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- Author or Editor: Hee-Jung Yang x
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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 (T sfc), wind speed (WSsfc), and the east–west (u sfc) and north–south (υ sfc) components of wind speed, as well as wind components at 850-hPa geopotential height (u 850 and υ 850, respectively) and the vertical temperature gradient between 850 and 500 hPa. Our two-step analysis of data collected during the period 2018–19 revealed that the dominant factors influencing high-PM2.5 days in Seoul (129 days) were upper-wind characteristics in winter, including positive u 850 and negative υ 850, 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.
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 (T sfc), wind speed (WSsfc), and the east–west (u sfc) and north–south (υ sfc) components of wind speed, as well as wind components at 850-hPa geopotential height (u 850 and υ 850, respectively) and the vertical temperature gradient between 850 and 500 hPa. Our two-step analysis of data collected during the period 2018–19 revealed that the dominant factors influencing high-PM2.5 days in Seoul (129 days) were upper-wind characteristics in winter, including positive u 850 and negative υ 850, 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.
