Chapter 10 Water-Sediment Studies Jeremy Dyson Basel, Switzerland.

Slides:



Advertisements
Similar presentations
Requirements Engineering Process
Advertisements

Group 5: Historical control data Follow-up of 2005 IWGT where the use of historical control data in interpretation of in vitro results was identified as.
1 of 21 Information Strategy Developing an Information Strategy © FAO 2005 IMARK Investing in Information for Development Information Strategy Developing.
Knowledge Dietary Managers Association 1 PART II - DMA Certification Exam Blueprint and Exam Development-
SMA 6304 / MIT / MIT Manufacturing Systems Lecture 11: Forecasting Lecturer: Prof. Duane S. Boning Copyright 2003 © Duane S. Boning. 1.
Chapter 9 Normalisation of Field Half-lives
Data handling Sabine Beulke, CSL, York, UK FOCUS Work Group on Degradation Kinetics Estimating Persistence and Degradation Kinetics from Environmental.
Theory Metabolites Karin Aden (BVL, Germany)
KINETIC MODELS Guy SOULAS UMR Œnologie-Ampélologie
30 Jan 2006 Page 1 FOCUS Kinetics training workshop Chapter 7 Recommended Procedures to Derive Endpoints for Parent Compounds Ralph L. Warren, Ph.D. DuPont.
Claude Beigel, PhD. Exposure Assessment Senior Scientist Research Triangle Park, USA Practical session metabolites Part II: goodness of fit and decision.
26-27 Jan 2005 Page 1 FOCUS Kinetics training workshop Chapter 7 Recommended Procedures to Derive Endpoints for Parent Compounds Ralph L. Warren, Ph.D.
Claude Beigel, PhD. Exposure Assessment Senior Scientist Research Triangle Park, USA Practical session metabolites Part I: curve fitting.
Introduction to parameter optimization
26-27 Jan 2005 Page 1 FOCUS Kinetics training workshop Chapter 7 Recommended Procedures to Derive Endpoints for Parent Compounds Practical Exercise Ralph.
Outline Introduction Kinetic endpoints General fitting recommendations
Demonstration of fitting with Berkeley Madonna FOCUS Degradation Kinetics, Ton van der Linden, January 27, 2005.
Introduction to ModelMaker
Introduction and Project Definition Russell L. Jones January 26, 2005.
Improving imputation methodology in the Hungarian Central Statistical Office (HCSO) NTTS 2009 seminar, Bruxelles February 2009 Improving imputation.
Kinetic Models Considered Jeremy Dyson Basel, Switzerland.
1 FOCUS Degradation Kinetics Training course January 2005 Regulatory use of degradation endpoints Sylvia Karlsson Swedish Chemicals Inspectorate.
1 Adding a statistics package Module 2 Session 7.
SADC Course in Statistics Common Non- Parametric Methods for Comparing Two Samples (Session 20)
SADC Course in Statistics Introduction to Non- Parametric Methods (Session 19)
Assumptions underlying regression analysis
SADC Course in Statistics Comparing two proportions (Session 14)
1 Alberto Montanari University of Bologna Basic Principles of Water Resources Management.
1 Revisiting salary Acme Bank: Background A bank is facing a discrimination suit in which it is accused of paying its female employees.
Quality Assurance/Quality Control Plan Evaluation February 16, 2005.
Copyright © 2007 Ramez Elmasri and Shamkant B. Navathe Slide
OOAD – Dr. A. Alghamdi Mastering Object-Oriented Analysis and Design with UML Module 3: Requirements Overview Module 3 - Requirements Overview.
Stability Studies - Evaluation of Outcomes and Development of Documentation For Regulatory Submissions Bob Seevers.
S-Curves & the Zero Bug Bounce:
Defect testing Objectives
Testing Workflow Purpose
IPCC Good Practices Guidance and the electronic reporting of GHG inventory tables: useful tools for improving the quality of national GHG inventories of.
Energy Balancing Credit Proposal MOD 315 Energy Balancing Credit Proposal MOD 315 To Enhance Section X of the UNC Transportation Principal Document to.
Lecture 8: Testing, Verification and Validation
Introduction and Project Definition Russell L. Jones January 30, 2006.
1 Project Nexus Modelling costs and benefits Andrew Wallace, Cesar Coelho Ofgem Project Nexus IA Subgroup 25 July 2012.
Approximation of heavy models using Radial Basis Functions Graeme Alexander (Deloitte) Jeremy Levesley (Leicester)
Determining How Costs Behave
Week 1.
Chapter 11 Describing Process Specifications and Structured Decisions
Simple Linear Regression Analysis
1 Chapter 13 Weighing Net Present Value and Other Capital Budgeting Criteria McGraw-Hill/Irwin Copyright © 2012 by The McGraw-Hill Companies, Inc. All.
4/4/2015Slide 1 SOLVING THE PROBLEM A one-sample t-test of a population mean requires that the variable be quantitative. A one-sample test of a population.
Summary Slide Some Industry views on POP/PBT identification in Europe.
Chapter 9 Hypothesis Testing Understandable Statistics Ninth Edition
Climate Change Committee WG1 QA/QC terminology and requirements from the IPCC Good Practice Guidance and the Guidelines for National Inventory Systems.
Designing Scoring Rubrics. What is a Rubric? Guidelines by which a product is judged Guidelines by which a product is judged Explain the standards for.
Training session File Note and Registration Report, 23 rd October Registration report : Partim Fate and Behavior in the environment 23 rd October.
Research Methods for Counselors COUN 597 University of Saint Joseph Class # 8 Copyright © 2015 by R. Halstead. All rights reserved.
AP Statistics – Chapter 9 Test Review
Implementation. We we came from… Planning Analysis Design Implementation Identify Problem/Value. Feasibility Analysis. Project Management. Understand.
WMO UNEP INTERGOVERNMENTAL PANEL ON CLIMATE CHANGE NATIONAL GREENHOUSE GAS INVENTORIES PROGRAMME WMO UNEP IPCC Good Practice Guidance Simon Eggleston Technical.
Chapter 9 Title and Outline 1 9 Tests of Hypotheses for a Single Sample 9-1 Hypothesis Testing Statistical Hypotheses Tests of Statistical.
Slide 1 SOLVING THE HOMEWORK PROBLEMS Simple linear regression is an appropriate model of the relationship between two quantitative variables provided.
Marketing Research Aaker, Kumar, Day and Leone Tenth Edition
University of Palestine software engineering department Testing of Software Systems Fundamentals of testing instructor: Tasneem Darwish.
Spreadsheet-Based Decision Support Systems Chapter 22:
Design - programming Cmpe 450 Fall Dynamic Analysis Software quality Design carefully from the start Simple and clean Fewer errors Finding errors.
Evaluation of structural equation models Hans Baumgartner Penn State University.
Data handling Sabine Beulke, Central Science Laboratory, York, UK Kinetic Evaluation according to Recommendations by the FOCUS Work Group on Degradation.
Chapter 9 Hypothesis Testing Understanding Basic Statistics Fifth Edition By Brase and Brase Prepared by Jon Booze.
Designing Scoring Rubrics
Outdoor Water Sediment Study – Adding Effects of Sunlight to Aquatic System Exposure Assessment Cecilia Mucha Hirata (DuPont Crop Protection, Newark DE,
Rochelle F.H. Bohaty, William P. Eckel, Katrina White, Dirk F. Young
9 Tests of Hypotheses for a Single Sample CHAPTER OUTLINE
Presentation transcript:

Chapter 10 Water-Sediment Studies Jeremy Dyson Basel, Switzerland

Outline Defining, Estimating & Using Endpoints Parent Kinetics –Similarities/differences to other test systems –Models and flowcharts –Statistics and examples Metabolite Kinetics –Similarities to other test systems –When are metabolite kinetics not required? –Models and flowcharts Concluding Remarks

Defining, Estimating & Using Endpoints Water Column Well-mixed Aerobic Water+particulates Sediment Slow-mixing Oxic to anoxic Application of Parent or Metabolite Metabolism: Formation & Degradation Transfer Processes Volatilisation Water-Sediment Interface

Defining, Using & Estimating Endpoints Persistence Endpoints –To determine whether various aquatic ecotoxicolgy studies are triggered, e.g. fish accumulations studies Modelling Endpoints –To use in calculating PEC values as part of an aquatic risk assessment, e.g. FOCUS surface water scenarios Further Aspects of these Endpoints –For Parent or Metabolites –For Degradation or Dissipation –For Whole System, Water Column or Sediment

Defining, Using & Estimating Endpoints The Water-Sediment System & Definitions –Behaviour can be more complex than in other systems –Straightforward definitions e.g. dissipation from compartments –Non-straightforward definitions, e.g. degradation in compartments Study Guidelines and Use –Not always clear if dissipation or degradation required –Decisions about endpoints used made on a case-by-case basis Difficulties of Estimation –Main problem over degradation-transfer correlations –No simple, robust & reliable constraints procedures –Default worst-case approach if lack of degradation in one compartment, implausible transfer rates (Fsed test), or generally inconsistent with other environmental fate studies

Defining, Using & Estimating Endpoints Kinetic Persistence/Modelling Disappearance Level Endpoints Endpoints Level I System (Parent & Metabs) Degradation (1 comp.) Water column (Both) Dissipation Sediment (Both) Dissipation Level II Water column (Parent) Degradation (2 comp.) Sediment (Parent) Degradation

Parent Kinetics Similarities to Other Test Systems –Data entry and exclusion –Selection of fitting routine –Standard constraints, underlying kinetics etc. –Methods of making kinetic decisions Differences to Other Test Systems –Day zero data: put all in water column –Data in terms of mass or equivalent, e.g. %AR –Do not use concentration data –Operation of the worst-case default approach at Level P-II

Models and Flowcharts: Level P-I

SFO Kinetics –Default first choice –Required for modelling endpoints FOMC Kinetics –Evaluate if data depart appreciably from SFO kinetics DFOP Kinetics –Offers more flexibility than FOMC with extra parameter Hockey Stick Kinetics –Data sometimes appear to have some breakpoint in rate

Models and Flowcharts: Level P-I System Degradation/Compartment Dissipation Persistence Endpoints –Tier 1: Check if SFO is an appropriate model –Tier 2: Identify best-fit model if required Modelling Endpoints –Tier 1: Check if SFO is an acceptable model –Tier 2: Correction procedures if SFO not an acceptable model

Models and Flowcharts: Level P-II

Empirical Transfer Pattern –Able to approximate quite closely Simple Transfer Kinetics –No assumptions about sediment concentration gradients –Appropriate if gradients are complex and not measured –Appropriate to consider before more complex alternatives First-Order Transfer Kinetics –Relatively easy to implement in software packages

Models and Flowcharts: Level P-II Example of Transfer Pattern without Degradation

Models and Flowcharts: Level P-II The Fsed Test Definition –Fraction in sediment at equilibrium in absence of degradation Modelled Fsed Values –Calculated from fitted transfer parameters of Level P-II model Fsed = r w-s / (r w-s + r s-w ) Theoretical Fsed Values –Based on system/pesticide properties & diffusion assumptions Fsed = (Kd b + ) / [(Z w /Z D )+(Kd b + )]

Models and Flowcharts: Level P-II Persistence/Modelling Degradation Endpoints SFO Fit (Criteria to be met even if fit acceptable) –Consistent with environmental fate data –Degradation rates k w and k s >0 as demonstrated by t-test –The Fsed test needs to be passed Criteria met? YesNo Use estimates as required against triggers/ in modelling Use 1 of 3 default approaches tested to ensure they lead to worst-case PEC values

Models and Flowcharts: Level P-II Persistence/Modelling Degradation Endpoints Default approach 1 Passes Fsed test but one degradation rate is zero or fails t-test Use default as required in modelling Set degradation rate to overall system half-life in degrading compartment Set degradation rate to day half-life in non-degrading compartment

Models and Flowcharts: Level P-II Persistence/Modelling Degradation Endpoints Default approach 2 Fails Fsed test due to zero transfer rate from sediment to water Set water column degradation rate to overall system half-life Set sediment degradation rate to day half-life Set water column degradation rate to estimated half-life Set sediment degradation rate to overall system half-life Use default as required in modelling Fitted degradation faster in water column than in sediment? Yes No

Models and Flowcharts: Level P-II Persistence/Modelling Degradation Endpoints Default approach 3 Fails Fsed test or inconsistent with E Fate data (degradation) Determine and use default that results in worst-case PEC values: Water column degradation half-life=overall system; Sediment half-life= days, or vice versa Use default as required in modelling

Models and Flowcharts: Level P-II Persistence/Modelling Degradation Endpoints Default approach 3 Strongly sorbing compound no degration in water column

Models and Flowcharts: Level P-II Persistence/Modelling Degradation Endpoints Default approach 3 Weakly sorbing compound no degration in water column

Models and Flowcharts: Level P-II What If the Default Options Need Refining? Fit a diffusion-based model to water-sediment data –A TOXSWA example for such refinement is in Appendix 12 –Development needed for a user-friendly implementation of TOXSWA, or a diffusion-based model specific to water- sediment systems

Statistics and Examples Assessing Goodness of Fit Visual Assessment –Main tool for assessment –Plots of model fits & residuals 2 Test –Performed for each compartment, even at Level P-II –Supplements visual assessment & model comparison –Only a guidance value of 15% error value to pass test t-Test –Reliability of individual dissipation/degradation rates –Total df with a significance level of 10% to pass test

Statistics and Examples: Level P-I Compound 6 wc+sed Compound 6 wc Compound 6 sed

Statistics and Examples : Level P-I Compartment Modification DegT50/DT50 in days ( 2 ) SFO FOMC HS wc + sed Remove outlier 20.1 (3.6) 20.1 (3.6) 19.8 (3.0) wc Remove outlier 19.1 (2.8) 18.6 (2.7) 18.7 (1.9) sed Remove outlier 21.1 (9.4) 15.2 (6.5) 17.7 (7.7)

Statistics and Examples : Level P-II Compound 6

Statistics and Examples : Level P-II Compartment Modification DegT1/2 Fsed (%) ( 2 value) Modelled Theoretical wc Fix Mo (3.1) sed 2.16 (9.0)

Metabolite Kinetics Similarities to Other Test Systems –Data entry and exclusion –Selection of fitting routine –Standard constraints, data exclusion, underlying kinetics etc. –Methods of making kinetic decisions When Are Metabolite Kinetics Not Required? –Sometimes not required for minor metabolites –If risks implicitly assessed via higher tier studies –Sometimes not if also applied as a parent substance –Sometimes not if can add metabolite residues to parent

Models and Flow Charts: Level M-I Defining Persistence/Modelling Endpoints Type of Endpoint Compartment Kinetic Model Dissipation System Decline from peak Water Column Sediment Degradation System Formation & degradation

Models and Flowcharts: Level M-I SFO Kinetics –Default first choice –Required for modelling endpoints FOMC Kinetics –Evaluate if data depart appreciably from SFO kinetics DFOP Kinetics –Offers more flexibility than FOMC with extra parameter Hockey Stick Kinetics –Not used

Models and Flowcharts: Level M-I System/Compartment Dissipation/Degradation Persistence Endpoints –Tier 1: Check if SFO is an appropriate model –Tier 2: Identify best-fit model if required Modelling Endpoints –Tier 1: Check if SFO is an acceptable model –Tier 2: Correction procedures if SFO not an acceptable model

Models and Flowcharts: Dissipation Level M-I

Models and Flowcharts: Degradation Level M-I

Models and Flowcharts: Level M-II General Recommendations for Development Data/Parameter Requirements –Minimise, e.g. do not use sink data as a first step Kinetics –Use first-order kinetics for transfer & degradation processes Formation Fraction –Option to use same fraction for water column & sediment –Option to use a default fraction, i.e. that estimated at Level M-I

Concluding Remarks General Remarks –Complex area of kinetics, but the workgroup has increased understanding of strengths & limitations of approaches, bringing greater transparancy & consistency Parent Kinetics –Resolved endpoint definition, use and estimation –In a framework and developed degradation refinement process Metabolite Kinetics –Resolving endpoint definition, use and estimation –Kinetics still need actively developing for Level M-II