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EEM6-UCRA: Constructing a Sediment Exposure Module in GREAT-ER

Principal Investigator

Dr. Susan White
Institute of Water and Environment
University of Cranfield
Silsoe
UK - MK45 4DT Beds
sue.white@cranfield.ac.uk
Tel: +44 152 586 31 40
Fax: +44 152 586 33 44

Collaborators

Dr. Fred Worrall - Department of Earth Sciences - University of Durham
fred.worrall@durham.ac.uk
LRI Monitor:
Dr Mick Whelan - Unilever
mick.whelan@unilever.com

Description

Assessment of chemical exposure in sediments is part of the current TGD and is encapsulated in EUSES. In order to convince regulators that GREAT-ER provides an exposure assessment methodology which is at least equivalent to EUSES (in terms of sophistication) in several environmental compartments, an explicit exposure assessment in sediments is required. Currently GREAT-ER produces a prediction of total (adsorbed and dissolved) concentration but the user cannot assess sediment-associated chemical concentrations (suspended or settled). An explicit prediction of the partitioning of chemical between the dissolved, suspended sediment and bed-sediment phases will also provide enhanced input to the LRI estuary model (GEMCO). More specifically, it will provide a more realistic distribution of the flux of sediment associated pollutants to estuaries. This study will define the form of suspended sediment concentration distributions in rivers in the form of probability distribution functions (pdfs) for inclusion in the GREAT-ER 2.0 software package. Furthermore linkage between river flow or other catchment descriptors will be linked to expected sediment pdfs to allow users to define pdfs for a particular river in the absence of any monitored sediment data. Within the river network the movement of a wide range of contaminants often occurs via sediment movement. Contaminants may themselves be particulate in form or may bind to sediment particles at some point in their journey from land to river to estuary. Often, contaminants bound to sediments will form the major part of the contaminant load. It is thus important that sediment concentrations are consistently and accurately represented within any computer models which study contaminant movement and accumulation. This study will add an enhanced sediment component to an existing software package, GREAT-ER 2.0, the river modeling component of a range of contaminant risk assessment models which look at contaminant transfer to/from the atmosphere and through the land-river-estuary cycle. The study will also provide a simple means of assessing likely sediment concentrations for a particular river of interest using river flow and catchment characteristics.

Timeline: July 2004 > April 2005

LRI funding: € 21 410

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