Mt. Cimone Observatory is a background station for the measurement of greenhouse gases and other atmospheric pollutants located on the top of the highest peak of the Italian Northern Appenines. Continuous Measurements of atmospheric CO₂ were started in March 1979 by the Italian Air Force Meteorological Service using NDIR analysers. A number of case studies are presented in order to show the influence of certain polluted or vegetated areas on the concentration of carbon dioxide. Chemical tracers are used to asses the origin of the air masses together with an analysis of the back trajectories.

Atmospheric Observing Systems, Inc. has developed a new Airborne Analyzer System for autonomous observations of dry mole fraction of Carbon Dioxide from light aircraft. AOS presents an archive of more than 100 vertical profiles to prove its performance. The observed site was Ameriflux (40.734N, 104.301W) in northern Colorado.

We have carried out the tank experiment in the low-temperature room to clarify the CO₂ gas exchange mechanism between the sea and the overlying air during the sea-ice formation process. The air CO₂ concentration in the headspace of the tank began to increase simultaneously with the sea-ice formation and growth. The CO₂ flux was with in the range from 2.1x10^-4 to 4.5x10^-4 g-C m^-2 hour^-1 at ice thickness of 5cm. The CO₂ flux was mainly dependent on the brine salinity in the upper layer of sea-ice, which suggests that CO₂ was released from the brine in the sea-ice, and transported to the atmosphere.

We evaluate the impact on modeled atmospheric CO₂ concentrations of explicitly representing the tropospheric CO₂ source from reduced carbon oxidation. We also calculate the bias in inverse flux estimates that results from omitting this influence.

Transport-based inversions of atmospheric CO₂ concentration measurements have been used by several groups [e.g., Bousquet, et al., 2000; Rödenbeck, et al., 2003; Baker, et al., 2005] to estimate monthly regional CO₂ fluxes from the 1980s to the present. When compared at the scale of broad latitude bands, the inter-annual variability (IAV) of these results is broadly consistent. This agreement breaks down, however, when the fluxes are partitioned regionally inside these latitude bands, or even into global land/ocean totals. We show here that this disagreement can largely be explained by random estimation errors and transport model errors affecting the estimates.

Physical processes in the Southern Ocean are known to profoundly impact the global carbon cycle, but this region is one of the most difficult to simulate consistently in ocean general circulation models (OGCMs). Here we show that Southern Hemisphere winds, by altering the volume of light, actively-ventilated ocean water as well as the relative contribution to this volume from Ekman transport, exert strong control over both the magnitude and distribution of anthropogenic carbon uptake in an OGCM. These results are provocative in suggesting that climate warming, by increasing the magnitude of the wind stress at high southern latitudes, may act as a negative feedback on the global carbon cycle.

With the increasing temporal and spatial density of CO₂ flux and concentration observations from worldwide tower networks, the importance of interpreting the data is becoming more conspicuous. Previous work shows that tower observations might be able to catch synoptic, regional, and local signals of CO₂ simultaneously. Thus a study that can explain CO₂ transport and the response of the ecosystem to the weather change simultaneously is necessary and will help the development of the regional inverse modeling technique in the future.

We present an analysis of terrestrial net CO₂ fluxes from North America for the period 2000-2004. These fluxes consist of hourly maps at ~70km×100km resolution that are consistent with observed atmospheric CO₂ mixing ratios, as well as with varying climatic conditions across different ecosystems as observed from space. The flux maps are created in a newly developed ensemble data assimilation system that consists of the atmospheric Transport Model v5 (TM5), the Vegetation Photosynthesis Respiration Model (VPRM), and an efficient Bayesian least-squares algorithm to optimize the fluxes from different biomes in VPRM against CO₂ mixing ratios from the NOAA-CMDL observing network. The stochastic nature of the ensemble data assimilation system allows us to consistently include uncertainty on net CO₂ fluxes from the neighboring oceans and more distant continents in the flux estimates for North America.