and a drop after 30 days from supernatants of hydrothermally treated municipal sludge by up-flow anaerobic sludge blanket reactor. Alkan-Ozkaynak and Karthikayan [47] also reported a high rate of biogas production from treated thin sillage with a drop towards the end of the experiment.

Seeding of co-digested pig waste and cassava with wood ash was reported to result in significant increase in biogas production compared with unseeded mixture of pig waste and cassava peels [20]. Odeyemi [9] identified four other substrates, namely Eupatorium odoratum, water lettuce, water hyacinth and cow dung as potential substrates for biogas production. Eupatorium odoratum gave the highest yield of biogas and cow dung was the poorest substrate. These laboratory studies demonstrated the potential of biogas production from agricultural, industrial, urban and animal wastes in Nigeria.

  1. CONCLUSION

The purpose of this study was to evaluate the biogas yielding potential of mixtures of some selected biomass feedstocks and their corresponding microbial load in the respective biodigesters. The findings from this research show that biomass wastes which are the substrates for anaerobic digestion are abundant and readily available in the country.

Bioconversion offers a cheap and safe method of not only disposing the agricultural residues, but also it has the potential to convert agro-based waste into usable forms such as bioenergy that could be used for domestic and industrial activities. Hence the conversion of agro-based “wastes” into bioenergy such as biogas will help reduce environmental pollution, contribute toward the mitigation of greenhouse gases emissions and serve as a sustainable solid waste management strategy. The study concludes that methanogens which are the culprits in biogas production are affected by pH and temperature of the biodigester. There was reduction in the BOD, COD and microbial load (most human pathogens) of the slurries after undergoing anaerobic digestion. Among the substrates utilized in the study, co-digestion of pig dung with water hyacinth had the highest number of anaerobes and biogas yield as compared to single feedstocks. Therefore, the use of multi-biomass feedstocks for biogas production as a source of alternative energy production should be fully optimized.  

  1. AKNOWLEDGEMENTS

The authors are grateful to all those who contributed to the success of this study most especially, Dr. Taiwo B. Hammed of the Department of Environmental Health Sciences, Faculty of Public Health, College of Medicine, who contributed technically; and Dr. J. O. Akinyemi and Mrs. M. O. Oluwaseun of the Department of Epidemiology and Medical Biostatistics, Faculty of Public Health, College of Medicine who played a major role in the statistical analysis of this work.

Conflict of Interest

The authors declare no conflict of interest.

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