Oil Spill Environmental Risk Assessment and Mapping in Coastal China Using Automatic Identification System (AIS) Data

被引:17
|
作者
Zhu, Gaoru [1 ]
Xie, Zhenglei [2 ,3 ]
Xu, Honglei [1 ]
Wang, Nan [2 ]
Zhang, Liguo [1 ]
Mao, Ning [1 ]
Cheng, Jinxiang [1 ]
机构
[1] Minist Transport Peoples Republ China, Transport Planning & Res Inst, Lab Transport Pollut Control & Monitoring Technol, Beijing 100028, Peoples R China
[2] Nanjing Normal Univ, Coll Marine Sci & Engn, Nanjing 210023, Peoples R China
[3] Minist Nat Resources, Key Lab Coastal Salt Marsh Ecosyst & Resources, Nanjing 210007, Peoples R China
基金
中国国家自然科学基金;
关键词
oil spill; environmental pollution risk; coastal area; China; BOHAI SEA; VULNERABILITY; POLLUTION; PREVENTION; FRAMEWORK; IMPACTS;
D O I
10.3390/su14105837
中图分类号
X [环境科学、安全科学];
学科分类号
08 ; 0830 ;
摘要
The rapid expansion in shipping traffic, oil tankers, and oil field exploration in coastal and marine areas has, inevitably, resulted in the occurrence of many oil spill accidents. Oil spill accidents, which cause serious socio-economic, health, and environmental risks in coastal and marine areas, are a global concern. An oil spill pollution risk distribution map, combining multiple spill sources, is an effective tool by which to identify high-risk areas, which may help decision-makers in adopting contingency response and integrated coastal management. However, the assessment of oil spill distribution and risk assessment has been restricted, due to their heavy dependence on laboratory experiments and model simulations lacking reliable shipping data, which often derive inaccurate mapping results. This study combines the automatic identification system (AIS) and other data to precisely quantify the spatial extent of accident risk in coastal China. Based on oil quantity, oil spill rate, and accident probability, the ship, oil storage tank, submarine pipeline, and oil platform accidents spill risk index is analyzed. Next, combined with the sensitive degree of a coastal area, considering environmental and social issues, the oil spill environmental risk index is calculated. The oil spill pollution risk level is classified into five categories based on the oil spill pollution risk index, namely the low-risk zone, relatively low-risk zone, moderate-risk zone, relatively high-risk zone, and high-risk zone. The relatively high oil spill environmental risk concentration zone is located in the Bohai Sea, inter-border area between the Yellow Sea and Bohai Sea, the Yangtze River estuary, south of the Taiwan Strait, and the Pearl River estuary. The high-risk zone in the Bohai Sea is 36,018 km(2) in area, with an average risk value of 32.23, whereas the high-risk area in the Pearl River estuary is only 14,007 km(2). The high-risk area proportions in Tianjin are 23.5%, while those in Fujian, Hainan, Jiangsu, and Guangxi are very low. The low-risk area proportion in Hainan Province is 62%, while the value in Tianjin is only 2.9%. This study will be helpful in assisting decision-makers in mapping the influence area of oil spills and adopting the important strategies and effective management and conservation countermeasures for ship accidents in the coastal areas of China.
引用
收藏
页数:16
相关论文
共 50 条
  • [11] Analysis of ship drifting in a narrow channel using Automatic Identification System (AIS) data
    Gao X.
    Makino H.
    Furusho M.
    [J]. WMU Journal of Maritime Affairs, 2017, 16 (3) : 351 - 363
  • [12] Maximizing Maritime Safety and Environmental Protection with AIS (Automatic Identification System)
    Page, Captain Edward
    [J]. OCEANS 2017 - ANCHORAGE, 2017,
  • [13] Mapping risk of leptospirosis in China using environmental and socioeconomic data
    Jian Zhao
    Jishan Liao
    Xu Huang
    Jing Zhao
    Yeping Wang
    Jinghuan Ren
    Xiaoye Wang
    Fan Ding
    [J]. BMC Infectious Diseases, 16
  • [14] Mapping risk of leptospirosis in China using environmental and socioeconomic data
    Zhao, Jian
    Liao, Jishan
    Huang, Xu
    Zhao, Jing
    Wang, Yeping
    Ren, Jinghuan
    Wang, Xiaoye
    Ding, Fan
    [J]. BMC INFECTIOUS DISEASES, 2016, 16
  • [15] USING HF SURFACE WAVE RADAR AND THE SHIP AUTOMATIC IDENTIFICATION SYSTEM (AIS) TO MONITOR COASTAL VESSELS
    Vesecky, John F.
    Laws, Kenneth E.
    Paduan, Jeffery D.
    [J]. 2009 IEEE INTERNATIONAL GEOSCIENCE AND REMOTE SENSING SYMPOSIUM, VOLS 1-5, 2009, : 2063 - +
  • [16] Marine Observing Applications Using AIS: Automatic Identification System
    Wright, Darren
    Janzen, Carol
    Bochenek, Robert
    Austin, Jessica
    Page, Edward
    [J]. FRONTIERS IN MARINE SCIENCE, 2019, 6
  • [17] Developing an expert system and fuzzy-based model for the oil spill environmental risk assessment
    Moharramnejad, Naser
    Roayaii, Emad
    Lotfi, Farhad Hosseinzadeh
    Javid, Amir Hossein
    Razavian, Fatemeh
    [J]. JOURNAL OF FOOD AGRICULTURE & ENVIRONMENT, 2010, 8 (02): : 919 - 923
  • [18] Automatic identification system (AIS): Data reliability and human error implications
    Harati-Mokhtari, Abbas
    Wall, Alan
    Brooks, Philip
    Wang, Jin
    [J]. JOURNAL OF NAVIGATION, 2007, 60 (03): : 373 - 389
  • [19] A Deep Learning Model for Ship Trajectory Prediction Using Automatic Identification System (AIS) Data
    Wang, Xinyu
    Xiao, Yingjie
    [J]. INFORMATION, 2023, 14 (04)
  • [20] Marine oil spill risk mapping for accidental pollution and its application in a coastal city
    Lan Dongdong
    Liang Bin
    Bao Chenguang
    Ma Minghui
    Xu Yan
    Yu Chunyan
    [J]. MARINE POLLUTION BULLETIN, 2015, 96 (1-2) : 220 - 225