Describes a tracer model, DREAM (the Danish Rimpuff and Eulerian Accidental release Model), developed for studying transport, dispersion, and deposition of air pollution caused by a single but strong source. The model is based on a combination of a Lagrangian short‐range puff model and a Eulerian long‐range transport model. It has been run and validated against measurements from the two European Tracer Experiment (ETEX) releases and from the Chernobyl accident. An air pollution forecast system, THOR, is under development, to make forecasts of various air pollutants on a European scale. Some preliminary results are shown. DREAM will be implemented in THOR for calculations of real time predictions of transport, dispersion and deposition of radioactive material from accidental releases (e.g. Chernobyl). Some applications of the DREAM model and examples of model results are described.
Skip Nav Destination
Article navigation
1 October 1999
This article was originally published in
Environmental Management and Health
Article Contents
Research Article|
October 01 1999
Real time predictions of transport, dispersion and deposition from nuclear accidents Available to Purchase
Jørgen Brandt;
Jørgen Brandt
National Environmental Research Institute, Department of Atmospheric Environment, Roskilde, Denmark
Search for other works by this author on:
Jesper H. Christensen;
Jesper H. Christensen
National Environmental Research Institute, Department of Atmospheric Environment, Roskilde, Denmark
Search for other works by this author on:
Zahari Zlatev
Zahari Zlatev
National Environmental Research Institute, Department of Atmospheric Environment, Roskilde, Denmark
Search for other works by this author on:
Publisher: Emerald Publishing
Online ISSN: 1758-7085
Print ISSN: 0956-6163
© MCB UP Limited
1999
Environmental Management and Health (1999) 10 (4): 216–223.
Citation
Brandt J, Christensen JH, Zlatev Z (1999), "Real time predictions of transport, dispersion and deposition from nuclear accidents". Environmental Management and Health, Vol. 10 No. 4 pp. 216–223, doi: https://doi.org/10.1108/09566169910276058
Download citation file:
Sign in
Don't already have an account? Register
ICE Member Sign In
Log inPurchased this content as a guest? Enter your email address to restore access.
Please enter valid email address.
Pay-Per-View Access
$39.00
Rental
This article is also available for rental through DeepDyve.
260
Views
Suggested Reading
Improving Forecasting Accuracy through Trading Day Adjustment
International Journal of Operations & Production Management (January,1989)
EMMA model: an advanced operational mesoscale air quality model for urban and regional environments
Environmental Management and Health (October,1999)
Consensus Forecasting Using Relative Error Weights
Marketing Intelligence & Planning (February,1994)
Using Demand Forecasting Models
Marketing Intelligence & Planning (March,1987)
A mathematical model for modal shift to minimize NOx emissions
Integrated Manufacturing Systems (April,2000)
Related Chapters
A Novel Approach to Forecasting Regression and Cluster Analysis
Advances in Business and Management Forecasting
Development of a Practical and Effective Forecasting Performance Measure
Advances in Business and Management Forecasting
Construction
Sustainable Infrastructure: Principles into Practice
Recommended for you
These recommendations are informed by your reading behaviors and indicated interests.
