What Will Mobility Look Like in the “New Normal”?

- Article co-authored by Carbone 4 and Mobility Patterns (Hove) ^[7] -

On May 11, 2022, we marked the second anniversary of the end of the first lockdown. Two years later, have our travel habits changed significantly as a result of the health crisis? And, more importantly, what are the impacts on greenhouse gas emissions directly caused by our travel? Beyond anecdotal accounts and personal experiences, Carbone 4 and Patterns offer an analysis based on daily mobility data to understand these changes, taking into account the evolution of transportation options that have actually been implemented.

For this first use case, one large metropolitan area (Rennes Métropole) and one medium-sized metropolitan area (Métropole du Grand Nancy) were selected. Travel^[1] The figures recorded in February 2020 were compared with those from February 2022.

The method used

The measurement is based on a sample^[2] trips originating from the smartphone geolocation, collected from a variety of mobile apps. The accuracy of geolocation makes it possible to distinguish between the modes of transportation used and to calculate the distances traveledassociated modes. More specifically, a modal allocation algorithm compares temporal and spatial compatibility with the various possible modal routes (public transit, cycling, walking, or private vehicle) to determine the specifics of the route taken: for example, a user traveling along bike paths is likely riding a bike, and a user whose path and exact schedule match those of a bus is likely riding the bus.

CO2-equivalent emissions are then estimated by correlating this distance with the emissions of each mode, expressed in passenger-kilometers^[3]. For trips taken by public transportation, these emissions depend heavily on the actual fill rate, which was calculated daily for each line transportation.

A statistical adjustment, based on sociodemographic data, allows for a Estimation of distances and equivalent emissions for the entire population^[4].

What insights do these data provide?

First of all, in terms of distances traveled, there was ultimately very little change: a slight increase in total distances (3.7%) in Nancy and a slight decrease (-3.5%) in Rennes. In both cities, we see that The use of public transportation has decreased. Both in absolute and relative terms, travel by foot and, above all, by public transportation has declined sharply, with a decrease of up to 32% in kilometers traveled by public transportation in Rennes. The moderate increase in bicycle and scooter traffic^[5] is not enough to offset this decline in ridership and public transportation. Thus, theThe number of kilometers traveled by car has increased in both cities (rising from 74.1% to 77.6% in Nancy and from 75.9% to 79.7% in Rennes).

Changes in Distances Traveled in Business Days (p.km)

Overall, the Emissions are on the rise in both cities (+10% in Nancy and +1% in Rennes). In fact, not only does the increase in car trips directly result in an almost proportional rise in emissions^[6] However, emissions from public transportation have decreased only slightly or have remained stable. In fact, to ensure a high-quality service, public transportation offerings have remained largely unchanged, even though ridership has declined.

What conclusions can we draw from this?

While these figures are certainly not exhaustive—since they cover only two cities in France and a period of just two months—they nevertheless illustrate a striking reality: the “world after” so often discussed during the COVID crisis still resembles the “world before” in many ways. There are still too many cars and not enough public transportation or sustainable mobility options, even in dense urban centers. Efforts to further reduce car use in daily life are more necessary than ever.