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Article

Analysis of Product Distribution and Quality from the Hydrothermal Liquefaction of Food Waste Feedstocks

by
Ezra Nash
1,
Zachary Rehg
2,
Rukiyat Thompson
3 and
Sarah Bauer
1,*
1
Department of Environmental and Civil Engineering, Mercer University, 1501 Mercer University Drive, Macon, GA 31207, USA
2
Department of Mechanical Engineering, Mercer University, 1501 Mercer University Drive, Macon, GA 31207, USA
3
Department of Biomedical Engineering, Mercer University, 1501 Mercer University Drive, Macon, GA 31207, USA
*
Author to whom correspondence should be addressed.
Energies 2026, 19(1), 109; https://doi.org/10.3390/en19010109 (registering DOI)
Submission received: 16 November 2025 / Revised: 19 December 2025 / Accepted: 22 December 2025 / Published: 25 December 2025
(This article belongs to the Topic Advances in Biomass Conversion, 2nd Edition)
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Abstract

Hydrothermal liquefaction (HTL) is a thermochemical process by which biomass feedstocks are converted into bio-oil and multiple by-products, including aqueous co-product (ACP), gaseous co-product (GCP), and biochar. Bio-oil produced from food waste feedstocks represents a potential candidate for use in commercial waste-to-energy conversions. The objective of this study is to further develop this technology by investigating the product distribution and quality from the HTL of food waste feedstocks. Four food waste feedstocks were selected for analysis: brewery grains, pear lees, coffee grounds, and honeydew skins. Solids analysis was conducted on each as-received feedstock, with the results determining dilution ratios for optimizing water content for HTL (≥80%). HTL conversions were conducted at 300 °C with a retention time of 30 min. Biochar was measured after product filtration, while ACP and bio-oil were measured via liquid–liquid phase separation. Coffee grounds produced the highest percentage of bio-oil (0.460%) and biochar (9.96%), while pear lees produced the highest percentage of ACP (89.5%). After quantification, ACP was characterized for nutrient concentrations. The quality of the ACP differed significantly from values in the literature, highlighting the influence of feedstock type and reaction conditions on HTL product characteristics (in addition to distribution) and underscoring the need for further research to optimize co-product utilization and process efficiency.

1. Introduction

Due to the limited supply and harmful environmental impacts of nonrenewable energy sources, there is a growing demand for renewable energy sources across the world. One such renewable energy source is biofuel, or fuel produced from organic biomass [1]. This energy source has seen significant growth, with global biofuel production surpassing 1400 TWh in 2024 as shown in Figure 1 [2].
Traditional biofuels (or first-generation biofuels) often rely on food crops for a biomass source, which scholars have argued creates some negative impacts in the food and water sectors when examined in the context of the Food–Energy–Water (FEW) Nexus [3,4,5]. While many definitions for the FEW Nexus may be found in the literature, it is defined here as an analysis framework for environmental problems that emphasizes the interrelationship between the food, energy, and water sectors, as well as the idea that these sectors should be prioritized equally [6]. First-generation biofuel production (and its associated crop consumption) was found to have negative impacts in both the water and food sectors when examined in this context.
The negative energy-to-water impacts of biofuel production include the fact that in 2017, it accounted for 2–3% of all global water consumption while only meeting 4% of the global demand for transportation fuels [4,5]. When considering that this is only one source of water withdrawals across the major categories of municipal, industrial, and agricultural usage, it is clear that the water footprint of first-generation biofuels is significant [7,8]. The crop cultivation associated with first-generation biofuels also presents a water quality issue from agricultural runoff causing fertilizers and pesticides to leach into runoff, with fertilizer-heavy crops such as U.S.-grown corn and Brazil-grown sugar cane being especially hazardous in this regard [5,9,10,11].
The negative energy-to-food impacts, on the other hand, primarily involve the fact that the aforementioned reliance of first-generation biofuels on food crops can lead to competition between food needs and energy needs [3,4,5,12]. This issue can be exacerbated by the fact that rising nonrenewable fuel (oil) prices, combined with environmental concerns, can cause existing food crop streams to switch to industrial (biofuel) uses, driving increases in food prices—an issue that has been termed the food–energy–environment trilemma or the food–feed–fuel trilemma in the previous literature [12,13,14]. The end result of this competition is that first-generation biofuel production consumes an amount of food and cropland that could be used to reduce food poverty by as much as 30% [5].
One potential solution to this FEW Nexus problem is the usage of alternative biomass sources for biofuel production. Biofuels reliant on these sources are termed second- and third-generation biofuels [15]. Babcock [3] suggests that the energy-to-food impacts of biofuel production could be mitigated by using higher-generation biomass sources that do not require additional cropland, particularly those that are of low (or negative) economic value, or those that are treated as waste. Similarly, Mathioudakis et al. [16] indicates that second-generation biomass sources may be able to achieve lower water footprints than first-generation sources, mitigating the energy-to-water impacts as well.
One biomass source that merits further consideration is food waste, which is classed as a second-generation biomass source because it is one of the primary components of municipal solid waste [15,17]. Food waste issues may be responsible for large economic losses, with a loss of $161.6 billion being attributed to food wastes in the U.S. in 2010 alone (see Figure 2 for a breakdown by specific food waste type) [18]. The usage of food waste as a biomass could potentially mitigate these losses while simultaneously providing the benefits of second-generation biofuels mentioned previously—food waste is already being generated in large quantities and is typically sent to municipal solid waste landfills [19,20], which suggests that the diversion of food waste streams to biofuel production would not significantly stress the world’s food and water resources. Many previous studies have examined the usage of a variety of food wastes in biofuel production. Most commonly, the usage of brewery waste (yeast, spent grains, spent lees, etc.) has been covered, but other wastes including (but not limited to) meat waste, dairy waste, coffee grounds, vegetable waste, and fruit waste have also been examined [21,22,23,24].
One challenge with the commercialization of food waste-based biofuels is that second-generation biomass sources are not suitable for direct conversion into bioethanol and biodiesel using the same technologies as first-generation biomass sources [25]. Instead, it is more viable to use thermochemical processes such as pyrolysis, transesterification, steam reforming, or the focus of this study: hydrothermal liquefaction (HTL; also termed direct biomass liquefaction) [26,27]. In HTL, a wet biomass feedstock is digested at high temperatures and pressures, producing bio-oil (or bio-crude oil) as a main product and three by-products: an aqueous co-product (ACP), a gaseous co-product (GCP), and biochar [28].
The HTL reaction pathway can be described using a series of three steps: depolymerization, decomposition, and recombination [29]. In depolymerization, the polymer macromolecules within the feedstock are sequentially broken down into monomers and dissolved [26,30]. Then, in decomposition, oxygen is removed from the biomass as water and carbon dioxide while the carbohydrate polymers break down further through a variety of smaller reactions [31,32]. The result of depolymerization and decomposition is that the biomass feedstock is broken down or degraded into many small and reactive compounds, which are dissolved in the removed water [26,32]. These compounds then polymerize during the recombination step, producing the bio-oil, GCP, and biochar (leaving the ACP as a by-product) [26,29]. This process is summarized in Figure 3.
HTL was selected for examination because of its reliance on a wet feedstock and aqueous medium for the reaction [33,34]. This provides an advantage of similar technologies such as pyrolysis, which rely on dry feedstocks (<10% water) and consequently require energy-intensive feedstock dewatering steps [35]. Bio-oil produced via pyrolysis has also been found to contain a lower energy content than is produced via other technologies, providing another advantage to HTL [33]. Additionally, many studies have examined the use of HTL for biofuel production (and the factors that affect this process), providing a basis for this study’s methodology and analysis. Multiple prior studies have found that the temperature at which the HTL reaction takes place heavily influences the quantity and composition of the bio-oil produced, with temperatures ranging from 300 to 350 °C being cited as optimal [36,37]. Chen et al. [37] further notes that while the duration of the reaction is less important, a reaction time of 30 min is optimal.
While the bio-oil is the main product of HTL, the three by-products (ACP, GCP, and biochar) warrant consideration as well, as their proper management is important to the commercialization of HTL technologies. The ACP is a wastewater by-product which contains high concentrations of nutrient pollutants, necessitating treatment before it can be discharged to a receiving water body [38]. Previous studies have examined various potential applications and treatment methods for ACP, including anaerobic digestion, nutrient recovery via struvite precipitation, and microalgae cultivation [38,39,40,41].
The biochar may be considered a solid waste, but research has shown that it has potential applications as a fuel source, as an adsorbent for metals or dyes, as an additive for livestock feed, and in anaerobic digestion processes [22,42,43,44,45,46,47,48]. A more recent research trend related to biochar is its potential application as a soil amendment for agricultural purposes. Several studies have found a positive impact of biochar additions on the growth of various crop plants [49,50,51,52,53], although other such as Nesheim [25] have yielded less conclusive results, indicating a need for further research in this area.
Unlike the ACP and biochar, the GCP has been relatively unexplored in the previous literature. While the treatment challenges and potential applications of the GCP have not been expanded upon, a study of GCP produced from the HTL of brewery grains found that the by-product was composed of approximately 95% carbon dioxide (CO2) and 1.6% diatomic hydrogen (H2), with trace quantities of diatomic nitrogen (N2), carbon monoxide (CO), methane (CH4), short-chain alkanes, and short-chain alkenes being identified as well [28].
The purpose of this study is to collect and provide data that may be used to evaluate the feasibility of using food waste feedstocks as a biomass source for commercial biofuel production via HTL. This data includes information regarding the HTL product and by-product yield distribution and ACP characteristics for four different food waste feedstocks: spent coffee grounds, spent brewery grains, pear wine lees, and homogenized honeydew skins. These feedstocks were selected for their high water contents, making them suitable for use in HTL reactions. The secondary goal of this study is to provide a review of previous studies on the HTL of food waste feedstocks, focusing on observations and trends found during the comparison of different studies that analyzed the same food waste feedstocks. This study provides novel insight by performing a comprehensive comparison of ACP nutrient and COD profiles across four food wastes under identical operating conditions.

2. Materials and Methods

This study was carried out in a series of five phases: (1) characterization and preparation of food waste feedstocks, (2) HTL of food wastes, (3) solid–liquid phase separation of products, (4) liquid–liquid phase separation of products, and (5) water quality analysis of the ACP. As mentioned previously, the four food wastes chosen for analysis were spent brewery grains, pear wine lees, spent coffee grounds, and homogenized honeydew skins. The grains, pear lees, and coffee grounds were selected due to the coverage of similar feedstocks in existing literature such as Bauer et al. [21] and Liakos et al. [24], which allowed for the comparison of each study’s results. The honeydew skins, on the other hand, were selected as a novel feedstock due to regular availability from the source location. The grains were sourced from Ocmulgee Brewpub, Macon, GA, USA; the pear lees were sourced from Myron Winery, Macon, GA, USA; the coffee grounds were sourced from Z Beans Coffee, Macon, GA, USA; and the honeydew skins were sourced from Fresh Food Company, Macon, GA, USA (homogenization was conducted via blender in the research lab). Feedstocks were frozen at −17.8 °C after collection and were thawed in a laboratory refrigerator for 48 h prior to experimentation.
The characterization and preparation of food waste feedstocks was conducted as in Bauer et al. [21] and Nesheim [25]. A solids analysis was conducted to determine the water content, total solids (TS), volatile solids (VS; organic solids content), and fixed solids (FS; ash content) of each food waste according to ASTM standards E1756-08R15 and E1755-01R20 (n = 3 replicates for all food wastes) [54,55]. Food wastes which had water contents of less than 80% by mass were diluted via the addition of deionized water to a water content of 80% by mass (20% TS by mass). Due to its especially high water content, it was feasible to conduct a water quality analysis of the pear lees as well, using the same methodology described for the water quality analysis of the ACP described later in this section.
The HTL of food waste was conducted using a benchtop Parr Hast 300 mL reactor (Parr Instrument Company, Moline, IL, USA) with a quartz liner, external heater, asbestos insulation, and a Parr 4848 reactor controller (Parr Instrument Company, Moline, IL, USA), as in Nesheim [25]. To prepare for each HTL run, a 100 g sample of the selected food waste feedstock was prepared in the quartz liner and loaded into the machine (n = 3 replicates was targeted for each food waste feedstock, although n = 4 was achieved for pear lees, while n = 2 was achieved for honeydew skins due to supply limitations). The reactor system was pressurized to 100 psi with diatomic nitrogen gas (N2) and purged three times before being pressurized to 100 psi once more. The reactor’s motor was set to run at 200 rpm. Each HTL run had three phases: a heating phase (1 h and 45 min), a digestion phase (30 min), and a natural cooling phase (approximately 3 to 4 h). During the heating phase, the system was heated to 300 °C using a 2.67 °C/min ramp, inducing a pressure increase to between 1300 and 1500 psi. The system was held at these conditions during the digestion phase, allowing the HTL reaction to progress. Finally, during the cooling phase, the heater was deactivated and removed from the reactor, allowing the system to naturally cool to room temperature. The GCP was vented from the system at the end of the cooling phase, leaving a mixture of the bio-oil, ACP, and biochar.
The separation of the three remaining products was conducted as in Nesheim [25]. The first phase of this process was the removal of the biochar in a solid–liquid phase separation, which was performed by passing the bio-oil/ACP/biochar mixture through pre-weighed 1.5 μm glass microfiber filters using a vacuum filtration setup with a Buchner funnel (Fisher Scientific, Pittsburgh, PA, USA). This allowed the solid biochar to be separated from the mixture, weighed, dried at 105 °C, and weighed again. The liquid losses during filtration were quantified as the difference between pre-drying and post-drying masses. Following this, the vs. (organic solids) and FS (ash) content of the dried biochar was quantified according to ASTM standard E1755-01R20 [55]. A summary of this process is shown in Figure 4a.
The second phase of the product separation process was the isolation of the bio-oil and ACP in a liquid–liquid phase separation, using the methodology of Nesheim [25]. The process liquid (i.e., the bio-oil/ACP mixture) was pipetted into a series of pre-weighed 15 mL glass vials, with dichloromethane (DCM) being added to each vial to achieve a 1:2 process liquid-to-DCM volume ratio. Typically, 4 mL of process liquid and 8 mL of DCM were added to each vial (note that at a density of 1.33 g/mL, the typical mass of DCM was 10.64 g) [56]. The vials were then centrifuged at 4000 rpm for a period of 14 min, catalyzing the phase separation. After centrifuging, the ACP had risen to the top of each vial, leaving a bio-oil/DCM mixture at the bottom. The ACP was pipetted out of each vial and weighed, while the remaining mixture was placed uncapped under a fume hood to facilitate the evaporation of the DCM. After the complete evaporation of the DCM had been ensured, the remaining bio-oil was weighed. The liquid losses during filtration were then added to the masses of bio-oil and ACP. In this calculation, it was assumed that the ratio of bio-oil to ACP in the liquid losses was the same as the ratio of bio-oil to ACP observed in the liquid-liquid phase separation. Consequently, this ratio was maintained in the final result. Because the GCP had been vented from the system, its mass was calculated indirectly using a mass balance at this point. The measured masses of bio-oil, ACP, and biochar were subtracted from the input mass (100 g), yielding the mass of GCP. A summary of this process is shown in Figure 4b.
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Figure 4. Visual summary of the experimental methodology for: (a) The solid–liquid phase separation of biochar from bio-oil and ACP; (b) The liquid–liquid phase separation of bio-oil and ACP, as adapted from Nash et al., 2025 [57].
Figure 4. Visual summary of the experimental methodology for: (a) The solid–liquid phase separation of biochar from bio-oil and ACP; (b) The liquid–liquid phase separation of bio-oil and ACP, as adapted from Nash et al., 2025 [57].
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The water quality analysis of the ACP was conducted using Hach Test ‘N Tube (TNT) (Hach Company, Loveland, CO, USA)test kits and a DRB200 digital spectrophotometer. Five water quality parameters were evaluated according to their respective Hach standard procedures: total nitrogen (TNT 828), nitrate (TNT 836), total phosphorus (TNT 845), reactive phosphorus (TNT 845), and chemical oxygen demand (COD; high range+) [58,59,60,61]. Two iterations of each test were conducted for each ACP sample produced from the HTL of grains, pear lees, and coffee grounds, while three iterations were conducted for the ACP samples produced from honeydew skins to account for the lower number of HTL runs conducted for this food waste (n = 6 replicates for grain, coffee grounds, and honeydew skins; n = 8 replicates for pear lees).

3. Results and Discussion

The data collected during each phase of the study was examined to identify trends in the results. Data was additionally compared with data available in existing literature to allow further conclusions to be drawn regarding the results.

3.1. Characterization of Food Waste Feedstocks

The data collected on unprocessed food waste feedstocks included water content, TS, VS, and FS as a mass percentage. Water quality tests including total nitrogen, nitrate, total phosphorus, reactive phosphorus, and COD (in mg/L) were additionally conducted on the pear lees. Table 1 lists the results of the data collected during these tests.
As noted in Table 1, all four food waste feedstocks were found to have very low FS (ash) contents, with the largest recorded value being 0.85% for the grains. The TS and water content values listed in Table 1 correspond to solid-to-liquid ratios of 42.67%, 0.59%, 57.06%, and 4.94% for the grains, pear lees, coffee grounds, and honeydew skins, respectively. Additionally, the pear lees were found to have an extremely high water content, at 99.4%. Finally, the coffee grounds were found to have the highest vs. (organic solids) and TS content, at 35.8% and 36.3%, respectively. Direct comparison data was found in the literature for grains and coffee grounds, as shown in Table 2, to demonstrate the degree of variation in reported feedstock characteristics across published HTL studies. Data for pear lees and honeydew skins was not available, as no published HTL studies using these feedstocks were identified, and because pear lees composition varies substantially between wineries and fermentation stages, making comparable data difficult to obtain. Note that some of the sources listed in Table 2 are not used for comparison in later subsections, due to either lacking sufficient data in their results or not being studies of the HTL of food waste feedstocks.
The grains examined in this study had characteristics that closely resembled those seen in Nesheim [25]. Specifically, the water content, TS, VS, and FS of the grains were within 0.5–1.5% of those reported by Nesheim [25], indicating strong similarity in moisture composition and organic loading. Additionally, most studies observed similar characteristics in grain feedstocks, with the differences between the highest and lowest water content and TS values measuring 7.80%. This indicates that there is a basis for comparing data reported for grain feedstocks in different studies. However, there are two exceptions to this trend: Canedo et al. [62] and Maddi et al. [63]. The former study reported a comparatively large FS value at 3.41%, while the latter reported a comparatively small vs. value at 12.8%. The cause of these differences is not clear, so it may be necessary to conduct further investigations to evaluate the factors that affect the solids and water content of spent brewery grains.
Large variations in the characteristics of wine lees were observed in this study and in the literature. While the red lees examined by Bauer et al. [21] and the rose lees examined by Adedeji et al. [64] displayed similar characteristics, the overall range of characteristics among all samples from both this study and the literature is large: water content ranged from 73.8% to 99.4% (25.6% difference), TS ranged from 0.588% to 26.2% (25.6% difference), vs. ranged from 0.581% to 21.5% (20.9% difference), and FS ranged from 0.00674% to 4.7% (4.69% difference). Large variations in water quality characteristics were noted as well, with the total nitrogen and COD values reported by García Álvaro et al. [65] being larger than the experimental values by factors of 15.25 and 1.58, respectively. These results may suggest that different types of wine lees are not directly comparable in HTL studies, due to the variability in their feedstock characteristics. The substantial differences in water content among feedstocks add important insight into how moisture level influences HTL behavior. Higher water contents reduce the effective organic loading in the reactor, leading to lower bio-oil formation and greater ACP volume.
The coffee grounds examined in this study presented characteristics resembling those reported in Nesheim [25], albeit not as closely as the resemblance between grain feedstocks noted earlier, as the difference between the water content and TS values of each study measured 5.00%. As this is a smaller difference than was reported for the most extreme grain samples, there is also a basis for comparing the data for coffee grounds reported in this study and in Nesheim. The coffee grounds studied in Liakos et al. [24] may not be comparable, on the other hand, as they were found to have a much lower water content: 11.34%. This difference was likely caused by differences in sample management procedures; however, as the coffee grounds studied by Liakos et al. were subjected to atmospheric drying before analysis. This shows a need for consistent sample management to obtain comparability between studies.

3.2. Yield Distribution of Hydrothermal Liquefaction Products

The average mass yield distributions of the four HTL products for each food waste are shown in Figure 5 (see Table A1 in Appendix A for tabulated results). Differences among feedstocks in post-HTL product yield, biochar solids content, and ACP water-quality parameters were evaluated using two-sample t-tests with a significance threshold of α = 0.05. Pairwise comparisons were performed between each feedstock combination for each parameter measured. Mean values throughout the text are reported alongside one standard deviation.
As shown in Figure 5, the coffee grounds yielded the greatest percentage of bio-oil and biochar, at 0.460% and 9.96% of the input mass, respectively. Additionally, the pear lees yielded the greatest percentage of ACP, at 89.5%, while the honeydew skins yielded the greatest percentage of GCP, at 29.2%. Since the bio-oil is the main product of HTL, while the biochar has several potential uses according to ongoing research, it can be concluded that the coffee grounds (which produces the greatest percentage of both) is the most optimal of the four feedstocks in terms of product yield [22,28,42,43,44,45,46,47,48]. Two-sample t-tests indicated that differences in bio-oil and biochar yields between feedstocks were statistically significant (p < 0.05). Because the feedstocks differed substantially in initial water content, the dilution ratio required to achieve the target ≥80% moisture varied among materials. These differences may have influenced the effective organic loading entering the reactor, in turn affecting the partitioning between bio-oil, biochar, ACP, and gaseous products.
Comparison data for the mass yield distribution of HTL products found in the literature is listed in Table 3.
Notably, the bio-oil mass yields found for the food waste feedstocks listed in Table 3 are much higher than those found in this study (although the bio-oil yield for coffee grounds presented by Liakos et al. [24] may not be comparable due to the usage of an atmospheric drying process). It is possible that the low bio-oil yield observed in this study may be caused by some condition of the reaction that was not accounted for between studies, such as the duration of the cooling phase. While the studies listed in Table 3 do not specify the duration of the cooling phase used in their respective studies [21,24,64], Bawono et al. [66] indicates that a longer cooling phase may cause the conversion of bio-oil into GCP. Other factors outside the scope of this research—such as detrimental secondary reactions (oligomerization, condensation, cracking, etc.)—may have lowered the bio-oil yields as well [67,68]. The exploration of these potential confounding factors in future research may help to further optimize the product mass yield of the HTL of food wastes.

3.3. Ash Content of the Biochar

The organic (VS) and ash (FS) content measured for the biochar produced by the HTL of each food waste is presented in Table 4.
While most of the food wastes examined during this study yielded biochar with low ash contents (below 2.5%), the ash content of the biochar produced from pear lees was much higher, at 10.6%. The higher ash content, and in turn the lower organic content, of the biochar produced from pear lees may indicate that a larger percentage of the pear lees’ organic content is present in the bio-oil and ACP that this food waste produced. While this result is not confirmed because an ultimate analysis of the HTL products and by-products was not conducted during this study, a higher percentage of organic content (and in turn carbon content) within the bio-oil produced from pear lees would indicate that the bio-oil has a higher energy content, as carbon content is positively correlated with high heating values of fuels [69]. However, one cannot fully directly comparable these datasets due to (1) differences in winery processing practices that produce chemically distinct types of lees, (2) variations in sample handling, such as atmospheric drying or storage time, prior to analysis, and (3) differences in solids content arising from fermentation stage or residual sugars.

3.4. Water Quality of the Aqueous Co-Product

The water quality data gathered for the ACP produced by the HTL of each food waste is presented in Table 5.
From Table 5, it can be seen that the honeydew skins are a superior feedstock when considering the need for proper ACP management in the implementation of commercial HTL systems, since the honeydew skins yielded the ACP with the lowest concentrations for all five pollutants that were evaluated. Two-sample t-tests indicated that ACP nutrient and COD concentrations differed significantly between feedstocks (p < 0.05).
Comparison data for the water quality of ACP found in the literature is listed in Table 6.
Notably, there are large variations in ACP water quality that have been observed both between this study and the literature and within the literature itself. These discrepancies are most notable when examining the ACP produced from the different types of wine lees evaluated during each study, where the total nitrogen and total phosphorus values reported for each waste range from the tens to the thousands of mg/L. Within these samples, it is clear that the white lees examined by Bauer et al. [21], and to a lesser extent the pear lees examined in this study, are preferable to other types of wine lees when prioritizing the need for ACP management. The overall variation in the water quality of ACP produced from wine lees may support the prior conclusion in Section 3.1 that different types of wine lees are not directly comparable with each other in HTL studies. Instead, a greater knowledge of the type of lees and the associated winery processes may need to be specified when including these food wastes in future research.
While the discrepancies observed in the ACP produced from wine lees may be attributable to fundamental differences in feedstock characteristics, the variations in characteristics for ACP produced from grains (which had comparable feedstock characteristics) are not. While the variations observed in ACP water quality are smaller for the grains than they are for the wine lees, it is observed that the grains examined in this study yielded lower pollutant concentrations in ACP than the grains examined in the literature. This is especially notable when comparing the nitrate and total phosphorus values reported in each study, as the concentrations observed in this study are significantly lower than those reported by Bauer et al. [21] and Maddi et al. [63]. Because these variations are not attributable to differences in feedstock characteristics, it is possible that they are instead attributable to some other underlying factor such as the conditions of the HTL reaction. Previous research on the optimizing the reaction conditions of HTL has prioritized the maximization of bio-oil yield [36,37], but it is likely that additional research may be necessary to evaluate the impact of these potential confounding factors on the water quality of the ACP as well.

4. Conclusions

Biomass-based fuels, or biofuels, present a promising solution to the issues presented by the usage of nonrenewable energy sources. These fuels present their own problems; however, due to their negative impacts in the food and water sectors [3,4,5]. The usage of food waste as a biomass feedstock in HTL processes presents a potential solution to this conundrum, which this research seeks to examine.
This research explored the effects of varying food waste feedstocks (spent brewery grains, pear wine lees, spent coffee grounds, and homogenized honeydew skins) on the yield and characteristics of the products and by-products of the HTL conversion process. A mass yield distribution analysis found that of the four feedstocks, the spent coffee grounds produced the largest percentage of bio-oil and biochar, the pear lees produced the highest percentage of ACP and the honeydew skins produced the highest percentage of biogas. Additionally, the pear lees yielded the highest concentration of ash in its biochar, while the honeydew skins yielded the lowest pollutant concentrations in its ACP.
A comparison of these results with pre-existing literature data found that additional factors, such as HTL reaction conditions, feedstock preparation techniques (such as atmospheric drying), or smaller variations in feedstock type (i.e., different types of wine lees) may have impacted the mass yield distributions and ACP characteristics of the HTL products.
For future research on the HTL of food waste feedstocks, it is recommended that specific attention be given to the source, production, and other ‘fine details’ that may contribute to or affect the categorization of food waste feedstocks, to ensure the comparability of results between studies. Additionally, further research may be needed to gain a deeper understanding of the impact of factors such as feedstock preparation techniques and HTL reaction conditions on the characteristics of the HTL products (particularly the ACP and biochar), as the existing literature does not explore these potential effects.

Author Contributions

Conceptualization, S.B.; methodology, S.B.; validation, E.N., Z.R. and R.T.; formal analysis, E.N., Z.R. and R.T.; investigation, E.N., Z.R. and R.T.; resources, S.B.; data curation, E.N., Z.R. and R.T.; writing—original draft preparation, E.N., Z.R. and R.T.; writing—review and editing, E.N. and S.B.; visualization, E.N.; supervision, S.B.; project administration, S.B.; funding acquisition, S.B. All authors have read and agreed to the published version of the manuscript.

Funding

This research and the APC were funded by the School of Engineering, Mercer University, Macon, GA, USA.

Data Availability Statement

The raw data supporting the conclusions of this article will be made available by the authors on request.

Acknowledgments

The authors would like to extend their sincerest gratitude to Philip McCreanor, Adaline Buerck, and Leslie Carroll at the Department of Environmental and Civil Engineering, Mercer University for their technical and laboratory support during this project. The authors would additionally like to give their thanks to Ocmulgee Brewpub, Myron Winery, Z Beans Coffee, and Fresh Food Company in Macon, GA, USA for providing the food waste feedstocks examined during this study.

Conflicts of Interest

The authors declare no conflicts of interest. The funders had no role in the design of the study; in the collection, analyses, or interpretation of data; in the writing of the manuscript; or in the decision to publish the results.

Abbreviations

The following abbreviations are used in this manuscript:
HTLHydrothermal liquefaction
ACPAqueous co-product
GCPGaseous co-product
FEWFood, energy, and water
TSTotal solids
VSVolatile solids
FSFixed solids
DCMDichloromethane
TNTTest ‘N Tube
CODChemical oxygen demand

Appendix A

The average mass distributions for the four HTL products for each food waste feedstock are presented in Table A1.
Table A1. Experimentally observed mass yield distribution of HTL products (tabular format; confidence intervals correspond to one standard deviation).
Table A1. Experimentally observed mass yield distribution of HTL products (tabular format; confidence intervals correspond to one standard deviation).
Food Waste FeedstockNBio-Oil (Mass%)ACP (Mass%)GCP (Mass%)Biochar (Mass%)
Grains30.42% ± 0.06%71.5% ± 3.3%19.3% ± 2.6%8.83% ± 0.86%
Pear Lees40.34% ± 0.16%89.5% ± 1.6%10.1% ± 1.9%0.05% ± 0.02%
Coffee Grounds30.46% ± 0.12%70.7% ± 3.4%18.8% ± 3.8%9.96% ± 0.22%
Honeydew Skins20.22% ± 0.09%69.4% ± 15.5%29.2% ± 14.1%1.17% ± 0.28%

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Energies 19 00109 g001
Figure 1. Biofuel energy production from 1990 to 2024, as adapted from Ritchie et al., 2025 [2].
Figure 1. Biofuel energy production from 1990 to 2024, as adapted from Ritchie et al., 2025 [2].
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Energies 19 00109 g002
Figure 2. Breakdown of estimated 2010 food losses in the U.S. by food waste type, as adapted from Buzby et al., 2014 [18].
Figure 2. Breakdown of estimated 2010 food losses in the U.S. by food waste type, as adapted from Buzby et al., 2014 [18].
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Energies 19 00109 g003
Figure 3. The reaction pathway of hydrothermal liquefaction, as adapted from Gollakota et al., 2018 [26].
Figure 3. The reaction pathway of hydrothermal liquefaction, as adapted from Gollakota et al., 2018 [26].
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Energies 19 00109 g005
Figure 5. Experimentally observed mass yield distribution of post-HTL products (confidence intervals correspond to one standard deviation).
Figure 5. Experimentally observed mass yield distribution of post-HTL products (confidence intervals correspond to one standard deviation).
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Table 1. Summary of experimental food waste feedstock characterization data of as-received feedstock (n = 3 replicates; confidence intervals correspond to one standard deviation).
Table 1. Summary of experimental food waste feedstock characterization data of as-received feedstock (n = 3 replicates; confidence intervals correspond to one standard deviation).
Food Waste FeedstockWater Content (Mass%)TS (Mass%)VS (Mass%)FS (Mass%)Total N (mg/L)Nitrate (mg/L)Total P (mg/L)Reactive P (mg/L)COD (mg/L)
Grains70.1% ± 0.5%29.9% ± 0.5%29.1% ± 0.4%0.85% ± 0.03%-----
Pear Lees99.4% ± 0.0% *0.59% ± 0.01%0.58% ± 0.01%0.01% ± 0.00% *418 ± 10224.5 ± 12.3285 ± 24236 ± 24236,000 ± 200
Coffee Grounds63.7% ± 0.2%36.3% ± 0.2%35.8% ± 0.4%0.55% ± 0.00% *-----
Honeydew Skins95.3% ± 0.1%4.71% ± 0.08%4.40% ± 0.08%0.31% ± 0.00% *-----
* Standard deviations equal to zero reflect small, non-zero deviations that have been rounded down.
Table 2. Summary of as-received food waste feedstock characterization data in the literature.
Table 2. Summary of as-received food waste feedstock characterization data in the literature.
Food Waste FeedstocksSourceWater Content (Mass%)TS (Mass%)VS (Mass%)FS (Mass%)Total N (mg/L)COD (mg/L)
Grains[21]77.9% ± 0.8%22.1% ± 0.8%21.2% ± 1.8%0.9% ± 0.1%4.6 ± 0.5-
Grains[25]70.5% ± 0.92%29.5% ± 1.03%28.8% ± 0.98%0.976% ± 0.04%--
Grains[62]72.54% ± 0.49%27.46% ± 0.49%24.05% ± 0.04%3.41% ± 0.04%--
Grains[63]--12.8%--55,900
White Lees[21]73.8% ± 0.3%26.2% ± 0.3%21.5% ± 1.1%4.7% ± 1.1%--
Red Lees[21]88.7% ± 0.9%11.3% ± 0.9%7.3% ± 0.2%4.0% ± 0.2%--
Rose Lees[64]87.40% ± 0.04%12.60% ± 0.04%8.19% ± 1.33%4.41% ± 0.02%--
Unspecified Lees[65]83.67% ± 0.015%16.330% ± 0.015%15.421% ± 0.085%0.909% ± 0.085%6370 ± 70372,280 ± 3420
Coffee Grounds[24]11.34%88.66%87.54%1.12%--
Coffee Grounds[25]58.7% ± 0.16%41.3% ± 0.15%40.4% ± 0.25%0.812% ± 0.14%--
Table 3. Summary of post-HTL product mass yield distribution data in the literature.
Table 3. Summary of post-HTL product mass yield distribution data in the literature.
Food Waste FeedstockSourceBio-Oil (Mass%)ACP (Mass%)GCP (Mass%)Biochar (Mass%)
Grains[21]5.0%75.0%18.2%1.8%
White Lees[21]10.0%70.9%15.5%3.6%
Red Lees[21]7.7%76.8%13.7%1.8%
Rose Lees[64]5.2%79.1%11.4%4.3%
Coffee Grounds[24]33.95%47.10% *47.10% *18.95%
* ACP and GCP combined.
Table 4. Summary of experimental biochar solids content data (confidence intervals correspond to one standard deviation).
Table 4. Summary of experimental biochar solids content data (confidence intervals correspond to one standard deviation).
Food Waste FeedstockNVS (Mass%)FS (Mass%)
Grains398.6% ± 0.9%1.39% ± 0.93%
Pear Lees489.4% ± 3.0%10.6% ± 3.0%
Coffee Grounds399.0% ± 0.4%0.97% ± 0.41%
Honeydew Skins297.8% ± 0.4%2.24% ± 0.45%
Table 5. Summary of experimental ACP water quality data (confidence intervals correspond to one standard deviation).
Table 5. Summary of experimental ACP water quality data (confidence intervals correspond to one standard deviation).
Food Waste FeedstockNTotal N (mg/L)Nitrate (mg/L)Total P (mg/L)Reactive P (mg/L)COD (mg/L)
Grains61600 ± 19734.4 ± 6.1142 ± 48298 ± 11729,200 ± 1630
Pear Lees8154 ± 10750.8 ± 5.338.7 ± 2.259.1 ± 23.0145,000 ± 19,200
Coffee Grounds6768 ± 18058.1 ± 23.444.9 ± 23.0255 ± 4930,700 ± 2030
Honeydew Skins689.0 ± 12.73.98 ± 6.3816.2 ± 1.712.0 ± 1.513,600 ± 3380
Table 6. Summary of ACP water quality data in the literature.
Table 6. Summary of ACP water quality data in the literature.
Food Waste FeedstockSourceTotal N (mg/L)Nitrate (mg/L)Total P (mg/L)Reactive P (mg/L)COD (mg/L)
Grains[21]2050 ± 600 -1038 ± 60352 ± 231,500 ± 1000
Grains[63]-106-46255,900
White Lees[21]96 ± 20-45 ± 1853 ± 6716,115 ± 610
Red Lees[21]1890 ± 220-3632 ± 180687 ± 80234,200 ± 6600
Rose Lees[64]1418.01 ± 5.29-769.62 ± 2.11--
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Nash, E.; Rehg, Z.; Thompson, R.; Bauer, S. Analysis of Product Distribution and Quality from the Hydrothermal Liquefaction of Food Waste Feedstocks. Energies 2026, 19, 109. https://doi.org/10.3390/en19010109

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Nash E, Rehg Z, Thompson R, Bauer S. Analysis of Product Distribution and Quality from the Hydrothermal Liquefaction of Food Waste Feedstocks. Energies. 2026; 19(1):109. https://doi.org/10.3390/en19010109

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Nash, Ezra, Zachary Rehg, Rukiyat Thompson, and Sarah Bauer. 2026. "Analysis of Product Distribution and Quality from the Hydrothermal Liquefaction of Food Waste Feedstocks" Energies 19, no. 1: 109. https://doi.org/10.3390/en19010109

APA Style

Nash, E., Rehg, Z., Thompson, R., & Bauer, S. (2026). Analysis of Product Distribution and Quality from the Hydrothermal Liquefaction of Food Waste Feedstocks. Energies, 19(1), 109. https://doi.org/10.3390/en19010109

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