کد مقاله | کد نشریه | سال انتشار | مقاله انگلیسی | نسخه تمام متن |
---|---|---|---|---|
6342741 | 1311021 | 2011 | 10 صفحه PDF | دانلود رایگان |
![عکس صفحه اول مقاله: Inverse modeling analysis of soil dust sources over East Asia Inverse modeling analysis of soil dust sources over East Asia](/preview/png/6342741.png)
Soil dust is the dominant aerosol by mass concentration in the troposphere and has considerable effects on air quality and climate. Parts of East Asia, including southern Mongolia, northern China, and the Taklamakan Desert, are important dust source regions. Accurate simulations of dust storm events are crucial for protecting human health and assessing the climatic impacts of dust events. However, even state-of-the-art aerosol models still contain large uncertainties in soil dust simulations, particularly for the dust emissions over East Asia. In this study, we attempted to reduce these uncertainties by using an inverse modeling technique to simulate dust emissions. We used the measured mass concentration of particles less than 10 μm in aerodynamic diameter (PM10) in the surface air over East Asia, in combination with an inverse model, to understand the dust sources. The global three-dimensional GEOS-Chem chemical transport model (CTM) was used as a forward model. The inverse model analysis yielded a 76% decrease in dust emissions from the southern region of the Gobi Desert, relative to the a priori result. The a posteriori dust emissions from the Taklamakan Desert and deserts in eastern and Inner Mongolia were two to three fold higher than the a priori dust emissions. The simulation results with the a posteriori dust sources showed much better agreement with these observations, indicating that the inverse modeling technique can be useful for estimation of the optimized dust emissions from individually sourced regions.
⺠Inverse modeling study using surface observations for soil dust sources. ⺠The a priori dust source is 38.2 Tg over Asia in April 2001. ⺠The a posteriori source is 35.4 Tg, slightly lower than the a priori value. ⺠The spatial pattern of the a posteriori differs significantly from the a priori.
Journal: Atmospheric Environment - Volume 45, Issue 32, October 2011, Pages 5903-5912