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Tornado Favorable Environments and Their Changing Geography
The methods used in this analysis included principal components analysis, artificial neural network-based SOM (Self Organizing Map) clustering, cluster validation/evaluation, trend analysis and correlative analysis. The SOM-based classification was applied to datasets of convective available potential energy (CAPE), convective inhibition (CIN), storm relative helicity (SRH), and 2m dew point to create a discrete set of 20 tornado favorable environments (TFEs). Tornado data gathered from the Storm Prediction Center was also mapped to a SOM, to further compare the similarities between the patterns of each of the atmospheric variables with the geographic distribution of tornadoes. After these SOMs were created, a spatial correlation was run on each and compared to the tornado distribution map. A number of different variables would have proven useful for this analysis, herein convective available potential energy, storm relative helicity, 2-meter dew point temperature, and convective inhibition were chosen as ideal for identifying tornado favorable environments. Daily average fields of each of these four variables were acquired from the North American Regional Reanalysis (NARR; Mesinger et al., 2006) project, for the years 1979-2017, at about 123km resolution (every 4th gridpoint of the native 32km resolution), spanning the spatial domain of 30°N to 50°N, and 105°W to 80°W, the area east of the Rocky Mountains, spanning to just before the coast (hereafter referred to as the area of study). Tornado data was retrieved from the Storm Prediction Center archive (SPC, 2019). The necessary data for this research were the date and latitude/longitude coordinate of every tornado touchdown from 1979-2017 in the domain. Tornado data was then binned into counts of tornadoes per day for each 1° x 1° latitude-longitude box across the area of study. The classification produced strong correlations between the spatial distributions of tornado days and atmospheric patterns for CAPE, CIN, dew point, and storm relative helicity (SRH). The results of this study suggest that the patterns with the highest spatial distribution of tornadoes are increasing, at an average of 5.6 more occurrences over this 38-year study period.
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Analyzing Spatial Patterns of Bikeshare Use on Kent Campus Utilizing Mixed Methods
Numerous colleges have implemented sustainable transportation methods on their campuses. Kent State University has teamed with Veoride to implement a bike share program on campus. The purpose of this study is to examine so far how the bike share program is being utilized on campus. By looking at the patterns of usage, where the bikes are most frequently placed, and who are using them will help the University better understand how a bike share program can be used on campus and improve services for the future. To further enhance the understanding on the bike share program, the universities recreational department was able to receive bike share data which included latitudinal and longitudinal coordinates, GPS data, bike numbers and type of bikes. This data allows us to use quantitative methods in order to draw conclusions on the utilization of the bike share program. In addition, to obtain qualitative data, surveys will be distributed on campus and throughout the community to determine how the student body, faculty and community use the bike share program. Furthermore, data will be analyzed using GIS to determine exact locations of where the bikes are and where they are frequently being placed at. IBM SPSS will further show the averages on time when they are used, weather conditions, and duration of riding time. With these results we hope to provide the community of Kent with better knowledge of the bike share program used on campus.
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Using VPCA Spectral Decomposition to Analyze Optical Components off the USVI with Sentinel – 3A/B OLCI
Using VPCA spectral decomposition to analyze optical components off the USVI with Sentinel – 3A/B OLCI By: Alex Rosul, Dulci Avouris, Joseph Ortiz Abstract The oceans are a diverse soup of organic life and are major regulators of the earth's many systems. Tracking ocean systems is necessary for the regulation of healthy habitats, maintaining clean recreational environments, and monitoring pollutants. Using satellite sensors, we have access to tons of real-time public data of the world's surface, which can be used to do all these things. In this project, a statistical approach to remote sensing called varimax--rotated, principal component analysis (VPCA) was utilized to identify the suspended matter in the water. This approach takes the derivative of the reflectance spectra and unmixes it to give us a more accurate reading of materials that influence the reflected light. Mainly we are looking for any color-producing agents (CPAs) suspended in the water i.e., phytoplankton, detritus, and dinoflagellates or sediment or sediment minerals. By comparing the values to an existing spectral library, we can identify the components. In 2017, Hurricane Irma struck the US Virgin Islands leaving behind a wake of destruction. By comparing images before and after the hurricane, we can track how pigment distribution changed after the event. We observe that all the same components were identified between both dates, but that their distributions vary. Possible further applications to this project include creating seasonal time series to understand distributions year-round and validating our data with samples collected in the USVI from around these dates.
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Potential Relationship Between Lead (Pb) and Soil Phases: A Case Study from Akron, Ohio
Exposure to lead (Pb) can have serious implications on a person’s health, and a major pathway of exposure is from inhalation or ingestion of soil. Soil in urban environments contain Pb primarily due to historic leaded gasoline use and Pb paint, as well as other industrial sources. However, the extent of historic lead in soils is still unknown. Further, the risk of Pb exposure is also dependent on the speciation (chemical form) of Pb in soils, and what soils phases Pb is associated with. As part of an on-going case study of Pb speciation and distribution in Akron, Ohio, we aim to determine the relationship between Pb and soil minerals and organic matter. We have used Loss on Ignition (LOI) as a proxy for the amount of soil organic matter, and X-ray diffraction (XRD) to determine the type and amount of minerals in the soils. Statistical analyses will be conducted to determine if any correlations exist between the amount of Pb (previously determined) and soil minerals and organic matter. These results could help determine the primary source of Pb in urban soils. Determining Pb speciation in soil can also help identify potential reclamation and remediation pathways.
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A Petrographic and Geochemical Study of the Breccia Pipe Intrusions, Black Hills, SD
In this study, we looked at the petrographic and geochemical aspects of small rhyolite breccia plutons that formed by volcanic explosions in the Black Hills region. These intrusions are roughly 58-50Ma (Eocene) and are the result of shallow level magma explosions. In this region we can see a wide variety of different intrusive bodies such as dikes, sills, laccoliths, diatremes, and breccia pipes. Each of the 18 samples we looked at plotted in the rhyolite field. According to Lockrem (1980), there are four possibilities for origins of breccia: igneous intrusion breccia, pyroclastic volcanic breccia, meteorite breccia, and breccia pipe origin. Based on the textural evidence like clasts within a fine-grained igneous matrix, with the clasts being composed mainly of quartz and feldspar, and evidence that both the clasts and the matrix are highly altered we can conclude that our samples are breccia pipe in origin (Lockrem, 1980). References: Lockrem, T.M., “Petrographic Analysis of an Early Cenozoic Breccia from the Tinto Area, Northern Black Hills, South Dakota” (1980). Undergraduate theses and senior Projects. 76. https://commons.und.edu/senior-projects/76
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Lead (Pb) in Urban Soils
Madison Wood Dr. David Singer Nicholas Santoro Lead (Pb), a versatile metal, is commonly found in urban soils because of its wide range of industrial uses and its resistance to degradation. Pb has been used over the past few centuries, primarily in gasoline and paint in the 20th century, and can have long-lasting negative health effects following exposure, particularly for children. This caused the USEPA to set a standard of 400 parts per million for bare soils to limit human exposure. The risk of Pb exposure is based on its speciation (chemical form) in soils, which can be determined by Scanning Electron Microscopy with Electron Dispersive Spectroscopy (SEM-EDS). SEM can be used as an initial identifier for Pb in soils because of its ease of sampling and quick analysis processes. The combination of SEM imaging and EDS element mapping can be used to identify Pb and other elements present, which can assist in understanding the phases that Pb is associated with. This is important because speciation is directly related to the potential bioaccessibility of Pb. Thus far, 16 of the samples collected from Akron (n=82) are above USEPA acceptable range. These samples contain Pb in insoluble phases that are galena like or lead aggregates with clays and iron phases. The analysis of these soils is being done, in part, through a collaboration between KSU and Akron Public Schools system. This information may also be used to streamline future Pb soil analysis by reducing the number of steps taken to prove if Pb is present within soils.
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