MnrAq

Annex 3 207
Table 15 – List of ship types (number of ships) used in this analysis
Ship Type 2007 2008 2009 2010 2011 2012
Bulk carrier 3 3 6 9 39 52
Chemical tanker 0 0 3 1 17 1
Container 1 1 0 4 4 10
General cargo 0 0 0 0 0 57
Liquefied gas tanker 1 3 2 7 17 10
Oil tanker 11 11 12 16 54 40
Service – tug 0 0 0 0 5 0
Miscellaneous – fishing 0 0 0 0 2 0
Offshore 0 0 0 0 1 0
The total number of ships for which data has been collected represents approximately 1% of the total number
of ships in the fleet, and approximately 2% of the total fuel consumption of the fleet.
Noon report data contains inherent uncertainties because measurement on board ships is of variable quality
depending on the techniques used. Many noon reports (including many of those used in this study) are
populated using tank soundings which can have high measurement error (see Aldous et al., 2013). To address
this issue, we have discussed quality procedures with the companies from which the data is collected (many
of which have processes in place to assure the quality of the data). Furthermore, we have aggregated the data
to quarterly totals (main engine and auxiliary engine fuel consumed, days at sea and in port, and distance
travelled) and averages (speed, draught and tonne-per-day fuel consumption). This process of aggregation
controls for the uncertainty in daily observations, providing there is no systemic bias in the reporting of any of
the data. While systemic bias (e.g. consistent under-reporting of fuel consumed by the crew) cannot be ruled
out, the magnitude of the error that this could create is not considered likely to be large relative to the level of
assurance that is sought from these comparisons.
Method of processing noon report data in preparation for comparison
against bottom-up model output
The noon report data for each ship was aggregated per quarter, and summary statistics on activity and fuel
consumption were output for comparison with the bottom-up method.
Only ships for which the noon report data are fully populated for a full quarter (plus or minus five days) is
suitable for comparison; incomplete quarters are filtered out. Obvious outliers, usually due to human error in
the reporting, are identified manually and removed.
There are a small number of observations for which ship speed and distance travelled is logged but fuel
consumption is not recorded. In this instance, the fuel consumption is filled in by conditional mean imputation:
fuel consumption is predicted based on information from fully observed variables (ship speed, loading
condition and weather) through multiple regressions. Filtering for part days precedes the regression in order
to avoid skewness arising from manoeuvring/in-port operations. If none of the coefficients from the regression
are found to be statistically significant, simply the mean at-sea fuel consumption for that ship is used. Overall,
this approach introduces additional uncertainty in the comparison, but since fuel consumption is compared
on an aggregate basis, on balance this is an improvement. Only a small number of observations are adjusted
in this way (approximately 2.3% of all observations).
Where a time and distance travelled is logged but there is no speed recorded, the speed is calculated from
these two fields and filled in (0.3% of observations).
Generally, the noon report fuel consumption fields cover only days at sea; where End of Sea Passage (EOSP) or
Free Away on Passage (FAP) are not explicitly defined in an “activities” field (or similar), port days are therefore
calculated when zero monitored fuel consumption coincides with zero speed and distance travelled.
Fuel consumption associated with part days – i.e. on a day when the ship is leaving or arriving in port – is
included in the per-quarter aggregates, and the hours’ steaming during part days are included in the totals for