Review Reports

Response to Reviewer 1 Comments

1. Summary

Thank you very much for taking the time to review this manuscript. Please find the detailed responses below and the corresponding revisions/corrections highlighted/in track changes in the re-submitted files.

2. Point-by-point response to Comments and Suggestions for Authors

Comments 1: I thank the Authors for allowing me to conduct this review, as I believe the proposed topic is interesting, timely, and highly relevant. I believe that the first part of the paper, up to the results section, is well written, properly referenced, and appropriate for the journal’s standards. Unfortunately, from the Results section onward, I think major revisions are needed. The paper would benefit from a clearer separation between a section dedicated to the results, to better highlight them, as they are numerous, and a distinct discussion section, since at the moment the discussion points are scattered throughout the text and the same ideas are often repeated. Having a separate discussion section would allow for a more critical analysis of the findings, which become particularly interesting from section 3.5 onwards.

Response 1: We sincerely thank the reviewer for the constructive and insightful comments. We appreciate the recognition that the introduction, methods, and early sections of the manuscript are well written and appropriate for the journal. We fully agree that improved structure and clarity in the latter part of the manuscript will significantly enhance the readability, coherence, and scientific impact of the work. In response, we have now separated the Discussion into a stand-alone section beginning on Page 11, Line 345 of the revised manuscript, in line with your recommendation, and we have reordered and renumbered all subsections accordingly to ensure a clear distinction between Results and Discussion.

Comments 2: It would also help to explain better why other sustainability indicators, beyond GHG emissions and water footprint, were not considered. Separating the two sections and avoiding the repetition of similar concepts across different results would also help reduce the overall length of the paper, which is currently rather long.

Response 2: We thank the reviewer for this valuable comment. We agree that clarifying the choice of indicators strengthens the manuscript. In this study, we focused on GHG emissions and water footprints because they are among the most widely used and policy-relevant high-level sustainability indicators for food systems, with consistent, well-validated coefficients available for all food categories included. These indicators are directly linked to national and EU monitoring frameworks on climate and resource use, and they allow for transparent comparison across households and food types. Other recognized sustainability indicators—such as material footprint, ecological footprint, carbon intensity, resource efficiency, food loss percentage, nutritional adequacy indicators, or environmental-economic productivity indicators—were not included because incorporating these indicators would have required assumptions beyond the scope of the current study and could’ve add substantial content to current manuscript which would be beyond the permitted length of articles by this journal. For these reasons, we selected GHG emissions and water footprint as the most robust and consistently quantifiable indicators for this dataset, while acknowledging in the Discussion that future work could expand the framework to include additional sustainability indicators as data availability improves.

Comments 3: Finally, throughout the paper, I recommend including the first author names in the references, as using only numbered citations makes the reading process much more difficult.

Response 3: We thank the reviewer for this helpful suggestion. We appreciate that numbered citations can make the reading experience less intuitive, particularly in sections where multiple references appear close together. However, the journal Clean Technologies follows the MDPI author-guidelines, which require numbered citation style in both the text and reference list. To ensure full compliance with the journal’s formatting standards, we must retain the numerical citation format throughout the manuscript.

5. Additional comments

Line 73: abbreviation not in line “GHG emissions (GWP)”: Thanks for your comment, we removed the term “(GWP)” from Page 2, Line 74.

Line 99: There is a missing period at the end of the sentence: Thanks, we added that as well. Please check Page 3, Line 99.  

Line 197: The abbreviation has already been introduced “Global warming potential (GWP)”: Thanks, corrected accordingly.

Line 211: Please cite the first author and not only the references: We thank the reviewer for this observation. We would like to clarify that the manuscript follows the journal’s required referencing style, which uses numbered citations in the text without author names. This format is part of the journal’s template and submission guidelines, and cannot be modified by the authors

Figure 1: Please standardize the capitalization and specify in the caption whether the data refer to the vertical or horizontal axis. In its current form, the figure is unclear.

Response 1: Thank you for your helpful comment. We have revised Figure 1 to improve clarity and consistency. Specifically:

1. Caption Clarified
   The caption has been updated to explicitly state that:
• The horizontal axis displays the food categories, and
• The vertical axis represents the average food waste generated per household per week (g).

Revised caption:
“Figure 1. Average food waste items per wet weight generated by Irish households. The horizontal axis lists food categories, and the vertical axis presents average waste per household per week (g).”. Please check page 9, line 225.

Lines 217–218: I would not highlight the difference between bread and vegetables, as it is only 0.02%. Please rephrase the sentence: We appreciate the reviewer’s observation. We have revised the sentence to avoid over-interpreting the 0.02% difference between bread and vegetables. The sentence now reads: ‘The data on food waste distribution indicates that bread (15.62%), vegetables (15.60%), and fruits (15.23%) are the predominant categories of waste by weight. Please check the relevant section on Page 9, Lines 265 to 266.

Line 216-224: The numbers reported in these lines do not match those shown in Figure 1, which makes this section somewhat confusing. I suggest aligning the figure with the data (or vice versa). Alternatively, you could create a new figure specifically for the data presented in these lines to make the results clearer to the reader.

Response: Thank you for pointing out this inconsistency. You are correct that the text originally reported percentage distributions, whereas Figure 1 presented absolute waste quantities (g/household/week), which created confusion. To resolve this: We have revised the text in Lines 257–265 to match the actual numeric values shown in Figure 1 (i.e., absolute quantities).

Line 223-234: Not results but discussion: We moved this section to Discussion on Page 12, Line 375.

Line 235-238: These four lines do not appear to be connected to the rest of the paragraph, and they are not part of your results. Therefore, they should be moved from this section to the Discussion: Thanks for the comment. After careful consideration we removed this section.

Figure 2: The items on the horizontal axis are difficult to read; please make them clearer or improve their readability.

Response 2: Thank you for this valuable comment. We have revised Figure 2 to improve the readability of the horizontal-axis item labels

Line 314 and 319: Errors at the beginning of these sentences. Thanks, we corrected them accordingly.

Linea 326: It is not clear why the value for Spain is in parentheses and why a global value is added at the end ('Spain (47.70 m³ per household) and 27 m³ globally'). The comparison data should be presented consistently. If a global value is included, please relate your results directly to it, and then choose at most one country with a higher value and one with a lower value for comparison.

Response: Thanks for your suggestion. We revised the content to include only volumetric values per household and removed the irrelevant values.

Line 326-328: Given this specification, the comparison is not valid, as you are comparing different types of data. Please keep only the global value as the reference for comparison: We thank the reviewer for this important clarification. We fully agree that the comparison presented in this section was not methodologically valid, as it juxtaposed values derived from different data types and system boundaries. To maintain scientific consistency, we have removed the disaggregated comparison and now report only the global aggregate value as the reference point, in line with the reviewer’s recommendation. This ensures that all comparisons in the Results section are based on methodologically compatible datasets and avoids misleading interpretation.

Line 332-336: This should be moved to the methodology section if it is not already included there: We moved them to Page 6, Line 183. Please check the revised manuscript.

Line 372-372: This section repeats content already presented in lines 256–312: We removed this section in line with your suggestions.

Line 391-420: Move to discussion: Done, please check the revised manuscript. Page 12, Line 465.

Line 454-462: This paragraph is completely disconnected from the rest and does not represent one of your results: We thank the reviewer for pointing this out. The paragraph in Lines 454–462 has been removed entirely to maintain clarity and ensure that the Results section includes only outputs directly derived from our analysis.

Response to Reviewer 3 Comments

Summary

Thank you very much for taking the time to review this manuscript. Please find detailed responses below and the corresponding revisions/corrections highlighted/in track changes in the re-submitted files.

Point-by-point response to Comments and Suggestions for Authors

Comments 1: Were there any criteria for selecting participants to compose the research sample?

Response 1: We appreciate this observation. We have now provided clear eligibility and inclusion criteria in Section 2.1. Participants were required to be 18 years or older and responsible for some aspects of food purchasing or management within the household. Participation was voluntary, nationwide, and anonymous. No exclusion criteria related to income, nationality, education, or dietary preferences were applied to avoid restricting representation. This information has been added on page 4, section 2.1 line 113 of the revised manuscript: “Participation was open to adults (≥18 years) residing in any of the 26 counties of the ROI. Eligibility required that participants representing households were involved in at least purchasing, handling or managing food and food waste in the household.”

Comments 2: Does the final sample (1,000 valid cases) proportionally represent all 26 counties of the Republic of Ireland? If not, could this have introduced bias in the data analysis and presentation of results?

Response 2: We thank the reviewer for highlighting the importance of representativeness. The final dataset includes valid responses from all 26 counties of the Republic of Ireland. However, we acknowledge that, females, higher-educated individuals, and higher-income and urban households were slightly over‐represented, which is typical of voluntary online surveys. To prevent regional bias, we did not perform comparative analysis between counties or sub‐regions and interpreted all findings at population‐average level. This is now clarified in the limitations (section 5.1 page 25, lines 914-919:

” This study’s online voluntary response format resulted in an over-representation of females, higher-educated individuals, and higher-income and urban households compared with existing Irish national survey data. While the sample covers all 26 counties, the demographic skew may limit the generalizability of behaviour-waste relationships to under-represented groups (e.g., lower-income, lower-education). To mitigate this, no regional or subgroup comparisons were made, and results were interpreted at the population level.”

Comments 3:  Furthermore, did the sample consider a certain proportion of male and

female respondents, as well as demographic aspects (education level, individual and/or family income

level, etc.) representative of the Irish population profile? If not, could this also have introduced bias in

the data analysis and presentation of results?

Response 3: We thank the reviewer for this important observation. As indicated under comments 3 the study collected full demographic information including gender, education, income, household type, ethnicity, settlement status and dietary patterns. While the sample represents a broad cross-section of Irish households, comparison with national statistics indicates modest over-representation of females, higher-income households and individuals with tertiary education. To avoid bias, no behavioral or waste-impact comparisons were made between demographic subgroups. All reported relationships therefore reflect population-level patterns rather than stratified inference. This demographic skew has been explicitly acknowledged in the revised results and limitation sections (section 3.1 page 8, lines 233 – 244)

 “The demographic profile of the sample (as shown in Table 2) reflects a heterogeneous mix of Irish households, with the majority (71%) aged between 25 and 54 years, corresponding to the most active food‐purchasing and family management stages. Women constituted a greater share of respondents (56.8%), a pattern that aligns with the gendered responsibility for domestic food provisioning reported in many European households. Educational attainment was rel-atively high, with 33.2% holding postgraduate qualifications, consistent with the online survey mode typically attracting more educated respondents. The sample also showed strong urban representation (58.9%). Collectively, these characteristics suggest that the sample constitutes a broad but slightly more affluent and educated segment of Irish households “

Comments 4: The cross-sectional survey was conducted over a fifteen-month period, beginning in late April 2023 and concluding in early August 2024." Considering this statement, was any type of test performed to assess whether it would be possible to sum the waves of data collection ("subsamples") in the reported period without creating any type of bias?  

Response 4: We appreciate this important observation. Because the data collection spanned 15 months, we evaluated whether food waste volumes varied significantly across quarterly collection periods. A one-way ANOVA test was conducted comparing household weekly waste estimates across four quarterly subsamples. No significant difference was observed, indicating stable waste reporting over time. In addition, details on subgroup analyses are outside the scope of this paper and has been included a separate manuscript which focuses on sociodemographic and behavioral drivers of waste volumes, currently under review.

Comments 5: Were there any missing data or outliers? If so, how were they handled?” Furthermore, a Table and two or three paragraphs presenting the profile of the research participants are missing.

Response 5: We thank the reviewer for highlighting this issue. The original dataset contained approximately 1,300 entries. As part of the data-cleaning process, cases with missing values on key food-waste quantity and sociodemographic variables were removed via listwise deletion. These procedures are now described in Section 2.2. and a table of sociodemographic profile of the sample has been added to the manuscript (page 4, lines 130-135):

“The initial dataset comprised 1,300 responses. Cases with missing values on food-waste quantity and sociodemographic variables were removed via listwise deletion. Additional cleaning involved checks for internal inconsistencies and removal of duplicate entries. Outliers were screened using z-scores; values beyond ±3 SD were retained when plausible. The final analytical sample consisted of 1,000 valid cases (a reduction of ~23%). The sample’s sociodemographic characteristics are presented in Table 2.”

Comments 6: Subsection 3.11 Limitations would be better placed within section 4 Conclusions. Furthermore, if there was any research bias regarding the sample composition in relation to the respondents’ profile (see previous questions), it would be important for the authors to explicitly state these aspects

Response 6. We thank the reviewer for this recommendation. The Limitations subsection has now been moved from Section 3 to Section 4, positioned after the main Conclusions. It has also been expanded to acknowledge sample biases as highlighted in earlier comments. (section 5.1, page 25 line 905-919):

“5.1. Limitations

A key limitation of this study is the use of water footprint coefficients sourced from Korean studies [25], which may not fully reflect the water use characteristics of Irish agricultural sys-tems. Agricultural water footprints are influenced by numerous regional variables including climate, irrigation practices, and crop/livestock types. The absence of publicly available Irish-specific WFi data necessitated reliance on international coefficients, which may introduce estimation bias. Future efforts should aim to develop regionally appropriate WFi databases to improve the geographic validity of sustainability indicators such as the EN-EC Index. This study’s online voluntary response format resulted in an over-representation of females, high-er-educated individuals, and higher-income and urban households compared with existing Irish national survey data. While the sample covers all 26 counties, the demographic skew may limit the generalizability of behaviour-waste relationships to under-represented groups (e.g., low-er-income, lower-education). To mitigate this, no regional or subgroup comparisons were made, and results were interpreted at the population level.”

Comments 7; In the Conclusions, it is appropriate for the authors to reinforce the theoretical and practical (or managerial) implications of the research in greater depth. It would also be appropriate for the authors to suggest areas for future studies

Response 7; We appreciate this constructive suggestion. The Conclusion section has been expanded to include clearer theoretical implications of the EN–EC Index for sustainability research, as well as practical (policy and household) interventions. We also provide specific recommendations for future research, including methodological enhancements (e.g., quota sampling, waste auditing) and applications of the EN–EC Index in policy and industry. This can be found under section 5, page 24, line 852:

“5. Conclusions

This study presents an innovative approach to assessing the environmental and economic impacts of household food waste through the development of the Environ-mental-Economic Footprint (EN-EC) Index. By integrating carbon emissions, water footprint, and economic costs, the EN-EC Index provides a comprehensive framework for evaluating the dual burden of food waste in Ireland. This multidimensional assessment surpasses traditional single-focused methods, offering policymakers a more data-driven tool to develop effective waste reduction strategies.

The findings highlight the disproportionate environmental and financial impact of specific food categories, particularly meat, bread, and dairy waste, underscoring the need for targeted interventions to enhance sustainability efforts. Red meat, despite comprising only 4% of household food waste by weight, accounts for over 50% of the total carbon footprint, emphasizing the urgent need for policy measures to mitigate high-impact food waste. Similarly, bread and dairy waste contribute significantly to economic losses due to over-purchasing, misinterpretation of expiration labels, and improper storage.

A key insight from this study is the weak relationship between economic and en-vironmental costs of food waste. This disconnect arises due to market distortions, government subsidies, and externalized environmental costs, which lower the economic burden of high-impact foods while their environmental footprint remains significant. Addressing these inefficiencies requires policy-driven pricing mechanisms, such as: Eco-taxation on high-waste foods, aligning food prices with their environmental impact; Reallocating subsidies from livestock production toward sustainable protein alternatives.

This study also benchmarks Ireland’s food waste patterns against those of other countries, identifying best practices in waste reduction policies: France’s supermarket food donation laws, which significantly reduced retail-level waste; Denmark’s public awareness campaigns, which led to a 25% national reduction in household food waste; China’s “Clean Plate” initiative, successfully targeting plate waste in the food service sector. Furthermore, a 50% reduction in household meat waste was modeled to estimate quantifiable benefits, demonstrating: CO₂ emissions reduction of 2.50 kg CO₂-eq., Water savings of 563.50 liters, Economic savings of €3,623.48 annually per household. These findings emphasize the potential impact of policy-driven interventions, reinforcing the importance of waste reduction strategies that combine financial incentives, consumer education, and regulatory measures.

Finally, our study focuses on immediate economic and environmental impacts, we acknowledge that a life-cycle costing (LCC) approach or an extended cost-benefit analysis could provide a more holistic perspective by incorporating these long-term effects.

From a practical perspective, the EN–EC Index can support public institutions, local authorities and waste‐management agencies in prioritizing targeted interventions, guiding food redistribution programmes, and informing date‐labelling reforms, dy-namic pricing and consumer education. For policymakers, the index offers a deci-sion-support tool that can be adapted to evaluate policy scenarios, track SDG 12.3 pro-gress, and identify the cost–benefit balance of behavioural or infrastructure-based interventions.

Future research could integrate environmental damage valuation, carbon pricing, and ecosystem service losses to better capture the full financial burden of food waste. The EN–EC framework could also be strengthened by incorporating direct waste measurement (e.g., compositional audits, sensor-enabled smart bins) to complement self-reported estimations. Applying demographic weighting or quota sampling would also improve representativeness and allow behavioural and socioeconomic subgroup analyses.. By providing data-driven insights, the EN-EC Index contributes to the global discourse on food sustainability, offering policymakers a practical tool to design targeted and effective waste reduction strategies. Addressing food waste through inte-grated policy, consumer education, and supply chain interventions is essential for building a more sustainable and resource-efficient food system in Ireland and beyond.”