The underlying objective of this thesis was to perform GHG simulation studies to predict the dispersion and transport of greenhouse gases emitted from a thermal power plant in order to assess the extent of dangerous living environment for those surrounding it in case of an unforeseen calamity. The research carried out during this thesis was to investigate the method of wind averaging techniques to analyse column measurements (XCO2). The reason for adopting this method of analysis was to correlate the physical aspect of wind data to average over a certain period of time wherein the amount of XCO2 (in ppm) observed displays values greater than the background concentration. CFD simulations were performed using the open source code, OpenFOAM, and steady RANS models modified with turbulence boundary conditions for the urban environment case with previously validated simulation studies carried out for the same region in Munich, Germany. Initial results performed during the testing stage indicated that maximum average XCO2 value (in ppm) was recorded at the lowest value of mean wind speed and at a more downwind location of the measurement site. The results obtained from simulation studies on comparison with experimental values (arithmetic average) also suggest that for the same time interval, the difference in values for similar wind conditions as mentioned before makes this technique a more favourable choice for comparison and verification at another time instant.  There have been recent developments in GHG simulation based studies and however the current method does represent certain drawbacks, an insight into performing averaging analysis at time intervals representing peak XCO2 moments could be demonstrated which can also help in reducing the overall number of simulations as well as provide information with respect to mitigation measures based on transport and diffusion behavior.