Prediction of Methyl Bromide Flux from Area Sources Using the ISCST Model

Abstract

AbstractGrowing concern about atmospheric exposure of humans to pesticides has led to increased air monitoring in California. Air monitoring data typically consist of measurements made downwind from point or area sources. The utility of monitoring at fixed stations is limited for establishing buffer zones to protect neighboring populations from pesticide exposure. A modeling approach designed to use these data would provide the flexibility needed to establish buffer zones. The Industrial Source Complex Short Term (ISCST) model is a gaussian plume dispersion model that predicts air concentrations around point or area sources using emission rates (flux) and meteorological conditions as model inputs. The flux data, however, are typically not collected in the field nor available in the literature. In order to use the field data currently available, we developed a procedure using methyl bromide (MeBr) concentrations around two area sources and the ISCST model, to back‐calculate flux. In addition, MeBr flux was measured concurrently by cooperators conducting an independent study. Air concentrations, together with actual meteorological data, were used as inputs to the ISCST model. Flux of MeBr was then back‐calculated using a two step process: (i) an arbitrary flux value of 100 µg m−2 s−1 was used as an initial input value. Resultant air concentrations predicted by the model were then regressed on air concentrations measured offsite and (ii) the resultant regression coefficient was then used to adjust the arbitrary flux to a back‐calculated flux. Using another regression analysis, back‐calculated and measured flux rates were found to be significantly correlated, indicating this approach may be suitable for indirect estimation of flux. Implications for the use of this method in establishing buffer zones designed to protect human health are discussed.