Demand for shipping

This part of the STAR methods section is based on Müller-Casseres et al. (2021a). International shipping was originally not represented in BLUES, given that it is a national model. As such, an important part of the methodology here is the incorporation of the shipping fuel demand into BLUES. This was performed based on the assumption that only a fraction of the fuel required by Brazil’s international trade is provided by national ports. The remaining part is supplied by ports of the commercial partners or along the shipping routes.

Brazil’s exports are way higher than its imports on a mass basis. Hence, while imports are treated as a single category, exports are divided into five categories that represent the country’s main export products: iron ore, crude oil, soybean, sugar, and others (MDIC 2020). Furthermore, iron ore is divided into two categories, reflecting the two different kinds of vessels used to transport it (Schaeffer et al., 2018). Coastal navigation is also modeled. Even though coastal navigation is not in the scope of IMO’s target, it is assumed that it will follow the trends of long-haul shipping.

Below table shows the estimation of the transport work related to Brazilian exports, imports, and coastal navigation (MDIC, 2020, Sea Distance, 2020). The proportion of the fuel supplied by Brazilian ports is similar for all products (around 31%). Estimates derivate from the comparison of the results of the modeling with historical data for the base year (5.3 million tonnes of bunker in 2018) (EPE 2019b).

Estimation of transport work associated with fuel supplied in Brazilian ports in 2018

Two demand scenarios are developed based on the literature on global shipping forecasts. The low demand scenario is based on the activity growth reported in DNV’s maritime forecast (DNV GL 2018), while the high demand scenario is based on the Business as Usual (BAU) scenario of IMO’s third GHG study (IMO 2015). It is assumed that the exported products do not change over the period of analysis. The adopted literature scenarios are based on secondary energy, not transport work (useful energy). In the case of the high demand scenario, which considers the maintenance of efficiencies base year conversion rates, this is not significant. In the case of the scenario with the lowest consumption, however, there is a lag between the profile of the energy curve and that of demand, given the premises related to efficiency. However, for simplicity and data limitation, the final energy is directly used as a proxy for the growth of the projected tonne-kilometers. This implies, in the worst-case scenario, a range of slightly wider demand.

The energy associated with Brazilian transport work in each scenario is determined using a simplified energy model and is calibrated with historical data for 2010-2018. The model estimates the demand for main engines (used for propulsion), auxiliary engines (electricity generation), and auxiliary boilers (heat production).

The propulsion energy demand is estimated through simplified hydrodynamic equations (Lindstad and Eskeland 2015; Bouman et al., 2017). The total hull resistance RT and the associated brake power PB are presented in Equations 2 and 3, respectively.

In Equations 2 and 3, ρ is the seawater density, CT is the total resistance coefficient, S is the wetted surface, m is the sea margin, v is the speed of the ship and ηT is the total propulsion efficiency. These parameters are estimated based on ship sizes and categories. Table above shows the vessels considered for each product, as well as their deadweight tonnage.

Auxiliary engines and boilers energy demand estimation follows IMO (2015). It considers typical loads for different vessel categories, sizes and operational modes (at-berth, at-anchorage, maneuvering and at-sea) (Vale 2014; Kristensen 2012; MAN 2015; Mitsui OSK Lines, 2020; Vale 2018; Transpetro 2019; Bulk Carrier Guide 2010; Vessel Finder, 2020) (see below table).

Ship types and categories

In terms of fuel use, three different powertrains are considered: conventional 2-stroke diesel engines, dual-fuel engines, and solid oxide fuel cells (SOFCs) used in combination with electric motors. See below table shows the fuels suited to each one of these configurations. The literature indicates that fuels with lower energy density, such as methanol, LNG, and ammonia, might reduce the space available for cargo. Therefore, a volume loss of approximately 5% is considered for dual-fuel engines and solid oxide fuel cells (Kim et al., 2020). Differences in investment costs are also considered (MAN 2013; Clarksons Research 2017; Kim et al., 2020).

Technology options regarding the powertrain

As shown in the below table, depending on the motorization, significant increases in the total CAPEX are observed, especially for the case of fuel cells. However, some drop-in alternative fuels need only minor changes of the ship and bunkering to be directly used.

Investment costs for the vessels considered in the modeling

As shown in the below table, specific fuel consumption (SFC) varies according to the fuel used (Gilbert et al., 2018; IMO 2015; Kim et al., 2020).

Main engine specific fuel consumption

Efficiency gains are also modeled, since this is expected to be a major aspect contributing to the reduction of the energy demand from international shipping. Consistently with the projections of the literature (ICCT 2013; Bouman et al., 2017) and with the Energy Efficiency Design Index (ICCT 2011), when compared to 2010, new vessels are taken to be 20% more efficient in 2030 and 30% in 2050.