Nitrogen oxides (NOx) are important air pollutants and play a crucial role in climate change. NOx emissions are important for chemical transport models to simulate and forecast air quality. Up-to-date emission information also helps policymakers to mitigate air pollution. In this thesis, we have focused on providing better NOx emission estimates with the DECSO (Daily Emission estimates Constrained by Satellite Observations) inversion algorithm applied to satellite observations. DECSO is a fast algorithm, which enables daily emissions estimates as soon as the satellite observations are available. Satellite-derived emissions reveal more specific information on the location and strength of sources than concentration observations. The monthly and yearly variability in emissions are well captured. This is demonstrated by our monitoring of the effect of air quality regulations on emissions during events like the 2014 Youth Olympic Games. Near the Chinese coast ship tracks, which are otherwise hidden under the outflow of air pollution from the mainland, are revealed in our NOx emissions derived with DECSO applied to OMI satellite observations. Trends of shipping emissions for a 10-year period (2007 to 2016) over Chinese seas are presented for the first time.
|Award date||26 Jan 2018|
|Publication status||Published - 2 Jan 2018|
- Air Quality
- Remote sensing