Effects of Air Pollution on Human Health and Costs: Current Situation in São Paulo, Brazil

Round 1

Reviewer 1 Report

Effects of air pollution on human health and costs: Current Situation in Sao Paulo, Brazil

Abstract

Air pollution is a highly topical subject. The injurious effects on human health are becoming an important topic in addressing the problems of climate change, pollution and , even  more recently, the potential for the spread of Corvid-19, the latter is yet to be established in peer reviewed journals.

This is a timely paper. He is aimed at studying the costs of respiratory illness on the hospitalisation of respiratory diseases. The translation of costs into hospitalisation provides one way of translating costs into political action based on economics. This is an important way to advance the need to protect the environment as well as to understand that human costs can often have unseen by consequential economic costs for society.

Introduction

Growing urban development and new technologies along with human population growth and development inevitably give rise to increased urbanisation and air pollution.  The paper outlines the challenges including changes in the way energy is used and produced. Fossil fuels and biomass have created air pollution on a scale that is unprecedented. The effects of air pollution on the human body. Medical research has developed to correlate the impact on human health, the respiratory system. Particularly significant is the impact on children. In Brazil, a staggering 22,000 people lose their lives prematurely because of exposure to pollutants.

The paper identifies children, the elderly and people with chronic disease to be the most vulnerable.

Outline and organisation of the paper

The first section is an overview of the sources of pollution in air quality. Pages 3- 5 set out very clearly the main causes of pollution, their identification and the breakdown of the different chemicals, particulates and their impact on human health.

Pages 5-8  provides a tabular presentation of the data, including rainfall index and levels of exposure to pollutants. Page 8 moves to a discussion of the main results of the research. This is the main part of the paper and includes monthly hospitalisation,  an explanation of costs and also the time-scale of the research. Pages 911 provide well illustrated data. On page 12 there is an important section on the behaviour of different forms of emissions and how the exposure to increased blood pressure can cause problems n hypersensitive outdoor workers. Page 12 looks at the effects of CO and NO2 emissions. Different years are used to estimate the behaviour of these emissions from 2010 to 2017. An important and relevant element in the amount of pollution is the implications of rainfall. On page 18 there is a correlation between the factors of hospitalisation for respiratory diseases and the costs. This is analysed in some detail from pages 18-26.

Conclusions ( page  20-21) and references.

 It is clear from the research that the level of hospitalisation for respiratory diseases behaved inversely to monthly rainfall.  In dry months the amount of pollutant concentrations in the atmosphere tend to increase and this leads to a rise in the number of hospitalisations for respiratory diseases. Air quality is poor during the driest months between June and September. There are many lessons to be drawn from this paper. Placing a cost on human health is significant, especially if the last sentence is considered:

 Brazil should implement stricter policies to improve the air quality of its major cities and develop a viable alternative to replace diesel vehicles.

The lessons from this excellent paper have global significance.

The paper is well prepared and references, footnotes are helpful and useful. The paper is an important contribution to knowledge in this area of study.

Author Response

Reviewer #1

Thank you very much for the compliments to our article. We took some suggestions from you and inserted in the article

Reviewer 2 Report

1. References in the main-text are incorrect. Please refer to the guidelines
2. Introduction and literature review need to be separated.
3. The interpretation of empirical analysis is rather ambiguous. Need to generalize
4. It is necessary to comprehensively describe the policy implications in the conclusion section.

Author Response

References in the main-text are incorrect. Please refer to the guidelines
Reply: We had to correct the citations in the text and the way of referencing in the bibliographic references item

Introduction and literature review need to be separated.
Reply: This was done as requested by you

The interpretation of empirical analysis is rather ambiguous. Need to generalize.
Reply: The city of São Paulo is surrounded by mountains and has a cold and dry climate in winter, which reduces the dispersion of polluting gases; few or perhaps no cities in Brazil have similar conditions. It is not possible to generalize to Brazil due to its great territorial extension and the great climatic and geographical variation of the country.

It is necessary to comprehensively describe the policy implications in the conclusion section.
Reply: This was inserted in the last paragraphs of the results and discussions.

Thank you very much for your suggestions, they contributed to the improvement of our article.

Reviewer 3 Report

The manuscript deals with an interesting topics, that is the effect of air pollution. It is well written, however I have some suggestions for the authors to improve their work.

These are my suggestions:

• It is better not to introduce subsections in the introduction.
• In many tables there is no indication of the font of the data.
• In table 2 it is useless to repeat “Short exposure time” (which can be moved to the caption).
• Did the authors check for the stationarity of the data before applying correlation coefficient?
• The correlation coefficient can also take negative values (its range is from -1 to 1)
• In tables 4 and 5 the row “Subtotal” should precede the row “Average”
• I think that the reader could benefit from a reorganization of table 6 collecting the rows Hospitalization and the rows Cost, avoiding continuous jumps.
• What does “good and optimal correlation” mean? At page 8 the correlation is interpreted in terms of “strong”, “moderate” and so on.
• In Table 7 there are various correlation coefficients equal to 1. Maybe it is better to consider more than one decimal. A unit correlation coefficient has a very special interpretation (maybe it is 0.97 or 0.99).

 

Author Response

It is better not to introduce subsections in the introduction.
R: We had to modify the introduction. We divided it into an introduction and a review of the literature.

In many tables there is no indication of the font of the data.
R: We had inserting the source in table 1 and table 2. The others already had the sources, except tables 6 and 7, which were the results of our research

In table 2 it is useless to repeat “Short exposure time” (which can be moved to the caption).
R: We made the changes. Thanks for the suggestion.

Did the authors check for the stationarity of the data before applying correlation coefficient?
R: Yes, that was verified. Most of the data goes from January to September. Most of the data shown in the figures show this growth (except for O3)

The correlation coefficient can also take negative values (its range is from -1 to 1)
R: this was written in the second line of the paragraph above the correlation ranges “Statistical analysis of the data was performed with Pearson’s correlation coefficient; the direction of this correlation (whether positive or negative)”

In tables 4 and 5 the row “Subtotal” should precede the row “Average”
I think that the reader could benefit from a reorganization of table 6 collecting the rows Hospitalization and the rows Cost, avoiding continuous jumps.
R: Ok, that had to be done, thank you very much for your suggestion

What does “good and optimal correlation” mean? At page 8 the correlation is interpreted in terms of “strong”, “moderate” and so on.
R: We had excluding the good and excellent correlation of the texts. They are applicable only for mathematical models.

In Table 7 there are various correlation coefficients equal to 1. Maybe it is better to consider more than one decimal. A unit correlation coefficient has a very special interpretation (maybe it is 0.97 or 0.99).
R: We had correcting that. In reality, the amount of data is high to fit the table, so we chose to use only one decimal unit.

Thank you very much for your suggestions, they contributed to the improvement of our article.

Reviewer 4 Report

It is a good paper.

Author Response

Thank you very much for your suggestions, they contributed to the improvement of our article.