A Kalman Filter Scheme for the Optimization of Low-Cost Gas Sensor Measurements

Round 1

Reviewer 1 Report

Comments and Suggestions for Authors

The manuscript applied the Kalman filter to improve the predicted values of low-cost sensors for NO2 and O3 gas. The low-cost sensor is a hot topic, which has drawn a lot of attention in recent years. Low-cost sensors of NO2 and O3 gas usually have a low correlation with the reference monitors, but the method applied in this study improves it significantly.

However, several problems in the manuscript affect reading fluency and ethnicity. 

The authors should check the appropriate way to cite references in the main text. Please cite [author name] et al. instead of a number. You can put the number of references at the end of the sentence or next to the name.

Reference 34 is retracted from the journal. So find another reference, or this will be a major issue.

Please remove citations in Figure 2 and Figure 3. Or it can be considered self-plagiarism. 

Figure 2: did the company agree to put their product in the manuscript? Please check with the company or this violates intellectual property protection law. 

Please improve the resolution of Figure 3, and add scale and north direction to the map.

Line 271: The equation is created by the Alphasene company in my recognition. It should be cited as their original source.

Line 381-385: there is no Kalman coefficient D in the results.

Comments on the Quality of English Language

Scientific language is used.

Author Response

Please see the attachement

Author Response File: Author Response.pdf

Reviewer 2 Report

Comments and Suggestions for Authors

I suggest to the authors to compare the benefits to use this kind of procedure for air quality forecasting in comparison with other methodologies that combines meteorological, emission and photochemical or dispersion models.

Also I suggest to discuss about other techniques like MOS (model output statistics), bias correction or artificial intelligence.

Author Response

Please see the attachment

Author Response File: Author Response.pdf

Reviewer 3 Report

Comments and Suggestions for Authors

Air pollution is a severe problem not only in industrial regions but also in most urban areas. This research article, proposes a model, based on Kalman filter that aims to predict the actual Nitrogen dioxide (NO₂) and Ozone (O₃) concentrations using as input the measurements performed by monitoring devices that incorporate corresponding low cost sensors. The research appears to have broad market application prospects, but there is a problem that must be addressed in the article.

The research background is too simple and not comprehensive, which did not allow me to understand the necessity and innovation of the study. So I recommend a major revision of this manuscript. Please add the following three aspects to the ‘1. Introduction’ section:

1. Introduce the commonly used calibration models for gas quality detection data at present.

2. Have other researchers applied the Kalman filter used in this article to the correction analysis of gas composition test data?

3. The advantages of this Kalman filter over other models.

Author Response

Please see the attachment

Author Response File: Author Response.pdf

Reviewer 4 Report

Comments and Suggestions for Authors

This manuscript reports the elimination of the measurements’ errors. This study is of great significance for improving people's quality of life. The writing of this article is fluent, the experimental design is reasonable, and the results are reliable. The article has a rigorous organizational structure

However, there are still some issues that need improvement:

1. The abstract section does not reflect the key content and results of the study. Please rewrite it.

2. P315…Figure 5a… should be  …Figure 5(a)…,P319: …Figure 5b… should be  …Figure 5(b)…. Please be careful with other similar questions in the text.

3. The first three sentences of the conclusion section can be simplified

Author Response

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Author Response File: Author Response.pdf

Round 2

Reviewer 1 Report

Comments and Suggestions for Authors

The authors have resolved all reviewer's concerns. 

The manuscript has been improved after adapting reviewers' comments. 

Reviewer 3 Report

Comments and Suggestions for Authors

It's OK.