REDUCING DIESEL DEPENDENCE IN NUNAVUT: INTEGRATING RENEWABLE ENERGY TECHNOLOGIES THROUGH POLICY ACTIONS

In the last fifty years, Nunavut has developed a deep dependence on diesel for virtually all of its energy needs, including electricity. This dependence has created a number of economic, environmental and health related challenges in the territory, with an estimated 20% of the territory’s annual budget being spent on energy, thereby limiting the Government of Nunavut’s ability to address other essential infrastructure and societal needs, such as education, nutrition and health care and housing. One solution to address this diesel dependency is the use of renewable energy technologies (RETs), such as wind, solar and hydropower. As such, this thesis explores energy alternatives in Nunavut, and through RETScreen renewable energy simulations, found that solar power and wind power are technically viable options for Nunavut communities and a potentially successful means to offset diesel-generated electricity in Nunavut. However, through this analysis it was also discovered that accurate data or renewable resources are often unavailable for most Nunavut communities. Moreover, through qualitative open-ended interviews, the perspectives of Nunavut residents with regards to developing RETs in Nunavut were explored, and it was found that respondents generally supported the use of renewable energy in their communities, while acknowledging that there still remains a knowledge gap among residents regarding renewable energy, stemming from a lack of communication between the communities, government and the utility company. In addition, the perceived challenges, opportunities and gaps that exist with regards to renewable energy policy and program development were discussed with government policy-makers through further interviews, and it was discovered that often government departments work largely independently of each other rather than collaboratively, creating gaps and oversights in renewable energy policy in Nunavut. Combined, the results of this thesis were used to develop a number of recommended policy actions that could be undertaken by the territorial and federal government to support a shift towards renewable energy in order to develop a sustainable and self-sufficient energy plan in Nunavut. They include: gathering accurate renewable resource data in Nunavut; increasing community consultations on the subject of renewable energy; building strong partnerships with universities, colleges and industry; developing a knowledge sharing network; and finally increasing accessibility to renewable energy programs and policies in Nunavut.

The Comparative Effectiveness of EEG Biomarkers in Antidepressant Response and Illness Prediction in Major Depressive Disorder

Background: There is growing evidence that individual EEG differences may aid in classifying patients with major depressive disorder (MDD) and also help predict clinical response to antidepressant treatment. This study aims to compare the effectiveness of EEG frequency band power, alpha asymmetry and prefrontal theta cordance towards escitalopram response prediction and MDD diagnosis, in a multi-site initiative. Methods: Resting EEG (eyes open and closed) was recorded from 64 electrodes in 44 depressed patients and 20 healthy controls at baseline, 2 weeks post-treatment and 8 weeks post-treatment. Clinical response was measured as change from baseline MADRS of 50% or more. EEG measures were analyzed (1) at baseline (2) at 2 weeks post-treatment and (3) as an ‘‘early change” variable defined as change in EEG from baseline to 2 weeks post-treatment. Results: At baseline, responders exhibited greater absolute alpha power in the left hemisphere versus the right while non-responders showed the opposite. Responders further exhibited a cortical asymmetry of greater right relative to left activity in parietal areas. Groups also differed in baseline relative delta power with responders showing greater power in the right hemisphere versus the left while non-responders showed the opposite. At 2 weeks post-treatment, responders exhibited greater absolute beta power in the left hemisphere relative to right and the opposite was noted for non-responders. The opposite pattern was noted for absolute and relative delta power at 2 weeks post-treatment. Responders exhibited early reduction in relative alpha power and early increments in relative theta power. Non-responders showed a significant early increase in prefrontal theta cordance. Absolute delta power helped distinguish MDD patients from healthy controls. Conclusions: Hemispheric asymmetries in the alpha and delta bands at pre-treatment baseline and at 2 weeks post-treatment have moderate to moderately strong predictive utility towards antidepressant treatment response. These findings have significant potential for improving clinical practice in psychiatry by eventually guiding clinical choice of treatments. This would greatly benefit patients awaiting relief from depressive symptoms as treatment optimization would help overcome problems associated with delayed recovery. Our results also indicate that resting EEG activity may have clinical utility in predicting MDD diagnosis.

Surface wave and storm surge prediction during Hurricane Sandy

Hurricane Sandy was the largest storm on historical record in the Atlantic Ocean basin with extensive coastal damage caused by large waves and high storm surge. The primary objectives of this thesis are to compare and evaluate three different spatially-varying surface wind fields of Hurricane Sandy to investigate the impact of the differences between the complex wind fields on predictions of the sea surface evolution, and to evaluate the impact of the storm on the hydrodynamics in Great South Bay (GSB) and the discharge of ocean water into the back-barrier bay from overwash over Fire Island. Three different spatially-varying surface wind fields were evaluated and compared to wind observations, including the parametric Holland (1980) model (H80), the parametric Generalized Asymmetric Holland Model (GAHM), and results from the WeatherFlow Regional Atmospheric Modelling System (WRAMS). The winds were used to drive the coupled Delft3D-SWAN hydrodynamic and ocean wave models on a regional grid. The results indicate that the WRAMS wind field produces wave model predictions in the best agreement with significant wave height observations, followed by the GAHM and H80 wind fields and that a regional atmospheric wind model is best for hindcasting hurricane waves and water levels when detailed observations are available, while a parametric vortex model is best for forecasting hurricane sea surface conditions. Using a series of four connected Delft3D-SWAN grids to achieve finer resolution over Fire Island and GSB, a higher resolution WRAMS was used to predict waves and storm surge. The results indicate that strong local winds have the largest influence on water level fluctuations in GSB. Three numerical solutions were conducted with varying extents of barrier island overwash. The simulations allowing for minor and major overwash indicated good agreement with observations in the east end of GSB and suggest that island overwash provided a significant contribution of ocean water to GSB during the storm. Limiting the overwash in the numerical model directly impacts the total discharge into GSB from the ocean through existing inlets. The results of this study indicate that barrier island overwash had a significant impact on the water levels in eastern GSB.