What we measure, and how.

The source data

Every journey is declared by the participant through the Signal: departure point, mode of transport, and the number of occupants for shared journeys. No personal data is collected. What is measured is actual behaviour, not an intention stated beforehand.

Emission factors

For a car, emissions per person = vehicle emissions ÷ the actual number of occupants declared.

These factors are French and are applied to every Bilan, including outside France. Differences between countries lie mainly in electricity — electric cars and rail — and can be significant; combustion modes vary little.

The baseline occupancy rate

The baseline scenario, the one describing the situation with no scheme in place, rests on an occupancy rate of 1.43 people per car. That is the average recorded in France for short-distance travel (under 100 km), source SDES-Insee, Enquête mobilité des personnes 2018-2019, the French national travel survey.

This choice is deliberately cautious. Averages for leisure travel are higher, but getting to an event starts from dominant single-occupancy driving, which is precisely what car-sharing corrects. Using 1.43 avoids overstating the impact of the scheme.

Cars potentially avoided

A car is counted as potentially avoided when a participant who would have travelled alone joins a journey that already exists.

We count how many participants travelled in a shared car and how many cars they actually used. That is compared with the number of cars those same participants would have needed at the baseline rate of 1.43.

Example: 40 participants in 10 cars. At the baseline rate: 40 ÷ 1.43 ≈ 28 cars needed. Avoided: 28 − 10 = 18.

The result is never extrapolated beyond the journeys actually measured. The word “potentially” is kept throughout.

What the data supports

The mobility and emissions values in this Bilan are calculated on the same factor logic as French regulatory GHG reporting. They can therefore feed the “travel” line of Scope 3 reporting, whether it is requested directly or, more often, by a funder, a partner or a local authority under its own value chain.

What the method does not do

MontioAlps does not manufacture false precision. The figures are estimates built on real declarations and official factors. They describe trends and orders of magnitude useful for a decision, never a measurement down to the gram.