2022
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Item PV potential projection under climate change and rooftop PV potential estimation(Electronic version published by Vancouver Island University, 2022-09-13) Yang, XiayueClimate change may cause changes in cloud cover to affect solar radiation, thereby affecting the solar PV potential. PV potential has an influence on the public's adoption of solar PV systems as well as the efficacy and efficiency of municipal PV subsidy schemes. The purpose of the research includes two main parts: the first is to examine the probable climate change impact on PV potential in Alberta and British Columbia, Canada, second is to evaluate the rooftop PV potential of a specific location with minor PV potential change from the result of the first part. Two sets of rooftops were selected for comparison. Set 1 describes a ‘complete set’ of rooftops. Set 2 describes a subset of relatively optimal rooftops for PV installation. The climate data of the solar radiation, temperature, and wind speed in 1995-2014 and 2031-2050 two periods from the CMIP6 were used to estimate the PV potential. The total Levelized Cost of Energy (LCOE) was calculated to analyze the economic feasibility of rooftop PV systems. The results show that climate change will mainly affect the future (2031-2050) PV potential by about 1%. The City of Vancouver with a small future PV change (-0.28%) was selected for the rooftop PV potential assessment. Area Solar Radiation tool from ArcGIS Pro was used to calculate the solar radiation of Vancouver. Rooftop PV power generation in Vancouver from Set 2 is approximately 7% of total electricity consumption yearly. In addition, most of the rooftops generated much more PV in July than in December. With subsidies from the government, the LCOE value of Set 2 rooftop PV is much lower than the BC average electricity price, and 96.2% of the Set 2 rooftop PV systems can pay for themselves within five years, while only 41.3% of Set 1 roofs can pay the investment back in a 5-year production. In conclusion, climate change in 2031-2050 is expected to have little effect on PV potential. Rooftop PV on suitable roof surfaces is economically feasible and can effectively reduce power consumption in Vancouver, especially in summer.Item Where the land meets the sea: Defining blue carbon extent within Nuu-chah-nulth Tribal Council boundaries(Electronic version published by Vancouver Island University, 2022-09-15) Foss, KaylaCoastal wetlands such as tidal marshes, eelgrass, and estuaries have the unique ability to sequester carbon and are commonly known as blue carbon sinks. As the impacts of climate change worldwide are becoming intensified, the use of blue carbon sinks as a carbon management tool through carbon credits is an innovative way to manage carbon emissions. The study uses multidimensional Landsat imagery in a Principal Component Analysis to classify and identify coastal wetland areas using Random Forest and Support Vector Machine classifiers. The classified coastal wetlands are then used as an input in the Coastal Blue Carbon Integrated Valuation of Environmental Services and Trade-offs (InVEST) tool to evaluate carbon storage found within Nuu-Chah-Nulth Tribal Council (NTC) boundaries. Coastal wetland extents were found to have grown at rates of 58.93 % to 42.3 % over a twenty-year period. The total gross carbon emission for the entire study area was found to be between 3,188 to 21,415 tonnes of carbon. This study estimates that the total net gain in carbon storage for the entire study area ranges from 16,761 to 460,998.1 tonnes of carbon for the nominal year 2019. The study also estimated a future prediction of total net carbon storage where 80,750.97 to 852,387.04 tonnes of carbon are predicted to be stored within the study area by 2030. The estimated carbon storage and coastal wetland trends support the importance of land management and long-term planning within the study area. Interested groups such as NTC Nations can use this study as a foundation for future blue carbon projects, enabling them to define revenue streams using carbon tax incentives, eco-tourism, and prioritize restoration projects.Item Identification of potential forest wildfire risk in Angeles National Forest by random forest and logistic regression(Electronic version published by Vancouver Island University, 2022) Li, HaoranFrequent wildfires have a growing negative impact on Los Angeles. Understanding the driving factors of wildfire disasters positively impacts predicting and preventing potential wildfire risk. From June to September every year, wildfire disasters frequently occur in the United States. Each wildfire event is associated with human or climatic factors. This paper compares the wildfire prediction ability of two different methods: Logistic Regression (LR) and Random Forest (RF), to determine the main structural factors that explain the possibility of fire in Los Angeles National Forest Park. Natural environmental factors and human social activities are considered essential predictors of fire. The prime natural drivers are natural resource location, climatic conditions, and topographic factors. With the rapid development of society, human activity has become an essential driving factor of wildfire. All samples were randomly divided into training samples, test samples, and validation sets. The results show that the RF model in the machine learning method is more scientific and effective in wildfire risk prediction. The RF model (area under the curve is 89%) provides higher prediction accuracy than the LR model (area under the curve is 81%) and ranks the importance of the factors. The results of the RF model show the spatial distribution of the high-risk regions for wildfire, which allows for a more efficient allocation of fire resources in the park.