MnrAq

238 Third IMO GHG Study 2014
Figure 26: Bottom-up model with overview of QA/QC
and uncertainty characterization
Table 17 – Characterization of uncertainty in bottom-up model
Modelling stage Uncertainty (examples) QA/QC measures to reduce
uncertainty
Pre-processor and multi-AIS
merger
Speed
Draught
Time observed
Variability in observed
activity at individual ship
IHSF fleet data Gaps in data Algorithm based on
empirically valid data to
gap-fill missing data
Activity and fleet data merger All equations
Load by mode
SFOC by mode
EFs
Fuel properties
Observed activity bottom-up
fuel and emissions
Imputed activity bottom-up
fuel and emissions
Extrapolation of known
activity to unobserved
periods in a year
Backfill of ship profile for
unobserved ships
Empirical validation;
fundamental principles;
noon reports comparison
Select well-observed ships;
Quantify percentage of year
extrapolated
Characterize ships subject to
backfill
Quantify backfill fleet
Remaining uncertainty
Measurement
Aleatory
Epistemic
Aleatory (aggregated
measurement uncertainty)
Epistemic
Aleatory
Epistemic
Aleatory
Fleet estimate assembly No new uncertainty Propagated from prior steps
From both Figure 26 and Table 17, we have broken down the uncertainty in the total emissions estimate into
three key interconnected components of uncertainty:
1 The uncertainty in the emissions from a ship in one hour:
a
b
When the ship is observed on AIS;
When the ship is not observed on AIS.
2 The uncertainty in the aggregation of (uncertain) hourly emissions (both observed and unobserved
hours) into annual estimates for each ship.