Integrating multi-source maritime information to estimate ship exhaust emissions under wind,wave and current conditions |
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| Institution: | 1. National Lab of Auto Performance and Emission Test, School of Mechanical and Vehicular Engineering, Beijing Institute of Technology, Beijing 100081, China;2. Collaborative Innovation Center of Electric Vehicles in Beijing, Beijing 100081, China;3. State Key Joint Laboratory of ESPC, School of Environment, Tsinghua University, Beijing 10084, China;4. State Environmental Protection Key Laboratory of Sources and Control of Air Pollution Complex, Beijing 100084, China;5. Collaborative Innovation Centre for Regional Environmental Quality, Beijing 100084, China;6. Department of Mechanical Engineering, University of Engineering and Technology, Lahore 54000, Pakistan;7. Vehicle Emission Control Center, Ministry of Environmental Protection, Beijing 100012, China;1. School of Environment and Energy, South China University of Technology, Guangzhou 510006, China;2. Guangdong Environmental Monitoring Center, Modiesha Street, Haizhu District, Guangzhou, 510308, China;3. Civic Exchange, 23/F, Chun Wo Commercial Centre, 23-29 Wing Wo Street, Central, Hong Kong |
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| Abstract: | How to accurately calculate ship exhaust emissions has become urgent needs. In this paper, multi-source maritime information is integrated to estimate ship exhaust emissions under ocean environment. Influences of wind, wave and current on ship speed are firstly analyzed and mathematically modeled. Based on the influences, ocean environment information and ship trajectories are integrated to identify ship activities exactly. After that, ship activity based calculation method is present to obtain exhaust emissions from ship in various activities. Contribution ratios of different ship type and ship activities have been further discussed. In a case study of Ningbo-Zhoushan port in China, greenhouse gas (CO2, CO, SOx, NOx and PM) emissions from ships in 2014 calculated by the proposed method are 8.72 × 105 ton, 2.07 × 103 ton, 1.47 × 104 ton, 2.60 × 104 ton and 1.40 × 103 ton respectively. The maximum error is under 10%. Experimental results illustrate that the proposed method can produce more accurate ship exhaust emissions than traditional method under ocean environment conditions. |
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| Keywords: | Ship emission inventory Marine data integration Ship trajectory Ocean environment |
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