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Probabilistic Aquatic Exposure Assessment for Pesticides I : Foundations

By Burns, Lawrence A., Ph. D.

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Book Id: WPLBN0000066430
Format Type: PDF eBook
File Size: 1.3 MB
Reproduction Date: 2007

Title: Probabilistic Aquatic Exposure Assessment for Pesticides I : Foundations  
Author: Burns, Lawrence A., Ph. D.
Volume:
Language: English
Subject: Ecology, Natural resource issues, Environemtal protection
Collections: Environmental Awareness Library Collection
Historic
Publication Date:
Publisher: United States Environmental Protection Agency

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Burns, Ph. D, L. A. (n.d.). Probabilistic Aquatic Exposure Assessment for Pesticides I : Foundations. Retrieved from http://kindle.worldlibrary.net/


Description
Excerpt: Abstract: Models that capture underlying mechanisms and processes are necessary for reliable extrapolation of laboratory chemical data to field conditions. For validation, these models require a major revision of the conventional model testing paradigm to better recognize the conflict between model user’s and model developer’s risk (as Type I and Type II errors) in statistical testing of model predictions. The predictive reliability of the models must be hypothesized and tested by methods that lead to conclusions of the form “the model predictions are within a factor-of-two of reality at least 95% of the time.” Once predictive reliability is established, it can be treated as a “method error” within a probabilistic risk assessment framework. This report, developed under APM 131 (“Develop a Probability-Based M ethodology for Conducting Regional Aquatic Ecosystem Exposure and V ulnerability Assessments for Pesticides”), describes a step-by-step process for establishing the predictive reliability of exposure models.

Table of Contents
Contents Notice .............................................................................. ii Abstract ............................................................................ ii Preface ............................................................................. iii Foreword ........................................................................... iii Abbreviations, Acronyms, and Symbols ................................................... vi Acknowledgments .................................................................... vi Introduction to Pesticide Safety Assessment ................................................ 1 Steps in Risk Assessment ........................................................... 1 TheOPP “Quotient Method” of Assessing Ecological Risk ................................. 2 Ecotoxicological Hazard Assessment .............................................. 2 Environmental Exposure Assessment .............................................. 3 Ecological Risk Characterization .................................................. 3 Probabilistic Assessment ........................................................... 4 Modeling Issues and Technique .......................................................... 6 Pesticide Exposure Modeling ........................................................ 6 Concepts of Model Building and Model Testing ...................................... 6 Empirical Science and Numerical Extrapolation Models ............................... 8 Variability and Uncertainty .......................................................... 9 Dealing with Variability and Uncertainty: The Monte Carlo Method ........................ 10 Interpretation and Presentation of the Results of Monte Carlo Analysis ...................... 11 Validation, Verification, and Performance Measures ........................................ 13 The Validation Problem ........................................................... 13 Why Can’t Models be Proven? .................................................. 13 Testing the Performance Capabilities of Models ........................................ 14 How Can Prediction Uncertainty be Quantified? .................................... 14 Risk and Decision Analysis in Model Testing ....................................... 15 Goals and Constraints of Performance Tests ........................................ 15 Good Statistical Practice for Testing Models ....................................... 17 A Methodology for Performance Testing (Validation) of Simulation Models .................. 17 A Step-Wise Procedure for Performance Testing .................................... 21 A Substantial Example: Photolysis of DMDE in EXAMS ............................... 21 Descriptive Statistics and Predictive Uncertainty .................................... 24 Predictive Validity of Exposure Models ............................................... 24 Current Model Validation Status .................................................... 25 AgDisp/AgDrift .............................................................. 25 Pesticide Root Zone Model (PRZM) ............................................... 26

 

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