Effect of Analysis Nudging Data Assimilation on the PM2.5 Concentration Simulation during a Haze Event in the Seoul Metropolitan Area in 2019

This study identified the key chemical components based on an analysis of the seasonal variations of ground level PM2.5 concentrations and its major chemical constituents (sulfate, nitrate, ammonium, organic carbon, and elemental carbon) in the Seoul Metropolitan Area (SMA), over a period of five years, ranging from 2012 to 2016. It was found that the mean PM2.5 concentration in the SMA was 33.7 μg/m3, while inorganic ions accounted for 53% of the total mass concentration. The component ratio of inorganic ions increased by up to 61%–63% as the daily mean PM2.5 concentration increased. In spring, nitrate was the dominant component of PM2.5, accounting for 17%–32% of the monthly mean PM2.5 concentrations. In order to quantify the impact of long-range transport on the SMA PM2.5, a set of sensitivity simulations with the community multiscale air-quality model was performed. Results show that the annual averaged impact of Chinese emissions on SMA PM2.5 concentrations ranged from 41% to 44% during the five years. Chinese emissions’ impact on SMA nitrate ranged from 50% (winter) to 67% (spring). This result exhibits that reductions in SO2 and NOX emissions are crucial to alleviate the PM2.5 concentration. It is expected that NOX emission reduction efforts in China will help decrease PM2.5 concentrations in the SMA.

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Analysis of a Severe PM2.5 Episode in the Seoul Metropolitan Area in South Korea from 27 February to 7 March 2019: Focused on Estimation of Domestic and Foreign Contribution

Atmosphere ◽

10.3390/atmos10120756 ◽

2019 ◽

Vol 10 (12) ◽

pp. 756 ◽

Cited By ~ 8

Author(s):

Daegyun Lee ◽

Jin-Young Choi ◽

Jisu Myoung ◽

Okgil Kim ◽

Jihoon Park ◽

...

Keyword(s):

South Korea ◽

Metropolitan Area ◽

Observation Data ◽

Brute Force ◽

Seoul Metropolitan Area ◽

Westerly Winds ◽

Brute Force Method ◽

Target Period ◽

Northwesterly Wind ◽

Pm2.5 Concentration

In this study, domestic and foreign contributions to a severe PM2.5 episode in South Korea, in which “emergency reduction measures against particulate matter” were issued, were analyzed. During the period between 27 February and 7 March in 2019 when high PM2.5 concentrations occurred, the PM2.5 concentration in the Seoul metropolitan area (SMA) in South Korea was approximately 87.3 μg/m3 on average, and a severe PM2.5 concentration level of approximately 113.4 μg/m3 was observed between 3 March and 5 March. The results of the analysis conducted using the HYSPLIT (Hybrid Single-Particle Lagrangian Integrated Trajectory) model and meteorological observation data showed that northwesterly wind or westerly winds were formed during the P1 and P3 periods when the PM2.5 concentration markedly increased. When the PM2.5 concentrations in East Asia were simulated using the Community Multiscale Air Quality (CMAQ), it was found that the high PM2.5 concentrations that occurred in the SMA of South Korea were mostly affected by PM2.5 transported over long distances and following atmospheric stagnation. When the domestic and foreign contributions were evaluated using the brute-force method (BFM), the foreign and domestic contribution concentrations were found to be 62.8 and 16.8 μg/m3, respectively, during the target period of this study. It was also found that the foreign contribution was 78.8%, while the domestic contribution was 21.2%.

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X-Net-Based Radar Data Assimilation Study over the Seoul Metropolitan Area

Remote Sensing ◽

10.3390/rs12050893 ◽

2020 ◽

Vol 12 (5) ◽

pp. 893 ◽

Cited By ~ 1

Author(s):

Ji-Won Lee ◽

Ki-Hong Min ◽

Young-Hee Lee ◽

GyuWon Lee

Keyword(s):

Data Assimilation ◽

Radial Velocity ◽

Metropolitan Area ◽

Numerical Data ◽

Radar Data ◽

Radar Reflectivity ◽

Model Verification ◽

Seoul Metropolitan Area ◽

X Band ◽

Reflectivity Data

This study investigates the ability of the high-resolution Weather Research and Forecasting (WRF) model to simulate summer precipitation with assimilation of X-band radar network data (X-Net) over the Seoul metropolitan area. Numerical data assimilation (DA) experiments with X-Net (S- and X-band Doppler radar) radial velocity and reflectivity data for three events of convective systems along the Changma front are conducted. In addition to the conventional assimilation of radar data, which focuses on assimilating the radial velocity and reflectivity of precipitation echoes, this study assimilates null-echoes and analyzes the effect of null-echo data assimilation on short-term quantitative precipitation forecasting (QPF). A null-echo is defined as a region with non-precipitation echoes within the radar observation range. The model removes excessive humidity and four types of hydrometeors (wet and dry snow, graupel, and rain) based on the radar reflectivity by using a three-dimensional variational (3D-Var) data assimilation technique within the WRFDA system. Some procedures for preprocessing radar reflectivity data and using null-echoes in this assimilation are discussed. Numerical experiments with conventional radar DA over-predicted the precipitation. However, experiments with additional null-echo information removed excessive water vapor and hydrometeors and suppressed erroneous model precipitation. The results of statistical model verification showed improvements in the analysis and objective forecast scores, reducing the amount of over-predicted precipitation. An analysis of a contoured frequency by altitude diagram (CFAD) and time–height cross-sections showed that increased hydrometeors throughout the data assimilation period enhanced precipitation formation, and reflectivity under the melting layer was simulated similarly to the observations during the peak precipitation times. In addition, overestimated hydrometeors were reduced through null-echo data assimilation.

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