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Mineral dust aerosol is a key player in the climate system. Determining dust sources and the spatio-temporal variability of dust emission fluxes is essential for estimating the impact of dust on the atmospheric radiation budget, cloud and precipitation formation processes, the bio-productivity and, ultimately, the carbon cycle. Although much effort has been put into determining dust sources from satellite observations, geo-locating active dust sources is still challenging and uncertainties in space and time are evident. One major source of uncertainty is the lack of clear differentiation between near-source dust aerosol and transported dust aerosol. In order to reduce this uncertainty, we use 3D information on the distribution of dust aerosol suspended in the atmosphere calculated from spectral measurements obtained by the Infrared Atmospheric Sounding Interferometer (IASI) by using the Mineral Aerosols Profiling from Infrared Radiance (MAPIR) algorithm. In addition to standard dust products from satellite observations, which provide 2D information on the horizontal distribution of dust, MAPIR allows for the retrieval of additional information on the vertical distribution of dust plumes. This ultimately enables us to separate between near-source and transported dust plumes. Combined with information on near-surface wind speed and surface properties, low-altitude dust plumes can be assigned to dust emission events and low-altitude transport regimes can be excluded. Consequently, this technique will reduce the uncertainty in automatically geo-locating active dust sources. The findings of our study illustrate the spatio-temporal distribution of North African dust sources based on 9 years of data, allowing for the observation of a full seasonal cycle of dust emissions, differentiating morning and afternoon/evening emissions and providing a first glance at long-term changes. In addition, we compare the results of this new method to the results from Schepanski et al. (2012), who manually identified dust sources from Spinning Enhanced Visible and InfraRed Imager (SEVIRI) red–green–blue (RGB) images. The comparison illustrates that each method has its strengths and weaknesses that must be taken into account when using the results. This study is of particular importance for understanding future environmental changes due to a changing climate.

In late March 2018, a large part of the Eastern Mediterranean experienced an extraordinary episode of African dust, one of the most intense in recent years, here referred to as the "Minoan Red" event. The episode mainly affected the Greek island of Crete, where the highest aerosol concentrations over the past 15 yeas were recorded, although impacts were also felt well beyond this core area. Our study fills a gap in dust research by assessing the multi-sectoral impacts of sand and dust storms and their socioeconomic implications. Specifically, we provide a multi-sectoral impact assessment of Crete during the occurrence of this exceptional African dust event. During the day of the occurrence of the maximum dust concentration in Crete, i.e. March 22nd, 2018, we identified impacts on meteorological conditions, agriculture, transport, energy, society (including closing of schools and cancellation of social events), and emergency response systems. As a result, the event led to a 3-fold increase in daily emergency responses compare to previous days associated with urban emergencies and wildfires, a 3.5-fold increase in hospital visits and admissions for Chronic Obstructive Pulmonary Disease (COPD) exacerbations and dyspnoea, a reduction of visibility causing aircraft traffic disruptions (eleven cancellations and seven delays), and a reduction of solar energy production. We estimate the cost of direct and indirect effects of the dust episode, considering the most affected socio-economic sectors (e.g. civil protection, aviation, health and solar energy production), to be between 3.4 and 3.8 million EUR for Crete. Since such desert dust transport episodes are natural, meteorology-driven and thus to a large extent unavoidable, we argue that the efficiency of actions to mitigate dust impacts depends on the accuracy of operational dust forecasting and the implementation of relevant early warning systems for social awareness., The authors gratefully acknowledge the COST Association for funding the COST Action inDust (CA16202) as well as the WMO Sand and Dust Storm Warning Advisory and Assessment System (SDS-WAS) and the ERA4CS DustClim and the AXA Research Fund for funding the AXA Chair on Sand and Dust Storms (hosted by the Barcelona Supercomputing Center). We thank the scientific team of the PROTEAS CSP facility for the feedback provided and T. Bojic and R. Burbidge for facilitating the access to the EUROCONTROL archive. We thank the scientific team of the PROTEAS CSP facility for providing DNI data for this case study. Thanks are due to FCT/MCTES for the financial support to CESAM (UIDP/50017/2020+UIDB/50017/2020) through national funds, and also to the Icelandic Research Fund for the grant no. 207057-051. Authors S. Kazadzis and P. Kosmopoulos would like to acknowledge the European Commission project EuroGEO e-shape (grant agreement No 820852). Also, International Cooperative for Aerosol Prediction (ICAP) and NASA mission researchers are gratefully for providing aerosol data for this study. Aurelio Tobias was supported by MCIN/AEI/10.13039/501100011033 (grant CEX2018-000794-S). S. Kutuzov acknowledges the Megagrant project (agreement No. 075-15-2021-599, 8.06.2021).

The Mineral Aerosol Profiling from Infrared Radiances (MAPIR) algorithm retrieves vertical dust concentration profiles from cloud-free Infrared Atmospheric Sounding Interferometer (IASI) thermal infrared (TIR) radiances using Rodgers' optimal estimation method (OEM). We describe the new version 4.1 and evaluation results. Main differences with respect to previous versions are the Levenberg–Marquardt modification of the OEM, the use of the logarithm of the concentration in the retrieval and the use of Radiative Transfer for TOVS (RTTOV) for in-line radiative transfer calculations. The dust aerosol concentrations are retrieved in seven 1 km thick layers centered at 0.5 to 6.5 km. A global data set of the daily dust distribution was generated with MAPIR v4.1 covering September 2007 to June 2018, with further extensions planned every 6 months. The post-retrieval quality filters reject about 16 % of the retrievals, a huge improvement with respect to the previous versions in which up to 40 % of the retrievals were of bad quality. The median difference between the observed and fitted spectra of the good-quality retrievals is 0.32 K, with lower values over oceans. The information content of the retrieved profiles shows a dependence on the total aerosol load due to the assumption of a lognormal state vector. The median degrees of freedom in dusty scenes (min 10 µm AOD of 0.5) is 1.4. An evaluation of the aerosol optical depth (AOD) obtained from the integrated MAPIR v4.1 profiles was performed against 72 AErosol RObotic NETwork (AERONET) stations. The MAPIR AOD correlates well with the ground-based data, with a mean correlation coefficient of 0.66 and values as high as 0.88. Overall, there is a mean AOD (550 nm) positive bias of only 0.04 with respect to AERONET, which is an extremely good result. The previous versions of MAPIR were known to largely overestimate AOD (about 0.28 for v3). A second evaluation exercise was performed comparing the mean aerosol layer altitude from MAPIR with the mean dust altitude from Cloud–Aerosol LIdar with Orthogonal Polarization (CALIOP). A small underestimation was found, with a mean difference of about 350 m (standard deviation of about 1 km) with respect to the CALIOP cumulative extinction altitude, which is again considered very good as the vertical resolution of MAPIR is 1 km. In the comparisons against AERONET and CALIOP, a dependence of MAPIR on the quality of the temperature profiles used in the retrieval is observed. Finally, a qualitative comparison of dust aerosol concentration profiles was done against lidar measurements from two ground-based stations (M'Bour and Al Dhaid) and from the Cloud–Aerosol Transport System (CATS) instrument on board the International Space Station (ISS). MAPIR v4.1 showed the ability to detect dust plumes at the same time and with a similar extent as the lidar instruments. This new MAPIR version shows a great improvement of the accuracy of the aerosol profile retrievals with respect to previous versions, especially so for the integrated AOD. It now offers a unique 3-D dust data set, which can be used to gain more insight into the transport and emission processes of mineral dust aerosols.

N2O is the third anthropogenic greenhouse gas, after CO2 and CH4. N2O is about a 1000 times less abundant than CO2, but is a much stronger greenhouse gas (265 times stronger, for the same amount of gas). N2O has an atmospheric lifetime of about 120 years, and resides mostly in the troposphere and lower stratosphere. N2O is also the principal source of nitrogen in the stratosphere, participating in the ozone destruction.Although N2O emissions are mostly natural as a part of biogeochemical cycles, a significant part of the emissions is anthropogenic, linked to agriculture, industry and transport. The N2O concentrations are continuously increasing since the industrial era. Because its greenhouse potential is very high, identifying and regulating the anthropogenic N2O emissions is crucial for climate change mitigation.The Infrared Atmospheric Sounding Interferometer (IASI) is a nadir viewing satellite instrument, measuring the outgoing radiation in the Infrared range. It flies on board the Metop satellite series, on a polar sun-synchronous orbit, and has been providing data since 2006 with a succession of 3 instruments. The follow-up instrument, IASI-NG (new generation), is already in preparation and will not only ensure data continuity for at least an additional decade, but it will also provide improved performances.In this work, we present N2O profiles with a limited resolution of maximum 2 degrees of freedom, and the corresponding integrated columns, retrieved from IASI measurements using a new retrieval strategy. We assess the quality of our data through comparisons with Network for the Detection of Atmospheric Composition Change (NDACC) and Total Carbon Column Observing Network (TCCON) measurements. We will discuss the main “trouble makers” in this retrieval, i.e. the non-retrieved parameters that have the highest impact on the resulting N2O data quality. Finally, we will discuss a preliminary trend assessment derived from the retrieved time series covering 13-years.

In the frame of the scientific preparation of ExoMars Trace Gas Orbiter (EMTGO), synergistic retrievals were performed on synthetic spectra of two different remote sensing instruments of the Martian atmosphere. To benefit from their diversity, we have simulated spectra of a Fourier transform spectrometer (FTS), working in the middle to far infrared and of a grating spectrometer (GA) working in the middle infrared. As control runs, non-synergistic retrievals were performed as well. Two molecules of interest in the Martian atmosphere were chosen to test this method: carbon monoxide and methane. Scenarios were selected and two different vibrational bands for each molecule were used to retrieve molecular volume mixing ratios. Synergistic retrievals for CO are useful both in solar occultation and in nadir, while for CH4, the concentration of which is expected to be very low, the results for FTS and GA in synergy are not as conclusive due to the weak signal in the ν4 vibrational band (covered by FTS) compared to the stronger ν3 band (covered by GA). Our results represent a first step to an optimized use of infrared spectra to be recorded in Martian orbit by two instruments of EMTGO.

The Mineral Aerosol Profiling from Infrared Radiances (MAPIR) algorithm retrieves vertical dust concentration profiles from cloud-free IASI thermal infrared (TIR) radiances using the Rodgers Optimal Estimation Method (OEM). We describe the new version 4.1 and validation results. Main differences with respect to previous versions are the Levenberg-Marquardt modification of the OEM, the use of the logarithm of the concentration in the retrieval and the use of RTTOV for in-line radiative transfer calculations. The dust aerosol concentrations are retrieved in seven 1 km thick layers centered at 0.5 to 6.5 km. A global data set of the daily dust distribution was generated with MAPIR v4.1 covering September 2007 to June 2018, with further extensions planned every six months. The post-retrieval quality filters reject about 16 % of the retrievals, a huge improvement with respect to the previous versions where up to 40 % of the retrievals were of bad quality. The median difference between the observed and fitted spectra of the good quality retrievals is 0.32 K, with lower values over oceans. The information content of the retrieved profiles shows dependency on the total aerosol load due to the assumption of a log-normal state vector. The median degrees of freedom in dusty scenes (min 10 µm AOD of 0.5) is 1.4. A validation of the aerosol optical depth (AOD) obtained from the integrated MAPIR v4.1 profiles was performed against 72 AERONET stations. The MAPIR AOD correlates well with the ground-based data with a mean correlation coefficient of 0.66 and values as high as 0.88. Overall, there is a mean AOD (500 nm) negative bias of only 0.04 with respect to AERONET, which is an extremely good result. The previous versions of MAPIR were known to largely overestimate AOD (about 0.28 for v3). A second validation exercise was performed comparing the mean aerosol layer altitude from MAPIR with the mean dust altitude from CALIOP. A small underestimation was found, with a mean difference of about 350 m (standard deviation of about 1 km) with respect to the CALIOP cumulative extinction altitude, which is again considered very good as the vertical resolution of MAPIR is 1 km. In the comparisons against AERONET and CALIOP, a dependency of MAPIR on the quality of the temperature profiles used in the retrieval is observed. Finally, a qualitative comparison of dust aerosol concentration profiles was done against lidar measurements from two ground-based stations (M'Bour and Al Dhaid) and from the CATS instrument onboard the ISS. MAPIR v4.1 showed the ability to detect dust plumes at the same time and with a similar extent as the lidar instruments. This new MAPIR version shows a great improvement of the accuracy of the aerosol profile retrievals with respect to previous versions, especially so for the integrated AOD. It now offers a unique 3-D dust data set, which can be used to gain more insight in the transport and emission processes of mineral dust aerosols.

The lack of aerosol information over the cryosphere introduces large uncertainties to our understanding of phenomenon, known as the Arctic Amplification (AA) and its feedback mechanisms. The aerosol optical depth (AOD) describes the optical characteristics of aerosol loading. This paper describes a novel algorithm, which retrieves AOD above snow-covered regions from the measurements of the up-welling radiation at the top of atmosphere, observed by the Advanced Along-Track Scanning Radiometer (AATSR) and the Sea and Land Surface Temperature Radiometer (SLSTR) instruments. The algorithm optimizes the generic eXtensible Bremen Aerosol/cloud and surfacE parameters Retrieval (XBAER) approach for longer wavelengths over the cryosphere. The algorithm utilizes the characteristics of solar bidirectional distribution properties of snow and aerosol at wavelength 3.7 μm to derive above-snow-AOD. Since the impact of fine-mode aerosol on 3.7 μm is ignorable, the retrieved AOD in this manuscript represents mainly coarse-mode dominated part. A novel method to extract the solar reflection part at 3.7 μm is presented and used in the surface parameterization. Two aerosol types (sea saltdominated and dust-dominated) are used and the best-fit type is derived by an iterative procedure, using a LookUp-Table (LUT) approach. Sensitivity studies of the impact on the retrieved AOD using XBAER algorithm, which investigate the impacts of aerosol type, snow surface emissivity and potential cloud contamination under typical AATSR observation conditions, are presented. The sensitivity studies show that the surface parametrization and aerosol typing are suitable for the retrieval of above-snow-AOD over the Arctic snow-covered region. AOD observations retrieved in this study from AATSR (2002–2012) observation collocated with those from the Aerosol Robotic Network (AERONET) sites over Greenland show good agreement. 72.1% of the match-ups fall into the expected error envelope of ( ± 0.15AOD ± 0.025). The AATSR derived above-snow-AOD at 0.55 μm research product has also been compared with Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO) aerosol product, the Mineral Aerosols Profiling from Infrared Radiances (MAPIR) derived Infrared Atmospheric Sounding Interferometer (IASI) AOD research product, and the Modern-Era Retrospective analysis for Research and Applications, Version 2 (MERRA-2) AOD simulations over Greenland on April 2011. The comparison reveals that all datasets show similar patterns for the AOD above Greenland. The AOD is smaller in central Greenland and larger over the coastline regions. The XBAER derived above-snow-AOD has improved coverage, as compared to that of the existing AATSR aerosol product. The transition between above-snow-AOD and AOD derived over surrounding ocean surfaces does not indicate any systematic errors. Two aerosol transport events have been well-captured by the XBAER derived above-snow-AOD research product. The new algorithm is also applied to the SLSTR onboard Sentinel-3 demonstrating new SLSTR above-snow-AOD data products, and its value for research in the changing AOD during the period of Arctic Amplification.

Aerosol-layer height is essential for understanding the impact of aerosols on the climate system. As part of the European Space Agency Aerosol_cci project, aerosol-layer height as derived from passive thermal and solar satellite sensors measurements have been compared with aerosol-layer heights estimated from CALIOP measurements. The Aerosol_cci project targeted dust-type aerosol for this study. This ensures relatively unambiguous aerosol identification by the CALIOP processing chain. Dust-layer height was estimated from thermal IASI measurements using four different algorithms (from BIRA-IASB, DLR, LMD, LISA) and from solar GOME-2 (KNMI) and SCIAMACHY (IUP) measurements. Due to differences in overpass time of the various satellites, a trajectory model was used to move the CALIOP-derived dust heights in space and time to the IASI, GOME-2 and SCIAMACHY dust height pixels. It is not possible to construct a unique dust-layer height from the CALIOP data. Thus two CALIOP-derived layer heights were used: the cumulative extinction height defined as the height where the CALIOP extinction column is half of the total extinction column, and the geometric mean height, which is defined as the geometrical mean of the top and bottom heights of the dust layer. In statistical average over all IASI data there is a general tendency to a positive bias of 0.5–0.8 km against CALIOP extinction-weighted height for three of the four algorithms assessed, while the fourth algorithm has almost no bias. When comparing geometric mean height there is a shift of −0.5 km for all algorithms (getting close to zero for the three algorithms and turning negative for the fourth). The standard deviation of all algorithms is quite similar and ranges between 1.0 and 1.3 km. When looking at different conditions (day, night, land, ocean), there is more detail in variabilities (e.g. all algorithms overestimate more at night than during the day). For the solar sensors it is found that on average SCIAMACHY data are lower by −1.097 km (−0.961 km) compared to the CALIOP geometric mean (cumulative extinction) height, and GOME-2 data are lower by −1.393 km (−0.818 km).

Desert dust aerosols are the most prominent tropospheric aerosols, playing an important role in the earth's climate. However, their radiative forcing is currently not known with sufficient precision to even determine its sign. The sources of uncertainty are multiple, one of them being a poor characterisation of the dust aerosol's vertical profile on a global scale. In this work, we tackle this scientific issue by designing a method for retrieving dust aerosol vertical profiles from Thermal Infrared measurements by Infrared Atmospheric Sounding Interferometer (IASI) instruments onboard the Metop satellite series. IASI offers almost global coverage twice a day, and long (past and future) time series of radiances, therefore being extremely well suited for climate studies. Our retrieval follows Rodger's formalism and is based on a two-step approach, treating separately the issues of low altitude sensitivity and difficult a priori definition. We compare our results for a selected test case above the Atlantic Ocean and North Africa in June 2009, with optical depth data from MODIS, aerosol absorbing index from GOME-2 and OMI, and vertical profiles of extinction coefficients from CALIOP. We also use literature information on desert dust sources to interpret our results above land. Our retrievals provide perfectly reasonable results in terms of optical depth. The retrieved vertical profiles (with on average 1.5 degrees of freedom) show most of the time sensitivity down to the lowest layer, and agree well with CALIOP extinction profiles for medium to high dust optical depth. We conclude that this new method is extremely promising for improving the scientific knowledge about the 3-D distribution of desert dust aerosols in the atmosphere.

Volcanic ash is emitted by most eruptions, sometimes reaching the stratosphere. In addition to its climate effect, ash may have a significant impact on civilian flights. Currently, the horizontal distribution of ash aerosols is quite extensively studied, but not its vertical profile, while of high importance for both applications mentioned. Here, we study the sensitivity of the thermal infrared spectral range to the altitude distribution of volcanic ash, based on similar work that was undertaken on mineral dust. We use measurements by the Infrared Atmospheric Sounding Interferometer (IASI) instruments onboard the MetOp satellite series. The retrieval method that we develop for the ash vertical profile is based on the optimal estimation formalism. This method is applied to study the eruption of the Chilean volcano Puyehue, which started on the 4th of June 2011. The retrieved profiles agree reasonably well with Cloud-Aerosol LiDAR with Orthogonal Polarization (CALIOP) measurements, and our results generally agree with literature studies of the same eruption. The retrieval strategy presented here therefore is very promising for improving our knowledge of the vertical distribution of volcanic ash and obtaining a global 3D ash distribution twice a day. Future improvements of our retrieval strategy are also discussed.

Producing a global and comprehensive description of atmospheric aerosols requires integration of ground-based, airborne, satellite and model datasets. Due to its complexity, aerosol monitoring requires the use of several data records with complementary information content. This paper describes the lessons learned while developing and qualifying algorithms to generate aerosol Climate Data Records (CDR) within the European Space Agency (ESA) Aerosol_cci project. An iterative algorithm development and evaluation cycle involving core users is applied. It begins with the application-specific refinement of user requirements, leading to algorithm development, dataset processing and independent validation followed by user evaluation. This cycle is demonstrated for a CDR of total Aerosol Optical Depth (AOD) from two subsequent dual-view radiometers. Specific aspects of its applicability to other aerosol algorithms are illustrated with four complementary aerosol datasets. An important element in the development of aerosol CDRs is the inclusion of several algorithms evaluating the same data to benefit from various solutions to the ill-determined retrieval problem. The iterative approach has produced a 17-year AOD CDR, a 10-year stratospheric extinction profile CDR and a 35-year Absorbing Aerosol Index record. Further evolution cycles have been initiated for complementary datasets to provide insight into aerosol properties (i.e. dust aerosol, aerosol absorption)., SCOPUS: ar.j, info:eu-repo/semantics/published

Recent MS studies have suggested that serine clusters could have played a role in the origin of homochirality on Earth. Aqueous serine solutions have been probed in order to see if serine clusters, such as those observed by MS, are present in solution. IR measurements as well as NMR chemical shift and diffusion coefficient measurements, as a function of pH and serine concentration, suggest that these clusters do not exist in solution. (© Wiley-VCH Verlag GmbH & Co. KGaA, 69451 Weinheim, Germany, 2006)

Observation and tracking of volcanic aerosols are important for preventing possible aviation hazards and determining the influence of aerosols on climate. The useful information primary includes the concentration, particle size and altitude of aerosol load. Moreover, volcanic eruptions are usually accompanied by strong emissions of SO2 and enhanced concentrations of H2O in the atmosphere. Volcanic ash particles can also catalyze the formation of ice clouds by serving as cloud nuclei. Hyperspectral infrared sounders, such as IASI (Infrared Atmospheric Sounding Interferometer), have proven to be powerful tools for capturing volcanic aerosol and ice cloud signatures and enhanced volcanic gas concentrations. Information on atmospheric constituents is extracted from such hyperspectral measurements with the help of radiative transfer (RT) codes capable of solving both direct and inverse RT problems. We will demonstrate the retrieval of aerosol and ice cloud physical properties together with gas concentration from IASI measurements with the help of the AVL RT model. AVL is one of the 'code combination packages' which are becoming more and more popular in the scientific domain. It consists of several codes, each of which handles a specific set of physics-related tasks. The codes function smoothly as a whole due to the use of a special interface. AVL is perfectly suitable (i) to model the propagation of UV-visible-IR radiation through a coupled atmosphere-surface system for a wide range of atmospheric, spectral and geometrical conditions; and (ii) to retrieve vertical gas profiles and aerosol concentration through the use of its embedded retrieval algorithm on the basis of an optimal estimation method (OEM). The retrievals are performed for IASI measurements (radiance, Level 1C product) carried out over Eyjafjallajokull volcano, Iceland, in April 2010.

Improved observation operators for atmospheric remote sensing data - describing the geographical offset and spread of the retrieved information from an observation - are presented and applied on sample atmospheric fields to illustrate the impact of smoothing and sampling issues on data comparisons. The use of those operators to reduce biases and noise in comparisons is demonstrated in the context of ground-based satellite validation, and possible applications in chemical data assimilation are discussed.

Amino-acid enantiomeric excesses (ee's) have been detected in different types of carbonaceous chondrites, all in favor of the L enantiomer. In this article, we discuss possible deterministic causes to the presence of these amino-acid ee's in meteorites and evaluate in particular enantioselective photolysis by circularly polarized light (CPL). The electronic circular dichroism spectra of a set of amino- and hydroxy-acids, all detected in chondritic matter but some with ee's and others without ee's, were calculated and compared. The spectra were calculated for the most stable conformation(s) of the considered molecules using quantum mechanical methods (density functional theory). Our results suggest that CPL photolysis in the gas phase was perhaps not at the origin of the presence of ee's in meteorites and that the search for another, but still unknown, deterministic cause must be seriously undertaken., SCOPUS: ar.j, FLWIN, info:eu-repo/semantics/published

9 páginas, 5 figuras, 2 tablas -- PAGS nros. 7570-7578, The interactions of simple carbohydrates with aromatic moieties have been investigated experimentally by NMR spectroscopy. The analysis of the changes in the chemical shifts of the sugar proton signals induced upon addition of aromatic entities has been interpreted in terms of interaction geometries. Phenol and aromatic amino acids (phenylalanine, tyrosine, tryptophan) have been used. The observed sugar-aromatic interactions depend on the chemical nature of the sugar, and thus on the stereochemistries of the different carbon atoms, and also on the solvent. A preliminary study of the solvation state of a model monosaccharide (methyl beta-galactopyranoside) in aqueous solution, both alone and in the presence of benzene and phenol, has also been carried out by monitoring of intermolecular homonuclear solvent-sugar and aromatic-sugar NOEs. These experimental results have been compared with those obtained by density functional theory methods and molecular mechanics calculations, The group in Madrid thanks the Ministry of Education and Science of Madrid for funding (Grant CTQ2006-10874-C02-01) and the CESGA for computing time. The group in Brussels thanks the “Communauté française de Belgique” for funding (ARC2002-7). D.D. thanks the Ramón y Cajal programme for her contract. S.V.D.B. thanks the Belgian FNRS for a PhD fellowship. J.J.B. and S.P.V. thank the European Commission through the MRTN-CT2005-019561 DYNAMIC project