989 resultados para technological innovation, climate change


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Most countries of Europe, as well as many countries in other parts of the world, are experiencing an increased impact of natural hazards. It is often speculated, but not yet proven, that climate change might influence the frequency and magnitude of certain hydro-meteorological natural hazards. What has certainly been observed is a sharp increase in financial losses caused by natural hazards worldwide. Eventhough Europe appears to be a space that is not affected by natural hazards to such catastrophic extents as other parts of the world are, the damages experienced here are certainly increasing too. Natural hazards, climate change and, in particular, risks have therefore recently been put high on the political agenda of the EU. In the search for appropriate instruments for mitigating impacts of natural hazards and climate change, as well as risks, the integration of these factors into spatial planning practices is constantly receiving higher attention. The focus of most approaches lies on single hazards and climate change mitigation strategies. The current paradigm shift of climate change mitigation to adaptation is used as a basis to draw conclusions and recommendations on what concepts could be further incorporated into spatial planning practices. Especially multi-hazard approaches are discussed as an important approach that should be developed further. One focal point is the definition and applicability of the terms natural hazard, vulnerability and risk in spatial planning practices. Especially vulnerability and risk concepts are so many-fold and complicated that their application in spatial planning has to be analysed most carefully. The PhD thesis is based on six published articles that describe the results of European research projects, which have elaborated strategies and tools for integrated communication and assessment practices on natural hazards and climate change impacts. The papers describe approaches on local, regional and European level, both from theoretical and practical perspectives. Based on these, passed, current and future potential spatial planning applications are reviewed and discussed. In conclusion it is recommended to shift from single hazard assessments to multi-hazard approaches, integrating potential climate change impacts. Vulnerability concepts should play a stronger role than present, and adaptation to natural hazards and climate change should be more emphasized in relation to mitigation. It is outlined that the integration of risk concepts in planning is rather complicated and would need very careful assessment to ensure applicability. Future spatial planning practices should also consider to be more interdisciplinary, i.e. to integrate as many stakeholders and experts as possible to ensure the sustainability of investments.

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The prospect of climate change has revived both fears of food insecurity and its corollary, market opportunities for agricultural production. In Australia, with its long history of state-sponsored agricultural development, there is renewed interest in the agricultural development of tropical and sub-tropical northern regions. Climate projections suggest that there will be less water available to the main irrigation systems of the eastern central and southern regions of Australia, while net rainfall could be sustained or even increase in the northern areas. Hence, there could be more intensive use of northern agricultural areas, with the relocation of some production of economically important commodities such as vegetables, rice and cotton. The problem is that the expansion of cropping in northern Australia has been constrained by agronomic and economic considerations. The present paper examines the economics, at both farm and regional level, of relocating some cotton production from the east-central irrigation areas to the north where there is an existing irrigation scheme together with some industry and individual interest in such relocation. Integrated modelling and expert knowledge are used to examine this example of prospective climate change adaptation. Farm-level simulations show that without adaptation, overall gross margins will decrease under a combination of climate change and reduction in water availability. A dynamic regional Computable General Equilibrium model is used to explore two scenarios of relocating cotton production from south east Queensland, to sugar-dominated areas in northern Queensland. Overall, an increase in real economic output and real income was realized when some cotton production was relocated to sugar cane fallow land/new land. There were, however, large negative effects on regional economies where cotton production displaced sugar cane. It is concluded that even excluding the agronomic uncertainties, which are not examined here, there is unlikely to be significant market-driven relocation of cotton production.

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Hydrologic impacts of climate change are usually assessed by downscaling the General Circulation Model (GCM) output of large-scale climate variables to local-scale hydrologic variables. Such an assessment is characterized by uncertainty resulting from the ensembles of projections generated with multiple GCMs, which is known as intermodel or GCM uncertainty. Ensemble averaging with the assignment of weights to GCMs based on model evaluation is one of the methods to address such uncertainty and is used in the present study for regional-scale impact assessment. GCM outputs of large-scale climate variables are downscaled to subdivisional-scale monsoon rainfall. Weights are assigned to the GCMs on the basis of model performance and model convergence, which are evaluated with the Cumulative Distribution Functions (CDFs) generated from the downscaled GCM output (for both 20th Century [20C3M] and future scenarios) and observed data. Ensemble averaging approach, with the assignment of weights to GCMs, is characterized by the uncertainty caused by partial ignorance, which stems from nonavailability of the outputs of some of the GCMs for a few scenarios (in Intergovernmental Panel on Climate Change [IPCC] data distribution center for Assessment Report 4 [AR4]). This uncertainty is modeled with imprecise probability, i.e., the probability being represented as an interval gray number. Furthermore, the CDF generated with one GCM is entirely different from that with another and therefore the use of multiple GCMs results in a band of CDFs. Representing this band of CDFs with a single valued weighted mean CDF may be misleading. Such a band of CDFs can only be represented with an envelope that contains all the CDFs generated with a number of GCMs. Imprecise CDF represents such an envelope, which not only contains the CDFs generated with all the available GCMs but also to an extent accounts for the uncertainty resulting from the missing GCM output. This concept of imprecise probability is also validated in the present study. The imprecise CDFs of monsoon rainfall are derived for three 30-year time slices, 2020s, 2050s and 2080s, with A1B, A2 and B1 scenarios. The model is demonstrated with the prediction of monsoon rainfall in Orissa meteorological subdivision, which shows a possible decreasing trend in the future.

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Downscaling to station-scale hydrologic variables from large-scale atmospheric variables simulated by general circulation models (GCMs) is usually necessary to assess the hydrologic impact of climate change. This work presents CRF-downscaling, a new probabilistic downscaling method that represents the daily precipitation sequence as a conditional random field (CRF). The conditional distribution of the precipitation sequence at a site, given the daily atmospheric (large-scale) variable sequence, is modeled as a linear chain CRF. CRFs do not make assumptions on independence of observations, which gives them flexibility in using high-dimensional feature vectors. Maximum likelihood parameter estimation for the model is performed using limited memory Broyden-Fletcher-Goldfarb-Shanno (L-BFGS) optimization. Maximum a posteriori estimation is used to determine the most likely precipitation sequence for a given set of atmospheric input variables using the Viterbi algorithm. Direct classification of dry/wet days as well as precipitation amount is achieved within a single modeling framework. The model is used to project the future cumulative distribution function of precipitation. Uncertainty in precipitation prediction is addressed through a modified Viterbi algorithm that predicts the n most likely sequences. The model is applied for downscaling monsoon (June-September) daily precipitation at eight sites in the Mahanadi basin in Orissa, India, using the MIROC3.2 medium-resolution GCM. The predicted distributions at all sites show an increase in the number of wet days, and also an increase in wet day precipitation amounts. A comparison of current and future predicted probability density functions for daily precipitation shows a change in shape of the density function with decreasing probability of lower precipitation and increasing probability of higher precipitation.

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This book investigates the ethical values that inform the global carbon integrity system, and reflects on alternative norms that could or should do so. The global carbon integrity system comprises the emerging international architecture being built to respond to the climate change. This architecture can be understood as an 'integrity system'- an inter-related set of institutions, governance arrangements, regulations and practices that work to ensure the system performs its role faithfully and effectively. This volume investigates the ways ethical values impact on where and how the integrity system works, where it fails, and how it can be improved. With a wide array of perspectives across many disciplines, including ethicists, philosophers, lawyers, governance experts and political theorists, the chapters seek to explore the positive values driving the global climate change processes, to offer an understanding of the motivations justifying the creation of the regime and the way that social norms impact upon the operation of the integrity system. The collection focuses on the nexus between ideal ethics and real-world implementation through institutions and laws. The book will be of interest to policy makers, climate change experts, carbon taxation regulators, academics, legal practitioners and researchers.

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In this paper, we examine the major predictions made so far regarding the nature of climate change and its impacts on our region in the light of the known errors of the set of models and the observations over this century. The major predictions of the climate models about the impact of increased concentration of greenhouse gases ave at variance with the observations over the Indian region during the last century characterized by such increases and global warming. It is important to note that as far as the Indian region is concerned, the impact of year-to-year variation of the monsoon will continue to be dominant over longer period changes even in the presence of global warming. Recent studies have also brought out the uncertainties in the yields simulated by crop models. It is suggested that a deeper understanding of the links between climate and agricultural productivity is essential for generating reliable predictions of impact of climate change. Such an insight is also required for identifying cropping patterns and management practices which are tailored for sustained maximum yield in the face of the vagaries of the monsoon.

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This case study has been carried out as a comparison between two different land-use strategies for climate change mitigation, with possible application within the Clean Development Mechanisms. The benefits of afforestation for carbon sequestration versus for bioenergy production are compared in the context of development planning to meet increasing domestic and agricultural demand for electricity in Hosahalli village, Karnataka, India. One option is to increase the local biomass based electricity generation, requiring an increased biomass plantation area. This option is compared with fossil based electricity generation where the area is instead used for producing wood for non-energy purposes while also sequestering carbon in the soil and standing biomass. The different options have been assessed using the PRO-COMAP model. The ranking of the different options varies depending on the system boundaries and time period. Results indicate that, in the short term (30 years) perspective, the mitigation potential of the long rotation plantation is largest, followed by the short rotation plantation delivering wood for energy. The bioenergy option is however preferred if a long-term view is taken. Short rotation forests delivering wood for short-lived non-energy products have the smallest mitigation potential, unless a large share of the wood products are used for energy purposes (replacing fossil fuels) after having served their initial purpose. If managed in a sustainable manner all of these strategies can contribute to the improvement of the social and environmental situation of the local community. (C) 2009 Elsevier Ltd. All rights reserved.

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This thesis explores how planning policy and practice is responding to the challenge of climate change, particularly in contexts where neoliberal rationales and practices frame decision making. It documents patterns of devolving government responsibilities and experiences of market based mechanisms before reporting on institutional and professional responses to these conditions. The research centred on a qualitative case study and involved thematic content analysis of policy documents and informant interviews. The contribution of the research and thesis is to establish the outlook for climate change adaptation under neoliberal conditions, and to introduce strategies for planners operating within these conditions.

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The fossil fuel divestment movement has undergone explosive growth over the last few years - expanding from encouraging educational institutions to adopt ethical investment policies to focusing upon cities, pension funds and philanthropic charities. The fossil fuel divestment movement has attained global ambitions - challenging sovereign wealth funds and national governments to engage in fossil fuel divestment, and pushing for fossil fuel divestment at international climate talks - such as the Paris Climate Summit in 2015. By exploring and analysing a key campaign to 'Divest Norway', this chapter considers the efforts to globalise and internationalise the fossil fuel divestment campaign. Part 1 explores the origins of the fossil fuel divestment movement, and the application of such strategies in a variety of contexts. Part 2 looks at the campaign to divest Norway's sovereign wealth fund of fossil fuel investments. There has been much discussion as to whether the bold decision of Norway to engage in coal divestment will encourage and inspire other sovereign wealth funds to engage in fossil fuel divestment. The conclusion considers the efforts to introduce fossil fuel divestment as a policy initiative for nation states as a policy option in international climate law.

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Relatively few studies have addressed water management and adaptation measures in the face of changing water balances due to climate change. The current work studies climate change impact on a multipurpose reservoir performance and derives adaptive policies for possible futurescenarios. The method developed in this work is illustrated with a case study of Hirakud reservoir on the Mahanadi river in Orissa, India,which is a multipurpose reservoir serving flood control, irrigation and power generation. Climate change effects on annual hydropower generation and four performance indices (reliability with respect to three reservoir functions, viz. hydropower, irrigation and flood control, resiliency, vulnerability and deficit ratio with respect to hydropower) are studied. Outputs from three general circulation models (GCMs) for three scenarios each are downscaled to monsoon streamflow in the Mahanadi river for two future time slices, 2045-65 and 2075-95. Increased irrigation demands, rule curves dictated by increased need for flood storage and downscaled projections of streamflow from the ensemble of GCMs and scenarios are used for projecting future hydrologic scenarios. It is seen that hydropower generation and reliability with respect to hydropower and irrigation are likely to show a decrease in future in most scenarios, whereas the deficit ratio and vulnerability are likely to increase as a result of climate change if the standard operating policy (SOP) using current rule curves for flood protection is employed. An optimal monthly operating policy is then derived using stochastic dynamic programming (SDP) as an adaptive policy for mitigating impacts of climate change on reservoir operation. The objective of this policy is to maximize reliabilities with respect to multiple reservoir functions of hydropower, irrigation and flood control. In variations to this adaptive policy, increasingly more weightage is given to the purpose of maximizing reliability with respect to hydropower for two extreme scenarios. It is seen that by marginally sacrificing reliability with respect to irrigation and flood control, hydropower reliability and generation can be increased for future scenarios. This suggests that reservoir rules for flood control may have to be revised in basins where climate change projects an increasing probability of droughts. However, it is also seen that power generation is unable to be restored to current levels, due in part to the large projected increases in irrigation demand. This suggests that future water balance deficits may limit the success of adaptive policy options. (C) 2010 Elsevier Ltd. All rights reserved.

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This Chapter considers the geopolitical conflicts in respect of intellectual property, trade, and climate change in the TRIPS Agreement 1994 under the World Trade Organization (WTO). In particular, it focuses upon debates in the TRIPS Council on the topic of patent law and clean energy in 2013 and 2014. The chapter highlights the development agenda of a number of developing countries who are keen for access to clean energy to combat climate change and global warming. It also considers the mixed contributions of members of the BRICS/ BASIC group – including Brazil, India, China, and South Africa. This chapter highlights the intellectual property maximalist position of a number of developed countries on intellectual property, climate change, and trade. Seeking to overcome this conflict and stalemate, this Chapter puts forward both procedural and substantial reform options in respect of intellectual property, trade, and climate change in the TRIPS Council and the WTO. It also flags that the TRIPS Agreement 1994 could well be displaced by the rise of mega-regional trade agreements – such as the Trans-Pacific Partnership (TPP), and the Trans-Atlantic Trade and Investment Partnership (TTIP).

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Impacts of climate change on hydrology are assessed by downscaling large scale general circulation model (GCM) outputs of climate variables to local scale hydrologic variables. This modelling approach is characterized by uncertainties resulting from the use of different models, different scenarios, etc. Modelling uncertainty in climate change impact assessment includes assigning weights to GCMs and scenarios, based on their performances, and providing weighted mean projection for the future. This projection is further used for water resources planning and adaptation to combat the adverse impacts of climate change. The present article summarizes the recent published work of the authors on uncertainty modelling and development of adaptation strategies to climate change for the Mahanadi river in India.

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An increase in atmospheric carbon dioxide (CO2) concentration influences climate both directly through its radiative effect (i.e., trapping longwave radiation) and indirectly through its physiological effect (i.e., reducing transpiration of land plants). Here we compare the climate response to radiative and physiological effects of increased CO2 using the National Center for Atmospheric Research (NCAR) coupled Community Land and Community Atmosphere Model. In response to a doubling of CO2, the radiative effect of CO2 causes mean surface air temperature over land to increase by 2.86 ± 0.02 K (± 1 standard error), whereas the physiological effects of CO2 on land plants alone causes air temperature over land to increase by 0.42 ± 0.02 K. Combined, these two effects cause a land surface warming of 3.33 ± 0.03 K. The radiative effect of doubling CO2 increases global runoff by 5.2 ± 0.6%, primarily by increasing precipitation over the continents. The physiological effect increases runoff by 8.4 ± 0.6%, primarily by diminishing evapotranspiration from the continents. Combined, these two effects cause a 14.9 ± 0.7% increase in runoff. Relative humidity remains roughly constant in response to CO2-radiative forcing, whereas relative humidity over land decreases in response to CO2-physiological forcing as a result of reduced plant transpiration. Our study points to an emerging consensus that the physiological effects of increasing atmospheric CO2 on land plants will increase global warming beyond that caused by the radiative effects of CO2.

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The indigenous cloud forests in the Taita Hills have suffered substantial degradation for several centuries due to agricultural expansion. Currently, only 1% of the original forested area remains preserved in this region. Furthermore, climate change imposes an imminent threat for local economy and environmental sustainability. In such circumstances, elaborating tools to conciliate socioeconomic growth and natural resources conservation is an enormous challenge. This dissertation tackles essential aspects for understanding the ongoing agricultural activities in the Taita Hills and their potential environmental consequences in the future. Initially, alternative methods were designed to improve our understanding of the ongoing agricultural activities. Namely, methods for agricultural survey planning and to estimate evapotranspiration were evaluated, taking into account a number of limitations regarding data and resources availability. Next, this dissertation evaluates how upcoming agricultural expansion, together with climate change, will affect the natural resources in the Taita Hills up to the year 2030. The driving forces of agricultural expansion in the region were identified as aiming to delineate future landscape scenarios and evaluate potential impacts from the soil and water conservation point of view. In order to investigate these issues and answer the research questions, this dissertation combined state of the art modelling tools with renowned statistical methods. The results indicate that, if current trends persist, agricultural areas will occupy roughly 60% of the study area by 2030. Although the simulated land use changes will certainly increase soil erosion figures, new croplands are likely to come up predominantly in the lowlands, which comprise areas with lower soil erosion potential. By 2030, rainfall erosivity is likely to increase during April and November due to climate change. Finally, this thesis addressed the potential impacts of agricultural expansion and climate changes on Irrigation Water Requirements (IWR), which is considered another major issue in the context of the relations between land use and climate. Although the simulations indicate that climate change will likely increase annual volumes of rainfall during the following decades, IWR will continue to increase due to agricultural expansion. By 2030, new cropland areas may cause an increase of approximately 40% in the annual volume of water necessary for irrigation.