Influence of Time–Activity Patterns on Indoor Air Quality in Italian Restaurant Kitchens
, Davide Campagnolo 1, Francesca Borghi 2, Alessio Carminati 1, Giacomo Fanti 1, Sabrina Rovelli 1, Carolina Zellino 1, Rocco Loris Del Vecchio 3, Giovanni De Vito 3, Andrea Spinazzé 1, Viktor Gábor Mihucz 4, Carlo Dossi 5, Mariella Carrieri 6,*, Andrea Cattaneo 1,* and Domenico Maria Cavallo 1Round 1
Reviewer 1 Report
Comments and Suggestions for AuthorsThe readability of figures 1-3 is poor. The resolution and scale of the graphs need adjustment.
The author conducted measurements of various pollutants. However, the analysis in the results section is too simple and superficial compared to the level of the measured data.
Additionally, the conclusions drawn are very simplistic. To be the publication of this paper in 'Atmosphere,' the innovative points of this paper need to be further elaborated.
Comments on the Quality of English LanguageOverall improvement in the quality of English is necessary.
Author Response
Comment 1: The readability of figures 1-3 is poor. The resolution and scale of the graphs need adjustment.
Response 1: Thanks for this very useful recommendation. We realized that the overall quality of the figures was poor, so we have redone them improving also resolution and scale. We have also modified the sequence of figures in the SMs to improve readability.
Comment 2: The author conducted measurements of various pollutants. However, the analysis in the results section is too simple and superficial compared to the level of the measured data.
Response 2: We would like to thank the Reviewer for this comment. However, the present study wanted to perform an exploratory analysis of the real-time data collected during the two sampling campaigns. Considering this, we decided to use a double approach that, in our opinion, was enough to reach that goal. Indeed, both a statistical analysis (i.e., non-parametric methods for testing whether samples originate from the same distribution) and a graphical comparison (i.e., performing a preliminary correlation of short-term concentration trends and peaks with specific events) were carried out. This allowed us to underline the importance of collecting a Time Activity Diary that is as complete and detailed as possible. Anyway, we remain opened to implement data analysis should we receive more detailed information on the areas to improve and agree with the Reviewer believing that the measured data deserve more in-depth analysis. In light of this, we have implemented the future developments section of this study.
Comment 3: Additionally, the conclusions drawn are very simplistic. To be the publication of this paper in 'Atmosphere,' the innovative points of this paper need to be further elaborated.
Response 3: We agree with the Reviewer that the conclusions were too brief and simplistic. Therefore, we have added quantitative information to better substantiate the main findings of our work, while maintaining the bullet-point format of the paragraph. What we think is the most relevant innovative point of our work (i.e. the real-time multipollutant monitoring approach focused not only on cooking but also on washing/cleaning) was now reported in the “Strengths and weaknesses” paragraph.
Comment 4: Overall improvement in the quality of English is necessary.
Response 4: Thank you for this suggestion. We have revised all the manuscript text and found grammatical errors, typos, as well as punctuation and article usage issues. Hope now we had effectively corrected all the major errors in grammar, punctuation and style.
Reviewer 2 Report
Comments and Suggestions for AuthorsThis is an interesting study, aimed at evaluating the impact of the main activities carried out within restaurant kitchens and some key air pollutants such as the ultra-fine particles (UFPs), nitrogen dioxide (NO2), ozone (O3), Total Volatile Organic Compounds (TVOCs) and formaldehyde (HCHO) indoor air concentrations, which were determined using real-time monitors. Both the approach and methodology presented would be interesting for other scholars working in the related field, and the conclusions derived from the study are also offering very useful findings. Overall, this is an excellent contribution to the body of knowledge in the associated field. Otherwise. I do not have any further comments or suggestions for further improving this paper.
Comments on the Quality of English LanguageMinor editing of English language required
Author Response
Comment 1: This is an interesting study, aimed at evaluating the impact of the main activities carried out within restaurant kitchens and some key air pollutants such as the ultra-fine particles (UFPs), nitrogen dioxide (NO2), ozone (O3), Total Volatile Organic Compounds (TVOCs) and formaldehyde (HCHO) indoor air concentrations, which were determined using real-time monitors. Both the approach and methodology presented would be interesting for other scholars working in the related field, and the conclusions derived from the study are also offering very useful findings. Overall, this is an excellent contribution to the body of knowledge in the associated field. Otherwise. I do not have any further comments or suggestions for further improving this paper.
Response 1: Thank you very much for this positive comment.
Comment 2: Minor editing of English language required
Response 2: Thank you for having pointed out this manuscript weakness. We carefully revised all the text and found some grammatical errors, as well as some punctuation, article usage, and improved phrasing issues to correct for ensuring more clarity and coherence. Hope now we had successfully corrected all the major grammatical errors and typos.
Reviewer 3 Report
Comments and Suggestions for AuthorsThis study investigates the relationship between the professional activities carried out in restaurant kitchens and some key air pollutants by monitoring a bunch of pollutants. The overall quality of the manuscript is high, the manuscript can be accepted after addressing the following concerns.
1. Check the gaps on page 3.
2. It is recommended to summarize the experimental devices (accuracy, brands, etc.) in a table for improved clarification for readers.
3. For video analysis, is that analysis based on manual count?
4. Why not use advanced machine learning algorithms to determine the data sensitivity and relationship?
5. Please consider adding the following literature to enhance the introduction. Some example literature is listed as follows:
l https://www.sciencedirect.com/science/article/pii/S2352710224014402
l https://link.springer.com/article/10.1007/s42757-023-0183-9
6. Check Figure 1-3, some text is distorted.
7. The limitation of the study should be clarified.
8. The conclusion is too general. Please considering includes some quantitative results to highlight the effect of different influential factors.
9. Please carefully check grammar and typo errors in the manuscript.
Author Response
This study investigates the relationship between the professional activities carried out in restaurant kitchens and some key air pollutants by monitoring a bunch of pollutants. The overall quality of the manuscript is high, the manuscript can be accepted after addressing the following concerns.
Thank you for this positive comment and for the very useful suggestions, which helped us to greatly improve the manuscript quality.
Comment 1. Check the gaps on page 3.
Thank you, this oversight has been corrected as indicated.
Comment 2. It is recommended to summarize the experimental devices (accuracy, brands, etc.) in a table for improved clarification for readers.
The authors warmly thank the Reviewer for her/his comment. As suggested, the experimental devices and their characteristics were put in a dedicated table in Section 2.1, to get a complete picture of instrumental features at a glance.
Comment 3. For video analysis, is that analysis based on manual count?
Yes, the videos were manually analysed by a research team member to extract time-resolved information about the activities carried out in the kitchens. This is now reported more clearly in the revised version of the manuscript.
Comment 4. Why not use advanced machine learning algorithms to determine the data sensitivity and relationship?
Thanks for pointing this out. This paper was an exploratory analysis of the real-time data collected during the sampling campaigns. Accordingly, at this phase, we did not consider advanced machine learning algorithms to determine and/or improve data sensitivity. However, this suggestion can be very useful for future developments of the present study. A machine-learning based approach to improve data quality can be applied (see for instance Chojer et al 2022. Can data reliability of low-cost sensor devices for indoor air particulate matter monitoring be improved? An approach using machine learning. Atmos. Environ. 286, 11925). Moreover, the use of multiple linear regression analysis can be considered to identify and quantify the relationship between the pollutant concentrations and the main activities simultaneously performed by professional cooks and all the kitchen staff, and peak detection algorithms could be used for a more robust analysis of short-term spikes. These considerations have been added to the text while discussing about future developments of this research, with new references.
Comment 5. Please consider adding the following literature to enhance the introduction. Some example literature is listed as follows:
l https://www.sciencedirect.com/science/article/pii/S2352710224014402
l https://link.springer.com/article/10.1007/s42757-023-0183-9
Thank you very much for your suggestion. We are aware that the introduction could be enhanced by citing other literature. However, our choice was to focus on kitchen environments and cooking/washing/cleaning emissions. The suggested papers are actually very interesting, but they deal with aircraft cockpits and school classrooms characterized by different indoor pollutants and emission sources with respect to kitchens, so we were not able to transfer that information in a straight way into our manuscript. We are sorry for that and remain opened to integrate the requested changes into the manuscript should we receive more detailed information on the areas to improve.
Comment 6. Check Figure 1-3, some text is distorted.
Thanks for this very useful recommendation. We realized that the overall quality of the figures was poor, so we have redone them improving also resolution and scale.
Comment 7. The limitation of the study should be clarified.
In our opinion, we had already addressed one of the major study limitations in the original version of the text, which is the poor sample size (15 restaurants) and the challenge of deriving generalized conclusions due to the large variability in occupational activities performed day by day and across kitchens. However, thanks to your suggestion, we realized that another weakness should be acknowledged, so we added the following sentence to the “Strengths and weaknesses” paragraph. “Another limitation of the study is the reliance on real-time data from alternative monitoring methods rather than reference-grade instruments. These methods, particularly those used for measuring HCHO, O3, and NO2, are typically characterized by lower precision and accuracy. While we were able to correct formaldehyde levels using reference standards, we were unable to do the same for O3 and NO2.”
Comment 8. The conclusion is too general. Please considering includes some quantitative results to highlight the effect of different influential factors.
We have now tried to improve the conclusion by reporting quantitative results to substantiate some of the main findings of our work.
Comment 9. Please carefully check grammar and typo errors in the manuscript.
Thank you very much for this suggestion. We carefully revised all the text and found some grammatical errors, as well as some punctuation, article usage, and improved phrasing issues to correct for ensuring more clarity and coherence. Hope now we had successfully corrected all the major grammatical errors and typos.
