Estimation of Vessel Emissions Inventory in Qingdao Port Based on Big data Analysis
Estimation of Vessel Emissions Inventory in Qingdao Port Based on Big data Analysis
复制标题
基于大数据分析的青岛港船舶排放清单估算
DOI：
10.3390/sym10100452
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发表时间：
2018-10
期刊：
影响因子：
2.7
通讯作者：
Li Zhixiong
中科院分区：
文献类型：
--
作者：
Sun Xing;Tian Zhe;Malekian Reza;Li Zhixiong
在不断增长的海运世界贸易市场中，船舶的废气排放日益引起人们的关注。国际海事组织（海事组织）采取了一系列旨在减少全球航运废气排放的措施。作为世界上最繁忙的港口之一，青岛港已被研究，提出可能的支持，以发展高效减排。本研究利用青岛港排放清单的大量数据，预测其年排放量，从而了解青岛港的海洋污染状况。采用大数据分析方法对船舶排放进行准确预测。分析结果表明，集装箱船、油轮和散货船的排放量占主导地位。通过青岛港与排放控制区内其他港口的比较，论证了采取废气排放控制措施的必要性。采用海岸电力和高效的货物处理似乎是减少废气排放的潜在解决方案。研究结果对海事管理部门了解青岛港船舶排放现状，提出相应的控制措施，进行污染防治具有重要意义。
Exhaust emissions from vessels have increasingly attracted attention in the continuously growing marine transport world trade market. The International Maritime Organization (IMO) has introduced a number of measures designed to reduce exhaust emissions from global shipping. As one of the busiest ports in the world, Qingdao port has been studied to propose possible support to the development of efficient emission reduction. In this study, a large amount data of emissions inventory in Qingdao port was used to predict its annual exhaust emissions, and hence, to help understand maritime pollution in Qingdao port. Bigdata analysis methodology was employed to perform accurate predictions on vessel emissions. The analysis results show that the emissions were dominated by container ships, oil tankers, and bulk cargo ships. The comparison between Qingdao port and other ports in emission control areas demonstrates the necessity of control measures for exhaust emissions. The adoption of shore power and efficient cargo handling seems to be a potential solution to reduce exhaust emissions. The findings of this study are meaningful for maritime safety administration to understand the current emission situation in Qingdao port, propose corresponding control measures, and perform pollution prevention.
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