The role of meteorological inputs in estimating dispersion from surface releases

Abstract

Abstract Currently used models for dispersion in the surface layer are explicitly based on Monin–Obukhov (M–O) theory. Because M–O variables such as the surface friction velocity and M–O length are not always accessible or M–O similarity might not hold at the site of interest, there is a need for a model that uses alternative meteorological inputs. Here, we examine the use of near-surface profiles of turbulence and wind speeds instead of M–O variables. We use data from the Prairie Grass experiment (1958, Project Prairie Grass, a field program in diffusion, Vol. 1, Geophysics Research Paper No. 59. Air Force Cambridge Research Center, Bedford, MA) because of its completeness in terms of meteorological inputs as well as spatial coverage of concentration measurements. The maximum surface concentrations and the crosswind plume spreads are first explained using an M–O theory-based model proposed by van Ulden (1978, Simple estimates for vertical dispersion from sources near the ground. Atmospheric Environment 12, 2125–2129), whose performance has already been documented in the literature. The performance of this model is compared with those of models using alternative meteorological inputs. The results from the study indicate that, under stable conditions, models that use profiles of winds and turbulence do not perform as well as van Ulden's model. On the other hand, under unstable conditions, the differences in model performance are much smaller. This supports other studies that indicate that relatively simple dispersion models can be used to estimate concentrations in urban areas, where the boundary layer is often unstable even during the night.