English (United Kingdom)

https://curated-unify.zendy.io/wp-json/zendy-region/v1/featured_content/oa?rat=en

https://curated-unify.zendy.io/wp-json/zendy-region/v1/highlighted_journal/

Global: Zendy Plus annual

Presents the access of premium content as premium feature

Premium Content

Presents the keyphrase highlighting as premium feature

Keyphrase Highlighting

Presents the summarisation as premium feature

Summarisation

Insights

Presents the pdf analysis as premium feature

PDF Analysis

Presents the zaia usage as premium feature

ZAIA

Global: Zendy Plus monthly

Global: Zendy Tools annual

Global: Zendy Tools monthly

Global: Zendy Free Plan

A single particle Lagrangian Stochastic model has been developed and applied with the purpose of simulating the concentration fluctuations dispersion. This model treats concentration variance as a quantity whose motion is driven by an advection-diffusion process so that it can be studied by a single particle model. A parameterization for both velocity standard deviations and Lagrangian time-scales is required as input to the model. The paper is focused on the estimation of the best parameterization needed to simulate both mean and standard deviation concentrations in a case study. We consider the FFT-07 field experiment. The trials took place at Dugway Proving Ground, UTAH (USA) and consist of a dispersion analysis of a gas emitted from a point-like source in different atmospheric conditions with a continuous emission technique. The very small spatial scales (a few hundred meters) and short duration (about 10 minutes) that characterize the trials make the comparison with model results very challenging, since traditional boundary layer parameterizations fail in correctly reproducing the turbulent field and, as a consequence, the dispersion simulation yields unsatisfactorily results. We vary the coefficients of the turbulence parameterization to match the small-scale turbulence. Furthermore, we show that the parameterization for the variance dissipation time-scale, already tested in neutral conditions, can be used also in stable and unstable conditions and in low-wind speed conditions. The model gives good results as far as mean concentration is concerned and rather satisfactory results for the concentration standard deviations. Comparison between model results and observation is shown through both statistical and graphical analyses.

Concentration Fluctuations of Single Particle Stochastic Lagrangian Model Assessment with Experimental Field Data