Self-organized classification of boundary layer meteorology and associated characteristics of air quality in Beijing

Liao, Zhiheng; Sun, Jianqi; Jialin, Yao; Liu, Li; Li, Haowen; Liu, Jian; Xie, Jielan; Wu, Dui; Fan, Saijun

doi:10.5194/acp-18-6771-2018

Cited by 20 publications

(12 citation statements)

References 55 publications

(53 reference statements)

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“…Depending on the study domain and research objectives, different meteorological variables including geopotential height, mean sea level pressure, and zonal and meridional winds are used for the classification. The SOM, an artificial neural network method with unsupervised learning (Kohonen, 1990;Michaelides et al, 2007), is widely used in cluster analysis in atmospheric sciences (Jiang et al, 2017;Liao et al, 2018;Stauffer et al, 2018) because of its superiority over other algorithms (Liu et al, 2006;Jensen et al, 2012). The SOM performs a nonlinear projection from the input data space to a two-dimensional array of nodes objectively.…”

Section: Classification Of the Synoptic Weather Patternsmentioning

confidence: 99%

Local and synoptic meteorological influences on daily variability in summertime surface ozone in eastern China

et al. 2020

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Abstract. Ozone pollution in China is influenced by meteorological processes on multiple scales. Using regression analysis and weather classification, we statistically assess the impacts of local and synoptic meteorology on daily variability in surface ozone in eastern China in summer during 2013–2018. In this period, summertime surface ozone in eastern China (20–42∘ N, 110–130∘ E) is among the highest in the world, with regional means of 73.1 and 114.7 µg m−3, respectively, in daily mean and daily maximum 8 h average. Through developing a multiple linear regression (MLR) model driven by local and synoptic weather factors, we establish a quantitative linkage between the daily mean ozone concentrations and meteorology in the study region. The meteorology described by the MLR can explain ∼43 % of the daily variability in summertime surface ozone across eastern China. Among local meteorological factors, relative humidity is the most influential variable in the center and south of eastern China, including the Yangtze River Delta and the Pearl River Delta regions, while temperature is the most influential variable in the north, covering the Beijing–Tianjin–Hebei region. To further examine the synoptic influence of weather conditions explicitly, six predominant synoptic weather patterns (SWPs) over eastern China in summer are objectively identified using the self-organizing map clustering technique. The six SWPs are formed under the integral influence of the East Asian summer monsoon, the western Pacific subtropical high, the Meiyu front, and the typhoon activities. On average, regionally, two SWPs bring about positive ozone anomalies (1.1 µg m−3 or 1.7 % and 2.7 µg m−3 or 4.6 %), when eastern China is under a weak cyclone system or under the prevailing southerly wind. The impact of SWPs on the daily variability in surface ozone varies largely within eastern China. The maximum impact can reach ±8 µg m−3 or ±16 % of the daily mean in some areas. A combination of the regression and the clustering approaches suggests a strong performance of the MLR in predicting the sensitivity of surface ozone in eastern China to the variation of synoptic weather. Our assessment highlights the importance of meteorology in modulating ozone pollution over China.

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Section: Classification Of the Synoptic Weather Patternsmentioning

confidence: 99%

Local and synoptic meteorological influences on daily variability in summertime surface ozone in eastern China

et al. 2020

View full text Add to dashboard Cite

show abstract

“…SOM, an artificial neural network method with unsupervised learning (Kohonen, 1990;Michaelides et al, 2007), is widely used in cluster analysis in atmospheric sciences (Jiang et al, 2017;Liao et al, 2018;Stauffer et al, 2018) because of its superiorities over other algorithms (Liu et al, 2006;Jensen et al, 2012). SOM performs a nonlinear projection from the input data space to a two-dimensional array of nodes objectively.…”

Section: Classification Of the Synoptic Weather Patternsmentioning

confidence: 99%

Local and synoptic meteorological influences on daily variability of summertime surface ozone in eastern China

Han¹,

Liu²,

Shu³

et al. 2019

Preprint

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Abstract. Ozone pollution in China is influenced by meteorological processes on multiple scales. Using multiple linear regression and weather classification, we statistically assess the impacts of local and synoptic meteorology on daily variability of surface ozone in eastern China in summer during 2013–2018. In this period, summertime surface ozone in eastern China (110–130° E, 20–42° N) is among the highest in the world with regional means of 73.1 and 114.7 µg m−3, respectively, in daily mean and daily maximum 8-hour average. By developing a multiple linear regression (MLR) model driven by local and synoptic weather factors, we establish a quantitative linkage between the daily ozone concentrations and meteorology in the study region. The meteorology described by the MLR model can explain ~ 46 % of the daily variability in summertime surface ozone across eastern China. The model shows that synoptic factors contribute to ~ 37 % of the overall meteorological effects on daily variability of surface ozone in eastern China. Among local meteorological factors, relative humidity is the most influential variable in the center and south of eastern China including the Yangtze River Delta and the Pearl River Delta regions, while temperature is the most influential variable in the north covering the Beijing-Tianjin-Hebei region. To further examine the synoptic influence of weather conditions explicitly, six predominant synoptic weather patterns (SWPs) over eastern China in summer are objectively identified using the self-organizing map clustering technique. The six SWPs are formed under the integral influence of the East Asian summer monsoon, the western Pacific subtropical high, the Meiyu front, and the typhoon activities. The results show that the impacts of each of the SWPs on the daily variability of surface ozone vary largely inside the study area. The maximum impact can reach &pm;8 µg m−3 or &pm;16 % of the daily mean over some subregions in eastern China. A combination of the regression and the clustering approaches suggests a strong performance of the MLR model in predicting the sensitivity of surface ozone in eastern China to the variation of synoptic weather. Our assessment highlights the important role of meteorology in modulating ozone pollution over China.

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“…Temperature expectedly tracks the trend of incident solar radiation quite well, peaking first in April and then in October-November ( Figure 1d). BLH, a driver of aerosol transport and concentration (Liao et al, 2018;Xiang et al, 2019), shows a seasonal maximum (minimum) from November-April (May-October) ( Figure 1e). Lastly, wind speed shows maxima in April and August with minima in May-June and October-December ( Figure 1f).…”

Section: Meteorological Profile and Seasonal Trajectoriesmentioning

confidence: 99%

Characterizing Weekly Cycles of Particulate Matter in a Coastal Megacity: The Importance of a Seasonal, Size‐Resolved, and Chemically Speciated Analysis

et al. 2020

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We present the first study of the weekly cycles (WCs) of chemically speciated and size‐resolved particulate matter (PM) in Metro Manila, Philippines, a coastal megacity located within a highly complex meteorological environment that is subject to both anthropogenic and natural sources. To measure PM, Micro‐Orifice Uniform Deposit Impactors (MOUDIs) were deployed in Metro Manila from August 2018 to October 2019 and samples were analyzed for ionic and elemental species, including black carbon (BC). The WC in Metro Manila varied remarkably across seasons, linked to shifts in meteorology, transport, and aerosol source. Identified aerosol sources were traffic, local and regional burning, dust, sea salt, and secondary aerosol formation. Direct emissions induced a late workweek peak, while secondary aerosol formation led to a weekend peak in response to precursor buildup mainly from traffic. Seasonal analysis revealed that local burning from solid waste management and agricultural fires induced a strong WC peak while regional burning emissions from the Maritime Continent (MC) and possibly the Asian continent elevated seasonal baseline concentrations of the WC. BC showed a seasonally persistent WC, consistent in magnitude, weekly peak timing, and particle size. The dominant submicrometer WC and the contribution of BC across seasons have important ramifications on public health and policymaking, which are also discussed. As many of the observed WC patterns are undetectable when using only bulk PM, this study demonstrates that a seasonal, size‐resolved, and chemically speciated characterization is required to more fully understand the driving mechanisms governing WCs.

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Self-organized classification of boundary layer meteorology and associated characteristics of air quality in Beijing

Cited by 20 publications

References 55 publications

Local and synoptic meteorological influences on daily variability in summertime surface ozone in eastern China

Local and synoptic meteorological influences on daily variability in summertime surface ozone in eastern China

Local and synoptic meteorological influences on daily variability of summertime surface ozone in eastern China

Characterizing Weekly Cycles of Particulate Matter in a Coastal Megacity: The Importance of a Seasonal, Size‐Resolved, and Chemically Speciated Analysis

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