Assumptions
Scope of sector
The IPCC GHG inventory guidelines divide shipping into international navigation, domestic navigation and fishing (IPCC, 2006). It defines international shipping as “journeys that depart in one country and arrive in a different country”, while domestic shipping includes “journeys from ports to ports within the same country”. International shipping is responsible for most emissions (87% in 2017) (ICCT, 2017). Data incorporating both international, domestic shipping and fishing is often referred to as ‘total shipping’.
Our assessment is of international shipping only and all references to shipping should be taken to mean ‘international shipping’ unless otherwise stated.
Emissions from domestic shipping and fishing are considered as part of national totals and are included in the assessment of individual CAT countries.
Gas Coverage
Our analysis is limited to CO2 emissions, in line with the CO2 carbon intensity target of the IMO and which represents the lion’s share of emissions. In 2015, 91% of emissions for total shipping were CO2 emissions on a 100 year time-scale GWP (ICCT, 2017).
International shipping is also a source of black carbon, methane and N2O emissions. Black carbon is the second largest contributor to climate change emissions from shipping after direct CO2 emissions, accounting for 7% of total MtCO2eq on a 100 year time-scale GWP and 21% on total MtCO2eq on a 20 year time-scale GWP in 2015 (ICCT, 2017).
Historical emissions
The CAT derived its historical emissions data for the period 1990 to 2017 from a variety of sources (ICCT, 2017; IEA, 2019; IMO, 2009; Smith et al., 2014). Such an approach was necessary due to the lack of a historical timeseries for this sector (Hoesly et al., 2018; SEI, 2019). The IEA provides the most recent historical data, which is updated annually; however, it has historically underestimated shipping emissions (Hoesly et al., 2018; Olmer et al., 2017).
We use data from the IMO’s second GHG study and the IEA to calculate growth rates in order to extend the time series from the International Council on Clean Transportation back to 1990 and forwards to 2017. The ICCT data covers the period 2007 to 2015; though only the most recent years (2013-2015) are ICCT’s own estimates. Data for the 2007 to 2012 period are derived from the IMO’s third GHG study. As the ICCT uses a different methodology, its figures are slightly different to those contained in the third study (ICCT, 2017; IEA, 2019; IMO, 2009; Smith et al., 2014).
Sector targets
Carbon intensity target
Carbon intensity target is defined as CO2 emissions per transport work across the international shipping fleet. We used OECD ITF data on global freight transport to approximate transport work (tonnes per nautical mile). Maritime transport accounted in 2011 for 87% of global freight transport, which we assumed to remain constant and converted the data into nautical miles (OECD - ITF, 2017). This estimate of transport work does not include passenger transport work.
To calculate the 2030 and 2050 targets, we applied the respective reductions to the carbon intensity in 2008.
To calculate emissions level in these years, we took the projections from the OECD Transport Outlook 2017 for global freight transport (devising the international shipping freight projection as described above) for the pre-COVID projection. For the low and high emissions scenarios, we used the WTO projections for the changes in trade volume to estimate the reductions in international freight work for 2020 and 2021 and applied the growth rates from the OECD Transport Outlook 2017 for the period of 2023-2050 (OECD - ITF, 2017).
Absolute Target
The 2050 target applies to all GHG emissions; however, we applied it to CO2 emissions only. Based on the ICCT historical emissions data, the emission reduction target would be 471 MtCO2eq for all greenhouse gases, which is about 3% higher than the CO2 emissions only (ICCT, 2017).
Current policy projections
Our pre-COVID-19 current policy projection is based on projections from the IMO Strategy including energy efficiency measures implemented such as the Energy Efficiency Design Index (EEDI) and the Ship Energy Efficiency Management Plan (SEEMP). As the IMO does not provide the underlying data of its projections, we extracted the current policy projections from the IMO strategy from 2015 to 2050 with five-year intervals. We then harmonised to this last historical year 2017 (ICCT, 2017; IEA, 2019; IMO, 2009; Smith et al., 2014).
COVID-19 Impact Assessment
We analyse the impact of the COVID-19 on merchandise transport and passenger transport through two scenarios: a high emissions scenario and a low emissions scenario.
We assume that passenger based maritime transport represents 9% of emissions in 2019 based on its historic share (ICCT, 2017).
Emissions for 2018-2019 are from the pre-COVID current policy projections (described above).
To estimate merchandise transport emissions, we use as proxies the WTO projections for changes in trade volume for 2020 and 2021, namely a 13% reduction in 2020 and 21% growth in 2021 for the high emissions scenario (full recovery) and a 32% drop in 2020 and 24% growth in 2021 for the low emissions scenario (partial recovery) (WTO, 2020). In the case of the high emissions scenario, we assume that trade emissions growth have returned to pre-COVID-19 crisis from 2022 onwards.
To estimate passenger transport (cruise/ferries) emissions, we use as proxy an estimate from the UN World Tourism Organization of a 70% reduction in international arrivals in 2019 assuming travel restrictions ease in September (UNWTO, 2020). In the high emissions scenario, we assume passenger transport returns to 2019 levels in 2021 (fast recovery) and in 2022 in the low emissions scenario (slow recovery).
Emissions from 2023-2050 are calculated using the growth rates in the pre-COVID current policy projections.
Further analysis
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