Abstract
Multiple statistical prediction modeling of PM10, PM2.5 and PM1 at Gangneung city, Korea, was performed in association with local meteorological parameters (air temperature, wind speed and relative humidity) and PM10 and PM2.5 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 PM10, PM2.5 and PM1 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 PM10, PM2.5 and PM1 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.
Highlights
Atmospheric pollution consists of great amounts of different compounds, such as particulate matter and gas, mainly from vehicles and flying dusts on the road, industries, the burning of trash, forest fires and yellow dusts of the desert and arid areas to the atmosphere [1,2]
During spring, when the wind speed is over 10 m/s and the relative humidity is less than 40% in the air near the surface of the Gobi Desert in southern Mongolia, the Kubuchi Desert in Inner Mongolia, the Ordos Desert, the Huangtu Plateau and 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
We propose multiple regression statistical models to improve the predictions of PM10, PM2.5 and PM1 concentrations for Gangneung city, Korea affected by local meteorological variables and PM10 and PM2.5 concentrations in Beijing city, China before, during and after the dust periods
Summary
Atmospheric pollution consists of great amounts of different compounds, such as particulate matter and gas, mainly from vehicles and flying dusts on the road, industries, the burning of trash, forest fires and yellow dusts of the desert and arid areas to the atmosphere [1,2]. During spring, when the wind speed is over 10 m/s and the relative humidity is less than 40% in the air near the surface of the Gobi Desert in southern Mongolia, the Kubuchi Desert in Inner Mongolia, the Ordos Desert, the Huangtu Plateau (the Loess Plateau) and 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. As this city has no special factories to emit a large amounts of air pollutants, the main atmospheric pollution sources are vehicles on the road and heating boilers in the resident area during both winter and the early spring; it always maintains very low concentrations of PM, more or less 40 μg/m3, except for during the dust period
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