Dissertations / Theses on the topic 'Climate evaluation'

Thesis (S.M. in Technology and Policy)--Massachusetts Institute of Technology, Engineering Systems Division, 2013.
Cataloged from PDF version of thesis.
Includes bibliographical references (p. 87-97).
The climate change mitigation potential of energy technologies depends on how their lifecycle greenhouse gas emissions compare to global climate stabilization goals. Current methods for comparing technologies, which assess impacts over an arbitrary, fixed time horizon, do not acknowledge the critical link between technology choices and climate dynamics. In this thesis, I ask how we can use information about the temporal characteristics of greenhouse gases to design new metrics for comparing energy technologies. I propose two new metrics: the Cumulative Climate Impact (CCI) and Instantaneous Climate Impact (ICI). These metrics use limited information about the climate system, such as the year when stabilization occurs, to calculate tradeoffs between greenhouse gases, and hence the technologies that emit these gases. The CCI and ICI represent a middle ground between current metrics and commonly-proposed alternatives, in terms of their level of complexity and information requirements. I apply the CCI and ICI to evaluate the climate change mitigation potential of energy technologies in the transportation sector, with a focus on alternative fuels. I highlight key policy debates about the role of (a) natural gas as a "bridge" to a low carbon energy future and (b) third generation biofuels as a long-term energy solution. New metrics shed light on critical timing-related questions that current metrics gloss over. If natural gas is a bridge fuel, how long is this bridge? If algae biofuels are not commercially viable for the next twenty years, can they still provide a significant climate benefit? I simulate technology decisions using new metrics, and existing metrics like the Global Warming Potential (GWP), identifying the conditions where new metrics improve on existing methods as well as the conditions under which new metrics fail. I show that metrics of intermediate complexity, such as the CCI and ICI, provide a simple, reliable, and policy-relevant approach to technology evaluation and capture key features of the future climate system. I extend these insights to energy technologies in the electricity sector as well as a variety of environmental impact categories.
by Morgan R. Edwards.
S.M.in Technology and Policy

Climate services, often refers as decision support tools, are developed to provide information with a view to aid in decision making and policy planning for adaptation due to climate variability and change. This study investigated different publicly available climate services and decision support tools based on previously proposed evaluation framework. This evaluation framework originally consists of four design elements which are divided into nine evaluation metrics for this study. These evaluation metrics are: identification of decision making context, discussion of the role of climate information in decision making, discussion of non-climatic factors, uncertainty of the data presented, accessibility of information, discussion on the development process, sustainability/ ongoing process, discussion of funding sources, and evaluation of the tool through survey, modeling or contingent valuation method. Tools were then given "High", "Medium", and "Low" score for each of the criterion. A total of 19 tools were evaluation for this study. Tools performed relatively well in "characteristics, tailoring, and communication of the climate information" and "governance, process, and structure of the climate service" whereas they got average scores in "problem identification and the decision-making context" and "value of the service provided". Additionally, four case study evaluation of tools showed detail evaluation of how the tools performed against each of the criterion. The results of this study showed the relative strengths and weakness of the evaluated tools which can be used to improve existing climate services to aid in adaptation decision needs for climate change. This will also help in better decision making and policy planning for different sectors impacted by the changing climate.
Master of Science
Climate services, often refers as decision support tools, are developed to provide information with a view to aid in decision making and policy planning for adaptation due to the adverse impacts caused by climate variability and change. This study investigated a total of 19 publicly available climate services and decision support tools based on previously proposed evaluation framework. This evaluation framework originally consists of four design elements which further classified into nine evaluation metrics and each of tools were given "High", "Medium", and "Low" score against these criteria. These metrics are: identification of decision making context, discussion of the role of climate information in decision making, discussion of non-climatic factors, uncertainty of the data presented, accessibility of information, discussion on the development process, sustainability/ ongoing process, discussion of funding sources, and evaluation of the tool through survey, modeling or contingent valuation method. Evaluated tools performed better than average in terms of uncertainty of the data presented, accessibility of information, discussion on the development process, sustainability/ ongoing process, discussion of funding sources, and feedback/ evaluation criteria whereas they performed below average in problem identification and decision making context, discussion of the role of climate information in decision making, and discussion of non-climatic factors. Four case study evaluation were also presented in this study for better understanding of how the evaluation process works for the tools. The results of this study provide an insight about the relative strengths and weakness of the evaluated tools and these can be used to improve existing climate services tools. This will also help in better decision making and policy planning for different sectors that are being impacted by the changing climate.

The purpose of this study is to provide data which will enable administrators, through climate assessment, to make concrete decisions regarding perceptions that can be utilized in targeting areas within the school which need intervention or improvement. The main emphasis of the study is to assess various stakeholders' perceptions regarding school variables (teacher/student relationships, security and maintenance, administration, student academic orientation, student behavioral values, guidance, student/peer relationships, parent and community/school relationships, instructional management, and student activities) and to note perceptual trends, similarities, and differences among stakeholder groups. Much of the existing literature views climate as a separate, yet related, component of effective schools. This study's focus is on better understanding climate from the ecological perspective, viewing climate as a tool in which school climate research can be used in school improvement programs to ensure consistency in conceptualizing and measuring school climate. This study goes beyond many in that it attempts to understand climate from various stakeholders' perceptions, and to discern any patterns or relationships among these. Unlike the previous studies of school climate which consider the perceptions of only one or two groups, this concept of school climate is driven by the shared perceptions of key stakeholder groups in the school operation of itself--Board members, Administration, classified staff, the students, teachers, and parents/community members. Because an inductive research method is most appropriate for a study of this type, a quasi-case study approach was selected as the research procedure. The following data analysis process was used in the study, for each of the ten subcategories of respondent, gender, ethnicity, and group/role, an analysis of variance and test of significance were conducted. These results are presented according to the research questions and subcategory. The contribution that this study makes is in the analysis of climate data. The data presented, looking at group means in the climate subcategories to give a broad, general impression of the school's climate. As the data were broken apart and regrouped, important patterns emerged. This information provides much more specific guidance in targeting school improvement, as well as delineating precisely the subcategories of particular concern to various stakeholder groups. This approach to unpacking the school climate concept takes advantage of the multiple characteristics of this school climate study, and acknowledges the different interests of groups within a school. Given scarce resources and competition for people's time, a finer grained analysis of a school's problems is a rational beginning to focused interventions.

The prediction of the Earth's climate system is of immediate importance to many decision-makers. Anthropogenic climate change is a key area of public policy and will likely have widespread impacts across the world over the 21st Century. Understanding potential climate changes, and their magnitudes, is important for effective decision making. The principal tools used to provide such climate predictions are physical models, some of the largest and most complex models ever built. Evaluation of state-of-the-art climate models is vital to understanding our ability to make statements about future climate. This Thesis presents a framework for the analysis of climate models in light of their inherent uncertainties and principles of statistical good practice. The assessment of uncertainties in model predictions to-date is incomplete and warrants more attention that it has previously received. This Thesis aims to motivate a more thorough investigation of climate models as fit for use in decision-support. The behaviour of climate models is explored using data from the largest ever climate modelling experiment, the climateprediction.net project. The availability of a large set of simulations allows novel methods of analysis for the exploration of the uncertainties present in climate simulations. It is shown that climate models are capable of producing very different behaviour and that the associated uncertainties can be large. Whilst no results are found that cast doubt on the hypothesis that greenhouse gases are a significant driver of climate change, the range of behaviour shown in the climateprediction.net data set has implications for our ability to predict future climate and for the interpretation of climate model output. It is argued that uncertainties should be explored and communicated to users of climate predictions in such a way that decision-makers are aware of the relative robustness of climate model output.

Most of nowadays base load LNG plants are localized in the area around equator, with stable warm air and cooling water temperature. For new LNG developments in arctic areas there are several features that differ them from plants operating further south. In this work a ConocoPhillips Optimized Cascade LNG process model has been established in HYSYS® and evaluated. The evaluation focus on the driver configuration and cooling method used in order to optimize process efficiency and capacity of the plant for operation in cold climate. Simulations with air cooling and water cooling have been done. Each cooling method has been evaluated for an aero derivative gas turbine compressor driver, an industrial heavy duty gas turbine compressor driver, and an electric compressor driver configuration. Yearly temperature statistics from Kola has been used. The air cooled simulations have a design temperature of 20°C and the water cooled simulations have a design temperature of 4°C seawater temperature and an air temperature of 5°C. The air cooled cases are not close to design operation the entire year. The aero derivative driver configuration will have problems operating at high air temperatures and a higher design temperature is needed. The heavy duty gas turbine driver configurations have limitation in speed variation and this leads to low process efficiency at low temperatures. The electrical driver configuration will not have problems operating. The results show that air cooling is not the desired cooling method because of lower production variation and lower process efficiency. The water cooled cases are close to design conditions the entire year; hence it has the highest flexibility when it comes to production variation and highest process efficiency. The aero derivative driver configuration varies most throughout the year with lowest production in the summer. The heavy duty gas turbine driver configuration has a lower variation in production. The power delivered to the electrical motors will not be affected by air temperature which lead to high process efficiency and stable production plateau throughout the year.

Mestrado em Meteorologia e Oceanografia Física
O objetivo deste trabalho é a análise da performance de Modelos Climáticos Regionais (RCMs) e Globais (GCMs) na Península Ibérica. Para tal, foram utilizados dados de precipitação, temperatura máxima e mínima (aos 2 metros) para o passado recente (1962-2000) disponibilizados pelo projeto ENSEMBLES, bem como dados observados da European Climate Assessment & Dataset (ECA&D). A análise foi separada em duas secções: a avaliação de performance dos modelos regionais (utilizando o ensemble das simulações forçadas pelas reanálises ERA40) e a avaliação dos modelos globais (utilizando o ensemble de simulações de modelos regionais forçados por modelos globais). Foram calculadas as climatologias sazonais das variáveis originais, bem como as tendências de índices, de forma a verificar a capacidade dos ensembles de simular as variáveis, os seus extremos e variabilidade temporal. Para alem disso, calcularam-se parâmetros estatísticos, como o Erro Quadrático Médio (RMSE), o viés, o desvio padrão e o Coeficiente de Correlação de Pearson. Com o objetivo de verificar se as distribuições modeladas dos índices são estatisticamente semelhantes, utilizou-se o teste de Kolmogorov- Smirnov. Concluiu-se que o ensemble das simulações forçadas pelas reanálises ERA40 mostram melhor performance, enquanto que a incerteza associada ao ensemble das simulações forçadas por GCMs é superior. Os índices de precipitação que mostram a ocorrência de dias secos têm melhor performance que os que contabilizam os dias molhados. Ambas as temperaturas mostram diferenças entre observações e ensembles inferiores ás da precipitação, bem como melhor representação dos padrões espaciais. No entanto, os dados modelados mostram pior performance em zonas de orografia complexa e ao longo de zonas costeiras, tanto para as variáveis originais como para os índices extremos. A análise dos dados observados mostra que há, em geral, aumento no número de dias em que a temperatura Máxima esteve acima do percentil 90 e uma diminuição no número de dias em que a precipitação foi acima do percentil 90 e a temperatura mínima foi abaixo do percentil 10. Embora não apresentando sempre significância estatística, as tendências destes índices apontam para a existência de alterações climáticas que ocorreram na Península Ibérica durante o século XX.
The goal of this work is to analyse the performance of both Regional Climate Models and simulations where these are driven by Global Climate Models over the Iberian Peninsula. To do so, ENSEMBLES datasets of precipitation, maximum and minimum temperature (at 2 meters) for the recent-past (1961-2000) were used, as well as the European Climate Assessment & Dataset (ECA&D) observed data. The analysis is performed in two parts: RCM performance evaluation (using ERA40- driven simulation ensemble) and GCM performance evaluation (using the ensemble of RCM-GCM simulations). Seasonal climatologies of the original variables, as well as trends of the indices were analysed in order to evaluate the ensembles' ability to simulate the variables, their extremes and their time variability. The skill of the ensembles was measured using statistics such as the root mean square error, BIAS, standard deviation error and Pearson correlation coe_cient. Two sample Kolmogorov-Smirnov tests were performed to verify the similarity of the distributions of the yearly indices. It was found that ERA40-driven ensemble shows results more closely related to the observations than GCM-driven ensemble. Furthermore, the uncertainty associated with the GCM-driven ensemble is generally higher than that of ERA40-driven. Precipitation indices that evaluate the occurrence of dry days perform better than the wet days indices. Temperature shows smaller difference between observations and models and higher spatial pattern reproduction. However, models show lower skill and performance in areas of complex orography and along the coastline, for the original variables, as well as the extreme indices. The analysis of the observed data, showed an overall increase in number of days with maximum temperature over the 90th percentile and a decrease in number of days with precipitation over the 90th percentile and minimum temperature under the 10th percentile. Although not always statistically significant these trends point to changes in the Iberian climate that have already taken place during the 20th century.

A substantial segment of the error in numerical weather prediction and climate projections comes from the intrinsic uncertainties of General Circulation Models of the atmosphere. Stochastic physics schemes are one of the preferred methods to represent the model uncertainty in Ensemble Prediction Systems, where different realizations of the same forecast are created to quantify the probabilities of different outcomes in the atmospheric flow. Stochastic physics schemes have been successfully employed in medium-range and seasonal forecasting systems, as they increase the skill of probabilistic forecasts. Similarly it has been demonstrated than these schemes can improve certain aspects of the model's climate. However, it is still not clear whether they are a truthful representation of the model uncertainties they aim to represent. In this thesis, a collection of stochastic physics schemes are evaluated using a seamless approach. It is found that they can improve the representation of the tropical climate and extra-tropical cyclones, but they degrade the individual representation of these processes deteriorating the deterministic skill of the model. Some important features of the model can be degraded by the stochastic physics schemes, like energy and moisture conservation on climate scales. Some closures to the schemes are proposed and successfully tested to remove or reduce some of the problems found. Alternative approaches in the development of stochastic parametrizations are also investigated. Stochastic physics schemes have some benefits but still require further development to produce a realistic representation of model error. It is also recommended that evaluation methodologies must be expanded to include process-based diagnostics to display the realism of its perturbations.

Increasing concern about energy consumption and thesimultaneous need for an acceptable thermal environment makesit necessary to estimate in advance what effect differentthermal factors will have on the occupants. Temperaturemeasurements alone do not account for all climate effects onthe human body and especially not for local effects ofconvection and radiation. People as well as thermal manikinscan detect heat loss changes on local body parts. This factmakes it appropriate to develop measurement methods andcomputer models with the corresponding working principles andlevels of resolution. One purpose of this thesis is to linktogether results from these various investigation techniqueswith the aim of assessing different effects of the thermalclimate on people. The results can be used to facilitatedetailed evaluations of thermal influences both in indoorenvironments in buildings and in different types ofvehicles.

This thesis presents a comprehensive and detaileddescription of the theories and methods behind full-scalemeasurements with thermal manikins. This is done with new,extended definitions of the concept of equivalent temperature,and new theories describing equivalent temperature as avector-valued function. One specific advantage is that thelocally measured or simulated results are presented with newlydeveloped "comfort zone diagrams". These diagrams provide newways of taking into consideration both seat zone qualities aswell as the influence of different clothing types on theclimate assessment with "clothing-independent" comfort zonediagrams.

Today, different types of computer programs such as CAD(Computer Aided Design) and CFD (Computational Fluid Dynamics)are used for product development, simulation and testing of,for instance, HVAC (Heating, Ventilation and Air Conditioning)systems, particularly in the building and vehicle industry.Three different climate evaluation methods are used andcompared in this thesis: human subjective measurements, manikinmeasurements and computer modelling. A detailed description ispresented of how developed simulation methods can be used toevaluate the influence of thermal climate in existing andplanned environments. In different climate situationssubjective human experiences are compared to heat lossmeasurements and simulations with thermal manikins. Thecalculation relationships developed in this research agree wellwith full-scale measurements and subject experiments indifferent thermal environments. The use of temperature and flowfield data from CFD calculations as input produces acceptableresults, especially in relatively homogeneous environments. Inmore heterogeneous environments the deviations are slightlylarger. Possible reasons for this are presented along withsuggestions for continued research, new relationships andcomputer codes.

Key-words:equivalent temperature, subject, thermalmanikin, mannequin, thermal climate assessment, heat loss,office environment, cabin climate, ventilated seat, computermodel, CFD, clothing-independent, comfort zone diagram.

This thesis assesses regional and temporal dependent biases in several microwave rainfall climatologies and considers their implications for monitoring the El Nino Southern Oscillation. Seasonal rainfall climatologies from the Tropical Rainfall Measuring Mission (TRMM) are evaluated during the transition from the 1997/1998 El Nino to the 1998/2000 La Nina. The satellite algorithms include version 5 TRMM rainfall products (GPROF (2A12), COMBINED (2B31) and PR (2A25», several passive microwave algorithms and GPCP (Global Precipitation Climatology Project) satellite-gauge estimates. All are compared to GPCC (Global Precipitation Climatology Centre) gauge estimates and two benchmark climatologies. The passive microwave algorithms are spatially and temporally calibrated to the Precipitation Radar using the histogram matching approach, which minimises spatial and temporal algorithm biases. Each algorithm detects seasonal and inter-annual variations in the rainfall distributions, although absolute values are shown to be significantly different. Despite three year quasiglobal averages converging to within -20%, zonal averages show large variations in the magnitude of the biases, e.g. >55% (-30%) for the austral (boreal) summer over land and >40% (-20-25%) during El Nifio (La Nina) over the ocean. Fine-scale comparisons show regional differences vary from <20% to >200%. Biases are attributed to variations in cloud microphysical characteristics, sampling problems and passive microwave coastal and surface artefacts. Unless temporal and spatial algorithm biases are accounted for, all satellite retrievals should be restricted to qualitative assessments of climatic rainfall.

In order to make informed decisions in response to future climate change, researchers, policy-makers, and the public need climate projections at the scale of few kilometers, rather than the scales provided by Global Climate Models. The North American Regional Climate Change Assessment Program (NARCCAP) is such a recent effort that addresses this necessity. As the climate models contain various levels of uncertainty, it is essential to evaluate the performance of such models and their representativeness of regional climate characteristics. When assessing climate change impacts, precipitation is a crucial variable, due to its direct influence on many aspects of our natural-human ecosystems such as freshwater resources, agriculture and energy production, and health and infrastructure. The current study performs an evaluation analysis of precipitation simulations produced by a set of dynamically downscaled climate models provided by the NARCCAP program. The Assessment analysis is implemented for a period that covers 20 to 30 years (1970-1999), depending on joint availability of both the observational and the NARCCAP datasets. In addition to direct comparison versus observations, the hindcast NARCCAP simulations are used within a hydrologic modeling analysis for a regional ecosystem in coastal Louisiana (Chenier Plain). The study concludes the NARCCAP simulations have systematic biases in representing average precipitation amounts, but are successful at capturing some of the characteristics on spatial and temporal variability. The study also reveals the effect of precipitation on salinity concentrations in the Chenier Plain as a result of using different precipitation forcing fields. In the future, special efforts should be made to reduce biases in the NARCCAP simulations, which can then lead to a better presentation of regional climate scenarios for use by decision makers and resource managers.

Diese Dissertation beschäftigt sich mit regionaler Klimamodellierung über Südamerika, der Analyse von Modellsensitivitäten bezüglich Wolkenparametrisierungen und der Entwicklung neuer Methoden zur Modellevaluierung mithilfe von Klimanetzwerken. Im ersten Teil untersuchen wir Simulationen mit dem COnsortium for Small scale MOdeling model in CLimate Mode (COSMO-CLM) und stellen die erste umfassende Evaluierung dieses dynamischen regionalen Klimamodells über Südamerika vor. Dabei untersuchen wir insbesondere die Abhängigkeit simulierter tropischer Niederschläge von Parametrisierungen subgitterskaliger cumuliformer und stratiformer Wolken und finden starke Sensitivitäten bezüglich beider Wolkenparametrisierungen über Land. Durch einen simultanen Austausch der entsprechenden Schemata gelingt uns eine beträchtliche Reduzierung von Fehlern in klimatologischen Niederschlags- und Strahlungsmitteln, die das COSMO-CLM über tropischen Regionen für lange Zeit charakterisierten. Im zweiten Teil führen wir neue Metriken für die Evaluierung von Klimamodellen bezüglich räumlicher Kovariabilitäten ein. Im Kern bestehen diese Metriken aus Unähnlichkeitsmaßen für den Vergleich von simulierten mit beobachteten Klimanetzwerken. Wir entwickeln lokale und globale Unähnlichkeitsmaße zum Zwecke der Darstellung lokaler Unähnlichkeiten in Form von Fehlerkarten sowie der Rangordnung von Modellen durch Zusammenfassung lokaler zu globalen Unähnlichkeiten. Die neuen Maße werden dann für eine vergleichende Evaluierung regionaler Klimasimulationen mit COSMO-CLM und dem Statistical Analogue Resampling Scheme über Südamerika verwendet. Dabei vergleichen wir die sich ergebenden Modellrangfolgen mit solchen basierend auf mittleren quadratischen Abweichungen klimatologischer Mittelwerte und Varianzen und untersuchen die Abhängigkeit dieser Rangfolgen von der betrachteten Jahreszeit, Variable, dem verwendeten Referenzdatensatz und Klimanetzwerktyp.
This dissertation is about regional climate modeling over South America, the analysis of model sensitivities to cloud parameterizations, and the development of novel model evaluation techniques based on climate networks. In the first part we examine simulations with the COnsortium for Small scale MOdeling weather prediction model in CLimate Mode (COSMO-CLM) and provide the first thorough evaluation of this dynamical regional climate model over South America. We focus our analysis on the sensitivity of simulated tropical precipitation to the parameterizations of subgrid-scale cumuliform and stratiform clouds. It is shown that COSMO-CLM is strongly sensitive to both cloud parameterizations over tropical land. Using nondefault cumulus and stratus parameterization schemes we are able to considerably reduce long-standing precipitation and radiation biases that have plagued COSMO-CLM across tropical domains. In the second part we introduce new performance metrics for climate model evaluation with respect to spatial covariabilities. In essence, these metrics consist of dissimilarity measures for climate networks constructed from simulations and observations. We develop both local and global dissimilarity measures to facilitate the depiction of local dissimilarities in the form of bias maps as well as the aggregation of those local to global dissimilarities for the purposes of climate model intercomparison and ranking. The new measures are then applied for a comparative evaluation of regional climate simulations with COSMO-CLM and the STatistical Analogue Resampling Scheme (STARS) over South America. We compare model rankings obtained with our new performance metrics to those obtained with conventional root-mean-square errors of climatological mean values and variances, and analyze how these rankings depend on season, variable, reference data set, and climate network type.

Awareness of anthropogenic climate change has increased drastically in the last decade. With the help of the United Nations and the 17 sustainable development goals, there is now an international consensus that measures must be taken urgently. Actions towards reducing our climate impact have started to take place in various industries and one important sector is the food sector. This thesis is addressed to companies that help consumers make smarter and more climate friendly food decisions with the help of climate data. More specifically the scope of this thesis was to develop and evaluate a climate impact visualization application with consumers as the intended target group. The foundation of the intervention included theories in behaviour change and information visualization design principles. The application was evaluated with 11 participants looking to reduce their climate impact. A user study was conducted where the participants used the developed intervention by completing different tasks and then evaluated the experience and the different components of the application. The purpose of the evaluation was to gain qualitative insights of which components should be considered in the development process of a final product. The results indicate that visualizations of the products carbon dioxide emissions, receipt list and personal progress tracking were the most important components for the application. The result also gave positive indications that a similar application could help change the user’s behaviour when purchasing food to a more climate friendly pattern.
Medvetenheten om antropogena klimatförändringar har ökat drastiskt under det senaste decenniet. Med hjälp av FN och de 17 målen för hållbar utveckling finns det nu en internationell enighet om att åtgärder måste vidtas snarast. Åtgärder för att minska vår klimatpåverkan har börjat äga rum i olika branscher och en viktig sektor är livsmedelssektorn. Denna avhandling riktar sig till företag som hjälper konsumenter att fatta smartare och mer klimatvänliga livsmedelsbeslut med hjälp av klimatdata. Mer specifikt omfattar denna avhandling att utveckla och utvärdera en visualiseringsapplikation för klimatpåverkan med konsumenter som den avsedda målgruppen. Grunden för interventionen inkluderar teorier inom beteendeförändring och design-principer för informationsvisualisering. Applikationen utvärderades med 11 deltagare som ville minska sin klimatpåverkan. En användarstudie genomfördes där deltagarna använde den utvecklade applikationen genom att utföra olika uppgifter för att sedan utvärdera upplevelsen och de olika komponenterna i applikationen. Syftet med utvärderingen var att få kvalitativa insikter om vilka komponenter som bör beaktas i utvecklingsprocessen för en slutprodukt. Resultaten indikerar att visualiseringar av produkternas koldioxidutsläpp, kvittolista och personlig framstegsspårning var de viktigaste komponenterna för applikationen. Resultatet gav också positiva indikationer på att en liknande applikation skulle kunna hjälpa till att ändra användarens beteende när man handlar mat till ett mer klimatvänligt mönster.

Contending with a changing climate presents a necessary push for planning. Although climate change is considered a global environmental problem requiring a global commitment and trans-national action, more and more, policymakers are recognizing the vital need for action at the local level. In the US, especially in the absence of national climate legislation, many local governments have begun developing strategic plans, or climate action plans (CAPs), to address adapting to impacts of climate change and mitigating greenhouse gas emissions. This thesis involves case studies of Portland, OR and Chicago, IL, cities with recently adopted CAPs and with considerable recognition in the field. The analysis involves an evaluation each city’s CAP and an evaluation of its implementation. The studies help elicit an understanding of the measures cites are employing to mitigate climate change and determine ways the planning profession can better assist communities in climate policy development and its prompt implementation.

El objetivo de investigación ha sido determinar la implicancia del clima organizacional en la gestión institucional de la Superintendencia Nacional de Aseguramiento en Salud. La hipótesis general ha comprobado la existencia de una relación directa y significativa entre el clima organizacional y la gestión institucional; obteniéndose una débil relación entre las variables. The research objective has been to determine the implication of the organizational climate in the institutional management of the National Superintendence of Health Insurance. The The general hypothesis has proven the existence of a direct and significant relationship between the organizational climate and institutional management; obtaining a weak relationship between variables

Perceived failures in top-down climate governance and many emerging bottom-up activities have prompted scholars to pay more attention to the promise and limits of polycentric governance, in which activities are spread across many levels, actors, and scales (E. Ostrom, 2010c; E. Ostrom, 2014b). In adopting the Paris Agreement, policy makers also appear to be moving in the direction of greater polycentricity. But many aspects of polycentric governance remain theoretically and empirically underexplored, especially with a view to policy evaluation, a vital but often neglected governance activity. This thesis addresses these gaps by: (1) considering the potential (theoretical) role of policy evaluation in polycentric governance and (2) empirically exploring the case of the European Union, an active adopter and evaluator of climate policy whose climate governance has been described as polycentric. The thesis argues that polycentric governance theory is based on three foundational ideas, namely that that actors can and do self-organize, that context matters in governance, and that governance centres, while independent, interact in order to fully realize the benefits of polycentric governance. These foundational ideas provide a means to explore climate policy evaluation, and to connect with related debates in the evaluation literatures. Fresh empirical data from a new database of 618 climate policy evaluations (1997-2014) suggest that formal (state) actors produced many more evaluations that informal (societal) ones-pointing to limited self-organization and a key role for public actors in evaluation-but that informal evaluations also emerged in empirically detectable and relevant quantities. By using a new coding scheme to analyse a sub-set of the evaluations this thesis reveals that the limited attention to various contextual factors and the fact that climate policy evaluation tends to happen in and focus on individual governance centres restricts the potential travel of evaluative insights from one governance centre to another. In toto, the empirical characteristics equip climate policy evaluation only partially to facilitate polycentric climate governance in the EU.

Abstract: This study evaluated future climate change impacts on water resources, extreme discharges and sediment yields for the medium-sized (705-km2) agriculture dominated Cobres basin, Portugal, in the context of anti-desertification strategies. We applied the physically-based spatially-distributed hydrological model—SHETRAN, obtaining the optimized parameters and spatial resolution by using the Modified Shuffled Complex Evolution (MSCE) method and the Non-dominated Sorting Genetic Algorithm II (NSGA-II), to simulate the hydrological processes of runoff and sediment transport. We used the model RanSim V3, the rainfall conditioned weather generator—ICAAM-WG, developed in this study, based on the modified Climate Research Unit daily Weather Generator (CRU-WG), and SHETRAN, to downscale projections of change for 2041–2070, from the RCM HadRM3Q0 with boundary conditions provided by the AOGCM HadCM3Q0, provided by the ENSEMBLES project, under SRES A1B emission scenario. We found future climate with increased meteorological, agricultural and hydrological droughts. The future mean annual rainfall, actual evapotranspiration, runoff and sediment yield are projected to decrease by the orders of magnitude of respectively ~88 mm (19%), ~41 mm (11%), ~48 mm (50%) and ~1.06 t/ha/year (45%). We also found reductions in extreme runoff and sediment discharges, for return periods smaller than 20 years; however for return periods in the range of 20–50 years, future extremes are of the same order of magnitude of those in the reference climate; Modelação integrada para avaliação dos impactos das alterações climáticas sobre bacias hidrográficas com uso predominantemente agrícola Resumo: Neste estudo são avaliados os impactos futuros das alterações climáticas nos recursos hídricos e em extremos do escoamento e transporte de sedimentos, na bacia hidrográfica do rio Cobres, Portugal, agrícola, de dimensão média (705 Km2), no contexto do combate à desertificação. Foi aplicado o modelo hidrológico fisicamente baseado e espacialmente distribuído SHETRAN, tendo sido obtidos os valores optimizados de parâmetros e da resolução espacial, utilizando o método “Modified Shuffled Complex Evolution” (MSCE) e o algoritmo “Non-dominated Sorting Genetic Algorithm II” (NSGA-II), para simular os processos hidrológicos de escoamento e transportes de sedimentos. Foram utilizados o modelo de RainSim V3, o gerador de tempo ICAAM-WG, desenvolvido neste estudo, baseado no CRU-WG, e o SHETRAN, para o “downscaling” das projecções climáticas para 2041 – 2070, geradas pelo MRC HadRM3Q0 com condições de fronteira fornecida pelo MCG HadCM3Q0, projecto ENSEMBLES, sob o cenário SRES A1B. O clima futuro é caracterizado por um número crescente de secas meteorológicas, agrícolas e hidrológicas. Os valores médios anuais da precipitação, evapotranspiração real, escoamento superficial e transporte de sedimentos, revelam decréscimos com ordens de grandeza respectivamente de ~88 mm (19%), ~41 mm (11%), ~48 mm (50%) e ~1.06 t/há/ano (45%). Encontraram-se ainda reduções nos valores extremos do escoamento superficial e do transporte de sedimentos para períodos de retorno inferiores a 20 anos; contudo, para períodos de retorno no intervalo 20–50 anos, os valores extremos futuros apresentam a mesma ordem de grandeza que os relativos ao período de referência mas mantendo níveis equivalentes para os com 20–50 anos.

Resource managers and decision-makers are increasingly tasked with integrating climate change science into their decisions about resource management and policy development. This often requires climate scientists, resource managers, and decision-makers to work collaboratively throughout the research processes, an approach to knowledge development that is often called "coproduction of knowledge." The goal of this paper is to synthesize the social science theory of coproduction of knowledge, the metrics currently used to evaluate usable or actionable science in several federal agencies, and insights from experienced climate researchers and program managers to develop a set of 45 indicators supporting an evaluation framework for coproduced usable climate science. Here the proposed indicators and results from two case studies that were used to test the indicators are presented, as well as lessons about the process of evaluating the coproduction of knowledge and collaboratively producing climate knowledge.

This thesis explores the ability of global climate models (GCMs) to simulate observed conditions at regional scales by examining probability density functions (PDFs) of daily minimum temperature (Tmin), maximum temperature (Tmax) and precipitation (P). Two new measures of model skill are proposed using PDFs of observed and modelled data. The first metric (Sscore) compares the amount of overlap between the two PDFs. The second metric (Tailskill) is the weighted difference between the PDF tails, where extreme events are represented. The resulting measures of skill are used to differentiate, at a regional scale, between weaker and stronger models. It is investigated whether the weaker models bias future projections given by multi-model ensembles, increasing the uncertainty in the range of projected values and the change from the 20th Century. The Sscore is demonstrated to be robust against inhomogenities found in highdensity Australian datasets, and is a simple and quantitative measure of how well each GCM can simulate all observed events. This methodology is executed for twelve Australian regions of varying climates for all Intergovernmental Panel on Climate Change 4th Assessment Report models for which daily data was available for 1961-2000. Across Tmin, Tmax and P some GCMs perform well, demonstrating that some GCMs provide credible simulations of climate at sub-continental scales. Projections of the annual and seasonal mean and yearly return values over the A2 and B1 emission scenarios are investigated. Models are omitted from an ensemble based on their ability to simulate the observed PDF at regional scales. The stronger models are generally in agreement with the change in mean values, particularly for Tmin and Tmax, though it is shown that they vary in their projections of the yearly return value at least twice as much as projections in the mean values. Lastly, a means-based evaluation method, the Sscore and the Tailskill are employed to differentiate between weaker and stronger models for projections in the 20-year return value of Tmin and Tmax. Weaker-skilled ensembles project larger increases in 20-year return values than stronger-skilled ensembles, such that in some regions for maximum temperature the ensembles are statistically significantly different. Demonstrably weaker models bias projections given by an all-model ensemble and should be excluded so the most reliable estimates of future climate can be obtained.

Climate models have anticipated higher future extreme precipitations and streamflows for various regions. Urban stormwater facilities are vulnerable to these changes as the design assumes stationarity. However, recent climate change studies have argued about the existence of non-stationarity of the climate. Distribution method adopted on extreme precipitation varies spatially and may not always follow same distribution method. In this research, two different natural extremities were analyzed for two separate study areas. First, the future design storm depth based on the stationarity of climate and GEV distribution method was examined with non-stationarity and best fit distribution. Second, future design flood was analyzed and routed on a river to estimate the future flooding. Climate models from North American Regional Climate Change Assessment Program (NARCCAP) and Coupled Model Intercomparison Project phase 5 (CMIP5) were fitted to 27 different distribution using Chi-square and Kolmogorov Smirnov goodness of fit. The best fit distribution method was used to calculate design storm depth as well as design flood. Climate change scenarios were adopted as delta change factor, a downscaling approach to transfer historical design value to the climate adopted future design value. Most of the delta change factor calculated were higher than one, representing strong climate change impact on future. HEC-HMS and HEC-RAS models were used to simulate the stormwater infrastructures and river flow. The result shows an adverse effect on stormwater infrastructure in the future. The research highlights the importance of available climate information and suggests a possible approach for climate change adaptation on stormwater design practice.

The purpose of this study was to determine the relationship between organizational school climate and middle school student achievement on state assessments. The author also sought to determine the relative weight of each of the factors of school organizational climate (collegial leadership, teacher professionalism, academic press and community engagement) in relation to student achievement. Finally, this study examined the relative effects of organizational climate and the socio-economic status (SES) of participating schools on student achievement.;Suburban, rural and urban middle schools in Virginia participated in this study. The study explored middle school teachers' perceptions regarding organizational school climate in terms of collegial leadership, teacher professionalism, academic press, and community engagement. The School Climate Index (SCI) was used to survey 696 teachers' perceptions of these factors in 49 middle schools in Virginia. The eighth grade Virginia Standards of Learning (SOL) Tests in the areas of math and English were the measurement tools for student achievement in the study.;It was concluded that there was a significant relationship between organizational climate and student achievement for both English and math. When the sub-scales of school climate (collegial leadership, teacher professionalism, academic press and community engagement) were analyzed separately, multiple regression indicated that only community engagement had a significant independent effect on student achievement on the math SOL test. Both academic press and community engagement had independent effects on student achievement on the English SOL test. Further analysis indicated that SES had a significant independent effect on student achievement in English, while both school climate and SES had independent effects on student achievement on the math SOL test. School climate and SES explained much of the variance in student achievement.

The researcher conducted a mixed-methods study at a private, Midwestern, Predominantly White institution in order to determine the relationship between minority student perceptions of higher education and minority student perceptions of their institution. The goal of the study was to determine whether minority student perceptions of the climate and culture of their institution influenced their perception of higher education as a whole. Another objective was to determine whether minority student perceptions connected to minority student retention. To determine the relationship, the researcher surveyed 20 undergraduate, African American students and conducted one-on-one interviews with three of the students between the fall of 2017 and the summer of 2018.

The researcher analyzed the results of the climate and culture perceptions survey instruments to determine relationships between minority student perceptions of the culture of higher education and minority student perceptions of the culture of their school. Secondly, the researcher analyzed the relationship between minority student perceptions of the climate of higher education and minority student perceptions of the climate of the school. Through quantitative analysis, the researcher determined there was no relationship between minority student perceptions of the culture and climate of higher education broadly, and their perceptions of the culture and climate of their institution.

Qualitative analyses suggested students believed their perception of school climate and culture mirrored the climate and culture of higher education. Perceptions included facing racism and microaggressions, a lack of support from faculty, and not feeling intentionally included in campus programming all while having a sense of safety on campus. Regardless of whether student perceptions of higher education were positive or negative, each student who did not graduate that year intended to return the following academic year. Individual reasons for intent to return determined the relationship between minority student perceptions of higher education and minority student retention.

Recommendations from the researcher included exploring mentoring programs geared toward minority students, investigating the benefits of a diversity course for all students, implementing an African American Studies program, conducting research focused on reasons minority students remain at an institution, and the functionality of other groups considered minority in higher education. Exploring the aforementioned suggestions in depth could lead to a better overall understanding of how minority students can receive support and experience more retention in higher education.

This multimethod, multiphase study was designed to determine the impact of charter school reform on achievement in North Carolina. The study was designed to be an analysis of the relationship between classroom climate, interactions, and student achievement, through a complexity systems context. This methodology allowed for combined qualitative, quantitative, network analysis, and agent-based modeling to capture the simple, complicated, complex, and chaotic interactions in classrooms. The data for the study were drawn from eighth-grade mathematics teachers and students at four charter schools in a North Carolina urban area (n = 300). Through the analysis of data, a more detailed and nuanced picture of the relationship between classroom climate, interactions, and charter school achievement emerged. The findings suggest that teacher control and second-semester math grades are statistically significant; the higher the level of control teachers exercise, the higher students score on common core achievement. According to the findings of this study, North Carolina charter schools have served as a successful reform strategy to address the achievement gap problem in North Carolina, with school-specific strategies including high teacher support, students’ teaching students, IAP/tutoring/online supplemental program, and small classrooms. All schools, on average, scored 30.9% to 56.8% higher on grade-level proficiency (GLP) than the North Carolina 2014–2015 average. The network analysis showed how classrooms can be more or less complex in different ways with instructional, emotional support, and behavior management interactions that fit into network structures of teacher to one-student, teacher to whole class, whole class to teacher, and student to student or students. The predictive ABM, based on achievement scores over time, school achievement strategy, classroom climate, high teacher control, and second-semester math grades, demonstrated accuracy. The ABM captured macroclassroom and microstudent outcomes, along with climate changes based on interactions that either increased or reduced positive climate. This is important because a teacher has limited resources and must deal with uncontrollable influences from outside the classroom. Teachers have the power to create a positive or negative climate by their verbal and nonverbal interactions. Teachers’ interactions have consequences that impact students’ achievement and students’ lives. Consequently, every interaction matters.

The core analysis of this work is divided in three different but thematically related studies, analysing, first, how climate change policies can help to limiting global warming and one of its direct causes, the emission of greenhouse gases (GHG); second, how such policies can foster “green” technological change; and, third, how technological change can help to reach ambitious policy goals outlined in Europe’s 2020 climate and energy package. Respectively, in the first work with the title “Emission Abatement: Untangling the effects of the EU ETS and the Economic Crisis”, I seek to untangle the effects of the European Union Emission Trading System (EU EST) against the impact of the economic crisis 2008/2009 with respect to GHG emissions for sectors subject to the policy. Thereby, an Arellano-Bond regression is performed due to the dynamic character of the estimation equation. One of the major conclusions of this chapter is, that the EU ETS was only responsible for a minor part of emission abatement whilst the economic downturn accounted for the lion’s share which led to the built-up of an excess of emission allowances in the market and hampered policy stringency under the EU ETS. In the second study “Policy Stringency under the European Union Emission Trading System and its Impact on Technological Change in the Energy Sector”, therefore, I am interested to analysis how this negative evolution, on the one side, and an increase of stringency, on the other, affects innovative activity. For this reason, I relate two measures for policy stringency, namely the certificate oversupply in the market and the transition from phase I to phase II under the EU ETS, to “green” technological change approximated by climate change mitigation technology (CCMT) patent counts. Thereby, I am interested to measure the effects of these two different but not mutually exclusive impacts on the estimated number of patents in my data sample. For this empirical exercise, I make use of a panel negative binomial estimator due to the distributional characteristics of the patent data in my data frame. The main results for this study is, that policy stringency matters in order to spur technological change. Thereby, greater stringency measured in the transition from phase I to phase II is related to an increase in the predicted number of patents. On the other side, decreasing stringency, measured by the excess supply of certificates in the market, is related to a decrease in the predicted number of patents. In the last work “Climate Change Mitigation and the Role of Technologic Change: Impact on selected headline targets of Europe’s 2020 climate and energy package” an impact assessment of these CCMTs is performed with respect to different policy goal measures of Europe’s 2020 climate and energy package. Thereby, I relate CCMT patents for energy generation and distribution to the goal of a 20% share of renewables in gross final energy consumption and well CCMTs to total final energy consumption and to final energy consumption in the transport sector, respectively, to the goal of a 20% increase in energy efficiency. As a regression method, a panel fixed effects approach is chosen. Thereby, the main observation is, that these technologies can make a different if goals are reached or not and, that penetration for final users differs among goals and sectors. In the last chapter, a summary of the obtained results is presented and the respective policy implications for the EU ETS and the development and deployment of CCMTs.

This Thesis explored a range of approaches to study the uncertainty and impacts associated with climate change at the farm scale in Scotland. The research objective was to use a process of uncertainty evaluation and simulation modelling to provide evidence of how primary production components of agriculture in Scotland may change under a future climate. The work used a generic Integrated Modelling Framework to structure the following sequence of investigations: Evaluate a Regional Climate Model‟s hindcast estimates (1960-1990) against observed weather data; Develop bias correction „downscaling factors‟ to be applied to the Regional Climate Model‟s future estimates; Evaluate the impacts of weather data sources (observed and modelled) on estimates made by a cropping systems model (CropSyst); Estimate values for a range of agro-meteorological metrics using observed and estimated downscaled future weather data; Simulate spring barley and winter wheat growth using CropSyst with observed and modelled weather data; Develop CropSyst in order to represent grass growth, evaluate estimates against a set of a priori criteria and determine suitability for use in a whole farm model. Conduct counter-factual assessments of the impacts of climate change and potential adaptation options using a whole farm model (LADSS). The study aimed to use tools on a spectrum of land use modelling complexity: agro-meteorological metrics (simple), CropSyst (intermediate), and the whole-farm integrated model (complex). Such an approach had a path dependency, in that to use the livestock system model component within the whole farm model, CropSyst had to make estimates of an acceptable quality for grass production. CropSyst however failed to meet the a priori evaluation criteria. This, coupled with technical and time constraints in running LADSS, led to the decision not to run the whole farm model. The findings were organised within the concepts of resilience and adaptive capacity. Results gained showed that the HadRM3 Regional Climate Model was capable of making both good and poor estimates of weather variables in the UK, and that downscaling improved the match between hindcast and observed weather data significantly. A sensitivity analysis involving introducing uncertainty from weather data sources within CropSyst showed that care was needed in interpreting estimates of future crop production. The agro-meteorological metrics indicated that whilst growing season length increases, the date of end of field capacity does not. The projected changes in crop production will likely be more positive if crop responses to elevated CO2 are considered. However, there will be additional constraints on crop growth due to increases in duration and magnitude of periods of growth limiting soil water deficits. Without adaptation to crop varieties with slower phenological development, yield decreases are seen in spring barley and winter wheat. The thesis concludes, whilst recognising the caveats and limitations of the methods used and the multiple range of external influencing issues, that the biophysical impacts at the farm scale in Scotland are within the boundaries of resilience, given that achievable adaptation options exist and are undertaken. The dynamics of farm scale management will need to adjust to cope with higher levels of water stress, but opportunities will also arise for greater flexibility in land use mixes. Crop yield can increase due to more favourable growing conditions and cultivar adaptations. These conclusions, when placed within the context of climate change impacts and adaptive cycles at a global scale, indicate that agriculture in Scotland has the potential to cope with the impacts but that substantial changes are required in farming practices.

Statistically downscaled CMIP5 precipitation data are available at higher spatial resolution compared to global climate models. The downscaled climate models have been used in many hydrological applications. However, limited numbers of studies focused on downscaled CMIP5 precipitation data for Louisiana. Statistically downscaled precipitation data for Louisiana is critically needed for various water resources engineering, planning and design purposes. This study has focused on assessing the skill of CMIP5 climate models in reproducing observed precipitation of Louisiana and application of CMIP5 precipitation data to analyze the impact of precipitation on hydrology (salinity and water level). Assessment of CMIP5 precipitation showed that statistically downscaled and bias corrected precipitation data reproduce observed average annual precipitation. But for other statistics (standard deviation), model data are not the same as observation data. The bias correction procedure ensured that models would reproduce the observed average precipitation. The maps of correlation distance for the models do not match with that of observation. This may be an indication that bias correction does not force the model to perform better in all statistics except annual average. Based on the analysis over climate divisions, it can be stated that spatial and temporal aggregation enables the models to perform better than gridded dataset. Application of CMIP5 precipitation data indicates that precipitation has a significant effect on salinity and almost zero effect on water level. Different salinity variables control the hydrologic and habitat suitability indices in coastal Louisiana. The cell-based analysis shows that different variables have different degrees of effect on vegetation and species (brown shrimp and oyster). Some species thrive in a high salinity environment while some others in low salinity. The uncertainty in the salinity and water level may occur due to insufficient data and boundary conditions provided in the Eco-hydrology model environment.

This strategic marketing thesis explores the effects of the service environment (servicescape) on customers' loyalty intentions towards UK restaurants. To obtain a deeper understanding of approach-avoidance behaviour, the study draws from broadly parallel perspectives in the economics, psychology and organizational behaviour academies, in conceptualizing and operationalizing loyalty intentions. The organizational behaviour domain was particularly integral to the study as the climate and culture of an organization were shown to respectively determine the cues placed in the servicescape and the performance of service staff, thereby proving useful lenses through which the servicescape could be explored, conceptualized and rigorously tested. In furtherance of conceptualization efforts, a model was developed to evaluate the linear influences of nine servicescape variables on customers' loyalty intentions. Additionally, the model appraised the impact of personal and environmental factors which were believed to moderate the servicescape - loyalty intentions relationship. The insertion of nine servicescape variables and four moderating factors into the model allowed for the development of a global configuration of the servicescape and provided a variation to the traditional servicescapes model. The results of rigorous statistical and econometric testing support ten of the thirteen advanced hypotheses, thus sustaining the adoption of an organizational behaviour perspective as a legitimate approach to servicescape study. To validate these findings, triangulate empirical results and add richness to the study, a series of focus group sessions were conducted to obtain high-quality data on customers' perceptions of servicescape cues. The findings of these sessions were shown to complement utilized empirical techniques and enrich understanding of the restaurant servicescape via the organizational behaviour domain. Consequently, organizational climate and organizational culture should, at the very least, be equated in importance to overall services marketing strategy.

Lipids preserved in soils and sediments are important proxies in paleoclimate research. However, various growth conditions that affect the organisms synthesizing the lipids can in turn affect the abundance and stable isotopic compositions of the lipids themselves, and, consequently, can introduce significant errors in the paleoclimatic inferences drawn from them. This work examines how two climate proxies based on lipids, namely, glycerol dialkyl glycerol tetraether (GDGT)-based paleotemperature proxies in soils, and paleohydrological proxies based on hydrogen isotopic composition of lipids, respond to variability in environmental and other growth conditions (e.g., carbon source).

In order to evaluate the role of annual precipitation amount on the distribution of soil GDGTs and on GDGT-based temperature proxies in soils, we studied GDGT distribution in soils collected from two environmental transects in the USA—a dry, western transect covering six western states and a wet, east coast transect from Maine to Georgia. Our results indicate a significant impact of precipitation amount on soil GDGT distribution, which is related to soil aeration that in turn depends on precipitation amount, and also to soil pH. Our results also indicate that below an annual precipitation of 700-800 mm yr^–1 the MBT/CBT-temperature proxy based on soil GDGTs is not applicable. Furthermore, due to the distinct GDGT distributions in soils under arid conditions, soil input into lacustrine or marginal marine environments cannot be estimated using BIT index.

In order to estimate the effects of variability in environmental conditions and utilization of different substrates on D/H_lipid, we studied two heterotrophic organisms—Haloarcula marismortui, a halophilic archaeon and Tetrahymena thermophila, a ciliated protozoan, in pure cultures. Our results from experiments with H. marismortui indicate that metabolism of different substrates leads to formation of reducing agents (mainly nicotinamide adenine dinucleotide phosphate or NADPH) with distinct D/H signatures, which is reflected in the significant D/H variations in isoprenoidal lipids (ca. 100‰). Growth temperature affects growth rate as well as enzyme activities, and salinity of the growth media affects mainly growth rate of H. marismortui, and both cause similar variations in D/H_lipid (ca. 20-30‰) that are smaller compared to the substrate-effect. T. thermophila , on the other hand, responds to variations in growth temperature in a different manner. Isoprenoid and fatty acids synthesized by T. thermophila generally become more D-enriched with temperature increase. The isoprenoid ranges from being D-depleted to D-enriched relative to water with temperature increase, but the fatty acids do not display similar patterns. Our results from T. thermophila culture experiments indicate that temperature has a critical control on the D/H ratios of NADPH and possibly also intracellular water, due probably to temperature effects on processes that are related to growth and metabolism of T. thermophila.

In the context of a rapidly changing world, higher order thinking skills are necessary for sustainability of U.S. society. Beginning with the premise that U.S. public schools are charged with the constitutional duty of growing children into informed and educated citizens, prepared to thrive in the world of work and to participate in democratic processes; and, that higher order thinking is a core part of that mission, this study examined children’s perspectives on school climate and the environment for the teaching and learning of higher order thinking in twenty five public elementary schools in an urban Connecticut school district. This integrated program of research used an exploratory sequential/concurrent mixed methods design to construct a pair of new psychometric instruments to measure student attitudes toward school climate and the environment for teaching and learning higher order thinking in a public elementary school. The intended uses and interpretations of the scores reported by the Climate4Creativity Elementary (C4C/SPE) and Middle School (C4C/SPM) Student Perspectives measurement instruments, were validated to professional standards. The study concluded that these instruments have utility for public elementary schools, particularly in identifying areas of focus and in the management of strategic and tactical school improvement work as part of a wider program of transformation in a school. Cronbach’s Alpha reliability scores in excess of 0.90 were reported for all measures. This study supported the core idea that safer schools with stronger, more caring communities provide individual students with better learning environments, and that general learning and the learning of creativity are intrinsically linked in the minds of students in public elementary schools, even though these students may not always name these components as such. The environment for learning higher order thinking measure tends to deteriorate from the early grades to middle school grades, implying both raised expectations, and an increase in variability in the data due to more and more variety in classroom settings and teacher practices. Examination of reported bullying experience shows bullying victimization to be a powerful, pervasive determinant of school climate and feelings of safety and community in all grades, but, bullying victimization tends not to penetrate into perceptions of the classroom learning environment to the same degree. By exploring school safety, community, and the structure of the learning environment required for the teaching and learning of higher order thinking in a public elementary school, this work begins the creation of a framework to enable school leaders to make significant, transformational, strategic change in their schools.

Programs and reforms have come and gone in the educational arena with little impact on student performance. The problem at the school of study was the students' perception of their sense of belonging and the sense of the school as a community and the students' academic performance did not show adequate growth. The study took place in a mid-western suburban elementary school serving 440 students kindergarten through fifth grade.

The significance of the study was to examine the impact of a Goal-Setting Worksheet, along with regular teacher-student conferences, as a strategy to improve the overall school climate and academic achievement as measured by climate survey results, standardized test scores, attendance rates, and office referrals.

The process allowed teachers and students in 3rd, 4th, and 5th grade the opportunity to work together to complete the Goal-Setting Worksheet by setting goals, establishing a plan of action, and providing feedback through conferences throughout the goal-setting period. Students assessed their progress and worked with the teachers to determine if the student needed to revisit their goal or establish a new goal. The purpose of this process was to increase the students' perception of their sense of belonging and academic achievement.

To determine if there was a change in the students' perception of school climate, students took the Caring School Community climate spring survey and the pre and post School Climate survey. Academic performance was measured by comparing scores on the Missouri Assessment Program Communication Arts and Math test and the Gates-MacGinitie Reading Test. Survey results and academic scores were compared over a four year period.

The results were that the implementation of the goal-setting worksheet and teacher-student conferences to school climate did not yield the desired change at the school of study in the areas of overall school climate or academic achievement. However, the understanding of the value of the two has influenced the staff to continue the desire, process, and pursuit to improve the students' perception of the school climate and increase academic performance. Because of the limited timeframe of the study, further investigation of this process is recommended.

Cette thèse traite de la coopération et de la gouvernance climat dans l'ère post Copenhague. Son objectif est de caractériser l'évolution du régime climatique, prenant appui sur les positions de l'Union européenne, la Chine et les États-Unis, qui peuvent être désignés, à la fois en tant que gros émetteurs, économies majeures et grandes puissances. Deux déterminants sont considérés structurants pour cette analyse : les coûts d'atténuation des émissions et les coûts d'adaptation. Le point de départ de notre thèse se trouve dans l'évolution polarisée du régime climatique. Le fait le plus marquant de cette « métamorphose » est le passage, en 2009, de l'approche top-down à une approche bottom-up.Pour ce faire, nous mobilisons un cadre théorique hybride, qui comprend l'Économie politique internationale et l'économie du changement climatique. L'apport combiné de ces deux approches permet d'analyser la politique internationale du climat à travers l'économie de l'environnement et inversement, de renseigner l'incidence que ces relations peuvent avoir sur la logique économique. Nous proposons une approche spécifique de la coopération, basée sur la théorie du « k-groupe » de Duncan Snidal (1985).Dans ce cadre coopératif minilatéral, la thèse que nous soutenons est qu'il est possible d'avoir un k-groupe pour le climat et que celui-ci peut avoir un effet bénéfique sur la mise en place du régime climat. Nous argumentons que ce groupe peut être considéré comme un « club of the relevant » et que, pour former un k-groupe, il est nécessaire que les pays constituent une « coalition of the willing ». Ce qui structure la capacité et la volonté de l'action, ce sont principalement les coûts que cela implique, coûts d'atténuation et d'adaptation. En même temps, l'engagement de ce groupe se base sur le conditionnement. Le dispositif incitatif est constitué par l'idée d'une coopération de plus en plus large, qui atténue le problème du passager clandestin.Les résultats de recherche sont appréciés à la lumière de l'aboutissement de la COP 21. Si le k-groupe fonctionne, c'est que les trois pays décident d'aller de l'avant et acceptent d'endosser des coûts d'atténuation plus importants que les autres pays. Cet engagement collectif déclencherait un mouvement vertueux qui imposerait au régime climat un leadership partagé entre ces trois pays, ouvrant la voie aux autres. Si le k-groupe ne fonctionne pas, c'est parce que nos acteurs considèrent les coûts à court terme trop importants au regard de leurs propres intérêts et au regard du risque du free riding de la part des autres États. Compte tenu de la conjoncture économique dans laquelle se trouvent nos trois acteurs, ce scénario apparait comme étant probable.Enfin, dans notre modèle de l'analyse de la coopération nous privilégions le tandem Europe-Chine. Nous montrons que cette coopération tripartite devrait se construire à partir de ce binôme, du moment où, à la différence des États-Unis, c'est l'Europe qui apparait comme étant plus volontaire. La Chine, l'acteur incontournable du climat, qui risque de subir les conséquences du changement climatique de plein fouet, a plus d'intérêt à se rallier à l'Europe si elle souhaite obtenir un accord qui ne soit pas basé uniquement sur des contributions (nationales) minimales
Our research focuses on the cooperation and climate governance in the post-Copenhagen era. Its main purpose is to observe and define the evolution of the climate regime, based on the positions of the European Union, China and the United States. These three countries can be considered as big emitters, major economies, as well as great powers. Two main drivers are taken into account in our analysis: mitigation and adaptation costs to climate change. The starting point for our research is to be found in the polarized evolution of the climate regime. The most illustrative aspect of this “metamorphosis” is the shift, in 2009, from the top-down to the bottom-up architecture of the climate regime.Thus, we resort to a hybrid theoretical background, which consists of both international political economy and climate change economy. The joint contribution of the two approaches allows us to analyze international political economy with climate economy as an input, as well as the impact of international relations on the main economic framework of climate change. Our research is based on a specific cooperation model, known as the “k-group” theory, as developed by Duncan Snidal (1985).Within this framework of minilateral cooperation, the thesis that we defend is that it is possible to have a climate k-group which may have a trigger effect in order to obtain an ambitious regime. The starting point for our argument is that this group can be considered as a “club of the relevant”, and that what it needs to achieve in order to constitute a k-group is to establish a “coalition of the willing”. The capacity and the willingness to act are mainly influenced by the costs they have to bear, that is the costs to mitigate their emissions and to adapt to the climate change consequences. Meanwhile, the group's collective commitment depends on other countries' actions. More precisely, the incentive mechanism is built on the idea that cooperation is meant to widen, in order to eventually prevent free riding.Our main results are to be regarded in the light of the COP 21 outcome. If the k-group works, it is because our three countries decide to move forward and accept to bear mitigation costs that are higher than those of other countries'. Their collective commitment should trigger a virtuous dynamic which would impose on climate regime a collective leadership of these three countries, thus leaving the others with no other way than to follow. If the k-group does not work, it is because our three actors consider upfront costs too high with respect to their own interests, as well as to the risk of free riding (if the others do not go along). Given our three actors' economic and political context, this scenario seems likely.Finally, we rather favor in our work the Europe-China tandem. We argue that the k-group should be built on this joint cooperation, since, unlike the United States, Europe appears to be more willing to endorse an ambitious regime, whereas China seems an unavoidable actor. Thus, China, which faces a major impact of climate change, should play along with Europe if it wishes to obtain an agreement that is not solely based on minimal (national) contributions

Drought is one of the most severe natural disasters and detrimentally impacts water resources, agricultural production, the environment, and the economy. Climate change is expected to influence the frequency and severity of extreme droughts. This dissertation evaluates drought conditions using a variety of hydrologic modeling approaches include short-term drought forecasting, long-term drought projection, and a coupled surface-groundwater dynamic drought assessment. The economic impacts of drought are also explored through a linked economic impact model. Study results highlight the need for various drought assessment approaches and provide insights into the array of tools and techniques that can be employed to generate decision-support tools for drought mitigation plans and water resource allocation. For short-term drought forecasting, the Soil and Water Assessment Tool (SWAT) and Variable Infiltration Capacity (VIC) models are used with a meteorological forecasting dataset. Results indicate that eight weeks of lead-time drought forecasting show good drought predictability for the Contiguous United States (CONUS). For the drought projection at a finer scale, both SWAT and VIC models are applied with Coupled Model Intercomparison Project Phase 5 (CMIP5) climate model outputs to derive multiple drought indices for the Chesapeake Bay watershed and five river basins in Virginia. The results indicate that current climate change projections will lead to increased drought in the entire Chesapeake Bay watershed and Virginia river basins because of increases in the sum of evapotranspiration, and surface and groundwater discharge. The impacts of climate change on future agricultural droughts and associated economy-wide implications are then evaluated using the VIC and IMPLAN (IMpact analysis for PLANning) model for the several congressional districts in Virginia. The result indicated that increases in agricultural drought in the future would lead to decreases in agricultural productions and job losses. Finally, a coupled framework using the VIC and MODFLOW models is implemented for the Chesapeake Bay and the Northern Atlantic Coastal Plain aquifer system, and the results of a drought index that incorporates groundwater conditions performs better for some drought periods. Hydrologic modeling framework with multiple hydrologic models and various scales can provide a better understanding of drought assessments because the comparisons and contrasts of diverse methods are available.
PHD

This study investigated teacher targeted bullying in primary schools to examine whether students serve as an unsafe work stressor for teachers, because teacher targeted bullying is on the rise. This study looked at teacher targeted bullying as an antecedent of stress and the mechanisms, such as mediators and moderators, which affected this bullying-stress relationship. 113 primary school teachers completed a self-report questionnaire which measured bullying, self-efficacy, safety climate perceptions, social support and stress. The results provided evidence that social support from others outside work moderated the mow level bullying-stress, and severe bullying-stress relationships. Most importantly, unsafe job perceptions mediated the relationship between low level bullying and stress. The results of this research imply that student bullying can influence teachers to perceive their job as unsafe and lead to stress. These findings can be used to develop effective strategies to not only prevent and manage bullying, but create safer schools for teachers and pupils.

The construction industry leads the private sector with the most fatalities of any industry in the United States. With an expected growth of the industry in the next century, safe work environments are imperative. They will impact the bottom line of the industry through the reduction of fatal and non-fatal injuries. Although the causes of injuries and illnesses in construction have long been tracked, reported and researched, the industry continues to lead in occupational related fatal and non-fatal injuries. It is critical to understand if a tradeoff exists between safety and productivity to avoid shortcut behaviors in the field. This is specifically important due to the number of contractors, subcontractors and laborers that participate in the different projects. The overall objective of this research was to increase the understanding of the relationship between perceived and observed safety and productivity and to understand the variability in perception and behavior between crews working for the same general contractor in the homebuilding construction industry. For this research, questionnaires and behavioral observations were employed. The results demonstrated a significant moderate positive relationship between safety climate and perceived risk behavior at the crew level. A model was developed that suggests that safety climate and work ownership are predictors of perceived risk behaviors. This relationship is important to understand since employee attitudes, safety commitment and organizational factors may affect acceptability of safety processes and procedures. The differences among construction crews were evaluated at two levels, individual crews and critical path groups. All tests were significant for differences among crews. To further understand these differences, crews were grouped in accordance with the critical path of a homebuilding schedule. A significant difference existed for risk behavior, productivity loss and work ownership. Behavioral observations were used to evaluate crew performance. Top contributing behaviors of productivity, safety and waste were identified. The top behaviors provide improvement areas for productivity, safety and waste. Overall, learning from this research provided insight into the relationships between safety climate, risk behavior, productivity and work ownership. Understanding this relationship can contribute to the design of safety interventions, and consequently, the reduction of injuries and fatalities.
Ph. D.

This study was guided by Deci and Ryan’s (2015) self-determination theory, which focuses on meeting three specific psychological needs: autonomy, relatedness, and competence. The literature review for this study included topics relating to alternative education such as educational reform, school improvement, school climate, student discipline, intervention strategies, at-risk students, and the achievement gap. This study involved determining the effectiveness of alternative schools through a mixed-methods examination of graduation rates, school climate, student motivation, and academic rigor in high schools from the southwest Missouri region. Graduation rate data were compared from school districts without alternative schools and those with alternative schools utilizing a t-test. The mean of the graduation rates of districts with alternative schools was significantly higher than districts without alternative schools. Quantitative data collection continued via a survey designed to measure the degree to which high school principals report an improved school climate upon implementation of an alternative school. These data demonstrated an improved school climate within the traditional school due to the implementation of an alternative school. Qualitative data collection consisted of interviewing subject-area high school teachers and alternative school teachers from randomly selected school districts in southwest Missouri. These interviews were designed and conducted by the researcher to gather teacher perceptions of the degree of student motivation and academic rigor evident among alternative school students within their respective school districts. These data demonstrated increased student motivation with mixed results pertaining to academic rigor in alternative schools.

In 2017, the Swedish Parliament voted for a climate aim which says Sweden should achieve zero net emissions of greenhouse gases in 2045. The building and construction sector is one of the sectors that needs to reduce it’s climate impact. As of 2016, 12.8 million tons of CO2-equivalents was estimated emitted from the sector, which represented about 21 percent oftotal amounts of GHG-gases emitted from Sweden in that year. Several studies has shown that the operational energy use in the life cycle of buildings is source to the majority of the emissions. This thesis was written in collaboration with Skanska Sweden, a Swedish construction company. Currently, there is no available value for the CO2-emissions emitted per m2 from the operational energy use in facilities and households at Skanska Sweden. The aim of this report is therefore to estimate the CO2-emissions emitted per m2 from various building types.This has been achieved through data investigations of what data is available and missing. Furthermore, methodologies have been investigated as well as energy sources for various buildings. Then the emissions were calculated as CO2-eq/m2 per building type. A sensitivity scenario was additionally performed by calcuating climate impact from different electric grids (Swedish, Nordic and European). Finally, a future energy scenario was investigated for2050 to estimate future climate impact from the operational energy use in various building types. The energy data was based on two different databases, Base and Follow Up, whereas Base presented estimated energy interval values. Follow Up presented estimated and verified values. In the data collection, a categorisation was made depending on the various building types Skanska Sweden produces. The 7 categories was Houses, Multi-dwelling buildings,Offices, Care centers, Schools, Pre-schools and Other. The findings were that in all categories but two (schools and offices), the operational energy use is higher when the values are verified, rather than estimated. Recommendations are therefore to increase the amount of available verified values, however, at the same time the amount of estimated values need to increase as well as many categories had a deficient amount of available data, this to increase the reliability of the results. The difference in calculated climate impact is relatively large between categories, depending on energy sources for heating and hot tap water. For instance is the climate impact lowest for Houses when the majority of the energy comes from electricity. At the same time, the climate impact from the category Other is highest, which is because the energy use is high, but additionally because the majority of the energy comes from district heating. Overall, this energy source has higher climate impact than when the electricity is used. Nevertheless, it should be observed that the difference in categories is overall huge, depending on the chosen electricity grid. Future emissions (2050) will be significantly lower than today, especially when the European grid and the EU reference scenario is chosen, but will be dependent on electricity prices additionally. However, if the Swedish climate aim of climate neutrality will be achieved, the climate impact from the operational energy will be minimal in 2050. An important aspect in environmental evaluations of energy is methodological choice. In this project, the attributional perspective has been chosen, however, many studies imply the importance of margin energy, which the attributional perspective does not include.Furthermore, the attributional may present a lower climate impact than when other methodologies are chosen. It is therefore important to be aware of the methodology used and recommendations for future studies would be to investigate the methods more thouroughly.
Under 2017 röstade svenska riksdagen igenom en klimatlag som begränsar klimatpåverkan till netto noll år 2045 från samtliga sektorer. Bygg- och fastighetssektorn är en sektor medstor klimatpåverkan och utgjorde år 2016 21 procent (12.8 miljoner ton) av totala utsläpp i Sverige. Historiskt sett har energianvändningen i drift av byggnader utgjort majoriteten av utsläppen från bygg- och fastighetssektorn och är därför en viktig del att utforska. Skanska Sverige är ett svenskt byggföretag och detta arbete har gjorts i samarbete med företaget. För tillfället finns inget värde på CO2-utsläppen kopplade till energin i drift av byggnader (hushåll och lokaler) som byggts av Skanska Sverige och målet med denna rapport är därför att estimera CO2-utsläpp/m2 från olika byggnadstyper. Detta har upnåtts genom att bland annat utforska vilken data som finns tillgänglig och vad som saknats, samt att utforska metodval och energikällor för olika byggnader för att sedan omvandla energidatan til lgenererade CO2-utsläpp/m2. Vidare utfördes en känslighetsanalys genom att beräkna CO2/m2 för olika elnät (svenskt, nordiskt och europeiskt). Slutligen har även ett framtida energiscenario beräknat för år 2050 använts för att beräkna klimatutsläpp från driftenergin iframtiden. Datan är baserad på två olika databaser, Base och Follow Up, där Base har endast redovisat estimerade energivärden som anges som intervall av nio kWh, samtidigt har Follow Up redovisat både estimerade och verifierade värden. På grund av större datatillgänglighet i Base valdes denna att huvudsakligen basera beräkningar på, men Follow Up och dess verifierade värden har använts till jämförelse. En kategorisering gjordes beroende av vilka byggnadstyper Skanska producerar mest av. De 7 kategorierna var småhus (villor och radhus), flerfamiljshus (lägenheter), kontor, sjukhem, förskolor, skolor och övrigt som inkluderade bland annat sjukhus och hotell. Resultaten har visat att i alla kategorier utom två (skolor och kontor) är energianvändning högre när energin är verifierad än när den är estimerad. Rekommendationer är därför att öka antalet verifierade värden som samlas in, samtidigt som de estimerade även behöver öka för att öka pålitligheten av resultaten då många kategorier har begränsad mängd indata. Skillnaden i beräknad klimatpåverkan är relativt stor mellan olika kategorier, beroende av energikällor för värme och varmvatten. Exempelvis är klimatpåverkan lägst för småhus då största andelen energitillförsel för småhus utgörs av elektricitet. Samtidigt är klimatpåverkan hög från kategori Other, vilket till stor del beror på att energianvändningen (kWh/m2) är hög, men även på grund av att majoriteten av energitillförseln kommer från fjärrvärme. Generellt sett har denna energikälla högre klimatpåverkan. Dock skall det observeras att skillnaden inom kategorier även den är stor, beroende av vilket elnät som valts. Exempelvis är skillnaden stor mellan småhus där elnätet som använts är svenskt, och när elnätet varit europeiskt. Framtida utsläpp kommer vara betydligt lägre än idag, speciellt när det europeiska nätet väljs och EUs referensscenario är utforskat, men är även beroende av framtida elpriser och satsningar på förnybart. Ska det svenska målet om klimatneutralitet 2045 dock uppfyllas kommer klimatpåverkan vara minimal år 2050. En viktig aspekt vid miljövärdering av energi är metodval. I detta projekt har bokföringsperspektivet använts, men flertalet studier har påpekat vikten av att inkludera marginalenergi, samt visat att perspektivet ofta redovisar lägre klimatpåverkan än till exempel konsekvensperspektivet. Det är därför viktigt att vara medveten om vilken metodik som väljs och framtida rekommendationer för studier är förslagsvis att utforska flera metoder,gärna parallellt för att se skillnader.