Modeling pesticides in global surface soils: Evaluating spatiotemporal patterns for USEtox-based steady-state concentrations.

To better manage pesticide pollution in surface soils, we introduced a first-order-kinetics-based screening model to evaluate the steady-state concentrations of pesticides in surface soils while considering degradation, volatilization, plant uptake, and precipitation processes. For each process, we developed a spatiotemporal-pattern-based model using spatiotemporal variables, including air temperature (T), relative humidity (RH), and rainfall intensity (I), to characterize the overall dissipation rates (k) of pesticides in the soil. These dissipation rates were converted to fate factors (FFs), which are commonly used in life cycle analyses. The results indicate that, in general, the k values increase with increasing T and I and decrease with increasing RH. This is because increased T boosts the degradation, volatilization, and plant uptake processes, whereas increased RH lowers the plant transpiration rate. Also, the simulation for over 700 pesticides indicated that the degradation process dominates the overall dissipation of most pesticides in the soil, and the volatilization process contributes the least. In addition, we simulated chlorpyrifos FFs for Brazil, China, the US, and the European Union (EU) using the annual average T, RH, and I values. The results indicate that, in general, Brazilian federal units have the smallest FFs and the narrowest simulated FF range because of their humid tropical climates. Meanwhile, the EU member states have the largest FFs and the widest FF range because of their range in locations. In addition, our simulated results show that the surface soils in the high-latitude regions could accumulate more chlorpyrifos than those in low-latitude regions because of the larger simulated FFs. Furthermore, we parameterized our model using 737 pesticides with the USEtox, thereby providing an alternative approach to simulate the steady-state concentration of pesticides in surface soils from the USEtox available data. The model developed herein is a useful screening tool for predicting pesticide concentrations in surface soil worldwide to improve soil and ecological health risk management.