Prejudices May Be Wrong: Exploring Spatial Patterns of Vulnerability to Energy Poverty in Italian Metropolitan Areas
Round 1
Reviewer 1 Report
Comments and Suggestions for AuthorsThis paper has investigated the spatial distribution and determinants of vulnerability to energy poverty across 15 Italian metropolitan areas. The study has employed both Principal Component Analysis (PCA) and Geographically Weighted Principal Component Analysis (GWPCA) to identify key factors influencing vulnerability at both national and local scales. The results have highlighted the relevance of factors like employment, socio-economic conditions, and household characteristics, and their spatial variation across regions. The authors aimed to inform more effective energy poverty policies by providing a clearer understanding of local versus national vulnerability drivers. As I read through your paper, I acknowledge the importance of the research topic, exploring spatial patterns of vulnerability to energy poverty in Italian metropolitan areas. However, several methodological choices and the interpretation of results raise some concerns that need to be addressed, before this paper can be accepted!
1. You have utilized PCA to reduce the dimensionality of the dataset and identify the most significant factors contributing to vulnerability to energy poverty. However, I question the appropriateness of using PCA alone in this context. PCA does not take into account the spatial relationships between municipalities, which could be crucial in a study focusing on spatial vulnerability. Why wasn't a method that incorporates spatial dependency, like a spatial regression or Moran’s I, used alongside PCA? This seems like a missed opportunity to capture the full complexity of spatial interactions.
Moreover, how do the authors account for potential multicollinearity among the variables before conducting PCA? It is essential to ensure that the variables included in the analysis do not produce misleading results due to high correlations. Were sufficient diagnostics performed before applying PCA?
2. The GWPCA is a strong methodological choice for exploring spatial heterogeneity, and it is commendable that the authors applied this technique. However, I am concerned that the results are only presented for one metropolitan area, Venice. If GWPCA was applied across 15 metropolitan areas, why weren’t the results for other cities discussed? This omission weakens the overall impact of your paper. I would like to know how consistent the findings are across other regions—do the patterns observed in Venice generalize to other parts of Italy?
3. Additionally, the use of GWPCA provides localized insights, but the selection of bandwidth (i.e., the spatial extent of the analysis) is a critical decision. How was the bandwidth determined, and why did the authors opt for an adaptive bandwidth rather than a fixed one? This needs to be clarified!
4. A major concern I have is that the data used for this study is from 2011. Given that this paper is published in 2024, how do the authors account for the significant temporal gap? Socioeconomic factors, energy prices, and policy measures related to energy poverty have evolved substantially over the past decade, and I am unsure how well these results reflect the current situation. Why was more recent data not included? If the data was unavailable, was this limitation explored in more depth to explain its potential impact on the findings?
5. The authors selected 15 variables related to vulnerability, but I am left wondering about potential omitted variables. Could there be other factors, such as access to renewable energy or changes in urban infrastructure, that also play a significant role in determining vulnerability to energy poverty? A more comprehensive variable selection might have enriched the analysis.
6. The PCA results highlight three components: employment-related factors, individual socio-economic factors, and household socio-economic factors. While this provides a useful framework, the authors do not fully explain the policy implications of these components. For instance, if employment-related factors explain a large part of the variance, what specific policies are needed to address these vulnerabilities? The paper remains vague on how policymakers can act on these findings.
7. Furthermore, the spatial distribution of these components shows some expected trends (e.g., the North-South divide in Italy), but there is little discussion of the unexpected results. For example, you mention a strong "peninsula-island divide" but do not elaborate on the underlying causes. Why is this divide significant, and how does it differ from other regional patterns of vulnerability? More interpretation is needed to make sense of these spatial trends.
8. The GWPCA results for Venice provide valuable localized insights, showing that the elderly population, children, and foreign residents are significant drivers of vulnerability. However, given the large number of metropolitan areas analyzed, why are the results from only Venice discussed in detail? This selective presentation makes me question whether similar patterns were found in other cities, or if Venice is an outlier. The authors should have provided a broader analysis across all metropolitan areas to strengthen their conclusions.
9. Another issue with the GWPCA results is the lack of discussion on the scalability of local-level findings. If the vulnerability patterns identified in Venice do not generalize to other cities, how can national policies be informed by such localized data? The authors should clarify how local-level findings can influence broader policy measures.
10. Your paper makes the case that current policies in Italy focus too much on short-term fixes (e.g., subsidies, tax credits) without addressing the root causes of energy poverty. This is an important point, but I am left wondering how the authors’ findings specifically address these gaps. What long-term strategies do they recommend based on their analysis? While the identification of key vulnerability factors is valuable, the translation of these results into actionable policy recommendations is underdeveloped.
11. The authors also have acknowledged that the policies currently in place may not adequately address household or individual socio-economic factors. However, the paper does not offer concrete suggestions on how to design policies that can better target these issues. A more in-depth discussion of alternative policy frameworks, perhaps informed by case studies from other countries, would be helpful in providing practical guidance.
In short, in my understanding while the paper provides important insights into the spatial dimensions of vulnerability to energy poverty, several methodological and interpretative issues remain unresolved. I strongly suggest revising your paper based on above suggestions. Looking forward to receiving the revised manuscript.
Author Response
We would like to thank the reviewer for the comments, which were useful to improve the manuscript. We are attaching a document presenting our point-by-point response.
Author Response File: 
Author Response.pdf
Reviewer 2 Report
Comments and Suggestions for AuthorsThe introduction gives a good summary of the issues around energy poverty including the problems of an agreed definition, even within the EU. The evidence that the drivers of vulnerability differ with location has been a particularly important finding which should influence policy decisions.
You use general concepts such as ‘the elderly’ when referring to excess temperatures. However, the elderly are not a homogeneous group. Evidence shows that women are more sensitive to ambient temperature than men. Also, young children compared to adults – although this appears to be recognised under indicator 1 in Table 1.
I am surprised that a publication you cite on p4 line 164 published in 2022 uses the term ‘developed countries’. How is this defined? All countries are developing because they are all changing. An alternative is ‘industrialised’.
Line 173/4 – I wasn’t sure what the basis of your claim that Italian cities are potentially more exposed than other European cities to the impacts of expected climatic changes.
P5 I would like some more explanation about the data set. How is it collected? How is verified? A study by the Netherlands Environmental Assessment Agency in 2018 found that it couldn’t account for 13% of all Dutch households due to the nature of their residence e.g. people living in unusual dwellings, such as houseboats, or multi-occupancy dwellings.
P5 As a native English speaker, I find the term ‘elderlies’ uncomfortable – there are more acceptable terms in the academic literature, e.g. older adults (giving the age – as you do). In line 304 you use ‘the elderly population’ so you need to be consistent.
You also have two categories ‘elderlies’, which has an age classification, and ‘retired’ which doesn’t. How do you distinguish between the two? Do you mean that the latter could have left the workforce before the official retirement age (which you should state – not all readers will be familiar with the Italian situation) or are between the official retirement age and your ‘elderlies’ threshold.
It seems rather contradictory that on page 4 you talk about excess temperatures being a major problem for those living in energy poverty, yet your table on 5 refers only to ‘heating’ – surely you need ‘cooling’?!
Please keep in mind that ‘Sustainability’ is a multidisciplinary journal and not all readers who are interested in your paper will be fully familiar with your concepts. You refer to ‘metropolitan areas’. Are these entirely urban? There is evidence to show that energy poverty is different between urban and rural areas – both drivers and policy experiences.
Line 442 ‘peripherical areas’ – do you mean ‘peripheral areas’?
Line 438 ‘peculiar patterns’ – the use of ‘peculiar’ is not correct since this would mean they are unusual or uncharacteristic whereas what you describe as the explanation for the data is not. Although in line 454 you state that the strong peninsula-island divide is surprising – for those of us not so familiar with Italy you need to explain this statement.
You are realistic in recognising that your modelling is based on 2011 data. It would be interesting to compare these results with more up-to-date data – particularly in view of the energy price hikes and the extreme temperatures we’ve experienced since 2011. I would also strongly recommend that you also work with qualitative researchers to do correlation between what your numbers show and what households actually report. I also recommend that you look at some of the work done by the IEA Users TCP and some research done for the European Commission which points to issues you are not addressing, particularly, if I’ve understood correctly that you are taking the household as unified entity. You can have households that appear not to be living in energy poverty but unpacking the household reveals that individual members might be experiencing energy poverty. The issue of multiple occupancy I mentioned above also might hide people who are not registered citizens.
Comments on the Quality of English LanguageThe standard of English is generally good. There are however one or two words which I think are not correct and should be discussed with a native English speaker.
Author Response
We would like to thank the reviewer for the comments, which were useful to improve the manuscript. We are attaching a document presenting our point-by-point replies.
Author Response File: Author Response.pdf
Reviewer 3 Report
Comments and Suggestions for AuthorsExcellent results represented, more results and graphs should be presented. Overall acceptable paper.
Comments on the Quality of English LanguageAcceptable
Author Response
We would like to thank the reviewer for the comments, which were useful to improve the manuscript. We are attaching a document presenting our point-by-point replies.
Author Response File: Author Response.pdf
Reviewer 4 Report
Comments and Suggestions for AuthorsDear Authors,
Based on the analysis of the manuscript, I organized my notes into favorable points of article that make it interesting for publication in Sustainability and the critical points that need to be reviewed to make the manuscript suitable and up-to-date in light of the studies and public policies around the world that have been advancing with the implementation of this type of work. The key contributions and areas for improvement are as follows:
1) Identification of Vulnerability Components: The paper identifies three main components of vulnerability to energy poverty: job-related factors, individual socio-economic conditions, and household socio-economic conditions. These insights are critical for policymakers to tailor interventions at the national level.
2) Methodological Innovation: The use of both PCA (Principal Component Analysis) and GWPCA (Geographically Weighted Principal Component Analysis) is a novel approach. This allows the study to assess vulnerabilities at both national and local levels, offering a detailed spatial distribution of vulnerability factors that vary between regions.
3) Policy Implications: The study’s findings provide clear policy directions. For instance, policies can be designed to focus on unemployment in northern regions, and household economic support in southern areas. Additionally, the GWPCA offers valuable insights for localized interventions, making it an effective decision-support tool.
4) Addressing Energy Poverty Holistically: By focusing on vulnerability rather than solely on energy poverty, the study accounts for diverse factors such as climate, age, income, and household composition. This broadens the scope of understanding and addressing energy poverty across regions.
Areas for Improvement:
1) Data Limitations: The use of 2011 census data is a significant limitation, as the analysis may not reflect recent socio-economic or demographic changes. Incorporating more recent data would increase the relevance of the findings.
2) Limited GWPCA Application: The GWPCA results are only fully presented for Venice. Expanding this analysis to other metropolitan areas could strengthen the study's findings and provide more comprehensive insights for regional policymakers.
3) Clarification of Policy Gaps: While the paper identifies gaps between current policies and the multidimensional nature of energy poverty, further exploration of these gaps and concrete policy recommendations would enhance its practical relevance.
4) Discussion of Multidimensional Poverty: The article briefly touches on the limitations of existing energy poverty definitions but could provide a deeper analysis of how these limitations affect policy outcomes. A more extensive comparison between vulnerability and traditional energy poverty measures would be valuable.
5) Visual Representation: While the paper includes maps and figures, more intuitive visualizations could help clarify the spatial distribution of vulnerability factors and make the findings more accessible to non-expert readers.
Incorporating these improvements could help ensure the article’s readiness for publication.
Good job
Author Response
We would like to thank the reviewer for the comments, which were useful to improve the manuscript. We are attaching a document presenting our point-by-point replies.
Author Response File: Author Response.pdf
Reviewer 5 Report
Comments and Suggestions for AuthorsDear authors,
This research is very interesting, well presented, the results are presented very accurately.
I suggest reviewing the text for the presence of editorial errors in the writing of some words (e.g. Deter-minants, effec-tively, etc.)
The method of presentation of the indicators, when compared, is extremely interesting and allows for a rapid evaluation.
I congratulate the authors for having been able to compare so many indicators in an effective way. Your work highlights how data is fundamental and systematization
with graphical visualization is extremely useful for policy makers.
The replicability of the analyzes conducted throughout the Italian territory would be extremely useful, especially if carried out with updated data.
I encourage you to publish the detailed results of your research,
even if the data is old, because it highlights an interesting situation of
energy poverty that is not immediately evident, given the high number
of municipalities present in Italy.
Author Response
We would like to thank the reviewer for the comments, which were useful to improve the manuscript. We are attaching a document presenting our point-by-point replies.
Author Response File: Author Response.pdf
Round 2
Reviewer 1 Report
Comments and Suggestions for AuthorsThank you for incorporating majority of my suggestions and providing apt responses to many that required your replies. I agree with your explanations. Thank you.
Reviewer 4 Report
Comments and Suggestions for AuthorsDear authors,
After re-reading the manuscript, I have found that the entire structure of the article (introduction, references, methodology and discussion of results) has been adapted and improved. In this sense, I consider the manuscript suitable for publication in Sustainability.
This is the opinion.
Good work!
Reviewer
