Use this URL to cite or link to this record in EThOS:
Title: RADPOP : a new modelling framework for radiation protection
Author: Alexis-Martin, Becky
ISNI:       0000 0004 6347 7009
Awarding Body: University of Southampton
Current Institution: University of Southampton
Date of Award: 2017
Availability of Full Text:
Access from EThOS:
Full text unavailable from EThOS. Please try the link below.
Access from Institution:
Ionising radiation is often useful to our society, and has been implemented for medicine, industry, energy generation and defence. However, nuclear and radiation accidents have the capacity to have a negative impact upon humans and may have a long-lasting legacy due to challenges associated with remediation and the slow decay of radionuclides. It is therefore a priority to ensure that there is adequate emergency preparedness, to prevent and manage any accidental release of ionising radiation to the communities that surround nuclear installations (NI). The emergency planning process includes desktop studies and exercises which are designed to examine the impact of hypothetical scenarios in real-time. However, greater spatiotemporal realism is required to understand the scale of a hypothetical radiation exposure to specific populations in space and time, to anticipate how the behaviour of the population will affect the outcome of an emergency, and to determine the strategy required for its management. This thesis presents a new modelling framework for radiation protection, called RADPOP. This framework combines spatiotemporal aggregate population density subgroup estimates with radionuclide plume dispersal modelling and agent-based modelling, to begin to understand how changes in spatiotemporal population density can influence the likelihood of exposure. Whilst sophisticated estimates of meteorological and atmospheric dispersal exist, there limited resources for the production of equivalent and contemporary high-resolution spatiotemporal population statistics. There is also no existing modelling framework for radiation protection and emergency preparedness, which implements spatiotemporal population estimates to understand the subsequent movement of an aggregate population, as it seeks shelter during a radiation emergency. This thesis investigates these challenges with focus upon the female population subgroup, as a group which has been identified in the literature as having greater vulnerability during evacuation.
Supervisor: Cockings, Samantha ; Martin, David Sponsor: Not available
Qualification Name: Thesis (Ph.D.) Qualification Level: Doctoral
EThOS ID:  DOI: Not available