Liu Jiahui, Duru Okan, Law Adrian Wing-Keung
School of Civil and Environmental Engineering, Nanyang Technological University, 50 Nanyang Avenue, 639798, Singapore.
School of Civil and Environmental Engineering, Nanyang Technological University, 50 Nanyang Avenue, 639798, Singapore.
Environ Pollut. 2021 Feb 1;270:116068. doi: 10.1016/j.envpol.2020.116068. Epub 2020 Nov 24.
With increasingly stringent regulations on emission criteria and environment pollution concerns, marine fuel oils (particularly heavy fuel oils) that are commonly used today for powering ships will no longer be allowed in the future. Various maritime energy strategies are now needed for the long-term upgrade that might span decades, and quantitative predictions are necessary to assess the outcomes of their implementation for decision support purpose. To address the technical need, a novel approach is developed in this study that can incorporate the strategic implementation of fuel choices and quantify their adequacy in meeting future environmental pollution legislations for ship emissions. The core algorithm in this approach is based on probabilistic simulations with a large sample size of ship movement in the designated port area, derived using a Bayesian ship traffic generator from existing real activity data. Its usefulness with scenario modelling is demonstrated with application examples at five major ports, namely the Ports of Shanghai, Singapore, Tokyo, Long Beach, and Hamburg, for assessment at Years 2020, 2030, and 2050 with three economic scenarios. The included fuel choices in the application examples are comprehensive, including heavy fuel oils, distillates, low sulphur fuel oils, ultra-low sulphur fuel oils, liquefied natural gas, hydrogen, biofuel, methanol, and electricity (battery). Various features are fine-tuned to reflect micro-level changes on the fuel choices, terminal location, and/or ship technology. Future atmospheric pollutant emissions with various maritime energy strategies implemented at these ports are then discussed comprehensively in details to demonstrate the usefulness of the approach.
随着对排放标准和环境污染问题的监管日益严格，如今常用于船舶动力的船用燃料油（特别是重质燃料油）在未来将不再被允许使用。现在需要各种海上能源战略来实现可能长达数十年的长期升级，并且需要进行定量预测以评估其实施结果，为决策提供支持。为满足技术需求，本研究开发了一种新方法，该方法可以纳入燃料选择的战略实施，并量化其在满足未来船舶排放环境污染法规方面的充分性。该方法的核心算法基于概率模拟，使用贝叶斯船舶交通生成器从现有的实际活动数据中得出在指定港口区域内大量船舶运动的样本。通过在上海港、新加坡港、东京港、长滩港和汉堡港这五个主要港口的应用示例，展示了其在情景建模中的实用性，这些示例在三种经济情景下对2020年、2030年和2050年进行评估。应用示例中包含的燃料选择是全面的，包括重质燃料油、馏分油、低硫燃料油、超低硫燃料油、液化天然气、氢气、生物燃料、甲醇和电力（电池）。对各种特征进行了微调，以反映燃料选择、码头位置和/或船舶技术的微观层面变化。然后详细全面地讨论了在这些港口实施各种海上能源战略后的未来大气污染物排放情况，以证明该方法的实用性。
