Next Article in Journal
Assessing the Static Security of the Italian Grid by Means of the N-1 Three-Phase Contingency Analysis
Next Article in Special Issue
Optimization of Energy Recovery Processes from Sunflower Stalks Using Expired Non-Steroidal Anti-Inflammatory Drugs (NSAIDs)
Previous Article in Journal
Investigating PEM Fuel Cells as an Alternative Power Source for Electric UAVs: Modeling, Optimization, and Performance Analysis
Previous Article in Special Issue
Qualities and Quantities of Poultry Litter Biochar Characterization and Investigation
 
 
Font Type:
Arial Georgia Verdana
Font Size:
Aa Aa Aa
Line Spacing:
Column Width:
Background:
Article

Biogas Potential of Food Waste-Recycling Wastewater after Oil–Water Separation

1
Eco-Technology Research Team, Technology Research Center, Hyundai Engineering & Construction, 75 Yulgok-ro, Jongno-gu, Seoul 03058, Republic of Korea
2
Future Convergence Technology Research Institute, Gyeongsang National University, 501 Jinjudae-ro, Jinju 52828, Republic of Korea
3
Department of Energy Engineering, Gyeongsang National University, 501 Jinjudae-ro, Jinju 52828, Republic of Korea
*
Author to whom correspondence should be addressed.
These authors contributed equally to this work.
Energies 2024, 17(17), 4428; https://doi.org/10.3390/en17174428
Submission received: 14 August 2024 / Revised: 27 August 2024 / Accepted: 2 September 2024 / Published: 4 September 2024
(This article belongs to the Special Issue Biomass and Bio-Energy—2nd Edition)

Abstract

:
This study explores the potential of food waste-recycling wastewater (FRW) for biogas production, emphasizing oil–water separation before anaerobic digestion. Three FRW samples were analyzed: non-treated (FRW), water–oil separated (FRW_sep), and mixed with domestic sewage (FRW_mix). Physicochemical characterization showed a 26% reduction in crude lipid content after oil–water separation. The biochemical methane potential (BMP) tests revealed similar methane yields for FRW_sep and FRW_mix compared to non-treated FRW. Microbial analysis identified Firmicutes and Methanoculleus as active populations. Energy balance suggests that combining biodiesel and biogas production can enhance net energy recovery. This research indicates that oil–water separation in FRW treatment can optimize anaerobic digestion, contributing to sustainable waste management and renewable energy generation.

1. Introduction

Food waste is one of the significant organic waste streams in most countries. Yearly, ca. 1.3 billion tons of food waste is discharged worldwide [1]. Korea generated 5.0 million tons of food waste in 2022, and 96.8% of this has been recycled by various means, such as composting, converting to animal feed, and recovering energy by anaerobic digestion [2]. The former two recycling methods (i.e., compost and animal feed) account for approximately 75% of the total treatment volume. However, the recycling process inevitably generates leachate, condensate, and other wastewater from washing, which equal approximately 70% of the food waste recycled. This food waste-recycling wastewater (FRW) has been regarded as an attractive feedstock for anaerobic digestion due to its large generation volume and high biodegradability [3]. Both the single digestion of FRW and the co-digestion of it with other organic wastes have been reported [4,5,6]. Currently, dozens of biogas plants that treat FRW as the sole feedstock or one of the co-digestion substrates are being operated in Korea.
The organic materials in food waste and FRW mainly comprise crude carbohydrates, crude protein, and crude lipids [7]. Among these, the separation of crude lipids before anaerobic digestion could be beneficial because (1) this separation can be accomplished relatively easily by an oil–water separator and (2) the separated lipid can be collected for external use, such as biodiesel or bio-oil production. Although oil–water separation has been studied for different biofuel production [8], this separation strategy has been highlighted by only a few studies for FRW [9], and no study has yet reported its utilization as a biogas feedstock.
The current treatment technologies for food waste include anaerobic digestion, composting, landfilling, thermal treatment, hydrothermal treatment, refuse-derived fuel (RDF) production, oil–water separation, and black soldier larvae (BSL) conversion [10,11]. Among these, anaerobic digestion is regarded as one of the best technologies [12]. Composting, thermal treatment, RDF, and BSF were highlighted for their potential to produce energy or resources from the waste [10]. Oil–water separation of high-oil wastewater has been suggested to improve the feasibility of the recycling process [11]. New technical advancements are being assessed based on technical performance, economic feasibility, and life-cycle assessment.
This paper was conducted to test the biogas production potential of an oil–water-separated FRW. The FRWs before and after separation were taken from a local food waste-to-animal feed recycling plant in Korea. The recycling processes of the facility comprise (1) washing, (2) chopping, (3) steaming for sterilization, and (4) drying. Besides the two FRW samples, a third sample was tested to be mixed with FRW and domestic sewage generated from and near the facility (5:1, v/v). The samples were characterized physicochemically, and a biochemical methane potential (BMP) test was conducted to estimate the capability of biogas production. The growth of key microbes during the anaerobic digestion was analyzed using high-throughput sequencing. The potential pros and cons of using oil–water separation for FRW anaerobic digestion are discussed.

2. Materials and Methods

2.1. Sampling and Analysis

Three types of differently treated FRW samples were sampled in duplicates from the public food waste-recycling facility in Changwon city, Republic of Korea. The three FRW samples included non-treated FRW (designated as FRW hereafter), water–oil separated FRW (FRW_sep), and FRW mixed with domestic sewage after water–oil separation (FRW_mix). The oil–water separation system was equipped with a centrifugal three-phase separator to separate oil, water, and solids (June Bio Co., Hwaseong city, Republic of Korea). The samples were characterized in terms of pH, total solids (TS), volatile solids (VS), chemical oxygen demand (COD), crude carbohydrate, crude protein, and crude lipid levels. The pH, solids, and COD were measured following the standard methods [13]. The crude carbohydrate content was analyzed using the phenol-sulfuric acid method [14]. The crude protein content was quantified according to the Dumas method [15], assuming 6.25 g protein for 1 g organic nitrogen, where the organic nitrogen was measured using an elemental analyzer (rapid N cube, Elementar Analysensysteme GmbH, Langenselbold, Germany). The crude lipid content was determined using gravimetry after extraction with a solvent (chloroform:methanol = 1:2, v/v) [16]. All physicochemical analyses except for pH were conducted in duplicate.

2.2. Biochemical Methane Potential (BMP) Assay

The BMP tests were performed in serum bottles with a working volume of 60 mL. The sampled substrates were tested in duplicate (3 types of substrate × duplicated sampling × duplicated BMP = 12 bottles), and two blank bottles containing only inoculum were additionally tested to correct for the background methane potential of the inoculum (total of 14 bottles). The reaction mixture in each bottle contained 2.5 g VS/L of substrate, 5 g VS/L of inoculum, and the basal medium. The inoculum was taken from a full-scale mesophilic anaerobic digester treating sewage sludge in Jinju, Republic of Korea (pH 7.86, 16.08 g VS/L). The basal medium was slightly modified from a previous study [17], containing (L−1): K2HPO4·3H2O, 0.4 g; NH4Cl, 1 g; NaCl, 0.1 g; MgCl2·6H2O, 0.4 g; CaCl2·2H2O, 0.25 g; FeCl2·4H2O, 2 mg; H3BO3, 0.05 mg; ZnCl2, 0.1 mg; CuCl2·2H2O, 0.13 mg; MnCl2·4H2O, 0.1 mg; (NH4)6Mo7O24·4H2O, 0.19 mg; AlCl3, 0.05 mg; CoCl2·6H2O, 0.19 mg; NiCl2·6H2O, 0.1 mg; EDTA, 0.5 mg; Na2SeO3·5H2O, 0.1 mg; Na2WO4·2H2O, 0.04 mg; biotin, 0.02 mg; folic acid, 0.02 mg; pyridoxine acid, 0.1 mg; thiamine hydrochloride, 0.05 mg; riboflavin, 0.05 mg; nicotinic acid, 0.05 mg; DL-pantothenic acid, 0.05 mg; cyanocobalamin, 0.001 mg; p-aminobenzoic acid, 0.05 mg; lipoic acid, 0.05 mg; resazurin, 0.5 g; and NaHCO3, 1.3 g. After sealing the bottles, the headspace was purged with N2/CO2 (80:20, v/v) for 3 min. The bottles were placed at 35 °C and hand-shaken before each pressure monitoring event, which was performed using a digital manometer (LEO2, Keller, Winterthur, Switzerland). The pressure was converted to the volume of biogas by following the ideal gas equation. The termination of the BMP assay was assumed when the daily biogas production volume was less than 1% of the accumulated biogas production volume [18]. The biogas production volume was also checked using a gas-tight syringe. The composition of biogas was measured using a gas chromatograph (GC-2030, Shimadzu, Tokyo, Japan) equipped with a thermal conductivity detector and a capillary column (GS-Carbon Plot, Agilent, Santa Clara, CA, USA).

2.3. DNA Extraction and High-Throughput Sequencing

After the end of the BMP test, equal volumes of digestate were collected and pooled from the duplicate bottles. Then, 0.2 mL of the pooled samples were centrifuged (15,000× g, 5 min) to remove the supernatant. The pellets of 7 samples (3 types of substrate × duplicated sampling + 1 pooled from the blank assay) were processed for DNA extraction using the AccuPrep genomic DNA extraction kit (Bioneer, Daejeon, Republic of Korea). The amplicon sequencing was performed according to the manufacturer’s instructions (Illumina, San Diego, CA, USA). Oligomers containing the Illumina overhang adapter sequence as well as the following 16S rDNA region-specific sequence were used as amplicon primers: V3–4 region for bacteria, 518F (5′-CCAGCAGCCGCGGTAATACG-3′) and 805R (5′-GACTACCAGGGTATCTAATCC-3′) [19,20]; and V4–5 region for archaea, 787F (5′-ATTAGATACCCSBGTAGTCC-3′) and 1059R (5′-GCCATGCACCWCCTCT-3′) [20]. The purified amplicons were PCR-indexed using the Illumina Nextera XT index kit. The purified library was quantified, pooled, and combined with the PhiX control (Illumina). The library was paired-end (151 bp × 2) sequenced using the iSeq 100 platform (Illumina) at Gyeongsang National University. The sequencing results were analyzed using an in-house pipeline [21]. The paired reads were merged and processed to remove short or low-quality sequences and potential chimeras. Operational taxonomic units (OTUs) were defined at 97% sequence-identity cutoff using the VSEARCH algorithm [22]. A taxonomic assignment was conducted online using the RDP classifier (https://rdp.cme.msu.edu/classifier/ (accessed on 30 November 2020)).

3. Results

3.1. Sample Characterization

Three types of differently treated FRW samples, non-treated (FRW), water–oil separated (FRW_sep), and mixed with domestic sewage after water–oil separation (FRW_mix), were analyzed in terms of pH, TS, VS, COD, carbohydrate, protein, and lipid (Table 1 and Figure 1). The pH measurements showed that the FRW gradually became more acidic as it underwent further treatment: pH 4.24 ± 0.06 in the untreated FRW, 4.04 ± 0.00 after the water–oil separation, and pH 3.86 ± 0.04 after mixing with domestic sewage. The average TS was 73.37 ± 0.28 g/L, 58.30 ± 0.86 g/L, and 48.49 ± 1.54 g/L, and the average VS was 63.38 ± 0.23 g/L, 50.37 ± 0.80 g/L, and 41.74 ± 1.49 g/L for FRW, FRW_sep, and FRW_mix, respectively. These two parameters also showed a declining tendency from FRW to FRW_sep and FRW_mix. Likewise, COD (97.75 ± 3.75 g/L, 91.28 ± 10.26 g/L, and 72.55 ± 1.30 g/L), crude carbohydrate (21.39 ± 0.65 g/L, 14.28 ± 0.77 g/L, and 10.10 ± 0.63 g/L), crude protein (18.58 ± 0.42 g/L, 16.53 ± 0.41 g/L, and 14.37 ± 0.28 g/L), and crude lipid (14.50 ± 0.30 g/L, 10.73 ± 0.40 g/L, and 9.83 ± 0.72 g/L) were the highest for FRW and the lowest for FRW_mix.
The parameters of FWR_sep were reduced at different ratios than those of FWR (Figure 1). The reduction ratios of the TS, VS, COD, carbohydrate, protein, and lipid concentrations of FWR_sep were 20.5%, 20.5%, 6.6%, 33.2%, 11.0%, and 26.0%, respectively. The most significant gap was observed for carbohydrate (33.2%), followed by lipid (26.0%). COD was the only parameter with less than 10% gap (6.6%) between the two samples. The parameter values of FWR_mix were 16.8%, 17.1%, 20.5%, 29.3%, 13.1%, and 8.4% lower than those of FWR_sep for TS, VS, COD, carbohydrate, protein, and lipid, respectively. Unlike FWR and FWR_sep, the reduction ratios for the general parameters (TS, VS, and COD) were similar between FWR_sep and FWR_mix but varied for the other specific parameters.

3.2. Biogas Potential Assessment through BMP Assay

The BMP assays were conducted to estimate the biogas production potential of the three FWR samples (Figure 2). The anaerobic digestion reaction was completed by 27 days of batch operation for all three samples. The accumulated biogas production volumes at the endpoint were 750 ± 28 N mL/g VS, 799 ± 31 N mL/g VS, and 790 ± 22 N mL/g vs. for the FRW, FRW_sep, and FRW_mix samples, respectively. The CH4 composition of the biogas was 61.9%, 67.8%, and 72.6% for FRW, FRW_sep, and FRW_mix; and the CH4 production potential was estimated as 465 N mL CH4/g VS, 541 N mL CH4/g VS, and 573 N mL CH4/g VS for FRW, FRW_sep, and FRW_mix, respectively.
The biogas production profiles showed diauxic patterns rather than a simple sigmoidal growth pattern. The biogas production rates initially showed local maxima of 74–85 N mL/g VS for the first two days, but then they slowed down until day 7. After day 7, the biogas production rates started to elevate again, reaching 95–111 N mL/g VS at day 10. After that, the biogas production rates decreased in all three reactors to reach a plateau by day 27. Due to the diauxic growth patterns, neither the modified Gompertz model nor the first-order model fitted well with the biogas data.

3.3. Microbial Community Results

After the end of the BMP tests, the digestate samples were prepared from the bottles to analyze the bacterial and archaeal communities. Overall, 11 bacterial phyla were identified in the samples (Table 2). Firmicutes (62.0 ± 1.8%), Cloacimonetes (11.6 ± 0.4%), Proteobacteria (6.5 ± 0.4%), and Bacteroidetes (3.7 ± 0.2%) were the most prominent phyla (83.9 ± 1.1% in total) from anaerobic digestion of the differently treated FRW samples. The population variation between the differently treated FRW assays was insignificant for the bacterial communities. In contrast, the blank assay showed a significantly different bacterial community profile, with a much lower Firmicutes (32.1%) level but much higher Cloacimonetes (18.3%) and Proteobacteria (14.5%) levels. In addition, Armatimonadetes (0.5%) was underrepresented in the blank assay compared to the FRW assays, while Planctomycetes (1.2%) and Actinobacteria (1.1%) were overrepresented.
Five genera were revealed for the archaeal community analysis (Table 3). Methanolinea (61.9 ± 1.7%), Methanoculleus (24.6 ± 1.7%), Methanothrix (9.4 ± 0.4%), Methanospirillum (4.0 ± 0.2%), and Methanobrevibacter (0.1 ± 0.0%) summed up all the archaea from anaerobic digestion of the differently treated FRW samples in this study. Similar to bacteria, the archaeal populations were not significantly different for BMP bottles fed with FRW variations. However, the archaea in the blank assay showed distinct populations, with higher Methanolinea (78.1%), Methanothrix (11.8%), Methanospirillum (6.3%), and Methanobrevibacter (0.3%) levels and a lower Methanoculleus (3.6%) level.

4. Discussion

Using food waste and its derivatives as energy sources has recently been increasingly emphasized. Biodiesel, bioethanol, biohydrogen, bio-oil, biochar, and biogas (CH4) are among the efficient valorization technologies for food waste [23]. Among them, biogas reaches the commercial level of technical readiness, with multiple commercial-scale food waste and FRW treatment facilities in operation. Crude carbohydrates, crude protein, and crude lipids comprise food waste’s main organic constituents and FRW. Although many carbohydrates are readily biodegradable in anaerobic digestion, food waste’s anaerobic proteolysis and lipolysis often lead to less complete bioconversion to CH4. On the other hand, lipids extracted from oily biomass or recycled from wastes/byproducts can be converted to biodiesel through transesterification [24]. As lipids account for approximately 13–30% of food waste [25] or approximately 37% of FRW, separating lipids for biodiesel conversion before anaerobic digestion could be a viable option to recover energy from food waste or FRW.
In this regard, an energy balance estimation was conducted to compare two possible scenarios of FRW utilization (Table 4). For the treatment of 100 m3/day FRW, Scenario 1 assumes all the FRW is directly treated by anaerobic digestion. In contrast, Scenario 2 employs an oil–water separation for biodiesel production, and the remainder is used for biogas production. With 5% loss during oil–water separation and 0.5% yield of biodiesel (personal communication, Sewon E&E, Youngcheon city, Republic of Korea), Scenario 1 generates 105,500 MJ/day of energy (100% biogas), and Scenario 2 produces net 108,318 MJ/day of energy (85% biogas and 15% biodiesel). Although this comparison is rooted in a simplified calculation that excludes detailed energy costs for anaerobic digestion, transesterification, and purification, it gives a clear idea that combined biodiesel and biogas operations could be a feasible scenario for FRW. The characteristics of the material can tune the energy balance. The VS and the lipid contents of the FRW used in this study were, respectively, 63.4 g/L and 22.9% of the VS; these values were comparable to those in a previous study [26]. This means that the energy balance of Scenario 2 may be improved for a more lipid-rich substrate. Notably, the economic impact of employing biodiesel production can also be leveraged by the market price of biofuels (i.e., biogas, biomethane, and biodiesel). These results imply that the system involving Scenario 2 (with oil–water separation) has higher energy throughput and more versatility to respond to the energy market. It should be noted that the economic feasibility of introducing an oil–water separator into the food waste-recycling system needs to be evaluated in a future study to support decision-making.
The FRW samples used in this study showed acidic characteristics (Table 1). The acidity of FRW is shared with food waste [28], likely due to a partial fermentation of carbohydrates during the transportation and storage steps. This is probably why the pH values declined as the FRW went through more steps (i.e., oil–water separation and mixing with sewage) in this study. Following this explanation, the most abundant macromolecules in the VS of the untreated FRW were carbohydrates (21.39 ± 0.65 g/L), but they decreased by 33.2% and 52.8% in FRW_sep (14.28 ± 0.77 g/L) and FRW_mix (10.10 ± 0.63), respectively, compared to the untreated FRW. In the untreated FRW, carbohydrates were the most abundant organic macromolecules rather than protein and lipid, but in the FRW_sep and FRW_mix samples, the protein content was the highest. The protein content was reduced by 11.0% and 22.6% in FRW_sep (16.53 ± 0.41 g/L) and FRW_mix (14.37 ± 0.28 g/L), respectively, compared to the untreated FRW (18.58 ± 0.42 g/L) samples.
The lipid content in the FRW_sep (10.73 ± 0.40 g/L) was 26.0% lower than that in the FRW (14.50 ± 0.30 g/L) (Figure 1). The oil–water separation significantly removed crude lipids from the FRW sample. However, the lipid removal (26.0%) was far from perfection, and the FRW_sep sample containing the remaining lipid was tested as a substrate for anaerobic digestion, which led to a comparable BMP (Figure 2). When observed by the naked eye, removing the lipid layer was evident in the FRW_sep sample. This indicates that the oil–water separation process effectively removed the lipid layer but did not guarantee a complete removal of some lipids in the water phase.
The batch anaerobic digestion of the FRW samples showed diauxic growth patterns in this study (Figure 2). Diauxic growth profiles are often observed in anaerobic digestion of complex materials [29]. Kim and Kim [30] explained that a diauxic pattern is derived from the two-phase decomposition of high-carbohydrate and high-fat portions following the adaptation of the microorganisms. Gomes et al. [31] have shown that the two-phase Gompertz model successfully fits diauxic biogas production profiles from the anaerobic digestion of gelatin. A substrate-to-inoculum ratio higher than 1.4 was accompanied by the diauxic pattern. The first peak was attributed to the hydrolysis of gelatin and the beginning of acidogenesis, while the second peak was likely the result of methanogenesis. The FRW samples used in this study had both high carbohydrate and lipid contents, suggesting that the diauxic growth occurred by the sequential biodegradation of the two macromolecules and/or the delay in hydrolysis–acidogenesis and methanogenesis using these substrates.
The three samples (FRW, FRW_sep, and FRW_mix) showed similar amounts of biogas evolution from the BMP test (Figure 2). This is likely the combination of the waste characteristics and the biodegradability. Carbohydrates have a lower chemical oxygen demand (COD) per VS ratio of 1.13, while protein and lipid ratios are 1.20 and 2.03 [32]. The higher the COD, the more CH4 production is expected from the feedstock. Therefore, more CH4 is expected from lipid degradation than an equal mass of protein or carbohydrate. On the other hand, carbohydrates are generally highly biodegradable in anaerobic digestion, while biodegradability is usually lower for lipids and proteins [33]. Thus, combining the two factors, the organic composition and the biodegradability, should have collectively yielded biogas production. It should be noted that the addition of the domestic sewage did not significantly affect the biogas production per VS, probably due to the relatively low volume (ca. 5%) of domestic sewage introduced and the similar composition (such as carbohydrates and proteins) of the organics in domestic sewage [34].
Considering that the blank was not fed with an external substrate for the batch operation, the bacterial community in the blank sample should be similar to that of the inoculum. After the batch operation, the relative abundance of some bacteria and archaea increased while that of others decreased (Table 2 and Table 3). Firmicutes is known for its versatility to utilize various organic compounds and has been identified as one of the major bacteria in food waste digestion [35]. Methanoculleus, a hydrogenotrophic methanogenic genus, has been reported as the dominant archaeal population in anaerobic digestion of food waste leachate [26]. The FRW-fed anaerobic digestion in this study has increased the relative abundance of these two taxa, implying their active roles in the biogas production from FRW.

5. Conclusions

This study underscores the potential of using oil–water-separated FRW for biogas production. The assessment of three different FRW samples revealed that oil–water separation reduced a quarter of the crude lipid content, which can be repurposed for biodiesel production. The BMP test demonstrated that separated FRW samples exhibit significant methane production, comparable to non-treated samples. The microbial community analysis indicated distinct bacterial and archaeal populations adapted to the different substrates. Combining biodiesel and biogas production strategies could enhance energy recovery from FRW, offering a feasible and efficient approach for waste management and renewable energy generation.

Author Contributions

Conceptualization, G.H.; methodology, G.H. and J.S.; investigation, J.S. and M.-E.L.; writing—original draft preparation, G.H. and J.S.; writing—review and editing, all authors; supervision, S.G.S.; funding acquisition, S.G.S., G.H. and J.S. contributed equally to this work. All authors have read and agreed to the published version of the manuscript.

Funding

This work was supported by the Korea Environment Industry & Technology Institute (KEITI) through Research and development project for resource and energy recovery type high-concentration wastewater and sewage treatment process Program, funded by Korea Ministry of Environment (MOE) (RS-2022-KE002038) and through its Ecological Imitation-based Environmental Pollution Management Technology funded by MOE (2019002790004). This research was also supported by the 2021 Post-Doc. Fellowship Program of Gyeongsang National University.

Data Availability Statement

The data presented in this study are available on request from the corresponding author due to privacy.

Conflicts of Interest

Author Gyuseong Han was employed by the company Hyundai Engineering & Construction. The remaining authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

References

  1. Sravani, A.; Patil, C.R.; Sharma, S. Value-Added Product Development Utilising the Food Wastes. In Valorization of Biomass Wastes for Environmental Sustainability: Green Practices for the Rural Circular Economy; Srivastav, A.L., Bhardwaj, A.K., Kumar, M., Eds.; Springer Nature Switzerland: Cham, Switzerland, 2024; pp. 287–301. [Google Scholar]
  2. MoE. Statistical Data of Korean Waste Generation and Treatment; Ministry of Environment: Sejong, Republic of Korea, 2023.
  3. Lee, E.; Jin Min, K.; Choi, H.; Young Park, K. Impact of dewatering inorganic coagulants on anaerobic digestion treating food waste leachate. Bioresour. Technol. 2024, 393, 130136. [Google Scholar] [CrossRef]
  4. Bae, J.S.; Yoon, Y.M.; Shin, S.K.; Lee, D.J.; Seo, D.C. Biogas potential and methanogenic community shift in in-situ anaerobic sewage sludge digestion with food waste leachate additions. Appl. Biol. Chem. 2020, 63, 62. [Google Scholar] [CrossRef]
  5. Pham, V.H.T.; Ahn, J.; Kim, J.; Lee, S.; Lee, I.; Kim, S.; Chang, S.; Chung, W. Volatile fatty acid production from food waste leachate using enriched bacterial culture and soil bacteria as co-digester. Sustainability 2021, 13, 9606. [Google Scholar] [CrossRef]
  6. Zhang, H.; Fu, Z.; Guan, D.; Zhao, J.; Wang, Y.; Zhang, Q.; Xie, J.; Sun, Y.; Guo, L.; Wang, D. A comprehensive review on food waste anaerobic co-digestion: Current situation and research prospect. Process Saf. Environ. Prot. 2023, 179, 546–558. [Google Scholar] [CrossRef]
  7. Zhang, R.; El-Mashad, H.M.; Hartman, K.; Wang, F.; Liu, G.; Choate, C.; Gamble, P. Characterization of food waste as feedstock for anaerobic digestion. Bioresour. Technol. 2007, 98, 929–935. [Google Scholar] [CrossRef]
  8. Karmee, S.K. Liquid biofuels from food waste: Current trends, prospect and limitation. Renew. Sustain. Energy Rev. 2016, 53, 945–953. [Google Scholar] [CrossRef]
  9. Heo, H.S.; Kim, S.G.; Jeong, K.-E.; Jeon, J.-K.; Park, S.H.; Kim, J.M.; Kim, S.-S.; Park, Y.-K. Catalytic upgrading of oil fractions separated from food waste leachate. Bioresour. Technol. 2011, 102, 3952–3957. [Google Scholar] [CrossRef]
  10. Farahdiba, A.U.; Warmadewanthi, I.D.A.A.; Fransiscus, Y.; Rosyidah, E.; Hermana, J.; Yuniarto, A. The present and proposed sustainable food waste treatment technology in Indonesia: A review. Environ. Technol. Innov. 2023, 32, 103256. [Google Scholar] [CrossRef]
  11. Wang, H.; Xu, J.; Sheng, L. Study on the comprehensive utilization of city kitchen waste as a resource in China. Energy 2019, 173, 263–277. [Google Scholar] [CrossRef]
  12. Batool, F.; Kurniawan, T.A.; Mohyuddin, A.; Othman, M.H.D.; Aziz, F.; Al-Hazmi, H.E.; Goh, H.H.; Anouzla, A. Environmental impacts of food waste management technologies: A critical review of life cycle assessment (LCA) studies. Trends Food Sci. Technol. 2024, 143, 104287. [Google Scholar] [CrossRef]
  13. Eaton, A.D.; Clesceri, L.S.; Greenberg, A.E. Standard Methods for the Examination of Water and Wastewater, 21st ed.; American Public Health Association: Washington, DC, USA, 2005; pp. 2–56. [Google Scholar]
  14. Dubois, M.; Gilles, K.A.; Hamilton, J.K.; Rebers, P.A.; Smith, F. Colorimetric determination of sugars and related substances. Anal. Chem. 1956, 28, 350–356. [Google Scholar] [CrossRef]
  15. Ribadeau-Dumas, B.; Grappin, R. Milk protein analysis. Le Lait 1989, 69, 357–416. [Google Scholar] [CrossRef]
  16. Bligh, E.G.; Dyer, W.J. A rapid method of total lipid extraction and purification. Can. J. Biochem. Physiol. 1959, 37, 911–917. [Google Scholar] [CrossRef] [PubMed]
  17. Angelidaki, I.; Alves, M.; Bolzonella, D.; Borzacconi, L.; Campos, J.L.; Guwy, A.J.; Kalyuzhnyi, S.; Jenicek, P.; van Lier, J.B. Defining the biomethane potential (BMP) of solid organic wastes and energy crops: A proposed protocol for batch assays. Water Sci. Technol. 2009, 59, 927–934. [Google Scholar] [CrossRef] [PubMed]
  18. Thygesen, O.; Sommer, S.G.; Shin, S.G.; Triolo, J.M. Residual biochemical methane potential (BMP) of concentrated digestate from full-scale biogas plants. Fuel 2014, 132, 44–46. [Google Scholar] [CrossRef]
  19. Lane, D.J. 16S/23S rRNA sequencing. In Nucleic Acid Techniques in Bacterial Systematics; Stackebrandt, E., Goodfellow, M., Eds.; Wiley and Sons: Chichester, UK, 1991; pp. 115–175. [Google Scholar]
  20. Yu, Y.; Lee, C.; Kim, J.; Hwang, S. Group-specific primer and probe sets to detect methanogenic communities using quantitative real-time polymerase chain reaction. Biotechnol. Bioeng. 2005, 89, 670–679. [Google Scholar] [CrossRef]
  21. Rhee, C.; Park, S.-G.; Yu, S.I.; Dalantai, T.; Shin, J.; Chae, K.-J.; Shin, S.G. Mapping microbial dynamics in anaerobic digestion system linked with organic composition of substrates: Protein and lipid. Energy 2023, 275, 127411. [Google Scholar] [CrossRef]
  22. Rognes, T.; Flouri, T.; Nichols, B.; Quince, C.; Mahe, F. VSEARCH: A versatile open source tool for metagenomics. PeerJ 2016, 4, e2584. [Google Scholar] [CrossRef] [PubMed]
  23. Dhiman, S.; Mukherjee, G. Present scenario and future scope of food waste to biofuel production. J. Food Process Eng. 2021, 44, e13594. [Google Scholar] [CrossRef]
  24. Economou, F.; Voukkali, I.; Papamichael, I.; Phinikettou, V.; Loizia, P.; Naddeo, V.; Sospiro, P.; Liscio, M.C.; Zoumides, C.; Țîrcă, D.M.; et al. Turning Food Loss and Food Waste into Watts: A Review of Food Waste as an Energy Source. Energies 2024, 17, 3191. [Google Scholar] [CrossRef]
  25. Lelicińska-Serafin, K.; Manczarski, P.; Rolewicz-Kalińska, A. An Insight into Post-Consumer Food Waste Characteristics as the Key to an Organic Recycling Method Selection in a Circular Economy. Energies 2023, 16, 1735. [Google Scholar] [CrossRef]
  26. Kim, S.I.; Aghasa, A.; Choi, S.; Hong, S.; Park, T.; Hwang, S. Variations in Lipid Accumulation and Methanogenic Predominance in Full-Scale Anerobic Digestors Treating Food Waste Leachate. Waste Biomass Valorization 2023, 14, 3223–3234. [Google Scholar] [CrossRef]
  27. Ansari, K.; Goga, G.; Mohan, R. Utilization of food waste into ethanol and biodiesel. Mater. Today Proc. 2022, 65, 3596–3601. [Google Scholar] [CrossRef]
  28. Jeon, D.; Chung, K.; Shin, J.; Min Park, C.; Shin, S.G.; Mo Kim, Y. Reducing food waste in residential complexes using a pilot-scale on-site system. Bioresour. Technol. 2020, 311, 123497. [Google Scholar] [CrossRef] [PubMed]
  29. Buendia-Kandia, F.; Rondags, E.; Framboisier, X.; Mauviel, G.; Dufour, A.; Guedon, E. Diauxic growth of Clostridium acetobutylicum ATCC 824 when grown on mixtures of glucose and cellobiose. AMB Express 2018, 8, 85. [Google Scholar] [CrossRef]
  30. Kim, M.J.; Kim, S.H. Minimization of diauxic growth lag-phase for high-efficiency biogas production. J. Environ. Manag. 2017, 187, 456–463. [Google Scholar] [CrossRef]
  31. Gomes, C.S.; Strangfeld, M.; Meyer, M. Diauxie Studies in Biogas Production from Gelatin and Adaptation of the Modified Gompertz Model: Two-Phase Gompertz Model. Appl. Sci. 2021, 11, 1067. [Google Scholar] [CrossRef]
  32. Sophonsiri, C.; Morgenroth, E. Chemical composition associated with different particle size fractions in municipal, industrial, and agricultural wastewaters. Chemosphere 2004, 55, 691–703. [Google Scholar] [CrossRef]
  33. Xue, S.; Wang, Y.; Lyu, X.; Zhao, N.; Song, J.; Wang, X.; Yang, G. Interactive effects of carbohydrate, lipid, protein composition and carbon/nitrogen ratio on biogas production of different food wastes. Bioresour. Technol. 2020, 312, 123566. [Google Scholar] [CrossRef]
  34. Peng, Y.-Y.; Gao, F.; Hang, W.-J.W.; Yang, H.-L.; Jin, W.-H.; Li, C. Effects of organic matters in domestic wastewater on lipid/carbohydrate production and nutrient removal of Chlorella vulgaris cultivated under mixotrophic growth conditions. J. Chem. Technol. Biotechnol. 2019, 94, 3578–3584. [Google Scholar] [CrossRef]
  35. Wang, P.; Wang, H.; Qiu, Y.; Ren, L.; Jiang, B. Microbial characteristics in anaerobic digestion process of food waste for methane production—A review. Bioresour. Technol. 2018, 248, 29–36. [Google Scholar] [CrossRef] [PubMed]
Figure 1. Analysis of the organic substances in differently treated FRW samples: (a) TS, VS, and COD values; (b) carbohydrate, protein, and lipid contents.
Figure 1. Analysis of the organic substances in differently treated FRW samples: (a) TS, VS, and COD values; (b) carbohydrate, protein, and lipid contents.
Energies 17 04428 g001
Figure 2. Accumulated biogas production from the BMP assay. Data points represent the mean of the duplicate biogas production results, and the error bars represent standard deviations.
Figure 2. Accumulated biogas production from the BMP assay. Data points represent the mean of the duplicate biogas production results, and the error bars represent standard deviations.
Energies 17 04428 g002
Table 1. Physicochemical analysis results of the duplicated FRW samples.
Table 1. Physicochemical analysis results of the duplicated FRW samples.
ParameterFRWFRW_sepFRW_mix
A *B *ABAB
pH4.204.284.044.043.893.83
TS (g/L)73.3 ± 0.2 **73.5 ± 0.457.6 ± 0.159.0 ± 0.447.2 ± 0.349.7 ± 0.9
VS (g/L)63.3 ± 0.263.4 ± 0.349.7 ± 0.151.0 ± 0.340.5 ± 0.242.9 ± 0.9
COD (g/L)94.7 ± 1.0100.8 ± 1.987.9 ± 1.094.7 ± 8.272.2 ± 1.972.9 ± 1.0
Carbohydrate (g/L)21.0 ± 0.721.8 ± 0.313.7 ± 0.014.9 ± 0.610.5 ± 0.49.7 ± 0.7
Protein (g/L)18.9 ± 0.018.2 ± 0.116.7 ± 0.016.0 ± 0.114.2 ± 0.114.6 ± 0.3
Lipid (g/L)14.3 ± 0.014.7 ± 0.410.4 ± 0.311.0 ± 0.19.4 ± 0.510.3 ± 0.8
* A and B represent duplicate samples from each category. ** Average ± standard deviation.
Table 2. Bacterial phyla detected at the end of the BMP assays.
Table 2. Bacterial phyla detected at the end of the BMP assays.
Bacteria (%)BlankFRWFRW_sepFRW_mix
Firmicutes32.0861.9163.8460.32
Cloacimonetes18.2811.5011.1712.04
Proteobacteria14.526.516.146.93
Bacteroidetes3.003.653.913.63
Chloroflexi2.011.721.221.46
Armatimonadetes0.470.860.820.85
Planctomycetes1.190.360.350.43
Actinobacteria1.130.300.320.56
Verrucomicrobia0.250.290.330.31
Acidobacteria0.710.260.200.32
Synergistetes0.170.110.100.06
Unclassified26.1912.8911.7413.06
Table 3. Archaeal genera detected at the end of the BMP assays.
Table 3. Archaeal genera detected at the end of the BMP assays.
Archaea (%)BlankFRWFRW_sepFRW_mix
Methanolinea78.1163.8861.0860.73
Methanoculleus3.5622.7125.2025.90
Methanothrix11.759.129.799.15
Methanospirillum6.314.193.854.07
Methanobrevibacter0.250.050.040.06
Unclassified0.010.040.030.08
Table 4. Energy balance estimation of the two scenarios.
Table 4. Energy balance estimation of the two scenarios.
ParameterUnitScenario 1Scenario 2Remark
FRW treatmentm3/day100100
FRW used for biogasm3/day100955% loss during oil–water separation
VS concentrationkg/m363.3850.37Obtained from the characterization
VS used for biogaskg VS/day63384785[FRW used] × [VS concentration]
CH4 productivityNm3/kg VS0.4650.541Obtained from the BMP assay
CH4 productionNm3/day29472589[VS used] × [CH4 productivity]
Energy value of CH4MJ/Nm335.835.8
CH4 production (energy)MJ/day105,50092,678[CH4 production] × [Energy value]
Biodiesel (BD) productionm3/day-0.50.5% yield
Energy value of BDMJ/m3-32Reference from [27]
BD production (energy)MJ/day-16,000[BD production] × [Energy value]
BD operation cost (energy)MJ/day-360Oil–water separator, 3.6 MJ per ton of FRW
Net energy gain *MJ/day105,500108,318[CH4 energy] + [BD energy] − [BD operation]
* Only differential factors for the two scenarios were considered in the calculation. Communal factors, such as the energy cost for anaerobic digestion operation and transportation, were excluded.
Disclaimer/Publisher’s Note: The statements, opinions and data contained in all publications are solely those of the individual author(s) and contributor(s) and not of MDPI and/or the editor(s). MDPI and/or the editor(s) disclaim responsibility for any injury to people or property resulting from any ideas, methods, instructions or products referred to in the content.

Share and Cite

MDPI and ACS Style

Han, G.; Shin, J.; Lee, M.-E.; Shin, S.G. Biogas Potential of Food Waste-Recycling Wastewater after Oil–Water Separation. Energies 2024, 17, 4428. https://doi.org/10.3390/en17174428

AMA Style

Han G, Shin J, Lee M-E, Shin SG. Biogas Potential of Food Waste-Recycling Wastewater after Oil–Water Separation. Energies. 2024; 17(17):4428. https://doi.org/10.3390/en17174428

Chicago/Turabian Style

Han, Gyuseong, Juhee Shin, Myoung-Eun Lee, and Seung Gu Shin. 2024. "Biogas Potential of Food Waste-Recycling Wastewater after Oil–Water Separation" Energies 17, no. 17: 4428. https://doi.org/10.3390/en17174428

APA Style

Han, G., Shin, J., Lee, M.-E., & Shin, S. G. (2024). Biogas Potential of Food Waste-Recycling Wastewater after Oil–Water Separation. Energies, 17(17), 4428. https://doi.org/10.3390/en17174428

Note that from the first issue of 2016, this journal uses article numbers instead of page numbers. See further details here.

Article Metrics

Back to TopTop