ExpoQual: Evaluating measured and modeled human exposure data

Area of Science:

• Environmental Health Sciences
• Risk Assessment
• Data Science

Background:

• Technological advancements generate complex exposure data lacking quality assessment tools.
• Regulatory bodies increasingly require data quality assessment for environmental risk evaluations.
• Existing data quality approaches are not universally applicable to both measured and modeled exposure data.

Purpose of the Study:

• To introduce ExpoQual, a novel instrument for evaluating human exposure data quality.
• To provide a systematic, transparent, and reproducible method for data quality assessment.
• To ensure exposure data is fit-for-purpose for environmental risk assessment and decision-making.

Main Methods:

• ExpoQual integrates recognized parameters and data quality elements from existing methodologies.
• It evaluates diverse data streams, including quantitative measured and modeled human exposure data.
• The instrument is designed to minimize subjectivity and incorporate professional judgment transparently.

Main Results:

• ExpoQual facilitates a structured approach to exposure data quality evaluation.
• It enables an explicit determination of data's fitness-for-purpose.
• The tool can assess both traditional and emerging exposure data approaches.

Conclusions:

• ExpoQual addresses the need for a user-friendly, comprehensive tool for exposure data quality assessment.
• It supports regulatory efforts by providing reliable and transparent data evaluation.
• The freely available online tool invites user feedback for further development.