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ARS Home » Pacific West Area » Riverside, California » U.S. Salinity Laboratory » Contaminant Fate and Transport Research » Research » Research Project #422015

Research Project: Development of Improved Methods to Predict Emissions of Pesticides and Soil Fumigants in Semi-Arid Regions

Location: Contaminant Fate and Transport Research

2012 Annual Report

1a. Objectives (from AD-416):
(a) To determine the impact of vapor sorption on pesticide volatilization from variably saturated soil. Determine the affect of heat transport and energy/mass exchanges at the soil surface on pesticide volatilization. (b) Develop the capability to predict the effects of soil heating and changes in soil moisture content on vapor sorption and on the fate and transport of volatile pesticides and soil fumigants. (c) Relate this information to agronomic production systems and the protection of atmospheric resources.

1b. Approach (from AD-416):
Conduct laboratory, field and modeling research as needed to develop a data set that can be used to predict pesticide emissions as affected by soil drying and heat transport. Conduct laboratory experiments to investigate the effect of soil water content and soil temperature on emissions of volatile pesticides and soil fumigants under highly controlled conditions. These experiments will obtain information on degradation, adsorption, soil diffusion and volatilization. Utilize the experimental results to design a field experiment to study pesticide volatilization under typical agricultural conditions. Conduct experiments to measure needed soil physical properties, evaporation, and heat transfer to characterize the moisture status of soils and relate to changes in vapor sorption. Determine the effect soil moisture has on near-surface exchange processes. Test, and develop when necessary, a model to enable prediction of pesticide volatilization as the soil moisture content varies from saturated to very dry conditions. Develop, as needed, relationships between soil moisture content and sorption of volatile organic chemicals on soil particles.

3. Progress Report:
This research is related to objective 1 of the parent project, "Measure and model mechanisms and processes that affect exchange of pesticides between soil, water, plants and air; and that improve prediction of atmospheric emissions". The use of pesticides in modern agriculture has led to large increases in crop production. However, pesticide volatilization is a primary mechanism leading to the dispersion and accumulation of toxic chemicals in the environment. To assess the effects of pesticide emissions upon risks to ecosystems and human health, accurate prediction of volatilization rates is critical. The soil water content influences the partitioning of a pesticide among the soil water, gas, and sorption phases. Studies have shown that pesticide adsorption increases dramatically when the water content decreases below a critical value, which signifies the point where the solid phase is no longer covered by several molecular layers of water. Above this critical value the equilibrium vapor density is generally not affected by soil-water content. To accurately predict the volatilization rate, it is very important to account for the effects of the soil water content. This research shows the impact of soil water content on pesticide vapor adsorption to the soil particles and their effect on the diurnal pattern of pesticide emission. The results demonstrate that the daily peak emission rate depends on the soil water content, the threshold value and the vapor sorption process. Although additional study is needed, this research will one day provide a more accurate and reliable method to predict pesticide emissions and will be of great use to the scientific community, regulators, agricultural consultants and farm advisors. Simulations were performed using a comprehensive non-isothermal model, two water retention functions, and two soil surface resistance functions, resulting in four tested models. Results show that the degree of similarity between volatilization curves simulated using the four models depended on the initial water content. Under fairly wet conditions, the simulated values differed from the measured values but the trends were the same. However, under intermediate and low moisture conditions, both the values and trends differed. The accuracy of the model prediction depended on soil moisture. Under normal practices, where initial soil moisture was near field capacity or higher, a combination of Brooks and Corey water retention and the van de Grind and Owe soil surface resistance functions led to the most accurate predictions. However, under extremely dry conditions, when soil-water content in the top 1 cm is below the volumetric threshold value, the use of a full-range water retention function increased prediction accuracy. The most accurate predictions of the volatilization rate were within about a factor of 4, and correspond to RMSE value of 0.64 (100.64). The different models did not affect the soil temperature predictions, and had a minor effect on the predicted soil-water content of Yolo silty clay soil. Further research is needed to improve prediction accuracy and to find the source(s) of the discrepancies.

4. Accomplishments