Evaluation of two common source estimation measurement strategies using large-eddy simulation of plume dispersion under neutral atmospheric conditions

Abstract

Abstract. This study uses large-eddy simulations (LESs) to evaluate two widely used observational techniques that estimate point source emissions. We evaluate the use of car measurements perpendicular to the wind direction and the commonly used Other Test Method 33A (OTM 33A). The LES study simulates a plume from a point source released into a stationary, homogeneous, and neutral atmospheric surface layer over flat terrain. This choice is motivated by our ambition to validate the observational methods under controlled conditions where they are expected to perform well since the sources of uncertainties are minimized. Three plumes with different release heights were sampled in a manner that mimics sampling according to car transects and the stationary OTM 33A. Subsequently, source strength estimates are compared to the true source strength used in the simulation. Standard deviations of the estimated source strengths decay proportionally to the inverse of the square root of the number of averaged transects, showing statistical independence of individual samples. The analysis shows that for the car transect measurements at least 15 repeated measurement series need to be averaged to obtain a source strength within 40 % of the true source strength. For the OTM 33A analysis, which recommends measurements within 200 m of the source, the estimates of source strengths have similar values close to the source, which is caused by insufficient dispersion of the plume by turbulent mixing close to the source. Additionally, the derived source strength is substantially overestimated with OTM 33A. This overestimation is driven by the proposed OTM 33A dispersion coefficients, which are too large for this specific case. This suggests that the conditions under which the OTM 33A dispersion constants were derived were likely influenced by motions with length scales beyond the scale of the surface layer. Lastly, our simulations indicate that, due to wind-shear effects, the position of the time-averaged centerline of the plumes may differ from the plume emission height. This mismatch can be an additional source of error if a Gaussian plume model (GPM) is used to interpret the measurement. In the case of the car transect measurements, a correct source estimate then requires an adjustment of the source height in the GPM.