The global biogeochemical cycle of oxygen is closely linked to that of carbon dioxide, because key biological processes, as well as fossil fuel burning, occur with specific stochiometric ratios. In the ocean, however, several processes – carbonate chemistry (buffer effect), physical transport (dilution), and warming/cooling (solubility changes) – decouple O₂ and CO₂ exchanges. Based on a decade of atmospheric O₂/N₂ and CO₂ data, we estimated spatial and temporal patterns of oceanic APO fluxes, using an inversion of atmospheric transport. Seasonal and interannual variations are interpreted in the light of climate variables.

Atmospheric CO₂ concentrations have been obtained from the Atmospheric Infrared Sounder (AIRS) radiance data within the European Centre for Medium-Range Weather Forecasts (ECMWF) data assimilation system. In a first explorative configuration, a subset of channels from the AIRS instrument has been assimilated providing estimates of tropospheric column-averaged CO₂ mixing ratios representative of a layer between the tropopause and about 700 hPa at observation locations only. Results show considerable geographical and temporal variability with values ranging between 370 and 382 ppmv. The 5-day mean estimated random error is about 1%, which is confirmed by comparisons with flask observations on board flights of Japanese airliners in the west-Pacific region. This study demonstrates the feasibility of global CO₂ estimation using high spectral resolution infrared satellite data in a numerical weather prediction data assimilation system. Currently, the system is being improved to treat CO₂ as a full three-dimensional atmospheric variable included in the forecast model. This allows more flexibility in the constraints on the CO₂ estimation as well as the possibility of assimilating other data sources (e.g., near-infrared satellite data and flasks). The CO₂ fields provided by the data assimilation system have great potential to assist the surface flask network in constraining current top-down carbon flux estimates.

The WLEF TV tower in northern Wisconsin is instrumented to take continuous measurements of CO₂ mixing ratio at 6 levels from 11 to 396m. During the spring and summer of 2004 additional CO₂ measurements were deployed on five 76 m communication towers forming a ring around the WLEF tower with a 100-150 km radius.

Simulations with a regional transport model are evaluated in order to determine to which extend the indirect fossil fuel combustion tracer CO or the purely anthropogenic tracer SF₆ can be used to retrieve the contribution of fossil fuel emissions in the atmospheric CO₂ signal.

Three years of quasi-continuous atmospheric ¹⁴CO₂ observations in Heidelberg (Germany) have been used together with continuous CO measurements to determine the CO/fossil fuel CO₂ ratio in a regional polluted area. Comparison with bottom-up information on fossil fuel CO₂ and CO emissions for the respective catchment area shows that large discrepancies (up to 60%) between inventory data and observations exist. Therefore both, a lot of care and reliable emissions inventory data are necessary if CO shall be used as a quantitative surrogate for fossil fuel CO₂.

The Dole-Morita effect (DME) describes the d¹⁸O enrichment of atmospheric O₂ with respect to ocean water [Dole 1935, Morita 1935]. The magnitude of the DME (23.8 ± 0.1‰ at present, Horibe et al. [1973]) varies over geologic time scales, and might have changed as a result of human activity. Such variations are preserved in the air enclosed in polar firn and ice. Here, we explore the potential effects of human activity on the DME. We estimate that global changes in the land biosphere may have led to a decrease in the DME in the order of 0.07‰ over the last 150 years. We then predict profiles of d¹⁸O-O₂ in firn air resulting from a range of atmospheric scenarios using a model [Severinghaus and Battle, submitted] and compare the simulated profiles to measurements of air samples extracted from polar firn.

We report on the set-up of and first experiences with a medium-precision CO₂ concentration monitoring network in Europe, linked to existing flux towers. The system is to be embedded in an integral GHG monitoring system to be developed for the Netherlands and into the CABOEUROPE effort to quantify the European carbon balance. The proof of concept has not been fully satisfactory as yet, but work continues.

CHIOTTO – Continuous HIgh-precisiOn Tall Tower Observations of greenhouse gases – is a European Union-funded project which has as objective to build an infrastructure for the continuous monitoring of greenhouse gas concentrations across Europe above the surface layer using tall towers (~300m height). For this purpose a new analysis system for continuous atmospheric measurements was built and tested at Max Planck Institute for Biogeochemistry, Jena, Germany and was recently installed at a 300 m tower close to Bialystok, Poland (Lat 53°14'N, Long 23°01'E, Alt 180m), as part of the “CHIOTTO” tall tower network. Since July 2005 this system is measuring quasi-continuously the atmospheric concentration of CO₂, CH₄, CO, N₂O, SF₆ and the O₂/N₂ ratio as well as meteorological parameters (atmospheric pressure, temperature, humidity; wind speed and direction) from 5 heights on the tower ranging from 5 to 300 m. The measurement devices are: an Oxzilla O₂ fuel cell analyzer, a LiCor 7000 NDIR CO₂ analyzer, an Agilent gas chromatograph (GC) with flame ionization detector (FID) and electronic capture detector (ECD) for CH₄, CO, N₂O, SF₆. The challenge was to build a reliable automatic system which can run continuously with very little maintenance and to fulfill at the same time the high precision requirements for all the measured species prescribed by the CHIOTTO project goals. The high temporal resolution achieved will capture short term events and diurnal variability. In addition, the system is planned to run for at least several years in order to observe long-term trends as well. We describe the technical setup of the measurement system, the region of influence of the station and present the first months of data if available: correlations between species, observed short term variability patterns and their relation to meteorology and air parcel paths.