«Multimedia and food chain modelling of toxics for comparative risk and life cycle impact assessment Article · June 2006 ...»
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Multimedia and food chain
modelling of toxics for
comparative risk and life
cycle impact assessment
Article · June 2006
DOI: 10.5075/epfl-thesis-3539 · Source: OAI
Ralph K Rosenbaum
Irstea (National Research I…
45 PUBLICATIONS 1,979 CITATIONS SEE PROFILE Available from: Ralph K Rosenbaum Retrieved on: 20 May 2016 multimedia and food chain modelling of toxics for comparative risk and life cyle impact assessment THÈSE NO 3539 (2006) PRÉSENTÉE LE 30 JUIN 2006
à LA FACULTÉ ENVIRONNEMENT NATUREL, ARCHITECTURAL ET CONSTRUITLaboratoire de gestion des écosystèmes
SECTION DES SCIENCES ET INGÉNIERIE DE L'ENVIRONNEMENT
ÉCOLE POLYTECHNIQUE FÉDÉRALE DE LAUSANNE
POUR L'OBTENTION DU GRADE DE DOCTEUR ÈS SCIENCESPAR Ralph ROSENBAUM Dipl.-Ing., Technische Universität Berlin, Allemagne et de nationalité allemande
acceptée sur proposition du jury:
Prof. M. Parlange, président du jury Prof. O. Jolliet, directeur de thèse Prof. C. Friedli, rapporteur Prof. T. McKone, rapporteur Dr D. Pennington, rapporteur Lausanne, EPFL Table of Content
TABLE OF CONTENTTable of Content
1.2 Problem setting
1.2.1 Life Cycle Assessment (LCA)
1.2.2 Life Cycle Impact and Toxicity Assessment
1.2.3 Environmental risk and comparative impact assessment
1.3 Current fate and exposure modelling issues
1.4 Aim and structure of the thesis
2 A Flexible Matrix Algebra Framework for the Multimedia Multipathway Modeling of Emission to Impacts
2.3 Selected approach
2.4 General framework for human health impacts
2.5 Illustrative example and detailed matrix interpretation for human health............... 32 2.5.1 The fate matrix
2.5.2 The exposure matrix
2.5.3 Intake fraction – combining fate and exposure matrix
2.5.4 The human health effects matrix
2.5.5 The damage matrix
2.5.6 The human damage matrix
2.6 Application to Impacts on ecosystems
3 CKow – A More Transparent and Reliable Model for Chemical Transfer to Meat and Milk
VTable of Content
3.3.1 Carry Over Rate as the Metric of Biotransfer
3.3.2 Model description
4 Comparing and Analysing the Toxic Impact Characterisation Models IMPACT 2002, CalTOX, USES-LCA and EDIP
4.3.1 Comparison approach
4.3.2 Organic test set for non-dissociating and non-amphiphilic chemicals................. 71
4.4.1 Aquatic Ecotoxicity
4.4.2 Human health
4.5 Conclusions and recommendations
5 Identification and Quantification of Key Sources of Uncertainty for Large Sets of Chemicals
5.3.1 Chemical test set
5.3.2 Uncertainty distributions
5.3.3 Integrating regression model and parameter uncertainty
5.3.4 Analytical method using Taylor series expansion
5.3.5 Estimating uncertainties using representative GSD2 on main intermediary parameters
5.4.1 Integrating regression model and parameter uncertainty
5.4.2 Analytical approach using Taylor series expansion
5.4.3 Estimating uncertainties using representative GSD2 on main intermediary parameters
6 General Conclusions
List of Tables
List of Figures
Background on the fate matrix
Illustrative example: Heptachlor (CAS 76-44-8) fate
Human health effects model
General Matrix framework for ecotoxicity effects
Ecotoxicological effects model
Basic mass balance equations
Derivation of dynamic solution
Improvement of the exposure estimate by improving the COR
Measured concentrations and corresponding BTF and COR in milk from feeding experiments or mass balance studies
Measured concentrations and corresponding BTF and COR in meat from feeding experiments or mass balance studies
Background information on uncertainty distributions
Additional information on the Monte Carlo analysis and analytical approach............... 186 Publications
Research articles in peer reviewed journals/books:
Conference proceedings papers:
Conference presentations and posters:
The overall goal of this dissertation is to contribute to the development of best available practice in environmental multimedia fate and multipathway exposure modelling for human health and ecosystem impacts, addressing several important aspects.
Environmental multimedia models relate environmental emissions to impacts (or risk factors) combining multimedia fate and multipathway exposure estimates with effect assessment data.
Many organic chemicals formed in combustion and released to air as well as organic chemicals released to air, water, and soil from industrial activities enter humans primarily through food--in particular through meat and dairy products. Therefore, food chain modelling is of utmost importance for human exposure assessment. Model comparison and quantification of uncertainties of model results are vital for their correct interpretation.
This leads to the following questions:
1. How would a model framework be structured favouring flexibility, transparency, comparability, interpretability, without limiting the capabilities of the model parts?
2. How can carry-over modelling of chemical biotransfer into biota such as meat or milk be improved considering limited data availability and high uncertainties?
3. How can environmental multimedia multipathway models be compared in a systematic and detailed way, and what are important sources of differences?
4. How to identify important sources of uncertainty in a model result, including regression models used for estimation and when modelling large sets of chemicals?
In order to answer that, the following specific goals are addressed:
1. Develop a consistent matrix algebra framework for multimedia fate, multipathway exposure and toxicity effects models.
2. Review existing biotransfer models for chemical transfer into meat and milk and develop, compare and evaluate an improved carry-over model for meat and milk.
3. Compare selected multimedia fate, multipathway exposure and toxicity effects models on the level of final characterisation factors as well as for intermediate results.
4. Develop and test approaches to assess the uncertainty of model results accounting for regression model uncertainty and main parameters contributing to overall uncertainty.
Chapter 1 puts this dissertation into its context and introduces multimedia fate, multipathway exposure and human health and ecosystem effects modelling with a focus on the food chain exposure in the frame of comparative risk and Life Cycle Impact Assessment.
Chapter 2 presents a framework for multimedia multipathway models entirely based on matrix algebra. When assessing human health or ecosystem impacts of chemicals several calculation steps need to be addressed. We suggest a matrix algebra framework which includes the fate, exposure, effect, and damage assessment for human health and ecosystems, also applicable to spatial modelling. Special emphasis is laid upon interpretation of the physical meaning of different elements within the matrices.
Chapter 3 describes the development, comparison and evaluation of an improved carry-over model for chemical transfer into meat and milk. The objective of this study is to increase the reliability and transparency of chemical biotransfer modelling into meat and milk and explicitly confront the uncertainties in exposure assessments of chemicals that require such estimates. To address this we developed a dynamic three compartment cow model (called CKow), able to distinguish lactating and non-lactating cows, to more accurately track the transport of a chemical into meat fat and milk within the cow. Using the CKow model as base model we derived a simplified model proposing an improved, less uncertain regression model to predict COR for meat and milk based on Kow.
Chapter 4 is a detailed comparison of four characterisation methods used in LCIA. The main objective was to investigate whether or not the models’ results agree with each other in terms of ranking as well as in absolute values and identify where differences come from. A comparison of characterisation factors and intermediate results of IMPACT 2002, CalTOX, USES-LCA, and EDIP97 has been performed for generic organic compounds. The comparison procedure was undertaken in three tiers: 1) comparison of available published factors, 2) calculated factors based on the harmonised chemical test set and 3) an in depth comparison revealing differences of the models on the level of processes and algorithms.
Chapter 5 explores possibilities to estimate the uncertainty of results from multimedia fate and multipathway exposure models and to account for regression model uncertainty.
Quantification and communication of uncertainties related to model results is vital for their correct interpretation and use. We explore and compare approaches to identify and quantify main sources of uncertainty, enabling to focus the data acquisition for the uncertainty assessment, especially when modelling large sets of chemicals.
Chapter 6 presents general conclusions, wrapping up the achievements of this dissertation and answering the scientific questions raised above.
Keywords: life cycle impact assessment (LCIA), environmental risk assessment (ERA), environmental multimedia modelling, chemical fate, human exposure, human toxicity, ecotoxicity, matrix algebra, spatial differentiation, biotransfer factor (BTF), carry over rate (COR), cow, cattle, milk, meat, intake fraction, model comparison, uncertainty analysis
Das Hauptziel dieser Dissertation ist es, zur Weiterentwicklung der Besten Verfügbaren Technik in Umwelt-, Multimediaausbreitungs- und Multiexpositionswegemodellierung von Umwelteinflüssen auf menschliche Gesundheit und Ökosysteme beizutragen.
Multimediale Umweltmodelle beziehen Umwelteinflüsse auf Emissionen, indem sie die Ausbreitung in Umweltmedien und die Exposition über verschiedenste Wege zum Menschen berücksichtigen und mit toxikologischen Effektdaten kombinieren. Viele organische Stoffe, die bei Verbrennungen in die Luft gelangen, sowie organische Verbindungen, die aus Industrieanlagen in die Luft, das Wasser und den Boden gelangen, werden vom Menschen primär über die Nahrung aufgenommen – im besonderen mit Fleisch und Milchprodukten.
Daher ist die Modellierung der Exposition über die Nahrungskette ein sehr wichtiges Element der Humanexpositionsanalyse. Modellvergleich und die Quantifizierung von Unsicherheiten von Modellergebnissen ist von großer Bedeutung für deren korrekte Interpretation.
Das führt zu folgenden Fragestellungen: