UV-Visible DOAS Research
The UV-Vis DOAS group
The DOAS group concentrates on atmospheric chemistry related research,
based on remote-sensing observations performed using the
Differential Optical Absorption Spectroscopy (DOAS) technique.
Retrieval algorithms applied to ground-based, airborne and satellite instruments
are developed and used to quantify the abundance of atmospheric trace gases such as
O3, NO2, SO2, HCHO, CHOCHO or HONO, which all play an important role for air
quality and climate change related studies. These activities are performed in the
context of international ground-based networks
and ACTRIS) and in
support of various environmental research programmes such as the ESA
Climate Change Initiative and the Copernicus programme of the European Union.
The group is lead by
Van Roozendael. See the members of our group here
Recent highlight (previous)
Detecting new SO2 sources with COBRA
In order to monitor and estimate global atmospheric sulfur dioxide (SO2) emissions, accurate and sensitive detetion of this trace gas from space is highly important. Traditionally the detection of SO2 is done with the DOAS technique . Although this method has faitfully been applied in the retrieval of SO2 from satellite for years, it is accopanied by substantial biases (requiring a post-retrieval offset-correction) and noise levels. Inspired by detection methods applied in the thermal infrared spectral domain, a new algorithm for the retrieval of SO2 columns from satellite observations in the ultraviolet spectral range was recently proposed in a highlight paper in the journal Atmospheric Chemistry and Physics (ACP, ). The retrieval scheme is based on a measurement error covariance matrix to fully represent the radiance variability over SO2-free areas, so that the SO2 slant column density is the only retrieved parameter of the algorithm. The validity of this approach, named COBRA, was demonstrated on measurements from the TROPOspheric Monitoring Instrument (TROPOMI) aboard the Sentinel-5 Precursor (S-5P) satellite. The method significantly reduces both the noise and biases present in the current TROPOMI operational DOAS SO2 retrievals.