How It Works
Our COâ‚‚ calculator or algorithm is grounded in scientific research conducted at the Royal Institute of Technology in Stockholm. This research was subsequently published in the scientific newspaper "Sustainable Environment Research".
The Only CO2e Calculator Using Live Data
Our algorithm utilizes live data, boasting an extensive database covering all current and historical flights worldwide. This rich dataset enables us to match the exact aircraft for your trip, identify the fuel consumption corresponding to each engine, determine the number of passengers on board, consider seating classes, account for height factors, and more. This level of detail ensures highly accurate COâ‚‚ calculations. Did you know that a same distance trip can have a CO2e difference of 60% or more just because of aircraft and number of seats used? Further details about the algorithm can be found in our papers below.
Did You Really Fly Straight?
The conventional method for calculating CO2e among other calculators involves using Vincenty's formula from point A to B multiplied by a carbon factor. Some more advanced calculators also consider engine type and the number of seats. However, in reality, many flights do not follow a straight line due to factors such as no-fly zones caused by covid or conflict zones, geographical features like mountains, or landing patterns. This deviation significantly affects emission levels. Carbon Compute's algorithm stands out as the only one using live data, providing the most accurate CO2e calculations possible.
Details
Before delving into the algorithm, it's good to start by reading the scientific papers to gain a comprehensive understanding. However, here's a crash course, as there have been some improvements to it over the years:
U (emissions CO2e (equivalents))
C (Carbon Dioxide Conversion Factor)
This is a constant. For every kilogram of jet fuel burnt, 3.15 kilograms of CO2 is produced.
LTO / CCD (Landing, TakeOff Taxi / Climb Cruise Descent)
Carbon Compute utilizes data from the European Environmental Agency (EEA) to obtain the latest fuel consumption data for all aircraft worldwide. Three different y = kx + m curve fittings are employed, depending on the distance, as fuel consumption varies over distance.
D (Distance)
Real distance is used, as discussed above, with data sourced from flightera.net. For some routes, this distance can differ by more than 100%.
F (heigh factor)
The overall height factor is x1.7 for all flights worldwide. This factor comprises the equivalents for all non-CO2 effects created during combustion. The most significant factor by far is the radiative forcing (RF) caused by contrails - small clouds visible in the sky after an aircraft have flown. Contrails are only formed when it is cold enough and the air is ice super-saturated, typically occurring in the tropopause, where medium and long-haul aircraft operate. Depending on factors such as albedo and whether contrails are produced during day or night, some contrails cause warming, while others have a cooling effect on the climate. However, the net effect is always warming.
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As one can see, this topic quickly becomes very complicated. In reality, only a few aircraft produce contrails, but when they do, it results in a significant height factor. Passengers may be aware that short flights never create this effect, but medium and long flights may or may not produce contrails. To simplify, Carbon Compute has chosen to use the calculated average height factor for the part of the trip that is over 8000 meters. This implies that short-haul flights and turboprop flights usually never have this factor. Meanwhile, medium and long-haul flights will always have this height factor, gradually increasing to around x1.9 once it kicks in (over approximately 8000 meters).
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The height factor is a heavily debated topic among researchers, with high uncertainty. Some scientists argue for a slightly lower factor, while others advocate for a much higher one. To avoid this variability, some calculators opt for the easy way out and use a height factor of 1. However, Carbon Compute aims to take responsibility and apply a wise and fair approach as explained above.
Recent discussions propose adjusting aircraft altitudes or predicting contrail occurrence, which could potentially significantly reduce CO2 equivalents.
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B (Occupancy)
This value represents the seat occupancy for each airline. Different airlines experience varying occupancy rates, which may fluctuate monthly or annually. Typically, occupancy hovers around 80%, but certain low-cost airlines manage to reach over 90% during peak periods. Conversely, more luxurious airlines may have considerably lower occupancy rates. The COVID-19 pandemic has introduced significant fluctuations in this value.
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P (Number of Seats)
This is the weighted number of seats in an aircraft. Airlines feature diverse cabin layouts, even for the same type of aircraft (e.g., A330), with differences of up to 40%.
The weighted part is calculated using the following formulas:
The actual size of the seat is determined by equation 3, multiplying the pitch by the width for each seating class (n). Subsequently, the weighted number of seats (Pn) can be calculated using equation 2, dividing the number of all seats for a specific class (An) by the sum of the number of seats (N x A) for each class.
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n (Type of Seat)
Different-sized seats correspond to different amounts of CO2e emissions. In many cases, the number of seats in an aircraft can be configured just before departure. For example, if a CY seat is used, signifying that class Y is purchased, there will be three seats in a row (or a side). However, if class C is purchased, the middle seat will be removed, creating more space for the two passengers left. In this scenario, the seating area is x1.5 or 50% larger for a C seat than a Y seat, although such variations can differ widely.
Our Publications
Science Paper -
Schennings, A., Larsson, J., Robért, M.
Masters Thesis -
Schennings, A., Larsson, J.
Masters Thesis -
Lindberg, E.