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Assimilation of satellite data for regional air pollution forecasting


The scientific objective of the proposal is to investigate the added value ofsatellite observation for regional and continental tropospheric air pollutionstudies. Satellite observations of trace gases in the troposphere have become available only recently. Most of our sparse present day knowledge of air pollution is based on routine surface observations at a limited number of sites, and a few aircraft measurement campaigns.

The high-resolution CHIMERE Chemistry Transport Model (CTM) will be used in conjunction with GOME, SCIAMACHY, and OMI satellite data, to (1) study if these data sets can contribute to improved surface emission inventories and air pollution forecasts for Europe, (2) identify shortcomings in the transport and chemistry ASSSATAIRPOLs of CHIMERE, and (3) quantify how much realistic tracer profile information from a high-resolution CTM can improve the satellite retrievals.

The approach is to develop innovative chemical data assimilation algorithms. These algorithms will be used to assimilate nitrogen dioxide (Nu2) tropospheric columns into CHIMERE in order to constraint nitrogen oxide (NOX) emission used as input in the model. An improved description of NOX sources will have an important positive impact on air pollution forecasts. The project will build on the successful assimilation of ozone surface observations in CHIMERE, as part of my PhD work, and the expertise of the host institute on satellite NO2 retrievals, global-scale atmospheric modelling, and advanced data assimilation techniques.

The work will be done in the Atmospheric Composition Division led by Prof.H. M. Kelder, at KNMI, The Netherlands. The project involves my collaboration with this research group with many years of expertise in atmospheric chemistry research on a global scale, which is complementary to my experience in air pollution research

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