A stochastic time series model for threshold crossing statistics of concentration fluctuations in non-intermittent plumes

A numerical stochastic model is developed for the upcrossing rate across a specified threshold concentration. The model assumes that the concentration time series at a given spatial point within a dispersing plume can be appr oximated as a first-order Markovian process designed to be consistent with a given time-invariant concentration probability density function (pdf). Th e model requires only the specification of a concentration pdf with a given mean and variance and a concentration fluctuation integral time scale. Pre dicted upcrossing rates are compared with atmospheric plume concentration d ata obtained from a point source near the ground. For this data set, a log- normal pdf is found to give better estimates of the threshold crossing rate than a gamma pdf.