当前位置: X-MOL 学术Environ. Pollut. › 论文详情
Our official English website, www.x-mol.net, welcomes your feedback! (Note: you will need to create a separate account there.)
Assessment of Atmospheric Pollutant Emissions with Maritime Energy Strategies using Bayesian Simulations and Time Series Forecasting
Environmental Pollution ( IF 8.9 ) Pub Date : 2020-11-24 , DOI: 10.1016/j.envpol.2020.116068
Jiahui Liu , Okan Duru , Adrian Wing-Keung Law

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, with quantitative predictions 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 designed 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 Ports of Shanghai, Singapore, Tokyo, Long Beach, and Hamburg, for assessment at Years 2020, 2030, and 2050 with three economic projects. 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.



中文翻译:

利用贝叶斯模拟和时间序列预测的海洋能战略评估大气污染物排放

随着有关排放标准和环境污染问题的法规越来越严格,将来将不再允许使用当今为船舶提供动力的船用燃料油(尤其是重质燃料油)。对于可能跨越数十年的长期升级,现在需要各种海洋能源战略,并进行定量预测以评估其实施结果以支持决策。为了满足技术需求,本研究开发了一种新颖的方法,该方法可以纳入燃料选择的战略实施并量化其满足未来船舶排放环境污染法规的适当性。这种方法的核心算法基于概率模拟,该模拟在设计的港口区域内有大量的船舶运动样本,使用贝叶斯船舶交通量生成器从现有真实活动数据中得出。通过在五个主要港口(上海,新加坡,东京,长滩和汉堡)的应用实例展示了其在情景建模中的有用性,并通过三个经济项目在2020年,2030年和2050年进行了评估。应用示例中包括的燃料选择是全面的,包括重质燃料油,馏出物,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)。微调了各种功能,以反映燃料选择,终端位置和/或船舶技术上的微观变化。

更新日期:2020-11-25
down
wechat
bug