Development of New Inversion Technique for Updating Global Emission Inventory Using Satellite Measurement and Chemical Transport Model


Student thesis: Doctoral Thesis

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  • Chun Sing LAI

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Award date9 May 2016


Emission inventory has a wide variety of usage such as policy application and inputs for the chemical transport model. Emission inventory is commonly developed by the bottom-up approach that requires lengthy processes with huge data demand. It often suffers from long update time which limits its usage on regulatory implementation. Recent research has attempted to use an alternative approach (i.e., top-down approach) to generate/update global emission inventory. It employed observation data with global chemistry model to modify/update an existing emission inventory through data inversion. It provides a faster process than the traditional bottom up approach. In this study, a new inversion technique was developed to better separate emissions from neighboring grids when estimating emission inventory using the top-down approach. The new technique has been tested with GOCART model and OMI satellite measurement, where estimation of global SO2 emission inventory was performed for June 2007. The overall results estimated by the new technique have been found to be superior to the previous technique suggested by Martin et al. (2003). It is a better and faster approach with less inversion noise when applying satellite measurement data to update SO2 global emission inventory.