UK Public Private Partnerships and the Credit Crunch: A Case of Risk Contagion?

During the past twenty years, the UK has relied heavily on Public Private Partnerships (PPP) and especially the Private Finance Initiative in the procurement of infrastructure and services. Discussing the causes of the credit crunch and its effects on PPP, this paper notes that the provision of new public sector infrastructure and related services has been adversely affected by the impact of the credit crunch on Private Finance Initiatives (PFIs). These problems have arisen primarily from the unwillingness of commercial banks to replace collapsed PFI bond financing unless new PFI contracts reduce financial risks; which, in turn, is likely to increase the cost of these projects to the public sector. Additional financial strains have arisen for the UK government from the need to bail out collapsed PFI projects. Overall we find evidence that the UK commitment to PFI has not only increased immediate fiscal pressures on the UK when these have become least palatable, but has also created fiscal vulnerabilities at local and national levels which are likely to hamper the country’s ability to launch counter-cyclical responses to the ongoing crisis.

Non-parametric bill of quantities estimation of concrete road bridges' superstructure: an artificial neural networks approach

Bridge construction responds to the need for environmentally friendly design of motorways and facilitates the passage through sensitive natural areas and the bypassing of urban areas. However, according to numerous research studies, bridge construction presents substantial budget overruns. Therefore, it is necessary early in the planning process for the decision makers to have reliable estimates of the final cost based on previously constructed projects. At the same time, the current European financial crisis reduces the available capital for investments and financial institutions are even less willing to finance transportation infrastructure. Consequently, it is even more necessary today to estimate the budget of high-cost construction projects -such as road bridges- with reasonable accuracy, in order for the state funds to be invested with lower risk and the projects to be designed with the highest possible efficiency. In this paper, a Bill-of-Quantities (BoQ) estimation tool for road bridges is developed in order to support the decisions made at the preliminary planning and design stages of highways. Specifically, a Feed-Forward Artificial Neural Network (ANN) with a hidden layer of 10 neurons is trained to predict the superstructure material quantities (concrete, pre-stressed steel and reinforcing steel) using the width of the deck, the adjusted length of span or cantilever and the type of the bridge as input variables. The training dataset includes actual data from 68 recently constructed concrete motorway bridges in Greece. According to the relevant metrics, the developed model captures very well the complex interrelations in the dataset and demonstrates strong generalisation capability. Furthermore, it outperforms the linear regression models developed for the same dataset. Therefore, the proposed cost estimation model stands as a useful and reliable tool for the construction industry as it enables planners to reach informed decisions for technical and economic planning of concrete bridge projects from their early implementation stages.

Evolving techniques for characterising and monitoring the stability of infrastructure slopes

Landslides and debris flows, commonly triggered by rainfall, pose a geotechnical risk causing disruption to transport routes and incur significant financial expenditure. With infrastructure maintenance budgets becoming ever more constrained, this paper provides an overview of some of the developing methods being implemented by Queen’s University, Belfast in collaboration with the Department for Regional Development to monitor the stability of two distinctly different infrastructure slopes in Northern Ireland. In addition to the traditional, intrusive ground investigative and laboratory testing methods, aerial LiDAR, terrestrial LiDAR, geophysical techniques and differential Global Positioning Systems have been used to monitor slope stability. Finally, a comparison between terrestrial LiDAR, pore water pressure and soil moisture deficit (SMD) is presented to outline the processes for a more informed management regime and to highlight the season relationship between landslide activity and the aforementioned parameters.

Research-informed design, management and maintenance of infrastructure slopes: development of a multi-scalar approach

The UK’s transport infrastructure is one of the most heavily used in the world. The performance of these networks is critically dependent on the performance of cutting and embankment slopes which make up £20B of the £60B asset value of major highway infrastructure alone. The rail network in particular is also one of the oldest in the world: many of these slopes are suffering high incidents of instability (increasing with time). This paper describes the development of a fundamental understanding of earthwork material and system behaviour, through the systematic integration of research across a range of spatial and temporal scales. Spatially these range from microscopic studies of soil fabric, through elemental materials behaviour to whole slope modelling and monitoring and scaling up to transport networks. Temporally, historical and current weather event sequences are being used to understand and model soil deterioration processes, and climate change scenarios to examine their potential effects on slope performance in futures up to and including the 2080s. The outputs of this research are being mapped onto the different spatial and temporal scales of infrastructure slope asset management to inform the design of new slopes through to changing the way in which investment is made into aging assets. The aim ultimately is to help create a more reliable, cost effective, safer and more resilient transport system.

Using administrative data to understand mental health in Northern Ireland:Results from two exemplar projects

Mental health is unevenly distributed in the Northern Ireland population. Administrative data on psychotropic medication prescribing is increasingly being used in research into population mental health. This paper illustrates how these data indicate concentrations of poor mental health in Northern Ireland, e.g. within deprived neighbourhoods, at interfaces, among older persons admitted to care homes and among persons bereaved through sudden death or suicide. This briefing also aims to widen the debate about mental health from a disorder/service paradigm to a whole population approach.