2,4-D Exposure and risk assessment: Comparison of external dose and biomonitoring based approaches

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Abstract

Highlights

★ Biomonitoring-based exposure assessments provide valuable insights. ★ Lots of biomonitoring and external dose exposure data exists for 2,4-D. ★ Internal and external dose based risk assessments are conducted for 2,4-D. ★ Internal dose based risk assessment for 2,4-D yields lower hazard. ★ Significant margins of safety (HQ values less than 0.1) exist for 2,4-D.

Conventional chemical exposure assessment relies upon measurements or estimates of chemical concentrations in environmental media, food, or products, in combination with assumptions regarding contact rates, in order to estimate external doses (ppm in air) or intake rates of chemicals (e.g., mg/kg/day ingested). A risk assessment is conducted by comparing these external or intake dose estimates to appropriate (e.g., route-specific) exposure guidance values (e.g., Reference Dose or Reference Concentration) to assess whether exposures are exceeding levels of concern. Human biomonitoring, in which concentrations of chemicals are measured in blood or urine, is being increasingly used as an alternative or complementary exposure assessment. The Biomonitoring Equivalent, which is the translation of a Reference Dose to an equivalent concentration of a compound in blood or urine, provides a parallel means to interpret biomonitoring data in order to assess whether chemical-specific exposures exceed levels of concern. This manuscript presents a side-by-side comparison of the two approaches for assessing exposures and risks for a case study compound, 2,4-dichlorophenoxyacetic acid (2,4-D). The findings from this case study indicate that the external dose-based assessments result in estimates of exposure and resulting hazard quotients that are consistently several-fold higher than those based on biomonitoring data. These comparisons support a conclusion that exposure assessments conducted as part of the registration process for 2,4-D incorporate sufficiently conservative assumptions.

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