Community Solar: A Pathway toward Leadership for Higher Education Institutions

Higher education institutions equip their graduates with the skills and knowledge to become leaders and future problem-solvers. Increasingly, higher education institutions are seeking ways to lead in sustainability and ensure a legacy of progressive environmental change. One option for these institutions to enhance sustainability is to hosting community solar projects. Community Solar, defined by Northwest SEED, is a voluntary solar program providing power and/or financial benefits to, or is owned by, multiple community members. This research details two potential community solar models for higher education institutions: non-profit and for-profit. Through informal interviews with key informants, National Renewable Energy Laboratory technical assistance, undergraduate research and financial modeling the non-profit option is recommended. Using upfront payments from community solar participants, a Western Washington University Foundation partnership, federal tax incentives, value of energy produced and a university buyout, the non-profit community solar project is feasible to be hosted at Western Washington University. Being a community solar host provides higher education institutions with a means of decreasing community carbon emissions, increasing access to renewable energy, advancing institution-community relations, normalizing renewable energy for students, providing faculty and student research opportunities, and positioning these institutions as leaders in sustainability

Beyond Vision: Designing for the Deaf

I propose a Deaf/Hearing Cultural Center as a means of testing these relationships. The center would enable the increased awareness of Deaf culture by the Hearing population while providing a space for the Deaf community. The varied programs of a cultural center would enable the investigation of a sensory architecture in combination with the social aspects of being Deaf

The Development of Regional Forest Inventories Through Novel Means

For two decades Light Detection and Ranging (LiDAR) data has been used to develop spatially-explicit forest inventories. Data derived from LiDAR depict three-dimensional forest canopy structure and are useful for predicting forest attributes such as biomass, stem density, and species. Such enhanced forest inventories (EFIs) are useful for carbon accounting, forest management, and wildlife habitat characterization by allowing practitioners to target specific areas without extensive field work. Here in New England, LiDAR data covers nearly the entire geographical extent of the region. However, until now the region’s forest attributes have not been mapped. Developing regional inventories has traditionally been problematic because most regions – including New England – are comprised of a patchwork of datasets acquired with various specifications. These variations in specifications prohibit developing a single set of predictive models for a region. The purpose of this work is to develop a new set of modeling techniques, allowing for EFIs consisting of disparate LiDAR datasets. The work presented in the first chapter improves upon existing LiDAR modeling techniques by developing a new set of metrics for quantifying LiDAR based on ecological ii principles. These fall into five categories: canopy height, canopy complexity, individual tree attributes, crowding, and abiotic. These metrics were compared to those traditionally used, and results indicated that they are a more effective means of modeling forest attributes across multiple LiDAR datasets. In the following chapters, artificial intelligence (AI) algorithms were developed to interpret LiDAR data and make forest predictions. After settling on the optimal algorithm, we incorporated satellite spectral, disturbance, and climate data. Our results indicated that this approach dramatically outperformed the traditional modeling techniques. We then applied the AI model to the region’s LiDAR, developing 10 m resolution wall-to-wall forest inventory maps of fourteen forest attributes. We assessed error using U.S. federal inventory data, and determined that our EFIs did not differ significantly in 33, 25, and 30/38 counties when predicting biomass, percent conifer, and stem density. We were ultimately able to develop the region’s most complete and detailed forest inventories. This will allow practitioners to assess forest characteristics without the cost and effort associated with extensive field-inventories

Cancellous bone and theropod dinosaur locomotion. Part II—a new approach to inferring posture and locomotor biomechanics in extinct tetrapod vertebrates

This paper is the second of a three-part series that investigates the architecture of cancellous bone in the main hindlimb bones of theropod dinosaurs, and uses cancellous bone architectural patterns to infer locomotor biomechanics in extinct non-avian species. Cancellous bone is widely known to be highly sensitive to its mechanical environment, and therefore has the potential to provide insight into locomotor biomechanics in extinct tetrapod vertebrates such as dinosaurs. Here in Part II, a new biomechanical modelling approach is outlined, one which mechanistically links cancellous bone architectural patterns with three-dimensional musculoskeletal and finite element modelling of the hindlimb. In particular, the architecture of cancellous bone is used to derive a single ‘characteristic posture’ for a given species—one in which bone continuum-level principal stresses best align with cancellous bone fabric—and thereby clarify hindlimb locomotor biomechanics. The quasi-static approach was validated for an extant theropod, the chicken, and is shown to provide a good estimate of limb posture at around mid-stance. It also provides reasonable predictions of bone loading mechanics, especially for the proximal hindlimb, and also provides a broadly accurate assessment of muscle recruitment insofar as limb stabilization is concerned. In addition to being useful for better understanding locomotor biomechanics in extant species, the approach hence provides a new avenue by which to analyse, test and refine palaeobiomechanical hypotheses, not just for extinct theropods, but potentially many other extinct tetrapod groups as well

The Effects of Forecasted Climate Change on Mass Wasting Susceptibility in the Nooksack River Basin

The Nooksack River in Whatcom County, Washington­ is an essential fresh water resource for industry, agriculture, municipalities and serves as vital fish habitat. Like many mountainous watersheds in the western Cascades, the Nooksack Basin is susceptible to shallow mass wasting and debris flows because of its steep slopes, young glaciated terrain, and storms with high intensity precipitation. Understanding how projected reductions in snowpack and increased winter rainfall will affect mass-wasting susceptibility in the Nooksack basin is important, because sediment produced mass wasting will jeopardize valuable aquatic and fish habitat, increase flooding risk in the Nooksack River, and affect estuarine and coastal dynamics. With a projected 60% decrease in snowpack and increase in the snowline elevation by the 2075 climate normal, there will be an increase in exposed forest roads, harvestable forest areas, and previously mapped landsides, which are all documented to increase sediment delivery to streams. Retreating glaciers will produce at least 2 km2 of exposed moraines, which have the potential to erode, fail and provide additional sediment to streams, especially during large storm events coinciding with minimum snowpack during the fall and early spring seasons. I applied a static infinite-slope ArcGIS model and a dynamic, probabilistic mass-wasting model integrated into the Distributed Hydrology Soil Vegetation Model (DHSVM) to the Nooksack River watershed to determine areas susceptible to mass wasting into the 21st century. Susceptibility maps produced by the models indicate an increase in regions susceptible to slope failure during the winter months in snow free areas at higher elevations later in the 21st century. Slope failure susceptibility increased with soil saturation, which is anticipated with higher intense winter rainfall events. Slopes greater than about 30o with thick regolith deposits and lower soil mechanical strength, e.g., sand, loamy sand, sandy loam, silt, moraines, glacial outwash and former landslide deposits were correlated with higher mass-wasting susceptibility. The simpler static ArcGIS infinite-slope model yielded comparable results to the more complex probabilistic method integrated into the DHSVM for identifying areas susceptible to mass wasting