Distinct Meteorological Mode associated with High PM2.5 Episodes in Seoul, South Korea

IF 2.6 3区 地球科学 Q3 METEOROLOGY & ATMOSPHERIC SCIENCES
Daniel Choi, Hyo-Jung Lee, L. Chang, Hyun-Young Jo, Yu-Jin Jo, Shin-Young Park, Geum-Hee Yang, Cheol-Hee Kim
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引用次数: 0

Abstract

In this study, high particulate matter (PM2.5) pollution episodes were examined in Seoul, the capital city of South Korea, which, based on the episode characteristics, were influenced by a distinct meteorological mode, long-range transport (LRT), from two-level meteorological observations: surface and 850-500 hPa level. We performed two-step statistical analysis including principal component (PC) analysis of meteorological variables based on the observation data, followed by multiple linear regression (MLR). The meteorological variables included surface temperature (Tsfc), wind speed (WSsfc), and the east–west (usfc) and north– south (vsfc) components of wind speed, as well as wind components at 850 hPa geopotential height (u850 and v850, respectively) and the vertical temperature gradient between 850 and 500 hPa. Our two-step analysis of data collected during 2018–2019 revealed that the dominant factors influencing high-PM2.5 days in Seoul (129 days) were upper wind characteristics in winter, including positive u850 and negative v850, that were controlled by the presence of continental anticyclones that increased the likelihood of LRT of PM2.5 pollutants. Regional-scale meteorological variables, including surface and upper meteorological variables on normal and high-PM2.5 days, showed distinct covariation over Seoul, a megacity in the eastern part of northeast Asia with large anthropogenic emissions. Although this study examined only two atmospheric layers (surface and 500-850 hPa), our results clearly detected high-PM2.5 episodes with LRT characteristics, suggesting the importance of considering both geographical distinctiveness and seasonal meteorological covariability when scaling down continental-to-local response to emission reduction.
与韩国首尔高PM2.5事件相关的独特气象模式
本研究对韩国首都首尔的高颗粒物(PM2.5)污染事件进行了研究,根据事件特征,该事件受到地表和850-500 hPa两层气象观测的远程传输(LRT)气象模式的影响。采用主成分分析(PC)和多元线性回归(MLR)两步统计分析方法。气象变量包括地表温度(Tsfc)、风速(WSsfc)、风速的东西分量(usfc)和南北分量(vsfc),以及850 hPa位势高度的风分量(分别为u850和v850)和850 - 500 hPa之间的垂直温度梯度。我们对2018-2019年收集的数据进行了两步分析,结果显示,影响首尔(129天)高PM2.5天数的主要因素是冬季的高空风特征,包括正的v850和负的v850,这是由大陆反气旋的存在控制的,这增加了PM2.5污染物LRT的可能性。在东北亚东部特大城市首尔,区域尺度气象变量(包括正常和高pm2.5日的地面和高空气象变量)呈现出明显的共变特征。虽然这项研究只考察了两个大气层(表层和500-850 hPa),但我们的结果清楚地发现了具有LRT特征的高pm2.5事件,这表明在缩小大陆对局部减排响应时,考虑地理独特性和季节气象协变的重要性。
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来源期刊
Journal of Applied Meteorology and Climatology
Journal of Applied Meteorology and Climatology 地学-气象与大气科学
CiteScore
5.10
自引率
6.70%
发文量
97
审稿时长
3 months
期刊介绍: The Journal of Applied Meteorology and Climatology (JAMC) (ISSN: 1558-8424; eISSN: 1558-8432) publishes applied research on meteorology and climatology. Examples of meteorological research include topics such as weather modification, satellite meteorology, radar meteorology, boundary layer processes, physical meteorology, air pollution meteorology (including dispersion and chemical processes), agricultural and forest meteorology, mountain meteorology, and applied meteorological numerical models. Examples of climatological research include the use of climate information in impact assessments, dynamical and statistical downscaling, seasonal climate forecast applications and verification, climate risk and vulnerability, development of climate monitoring tools, and urban and local climates.
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