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A Procedure to Select Meteorological Data for Air Dispersion Modeling of Pesticide Applications in California

This study developed a procedure to select a set of 5‐y meteorological data with the potential to estimate the highest concentrations (“worst‐case scenario”) in air dispersion modeling of pesticide applications with American Meteorological Society/Environmental Protection Agency Regulatory Model (AERMOD). The study analyzed the relationship between the 95th 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‐y data could be used to predict the LWS percentages of 5‐y data for the same station. Based on these results, the selection procedure for meteorological data began with the evaluation of 1‐y data quality and LWS percentages for all the available stations in California, USA, 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 applications in California. The procedure was applied to the modeling of residential structural fumigations and determined that the 5‐y (2011–2015) data of the weather station WBAN 93134 (downtown Los Angeles, University of Southern California campus) was the worst‐case scenario meteorological data for this modeling case. Integr Environ Assess Manag 2019;15:648–658. Published 2019. This article is a U.S. Government work and is in the public domain in the USA.