Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
6336864 | Atmospheric Environment | 2016 | 37 Pages |
Abstract
Great difference exists in the aerosol optical depth (AOD) between summer and winter over the North China Plain (NCP). Monthly mean AOD at 550 nm derived from the MODIS (MODerate Resolution Imaging Spectroradiometer) products during 2000-2014 over the area of 30-40° N and 110-125° E exhibits an annual maximum in June (0.855 ± 0.130) and a minimum in December (0.381 ± 0.032). This seasonality of AOD is in the opposite phase with the surface particulate matter (PM) concentration (higher in winter and lower in summer). The possible causes for the higher AOD in June (compared with December) include (a) a higher boundary layer height (BLH) that results in more efficient transport and mixing of aerosol particles to a higher altitude (corresponding to a lower particle concentration near surface) as revealed by the Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observations profile, (b) a higher relative humidity (RH) due to the inshore monsoon circulation that leads to enhancement of aerosol extinction, (c) emission from the regional open stalk burning in the summer harvest season (as seen from MODIS fire products), and (d) the typical eastward open topographical basin over NCP. Under the assumption that the aerosol and water vapor are well mixed within the boundary layer, analysis on multi-year average shows that the differences in BLH, RH and surface PM concentration can explain up to 81% of the variance of monthly averaged AOD over NCP. A preliminarily hypothesis is also suggested to interpret the shift of AOD pattern from winter to summer with an abrupt increase of AOD from May to June, as well as an increase of surface PM2.5 concentration over NCP during the early phase of northward progress of the East Asia summer monsoon front.
Related Topics
Physical Sciences and Engineering
Earth and Planetary Sciences
Atmospheric Science
Authors
Wenjun Qu, Jun Wang, Xiaoye Zhang, Lifang Sheng, Wencai Wang,