Distribution and Trends Of Natural and Anthropogenic Voc Emissions Using Omi/Aura Hcho Measurements
De Smedt, Isabelle1; Danckaert, Thomas1; Lerot, Christophe1; Stavrakou, Trissevgeni1; Müller, Jean-François1; Boersma, Folkert2; Van Roozendael, Michel1

Formaldehyde (HCHO) is a short-lived intermediate product in the oxidation of non-methane volatile organic compounds (NMVOCs) emitted by vegetation, fires and human activities. For more than a decade, tropospheric columns of HCHO have been monitored at the global scale using spaceborne nadir UV-VIS spectrometers. Based on the Differential Optical Absorption Spectroscopy (DOAS) technique, the retrieval of HCHO is particularly challenging and is characterised by large systematic and random uncertainties. In order to produce coherent long series of observations from multiple satellite sounders, it is therefore essential to carefully control and harmonise the retrieval settings for each individual sensor. Such data harmonisation has been successfully demonstrated in past studies making use of the European sensors GOME, SCIAMACHY and GOME-2. In this work, we further extend our investigations to the analysis of OMI/AURA HCHO measurements (2005-2012). OMI retrievals presented here are being performed in the framework of the preparation of the future Copernicus Sentinel 5 Precursor (S5P) mission to be launched in summer 2015. We first intercompare the HCHO column data products derived from OMI and past sensors and assess their internal consistency. Second the GOME-2 and OMI observations are exploited to investigate the role of diurnal variation effects on the HCHO distributions seen by both sensors, supported by model simulations from two different 3D-CTMs (IMAGES v2 and TM5) and by ground-based MAX-DOAS data. The long-term trends in HCHO columns, resulting from biogenic and anthropogenic NMVOC emission changes, are also revisited making use of all available sensors. Finally the high spatial resolution of OMI is used to better characterise the anthropogenic emissions with a focus on occidental cities which are particularly better captured by OMI than by other existing sensors.