To better understand complex processes between the land and the atmosphere and to more accurately quantify surface sources and sinks of Greenhouse Gases (GHG) at smaller scales, an increased density of continuous in situ measurements is needed. During the next five years, Earth Networks will deploy a network of GHG measuring instruments installed at tall towers with collocated weather stations. A typical design has a sensor taking continuous observations of atmospheric carbon dioxide and methane mixing ratios at multiple heights, as well as a calibration unit to ensure that data meets international GHG monitoring standards. To relate changes in GHG concentrations observed at the towers, to varying-with-time sources and sinks of carbon at the surface, inversions are used. These inversions are based on trajectories simulated by atmospheric transport models. We discuss a setup, where the atmospheric trajectories and surface footprints are computed using the STILT (Stochastic Time-Inverted Lagrangian Transport) model coupled to the WRF (Weather Research and Forecasting) model providing transport fields at refined spatial and temporal resolution. Transport errors and particle dispersion parameters in this inversion setup are based on differences between simulated and observed winds. Observations at high temporal resolution are available from more than 8,000 professional grade surface weather stations operated by Earth Networks, in addition to data from NOAA (National Oceanic and Atmospheric Administration) sites. In this study we use dispersion parameters varying both spatially and in time and compare footprints with different averaging time intervals. Potential advantages of using shorter averaging intervals are discussed. http://ghg.earthnetworks.com/