Exploring the spatiotemporal distribution patterns of carbon emissions driven by massive ship trajectory data
YU Hong-chu1,3, FANG Qing-long1, FANG Zhi-xiang2, LIU Jing-xian1
1. School of Navigation, Wuhan University of Technology, Wuhan 430063, China; 2. State Key Laboratory of Information Engineering in Surveying, Mapping and Remote Sensing, Wuhan University, Wuhan 430079, China; 3. Sanya Science and Education Innovation Park, Wuhan University of Technology, Sanya 572025, China
Abstract：AIS trajectory data from container ships in 2018 is leveraged and a bottom-up approach is adopted to comprehensively understand the CO2 emissions of these vessels. The global monthly spatial distribution map of CO2 emissions from container ships is achieved through the coordinated analysis of ship emission data and world maps through the fundamental theories and techniques of Geographic Information Science. The intricate spatiotemporal patterns of CO2 emissions, coupled with a detailed exploration of emissions along major shipping routes. The findings underscore that the annual CO2 emissions from container ships amounted to 123.55million tons in 2018, with the highest emissions occurring in January and the lowest in November, indicative of pronounced temporal variations. Monthly emissions demonstrate a generally consistent spatial distribution, concentrating predominantly near coastlines and major routes.
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