Publications by authors named "M J Dowdall"

A detector's ability to obtain the direction of a radioactive source is an invaluable operational asset. A 2D/3D model was developed based on directionally sensitive arrays. The average location of photon interactions within a symmetrical array yields the direction of the source.

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Deployment of radiation detectors under field conditions for the purposes of security, safety or response has increased in recent years. Effective use of such instruments in the field necessitates careful consideration of the efficiency of the detector - both peak and total - at distances which may extend beyond 100 m. Difficulties in addressing the determination of both peak and total efficiencies across the energy range of interest and at long distances reduces the utility of such systems in effectively characterising radiation sources in the field.

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In-field measurements have particular challenges as compared with those conducted under laboratory conditions. Besides unknown source shielding, the source-detector distance varies and the detector orientation relative to the incident radiation is not necessarily constant. The incoming flux facing a detector is a parallel beam at long source-detector distances (>1 m).

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The Chernobyl nuclear power meltdown that took place in 1986 has left a radioactive contamination legacy that currently severely limits the economic potential of impacted regions including the Polessie State Radioecology Reserve in Southern Belarus. Extensive areas of forested land could potentially become economically viable for firewood and building materials if radioactive contamination, notably Cs, could be characterised faster, whilst closely adhering to regulatory limits. Currently, laboursome tree coring and unreliable transfer factors derived from limited soil sampling data are routinely employed in felling decision making, which has financial repercussions owed to the large amounts of waste produced and unnecessary transportation costs.

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Measurements of external contaminant exposures on individual wildlife are rare because of difficulties in using contaminant monitors on free-ranging animals. Most wildlife contaminant exposure data are therefore simulated with computer models. Rarely are empirical exposure data available to verify model simulations, or to test fundamental assumptions inherent in exposure assessments.

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