the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Rapid reappearance of air pollution after cold air outbreaks in northern and eastern China
Qian Liu
Guixing Chen
Lifang Sheng
Toshiki Iwasaki
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- Final revised paper (published on 18 Oct 2022)
- Preprint (discussion started on 04 Apr 2022)
Interactive discussion
Status: closed
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RC1: 'Comment on acp-2022-9', Anonymous Referee #2, 17 May 2022
Using observation data and reanalysis data, this paper utilizes a quantitative measurement of cold airmass to identify CAO and related dynamic/thermodynamic properties. The authors find the generic existence of air pollution reappearance after CAO, and raise a possible mechanism in the manuscript. This manuscript overall is interesting, but I do have some comments regarding the details of data and methods.
My major and minor concerns are described below.
Major comments:
1. The authors define north China as 30-40 N, 114-122 E. However, this is not a good definition. Furthermore, two sounding stations used in this manuscript, Nanjing and Baoshan (which is in Shanghai), are in East China. The authors can refer to the definition of the North China Plain in Kang et al. 2018
Kang, S., Eltahir, E.A.B. North China Plain threatened by deadly heatwaves due to climate change and irrigation. Nat Commun 9, 2894,2018. https://doi.org/10.1038/s41467-018-05252-y
2. In Section 2.1, more details are needed. For example
(1) What’s the spatial distribution of those local AQI stations? Are most of them in the big cities?
(2) What’s the vertical and horizontal resolution for the sounding data? And why do authors use sounding station data for the wind and air temperature? The temporal resolution is not good. Why don’t you use reanalysis data as well?
(3) I am not sure which JRA-55 products are used in this study. First of all, JRA-55 should have a 3-hourly reanalysis, and usually, the vertical pressure levels are 60 levels.
Minor comments:
1. In the introduction, the recent COVID-19 lockdowns also provide a unique opportunity to study the complex chemical effects of air pollution as well as meteorology. Here are some references.
1) Le T, Wang Y, Liu L, Yang J, Yung YL, Li G, Seinfeld JH. Unexpected air pollution with marked emission reductions during the COVID-19 outbreak in China. Science. 2020 Aug 7;369(6504):702-6.
2). Wang Y, Wen Y, Wang Y, Zhang S, Zhang KM, Zheng H, Xing J, Wu Y, Hao J. Four-month changes in air quality during and after the COVID-19 lockdown in six megacities in China. Environmental Science & Technology Letters. 2020 Sep 9;7(11):802-8
3). Zhao N, Wang G, Li G, Lang J, Zhang H. Air pollution episodes during the COVID-19 outbreak in the Beijing–Tianjin–Hebei region of China: an insight into the transport pathways and source distribution. Environmental Pollution. 2020 Dec 1;267:115617.
2. Section 2.1, “with observations made 24 times per day”, is it measured equal frequency (i.e., 1h frequency)?
3. Line 87, 89, vertical integral -> vertical integration.
4. For the definition of mass flux, the common definition is the rate of mass flow (SI unit kg/(m^2 s).
5. Line 95, why do authors use the standard deviation to define the CAO? This only makes sense when the mean value of cold airmass depth is very close to zero. (Think about one example, if the cold airmass depth is 50 hPa, the standard deviation is still 169.7 hPa, then CAO should be defined as a cold airmass depth exceeding 50+169.7 = 219.7 hPa
6. In Figure 1, The day0 (March 09) are both in before-CAO and During-CAO periods. But Mar 10 is only in the During-CAO period. So, the definition of the period boundaries is not consistent. This may affect the analysis results (e.g., Figure 4 and so on).
7. Figure 4, better to define the different color lines in the caption.
Citation: https://doi.org/10.5194/acp-2022-9-RC1 -
AC1: 'Reply on RC1', Guixing Chen, 18 Jul 2022
SUMMARY:
Using observation data and reanalysis data, this paper utilizes a quantitative measurement of cold airmass to identify CAO and related dynamic/thermodynamic properties. The authors find the generic existence of air pollution reappearance after CAO, and raise a possible mechanism in the manuscript. This manuscript overall is interesting, but I do have some comments regarding the details of data and methods. My major and minor concerns are described below.
Response: Thank you very much for your kind evaluation. All of your comments are accepted and revised accordingly. We consider that your comments have helped greatly to improve the manuscript. The detailed response and revision are given below. The high-resolution figures can be found in the supplementary file (Reply_on_RC1.pdf).
MAJOR COMMENTS:
1. The authors define north China as 30-40 N, 114-122 E. However, this is not a good definition. Furthermore, two sounding stations used in this manuscript, Nanjing and Baoshan (which is in Shanghai), are in East China. The authors can refer to the definition of the North China Plain in Kang et al. 2018
Kang, S., Eltahir, E.A.B. North China Plain threatened by deadly heatwaves due to climate change and irrigation. Nat Commun. 9, 2894,2018. https://doi.org/10.1038/s41467-018-05252-y
Response: We agree that the spatial range of North China Plain is usually defined as 113°–121°E, 34°–41°N (Kang and Eltahir, 2018), which is slightly north than the definition in our study. Here, we would like to explain why we select the region 114°–122°E, 30°–40°N as the study area. The determination of study area is based on the characteristics of air pollution and cold air activity. Figure R1 shows that the air pollution (AQI > 100) mainly occurs between the latitudes of 30°N and 40°N. The cold airmass activities also can affect areas around 30°N. In addition, our previous study shows the air quality at 30°N (Nanjing and Shanghai) usually varies following (only a half day’s delay) the changes of air quality at 40°N during a CAO (Figure 7 in Liu et al., 2019). This suggest the changes of air quality in area between 30°N and 40°N could be considered as a whole.
In addition, Figure 1 in Kang and Eltahir (2018) shows the spatial distribution of topography, area equipped for irrigation, highest daily maximum wet-bulb temperature and population density. The characteristics of these variables, as well as AQI and cold airmass depth in Figure R1, in areas 30°–34°N and 34°–40°N are highly consistent, indicating the area 30°–40°N (Black boxes) is more appropriate to be selected as the study region.
Following your suggestion, we refer to the study region (114°–122°E, 30°–40°N) as “Northern and Eastern China” (NEC). We also add some explanations of the study region in Section 2 at Lines 85–88: “The determination of study area (NEC), including parts of both northern China and eastern China, is based on the characteristics of both air pollution and cold air activity. The air pollution (AQI > 100) mainly occurs between the latitudes of 30°N and 40°N, and the CAOs also usually affect areas around 30°N (figure omitted).”
Figure R1. Winter mean cold airmass depth (shading) and AQI (colored dots) during 2014/2015–2021/2022.
Figure 1 in Kang and Eltahir 2018. Brief characterization of Eastern China. Spatial distribution of a topographic map (m), b area equipped for irrigation (AEI, %) for 2005 from Historical Irrigation Data with climatology of annual precipitation from TRMM (contour, mm) in modern record (1998–2015), c highest daily maximum wet-bulb temperature from ERA-Interim, TWmax (°C) in modern record (1979–2016), and d population density in people/km2. The box in each plot indicates the North China Plain used for regional analysis in this study.
References
Liu Q, Chen G and Iwasaki T 2019 Quantifying the impacts of cold airmass on aerosol concentrations over North China using isentropic analysis J. Geophys. Res. Atmos. 124 7308–7326
2. In Section 2.1, more details are needed. For example
(1) What’s the spatial distribution of those local AQI stations? Are most of them in the big cities?
Response: Figure R2 shows the spatial distribution of AQI stations used in our study. The stations have a relative even distribution in the study area. Some of the AQI stations are located in big cities (shaded by dark red) and some of them are in rural/suburban region (shaded by light yellow). According to your comments, we add description about the AQI observations at Lines 88–89: “The AQI stations have a relative even distribution in the study area (figure omitted). The stations are located in not only urban areas but also suburban and rural areas.”
Figure R2. Spatial distribution of AQI stations (green circles) and nighttime light (shading) in 2013. The nighttime light values range from 0-63 and large (small) value denotes the urban (rural/suburban). The white box denotes the northern and eastern China. (Data source https://www.ngdc.noaa.gov/eog/dmsp.html).
(2) What’s the vertical and horizontal resolution for the sounding data? And why do authors use sounding station data for the wind and air temperature? The temporal resolution is not good. Why don’t you use reanalysis data as well?
Response: The sounding data used in our study has a higher vertical resolution than reanalysis data especially in atmospheric boundary layer. For example, sounding data at Beijing station has 60–70 levels in total and 8–14 levels below 850 hPa during study period of 14–17 Dec 2016 (Figure 7a in manuscript), while the reanalysis data has 37 vertical levels with 7 levels below 850 hPa (see reply to MAJOR COMMENT #2(3)). For spatial resolution, there are not many available radiosonde stations in the study area. So, we only selected four stations distributed from north to south. We add some of above descriptions of sounding data at Lines 95–97: “The sounding data used in our study usually has a higher vertical resolution than mainstream reanalysis data especially in atmospheric boundary layer. For example, sounding data at Beijing station has 60–70 levels in total and 8–14 levels below 850 hPa during a CAO event of 14–17 Dec 2016.”
The sounding data provides a direct detection of atmospheric vertical profiles, which is more reliable than the model-simulated reanalysis data. Some studies also show that the boundary layer height calculated by reanalysis data has some biases as compared to sounding observation (Guo et al., 2021). Moreover, the atmospheric boundary layer conditions calculated by sounding observation data could well explain the changes of AQI observations. Therefore, we need first to verify the reliability of reanalysis data with sounding data.
We agree with the reviewer’s suggestion that reanalysis data may be a good substitute for sounding data, since reanalysis data has a higher spatial and temporal resolution. Indeed, we have used reanalysis data to analyze the boundary layer characteristics. In section 4.1, we found the depth of residual cold airmass calculated by reanalysis data is highly consistent with the mixing layer height calculated by sounding data. The depth of residual cold airmass and mixing layer height also has a physical connection as discussed in the manuscript at Lines 233–243. This result suggests the use of reanalysis data is appropriate and reliable in our study. In addition, the calculation of cold airmass depth using reanalysis data is much easier than the calculation of MLH using sounding. Therefore, we used the reanalysis data instead of sounding data in the rest part of section 4.
References
Guo J, Zhang J, Yang K, Liao H, Zhang S, Huang K, Lv Y, Shao J, Yu T, Tong B, Li J, Su T, Yim S H L, Stoffelen A, Zhai P and Xu X 2021 Investigation of near-global daytime boundary layer height using high-resolution radiosondes: first results and comparison with ERA5, MERRA-2, JRA-55, and NCEP-2 reanalyses Atmos. Chem. Phys. 21 17079–17097
(3) I am not sure which JRA-55 products are used in this study. First of all, JRA-55 should have a 3-hourly reanalysis, and usually, the vertical pressure levels are 60 levels.
Response: In this study, we use the standard product of isobaric analysis data (6-hourly, 37 layers) of JRA-55 following previous studies on cold air outbreak (Kanno et al., 2015; Abdillah et al., 2017; Liu et al., 2021). This data is freely available at JMA (http://search.diasjp.net/en/dataset/JRA55) and NCAR (https://rda.ucar.edu/datasets/ds628.0/).
The JRA-55 product users’ handbook can be found in this website (https://jra.kishou.go.jp/JRA-55/document/JRA-55_handbook_LL125_en.pdf). At page 8 of the handbook, the time interval of isobaric analysis data is described as: “These fields are produced every six hours at 00, 06, 12 and 18 UTC”. Page 14 shows the vertical coordinates of the data in isobaric fields as follow: “Isobaric fields are produced for 37 isobaric surfaces (1000, 975, 950, 925, 900, 875, 850, 825, 800, 775, 750, 700, 650, 600, 550, 500, 450, 400, 350, 300, 250, 225, 200, 175, 150, 125, 100, 70, 50, 30, 20, 10, 7, 5, 3, 2 and 1 hPa) except dew-point depression (or deficit), specific humidity, relative humidity, cloud cover, cloud water, cloud liquid water and cloud ice, which are produced for 27 levels from 1000 to 100 hPa only”.
Following your suggestion, we add some detailed descriptions at Lines 77–79: “To identify the CAO events, we used isobaric analysis data of Japanese 55-year reanalysis (JRA-55). This dataset is freely available at JMA (http://search.diasjp.net/en/dataset/JRA55) and NCAR (https://rda.ucar.edu/datasets/ds628.0/). The JRA-55 has a horizontal resolution of 1.25° with 37 vertical pressure levels and a time interval of 6 hours (00, 06, 12 and 18 UTC).”
References
Kanno Y, Abdillah M R and Iwasaki T 2015 Charge and discharge of polar cold air mass in northern hemispheric winter Geophys. Res. Lett. 42 7187–7193
Abdillah M R, Kanno Y and Iwasaki T 2017 Tropical–extratropical interactions associated with East Asian cold air outbreaks. Part I: Interannual variability J. Clim. 30 2989–3007
Liu Q, Chen G, Wang L, Kanno Y, and Iwasaki T 2021 Southward cold airmass flux of the East Asian winter monsoon: Diversity and impacts J. Clim. 34 3239–3254
MINOR COMMENTS:
1. In the introduction, the recent COVID-19 lockdowns also provide a unique opportunity to study the complex chemical effects of air pollution as well as meteorology. Here are some references.
1) Le T, Wang Y, Liu L, Yang J, Yung YL, Li G, Seinfeld JH. Unexpected air pollution with marked emission reductions during the COVID-19 outbreak in China. Science. 2020 Aug 7;369(6504):702-6.
2) Wang Y, Wen Y, Wang Y, Zhang S, Zhang KM, Zheng H, Xing J, Wu Y, Hao J. Four-month changes in air quality during and after the COVID-19 lockdown in six megacities in China. Environmental Science & Technology Letters. 2020 Sep 9;7(11):802-8.
3) Zhao N, Wang G, Li G, Lang J, Zhang H. Air pollution episodes during the COVID-19 outbreak in the Beijing–Tianjin–Hebei region of China: an insight into the transport pathways and source distribution. Environmental Pollution. 2020 Dec 1;267:115617.
Response: Following your suggestion, we add above references and some discussions in the introduction at Lines 36–37: “Even when local emission is obviously reduced during COVID-19 lockdown, severe air pollution still occurs in North China (Zhao et al., 2020).” and Lines 40–42: “The recent COVID-19 lockdowns also provide a unique opportunity for studying the complex chemical effects of air pollution as well as meteorology (Le et al., 2020; Wang et al., 2020).”
2. Section 2.1, “with observations made 24 times per day”, is it measured equal frequency (i.e., 1h frequency)?
Response: Yes, the observation has a time interval of 1 hour. The revised text can be found at Line 84: “with observations of 1hour frequency”.
3. Line 87, 89, vertical integral -> vertical integration.
Response: Revised as your suggestion.
4. For the definition of mass flux, the common definition is the rate of mass flow (SI unit kg/(m^2 s).
Response: We agree the unit of mass flux is usually expressed as kg/(m2 s). In our study, we use the horizontal flux of cold airmass to describe the horizontal movement of cold air, which is different from the mass flux of cold air.
Following Iwasaki et al. (2014), the total cold airmass amount/depth (DP) is defined as the depth of air layer between ground surface (ps) the isentropic surface of threshold potential temperature (θT), DP= ps – p(θT) (area below the thick solid contour of 280K in Figure 2 in Iwasaki et al., 2014). Thus, the definitions of dynamical and thermal properties are based on such definition of cold airmass (DP, unit: hPa).
Here, the isentropic mass continuity equation can be written as
The vertical integration of above equation from surface boundary (θs) to θT leads us to total cold airmass conservation
where is defined as the horizontal flux of cold airmass (F). Thus, the cold airmass flux (F) has a unit of hPa m s–1.
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AC1: 'Reply on RC1', Guixing Chen, 18 Jul 2022