Improving spatial representation of global ship emissions inventories.
Ship activity patterns depicted by the International Comprehensive Ocean-Atmosphere Data Set (ICOADS), the Automated Mutual-Assistance Vessel Rescue System (AMVER) data set, and their combination demonstrate different spatial and statistical sampling biases. These differences could significantly affect the accuracy of ship emissions inventories and atmospheric modeling. We demonstrate (using ICOADS) a method to improve global-proxy representativeness by trimming over-reporting vessels that mitigates sampling bias, augment the sample data set, and account for ship heterogeneity. Apparent underreporting to ICOADS and AMVER by ships near coastlines, perhaps engaged in coastwise (short sea) shipping especially in Europe, indicates that bottom-up regional inventories may be more representative locally. Primarily due to the long time series available publicly for ICOADS data, the improved ICOADS data set may be the most appropriate global ship traffic proxy identified to date to be used for a top-down approach. More generally, these three spatial proxies can be used together to perform uncertainty analyses of ship air-emissions impacts on a global scale (http://coast.cms.udel.edu/GlobalShipEmissions/).
Wang
Chengfeng
C
College of Marine and Earth Studies, University of Delaware, Robinson Hall, Newark, Delaware 19716, USA.
Corbett
James J
JJ
Firestone
Jeremy
J
D000393:Air Pollutants / Q000032:analysis*; D016208:Databases, Factual; D004784:Environmental Monitoring / Q000706:statistics & numerical data*; D005843:Geography; D009589:Nitrogen Oxides / Q000032:analysis; D012767:Ships; D013458:Sulfur Dioxide / Q000032:analysis
D000393:Air Pollutants; D009589:Nitrogen Oxides; D013458:Sulfur Dioxide