This study developed a procedure to select a set of 5-year meteorological data with the potential to result in the highest modeled concentrations (worst-case scenario) as the input data for air dispersion modeling of pesticide applications using AERMOD. The study analyzed the relationship between the 95<sup>th</sup> percentile maximum concentrations estimated by AERMOD and the percentages of low wind speed (LWS, 0.5 – 2 m/s) in the meteorological data used for the modeling. Statistical analysis showed that they were positively correlated within various distances to different types of emission sources. In addition, the LWS percentages of 1-year data could be used to predict the LWS percentages of 5-year data for the same station. Based on these results, the selection procedure for meteorological data began with the evaluation of 1-year data quality and LWS percentages for all the available stations in California counties with high use of a pesticide of interest. Five-year meteorological data were then processed for the top 5 stations with the highest LWS percentages to perform AERMOD modeling. Finally, the air concentration estimates of the modeled meteorological data were compared to determine the worst-case scenario data. This procedure provided a strategic plan for selecting meteorological data for AERMOD modeling of pesticide uses in California. The procedure was applied to the modeling of residential structural fumigations and determined that the 5-year (2011 – 2015) data of the weather station WBAN 93134 (DOWNTOWN L.A./USC CAMPUS) was the worst-case scenario meteorological data for this modeling case.

Procedure to select meteorological data for air dispersion modeling of pesticide applications in California

2019 Fall National Meeting

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