Kettleman City, California, reported a higher than expected number of birth defect cases between 2007 and 2010, raising the concern of community and government agencies. A pesticide exposure evaluation was conducted as part of a complete assessment of community chemical exposure. Nineteen pesticides that potentially cause birth defects were investigated. The Industrial Source Complex Short-Term Model Version 3 (ISCST3) was used to estimate off-site air concentrations associated with pesticide applications within 8 km of the community from late 2006 to 2009. The health screening levels were designed to indicate potential health effects and used for preliminary health evaluations of estimated air concentrations. A tiered approach was conducted. The first tier modeled simple, hypothetical worst-case situations for each of 19 pesticides. The second tier modeled specific applications of the pesticides with estimated concentrations exceeding health screening levels in the first tier. The pesticide use report database of the California Department of Pesticide Regulation provided application information. Weather input data were summarized from the measurements of a local weather station in the California Irrigation Management Information System. The ISCST3 modeling results showed that during the target period, only two application days of one pesticide (methyl isothiocyanate) produced air concentration estimates above the health screening level for developmental effects at the boundary of Kettleman City. These results suggest that the likelihood of birth defects caused by pesticide exposure was low.
We evaluated the ability of the HYDRUS 2D/3D model to simulate chloropicrin (CP) and 1,3‐dichloropropene (13D) fate, transport, and volatilization. Three fields with similar soil conditions were broadcast fumigated under a totally impermeable film (TIF). One field was used to calibrate HYDRUS by adjusting fumigant degradation rates, soil sorption coefficients, and TIF tarp resistance factors. In comparisons of simulated and measured soil gas concentrations, soil temperature, soil water contents, and inverse‐modeled estimates of fumigant volatilization flux, the model accurately simulated the basic individual processes of fumigant partitioning and degradation, heat transport, and soil water dynamics in the calibration field. Subsequent flux simulations of the remaining two fields were performed using only measured, independently estimated or calibrated inputs with no further adjustments. The magnitudes of simulated cumulative fluxes and both pre‐ and post‐tarpcut discrete flux densities were within the estimated range of uncertainty (factor of ∼2) of conventional inverse‐modeled field‐based flux estimates. However, the timing of maximum discrete flux densities was delayed by 1 to 2 d relative to inverse‐modeled estimates. While HYDRUS provided reasonably accurate flux estimates, it was also evident that parameterization, particularly for TIF tarp permeability properties, generally requires field‐based calibration because of a lack of representative field effective permeability data.
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.
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