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University of Technology, Sydney. Faculty of Engineering. / This research has analysed the economy-wide impacts of carbon tax as a policy option to reduce the rate of growth of carbon-dioxide emissions from the electricity sector in Australia. These impacts are analysed for energy and non energy sectors of the economy. An energy-oriented Input–Output framework, with ‘flexible’ production functions, based on Translog and Cobb-Douglas formulations, is employed for the analysis of various impacts. Further, two alternative conceptions of carbon tax are considered in this research, namely, based on Polluter Pays Principle (PPP) and Shared Responsibility Principle (SRP). In the first instance, the impacts are analysed, for the period 2005–2020, for tax levels of $10 and $20 per tonne of CO2, in a situation of no a-priori limit on CO2 emissions. The analysis shows that CO2 emissions from the electricity sector, when carbon tax is based on PPP, would be 211 and 152 Mt, for tax levels of $10 and $20, respectively (as compared to 250 Mt in the Base Case scenario, that is, the business-as-usual-case). The net economic costs, corresponding with these tax levels, expressed in present value terms, would be $27 and $49 billion, respectively, over the period 2005-2020. These economic costs are equivalent to 0.43 and 0.78 per cent of the estimated GDP of Australia. Further, most of the economic burden, in this instance, would fall on the electricity sector, particularly coal-fired electricity generators – large consumers of direct fossil fuel. On the other hand, in the case of a carbon tax based on SRP, CO2 emissions would be 172 and 116 Mt, for tax levels of $10 and $20, respectively. The corresponding net economic costs would be $47 (0.74 per cent of GDP) and $84 (1.34 per cent of GDP) billion, respectively, with significant burden felt by the commercial sector – large consumers of indirect energy and materials whose production would contribute to CO2 emissions. Next, the impacts are analysed by placing an a-priori limit on CO2 emissions from the electricity sector – equivalent to 108 per cent of the 1990 level (that is, 138 Mt), by the year 2020. Two cases are analysed, namely, early action (carbon tax introduced in 2005) and deferred action (carbon tax introduced in 2010). In the case of early action, the analysis suggests, carbon tax of $25 and $15, based on PPP and SRP, respectively, would be required to achieve the above noted emissions target. The corresponding tax levels in the case of deferred action are $51 and $26, respectively. This research also shows that the net economic costs, in the case of early action, would be $32 billion (for PPP) and $18 billion (for SRP) higher than those in the case of deferred action. However, this research has demonstrated, that this inference is largely due to the selection of particular indicator (that is, present value) and the relatively short time frame (that is, 2005–2020) for analysis. By extending the time frame of the analysis to the year 2040, the case for an early introduction of carbon tax strengthens. Overall, the analysis in this research suggests that an immediate introduction of carbon tax, based on SRP, is the most attractive approach to reduce the rate of growth of CO2 emissions from the electricity sector and to simultaneously meet economic and social objectives. If the decision to introduce such a tax is deferred, it would be rather difficult to achieve not only environmental objectives but economic and social objectives as well.

The IPCC Third Assessment report (IPCC 2001a) concludes that Australia has significant vulnerability to the changes in temperature and rainfall projected over the next decades to 100 years. Agriculture and natural resources were two of the key sectors identified as likely to be strongly affected. Climate change will add to the existing, substantial pressures on Australia’s grape and wine industry sector. Vineyards have a life of thirty plus years so right now, when selecting vineyard sites, or when managing existing vineyards, consideration of the changing climate is prudent. (For complete abstract open document)

Understanding the evolution, biogeography and extinction of Australopapuan vertebrate lineages is fundamental to determining baseline responses of those groups to past environmental change. In light of predicted climatic change and anthropogenic impact, it is imperative to determine the trajectories of Australia???s modern flora and fauna. In particular, mesothermic rainforest faunas are among Australia???s most vulnerable terrestrial biota under threat from both natural and anthropogenic causes. There is a gap in knowledge of past patterns of change and, in particular, a conspicuous lack of direct evidence of response of rainforest faunas to past climatic change. This study documents the late Cainozoic Australopapuan rainforest vertebrate record and its response to environmental change via adaptive radiation, biogeographical change and extinction. In particular, it provides the first detailed systematic appraisal of Quaternary fossil sites and local faunas from northern Australia. The study documents the only known Quaternary mesothermic rainforest fauna in Australia and its transition to a xeric-adapted fauna during the middle Pleistocene. The fossil assemblages analysed are comprised of dozens of species, including several new genera and species. Each fossil taxon shares a close phylogenetic relationship with others either known only from the Australian Tertiary record or from Quaternary-Recent New Guinea and Wet Tropics rainforests. The presence of many species is evidence of previously much larger distributions followed by subsequent massive range retractions. Detailed documentation of this rare fauna testifies to rainforest stability in central eastern Queensland until approximately 280,000 years ago, when the development of an El Nino dominated climate generated variable climatic patterns that could not support aeseasonal rainforest. Extinction of this late Pleistocene rainforest fauna serves as one of only two examples of major rainforest faunal turnover in Cainozoic Australia, the other occurring in the late Miocene. These two major extinction events are compared. The late Pleistocene faunal extinction differs from the late Miocene event in being biased towards large-bodied, terrestrial herbivores and carnivores (both reptile and mammal). This study also combines fossil and phylogenetic data with latest understanding of palaeogeography, tectonics and sea level history along Australia???s northern margin to provide hypotheses of faunal dispersal between New Guinea and mainland Australia throughout the Neogene.

There is strong scientific consensus on the evidence of anthropogenic climate change which will increasingly present social, economic and institutional challenges. The Fifth Assessment report (AR5) of the Intergovernmental Panel on Climate Change (IPCC) established that ‘human influence on the climate system is clear’ and that ‘changes in many extreme weather and climate events have been observed since about 1950’ (IPCC 2014a). Associated impacts include sea level rise and increased likelihood of extreme weather worldwide such extreme rainfall, heat waves, hurricanes and tornados (IPCC 2014a; Klijn et al. 2015). Climate change adaptation is the adjustment in natural or human systems in response to actual or expected climatic stimuli or their effects in order to minimise the impacts and to take advantage of new opportunities (IPCC 2007). Many vulnerable countries, regions and cities have accepted that some form of adaptation is inevitable (Swart et al. 2014). This thesis contributes to the research on decision-making for climate change adaptation in order to reduce vulnerability. Both bottom-up and top-down analyses are applied to complement one another with an application to flooding. Flood risk is expected to increase in the UK under climate change (Alfieri et al. 2016; Scottish Government 2016) associated significant economic damage (CEA 2007). From a top-down perspective, the thesis explores how to enhance economic decision-making under climate change uncertainty. In a situation of uncertainty the costs may be clear and immediate whereas the benefits are uncertain and often only realised in the distant future. This impedes the use of standard decision-making tools such as cost-benefit analysis that rely on the quantification of (expected) costs and benefits. The thesis begins on the macro scale with a taxonomy of economic decision-making tools for climate change adaptation, discusses the sector level and subsequently proceeds to the case study micro-scale with applications of adaptation decision-making. First, the potential of alternative decision-making tools, so-called robust decision-making approaches, is examined. The strengths and weaknesses of these tools relative to traditional decision-making processes such as CBA are explored and their future potential in the adaptation process evaluated. It is found that robust decision-making tools under uncertainty provide performance across a range of climate change scenarios, but they may yield lower overall performance if compared with the alternative strategy under the actual climate outturn. Furthermore, they are resource intense and decision makers need to balance the resources required for employing the methods with the added value they can offer. A flow-chart is developed to provide guidance on which decision-making tool should be applied depending on the scale and type of adaptation project. On the sector level, the economic appraisal of adaptation options for agriculture is explored. Agriculture is particularly vulnerable to climate change due to the direct impacts of weather and climate on agricultural output and the sector plays an indispensable role in providing (and improving) food security as well as creating employment. Many of the adaptation options in agriculture involve short-term managerial changes and can be appraised with standard economic decision-making and the options can be carried out after the climate signal has been observed. For those adaptations that do require a longer time to take effect or are long-lived and are (partly) irreversible in nature, robust approaches have a valuable role to play in decision-making. Suggestions are made regarding how robust decisionmaking tools under uncertainty can be practically applied to adaptations in agriculture, outlining the data needs and the steps of the data analysis for three different applications. On the micro level, for a case study in the Eddleston Water catchment in the Scottish borders, UK, two different economic appraisal tools are applied. These include a cost-benefit analysis of afforestation as a flood management measure under different climate change scenarios which can provide important insights for adaptation decisions when robust decision-making tools under uncertainty are not feasible due to resource constraints. It is found that the flood risk under climate change increases substantially in the case study area which needs to be taken into consideration for economic appraisal. The results of the CBA reveal that all modelled scenarios of afforestation have positive NPVs which are driven by further eco-system services (including climate regulation, water quality and recreation) rather than flood regulation benefits. It is concluded that eco-system services beyond flood regulation should be considered for the appraisal of NFM to enable policy-makers to make informed decisions. Second, the Expected values can be used in situations of quantifiable uncertainty, i.e risk. But for climate change we do not have a strong methodology to assess these subjective probabilities. They cannot be fully based on the past, because climate change is a new process for which we have no historical equivalent. Models share common flaws in their assumptions and their dispersion in results cannot be used to assess the real uncertainty (Hallegatte, 2012). The term deep uncertainty (Lempert et al., 2003) or severe uncertainty is used (Ben-Haim, 2006) in these contexts. Such uncertainty is characterised as a condition where decision makers do not know or cannot agree upon a model that adequately describes cause and effect or its key parameters (Walker et al., 2012). This leads to a situation where it is not possible to say with confidence whether one future state of the world is more plausible than another. The robust decision-making tool under uncertainty real option analysis is applied to the same case study to allow for adjusting adaptation options over time by integrating lessons learned about climate change in the appraisal process. A simplified ROA is presented to minimise the life cycle cost of a system that aims to prevent flooding of a return period of 1/20 using tools which should be available to most public authorities. This includes the use of UKCP09 climate data, analysis of changes of peak flow under the measure implemented, cost structures for the measure and damage cost under different outcomes. The analysis can be carried out in an excel spread sheet with the aforementioned types of input. The results of the analysis demonstrate that the obtained strategy is significantly cheaper than planting for the worst case scenario and presents the potential for learning under climate change uncertainty as a way to allocate resources in a more efficient way. The complementing bottom up approach investigates behavioural barriers to decisionmaking for adaptation. Standard economic theory tells us that self-interest will motivate most actors to engage in efficient private adaptation as long as the costs do not exceed the benefits. Thus, we would expect households at flood risk to invest in flood adaptation measures. However, it has been observed that households do not necessarily take action to protect themselves and their assets from flooding. In a study carried out in co-operation with 36 communities around Scotland, protection motivation theory is used to explain the uptake of household flood protection and whether community led flood action groups can increase uptake. It is found that flood action groups directly and indirectly influence the uptake of some flood protection measures positively in particular if tailored information is provided. Overall, it is concluded that both top-down and bottom-up approaches play an important role to move towards an economically efficient adaptation in the context of flooding. / From a top-down perspective, uncertainty should be explicitly acknowledged and included in economic decision-making for adaptation (to flooding) to make an informed decision. The type of analysis will depend on the adaptation project and resources at hand. Developing and fostering bottom-up tools such as flood action groups to increase the uptake of the type of household flood protection with a benefit-cost ratio above 1 may also contribute towards the more efficient allocation of resources.

<p> The climate over Ecuador is complex due to several interacting factors, such as its location at the equator, the Andean topography, and several modes of internal variability, including the El Ni&ntilde;o&ndash;Southern Oscillation (ENSO), affecting the region. In addition, the rapid increase in greenhouse gas concentrations will continue to affect both the mean state and climate variability in Ecuador over the coming decades. Hence, a thorough understanding of both natural and anthropogenic forcings and how they combine to influence Ecuadorian climate is a necessity for decision-making and implementation of adequate adaptation measures. However, the lack of observational data, both in space and time, severely limits our ability to study climate changes that affect Ecuador today. Employing a high-resolution regional climate model (RCM) can help to better diagnose the mechanisms and feedbacks that lead to climate changes and how they differ in space and time, as long as the model is able to adequately reproduce what is observed in the limited observational data. </p><p> With the purpose of contributing to a better understanding of how and why Ecuador&rsquo;s climate will change in the coming decades, three topics of specific relevance for this country are addressed in this dissertation: a) how well can a RCM simulate the mean climate state and its variability over a region of complex topography such as Ecuador under different parameterization schemes? b) what feedbacks are involved in producing elevation-dependent warming (EDW) in the Ecuadorian Andes? And c) how are the characteristics of climate extreme events (CEEs) over Ecuador projected to change by the middle of the 21st century? These three questions are addressed by use of observations and simulations using the Weather Research and Forecasting Model (WRF) configured as a RCM with a high-resolution of 10 km horizontal grid spacing and 51 vertical levels. </p><p> Sensitivity test runs were performed to choose a proper combination of parameterization schemes for conducting four WRF simulations comprising the territory of Ecuador and spanning 30 years. The first simulation was driven by the Climate Forecast System Reanalysis (CFSR) for the period 1980&ndash;2010 and used to evaluate the model&rsquo;s ability to realistically portray present-day climate over the region. The other three simulations used the output from the Community Climate System Model version 4 (CCSM4) as the boundary conditions to produce a baseline simulation (1976&ndash;2005) and two future simulations (2041&ndash; 2070) following the moderate-emissions scenario RCP 4.5 and the high-emissions scenario RCP 8.5. </p><p> EDW over the Ecuadorian Andes is studied by analyzing observations and the present-day WRF-simulation, while the future simulations were used to test the contribution to this effect caused by future changes in feedback mechanisms. Surface net radiation changes due to future changes in cloudiness were identified as the most important mechanisms leading to EDW over the Ecuadorian Andes, with future reductions in cloudiness dominating at high elevations. The model results also indicate different future warming signals on both sides of the Andes, with higher warming rates at the high elevations of the western Andes, likely due to enhanced subsidence and adiabatic warming in the mid-troposphere. </p><p> CEEs are analyzed by using annual climatic indices. First the present-day relationship between CEEs and Pacific (ENSO) and Atlantic modes of variability are investigated in both models and observations. Results confirm the dominant role played by ENSO in governing the occurrence of many CCEs over Ecuador, while calling for more studies on the potential influence of Atlantic modes over Ecuador&rsquo;s CEEs. The model projections suggest significant future changes in CEEs, with large increases in warm and wet extremes over most regions, but the simulations also highlight significant spatial heterogeneity, which suggests that it is important to study changes in extreme events using high-spatial resolution data.</p><p>

<p> Unforced internal variability abounds in the climate system and often confounds the identification of climate change due to external forcings. Given that greenhouse gas concentrations are projected to increase for the foreseeable future, separating forced climate change from internal variability is a key concern with important implications. Here, we leverage a 40-member ensemble, the Community Earth System Model Large Ensemble (CESM-LE) to investigate the influence of internal variability on the detection of forced changes in two climate phenomena. First, using cyclone identification and compositing techniques within the CESM-LE, we investigate precipitation changes in extratropical cyclones under greenhouse gas forcing and the effect of internal variability on the detection of these changes. We find that the ensemble projects increased cyclone precipitation under twenty-first century business-as-usual greenhouse gas forcing and this response exceeds internal variability in both near- and far- futures. Further, we find that these changes are almost entirely driven by increases in cyclone moisture. Next, we explore the role of internal variability in projections of the annual cycle of surface temperature over Northern Hemisphere land. Internal variability strongly confounds forced changes in the annual cycle over many regions of the Northern Hemisphere. Changes over Europe, North Africa and Siberia, however, are large and easily detectable and further, are remarkably robust across model ensembles from the Coupled Model Intercomparison Project Phase 5 (CMIP5) archive. Using a simple energy balance model, we find that changes in the annual cycle over the three regions are mostly driven by changes in surface heat fluxes. </p><p> The thesis also presents a novel ensemble-based framework for diagnosing forced changes in regional climate variability. Changes in climate variability are commonly assessed in terms of changes in the variances of climate variables. The covariance response has received much less attention, despite the existence of large-scale modes of variability that induce covariations in climate variables over a wide range of spatial scales. Addressing this, the framework facilitiates a unified assessment of forced changes in the regional variances and covariances of climate variables.</p><p>

<p> An interdisciplinary approach at the interface between geodesy and geophysics has recently resolved several Earth science problems at regional and global scales. I use the term &ldquo;geophysical geodesy&rdquo; to distinguish the technical and theoretical aspect of geodesy from geophysical applications of geodetic techniques. Using a wide range of Earth observation data, I study the spatio-temporal characteristics of Earth surface deformation in the United States associated with several geophysical processes, including natural and anthropogenic subsidence and uplift, regional relative sea-level rise, and continental hydrological loading. The theoretical portion of this dissertation applies loading theory and develops a new hybrid method to improve the estimate of hydrologically-induced vertical deformation at time scales from sub-annual to multi-annual. The application part of this dissertation benefits from GPS and other geodetic and geologic data sets to study and model Earth&rsquo;s surface uplift due to CO2 injection at an oil reservoir in coastal Texas, and coastal subsidence and nuisance flooding along the Mississippi River Delta and eastern seaboard of the United States.</p><p>

<p>Chapter One of this thesis focuses on critiques of modernity and capitalism, both of which are deeply implicated in the advent of the Anthropocene. Drawing from Bruno Latour, Anna L. Tsing, Caroline Levine, and Adam Seligman, I examine the sincere drive to ?purify? the world of its entangled networks. I then consider Francois Jullien?s critique of the Western ?cult of action,? discussing it alongside Latour?s critique of modern temporality and Tsing?s critique of progress. Finally, I read David Mitchell?s novel, Ghostwritten, in the context of this discussion. In the second chapter I discuss how Latour, Tsing, and Jullien ask us to turn our attention to the entangled world, rather than striving to purify it. I present a metaphor of fermentation in order to consider how we rely on natural processes to bring about change rather than individual will. This alternate form of action relies on the propensity for transformation already latent in an assemblage. I end with a discussion of Ursula Le Guin?s Earthsea Cycle, arguing that the Immanent Grove and the Master Patterner illustrate this amodern form of action.

abstract: Due to decrease in fossil fuel levels, the world is shifting focus towards renewable sources of energy. With an annual average growth rate of 25%, wind is one of the foremost source of harnessing cleaner energy for production of electricity. Wind turbines have been developed to tap power from wind. As a single wind turbine is insufficient, multiple turbines are installed forming a wind farm. Generally, wind farms can have hundreds to thousands of turbines concentrated in a small region. There have been multiple studies centering the influence of weather on such wind farms, but no substantial research focused on how wind farms effect local climate. Technological advances have allowed development of commercial wind turbines with a power output greater than 7.58 MW. This has led to a reduction in required number of turbines and has optimized land usage. Hence, current research considers higher power density compared to previous works that relied on wind farm density of 2 to 4 W/m 2 . Simulations were performed using Weather Research and Forecasting software provided by NCAR. The region of simulation is Southern Oregon, with domains including both onshore and offshore wind farms. Unlike most previous works, where wind farms were considered to be on a flat ground, effects of topography have also been considered here. Study of seasonal effects over wind farms has provided better insight into changes in local wind direction. Analysis of mean velocity difference across wind farms at a height of 10m and 150m gives an understanding of wind velocity profiles. Results presented in this research tends to contradict earlier belief that velocity reduces throughout the farm. Large scale simulations have shown that sometimes, more than 50% of the farm can have an increased wind velocity of up to 1m/s at an altitude of 10m. / Dissertation/Thesis / Masters Thesis Engineering 2015