Assessment of Potential of Organic Waste Methane for Implementation in Energy Self-Sufficient Wastewater Treatment Facilities

Abstract

The water sector faces a dual challenge: reducing energy consumption and carbon footprint while improving wastewater treatment efficiency. Anaerobic digestion (AD) remains the primary method for energy recovery in wastewater treatment plants (WWTPs). To enhance methane production and move toward carbon neutrality, co-digestion of sewage sludge with external substrates is gaining attention. This study evaluated nine organic substrates for their methane potential using the standardized Automatic Methane Potential Test System (AMPTS). The highest methane yield was obtained from sediment from a wine tank, reaching 1387 NmL CH₄/g VS, followed by yeast slurry, with 524 NmL CH₄/g VS. These values were over 6 and 2.5 times higher, respectively, compared to the methane potential of conventional mixed municipal sludge. Apple pomace, whey, food biowaste, and herbal maceration waste showed moderate improvements (301–388 NmL CH₄/gVS). When considering methane yield per gram of wet substrate, herbal maceration waste was the most efficient. A techno-economic analysis revealed that this substrate consistently achieved a net-positive energy balance (up to 170%) in large WWTPs, even at transport distances of 50 km. Other substrates also showed high potential, covering nearly 100% of energy demand under optimal conditions. In contrast, whey showed limited applicability due to transport constraints. These findings highlight the importance of substrate selection, particularly in practical efforts aimed at achieving energy self-sufficiency in wastewater treatment plants. It also provides WWTP operators with clear and practical insights into enhancing methane yields from anaerobic digesters while minimizing the risk of process inhibition.

1. Introduction

The European Union is perceived globally as a pioneer in the pursuit of climate neutrality. This concept extends beyond achieving net-zero greenhouse gas emissions and encompasses a broad range of actions aimed at eliminating or significantly minimizing human-induced environmental pressures and providing proportional compensation—such as enforcing the repairability of electrical appliances or the recycling of materials. In wastewater treatment plants (WWTPs), climate neutrality is assessed through reduced energy consumption and greenhouse gas emissions, alongside the generation and use of renewable energy, primarily biogas from anaerobic digestion and recovered waste heat [1]. Water and wastewater treatment plants are significant energy consumers. Each year, scientists expand our understanding of potential hazards present or transferred through water, prompting authorities to impose increasingly strict regulations on water and wastewater facilities. A strong correlation often exists between the extent of water purification, and the energy demands of the treatment processes—including coagulation, flocculation, filtration, and disinfection—necessary to achieve the desired water quality.

Wastewater is increasingly being recognized not as a problem, but as a valuable resource—a medium rich in nutrients and energy. Among the most effective methods for energy recovery is anaerobic digestion of sludge generated during the treatment processes. Anaerobic digestion—also commonly referred to as methane fermentation—is a well-known and extensively studied sludge stabilization method, commonly applied at medium and large-scale wastewater treatment plants. It is a biochemical process in which organic compounds are broken down in the absence of oxygen, leading to the production of methane [2,3]. Unlike aerobic sludge treatment, anaerobic digestion not only reduces organic content and odors but also enables energy recovery.

One way to improve the efficiency of anaerobic digestion is through co-digestion, which involves adding other organic wastes to sewage sludge to increase (enhance) biogas production process [3,4]. After purification, biogas can be used directly on-site in combined heat and power (CHP) units to generate electricity and heat. It can also be injected into the gas grid and distributed to end users without requiring significant infrastructure upgrades. In areas without a grid connection, compressed biogas (CNG—Compressed Natural Gas) may be used as an alternative vehicle fuel.

To date, many publications have focused on only a small number of substrates [5,6], often originating from a single sector such as agriculture or food processing. There is a noticeable lack of studies that assess a wider range of organic substrates under identical experimental conditions, particularly using the same inoculum. The origin and characteristics of the inoculum have a significant influence on methane potential [7]; therefore, to ensure comparability, all tests should be conducted using the same inoculum source. Moreover, most publications emphasize methane yield per unit of dry matter, organic matter, or volatile solids. From the perspective of investors, operators, or engineers, the actual wet volume of the substrate is often more relevant, as it determines both digester loading capacity and the economic feasibility of transport. Addressing this gap is crucial for linking scientific research with the practical needs of WWTPs. While scientifically valuable, these measures overlook the reality faced by WWTP operators, for whom the wet volume of the substrate is the decisive parameter. Wet-based yields directly determine digester loading capacity, transport logistics, and ultimately the feasibility of implementing co-digestion in practice. Highlighting this practical perspective represents one of the central motivations for the present study.

There are approximately 20,000 biogas installations across Europe, with agricultural plants comprising around 90% of this total. Municipal wastewater and landfill gas recovery systems account for the remaining 10% [8]. Meanwhile, Europe has about 26,500 wastewater treatment plants, indicating that fewer than 10% are equipped with anaerobic digesters for sludge stabilization via methane fermentation. According to the new Urban Wastewater Treatment Directive [1], by 2045, all WWTPs serving populations greater than 10,000 PE—equivalent to a daily throughput of approximately 1500 m³, assuming an average water consumption of 150 L/person—must achieve full climate neutrality. Intermediate targets begin as early as 2030, when such plants will be required to reach 20% neutrality. While smaller plants may meet the 20% neutrality threshold using photovoltaic panels, the next target—40% neutrality by 2035—will likely be unattainable relying solely on this technology.

Over the past year, increasing signals have emerged indicating governmental support for further development of this energy segment. For WWTPs, this may be the final opportunity to invest in anaerobic reactors and adopt co-digestion practices, combining sewage sludge with organic waste from the agri-food industry—a strategy that scientific studies have shown to be more cost-effective and efficient than mono-digestion [9,10].

To achieve globally comparable results, the standardization of methodologies represents another key justification for this study. Biochemical methane potential (BMP) assessment methods have evolved—from simple closed-jar digesters and manual gas volume measurements to much more precise and controlled devices, such as the Automatic Methane Potential Test System (AMPTS). Consequently, researchers have proposed standardized procedures [11,12], and this publication follows that approach. It should also be noted that the same plant species, when cultivated in different climate zones, will not have the exact same chemical composition [13,14], which directly influences the methane yield that can be obtained from the material.

The present study aims to assess the methane potential of various organic waste streams, providing insights that may support their implementation in energy self-sufficient wastewater treatment facilities.

2. Materials and Methods

2.1. Experimental Design

The study aimed to evaluate the methane potential of selected organic waste and by-products that could potentially be co-digested with sewage sludge. Ten substrates were subjected to biochemical methane potential (BMP) tests using the Automatic Methane Potential Test System (AMPTS, Bioprocess Control, Lund, Sweden) over a 21-day anaerobic digestion period.

The experiment was conducted using two AMPTS devices, comprising a total of 30 reactors, each with a volume of 1000 mL. Each substrate was analyzed in triplicate. The experiment was carried out in accordance with the guidelines provided in the AMPTS manual by BPC Instruments (Lund, Sweden). The organic loading rate for each reactor was 5 g VS per 1 L of inoculum. Based on the inoculum characteristics (3.6% TS and 57.33% VS/TS, corresponding to 20.6 g VS/L), this resulted in a substrate-to-inoculum (S/I) ratio of approximately 0.24 g VS/g VS, which lies within the commonly recommended range for BMP assays.

2.2. Substrates

All substrates were obtained as real waste/by-products from local agri-food industries in Poland, directly from the factories. The decision to select substrates from the dominant agri-food industries in Poland was driven by their significant share in the national market. Currently, there are as many as 340 breweries [15], 356 dairy processing plants [16], and 300 fruit and vegetable processing facilities [17] operating in Poland. Additionally, the study aimed to include substrates that are less frequently reported in the literature. In total, ten substrates were ultimately selected for the experiment, based on factors such as organic content, current reuse rate (e.g., as animal feed), and the waste-stream quantity generated.

Apple pomace and food biowaste were ground and sieved through a 3 mm mesh to achieve proper homogenization before the BMP tests. Liquid substrates were used as-collected without further pretreatment, while solid materials were carefully mixed to ensure sample uniformity before feeding into the reactors. All substrates used in the experiment are shown in Figure 1.

The origin, total solids (TS), and volatile solids (VS) content of the tested substrates are summarized in

Table 1. Short description of substrates used in the experiment.

Figure 1 No.	Substrate	Origin	Total Solids (TS) [%]	Volatile Solids (VS) [%TS]
1	Whey	By-product of curd cheese production	6.0	87.67
2	Sediment from a wine tank	Post-clarification sludge from fruit wine production	5.12	97.58
3	Yeast slurry	Biomass of brewing yeast cells	16.10	93.66
4	Activated sludge from a brewery	Microbial suspension from brewery wastewater treatment	0.98	61.39
5 and 6	Sewage sludge	Mixture of thickened primary and waste activated sludge (1:1)	5.67	74.26
7	Inoculum (control)	Anaerobic inoculum pre-incubated for 7 days	3.6	57.33
8	Herbal maceration waste	Residue from herbal extraction	35.90	95.86
9	Apple pomace	Residue from apple juice production	24.36	98.58
10	Food biowaste	Kitchen residues from a restaurant	20.55	93.84
11	Dewatered sludge from a brewery	Post-treatment waste from mechanically thickened sludge	8.28	77.00

.

The materials included various industrial and food-processing by-products such as whey, herbal maceration waste, food biowaste, wine sediment, brewery sludge, yeast slurry, and apple pomace. A mixture of thickened primary sludge and waste activated sludge served as the reference substrate, while anaerobic inoculum was used as the control. Both the reference and inoculum were obtained from the same local wastewater treatment plant, a large municipal facility with a capacity exceeding 1 million PE, specifically from an operating mesophilic mono-digester chamber. The digester operates at 37 °C, and the characteristics of the inoculum are summarized in Table 1 and

Table 2. Table physicochemical substrate characterization.

	COD [mg O2/L]	VFA [mg CH3COOH/L]	N–Total [mg N/L]	P–Total [mg P/L]	pH [–]	Alkality [mval/L]
Whey	55,600	6900	721	690	4.6	30
Activated sludge from a brewery	1212	132.6	194.7	4.85	7.79	24
Yeast slurry	112,250	7550	3845	1720	5.15	80
Sediment from a wine tank	114,050	3885	1450	91.2	3.7	0
Primary thickened sludge	4077	1799	249	4.45	6.1	22
Waste thickened sludge	618	734	682.4	115.6	7	18
Mixed thickened sludge	2347.5	1266.5	465.7	60.0	6.55	20
Inoculum	1664	239	1090	45.8	7.5	65

.

2.3. Step-by-Step Procedure

As mentioned in Section 2.1, the experiment was carried out using the AMPTS. The experimental procedure consisted of several sequential steps. Initially, each reactor was filled with 200 mL of anaerobic inoculum, and the selected substrates were added in quantities corresponding to 1 g of volatile solids (VS). Subsequently, the mixing system and tubing were carefully assembled. To ensure anaerobic conditions, the entire setup—including reactors and tubing—was flushed with nitrogen gas. Once the system was sealed, water baths were heated to 37 °C to maintain mesophilic conditions, and the operational components such as magnetic stirrers, gas transmitters, and receivers were activated. The reactors were mixed periodically for 1 min every 10 min, resulting in a total mixing time of 6 min per hour. The experiment was initiated using dedicated software, and methane production was continuously monitored over a 21-day period, for which a volumetric gas flow cell with an integrated CO₂ absorption unit was employed. Throughout the test, the functioning of the device and water levels were regularly inspected and maintained. After 21 days, methane production had stabilized, showing less than a 1% increase over 3 consecutive days, which met the criteria for terminating the test. Finally, the system was disassembled, and samples were collected for further analysis.

2.4. Methane Potential Calculation

The methane potential was calculated based on the volume of methane produced during the experiment, normalized to 1 g of volatile solids (VS).

$$P_m=({\displaystyle \frac{{(V}_p-V_k)}{L_{vs}}})$$

(1)

P_m—methane potential [mL/g VS],

V_s—cumulative methane volume from the substrate sample after digestion [mL],

V_k—cumulative methane volume from the control sample (inoculum only) after digestion [mL],

L_vs—volatile solids (organic dry matter) load of the substrate (excluding inoculum) [g VS].

2.5. Analytical Methods

Prior to the batch anaerobic digestion tests, all substrates were analyzed for total solids (TS) and volatile solids (VS) content to determine appropriate dosing, following APHA Standard Methods [18]. Additional physicochemical analyses included chemical oxygen demand (COD), total organic carbon (TOC), pH, electrical conductivity (EC), total dissolved solids (TDS), total nitrogen (TN), ammonium nitrogen (NH₄⁺–N), total phosphorus (TP), alkalinity, and volatile fatty acids (VFAs) were determined following the protocols provided in APHA [18]. For liquid substrates, all parameters were determined in the dissolved fraction, obtained by filtration through a 0.45 µm membrane. In case of solid substrates, only TOC was analyzed, using a dedicated solid sample module. These parameters were selected to characterize substrate biodegradability and monitor process stability during fermentation.

pH, EC, and TDS were measured using a portable multiparameter meter (Hach HQ40d, Loveland, CO, USA). COD was determined spectrophotometrically using Hach LCI 500 cuvette tests and a DR3900 spectrophotometer (Loveland, CO, USA), following the manufacturer’s protocol. TOC was analyzed using a Shimadzu TOC–L analyzer (Kyoto, Japan). Ammonium nitrogen and total phosphorus were quantified using standard Hach cuvette test kits. VFAs were measured using the Hach TNTplus method, based on the esterification principle. Alkalinity was determined by titration using methyl orange as an indicator.

2.6. A Techno-Economic Model

A techno-economic model was developed to evaluate the feasibility of co-digestion in municipal wastewater treatment plants (WWTPs) of various sizes. The simulation considered three key parameters: (1) available digester capacity (5%, 10%, 20% of total volume), (2) distance from the WWTP to the substrate source (10, 25, and 50 km), and (3) plant size expressed in population equivalent (PE): 5000, 25,000, and 100,000 PE. For each scenario, the model calculated the annual volume of co-substrate that could be added, the corresponding methane production and the electrical energy generated, based on a biogas conversion rate of 2.2 kWh/Nm³ CH₄. Transport costs were estimated assuming 1.5 EUR/km for a 20-ton truck and round-trip distances. The value of electricity was calculated based on a unit price of 200 EUR/MWh. The net economic balance for each scenario was derived by comparing energy value with transport costs. Substrate costs and digester operational costs were excluded at this stage, assuming zero feedstock purchase cost and existing infrastructure. For the final comparison of net energy gain against total energy consumption at WWTPs, the following electricity consumption factors were applied: 62.68, 50.25, and 35.0 kWh/PE/year [19] for the respective WWTP sizes of 5000, 25,000, and 100,000 PE. This translates to total annual electricity demands of approx. 313, 533, 1256, and 3500 MWh, respectively. Additionally, the effects of various energy price fluctuations on the final energy balance were considered: a 50% decrease, a baseline scenario, and a 50% increase relative to the average European electricity price of 200 EUR per 1 MWh. To check the strength of the relationships between various parameters that could influence the Electricity Coverage Ratio (ECR), Pearson Correlation was performed.

3. Results

3.1. Physicochemical Characteristics of Substrates

The tested substrates varied considerably in terms of their basic physicochemical parameters. The results for liquid fraction analysis are presented in Table 2.

Dry matter content ranged from just above 1% in the brewery sludge to almost 36% in the herbal maceration wastes. Among liquid substrates, the highest share of organic matter in total solids was observed in apple pomace (98.58%) and sediment from a wine tank (97.58%), while lower values were recorded in sludges from municipal and brewery wastewater treatment plants. Most of the tested substrates exhibited acidic pH values, with the lowest recorded in wine sludge (3.7) and whey (4.6). Only the mixed sludge from the municipal WWTP and certain brewery sludges showed near-neutral pH levels. Significant differences were observed in COD concentrations. The highest values were noted in sediment from a wine tank (approx. 114 g O₂/L) and yeast slurry (up to 112 g O₂/L), both rich in easily degradable organic compounds. Although whey had lower COD, it still exceeded 50 g O₂/L, which is over 20 times higher than the COD of the reference sewage sludge. The concentration of volatile fatty acids (VFA) followed a similar trend. Yeast concentrate showed the highest VFA content (7550 mg CH₃COOH/L), followed by whey and sediment from a wine tank. In contrast, VFA levels in the brewery sludges and sewage sludge remained low and did not significantly differ from the inoculum used in the experiment. In terms of nutrient content, yeast concentrate was notable for its high nitrogen level of almost 4 g/L and approximately 15% of its dry mass. This reflects the high protein content typical of yeast cells. Phosphorus content was also elevated in yeast concentrate and whey, likely due to cell structures and the use of phosphorus-based additives in industrial processes. The dissolved and particulate fractions of total organic carbon (TOC) were highly variable. Herbal maceration residue exhibited the highest dissolved TOC (93 g/L), while solid substrates such as apple pomace were dominated by particulate carbon. In contrast, municipal and brewery sludges showed TOC values in the range of 0.3–8.2 mg/L, consistent with their lower methane potential.

3.2. AMPTS Results

The AMPTS device performed volumetric measurements of methane production over a period of 21 consecutive days. Figure 2 presents the cumulative methane production curves produced from each substrate.

The highest intensity of methane production for each substrate was observed within the first 2–5 days. After this period, the daily methane yield declined sharply in all cases. A slight exception was noted for the herbal maceration residue, which exhibited methane emission up to day 13, meaning that the daily biogas production increase remained above 2% until that point, whereas for the other substrates this typically occurred within the first week after reactor startup. This may be attributed to the fact that the technological process at the factory involves extraction of plant material at high temperatures, which can be considered a form of thermal pretreatment. As a result, more polymers become accessible to microorganisms. The degradation of lignocellulosic substrate is clearly more prolonged. Another exception was the sediment from the wine tank, which generated the highest methane yields on days 3 and 4 of the experiment, rather than on day 1, as was the case for all other substrates. A distinct difference was observed for this substrate, which produced a significantly higher volume of biogas compared to the others. From 5 g of volatile solids (VS), nearly 1700 mL of methane was obtained. In second place, with half the yield, was the yeast slurry, which generated 830 mL of methane. The herbal maceration residue, biowaste, whey, and apple pomace each produced approximately 600–700 mL of methane.

In terms of kinetic behavior, most substrates demonstrated short lag phases (1–2 days), indicating rapid microbial adaptation and effective substrate biodegradability. However, the progression of methane production rates revealed distinct differences between the tested materials. The yeast slurry was the first substrate for which the daily increase in cumulative methane yield dropped below 1%, on day 8 of the experiment. For the sediment from the wine tank, this threshold was reached on day 10, whereas for the remaining substrates it occurred significantly later. This suggests that both materials are highly biodegradable and consist mainly of easily degradable organic fractions. In contrast, the herbal maceration waste maintained daily methane increases above 2% until day 13, reflecting its lignocellulosic composition. Nonetheless, the preliminary thermal treatment applied to the herbs at the production facility likely enhanced the accessibility of complex polymers to microorganisms, improving overall methane yield despite the slower degradation rate.

All the aforementioned substrates generated more methane than the mixed sludge from the wastewater treatment plant. Methane production from the activated sludge and dewatered sludge from a brewery was 32% and 24% lower, respectively, than that from the mixed sludge from the municipal WWTP.

3.3. Methane Potential

The methane potential of the samples can be referenced to the mixed sludge that is currently used at many wastewater treatment plants as the only substrate for anaerobic digestion. Therefore, this sample represents the baseline scenario. Figure 3 presents the methane potential expressed in two units: per gram of volatile solids (g VS) and per gram of wet substrate (wet weight basis).

Among the eight tested substrates, six demonstrated higher methane production compared to the mixed sludge, which yielded 227 NmL CH₄/g VS. The highest methane volume was obtained from the digestion of sediment from the wine tank. The methane potential of this substrate is more than six times higher than that of the mixed sludge, reaching 1387 NmL CH₄/g VS. The second-highest value was observed for yeast slurry, which produced almost 2.5 times more methane compared to the mixed sludge. Methane yields from apple pomace, whey, biowaste, and herbal maceration waste ranged from 301 to 388 NmL CH₄/g VS, representing an increase of 33% to 71% compared to the mixed sludge. The poorest results were obtained from brewery sludge digestion. From non-dewatered and dewatered activated sludge, methane production was four and two times lower, respectively, compared to the sewage sludge from the WWTP.

While methane potential is a key parameter, it is important to consider that each waste stream has different total solids (TS) and volatile solids (VS) content. Therefore, the substrate with the highest methane potential is not necessarily the most suitable choice, particularly if it is highly diluted, as this may exclude it due to high transportation costs. To account for these practical limitations, the methane potential results were also recalculated based on the fresh mass of each substrate. From the perspective of the limited volume of existing digesters at WWTPs and the logistics of co-substrate transport, this parameter enables a more realistic assessment of the practical applicability of a given substrate for co-digestion with sewage sludge.

Considering the actual weight of the substrate and the amount of methane obtained from it, the most favorable result was observed for the herbal maceration residue, which yielded over 130 mL of CH₄ per gram of wet substrate. Approximately half as much methane was produced from the yeast slurry, apple pomace, sediment from a wine tank, and biowaste.

Although the sediment from a wine tank significantly outperformed all other substrates in terms of methane potential per gram of volatile solids, when expressed per ton of wet substrate, it ranked only fourth. As many as five substrates generated several times more methane per gram of substrate than the mixed sludge from the wastewater treatment plant. This indicates that each of them could be considered as a potential co-substrate for sewage sludge co-digestion. The digester loading in this experiment was relatively low, as required by the methodology for determining methane potential. For this reason, methane production in all cases declined after just a few days. In contrast, the standard organic loading rate in full-scale wastewater treatment plants typically ranges between 1.0 and 1.6 g TS/L which corresponds to approximately 0.75 to 1.2 g VS/L, i.e., about five times higher than the loading applied in the current experiment. Six out of the eight tested substrates demonstrated a higher methane potential than mixed sludge, which is typically the sole substrate used for anaerobic digestion at most WWTPs.

When considering both volatile solids content and total solids fraction, it becomes evident that substrates with high VS and moderate TS, such as herbal maceration waste (95.9% VS, 35.9% TS) and apple pomace (98.6% VS, 24.4% TS), provide a favorable balance between methane production per gram of substrate and per unit wet mass. In contrast, sediment from a wine tank, despite its very high VS content (97.6%), has low TS (5.1%), which reduces its volumetric methane yield and highlights the importance of evaluating both metrics when assessing practical applicability for co-digestion. These observations underscore that TS and VS are critical parameters for translating laboratory-scale BMP results into realistic expectations for WWTP co-digestion.

3.4. Simulation of the Economic Feasibility of Co-Digestion in Wastewater Treatment Plants

3.4.1. Feasibility Study

To better understand the methane potential of the analyzed substrates and their applicability, an analysis was conducted to determine which ones would be feasible for small and large WWTPs, as well as to assess the transportation distance at which the costs exceed the benefits of co-digestion. The results are presented in Figure 4.

The analysis of the Electricity Coverage Ratio (ECR) revealed clear trends associated with the type of substrate used for co-fermentation, the size of the WWTPs, the free fermentation volume available, and the transport distance of substrates.

Firstly, the data indicate that co-fermentation with traditional sludge substrates such as activated sludge and dewatered sludge from breweries consistently results in negative or near-zero ECR values, regardless of WWTP size or transport distance. This suggests limited energy recovery potential from these substrates under the tested conditions, which may be due to their relatively low biodegradable organic content or inhibitory compounds that affect biogas yield.

Herbal maceration waste consistently outperformed all other substrates, achieving a net-positive energy balance of approximately 150–170% in large WWTPs with 20% free digester volume at distances of 50, 25, and 10 km, respectively. Notably, even small WWTPs with only 5% free digester capacity could reach similar values (130–140%) at 50 and 25 km. Apple pomace, food biowaste, yeast slurry, and sediment from wine tanks demonstrated comparable potential, covering almost 100% of the plant’s energy demand when applied at 20% free digester volume. In contrast, whey showed limited applicability: regardless of WWTP size or available volume, the transport distance could not exceed 25 km, and even at 10 km with 20% free digester capacity in a large WWTP, it contributed only around 18% of the plant’s electricity demand.

The free volume of fermentation reactors appears to be a critical factor. Increasing the free fermentation volume from 5% to 20% generally leads to an increase in ECR by up to 10–20 percentage points. This can be attributed to the larger volume allowing higher organic loading rates and longer retention times, improving biogas production efficiency.

Transport distance negatively impacts ECR, though its effect is substrate- and WWTP size-dependent. Longer transport distances (50 km) generally reduce the net energy gain due to increased fuel consumption for substrate transport, which diminishes the overall energy recovery benefit. Shorter transport distances (10–25 km) minimize these losses and thus support better ECR values.

The interplay of these factors highlights the necessity of site-specific assessment when considering co-fermentation substrates for energy recovery in WWTPs. Particularly, substrates with high methane potential, combined with sufficiently large fermentation volumes and minimized transport distances, can significantly enhance the energy self-sufficiency of wastewater treatment plants.

Data presented in Figure 5 show how market energy price fluctuations affect the economic feasibility of biogas utilization. Increasing the electricity price from 0.1 to 0.3 EUR/kWh led to a non-linear improvement in ECR across all tested substrates. When the price increased from 0.1 to 0.2 EUR/kWh, the average ECR rose by approximately 6 percentage points, whereas a further increase to 0.3 EUR/kWh resulted in a smaller gain of about 2 percentage points. This pattern reflects a logarithmic growth trend, where profitability increases rapidly at low electricity prices but stabilizes as the price continues to rise.

Among the analyzed substrates, herbal maceration waste achieved the highest ECR values (69–77%), followed by yeast slurry (36–44%), apple pomace (32–40%), and food biowaste (26–34%), confirming their strong energetic potential. Substrates such as activated sludge and dewatered brewery sludge showed negative or near-zero ECR values, indicating limited feasibility for co-digestion.

Overall, the results demonstrate that although higher electricity prices improve apparent profitability, the effect is subject to diminishing returns. Therefore, optimizing substrate selection and methane yield remains far more critical for improving the energy balance of wastewater treatment plants than fluctuations in market electricity prices.

While the feasibility analysis identified the most promising substrates and operational conditions for enhancing energy self-sufficiency, the following section provides a statistical and parametric evaluation of these findings. The Pearson correlation analysis quantifies the strength of relationships between key variables.

3.4.2. Pearson Correlation Analysis

To evaluate the relationships between key operational and economic factors and the overall energy performance of the wastewater treatment plant, a Pearson correlation analysis was conducted (Figure 6). The analysis examined five parameters—WWTP size (PE), free digester volume [%], transport distance [km], electricity price [EUR/kWh], and annual methane yield [m³/year]—in relation to the Electricity Coverage Ratio [%].

The results revealed varying degrees of correlation between the selected parameters and ECR. The strongest positive correlation was observed for annual methane yield (r = 0.69), indicating that methane production is the primary factor influencing the share of electricity demand covered by biogas utilization. A moderate positive correlation was found for free volume (r = 0.30), suggesting that increasing the available digester capacity enhances energy recovery efficiency.

In contrast, WWTP size (r = 0.11) and electricity price (r = 0.08) exhibited only weak positive correlations with ECR, implying a limited influence on energy self-sufficiency within the tested range. Transport distance (r = −0.09) showed a weak negative correlation, indicating that longer substrate transport distances slightly reduce overall energy performance due to higher energy consumption for logistics.

Overall, the correlation analysis statistically confirms that biogas production potential (methane yield) and process capacity utilization (free volume) are the key drivers of energy recovery efficiency, while economic and logistic parameters exert secondary influence.

4. Discussion

The results of the biomethane potential (BMP) tests indicated a significant variation in methane yield among the tested substrates, with values ranging from as low as 58.9 NmL/g VS to as high as 1386.9 NmL/g VS. This clearly demonstrates the influence of substrate origin and composition on anaerobic degradability.

The highest methane production was observed for sediment from a wine tank, reaching 1386.9 NmL/g VS, followed by yeast slurry (524.4 NmL/g VS). This corresponds with the findings of Chiappero et al. [20], who reported a methane potential of 1257 NmL CH₄/g VS for wine sludge, but emphasized the risk of process inhibition due to the accumulation of organic acids. Herbal maceration waste (388.1 NmL/g VS) and apple pomace (301.3 NmL/g VS) are by-products of the food processing industry, rich in lignin–cellulose compounds. Ampese et al. [21] reported a much lower methane yield of 2.75 NmL/g VS for apple pomace, which differs substantially from the results obtained in this study. This discrepancy may be attributed to several methodological and substrate-related factors. A key difference lies in the experimental setup—in the present work, digestion was terminated once biogas production had ceased, whereas Ampese et al. [21] employed a semi-continuous operation mode. Such systems often operate under higher organic loading rates and shorter hydraulic retention times, which can lead to incomplete substrate degradation and consequently, lower methane yields. Additionally, the origin and storage conditions of the substrates could have played a role. Apple pomace is a highly perishable material, rich in easily degradable sugars that may be lost during transport or storage, especially under warm climatic conditions, such as those in Brazil, where the study by Ampese et al. [21] was conducted. Extended storage or partial decomposition prior to testing could significantly reduce the organic fraction available for methanogenesis. Finally, differences in particle size, pretreatment methods, and inoculum characteristics may have further influenced the observed variability. In this study, apple pomace was mechanically homogenized and sieved through a 3 mm mesh, improving substrate accessibility and promoting more complete degradation. Herbal maceration waste is a poorly tested substrate. Nayak et al [22], Patel et al. [23] and Hjouji et al. [24] used herbal residues in their work, but they did not straightforwardly report their methane potential.

Moderate methane yields were recorded for whey (325.7 NmL/g VS), food biowaste (327.5 NmL/g VS), and sewage sludge (226.9 NmL/g VS). These results are aligned with ranges reported in the recent literature. Under mesophilic conditions (37 °C), Bi et al. [25] reported a cumulative methane yield of 364 NmL/g VS for food waste, which is very close to the value obtained in this study. This consistency suggests that, despite differences in feedstock origin and operational settings, the biodegradability of food biowaste remains within a narrow range under mesophilic digestion. The methane yield of 325.7 mL CH₄/g VS obtained from our acidic cow milk whey is consistent with values found in the literature, falling between the 274 mL CH₄/g VS reported for goat cheese whey by Fernández-Rodríguez et al. [26] and the higher yield of up to 437.3 mL CH₄/g VS observed by Mainardi et al. in Italian dairies [27]. The lower yield in Fernández-Rodríguez’s study may be related to the different substrate source and potential ammonia inhibition during pure whey digestion, while the higher yields reported by Mainardi et al. [27] likely benefited from ultrasound pre-treatment and higher inoculum-to-substrate ratios. Overall, our results confirm that cow milk whey possesses a substantial methane potential comparable to previously reported values, with room for enhancement through process optimization.

The lowest methane yields were observed for brewery-derived activated sludge (58.9 NmL/g VS) and dewatered brewery sludge (97.2 NmL/g VS). These low values may be attributed to prior microbial degradation, high fractions of recalcitrant organics, and possible inhibitory substances like detergents used in industrial cleaning. Such observations are supported by Angelidaki and Ellegaard [28], who highlighted the low BMP of industrial sludges.

When normalized per gram of wet substrate, herbal maceration waste exhibited the highest yield (133.6 NmL/g wet), due to its high total solids content (35.9%). This demonstrates the importance of both VS-specific and volumetric (wet weight) methane yield in evaluating substrate suitability. Although sediment from a wine tank had the highest yield per VS, its methane yield per wet mass was lower (69.3 NmL/g wet), due to higher water content. Food biowaste showed relatively high volumetric performance (63.1 NmL/g wet), supporting its use in co-digestion systems, despite known variability in composition and fat content. In contrast, sewage sludge had modest VS-based BMP and very low methane output per wet weight (9.6 NmL/g wet), highlighting the limited energy recovery potential from low-solids feedstocks.

These findings emphasize the importance of substrate selection in optimizing co-digestion performance. Substrates with high VS content and readily fermentable organics—such as fruit residues, yeast-rich slurries, and herbal waste—clearly outperform sludge-based materials. Co-digestion of such agro-industrial by-products with municipal sludge can enhance biogas production, improve process stability, and reduce sludge disposal volumes, as confirmed by multiple authors [2,3,4].

The implementation of co-digestion, i.e., the addition of external substrates, is not without risk. Along with these substrates, inhibitory compounds may enter the digester, potentially disturbing the anaerobic digestion process, reducing its efficiency, or, in extreme cases, even leading to complete process failure. Of particular concern are substrates such as yeast slurry, which in this study contained up to 4 g total nitrogen/L and more than 1.7 g phosphorus/L. Previous studies have reported an inhibitory effect of ammonium nitrogen in the range of 1.5–3 g/L [29], highlighting the need for careful control when dosing substrates rich in total nitrogen, as the resulting ammonium may accumulate in the digester liquor. Another important inhibitory factor is volatile fatty acids (VFAs). Although VFAs are intermediates and precursors for methane formation, their excessive accumulation can lead to acidification and disruption of methanogenesis. Phosphorus may also exert an inhibitory effect on methanogenic activity. Mancipe-Jiménez et al. [30] demonstrated that increasing the phosphorus concentration in the influent to 33.3 mg/L led to an 18% reduction in gas production and a 54% decrease in the bacterial growth coefficient. These findings underline the need for caution and comprehensive characterization of substrates intended for co-digestion, as excessive nutrient loads—particularly nitrogen and phosphorus—can disrupt the microbial balance and reduce overall process efficiency.

Future research should focus on determining optimal substrate ratios, retention times, and pre-treatment methods to maximize energy recovery from locally available organic residues. It should be noted that, in line with the principles of the circular economy, an increasing proportion of organic waste is being eliminated, reduced, or recovered. Many substrates traditionally available for anaerobic digestion, such as root and stem residues or processed vegetables, are now utilized as livestock feed, while waste oils are refined into biodiesel, and whey is dried and incorporated into various food applications. This trend indicates that biogas plant operators must broaden their search for feedstocks beyond conventional sources, as certain smaller-scale industries can generate highly valuable wastes capable of substantially enhancing methane yields. Future research should also focus on detailed techno-economic assessments and pilot-scale validations to support practical implementation. Additionally, investigations are warranted into the long-term stability of co-digestion systems, the microbial community dynamics under varying substrate compositions, and the development of predictive models for biogas yield. Exploring the integration of co-fermentation with nutrient recovery technologies and assessing the environmental impacts through life cycle analysis would also provide valuable insights for sustainable process design.

5. Practical Implementation Aspects

The results of this study provide valuable insights into the implementation of co-digestion strategies under full-scale conditions. Scaling up from laboratory to operational WWTPs requires consideration of several factors that influence process stability and methane recovery. Variations in waste composition—particularly in nitrogen, phosphorus, and organic load—necessitate adaptive feeding regimes to prevent inhibitory accumulation of ammonia or volatile fatty acids. Continuous monitoring of digester alkalinity, pH, and ammonium concentration is essential to maintain microbial balance and avoid process upset.

Furthermore, the integration of external substrates should be optimized according to the available digester capacity and substrate biodegradability. Substrates with high concentrations of soluble organics, such as sediment from a wine tank or yeast slurry, may require phased or diluted feeding to minimize shock loading effects. Conversely, slowly degradable lignocellulosic materials, such as herbal maceration residue or apple pomace, could benefit from pre-treatment or co-digestion with easily degradable wastes to enhance hydrolysis rates. From an operational standpoint, predictive control based on substrate characterization and real-time monitoring could support dynamic adjustment of loading rates. Such strategies would improve methane yield, process resilience, and energy recovery efficiency, while mitigating the risks associated with the heterogeneous nature of co-substrates.

It is also important to recognize that the conditions applied in laboratory BMP assays, such as those in the present study, do not fully represent the complex environment of full-scale wastewater treatment plants. Pasciucco et al. [31] demonstrated that the use of aluminum-based coagulants—commonly employed for sludge conditioning and phosphorus removal in WWTPs—can markedly inhibit anaerobic digestion performance. In their study, both polyaluminum chloride (PAC) and aluminum sulfate (AS) reduced methane yields in proportion to the dosage, with AS causing up to a 31.7% reduction compared to the control. The inhibition was attributed to the negative influence of aluminum on solubilization, hydrolysis, and acidogenesis, as well as to the increased generation of hydrogen sulfide (H₂S), which suppressed methanogenesis.

These findings highlight that chemical conditioning and sludge treatment practices in WWTPs can substantially reduce the methane potential of sewage sludge, which implies that BMP values obtained under ideal laboratory conditions using substrates free from such chemical residues may overestimate the actual biogas yields achievable in practice.

6. Conclusions

This study underscores the importance of selecting appropriate substrates to maximize the energy recovery potential from co-fermentation processes in wastewater treatment plants.

Among the tested substrates, the highest methane yield was obtained from sediment from a wine tank (1387 NmL CH₄/g VS), followed by yeast slurry (524 NmL CH₄/g VS). Herbal maceration waste (388 NmL CH₄/g VS), apple pomace (301 NmL CH₄/g VS), whey (326 NmL CH₄/g VS), and biowaste (328 NmL CH₄/g VS) also showed substantially higher methane potential compared to mixed sludge (227 NmL CH₄/g VS). The lowest values were recorded for brewery sludge, with only 59–97 NmL CH₄/g VS, confirming its poor suitability for methane recovery.

The study revealed that herbal maceration waste is the most promising co-substrate, reaching 150–170% Electricity Coverage Ratio (ECR) in large WWTPs and over 130% even in small facilities. Apple pomace, food biowaste, yeast slurry, and sediment from a wine tank also demonstrated high potential, with values close to 100% ECR when 20% free digester volume was available. In contrast, whey contributed very little to energy recovery, with a maximum of about 18% under the most favorable conditions. Increasing the free digester volume from 5% to 20% was shown to improve ECR by up to 20 percentage points. Overall, the results highlight that the choice of substrate strongly influences energy recovery, and several tested wastes could substantially enhance the energy self-sufficiency of WWTPs.

The model demonstrates that, although higher electricity prices can improve apparent profitability, the effect exhibits diminishing returns. Consequently, optimizing substrate selection and maximizing methane yield are far more critical strategies for improving the energy balance of wastewater treatment plants than relying on market electricity price fluctuations. These results also allow a recommendation to be formulated for WWTP operators to conduct preliminary research prior to choosing a potential co-substrate to determine whether the application of specific co-fermentation strategies is technically viable for implementation in order to define process conditions, evaluate co-substrate availability, and ensure that their use is economically feasible for a given plant.