> General objectives

The more specific objectives of the ACROSAT project are to quantify and possibly explain the spatial distribution and long-term changes in the abundance of key compounds involved in:

  • tropospheric ozone formation (NOx and hydrocarbons, WP1),
  • stratospheric ozone depletion (HCl in WP2 and O3 in WP5) and
  • aerosol formation in both the stratosphere and the troposphere (OCS and SO2, WP4).

In addition, it will better characterize the short-term variations (diurnal cycle, WP3) of short-lived compounds and their impact on the accuracy of satellite retrievals and on the mutual consistency between different satellites. These objectives are detailed below per work pakage.

Below the abbreviations mean : TMOD=Tropospheric Modelling Team, SMOD=Stratospheric Modelling Team, SYN=Synergistic Exploitation of atmospheric data Team, and ULg=University of Liège.

WP I. Emissions of ozone precursors  (TMOD)

Despite progress in recent years, the emissions of key tropospheric precursors of ozone and aerosols (NOx, VOCs) remain poorly quantified. Satellite UV-Visible data offer the opportunity to constrain not only the spatial distribution, but also the interannual variability and trends of their emissions using an inverse modeling methodology developed by the TMOD team.

  • The interannual variability of biogenic and biomass burning emissions of VOCs will be derived based on GOME2/OMI HCHO data between 2007 and 2012. As a support to PEEX (Pan-Eurasian Experiment), the observed HCHO variability during the last decade will be used to investigate its relationship to climate change in Siberia. 
  • Using a two-compound (HCHO and CHOCHO) inversion setup, the direct and indirect glyoxal sources will be determined. The focus will be on East Asia, where the anthropogenic signal of glyoxal is strong, and on tropical forests, where isoprene emissions are dominant. Whenever available, ground-based measurements will be used for evaluation.
  • Satellite NO2 columns from GOME-2/OMI will be used to constrain the emissions and their evolution between 2006 and 2012, in particular over heavily industrialized areas. The role of uncertainties in chemistry (which were shown to strongly influence top-down emission estimates, Stavrakou et al.(2013)) will be evaluated.

WP II. Recent trend in stratospheric chlorine  (ULg, SMOD)

Over the recent years, significant inconsistencies were detected between the trends of important source gases and those of stratospheric reservoirs. This was e.g. the case for NO2 showing a negative and significant trend at northern mid-latitudes, on the basis of ground-based and satellite measurements. Moreover, an upturn in the evolution of HCl near 45ºN since 2007-2008 has been demonstrated using ground-based and satellite measurements, unexpected based on the known evolution of the organic chlorine budget. These observations, possibly related to changes in the atmospheric circulation, need to be investigated on a larger scale in order to determine their geographical extent and to identify their causes.

WP III. Diurnal cycles  (SYN, TMOD, SMOD, ULg)

Several of the chemical compounds addressed by this proposal exhibit a pronounced diurnal cycle, partly of photochemical origin. For example, stratospheric NO2 varies by typically a factor of two between its daily minimum and its night-time maximum.  Tropospheric formaldehyde and upper stratospheric ozone also show pronounced diurnal variations. The impact of these cycles on remote sensing data retrieval and interpretation has not been given satisfactory attention, leading to unknown errors in the retrievals and in apparent discrepancies between data measured from different platforms like e.g. GOME-2 on MetOp-A and MetOp-B, and OMI on Aura. We propose to study diurnal cycle effects impacting the retrieval and interpretation of satellite measurements of trace species addressed in this project.

In ACROSAT, multi-dimensional observation operators developed in past PRODEX projects will be coupled to the output of atmospheric chemistry models developed by the TMOD and SMOD teams. Ground-based FTIR measurements of NO2 and HCHO acquired by ULg will provide observational insight in the modelling results. The output will consist first in a systematic study of the diurnal cycle of target species, and second in the assessment of errors in retrieved GOME-2 data due to diurnal cycle effects in the currently operational retrieval chains established by the O3M-SAF.  A detailed assessment is also required in order to elucidate the origin of known biases between different sensors. The current proposal focuses on urgent issues regarding GOME-2/MetOp-A and its apparent inconsistencies with GOME-2/MetOp-B and OMI/Aura, not covered by O3M-SAF research.

WP IV. Sulfur compounds  (ULg, TMOD)

Carbonyl sulfide (OCS) is a major source of sulfur to the stratosphere, playing a role both in climate and in stratospheric ozone chemistry. Its recent accumulation in the northern mid-latitude troposphere might be related to increasing use of coal, in particular in China. The current evolution of OCS in both the troposphere and stratosphere will be characterized and possibly explained, on the global scale, using (as in WP2) NDACC ground-based data at a suite of selected stations spanning both hemispheres as well as ACE-FTS satellite observations.

The emission and subsequent oxidation of SO2 leads to acid deposition and aerosol (sulfate) formation, with important air quality and climate impacts through both the direct cooling effect (due to scattering of solar radiation) and indirect effects (changes in cloud properties). Using methodologies as in WP I, SO2 column abundances from GOME-2/OMI will be used by the TMOD team to constrain the anthropogenic emissions of SO2. Comparisons with available ground-based and airborne measurements, as well as with previous studies, will be conducted to evaluate the model. The impact of improved emission estimates on aerosol abundances will be assessed.

WP V. Reducing the model ozone deficit  (SMOD)

A long standing problem in stratospheric modelling is the model ozone deficit, i.e. the systematic underestimation of modelled ozone in the upper stratosphere/lower mesosphere (USLM) between 45 and 60 km with respect to observations. This is in particular the case for the BASCOE model developed by the SMOD team. In order to reduce this deficit, we propose to use BASCOE in combination with satellite observations of ozone and temperature. More specifically: (i) the ozone deficit in BASCOE will be quantified using ozone measurements provided by GOME-2, ACE-FTS, Odin-SMR and Odin-OSIRIS, (ii) the temperature fields used in BASCOE (from ECMWF analyses) will be evaluated against independent observations from ACE-FTS and ground-based lidar.  On this basis, a temperature bias correction scheme will be introduced, which is expected to improve the calculated ozone in comparison with observations in the USLM. Furthermore, model sensitivity tests regarding key reaction rates known to drive ozone in the USLM will be conducted, and if the improvements turn out to be small, new reactions (and species) will be implemented in the model.


>> Partners



Avenue Circulaire, 3
1180 Brussels
Fax : ++3223748423


Dr. Jean-Francois Müller (Coordinator)

Tropospheric Modelling Team (TMOD)
Tel.: ++32(0)2373366

Team members involved in ACROSAT : Dr. Trissevgeni Stavrakou, Dr. Maite Bauwens

Dr. Quentin Errera

Stratospheric Modelling Team (SMOD)
Tel.: ++32(0)23736767

Team members involved in ACROSAT : Dr. Sergey Skachko

Dr. Jean-Chrisopher Lambert

Synergistic Exploitation of atmospheric data Team (SYN)
Tel.: ++32(0)23730468

Team members involved in ACROSAT : Anne De Rudder, José Granville, Dr. Daan Hubert, A. Keppens, Gaia Pinardi, Dr. Tijl Verhoelst



Allée du 6 Août 17
B-4000 Liège (Sart-Tilman) Belgium
Fax: ++3243669747

Dr. Emmanuel Mahieu

Dept. of Astrophysics-Geophysics-Oceanography/Groupe Infra-Rouge de Physique Atmosphérique et Solaire (GIRPAS)
Tel.: ++32-4-3669786

Team members involved in ACROSAT : Whitney Bader, Benoît Bovy, Philippe Demoulin, Olivier Flock, Bernard Lejeune, Diane Zander


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