船舶动态驱动的碳排放时空分布规律  

Exploring the spatiotemporal distribution patterns of carbon emissions driven by massive ship trajectory data

作　　者：余红楚 方庆龙 方志祥[2] 刘敬贤[1] YU Hong-chu;FANG Qing-long;FANG Zhi-xiang;LIU Jing-xian(School of Navigation,Wuhan University of Technology,Wuhan 430063,China;State Key Laboratory of Information Engineering in Surveying,Mapping and Remote Sensing,Wuhan University,Wuhan 430079,China;Sanya Science and Education Innovation Park,Wuhan University of Technology,Sanya 572025,China)

机构地区：[1]武汉理工大学航运学院,湖北武汉430063 [2]武汉大学测绘遥感信息工程国家重点实验室,湖北武汉430079 [3]武汉理工大学三亚科教创新园,海南三亚572025

出　　处：《中国环境科学》2024年第3期1769-1776,共8页China Environmental Science

基　　金：国家自然科学基金资助项目(42371415,42101429);测绘遥感信息工程国家重点实验室开放基金资助项目(21S04);中国科学技术协会青年人才托举工程资助项目(YESS20220491)。

摘　　要：本文基于2018年全球集装箱船的AIS(Automatic Identification System)轨迹数据,采用自下而上的方法,计算2018年全球集装箱船的CO_(2)排放量.进一步,采用地理信息科学基础理论与技术,通过船舶排放量与地图的联动分析,挖掘集装箱船CO_(2)排放的时空分布规律,并分析主要远洋运输航线的排放特征.结果表明,2018年全球集装箱船的CO_(2)年排放量达到1.2355亿t,1月份的排放最高,而11月份排放量全年最低,在时间上呈现明显的分异特性.集装箱船月度排放的空间分布总体较为相似,排放高峰区域主要分布在靠近海岸线和主要远洋航路上,远东-欧洲航线的排放量最高.AIS trajectory data from container ships in 2018 is leveraged and a bottom-up approach is adopted to comprehensively understand the CO_(2)emissions of these vessels.The global monthly spatial distribution map of CO_(2)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 CO_(2)emissions,coupled with a detailed exploration of emissions along major shipping routes.The findings underscore that the annual CO_(2)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.

关 键 词：集装箱船 CO_(2)排放 AIS轨迹 时空分布 

分 类 号：X511[环境科学与工程—环境工程]