DOI: 10.3303/CET25115005 Paper Received: 21 October 2024; Revised: 04 January 2025; Accepted: 25 February 2025 Please cite this article as: Im-Orb K., Piroonlerkgul P., 2025, Exergy Analysis of Biogas Production from Food Waste Through Anaerobic Digestion, Chemical Engineering Transactions, 115, 25-30 DOI:10.3303/CET25115005 CHEMICAL ENGINEERING TRANSACTIONS VOL. 115, 2025 A publication of The Italian Association of Chemical Engineering Online at www.cetjournal.it Guest Editors: Carlo Pirola, Antonio Espuña, Sabrina Copelli Copyright © 2025, AIDIC Servizi S.r.l. ISBN 979-12-81206-16-8; ISSN 2283-9216 Exergy Analysis of Biogas Production from Food Waste through Anaerobic Digestion Karittha Im-orba,*, Pakorn Piroonlerkgulb, aProgram in Food Process Engineering, School of Food-Industry, King Mongkut’s Institute of Technology Ladkrabang, Bangkok 10520, Thailand bPatum Vegetable Oil Company Limited, Lat Lum Kaeo, Pathum Thani 12140, Thailand karittha.im@kmitl.ac.th The anaerobic digestion (AD) of food waste with different fat concentration was studied. The impact of hydraulic retention time (HRT) and organic loading rates (OLR) at thermophilic condition of 55 oC on CH4 concentration, CH4 yield, and exegetic performance of AD system was investigated using the model developed in Aspen Plus software. The CH4 concentration and yield decreased as fat concentration increased. The CH4 yield increased with increasing OLR while the CH4 concentration did not change for each fat concentration. The maximum CH4 yield of 1.36E-5 kmol/h was found at OLR 1.5 l/day and HRT of 15 days when food waste with 5% fat concentration was used. The exergy analysis indicated that the irreversibility of AD caused the highest exergy loss, followed by the biogas, liquid sludge and net waste heat released from the system. The highest exergy efficiency of 35.52% was derived when OLR and HRT were set at 0.5 l/day and 25 days, respectively, and food waste with 5% fat concentration was used. At this condition the exergy destruction of 1.34 kW was found. 1. Introduction The problems of global warming caused from GHG emission and the reduction in fossil fuel availability enforce many countries to put the issue of renewable energy production as one of their top agenda to be able to move toward sustainability. Food waste is an organic waste that has massive environmental impact because it is a large source of potent GHG emissions. One-fifth of food produced for human consumption was globally wasted which generated up to 10 percent of global GHG emission (UNEP, 2024). Due to characteristic in term of high organic content (including protein, carbohydrate and fat) and fast degradability, food waste can be potentially converted to biogas via the AD. The biogas which mainly consisted of CH4 and CO2 can be directly used as fuel for cooking or upgraded to biomethane and used for power generation. Moreover, biogas can be raw material for H2 production (Rajendran et al., 2012). Therefore, reducing food waste by converting to biogas not only benefits to reduce GHG emission but also enhances the renewable energy production. Several studies investigated the biogas production from food waste via AD using the mathematical model. Moretta et al. (2022) studied an anaerobic co-digestion feedstock blending using the process model. The best blending conditions offering the highest methane yield was obtained. Menacho et al., (2022) investigated the influence of different fat concentration, HRT and OLR on concentration of methane. The result presented that the highest methane concentration of 77.1% was obtained at fat concentration of 60% and OLR of 5 l/day when the HRT was in a range of 10-20 days. Aguilar et al. (2017) studied the AD of the blended primary sludge and food waste at thermophilic and mesophilic conditions. It was found that at constant primary sludge: food waste ratio of 2:1, the methane concentration derived from mesophilic condition was 25% higher than thermophilic one. Moreover, the influence of food waste composition at HRT of 15 days on biogas production was investigated by Harun et al. (2019). The result indicated that the methane concentration of 53% and 55% was obtained at fat and carbohydrate concentration of 50% and 54.95%, respectively. The pH, which is an important parameter that can be adjusted by using sodium hydroxide and hydrochloric acid, influences biogas production from food waste. The optimal pH range of AD for biogas generation is between 6 and 8. Zhang et al. (2021) reported that pH control was important for achieving optimal process stability and maximizing methane recovery under high load. Maximum methane recovery was obtained with pH control at 7.5 under high load. 25 Although there were some studies examined the production of biogas from food waste, they were restricted in the parametric analysis investigating the influence of operating parameters on biogas yield. Nonetheless, the intensive study of the biogas production from food waste via the AD in term of exergetic performance to discover the drawback for enhancement of thermodynamic performance was limited. Therefore, the objective of this study is to perform the exergy analysis of the biogas production from food waste through AD at thermophilic condition of 55 oC. The effect of OLR (0.5, 1.0, and 1.5 l/day), HRT (15, 20 and 25 days), and fat concentration (5%, 10% and 15%) which has strong influence on methane content (Rasapoor et al., 2020), on the CH4 concentration, CH4 yield, and exergetic performance of the AD was investigated. 2. Model development The production of biogas from food waste via the AD consisted of 4 major steps i.e. 1) hydrolysis of organic substrates, 2) Acidogenesis of hydrolyzed monomers, 3) Acetogenesis of volatile fatty acids (VFA), and 4) Methanogenesis of acetogenesis products (Rajendran et al., 2014). Modeling of the biogas production through AD was performed in Aspen Plus software version 8.8 and a Non-Random Two-Liquid (NRTL) property method was selected to estimate the properties of substances. Firstly, the food waste (FW) was fed to a stoichiometric reactor (B1) that simulated the hydrolysis reactions operating at thermophilic conditions (55 oC) by specifying the stoichiometry and fractional conversion of reactants into products on a scale of 0.0-1.0, and then the hydrolyzed products entered a continuous stirred tank reactor (B2) that simulated acidogenesis, acetogenesis, and methanogenesis reactions by specifying kinetic constants obtained from previous literature. The first-order rate law was used to calculate the rate of reaction. Finally, the biogas (BIOGAS) and liquid sludge (LIQUID) were separated as final products. The reactions occur in AD were summarized in Table 1. And the flowsheet of AD model developed in aspen plus is shown in Figure 1. In this study, the rate of biogas production predicted from the developed AD model was validated against the experimental results which used cow manure as a substrate in a 5 l reactor with HRT of 12 days at OLR of 0.33 l/day and the biogas production of 353.5 l/ kgVSday was produced (Kaparaju et al., 2009). It was found that the 369 l/ kgVSday of biogas production calculated from the model was approximately 4% deviated from experimental data. Table 1: The related reactions in AD process (Rajendran et al., 2014) Reactions Compound Eq. hydrolysis reactions Conversion 2 6 2 2 4 2 42 2C H O CO C H O CH+ → + Ethanol 0.6 ± 0.1 (1) 5 8 4 2 5 10 5C H O H O C H O+ → Hemicellulose 0.6 ± 0.0 (2) 5 8 4 2 2 4 22.5C H O H O C H O+ → Hemicellulose 0.5 ± 0.2 (3) 5 10 5 5 4 2 23C H O C H O H O+ → Xylose 0.6 ± 0.0 (4) 6 12 6 2 2 6 22 2C H O H O C H O CO+ → + Cellulose 0.4 ± 0.1 (5) ( )6 12 6 2 6 12 6n C H O H O nC H O+ → Cellulose 0.4 ± 0.1 (6) ( )6 12 6 2 6 12 6n C H O H O nC H O+ → Starch 0.6 ± 0.2 (7) 2 2 5 2 3 7 2 3 7 3 3 6 2 4 7 4 4 9 3 5 9 4 5 9 2 5 11 2 6 14 4 2 6 13 2 6 13 2 9 11 2 . . 0.3337 0.25 0.047 0.172 0.067 0.048 0.047 0.074 0.111 0.074 0.045 0.046 0.07 0.036 I P H O C H NO C H NO C H NO C H NO S C H NO C H NO C H NO C H NO C H NO C H N O C H NO C H NO C H NO + → + + + + + + + + + + + + Insoluble protection (I.P.) 0.6 ± 0.1 (8) 13 25 7 3 2 2 4 4 26 6.5 6.5 3C H O N S H O CO CH H N H S+ → + + + Soluble protein 0.5 ± 0.2 (9) 37 68 5 2 3 8 3 16 34 18 32 24.3 2.2 0.9 0.9C H O H O C H O C H O C H O+ → + + Palmito-linolein 0.6 ± 0.2 (10) 37 70 5 2 3 8 3 16 34 18 34 24.1 2.1 0.9 0.9C H O H O C H O C H O C H O+ → + + Palmito-olein 0.6 ± 0.2 (11) 51 98 6 2 3 8 3 16 348.436 4 2.43C H O H O C H O C H O+ → + Tripalmate 0.5 ± 0.3 (12) 57 104 6 2 3 8 3 18 34 23 3C H O H O C H O C H O+ → + Triolein 0.5 ± 0.2 (13) Acidogenesis reactions Kinetic constant (s-1) 2 5 2 2 2 4 2 3C H NO H C H O H N+ → + Glycine 1.28 x 10-2 (14) 2 5 2 2 2 3 2 4 20.5 0.5 0.75C H NO H O CO H N C H O+ → + + Glycine 1.28 x 10-2 (15) 3 6 2 2 2 2 3 2 4 2 22 0.5C H NO S H O H H S H N C H O CO+ → + + + + Cysteine 1.28 x 10-2 (16) 3 7 2 2 3 2 2 4 2 22 2C H NO H O H N CO C H O H+ → + + + Alanine 1.28 x 10-2 (17) 3 7 3 2 3 2 2 4 2 2C H NO H O H N H C H O CO+ → + + + Serene 1.28 x 10-2 (18) 4 9 3 2 3 2 4 2 4 8 20.5C H NO H H N C H O C H O+ → + + Threonine 1.28 x 10-2 (19) 4 9 3 2 3 6 2 2 2 3C H NO H O C H O H CO H N+ → + + + Threonine 1.28 x 10-2 (20) 26 4 7 4 2 2 4 2 2 2 32 2 2C H NO H O C H O CO H H N+ → + + + Aspartic acid 1.28 x 10-2 (21) 5 9 2 2 2 3 2 4 3 6 2 5 10 2 0.5 0.5 0.5 C H NO H O H H N C H O C H O C H O + + → + + + Proline 1.28 x 10-2 (22) 5 9 4 2 2 4 2 4 8 2 2 30.5C H NO H O C H O C H O CO H N+ → + + + Glutamic acid 1.28 x 10-2 (23) 5 9 4 2 2 2 4 2 2 32 2C H NO H O CO C H O H H N+ → + + + Glutamic acid 1.28 x 10-2 (24) 5 11 2 2 2 3 6 2 4 2 3 2C H NO S H O CO C H O CH S H H N + → + + + + Methionine 1.28 x 10-2 (25) 5 11 2 2 2 3 4 8 2 22 2C H NO H O H H N C H O CO+ → + + + Valine 1.28 x 10-2 (26) 6 8 3 2 2 2 2 4 2 3 4 8 2 2 3 4 0.5 0.5 2 C H N O H O H C H O CH NO C H O CO H N + + → + + + + Histidine 1.28 x 10-2 (27) 6 8 3 2 2 2 4 2 3 3 2 2 5 2 2 0.5 C H N O H O C H O CH NO H N H CO + → + + + + Histidine 1.28 x 10-2 (28) 6 13 2 2 5 10 2 2 2 32 2C H NO H O C H O CO H H N+ → + + + Isoleucine 1.28 x 10-2 (29) 6 13 2 2 5 10 2 2 2 32 2C H NO H O C H O CO H H N+ → + + + Leucine 1.28 x 10-2 (30) 6 14 4 2 2 2 4 2 3 6 2 5 10 2 2 3 3 0.5 0.5 0.5 4 C H N O H H O C H O C H O C H O CO H N + + → + + + + Arginine 1.28 x 10-2 (31) 6 14 4 2 2 2 4 2 2 2 36 2 2 3 4C H N O H O C H O CO H H N+ → + + + Arginine 1.28 x 10-2 (32) 6 14 2 2 2 2 4 2 4 8 2 32 2C H N O H O C H O C H O H N+ → + + Lysine 1.28 x 10-2 (33) 9 11 3 2 6 6 2 4 2 2 2 32C H NO H O C H O C H O CO H H N+ → + + + + Tyrosine 1.28 x 10-2 (34) 9 11 2 2 6 6 2 4 2 2 2 32C H NO H O C H C H O CO H H N+ → + + + + Phenyalanine 1.28 x 10-2 (35) 11 12 2 2 2 8 7 2 4 2 2 2 32C H N O H O C H N C H O CO H H N+ → + + + + Typtophan 1.28 x 10-2 (36) Acidogenic reactions 3 8 3 2 2 3 5 7 2 3 6 2 2 0.0005 0.0291 0.4071 0.04071 0.94185 1.09308 C H O H CO H N C H NO C H O H O + + + → + + Dextrose 1.01 x 10-2 (37) 6 12 8 3 2 4 2 3 6 2 5 7 2 4 8 2 2 2 0.1115 0.744 0.5 0.1115 0.4409 1.0254 0.6909 C H O H N C H O C H O C H NO C H O H O CO + → + + + + + Glycerol 9.54 x 10-3 (38) Acetogenic reactions 3 6 2 2 3 4 2 4 2 5 7 2 2 2 0.314336 0.06198 0.660412 0.9345 0.06198 0.00055 0.160688 C H O H O H N CH C H O C H NO H CO + + → + + + + Propionic acid 1.95 x 10-7 (39) 4 8 2 2 2 3 2 4 2 4 2 5 7 2 0.0006 0.8038 0.0653 0.5543 0.446 1.8909 0.0653 C H O H H O H N CO CH C H O C H NO + + + + → + + Isobutyric acid 5.88 x 10-6 (40) 5 10 2 2 3 2 4 2 4 2 3 6 2 5 7 2 2 0.8044 0.0653 0.5543 0.4454 0.8912 0.0653 0.0006 C H O H O H N CO CH C H O C H O C H NO H + + + → + + + + Isovaleric acid 3.01 x 10-8 (41) 16 34 3 2 2 2 4 2 5 7 2 2 0.1701 0.482 15.253 8.4402 0.1701 14.9748 C H O H N CO H O C H O C H NO H + + + → + + Palmitic acid 3.64 x 10-12 (42) 18 32 2 3 2 2 2 4 2 5 7 2 2 0.1701 15.356 0.482 9.02 0.1701 10.0723 C H O H N H O CO C H O C H NO H + + + → + + Linoleic acid 3.64 x 10-12 (43) 18 34 2 2 2 3 2 4 2 5 7 2 2 15.2396 0.2501 0.1701 8.6998 0.1701 14.4978 C H O H O CO H N C H O C H NO H + + + → + + Oleic acid 3.64 x 10-12 (44) Methanogenic reactions 2 3 2 4 5 7 2 2 14.4976 0.0836 3.8334 3.4154 0.0836 7.4996 H H N CO CH C H NO H O + + → + + Hydrogen 2.39 x 10-3 (45) 2 4 2 3 4 5 7 2 2 2 0.022 0.945 0.022 0.945 0.066 C H O H N CH C H NO CO H O + → + + + Acetic acid 2.39 x 10-3 (46) Figure 1: Aspen plus model flowsheet of the AD. B1 B2 FW S2 LIQUID BIOGAS 27 3. Exergy analysis Exergy analysis regarded to the first and the second law of thermodynamic was done to assess the thermodynamic performance of the energy production process. Exergy analysis was studied by doing exergy balance for steady state process. The equations used in exergy analysis were summarized in Table 2. Table 2: The equations used in exergy analysis (Kasemanand et al., 2017) Eq. Exergy balance ( ) ( )i in j out destEx Ex Ex= +   (47) Exergy of material ph chEx Ex Ex= + (48) Physical exergy 0 0 0( ) ( )phEx H H T S S= − − − (49) Chemical exergy , 0( ln )ch i ch i i i Ex x Ex RT x= − (50) Exergy related to heat transfer 0(1 )Q T Ex Q T = − Exergy efficiency 100 output input Ex Ex  =    (51) Exergy destruction ( ) ( )dest i in i outEx Ex Ex= −  (52) 4. Results and discussions 4.1 Effect of OLR and HRT on CH4 concentration and yield The effect of OLR (0.5, 1.0 and 1.5 l/day) of AD of food waste with different fat concentration of 5%, 10% and 15% on CH4 concentration and yield was investigated at constant HRT of 15 days. Figure 2(a) indicated that the CH4 concentration decreased as fat concentration increased at constant OLR but CH4 concentration did not change with OLR. The CH4 yield increased with OLR while slightly decreased as the fat concentration increased (Figure 2(b)). At HRT of 15 days, the highest CH4 concentration of 43.68 %mol and CH4 yield of 1.4E-6 kmol/h was achieved at OLR of 1.5 l/day when food waste with 5% fat concentration was used. The effect of HRT (15, 20 and 25 days) of AD of food waste with different fat concentration of 5%, 10% and 15% was examined at constant OLR of 0.5 l/day. Figure 3(a) showed that the CH4 concentration decreased as fat concentration increased whereas increased with increasing HRT. The result was consistent with the previous literature (Harun et al., 2019). The CH4 yield decreased as fat concentration increased whereas increased with increasing HRT as illustrated in Figure 3(b). At OLR of 0.5 l/day, the suitable condition offering maximum CH4 concentration of 43.79 %mol and yield of 5.0E-6 kmol/h was achieved at HRT of 25 days when food waste with 5% fat concentration was used. (a) (b) Figure 2: Effect of OLR on (a) CH4 concentration and (b) CH4 yield at HRT of 15 days (a) (b) Figure 3: Effect of HRT on (a) CH4 concentration and (b) CH4 yield at OLR of 0.5 l/day 43.666 43.668 43.67 43.672 43.674 43.676 0.5 1 1.5 C H 4 c o n c e n tr a ti o n ( % m o l) OLR (l/day) Fat 5% Fat 10% Fat 15% 0 2 4 6 8 10 12 14 16 0.5 1 1.5 C H 4 y ie ld ( x 1 0 -6 k m o t/ h ) OLR (l/day) Fat 5% Fat 10% Fat 15% 43.60 43.65 43.70 43.75 43.80 43.85 15 20 25C H 4 c o n c e n tr a ti o n ( % m o l) HRT (days) Fat 5% Fat 10% Fat 15% 4.40 4.45 4.50 4.55 4.60 4.65 4.70 15 20 25 C H 4 y ie ld ( x 1 0 -6 k m o t/ h ) HRT (days) Fat 5% Fat 10% Fat 15% 28 4.2 Effect of OLR on exergy efficiency and destruction of AD The effect of OLR on exergy efficiency and destruction of the AD was studied by varying the OLR in a range of 0.5-1.5 l/day at HRT of 15 days. Table 2 showed that at OLR of 0.5 l/day, the exergy efficiency increased with increasing fat concentration whereas the opposite trend was found when OLR was in a rage of 1.0-1.5 l/day. For the exergy destruction, the fat concentration had slightly effect on the exergy destruction for each OLR but the exergy destruction increased with increasing OLR due to an increase in irreversibility of AD for biogas production. The highest exergy efficiency of 34.52% was attained at OLR of 0.5 l/day when food waste with fat concentration of 15% was used. At this condition the lowest exergy destruction of 1.34 kW was found. Table 2: Effect of OLR on exergy efficiency and destruction of AD at HRT 0f 15 days Fat concentration (%mol) OLR (l/day) 0.5 1.0 1.5  (%) destEx (kW)  (%) destEx (kW)  (%) destEx (kW) 5 34.512 1.355 34.512 2.709 34.512 4.064 10 34.516 1.348 34.506 2.696 34.506 4.044 15 34.522 1.340 34.502 2.681 34.502 4.021 4.3 Effect of HRT on exergy efficiency and destruction of AD The effect of HRT on exergy efficiency and destruction of the AD was examined by varying the HRT in a range of 15 to 25 days at OLR of 0.5 l/day. Table 3 indicated that the exergy efficiency increased as HRT increased for each fat concentration whereas the exergy destruction showed contrary trend. At OLR of 0.5 l/day, the highest exergy efficiency of 35.312% was achieved at HRT of 25 days and food waste with fat concentration of 5% was used. At this condition the exergy destruction of 1.34 kW was found. Table 3: Effect of HRT on exergy efficiency and destruction of AD at OLR of 0.5 l/day Fat concentration (%mol) HRT (days) 15 20 25  (%) destEx (kW)  (%) destEx (kW)  (%) destEx (kW) 5 34.512 1.355 34.937 1.346 35.312 1.338 10 34.516 1.348 34.932 1.339 35.307 1.331 15 34.522 1.340 34.927 1.332 35.302 1.324 4.4 The exergy flows through the AD The exergy flows through the top two high exergy efficient AD units of food waste i.e., case 1) food waste with 5% fat concentration, OLR 0.5 l/day, HRT 25 days (Figure 4), and case 2) food waste with 15% fat concentration, OLR 0.5 l/day, HRT 15 days (Figure 5), were investigated. The highest exergy loss caused from irreversibility of anerobic digestion, followed by the biogas, liquid sludge and net waste heat released from the AD unit, respectively. For case 1, the exergy loss associated with irreversibility of AD, the biogas, liquid sludge and net waste heat accounted for 64.69%, 23.19%, 9.16% and 2.96%, respectively. For case 2, the exergy loss associated with irreversibility of AD, the biogas, liquid sludge and net waste heat accounted for 65.49%, 22.46%, 9.16% and 2.89%, respectively. (a) (b) Figure 4: Exergy flow through the AD of food waste a) case1, and b) case2 29 5. Conclusions The AD of food waste with different fat concentration was investigated in this study. The influence of fat concentration of food waste (5%, 10%, and 15%), HRT (15, 20, and 25 days) and OLR (0.5, 1.0, and 1.5 l/day) on the CH4 concentration, CH4 yield and exergetic performance of AD at thermophilic condition of 55 oC was investigated using the model developed in Aspen plus. The CH4 concentration and CH4 yield decreased as fat concentration of food waste increased. The exergy flows through the AD indicated that the highest exergy loss caused from irreversibility of AD, followed by the biogas, liquid sludge, and net waste heat released from the AD unit. The maximum exergy efficiency of 35.52% was attained at OLR of 0.5 l/day and HRT of 15 days when food waste with fat concentration of 5% was used. At this condition, CH4 concentration and yield were 43.67 %mol and 1.36E-5 kmol/h, respectively. Nevertheless, to justify which condition was the most suitable condition, the economic analysis should be further performed. Nomenclature Ex – exergy of material, kW chEx – chemical exergy, kW phEx – physical exergy, kW destEx – exergy destruction, kW inputEx – exergy input to the system, kW outputEx – exergy output to the system, kW QEx – exergy related to heat transfer, kW H – enthalpy, kW 0H – enthalpy at reference condition, kW Q – net heat transfer, kW R – gas constant, 8.314 J/mol K S – entropy, J/mol K 0S – entropy at reference condition, J/mol K 0H – enthalpy at reference condition, kW T – operating temperature, oC 0T – reference temperature, oC ix – mole fraction of component i, -  – exergy efficiency, % Acknowledgments This work was supported by School of Food industry, King Mongkut’s institute of Technology Ladkrabang. References Aguilar M.C., Wang Y.D., Roskilly T., Pathare P.B., 2017, Biogas from anaerobic co-digestion of food waste and primary sludge for cogeneration of power and heat, Energy Procedia, 142, 70–76. 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