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As the U.S. and the International Community come to grips with anthropogenic climate change, it will be necessary to develop accurate techniques with global span for remote measurement of emissions and uptake of greenhouse gases (GHGs), with special emphasis on carbon dioxide. Presently, techniques exist for in situ and local remote measurements. The first steps towards expansion of these techniques to span the world are only now being taken with the launch of satellites with the capability to accurately measure column abundances of selected GHGs, including carbon dioxide. These satellite sensors do not directly measure emissions and uptake. The satellite data, appropriately filtered and processed, provide only one necessary, but not sufficient, input for the determination of emission and uptake rates. Optimal filtering and processing is a challenge in itself. But these data must be further combined with output from data-assimilation models of atmospheric structure and flows in order to infer emission and uptake rates for relevant points and regions. In addition, it is likely that substantially more accurate determinations would be possible given the addition of data from a sparse network of in situ and/or upward-looking remote GHG sensors. We will present the most promising approaches we've found for combining satellite, in situ, fixed remote sensing, and other potentially available data with atmospheric data-assimilation and backward-dispersion models for the purpose of determination of point and regional GHG emission and uptake rates. We anticipate that the first application of these techniques will be to GHG management for the U.S. Subsequent application may be to confirmation of compliance of other nations with future international GHG agreements.