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    Investigations on the impacts of ship traffic in the Bering Sea on aerosol optical depth using automatic identification systems data, and MODIS collection 6.1 data

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    Author
    Summers, Tyler
    Chair
    Mölders, Nicole
    Committee
    Friberg, Mariel
    Fochesatto, Javier
    Keyword
    Atmospheric aerosols
    Shipping
    Bering Sea
    Marine engines
    Exhaust gas
    MODIS (Spectroradiometer)
    Metadata
    Show full item record
    URI
    http://hdl.handle.net/11122/12572
    Abstract
    Increasing Arctic shipping requires study of the increasing aerosol emissions impact on aerosol optical depth (AOD) in the Bering Sea and the Bering Strait. This study used Moderate Resolution Imaging Spectroradiometer (MODIS) 550 nm AOD 3 km products to study the seasonal variability over the length of the Arctic shipping season, from June to October, over 2011 and 2014. Bucket resampling was used to project and downscale the MODIS AOD to a 0:25 by 0:25 grid during overpasses. An overpass is dened as consecutive MODIS granules from both the Terra and Aqua satellites. Ship positional data obtained from automatic identication systems (AIS) was aggregated to hourly data. Collocation of ships and AOD from overpasses were determined for all quarter degree grid cells and times. Area-weighted means for both grid-cells with ship occurrence and without ships were determined for each month. AOD decreases with increasing time in the shipping season due to the increasing frequency of low pressure system and hence aerosol removal via washout and scavenging. Comparison of the AOD of 2011 and 2014 revealed that the position of the Aleutian Low not only strongly aects the sample size, but also AOD over the Bering Sea. The sea-ice area seemed to be without notable impact on the number of ships and AOD. A weak positive correlation was found between AOD and the number of ships present in the same grid cell during a overpass for 7 out of the 10 months. A strong skewing towards October occurred in 2011 due to a strong positive correlation of the number of data points.
    Description
    Thesis (M.S.) University of Alaska Fairbanks, 2021
    Date
    2021-05
    Type
    Thesis
    Collections
    Atmospheric Sciences

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