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Discharges of dust from NORM facilities: Key parameters to assess effective doses for public exposure

Kunze Christian, Schulz Hartmut, Ettenhuber Eckard, Schellenberger Astrid, Dilling Jorg

Journal of Sustainable Mining

2019

Vol. 18, iss. 1

31--37

In transposing Directive 2013/59/Euratom (European Basic Safety Standards or EU BSS) into national law, it was necessary to identify industrial sectors which involve naturally occurring radioactive materials (NORM) which may lead to public exposure that cannot be disregarded from a radiation protection point of view. A research project was implemented that resulted in a comprehensive survey of all potentially relevant industrial sectors operating in Germany. Major efforts were made to determine source terms of airborne discharges, atmospheric dispersion models, and dose calculations. The study arrived at the conclusion that the discharge and the settlement of dust in agricultural and horticultural areas is the most relevant dispersion and exposure pathway, while discharges of radon are of minor importance. The original study used a number of rather complex models that may distract from the fact that very few key parameters and assumptions determine the effective dose of members of the public. This paper revisits the study and identifies those parameters and assumptions and provides a simplified, generic, yet sufficiently reliable and robust assessment methodology to determine the radiological relevance of dust discharges from NORM industries under the typical geographical and meteorological conditions of Germany. This paper provides examples of dose estimates for members of the public for selected industries operating in Germany. Due to its simplicity and robustness, the methodology can also be used to assess effective doses resulting from discharges in other industries in Germany, and it can be adapted to conditions in other countries in a straightforward way.

Recognition of the atmospheric contamination source localization with the Genetic Algorithm

Wawrzynczak A., Jaroszynski M., Borysiewicz M.

Studia Informatica : systems and information technology

2015

Vol. 1-2(19)

27--42

We have applied the Genetic Algorithm (GA) to the problem of the atmospheric contaminant source localization. The algorithm input data are concentrations of given substance registered by sensor network. To achieve rapid-response event reconstruction,the fast-running Gaussian plume dispersion model is adopted as the forward model. The proposed GA scans 5-dimensional parameters space searching for the contaminant source coordinates (x,y), release strength (Q) and the atmospheric transport dispersion coefficients. Based on the synthetic experiment data the GA parameters like population size, number of generations and the genetic operators best suitable for the algorithm performance are identified. We demonstrate that proposed GA configuration can successfully point out the parameters of abrupt contamination source. Results indicate the probability of a source to occur at a particular location with a particular release rate. The shapes of the probability distribution function of searched parameters values reflect the uncertainty in observed data.