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Earthquakes are amongst the worst natural disasters on Earth, resulting in an annual average of around 10,000 fatalities last century and progressively increasing in the amount of economic damage they cause, reaching US $20 billion per annum this decade. The mitigation of the unwanted consequences of earthquakes is normally achieved by Risk Management Strategies (RMS), which rely on the development of Earthquake Risk Assessment (ERA) techniques. This thesis aims to develop a framework for ERA for medium seismicity regions that incorporates the spatial aspects of the hazard and risk evaluation. The framework is used to undertake ERA for the island of Cyprus, and the information is used to propose RMS. The ERA framework relies on comprehensive data on the location, value and vulnerability of buildings and the population distribution. These data were collected from the various Cyprus Government Departments. Various hazard and attenuation models are examined, and the effect of their variability is taken into account through Monte Carlo simulations. The estimated annual risk for Cyprus is just below £ 10 million CY. This value was estimated based on the use of the re-appraised historical data for the past-century. Comparisons with other seismic hazard assessment methods, such as recurrence relationships, have revealed that, without a spatial distribution model, such approaches are unsuitable for ERA. Though the maximum intensities predicted are in line with the ones that underpin the aseismic code of Cyprus (CCEAA-CFEE, 1994), the predicted design accelerations are higher than given in the code. Hence, new seismic accelerations are proposed. Despite that, the current reduction in risk is comparable to the additional cost of aseismic design. Seismic retrofitting was also examined and it was found that as part of a general modernisation scheme seismic upgrading is cost effective. However, whatever the state of the building, it is recommended that earthquake insurance should be made mandatory. The current seismic insurance rates appear to be fair, though they seem to underestimate the risk in the areas of high seismicity. The number of likely human losses is also estimated. This study concludes that the result of ERA is heavily dependent on the models and data used, and both require constant updating for the ERA results to remain meaningful.

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The urban atmospheric environment contains a complex cocktail of pollution from numerous sources. However, the contribution to this mixture from power stations and other high-temperature combustion point sources is uncertain. Spheroidal carbonaceous particles (SCPs) and inorganic ash spheres (IASs) are uniquely formed as a by-product of high-temperature combustion of fossil fuels and therefore are ideal indicators of fossil-fuel derived pollution in London. Deposition of SCPs in London from power stations and other combustion processes regulated by the Environment Agencies under Part A of the Environment Act 1990 was modelled using the atmospheric dispersion modelling system (ADMS 3) developed by the Meteorological Office and the Cambridge Environmental Research Consultancy. The results agreed well with the spatial distribution of SCP concentrations in surface sediments from twenty-seven lakes and ponds within the M25. SCP size distributions were used to identify the dominant sources of SCPs for each site. Multivariate statistical analyses showed that lake and pond processes were generally not important variables affecting the concentration of SCPs in the surface sediments. High resolution SCP and IAS time-series collected by Burkard Spore Traps on a transect linking the centre of London with the power stations in the east Thames Corridor showed the presence of several pollution events, both SCP and IAS, that occurred simultaneously at a number of sites. Potential sources were identified for each IAS and SCP event based on SCP size data and meteorological conditions. The relationship between the IAS and SCP concentrations indicated whether the event was caused by a coal- or oil-fired source. Multivariate statistical analyses of the meteorological data did not consistently extract any one variable that would explain the SCP and IAS profiles. However, a subjective analysis of the data shows that many IAS events in London are caused by emissions from the power stations in the east Thames Corridor.