Development and Evaluation of a Fluctuating Plume Model for Odor Impact Assessment

Abstract

For environmental odor nuisance, it is extremely important to identify the instantaneous concentration statistics. In this work, a Fluctuating Plume Model for different statistical moments is proposed. It provides data in terms of mean concentrations, variance, and intensity of concentration. The 90th percentile peak-to-mean factor, R90, was tested here by comparing it with the experimental results (Uttenweiler field experiment), considering different Probability Distribution Functions (PDFs): Gamma and the Modified Weibull. Seventy-two percent of the simulated mean concentration values fell within a factor 2 compared to the experimental ones: the model was judged acceptable. Both the modelled results for standard deviation, σC, and concentration intensity, Ic, overestimate the experimental data. This evidence can be due to the non-ideality of the measurement system. The propagation of those errors to the estimation of R90 is complex, but the ranges covered are quite repeatable: the obtained values are 1–3 for the Gamma, 1.5–4 for Modified Weibull PDF, and experimental ones from 1.4 to 3.6.

Assessment of environmental odor pollution using a dispersion model in an industrialized urban area of Kocaeli, Turkey

“…In studies evaluating the odor effect, it is necessary to calculate short‐term peak concentrations and examine concentration fluctuations. [ 32,33 ]…”

Cannabis Cultivation Facilities: A Review of Their Air Quality Impacts from the Occupational to Community Scale

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