Comparison of regional air dispersion simulation and ambient air monitoring data for the soil fumigant 1,3-dichloropropene.

SOFEA v2.0 is an air dispersion modeling tool used to predict acute and chronic pesticide concentrations in air for large air sheds resulting from agronomic practices. A 1,3-dichloropropene (1,3-D) air monitoring study in high use townships in Merced County, CA, logged 3-day average air concentrations at nine locations over a 14.5month period. SOFEA, using weather data measured at the site, and using a historical CDPR regulatory assumption of a constant 320m mixing height, predicted the general pattern and correct order of magnitude for 1,3-D air concentrations as a function of time, but failed to estimate the highest observed 1,3-D concentrations of the monitoring study. A time series and statistical comparison of the measured and modeled data indicated that the model underestimated 1,3-D concentrations during calm periods (wind speed <1m/s), such that the annual average concentration was under predicted by approximately 4.7-fold, and the variability was not representative of the measured data. Calm periods are associated with low mixing heights (MHs) and are more prevalent in the Central Valley of CA during the winter months, and thus the assumption of a constant 320m mixing height is not appropriate. An algorithm was developed to calculate the MH using the air temperature in the weather file when the wind speed was <1m/s. When the model was run using the revised MHs, the average of the modeled 1,3-D concentration Probability Distribution Function (PDF) was within 5% of the measured PDF, and the variability in modeled concentrations more closely matched the measured dataset. Use of the PCRAMMET processed weather data from the site (including PCRAMMET MH) resulted in the global annual average concentration within 2-fold of measured data. Receptor density was also found to have an effect on the modeled 1,3-D concentration PDF, and a 50×50 receptor grid in the nine township domain captured the measured 1,3-D concentration distribution much better than a 3×3 receptor grid (i.e., simulated receptors at the nine monitoring locations). Comparison of the monitored and simulated PDF for 72-h 1,3-D concentrations indicated that SOFEA slightly over predicts the 1,3-D concentration distribution at all percentiles below the 99th with slight under prediction of the 99-100th percentile values. This suggests that without further refinement, the SOFEA2 model, based upon field validation observations, will result in representative but conservative estimates of lifetime exposure to 1,3-D for bystanders in 1,3-D use areas.

Coupling field observations, soil modeling, and air dispersion algorithms to estimate 1,3-dichloropropene and chloropicrin flux and exposure.

Soil fumigants are volatile compounds applied to agricultural land to control nematode populations, weeds, and crop diseases. Field trials used for measuring fumigant loss from soil to the atmosphere encompass only a small proportion of the near semi-infinite parameter combinations of environmental, agronomic, and meteorological conditions. One approach to supplement field observations uses a soil physics model for fumigant emission predictions. A model is first validated against existing field study observations and then used to extrapolate results to a wider range of edaphic and climatic conditions. This work compares field observations of 1,3-dichloropropene and chloropicrin emissions to predictions from the USDA soil model CHAIN_2D. Comparison between model predictions and field observations for a Florida and California study had values between 0.62 to 0.81 and 0.99 to 1.0 for discrete and cumulative emission flux, respectively. CHAIN_2D emission rates were then coupled to several USEPA air dispersion models (ISCST3, CALPUFF6) to extend emission estimates to near field air concentrations. CALPUFF6 predicted slightly higher 1-h maximum air concentrations than ISCST3 for the same source strength (26.2-36.0% for setbacks between 1 and 250 m from the field edge, respectively). A sensitivity analysis for the CHAIN_2D/ISCST3 coupled numerical system is provided, with several soil and irrigation parameters consistently the most sensitive. Changes in the depth of incorporation, tarp material, and initial soil water content illustrate the predicted impact to emission strength and resulting near-field air concentrations with reductions of cumulative emission loss from 8.1 to 71% and average 1-h maximum air concentration reductions between 6.2 and 41% depending on the mitigation strategy chosen. Additionally, a stochastic framework based on the published SOFEA system that couples variability in experiment, model sensitivity, and site specific attributes is outlined should regional air concentration estimates resulting from fumigant use be sought.

Use of SOFEA to predict 1,3-D concentrations in air in high-use regions of California.

Methyl bromide, a commonly used soil fumigant, is being phased out per the Montreal Protocol and multiple fumigants are being positioned as replacements. Most effective soil fumigants, including methyl bromide, have the potential for inhalation exposure if the material volatilizes from soil. Chronic exposures for the fumigant 1,3-dichloropropene (1,3-D) are managed in part by the California Department of Pesticide Regulation by limiting the annual amount that can be used within a given township. A stochastic/deterministic numerical system (SOil Fumigant Exposure Assessment system [SOFEA]) was developed using the USEPA air dispersion model ISCST3, field study observations for flux loss, and links to Geographic Information Systems (GIS). SOFEA was used retrospectively to simulate concentrations of 1,3-D in air for direct comparison with monitoring program observations conducted by California Air Resources Board in Fresno County. These results indicated slight overprediction but correct magnitudes for regional air concentrations, especially at the higher percentiles, and provide a performance test. SOFEA was also used, prospectively, to predict air concentrations in potential future-use scenarios. These simulations of chronic air concentrations in two high-use 1,3-D counties of California (Ventura, Merced) consisted of 25 contiguous townships treated either at 1.5 times the current township allocation (40,937 kg) or at the maximum levels of 1,3-D used between 1999 and 2006. Exposure predictions for large regions are necessary to evaluate chronic population-based lifetime exposure and risk to 1,3-D should use patterns change. SOFEA provides a tool to estimate regional air concentrations within high-use areas required for such risk assessments.

Predicting regional emissions and near-field air concentrations of soil fumigants using modest numerical algorithms: a case study using 1,3-dichloropropene.

Soil fumigants, used to control nematodes and crop disease, can volatilize from the soil application zone and into the atmosphere to create the potential for human inhalation exposure. An objective for this work is to illustrate the ability of simple numerical models to correctly predict pesticide volatilization rates from agricultural fields and to expand emission predictions to nearby air concentrations for use in the exposure component of a risk assessment. This work focuses on a numerical system using two U.S. EPA models (PRZM3 and ISCST3) to predict regional volatilization and nearby air concentrations for the soil fumigant 1,3-dichloropropene. New approaches deal with links to regional databases, seamless coupling of emission and dispersion models, incorporation of Monte Carlo sampling techniques to account for parametric uncertainty, and model input sensitivity analysis. Predicted volatility flux profiles of 1,3-dichloropropene (1,3-D) from soil for tarped and untarped fields were compared against field data and used as source terms for ISCST3. PRZM3 can successfully estimate correct order of magnitude regional soil volatilization losses of 1,3-D when representative regional input parameters are used (soil, weather, chemical, and management practices). Estimated 1,3-D emission losses and resulting air concentrations were investigated for five geographically diverse regions. Air concentrations (15-day averages) are compared with the current U.S. EPA's criteria for human exposure and risk assessment to determine appropriate setback distances from treated fields. Sensitive input parameters for volatility losses were functions of the region being simulated.

Designing herbicide formulation characteristics to maximize efficacy and minimize rice injury in paddy environments.

Mathematical descriptors, coupled with experimental observations, are used to quantify differential uptake of an experimental herbicide in Japonica and Indica rice (Oryza sativa, non-target) and barnyardgrass (Echinochloa crus-galli, target). Partitioning, degradation, plant uptake and metabolism are described using mass-balance conservation equations in the form of kinetic approximations. Estimated environmental concentrations, governed by the pesticide formulation, are described using superimposed analytical solutions for the one-dimensional diffusion equation in spherical coordinates and by a finite difference representation of the two-dimensional diffusion equation in Cartesian coordinates. Formulation attributes from granules include active ingredient release rates, particle sizes, pesticide loading, and granule spacing. The diffusion model for pesticide transport is coupled with the compartment model to follow the fate and transport of a pesticide from its initial application location to various environmental matrices of interest. Formulation effects, partitioning and degradation in the various environmental matrices, differential plant uptake and metabolism, and dose-response information for plants are accounted for. This novel model provides a mechanism for selecting formulation delivery systems that optimize specific attributes (such as weed control or the therapeutic index) for risk-assessment procedures. In this report we describe how this methodology was used to explore the factors affecting herbicide efficacy and to define an optimal release rate for a granule formulation.

Predicted 1,3-dichloropropene air concentrations resulting from tree and vine applications in California.

The preplant soil fumigant 1,3-dichloropropene (1,3-D) is effective for nematode control and is expected to further replace methyl bromide (MeBr) as MeBr use is phased out. Acute human exposure to soil fumigants is managed in part by using buffer zones between treated fields and occupied structures. The required buffer zone for 1,3-D in California is 91.4 m (300 ft) for all uses. However, a 30.5-m (100-ft) buffer setback is desired for 1,3-D to be an important replacement for MeBr in the orchard and vineyard markets. The Industrial Source Complex Short-Term model, Version 3 (ISCST3) was used to simulate township-wide long-term average and short-term air concentration distributions of 1,3-D. The Gaussian plume model ISCST3 can be used to assess dispersion of air pollutants and pollutant concentrations on receptors from a variety of sources and in diverse airsheds. Long-term and daily-average air concentrations can be compared with the California permitted chronic or acute toxicity endpoints, respectively, to assess the potential risk for individuals living within the township at the proposed buffer setback. Modifications to ISCST3 were made for specific nonpoint-source agricultural constraints and management practices. Chronic and acute air concentration distributions of 1,3-D with a 30.5-m buffer constraint around treated fields are similar to currently permitted air concentration distributions in California. Refinement of exposure as a function of buffer distance, application rate, and field size is possible due to the resolution of the simulation and external post-processing capabilities. Simulated examples of 1,3-D acute and chronic exposure cumulative distributions are presented.