Voyage Optimization with the VISIR-2 Model on the Shanghai–Los Angeles Green Corridor of shipping

In 2018, international shipping accounted for significant anthropogenic greenhouse gas emissions, contributing approximately 740 million tons of CO₂ according to the voyage-based method of the Fourth International Maritime Organization (IMO) Greenhouse Gases Study [1] and 880 million tons based on the CEDS and EDGAR inventories [2]. Recognizing this impact, the IMO adopted a long-term strategy in 2023 to achieve decarbonisation of global shipping by mid-century. However, concrete measures remain under development. A recent assessment of the 2018–2022 period suggests emissions are once again approaching 2008 levels, attributed to stagnation in improving energy efficiency [3]. This highlights the urgency of evaluating the potential of operational measures to mitigate emissions.Voyage optimization, or ship weather routing, is an operational strategy leveraging meteo-oceanographic data to minimize energy consumption. This reduction can be achieved through spatial diversions, speed variations, or a combination of both. VISIR-2 [4], an open-source Python-based model, computes least-CO₂ routes by optimizing spatial diversions. Using a validated graph-search algorithm, the model integrates ocean currents and avoids adverse sea conditions [5].In this study, we apply VISIR-2 to an ocean-going vessel operating on the Shanghai–Los Angeles/Long Beach route, identified as one of the first green corridors of shipping [6]. Simulations are conducted for both eastbound and westbound voyages over an entire calendar year, with and without the influence of ocean currents. We evaluate the resulting CO₂ savings, analysing their dependence on engine load and environmental conditions.These results demonstrate the potential of operational measures like voyage optimization to contribute to shipping decarbonisation. The VISIR-2 model is currently employed within the EDITO-Model Lab project [7], contributing to developing a digital twin of the ocean. This work underscores the importance of open-source tools in fostering sustainable maritime practices and achieving the IMO's decarbonisation goals. References[1] https://www.imo.org/en/ourwork/Environment/Pages/Fourth-IMO-Greenhouse-Gas-Study-2020.aspx[2] Deng, S., Mi, Z. A review on carbon emissions of global shipping. Mar Dev 1, 4 (2023). https://doi.org/10.1007/s44312-023-00001-2[3] https://www.shippingandoceans.com/post/international-shipping-emissions-return-to-peak-2008-levels-due-to-insufficient-energy-efficiency-im[4] https://doi.org/10.5281/zenodo.8305526[5] Mannarini, G., Salinas, M. L., Carelli, L., Petacco, N., and Orović, J.: VISIR-2: ship weather routing in Python, Geosci. Model Dev., 17, 4355–4382, https://doi.org/10.5194/gmd-17-4355-2024, 2024[6] https://www.c40.org/news/la-shanghai-implementation-plan-outline-green-shipping-corridor/[7] https://www.edito-modellab.eu/