Hydrothermal Treatment of Kitchen Waste as a Strategy for Dark Fermentation Biohydrogen Production

Round 1

Reviewer 1 Report

Comments and Suggestions for Authors

The manuscript presents an interesting study on biohydrogen production through dark fermentation using hydrothermally treated kitchen waste, supported by kinetic modeling via the Gompertz equation. However, the paper suffers from several issues that must be addressed before it can be considered for publication.

1. The number of replicates and statistical significance are not specified, figures lack error bars or standard deviations, reducing data credibility. 
2. Inhibitory compounds such as catechol and hydroquinone are only semi-quantitatively analyzed. Quantitative concentration–effect relationships are missing.
3. The Gompertz model fitting focuses only on the 180°C condition, comparative kinetic parameters for other temperatures are absent.
4. The discussion section is largely descriptive and lacks mechanistic reasoning linking hydrothermal pretreatment temperature to microbial pathway shifts. 
5. Numerous grammatical and typographical errors (e.g., “witch respect to” instead of “with respect to”).

Author Response

Comments 1:The number of replicates and statistical significance are not specified, figures lack error bars or standard deviations, reducing data credibility. 

Response 1: In the revised version of the manuscript, the number of replicates has been specified, and error bars representing standard deviations have been added to the experimental results. Furthermore, all figures have been completely redrawn using a different software to ensure higher graphical quality, consistency, and improved readability.

Comments 2: Inhibitory compounds such as catechol and hydroquinone are only semi-quantitatively analyzed. Quantitative concentration–effect relationships are missing.

Response 2: We agree with that catechol and hydroquinone were identified only semi-quantitatively. Their presence was confirmed in the GC chromatograms; however, due to the coexistence of a large number of other compounds (over 30 identified peaks), it was not possible to determine their exact concentrations. Only based on the relative peak areas in the GC spectra, their significant contribution to the mixture can be observed.

Comments 3: The Gompertz model fitting focuses only on the 180°C condition, comparative kinetic parameters for other temperatures are absent.

Response 3: The text was revised to include a brief comparative discussion of kinetic parameters for all pretreatment temperatures (Table 2, Figure 5). The new sentences highlight the general trends across variants and confirm that 180°C showed the most favorable kinetics of H₂ production.

Comments 4: The discussion section is largely descriptive and lacks mechanistic reasoning linking hydrothermal pretreatment temperature to microbial pathway shifts. 

Response 4: We agree that the discussion could better address possible mechanisms. Although our study did not include direct microbial analyses, we added a plausible explanation. This explanation suggests that moderate pretreatment temperatures favor hydrogen-producing and acidogenic pathways. In contrast, high temperatures lead to inhibitory compounds that suppress H₂ production and alter VFA profiles. This provides a plausible framework linking pretreatment temperature to shifts in microbial metabolism.

Comments 5: Numerous grammatical and typographical errors (e.g., “witch respect to” instead of “with respect to”).

Response 5: We thank the reviewer for pointing out the grammatical and typographical errors. All such errors, including the example “witch respect to” corrected to “with respect to,” have been carefully revised throughout the manuscript.

Author Response File: Author Response.docx

Reviewer 2 Report

Comments and Suggestions for Authors

This study presents an innovative approach to the production of hydrogen from liquids following hydrothermal treatment of biowaste, offering a potential solution for renewable energy generation and waste management. The following comments are provided to help improve the overall quality of the manuscript.

1. Please include a more detailed description of the chemical and mathematical models used to characterize the hydrothermal and dark fermentation processes. Besides, the following related research can be reviewed: a: Two stage stochastic energy scheduling for multi energy rural microgrids with irrigation systems and biomass fermentation; b: Capacity credit evaluation of generalized energy storage considering strategic capacity withholding and decision-dependent uncertainty
2. It is recommended to add a flowchart or schematic diagram summarizing the overall experimental process to help readers better understand the workflow and logical connections between process stages.
3. Several recent studies have incorporated biomass fermentation into multi-energy systems, such as “Two-stage stochastic energy scheduling for multi-energy rural microgrids with irrigation systems and biomass fermentation.” and “Energy, exergy, and exergoeconomic cost optimization of wind-biomass multi-energy systems integrated for hydrogen production”. Please compare it in the introduction.
4. More details about experimental conditions should be provided to improve the reproducibility and technical clarity of the work.
5. Please consider including error bars or confidence intervals for experimental results. Statistical significance tests (e.g., ANOVA) could be used to confirm whether variations in hydrogen yield across temperatures are significant.
6. It is suggested to conduct or discuss a sensitivity analysis of key operating parameters to demonstrate the robustness of the proposed method and identify dominant factors influencing hydrogen yield.
7. The quality of figures needs significant improvement.

Comments on the Quality of English Language

good

Author Response

Comments 1: Please include a more detailed description of the chemical and mathematical models used to characterize the hydrothermal and dark fermentation processes. Besides, the following related research can be reviewed: a: Two stage stochastic energy scheduling for multi energy rural microgrids with irrigation systems and biomass fermentation; b: Capacity credit evaluation of generalized energy storage considering strategic capacity withholding and decision-dependent uncertainty.

Response 1: We have expanded the manuscript to address the comment by including a broader description of the kinetic and mathematical models used for dark and hydrothermal fermentation. In addition to the Gompertz model, which is widely applied for describing microbial growth and hydrogen production in DF, we now discuss other commonly used approaches, including Logistic, ADM1, and Cone models, as well as structural and unstructured modeling frameworks. Furthermore, we have highlighted that more complex, mechanistic models such as Anaerobic Biomass Fermentation (ABF) are available in the literature to capture detailed biochemical pathways and the dynamic changes of substrates, intermediate metabolites, and gases. These additions provide a clearer picture of the range of modeling approaches, from simple empirical models to more detailed mechanistic descriptions, and their applicability in studying fermentation processes.

Comments 2: It is recommended to add a flowchart or schematic diagram summarizing the overall experimental process to help readers better understand the workflow and logical connections between process stages.

Response 2: Thank you for this valuable suggestion. A schematic diagram summarizing the overall experimental process has been added to the revised manuscript to clearly present the workflow and relationships between the process stages. Additionally, the effect of hydrochar addition is also being investigated, and the corresponding results are currently in the process of publication in Int. J. Hydrogen Energy (2025). Enhanced Dark Fermentation of Kitchen Waste Using Hydrothermal Carbonization Char. Reference: HE_152158

Comments 3: Several recent studies have incorporated biomass fermentation into multi-energy systems, such as “Two-stage stochastic energy scheduling for multi-energy rural microgrids with irrigation systems and biomass fermentation.” and “Energy, exergy, and exergoeconomic cost optimization of wind-biomass multi-energy systems integrated for hydrogen production”. Please compare it in the introduction.

Response 3: Thank you for your comment. At this stage, we do not aim to directly compare our work with multi-energy system studies. Large-scale methane fermentation is already well described in the literature, while dark fermentation combined with thermal processes, such as thermal hydrolysis and hydrothermal carbonization (HTC), remains less explored. Here, we focus on preliminary investigations to assess whether this combination is feasible. Among the suggested publications, we have cited only the one that includes a kinetic model of methane fermentation, as such a model could also be considered relevant for dark fermentation modeling.

Comments 4: More details about experimental conditions should be provided to improve the reproducibility and technical clarity of the work.

Response 4: The manuscript has been updated to include additional details regarding the experimental conditions, enhancing both reproducibility and technical clarity of the work.

Comments 5: Please consider including error bars or confidence intervals for experimental results. Statistical significance tests (e.g., ANOVA) could be used to confirm whether variations in hydrogen yield across temperatures are significant.

Response 5: In response to comments 5 and 7, the revised manuscript specifies the number of replicates, includes error bars representing standard deviations, and presents statistical analyses. All figures have been redrawn using new software to improve quality and readability.

No clear linear relationship was observed between temperature and hydrogen production yield, suggesting that other experimental factors may have influenced the results.

Comments 6: It is suggested to conduct or discuss a sensitivity analysis of key operating parameters to demonstrate the robustness of the proposed method and identify dominant factors influencing hydrogen yield.

Response 6: We agree that the general factors influencing dark fermentation – such as substrate selection, inoculum composition, and physicochemical conditions – have been extensively discussed in previous studies. In our manuscript, these aspects were mentioned only to provide background context. The main focus of our work was to investigate the effect of using liquid residues obtained after thermal processes on the course and efficiency of dark fermentation, rather than to explore the synergistic interactions between different biological or technological factors. Therefore, our study emphasizes the experimental evaluation of this specific medium, which, to the best of our knowledge, has not been widely examined in this context.

Comments 7: The quality of figures needs significant improvement.

Response 7: In response to comments 5 and 7, the revised manuscript specifies the number of replicates, includes error bars representing standard deviations, and presents statistical analyses. All figures have been redrawn using new software to improve quality and readability.

No clear linear relationship was observed between temperature and hydrogen production yield, suggesting that other experimental factors may have influenced the results.

Author Response File: Author Response.docx