Third IMO Greenhouse Gas Study 2014

Scenarios for shipping emissions 2012–2050 131
This procedure has resulted in the following scenarios:
• RCP8.5 combined with SSP5;
• RCP6 combined with SSP1;
• RCP4.5 combined with SSP3;
• RCP2.6 combined with SSP4/2.
In all the work by IPCC on future scenarios of climate and its impacts, it has never assumed a BAU underlying
growth scenario. IPCC has always argued that it does not produce any one emissions scenario that is more
likely than another, ergo no overall BAU scenario exists. This is therefore reflected in this study and no one
basic RCP/SSP scenario that underlies the shipping emissions scenarios can be considered more likely than
another: they are all BAU scenarios.
3.2.3 Transport demand projections
Transport work data (in billion tonne-miles per year) were kindly provided for the years 1970–2012 by
UNCTAD (see Annex 7). The categories considered were crude oil and oil products (combined), coal bulk dry
cargo, non-coal bulk dry cargo (iron ore, coal, grain, bauxite and aluminia and phosphate, all combined) and
other dry cargo (essentially considered as container and other similar purpose shipping). The data were for
international shipping only. Transport work (i.e. tonne-miles), as opposed to the absolute amount transported
(tonnes), is considered to be a better variable to predict transport demand and emissions. However, this
assumes that average hauls remain constant: this is in fact borne out by the data and the two variables
correlate significantly with an R 2 value of >0.95.
Cargo types were treated separately, as it is evident from the data that they are growing at different rates and
subject to different market demands.
Thus, as a refinement to the approach taken in the Second IMO GHG Study 2009, the current study has
developed the methodology of CE Delft (2012), which considered different ship types and has gone a step
further by decoupling the transport of fossil fuel (oil and coal products) from GDP, as in the RCP/SSP scenarios
in which fossil fuel use is decoupled from economic development.
In order to predict ship transport work (by type, or total), the general principle is to look for a predictor variable
that has a meaningful physical relationship with it. In previous scenario studies, global GDP has been used as
a predictor for total ship transport work, in that it has a significant positive statistical correlation, and is also
meaningful in the sense that an increase in global GDP is likely to result in an increase in global trade and
therefore ship transport of goods.
If an independent assessment of the predictor variable (e.g. GDP) is available for future years, this allows
prediction of ship transport work. It assumes that such a physical relationship is as robust for the future as it has
been for the past. Previously, a linear assumption has been made, i.e. a linear regression model has been used
between the ratio of historical transport work to historical GDP against time. In this study, this assumption
has been improved by the use of a non-linear model, commonly used in economics, that assumes classic
emergence, growth and maturation phases.
However, the assumption of a historical relationship between coal and oil transport by shipping and GDP
inherently means that GDP growth and fossil fuel use will remain tightly coupled in the future, i.e. that with
increased economic growth, it is not possible to limit fossil fuel use. This clearly does not reflect certain
desired policy and environmental outcomes, where a decrease in fossil fuel dependence and an increase in
GDP can be achieved.
In order to overcome this, this study has investigated the relationship between historical ship-transported coal
and oil and historical global coal and oil consumption. This relationship has been found to be as robust as that
between historical coal and oil transport work and historical GDP (r2 >0.9) and is arguably a better physical
relationship than between fossil fuel transported by shipping and GDP. The RCP scenarios have provided
projections of fossil fuel consumption, split between coal and oil. This conveniently allows us to use these
predictor variables to determine potential future ship transport of coal and oil but decoupled from GDP. Other
ship transported goods and products remain predicted by independent future GDP assessments provided by
the RCPs.