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pproximately half of human-induced carbon dioxide (CO) emissions are taken up by the land and ocean, and the rest stays in the atmosphere, increasing the global concentration and acting as a major greenhouse-gas (GHG) climate-forcing element. Although GHG mitigation is now in the political arena, the exact spatial distribution of the land sink is not well known. In this paper, an estimation of mean European net ecosystem exchange (NEE) carbon fluxes for the period 1998-2001 is performed with three mesoscale and two global transport models, based on the integration of atmospheric CO measurements into the same Bayesian synthesis inverse approach. A special focus is given to sub-continental regions of Europe making use of newly available CO concentration measurements in this region. Inverse flux estimates from the five transport models are compared with independent flux estimates from four ecosystem models. All inversions detect a strong annual carbon sink in the southwestern part of Europe and a source in the northeastern part. Such a dipole, although robust with respect to the network of stations used, remains uncertain and still to be confirmed with independent estimates. Comparison of the seasonal variations of the inversion-based net land biosphere fluxes (NEP) with the NEP predicted by the ecosystem models indicates a shift of the maximum uptake period, from June in the ecosystem models to July in the inversions. This study thus improves on the understanding of the carbon cycle at sub-continental scales over Europe, demonstrating that the methodology for understanding regional carbon cycle is advancing, which increases its relevance in terms of issues related to regional mitigation policies. [ABSTRACT FROM AUTHOR]

In this paper we consider the buying/selling prices of carbon dioxide (CO) emission permits in trading models with uncertainty. Permission prices, although usually omitted from standard models, may significantly influence the trading market. We thus undertook to construct a more realistic trade model and to compare it with the standard one. To do this, we introduced several important changes to the standard model, namely, (1) a new optimized quality function; and (2) transactions with price negotiations between regions. We also enhanced the model using methods described in the literature to allow it to deal with reported emissions uncertainty. Additionally, we used an original method of simulating this kind of market based on a specialized evolutionary algorithm (EA). [ABSTRACT FROM AUTHOR]

We provide a review description of atmospheric inversion methods for the determination of fluxes of long-lived trace gases based on measurements of atmospheric concentration. Emphasis is given to technical aspects of inversion settings, which are crucial to inter-compare and understand inversion results. We briefly sketch the formalism used in such methods, then provide a summary of major currents in research and contemporary problems. Most attention is given to carbon dioxide (CO) which poses the threat of future climate change. Therefore, there is keen interest in better understanding where and when CO emitted by the combustion of fossil fuels is reabsorbed by land ecosystems and oceans. Using the information contained in concentration fields observed from ground-based networks and from upcoming satellite observations in order to constrain the geographic distribution of surface fluxes is an inverse problem; it consists of finding a set of fluxes that optimally matches the observations available. We review the application of inverse methods to quantify the distribution of the sources and sinks of CO at the surface of the Earth based on global measurements of atmospheric concentration and three-dimensional models of atmospheric transport. We describe the use of top-down atmospheric inversion methods in terms of numerical transport modeling and atmospheric observation networks, and detail some of the currently important issues in assigning uncertainties. [ABSTRACT FROM AUTHOR]