###### Abstract  
Multiple statistical prediction modeling of PM\({}_{10}\), PM\({}_{2.5}\) and PM\({}_{1}\) at Gangneung city, Korea, was performed in association with local meteorological parameters (air temperature, wind speed and relative humidity) and PM\({}_{10}\) and PM\({}_{2.5}\) concentrations of an upwind site in Beijing, China, in the transport route of Chinese yellow dusts which originated from the Gobi Desert and passed through Beijing to the city from 18 March to 27 March 2015. Before and after the dust periods, the PM\({}_{10}\), PM\({}_{2.5}\) and PM\({}_{1}\) concentrations showed as being very high at 09:00 LST (the morning rush hour) by the increasing emitted pollutants from vehicles and flying dust from the road and their maxima occurred at 20:00 to 22:00 LST (the evening departure time) from the additional pollutants from resident heating boilers. During the dust period, these peak trends were not found due to the persistent accumulation of dust in the city from the Gobi Desert through Beijing, China, as shown in real-time COMS-AI satellite images. Multiple correlation coefficients among PM\({}_{10}\), PM\({}_{2.5}\) and PM\({}_{1}\) at Gangneung were in the range of 0.916 to 0.998. Multiple statistical models were devised to predict each PM concentration, and the significant levels through multi-regression analyses were \(p<0.001\), showing all the coefficients to be significant. The observed and calculated PM concentrations were compared, and new linear regression models were sequentially suggested to reproduce the original observed PM values with improved correlation coefficients, to some extent. PM\({}_{10}\); PM\({}_{2.5}\); PM\({}_{1}\); yellow dust; COMS-AI satellite images; correlation coefficient; multiple regression model +
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the Taklamakan Desert in northwest China, huge amounts of yellow sands and dusts are raised from the ground surface up to a 3 km or 5 km height, and they are vertically and horizontally transported to the wide downwind regions, such as eastern China, Korea, Japan and southeastern Asian countries. This phenomenon is referred to in a variety of ways: Huang Chen, KOSA, Asian Dust, Yellow Sand, Sand Storm and Dust Storm [17; 18; 19; 20; 21; 22]. Due to the persistent accumulation of dust particles in the lower atmosphere of the source area, visibility during the dust period in China and Mongolia is the worst, and it becomes rapidly worse in the further downwind countries of northeast and southeast Asia, including China, Taiwan, Korea, Japan and even the west coast of the U.S.A. by the deposition of a huge amount of transported dusts [23; 24; 25; 26]. Many environmental researchers have explained the chemical composition of fine and coarse particles in relation with Asian Dust events in detail [27; 28; 29]. Furthermore, [PERSON] [30] mentioned more severe air pollution in the case of a higher ratio of PM\({}_{2.5}\)/PM\({}_{10}\) in China. [PERSON] [31; 32] and [PERSON] and [PERSON] [33] indicated that, using a simple regression method, the coarse particle concentration (PM\({}_{10}\)-PM\({}_{2.5}\)) in Gangneung city, Korea, was greater than the fine particle concentration (PM\({}_{2.5}\)) during the dust period, and the coarse particulates larger than 2.5 \(\upmu\)m could significantly contribute to the PM\({}_{10}\) concentration, but PM\({}_{2.5}\) decreased sharply. We know that atmospheric circulation and atmospheric boundary layer structure from various numerical modeling on dust transportation and accumulation can greatly affect the dispersion and accumulation of particulate matters in the inland and coastal cities, resulting in very high pollutant concentrations [34; 35; 36; 37; 38; 39]. In recent years, multivariate statistical modeling was also carried out to predict temporal and spatial analyses of particulate matter affected by gases or meteorological parameters [8; 40].