Data Analysis
We expect to receive operators’ raw flight & fuel data in a single, organised Excel file after sharing the Audit Preparation Letter (APL), and we will transfer these data to Normec Verifavia’s Emissions Data Analysis System for review, which allows us to evaluate the accuracy and consistency of flight & fuel values. Among several checks that we perform on fuel values, let us begin with a few of them that are straightforward to understand:
- Tank capacity check. Each type of aircraft has a corresponding maximum tank capacity; it is not logical if the fuel uplift provided by the operator for some flights exceeds this limit.
- Negative value check. Fuel consumption for each sector must be positive. If any fuel consumption in operators’ raw data is negative, there is clearly an error.
- Block-on value or uplift value can never be greater than block-off value.
- The units of fuel values (Litre, Kilogram, and Gallon) should be standardized and there are no mistakes in the conversion between different units.
As verifiers, we also assess whether the aircraft operators apply the Fuel Use Monitoring Method (Method A, Method B, or Block-off / Block-on) correctly. That said, the fuel consumption of every flight reported by the operator must be calculated by the method recorded in the approved Monitoring Plan. Our data analysis system will identify and flag any flight that deviates significantly from the expected value, and the fuel values (fuel uplift, block-off value, block-on value) are then examined more closely.
Benchmarking is also a useful method for us to gain reasonable assurance that operators’ fuel data is duly recorded, transferred, and reported. We compare the reported consumption versus the estimation given by SET (Small Emitters Tool developed by EUROCONTROL) or CERT (CORSIA CO2 Estimation & Reporting Tool developed by ICAO). However, these tools are always ideal and conservative, since real-world inefficiencies in aircraft operation (diversions due to airspace closure, long holding procedures due to weather) are not taken into consideration. In addition to that, air cargo operators may find these tools less convincing for their fleet because they were developed using the aircraft statistics drawn from commercial passenger operations. Therefore, this check can also be reinforced further through a mean statistical check, measuring each flight against the average value for one specific aircraft for one specific leg. For instance, among all flights of one operator between Paris and London with A320 aircraft during 2025, two or three flights might record fuel consumption that is 52% above the average. Then we would like to investigate what leads to these exceptions. Is it because of the extremely long holding pattern above Heathrow on that day, or a simple data entry mistake?