Ship emission estimation with high spatial-temporal resolution in the Yangtze River estuary using AIS data

被引:59
|
作者
Weng, Jinxian [1 ]
Shi, Kun [1 ]
Gan, Xiafan [1 ]
Li, Guorong [1 ]
Huang, Zhi [2 ]
机构
[1] Shanghai Maritime Univ, Coll Transport & Commun, Shanghai 201306, Peoples R China
[2] Jimei Univ, Nav Inst, Xiamen 361021, Peoples R China
基金
中国国家自然科学基金;
关键词
Ship emissions; STEAM model; AIS; Estimation distribution; EXHAUST EMISSIONS; INVENTORY; CHINA; SEA; POLLUTANTS; SHANGHAI; VESSELS; COST;
D O I
10.1016/j.jclepro.2019.119297
中图分类号
X [环境科学、安全科学];
学科分类号
08 ; 0830 ;
摘要
A comprehensive analysis of ship emissions is a key step towards taking effective strategies to mitigate air pollution. Based on the AIS data, the objective of this study is to estimate ship emissions with high-resolution (0.001 degrees X 0.001 degrees) in the Yangtze River estuary using the STEAM model. Effects of ship types, operating modes, discharge equipment, time and location on ship emissions are also examined in this study. Results reveal that the annual ship emissions for CO2, CO, HC, NOx and SO2 in 2014 are 1.818 X 10(6) tons, 2.593 X 10(3) tons, 1.949 X 10(3) tons, 3.394 X 10(4) tons and 1.584 X 10(4) tons, respectively. Findings highlight that the majority of ship emissions are generated under the slow-steaming and normal cruising states. There exist strong temporal and spatial effects on ship emissions. Ship emissions are mainly distributed at the port areas, intersection areas and the north channel of the Yangtze River estuary. This study concludes with some future efforts and directions to mitigate ship emissions in this water area effectively (e.g., encouraging cargo ships to use the lower carbon fuels for propulsion, optimizing ship routes in the north channel and interactions of the Yangtze River estuary). (c) 2019 Elsevier Ltd. All rights reserved.
引用
收藏
页数:14
相关论文
共 50 条
  • [1] Ship Emission Inventories in Estuary of the Yangtze River Using Terrestrial AIS Data
    Yao, X.
    Mou, J.
    Chen, P.
    Zhang, X.
    [J]. TRANSNAV-INTERNATIONAL JOURNAL ON MARINE NAVIGATION AND SAFETY OF SEA TRANSPORTATION, 2016, 10 (04) : 633 - 640
  • [2] Ship carbon dioxide emission estimation in coastal domestic emission control areas using high spatial-temporal resolution data: A China case
    Li, Haijiang
    Jia, Peng
    Wang, Xinjian
    Yang, Zaili
    Wang, Jin
    Kuang, Haibo
    [J]. OCEAN & COASTAL MANAGEMENT, 2023, 232
  • [3] Spatial-temporal variability and transportation mechanism of polychlorinated biphenyls in the Yangtze River Estuary
    Chen, Lei
    Yang, Ye
    Chen, Jing
    Gao, Shuohan
    Qi, Shasha
    Sun, Cheng
    Shen, Zhenyao
    [J]. SCIENCE OF THE TOTAL ENVIRONMENT, 2017, 598 : 12 - 20
  • [4] A spatial-temporal forensic analysis for inland-water ship collisions using AIS data
    Wang, Yang
    Zhang, Jinfen
    Chen, Xianqiao
    Chu, Xiumin
    Yan, Xinping
    [J]. SAFETY SCIENCE, 2013, 57 : 187 - 202
  • [5] A spatial-temporal attention method for the prediction of multi ship time headways using AIS data
    Ma, Quandang
    Du, Xu
    Zhang, Mingyang
    Wang, Hongdong
    Lang, Xiao
    Mao, Wengang
    [J]. OCEAN ENGINEERING, 2024, 311
  • [6] Spatial-Temporal Variations of Chlorophyll-a in the Adjacent Sea Area of the Yangtze River Estuary Influenced by Yangtze River Discharge
    Wang, Ying
    Jiang, Hong
    Jin, Jiaxin
    Zhang, Xiuying
    Lu, Xuehe
    Wang, Yueqi
    [J]. INTERNATIONAL JOURNAL OF ENVIRONMENTAL RESEARCH AND PUBLIC HEALTH, 2015, 12 (05) : 5420 - 5438
  • [7] Spatial-temporal variation of heavy metals' sources in the surface sediments of the Yangtze River Estuary
    Liu, Ruimin
    Guo, Lijia
    Men, Cong
    Wang, Qingrui
    Miao, Yuexi
    Shen, Zhenyao
    [J]. MARINE POLLUTION BULLETIN, 2019, 138 : 526 - 533
  • [8] Uncertainty analysis of total phosphorus spatial-temporal variations in the Yangtze River Estuary using different interpolation methods
    Liu, Ruimin
    Chen, Yaxin
    Sun, Chengchun
    Zhang, Peipei
    Wang, Jiawei
    Yu, Wenwen
    Shen, Zhenyao
    [J]. MARINE POLLUTION BULLETIN, 2014, 86 (1-2) : 68 - 75
  • [9] Big AIS data based spatial-temporal analyses of ship traffic in Singapore port waters
    Zhang, Liye
    Meng, Qiang
    Fwa, Tien Fang
    [J]. TRANSPORTATION RESEARCH PART E-LOGISTICS AND TRANSPORTATION REVIEW, 2019, 129 : 287 - 304
  • [10] The spatial-temporal dynamics of daily intercity mobility in the Yangtze River Delta: An analysis using big data
    Cui, Can
    Wu, Xiaoli
    Liu, Liu
    Zhang, Weiyang
    [J]. HABITAT INTERNATIONAL, 2020, 106