995 resultados para Emotional climate


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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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Ensuring adequate water supply to urban areas is a challenging task due to factors such as rapid urban growth, increasing water demand and climate change. In developing a sustainable water supply system, it is important to identify the dominant water demand factors for any given water supply scheme. This paper applies principal components analysis to identify the factors that dominate residential water demand using the Blue Mountains Water Supply System in Australia as a case study. The results show that the influence of community intervention factors (e.g. use of water efficient appliances and rainwater tanks) on water demand are among the most significant. The result also confirmed that the community intervention programmes and water pricing policy together can play a noticeable role in reducing the overall water demand. On the other hand, the influence of rainfall on water demand is found to be very limited, while temperature shows some degree of correlation with water demand. The results of this study would help water authorities to plan for effective water demand management strategies and to develop a water demand forecasting model with appropriate climatic factors to achieve sustainable water resources management. The methodology developed in this paper can be adapted to other water supply systems to identify the influential factors in water demand modelling and to devise an effective demand management strategy.

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In the 21st century, human-induced global climate change has been highlighted as one of the most serious threats to ecosystems worldwide. According to global climate scenarios, the mean temperature in Finland is expected to increase by 1.8 4.0°C by the end of the century. The regional and seasonal change in temperature has predicted to be spatially and temporally asymmetric, where the High-Arctic and Antarctic areas and winter and spring seasons have been projected to face the highest temperature increase. To understand how species respond to the ongoing climate change, we need to study how climate affects species in different phases of their life cycle. The impact of climate on breeding and migration of eight large-sized bird species was studied in this thesis, taking food availability into account. The findings show that climatic variables have considerable impact on the life-history traits of large-sized birds in northern Europe. The magnitude of climatic effects on migration and breeding was comparable with that of food supply, conventionally regarded as the main factor affecting these life-history traits. Based on the results of this thesis and the current climate scenarios, the following not mutually exclusive responses are possible in the near future. Firstly, asymmetric climate change may result in a mistiming of breeding because mild winters and early spring may lead to earlier breeding, whereas offspring are hatching into colder conditions which elevate mortality. Secondly, climate induced responses can differ between species with different breeding tactics (income vs. capital breeding), so that especially capital breeders can gain advantage on global warming as they can sustain higher energy resources. Thirdly, increasing precipitation has the potential to reduce the breeding success of many species by exposing nestlings to more severe post-hatching conditions and hampering the hunting conditions of parents. Fourthly, decreasing ice cover and earlier ice-break in the Baltic Sea will allow earlier spring migration in waterfowl. In eiders, this can potentially lead to more productive breeding. Fifthly, warming temperatures can favour parents preparing for breeding and increase nestling survival. Lastly, the climate-induced phenological changes in life history events will likely continue. Furthermore, interactions between climate and food resources can be complex and interact with each other. Eiders provide an illustrative example of this complexity, being caught in the crossfire between more benign ice conditions and lower salinity negatively affecting their prime food resource. The general conclusion is that climate is controlling not only the phenology of the species but also their reproductive output, thus affecting the entire population dynamics.

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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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The emergence of new technologies has revolutionized the way companies interact and build relationships with customers. The channel–customer relationship has traditionally been managed via a push approach in communication (“What can we sell customers?”) with the hope of cultivating customer loyalty. However, emotional understandings of customers and how they feel about a product, service, or business can drastically alter consumers’ engagement, behavior, and purchasing preferences. This rapidly evolving landscape has left managers at a loss, and what they are experiencing is likely the beginning of a tectonic shift in the way digital channels are designed, monitored, and managed. In this article, digital channel relationships are examined, and useful concepts for clarifying and refining the emotional meaning behind company strategy and their relationship to corresponding digital channels are detailed. Using three case study examples, we discuss the process and impact of such emotionally aware digital channel designs. Recommendations are made regarding how companies can select, design, and maintain digital engagements based on their strategy and industry needs.

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Modern dairy farming in Australia relies on substantial inputs of fertiliser nitrogen (N) to underpin economic production. However, N lost from dairy systems represents an opportunity cost and can pose a number of environmental risks. Nitrogen cycle inhibitors can be co-applied with N fertilisers to slow the conversion of urea to NH4+ to reduce losses via volatilisation, and slow the conversion of NH4+ to NO3- to minimize leaching of NO3- and gaseous losses via nitrification and denitrification. In a field campaign in a high input ryegrass-kikuyu pasture system we compared the soil N pools, losses and pasture production between a) urea coated with the nitrification inhibitor (3,4-dimethyl pyrazole phosphate - DMPP) b) urea coated with the urease inhibitor (N-(n-butyl) thiophosphoric triamide - NBPT) and c) standard urea. There was no treatment effect (P>0.05) on soil mineral N, pasture yield, N2O flux nor leaching of NO3- cf. standard urea. We hypothesise that at our site, because gaseous losses were highly episodic (rainfall was erratic and displayed no seasonal rainfall nor soil wetting pattern) that there was a lack of coincidence of N application and conditions conducive to gaseous losses, thus the effectiveness of the inhibitor products was minimal and did not result in an increase in pasture yield. There remains a paucity of knowledge on N cycle inhibitors in relation to their effective use in field system to increase N use efficiency. Further research is required to define under what field conditions inhibitor products are effective in order to be able to provide accurate advice to managers of nitrogen in production systems.

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This thesis is an examination of how organisational context variables affect the performance of new product development (NPD) teams. Specifically, the extent to how team empowerment climate and supervisory support for creativity impact NPD team performance. Moreover, this thesis is a step forward in the ongoing development of work role performance theory by examining Griffin et al.'s (2007) work role performance model in the context of NPD teams. This thesis addresses the lack of research exploring work role performance dimensions in NPD teams and the extent to which a team empowerment climate and supervisory support for creativity impact NPDs performance.

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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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The terrestrial export of dissolved organic matter (DOM) is associated with climate, vegetation and land use, and thus is under the influence of climatic variability and human interference with terrestrial ecosystems, their soils and hydrological cycles. The present study provides an assessment of spatial variation of DOM concentrations and export, and interactions between DOM, catchment characteristics, land use and climatic factors in boreal catchments. The influence of catchment characteristics, land use and climatic drivers on the concentrations and export of total organic carbon (TOC), total organic nitrogen (TON) and dissolved organic phosphorus (DOP) was estimated using stream water quality, forest inventory and climatic data from 42 Finnish pristine forested headwater catchments, and water quality monitoring, GIS land use, forest inventory and climatic data from the 36 main Finnish rivers (and their sub-catchments) flowing to the Baltic Sea. Moreover, the export of DOM in relation to land use along a European climatic gradient was studied using river water quality and land use data from four European areas. Additionally, the role of organic and minerogenic acidity in controlling pH levels in Finnish rivers and pristine streams was studied by measuring organic anion, sulphate (SO4) and base cation (Ca, Mg, K and Na) concentrations. In all study catchments, TOC was a major fraction of DOM, with much lower proportions of TON and DOP. Moreover, most of TOC and TON was in a dissolved form. The correlation between TOC and TON concentrations was strong and TOC concentrations explained 78% of the variation in TON concentrations in pristine headwater streams. In a subgroup of 20 headwater catchments with similar climatic conditions and low N deposition in eastern Finland, the proportion of peatlands in the catchment and the proportion of Norway spruce (Picea abies Karsten) of the tree stand had the strongest correlation with the TOC and TON concentrations and export. In Finnish river basins, TOC export increased with the increasing proportion of peatland in the catchment, whereas TON export increased with increasing extent of agricultural land. The highest DOP concentrations and export were recorded in river basins with a high extent of agricultural land and urban areas, reflecting the influence of human impact on DOP loads. However, the most important predictor for TOC, TON and DOP export in Finnish rivers was the proportion of upstream lakes in the catchment. The higher the upstream lake percentage, the lower the export indicating organic matter retention in lakes. Molar TOC:TON ratio decreased from headwater catchments covered by forests and peatlands to the large river basins with mixed land use, emphasising the effect of the land use gradient on the stoichiometry of rivers. This study also demonstrated that the land use of the catchments is related to both organic and minerogenic acidity in rivers and pristine headwater streams. Organic anion dominated in rivers and streams situated in northern Finland, reflecting the higher extent of peatlands in these areas, whereas SO4 dominated in southern Finland and on western coastal areas, where the extent of fertile areas, agricultural land, urban areas, acid sulphate soils, and sulphate deposition is highest. High TOC concentrations decreased pH values in the stream and river water, whereas no correlation between SO4 concentrations and pH was observed. This underlines the importance of organic acids in controlling pH levels in Finnish pristine headwater streams and main rivers. High SO4 concentrations were associated with high base cation concentrations and fertile areas, which buffered the effects of SO4 on pH.

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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.