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Summer 2008 Oceanography Team Members: Brittany Maybin, Chelsea Goins, Yao Messan, Phillip Moore Team Mentor: Dr. Jinchun Yuan [Team Website] Temporal and Spatial Variations of Sea Surface Temperature and Chlorophyll a in Coastal Waters of North Carolina |
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Abstract |
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Temperature and chlorophyll a are two fundamental properties of seawater. Traditionally, both temperature and chlorophyll a are determined by shipboard sensors that can only provide limited temporal and spatial coverage. Consequently, the distribution of temperature and chlorophyll a in coastal waters of North Carolina is a poorly known. In this study, satellite remote sensing will be used to study the temporal and spatial variations of the coastal waters of North Carolina. The region (34N, 40N, 78W, 74W) of our study will include Chesapeake Bay, Albemarle and Pamlico Sound, and part of Northeast North Atlantic Ocean. Two sets of data, sea surface chlorophyll a (chl a) and sea surface temperature (SST) will be used for this study. Monthly sea surface chl a concentration based on 10 years of Sea-viewing Wide Field-of-view Sensor (SeaWiFS) data and SST data based on 5 years of Aqua-MODIS data will be obtained from NASA website (GIOVANNI). (1) The monthly climatology of sea surface chl a will be calculated from monthly remote sensing data; (2) Temporal variation of area averaged chl a and SST for selected regions (i.e. Albemarle Sound, Chesapeake Bay ) will also be calculated; (3) Temporal variations of both chl a and SST distribution animation will also be created. |
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May 2008 Team Members: Brittany Maybin, Unquiea Wade, La'Trent Brock, Alvin McClerkin, Michelle Burke Team Mentors: Dr. Andrea Lawrence & Dr. Constance Bland [Team Paper] An Investigation of Energy Consumption of 25 Universities in Measuring a Carbon Footprint Based on Carnegie Level Classification |
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Abstract |
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At various institutions of higher education all across the United States there is a substantial contribution of CO2 emissions to the environment because of excessive amounts of energy consumption. These CO2 emissions can be calculated by using a carbon footprint algorithm which finds the measurement of the impact of human activities on the environment as it relates to energy consumption and greenhouse gases produced. The standard of Carnegie classification will be used because of its attributes of classifying universities by undergraduate and graduate curriculum profile, enrollment profile, and the size/setting profile. This allows comparisons to be established between classification levels of Carnegie distinctions of universities. Our team will try to find connections between energy consumption and CO2 emissions. Our team will also evaluate amounts of emissions for a range of Carnegie Level Institutions. |
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