SCK•CEN authors are displayed in bold
| Title: | Evaluation of the environmental risk associated with the radiological liquid discharges from the Belgian nuclear power plants |
| Author(s): | Vandenhove, Hildegarde Sweeck, Lieve Van Hees, May Wannijn, Jean |
| Keywords: | evaluation environmental risk radiological liquid Belgian nuclear power plants |
| Issue Date: | 30-Jun-2010 |
| Publisher: | SCK•CEN, Mol, Belgium |
| Publication type: | Report |
| Citation: | Vandenhove H., Sweeck L., Van Hees M., Wannijn J.- Evaluation of the environmental risk associated with the radiological liquid discharges from the Belgian nuclear power plants.- Mol, Belgium: SCK•CEN, 2010.- 64 p.- (External Report of the Belgian Nuclear Research Centre; ER-132).- ISSN 1782-2335 |
| Series/Report no.: | External Report of the Belgian Nuclear Research Centre |
| Abstract: | SCK•CEN has been commissioned by Electrabel (GDF-Suez) to perform an environmental impact and risk assessment resulting from the liquid radioactive discharges from the Belgian Nuclear Power Plants (NPP) of Doel and Tihange. Present report provides the results of the dose and risk assessments based on the methodology presented in Deliverable 2. Environmental risk assessments were performed for the radiological discharge limits for the Doel and Tihange NPP and for the actual releases (maxima and averages over last 10 years 1999-2008) for these power plants. Environmental media concentrations for these situations were predicted following a conservative box-dilution approach and a more realistic approach using the Schaeffer model. The predicted concentrations are compared with monitoring results for the River Meuse and Scheldt obtained under the surveillance programme of the Federal Agency of Nuclear Control (FANC/AFCN). Only for a few radionuclides, sediment concentrations above the detection limits were measured. Comparison of these measurements with the predicted values show that most measured concentrations in sediment lie between those predicted by the box dilution river model (about 10 times higher) and those predicted by the Schaeffer river model at the sampling location. The Schaeffer river model takes into account more river processes. |
| Persistent URL: | http://hdl.handle.net/10038/7214  |
| ISSN: | 1782-2335 |
| SCK•CEN Report Number: | ER-132 |
| Attachments: |
Items in this repository are protected by copyright, with all rights reserved, unless otherwise indicated.