Background
In Environmental Risk Assessment, mathematical models are used to estimate exposure, effects and risk to biota. The vast majority of ERA conducted to date relied on a deterministic approach in which point estimates of exposure and effects were combined to produce a single estimate of risk. By making liberal use of conservative assumptions and uncertainty factors, the hope is that the resulting estimate of risk (usually termed the quotient) will have a very low probability of mistakenly stating that there is no effect when one is occurring. The consequences of this conservative approach are that limited resources are often used to manage chemicals that pose little or no threat to the environment.
Objectives
Proposals
Proposals submitted for consideration should follow the format of the application form'Application for a CEFIC-LRI Grant' and should address the following areas under individual sub-headings:
The title of the research.
The name of the principal investigator and laboratory or laboratories in which the research will be conducted.
Evidence of the principal investigator”˜s knowledge of, and contributions to, sensitivity and uncertainty analysis and probablistic risk assessment.
A clear definition of the research objectives, including a detailed proposal for the proposed approach.
A detailed plan of the investigation, including a clearly defined milestone plan which identifies all critical decision points in the research programme.
A detailed breakdown of costs.
Monitoring
The successful applicant(s) will be required to submit a progress report every 6 months during the course of the programme. At the end of the project a detailed review of the project and the achievements made will be provided by the principal investigator. The successful applicant or applicants will also be required to prepare for publication a manuscript describing the work undertaken and the results achieved.
Scope
The uncertainties inherent in assessments that estimate the effects of chemical stressors on biota are numerous. Their existence has long been recognised by ERA practitioners, however, to date few assessments have attempted to explicitly quantify the uncertainties and determine their consequences for effective environmental decision making. This is in spite of the recognised value of uncertainty analysis methods for improving environmental decision making and the existence of many methods for propagating uncertainties (e.g., Monte Carlo methods, Bayesian techniques). Uncertainty analysis methods have a long history of use in other fields such as safety assessments of nuclear reactors, design and manufacture of appliances and household products, and various engineering applications. The chemical industry recognises that part of the reason why few ERA have been probabilistic to date is due to the lack of appropriate guidance for selecting and using methods to propagate uncertainties, and the lack of statistical expertise amongst ERA practitioners.
Specific tasks to be addressed in the research include:
Reviewing existing software for uncertainty analysis methods and evaluate their'fitness' for use, identify methodological gaps, availability and ease of use and make recommendations on software development that needs to take place to ensure that practitioners have the necessary and valid tools for carrying out probabilistic risk assessments.
Development of toolbox that will fill the methodological gaps, and implementation of methodology into an easy-to-use software package.
Reviewing existing sources of information useful in developing distributions for input variables generically used in ERA of chemicals.
Conduct of case studies that illustrate and compare the various methods for quantifying uncertainty for scenarios of relevance to CMA / CEFIC.
Development of a guidance manual for ERA practitioners on how to quantify uncertainty in ERA and use the knowledge gained from such analyses to ensure effective decision making.
Training risk assessors and managers in the CMA, CEFIC and in the appropriate regulatory agencies on the use of uncertainty analysis methods in ERA.
