861 resultados para Climate change, political philosophy, neutrality, harm principle, responsibility, technocracy


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This chapter presents a broad overview of understanding of climate change over the past century or so, together with a discussion of some of the uncertainties. It provides a background to the developments in understanding of climate change, presents evidence that climate has changed and assesses the mechanisms that cause climate change, with a particular emphasis on those due to human activity. The concepts underlying climate modelling are introduced and results are then presented that strongly support the view that human activity has played a major role in the observed climate change over the past 50 years. Possible changes in climate over the coming century are then discussed.

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Policy-makers are creating mechanisms to help developing countries cope with loss and damage from climate change, but the negotiations are largely neglecting scientific questions about what the impacts of climate change actually are. Mitigation efforts have failed to prevent the continued increase of anthropogenic greenhouse gas (GHG) emissions. Adaptation is now unlikely to be sufficient to prevent negative impacts from current and future climate change1. In this context, vulnerable nations argue that existing frameworks to promote mitigation and adaptation are inadequate, and have called for a third international mechanism to deal with residual climate change impacts, or “loss and damage”2. In 2013, the United Nations Framework Convention on Climate Change (UNFCCC) responded to these calls and established the Warsaw International Mechanism (WIM) to address loss and damage from the impacts of climate change in developing countries3. An interim Executive Committee of party representatives has been set up, and is currently drafting a two-year workplan comprising meetings, reports, and expert groups; and aiming to enhance knowledge and understanding of loss and damage, strengthen dialogue among stakeholders, and promote enhanced action and support. Issues identified as priorities for the WIM thus far include: how to deal with non-economic losses, such as loss of life, livelihood, and cultural heritage; and linkages between loss and damage and patterns of migration and displacement2. In all this, one fundamental issue still demands our attention: which losses and damages are relevant to the WIM? What counts as loss and damage from climate change?

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Sea surface temperature (SST) datasets have been generated from satellite observations for the period 1991–2010, intended for use in climate science applications. Attributes of the datasets specifically relevant to climate applications are: first, independence from in situ observations; second, effort to ensure homogeneity and stability through the time-series; third, context-specific uncertainty estimates attached to each SST value; and, fourth, provision of estimates of both skin SST (the fundamental measure- ment, relevant to air-sea fluxes) and SST at standard depth and local time (partly model mediated, enabling comparison with his- torical in situ datasets). These attributes in part reflect requirements solicited from climate data users prior to and during the project. Datasets consisting of SSTs on satellite swaths are derived from the Along-Track Scanning Radiometers (ATSRs) and Advanced Very High Resolution Radiometers (AVHRRs). These are then used as sole SST inputs to a daily, spatially complete, analysis SST product, with a latitude-longitude resolution of 0.05°C and good discrimination of ocean surface thermal features. A product user guide is available, linking to reports describing the datasets’ algorithmic basis, validation results, format, uncer- tainty information and experimental use in trial climate applications. Future versions of the datasets will span at least 1982–2015, better addressing the need in many climate applications for stable records of global SST that are at least 30 years in length.

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Uncertainty regarding changes in dissolved organic carbon (DOC) quantity and quality has created interest in managing peatlands for their ecosystem services such as drinking water provision. The evidence base for such interventions is, however, sometimes contradictory. We performed a laboratory climate manipulation using a factorial design on two dominant peatland vegetation types (Calluna vulgaris and Sphagnum Spp.) and a peat soil collected from a drinking water catchment in Exmoor National Park, UK. Temperature and rainfall were set to represent baseline and future conditions under the UKCP09 2080s high emissions scenario for July and August. DOC leachate then underwent standard water treatment of coagulation/flocculation before chlorination. C. vulgaris leached more DOC than Sphagnum Spp. (7.17 versus 3.00 mg g−1) with higher specific ultraviolet (SUVA) values and a greater sensitivity to climate, leaching more DOC under simulated future conditions. The peat soil leached less DOC (0.37 mg g−1) than the vegetation and was less sensitive to climate. Differences in coagulation removal efficiency between the DOC sources appears to be driven by relative solubilisation of protein-like DOC, observed through the fluorescence peak C/T. Post-coagulation only differences between vegetation types were detected for the regulated disinfection by-products (DBPs), suggesting climate change influence at this scale can be removed via coagulation. Our results suggest current biodiversity restoration programmes to encourage Sphagnum Spp. will result in lower DOC concentrations and SUVA values, particularly with warmer and drier summers.

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Freshwater deficits and heavy rainfall have been projected to intensify in a warming climate. An analysis of hydrological data suggests that past changes in wet and dry extremes were more complex than a simple amplification of existing patterns.

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The evidence for anthropogenic climate change continues to strengthen, and concerns about severe weather events are increasing. As a result, scientific interest is rapidly shifting from detection and attribution of global climate change to prediction of its impacts at the regional scale. However, nearly everything we have any confidence in when it comes to climate change is related to global patterns of surface temperature, which are primarily controlled by thermodynamics. In contrast, we have much less confidence in atmospheric circulation aspects of climate change, which are primarily controlled by dynamics and exert a strong control on regional climate. Model projections of circulation-related fields, including precipitation, show a wide range of possible outcomes, even on centennial timescales. Sources of uncertainty include low-frequency chaotic variability and the sensitivity to model error of the circulation response to climate forcing. As the circulation response to external forcing appears to project strongly onto existing patterns of variability, knowledge of errors in the dynamics of variability may provide some constraints on model projections. Nevertheless, higher scientific confidence in circulation-related aspects of climate change will be difficult to obtain. For effective decision-making, it is necessary to move to a more explicitly probabilistic, risk-based approach.

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Purpose The sensitivity of soil organic carbon to global change drivers, according to the depth profile, is receiving increasing attention because of its importance in the global carbon cycle and its potential feedback to climate change. A better knowledge of the vertical distribution of SOC and its controlling factors—the aim of this study—will help scientists predict the consequences of global change. Materials and methods The study area was the Murcia Province (S.E. Spain) under semiarid Mediterranean conditions. The database used consists of 312 soil profiles collected in a systematic grid, each 12 km2 covering a total area of 11,004 km2. Statistical analysis to study the relationships between SOC concentration and control factors in different soil use scenarios was conducted at fixed depths of 0–20, 20–40, 40–60, and 60–100 cm. Results and discussion SOC concentration in the top 40 cm ranged between 6.1 and 31.5 g kg−1, with significant differences according to land use, soil type and lithology, while below this depth, no differences were observed (SOC concentration 2.1–6.8 g kg−1). The ANOVA showed that land use was the most important factor controlling SOC concentration in the 0–40 cm depth. Significant differences were found in the relative importance of environmental and textural factors according to land use and soil depth. In forestland, mean annual precipitation and texture were the main predictors of SOC, while in cropland and shrubland, the main predictors were mean annual temperature and lithology. Total SOC stored in the top 1 m in the region was about 79 Tg with a low mean density of 7.18 kg Cm−3. The vertical distribution of SOC was shallower in forestland and deeper in cropland. A reduction in rainfall would lead to SOC decrease in forestland and shrubland, and an increase of mean annual temperature would adversely affect SOC in croplands and shrubland. With increasing depth, the relative importance of climatic factors decreases and texture becomes more important in controlling SOC in all land uses. Conclusions Due to climate change, impacts will be much greater in surface SOC, the strategies for C sequestration should be focused on subsoil sequestration, which was hindered in forestland due to bedrock limitations to soil depth. In these conditions, sequestration in cropland through appropriate management practices is recommended.

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Water scarcity severely impairs food security and economic prosperity in many countries today. Expected future population changes will, in many countries as well as globally, increase the pressure on available water resources. On the supply side, renewable water resources will be affected by projected changes in precipitation patterns, temperature, and other climate variables. Here we use a large ensemble of global hydrological models (GHMs) forced by five global climate models and the latest greenhouse-gas concentration scenarios (Representative Concentration Pathways) to synthesize the current knowledge about climate change impacts on water resources. We show that climate change is likely to exacerbate regional and global water scarcity considerably. In particular, the ensemble average projects that a global warming of 2 degrees C above present (approximately 2.7 degrees C above preindustrial) will confront an additional approximate 15% of the global population with a severe decrease in water resources and will increase the number of people living under absolute water scarcity (< 500 m(3) per capita per year) by another 40% (according to some models, more than 100%) compared with the effect of population growth alone. For some indicators of moderate impacts, the steepest increase is seen between the present day and 2 degrees C, whereas indicators of very severe impacts increase unabated beyond 2 degrees C. At the same time, the study highlights large uncertainties associated with these estimates, with both global climate models and GHMs contributing to the spread. GHM uncertainty is particularly dominant in many regions affected by declining water resources, suggesting a high potential for improved water resource projections through hydrological model development.

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This paper presents an assessment of the effects of climate change on river flow regimes in representative English catchments, using the UKCP09 climate projections. These comprise a set of 10,000 coherent climate scenarios, used here (i) to evaluate the distribution of potential changes in hydrological behaviour and (ii) to construct relationships between indicators of climate change and hydrological change. The study uses six catchments, and focuses on change in average flow, high flow (Q5) and low flow (Q95). There is a large range in hydrological change in each catchment between the plausible UKCP09 climate projections, with differences between catchments largely due to differences in catchment geology and baseline water balance. The range in change between the UKCP09 projections is in most catchments smaller than the range between changes with scenarios based on the CMIP3 ensemble of climate models, and earlier UK scenarios produce changes that tend towards the lower (drier) end of the UKCP09 range. The difference between emissions scenarios is small compared to the range across the 10,000 scenarios. Changes in high flows are largely driven by changes in winter precipitation, whilst changes in low flows are determined by changes in summer precipitation and temperature.

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It is indisputable that climate is an important factor in many livestock diseases. Nevertheless, our knowledge of the impact of climate change on livestock infectious diseases is much less certain. Therefore, the aim of the article is to conduct a systematic review of the literature on the topic utilizing available retrospective data and information. Across a corpus of 175 formal publications, limited empirical evidence was offered to underpin many of the main arguments. The literature reviewed was highly polarized and often inconsistent regarding what the future may hold. Historical explorations were rare. However, identifying past drivers to livestock disease may not fully capture the extent that new and unknown drivers will influence future change. As such, our current predictive capacity is low. We offer a number of recommendations to strengthen this capacity in the coming years. We conclude that our current approach to research on the topic is limiting and unlikely to yield sufficient, actionable evidence to inform future praxis. Therefore, we argue for the creation of a reflexive, knowledge-based system, underpinned by a collective intelligence framework to support the drawing of inferences across the literature.

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This paper aims to assess the necessity of updating the intensity-duration-frequency (IDF) curves used in Portugal to design building storm-water drainage systems. A comparative analysis of the design was performed for the three predefined rainfall regions in Portugal using the IDF curves currently in use and estimated for future decades. Data for recent and future climate conditions simulated by a global and regional climate model chain are used to estimate possible changes of rainfall extremes and its implications for the drainage systems. The methodology includes the disaggregation of precipitation up to subhourly scales, the robust development of IDF curves, and the correction of model bias. Obtained results indicate that projected changes are largest for the plains in southern Portugal (5–33%) than for mountainous regions (3–9%) and that these trends are consistent with projected changes in the long-term 95th percentile of the daily precipitation throughout the 21st century. The authors conclude there is a need to review the current precipitation regime classification and change the new drainage systems towards larger dimensions to mitigate the projected changes in extreme precipitation.

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A statistical–dynamical downscaling (SDD) approach for the regionalization of wind energy output (Eout) over Europe with special focus on Germany is proposed. SDD uses an extended circulation weather type (CWT) analysis on global daily mean sea level pressure fields with the central point being located over Germany. Seventy-seven weather classes based on the associated CWT and the intensity of the geostrophic flow are identified. Representatives of these classes are dynamically downscaled with the regional climate model COSMO-CLM. By using weather class frequencies of different data sets, the simulated representatives are recombined to probability density functions (PDFs) of near-surface wind speed and finally to Eout of a sample wind turbine for present and future climate. This is performed for reanalysis, decadal hindcasts and long-term future projections. For evaluation purposes, results of SDD are compared to wind observations and to simulated Eout of purely dynamical downscaling (DD) methods. For the present climate, SDD is able to simulate realistic PDFs of 10-m wind speed for most stations in Germany. The resulting spatial Eout patterns are similar to DD-simulated Eout. In terms of decadal hindcasts, results of SDD are similar to DD-simulated Eout over Germany, Poland, Czech Republic, and Benelux, for which high correlations between annual Eout time series of SDD and DD are detected for selected hindcasts. Lower correlation is found for other European countries. It is demonstrated that SDD can be used to downscale the full ensemble of the Earth System Model of the Max Planck Institute (MPI-ESM) decadal prediction system. Long-term climate change projections in Special Report on Emission Scenarios of ECHAM5/MPI-OM as obtained by SDD agree well to the results of other studies using DD methods, with increasing Eout over northern Europe and a negative trend over southern Europe. Despite some biases, it is concluded that SDD is an adequate tool to assess regional wind energy changes in large model ensembles.

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Cities have developed into the hotspots of human economic activity. From the appearance of the first cities in the Neolithic to 21st century metropolis their impact on the environment has always been apparent. With more people living in cities than in rural environments now it becomes crucial to understand these environmental impacts. With the immergence of megacities in the 20th century and their continued growth in both, population and economic power, the environmental impact has reached the global scale. In this paper we examine megacity impacts on atmospheric composition and climate. We present basic concepts, discuss various definitions of footprints, summarize research on megacity impacts and assess the impact of megacity emissions on air quality and on the climate at the regional to global scale. The intention and ambition of this paper is to give a comprehensive but brief overview of the science with regard to megacities and the environment.