干旱区生态环境知识资源中心(Arid): Statistical Modeling for PM10, PM2.5 and PM1 at Gangneung Affected by Local Meteorological Variables and PM10 and PM2.5 at Beijing for Non- and Dust Periods

Arid

DOI	10.3390/app112411958
	Statistical Modeling for PM10, PM2.5 and PM1 at Gangneung Affected by Local Meteorological Variables and PM10 and PM2.5 at Beijing for Non- and Dust Periods
	Choi, Soo-Min; Choi, Hyo
通讯作者	Choi, H (corresponding author)，Atmospher & Ocean Disaster Res Inst, Kangnung 25563, South Korea.
来源期刊	APPLIED SCIENCES-BASEL
EISSN	2076-3417
出版年	2021
卷号	11 期号:24
英文摘要	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.
英文关键词	PM10 PM (2 5) PM1 yellow dust COMS-AI satellite images correlation coefficient multiple regression model
类型	Article
语种	英语
开放获取类型	gold
收录类别	SCI-E
WOS记录号	WOS:000735488900001
WOS关键词	ATMOSPHERIC BOUNDARY-LAYER ; LONG-RANGE TRANSPORT ; PARTICULATE AIR-POLLUTION ; YELLOW SAND ; HEALTH-RISKS ; RIVER DELTA ; CIRCULATION ; SEOUL ; POLLUTANTS ; MATTER
WOS类目	Chemistry, Multidisciplinary ; Engineering, Multidisciplinary ; Materials Science, Multidisciplinary ; Physics, Applied
WOS研究方向	Chemistry ; Engineering ; Materials Science ; Physics
资源类型	期刊论文
条目标识符	http://119.78.100.177/qdio/handle/2XILL650/375747
作者单位	[Choi, Soo-Min] Konkuk Univ, Dept Comp Engn, Chungju 27478, South Korea; [Choi, Hyo] Atmospher & Ocean Disaster Res Inst, Kangnung 25563, South Korea
推荐引用方式 GB/T 7714	Choi, Soo-Min,Choi, Hyo. Statistical Modeling for PM10, PM2.5 and PM1 at Gangneung Affected by Local Meteorological Variables and PM10 and PM2.5 at Beijing for Non- and Dust Periods[J],2021,11(24).
APA	Choi, Soo-Min,&Choi, Hyo.(2021).Statistical Modeling for PM10, PM2.5 and PM1 at Gangneung Affected by Local Meteorological Variables and PM10 and PM2.5 at Beijing for Non- and Dust Periods.APPLIED SCIENCES-BASEL,11(24).
MLA	Choi, Soo-Min,et al."Statistical Modeling for PM10, PM2.5 and PM1 at Gangneung Affected by Local Meteorological Variables and PM10 and PM2.5 at Beijing for Non- and Dust Periods".APPLIED SCIENCES-BASEL 11.24(2021).