This study analyzes the quantifiable impacts of low impact development features, sometimes referred to as green infrastructure, across three alternative proposals for the development of a city district along the edge of a lake and a creek. Low impact development is defined as a stormwater management approach designed to capture water before it goes into stormwater drains or directly into bodies of water in order to allow the water to infiltrate groundwater sources or evapotranspirtate back into the atmosphere. The study applies Carl Steinitz’s Framework for GeoDesign to the three alternative proposals and the existing conditions as a means of comparison in order to understand an informed decision based approach to design. / text

published_or_final_version / Medical Sciences / Master / Master of Medical Sciences

published_or_final_version / Geography / Doctoral / Doctor of Philosophy

With the implementation of the pilot Emission Trading Schemes (ETSs) in China since 2013, there emerges a new opportunity for investing in Chinese green technology (greentech) projects. Apart from trading the international CERs (Certified Emissions Reductions), investors nowadays can also trade the CCERs (Chinese Certified Emissions Reductions) in the domestic carbon market. However, the pricing of CCERs is different from that of CERs due to the distinct climate policies in China, thus making the investment decisions in Chinese greentech projects a complicated problem. This study is, to our knowledge, the first attempt to evaluate greentech projects under uncertain climate policies in developing countries like China. To identify the investment environment of Chinese greentech projects, a qualitative research on the development of climate policies and greentech market is first conducted. Based on the study of international climate polices and carbon markets, the pricing mechanisms of carbon assets (carbon allowances and carbon offsets) are investigated. Furthermore, China’s climate polices, including the energy policies and emission reduction policies, are analysed in detail. In addition, both the administrative and economic instruments used in China’s climate policies are investigated. Then, business opportunities and challenges in greentech market are investigated. It is shown that there is substantial demand for greentech projects, and the uncertainties embedded a Chinese greentech project in power sector mainly come from the CCER price and electricity price. To integrate the different stochastic price processes, a real-options-based greentech investment (ROGI) model is developed to derive the investment options value and the optimal investment timing. Considering the possible interventions of the government, the CCER price is modelled as mean-reverting process with jump and cap-floor. In addition, an equivalent electricity price is developed and also described by a mean-reverting process. To solve the ROGI model with various uncertainties involved, a least-square Monte Carlo (LSM) approach is developed. The proposed LSM algorithm is built within the dynamic programming framework. It is shown that the optimal investment strategy can be characterized by a continuation region. The proposed ROGI model is verified by a real case of wind power project investment in China. Sensitive analysis is conducted to examine the effects of the model parameters on the investment decisions. Different climate policy scenarios are then tested, including carbon price jump, carbon price cap and floor, and carbon tax. Several interesting findings are concluded from the results analysis in this study. First, it is found that investors are relatively insensitive to the jump in the CCER price, the volatility of the CCER price, or the mean-reverting speed. Second, the CCER price floor set by the government can effectively encourage greentech investments while the price cap is not a major concern of investors. Finally, the long-term growth rate of the CCER price as well as the carbon tax rate can also plays a significant role in investment decisions. / published_or_final_version / Industrial and Manufacturing Systems Engineering / Doctoral / Doctor of Philosophy

No description available.

An important fraction of the reservoirs in the Outer Continental Shelf of the Gulf of Mexico is comprised of thin-bedded deposits from channel-levee systems. These reservoirs are particularly difficult to describe. Not only is their architecture complex but the quality of the reservoir is determined by connection and length of beds below the resolution of usual reflection data. Improved characterization is needed to improve development and production of these reservoirs. This study presents an integrated approach to build a geologically consistent reservoir model, based on the 8 sand reservoir in Northern Green Canyon block 18. The underlying idea of the construction of this model is that reservoir quality is influenced more by the internal architecture than by the statistical values of petrophysical parameters. Seismic interpretation and attribute extraction provided the reservoir geometry and stratigraphy. The structural framework and the limits of the reservoir have been determined, showing the preeminent role of salt and faults in the constitution of this reservoir. Seismic attributes are calibrated to extract areal information on reservoir architecture. Gross thickness and net thickness maps have been estimated using geostatistical methods. Lateral variations in the quality of the 8 sand and the definition zones with different average properties were inferred from geostatistical results. Lithofacies characterization from core showed that 3 facies could be used to describe the internal variability. The fine-scale heterogeneity is described in each zone from vertical facies distribution determined from wells. A truncated Gaussian sequential simulation was performed to reflect both the regional trend and the internal variability on a 150*150*1 ft grid. The major contribution of this work is to show the efficiency of this approach to describe complex reservoirs where the impact of internal variability is a major control of flow efficiency. This is especially valuable when the well information is scarce or not uniformly distributed. This model will be used for flow simulation and sensitivity analysis to improve the field description.

No description available.

No description available.

This thesis is a study of the evolution and development of the flagellate green algae. The first part is a comparative study of the evolution of body size, multicellularity and segregated soma. The allometry of morphological characters, development, life history and the life cycle are also considered. The second part is an experimental test of the potential role of mutation as a determinant of the course of evolution. Mutation is directional for all the characters studied. The variances and covariances created by mutation are compared to those of 30 species of Volvocaceae; the correspondence between the two depends upon the characted examined. In the third part, the growth of germ cells grown with and without a soma is compared. The response to nutrient concentration of cells grown with an intact soma is steeper than that of cells grown without a soma. This result demonstrates a physiological advantage of soma in Volvox, attributable to a division of labour between 'source' and 'sink'.

Genomic sequence data from the three domains of life have revealed a remarkable diversity of genome architectures. The relative contributions of adaptive versus non-adaptive processes in shaping this diversity are poorly understood and hotly debated. This thesis investigates the evolution of genome architecture in the Chloroplastida (i.e., green algae and land plants), with a particular focus on the mitochondrial and plastid genomes of chlamydomonadalean algae (Chlorophyceae, Chlorophyta). Much of the work presented here describes unprecedented extremes in: i) genome compactness (i.e., the fraction of noncoding DNA in a genome), ii) genome conformation (e.g., circular vs. linear vs. linear fragmented genomes), iii) intron and repeat content; and iv) nucleotide-composition landscape (e.g., GC-rich vs. AT-rich genomes). These data are then combined with intra-population nucleotide diversity data to explore the degree to which non-adaptive forces, such as random genetic drift and mutation rate, have shaped the organelle and nuclear genomes of the Chloroplastida. The major conclusions from this dissertation are that chlamydomonadalean algae show a much greater variation in organelle genome architecture than previously thought — this group boasts some of the most unusual mitochondrial and plastid genomes from all eukaryotes — and that the majority of this variation can be explained in non-adaptive terms.