We now compare the simulated concentrations from the Gaussian plume and Gaussian puff models. For the Gaussian plume, we divide each emission event into multiple nonoverlapping intervals, in which we assume the transport of methane reaches steady state and hence use of the Gaussian plume model is valid. Within each interval, we use the mean emission rate, mean wind speed, and circular mean of the wind direction as inputs to the model (see equation ( )). A 10-minute interval has been identified in prior research as a good choice, maintaining the validity of the steady state assumption and enhancing the accuracy of the simulation . In this comparative analysis, time intervals of 10 minutes were used to represent the optimal accuracy for Gaussian plume simulations. For the Gaussian puff model, we use the algorithm described in Section 4.1 and create a puff every 1 second. As an example to demonstrate the difference between these two models, Fig. shows the observations and simulation output from both the plume and puff models at the NW sensor from an emission event that occurred on 18 April 2022 between 12:47 and 15:17 LT with two emission sources: one at West Wellhead with emission rate 0.67 kg h -1 and another one at East Wellhead with emission rate 1.73 kg h -1 . As the Gaussian puff model is able to accommodate time varying wind conditions, it creates more detailed concentration predictions. The Gaussian plume model, on the other hand, is characterized by periods of constant concentration predictions corresponding to the 10-minute intervals over which the steady state assumption is made. The Gaussian puff simulation results are consistently closer to the observations in terms of amplitude compared to the Gaussian plume.