Supplementary file 2_Chemical exposure and risk in river basins: Bayesian integration of e

A 20.6 KB Excel file contains data for a probabilistic modeling framework assessing chemical risk to aquatic ecosystems at the watershed level across Europe. The dataset was created by Sophie Mentzel for the ENCORE project and last updated on May 4, 2026. It integrates prior exposure probabilities from process-based simulations with monitoring evidence from the Waterbase Water Quality dataset for Bayesian updating.

Use Cases

• Update prior chemical exposure probabilities based on monitoring data using the described Bayesian network workflow.
• Identify pesticides with high contribution to risk in aquatic environments based on spatial exposure patterns.
• Test a proof-of-concept probabilistic risk modeling approach for scaling to larger European regions.
• Assess combined exposure risk from unintentional chemical mixtures in watersheds.

Strengths

• Integrates multiple sources of information including pan-European Waterbase Water Quality data.
• Implements a Bayesian updating framework to improve risk calculation accuracy.
• File size is 20.6 KB, making it lightweight for initial inspection.

Limitations

• Row count is unknown, which may limit suitability assessment.
• Column-level documentation is absent; field semantics must be inferred after download.
• The pilot study focuses on a subset of pesticides in Belgium, limiting immediate generalizability.

Provenance

Source

Sophie Mentzel, likely affiliated with the ENCORE (ENvironmental CO-exposure and Risk Estimation) project.

Collection Method

Developed for a Bayesian network model integrating process-based simulation data with monitoring evidence.

Freshness

Last updated 2026-05-04 05:32:15; freshness should be verified.

Geography

Pilot study focused on Belgium, with methodology intended for watersheds across Europe.