Open AccessArticle Hydrogen from Waste Plastics as a Low-Carbon Energy Pathway: A Socio-Technical Assessment of Thermochemical Conversion and Market Acceptance by Penka Zlateva Penka Zlateva SciProfiles Scilit Preprints.org Google Scholar 1,*, Mariana Murzova Mariana Murzova SciProfiles Scilit Preprints.org Google Scholar Dr. Mariana Murzova is a Chief Assistant Professor at the Technical University of Varna, Bulgaria, [...] Read more 2, Angel Terziev Angel Terziev SciProfiles Scilit Preprints.org Google Scholar 3,*, Krastin Yordanov Krastin Yordanov SciProfiles Scilit Preprints.org Google Scholar Dr. Krastin Yordanov is an Associate Professor of Industrial Heat Engineering at the Technical of a [...] Read more 1 and Nevena M. Mileva Nevena M. Mileva SciProfiles Scilit Preprints.org Google Scholar Dr. Nevena Milcheva Mileva is a Chief Assistant Professor in Thermal Engineering at the Technical a [...] Read more 1 1 Department of Thermal Engineering, Technical University of Varna, 9010 Varna, Bulgaria 2 Department of Industrial Design, Technical University of Varna, 9010 Varna, Bulgaria 3 Faculty of Power Engineering and Power Machines, Technical University of Sofia, 1756 Sofia, Bulgaria * Authors to whom correspondence should be addressed. Energies 2026, 19(12), 2746; https://doi.org/10.3390/en19122746 (registering DOI) Submission received: 28 March 2026 / Revised: 1 June 2026 / Accepted: 4 June 2026 / Published: 8 June 2026 Abstract Hydrogen production from waste plastics is emerging as a potential low-carbon pathway that integrates waste management with energy production. This study develops an integrated socio-technical framework combining a comparative assessment of thermochemical conversion pathways with market acceptance analysis based on survey data ( n = 162). The results show that acceptance is mainly driven by trust (β = 0.47) and environmental perception (β = 0.32), while price sensitivity has a negative effect (β = −0.21). Awareness does not significantly affect acceptance (β = 0.08). The model explains 48% of the variance (R 2 = 0.48), and a strong correlation is observed between trust and acceptance (r = 0.68). These results show that technological performance alone is insufficient; consumer perception and economic factors play an equally important role, highlighting the need for integrated socio-technical approaches in low-carbon energy systems. 1. Introduction Alternative pathways based on renewable resources and waste are gaining increasing attention, yet their evaluation is often influenced by simplified assumptions regarding their environmental performance [ 11]. Thermochemical conversion of waste plastics into hydrogen represents an approach that combines waste management with energy production within a circular economy framework [ 12]. The high carbon and hydrogen content of plastics makes them a suitable feedstock for energy recovery, particularly where mechanical recycling is not viable [ 13]. However, process outcomes are strongly influenced by feedstock composition, pre-treatment and technological configuration [ 14], which limits the general applicability of this approach [ 15]. In addition, emissions, energy demand and operational stability remain critical challenges that are often underestimated [ 16, 17]. The present study addresses this gap by developing an integrated socio-technical framework that combines a comparative assessment of thermochemical conversion pathways with techno-economic and market acceptance analysis, combining process engineering insights with empirical analysis of user perceptions in order to better understand the factors shaping the adoption of hydrogen produced from waste plastics. 2. Methodology 2.1. Research Approach This study combines literature analysis, survey data and statistical modeling to assess hydrogen from waste plastics as a low-carbon technology. Such approaches are increasingly used in energy transition studies because they link engineering performance with behavioral and market factors [ 2, 3]. The thermochemical component of the study is based on a comparative literature-based assessment of the main waste-to-hydrogen conversion pathways, rather than on original experimental investigation. By integrating technological analysis with empirical research, this approach overcomes the limitations of one-dimensional evaluations based solely on engineering or economic indicators and provides a more realistic assessment of the deployment potential of hydrogen from waste plastics within low-carbon energy systems. 2.2. Conceptual Model Figure 1 presents the integrated conceptual framework developed in this study. The framework illustrates the relationship between thermochemical conversion pathways, hydrogen production characteristics, socio-technical factors, and market acceptance of hydrogen produced from waste plastics. The model assumes that thermochemical process performance, including hydrogen yield, emissions, energy demand, and process limitations, indirectly influences market acceptance through factors such as trust, environmental perception, and price sensitivity. In this context, technological efficiency and environmental performance are considered important determinants shaping user perception and adoption willingness. In addition, the framework incorporates statistical analysis and modeling as tools for evaluating the relationships between the examined variables and identifying the main drivers influencing acceptance behavior. The inclusion of a feedback loop further emphasizes the interaction between engineering performance, user perception, and future technology development within low-carbon energy systems. 2.3. Sample and Respondent Profile The empirical study is based on a sample of 162 respondents, distributed across three main groups: (1) representatives from industry and the energy sector; (2) experts and academic staff; (3) end-users and individuals from sectors not directly related to hydrogen technologies. This composition was intentionally designed to ensure a balanced representation of perspectives and to avoid bias associated with a single stakeholder group. By including both professional and non-professional participants, the study captures a broader spectrum of attitudes toward hydrogen produced from waste plastics. Such a structure enables a comparative analysis between expert-driven evaluations and general user perceptions, which is particularly important in the context of emerging energy technologies. Previous research suggests that differences between these groups may significantly influence technology acceptance, particularly in situations characterized by uncertainty, perceived risk, and environmental concerns [ 24, 26]. Furthermore, the inclusion of respondents from diverse professional backgrounds allows for a more realistic approximation of market conditions, where adoption decisions are shaped by multiple actors within the energy system rather than solely by technical experts. The distribution of respondents by group is presented in Table 1, demonstrating a relatively balanced structure with a slight predominance of end-users, which aligns with the objective of capturing market-oriented perspectives. At the same time, the presence of industry representatives and experts ensures that the analysis incorporates informed and experience-based evaluations of the technology. The respondents were recruited using a convenience sampling approach through online distribution channels and professional networks related to energy and environmental topics. Considering the sample size of 162 respondents, the estimated margin of error is approximately ±7.7% at a 95% confidence level. 2.4. Questionnaire Design The questionnaire was structured into four main sections, designed to capture demographic characteristics, awareness, perception and behavioral intentions related to hydrogen produced from waste plastics. This structure follows established practices in energy-related behavioral studies, where cognitive, attitudinal and economic factors are analyzed simultaneously [ 24, 25]. 2.4.1. Demographic and Professional Characteristics The first section collected background information about the respondents in order to enable segmentation analysis. The variables included: age group; level of education; professional sector (industry/energy, academia, other sectors); prior experience or familiarity with energy-related topics. These variables are commonly used to identify differences in perception across social and professional groups and to assess the influence of expertise on technology acceptance [ 24]. 2.4.2. Assessment of Awareness of Hydrogen Technologies The second section aimed to assess the level of awareness and basic knowledge regarding hydrogen and its production pathways. The second section aimed to assess the level of awareness and basic knowledge regarding hydrogen and its production pathways. The awareness-related questions were evaluated using a five-point Likert scale ranging from 1 (very low awareness) to 5 (very high awareness). The respondents evaluated the following statements: “Are you familiar with hydrogen as an energy carrier?” “Are you aware that waste plastics can be used as a feedstock for hydrogen production?” This section reflects the assumption that awareness is a prerequisite for informed decision-making, although it does not necessarily lead to acceptance [ 25]. 2.4.3. Perception and Trust (Likert Scale) The third section evaluated attitudes, trust and perceived environmental benefits using a five-point Likert scale (1 = strongly disagree, 5 = strongly agree). The respondents were asked to evaluate the following statements: “Hydrogen produced from waste plastics is a promising low-carbon technology.” “The technology is sufficiently reliable for industrial applications.” “The environmental benefits of this type of hydrogen are convincing.” “I would support the use of such hydrogen in industry or transport.” These variables capture key psychological and perceptual factors influencing technology acceptance, particularly trust and perceived sustainability [ 24, 26]. 2.4.4. Market Acceptance and Behavioral Intentions The fourth section focused on behavioral intentions and market-related factors. It included both Likert-scale and preference-based questions: willingness to use hydrogen-based solutions; willingness to pay a premium for a low-carbon product; importance of the following factors in decision-making: price, regulatory support, supply reliability, and carbon footprint; preference between different hydrogen production pathways: hydrogen from waste plastics, conventional (“grey”) hydrogen, and electrolytic (“green”) hydrogen. This section is essential for linking perception with actual behavioral intentions, which is a critical step in assessing the real adoption potential of emerging energy technologies [ 26]. The structure of the questionnaire is summarized in Table 2. As shown in Table 2, the questionnaire is structured to progressively capture respondents’ characteristics, awareness levels, perceptions, and behavioral intentions, enabling a comprehensive assessment of factors influencing the acceptance of hydrogen technologies. 2.5. Variables and Hypotheses 2.5.1. Variables Definition The main variables included in the analysis are defined as follows: Awareness—reflects the level of familiarity with hydrogen technologies and hydrogen production from waste plastics (Likert scale, 1–5). Trust—represents the degree of confidence in the reliability, safety and industrial applicability of the technology (measured on a five-point Likert scale). Environmental Perception—captures the perceived contribution of the technology to carbon emission reduction and environmental sustainability (Likert scale). Price Sensitivity—reflects the importance of cost in the decision-making process and the willingness to pay for low-carbon alternatives (Likert scale). Adoption Willingness—represents the intention to use or support hydrogen produced from waste plastics (Likert scale). As shown in Table 3, the selected variables cover key dimensions influencing technology acceptance, enabling a comprehensive analysis of both perception-driven and economically driven factors. 2.5.2. Thermochemical Process Performance and Market Implications Research Hypotheses Based on the conceptual model and existing literature, the following hypotheses were formulated: H1.Higher awareness is positively associated with greater willingness to adopt hydrogen from waste plastics. H2.Trust in technology has a significant positive effect on adoption willingness. H3.Perceived environmental benefits positively influence both adoption willingness and willingness to pay for technology. H4.Price sensitivity has a negative effect on adoption willingness, acting as a barrier to market acceptance. H5.Trust mediates the relationship between environmental perception and adoption willingness, strengthening the impact of perceived sustainability on acceptance. 2.5.3. Statistical Analysis The hypotheses were tested using descriptive statistics, Pearson correlation analysis, multiple linear regression, and one-way ANOVA analysis to evaluate the relationships between the examined variables and identify the key determinants influencing market acceptance of hydrogen produced from waste plastics. Descriptive statistics were applied to summarize respondent attitudes, perception patterns, and behavioral tendencies related to the technology examined. Pearson correlation analysis was used to evaluate the strength and direction of the relationships between awareness, trust, environmental perception, price sensitivity, and adoption willingness. The multiple regression model used in the study is expressed as Y = β 0 + (β 1 ୍ଠ ଢ 1) + (β 2 ୍ଠ ଢ 2) + (β 3 ୍ଠ ଢ 3) + ε, (1) where “Y” represents adoption willingness, “X 1” awareness, “X 2” trust, “X 3” environmental perception, and “ε” the residual error term. Pearson correlation coefficients were calculated according to the following expression: r = ∑ ( x i − x ˉ ) ( y i − y ˉ ) ∑ ( x i − x ˉ ) 2 ∑ ( y i − y ˉ ) 2 (2) where “ r” represents the Pearson correlation coefficient between the examined variables. In addition, one-way ANOVA analysis was performed to evaluate statistically significant differences between respondent groups. This analytical framework provides empirical support for the conceptual model presented in Figure 1 and enables the identification of the main socio-technical factors influencing technology acceptance. 3. Results 3.1. Descriptive Statistics The descriptive analysis provides an overview of respondents’ perceptions regarding hydrogen produced from waste plastics. All Likert-scale variables presented in Table 4 were evaluated on a five-point scale ranging from 1 (strongly disagree) to 5 (strongly agree). The results indicate moderate awareness and generally positive attitudes toward the technology. The descriptive statistics of the main variables are presented in Table 4. The relatively low awareness score suggests that hydrogen production from waste plastics remains unfamiliar to a considerable proportion of respondents. In contrast, environmental perception demonstrates the highest mean value, indicating that participants generally associate the technology with positive environmental impacts and carbon reduction potential. Trust and adoption willingness show moderately high values, reflecting a generally favorable but still cautious attitude toward the implementation of hydrogen technologies. The results also indicate that economic considerations remain relevant, as reflected by the relatively high price sensitivity score. Overall, the descriptive statistics suggest that market acceptance is influenced more strongly by perceived environmental benefits and trust in the technology than by awareness alone. To further examine respondent attitudes, the distribution of responses across the Likert-scale categories was analyzed. Figure 2 presents the structure of responses for the main variables influencing the acceptance of hydrogen produced from waste plastics. Figure 2 illustrates the distribution of responses across the Likert-scale categories for the main variables influencing technology acceptance. The results indicate that positive responses (“agree” and “strongly agree”) dominate for environmental perception and adoption willingness, while price sensitivity demonstrates a more balanced distribution, reflecting the continued importance of economic considerations in technology acceptance. 3.2. Thermochemical Process Performance and Market Implications The comparison of thermochemical pathways indicates that hydrogen yield and process efficiency strongly depend on operating temperature, catalyst activity, and feedstock composition. Gasification and catalytic reforming demonstrate higher hydrogen productivity, while pyrolysis exhibits lower operational complexity and potentially lower environmental impact. These differences suggest that thermochemical performance plays an important role in determining both technological feasibility and market perception. The main characteristics of the examined thermochemical pathways are summarized in Table 5. As shown in Table 5, the thermochemical pathways differ substantially in terms of hydrogen yield, energy demand, and operational complexity. The analysis also suggests that technological characteristics may indirectly influence market acceptance. Processes associated with higher hydrogen purity and lower emissions are more likely to strengthen public trust and perceived environmental benefits, while high operating costs and energy demand may increase price sensitivity. This demonstrates that engineering performance and user perception are interconnected dimensions within low-carbon hydrogen systems. 3.3. Correlation Analysis A correlation analysis was conducted to examine the relationships between the main variables. The results of the Pearson correlation matrix are presented in Table 6. The strongest relationship is observed between trust and adoption willingness (r = 0.68), indicating that confidence in technology is the primary driver of acceptance. Environmental perception also shows a moderate positive correlation with adoption (r = 0.52), suggesting that perceived sustainability contributes to positive attitudes. Price sensitivity exhibits a negative relationship with adoption (r = −0.31), confirming its role as a barrier. Awareness shows a moderate correlation with adoption (r = 0.49), but weaker than trust, indicating that knowledge alone is not sufficient to drive acceptance. 3.4. Regression Analysis To evaluate the relative importance of the independent variables, a multiple regression model was applied. The results of the regression analysis are presented in Table 7. The results indicate that trust is the strongest predictor of adoption willingness (β = 0.47), followed by environmental perception (β = 0.32). Price sensitivity has a statistically significant negative effect (β = −0.21), confirming its role as a limiting factor. In contrast, awareness does not exhibit a statistically significant effect (β = 0.08), suggesting that familiarity with the technology does not directly translate into adoption. This finding indicates that increasing information alone may not be sufficient to drive behavioral change. These findings support hypotheses H2 and H3, while H1 is not confirmed, emphasizing the key role of trust and perceived environmental benefits in shaping adoption decisions. The relative importance of the independent variables is further illustrated in Figure 3. In contrast, awareness does not have a significant direct effect, indicating that familiarity with technology does not necessarily lead to acceptance. This suggests that information alone is insufficient to drive adoption. 3.5. Group Differences (ANOVA Analysis) To examine differences between respondent groups, a one-way ANOVA was conducted. The results for adoption willingness across the three groups are presented in Table 8. As shown in Table 8, the results indicate statistically significant differences in adoption willingness between the examined groups. To further explore these differences, a Tukey post hoc test was conducted. The results are presented in Table 9. The post hoc analysis reveals that both industry representatives and academic experts differ significantly from end-users, while no statistically significant difference is observed between the two professional groups. This suggests that professional stakeholders demonstrate consistently higher willingness to adopt hydrogen technologies, whereas end-users exhibit more cautious attitudes. The absence of significant differences between industry and academic respondents indicates a shared perspective, likely driven by higher levels of expertise and familiarity with technology. These findings highlight the importance of knowledge and professional experience in shaping positive attitudes toward emerging energy solutions. This gap between professional and non-professional respondents suggests the need for targeted communication and awareness strategies to bridge perception differences. The differences between the groups are further illustrated in Figure 4. 3.6. Visualization Between Trust and Adoption Willingness The relationship between trust in technology and adoption willingness is further illustrated in Figure 5. As illustrated in Figure 5, a clear positive relationship between trust and adoption willingness can be observed, reinforcing the regression results and confirming the key role of trust in shaping user acceptance of hydrogen technologies. 3.7. Key Findings The analysis reveals several important patterns. Trust emerges as the strongest determinant of adoption willingness, while environmental perception also contributes positively to technology acceptance. Price sensitivity acts as a barrier to adoption, although its influence is weaker than that of trust and environmental perception. In contrast, awareness does not significantly affect adoption willingness, indicating that knowledge alone is insufficient to stimulate behavioral change. The results further demonstrate that professional stakeholders exhibit a higher willingness to adopt hydrogen technologies than end-users. Overall, these findings suggest that market acceptance is driven primarily by trust, perception, and confidence rather than by awareness alone. 4. Discussion The results reveal a clear gap between technological development and market readiness in the context of hydrogen production from waste plastics. Although thermochemical processes are technically mature, adoption appears to depend more on socio-technical factors than on engineering performance. This finding aligns with previous research indicating that technical feasibility alone does not guarantee real-world adoption [ 24, 44]. To further position the present research within the current state of the art, a comparison with selected previous studies related to hydrogen technologies, market acceptance, and socio-technical assessment is presented in Table 10. As shown in Table 10, previous studies have primarily focused either on thermochemical hydrogen production technologies or on social acceptance factors separately. In contrast, the present study integrates engineering performance indicators with market acceptance analysis, providing a broader socio-technical perspective on hydrogen production from waste plastics. This study contributes to the literature by moving beyond purely technological or economic analyses and providing an integrated perspective on technology adoption. It highlights that the successful deployment of waste-to-hydrogen technologies depends on aligning engineering performance with user perception, institutional trust, and market expectations. Such an integrated approach is essential for bridging the gap between innovation and implementation in low-carbon energy systems. 5. Conclusions The present study investigated the market acceptance of hydrogen produced from waste plastics through an integrated socio-technical assessment combining a comparative literature-based evaluation of thermochemical conversion pathways with survey-based empirical analysis. The results demonstrate that trust represents the strongest determinant of adoption willingness (β = 0.47; r = 0.68), followed by environmental perception (β = 0.32; r = 0.52), while price sensitivity exerts a statistically significant negative effect (β = −0.21). In contrast, awareness does not exhibit a significant direct influence on adoption, indicating that familiarity with technology alone is insufficient to support behavioral change. The model explains 48% of the observed variance (R 2 = 0.48), confirming the importance of socio-technical factors in shaping market acceptance of emerging hydrogen technologies. The comparative literature-based assessment of thermochemical conversion pathways further indicates that process characteristics such as hydrogen yield, emissions, energy demand, and catalyst-related limitations may indirectly influence public perception and adoption behavior. In this context, the study demonstrates that market acceptance of hydrogen from waste plastics depends not only on technological feasibility but also on perceived reliability, environmental credibility, and economic considerations. These findings contribute to the current literature by integrating engineering-related process characteristics with behavioral and market-oriented analysis within a unified socio-technical framework. Several limitations of the study should also be acknowledged. The thermochemical component is based on a comparative literature-based assessment rather than on original experimental or numerical investigation. In addition, the survey sample size remains relatively limited and was obtained through convenience sampling, which may affect the generalizability of the results. The analysis also focuses primarily on perception-based variables without incorporating detailed lifecycle assessment or techno-economic optimization. Future research should therefore combine experimental thermochemical analysis, lifecycle assessment, and advanced techno-economic modeling with larger-scale empirical studies on public acceptance. Additional investigation of policy mechanisms, regional differences, and long-term adoption behavior would further improve the understanding of the deployment potential of hydrogen produced from waste plastics within low-carbon energy systems. Author Contributions A.T., P.Z. and M.M.; methodology, A.T., P.Z. and M.M.; software, N.M.M. and K.Y.; validation, N.M.M. and K.Y.; formal analysis, A.T. and P.Z.; investigation, M.M. and K.Y.; resources, N.M.M.; data curation, A.T. and N.M.M.; writing—original draft preparation, K.Y., P.Z. and M.M.; writing—review and editing, P.Z. and K.Y.; visualization, M.M. and N.M.M.; supervision, A.T.; project administration, A.T.; funding acquisition, A.T. All authors have read and agreed to the published version of the manuscript. Funding This study is financed by the European Union—NextGenerationEU, through the National Recovery and Resilience Plan of the Republic of Bulgaria, project No. BG-RRP-2.004-0005. Institutional Review Board Statement Not applicable. Informed Consent Statement Not applicable. Data Availability Statement The original contributions presented in this study are included in the article. Further inquiries can be directed to the corresponding authors. Conflicts of Interest The authors declare no conflicts of interest. References Abawalo, M.; Pikoń, K.; Landrat, M.; Ścierski, W. Hydrogen Production from Biowaste: A Systematic Review of Conversion Technologies, Environmental Impacts and Future Perspectives. Energies 2025, 18, 4520. [ Google Scholar] [ CrossRef] Dewangan, K.K.; Gopan, G.; Pattanayak, S. Overview of Hydrogen Production Processes: Health and Environmental Impact. Environ. Prog. Sustain. Energy 2025, 45, e70229. [ Google Scholar] [ CrossRef] Maniscalco, M.P.; Longo, S.; Cellura, M.; Miccichè, G.; Ferraro, M. Critical Review of Life Cycle Assessment of Hydrogen Production Pathways. Environments 2024, 11, 108. [ Google Scholar] [ CrossRef] Niu, F.; Wu, Z.; Chen, D.; Huang, Y.; Ordomsky, V.; Khodakov, A.Y.; Van Geem, K.V. State-of-the-Art and Perspectives of Hydrogen Generation from Waste Plastics. Chem. Soc. Rev. 2025, 54, 4948–4972. [ Google Scholar] [ CrossRef] [ PubMed] Rauch, R.; Kiros, Y.; Engvall, K.; Kantarelis, E.; Brito, P.; Nobre, C.; Santos, S.M.; Graefe, P.A. Hydrogen from Waste Gasification. Hydrogen 2024, 5, 70–101. [ Google Scholar] [ CrossRef] Jeong, Y.-S.; Park, K.-B.; Kim, J.-S. Hydrogen Production from Steam Gasification of Polyethylene Using a Two-Stage Gasifier and Active Carbon. Appl. Energy 2020, 262, 114495. [ Google Scholar] [ CrossRef] Appiah, H.; Asamoah, P.; McDonald, A.G. Waste-to-Energy Technologies and Their Role in Municipal Solid Waste Management. Recycling 2026, 11, 56. [ Google Scholar] [ CrossRef] Medaiyese, F.J.; Nasriani, H.R.; Khajenoori, L.; Khan, K.; Badiei, A. From Waste to Energy: Enhancing Fuel and Hydrogen Production through Pyrolysis and In-Line Reforming of Plastic Wastes. Sustainability 2024, 16, 4973. [ Google Scholar] [ CrossRef] Busto, M.; Nardi, F.; Dosso, L.; Badano, J.M.; Tarifa, E.E.; Vera, C.R. Review of Gasification of Thermoplastics and Thermosets. Processes 2025, 13, 647. [ Google Scholar] [ CrossRef] Straka, P.; Cihlář, J.; Bičáková, O. Production of Syngas and Hydrogen-Rich Gas from Lignocellulosic Biomass via Ru/Al 2O 3 Catalyst-Assisted Slow Pyrolysis. Catalysts 2025, 15, 1033. [ Google Scholar] [ CrossRef] Ashfaq, M.M.; Tüzemen, G.B.; Noor, A. Exploiting agricultural biomass via thermochemical processes for sustainable hydrogen and bioenergy: A critical review. Int. J. Hydrogen Energy 2024, 84, 1068–1084. [ Google Scholar] [ CrossRef] Kim, M.; Ghobadi, F.; Tayerani Charmchi, A.S.; Lee, M.; Lee, J. Digital Twins for Clean Energy Systems: A State-of-the-Art Review of Applications, Integrated Technologies, and Key Challenges. Sustainability 2026, 18, 43. [ Google Scholar] [ CrossRef] Zuorro, A.; Lavecchia, R.; Contreras-Ropero, J.E.; García-Martínez, J.B.; Barajas-Solano, A.F. Renewable Hydrogen from Biohybrid Systems: A Bibliometric Review of Technological Trends and Applications in the Energy Transition. Energies 2025, 18, 6563. [ Google Scholar] [ CrossRef] Hossain Bhuiyan, M.M.; Siddique, Z. Hydrogen as an Alternative Fuel: A Comprehensive Review of Challenges and Opportunities in Production, Storage, and Transportation. Int. J. Hydrogen Energy 2025, 102, 1026–1044. [ Google Scholar] [ CrossRef] Abbasian Hamedani, E.; Alenabi, S.A.; Talebi, S. Hydrogen as an Energy Source: A Review of Production Technologies and Challenges of Fuel Cell Vehicles. Energy Rep. 2024, 12, 3778–3794. [ Google Scholar] [ CrossRef] Sun, H. Hydrogen energy is arousing great attention all over the world. Int. J. Hydrogen Energy 2021, 46, 2845–2846. [ Google Scholar] [ CrossRef] Mirzania, P.; Huo, D.; Balta-Ozkan, N.; Panigrahi, N.; Knox, J.W. Decarbonising Agriculture with Green Hydrogen: A Stakeholder-Guided Feasibility Study. Sustainability 2025, 17, 9298. [ Google Scholar] [ CrossRef] Shamsi, M.; Obaid, A.; Farokhi, S.; Bayat, A. A novel process simulation model for hydrogen production via reforming of biomass gasification tar. Int. J. Hydrogen Energy 2022, 47, 772–781. [ Google Scholar] [ CrossRef] Oliveira, F.; Araujo, A.P.C.; Romao, B.B.; Cardoso, V.L.; Ferreira, J.S.; Batista, F.R.X. Hydrogen photo-production using Chlorella sp. through sulfur-deprived and hybrid system strategy. Chem. Eng. Trans. 2015, 43, 301–306. [ Google Scholar] Bade, S.O.; Tomomewo, O.S. A review of governance strategies, policy measures, and regulatory framework for hydrogen energy in the United States. Int. J. Hydrogen Energy 2024, 78, 1363–1381. [ Google Scholar] [ CrossRef] Jimenez-Llanos, J.; Ramirez-Carmona, M.; Rendon-Castrillon, L.; Ocampo-Lopez, C. Sustainable biohydrogen production by Chlorella sp. microalgae: A review. Int. J. Hydrogen Energy 2020, 45, 8310–8328. [ Google Scholar] [ CrossRef] Hwang, J.-H.; Lee, M.; Kang, E.H.; Lee, W.H. Renewable algal photo H 2 production without S control using acetate enriched fermenter effluents. Int. J. Hydrogen Energy 2021, 46, 1740–1751. [ Google Scholar] [ CrossRef] Nagarajan, D.; Dong, C.D.; Chen, C.Y.; Lee, D.J.; Chang, J.S. Biohydrogen production from microalgae-Major bottlenecks and future research perspectives. Biotechnol. J. 2021, 16, e2000124. [ Google Scholar] [ CrossRef] Schönauer, A.; Glanz, S. Hydrogen in future energy systems: Social acceptance of the technology and its large-scale infrastructure. Int. J. Hydrogen Energy 2022, 47, 12251–12263. [ Google Scholar] [ CrossRef] Tian, H.; Li, J.; Yan, M.; Tong, Y.W.; Wang, C.-H.; Wang, X. Organic Waste to Biohydrogen: A Critical Review from Technological Development and Environmental Impact Analysis Perspective. Appl. Energy 2019, 256, 113961. [ Google Scholar] [ CrossRef] Kazmi, B.; Sadiq, T.; Taqvi, S.A.A.; Nasir, S.; Khan, M.M.; Naqvi, S.R.; Al Mohamadi, H. Towards a Sustainable Future: Bio-Hydrogen Production from Food Waste for Clean Energy Generation. Process Saf. Environ. Prot. 2024, 183, 555–567. [ Google Scholar] [ CrossRef] Uekert, T.; Wikoff, H.M.; Badgett, A. Electrolyzer and Fuel Cell Recycling for a Circular Hydrogen Economy. Adv. Sustain. Syst. 2024, 8, 2300449. [ Google Scholar] [ CrossRef] Xu, Q.; Lan, P.; Zhang, B.; Ren, Z.; Yan, Y. Hydrogen Production via Catalytic Steam Reforming of Fast Pyrolysis Bio-oil in a Fluidized-Bed Reactor. Energy Fuels 2010, 24, 6456–6462. [ Google Scholar] [ CrossRef] Inayat, A.; Ahmad, M.M.; Mutalib, M.I.A.; Yusup, S.; Khan, Z. Economic analysis and optimization for bio-hydrogen production from oil palm waste via steam gasification. Energy Sources Part B Econ. Plan. Policy 2017, 12, 158–165. [ Google Scholar] [ CrossRef] Aziz, M.; Darmawan, A.; Juangsa, F.B. Hydrogen Production from Biomasses and Wastes: A Technological Review. Int. J. Hydrogen Energy 2021, 46, 33756–33781. [ Google Scholar] [ CrossRef] Janke, L.; McDonagh, S.; Weinrich, S.; Nilsson, D.; Hansson, P.-A.; Nordberg, Å. Techno-Economic Assessment of Demand-Driven Small-Scale Green Hydrogen Production for Low Carbon Agriculture in Sweden. Front. Energy Res. 2020, 8, 595224. [ Google Scholar] [ CrossRef] Kumari, P.; Mohanty, B. Hydrogen-rich gas production with CO 2 capture from steam gasification of pine needle using calcium oxide: Experimental and modeling study. Int. J. Energy Res. 2020, 44, 6927–6938. [ Google Scholar] [ CrossRef] Waheed, Q.; Wu, C.; Williams, P. Hydrogen production from high temperature steam catalytic gasification of bio-char. J. Energy Inst. 2016, 89, 222–230. [ Google Scholar] [ CrossRef] Mechery, J.; Thomas, D.M.; Kumar, C.P.; Joseph, L.; Sylas, V. Biohydrogen production from acidic and alkaline hydrolysates of paddy straw using locally isolated facultative bacteria through dark fermentation. Biomass Convers. Biorefin. 2021, 11, 1263–1272. [ Google Scholar] [ CrossRef] Kapdan, I.K.; Kargi, F. Bio-Hydrogen Production from Waste Materials. Enzym. Microb. Technol. 2006, 38, 569–582. [ Google Scholar] [ CrossRef] Magnino, A.; Marocco, P.; Santarelli, M.; Gandiglio, M. Economic viability and CO 2 emissions of hydrogen production for ammonia synthesis: A comparative analysis across Europe. Adv. Appl. Energy 2025, 17, 100204. [ Google Scholar] [ CrossRef] Sarma, S.; Ortega, D.; Minton, N.P.; Dubey, V.K.; Moholkar, V.S. Homologous Overexpression of Hydrogenase and Glycerol Dehydrogenase in Clostridium pasteurianum to Enhance Hydrogen Production from Crude Glycerol. Bioresour. Technol. 2019, 284, 168–177. [ Google Scholar] [ CrossRef] [ PubMed] Srivastava, P.; García-Quismondo, E.; Palma, J.; González-Fernández, C. Coupling Dark Fermentation and Microbial Electrolysis Cells for Higher Hydrogen Yield: Technological Competitiveness and Challenges. Int. J. Hydrogen Energy 2024, 52, 223–239. [ Google Scholar] [ CrossRef] Kumar, G.; Eswari, A.P.; Kavitha, S.; Kumar, M.D.; Kannah, R.Y.; How, L.C.; Muthukaruppan, G.; Banu, J.R. Thermochemical Conversion Routes of Hydrogen Production from Organic Biomass: Processes, Challenges and Limitations. Biomass Convers. Biorefin. 2023, 13, 8509–8534. [ Google Scholar] [ CrossRef] Vallejos-Romero, A.; Cordoves-Sánchez, M.; Cisternas, C.; Sáez-Ardura, F.; Rodríguez, I.; Aledo, A.; Boso, Á.; Prades, J.; Álvarez, B. Green Hydrogen and Social Sciences: Issues, Problems, and Future Challenges. Sustainability 2023, 15, 303. [ Google Scholar] [ CrossRef] Maroušek, J. Review: Nanoparticles Can Change (Bio)Hydrogen Competitiveness. Fuel 2022, 328, 125318. [ Google Scholar] [ CrossRef] Wu, S.Y.; Lin, C.N.; Chang, J.S. Hydrogen production with immobilized sewage sludge in three-phase fluidized-bed bioreactors. Biotechnol. Prog. 2003, 19, 828–832. [ Google Scholar] [ CrossRef] Cao, L.; Yu, I.K.M.; Xiong, X.; Tsang, D.C.W.; Zhang, S.; Clark, J.H.; Hu, C.; Ng, Y.H.; Shang, J.; Ok, Y.S. Biorenewable Hydrogen Production through Biomass Gasification: A Review and Future Prospects. Environ. Res. 2020, 186, 109547. [ Google Scholar] [ CrossRef] [ PubMed] Gordon, J.A.; Balta-Ozkan, N.; Haq, A.; Nabavi, S.A. Coupling green hydrogen production to community benefits: A pathway to social acceptance? Energy Res. Soc. Sci. 2024, 110, 103437. [ Google Scholar] [ CrossRef] Balachandar, G.; Varanasi, J.L.; Singh, V.; Singh, H.; Das, D. Biological Hydrogen Production via Dark Fermentation: A Holistic Approach from Lab-Scale to Pilot-Scale. Int. J. Hydrogen Energy 2020, 45, 5202–5215. [ Google Scholar] [ CrossRef] Patel, G.H.; Havukainen, J.; Horttanainen, M.; Soukka, R.; Tuomaala, M. Climate Change Performance of Hydrogen Production Based on Life Cycle Assessment. Green Chem. 2024, 26, 992–1006. [ Google Scholar] [ CrossRef] Sydney, E.B.; Duarte, E.R.; Martinez Burgos, W.J.; de Carvalho, J.C.; Larroche, C.; Soccol, C.R. Development of Short Chain Fatty Acid-Based Artificial Neuron Network Tools Applied to Biohydrogen Production. Int. J. Hydrogen Energy 2020, 45, 5175–5181. [ Google Scholar] [ CrossRef] Chen, W.-H.; Chen, C.-Y. Water Gas Shift Reaction for Hydrogen Production and Carbon Dioxide Capture: A Review. Appl. Energy 2020, 258, 114078. [ Google Scholar] [ CrossRef] Zhang, J.; Ling, B.; He, Y.; Zhu, Y.; Wang, Z. Life Cycle Assessment of Three Types of Hydrogen Production Methods Using Solar Energy. Int. J. Hydrogen Energy 2022, 47, 14158–14168. [ Google Scholar] [ CrossRef] Paillet, F.; Barrau, C.; Escudié, R.; Bernet, N.; Trably, E. Robust Operation Through Effluent Recycling for Hydrogen Production from the Organic Fraction of Municipal Solid Waste. Bioresour. Technol. 2021, 319, 124196. [ Google Scholar] [ CrossRef] Williams, J.M.; Bourtsalas, A.C. Assessment of Co-Gasification Methods for Hydrogen Production from Biomass and Plastic Wastes. Energies 2023, 16, 7548. [ Google Scholar] [ CrossRef] Zheng, X.; Wang, J.; Huang, J.; Xu, X.; Tang, J.; Hou, P.; Han, W.; Li, H. Environmental Impact Assessment of a Combined Bioprocess for Hydrogen Production from Food Waste. Waste Manag. 2024, 173, 152–159. [ Google Scholar] [ CrossRef] Wu, C.; Huang, Q.; Sui, M.; Yan, Y.; Wang, F. Hydrogen production via catalytic steam reforming of fast pyrolysis bio-oil in a two-stage fixed bed reactor system. Fuel Process. Technol. 2008, 89, 1306–1316. [ Google Scholar] [ CrossRef] Chisalita, D.-A.; Petrescu, L.; Galusnyak, S.C.; Cormos, C.-C. Environmental Evaluation of Hydrogen Production Employing Innovative Chemical Looping Technologies—A Romanian Case Study. Int. J. Hydrogen Energy 2023, 48, 12112–12128. [ Google Scholar] [ CrossRef] Figure 1. Integrated conceptual framework linking thermochemical conversion pathways, socio-technical factors, and market acceptance of hydrogen produced from waste plastics. Figure 1. Integrated conceptual framework linking thermochemical conversion pathways, socio-technical factors, and market acceptance of hydrogen produced from waste plastics. Figure 2. Distribution of respondent attitudes toward hydrogen from waste plastics. Figure 2. Distribution of respondent attitudes toward hydrogen from waste plastics. Figure 3. Standardized regression coefficients (β). Figure 3. Standardized regression coefficients (β). Figure 4. Adoption willingness across respondent groups. Figure 4. Adoption willingness across respondent groups. Figure 5. Relationship between trust and adoption willingness. Different colors are used solely to visually distinguish the variables and do not represent statistical significance or categorical grouping. Figure 5. Relationship between trust and adoption willingness. Different colors are used solely to visually distinguish the variables and do not represent statistical significance or categorical grouping. Table 1. Distribution of respondents by group. Table 1. Distribution of respondents by group. Respondent Group Number ( n) Share (%) Industry and energy sector 51 31.5 Experts and academic staff 34 21.0 End-users and other sectors 77 47.5 Total 162 100 Table 2. Structure of the questionnaire. Table 2. Structure of the questionnaire. Section Content Measurement Type A Demographics Categorical B Awareness Likert (1–5) C Trust and perception Likert (1–5) D Market acceptance and behavior Likert/Choice Table 3. Definition of variables. Table 3. Definition of variables. Variable Description Measurement Type Awareness Knowledge of hydrogen from waste plastics Likert (1–5) Trust Confidence in technology reliability Likert (1–5) Environmental perception Perceived environmental benefit Likert (1–5) Price sensitivity Importance of cost in decision-making Likert (1–5) Adoption willingness Intention to adopt the technology Likert (1–5) Table 4. Descriptive statistics of key variables. Table 4. Descriptive statistics of key variables. Variable Mean Standard Deviation (SD) Awareness 2.20 1.11 Trust 3.54 0.94 Environmental perception 4.07 0.79 Adoption willingness 3.72 0.91 Price sensitivity 3.18 1.02 Table 5. Comparison of thermochemical process parameters for hydrogen production from waste plastics. Table 5. Comparison of thermochemical process parameters for hydrogen production from waste plastics. Process Temperature, °C H 2 Yield Main Advantages Main Limitations Pyrolysis 500–700 Moderate Lower emissions Lower hydrogen purity Gasification 700–1200 High High conversion efficiency High energy demand Catalytic reforming 600–900 Very high Improved hydrogen selectivity Catalyst deactivation Table 6. Correlation matrix (Pearson r). Table 6. Correlation matrix (Pearson r). Variable 1 2 3 4 5 Awareness 1.00 Trust 0.41 1.00 Environmental perception 0.36 0.58 1.00 Price sensitivity −0.31 −0.44 −0.40 1.00 Adoption willingness 0.49 0.68 0.52 −0.52 1.00 All correlations are statistically significant at p < 0.01. Table 7. Regression results. Table 7. Regression results. Variable β Standard Error t-Value Significance Constant 0.74 0.29 2.55 0.012 Awareness 0.08 0.06 1.33 n.s. Trust 0.47 0.07 6.71 <0.001 Environmental perception 0.32 0.08 4.00 0.001 Price sensitivity −0.21 0.06 −3.50 0.001 Model statistics: R 2 = 0.48, F = 36.2, p < 0.001. Table 8. ANOVA results for adoption willingness. Table 8. ANOVA results for adoption willingness. Group Mean SD Industry and energy 3.95 0.82 Academic experts 3.88 0.79 End-users 3.52 0.95 Table 9. Tukey post hoc test results. Table 9. Tukey post hoc test results. Comparison Mean Difference Significance Industry vs. End-users 0.43 p < 0.05 Experts vs. End-users 0.36 p < 0.05 Industry vs. Experts 0.07 n.s. Table 10. Comparison of the present study with previous research. Table 10. Comparison of the present study with previous research. Study Research Focus Main Variables Key Findings Main Limitation 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. © 2026 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license. Share and Cite MDPI and ACS Style Zlateva, P.; Murzova, M.; Terziev, A.; Yordanov, K.; Mileva, N.M. Hydrogen from Waste Plastics as a Low-Carbon Energy Pathway: A Socio-Technical Assessment of Thermochemical Conversion and Market Acceptance. Energies 2026, 19, 2746. https://doi.org/10.3390/en19122746 AMA Style Zlateva P, Murzova M, Terziev A, Yordanov K, Mileva NM. Hydrogen from Waste Plastics as a Low-Carbon Energy Pathway: A Socio-Technical Assessment of Thermochemical Conversion and Market Acceptance. Energies. 2026; 19(12):2746. https://doi.org/10.3390/en19122746 Chicago/Turabian Style Zlateva, Penka, Mariana Murzova, Angel Terziev, Krastin Yordanov, and Nevena M. Mileva. 2026. "Hydrogen from Waste Plastics as a Low-Carbon Energy Pathway: A Socio-Technical Assessment of Thermochemical Conversion and Market Acceptance" Energies 19, no. 12: 2746. https://doi.org/10.3390/en19122746 APA Style Zlateva, P., Murzova, M., Terziev, A., Yordanov, K., & Mileva, N. M. (2026). Hydrogen from Waste Plastics as a Low-Carbon Energy Pathway: A Socio-Technical Assessment of Thermochemical Conversion and Market Acceptance. Energies, 19(12), 2746. https://doi.org/10.3390/en19122746 Note that from the first issue of 2016, this journal uses article numbers instead of page numbers. See further details here. Article Metrics Article metric data becomes available approximately 24 hours after publication online.
