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从井到航段的全球航运排放:MariTEAM 模型。

Global Shipping Emissions from a Well-to-Wake Perspective: The MariTEAM Model.

机构信息

Industrial Ecology Programme, NTNU, Trondheim 7034, Norway.

Department of Marine Technology, NTNU, Trondheim 7052, Norway.

出版信息

Environ Sci Technol. 2021 Nov 16;55(22):15040-15050. doi: 10.1021/acs.est.1c03937. Epub 2021 Oct 27.

DOI:10.1021/acs.est.1c03937
PMID:34705455
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC8600665/
Abstract

Improving the robustness of maritime emission inventories is important to ensure we fully understand the point of embarkment for transformation pathways of the sector toward the 1.5 and 2°C targets. A bottom-up assessment of emissions of greenhouse gases and aerosols from the maritime sector is presented, accounting for the emissions from fuel production and processing, resulting in a complete "well-to-wake" geospatial inventory. This high-resolution inventory is developed through the use of the state-of-the-art data-driven MariTEAM model, which combines ship technical specifications, ship location data, and historical weather data. The CO emissions for 2017 amount to 943 million tonnes, which is 11% lower than the fourth International Maritime Organization's greenhouse gas study for the same year, while larger discrepancies have been found across ship segments. If fuel production is accounted for when developing shipping inventories, total CO emissions reported could increase by 11%. In addition to fuel production, effects of weather and heavy traffic regions were found to significantly impact emissions at global and regional levels. The global annual efficiency for different fuels and ship segments in approximated operational conditions were also investigated, indicating the need for more holistic metrics than current ones when seeking appropriate solutions aiming at reducing emissions.

摘要

提高海上排放清单的稳健性对于确保我们充分了解该部门向 1.5 和 2°C 目标转变途径的出发点至关重要。本文提出了一种基于海运部门温室气体和气溶胶排放的自下而上评估方法,涵盖了燃料生产和加工过程中的排放,从而形成了完整的“从井到尾”的地理空间清单。该高分辨率清单是通过使用最先进的数据驱动的 MariTEAM 模型开发的,该模型结合了船舶技术规格、船舶位置数据和历史天气数据。2017 年的 CO 排放量达到 9.43 亿吨,比同年国际海事组织第四次温室气体研究低 11%,而在不同船舶细分领域发现了更大的差异。如果在编制航运清单时考虑燃料生产,报告的 CO 总排放量可能会增加 11%。除燃料生产外,天气和繁忙交通区域的影响也被发现对全球和区域水平的排放有重大影响。还研究了不同燃料和船舶细分领域在近似运行条件下的全球年度效率,表明在寻求减排的适当解决方案时,需要比当前更全面的指标。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3432/8600665/15573a7297be/es1c03937_0005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3432/8600665/b535f20c28ec/es1c03937_0001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3432/8600665/778732e4e383/es1c03937_0002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3432/8600665/9aeb2e3b1b00/es1c03937_0003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3432/8600665/329be7df565f/es1c03937_0004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3432/8600665/15573a7297be/es1c03937_0005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3432/8600665/b535f20c28ec/es1c03937_0001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3432/8600665/778732e4e383/es1c03937_0002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3432/8600665/9aeb2e3b1b00/es1c03937_0003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3432/8600665/329be7df565f/es1c03937_0004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3432/8600665/15573a7297be/es1c03937_0005.jpg

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