On the environmental valuation of catastrophe: revisiting mining disasters in the United Kingdom, 1851-1962

In the context of environmental valuation of natural disasters, an important component of the evaluation procedure lies in determining the periodicity of events. This paper explores alternative methodologies for determining such periodicity, illustrating the advantages and the disadvantages of the separate methods and their comparative predictions. The procedures employ Bayesian inference and explore recent advances in computational aspects of mixtures methodology. The procedures are applied to the classic data set of Maguire et al (Biometrika, 1952) which was subsequently updated by Jarrett (Biometrika, 1979) and which comprise the seminal investigations examining the periodicity of mining disasters within the United Kingdom, 1851-1962.

A methodology to measure the environmental impact of ICT operating systems across different device platforms

Abstract: A new methodology was created to measure the energy consumption and related green house gas (GHG) emissions of a computer operating system (OS) across different device platforms. The methodology involved the direct power measurement of devices under different activity states. In order to include all aspects of an OS, the methodology included measurements in various OS modes, whilst uniquely, also incorporating measurements when running an array of defined software activities, so as to include OS application management features. The methodology was demonstrated on a laptop and phone that could each run multiple OSs, results confirmed that OS can significantly impact the energy consumption of devices. In particular, the new versions of the Microsoft Windows OS were tested and highlighted significant differences between the OS versions on the same hardware. The developed methodology could enable a greater awareness of energy consumption, during both the software development and software marketing processes.

Aspects of particle filtering in high-dimensional spaces

Nonlinear data assimilation is high on the agenda in all fields of the geosciences as with ever increasing model resolution and inclusion of more physical (biological etc.) processes, and more complex observation operators the data-assimilation problem becomes more and more nonlinear. The suitability of particle filters to solve the nonlinear data assimilation problem in high-dimensional geophysical problems will be discussed. Several existing and new schemes will be presented and it is shown that at least one of them, the Equivalent-Weights Particle Filter, does indeed beat the curse of dimensionality and provides a way forward to solve the problem of nonlinear data assimilation in high-dimensional systems.

Biodiversity and green open space

Biodiversity has been defined as the totality of genes, species, and ecosystems that inhabit the earth with the field contributing to many aspects of our lives and livelihoods by providing us with food, drink, medicines and shelter, as well as contributing to improving our surrounding environment. Benefits include providing life services through improved horticultural production, improving the business and service of horticulture as well as our environment, as well as improving our health and wellbeing, and our social and cultural relationships. Threats to biodiversity can include fragmentation, degradation and deforestation of habitat, introduction of invasive and exotic species, climate change and extreme weather events, over-exploitation of our natural resources, hybridisation, genetic pollution/erosion and food security issues and human overpopulation. This chapter examines a series of examples that provide the dual aims of biodiversity conservation and horticultural production and service; namely organic horticultural cropping, turf management, and nature-based tourism, and ways of valuing biological biodiversity such as the payment of environmental services and bio-prospecting. Horticulture plays a major role in the preserving of biodiversity.