Australia's country towns 2050: what will a climate adapted settlement pattern look like?

Abstract This report considers the impact of anticipated climate change on Australia’s inland towns and centres to the year 2050. It examines the ways in which non-coastal settlements will be affected by the primary, secondary and tertiary impacts of climate change, including the impact of extreme climate events, a warming and drying climate over much of southern Australia and increased costs associated with both structural economic change and accelerated degradation of infrastructure. The research finds that climate change is likely to have a wide range of impacts on Australia’s system of inland settlement and that not all of these impacts are likely to be adverse. The published literature highlights the fact that some industries – including wool production, grains, viticulture and some grazing – are likely to benefit from climate change. While this is not the case in all instances, the fact that some industries will be enhanced runs contrary to both commonly held expectations and public discourse. In other sectors of the economy and society, technological change and/or investment in infrastructure will overcome many of the climate-change related challenges that have the potential to place the wellbeing of inland centres at risk. This project found that rural and regional centres across Australia will be affected by climate change in different ways, depending upon: Their industry structure; Their geographic location, especially their degree of remoteness; Their climatic conditions now and in the year 2030; and, The resource endowments of communities – and especially their stock of human, social, physical, fiscal and economic capital. The project reviewed the national and international literature on climate change adaptation to consider the vulnerability of individual inland centres. A vulnerability index was developed that was able to distinguish places that are more, and less, vulnerable to the negative impacts of climate change. This analysis was undertaken as a first step toward better understanding the differential impacts of climate change on the inland settlement system, and with a full awareness of the critiques of such approaches. The modelling highlighted that places that are remote confront some of the greatest risks from climate change, and that many – but not all – Indigenous communities are especially vulnerable. Detailed field work was undertaken in five case studies across Australia – Alice Springs, NT; Junee, NSW; Horsham, Victoria; Waikerie, South Australia; Moura, Queensland – in order to understand the steps taken by inland centres to plan and prepare for climate change. The research found that many persons within rural and regional communities do not accept that human-induced climate change is a reality, and that in consequence preparations for change are patchy. However, in many rural economies contemporary ‘good practice’ in farming or grazing is entirely consistent with the measures needed to plan for climate change. The fieldwork also highlighted the fact that while it is possible to model the potential impact of climate change, such measures overlook the commitment and willingness of groups to address this challenge. Finally, we conclude that climate change will contribute to the shifting nature of Australia’s inland settlement system to the year 2050 but that it will be just one of a number of factors contributing to change. Other factors, including global markets, demographic change, the relative prosperity of individual industries, and the investment decisions of government will be important also. Please cite this report as: Beer, A, Tually, S, Kroehn, M, Martin, J, Gerritsen, R, Taylor, M, Graymore, M, and Law, J, 2013, Australia’s country towns 2050: What will a climate adapted settlement pattern look like? National Climate Change Adaptation Research Facility, Gold Coast, pp.139.Abstract This report considers the impact of anticipated climate change on Australia’s inland towns and centres to the year 2050. It examines the ways in which non-coastal settlements will be affected by the primary, secondary and tertiary impacts of climate change, including the impact of extreme climate events, a warming and drying climate over much of southern Australia and increased costs associated with both structural economic change and accelerated degradation of infrastructure. The research finds that climate change is likely to have a wide range of impacts on Australia’s system of inland settlement and that not all of these impacts are likely to be adverse. The published literature highlights the fact that some industries – including wool production, grains, viticulture and some grazing – are likely to benefit from climate change. While this is not the case in all instances, the fact that some industries will be enhanced runs contrary to both commonly held expectations and public discourse. In other sectors of the economy and society, technological change and/or investment in infrastructure will overcome many of the climate-change related challenges that have the potential to place the wellbeing of inland centres at risk. This project found that rural and regional centres across Australia will be affected by climate change in different ways, depending upon: Their industry structure; Their geographic location, especially their degree of remoteness; Their climatic conditions now and in the year 2030; and, The resource endowments of communities – and especially their stock of human, social, physical, fiscal and economic capital. The project reviewed the national and international literature on climate change adaptation to consider the vulnerability of individual inland centres. A vulnerability index was developed that was able to distinguish places that are more, and less, vulnerable to the negative impacts of climate change. This analysis was undertaken as a first step toward better understanding the differential impacts of climate change on the inland settlement system, and with a full awareness of the critiques of such approaches. The modelling highlighted that places that are remote confront some of the greatest risks from climate change, and that many – but not all – Indigenous communities are especially vulnerable. Detailed field work was undertaken in five case studies across Australia – Alice Springs, NT; Junee, NSW; Horsham, Victoria; Waikerie, South Australia; Moura, Queensland – in order to understand the steps taken by inland centres to plan and prepare for climate change. The research found that many persons within rural and regional communities do not accept that human-induced climate change is a reality, and that in consequence preparations for change are patchy. However, in many rural economies contemporary ‘good practice’ in farming or grazing is entirely consistent with the measures needed to plan for climate change. The fieldwork also highlighted the fact that while it is possible to model the potential impact of climate change, such measures overlook the commitment and willingness of groups to address this challenge. Finally, we conclude that climate change will contribute to the shifting nature of Australia’s inland settlement system to the year 2050 but that it will be just one of a number of factors contributing to change. Other factors, including global markets, demographic change, the relative prosperity of individual industries, and the investment decisions of government will be important also

Bootstrapping a hedonic price index: experience from used cars data

Every hedonic price index is an estimate of an unknown economic parameter. It depends, in practice, on one or more random samples of prices and characteristics of acertain good. Bootstrap resampling methods provide atool for quantifying sampling errors. Following some general reflections on hedonic elementary price indices, this paper proposes acase-based, amodel-based, and awild bootstrap approach for estimating confidence intervals for hedonic price indices. Empirical results are obtained for adata set on used cars in Switzerland. Asimple and an enhanced adaptive semi-logarithmic model are fit to monthly samples, and bootstrap confidence intervals are estimated for Jevons-type hedonic elementary price indice

Lower-rim ferrocenyl substituted calixarenes: new electrochemical sensors for anions

New ferrocene substituted calix[4 and 5]arenes have been prepared and the crystal structure of a lower-rim substituted bis ferrocene calix[4]arene (7) has been elucidated. The respective ferrocene/ferrocenium redox-couples of compounds 6 (a calix[4]arene tetra ferrocene amide) and 8 (a calix[5]arene pentaferrocene amide) are shown to be significantly cathodically perturbed in the presence of anions by up to 160 mV in the presence of dihydrogen phosphate

Risk Assessment of Spent Nuclear Fuel Facilities Considering Climate Change

Natural hazards have the capability to affect technological installations, triggering multiple failures and putting the population and the surrounding environment at risk. Global climate change introduces an additional and not negligible element of uncertainty to the vulnerability quantification, threatening to intensify (both in terms of frequency and severity) the occurrence of extreme climate events. Sea level extremes and extreme coastal high waters are expected to change in the future as a result of both changes in atmospheric storminess and mean sea level rise, as well as extreme precipitation events. These trends clearly suggest a parallel increase in the risks affecting technological installations and the subsequent need for mitigation measures to enhance the reliability of existing systems and to improve the design standards of new facilities. In spite of this situation, the scientific research in this field lacks robust and reliable tools for this kind of assessment, often relying on the adoption of oversimplified models or strong assumptions, which affect the credibility of the results. The main purpose of this study is to provide a novel and general model for the evaluation of the risk of exposure of spent nuclear fuel stored in a facility subject to flood hazard, investigating the potential and limitations of Bayesian networks (BNs) in this field. The network aims to model the interaction between extreme weather conditions and the technological installation, as well as the propagation of failures within the system itself, taking into account the dependencies among the different components and the occurrence of human error. A real-world application concerning the nuclear power station of Sizewell B in East Anglia, in the United Kingdom, is extensively described, together with the models and data set used. Results are presented for three different time scenarios in which climate change projections have been adopted to estimate future risk

Robust vulnerability analysis of nuclear facilities subject to external hazards

Natural hazards have the potential to trigger complex chains of events in technological installations leading to disastrous effects for the surrounding population and environment. The threat of climate change of worsening extreme weather events exacerbates the need for new models and novel methodologies able to capture the complexity of the natural-technological interaction in intuitive frameworks suitable for an interdisciplinary field such as that of risk analysis. This study proposes a novel approach for the quantification of risk exposure of nuclear facilities subject to extreme natural events. A Bayesian Network model, initially developed for the quantification of the risk of exposure from spent nuclear material stored in facilities subject to flooding hazards, is adapted and enhanced to include in the analysis the quantification of the uncertainty affecting the output due to the imprecision of data available and the aleatory nature of the variables involved. The model is applied to the analysis of the nuclear power station of Sizewell B in East Anglia (UK), through the use of a novel computational tool. The network proposed models the direct effect of extreme weather conditions on the facility along several time scenarios considering climate change predictions as well as the indirect effects of external hazards on the internal subsystems and the occurrence of human error. The main novelty of the study consists of the fully computational integration of Bayesian Networks with advanced Structural Reliability Methods, which allows to adequately represent both aleatory and epistemic aspects of the uncertainty affecting the input through the use of probabilistic models, intervals, imprecise random variables as well as probability bounds. The uncertainty affecting the output is quantified in order to attest the significance of the results and provide a complete and effective tool for risk-informed decision making

Experimental approach to measuring functional food consumption for risk factor surveillance

Abstract Objective To develop and integrate the assessment of functional foods (FuF; manufactured foods with altered composition carrying a health claim) consumption into an existing risk factor surveillance system. Design FuF market research followed by an experimental FuF intake study incorporated into an ongoing community-based survey. Concurrent completion of a self-administered semi-quantitative FFQ and a self-administered, qualitative FuF frequency questionnaire (FuFFQ) followed by a face-to-face control step using FuF photographs and combined food group-based data analyses. Setting ‘Bus Santé' risk factor surveillance programme, Geneva/Switzerland. Subjects Population-based random sample of 639 residents (52 % women, aged 35-74 years) surveyed from September 2003 to April 2004. Results Local Geneva/French neighbourhood market research identified 148 FuF in five major FuF food groups which were compiled into a functional ingredient database. Prior to the face-to-face verification, 210 (33 %) individuals categorized themselves as FuF consumers, 429 (67 %) as non-consumers. The control step revealed that 70 % of the 639 participants were already familiar with the FuF concept, and thus were correctly self-categorized as FuF consumers or non-consumers. For the remaining 30 % of participants the true FuF consumption status was established, resulting in a final number of 285 FuF consumers (45 %; 12 % net increase) and 354 (55 %) non-consumers. Conclusions The developed self-administered, brief, qualitative food group-based FuF frequency check list in combination with an FFQ and a photo-assisted control step provides a flexible assessment tool for measuring FuF consumption in the context of a specific fluctuating FuF market and may be applicable to other population settings and time

Sensitivity Analysis of Material and Load Parameters to Fatigue Stresses of an Offshore Wind Turbine Monopile Substructure

Steel monopiles are support structures mostly applied for offshore wind turbines. Their installation is straightforward, in particular, in shallow and medium waters. While the wind turbine tower is primarily affected by wind, the wave loads are dominant for the monopile, as it is submerged to a large extent. This study deals with the influence of uncertainties in material and load parameters on the behaviour of those structures. It is investigated how the scattering of material properties (namely Young's modulus of elasticity) affect the structural response. In addition, loads with different characteristics are applied, and it is examined how the changes in loads influence the structural response. The analysed output data of interest are the extreme stresses leading to the accumulation of fatigue damage. In order for a realistic modelling, wave loads are considered with irregular sea states with different wave characteristics (significant wave heights and wave peak periods). The final aim of the analysis is to classify the effects of specific wave characteristics on the stresses by means of a sensitivity analysis. The analysis shows that variations in the wave peak period have the strongest influence on stress outputs. This effect results from the strong sensitivity of the structural dynamical response to the decrease of the difference between the values of the wave peak frequency and the natural frequencies of the structure. © 2017 The Authors. Published by Elsevier Ltd

infectious serum or culture-grown virus?

Schmallenberg virus (SBV), discovered in Europe in 2011, causes mild transient disease in adult ruminants, but fetal infection can lead to severe malformation in cattle, sheep and goats.To elucidate the pathogenesis of this novel orthobunyavirus, considerable efforts are required. A reliable and standardized infection model is essential for in vivo studies. In the present study, two groups of four cattle were inoculated with either serum passaged in cattle only or cell culture-grown virus. The replication of culture-grown SBV in cattle was reduced compared to virus inoculated via infectious serum. In a second experiment, the infectious serum was titrated in calves; the tested batch contained 102.83 infectious doses per mL. Hence, serum-borne virus that was only passaged in the natural host is a suitable option for a standardized SBV infection model