Pesticide exposure monitoring databases in applied risk analysis.

摘要

Faced with the need to evaluate under what conditions chemicals can be used with "reasonable certainty of no harm" to workers and consumers, industry and government agencies have embraced quantitative risk analysis as a science-based approach for product development, regulatory evaluations, and associated risk management decision making. Beginning in the 1990s, a variety of industry-sponsored task forces have been formed to develop exposure-related data to support safety evaluations for pesticide chemicals used in agricultural, industrial, institutional, residential, and other settings. Human exposure assessment and the underlying data (e.g., personal exposure and biological monitoring measurements, media-specific residue measurements, product use, and time-activity information) represent a critical component of the risk assessment process and a rapidly advancing science. While task forces have been created to develop databases for supporting the continued safe use of products, the development of these databases has served to advance general understanding of the basic principles underlying exposure assessment methodology and thereby provide the basis for improved science-based risk management by both industry and government. Given that developing chemical-specific data for every product use pattern and associated worker or consumer exposure scenario (e.g., professional mixer, loader and applicator activities associated with the use of a low-pressure sprayer, consumer residential lawn application via a ready-to-use hose-end sprayer product) is prohibitively expensive and time consuming, alternative approaches have been developed based upon meta-analyses and generalizations derived from databases of exposure monitoring studies for multiple chemicals, sorted by significant exposure covariates such as formulation type, method of application, amount of active ingredient applied, site of application, protective equipment and clothing, and task or activity. These generalizations can be used for predictive exposure analyses and have clearly demonstrated the value of "generic databases." Although data in these databases and associated generalizations are subject to interpretation, e.g., during the regulatory decision-making processes, and may be used in conjunction with additional considerations or assessment methods that result in conservative biases, the role of generic databases for risk management decision making, and advancing the science of applied exposure analysis continues to be realized.