SIMULATION OF ANAEROBIC DIGESTERS FOR THE
NON-UNIFORM LOADING OF BIOWASTE GENERATED FROM AN
EDUCATIONAL INSTITUTION
GODWIN GLIVIN
†and S. JOSEPH SEKHAR
‡ † Department of Mechanical Engineering, Marian Engineering College, Thiruvananthapuram, Kerala-695582, India. Email: [email protected]‡ Department of Mechanical Engineering, Shinas College of Technology,
Sultanate of Oman. Email: [email protected]
Abstract−− The environmental impacts of conven-tional energy sources and the importance given to re-newable energy technologies lead to the use of biogas in a number of applications such as power generation, heating and refrigeration. The quantity and quality of biogas depend on the ingredients and their composi-tions in the biowaste. In this present work, analytical and experimental studies have been conducted to pre-dict the generation of methane from the biowastes produced in an educational institution where the availability of biowaste is not uniform throughout an academic year. The Anaerobic Digestion Model 1 (ADM1) is used for analytical studies, and four port-able anaerobic digesters, manufactured by fibre-rein-forced plastic, are used in the experimental investiga-tion. The observations show that the biogas produced from the wastes available in the educational institu-tion could substitute 30 to 35% of the conveninstitu-tional cooking energy used inside the campus, and average methane contents in the biogas produced from cow dung, rice waste, mixed rice waste and vegetable waste are 58.01 %, 51.96 %, 54.85 %, and 52.28 % respectively. It is also observed that the yield and the quality of biogas are influenced by the uniformity in organic loading.
Keywords−− Biogas, Anaerobic Digestion, Organic loading rate, Rice waste, Vegetable waste.
I. INTRODUCTION
Anaerobic digestion process is one of the promising tech-nologies used to generate biogas from the natural decom-position of organic waste by anaerobic bacteria (Cho et al., 2013). The anaerobic digestion of waste disposed from the processing of food, livestock manure and mu-nicipal solid waste has received a lot of attention due to its contribution to environmental conservation and sus-tainability (Winquist et al., 2019). Besides, it presents an opportunity to recover additional value from the waste material in the form of a quality assured nutrient-rich fer-tilizer that can be used in agriculture (Xiao et al., 2013). Many developing countries are still struggling to find the right method to dispose municipal solid wastes from the available alternatives such as incineration, gasification, composting and landfilling (Hijaz et al., 2019; Banu et al., 2007; Karlson et al., 2005). Biological processes like anaerobic digestion could provide a vital element in an integrated solid waste management system for a
commu-nity in a developing country, besides preserving the nat-ural ecosystem within an acceptable cost (Malakahmad et al., 2011; Roediger et al., 1990).
Biogas production increases linearly from 0°C to 20°C and attains the most favourable values under meso-philic conditions (32–38°C) (Zhang et al., 2013). During this mesophilic condition, the biogas production is high when compared with thermophilic condition (50–55°C) (Cho et al., 2013). The increase in Carbon Nitrogen ratio (C/N) and optimization of the feedstock size will also en-hance the biogas production (Lee et al., 2009; Tanimu et al., 2014; Maurer and Winkler, 1980).
Household digester which produces biogas between 0.32 and 0.35 m3/day can burn a cooking stove for 43–47 min in a house having five members and average cooking time of 2.5 h/day. If the gas is used for lighting, it can burn a biogas lamp for 4 to 5 Hours (h). This would be particularly attractive to regions that are not connected to the electrical grid. The cost of biogas lighting is less when compared to the conventional lighting; however, the fuel consumption to provide illumination via biogas lamps is considerably less efficient as compared to electric lamps. Therefore, it would be preferable to utilize this biogas for cooking/heating purposes (Lou et al., 2012).
The previous studies on co-digestion strategies show that fish and grease trap wastes have inhibition to micro-organisms during the initial period of batch digestion un-der thermophilic con-ditions (Chen et al., 2010), Sodium Hydroxide (NaOH) can be used to control pH of the di-gestion of mixed food waste (Cho et al., 2013). Fresh maize and maize silage are added to have high degrada-tion rate even without pre-treatments (Bruni et al., 2010), apple waste can be a potential substrate for co-digestion with swine manure (Kafle and Kim, 2013) etc. The bio-gas production from mixed feed is significantly higher under thermophilic conditions compared to mesophilic conditions, but there is no significant difference in me-thane production (Chen et al., 2010). The biogas produc-tion also depends on the nature of food waste (Oleszek et al., 2014) and operating conditions. Moreover, ADM1 has been identified as a powerful tool for the modelling of anaerobic digestion of biowaste including grass silage (Koch et al., 2010).
Utilization of kitchen waste in universities is more useful because a lot of other energy sources like LPG, kerosene, coal, etc. can be saved or reduced for cooking purposes (Bohra and Rao, 2014; Lönnqvist et al., 2018;
Zhang et al., 2007). Although many researches have been conducted on biogas generation from household wastes, livestock manure, municipal solid waste and market waste (Montingelli et al., 2016), limited studies are avail-able at the institution level where we could get a lot of food wastes from hostels and canteens (Arthur et al., 2011). The availability of biowaste is not stable in aca-demic campuses due to the variations of student popula-tion during a year. Therefore, the quality and the quantity of biogas production will vary throughout the year (Ar-amrueang et al., 2016, Mittal et al., 2019), and there is a need for research to know the viability of biogas utiliza-tion. Hence in this work, biowastes such as Rice Waste (RW), Mixed Rice Waste (MRW) i.e. rice waste mixed with vegetable, meat and fish and Vegetable Waste (VW) produced in hostels and canteens are taken as feed-stock along with Cow Dung (CD) obtained from the cat-tle farm inside the campus. An experimental study has been carried out with four anaerobic digesters to predict the quality and the quantity of methane yield, and a tool box in Matlab that uses the Anaerobic Digestion Model1 (ADM1) has been used in the mathematical model (Gaida et al., 2011).
II. METHODS
A. Identification and characterization of feedstock
The feedstock was collected from the campus of an edu-cational institution situated in the southern part of India. Apart from cow dung, the wasted rice, vegetable, meat, fruits, etc. are the common biowastes generated in the campus. This biowaste is disposed in large amount with-out any use. The average biowaste for every month was calculated and plotted in Fig. 1. Feed-stock availability data were collected from the hostels and the canteens on a daily basis. The data was collected for a one year dura-tion for various seasons. The graph shows that an average of 394 kg of biowaste is available per day during January, February, March, April, May, August, September and October, and it is 190 kg during June, July, November and December.
The important chemical properties which decide the quality of biowastes are pH, TS and Volatile Solids (VS) (Barnert et al., 2014; Wu, 2013), and they were measured as per the standard procedure (APHA, 1995). Fig. 2 and Fig. 3 show the photographs of equipment used for the study. Table 1 shows the chemical properties of the bio-wastes obtained from the preliminary tests.
The percentage of Total Solids (TS) was determined as per the standard procedure (APHA, 1995). In the pre-weighed porcelain vessels, 50 g of each biowaste was taken and heated at 60ºC for 24 hours, and then at 103ºC for 3 hours using a hot air oven as shown in Fig. 2(a). An electronic weighing balance, having least count of 0.001g, was used for weighing the final weight of dried samples with porcelain container as shown in Fig. 2(b). The percentage of TS in each sample was calculated by
𝑇𝑆 = [𝑊𝑑
𝑊𝑤] ∙100 (1)
where 𝑊𝑑 and 𝑊𝑤 are the weight of dry and wet samples respectively.
Table 1. Chemical characterization of feedstock. Sl.No. FEED pH
% TS % VS% 1 Cow Dung (CD) 6.50 15.98 64.99 2 Mixed Rice Waste
(MRW) 4.91 20.25 90.15 3 Rice Waste (RW) 6.61 30.28 90.11 4 Vegetable Waste (VW) 6.35 10.55 90.45
Fig. 1. Biowaste availability per day throughout a year.
2(a) Biowaste samples before heating
2(b) Biowaste samples after heating
Fig. 2. Hot Air Oven and samples used to find Total Solids (TS).
The percentage of VS in biowaste was determined as per the standard method (APHA, 1995). The oven dried samples which were used to determine TS content were further dried at 550oC ± 50oC temperature for one hour in a muffle furnace, and then allowed to ignite completely as shown in Fig. 3. The dishes were then transferred to a desiccator for final cooling. The weight of each cooled porcelain dish with ash was measured and the VS was calculated using
𝑉𝑆 = [(𝑊𝑑−𝑊𝑎)
𝑊𝑎 ] ∙100 (2)
where 𝑊𝑑 and 𝑊𝑎 are the weight of dry biowaste and the dry ash left after igniting the sample in a muffle furnace. The pH of the biowaste (CD, RW, MRW and VW) was determined with pH electrode (Fig. 4) of accuracy 0.05 % which enables speedy and accurate quantitative analysis of the sample.
Fig. 3. Biowaste samples after heating in Muffle Furnace.
Fig. 4. Samples used to measure pH values.
Fig. 5. Stages in anaerobic digestion process.
B. Simulation of Anaerobic Digestion Process
Anaerobic Digestion Model 1 (ADM1) that uses the steps as shown in Fig. 5 has been used to theoretically analyse the anaerobic digestion for the selected biowaste. This highly complex model is characterized by 19 biochemi-cal conversion processes and 24 dynamic state variables. Simulation was carried out with Matlab/Simulink (Bat-stone et al., 2002) and the measured chemical properties of the biowaste as shown in Table 1 were used as input parameters for the analysis. The change in methane per-centage for each day has been obtained from the analysis, and graphs are plotted for each biowaste. The results are compared with experimental values to prove the theoret-ical approach.
C. Experimental Setup
The schema of the experimental setup is shown in Fig. 6. The experiment is carried out in four anaerobic digesters (AD1, AD2, AD3 and AD4) fabricated with reinforced glass fibre composite. Table 3 shows the various bio-wastes used in each digester. Each anaerobic digester
consists of an inlet and outlet to load the feed and drain out the digested feedstock respectively, and a floating drum with water seal is provided to store the biogas. The gas outlet from the digesters is connected to a multigas analyzer (NUCON) of 0.3 % accuracy which is capable of measuring the mass fraction of CH4, CO2, CO, N2, and H2. A thermal gas flow meter of accuracy 0.5 % Full Scale (FS) is also connected to the gas outlet. A pH elec-trode and a thermometer are kept inside the digester to measure the pH and temperature of the substrate respec-tively.
D. Experimental procedure
All the four digesters were first loaded with cow dung and water in 1:1 ratio for producing the methanogen bac-teria. Approximately a Hydraulic Retention Time (HRT) of 50 days is required for the complete digestion of the cow dung (Singh et al., 1985). During this period the gas generated was released using cooking stove. Once the bi-ogas production from cow dung became negligible, the starvation of bacteria was assured and the bio wastes such as RW, MRW and VW, collected from the campus, were loaded gradually in each digester as mentioned in Table 3.
The availability of biowaste was not uniform during the test period, therefore the Organic Loading Rate (OLR) was not constant. Since the digesters were not suf-ficient to use the total waste, a constant percentage from the available waste was taken for the loading in accord-ance with the capacity of the digesters. Methane produc-tion had been observed and its quality and quantity per day were measured. The temperature, pH and quality were also recorded for a minimum of four times per day, and the average was calculated. The atmospheric temper-ature throughout the year in the area, where the study has been conducted, was 19ºC to 34ºC; however, more than 90% of the readings showed the temperature above 28ºC.
Fig. 6. Schematic diagram of the experimental setup Table 3. Summary of the experimental design.
Di-gester Size Feed-stock Maximum OLR/day (kg) Test Dura-tion (days) Mixing Ratio (Feed + water) AD1 1 m3 CD 50 365 1:1 AD2 2 m3 MRW 20 365 1:1 AD3 0.25 m3 RW 5 365 1:1 AD4 0.25 m3 VW 5 365 1:1
Fig. 7. Methane composition of biogas produced from CD.
Fig. 8. (a) Methane Composition in biogas for Rice waste (RW), (b) Biogas Yield from Rice waste (RW) for 365 Days,
(c). Loading pattern of Rice waste (RW) for 365 days.
III. RESULT AND DISCUSSION
Methane is the combustible component of the biogas, and it dictates the quality of the biogas. Therefore, the me-thane content of the biogas generated from CD, RW, MRW and VW has been observed from experimental and simulation work and is depicted in Figs. 7 to 10.
In the case of CD, even though many studies have been reported in the literature (Krishania et al., 2013), the same has been investigated to validate the experimental
and simulation procedures used in the study. CD is avail-able throughout the year in the range between 35 kg and 70 kg per day. To incorporate the variations in the avail-ability of feed, 10% of the waste collected was loaded in the digester every day. The experimental and the theoret-ical studies show that the average methane composition is 58.01 % and 58.6 % respectively (Fig. 7). Biogas yield is defined as the quantity of biogas obtained in m3 per day, and it is observed between 0.14 m3 and 0.29 m3. This is in accordance with various research findings (Ezekoye and Ezekoye, 2009). Moreover, there is no sig-nificant difference between experimental and theoretical results, and hence the validity of the present approach is confirmed.
Similar procedure has been used to study RW, MRW and VW. Figure 8(a) shows that the theoretical and the experimental values of methane composition in the bio-gas generated from RW are 51.96 % and 52.92 % respec-tively. The quantity of RW available in hostels and can-teens is in the range of 4 kg to 35 kg. The quantity of feed changes each day according to the working days of can-teens and hostels. Figure 8(b) shows that the variation of biogas yield is from 0.005 m3 to 0.14 m3 while the feed-stock is varied according to the trend shown in Fig. 8(c).
Figure 9(a) shows that the theoretical and the experi-mental values of methane composition in biogas gener-ated from MRW are 55.69 % and 54.85 % respectively. The availability of MRW, throughout this year, varies from 16 kg to 280 kg. This variation is due to holidays and other factors like exam period and vacations. Figure 9(b) shows that the variation of biogas yield is between 0.01 m3 to 1.13 m3 which is due to the availability of MRW throughout the year (Fig. 9(c)).
The availability of VW from the hostels and the can-teens is less when compared with RW and MRW, and it is in the range of 4 kg to 21 kg. The experimental and the theoretical results depicted in Fig. 10(a) show that the methane compositions are 52.28 % and 53.26 % respec-tively. The variation in methane yield is observed from 0.007 m3 to 0.10 m3 (Fig. 10(b)) when the loading pattern was similar to the one shown in Fig. 10(c).
During the first seven days, the variation in biogas generation is very high and after 15 days both the theo-retical and the experimental values are close to each other. This is due to the large amount of feedstock load ed initially, and biogas yield attains a constant level after 30 days of loading (Zhu et al., 2014; Divya et al., 2015; Feng et al., 2016). The biogas generation fluctuates on a day-to-day basis due to the change in loading pattern, change in atmospheric conditions like climatic condi-tions, feedstock properties, etc. (Kim et al., 2011; Fang et al., 2011; Beyer et al., 1998).
This methane gas can be used for cooking purposes in hostels instead of Liquefied Petroleum Gas (LPG). An average of 12 kg of LPG is used during the working days to meet the cooking purposes. Biowastes collected from the institution generates an average of 10.4 m3 biogas which is equivalent to 4.68 kg of LPG (Singh and Sooch, 2004). The consumption of LPG and the LPG equivalent
(a)
(b)
Fig. 9. (a) Methane Composition in biogas for Mixed Rice Waste (MRW) for 365 days, (b) Biogas Yield from Mixed Rice Waste (MRW) for 365 days, (c) Loading pattern of
Mixed Rice Waste (MRW) for 365 days.
of the biogas produced during a year depicted in Fig. 11 shows that about 30 – 35 % of LPG usage can be reduced by utilising the food waste generated in the campus.
The digested feedstock which is drained out can be further used as fertilizers through proper mixing ratios (Banks et al., 2011; Franchetti, 2013; Kigozi et al., 2014).
A. Influence of loading rate on the quality and the quantity of biogas
The study was carried out to check the uniformity of bi-ogas generation in accordance with the availability of biowastes in an educational institution throughout a year. The study period was divided into four phases as phase I (1-150 days), phase II (151 to 225 days), phase III (226 to 315 days) and phase IV (316 to 365 days). First 150 days, i.e. from January to June the student population was high and an average of 2 to 5 kg RW was loaded daily for digestion. An average yield of 0.16 m3 is observed as shown in Fig. 8(b) with a maximum yield of 0.18 m3. It is observed that there is an initial lag in methane yield in accordance with the loading rate (Fig. 8(c)). For MRW, an average of 28 kg is loaded during this phase (Fig. 9(c)). The methane yield is observed to be 0.4 m3 initially and attains a maximum of 1.8 m3 during the 150th day (Fig. 9(b)). The methane yield increases gradually and at-tains a constant level after every three weeks till 90 days.
Fig. 10. (a) Methane Composition in biogas for Vegetable waste (VW), (b) Biogas Yield from Vegetable waste (VW) for
365 Days, (c) Loading pattern of Vegetable waste (VW) for 365 days
Fig. 11. The consumption of LPG and availability of Biogas for 365 days
After 90 days, a constant level of 1.8 m3 is recorded till the 150th day. The VW was loaded with an average quan-tity of 2 to 9 kg (Fig. 10c). The methane yield varied be-tween 0.02 m3 and 0.17 m3. The methane yield is ob-served to increase gradually with a time gap of 4 weeks which continued till the 90th day and attained a level be-tween 0.06 m3 and 0.17 m3 (Fig. 10(b))which varied ac-cording to the loading rate.
During phase II, the student population is less due to exam and vacation schedules. RW is loaded with an av-erage of 0.7 to 3.5 kg (Fig. 8c) according to the availabil-ity of the biowaste. Methane yield decreases gradually
(a) (b) (c) (a) (b) (c)
according to the loading rate and attains a level of 0.05 m3 during the 180th day. On the 225th day, the methane generation has a low value of 0.01 m3 (Fig. 8b). MRW is loaded with a variation between 2 to 16 kg (Fig. 9b) and its methane yield is found to be 0.3 m3 during 180 days and 0.1 m3 during the 225th day (Fig. 9c). Loading of VW varies between 1 and 5 kg (Fig. 10c). The methane yield on the 180th day and the 225th day are 0.04 m3 and 0.06 m3 respectively as shown in Fig. 10(b).
Like phase I, in phase III also the student population is high as the semester starts. The loading rate of bio-wastes increases and the methane yield increases accord-ingly. The loading rate for RW, MRW and VW is ob-served with an average range of 5 to 14 kg, 26 to 30 kg and 3 to 9 kg respectively. The methane yield for the same is observed to be from 0.03 m3 to 0.14 m3, 0.8 m3 to 1.3 m3 and 0.04 m3 to 0.14 m3 respectively.
During phase IV, the student population was less due to exam and vacation schedule and the loading rate of RW, MRW and VW were 1 to 4 kg, 2.5 to 11 kg and 1 to 7 kg respectively with an average methane yield of 0.01 m3 to 0.08 m3, 0.1 m3 to 0.3 m
3 and 0.01 m3 to 0.09 m3, respectively.
Figures 8-10, show that the yield according to the loading rates is not similar in all phases. The methanogen bacteria formed during phase I with uniform loading rate leads to proper digestion and good methane yield. In phase II, the yield was low due to less loading rate which leads to insufficiency of methanogen bacteria to undergo anaerobic digestion. This impact on the methane yields in phase III, even though the loading rate is similar to phase I, the methane yield was not similar to phase I and this is due to the fact that in phase I cow dung was loaded initially for generating methanogen bacteria which un-dergoes anaerobic digestion. But due to less loading rate, the activeness of anaerobic digestion process gets low due to insufficiency of methanogen bacteria. In phase IV, the loading rate was less and it is observed that the me-thane yield is reduced and similar to phase II (Mulka et al., 2016). This shows that the non-uniformity in loading rate could influence the biogas yield (Yong et al., 2015). However, the variation of methane composition in biogas is not significant in all phases.
III. CONCLUSIONS
In this present work, the anaerobic digestion has been simulated to predict their performance for non-uniform loading of biowaste in an educational institution and the experimental study was conducted to check the reliability of the simulation. The quality and yield of biogas gener-ated from biowastes such as rice waste, mixed rice waste, vegetable waste and cow dung collected from an educa-tional institution have been studied throughout a year, and the following conclusions are drawn.
• The average composition of methane predicted in bi-ogas throughout a year is 53.26 %, 52.96 %, 55.69 % and 58.6 % respectively for all the four types of bio-wastes considered in the study. For the above cases, the average experimental values are 52.28 %, 51.96 %, 54.85 %, and 58.01 % respectively. This shows
that the biogas produced from the biowaste in institu-tion can be used for any applicainstitu-tion like heating, power generation, refrigeration, etc.
• The methanogen bacteria formed during phase I (1st to 150th days) with uniform loading rate leads to proper digestion and good methane yield. In phase II ( 151st to 215th days), the yield was low due to less loading rate which leads to insufficiency of methano-gen bacteria to undergo anaerobic digestion. Even though the loading rate in phase III is similar to phase I, the methane yield was not similar. In phase IV, the loading rate is less and the methane yield is reduced similar to phase II. This shows that in the first phase of the second consecutive year, the methane yield may be similar to phase III.
• The study also proves that rice wastes can be used for biogas production in an effective way, and methane content in it is sufficient for its use in any relevant application.
• The observations show that the biogas produced from the biowastes available in an educational institution could substitute 30 to 35% of the conventional energy used for cooking.
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Sent to Subject Editor May 5, 2019 Accepted October 8, 2019
