# Influence of Intermittent Turbulence on Air Pollution and Its Dispersion in Winter 2016/2017 over Beijing, China

• Corresponding author: Hongsheng ZHANG, hsdq@pku.edu.cn
• Funds:

Supported by the National Key Research and Development Program of China (2016YFC0203300) and National Natural Science Foundation of China (91544216 and 41705003)

• doi: 10.1007/s13351-020-9128-4
• With rapid urbanization in recent years, severe air pollution has emerged as a major issue for many regions of China, especially in some metropolises. A persistent pollution case during 6 December 2016–8 January 2017 was selected to investigate the relations between turbulent intermittency and frequent PM2.5 (particulate matters with diameter less than 2.5 μm) pollution events over the metropolitan region of Beijing, China. The accumulation of PM2.5 near the surface frequently occurred as a combined result of strong inversion layers, stagnant winds, high ambient humidity levels, and stable stratification during this case. Arbitrary-order Hilbert spectral analysis indicated that steep decreases in the PM2.5 concentration were simultaneous with the occurrence of intermittent turbulence and strong vertical mixing. A wind profiler observation revealed existence of low-level jets (LLJs) at the end of the polluted periods, suggesting that the upper-level turbulent mixing accompanied by the wind shear of LLJ was transported downward and enhanced the vertical mixing near the surface, which might have caused an abrupt reduction in PM2.5 and improvement in air conditions.
• Fig. 1.  Comparison between a polluted day (left, 21 December 2016) and a clean day (right, 23 December 2016). Photos were taken near the Beijing TV station in the morning between 0700 and 0900 LST.

Fig. 2.  Temporal distributions of (a) PM2.5 concentration (30 min), (b) ozone concentration (1 min), (c) wind vector (30 min), (d) vertical velocity (10 Hz), (e) temperature (10 Hz, dashed line refers to daily average temperature), (f) density of water vapor (10 Hz), (g) stability parameter ${z}/{\rm{L}}$ (1 min), and (h) TKE (1 min) from 6 December 2016 to 8 January 2017. Shaded areas refer to polluted periods and remaining areas correspond to clean periods.

Fig. 3.  Comparison between the polluted periods (left panels) and the clean periods (right panels) of the diurnal change (10 Hz): (a, b) horizontal wind speed, (c, d) vertical velocity, (e, f) temperature, and (g, h) density of water vapor.

Fig. 4.  Height–time cross-sections of (a) temperature and (b) RH. Dashed boxes denote the inversion layers and explosive growth in RH.

Fig. 6.  Distributions of PM2.5 and ozone concentrations in (a, b) Case 3 and (c, d) Case 6 (boxes denote the abrupt change in pollutants).

Fig. 5.  Comparison of typical surface weather conditions at (a) 0200 LST 21 and 1400 LST 22 December 2016. Red dots refer to Beijing. Weather charts were obtained from the Korea Meteorological Administration (https://web.kma.go.kr/eng/weather/images/analysischart.jsp).

Fig. 7.  Representation of the Hilbert-based scaling exponent function $\xi \left(q \right) - 1$ of (a) Case 3 and (b) Case 6 compared with $q/3$ (black straight lines). (c) The original vertical velocity during 0500–0530 LST 22 December 2016.

Fig. 8.  Sample LLJ profiles of two cases (dashed line for Case 3; dash-dotted and solid lines for Case 6).

Fig. 9.  Schematic of the effect of intermittent turbulence on PM2.5 dispersion (shaded areas refer to the periods of accumulation).

•  [1] Zhaobin SUN, Xiaoling ZHANG, Xiujuan ZHAO, Xiangao XIA, Shiguang MIAO, Ziming LI, Zhigang CHENG, Wei WEN, Yixi TANG. Oscillation of Surface PM2.5 Concentration Resulting from an Alternation of Easterly and Southerly Winds in Beijing: Mechanisms and Implications. Journal of Meteorological Research, 2018, 32(2): 288-301.  doi: 10.1007/s13351-018-7064-3. [2] Yuzhi LIU, Bing WANG, Qingzhe ZHU, Run LUO, Chuqiao WU, Rui JIA. Dominant Synoptic Patterns and Their Relationships with PM2.5 Pollution in Winter over the Beijing–Tianjin–Hebei and Yangtze River Delta Regions in China. Journal of Meteorological Research, 2019, 33(4): 765-776.  doi: 10.1007/s13351-019-9007-z. [3] Tian LUAN, Xueliang GUO, Tianhang ZHANG, Lijun GUO. Below-Cloud Aerosol Scavenging by Different-Intensity Rains in Beijing City. Journal of Meteorological Research, 2019, 33(1): 126-137.  doi: 10.1007/s13351-019-8079-0. [4] Ting YOU, Renguang WU, Gang HUANG, Guangzhou FAN. Regional Meteorological Patterns for Heavy Pollution Events in Beijing. Journal of Meteorological Research, 2017, 31(3): 597-611.  doi: 10.1007/s13351-017-6143-1. [5] Linye SONG, Mingxuan CHEN, Feng GAO, Conglan CHENG, Min CHEN, Lu YANG, Yong WANG. Elevation Influence on Rainfall and a Parameterization Algorithm in the Beijing Area. Journal of Meteorological Research, 2019, 33(6): 1143-1156.  doi: 10.1007/s13351-019-9072-3. [6] Ping YANG, Guoyu REN, Pengcheng YAN, Jingmian DENG. Tempospatial Pattern of Surface Wind Speed and the “Urban Stilling Island” in Beijing City. Journal of Meteorological Research, 2020, 34(5): 1-11.  doi: 10.1007/s13351-020-9135-5. [7] Ting YOU, Renguang WU, Gang HUANG. Differences in Meteorological Conditions between Days with Persistent and Non-Persistent Pollution in Beijing, China. Journal of Meteorological Research, 2018, 32(1): 81-98.  doi: 10.1007/s13351-018-7086-x. [8] Chao WANG, Xingqin AN, Shixian ZHAI, Zhaobin SUN. Tracking a Severe Pollution Event in Beijing in December 2016 with the GRAPES–CUACE Adjoint Model. Journal of Meteorological Research, 2018, 32(1): 49-59.  doi: 10.1007/s13351-018-7062-5. [9] Kai SUN, Hongnian LIU, Xueyuan WANG, Zhen PENG, Zhe XIONG. The Aerosol Radiative Effect on a Severe Haze Episode in the Yangtze River Delta. Journal of Meteorological Research, 2017, 31(5): 865-873.  doi: 10.1007/s13351-017-7007-4. [10] Junting ZHONG, Xiaoye ZHANG, Yaqiang WANG, Junying SUN, Yangmei ZHANG, Jizhi WANG, Kaiyan TAN, Xiaojing SHEN, Haochi CHE, Lu ZHANG, Zhouxiang ZHANG, Xuefei QI, Huarong ZHAO, Sanxue REN, Yang LI. Relative Contributions of Boundary-Layer Meteorological Factors to the Explosive Growth of PM2.5 during the Red-Alert Heavy Pollution Episodes in Beijing in December 2016. Journal of Meteorological Research, 2017, 31(5): 809-819.  doi: 10.1007/s13351-017-7088-0. [11] Lihui LYU, Yunsheng DONG, Tianshu ZHANG, Cheng LIU, Wenqing LIU, Zhouqing XIE, Yan XIANG, Yi ZHANG, Zhenyi CHEN, Guangqiang FAN, Leibo ZHANG, Yang LIU, Yuchen SHI, Xiaowen SHU. Vertical Distribution Characteristics of PM2.5 Observed by a Mobile Vehicle Lidar in Tianjin, China in 2016. Journal of Meteorological Research, 2018, 32(1): 60-68.  doi: 10.1007/s13351-018-7068-z. [12] Yangmei ZHANG, Yaqiang WANG, Xiaoye ZHANG, Xiaojing SHEN, Junying SUN, Lingyan WU, Zhouxiang ZHANG, Haochi CHE. Chemical Components, Variation, and Source Identification of PM1 during the Heavy Air Pollution Episodes in Beijing in December 2016. Journal of Meteorological Research, 2018, 32(1): 1-13.  doi: 10.1007/s13351-018-7051-8. [13] Li Xingsheng. ON SIMILARITY AND THE TURBULENT STRUCTURE IN THE STABLE BOUNDARY LAYER. Journal of Meteorological Research, 1991, 5(2): 141-119. [14] Yan Banghua, Lu Daren, Wu Beiying, Liu Chuntian, Yu Ming, Zhang Wenxing. STUDY OF THE POLARIZATION CHARACTERISTICS OF SKYLIGHT OVER BEIJING. Journal of Meteorological Research, 1998, 12(4): 385-393. [15] WANG Yingchun, WANG Jianjie, CUI Bo, LU Duanjun, YU Wei, GUO Xiaorong, CHEN Dehui. THE BEIJING AREA MESOSCALE NWP SYSTEM AND ITS APPLICATION. Journal of Meteorological Research, 2000, 14(2): 233-246. [16] LANG Xianmei. Seasonal Prediction of Spring Dust Weather Frequency in Beijing. Journal of Meteorological Research, 2011, 25(5): 682-690. [17] Zhang Xixuan, Zhang Cuihua. SEARCH FOR CORRELATIVITY OF LIGHTNING(STROKE)WITH ATMOSPHERIC STRATIFICATION FACTORS. Journal of Meteorological Research, 1991, 5(2): 252-252. [18] Wang Yunfeng, Wu Rongsheng. THE INFLUENCE OF STRATIFICATION ON FRONTOGENESIS CAUSED BY GEOSTROPHIC ADJUSTMENT*. Journal of Meteorological Research, 1998, 12(3): 376-381. [19] Liu Shida. NONLINEAR DYNAMICS AND TURBULENCE. Journal of Meteorological Research, 1988, 2(2): 247-255. [20] Zhang Xinping, Xie Zichu, Yao Tandong. MATHEMATICAL MODELING OF VARIATIONS ON STABLE ISOTOPIC RATIOS IN FALLING RAINDROPS*. Journal of Meteorological Research, 1998, 12(2): 213-220.
###### 通讯作者: 陈斌, bchen63@163.com
• 1.

沈阳化工大学材料科学与工程学院 沈阳 110142

## Influence of Intermittent Turbulence on Air Pollution and Its Dispersion in Winter 2016/2017 over Beijing, China

###### Corresponding author: Hongsheng ZHANG, hsdq@pku.edu.cn;
• 1. State Key Laboratory of Severe Weather, Chinese Academy of Meteorological Sciences, China Meteorological Administration, Beijing 100081
• 2. Laboratory for Climate and Ocean–Atmosphere Studies, Department of Atmospheric and Oceanic Sciences, School of Physics, Peking University, Beijing 100871
• 3. State Key Joint Laboratory of Environmental Simulation and Pollution Control, Department of Environmental Science, Peking University, Beijing 100871
• 4. State Key Laboratory of NBC Protection for Civilian, Beijing 102205
Funds: Supported by the National Key Research and Development Program of China (2016YFC0203300) and National Natural Science Foundation of China (91544216 and 41705003)

Abstract: With rapid urbanization in recent years, severe air pollution has emerged as a major issue for many regions of China, especially in some metropolises. A persistent pollution case during 6 December 2016–8 January 2017 was selected to investigate the relations between turbulent intermittency and frequent PM2.5 (particulate matters with diameter less than 2.5 μm) pollution events over the metropolitan region of Beijing, China. The accumulation of PM2.5 near the surface frequently occurred as a combined result of strong inversion layers, stagnant winds, high ambient humidity levels, and stable stratification during this case. Arbitrary-order Hilbert spectral analysis indicated that steep decreases in the PM2.5 concentration were simultaneous with the occurrence of intermittent turbulence and strong vertical mixing. A wind profiler observation revealed existence of low-level jets (LLJs) at the end of the polluted periods, suggesting that the upper-level turbulent mixing accompanied by the wind shear of LLJ was transported downward and enhanced the vertical mixing near the surface, which might have caused an abrupt reduction in PM2.5 and improvement in air conditions.

Reference (78)

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