Assessing the Internal Variability of Large-Eddy Simulations for Microscale Pollutant Dispersion Prediction in an Idealized Urban Environment

Abstract

Abstract This study aims at estimating the inherent variability of microscale boundary-layer flows and its impact on the air pollutant dispersion in urban environment. For this purpose, we present a methodology combining a high-fidelity Large-Eddy Simulation (LES) model and a stationary bootstrap algorithm, to estimate the internal variability of time-averaged quantities over a given analysis period thanks to sub-averages samples. A detailed validation of a LES microscale air pollutant dispersion model in the framework of the Mock Urban Setting Test (MUST) field-scale experiment is performed. We show that the LES results are in overall good agreement with the experimental measurements of wind velocity and tracer concentration, especially in terms of fluctuations and peaks of concentrations. We also show that both LES estimates and the MUST experimental measurements are subject to a significant internal variability, which is therefore essential to take it into account in the model validation exercise. Moreover, we demonstrate that the LES model is able to accurately reproduce the observed internal variability. This study only accounts for the microscale wind fluctuations, and is therefore a first step in measuring the complete effect of the atmospheric boundary-layer (ABL) internal variability on pollutant dispersion.