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07:53
Single Cell Fate Mapping in Zebrafish
Published on: October 5, 2011
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Illustrating sensitivity and uncertainty in environmental fate models using partitioning maps
Torsten Meyer1, Frank Wania, Knut Breivik
1Department of Chemical Engineering and Applied Chemistry, University of Toronto at Scarborough, 1265 Military Trail, Toronto, Ontario, Canada M1C 1A4.
Environmental Science & Technology
|June 2, 2005
Summary
A new graphical method visualizes model sensitivity and uncertainty for organic contaminants, identifying key parameters affecting environmental fate predictions across all chemicals simultaneously. This approach aids in understanding chemical behavior and data needs for accurate environmental modeling.
Area of Science:
- Environmental Science
- Environmental Chemistry
- Computational Chemistry
Background:
- Environmental fate models predict contaminant behavior but often analyze limited chemicals.
- Parameter sensitivity and uncertainty vary significantly among different organic contaminants.
- A comprehensive approach is needed to assess model behavior across diverse chemical properties.
Purpose of the Study:
- To introduce a graphical method for simultaneous investigation of model sensitivity and uncertainty for all persistent organic nonelectrolytes.
- To enable comprehensive analysis of how input parameters influence environmental fate predictions.
- To facilitate categorization of chemicals based on shared sensitivities and comparable environmental behavior.
Main Methods:
- Defined a two-dimensional "chemical space" based on equilibrium partition coefficients (KOW, KAW, KOA).
- Plotted model sensitivity and uncertainty as a function of this chemical space using colored contour maps.
- Illustrated the approach using a Level III model for bulk phase concentrations in air, water, soil, and sediment.
Main Results:
- Colored contour maps effectively identify input parameters causing high output variation for various chemicals.
- The method allows for easy categorization of chemicals with similar parameter sensitivities and environmental behavior.
- Sensitivity analysis results are dependent on emission modes and chemical degradability, necessitating multiple map sets.
Conclusions:
- The graphical method provides a comprehensive tool for sensitivity and uncertainty analysis in environmental fate modeling.
- It aids in understanding model behavior, explaining divergent chemical behaviors, and grouping chemicals with similar model responses.
- The approach helps prioritize data collection by indicating when precise physical-chemical property data is critical for accurate modeling.
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