Competitiveness Comparison of the Electricity Production Alternatives

The competitiveness comparison is carried out for merely electricity producing alternatives. In Finland, further construction of CHP (combined heat and power) power plants will continue and cover part of the future power supply deficit, but also new condensing power plant capacity will be needed. The following types of power plants are studied: - nuclear power plant, - coal-fired condensing power plant - combined cycle gas turbine plant, - peat-fired condensing power plant. - wood-fired condensing power plant - wind power plant The calculations have been made using the annuity method with a real interest rate of 5 % perannum and with a fixed price level as of March 2003. With the annual full load utilization time of 8000 hours the nuclear electricity would cost 23,7 ¤/MWh, the gas based electricity 32,3 ¤/MWh and coal based electricity 28,1 ¤/MWh. If the influence of emission trading is taken into account,the advantage of the nuclear power will still be improved. Inorder to study the impact of changes in the input data, a sensitivity analysis has been carried out. It reveals that the advantage of the nuclear power is quite clear. E.g. the nuclear electricity is rather insensitive tothe changes of the uranium price, whereas for natural gas alternative the rising trend of gas price causes the greatest risk.

Statistical Analysis of an SEIR Epidemic Model

This thesis was focussed on statistical analysis methods and proposes the use of Bayesian inference to extract information contained in experimental data by estimating Ebola model parameters. The model is a system of differential equations expressing the behavior and dynamics of Ebola. Two sets of data (onset and death data) were both used to estimate parameters, which has not been done by previous researchers in (Chowell, 2004). To be able to use both data, a new version of the model has been built. Model parameters have been estimated and then used to calculate the basic reproduction number and to study the disease-free equilibrium. Estimates of the parameters were useful to determine how well the model fits the data and how good estimates were, in terms of the information they provided about the possible relationship between variables. The solution showed that Ebola model fits the observed onset data at 98.95% and the observed death data at 93.6%. Since Bayesian inference can not be performed analytically, the Markov chain Monte Carlo approach has been used to generate samples from the posterior distribution over parameters. Samples have been used to check the accuracy of the model and other characteristics of the target posteriors.

Bayesian analysis of SEIR epidemic models

This thesis concerns the analysis of epidemic models. We adopt the Bayesian paradigm and develop suitable Markov Chain Monte Carlo (MCMC) algorithms. This is done by considering an Ebola outbreak in the Democratic Republic of Congo, former Zaïre, 1995 as a case of SEIR epidemic models. We model the Ebola epidemic deterministically using ODEs and stochastically through SDEs to take into account a possible bias in each compartment. Since the model has unknown parameters, we use different methods to estimate them such as least squares, maximum likelihood and MCMC. The motivation behind choosing MCMC over other existing methods in this thesis is that it has the ability to tackle complicated nonlinear problems with large number of parameters. First, in a deterministic Ebola model, we compute the likelihood function by sum of square of residuals method and estimate parameters using the LSQ and MCMC methods. We sample parameters and then use them to calculate the basic reproduction number and to study the disease-free equilibrium. From the sampled chain from the posterior, we test the convergence diagnostic and confirm the viability of the model. The results show that the Ebola model fits the observed onset data with high precision, and all the unknown model parameters are well identified. Second, we convert the ODE model into a SDE Ebola model. We compute the likelihood function using extended Kalman filter (EKF) and estimate parameters again. The motivation of using the SDE formulation here is to consider the impact of modelling errors. Moreover, the EKF approach allows us to formulate a filtered likelihood for the parameters of such a stochastic model. We use the MCMC procedure to attain the posterior distributions of the parameters of the SDE Ebola model drift and diffusion parts. In this thesis, we analyse two cases: (1) the model error covariance matrix of the dynamic noise is close to zero , i.e. only small stochasticity added into the model. The results are then similar to the ones got from deterministic Ebola model, even if methods of computing the likelihood function are different (2) the model error covariance matrix is different from zero, i.e. a considerable stochasticity is introduced into the Ebola model. This accounts for the situation where we would know that the model is not exact. As a results, we obtain parameter posteriors with larger variances. Consequently, the model predictions then show larger uncertainties, in accordance with the assumption of an incomplete model.

Building climate justice : an analysis of how the nexus between climate change and human rights shapes public policy agendas and alternatives

This thesis provides an analysis of how the nexus between climate change and human rights shapes public policy agendas and alternatives. It draws upon seminal work conducted by John Kingdon, whose landmark publication “Agendas, alternatives, and public policy” described how separate streams of problems, solutions, and politics converge to move an issue onto the public policy agenda toward potential government action. Building on Kingdon’s framework, this research explores how human rights contribute to surfacing the problem of climate change; developing alternative approaches to tackling climate change; and improving the political environment necessary for addressing climate change with sufficient ambition. The study reveals that climate change undermines the realization of human rights and that human rights can be effective tools in building climate resilience. This analysis was developed using a mixed methods approach and drawing upon substantial literature review, the researcher’s own participation in international climate policy design; elite interviews with thought leaders dealing with climate change and human rights; and regular inputs from focus groups comprised of practitioners drawn from the fields of climate change, development and human rights. This is a journal based thesis with a total of six articles submitted for evaluation, published in peer‐reviewed publications, over a five year period. Denna avhandling analyserar hur klimatfrågan och mänskliga rättigheter i samverkan formar den politiska agendan och det politiskt möjliga. Den bygger på banbrytande forskning av John Kingdon, vars publikation “Agendas, alternatives, and public policy” beskriver hur en fråga blir politiskt viktig och lyfts upp på den politiska agendan. Med utgångspunkt i Kingdons ramverk, utforskar avhandlingen hur mänskliga rättigheter bidrar till att blottlägga klimatfrågan som problem; utveckla alternativa metoder för att angripa och hantera klimatfrågan; samt skapa ett politiskt klimat nödvändigt för att på ett ambitiöst sätt kunna angripa klimatfrågan. Studien visar att klimatförändringar undergräver mänskliga rättigheterna men att arbete med mänskliga rättigheter kan vara ett effektivt verktyg för att stå emot och hantera effekterna av klimatförändringar. Analysen har genomförts med hjälp av en rad olika metoder vilka inkluderar litteraturstudier, författarens egna observationer under klimatförhandlingar; intervjuer med ledande tänkare inom klimatfrågan och mänskliga rättigheter; samt data insamlad genom fokusgrupper bestående av yrkesverksamma inom klimat, utveckling och mänskliga rättigheter. Avhandlingen är baserad på totalt sex artiklar som publicerats i fackgranskade tidskrifter under en femårsperiod.