In this paper, a computational fluid dynamics (CFD) model is developed to simulate the methane (CH4) dispersion of exhaust gases from the Munich Oktoberfest, the world’s largest folk festival. Since we assume CH4 losses during the natural gas driven heating and cooking process, our aim is to provide a methodology for estimating these emissions. We developed a forward CFD dispersion model and combined it with on-the-site backpack measurements to quantify the emissions at the festival. The emission number is determined by scaling the simulated to the measured concentrations. Our sensitivity study reveals that the turbulent Schmidt number and the measured wind speed have high impacts on the emission results. Further, we investigated the effect of buoyancy, since there is a temperature gradient between the exhaust gases and the environment. Our results show that the buoyancy is an important factor for assessing hot emissions. Finally, we compared our findings to results determined by a Gaussian plume model and discussed advantages and disadvantages of each approach. Our findings show that CFD models can reproduce real dispersion processes in very complex environments with a high spatial resolution and are able to predict emissions. This study offers a completely new methodology to quantify local emissions on a real scale array and presents one of the first attempts to use CFD to study superimposed greenhouse gas sources.     «

In this paper, a computational fluid dynamics (CFD) model is developed to simulate the methane (CH4) dispersion of exhaust gases from the Munich Oktoberfest, the world’s largest folk festival. Since we assume CH4 losses during the natural gas driven heating and cooking process, our aim is to provide a methodology for estimating these emissions. We developed a forward CFD dispersion model and combined it with on-the-site backpack measurements to quantify the emissions at the festival. The emissio...     »