Third IMO Greenhouse Gas Study 2014

Inventories of CO2 emissions from international shipping 2007–2012 63
Figure 45: Confidence bands showing statistical difference between IEA and EIA data, 2000–2010
Results of top-down QA/QC
The top-down QA/QC provides a thorough understanding of the quality and limitations of the top-down
inventory. This review shows that IEA revisions to statistics can change the total fuel sales estimate by as much
as 10% owing to documented quality controls in place at IEA. A rigorous review of IEA QA/QC practices
indicates that the energy balances continue to represent high-quality representation of OECD and non-OECD
energy statistics.
Our IEA data comparison with EIA fuel oil statistics for international marine bunkers indicate that year-on-year
fuel sales data can differ by more than 10% and that IEA tends to report more international marine bunkers
over the period 2000–2010.
Lastly, the IEA presentation to the IMO Expert Workshop in 2013 indicated that significant uncertainties are
not fully documented and require further analysis (see Section 1.5). For example, under- or overestimates of
international marine bunkers could result from allocation or classification errors – imports, exports, marine
bunker statistics, fuel transfers between sectors (as is typical for blending marine bunkers with other fuels to
meet ship/engine fuel quality specifications) – and poor data quality among reporting countries could restrict
the accuracy of international bunkers estimates.
1.4.3 Bottom-up QA/QC
The key findings of the bottom-up quality assurance and quality control analysis include:
• Quality in fuel consumption totals is extensively analysed by a number of independent sources (both
independent of the data used in the model and independent of each other).
• This assurance effort represents significant progress relative to all prior global ship inventories (including
the Second IMO GHG Study 2009). These QA/QC efforts demonstrate that a reliable inventory of fuel
consumption broken down by fleets of ships and their associated activity statistics has been achieved
in this study.
• There is a step change improvement in quality in the bottom-up inventory between the earlier years
(2007–2009 inclusive) and the later years (2010–2012 inclusive), which can be attributed to the
increased coverage (both temporal and spatial) of AIS data and therefore the accuracy of the activity
estimate. This also underpins better confidence in bottom-up emissions totals, based on the same
methods, using consensus emissions factors derived from reviewing published emissions factors.
• The key data sources that have enabled the high quality of this study, particularly S-AIS data, continue
to increase in quality. This is owing to continuous improvement of the algorithms on the receivers,