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Article
Peer-Review Record

Estimating Regional PM2.5 Concentrations in China Using a Global-Local Regression Model Considering Global Spatial Autocorrelation and Local Spatial Heterogeneity

Remote Sens. 2022, 14(18), 4545; https://doi.org/10.3390/rs14184545
by Heng Su, Yumin Chen *, Huangyuan Tan, Annan Zhou, Guodong Chen and Yuejun Chen
Reviewer 1: Anonymous
Reviewer 2:
Remote Sens. 2022, 14(18), 4545; https://doi.org/10.3390/rs14184545
Submission received: 12 August 2022 / Revised: 2 September 2022 / Accepted: 8 September 2022 / Published: 11 September 2022
(This article belongs to the Special Issue Stereoscopic Remote Sensing of Air Pollutants and Applications)

Round 1

Reviewer 1 Report

The manuscript is of great relevance to the field of air pollution modelling. It approaches well global spatial autocorrelation and local spatial heterogeneity of distribution of PM2.5  ground concentrations. Proposed GLR model shows reasonable improvement to traditional ESF and GWR models by extracting global factors and weighting local spatial heterogeneity of geographical features within the study area.

The authors make a valuable contribution to urban air pollution estimations by improving accuracy enhancement of available modelling tools, thus increasing prediction potential in areas without monitoring stations.

I strongly recommend the manuscript to be published as it is.

Author Response

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Author Response File: Author Response.docx

Reviewer 2 Report

This paper studies the estimation of ground Fine particulate matter (PM) that have a diameter of less than 2.5 micrometers (PM2.5) concentrations in the Beijing-Tianjin-Hebei (BTH) and the Yangtze River Delta (YRD) regions of China using a global-local regression model (GLR) considering global spatial autocorrelation and local spatial heterogeneity. I believe the paper is accepted in its present form. However, the comparison of models and the inadequacy of each is well explained. The proposed explanation of the new model, a global-local regression (GLR) model, is convincing. In addition, the spatial-temporal comparison of the study areas is well discussed. As well as the results are clear and pertinent. Finally, the abstract is supported by the conclusion.

Author Response

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Author Response File: Author Response.docx

Reviewer 3 Report

I would like to congratulate the authors for their interest in researching in this field, however, the work presented presents some deficiencies.

a. Keywords are correct but the authors should eliminate superfluous terms such as "the" in “the YRD región” and “the BTH región”.

b. Abstract is correct in terms of content but should be improved in its structure. Authors should first explain the object of the research, then cite the methodologies and techniques used. They can also include a summary of the results and conclusions. In this way, a reader will be able, from this section, to classify the research and determine whether it is useful to him or her.

c. The discussion chapter should be expanded. In this section, it would be appropriate to include these references to reinforce or compare the results obtained with other research or sources.

 

I hope that these changes will help to improve your article and make it a document of great scientific interest.

Author Response

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Author Response File: Author Response.docx

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