A Grower-Oriented Online System for Site-Specific Pesticide Use Environmental Risk Evaluations (PURE).

To alleviate pesticide impact on environmental quality, a wealth of data and methods with regard to risk assessment of pesticides has been accumulated in governmental regulation and academic research.  However, it is difficult for growers to obtain the needed knowledge from the disparate information sources in the pest management practices (PMPs) of using materials having lower environmental impacts.  Therefore, the Pesticide Use Risk Evaluation (PURE) online system has been developed to assist growers in quantitatively assessing site-specific environmental risk of their PMPs for both past performance and future plans.  Initiated by the minimum user input (commodity, year, and field location), PURE automatically calculates product- and field-level risk scores, which are accompanied with spatial risk maps and temporal risk trends, by linking a precompiled database with a calculation model so-called risk indicator.  The database contains the data of 1) pesticide properties such as toxicity, half life, and volatility, 2) pesticide uses from the Pesticide Use Report (PUR) database managed by the California Department of Pesticide Regulation, and 3) environmental conditions such as climate, soil properties, and distances to water body.  The indicator evaluates pesticide risks to four environmental compartments, including surface water, groundwater, soil, and air, based on the combined effects of local environmental conditions and pesticide properties regarding exposure and toxicity.  The risks to surface water, groundwater, and air are estimated as the ratio of predicted environmental concentrations to acute/chronic toxicity of chosen non-targeted organism(s), while the risk to air is determined by application rates and the emission potential (EP) of pesticides.  The pesticide risk ranking list generated by the indicator is generally consistent with governmental pesticide regulation lists and surface water monitoring records, which serves as the preliminary validation of the employed algorithm and data.  In the refinement of the PURE online system, users’ feedback has been playing an important role.