Exploring Spatiotemporal Dynamics of PM2.5 Emission Based on Nighttime Light in China from 2012 to 2018
Jamiu Adetayo Adeniran
Round 1
Reviewer 1 Report
The authors discussed the issue of PM2.5 in China based on a large number of statistics. The authors take an approach similar to previous studies, and effective analysis provides valuable reference. I have no comment other than suggesting the authors to use more precise numbers instead of vague statements.
Author Response
Thank very much for the reviewers of their comments,we have further revised the article and detail changes are shown in the revision. And try our best to describle result and disscussion in detail number instead of vague statements
Reviewer 2 Report
The authors have done a very good work. However, there are some assertions and strong points in the manuscript that were not referenced. For example, page 4 lines 153 - 157. What are the sources of those assertions made?
Figure 2 should be converted to a table.
Resolution of other figures must be increased.
Author Response
1 For example, page 4 lines 153 - 157. What are the sources of those assertions made?
Response: We have changed the our expression in a more accurate way, and the assertions were based on our papers reviewed and referenced.
2 Figure 2 should be converted to a table.
Response: We have changed a table for figure 2, detail changes were shown in this revision.
3 Resolution of other figures must be increased.
Response: All figures in this revision were changed to more high resolution, and source files of all figures were uploaded at this revision.
Reviewer 3 Report
The presented manuscript promises to deliver the strong correlation between nighttime light data and subsequent PM2.5 emission. Todays it is imperative to curb the emission for human health and planet revival. However, the presented study has technical limitation and also losses the track in later half with respect to overall aim.
The study aims to deliver the correlation between nighttime light data and PM2.5 emission. The presented study initially set up the linear regression fit model to establish the correlation. However, the result section tends to establish the changes in PM2.5 emission over the years (2012-2018) at different regions of China, which totally goes offset with the flow and theme of the paper.
The only subsection 4.3.3, show the graphical representation the correlation between nighttime light data and PM2.5, which is obvious as it is directly related to population distribution and industry development.
The study only takes the data from 2012-2018, authors need to clarify this, as presently its 2022. Moreover, only past data has been shown with graphical representation for PM2.5. The study does not offer any prediction on PM2.5 distribution (increasing/decreasing).
Other than the technical limitations, please see the below for enhancing the readability of the manuscript.
1. The indices of figure 1 are not readable.
2. It is hard to differentiate the data/information provided in table 1. Authors are suggested to use all boarders of table.
3. Table 2 repeats the correlation value r for year 2012.
4. The statement, “In Table 2, the value of all the year is less than 0.01” does not clarify with respect to table 2.
5. The labels are not readable in figure 5.
6. Figure 13 is not readable.
Author Response
Overall Response: We all agree the reviewer’s comments of our manuscript, as our manuscript mainly analyzed the changes of PM2.5 emission in China from 2012 to 2018 by examining spatiotemporal dynamics of nighttime light data at a multi-scale, and the relationship between nighttime light data and PM2.5 is only presented in section 4.3.3. Thus, the title of our manuscript is not accurate to describe our work, so we change the title at this revision.
While for data used in this paper, when our first version of manuscript finished about one year ago, the pm2.5 dataset is updated only to the 2018 year, until today (2022.10.15) the data for China is also updated to 2018, so the data used in our manuscript up to 2018. And now the research team “Atmospheric Composition Analysis Group” of PM2.5 move to another college (Washington University in St. Louis), thus we change the data source link to the new link “
https://sites.wustl.edu/acag/datasets/surface-pm2-5/ “ at this revision.
- The indices of figure 1 are not readable.
Response: we change the indices of figures in this revision.
- It is hard to differentiate the data/information provided in table 1. Authors are suggested to use all boarders of table.
Response: we change figure 2 into a table, detail changes were shown in this revision.
- Table 2 repeats the correlation value r for year 2012.
Response: we give all the correlation values from 2012 to 2018 in this revision, details were shown in table 2.
- The statement, “In Table 2, the value of all the year is less than 0.01” does not clarify with respect to table 2.
Response: p values of all year were listed in the table, and we change our expression in this revision.
- The labels are not readable in figure 5.
Response: we change the labels of figure 5, detail changes were shown in this revision.
- Figure 13 is not readable.
Response: All figures are changed in this revision, made more readable and more clear.
Author Response File: 
Author Response.pdf
Reviewer 4 Report
1. On page 2 line 77-79, did Yan et al use nighttime light data in their study? It seems that their study did not use nighttime light data.
2. Do ‘regional’ and ‘economic’ mean the same thing in the passage? If so, pleas clarify in the paper.
3. The authors argued that the traditional ground monitoring stations were not suitable for analyzing PM2.5 emission because stations were distributed unevenly and used data from http://fizz.phys.dal.ca/~atmos/marti. Have this dataset been validated by relevant studies?
Author Response
- On page 2 line 77-79, did Yan et al use nighttime light data in their study? It seems that their study did not use nighttime light data.
Response: Yes, Yan et al didn’t use nighttime light data, they used a general regression neural network (GRNN) method to predict the PM2.5 concentration in these clusters on the second day. Thus, in this revision, we delete this reference.
- Do ‘regional’ and ‘economic’ mean the same thing in the passage? If so, pleas clarify in the paper.
Response: Yes, the full meaning of “regional” is economic regional, in this revision, we clarify this, the eight economic regions namely as the northeast, the northern coast, the eastern coast, the southern coast, the middle reaches of the Yellow River, the middle reaches of the Yangtze River, the southwest and the northwest.
- The authors argued that the traditional ground monitoring stations were not suitable for analyzing PM2.5 emission because stations were distributed unevenly and used data from http://fizz.phys.dal.ca/~atmos/marti. Have this dataset been validated by relevant studies?
Response:
Previous research of
［1］ Kahn Ｒ， Banerjee P， McDonald D， et al． Sensitivity of multiangle imaging to aerosol optical depth and to pure-particle size distribution and composition over ocean［J］． Journal of Geophysical Ｒesearch: Atmospheres，1998，103( D24) : 32195- 32213．
［2］ Kahn Ｒ，Banerjee P，McDonald D． Sensitivity of multiangle imaging to natural mixtures of aerosols over ocean［J］． Journal of Geophy
have noticed the questions of traditional ground monitoring.
The dataset of http://fizz.phys.dal.ca/~atmos/marti have validated by many previous studies,
The source of this dataset is from the paper of “”Van Donkelaar, Aaron, et al. "Global estimates of fine particulate matter using a combined geophysical-statistical method with information from satellites, models, and monitors." Environmental science & technology 50.7 (2016): 3762-3772.
And the number of references of this study is 864 (accessed at 10-15-2022), detail of this is shown below.
Reviewer 5 Report
1. The quality of figure 1 is not up to the mark.
Author Response
1 The quality of figure 1 is not up to the mark.
Response: All figures at revision were changed to new verison, at high resolution.
Round 2
Reviewer 3 Report
Authors have replied all the queries appropriately and modification in title justifies the study period. Few figures like 1 and 5 need modification as their axis legends are not completely in english.
Author Response
Few figures like 1 and 5 need modification as their axis legends are not completely in english.
Response: we have the word into english in figure1 ,figure 5 ad figure 13. Also we change the number of figure and table number.
