Advancements of Biohydrogen Production Based on Anaerobic Digestion: Technologies, Substrates, and Future Prospects

Abstract

Population growth has significantly increased energy and resource demands, driving research toward cost-effective technologies that repurpose waste into alternative energy forms such as biohydrogen. This review aims to comprehensively evaluate biohydrogen production via anaerobic digestion, addressing gaps in previous studies focusing on a single sustainable development goal or limited environmental benefits. The methodology used the Scopus database with specific keywords, the Preferred Reporting Items for Systematic Reviews and Meta-Analyses protocol to screen relevant articles, and bibliometric analysis to delineate research directions from 2002 to 2024. Findings indicate that research on biohydrogen production via anaerobic digestion has grown exponentially over the past two decades, with increasing emphasis on advanced techniques, innovative reactor configurations, and diverse microbial consortia. Emerging trends, including the integration of artificial intelligence for process optimization and comprehensive life cycle assessments, suggest promising avenues for large-scale implementation. Anaerobic digestion-based biohydrogen production supports several Sustainable Development Goals (SDGs), including the ones related to clean energy (SDG7), SDG 13 (climate action), and SDG 12 (waste management), among others. Recent advancements are synthesized to provide a clear roadmap for future research toward sustainable energy solutions.

1. Introduction

Fossil fuels, including coal, petrol, and gasoline, are some of the primary sources of energy satisfying the current energy demand. However, they are major contributors to greenhouse gas (GHG) emissions and climate change [1]. This environmental impact has driven researchers to explore alternative energy sources. Likewise, factors such as a fast-growing population, extreme weather events, resource scarcity, growing economy, and inadequate waste and biomass management have intensified the impacts across developing and developed countries, including energy power shortage [2]. Consequently, there is an urgent need for sustainable and efficient energy sources to meet the increasing energy demand in a balanced and cost-effective manner [3].

Biohydrogen offers a carbon-neutral and renewable energy solution, thereby mitigating the reliance on fossil fuels [4]. As the lightest and most abundant element, hydrogen is an energy carrier suitable for various applications, including transportation, heating, industry, and others [5,6]. Hydrogen’s versatility could boost the economy and diversify the energy matrix [7,8]. Hydrogen is considered one of the most promising energy carriers for future energy sources [9]. If it is generated from water, it is considered environmentally neutral [10], although some economic barriers still exist. Hydrogen is referred to as Bio-H₂ or biohydrogen when produced from biological sources. Biohydrogen represents a promising clean energy source [11,12], contributing to agricultural biomass residues, wastewater treatment, waste management [13], and overall system efficiency while creating new job opportunities [14,15,16]. Among BioH₂ production pathways, dark fermentation (DF) has been explored for its ability to produce volatile fatty acids (VFAs) as metabolic by-products. These VFAs serve as valuable substrates for anaerobic digestion (AD), facilitating the subsequent conversion of organic waste into biomethane. Recent studies have demonstrated the integration of DF-AD systems in construction and demolition waste (CDW) and asbestos-cement waste (ACW) management, highlighting their potential for biohydrogen production and waste valorization. For instance, Trancone et al. [17] explored the bioleaching of CDW using VFAs generated from a continuous DF process in a moving bed biofilm reactor. Their study demonstrates the feasibility of combining DF with resource recovery in construction waste treatment. Similarly, Trancone et al. [18] investigated the biological treatment of ACW, where DF under mesophilic and thermophilic conditions successfully degraded asbestos fibers, demonstrating a viable waste-to-energy pathway.

The International Energy Agency (IEA) reports that around 78% of hydrogen is produced from fossil fuels. For instance, natural gas is the primary fossil fuel used to produce hydrogen, accounting for around 47% of global hydrogen production in 2021. Coal accounted for around 27% of global hydrogen production in 2021, and oil contributes about 22% of global hydrogen production, mainly as a by-product [19]. This implies a significant environmental impact, with reports of emissions of up to 830 million tonnes of CO₂ each year to produce 74 million tonnes of hydrogen [20]. In 2022, 70% of the energy needed for hydrogen production came from natural gas [19].

In order to reduce this dependence, Bio-H₂ production needs to be effectively developed to provide sustainable, renewable energy sources. Different substrates that represent an environmental load have been recently evaluated for Bio-H₂ production, such as sugar cane molasses [21], cellulose [22], rice bran, rice husk, brewer’s spent grain, soybean waste, wheat waste [23], lignocellulosic biomass [16], cattle manure, food waste [24,25], and algae biomass [26,27]. This suggests a wide range of feedstock and opportunities to enhance the conventional technologies for hydrogen production.

Despite its promise, Bio-H₂ production faces several challenges in large-scale implementation. These include costly production systems [28], the need for optimized yields and efficient microbial and enzymatic processes, safe and controlled storage and transport, and limited efficiency compared to traditional energy carriers like coal [29].

To address these challenges, AD offers a promising solution as a biological process that decomposes organic matter in an oxygen-free environment [30]. This process produces energy and controls organic waste. The main product of this process treats the volatile solids (VS) [31] while producing biogas, composed mainly of methane and carbon dioxide, with a fraction of hydrogen [32]. This process may require additional purification methods, such as membrane separation or chemical absorption [33]. Fermentative bacteria (Clostridium sp., Enterobacter sp., Escherichia coli, and Bacillus sp.) or phototrophic bacteria (Rhodobacter sphaeroides, Rhodopseudomonas palustris, and Chlorobium tepidum) are commonly used to obtain Bio-H₂ under anaerobic conditions [34,35,36].

While some reviews have focused on bioprocesses, optimization, potential advances in Bio-H₂ production, biofuel production, utilization of iron-based additives [37], and the integration of biochar in dark fermentation reactors [38], there is a lack of up-to-date comprehensive reviews compiling optimal techniques, performances, and methodologies for producing Bio-H₂ from AD. This paper aims to fill that gap by thoroughly exploring contemporary Bio-H₂ production technologies based on AD. It highlights the advantages of these methodologies and outlines relevant avenues for future research. The study focuses on a diverse array of biomass substrates, pathways of Bio-H₂ generation, optimal process conditions, reactor configurations, and factors influencing Bio-H₂ production dynamics.

Previous reviews have evaluated biofuels in relation to the Sustainable Development Goals (SDGs) from a broad perspective [39]. In contrast, some studies have addressed this topic narrowly, focusing solely on SDG 7 (Affordable and Clean Energy), while others have concentrated only on the environmental benefits of AD (particularly its role in reducing GHG emissions) without integrating the SDG framework [40,41]. This fragmented approach highlights the lack of a comprehensive perspective on this promising technology for Bio-H₂ production via AD. Our review fills this gap by analyzing the intersections between Bio-H₂ production, SDG targets, and broader sustainability strategies. It explores recent advancements in Bio-H₂ technology, emphasizing its role in mitigating GHG emissions and enhancing waste management as part of a sustainable energy transition.

To bridge this gap, this review also examines key mechanisms (including microbial consortia, reactor optimization, and process integration) to enhance Bio-H₂ yields and scale up production. Additionally, it addresses fundamental research gaps by posing several critical questions: What are the most effective substrates and microbial consortia for optimizing Bio-H₂ yields? Which reactor configurations and integration strategies improve scalability? How can AD-based Bio-H₂ contribute to decarbonization while enhancing biomass and waste management? What policy frameworks and technological barriers hinder large-scale implementation, and how can they be overcome? Which countries lead in Bio-H₂ research, and how is international collaboration shaping its future? By exploring these questions, this study provides a foundation for future research and strategic decision-making in the transition toward a sustainable, low-carbon energy future.

2. Materials and Methods

This study followed the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) framework to ensure transparency, reproducibility, and rigor throughout the bibliometric and content analysis process [42,43]. The methodology was structured into three sequential phases: (I) selection of database and search criteria, (II) screening and eligibility assessment, and (III) bibliometric and content analysis (Figure 1).

2.1. Selection of Databases and Search Criteria

All bibliographic data were retrieved from the Scopus database in March 2024. The search targeted documents related to biohydrogen production via anaerobic digestion, using the Title, Abstract, and Author Keywords (TITLE-ABS-KEY) fields. The following Boolean query was applied: (TITLEABS–KEY (“biohydrogen production” OR “bio–h2” OR “biohydrogen” OR “bio–hydrogen” OR “bio–hydrogen production”) AND TITLE–ABS–KEY (“ad” OR “anaerobic digester” OR “anaerobic process” OR “fermentation” OR “anaerobic fermentation” OR “dark fermentation”)) AND (LIMIT–TO (PUBSTAGE, “final”)) AND (LIMIT–TO (DOCTYPE, “ar”) OR LIMIT–TO (DOCTYPE, “ch”)) AND (EXCLUDE (DOCTYPE, “ch” )) AND (EXCLUDE (SRCTYPE, “k”) OR EXCLUDE (SRCTYPE, “d”)). The search yielded 2061 documents, from which 58 were excluded due to duplication, missing DOI, or incomplete metadata. The final dataset consisted of 2003 peer-reviewed articles published in English between 2003 and 2024. Only full-length journal articles and reviews were considered; conference papers, editorials, letters, and book chapters were excluded.

2.2. Phase II—Screening and Eligibility

The selection process was based on three PRISMA stages:

• Identification: retrieval of 2061 documents from Scopus.
• Screening: elimination of 58 documents with metadata inconsistencies or duplications.
• Eligibility: Inclusion of 2003 full-length, peer-reviewed documents in English. No manual recovery of excluded records was performed.

2.3. Phase III—Bibliometric and Content Analysis

This phase comprised three analytical dimensions: performance analysis, bibliometric mapping, and prospective analysis, each described below with corresponding tools and variables.

2.3.1. Performance Analysis

Annual production trends, source rankings, and citation metrics were extracted from the Scopus metadata. The following analyses were performed:

Scientific production by year was examined using the publication year field, grouped into four periods: 2003–2007, 2008–2012, 2013–2017, and 2018–2024. Data were processed and visualized in Microsoft Excel 2019 and OriginPro 2019. Country-level contributions were calculated using the author affiliation country metadata. The number of publications per country was normalized by population (publications per million inhabitants) using 2024 UN demographic data. Geographic distribution was mapped using ArcMap 10.8, applying a world shapefile with WGS84 projection (EPSG:4326). Top publishing journals were ranked by the total number of documents. For each, the corresponding SJR index, quartile ranking, and subject areas were retrieved from the Scimago Journal & Country Rank (SJR 2022) database. Most-cited articles were identified based on the total citation count in Scopus, selecting the top-cited original research articles and reviews related explicitly to biohydrogen via anaerobic digestion.

2.3.2. Bibliometric Mapping

Visualization of scientific structures and collaboration patterns was conducted using the following tools:

VOSviewer 1.6.18 was used to build keyword co-occurrence networks based on author keywords. A minimum threshold of five occurrences was established to ensure robust clustering. Network layout and cluster colors were generated using the LinLog modularity algorithm. Country collaboration networks were also generated in VOSviewer using co-authorship metadata. A minimum threshold of 25 documents per country was set, and total link strength was used to represent the intensity of international cooperation. Subject area classification was based on Scopus journal classification. The most frequent disciplines included Renewable Energy, Sustainability and the Environment, Energy Engineering and Power Technology, Bioengineering, Waste Management and Disposal, Chemical Engineering, and Environmental Science.

2.3.3. Prospective Analysis

To identify emerging trends and research fronts, we used the following:

CiteSpace (version 6.2.R2) was employed for keyword burst detection and timeline analysis. A time-slicing configuration from 2003 to 2024 was applied (1-year intervals). Clustering was performed using the log-likelihood ratio algorithm, and citation bursts were identified using Kleinberg’s method.

Cluster evolution was visualized to track the chronological development of biohydrogen-related thematic areas, such as dark fermentation, co-digestion, and microbial consortia.

Content analysis of selected articles was performed to classify studies based on (i) feedstock types (e.g., lignocellulosic biomass, wastewater), (ii) additive use (e.g., alkaline agents, trace elements, nanoparticles), and (iii) sustainability indicators (e.g., GHG mitigation, energy efficiency, digestate valorization).

2.4. Exploring Research Frontiers in Biohydrogen Production by the Use of CiteSpace Network Analysis

To analyze research trends in Bio-H₂ production, CiteSpace was selected as the primary bibliometric tool due to its advanced capabilities for identifying research frontiers and collaboration patterns [44]. Unlike conventional bibliometric software, CiteSpace offers dynamic visualization tools and burst detection, allowing a more nuanced view of emerging topics and keyword trends over time [45]. After importing the dataset into CiteSpace, keyword co-occurrence and clustering analyses were conducted. Burst detection analysis was also performed by AD to identify the main cluster in hydrogen production.

3. Results and Discussion

3.1. Annual Scientific Production by Period

Figure 2 illustrates the annual production of scientific publications related to Bio-H₂ production through AD, categorized into four distinct periods: 2003–2007, 2008–2012, 2013–2017, and 2017–2024. The figure demonstrates a notable increase in the number of citations, especially from 2008 onwards; there is a marked acceleration in citation numbers. The most substantial citation rise occurs in the last period, where a sharp peak is observed. This can be attributed to exploring new substrates for Bio-H₂ production and a heightened global focus on sustainable and renewable energy sources in response to climate change.

On the other hand, scientific output peaked in 2022 with 216 publications, mainly focused on Bio-H₂ production but adding new elements such as sustainability and utilizing algae and microalgae to produce Bio-H₂ [46,47,48,49]. Scientists have also taken a keen interest in exploring the bioconversion of leachates and the collection of Bio-H₂ from wastewater. These topics have been subjected to extensive research owing to their potential for contributing to sustainable development [48]. On the other hand, 2003 had the lowest number of articles published on the subject (five papers). These articles focused on Bio-H₂ production from biosolid waste by anaerobic fermentation and the combination of wastewater and feedstocks such as starch.

The heightened interest in novel Bio-H₂ substrates corresponds closely with global energy policies emphasizing decarbonization and circular bioeconomy principles [50]. Sustainable feedstocks, including agricultural residues, microalgae, and wastewater, align with international climate commitments such as the Paris Agreement and the SDGs, as elaborated in this section. National policies, such as the EU Green Hydrogen Strategy [51] and US Inflation Reduction Act [52], actively promote research into bio-based hydrogen production, integrating these substrates into strategies for fossil-free energy systems and reinforcing their role in climate change mitigation.

The peak in Bio-H₂ research in 2022 underscores the growing focus on algae and microalgae as sustainable feedstocks, valued for their elevated hydrogen yields, CO₂ sequestration capacity, and consistent availability throughout the year. Recent studies have introduced significant innovations, including optimized photobioreactor designs that enhance light utilization and gas exchange, genetic modifications that improve metabolic pathways for increased hydrogen production, and hybrid DF-AD systems that maximize substrate conversion efficiency [53]. These advancements enhance scalability and efficiency by supporting continuous, high-density cultivation and reducing energy requirements compared to traditional sugar- or lignocellulose-based feedstocks [54]. Furthermore, the ability of algae to utilize non-arable land and integrate with wastewater treatment positions them as a low-carbon, highly effective option for large-scale biohydrogen production [55].

3.2. Analysis of Cooperation Between Countries and Regions

Over 2000 authors from 84 countries have contributed literature in this field.

Table 1. Bonds and total link strength of the top 10 countries with the most documents.

Country/Regions	Bond	Total Bond Strength	Documents	Contribution Rate (%)	Citations by Country	Population (Estimated in 2024 by UN) *	Documents Per Million Inhabitants
China	39	5428	552	27.56	16,435	1.42e + 09	0.39
India	39	3457	259	12.93	9611	1.45e + 09	0.18
United States	39	1959	122	6.09	6668	3.45e + 08	0.35
South Korea	39	1861	116	5.79	4570	5.17e + 07	2.24
Turkey	39	1500	106	5.29	4633	8.75e + 07	1.21
France	39	1489	84	4.19	3718	6.65e + 07	1.26
Malaysia	39	1319	95	4.74	2854	3.40e + 07	2.79
Brazil	39	1319	95	4.74	2854	2.12e + 08	0.45
Canada	38	1170	67	3.34	3634	3.93e + 07	1.71
Thailand	38	1099	83	4.14	2355	7.17e + 06	11.58

* The “e” in the table represents scientific notation, meaning ‘times ten raised to the power of’.

shows a summary that includes the two oldest articles, the two most-cited articles of each period, and the central theme of each period divided by the number of publications. Biohydrogen and hydrogen production were found to be linked with techniques like dark fermentation, photofermentation, production, and reactors [56,57]. At the same time, research on different raw materials used for Bio-H₂ production has changed as food and organic waste produced in households and municipal markets is now a core component of research [58,59,60], unlike in the past, when these products were not yet in use due to the lack of information on the subject.

A total of 40 of the 85 countries were listed as visualization elements (Figure 3). For instance, China (n = 552), Australia, Malaysia, the United Kingdom, and Egypt, among other countries, have collaborated extensively. In contrast, India (n = 259), Iran, Belgium, Canada, and Poland, as well as countries from America and Europe, have been deeply linked by the United States (n = 122), Poland, and Turkey. The fourth group includes countries and regions such as South Korea (n = 116), Hungary, Spain, Armenia, and Norway. Finally, the last group of countries, e.g., Japan and Thailand, have strong collaborations. Table 1 reveals that China is the world’s leading country in research output, with a total of 552; however, India is in second place, ahead of China, regarding the average annual number of publications. This indicates that China and India are the most engaged in bio-H2 production research worldwide, using AD technology. The density analysis revealed that the top three countries regarding research output, including China and India, have led research cooperation on Bio-H₂ production by AD.

3.3. Contributions by Country and Collaborations

The scientific contributions made by each country allowed the identification of the affiliations and study locations of the subjects in question. As shown in Figure 4, 84 countries have published at least one article. China (in red) is the most influential country, with 552 publications, collaborating with 37 countries, particularly the USA (in bright orange). The second most influential country is India, with 259 publications and collaborating with 31 countries, particularly South Korea and the United Kingdom.

Figure 5 illustrates the collaboration of 84 countries with the scientific literature on the subject. The darker the shade of blue, the higher the level of cooperation with other countries. This highlights more partnerships between Asia and the American continent and, to a lesser extent, with Africa and Oceania. Moreover, at least 20 countries had three collaborative research projects with authors from different countries.

Normalizing the number of scientific productions per million inhabitants, Thailand, Malaysia, and South Korea stand out. This contribution can be ascribed to academic and governmental support, the availability of appropriate substrates, and rapid technological advancements [61]. As described in Table 1, Thailand and Malaysia have exhibited a considerable increase in publications related to biohydrogen production. Both countries have set ambitious renewable energy targets, with Malaysia’s National Energy Transition Roadmap aiming for 70% renewable energy by 2050 and Thailand’s National Energy Plan 2023 seeking a 50% renewable energy ratio in new electricity generation; additionally, initiatives such as Malaysia’s National Hydrogen Economy and Technology Roadmap and collaborative projects, such as Malaysia’s H₂biscus and Thailand’s partnerships with international organizations [62], further demonstrate the commitment to advancing biohydrogen research. This upward trend reflects a boosted awareness of the significance of sustainable energy resources, driven by environmental obligations and governmental incentives to foster research in this domain.

China has also witnessed advancements in biohydrogen production techniques due to its increasing number of biogas plants. There are about 103,476 small to medium-sized biogas facilities, with a projected total of 128,976 plants expected to be operational by 2025 [63]. Recent upgrades enhance gas quality by removing impurities, while techniques like microbial electrolysis and nanobubble water are being explored to improve hydrogen yields and production efficiency [64]. These innovations contribute to renewable energy solutions and environmental sustainability and offer significant economic and environmental benefits to these areas [60].

Cooperation has occurred between different countries and regions (Figure 5). China is the country leading the research output on Bio-H₂ production using AD, with 552 documents, and is the country that has cooperated most with countries such as India, Malaysia, Australia, Egypt, and the United States. The United States ranks third with 122 documents, collaborating with Turkey, Canada, and Poland and cooperating with countries in America and Europe. Brazil ranks eighth (globally) in Latin America with 96 documents and has maintained ties with Uruguay, Mexico, Chile, and France.

The papers cited in the countries with the most publications allowed research to advance significantly. China, for instance, had 16,435 citations per country. Most of these citations were related to using different raw materials, such as molasses, sewage sludge, straw, and stem waste. These materials are frequently used in publications [48,65]. Currently, articles relating to Bio-H₂ production have been published in the same country using photofermentation from different substrates and co-substrates (using apoenzyme) [56,57,66]. Published articles led to new research on the subject. At the same time, in the United States, most of the 6668 citations per country are documents related to hydrogen and Bio-H₂ production. They differentiate from China by employing other technologies like electrohydrogenesis, anaerobic fermentation, and biological processes for producing Bio-H₂ [65,67,68]. In both countries, extensive research has been done on the biological processes of hydrogen and Bio-H₂ production [68,69].

3.4. Journals with the Highest Number of Articles

The performance and quality indices of the top ten journals on Bio-H₂ production by AD, with the most articles on the subject, are presented in

Table 2. Ranking journals by number of most relevant publications on biohydrogen production using AD technology.

Ranking	Journal	Publisher	Country	Number of Articles	SJR 2022	Quartile	Open Access Documents
1	International Journal of Hydrogen Energy	Elsevier	United Kingdom	604	1.32	Q1	All Open Access/Green Open Access/Gold Open Access/Bronze Open Access/Hybrid gold
2	Bioresource Technology	Elsevier	United Kingdom	349	2.47	Q1	All open access/Green Open Access/Gold Open Access/Bronze Open Access/Hybrid gold
3	Renewable Energy	Elsevier	United Kingdom	42	1.82	Q1	All open access/Green Open Access
4	Fuel	Elsevier	Netherlands	40	1.38	Q1	All open access/Green Open Access/Hybrid gold
5	Biomass and Bioenergy	Elsevier	United Kingdom	35	1.05	Q1	All Open Access/Green Open Access/Bronze Open Access
6	Journal of Cleaner Production	Elsevier	United Kingdom	33	1.98	Q1	All open access/Green Open Access/Hybrid gold
7	Chemical Engineering Journal	Elsevier	Netherlands	26	2.8	Q1	All Open Access/Bronze/Open Access/Green Open Access
8	Biotechnology For Biofuels	Biomed Central	United Kingdom	24	1.02	Q1	All Open Access/Gold Open Access/Green Open Access
9	Taiyangneng Xuebao Acta Energiae Solaris Sinica	Science Press	China	21	0.24	Q4	Open Access
10	Applied Energy	Elsevier	United Kingdom	18	2.91	Q1	All Open Access/Bronze Open Access/Green Open Access/Hybrid Gold Open Access

Note: Publishers and journal names have been kept in the original language as proper names.

. These journals contain 1192 of the 2003 publications analyzed (59.51% of scientific output). It also shows the performance indicators of the journals as Scimago Journal Rankings (SJR) and their respective quartile.

Table 2 presents the top ten journals with the highest number of papers published in the Scopus database. The top three journals at the forefront of scientific output are the International Journal of Hydrogen Energy, which contributes 604 articles or 30.2% of the total published articles. This journal has an SJR index 1.2 and is ranked in the first quartile (Q1). There are four quartiles: quartile 1, quartile 2, quartile 3 and quartile 4. Quartile 1 is the highest-ranked quartile. Bioresource Technology is ranked second, with 349 articles, representing 17.4% of the published papers. In this case, the SJR index is 2.35, and the journal is currently in Q1. The third journal with the most published articles is Renewable Energy, with 42 articles, equivalent to 2.1% of the total publications. It has an SJR index of 1.88 and ranks in Q1.

In terms of quartiles, the International Journal of Hydrogen Energy is in the first quartile. Unlike Taiyangneng Xuebao Acta Energiae Solaris Sinica, it has a high impact, in the fourth quartile with a lower impact index. In this research, nine out of ten journals have a high impact since they are in the first quartile. However, the impact index and influence of articles published in a journal differentiate them. Applied Energy has the highest impact (3.06) among the ten journals in Table 2, while Taiyangneng Xuebao Acta Energiae Solaris Sinica has the lowest impact (0.2). The International Journal of Hydrogen Energy obtained the highest number of citations in published articles, as shown in Table 3 [68,70,71]. All the research published in the journals is primarily related to AD and Bio-H₂ production, obtained from the keywords assigned for the search in the Scopus database.

The SJR index and quartile rankings shape perceptions of research credibility in the scientific community [72]. High-ranking Q1 journals, seen as benchmarks of prestige, attract researchers seeking wider dissemination and impact, boosting visibility and citation potential [73]. Their high publication volume speeds up knowledge growth and fosters consensus on sustainable energy challenges. Impact differences between journals like Applied Energy and Taiyangneng Xuebao Acta Energiae Solaris Sinica arise from distinct citation networks and reach. Applied Energy gains from the global readership and high citations, while Taiyangneng Xuebao serves a narrower, regional audience. This understanding helps researchers choose journals strategically, balancing academic impact with regional focus. Q1 journals secure their status with strict peer review, focus on cutting-edge topics, and interdisciplinary appeal. These practices steer article acceptance toward globally relevant trends, shaping renewable energy research scope and quality. High standards drive visibility and impact through trending topics and global collaboration [44].

A broad array of scientific disciplines underpins research into biohydrogen, as evidenced by the subject areas of the top 10 journals publishing on this topic. The most prevalent area is Renewable Energy, Sustainability, and the Environment, which is represented in nine out of ten journals, indicating a strong alignment with low-carbon energy systems. The field of Energy Engineering and Power Technology is represented in journals such as the International Journal of Hydrogen Energy and Taiyangneng Xuebao Acta Energiae Solaris Sinica, emphasizing the technical dimension of hydrogen production and integration. The subject of Chemical Engineering and Organic Chemistry is represented in journals such as Fuel and Chemical Engineering Journal, which focus on reaction mechanisms, process design, and thermodynamics. The field of Bioengineering and Biotechnology, as exemplified in Bioresource Technology and Biotechnology for Biofuels, underscores the microbial and metabolic facets of anaerobic digestion. Waste Management and Disposal is also a prominent field, especially in Bioresource Technology and Biomass and Bioenergy, supporting the role of organic waste as a key substrate. Finally, the field of Environmental Engineering, Environmental Science, and Environmental Chemistry offers a systems-level perspective, integrating biohydrogen production with environmental performance and pollution mitigation.

3.5. Top-Cited Articles

The most-cited publications were analyzed to highlight interesting topics on the selected research theme. In this context, the literature search yielded 2210 articles on Bio-H₂ production by AD worldwide. Table 3 shows the ten most-cited articles, with 5440 citations.

Four of the ten articles analyzed with the highest number of citations were published in 2004 [71,74,75]. Levin and Love’s research, published in the International Journal of Hydrogen Energy, was the most cited, with 1275 citations. The second most-cited article was published in the International Journal of Hydrogen Energy with 599 citations. The third most-cited article was Advances in Biological Hydrogen Production Processes, which had 561 citations in the International Journal of Hydrogen Energy. Only two articles were open access under this analysis. These two articles were published in Proceedings of the National Academy of Sciences of the United States of America and Environmental Science and Technology journals in 2004.

Table 3. Most-cited articles on Bio-H₂ production using AD.

N°	Article	Authors	Journals	Citations	Open Access Article
1	Biohydrogen production: Prospects and limitations to practical application	Levin and Love [71]	International Journal of Hydrogen Energy	1275	No
2	Hydrogen production from agricultural waste by dark fermentation: A review	Guo et al. [76]	International Journal of Hydrogen Energy	599	No
3	Advances in biological hydrogen production processes	Das and Veziroglu [68]	International Journal of Hydrogen Energy	561	No
4	Use of algae as biofuel sources	Demirbas [77]	Energy Conversion and Management	543	No
5	Sustainable and efficient biohydrogen production via electrohydrogenesis	Cheng and Logan [67]	Proceedings of the National Academy of Sciences of the United States of America	530	Yes
6	Biohydrogen production by anaerobic fermentation of food waste	Han and Shin [74]	International Journal of Hydrogen Energy	439	No
7	Comparison of biohydrogen production processes	Manish and Banerjee [69]	International Journal of Hydrogen Energy	385	No
8	Enhanced biohydrogen production from sewage sludge with alkaline pretreatment	Cai et al. [78]	Environmental Science and Technology	379	Yes
9	Feasibility of biohydrogen production by anaerobic co-digestion of food waste and sewage sludge	Kim et al. [75]	International Journal of Hydrogen Energy	367	No
10	Biofuels generation from sweet sorghum: Fermentative hydrogen production and anaerobic digestion of the remaining biomass	Antonopoulou et al. [79]	Bioresource Technology	362	No

Note: the journals have been kept in their original language as they are proper names and the titles and journals of each article.

Table 3. Most-cited articles on Bio-H₂ production using AD.

N°	Article	Authors	Journals	Citations	Open Access Article
1	Biohydrogen production: Prospects and limitations to practical application	Levin and Love [71]	International Journal of Hydrogen Energy	1275	No
2	Hydrogen production from agricultural waste by dark fermentation: A review	Guo et al. [76]	International Journal of Hydrogen Energy	599	No
3	Advances in biological hydrogen production processes	Das and Veziroglu [68]	International Journal of Hydrogen Energy	561	No
4	Use of algae as biofuel sources	Demirbas [77]	Energy Conversion and Management	543	No
5	Sustainable and efficient biohydrogen production via electrohydrogenesis	Cheng and Logan [67]	Proceedings of the National Academy of Sciences of the United States of America	530	Yes
6	Biohydrogen production by anaerobic fermentation of food waste	Han and Shin [74]	International Journal of Hydrogen Energy	439	No
7	Comparison of biohydrogen production processes	Manish and Banerjee [69]	International Journal of Hydrogen Energy	385	No
8	Enhanced biohydrogen production from sewage sludge with alkaline pretreatment	Cai et al. [78]	Environmental Science and Technology	379	Yes
9	Feasibility of biohydrogen production by anaerobic co-digestion of food waste and sewage sludge	Kim et al. [75]	International Journal of Hydrogen Energy	367	No
10	Biofuels generation from sweet sorghum: Fermentative hydrogen production and anaerobic digestion of the remaining biomass	Antonopoulou et al. [79]	Bioresource Technology	362	No

Note: the journals have been kept in their original language as they are proper names and the titles and journals of each article.

3.6. Keyword Analysis

The co-occurrence analysis was also investigated using the keywords of the 2003 documents obtained from the Scopus database, from which the most frequently used words by the authors were identified. Figure 6 displays the emerging keywords. The author’s keywords generate predominant themes in research on improving Bio-H₂ production using different types of organic waste (fruit and vegetables), sustainable waste, also known as orange biowaste, sewage sludge, and microalgae using techniques such as anaerobic fermentation, dark fermentation, fermentation, and AD [80,81].

The analysis results have revealed the identification of three primary groups related to AD, biohydrogen production, and biomass. The first group, named “anaerobic digestion” (with 263 occurrences), is the study area with the highest number of words related to the subject, with 26 words connected to 44 nodes. This group has focused on Bio-H₂ production from biological waste or via different types of inoculums, substrates, or municipal solid waste [82,83,84]. The second group, “biohydrogen production”, has 252 occurrences with 15 words linked to 44 nodes. This group relates to Bio-H₂ production by dark fermentation from wastewater, beet molasses, microbial fuel cells, or organic and food waste [60,76,85,86]. Finally, the third group, “dark fermentation”, with 267 occurrences, comprises seven words linked to 44 lines. This last group is related to studies aimed at producing Bio-H₂ using lignocellulosic biomass or silver coffee skin, algae such as Enterobacter cloacae, or nanoparticles [87,88,89].

The utilization of hydrogenase enzymes has significantly advanced the field of Bio-H₂ production by enhancing reaction kinetics [90]. Ongoing research continues to refine the potential of hydrogenases and nitrogenases, key catalysts in Bio-H₂ production, through enzymatic and genetic engineering [91]. The integration of Clostridium species is relevant in maximizing Bio-H₂ output, ensuring the viability and scalability of these processes for industrial applications [92]. This is due to Clostridium exhibiting a resilient fermentative metabolism, high substrate affinity, and strong acid tolerance, making it ideal for hydrogen fermentation [93]. Studies have demonstrated that pure cultures of Clostridium and co-cultures with other hydrogen-producing bacteria enhance hydrogen yields by promoting efficient electron transfer pathways and preventing metabolic inhibition [94]. Additionally, these bacteria secrete key enzymes that catalyze the degradation of complex organic compounds into fermentable substrates [95]. Advancements in metagenomics and metatranscriptomics now allow for in-depth microbial community composition and functional gene expression analysis, revealing key metabolic pathways regulating hydrogen production. Along with gene editing techniques (e.g., CRISPR/Cas9), these approaches improve efficiency by regulating microbial communities [96]. Additionally, tools such as flow cytometry, biosensors, and quantitative PCR enable precise tracking of microbial kinetics, linking substrate availability (e.g., glucose concentration) to bacterial growth rates and hydrogen yields [97]. These approaches provide actionable insights for adjusting reactor conditions and optimizing process efficiency. These methodologies offer actionable insights to adjust reactor conditions and optimizing process efficiency.

Beyond pure BioH₂, the production of biohythane and digestate presents additional benefits. Biohythane, a mixture of biohydrogen and biomethane, maximizes energy recovery, with studies reporting a 60% reduction in GHG emissions compared to single-stage systems [98]. Additionally, the valorization of digestate reduces dependence on synthetic fertilizers, contributing to circular bioeconomy frameworks [99]. Achieving industrial viability requires a rigorous assessment of energy and environmental parameters and regulatory compliance to ensure feasibility [100]. With continued research and technological advancements, biohydrogen production has the potential to become a cornerstone of the sustainable energy transition, promoting environmental conservation and long-term energy sustainability [101].

3.7. Network Analysis of Biohydrogen Production

This bibliometric network analysis reveals a clear progression in Bio-H₂ research, from foundational dark fermentation studies to sophisticated techniques involving microbial interactions (Figure 7). For future research, areas such as Direct Interspecies Electron Transfer (DIET) and microbial community structuring, combined with advanced pre-treatment methods, represent promising pathways to overcome current limitations in hydrogen yield and process stability. Additionally, integrating life-cycle assessments and cost analyses will be crucial to ensure that advancements in dark fermentation align with global sustainability and energy transition objectives. This framework offers a roadmap for researchers to explore cutting-edge applications in Bio-H₂ production while maintaining a focus on environmental impact and economic feasibility.

Cluster #2 (green) highlights AD and Bio-H2 production advancements, focusing on bioenergy from organic waste in bioreactors. Emphasis is on optimizing microbial processes, such as the activity of Clostridium in dark fermentation, to improve hydrogen yields and support circular economy goals. Cluster #0 (red) shows “dark fermentation” as a significant focus in Bio-H₂ research due to its adaptability to various feedstocks and potential in waste-to-energy systems. Despite its simplicity, challenges like low hydrogen yields and by-product accumulation drive research toward microbial innovations and process optimization. Cluster #2 underscores “volatile fatty acids” as key by-products in dark fermentation.

These can hinder microbial activity but are also potential bioenergy resources. Sewage sludge, a rich source of organic material, is increasingly being considered for co-fermentation alongside other organic waste materials, such as food waste. Hydrogen fermentation, a specific metabolic pathway where microbes break down organic compounds to produce Bio-H₂, is gaining attention due to its potential to convert sewage sludge into valuable bioenergy. Research explores various pretreatment methods to manage inhibitors, like fatty acids, that might suppress microbial growth and activity in these fermentation processes. This includes optimizing conditions to increase microbial diversity, which plays a key role in enhancing the efficiency and stability of H₂ production.

Clusters #4 and #6 reflect a growing interest in sustainable feedstocks like food waste, which when co-fermented with sewage sludge, can further improve hydrogen yields by providing complementary nutrients for a broader range of microorganisms [102]. Efforts to integrate waste materials such as sewage sludge and food waste into hydrogen fermentation systems align with the principles of the circular economy, aiming to reduce waste and produce valuable energy while minimizing environmental impact [103,104]. The ultimate goal is to refine metabolic pathways in microbial communities to boost cost-effectiveness and maximize energy yield, positioning Bio-H₂ as a scalable, environmentally sound renewable energy source [105,106].

3.8. Main Research Areas

After categorizing the published articles based on their main topics, they were divided into four periods: (a) period I (2003–2007), (b) period II (2008–2012), (c) period III (2013–2017), and the last period containing the last six years (2018–2024). As shown in

Table 4. Compilation of articles from the oldest to the most cited with the respective topics of interest according to the period.

	Older Articles	Most-Cited Articles	Topics of Interest for the Period
P E R I O D I	Using filtrate of waste biosolids to effectively produce byo-hydrogen by anaerobic fermentation [108]	Biohydrogen production: prospects and limitations for practical application [71].	− Production of biohydrogen from organic food or animal waste such as cow dung, using techniques such as anaerobic fermentation, electrohydrogenesis in which they used the bacterium Citrobacter sp. Y19.
	Biohydrogen production from starch in wastewater under thermophilic conditions [109].	Sustainable and efficient production of biohydrogen by electrohydrogenesis [67].
P E R I O D II	Simultaneous production of biohydrogen and treatment of starch-containing wastewater in a mixed-culture acid-generating expanded granular sludge bed reactor for long-term operation [70].	Hydrogen production from agricultural residues by dark fermentation: a review [76].	− Agricultural waste (sugarcane bagasse, cellulose, and algae). − Biofuel is produced by dark fermentation.
	Light fermentation of dark fermentation effluents for biohydrogen production by different Rhodobacter sp. at different initial volatile fatty acid concentrations (VFA) [110].	Advances in biological hydrogen production processes [68].
P E R I O D III	Feasibility study of biohydrogen production from pressed sludge using UASB processes and assessment of operational parameters [111].	Lignocellulosic materials in biohydrogen and biomethane: impact of structural characteristics and pretreatment [112].	− Microbial ecologies, microalgae, lignocellulosic materials, or nickel nanoparticles. − Dark fermentation, photofermentation, thermophilic anaerobic digestion. − Fixed-bed reactors
	Characterization by length heterogeneity-PCR of a hydrogen-producing community derived from obscure fermentation using coastal lake sediments as inoculum [113].	A biorefinery from Nannochloropsis sp. microalga—Extraction of oils and pigments. Production of biohydrogen from the leftover biomass [114]
P E R I O D IV	Sustainable bioenergy from residues and waste biofuels [115].	The waste-energy nexus for the circular economy and environmental protection: recent trends in hydrogen energy [116].	The aim is to optimize and determine the appropriate conditions for biohydrogen production from biowaste, solid or organic, and organic waste.
	Enhanced biohydrogen production from a nutrient-free anaerobic fermentation medium with rice straw pretreated with edible fungi [107].	Free nitrous acid promotes hydrogen production from the dark fermentation of activated sludge [117].

, Bio-H₂ production has used different types of feedstocks, including organic, agricultural, and food waste, produced in homes, factories, businesses, or municipalities, among others [67,76]. Dark fermentation is one of the most widely used techniques for producing Bio-H2, as it recovers Bio-H₂ through AD [107].

3.9. Scientific Progress in Biohydrogen: Innovations in Microbial Pathways, Feedstock Additives, and Environmental Strategies

This section explores recent advancements in Bio-H₂ production, focusing on three core areas: process optimization, feedstock and additive selection, and environmental sustainability (

Table 5. Top keywords with the strongest citation bursts.

Keywords	Year	Strength	Begin	End	2003–2024
Genetics	2015	12.06	2015	2017
Molecular Biology	2015	4.36	2015	2015
Bioremediation	2017	3.82	2017	2017
Electron Transport	2021	12.84	2021	2024
Pre-Treatments	2022	25.31	2022	2024
Lignin	2013	11.56	2021	2024
Maize	2021	7.79	2021	2024
Lignocellulose	2013	10.23	2022	2024
Iron	2022	6.62	2022	2022
Nanoparticles	2021	11.52	2021	2024
Additives	2022	4.21	2022	2022
Energy Yield	2023	5.57	2023	2024
Sustainable Development	2022	9.49	2022	2024
Cost Effectiveness	2022	7.43	2022	2024
Greenhouse Gases	2023	8.23	2023	2024

Note: The light blue bars represent the duration of keyword activity. The red color tones indicate periods of citation bursts, with different shades reflecting variations in burst intensity.

). The first set of keywords reflects a progression in research priorities, moving from foundational genetic and molecular biology towards enhancing the efficiency of Bio-H₂ production. Initial genetic advances laid the groundwork by modifying microorganisms to increase hydrogen yields. Over time, the focus on Bio-H₂ production via AD has shifted from foundational genetic studies to process optimization, with DIET emerging as a recent mechanism concerning other interspecies electron transfer IET processes [118]. DIET facilitates direct electron exchange between syntrophic microbes such as Geobacter and Methanosaeta through conductive pili and cytochromes, bypassing traditional hydrogen/formate intermediates and enhancing substrate conversion efficiency [119]. DIET also contributes to reduced VFA accumulation, promoting microbial resilience and shorter hydraulic retention times [120].

The second set emphasizes that feedstock selection significantly shapes process performance, i.e., lignocellulosic biomass offers high theoretical yields up to 17.5 gH₂/(100 g_biomass) [121]. However, it requires intensive pretreatment. In contrast, FW, which is rich in fermentable sugars, delivers faster hydrogen production with yields ranging from 4.22 mL/g VS to 42.61 mL/g VS, depending on the FW content (41.52–103.8 g VS/L, respectively) but may present logistical challenges [122]. Effective pretreatment boosts biomass digestibility and hydrogen yields. Thermal and alkaline methods break down complex structures [123], though thermal processes are energy-demanding and alkaline treatments generate waste. Additionally, iron and nanoparticle additives enhance microbial activity and stabilize AD processes. Iron acts as an electron acceptor and boosts key enzymatic activities, while nanoparticles stabilize the process by regulating pH, promoting microbial growth, and improving substrate availability [120]. For instance, zero-valent iron nanoparticles (nZVI), magnetite, and activated carbon further accelerate microbial syntrophy and stabilize REDOX conditions [124]. However, potential issues such as nanoparticle aggregation or toxicity at high dosages require control.

The final group’s focus on environmental and sustainability aspects underscores the multidimensional approach required for Bio-H₂ production. Evaluating energy yield is crucial for assessing efficiency and scaling Bio-H₂ as a renewable energy source. Sustainable development and greenhouse gas reduction goals reflect the process’s environmental benefits, particularly in reducing carbon footprints. Cost-effectiveness, on the other hand, is essential for financial viability, balancing production costs with energy output to ensure competitiveness. These aspects collectively advance Bio-H₂ as a practical and sustainable energy source that aligns with environmental targets without compromising economic feasibility.

Together, these advancements position Bio-H₂ as a promising energy solution with both ecological and economic benefits. By refining production processes and prioritizing sustainable feedstocks and additives, Bio-H₂ can contribute to a low-carbon economy.

3.10. Advancing Sustainability with Biohydrogen and Anaerobic Digestion

Table 6. Linkage of anaerobic digestion and biohydrogen production with sustainable development goals.

Stage of AD-BioH2	Relevant Sustainable Development Goals	Key Contributions/Benefits
Waste Collection and Sorting		Minimizes landfill waste; promotes recycling and resource efficiency; improves urban waste management.
Anaerobic Digestion Process		Converts organic waste into renewable energy (biohydrogen); reduces greenhouse gas emissions through waste valorization.
Biohydrogen Utilization		Provides a clean fuel alternative to fossil fuels; supports sustainable industrial processes and technological innovation.
Digestate Utilization		Produces nutrient-rich digestate for fertilizer, reducing reliance on chemical fertilizers; enhances soil quality and supports sustainable agriculture.
Technology Innovation and Infrastructure Development		Encourages research and development; improves process efficiencies; fosters integration of sustainable energy systems into urban infrastructure.

The SDG icons are used here for illustrative purposes, referencing the official United Nations Sustainable Development Goals. Icons and their descriptions are available at https://sdgs.un.org/goals (accessed on 11 January 2024).

summarizes the key stages of AD and BioH₂ production, highlighting how each stage aligns with specific Sustainable Development Goals (SDGs). This illustrates the direct and indirect contributions of AD-BioH₂ systems to global sustainability targets, focusing on waste management, clean energy generation, and technological innovation.

The first stage is the waste collection and sorting; its effectiveness is fundamental to obtaining high-quality feedstock for AD. By ensuring that organic waste is separated from non-recyclable materials, the process enhances resource efficiency and reduces landfill volumes. This stage directly supports SDG 12 (Responsible Consumption and Production) and SDG 11 (Sustainable Cities and Communities). For example, Dell’Orto and Trois [125] demonstrated that optimized waste segregation improves overall system efficiency and reduces contamination.

This step is followed by the AD process. The efficiency of the transformation of organic waste into BioH₂ improvements in reactor design [126] and process control directly contributes to SDG 7 (Affordable and Clean Energy) and SDG 13 (Climate Action). Then, the next stage is BioH₂ utilization, offering a sustainable instrumental in powering industrial applications [127]. This stage aligns with SDG 7 and SDG 9 (Industry, Innovation, and Infrastructure). It is followed by potential use of digestate, which can be applied as a biofertilizer, enhancing soil quality and reducing the dependency on synthetic fertilizers [40]. This practice supports SDG 2 (Zero Hunger) and reinforces SDG 12.

Finally, scaling up biohydrogen production from concept to reality requires ongoing innovation in technology and infrastructure. One major innovation is the development of two-stage AD systems optimized for hydrogen [128]. Such innovations illustrate how infrastructure development (SDG 9) is enabling larger-scale biohydrogen generation from existing facilities (like wastewater treatment plants), which are common in cities (supporting SDG 11). Early results from pilots and modeling studies indicate that these systems can produce substantial hydrogen yields without sacrificing methane production [129]. Another area of innovation is biogas upgrading and gas grid integration. As demonstrated in China and Europe, large-scale biogas can be upgraded via scrubbing or membrane separation to biomethane for grid injection [130]. Building on this, some projects are exploring pressure swing adsorption and methanation units that combine H₂ with CO₂ from biogas to boost methane output [131]. These advances aim to make biohydrogen a viable component of the clean energy mix in the coming decades.

4. Analysis of the Current Practices for Biohydrogen Production

This section summarizes a deeper analysis of the trending topics conducted to provide a complete overview of biohydrogen production. Key concepts, methodologies, and relevant case studies that illustrate the practical applications are detailed to deepen the reader’s understanding of the important trends and further research opportunities.

4.1. Applications of AD in Biohydrogen Production

The currently trending topics reflect the frequency of the keywords used in the research. A co-occurrence analysis of the keywords presented in Section 3.6 grouped these trending topics into eight classes, as shown in Figure 8. The first group, with 53% frequency compared to other groups, focuses on the main bioenergy outputs in AD. The second group, at 10%, is centered around the key biomass degradation and fermentation indicators for Bio-H₂ production by AD. The third group, also at 10%, examines the factors affecting Bio-H₂ production kinetics in AD systems. The fourth group, at 10%, highlights the diversity of biomass feedstocks for Bio-H₂ production via AD. The fifth group, at 6%, looks at the Bio-H₂ production pathways and process conditions in AD. The sixth group, at 4%, reveals the AD reactor configurations for Bio-H₂ production. The seventh group, at 4%, examines the main factors influencing Bio-H₂ production in AD systems. Finally, the eighth group, also at 4%, explores common microbial strains for Bio-H₂ production in AD studies.

4.2. The Main Bioenergy Outputs in AD for Biohydrogen Production

Over the last two decades, hydrogen has emerged as the most researched topic about AD, surpassing methane, energy, and ethanol production (Figure 8a). Energy recovery ranks second in priority. This trend can be attributed to a variety of factors, including a global shift towards renewable energy sources and sustainable fuel generation [132], the versatility and cleanliness of hydrogen as an energy carrier, and the increasing interest in hydrogen-based technologies and fuel cells [133]. Advancements in microbial community profiling and molecular biology tools have enabled a better understanding and optimization of the AD process, leading to a more targeted focus on specific products such as hydrogen and energy recovery [134]. Additionally, the optimization of AD through the response surface methodology and pretreatment techniques has likely bolstered the production of hydrogen and energy recovery [135]. Lastly, the growing interest in enhancing methane yield and biogas production using various pretreatment methods and co-digestion approaches may have indirectly influenced the shift toward hydrogen and energy recovery.

4.3. Key Biomass Degradation and Fermentation Indicators for Biohydrogen Production by AD

The primary focus in studying the indicators for Bio-H₂ production by AD has been volatile fatty acids such as butyric and propionic acids (Figure 8b). Butyric, lactic, and propionic acids are intermediate products of AD and fermentation processes. These acids are particularly important as they indicate the efficiency of the process and promote methanogen activity, ultimately impacting biogas yields [136]. The concentration of VFAs depends on the feedstock and can impact the pH and alkalinity balance of the AD system [137]. Their concentrations indicate the metabolic pathways involved in biomass degradation and Bio-H₂ production. Monitoring these acid levels helps evaluate the efficiency of fermentation and the microbial community dynamics in the system.

To complement this focus, research has also examined parameters such as Chemical Oxygen Demand (COD), total sugars, acetic acid, lactic acids, and volatile solids. It is necessary to monitor the sugar content during AD as it plays a crucial role in microbial fermentation. This information determines the number of fermentable sugars available to hydrogen-producing microorganisms, which directly affects the efficiency and yield of Bio-H₂ production [138]. COD is a critical measurement of the organic content in the substrate. Higher COD values indicate the presence of organic compounds that anaerobic microorganisms can digest to produce Bio-H₂ [89]. Regarding acetic acid concentration, its monitoring is essential to assess the acetogenesis pathway’s contribution to Bio-H₂ production and substrate utilization efficiency. Acetogenic bacteria can convert acetic acid into Bio-H₂ [139]. Volatile solids represent the organic matter content that can decompose under anaerobic conditions. Monitoring volatile solids tracks the progress of organic material degradation and biomass conversion into biogas components, including Bio-H2. Changes in volatile solids indicate the progress of substrate utilization and the general efficiency of Bio-H₂ production [140].

The target of monitoring these indicators is to optimize AD processes for optimal energy recovery, with advancements in pretreatment technologies and biorefinery processes [141]. Moreover, there is a growing interest in generating value-added chemicals and biofuels from biomass-derived substrates [142], driving investigations into the physical–chemical properties of both the feedstocks and the effluent of AD [143]. Researchers aim to optimize conversion processes for increased production of specific biofuels and added-value products from AD by-products.

4.4. Key Factors Affecting Biohydrogen Production Kinetics in AD Systems

The operational conditions studied in AD processes have advanced over time. Historically, retention time has been a key parameter influencing process efficiency (Figure 8c), and its relevance remains widely acknowledged in AD research [144]. However, recent studies have shifted attention toward the lag phase, highlighting an emerging interest in the early stages of bacterial growth. This transition stems from advancements in microbiological techniques that have deepened our understanding of microbial dynamics and underscored the importance of early-phase optimization [145]. High-resolution tools such as 16S rRNA sequencing and metagenomic analyses have made it possible to identify dominant microbial communities involved in hydrolysis and acidogenesis [146]. These insights allow for more targeted operational adjustments. For instance, optimizing environmental conditions during the lag phase can accelerate microbial activity, reduce startup time, and stabilize reactor performance [147].

The connection between substrate availability and microbial growth is increasingly understood through predictive models and experimental data. Tools such as the Monod equation help anticipate microbial responses to different substrate levels, informing dosing strategies that enhance hydrogen yields [148]. This reflects the growing interest in microbial kinetics, particularly in relation to glucose concentration and growth rates [149]. Furthermore, temperature and the carbon-to-nitrogen molar ratio (C/N) have been highlighted as critical factors in determining optimal AD conditions, reflecting the ongoing efforts to optimize process parameters for efficient reactor operation [150].

Emerging methodologies, including microfluidics, respirometry, and real-time molecular tracking provide a clearer view of how microbial populations react to operational changes. By aligning these insights with metagenomic data, researchers can more precisely refine substrate dosing and environmental controls [151]. Altogether, these microbiological advances are paving the way for more responsive and efficient AD systems, positioning microbial data as a central pillar in the future of biohydrogen production.

4.5. Diversity of Biomass Feedstocks for Biohydrogen Production via AD

From 2003 to 2024, the most commonly used feedstocks for AD to recover Bio-H₂ include wastewater, municipal organic waste, FW, dairy products like cheese whey, and lignocellulosic biomass sources such as wheat straw and corn stover (Figure 8d). The increasing emphasis on sustainable waste management and renewable energy sources has supported research into utilizing organic waste streams such as municipal organic waste and food waste for Bio-H₂ [152]. The potential for Bio-H₂ recovery from wastewater aligns with the growing interest in wastewater treatment and resource recovery in the last decades. The use of dairy industry by-products like cheese whey for Bio-H₂ production may have been driven by the need for waste stream valorization [153]. Cheese whey and other dairy industry by-products are rich in organic compounds such as lactose, proteins, and lipids, making them an ideal substrate for microbial fermentation [154]. Additionally, the AD of cheese whey generates valuable by-products such as biofertilizers or organic acids [155].

On the other hand, innovations in pretreatment techniques may have influenced the use of lignocellulosic biomass sources like wheat straw and corn stover for Bio-H₂ production [156,157]. Lignocellulosic biomass is an abundant and sustainable resource. Since the advancements in the AD process, microbial enzymes can break down cellulose into fermentable sugars, making it an invaluable substrate for Bio-H₂ production [158].

4.6. Biohydrogen Production Pathways and Process Conditions in AD

This study delves into the various anaerobic fermentation methods utilized in AD to produce Bio-H₂ and their corresponding conditions (Figure 8e). Dark fermentation is the most extensively explored among the groups composed of dark fermentation, photo fermentation, mesophilic conditions, and thermophilic conditions, in descending order. Research articles indicate that dark fermentation has a frequency of approximately 1200 by 2024, while the other methods have frequencies lower than 100. This suggests that dark fermentation has gained significant attention in the past twenty years.

The extensive exploration of dark fermentation for Bio-H₂ production through AD in the last two decades can be attributed to its potential for efficient Bio-H₂ production [140]. This method has been studied extensively in various conditions, including mesophilic and thermophilic environments, as evidenced by the research articles [157,158,159]. These studies have explored the optimization of process parameters, the production of volatile fatty acids, and the effects of temperature on Bio-H₂ production, highlighting the significant attention given to dark fermentation.

Fermentation is the process that offers the most advantages and has an enormous potential to replace fossil fuels owing to its ability to produce biofuels sustainably and efficiently [160]. Two major stages can be conducted for the production of Bio-H2, photofermentation, and dark fermentation.

Photofermentation is hydrogen production after photosynthesis powered by sunlight as the energy source [161]. Some studies suggest that this technique is more advantageous than other available routes [162,163]; the following Equation (1) describes hydrogen production using this technique.

$$16 ATP+N_2+16H_{2}O+10H^{+}+8e^{-}\to 16 ADP+2N{H}_4^{+}+16pi+H_2$$

(1)

Light energy is vital at this stage, leading to electron splitting [164]. After separation, the products are extracted from the organic substrate by photocatabolism. Electrons are generated from endogenous substrates by catabolism and then delivered to the plastoquinone group in PSI and PSII. At this stage, light energy is assimilated by the PSI and helps generate electrons.

Dark fermentation, also known as black fermentation, is a more studied process for Bio-H₂ production (Figure 8) [157]. Hydrolysis converts complex materials into more straightforward products. One advantage of this process is that different substrates, such as glucose, cellulose, sucrose, and starch, enhance the hydrogen production rate. Researchers are using machine learning (ML) to predict how much Bio-H₂ can be produced from wastewater using a dark fermentation process, considering the concentrations of acetate, butyrate, and ethanol, along with the presence of iron (Fe) and nickel (Ni) [165].

Dark fermentation is a technique that recovers Bio-H₂ in the first three stages of AD: hydrolysis, acidogenesis, acetogenesis. As described above, the organic matter is transformed into different compounds during each stage, culminating in Bio-H₂ production.

4.7. AD Reactor Configurations for Biohydrogen Production

The production of Bio-H₂ using AD has been mainly studied using batch reactors, followed by continuous stirred tank reactors (CSTRs), with a difference in frequency of around 50% (Figure 8f). Other reactors, such as the Upflow Anaerobic Sludge Blanket (UASB) reactor and the fluidized bed reactor, are also used, but not as frequently.

The notable difference of around 50% in frequency can be credited to several factors. One of them is the widespread use of batch reactors in research on Bio-H₂ production due to their versatility and ease of operation. Batch reactors allow for studying specific parameters and conditions in a controlled environment, making it easier to investigate Bio-H₂ production under varying conditions such as temperature, pH, and substrate concentration.

Another reason for the widespread use of batch reactors in Bio-H₂ production research is their suitability for kinetic studies. Batch reactors enable researchers to monitor Bio-H₂ production kinetics, providing valuable data on reaction rates, substrate utilization, and product formation. These data are crucial for understanding the underlying mechanisms of Bio-H₂ production and optimizing the process for enhanced efficiency in the early configuration steps [141].

In batch reactors, the reactants are charged in a single operation; then the AD reactions take place. After AD, the reactor is emptied, and a new batch is followed. This type of reactor is suitable for processes with a limited quantity of product or where the reaction is exothermic and needs to be cooled before continuing [166]. However, sequential batch reactors require frequent emptying and preparation, which limits their processing efficiency, resulting in a more significant investment in time and resources than continuous reactors. This type of reactor may be best suited for pilot-scale Bio-H₂ production as the process has limitations on an industrial scale.

The Continuous Stirred Tank Reactor (CSTR) is widely used in chemical and biological processes, as it enables the control of the rate of reaction and, therefore, the achievement of an optimum conversion to Bio-H₂ [167]. The CSTR constantly stirred the reactive mixture in a cylindrical tank to ensure adequate homogenization and efficient mass transfer [168]. The material or biomass continuously enters and exits the reactor, thereby maintaining a constant concentration of reactants and products inside the tank [169]. The CSTR reactor can produce hydrogen due to a process known as alcoholic fermentation [170,171]. In this process, a bacterial strain is added to a sugar-containing culture medium, and stirring is performed to maintain uniform mixing [172].

The UASB reactor uses an anaerobic sludge blanket that flows towards the reactor surface. In this reactor, the microorganisms used to carry out the AD attach themselves to the sludge, producing Bio-H₂ in an anaerobic environment [173]. In fluidized bed reactors, a gas separation system is used to recover Bio-H₂ and biomethane produced in an anaerobic environment [174].

The less concurrent use of reactors such as UASB reactors and fluidized bed reactors in Bio-H₂ production research may be due to their specific applications and operational complexities. UASB reactors are commonly employed in wastewater treatment and biogas production [159], and their adaptation for Bio-H₂ production may require additional modifications and optimizations. Similarly, fluidized bed reactors, while offering advantages such as enhanced mass transfer and microbial attachment, may present challenges in terms of reactor design, operation, and control, leading to their less frequent utilization in Bio-H₂ production research [175].

4.8. The Main Factors Influencing Biohydrogen Production in AD Systems

This review shows that in the past two decades, there has been increased focus on the ideal conditions for operating a reactor, with particular attention paid to various factors such as carbon sources, microbial metabolic pathways, soluble metabolites, mass transfer, and fermentation effluent. The attention paid to these factors reflects the complexity of the Bio-H₂ production process (Figure 8g).

The emphasis on carbon sources in Bio-H₂ production research is driven by the need to identify substrates that can support high Bio-H₂ yields [176]. Various carbon sources, including carbohydrates, organic acids, and lignocellulosic materials [177,178], have been investigated for their suitability in Bio-H₂ production through AD. Studies have focused on the selection and optimization of carbon sources to promote the growth of hydrogen-producing microorganisms and maximize Bio-H₂ production rates [176].

Exploring microbial metabolic pathways has also gained notoriety due to its importance in understanding the biochemical processes involved. This review also shows significant research into the metabolic pathways of hydrogen-producing microorganisms, such as dark fermentative bacteria and photosynthetic microorganisms to understand the mechanisms underlying Bio-H₂ production, which is essential for designing and operating reactors that can increase the activity of hydrogen-producing microorganisms [179].

The study of soluble metabolites is also crucial in optimizing reactor conditions. Soluble metabolites, including volatile fatty acids and alcohols, play a critical role in Bio-H₂ production as precursors for hydrogen generation [180].

4.9. Microbial Strains for Biohydrogen Production in AD Studies

Based on this comprehensive review, it was found that mixed cultures are more commonly used than pure bacterial strains for Bio-H₂ production (Figure 8h). The bacteria that are frequently used in AD include Clostridium acetobutylicum, Clostridium sp, Enterobacter aerogenes, Rhodobacter sphaeroides, Escherichia coli, Clostridium beijerinckii, Rhodopseudomonas palustris, Rhodobacter capsulatus, and Thermoanaerobacterium thermosaccharolyticum.

This review also revealed several reasons for using mixed cultures in AD for Bio-H₂ production, including that these cultures comprise a variety of microorganisms, which enables enhanced substrate utilization, metabolic diversity, and resilience to environmental changes [135]. This approach facilitates the efficient conversion of diverse substrates into Bio-H2, making it particularly suitable for the utilization of complex organic materials as feedstock in AD processes.

On the other hand, the pure strains of microorganisms mentioned above have been frequently employed in Bio-H₂ production through AD due to their unique metabolic capabilities and adaptability to anaerobic conditions. For example, Clostridium acetobutylicum, Clostridium sp., and Clostridium beijerinckii are well known for their ability to ferment a wide range of organic substrates into Bio-H₂ and other valuable by-products like acetate, butyrate, and ethanol through the dark fermentation process [34,181]. Clostridium utilizes the sugar and organic compounds present in the substrate to produce Bio-H₂.

Enterobacter aerogenes and Escherichia coli are facultative anaerobic bacteria that can produce Bio-H₂ through mixed acid fermentation under specific conditions. They can utilize a variety of substrates to generate Bio-H₂ as one of the fermentation end products [35]. Escherichia coli bacteria are commonly used for Bio-H₂ production due to their ease of cultivation and ability to utilize various carbon sources [36].

Rhodobacter sphaeroides, Rhodopseudomonas palustris, and Rhodobacter capsulatus are photosynthetic bacteria capable of producing Bio-H₂ through photofermentation [182]. These strains utilize light energy to convert organic substrates into Bio-H₂ in the presence of specific pigments like bacteriochlorophyll [183].

Thermoanaerobacterium thermosaccharolyticum is a thermophilic bacterium known for its Bio-H₂ production capabilities at elevated temperatures. This bacterium can efficiently metabolize various sugar substrates under thermophilic conditions, making it well suited for Bio-H₂ production processes operating at higher temperatures [184].

These microorganisms exhibit diverse metabolic pathways for Bio-H₂ production, including fermentative pathways, photosynthetic processes, and anaerobic respiration, thereby enabling the utilization of a wide range of substrates for Bio-H₂ generation.

4.10. Occurrences of Lab, Industry, and Pilot Scale in Publications

Figure 8i shows the progression of publications across three scales: lab, pilot, and industrial, with lab-scale research leading the group. Lab-scale studies are important for establishing foundational experimental methods and advancing biohydrogen production through AD. They test hypotheses, optimal conditions, and pretreatment methods and drive the development of innovative technologies for sustainable energy [185,186]

Pilot-scale publications bridge the gap between theoretical research and practical applications, evaluating the feasibility of lab-developed technologies and revealing operational challenges in real-world conditions [129]. The growth in pilot studies indicates a recognition of the need for scalable solutions in industrial AD applications.

Research at an industrial scale is less common than lab and pilot studies. This can be due to several challenges, such as high costs, complexity in maintaining process stability, and greater resource demands, which make industrial research riskier and less accessible [6]. Additionally, compliance with stringent regulations and environmental standards complicates projects and increases costs. The longer timeframes required for industrial research make it less attractive for academics seeking quicker results, leading to a preference for smaller, more manageable studies that allow for process refinement [186].

In biohydrogen production, maintaining stable conditions in larger reactors is complex due to issues like foam buildup and substrate mixing problems [29]. In some cases, the seasonal availability of substrates poses a challenge for continuous operation, which can be mitigated by co-digestion with year-round available substrates like manure [186]. Nevertheless, the upward trends reflect the interconnection between laboratory investigations and practical applications in AD. As the body of literature expands, it emphasizes the importance of integrating findings from laboratory investigations to address challenges encountered at pilot and industrial scales.

5. Future Perspectives and Final Remarks

5.1. Integration of Advanced Tools Based on Artificial Intelligence into Biohydrogen Production

Artificial intelligence (AI) has emerged as a powerful tool to address challenges by enabling data-driven insights and automation. AI can enhance Bio-H₂ production across various dimensions, including LCA, substrate optimization, and real-time monitoring. This discussion delves into how AI-driven approaches can foster more efficient and sustainable Bio-H₂ production practices.

Applying advanced AI-based tools in Bio-H₂ production represents an innovative approach to enhancing efficiency, sustainability, and scalability. AI and ML technologies enable the development of predictive models, real-time monitoring, and data-driven decision-making, which are key factors in optimizing production and minimizing environmental impact.

One of the main contributions of AI to Bio-H₂ production is process optimization, as ML algorithms can analyze large datasets to determine the optimal conditions for microbial fermentation, substrate selection, and operational parameter regulation. This not only increases hydrogen production but also optimizes resource utilization [187]. Additionally, AI-powered adaptive control systems can automatically adjust conditions based on real-time data, improving system stability and performance.

Moreover, LCA with AI plays a crucial role in evaluating the environmental impact of Bio-H₂ production. Integrating AI into LCA methodologies enables a more precise analysis of emissions, energy consumption, and long-term sustainability, facilitating more eco-friendly and responsible decision-making [188,189].

AI also contributes to early fault detection and predictive maintenance, reducing downtime and operational risks. By analyzing patterns in system behavior, AI tools can anticipate potential failures before they occur, lowering costs and enhancing process reliability [190,191].

As advancements in AI continue, the synergy between intelligent automation and biohydrogen production is expected to drive a new era of clean energy solutions. By leveraging these cutting-edge technologies, Bio-H₂ production can become more efficient, sustainable, and economically viable, contributing significantly to the global transition towards renewable energy.

5.2. Life Cycle Assessment and Environmental Impact Modeling

In Bio-H₂ production, LCA is crucial for evaluating the environmental impacts of different stages, from feedstock cultivation to energy conversion and waste management. AI models, particularly ML algorithms, can process complex LCA data to provide a comprehensive picture of carbon footprints, resource consumption, and emissions. For instance, [192] work demonstrates ML-based LCA tools can predict and analyze the environmental impact of various operational changes, supporting decisions to minimize carbon emissions and energy use. Additionally, integrating life cycle data with AI can enable real-time monitoring of environmental metrics, allowing operators to adjust parameters to maintain alignment with sustainability goals [193]. Therefore, integrating ML with LCA has significantly improved the accuracy and depth of environmental impact analyses. Advanced ML models—such as random forest, extreme gradient boosting, support vector machine, deep learning, and artificial neural networks—have been shown to accurately predict key life cycle inventories (e.g., yield metrics and reagent consumption) [194]. In addition, optimization algorithms like genetic algorithms, particle swarm optimization, and simulated annealing have demonstrated around 20% improvement in yield optimization [195]. These techniques enhance data quality and reliability, thereby enabling comprehensive process optimization by integrating techno-economic analysis with LCA [196]. In biohydrogen production, ML-driven predictive modeling is employed to analyze experimental data, while process optimization methodologies pinpoint variables that require adjustment, such as in pretreatment methods [88]. Overall, the integration of ML with LCA provides a robust framework for accurately evaluating environmental impacts and supports informed decision-making for sustainable BioH₂ production.

5.3. Substrate Selection and Mixture Optimization

One of the critical determinants of Bio-H₂ yield in AD is the selection and mixture of substrates. AI algorithms, including genetic algorithms and reinforcement learning models, can significantly enhance substrate optimization by identifying the ideal combinations of feedstock to maximize hydrogen yield and minimize costs [197,198]. For example, research indicates that specific substrate concentrations, such as glucose, significantly influence Bio-H₂ yields [199]. By simulating various substrate mixtures, these AI tools enable researchers to achieve resource-efficient Bio-H₂ production while addressing cost constraints associated with feedstock sourcing [200]. Additionally, AI-based optimization can consider the biodegradability and nutrient content of substrate. Optimizing substrate mixtures can ultimately contribute to cleaner and more cost-effective Bio-H₂ production.

5.4. Real-Time Monitoring and Anomaly Detection

Real-time monitoring of AD processes is crucial for maintaining operational stability and preventing failures. ML models can identify deviations from optimal operating conditions by analyzing real-time data streams, allowing timely interventions [201]. This capability is relevant in Bio-H₂ production, where maintaining specific parameters is vital for maximizing yield [202]. ML models, particularly predictive algorithms such as k-nearest neighbors and logistic regression, are employed to forecast reactor performance by continuously monitoring key parameters (total carbon, pH, temperature, oxidation–reduction potential, biogas composition, and fluid flow rates) [203]. These models isolate the critical variables needed to maintain process stability and efficiency by evaluating feature importance. Moreover, time-based data processed by models like random forest and artificial neural networks capture the microbial acclimation period, providing a dynamic view of process stability [204]. Continuous monitoring software, often web-enabled, tracks fermentation dynamics in real-time and identifies correlations between parameters (e.g., medium conductivity and BioH₂ evolution) to optimize the production environment conditions [205,206]. When deviations from optimal conditions are detected, these ML models promptly trigger alerts or automated responses to adjust operational parameters, mitigating uncertainties in the non-linear AD process [207]. This integrated approach ensures dynamic process control and enhances overall reactor efficiency.

Furthermore, integrating AI in monitoring can incur significant operational costs, as presented by [208]. However, the substantial upfront investment in sensor networks, data management, and automated control systems is primarily offset by the financial benefits of reduced downtime, lower maintenance, and minimized resource wastage [209]. AI and ML enhance biofuel production by accurately predicting optimal operating conditions and calibrating processes in real-time, thereby reducing experimental workload and associated costs [210]. Continuous monitoring systems prevent overproduction and waste and could achieve 15–25% operational cost reductions [197,198]. Enhanced predictive accuracy further improves yield and product quality, supporting robust techno-economic analyses that justify these investments [211]. Moreover, ML applications in cow dung biogas production offer a more advanced, cost-effective strategy [210]. These improvements justify the initial expenditures and underscore the economic viability of integrating AI and ML in anaerobic digestion systems for biohydrogen production.

Despite the promising benefits of AI applications in Bio-H₂ production, several challenges remain. Data quality and availability are significant concerns, as well as the high computational requirements of some AI algorithms. Addressing these challenges requires coordinated efforts among industry stakeholders, researchers, and policymakers. Establishing industry-wide standards for data exchange, monitoring practices, and AI algorithm validation can ensure seamless interoperability [212], while dedicated workshops and collaborative platforms would facilitate the sharing of best practices and technological advancements [213]. Researchers and industry partners can jointly undertake pilot projects to demonstrate improved substrate utilization and operational efficiency at pilot and commercial scales [214] and policymakers can support these initiatives with targeted funding, incentives, and regulations that promote sustainable practices [215] by collaborating with research centers and associations [216]. Together, these collaborative actions lead to optimized reactor performance that reduces GHG and enhances energy conversion efficiency, ultimately contributing to developing more sustainable energy systems and a lower carbon footprint in biological processes [217]. Ultimately, these technological advancements and collaborative policies must extend beyond industrial applications to ensure that sustainable energy solutions provide tangible benefits for underserved rural communities [218], fostering inclusive socio-economic development.

6. Conclusions

Although most studies of biohydrogen using anaerobic digestions had been conducted under controlled laboratory conditions, evidence from pilot-scale demonstration projects was established as a foundation for potential commercial applications. Contributions from leading research institutions in emerging economies such as China, India, and Brazil, as well as from established research hubs in the United States and Italy, were highlighted, underscoring the need for global collaboration to advance this technology. Recommendations were made for industry stakeholders, researchers, and policymakers, including standardization of data exchange protocols, promoting collaborative larger projects, and adopting targeted policies to support technological innovation. These collaborative actions were essential to catalyze the transition from pilot and industrial scales to a higher technology readiness level, exemplified by commercial plants that substantiated viability in real-world applications. Integrating artificial intelligence methodologies with life cycle assessment frameworks was also discussed to quantify environmental impacts, thereby guiding targeted process improvements accurately. Technical aspects were analyzed, as well as economic and social implications. Adopting this technology was expected to contribute substantially to sustainable energy systems and ensure that the benefits of these advancements extended not only to mega-cities but also to underserved rural communities.