Enhanced biomethane production via hydrodynamic cavitation pretreatment and co-digestion of brown and DAF sludge Open Access

Dairy (milk) processing facilities are tasked with managing the disposal of large quantities of excess sludge generated during effluent treatment processes (Kwapinska et al. 2022). Improvements in dairy effluent treatments regarding efficient water, energy, and chemical use, and cost-effectiveness, are necessary. These dairy sludges are rich in organic content and pose environmental concerns due to stringent regulations governing waste disposal. In dairy wastewater treatment facilities, activated sludge with lower concentrations is typically treated using aerobic stabilization, whereas higher concentrations require the addition of oxygen to facilitate the process. However, compared to aerobic treatment, anaerobic digestion (AD) is a more advantageous approach as it provides a sustainable valorisation pathway (Logan et al. 2021). Dairy processing sludge serves as a suitable substrate for AD, despite the challenges associated with the biodegradability of fats present in the sludge (Petruy & Lettinga 1997; Pankakoski et al. 2000; Watkins & Nash 2010). Though AD is in limited use in dairy processing industries (Ye et al. 2023), proper pretreatment of sludge followed by AD will be an attractive alternative for dairy waste treatment and contribute to the energy sector.

Various pretreatment techniques, including physical, chemical, biological, and physicochemical methods, are employed to enhance biomass bioavailability for microbial processes (Sun & Cheng 2002; Konde et al. 2021). A suitable pretreatment should be cost-efficient, scalable, and environmentally sustainable. Physical methods focus on particle size reduction but are less effective for wet biomass. Chemical pretreatments often generate inhibitory byproducts, necessitating additional chemical treatments for neutralization (Islam et al. 2018; Nagarajan & Ranade 2021). Biological pretreatment, though effective, is typically slow and expensive (Islam et al. 2017, 2021). Among physicochemical methods, steam explosion requires substantial energy input with only moderate improvements in biodegradability, while techniques like acoustic cavitation and microwave treatment demand high energy consumption, making them less viable due to increased operational costs and environmental concerns (Dwyer et al. 2008; Uma Rani et al. 2014; Al Ramahi et al. 2020). Recently, a vortex-based hydrodynamic cavitation (HC) pretreatment has been used for enhancing the realizable BMP of dairy sludges (Islam & Ranade 2023). HC pretreatment significantly enhanced substrate solubility, increasing the bioavailability of organic matter for fermentation. The process effectively degraded solids and solubilized floating fats, oil, and grease (FOG) components, improving sludge mixing and minimizing flotation issues. These changes optimized AD, particularly during hydrolysis and methanogenesis, as evidenced by increased sCOD and a higher degree of disintegration (DD) (Petkovšek et al. 2015; Vilarroig et al. 2020; Yao et al. 2022). Additionally, HC treatment altered sludge consistency and viscosity, likely due to structural modifications caused by cavitation-induced shear stress (Kim et al. 2020). The disintegration of solids resulted in reduced particles, which absorbed more moisture, contributing to increased viscosity and hence enhancing sludge characteristics for improved digestion efficiency (Xu et al. 2020; Yao et al. 2022).

Long-chain fatty acids (LCFA) present in sludge lead to various troublesome issues like immiscible phases, float, and inhibition of methanogenic bacteria by encapsulating them (Bhatt & Tao 2020). The strategies to solve these problems are pretreatment, co-digestion with a high C-source for denitrification, and dilution for anaerobic reactors (Tandukar & Pavlostathis 2022). The co-digestion process offers several advantages, including increased biogas production and enhanced solids destruction, leading to biosolids with improved dewaterability, ease of handling, and disposal. High-strength wastes like FOG are suitable co-substrates for co-digestion with low-carbon waste like municipal sludge (Tandukar & Pavlostathis 2022). Co-digestion promotes the enhanced degradation of these co-substrates, which, alongside greater biogas production, contributes to higher destruction of solids (Karki et al. 2021). To our knowledge, this is the first study reporting the effectiveness of HC pretreatment for co-digestion of brown and DAF sludges.

All brown and DAF sludge samples were collected from local dairy processing industries in Ireland (Figure 1). Inoculum was collected from an anaerobic digester using dairy sludge as feedstock. Sludge samples were pretreated using bench-scale vortex-based HC pretreatment with a nominal flow rate of 20 L/min at 250 kPa. A progressive cavity pump was used in this pretreatment process. The vortex-based HC device utilised in this study was constructed from stainless steel and was obtained from Vivira Process Technologies (www.vorta.com). A substrate volume of 10 L containing 5% of total solids (TS), inclusive of the internal volume of the pump and pipes, was subjected to treatment for both cases of brown and DAF sludge. The substrate was diluted with tap water to achieve this concentration, and tap water was consistently utilized for all dilution and BMP experiments. Samples of pretreated sludge were collected following varying numbers of passes through the HC device (0, 20, 40, and 80 passes). Subsequently, all treated and untreated samples were characterized and utilized for the BMP experiment to assess biomethane production.

The BMP using HC-treated brown and DAF sludge samples (80 passes) were assessed using the Automatic Methane Potential Test System (AMPTS II), designed by Bioprocess Control (Lund, Sweden). This system consists of 15 reactors, each with a capacity of 500 mL and an operational working volume of 400 mL. The feed ratios of brown and DAF sludge were 2:0; 1:1; 3:1 and 0:2 (as % volatile solids (VS)). All reactors were submerged in a water bath maintained at a constant temperature of 39 °C to simulate mesophilic AD conditions. The substrate-to-inoculum ratio was maintained at 1:2 based on VS. Each reactor was fitted with an overhead stirrer, which continuously operated at a speed of 80 rotations per minute to ensure proper mixing of the substrate and inoculum. The reactors were connected to a gas collection system through Tygon tubing and connectors. Gas produced during the digestion process was channelled through a container holding 80 mL of 3M NaOH solution to absorb carbon dioxide (CO₂) and hydrogen sulfide (H₂S). To monitor the end of the absorption capacity, 5 mL of a 0.4% thymolphthalein pH indicator was added to 1 L of the NaOH solution. After CO₂ and H₂S absorption, the remaining gas (primarily methane) was routed to a flow cell unit for precise volume measurement. All experiments were conducted in triplicate, including a blank control to account for any background methane production from the inoculum alone. Methane production was continuously tracked in real-time using dedicated software connected to the AMPTS II system. The experiments were terminated once the cumulative gas production plateaued, indicating the completion of AD. BMP values were calculated as the volume of methane produced per gram of VS introduced into the reactor.

The rheological characteristics change due to the HC treatment of the brown and DAF sludge was assessed using the Brookfield rheometer. Additionally, all the sludge samples and inoculum used in the BMP experiments were analysed according to standard methods for TS and VS determination (APHA 2022). Total COD (tCOD) and sCOD, total phosphorus, and organic acids were determined using the methods LCK014, LCK350, and LCK365 cuvette tests, respectively. The elemental composition (CHNSO) of brown and DAF sludge was determined by CHNSO elemental analyser. Based on the atomic composition (C, H, O, N) and following Boyel's equation, BMPth was calculated (Islam & Ranade 2023).

The characteristics of brown sludge, DAF sludge, and inoculum used in the anaerobic digester have been presented in Table 1. Sludge characteristics highlight distinct differences in their composition and biomethane production potential. These variations are crucial for determining the most effective treatment and valorisation strategies. Brown sludge and DAF sludge contain closer TS (16.8% w/w) and (16.24% w/w), respectively, but the VS content is lower in brown sludge (12.4% w/w) than in DAF sludge (15.44% w/w). VS is an essential indicator of the organic matter content, significantly influencing biomethane production potential.

The elemental composition shows stark contrasts, with DAF sludge having a much higher carbon content (69.8% w/w) than brown sludge (37.46% w/w). Hydrogen content also follows this trend, with DAF sludge at 9.2% w/w compared to 4.51% w/w for brown sludge. In contrast, brown sludge has a higher nitrogen content (7.01% w/w) than DAF sludge (5.02% w/w), leading to significant differences in the carbon-to-nitrogen (C/N) ratio. The C/N ratio of brown sludge is 6.23, while DAF sludge has a much higher C/N ratio of 23.37. These differences indicate that DAF sludge has a more balanced nutrient profile suitable for AD. In contrast, the lower C/N ratio in brown sludge may require co-digestion with carbon-rich substrates to optimize performance. Similar characteristics of dairy processing sludge were reported by other studies (Danalewich et al. 1998; Ashekuzzaman et al. 2019; Lutze & Engelhart 2020; Shi et al. 2021).

Regarding theoretical biomethane potential (BMPth), DAF sludge demonstrates a superior capacity, producing 905.4 mL/g-VS compared to 484.3 mL/g-VS for brown sludge. This significant difference reflects the higher organic content, particularly lipids, in DAF sludge, which is more conducive to methane generation (Logan et al. 2021). However, the high lipid content in DAF sludge could also introduce challenges, such as LCFA inhibition, during AD, requiring careful process optimization (Bhatt & Tao 2020; Logan et al. 2021; Tandukar & Pavlostathis 2022).

The HC treatment was found to increase consistency or viscosity. This may be attributed to the change in sludge structure with the HC treatment. HC treatment disintegrates solids and thereby may increase the viscosity. This is in agreement with the results reported by Wolny et al. (2008). Other studies also reported that HC and shear stress degrade the sludge structure, resulting in a reduction of particle size (Bandelin et al. 2018; Kim et al. 2020); smaller particles were likely to absorb moisture (Yao et al. 2022) and hence increase the sludge viscosity (Mancuso et al. 2017; Xu et al. 2019).

HC pretreatment was applied to brown and DAF sludge samples to enhance their degradation during AD, focusing on two critical parameters: the pressure drops across the HC device and the number of passes through the device. A pressure drop of 250 kPa was maintained, and the impact of 10, 20, 40, and 80 passes on biomethane yield was evaluated. The HC pretreatment significantly improved the substrate's solubility, thereby increasing the bioavailability of organic matter in the sludge for subsequent fermentation reactions. The treatment also effectively degraded solids and solubilized floating FOG components, ensuring better mixing of floating sludge and reducing flotation issues. This improved the AD process, particularly during hydrolysis and methanogenesis. This was reflected in increased sCOD and increased DD, as well as the physical appearance observed after the pretreatment. It demonstrated the HC's role in reducing particle size and enhancing sludge characteristics for improved digestion efficiency.

These findings align with other studies that have demonstrated the effectiveness of HC in improving sludge degradation. Yao et al. reported an increase in sCOD from 50 to 320 mg/L and a DD up to 22.98% after 240 min of HC treatment of waste-activated sludge using an orifice device with 20 holes of 2 mm diameter (Yao et al. 2022). Similarly, other research has shown DD increases of 12.7% with 20 passes using a rotational cavitation generator (Petkovšek et al. 2015), 10.1–26% using serrated disc rotational HC devices (Vilarroig et al. 2020), and 3.3–7.7% with pin-disc rotational generators (Repinc et al. 2022).

In comparison, this study employed a vortex-based HC device, which offers significant advantages over conventional cavitation devices such as orifice, venturi, or rotor-stator configurations. Vortex-based devices exhibit lower erosion, earlier inception of cavitation, and reduced pressure drops, which results in lower energy consumption while achieving effective pretreatment (Ranade et al. 2022). This makes them a highly efficient and scalable option for the pretreatment of dairy sludge, particularly for substrates like brown and DAF sludge, which demand careful optimization to maximize biomethane production.

Figure 4(b) shows the BMP along with BMP_th for HC-treated (80 passes) brown and DAF sludge alone and their co-digestion. When AD was conducted for brown sludge and DAF sludge individually at a 2% VS concentration, the achieved BMP corresponded to 73 and 84% of the BMP_th, respectively. However, co-digestion significantly improved methane yields, with BMP_th exceeding 95% when 1% brown sludge was combined with 1% DAF sludge. Even in the case of co-digesting 3% brown sludge with 1% DAF sludge, the BMPth reached 89%, which is a marked improvement compared to mono-digestion.

The observed reduction in the AD lag phase (Figure 4(a)) with increasing DAF sludge proportions suggests that co-digestion promotes faster microbial acclimatization. This is likely due to the enhanced solubilization of organic matter facilitated by HC pretreatment. The combination of reduced lag phase and higher methane yields underscores the potential of HC-enhanced co-digestion as an effective strategy for optimizing dairy sludge valorization.

Other studies align with these results, such as the co-digestion of concentrated FOG with primary sludge and thickened waste-activated sludge, which increased degradation by 10.9% (from 42.2 to 53.1%) with the addition of 18.5% FOG (Tandukar & Pavlostathis 2022). Another study incorporating waste cooking oil with pig slurry reported a methane yield of 811 mL/g-VS, signifying a 15.5% increase, and a shortened lag phase by 58.3% (Marchetti et al. 2019). These results collectively underscore the potential of co-digestion strategies to enhance methane production and process efficiency in AD systems. These findings demonstrate that the addition of DAF sludge to brown sludge not only amplifies the degradation process but also enhances the efficiency of methane production. The superior methane yields achieved in co-digestion, particularly with lower concentrations of brown sludge, indicate a more effective breakdown of organic matter and improved bioavailability of substrate components. The results suggest that incorporating DAF sludge into AD systems, even in small proportions, has the potential to optimize methane generation and improve the overall efficiency of the process.

Most conventional kinetic models for biochemical methane production are primarily based on first-order kinetics, with some incorporating modifications of the Gompertz model (Tjørve & Tjørve 2017; Zhong et al. 2021). However, to better capture the complex dynamics of cellular growth, a two-phase model of first-order and modified Gompertz equations was proposed by (Equation (2)) Islam & Ranade (2024). This model explains how initial-stage inhibition and substrate breakdown impede gas production in the first phase. Subsequently, there is an accelerated cumulative gas production in the second AD phase (Gomes et al. 2021). This acceleration is attributed to the substrate breaking down in the first phase, leading to a rise in the concentration of soluble materials, which in turn prompts acidogenic, acetogenic, and ultimately methanogenic bacteria. The modified Gompertz kinetic model developed by Zwietering et al. (1990) forecasts the exponential cumulative methane production.

The kinetic parameters obtained for all methane production reactions using various brown and DAF sludge concentrations are presented in Table 2. AD using 2% VS of brown sludge exhibited the shortest lag phase of 2.5 days, whereas, at the same concentration of DAF sludge, it was 17 days. In the case of co-digestion using a 1:1 ratio of brown and DAF sludge, the lag phase was 7.3 days, longer than brown sludge alone but shorter than that of DAF sludge alone. However, with a higher concentration, the lag phase increased significantly to 24 days when the concentration of brown and DAF sludge was 4% VS (3:1). Previous studies have also reported an increase in the lag phase with the concentration of DAF sludge (Islam & Ranade 2024). The findings demonstrate that DAF sludge inhibited methanogens initially, resulting in an increased adaptation time for these microorganisms as the concentration increased.

Due to the highest lag phase for DAF sludge alone, methane production was lowest at 262 mL/g VS in the first phase with 2% VS, whereas brown sludge alone produced more methane in the first phase due to its very low lag phase. When DAF sludge was added to brown sludge at a 1:1 ratio and the total VS was 2%, methane production was highest at 364 mL/g VS, slightly increasing in the lag phase to 7.3 days. However, when the mixed sludge concentration was increased to 4% VS, the lag phase increased even more than with DAF sludge alone, resulting in a decrease in methane production in the first phase to 325 mL/g VS. After passing the inhibition stage in the first phase, methane production increased exponentially with the increase of DAF sludge concentration in the second stage. Methane production ranged from 41 mL/g VS for brown sludge alone to 525 mL CH₄/g VS for DAF sludge alone, with intermediate values for brown-to-DAF sludge ratios of 3:1 and 1:1. Maximum methane production rates were observed to be 15 mL CH₄/g VS/day for brown sludge, the lowest among the tested samples, while the highest rate of 39 mL CH₄/g VS/day was recorded for DAF sludge alone. When DAF sludge was added to brown sludge, the methane production rate increased, reaching 19 and 24 mL CH₄/g VS/day for brown and DAF sludge ratios of 3:1 and 1:1, respectively.

Assessing the techno-economic viability of utilizing HC treatment for biomethane production using different proportions of brown and DAF sludge is essential. This evaluation encompasses key economic factors such as energy consumption, biomethane yield enhancement, and comparison with alternative techniques. The energy requirements in HC treatment primarily relate to sludge pumping through the cavitation device, which is quantified through Equation (3).

The HC pretreatment improved the biodegradability of sludge, resulting in a boosted biomethane output. Equation (4) calculates the energy increased from this enhanced biomethane generation.

Table 3 compares techno-economic values resulting from co-digestion of pretreated brown and DAF sludge at varying proportions. The pretreatment pressure drop (ΔP) is set at 250 kPa with 80 passes, while the pump efficiency (η) is 70%. The densities of brown and DAF sludge are 897 and 981 kg/m³, respectively, with VS concentrations of 0.036 and 0.05 ton/ton of sludge used for HC treatment. Methane yields of untreated sludge were 288 and 551 m³/ton sludge (Islam & Ranade 2023, 2024) and the heat of combustion of methane (ΔH) is noted as 10 kWh/m³.

Table 3 also illustrates the notable increase in energy yields resulting from digestion, thereby leading to an increased net energy gain. HC treatment of brown sludge amounted to a net energy gain of 78 kWh/ton of sludge, whereas DAF sludge surged to 353 kWh/ton. Prior research reported energy gains of 38 and 103 kWh per ton from brown and DAF sludge, respectively, with VS concentrations of 3.6 and 5.0% (Islam & Ranade 2023,2024). The highest net energy gain was achieved in co-digestion using HC-treated brown and DAF sludge at the ratio of 1:1 as VS, which was 423 kWh/ton. Net energy gain was 251 kWh/ton for the AD of 3:1 brown and DAF sludge ratio. The research indicates that the energy consumption associated with HC treatment is notably lower compared to reported figures for alternative techniques used in analogous contexts, such as 4.4 − 35.6 kWh/ton sludge was required for the sludge disintegration using swirling jet HC treatment (Ferrentino & Andreottola 2020), suggesting potential cost savings. Furthermore, recent research reported energy requirements ranging from 20 to 440 kWh per ton TS, with energy gains ranging from 2,550 to 2,890 kWh per ton TS, utilizing rotor-stator-based HC treatment of activated granular sludge for AD (Zieliński et al. 2024). A more comprehensive assessment through the expansion of the techno-economic analysis to incorporate factors such as initial capital investment, ongoing operational costs, and potential revenue streams could provide valuable insights. These findings underscore the potential of HC pretreatment followed by biomethane generation to enhance the valorisation of dairy sludge.

The co-digestion of brown sludge with DAF sludge resulted in increased methane production and improved destruction of sludge VS compared to digesting each sludge alone. Maximum methane yield was observed at a brown and DAF sludge ratio of 50:50 (totalling 2% VS). However, the enhanced methane production and VS destruction decreased when the brown and DAF sludge ratio shifted to 75:25 (totalling 4% VS). Techno-economic calculation shows the highest net energy gain was more than 422 kWh/ton of sludge using HC-treated brown and DAF sludge with 80 passes at the ratio of 50:50. These findings underscore the transformative potential of HC treatment and co-digestion strategies for improving methane production efficiency in AD systems. Future long-term studies are warranted to validate the sustainability and reliability of these enhancements.

This work has been supported by the Dairy Processing Technology Centre funded through Enterprise Ireland. Grant Agreement number: TC 2020 0028.

All relevant data are included in the paper or its Supplementary Information.

The authors declare there is no conflict.