{"title":"The Linkages between Atmospheric Boundary Layer and PM 2.5 from Different Region in China","authors":"Mengyun Lou, Qing Zhou, J. Jin, Yanfen Peng, Rui Dai, Yong Zhang, Jianping Guo","doi":"10.1109/ICMO49322.2019.9026117","DOIUrl":null,"url":null,"abstract":"Planetary boundary layer (PBL) – aerosol interaction is one of a major causes for the deterioration of air quality. Elucidating the relationship between pollution–PBL becomes essential for improving the prediction of air quality. Ground-based air quality and meteorological data, in combination with L-band high resolution (1-sec) radiosonde measurements from 2014 to 2017, were used to study the fine structures of PBL, and the correlations between boundary layer height (BLH) and PM2.5 from different region in China.There is a significant difference in the PBL–PM2.5 interaction in different regions. On the inner-annual timescale, the strongest negative correlation is observed over the North China Plain (NCP) with highly polluted conditions, followed by the Yangtze River Delta (YRD). Meanwhile, the air quality of Qinghai-Tibet Plateau (TBP) is relatively clean, where it shows the lowest negative correlation coefficient. The correlation coefficient are 0.34, -0.25 and -0.18 for the NCP, the YRD and the TBP. In the heavily polluted region, the pollutant–PBL–meteorology is closely related, indicating that their interaction is most obvious. Under clean conditions, no distinct interaction can be found between BLH and PM2.5 in the TBP, whereas the meteorological conditions show a greater impact on the development of PBL.The PBL-pollution interaction depends in the degree of pollution and the background value of BLHs, and the relationship between PM2.5 and BLHs is nonlinear, which is more obvious with high concentration of pollutants or the low BLHs. Of course, this relationship is also significantly affected by other meteorological variables.","PeriodicalId":257532,"journal":{"name":"2019 International Conference on Meteorology Observations (ICMO)","volume":"10 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2019-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2019 International Conference on Meteorology Observations (ICMO)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICMO49322.2019.9026117","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
Planetary boundary layer (PBL) – aerosol interaction is one of a major causes for the deterioration of air quality. Elucidating the relationship between pollution–PBL becomes essential for improving the prediction of air quality. Ground-based air quality and meteorological data, in combination with L-band high resolution (1-sec) radiosonde measurements from 2014 to 2017, were used to study the fine structures of PBL, and the correlations between boundary layer height (BLH) and PM2.5 from different region in China.There is a significant difference in the PBL–PM2.5 interaction in different regions. On the inner-annual timescale, the strongest negative correlation is observed over the North China Plain (NCP) with highly polluted conditions, followed by the Yangtze River Delta (YRD). Meanwhile, the air quality of Qinghai-Tibet Plateau (TBP) is relatively clean, where it shows the lowest negative correlation coefficient. The correlation coefficient are 0.34, -0.25 and -0.18 for the NCP, the YRD and the TBP. In the heavily polluted region, the pollutant–PBL–meteorology is closely related, indicating that their interaction is most obvious. Under clean conditions, no distinct interaction can be found between BLH and PM2.5 in the TBP, whereas the meteorological conditions show a greater impact on the development of PBL.The PBL-pollution interaction depends in the degree of pollution and the background value of BLHs, and the relationship between PM2.5 and BLHs is nonlinear, which is more obvious with high concentration of pollutants or the low BLHs. Of course, this relationship is also significantly affected by other meteorological variables.