"I am always doing what I cannot do yet, in order to learn how to do it"
-Vincent Van Gogh

MS student Xinyi Ling

My research is focused on improving the accuracy of PM2.5 concentration and chemical composition estimates by using novel remote sensing techniques. The remote sensing component of the proposed study is from the NASA Langley HSRL aerosol types retrieved during Discover-AQ campaign. The modeling component is the EPA's CMAQ Model. The linkage between the remotely sensed and the modeled data is provided by CATCH - a recently developed algorithm that that takes GEOS-Chem model-predicted data on aerosol microphysics and chemical composition and generates aerosol types similar to that retrieved by HSRL. The data from the US EPA ground monitoring stations is used for the performance evaluation in prior and posterior assessments.

My research is supported by NASA Earth and Space Science Fellowship.

I obtained my undergraduate degree in Atmospheric Sciences from Nanjing University in China. Due to the deteriorating air conditions in China, I decided to further my study on the issue of air pollution. Therefore, I came to North Carolina State University to pursue a master's degree.