Next Article in Journal
Survey of School Direct-Drinking Water Access for Children and Youth in Shanghai, China
Next Article in Special Issue
Multi-Criteria Decision Making: Sustainable Water Desalination
Previous Article in Journal
Comparing UAV-Based Hyperspectral and Satellite-Based Multispectral Data for Soil Moisture Estimation Using Machine Learning
Previous Article in Special Issue
Ultrafiltration of Car Wash Wastewater: Pilot-Scale Studies
 
 
Search for Articles:
Title / Keyword
Author / Affiliation / Email
Journal
Article Type
 
 
Advanced Search
 
Section
Special Issue
Volume
Issue
Number
Page
 
Journals
Water
Volume 17
Issue 11
10.3390/w17111716
water-logo
Submit to this Journal Review for this Journal Propose a Special Issue
► Article Menu

Article Menu

share Share announcement Help format_quote Cite question_answer Discuss in SciProfiles
first_page
settings
Order Article Reprints
Font Type:
Arial Georgia Verdana
Font Size:
Aa Aa Aa
Line Spacing:
Column Width:
Background:
Article

Dark Fermentation of Sizing Process Waste: A Sustainable Solution for Hydrogen Production and Industrial Waste Management

by
Marlena Domińska
1,*,
Martyna Gloc
1,2,
Magdalena Olak-Kucharczyk
2 and
Katarzyna Paździor
1
1
Department of Bioprocess Engineering, Faculty of Process and Environmental Engineering, Lodz University of Technology, 213 Wolczanska Street, 90-924 Lodz, Poland
2
Lukasiewicz Research Network-Lodz Institute of Technology, 19/27 Marii Sklodowskiej-Curie Street, 90-570 Lodz, Poland
*
Author to whom correspondence should be addressed.
Water 2025, 17(11), 1716; https://doi.org/10.3390/w17111716
Submission received: 7 April 2025 / Revised: 21 May 2025 / Accepted: 29 May 2025 / Published: 5 June 2025
(This article belongs to the Special Issue Novel Methods in Wastewater and Stormwater Treatment)
Browse Figures
Review Reports Versions Notes

Abstract

The possibility of hydrogen (H2) production from sizing waste, specifically starch-based substrates, was investigated through dark fermentation. Modified starch substrates produced less (up to 54% without heating and 18% after heating) H2 than natural ones. However, heating modified starch samples led to 18% higher H2 production than unheated ones, suggesting that high temperatures activate more favorable metabolic pathways. The highest H2 production (215 mL/gTVS_substrate) was observed with unheated natural starch, where the classic butyric–acetic fermentation pathway predominated. This variant also generated the highest CO2 levels (250 mL/gTVS_substrate), confirming the correlation between H2 and CO2 production in these pathways. Modified starch substrates shifted fermentation towards fatty acid chain elongation, reducing CO2 production. The proportion of CO2 in the fermentation gases correlated strongly with H2 production across all variants. A decrease in total volatile solids (TVS) indicated effective organic matter conversion, while varying dissolved organic carbon (DOC) levels suggested different degradation rates. Nitrogen analysis (TN) revealed that the differences between variants were due to varying nitrogen processing mechanisms by microorganisms. These results highlight the potential of sizing waste as a substrate for bioH2 production and offer insights for optimizing the process and developing industrial technologies for bioH2 and other valuable products.

1. Introduction

For years, a global increase in the world’s population has been observed, bringing a range of consequences, including increased demand for Earth’s resources and environmental degradation [1,2]. Energy, water, and food are among the basic necessities of human life [3]. The constantly growing population requires more food, drinking water, and services, which leads to a greater demand for energy and other resources [1,3,4]. As a result of this process, climate change and decreasing freshwater resources have become some of the major challenges in environmental protection [5].
One aspect of climate change is global warming, which refers to the long-term increase in average temperatures on Earth. The main cause of global warming is the rise in the concentration of greenhouse gases in the environment, such as carbon dioxide (CO2), methane (CH4), nitrous oxide (N2O), and fluorinated greenhouse gases. The largest source of emissions of these gases is the burning of fossil fuels, such as coal, oil, and natural gas, which are widely used in energy production, transportation, and industry [6,7,8]. To mitigate the phenomenon of climate change and its effects, including water scarcity and the amount of greenhouse gases generated, decisive actions must be taken to reduce emissions, treat water and wastewater, and protect the environment. A solution may include, among others, the development of better management of water resources and other raw materials, the creation of innovative wastewater treatment technologies, energy transformation, and counteracting climate change.
In the context of technological solutions for energy transformation, the production of H2, especially, which is produced as a result of biological processes, including dark fermentation (DF), is becoming increasingly important. In DF, anaerobic bacteria such as Clostridium and other microorganisms convert organic substances into H2, carbon dioxide, and other byproducts. This process occurs in conditions where there is no oxygen and light, and energy is obtained by decomposing organic substances [9,10]. In this case, H2 production is the result of the metabolism of microorganisms, which, using enzymes such as hydrogenases, catalyze the reactions of decomposition of organic compounds and the release of H2 [11]. The process of dark fermentation is highly sensitive to environmental conditions that can significantly influence the efficiency of hydrogen production. Typically, the optimal temperature range for dark fermentation is between 30 °C and 40 °C, as this range supports the growth and activity of the microorganisms involved. If the temperature falls outside of this range, microbial activity can decrease, leading to lower yields of hydrogen gas. The pH is also a crucial factor; dark fermentation usually occurs under slightly acidic conditions, with a pH between 5.5 and 7.0 being ideal. Maintaining this pH range ensures optimal enzymatic activity and metabolic efficiency. In addition to temperature and pH, other factors like nutrient availability, the concentration of carbon sources, and the ionic strength of the medium can all impact the rate of hydrogen production during dark fermentation. Thus, precise control of these conditions is essential for achieving high yields and stability in the process [12,13,14]. As a result of these processes, other byproducts are also created, such as organic acids or CO2, which can be used in various industries [15,16]. The CO2 captured during the process can be utilized to produce valuable materials, such as carbonates, which have potential applications in construction. These materials could be used in concrete production or as part of the building materials industry, offering an innovative way to recycle CO2 and contribute to sustainable development [17]. Organic acids can be used in the biological removal of phosphorus and nitrogen from wastewater, as well as to produce biogas, electricity, hydrogen, polyhydroxyalkanoates (PHAs), and lipids for biodiesel production [18]. Although fermentation has been known for centuries, its use in H2 production is gaining importance as it offers an eco-friendly approach to energy generation. One of the main advantages of DF is its environmental sustainability. This process can be carried out using organic waste, such as plant residues, food waste, or biomass. As a result, fermentation can support a circular economy by aiding in the recycling of organic materials and the production of valuable products like H2 [19,20]. H2 produced through this process is particularly valued for its use as a clean fuel, which can be utilized across various industries and the energy sector. However, despite its numerous advantages, DF also has its limitations. The H2 production in this process is not yet sufficiently efficient. Additionally, fermentation is still in the phase of intensive research, and the technologies associated with scaling it up or getting rid of the CO2 produced in the process have not yet been fully developed, which requires further investments and improvements in existing methods [21]. Nevertheless, DF remains a promising method for H2 production, especially in the context of utilizing organic waste and supporting sustainable development.
Literature reports indicate that the possibility of using industrial wastewater as a feedstock for H2 production has also been explored, utilizing methods such as electrolysis or DF technologies [22,23,24,25,26]. H2 production from wastewater is a new and highly intriguing direction that is gaining popularity [23,27]. In recent years, studies have been conducted on the production of bioH2 through DF using industrial wastewater from various economic sectors, including treated textile wastewater, food industry wastewater, lactate wastewater, distillery wastewater, starch factory wastewater, and swine wastewater [22,25,28,29,30,31,32,33].
One of the key criteria for selecting a substrate is its availability, carbohydrate content, biodegradability, and cost. Therefore, wastewater can be an excellent material for H2 production [25]. One possible approach is the use of wastewater containing starch. Starch, in addition to simple sugars such as glucose, is one of the most commonly used raw materials in DF processes because it is a polysaccharide with a high carbohydrate content that microorganisms can easily break down under anaerobic conditions. The main reason why starch is an effective substrate in this process is its high carbohydrate content, which is rapidly converted into simpler sugars like glucose. These sugars are then utilized by microorganisms during fermentation, leading to the production of H2 and other byproducts. Additionally, starch is a natural, biodegradable organic compound that is easily broken down by various anaerobic microorganisms. This is particularly important in biotechnological processes such as anaerobic fermentation, where microorganisms like Clostridium or Bacillus can break down starch into simpler molecules. These molecules are then metabolized, leading to H2 production, which can be used as a clean energy source [34,35]. Starch can be obtained directly from plants, and this starch is referred to as natural starch. In its original form, it has limited practical properties [36]. Therefore, it is often necessary to alter its properties through chemical, physical, or biological transformation. This type of starch is called modified starch [37,38]. Due to its wide range of potential applications, the global demand for this substrate continues to rise [39,40]. Therefore, research is constantly being carried out into new possibilities for obtaining starch and its modification [41]. Both natural and modified starch are used in many industries, including food, pharmaceutical, paper, cosmetics, and textile industries [39,40,42,43]. Starch is the primary source of energy in the human diet, which makes it an essential ingredient in many staple foods [44]. In the food industry, it is used, among others, in the production of ice cream, jams, candies, sauces, and meat products [45]. In the pharmaceutical industry, it is used, among others, to encapsulate active ingredients such as drugs, probiotics, vitamins, or lipids [42,46]. Starch is also used in the production of adhesives, aerogels, foils, and bioplastics [45].
In the textile industry, it has found its application in many processes improving the quality and appearance of the product. One of the key textile processes in which starch plays an important role is the process of sizing the warp [47]. This process involves applying a layer of starch to the warp. This action is intended to provide it with temporary protection during weaving. The process of applying the layer is not complicated. The yarns are wound on a shaft and then immersed in a tank containing the sizing agent. Then they are transported to the wringing shafts, where the sizing agent is pressed into the threads and its excess is removed. Then the yarns are dried and wound on the warp shaft. At the end of the process, the entire equipment (sizing machine) is washed, which generates wastewater containing unused sizing [48]. This wastewater, rich in organic matter and starch residues, can have significant environmental impacts. The high levels of Biological Oxygen Demand (BOD) and Chemical Oxygen Demand (COD) in the wastewater indicate that it consumes a large amount of oxygen in the water as microorganisms break down the organic materials. This can lead to hypoxic conditions in receiving water bodies, harming aquatic ecosystems. Furthermore, the residual starch and other chemicals can contribute to eutrophication, causing excessive algae growth and further depleting oxygen levels, ultimately damaging water quality and aquatic life [49,50]. To mitigate these environmental impacts, textile manufacturers employ a range of wastewater treatment technologies. Primary treatments such as filtration and sedimentation remove larger particles, while secondary treatments (like activated sludge systems) use microorganisms to break down organic materials. Advanced treatments, including membrane filtration, ozonation, and coagulation–flocculation, can further remove pollutants. Additionally, many companies are focusing on water recycling within the plant to minimize wastewater discharge [51,52]. As for alternatives to starch, several sizing agents with potential environmental benefits are available; however, their overall sustainability depends on multiple factors including biodegradability, production processes, and environmental impact throughout their life cycle. For example, biodegradable sizing agents derived from cellulose, such as carboxymethyl cellulose (CMC), or protein-based agents from soy and wheat gluten, are renewable and generally more environmentally friendly, although their production may require significant resources. Enzyme-based treatments are emerging as a promising solution due to reduced chemical use and wastewater generation. Natural polysaccharides like guar gum and chitosan also represent sustainable alternatives. Further detailed analysis of these options is needed to fully assess their environmental benefits compared to starch. By adopting such alternatives and improving wastewater treatment and recycling, the textile industry can reduce its environmental footprint and move toward more sustainable production practices [53,54,55].
Currently, there is an increasing focus on improving wastewater treatment processes, creating closed-loop systems, and designing new, more efficient technologies [56]. Wastewater generated in the sizing process in the textile industry is an example of industrial waste that is often not properly managed, meaning it is frequently neither pretreated nor adequately treated before discharge or is stored and handled in ways that pose environmental risks [57,58]. However, they can become a valuable resource for H2 production through biotechnological processes. The high carbohydrate content, such as starch, makes these wastewaters suitable for DF. H2 production from textile waste can be an eco-friendly solution that not only enables the effective use of these wastes but also contributes to the generation of renewable energy sources. The application of biotechnology in wastewater treatment from the sizing process can therefore offer numerous benefits, such as waste volume reduction and the production of clean energy sources. Anaerobic fermentation can also reduce the negative environmental impact of the textile industry by eliminating toxic chemicals found in the wastewater and transforming them into useful products. This approach aligns with the idea of a circular economy, where waste is reused, and industrial processes become more sustainable. As discussed in the study by Biyada and Urbonavičius (2025) [59], textile waste—especially from natural fibers such as cotton or wool—can be biologically treated using microorganisms and enzymes, turning it into biogas, organic acids, or biofertilizers. The article emphasizes that biological means like anaerobic digestion not only help reduce the harmful effects of conventional waste management methods such as landfilling or incineration but also create added value from discarded materials. Integrating such processes into the textile sector contributes to closing material loops and reducing the environmental footprint of fashion production [60]. Furthermore, the H2 obtained through fermentation can be used as a source of clean energy in various industries, contributing to CO2 emission reduction and supporting the energy transition towards renewable energy sources.
The aim of this study was to produce H2 from industrial textile wastewater originating from the warp sizing process. During this experiment, the impact of using different types of starch during the sizing process on the production of bioH2 was analyzed. Additionally, the effect of thermal treatment of the wastewater before the DF process was also determined, as it may significantly affect the substrate properties, particularly in terms of the starch distribution in the waste. Starch, as a polysaccharide made of long chains of glucose, undergoes a gelatinization process under high temperatures. During this process, the bonds between glucose molecules are weakened, leading to the breakdown of the starch structure and its conversion into more accessible forms—primarily dextrins and glucose. This treatment significantly increases the bioavailability of starch for microorganisms involved in the anaerobic fermentation process. The breakdown of starch into simpler sugars facilitates their metabolism by microorganisms, contributing to more efficient H2 production and other products such as organic acids and methane. Thermal treatment can also help eliminate some contaminants and pathogens present in the wastewater, further improving the safety and efficiency of the fermentation process.

2. Materials and Methods

2.1. Inoculum and Substrate

The inoculum was a pre-fermented sludge from the Wastewater Treatment Plant (WWTP) in Lodz, Poland (Table 1). Before beginning the DF process, the sludge was thermally pretreated—heated to 70 °C for 30 min. This thermal pretreatment was necessary to eliminate microorganisms responsible for methane production, to enhance the required microbiological activity, and to improve the overall efficiency of the fermentation process, as described in previous studies [61], which also utilized similar methods for sample preparation and experimental conditions.
The industrial wastewater used as a substrate in the DF process came from the Experimental Production of the Łukasiewicz Research Network—Lodz Institute of Technology, Lodz, Poland (Ł-ŁIT). The Ł-ŁIT production process includes, among others, the matrix sizing process, during which wastewater containing various types of starch is generated (Table 1).

2.2. Experimental Setup

The process was carried out for 48 h in mesophilic conditions at a temperature of 37 °C in batch mode. Glass bioreactors with a volume of 0.5 L were used for the experiments, with a working volume of 400 mL. For each experiment, 300 mL of starch-based hydrolysate (native or modified, heated or unheated) was mixed with 200 mL of inoculum, prepared from a previously preheated microbial culture. From this 500 mL mixture, 100 mL was withdrawn for other parallel analyses, leaving the intended 400 mL working volume in the reactor.
The inoculum and substrate were mixed immediately before the start of fermentation to ensure homogeneity and consistent conditions across all replicates. The substrate load was determined based on previous optimization studies using kitchen waste. Specifically, the dry matter content of the starch solution was matched to the dry matter content of kitchen waste from earlier experiments, under conditions that had yielded the highest hydrogen production. This approach ensured that the organic load was comparable to the most efficient previous trials, allowing for meaningful comparisons and consistency in microbial activity [62].
The bioreactors were placed in a thermostatic shaker, the New Brunswick Scientific Excella E24 Incubator Shaker Series, Eppendorf, St. Albans, UK, ensuring constant temperature and continuous mixing at 140 rpm. The use of the shaker was essential to maintain uniform conditions and efficient interaction between the substrates and microorganisms, as well as to maintain a constant process temperature. Each bioreactor was equipped with a cap featuring two outlets:
-
I connected to a tube with a partition, which allowed for gas sampling;
-
II connected to a tube that linked the reactors to bottles containing saline solution, used for measuring the volume of gas produced during the process. This volume was measured using the displacement method.
The experiments were conducted over a period of 48 h. Although hydrogen production was observed mainly during the first 24 h, the extended duration was necessary to ensure the process had fully ceased and no further gas generation occurred, thereby improving the accuracy and completeness of the measurements.
A total of three replicates were analyzed for each experimental variant, including both heated and unheated starch samples, in their native and modified forms, resulting in 12 experimental setups. Each variant was tested under identical conditions to ensure statistical significance and repeatability of the results.
Statistical processing was performed on the full set of experimental data points obtained from these 12 replicates. This includes all recorded hydrogen volumes and calculated production rates, which were used to assess significant differences between the tested conditions.

2.3. Analysis Procedures

Samples of the DF were taken from the bioreactor before and after the fermentation process. To separate the samples into solid and liquid phases, an MPW-250 centrifuge from MPW Med-Instruments, Warsaw, Poland, was used, operating at a speed of 5000 rpm for five minutes.
For the reaction mixture, pH, total solids (TS), and total volatile solids (TVS) were measured. The results for total solids and total volatile solids were analyzed using the gravimetric method [62]. The pH of the mixture was measured using the WTW pH 540 GLP electrode, WTW GmbH, Weilheim, Germany.
For the liquid fraction, dissolved organic carbon (DOC), total nitrogen (TN), and volatile fatty acids (VFAs) were measured. DOC and TN concentrations were determined using an IL 550 TOC-TN analyzer, Hach Lange GmbH, Düsseldorf, Germany.
The quantity and composition of the VFAs produced were analyzed using a VARIAN CP4800 gas chromatograph, Varian Inc., Palo Alto, CA, USA. This chromatograph is equipped with a BP21 capillary column, 25 m in length, 0.25 mm in diameter, and a film thickness of 0.25 μm. Prior to analysis, the liquid samples were filtered through a 0.2 μm membrane and acidified with formic acid. The helium flow rate was calibrated to 1.4 mL/min, and the flame ionization detector (FID) was set to a temperature of 250 °C. A split ratio of 1:100 was used during analysis, with a 1 μL injection volume. The capillary column was preheated to 110 °C and maintained for one minute, after which the temperature was gradually increased by 10 °C per minute until it reached 230 °C, where it was held for an additional two minutes. These analytical methods, including the use of the IL 550 TOC-TN analyzer, Hach Lange GmbH, Düsseldorf, Germany for DOC and TN measurements, as well as the VARIAN CP4800 gas chromatograph, Varian Inc., Palo Alto, CA, USA for VFA analysis, are consistent with those described in the study by Trancone et al. [60]. The precise methodologies outlined in this reference serve to validate the reliability and accuracy of these techniques in similar experimental setups, ensuring robust results for the analysis of fermentation products [60].
The volume of gas produced during the DF process was determined using the displacement method. Its composition was analyzed using an 8610C gas chromatograph (SRI Instruments), measuring hydrogen (H2), methane (CH4), and carbon dioxide (CO2). The chromatograph was equipped with two columns: one filled with only silica gel (1 m in length, 1/8″ restrictive, 80/100 mesh) and the other filled with molecular sieves (1 m in length, 1/8″ restrictive, 80/100 mesh). The chromatograph had a thermal conductivity detector (TCD). Helium was used as the carrier gas, with a flow rate of 8 mL/min, at a controlled temperature of 60 °C, and the TCD detector was maintained at 150 °C. The volume of the sample analyzed was 0.25 mL. To ensure accuracy, the analysis was performed three times, and the results were averaged.

3. Results and Discussion

3.1. pH of the Process Environment

In all samples, a decrease in pH is observed (Figure 1), which is characteristic of DF. The acidic environment at the end of the process may result from the accumulation of VFAs, such as acetic or butyric acid, which are the main acids produced in this process [14]. The pH dropped to the lowest value in the sample with the modified, unheated starch (down to 4.97), which may suggest the most intense production of fermentation acids. The decrease in pH to below 5.0 may inhibit further fermentation, which is important for process optimization [13]. The stronger acidification in the modified samples suggests that they were more active in terms of fermentation.

3.2. Degradation of Organic Substances

In DF, microorganisms break down complex organic substances (TV, TVS) into simpler compounds, leading to a decrease in their content [63]. In Figure 2, changes in TVS are observed, while Figure 3 shows changes in DOC during the DF process. The largest decrease in TVS was observed in the sample with natural, unheated starch, which may indicate more intensive substrate utilization by fermentative microorganisms. The decrease in DOC in this sample also confirms greater substrate utilization. On the other hand, DOC for the other variants did not show a clear downward trend and remained at a similar level. This may suggest transformations of organic compounds that, instead of being degraded, transitioned into more stable forms. The decrease in TVS indicates that the organic material was effectively converted into fermentation products, but the lack of changes in DOC suggests that the hydrolyzed organic matter from the solid phase was primarily converted into carbon dioxide, rather than being further transformed into other forms of organic carbon [64]. During dark fermentation, complex organic compounds (such as proteins, lipids, and non-starch polysaccharides) undergo anaerobic digestion. Some of the organic matter is converted into gases (e.g., hydrogen and methane), while the remaining portion may form more resistant, stable organic compounds, such as humic substances or high molecular weight compounds. These compounds can be difficult to degrade and are not easily detected by standard DOC assays, which typically measure low molecular weight and soluble organic carbon. Therefore, even though TVS (which reflects total organic matter) may decrease, DOC levels may remain stable or change only slightly, as soluble carbon is transformed into forms that are not detectable by standard DOC tests [65,66,67].

3.3. Stability of Total Nitrogen

Organic and ammonium nitrogen can influence the activity of fermentative bacteria. In the conducted experiments, total nitrogen (TN) remains relatively stable, as shown in Figure 4, suggesting that the degradation processes of proteins and amino acids were not the dominant mechanism, and no excessive accumulation of ammonia occurred, which, at high concentrations, can be toxic to fermentative bacteria. The variants with modified starch initially had a higher TN level than the samples with natural starch, which may result from the introduction of additional nitrogen components during the modification [63]. The largest decrease was recorded for the variant with modified, unheated starch, which suggests intensive nitrogen utilization by microorganisms in metabolic processes. The increase in TN in the sample with natural, heated starch may result from the release of nitrogen from decomposing organic compounds or from reduced microbial activity [68].

3.4. Volatile Fatty Acids

Figure 5 shows the quantity and composition of the produced VFAs. The highest production of VFAs occurred in the variant with modified, unheated starch (9.43 g/Lmixture), followed by modified, heated starch. In the variants with natural starch, the production of VFAs was noticeably lower by as much as 38% in the case of unheated variants. This suggests that the use of modified starch promoted VFA production. Heating worsened the production, but the modified sample still produced more VFAs than the natural starch samples.
Acetic acid was produced in the highest amount in the variant with natural, unheated starch (32.05%), with slightly lower production in the other variants, though the differences were small—around 2%. Starch modification and heating of the substrate had little impact on the proportion of acetic acid.
In the variant with natural, heated starch, the highest amount of propionic acid was produced (0.95%), while the lowest amount was found in the variant with modified, unheated starch. However, its quantity was small.
Butyric acid was the dominant acid in all variants (over 65%). The proportion of butyric acid in the VFAs was similar across all variants. The dominance of butyric acid across all variants suggests that the fermentation environment—regardless of the starch type—favored microorganisms specialized in its production, such as Clostridium butyricum or other butyrate-producing bacteria. Modified starch may have increased the overall availability of more easily fermentable carbohydrates, thereby enhancing total VFA production. However, the relative proportions of individual fatty acids are largely determined by the composition of the microbial community, the pH and redox conditions of the environment, and the metabolic pathways prevalent among the dominant bacteria. As a result, the relative share of butyric acid remained stable [69,70,71].
In the case of isobutyric acid, trace amounts were only found in the sample with modified, unheated starch. Trace amounts of isobutyric acid—a byproduct of valine fermentation, a branched-chain amino acid—may indicate the presence of specific bacteria capable of valine deamination, such as Peptostreptococcus or Clostridium species, or the activation of alternative metabolic pathways that require a specific combination of substrates and enzymatic conditions. Heating could have denatured the enzymes responsible for these pathways, eliminated heat-sensitive microorganisms present only in the unheated state, or altered the structure of the modified starch (e.g., through gelatinization), making it less favorable for bacteria involved in this pathway. Therefore, the detection of isobutyric acid exclusively in the unheated, modified starch variant suggests that the activation of this specific fermentation route depends on both the physical characteristics of the substrate and the preservation of the native microbial community [70,71].
The proportion of isovaleric acid was noticeably higher in the samples with natural starch (0.36–0.52% for modified starch and 1.12–1.31% for natural starch). On the other hand, valeric acid was not detected in the tested samples.
The samples with modified starch had significantly more caproic acid than those with natural starch (0.10–0.95%). Caproic and isovaleric acids are often products of amino acid fermentation rather than purely carbohydrate-driven pathways. Their increase in the presence of modified starch may indicate stimulation of proteolytic bacteria that degrade proteins or peptides—potentially due to greater energy availability from carbohydrates, which indirectly supports their growth. It is also possible that modified starch affects the biofilm or physicochemical structure of the environment in a way that facilitates protein fermentation. In other words, modified starch may have influenced amino acid-fermenting microorganisms not directly but indirectly, leading to higher production of these specific acids [72,73].
Different amounts of trace acids (such as isobutyric or caproic acid) may suggest a different metabolic pathway in the fermentation process when using natural starch substrate compared to modified starch. For example, the higher content of caproic acid may indicate that in these variants, processes of fatty acid chain elongation (caproic fermentation) occurred, suggesting a change in the dominant metabolic pathways. On the other hand, the lower content of isovaleric acid may mean that pathways associated with amino acid fermentation were less active. However, the lack of significant changes in the proportions of butyric and acetic acids suggests that the main fermentation pathway still relied on typical butyric fermentation, but in the modified starch samples, additional reactions may have occurred that influenced the composition of the VFAs [14,28,74].

3.5. Hydrogen and Carbon Dioxide

The production of H2 and CO2 is directly related to the metabolic pathways dominant in the fermentation process [28]. Data analysis reveals differences between variants with natural and modified starch, suggesting changes in microorganism activity and fermentation metabolism (Figure 6). The main pathways generating H2 are butyric and acetic acid fermentation, with butyric acid being more favorable for H2 production. In the above experiment, butyric acid was the dominant acid, indicating that conditions favored the activity of Clostridium bacteria [75]. The modified samples had a higher proportion of caproic acid, suggesting alternative processes that may compete for available electrons and reduce H2 production. Increased production of caproic acid in the modified starch variants indicates a shift in the electron flow towards fatty acid chain elongation rather than hydrogen production. In this process, electrons that could be released as H2 (e.g., through the decarboxylation of pyruvate to acetyl-CoA and hydrogen) are instead used to reduce intermediates such as acetate and butyrate towards caproate. Chain elongation utilizes NADH/FADH2 as reductants. More electrons are directed towards the formation of more reduced products (e.g., caproic acid), limiting the pool of electrons available for H2 production. This shift in electron allocation is often driven by the presence of appropriate electron donors (e.g., ethanol and lactate), which support chain elongation [76,77,78]. The lower proportion of propionic acid in the modified starch variants suggests fewer competing processes (propionic fermentation), which consume H2, potentially positively influencing H2 production efficiency [13,28].
DF using modified starch as a substrate generates lower amounts of H2 compared to variants based on natural starch. However, heating the samples with modified starch positively influenced H2 production, which was higher than in unheated samples. This may indicate the activation of more efficient metabolic pathways due to the high temperature. Thermal activation of enzymes, such as amylases, increases the rate of starch hydrolysis, which enhances the availability of easily fermentable sugars like glucose and maltose. This, in turn, intensifies bacterial metabolism and promotes hydrogen production. On the other hand, changes in the microbial community structure, such as the thermal selection of microorganisms tolerant to higher temperatures (e.g., certain Clostridium species), can shift the dominant metabolic pathway, potentially favoring hydrogen production over chain elongation. In the short term, enzymatic activation is typically the dominant factor, while with prolonged exposure to heat, changes in the microbiome may have a greater impact on the process [35,78,79,80]. The highest amount of H2 was obtained from unheated natural starch, suggesting that under these conditions, the traditional butyric–acetic fermentation mechanism dominated. Studies indicate that starch modification, especially through processes like enzymatic modification, can alter its structural availability, thus affecting the efficiency of fermentation, including H2 production. Results, which show lower H2 production from modified starch, are consistent with the theory that starch modification can introduce structural changes that limit the availability of substances for complete fermentation, leading to lower H2 production [81,82,83].
CO2 is a natural byproduct of anaerobic fermentation, particularly in acetic and butyric pathways. High H2 production is typically accompanied by high CO2 production, indicating that processes generating both gases were occurring intensively [13]. In the variants with a higher proportion of caproic fermentation (modified starch), CO2 production was lower because fatty acid chain elongation does not generate CO2 to the same extent as butyric fermentation. The highest CO2 production was observed in the unheated substrates, similar to H2 production, confirming that CO2 production was correlated with H2 production.

4. Conclusions

The use of modified starch as a substrate for dark fermentation results in lower H2 production efficiency compared to using natural starch. However, in the heated variant, modified starch showed slightly higher H2 production than the unheated sample, suggesting that high temperature may have activated more favorable fermentation pathways in this sample. The highest H2 production (214.89 mL H2 per gram TVS of substrate) was observed in the unheated natural starch, indicating that under natural conditions and without heating, the most classical butyric–acetic fermentation dominated. In this variant, the highest CO2 production was also recorded, which aligns with the correlation between H2 and CO2 production in acetic–butyric pathways. The use of modified starch shifted the fermentation process toward fatty acid chain elongation. The proportion of CO2 in the fermentation gases was strongly correlated with H2 production in all variants. The decrease in TVS indicates that organic matter was effectively converted. However, the fact that DOC did not decrease uniformly suggests that the rate of organic substance breakdown varied. Based on the TN analysis, the observed differences between variants may result from distinct nitrogen transformation pathways employed by microorganisms; however, to confirm this, a more detailed analysis of nitrogen species is necessary. Future studies should also include microbiological analyses to better understand the underlying biological mechanisms.
The obtained results can be used for further optimization of the process and the development of industrial technologies that use this mechanism for the production of bioH2 and other valuable products.

Author Contributions

Conceptualization, M.D. and M.G.; methodology, M.D. and M.G.; validation, M.O.-K. and K.P.; formal analysis, M.O.-K. and K.P.; investigation, M.D. and M.G.; resources, M.O.-K. and K.P.; data curation, M.D.; writing—original draft preparation, M.D. and M.G.; writing—review and editing, M.O.-K. and K.P.; visualization, M.D.; supervision, K.P.; project administration, M.D. and M.O.-K.; funding acquisition, M.D. and M.O.-K. All authors have read and agreed to the published version of the manuscript.

Funding

This research received no external funding.

Data Availability Statement

The data that support the findings of this study are available from the corresponding author upon reasonable request.

Acknowledgments

The authors gratefully acknowledge the Group Wastewater Treatment Plant in Lodz (Poland) for providing the research material. This work was completed while the first and second authors were Doctoral Candidates in the Interdisciplinary Doctoral School at the Lodz University of Technology, Poland.

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.

References

  1. Schneider, U.A.; Havlík, P.; Schmid, E.; Valin, H.; Mosnier, A.; Obersteiner, M.; Böttcher, H.; Skalský, R.; Balkovič, J.; Sauer, T.; et al. Impacts of Population Growth, Economic Development, and Technical Change on Global Food Production and Consumption. Agric. Syst. 2011, 104, 204–215. [Google Scholar] [CrossRef]
  2. Harte, J. Human Population as a Dynamic Factor in Environmental Degradation. Popul. Environ. 2007, 28, 223–236. [Google Scholar] [CrossRef]
  3. Raj Kandel, D.; Kwak, D.; Lee, S.; Jie Lim, Y.; Subedi, S.; Lee, J. Harnessing Natural Antifouling Agents for Enhancing Water and Wastewater Treatment Membranes. Sep. Purif. Technol. 2025, 359, 130254. [Google Scholar] [CrossRef]
  4. Pimentel, D.; Pimentel, M. Global Environmental Resources versus World Population Growth. Ecol. Econ. 2006, 59, 195–198. [Google Scholar] [CrossRef]
  5. United Nations. Transforming Our World: The 2030 Agenda for Sustainable Development; United Nations: New York, NY, USA, 2015. [Google Scholar]
  6. Borkowski, A. Akademia Marynarki Wojennej w Gdyni. Przyczyny I Skutki Globalnego Ocieplenia Klimatu. 2021. Available online: https://nawigacja.gdynia.pl/wp-content/uploads/2021/03/PRZYCZYNY-I-SKUTKI-GLOBALNEGO-OCIEPLENIA-KLIMATU.pdf (accessed on 27 January 2025).
  7. Malucha, M. Przyczyny Zmian Klimatu. Próba Eksplikacji Głównych Problemów. Pr. Nauk. Uniw. Ekon. We Wrocławiu 2010, 140, 53–67. [Google Scholar]
  8. European Commission. Causes of Climate Change. Available online: https://climate.ec.europa.eu/climate-change/causes-climate-change_en (accessed on 27 January 2025).
  9. Logan, B.E.; Oh, S.-E.; Kim, I.S.; Van Ginkel, S. Biological Hydrogen Production Measured in Batch Anaerobic Respirometers. Environ. Sci. Technol. 2002, 36, 2530–2535. [Google Scholar] [CrossRef]
  10. Chen, W.; Chen, S.; Kumarkhanal, S.; Sung, S. Kinetic Study of Biological Hydrogen Production by Anaerobic Fermentation. Int. J. Hydrogen Energy 2006, 31, 2170–2178. [Google Scholar] [CrossRef]
  11. Sun, J.; Hopkins, R.C.; Jenney, F.E.; McTernan, P.M.; Adams, M.W.W. Heterologous Expression and Maturation of an NADP-Dependent [NiFe]-Hydrogenase: A Key Enzyme in Biofuel Production. PLoS ONE 2010, 5, e10526. [Google Scholar] [CrossRef]
  12. Das, D. Hydrogen Production by Biological Processes: A Survey of Literature. Int. J. Hydrogen Energy 2001, 26, 13–28. [Google Scholar] [CrossRef]
  13. Gopalakrishnan, B.; Khanna, N.; Das, D. Dark-Fermentative Biohydrogen Production. In Biomass, Biofuels, Biochemicals: Biohydrogen, 2nd ed.; Elsevier: Amsterdam, The Netherlands, 2019; pp. 79–122. ISBN 9780444642035. [Google Scholar]
  14. Albuquerque, M.M.; Sartor, G.D.; Martinez-Burgos, W.J.; Scapini, T.; Edwiges, T.; Soccol, C.R.; Medeiros, A.B. Biohydrogen Produced via Dark Fermentation: A Review. Methane 2024, 3, 500–532. [Google Scholar] [CrossRef]
  15. Guo, X.M.; Trably, E.; Latrille, E.; Carrère, H.; Steyer, J.-P. Hydrogen Production from Agricultural Waste by Dark Fermentation: A Review. Int. J. Hydrogen Energy 2010, 35, 10660–10673. [Google Scholar] [CrossRef]
  16. Chalima, A.; Oliver, L.; Fernández de Castro, L.; Karnaouri, A.; Dietrich, T.; Topakas, E. Utilization of Volatile Fatty Acids from Microalgae for the Production of High Added Value Compounds. Fermentation 2017, 3, 54. [Google Scholar] [CrossRef]
  17. Trancone, G.; Policastro, G.; Spasiano, D.; Race, M.; Parrino, F.; Fratino, U.; Fabbricino, M.; Pirozzi, F. Treatment of Concrete Waste from Construction and Demolition Activities: Application of Organic Acids from Continuous Dark Fermentation in Moving Bed Biofilm Reactors. Chem. Eng. J. 2025, 505, 159536. [Google Scholar] [CrossRef]
  18. Lee, W.S.; Chua, A.S.M.; Yeoh, H.K.; Ngoh, G.C. A Review of the Production and Applications of Waste-Derived Volatile Fatty Acids. Chem. Eng. J. 2014, 235, 83–99. [Google Scholar] [CrossRef]
  19. Guilayn, F.; Jimenez, J.; Monlau, F.; Vaneeckhaute, C. Valorisation of Anaerobic Digestate: Towards Value-Added Products. In Renewable Energy Technologies for Energy Efficient Sustainable Development; Springer: Berlin/Heidelberg, Germany, 2022; pp. 227–262. [Google Scholar]
  20. Kumar, S. Hydrothermal Processing of Biomass for Biofuels. Biofuel Res. J. 2014, 1, 43. [Google Scholar] [CrossRef]
  21. Tapia-Venegas, E.; Ramirez-Morales, J.E.; Silva-Illanes, F.; Toledo-Alarcón, J.; Paillet, F.; Escudie, R.; Lay, C.-H.; Chu, C.-Y.; Leu, H.-J.; Marone, A.; et al. Biohydrogen Production by Dark Fermentation: Scaling-up and Technologies Integration for a Sustainable System. Rev. Environ. Sci. Bio/Technol. 2015, 14, 761–785. [Google Scholar] [CrossRef]
  22. Li, Y.-C.; Chu, C.-Y.; Wu, S.-Y.; Tsai, C.-Y.; Wang, C.-C.; Hung, C.-H.; Lin, C.-Y. Feasible Pretreatment of Textile Wastewater for Dark Fermentative Hydrogen Production. Int. J. Hydrogen Energy 2012, 37, 15511–15517. [Google Scholar] [CrossRef]
  23. Alqahtani, H.S. Lower-Carbon Hydrogen Production from Wastewater: A Comprehensive Review. Sustainability 2024, 16, 8659. [Google Scholar] [CrossRef]
  24. Rosa e Silva, G.O.; Carpanez, T.G.; Dos Santos, C.R.; Casella, G.S.; Moreira, V.R.; de Paula, E.C.; Amaral, M.C.S. Biohydrogen Production from Wastewater: Production Technologies, Environmental and Economic Aspects. J. Environ. Chem. Eng. 2024, 12, 114104. [Google Scholar] [CrossRef]
  25. Casanova-Mina, A.A.; Suárez-Vázquez, S.I.; Acuña-Askar, K.; Alfaro-Barbosa, J.M.; Cruz-López, A. Continuous Dark Fermentation by Industrial Food Wastewater: The Effect of Hydraulic Retention Time on Hydrogen Production and Microbial Variation. Biomass Convers. Biorefinery 2024, 14, 23909–23920. [Google Scholar] [CrossRef]
  26. Elsayad, R.M.; Sharshir, S.W.; Khalil, A.; Basha, A.M. Recent Advancements in Wastewater Treatment via Anaerobic Fermentation Process: A Systematic Review. J. Environ. Manag. 2024, 366, 121724. [Google Scholar] [CrossRef] [PubMed]
  27. Hosseinzadeh, A.; Zhou, J.L.; Altaee, A.; Li, D. Machine Learning Modeling and Analysis of Biohydrogen Production from Wastewater by Dark Fermentation Process. Bioresour. Technol. 2022, 343, 126111. [Google Scholar] [CrossRef] [PubMed]
  28. Dzulkarnain, E.L.N.; Audu, J.O.; Wan Dagang, W.R.Z.; Abdul-Wahab, M.F. Microbiomes of Biohydrogen Production from Dark Fermentation of Industrial Wastes: Current Trends, Advanced Tools and Future Outlook. Bioresour. Bioprocess. 2022, 9, 16. [Google Scholar] [CrossRef] [PubMed]
  29. Barca, C.; Soric, A.; Ranava, D.; Giudici-Orticoni, M.-T.; Ferrasse, J.-H. Anaerobic Biofilm Reactors for Dark Fermentative Hydrogen Production from Wastewater: A Review. Bioresour. Technol. 2015, 185, 386–398. [Google Scholar] [CrossRef]
  30. Li, X.; Guo, L.; Liu, Y.; Wang, Y.; She, Z.; Gao, M.; Zhao, Y. Effect of Salinity and PH on Dark Fermentation with Thermophilic Bacteria Pretreated Swine Wastewater. J. Environ. Manage. 2020, 271, 111023. [Google Scholar] [CrossRef]
  31. Ziara, R.M.M.; Miller, D.N.; Subbiah, J.; Dvorak, B.I. Lactate Wastewater Dark Fermentation: The Effect of Temperature and Initial PH on Biohydrogen Production and Microbial Community. Int. J. Hydrogen Energy 2019, 44, 661–673. [Google Scholar] [CrossRef]
  32. Wicher, E.; Seifert, K.; Zagrodnik, R.; Pietrzyk, B.; Laniecki, M. Hydrogen Gas Production from Distillery Wastewater by Dark Fermentation. Int. J. Hydrogen Energy 2013, 38, 7767–7773. [Google Scholar] [CrossRef]
  33. Sinbuathong, N.; Sillapacharoenkul, B. Dark Fermentation of Starch Factory Wastewater with Acid- and Base-Treated Mixed Microorganisms for Biohydrogen Production. Int. J. Hydrogen Energy 2021, 46, 16622–16630. [Google Scholar] [CrossRef]
  34. Chen, S.; Sheu, D.; Chen, W.; Lo, Y.; Huang, T.; Lin, C.; Chang, J. Dark Hydrogen Fermentation from Hydrolyzed Starch Treated with Recombinant Amylase Originating from Caldimonas Taiwanensis On1. Biotechnol. Prog. 2007, 23, 1312–1320. [Google Scholar] [CrossRef]
  35. Masset, J.; Calusinska, M.; Hamilton, C.; Hiligsmann, S.; Joris, B.; Wilmotte, A.; Thonart, P. Fermentative Hydrogen Production from Glucose and Starch Using Pure Strains and Artificial Co-Cultures of Clostridium spp. Biotechnol. Biofuels 2012, 5, 35. [Google Scholar] [CrossRef]
  36. Tagrida, M.; Gulzar, S.; Martín-Belloso, O.; Elez-Martínez, P.; Soliva-Fortuny, R. Ultrasound and Freeze-Thaw Modifications of Cassava Starch: Microstructure, Functionality, and 3D Printing Potential. Food Hydrocoll. 2025, 162, 110963. [Google Scholar] [CrossRef]
  37. Parker, R.; Ring, S.G. Aspects of the Physical Chemistry of Starch. J. Cereal Sci. 2001, 34, 1–17. [Google Scholar] [CrossRef]
  38. Fortuna, T. Skrobie Modyfikowane w Produkcji Żywności. Żywność. Technol. Jakość 1995, 1, 3–7. [Google Scholar]
  39. Adewale, P.; Yancheshmeh, M.S.; Lam, E. Starch Modification for Non-Food, Industrial Applications: Market Intelligence and Critical Review. Carbohydr. Polym. 2022, 291, 119590. [Google Scholar] [CrossRef]
  40. Bangar, S.P.; Balakrishnan, G.; Navaf, M.; Sunooj, K.V. Recent Advancements on Barnyard Millet Starch: A Sustainable Alternative to Conventional Starch. Starch-Stärke 2024, 76, 2300232. [Google Scholar] [CrossRef]
  41. Makroo, H.A.; Naqash, S.; Saxena, J.; Sharma, S.; Majid, D.; Dar, B.N. Recovery and Characteristics of Starches from Unconventional Sources and Their Potential Applications: A Review. Appl. Food Res. 2021, 1, 100001. [Google Scholar] [CrossRef]
  42. Barbhuiya, R.I.; Wroblewski, C.; Ravikumar, S.P.; Kaur, G.; Routray, W.; Subramanian, J.; Elsayed, A.; Singh, A. Upcycling of Industrial Pea Starch by Rapid Spray Nanoprecipitation to Develop Plant-Derived Oil Encapsulated Starch Nanoparticles for Potential Agricultural Applications. Carbohydr. Polym. 2024, 346, 122618. [Google Scholar] [CrossRef]
  43. Fortuna, T.; Rożnowski, J. Skrobie Modyfikowane Chemicznie, Ich Właściwości i Zastosowanie. Żywność 2002, 2, 16–29. [Google Scholar]
  44. Wang, J.; Wang, C.; Yu, J.; Yang, Y.; Copeland, L.; Wang, S. A Novel Composite Resistant Starch with Improved Prebiotic Functions. Food Hydrocoll. 2025, 162, 111015. [Google Scholar] [CrossRef]
  45. Carvalho, H.J.; Barcia, M.T.; Schmiele, M. Non-Conventional Starches: Properties and Potential Applications in Food and Non-Food Products. Macromol 2024, 4, 886–909. [Google Scholar] [CrossRef]
  46. Shoukat, L.; Javed, S.; Afzaal, M.; Akhter, N.; Shah, Y.A. Starch-Based Encapsulation to Enhance Probiotic Viability in Simulated Digestion Conditions. Int. J. Biol. Macromol. 2024, 283, 137606. [Google Scholar] [CrossRef] [PubMed]
  47. Zhu, Y.; Guo, F.; Li, J.; Wang, Z.; Liang, Z.; Yi, C. Development of a Novel Energy Saving and Environmentally Friendly Starch via a Graft Copolymerization Strategy for Efficient Warp Sizing and Easy Removal. Polymers 2024, 16, 182. [Google Scholar] [CrossRef] [PubMed]
  48. Szosland, J. Podstawy Budowy i Technologii Kanin; Wydawnictwo Naukowo-Techniczne: Warsaw, Poland, 1974. [Google Scholar]
  49. Islam, M.M.; Mahmud, K.; Faruk, O.; Billah, S. Assessment of Environmental Impacts for Textile Dyeing Industries in Bangladesh. In Proceedings of the International Conference on Green Technology and Environmental Conservation (GTEC-2011), Chennai, India, 15–17 December 2011; IEEE: Piscataway, NJ, USA, 2011; pp. 173–181. [Google Scholar]
  50. Drumond Chequer, F.M.; de Oliveira, G.A.R.; Anastacio Ferraz, E.R.; Carvalho, J.; Boldrin Zanoni, M.V.; de Oliveir, D.P. Textile Dyes: Dyeing Process and Environmental Impact. In Eco-Friendly Textile Dyeing and Finishing; InTech: London, UK, 2013. [Google Scholar]
  51. Khattab, T.A.; Abdelrahman, M.S.; Rehan, M. Textile Dyeing Industry: Environmental Impacts and Remediation. Environ. Sci. Pollut. Res. 2020, 27, 3803–3818. [Google Scholar] [CrossRef] [PubMed]
  52. Kant, R. Textile Dyeing Industry an Environmental Hazard. Nat. Sci. 2012, 4, 22–26. [Google Scholar] [CrossRef]
  53. Zeeshan, M.H.; Ruman, U.E.; He, G.; Sabir, A.; Shafiq, M.; Zubair, M. Environmental Issues Concerned with Poly (Vinyl Alcohol) (PVA) in Textile Wastewater. In Polymer Technology in Dye-containing Wastewater. Sustainable Textiles: Production, Processing, Manufacturing & Chemistry; Springer: Singapore, 2022; pp. 225–236. [Google Scholar]
  54. Var, C.; Palamutcu, S. Sustainable Approaches in Textile-Sizing Process. In Sustainable Manufacturing Practices in the Textiles and Fashion Sector; Springer: Cham, Switzerland, 2024; pp. 55–74. [Google Scholar]
  55. Sarkodie, B.; Feng, Q.; Xu, C.; Xu, Z. Desizability and Biodegradability of Textile Warp Sizing Materials and Their Mechanism: A Review. J. Polym. Environ. 2023, 31, 3317–3337. [Google Scholar] [CrossRef]
  56. Xue, Y.; Chew, J.W. Sustainable Carbonaceous Materials-Based Catalytic Membranes for Organic Wastewater Treatment: Progress and Prospects. Sep. Purif. Technol. 2025, 360, 131119. [Google Scholar] [CrossRef]
  57. Goswami, B.C.; Anandjiwala, R.D.; Hall, D. Textile Sizing; CRC Press: Boca Raton, FL, USA, 2004; ISBN 9780429223945. [Google Scholar]
  58. Madhav, S.; Ahamad, A.; Singh, P.; Mishra, P.K. A Review of Textile Industry: Wet Processing, Environmental Impacts, and Effluent Treatment Methods. Environ. Qual. Manag. 2018, 27, 31–41. [Google Scholar] [CrossRef]
  59. Biyada, S.; Urbonavičius, J. Circularity in Textile Waste: Challenges and Pathways to Sustainability. Clean. Eng. Technol. 2025, 24, 100905. [Google Scholar] [CrossRef]
  60. Trancone, G.; Spasiano, D.; Race, M.; Luongo, V.; Petrella, A.; Pirozzi, F.; Fratino, U.; Piccinni, A.F. A Combined System for Asbestos-Cement Waste Degradation by Dark Fermentation and Resulting Supernatant Valorization in Anaerobic Digestion. Chemosphere 2022, 300, 134500. [Google Scholar] [CrossRef]
  61. Domińska, M.; Paździor, K.; Ślęzak, R.; Ledakowicz, S. The Influence of Inoculum Source and Pretreatment on the Biohydrogen Production in the Dark Fermentation Process. Chem. Process Eng. New Front. 2024, 45, e63. [Google Scholar] [CrossRef]
  62. Broekaert, J.A.C. Daniel C. Harris: Quantitative Chemical Analysis, 9th Ed. Anal. Bioanal. Chem. 2015, 407, 8943–8944. [Google Scholar] [CrossRef]
  63. Magrel, L. Metodyka Oceny Efektywności Procesu Fermentacji Metanowej Wybranych Osadów Ściekowych; Wydawnictwo PB: Białystok, Poland, 2002. [Google Scholar]
  64. Boruszko, D.; Butarewicz, A.; Dąbrowski, W.; Magrel, L. Badania Nad Ostatecznym Wykorzystaniem Odwodnionych Osadów Ściekowych Do Nieprzemysłowego Wykorzystania; Wydawnictwo PB: Białystok, Poland, 2005. [Google Scholar]
  65. Stevenson, F.J. Humus Chemistry: Genesis, Composition, Reactions; John Wiley & Sons: Hoboken, NJ, USA, 1994; ISBN 978-0-471-59474-1. [Google Scholar]
  66. Jain, R.; Panwar, N.L.; Jain, S.K.; Gupta, T.; Agarwal, C.; Meena, S.S. Bio-Hydrogen Production through Dark Fermentation: An Overview. Biomass Convers. Biorefinery 2024, 14, 12699–12724. [Google Scholar] [CrossRef]
  67. Marschner, B.; Kalbitz, K. Controls of Bioavailability and Biodegradability of Dissolved Organic Matter in Soils. Geoderma 2003, 113, 211–235. [Google Scholar] [CrossRef]
  68. Fog, K. The Effect of Added Nitrogen on The Rate of Decomposition of Organic Matter. Biol. Rev. 1988, 63, 433–462. [Google Scholar] [CrossRef]
  69. Louis, P.; Flint, H.J. Formation of Propionate and Butyrate by the Human Colonic Microbiota. Environ. Microbiol. 2017, 19, 29–41. [Google Scholar] [CrossRef]
  70. Macfarlane, S.; Macfarlane, G.T. Regulation of Short-Chain Fatty Acid Production. Proc. Nutr. Soc. 2003, 62, 67–72. [Google Scholar] [CrossRef]
  71. Mead, G.C. The Amino Acid-Fermenting Clostridia. J. Gen. Microbiol. 1971, 67, 47–56. [Google Scholar] [CrossRef]
  72. Smith, E.A.; Macfarlane, G.T. Formation of Phenolic and Indolic Compounds by Anaerobic Bacteria in the Human Large Intestine. Microb. Ecol. 1997, 33, 180–188. [Google Scholar] [CrossRef]
  73. Elsden, S.R.; Hilton, M.G. Volatile Acid Production from Threonine, Valine, Leucine and Isoleucine by Clostridia. Arch. Microbiol. 1978, 117, 165–172. [Google Scholar] [CrossRef]
  74. Huang, X.-Y.; Liu, C.-G.; Lin, Y.-H. A Novel Explainable Kinetic Model for Two-Stage Fermentation Profile. Chem. Eng. J. 2024, 493, 152745. [Google Scholar] [CrossRef]
  75. Detman, A.; Laubitz, D.; Chojnacka, A.; Kiela, P.R.; Salamon, A.; Barberan, A.; Chen, Y.; Yang, F.; Błaszczyk, M.K.; Sikora, A. Dynamics of Dark Fermentation Microbial Communities in the Light of Lactate and Butyrate Production. Microbiome 2021, 9, 1–21. [Google Scholar] [CrossRef]
  76. Nzeteu, C.o.; Coelho, F.; Trego, A.C.; Abram, F.; Ramiro-Garcia, J.; Paulo, L.; O’Flaherty, V. Development of an Enhanced Chain Elongation Process for Caproic Acid Production from Waste-Derived Lactic Acid and Butyric Acid. J. Clean. Prod. 2022, 338, 130655. [Google Scholar] [CrossRef]
  77. Ding, H.-B.; Tan, G.-Y.A.; Wang, J.-Y. Caproate Formation in Mixed-Culture Fermentative Hydrogen Production. Bioresour. Technol. 2010, 101, 9550–9559. [Google Scholar] [CrossRef] [PubMed]
  78. Wang, J.; Yin, Y. Clostridium Species for Fermentative Hydrogen Production: An Overview. Int. J. Hydrogen Energy 2021, 46, 34599–34625. [Google Scholar] [CrossRef]
  79. Cheng, C.-H.; Hung, C.-H.; Lee, K.-S.; Liau, P.-Y.; Liang, C.-M.; Yang, L.-H.; Lin, P.-J.; Lin, C.-Y. Microbial Community Structure of a Starch-Feeding Fermentative Hydrogen Production Reactor Operated under Different Incubation Conditions. Int. J. Hydrogen Energy 2008, 33, 5242–5249. [Google Scholar] [CrossRef]
  80. Nissilä, M.E.; Tähti, H.P.; Rintala, J.A.; Puhakka, J.A. Effects of Heat Treatment on Hydrogen Production Potential and Microbial Community of Thermophilic Compost Enrichment Cultures. Bioresour. Technol. 2011, 102, 4501–4506. [Google Scholar] [CrossRef]
  81. Punia Bangar, S.; Ashogbon, A.O.; Singh, A.; Chaudhary, V.; Whiteside, W.S. Enzymatic Modification of Starch: A Green Approach for Starch Applications. Carbohydr. Polym. 2022, 287, 119265. [Google Scholar] [CrossRef]
  82. Su, H.; Cheng, J.; Zhou, J.; Song, W.; Cen, K. Improving Hydrogen Production from Cassava Starch by Combination of Dark and Photo Fermentation. Int. J. Hydrogen Energy 2009, 34, 1780–1786. [Google Scholar] [CrossRef]
  83. Zhang, Y.-H.P.; Evans, B.R.; Mielenz, J.R.; Hopkins, R.C.; Adams, M.W.W. High-Yield Hydrogen Production from Starch and Water by a Synthetic Enzymatic Pathway. PLoS ONE 2007, 2, e456. [Google Scholar] [CrossRef]
Water 17 01716 g001
Figure 1. Effect of dark fermentation on pH: pre- and post-fermentation values.
Figure 1. Effect of dark fermentation on pH: pre- and post-fermentation values.
Water 17 01716 g001
Water 17 01716 g002
Figure 2. TVS reduction as an indicator of organic matter degradation during dark fermentation.
Figure 2. TVS reduction as an indicator of organic matter degradation during dark fermentation.
Water 17 01716 g002
Water 17 01716 g003
Figure 3. DOC changes during the dark fermentation: initial and final values.
Figure 3. DOC changes during the dark fermentation: initial and final values.
Water 17 01716 g003
Water 17 01716 g004
Figure 4. Variation in TN levels as a result of acidic fermentation process.
Figure 4. Variation in TN levels as a result of acidic fermentation process.
Water 17 01716 g004
Water 17 01716 g005
Figure 5. Concentration and profile of VFAs produced during the acidogenesis stage.
Figure 5. Concentration and profile of VFAs produced during the acidogenesis stage.
Water 17 01716 g005
Water 17 01716 g006
Figure 6. Volumetric production of hydrogen and carbon dioxide during the dark fermentation.
Figure 6. Volumetric production of hydrogen and carbon dioxide during the dark fermentation.
Water 17 01716 g006
Table 1. Characteristics of the inoculum and wastewater as substrate used in the dark fermentation (the tests were performed in triplicate).
Table 1. Characteristics of the inoculum and wastewater as substrate used in the dark fermentation (the tests were performed in triplicate).
ParameterInoculum (After 70 °C)Natural StarchModified Starch
pH7.24 ± 0.027.55 ± 0.207.73 ± 0.15
TS (g/L)33.95 ± 0.3314.01 ± 0.0812.05 ± 0.14
TVS (g/L)11.75 ± 0.1513.57 ± 0.2011.73 ± 0.13
DOC (g/L)1.46 ± 0.015.01 ± 0.057.85 ± 0.01
TN (g/L)1.35 ± 0.040.011 ± 0.1100.019 ± 0.003
Disclaimer/Publisher’s Note: The statements, opinions and data contained in all publications are solely those of the individual author(s) and contributor(s) and not of MDPI and/or the editor(s). MDPI and/or the editor(s) disclaim responsibility for any injury to people or property resulting from any ideas, methods, instructions or products referred to in the content.

Share and Cite

MDPI and ACS Style

Domińska, M.; Gloc, M.; Olak-Kucharczyk, M.; Paździor, K. Dark Fermentation of Sizing Process Waste: A Sustainable Solution for Hydrogen Production and Industrial Waste Management. Water 2025, 17, 1716. https://doi.org/10.3390/w17111716

AMA Style

Domińska M, Gloc M, Olak-Kucharczyk M, Paździor K. Dark Fermentation of Sizing Process Waste: A Sustainable Solution for Hydrogen Production and Industrial Waste Management. Water. 2025; 17(11):1716. https://doi.org/10.3390/w17111716

Chicago/Turabian Style

Domińska, Marlena, Martyna Gloc, Magdalena Olak-Kucharczyk, and Katarzyna Paździor. 2025. "Dark Fermentation of Sizing Process Waste: A Sustainable Solution for Hydrogen Production and Industrial Waste Management" Water 17, no. 11: 1716. https://doi.org/10.3390/w17111716

APA Style

Domińska, M., Gloc, M., Olak-Kucharczyk, M., & Paździor, K. (2025). Dark Fermentation of Sizing Process Waste: A Sustainable Solution for Hydrogen Production and Industrial Waste Management. Water, 17(11), 1716. https://doi.org/10.3390/w17111716

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

Article Metrics

Back to TopTop