| 1. |
- Huang, Hongxun, et al.
(author)
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Identification and detection of high NOx emitting inland ships using multi-source shore-based monitoring data
- 2024
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In: Environmental Research Letters. - : Institute of Physics Publishing (IOPP). - 1748-9326. ; 19:4
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Journal article (peer-reviewed)abstract
- In urban areas situated along busy waterways like the Yangtze River, the diesel engines of inland navigation ships emerge as significant contributors to air pollution. Among these vessels, certain high-emission ships exhibit considerably higher levels of nitrogen oxides (NOx) emissions compared to others. To effectively identify such ships, this study employed a cost-effective ship emission monitoring sensor platform, comprising high-precision gas sensors, automatic identification system (AIS) receiver, and sensitive meteorological sensors, along the Yangtze River in Wuhan City. By combining multi-source shore-based monitoring data, we identified ship emission signals and proposed a high-emission ship detection method using inverse modelling. Using this method, we successfully detected inland high-emission ships based on two months of monitoring data. Furthermore, the relationship between different ship types, sizes, speeds, and ship NOx emission rates were investigated. The results of this study are beneficial for strengthening the regulation of high-emission vessels in inland waterways, thereby reducing the adverse impact of ship emissions on the environment and climate. It also encourages the inland shipping industry to adopt more environmentally friendly technologies and fuels, as advocated by the International Maritime Organization.
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| 2. |
- Peng, Xin, et al.
(author)
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A sampling method for calculating regional ship emission inventories
- 2020
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In: Transportation Research Part D. - : Elsevier BV. - 1361-9209 .- 1879-2340. ; 89
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Journal article (peer-reviewed)abstract
- In this study, we propose a sampling method for calculating ship exhaust emission inventories, which reduces the uncertainties induced by missing ship static data in traditional methods. The stratified random sampling method is utilized to take sample ships based on the ship density, ship type, and main engine power. The exhaust emissions from sample ship are calculated using an activity-based method with 1Â s temporal resolution AIS (Automatic Identification System) data. Then the regional ship exhaust emissions are estimated based on the sampling relationship. Sensitivity experiments show that the relative error of the proposed method decreases quickly with the sampling ratio (the ratio between the number of sampled ships and total ships) and it is less than 3.5% when the sampling ratio is higher than 10%. The method is used to estimate the inventories of ship exhaust emissions in the Yangtze river, which can improve the computational accuracy of ship emissions.
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| 3. |
- Peng, Xin, et al.
(author)
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Remote detection sulfur content in fuel oil used by ships in emission control areas : A case study of the Yantian model in Shenzhen
- 2021
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In: Ocean Engineering. - : Elsevier. - 0029-8018 .- 1873-5258. ; 237
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Journal article (peer-reviewed)abstract
- A method is proposed for remotely detecting sulfur content in fuel oil used by ships in emission control areas (ECAs) based on the direct collection of SO2 emission data from the plume of the ship and numerical simulation models. Assuming a ship in the ECA uses fuel oil with compliance fuel sulfur content (FSC), activity-based ship emission assessment model is firstly utilized to calculate the SO2 concentration emitted from the ship. Numerical simulation models are then used to estimate the theoretical SO2 diffusion concentration at the location of the monitoring equipment. The observed SO2 concentration at the same time can then be integrated to estimate the FSC of the ship. A sample of eleven ships was selected to verify the proposed method in Yantian port, Shenzhen, China in June 2018. The result illustrates that the method can remotely detect ships using fuel oil with the FSC greater than 0.146%m/m in the ECAs, the relative error is 46%.
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| 4. |
- Wu, Lichuan, et al.
(author)
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Modeling the Vulnerability of Waterway Networks
- 2014
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In: Journal of waterway, port, coastal, and ocean engineering. - 0733-950X .- 1943-5460. ; 140:4, s. 04014012-
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Journal article (peer-reviewed)abstract
- In some areas, rivers and canals interweave into a network, making inland waterway transportation feasible. Significant losses will occur if a vulnerable waterway (where vulnerability is defined in terms of susceptibility to interference and difficulty in restoring the initial state) that is vital to a network is blocked. System vulnerabilities combined with hazard factors trigger disasters; therefore, reducing the vulnerability of a network system is a useful means of reducing major losses. In this paper, a model to calculate vulnerability based on inherent characteristics of waterways such as channel connectivity, transportation efficiency, and economic cost is developed. Three influence factors-importance, efficiency contribution, and loss-are used to build a vulnerability assessment model in which the relative vulnerabilities of various waterways can be assessed and the most vulnerable waterway can be found. Using this model, a simple waterway network is tested to identify vulnerable waterways. (C) 2014 American Society of Civil Engineers.
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