In this study, we aim to couple the full bottom-up MariTeam model20,21 which combines ship technical specifications, ship location data, and weather data in high spatial and temporal resolution obtained from satellite data to calculate emissions, with the MESSAGEix-GLOBIOM24–27 framework, a dynamic systems-optimization modeling framework that enables comprehensive analyses of energy, economy, and the environment in the context of sustainable development and climate change mitigation. Through that, we aim to increase the robustness of how shipping is modelled using extensive data obtained from the MariTeam model, while integrating the sector with the global energy sector.
The MariTeam model is used to inform the energy demand of international shipping across seven major ship types (i.e., bulk carriers, car carriers, chemical tankers, container ships, general cargo ships, liquefied natural gas carriers, oil tankers) for the year 2025, and an extra ship type that comprises other segments (e.g., passenger ships, offshore supply vessels, refrigerated cargo ships). A comparison of the baseline values with the 4th IMO GHG study can be found in supplementary information (SI). Projections from 2025 to 2100 are developed using a gravity model of bilateral trade in alignment with the GDP and population projections of SSP2. For more details, see the methodology presented in Kramel et al. (2024)28 and the SI. Energy demand is divided into short- and long-haul (longer than 1000km) voyages, so we can account for technological limitations in the maximum operation range of liquified hydrogen (LH2). Additionally, energy projections for each of the ship types are divided into new builds (ships built after 2025) and the current cohort (ships built prior to 2025) using a dynamic stock model29 and stock data for around 50 thousand operating ships. We adopt a ship lifetime of 25 years, meaning that most of the current fleet will be completely phased out most by 2050. We also investigate the role of technological and operational measures, in parallel to fuel switching, as a strategy to increase the overall energy efficiency of the sector and therefore reduce sectoral emissions. For that, we include three groups of measures (i.e., hull design, operation, and power and propulsion)30, resulting in an efficiency gain of around 25%. Because they are mostly not retrofittable, they are implemented only in the future cohort to simulate the gradual uptake of the measures. Increase in shipping operational cost are not included because the measures included have a neutral or negative Marginal Abatement Cost Curve (MACC)5,31,32. The modelling detailed so far provides the shipping energy demand necessary to MESSAGEix for ships transporting non-energy-related commodities. In the case of bulk carriers (involved in the trade of biomass, coal, and steel), oil tankers, gas carriers, and chemical tankers (methanol, ethanol, ammonia, and petrochemicals) - we adjust their demand to the demand of the correspondent cargo in MESSAGEix, as described in the SI. Thus, a reduction of 50% in trade of one of those commodities would imply a reduction of 50% in energy demand in the energy share of the correspondent ship type. Additionally, in order to reduce their direct emissions, ships can install onboard carbon capture and storage (OCCS) solutions33. For that, we consider a mono-ethanolamine (MEA) post-combustion capture system with flue gas heat integration for diesel and LNG-fueled engines, that uses heat from engine’s exhaust gases which reduces the fuel penalty to operate such a system to 12% for diesel engines and 9% for LNG engines33 - which have more heating available from engine’s exhaust. Carbon capture rates are considered to be 70% for diesel engines and 85% for LNG engines, considering the increase of fuel penalty, having an overall capture rate of 66% and 84%. We also assume that HFO engines will be running with Sulphur scrubbers from 2030 onwards, due to health and pollution concerns in face of the high Sulphur and black carbon emissions, leading to a fuel penalty of 5%. Capital investment and operational costs are derived from DNV’s ship study case sailing from China to Europe34.
For MESSAGEix, conventional (heavy fuel oil - HFO, marine gas oil - MGO, liquefied natural gas - LNG) and alternative fuels (ethanol, methanol, liquefied hydrogen - LH2, ammonia - NH3) have been implemented to supply the maritime sector. They can be equally supplied to any ship type, meaning that oil tankers and LNG carriers can also sail with alternative fuels. LH2 is used only for voyages shorter than 1000 km, whereas compressed hydrogen is not included due to its relatively poor energy density by volume, making storage in a setting where space is a premium unlikely to happen. For engine technology, we prioritize the inclusion of internal combustion engines (ICE) over fuel cells (FC) since they are considered to be the primary choice for power systems in the future35. We also take into consideration the technology readiness level (TLR) of different fuels and technologies, limiting the first year they can be deployed in the model. Biofuels and OCCS are set to start in 2025, whereas ammonia and hydrogen become available in 2030. Several emission species are covered based on the literature36, see more in the SI. For ammonia engines, we assume that despite current high N2O emissions, technological advancements will be able to drastically reduce N2O emissions by mid-century (see SI), as suggested by novel articles that have achieved GHG reductions of 84%37 in ammonia engines. Land-use and land-use-change (LULUC), especially at the scale of the world transitioning to 1.5 and 2oC peak warming levels, imply vast emissions associated with biomass production and they are also accounted in the fuel production. To derive emission factors that are internally consistent with the MESSAGEix-GLOBIOM framework, we use the same procedure as adopted by the Sixth Assessment Report (AR6) of the IPCC38 to derive emissions associated with primary biomass supply using stylized scenarios from the EMF-3339. For that, LU emissions are taken by the difference of a baseline scenario and a scenario running with no bioenergy demand. The cumulative LU emissions between 2020 and 2100 is divided by the cumulative bio-energy production over the 2020–2100 period, from which we obtain 19gCO2eqMJ− 1. A summary of fuel pathways and GHG emissions is shown in Fig. 1.
The scenario analysis in this study considers two illustrative mitigation pathways (B600 and B1000) for the global system. Scenarios B600 have around 600GtCO2 of cumulative emissions until net-zero and 300 GtCO2 for the period 2021 to 2100, equivalent to the C3 IPCC scenarios (1.5oC with high overshoot) that limits warming to around 1.5°C with the world reaching net-zero CO2 emission around 2060. The second variant, B1000, has carbon cumulative emissions until net-zero of 1000GtCO2 and 800GtCO2 of cumulative emissions until 2100, compatible with the C4 scenario (likely below 2oC), where warming peaks at 1.8°C throughout the 21st century reaching net-zero emissions globally around 2070 (see Fig. 2a). For the shipping sector, we developed sectoral variants within both B1000 and B600 scenarios. For understanding the attainability of sectoral targets and the implications in the shipping fuel composition, we develop scenarios with shipping reaching net-zero emissions by or around 2050 as proposed by the IMO’s revised GHG strategy (in our study tha means no later than 2055), as well as 2060 and 2070 in case the sector fails to reach the target (see Fig. 2b). Additionally, we perform a sensitivity analysis where we constrain the deployment of certain fuels (i.e., ammonia, biofuels), resources (i.e., biomass for fuel production) and technology (i.e., energy efficiency gains) (see Fig. 2c).