1,560 research outputs found

    Bayesian spatio-temporal modelling for forecasting ground level ozone concentration levels

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    Accurate, instantaneous and high resolution spatial air-quality information can better inform the public and regulatory agencies of the air pollution levels that could cause adverse health effects. The most direct way to obtain accurate air quality information is from measurements made at surface monitoring stations across a study region of interest. Typically, however, air monitoring sites are sparsely and irregularly spaced over large areas. That is why, it is now very important to develop space-time models for air pollution which can produce accurate spatial predictions and temporal forecasts.This thesis focuses on developing spatio-temporal models for interpolating and forecasting ground level ozone concentration levels over a vast study region in the eastern United States. These models incorporate output from a computer simulation model known as the Community Multi-scale Air Quality (Eta-CMAQ) forecast model that can forecast up to 24 hours in advance. However, these forecasts are known to be biased. The models proposed hereare shown to improve upon these forecasts for a two-week study period during August 2005.The forecasting problems in both hourly and daily time units are investigated in detail. A fast method, based on Gaussian models is constructed for instantaneous interpolation and forecasts of hourly data. A more complexdynamic model, requiring the use of Markov chain Monte Carlo (MCMC) techniques, is developed for forecasting daily ozone concentration levels. A set of model validation analyses shows that the prediction maps that are generated by the aforementioned models are more accurate than the maps based solely on the Eta-CMAQ forecast data. A non-Gaussian measurement error model is also considered when forecasting the extreme levels of ozone concentration. All of the methods presented are based on Bayesian methods and MCMC sampling techniques are used in exploring posterior and predictive distributions

    Structural Modelling And Analysis Of The Behavioural Dynamics Of Foreign Exchange Rate [HG3851. Y51 2006 f rb].

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    Tesis ini berkaitan dengan Kadar Wang Pertukaran Asing (KWPA) yang dihasilkan oleh satu regime urusniaga bebas. Pada amnya, kita mengkaji Pemodelan Struktur dan Analisis Tingkahlaku Dinamik Kadar Pertukaran Wang Asing. This thesis deals specifically with the foreign exchange rates that resulted from free float regimes. In general, we study the structural modelling and analysis of the behavioural dynamics of foreign exchange rates

    Disrupting Desalination: Novel Energy Efficient Technologies for Hypersaline Brines

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    Management and treatment of hypersaline brines, e.g., produced water from oil and gas extraction, zero liquid discharge effluent, and flue gas desulfurization wastewater, are of growing environmental importance. Prevailing practice of distilling brines is highly energy-intensive and costly because the evaporation of water is enthalpically unfavorable. Here, we present two novel technologies for hypersaline desalination: cascading osmotically mediated reverse osmosis (COMRO) and temperature swing solvent extraction (TSSE). The first technology, COMRO, utilizes the novel design of bilateral countercurrent reverse osmosis stages to lessening the osmotic pressure difference across the membrane, thereby simultaneously depressing the hydraulic pressure needed and reducing energy demand. The second technology, TSSE, is membrane-less, not based on evaporative phase-change, and utilizes low-grade waste heat to drive the separation. Working principles of the technologies are presented, the desalination performance are examined, and implications for the treatment of hypersaline brines are discussed

    The impacts of oil shocks on Malaysia's GDP growth

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    This paper suggests that instrumental variable regression is a good alternative to nonlinear specification model when estimating the impacts of oil shocks on GDP growth in Malaysia

    Thermodynamic and Energy Efficiency Analysis of Power Generation from Natural Salinity Gradients by Pressure Retarded Osmosis

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    The Gibbs free energy of mixing dissipated when fresh river water flows into the sea can be harnessed for sustainable power generation. Pressure retarded osmosis (PRO) is one of the methods proposed to generate power from natural salinity gradients. In this study, we carry out a thermodynamic and energy efficiency analysis of PRO work extraction. First, we present a reversible thermodynamic model for PRO and verify that the theoretical maximum extractable work in a reversible PRO process is identical to the Gibbs free energy of mixing. Work extraction in an irreversible constant-pressure PRO process is then examined. We derive an expression for the maximum extractable work in a constant-pressure PRO process and show that it is less than the ideal work (i.e., Gibbs free energy of mixing) due to inefficiencies intrinsic to the process. These inherent inefficiencies are attributed to (i) frictional losses required to overcome hydraulic resistance and drive water permeation and (ii) unutilized energy due to the discontinuation of water permeation when the osmotic pressure difference becomes equal to the applied hydraulic pressure. The highest extractable work in constant-pressure PRO with a seawater draw solution and river water feed solution is 0.75 kWh/m3 while the free energy of mixing is 0.81 kWh/m3—a thermodynamic extraction efficiency of 91.1%. Our analysis further reveals that the operational objective to achieve high power density in a practical PRO process is inconsistent with the goal of maximum energy extraction. This study demonstrates thermodynamic and energetic approaches for PRO and offers insights on actual energy accessible for utilization in PRO power generation through salinity gradients
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