08 Jan 2021
08 Jan 2021
Lidar vertical observation network and data assimilation reveal key processes driving the 3-D dynamic evolution of PM2.5 concentrations over the North China Plain
- 1Institutes of Physical Science and Information Technology, Anhui University, Hefei 230601, China
- 2Key Laboratory of Environmental Optics and Technology, Anhui Institute of Optics and Fine Mechanics, Chinese Academy of Sciences, Hefei 230031, China
- 3Minerva Research Group, Max Planck Institute for Chemistry, Mainz, Germany
- 1Institutes of Physical Science and Information Technology, Anhui University, Hefei 230601, China
- 2Key Laboratory of Environmental Optics and Technology, Anhui Institute of Optics and Fine Mechanics, Chinese Academy of Sciences, Hefei 230031, China
- 3Minerva Research Group, Max Planck Institute for Chemistry, Mainz, Germany
Abstract. China has made great efforts to monitor and control air pollution in the past decade. Comprehensive characterization and understanding of pollutants in three-dimension (3-D) are, however, still lacking. Here, we used data from an observation network consisting of 13 aerosol lidars and more than 1000 ground observation stations, combined with a data assimilation technique, to conduct a comprehensive analysis of an extreme heavy aerosol pollution (HAP) over the North China Plain (NCP) from November–December 2017. During the studied period, the maximum hourly mass concentration of surface PM2.5 reached ~390 μg m−3. After assimilation, the correlation between model results and the independent observation sub-dataset was ~50 % higher than the that without the assimilation, and the root mean square error was reduced by ~40 %. From pollution development to dissipation, we divided the HAP in the NCP (especially in Beijing) into four phases – an early phase (EP), a transport phase (TP), an accumulation phase (AP), and a removal phase (RP). We then analyzed the evolutionary characteristics of PM2.5 concentration during different phases on the surface and in 3-D space. We found that the particles were mainly transported from south to north at a height of 1–2 km (during EP and RP) and near the surface (during TP and AP). The amounts of PM2.5 advected into Beijing with the maximum transport flux intensity (TFI) were through the pathways in the relative order of the southwest > southeast > east pathways. The dissipation of PM2.5 in the RP stage (with negative TFI) was mainly from north to south, with an average transport height of ~1 km above the surface. Our results quantified the multi-dimensional distribution and evolution of PM2.5 concentration over the NCP, which may help policymakers develop efficient air pollution control strategies.
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Yan Xiang et al.
Status: closed
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RC1: 'Comment on acp-2020-1273', Anonymous Referee #1, 19 Jan 2021
Summary and general comments:
This manuscript reports the evolution characteristics of PM2.5 concentration in different dimensions (surface-layer, vertical-distribution and three-dimensional) under four different phases (an early phase, a transport phase, an accumulation phase, and a removal phase) of heavy pollution process in North China Plain. The authors used data from an observation network consisting of 13 aerosol lidars and more than 1000 ground observation stations, combined with a data assimilation technique, to conduct a comprehensive analysis of an extreme heavy aerosol pollution over the North China Plain from November–December 2017. Meanwhile, the regional transport of PM2.5 over different transport channels was quantified, including PM2.5 concentration, transport flux and transport flux intensity. Moreover, the authors also captured the regional transport of air pollutants stretching over 1000 km, proving the necessity and importance of the joint prevention and control of regional air pollution.
These results could significantly improve our understanding on the key processes driving the 3-D dynamic evolution of PM2.5 concentrations. The scope of this manuscript is well suited to ACP, and the data obtained by the authors are valuable. The data set is meaningful to further verify or constrain the representation of aerosols in air quality model and satellite remote sensing. This paper is very well-written and should be considered for publication after addressing my comments below.
List of minor comments:
- Page 4, Line 10: The map information shown in Fig. 1a and Fig. 1b is too duplicate with that shown in Fig. 1c and Fig. 1d respectively. It is suggested to delete Fig. 1c and Fig. 1d or put them in the supporting material.
- Page 5, Line 5: The time resolution of 3-10 minutes refers to the time resolution of the original data or the smoothed data. If it is original, please describe clearly; if it is smooth, please give a detailed smoothing method in the manuscript.
- Page 5, Line 6: The semicolon should be changed to a comma.
- Page 5, Line 17: Please provide the WRF Chem version used in the manuscript.
- Page 6, Line 26: A space needs to be added between 1 and km to be consistent with other contents of the manuscript.
- Page 9, Line 7: Xintai should be Xingtai.
- Page 12, Line 5: What is the meaning of white color in j, k and l of Figure 6? Does it mean that the current moment is missing data? Or is it deleted due to low SNR? Please add a clear description to the manuscript.
- Page 16, Line 4: Why choose 1.5 km to calculate the total amount of PM5 transportation. Why not 1 km or 2 km, 3 km? Please give reasons. Is it based on the height of the atmospheric boundary layer? Or is it due to the 1.5 km explained in line 9 on page 15?
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AC1: 'Reply on RC1', Yan Xiang, 04 Mar 2021
The comment was uploaded in the form of a supplement: https://acp.copernicus.org/preprints/acp-2020-1273/acp-2020-1273-AC1-supplement.pdf
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RC2: 'Comment on acp-2020-1273', Anonymous Referee #2, 14 Feb 2021
General Comments:
Xiang et al. report on using three-dimensional variational data assimilation to refine WRF-Chem simulations of PM2.5 transport throughout the North China Plain based on surface and lidar observations. This paper extends on a number of other recent studies from this region by incorporating aerosol vertical profiles from a network of 13 lidars located along the main corridors for air pollution transport. The resulting three-dimensional characterisation of PM2.5 concentrations and fluxes allows characterisation of the inflow and outflow pathways for this region and the vertical structure of heavy aerosol pollution events. Furthermore, the authors were able to identify altitude-dependent differences in flux rates and direction.
The manuscript is well written and within the scope of Atmospheric Chemistry and Physics. While only examining a single heavy aerosol pollution event, the method may significantly enhance aerosol transport models in this region and could be particularly valuable in assessing air pollution control strategies. The study is presented in a clear and engaging manner and should be considered for publication after addressing the following minor comments:
Specific Comments:
Page 6, Line 33: Are the quoted root-mean-square errors and correlation coefficients calculated from the combined data at the four selected heights (surface, 0.2, 0.5 and 1 km)?
Page 11, Line 14: Although elevated concentrations are briefly visible at approximately 1km over HD and XX in the removal phase (Figs 6f & 6g), it is not immediately clear that this corresponds to north-south transport from BJ. Perhaps some elaboration is required or at least the upward wind vectors shown in Fig 8 could be mentioned here.
Page 15, Line 9: As suggested by the other reviewer, some reasoning should be included to explain why the TFI was calculated up to a height of 1.5 km, rather than some other limit.
Additional Comments:
Figure 3: For clarity, the episode numbers should be centered over each episode
Figures 4 & 5: Figure 5 should be inserted before Figure 4 since it is discussed first in the text (page 10)
Page 13, line 11: Change “come from” to “coming from”
Page 15, line 13: It is not clear what is being compared against the ground surface flux. What are the height of these fluxes? Or is this sentence providing ground surface fluxes for comparison against the maximum values across the 0 – 1.5 km range, as given in the previous sentence?
Page 16, line 10: “On the contrary” implies that the TFI value for EP contradicts the value for RP. Perhaps “In contrast” or “In comparison” would be more appropriate.
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AC2: 'Reply on RC2', Yan Xiang, 04 Mar 2021
The comment was uploaded in the form of a supplement: https://acp.copernicus.org/preprints/acp-2020-1273/acp-2020-1273-AC2-supplement.pdf
-
AC2: 'Reply on RC2', Yan Xiang, 04 Mar 2021
Status: closed
-
RC1: 'Comment on acp-2020-1273', Anonymous Referee #1, 19 Jan 2021
Summary and general comments:
This manuscript reports the evolution characteristics of PM2.5 concentration in different dimensions (surface-layer, vertical-distribution and three-dimensional) under four different phases (an early phase, a transport phase, an accumulation phase, and a removal phase) of heavy pollution process in North China Plain. The authors used data from an observation network consisting of 13 aerosol lidars and more than 1000 ground observation stations, combined with a data assimilation technique, to conduct a comprehensive analysis of an extreme heavy aerosol pollution over the North China Plain from November–December 2017. Meanwhile, the regional transport of PM2.5 over different transport channels was quantified, including PM2.5 concentration, transport flux and transport flux intensity. Moreover, the authors also captured the regional transport of air pollutants stretching over 1000 km, proving the necessity and importance of the joint prevention and control of regional air pollution.
These results could significantly improve our understanding on the key processes driving the 3-D dynamic evolution of PM2.5 concentrations. The scope of this manuscript is well suited to ACP, and the data obtained by the authors are valuable. The data set is meaningful to further verify or constrain the representation of aerosols in air quality model and satellite remote sensing. This paper is very well-written and should be considered for publication after addressing my comments below.
List of minor comments:
- Page 4, Line 10: The map information shown in Fig. 1a and Fig. 1b is too duplicate with that shown in Fig. 1c and Fig. 1d respectively. It is suggested to delete Fig. 1c and Fig. 1d or put them in the supporting material.
- Page 5, Line 5: The time resolution of 3-10 minutes refers to the time resolution of the original data or the smoothed data. If it is original, please describe clearly; if it is smooth, please give a detailed smoothing method in the manuscript.
- Page 5, Line 6: The semicolon should be changed to a comma.
- Page 5, Line 17: Please provide the WRF Chem version used in the manuscript.
- Page 6, Line 26: A space needs to be added between 1 and km to be consistent with other contents of the manuscript.
- Page 9, Line 7: Xintai should be Xingtai.
- Page 12, Line 5: What is the meaning of white color in j, k and l of Figure 6? Does it mean that the current moment is missing data? Or is it deleted due to low SNR? Please add a clear description to the manuscript.
- Page 16, Line 4: Why choose 1.5 km to calculate the total amount of PM5 transportation. Why not 1 km or 2 km, 3 km? Please give reasons. Is it based on the height of the atmospheric boundary layer? Or is it due to the 1.5 km explained in line 9 on page 15?
-
AC1: 'Reply on RC1', Yan Xiang, 04 Mar 2021
The comment was uploaded in the form of a supplement: https://acp.copernicus.org/preprints/acp-2020-1273/acp-2020-1273-AC1-supplement.pdf
-
RC2: 'Comment on acp-2020-1273', Anonymous Referee #2, 14 Feb 2021
General Comments:
Xiang et al. report on using three-dimensional variational data assimilation to refine WRF-Chem simulations of PM2.5 transport throughout the North China Plain based on surface and lidar observations. This paper extends on a number of other recent studies from this region by incorporating aerosol vertical profiles from a network of 13 lidars located along the main corridors for air pollution transport. The resulting three-dimensional characterisation of PM2.5 concentrations and fluxes allows characterisation of the inflow and outflow pathways for this region and the vertical structure of heavy aerosol pollution events. Furthermore, the authors were able to identify altitude-dependent differences in flux rates and direction.
The manuscript is well written and within the scope of Atmospheric Chemistry and Physics. While only examining a single heavy aerosol pollution event, the method may significantly enhance aerosol transport models in this region and could be particularly valuable in assessing air pollution control strategies. The study is presented in a clear and engaging manner and should be considered for publication after addressing the following minor comments:
Specific Comments:
Page 6, Line 33: Are the quoted root-mean-square errors and correlation coefficients calculated from the combined data at the four selected heights (surface, 0.2, 0.5 and 1 km)?
Page 11, Line 14: Although elevated concentrations are briefly visible at approximately 1km over HD and XX in the removal phase (Figs 6f & 6g), it is not immediately clear that this corresponds to north-south transport from BJ. Perhaps some elaboration is required or at least the upward wind vectors shown in Fig 8 could be mentioned here.
Page 15, Line 9: As suggested by the other reviewer, some reasoning should be included to explain why the TFI was calculated up to a height of 1.5 km, rather than some other limit.
Additional Comments:
Figure 3: For clarity, the episode numbers should be centered over each episode
Figures 4 & 5: Figure 5 should be inserted before Figure 4 since it is discussed first in the text (page 10)
Page 13, line 11: Change “come from” to “coming from”
Page 15, line 13: It is not clear what is being compared against the ground surface flux. What are the height of these fluxes? Or is this sentence providing ground surface fluxes for comparison against the maximum values across the 0 – 1.5 km range, as given in the previous sentence?
Page 16, line 10: “On the contrary” implies that the TFI value for EP contradicts the value for RP. Perhaps “In contrast” or “In comparison” would be more appropriate.
-
AC2: 'Reply on RC2', Yan Xiang, 04 Mar 2021
The comment was uploaded in the form of a supplement: https://acp.copernicus.org/preprints/acp-2020-1273/acp-2020-1273-AC2-supplement.pdf
-
AC2: 'Reply on RC2', Yan Xiang, 04 Mar 2021
Yan Xiang et al.
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