the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
A comprehensive insight into trajectory climatology and spatiotemporal distribution of dust aerosols in China
Abstract. Airborne dust aerosols impact negatively the climate, ecosystems, air quality, and human health. To mitigate these impacts, it is crucial to identify their three–dimensional spatiotemporal distribution, transport pathways and driving factors. In this study, the three–dimensional spatiotemporal variations and distribution of dust aerosols in China from 2007 to 2021 were first analyzed using multiple dust datasets, including Modern Era Retrospective Analysis for Research and Applications version 2 (MERRA–2) dust aerosol optical depth (DAOD) data, ultraviolet aerosol index (UVAI) data from the Ozone Monitoring Instrument (OMI), and the Vertical Feature Mask (VFM) product of Cloud–Aerosol Lidar with Orthogonal Polarization (CALIOP). Also, the transport pathways and potential source regions for dust haze in principle provincial capital cities of West and North China in spring were identified using the Hybrid Single–Particle Lagrangian Integrated Trajectory (HYSPLIT) model and Potential Source Contribution Function (PSCF). Additionally, DAOD variations over different land cover types and the impacts of meteorological driving factors were discussed with geographic detectors. Results indicate that: (1) The multi–year average of DAOD in China from 2007 to 2021 was 0.076. A mutation in annual average DAOD occurred between 2010 and 2011, with an insignificant increasing trend between 2007–2010, a downward trend between 2011–2021 and a significant downward trend between 2014–2017. (2) The Taklamakan Desert exhibited the highest DAOD for the entire China during spring throughout the years, with DAOD values ranging from 0.4 to 0.6 and UVAI values exceeding 2.0. The highest frequency of dust occurrence in the northwest and northern regions is at an altitude of 2–4 km in spring and summer, and of 0–2 km in autumn and winter, while it is at an altitude of 4–6 km for the Qinghai–Tibet region. (3) The dust transport routes for the provincial capital cities can be primarily divided into: western, northwestern, northern, southwestern, and local. Northwest cities are notably affected by dust from surrounding deserts. Dust originating from the Qaidam Basin and the Hexi Corridor can be carried further downwind to inland cities, such as Xining and Lanzhou. A dust backflow was found in Beijing and Tianjin. Moreover, the discussion revealed that barren and cropland had the highest DAOD and additionally precipitation, evaporation, and soil moisture were identified as the strongest driving factors affecting dust aerosol variations. The combination effect of precipitation and temperature had the highest explanatory power, ranging from 0.72–0.84, followed by 0.75–0.81 for precipitation and U10m wind speed and 0.67–0.75 for temperature and evaporation.
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RC1: 'Comment on egusphere-2024-357', Anonymous Referee #1, 10 Apr 2024
Review comments of “A comprehensive insight into trajectory climatology and spatiotemporal distribution of dust aerosols in China” by Li et al.
General comments
This study uses multiple data sets of satellite retrievals to show the spatiotemporal distribution and variation of dust aerosols over China. The transport pathways and potential source regions for dust aerosols are identified using back trajectory (HYSPLIT) model and Potential Source Contribution Function (PSCF). However, there are quite a few problems with this paper. Generally, the paper could hardly be “comprehensive” and lacks of new “insights” into this problem. Additionally, there are quite a lot of errors in sentence expressions and typos which makes the paper not easy to follow. The whole paper seems to be rough and without polishing. The authors should have been more serious in preparing their paper for submission to renowned journals like ACP. The paper definitely needs major revisions to be further considered for publication.
Specific comments
- Introduction: Line 128: “Notably, the long term transport characterises of dust based on metrological observations have been rarely included.” It’s too arbitrary to say this.
- Line 131: “This study aims to address this gap by …” – Please be specific about what “gap” do you mean?
- Line 132: A “five–years trajectory climatology of dust trajectory” seems too short to be called “long-term”. Additionally, please explain why two time ranges of “2017-2021” and “2007-2021” are used instead of a uniform range (i.e., 2007-2021)?
- Line 150-152: It is arguable to say “Due to the environmental impacts governed by high pressure in the Pacific Ocean, Indian Ocean, and Siberia, China, located in the eastern part of the Asian continent, is one of the world’s dust storm hotspots”. Additionally, this sentence is not complete!
- Line 154-156: “This classification is based on their geographic locations, land covers, and climate conditions, aligning with the four major geographic divisions in China characterized by geographic location, natural geography, and cultural geography” – Redundant but not convincing. A lot of factors are mentioned, but which one is decisive?
Additionally, how do the authors “pick” out the data within the regions since the boundaries are curves?
- Line 165: Figure 1 is not properly described in the main text. What are the “PM sites”?
- Line 190-191: “Mielonen et al. (2009) verified CALIOP with 36 AERONET globally” – please be specific about what variables are validated?
- Line 206-208: Why the “six” land types are chosen instead of others?
- Line 224: How do you define “sufficient data”? Please be specific!
- Line 226-227: the “south region” defined in this study still contain a large portion of areas which could be influenced by dust. Maybe too arbitrary here.
- Line 233-234: “Therefore”? How do you “select” the cities to be included?
- Line 252: “Above steps were repeated while”? which steps?
- Line 254: how do you define and set the “the critical value”?
- Line 262-263: Please explain why this is the best choice?
- Line 270: only (1) end time criteria?
- Line 312: what are the “number of layers of influencing factors “ and ”the number of units in layer h”?
- Line 315-318: difficult to understand here!
- Line 338: Figure 2: part of the figure caption is missing. BTW, the organization of (a), (b), (c) is strange.
- Line 343-345: the relation between DAOD and dust severity is not convincing.
- Line 370-371: The validation of the MERRA-2 data should be done more rigorously. More quantitative analysis should be given instead of just the figures. Previous studies frequently point out the underestimation of MERRA-2 AOD compared with other observations, which can be also seen here.
- Line 425: Figure 6: please use some other colors to plot the trajectories so that they can be distinguished from the shadings.
- Line 516: The so-called “factor detectors” does not seem to give much information about the changes in DAOD and why the factors change year by year?
- This paper needs a thorough proofread. There are lots of typos and errors to be corrected.
Minor problems
Line 7: It seems arbitrary to say the dust aerosol impact is “negative”.
Line 8: Shouldn’t that be 4-dimensional instead of 3?
Line 9: “variations and distribution” – distribution and variation
Line 29-30: As “explanatory power” is not a common sense for ordinary people, listing the ranges is not useful.
Line 48: “a rich material basis”?
Line 60: “Remote sensing datasets can be primarily divided into three types” – it may not be appropriate to divide in this way.
Line 61: “the early developed the absorbing aerosol index based on ultraviolet wavelengths”?
Line 129: “characterises”? “metrological”?
Line 141: “CALOP”?
Line 154: “, according to. ”?
Line 197: “from 2001 to the present” – when is “present”?
Line 198: “0.05o×0.05o”?
Line 278: “NECP”??
Citation: https://doi.org/10.5194/egusphere-2024-357-RC1 - AC1: 'Reply on RC1', Lu Yang, 25 Jun 2024
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RC2: 'Comment on egusphere-2024-357', Anonymous Referee #2, 14 May 2024
General comments
Multiple dust aerosol related datasets of MERRA-2, OMI and CALIPSO were used in this manuscript to study the spatiotemporal distribution of dust in China. Also, the dust transport and sources were analyzed using air mass trajectory statistic methods. Although the manuscript includes many valuable data and statistic results, it lacks one or more focused scientific points which leading the data analysis and most results are basic statistics from the data directly. The spatiotemporal characteristics of China dust have been investigated in many previous studies, what are the new scientific discoveries in this study? In my opinion, the manuscript needs to be rearranged focused one or two scientific points with deeper data analysis and scientific discussion.
Specific comments
- Figure 1, Inner Mongolia should not be included in Northwest area.
- For PSCF dust source analysis, how to distinguish the contibution of local emitted air pollution and long-range transported dust aerosol?
Citation: https://doi.org/10.5194/egusphere-2024-357-RC2 - AC2: 'Reply on RC2', Lu Yang, 25 Jun 2024
Status: closed
-
RC1: 'Comment on egusphere-2024-357', Anonymous Referee #1, 10 Apr 2024
Review comments of “A comprehensive insight into trajectory climatology and spatiotemporal distribution of dust aerosols in China” by Li et al.
General comments
This study uses multiple data sets of satellite retrievals to show the spatiotemporal distribution and variation of dust aerosols over China. The transport pathways and potential source regions for dust aerosols are identified using back trajectory (HYSPLIT) model and Potential Source Contribution Function (PSCF). However, there are quite a few problems with this paper. Generally, the paper could hardly be “comprehensive” and lacks of new “insights” into this problem. Additionally, there are quite a lot of errors in sentence expressions and typos which makes the paper not easy to follow. The whole paper seems to be rough and without polishing. The authors should have been more serious in preparing their paper for submission to renowned journals like ACP. The paper definitely needs major revisions to be further considered for publication.
Specific comments
- Introduction: Line 128: “Notably, the long term transport characterises of dust based on metrological observations have been rarely included.” It’s too arbitrary to say this.
- Line 131: “This study aims to address this gap by …” – Please be specific about what “gap” do you mean?
- Line 132: A “five–years trajectory climatology of dust trajectory” seems too short to be called “long-term”. Additionally, please explain why two time ranges of “2017-2021” and “2007-2021” are used instead of a uniform range (i.e., 2007-2021)?
- Line 150-152: It is arguable to say “Due to the environmental impacts governed by high pressure in the Pacific Ocean, Indian Ocean, and Siberia, China, located in the eastern part of the Asian continent, is one of the world’s dust storm hotspots”. Additionally, this sentence is not complete!
- Line 154-156: “This classification is based on their geographic locations, land covers, and climate conditions, aligning with the four major geographic divisions in China characterized by geographic location, natural geography, and cultural geography” – Redundant but not convincing. A lot of factors are mentioned, but which one is decisive?
Additionally, how do the authors “pick” out the data within the regions since the boundaries are curves?
- Line 165: Figure 1 is not properly described in the main text. What are the “PM sites”?
- Line 190-191: “Mielonen et al. (2009) verified CALIOP with 36 AERONET globally” – please be specific about what variables are validated?
- Line 206-208: Why the “six” land types are chosen instead of others?
- Line 224: How do you define “sufficient data”? Please be specific!
- Line 226-227: the “south region” defined in this study still contain a large portion of areas which could be influenced by dust. Maybe too arbitrary here.
- Line 233-234: “Therefore”? How do you “select” the cities to be included?
- Line 252: “Above steps were repeated while”? which steps?
- Line 254: how do you define and set the “the critical value”?
- Line 262-263: Please explain why this is the best choice?
- Line 270: only (1) end time criteria?
- Line 312: what are the “number of layers of influencing factors “ and ”the number of units in layer h”?
- Line 315-318: difficult to understand here!
- Line 338: Figure 2: part of the figure caption is missing. BTW, the organization of (a), (b), (c) is strange.
- Line 343-345: the relation between DAOD and dust severity is not convincing.
- Line 370-371: The validation of the MERRA-2 data should be done more rigorously. More quantitative analysis should be given instead of just the figures. Previous studies frequently point out the underestimation of MERRA-2 AOD compared with other observations, which can be also seen here.
- Line 425: Figure 6: please use some other colors to plot the trajectories so that they can be distinguished from the shadings.
- Line 516: The so-called “factor detectors” does not seem to give much information about the changes in DAOD and why the factors change year by year?
- This paper needs a thorough proofread. There are lots of typos and errors to be corrected.
Minor problems
Line 7: It seems arbitrary to say the dust aerosol impact is “negative”.
Line 8: Shouldn’t that be 4-dimensional instead of 3?
Line 9: “variations and distribution” – distribution and variation
Line 29-30: As “explanatory power” is not a common sense for ordinary people, listing the ranges is not useful.
Line 48: “a rich material basis”?
Line 60: “Remote sensing datasets can be primarily divided into three types” – it may not be appropriate to divide in this way.
Line 61: “the early developed the absorbing aerosol index based on ultraviolet wavelengths”?
Line 129: “characterises”? “metrological”?
Line 141: “CALOP”?
Line 154: “, according to. ”?
Line 197: “from 2001 to the present” – when is “present”?
Line 198: “0.05o×0.05o”?
Line 278: “NECP”??
Citation: https://doi.org/10.5194/egusphere-2024-357-RC1 - AC1: 'Reply on RC1', Lu Yang, 25 Jun 2024
-
RC2: 'Comment on egusphere-2024-357', Anonymous Referee #2, 14 May 2024
General comments
Multiple dust aerosol related datasets of MERRA-2, OMI and CALIPSO were used in this manuscript to study the spatiotemporal distribution of dust in China. Also, the dust transport and sources were analyzed using air mass trajectory statistic methods. Although the manuscript includes many valuable data and statistic results, it lacks one or more focused scientific points which leading the data analysis and most results are basic statistics from the data directly. The spatiotemporal characteristics of China dust have been investigated in many previous studies, what are the new scientific discoveries in this study? In my opinion, the manuscript needs to be rearranged focused one or two scientific points with deeper data analysis and scientific discussion.
Specific comments
- Figure 1, Inner Mongolia should not be included in Northwest area.
- For PSCF dust source analysis, how to distinguish the contibution of local emitted air pollution and long-range transported dust aerosol?
Citation: https://doi.org/10.5194/egusphere-2024-357-RC2 - AC2: 'Reply on RC2', Lu Yang, 25 Jun 2024
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