Environmental report · We breathe
An innovative solution for a smaller environmental footprint.
How 2FLOW, our solution for counting and making the most of passenger flows, helps public transport networks attract more passengers, adjust their service and avoid thousands of tonnes of CO₂, nitrogen oxides and fine particles. Method, emission factors and four case studies measured in the field.
WEBREATHE estimates based on ridership measured by 2FLOW and ADEME emission factors (Base Carbone 23.3, July 2024), using conservative assumptions. The method is detailed in section 5.
1Introduction
At WEBREATHE, we believe the future of mobility depends on a sustainable approach. Our 2FLOW solution, dedicated to counting and making the most of passenger flows, gives public transport networks the data they need to understand travel patterns, adjust their service and, in turn, reduce their environmental footprint.
We put passengers and crowding levels back at the heart of the decisions made by operators and transport authorities. By making it easier to match supply with demand, 2FLOW brings passengers greater comfort, renews their desire to use public transport and reduces the use of private cars. The goal is simple: make public transport more attractive so that it is used more and, as a result, the car is used less.
Greenhouse gases, foremost among them carbon dioxide (CO₂), together with nitrogen oxides (NOₓ) and fine particles (PM), have a significant impact on the climate, the environment and human health. CO₂ contributes to global warming; nitrogen oxides degrade air quality and cause acid rain; fine particles penetrate the respiratory tract and affect cardiovascular health. According to the World Health Organization, air pollution is the leading environmental risk to health worldwide.
The name WEBREATHE, “we breathe”, sums up our mission on three levels. On board: vehicles sized to actual ridership, less crowded and more comfortable. In the city: every passenger who leaves their car behind means less CO₂, NOₓ and fine particles in the air we breathe. In the wallet: heavily subsidised, public transport costs far less than the car, so passengers can also breathe easier at the end of the month.
1.1Optimising service according to ridership
2FLOW is a complete, turnkey, customisable and scalable solution designed for public transport. It does more than count passengers: it makes use of the data collected to provide a comprehensive, reliable view of ridership, taking into account the integration, communication and data quality constraints specific to the sector. It is built on eight complementary building blocks.
A 100% French solution, remotely manageable, combining miniaturised counting cells with latest-generation multifunction on-board computers.
An open system that interfaces on board and on the ground with third-party systems (AVL/real-time passenger information systems, ticketing, passenger information), with partnerships continually being extended.
Secure cloud hosting, or on-premises hosting at the customer’s site, with particular emphasis on data security.
A complete, customisable SaaS suite to make the most of counting data: ridership, vehicle load and origin-destination flows, in real time.
Data delivered where it is useful: BI tools and open data (API-DATA), passenger information with vehicle position and occupancy rate (API-IV).
Remote supervision of the status of on-board equipment (Monitoring & Debug), without taking vehicles out of service.
A dedicated project manager, from preliminary design to acceptance testing, who remains on hand for support throughout the contract.
An engineering consultancy with ten years’ experience in public transport and telecommunications, to advise on and carry out the project’s technical studies.
With 2FLOW, operators have a technology that can adapt service to ridership. By analysing the data, they adjust timetables, routes, the number of vehicles in service and their size to offer a consistently optimised service. The result: smoother, more environmentally responsible operations that reconcile performance and sustainability.
- Fewer empty and under-used trips. The data make it possible to adjust lines and timetables to actual needs: extra services on the busiest trips, reduced frequencies on less-used lines. Fewer unnecessary trips mean less fuel burnt, and therefore less CO₂, NOₓ and fine particles.
- Better energy efficiency per passenger. By optimising the use of vehicles (buses, trams, trains) during demand peaks, 2FLOW improves energy performance per person carried and reduces the carbon footprint of every trip.
1.2Analysing ridership peaks precisely
2FLOW collects and analyses ridership data in fine detail. This analysis reveals the times and places where demand is highest, particularly on bus rapid transit lines (BRT), and paves the way for optimised resource management.
- Less under-loading in off-peak hours. Operators adjust the number of vehicles in service while maintaining service quality, and cut fuel consumption and emissions during quiet hours.
- The right resources at peak times. 2FLOW provides the indicators needed to deploy exactly the number of buses required, no more and no less: smart management that maximises operational efficiency and minimises emissions per trip.
1.3Planning proactively
Thanks to historical data, operators anticipate future needs and optimise their fleet proactively. Tailored planning based on seasonal trends and events: by analysing past data, 2FLOW helps anticipate the impact of seasons or specific events, so that services can be adjusted and both over-use and under-use of vehicles avoided.
Our API-IV (Passenger Information) easily integrates essential data into existing applications: vehicle occupancy rates and real-time location, so that passengers can optimise their journeys and operators gain even greater visibility over their flows.
All in all, our customers benefit from far more than a counting tool: better planning, a better-used fleet and fewer unnecessary trips mean an improved passenger experience and lower CO₂, NOₓ and fine particle emissions, for a service that is both greener and more cost-effective.
2Equivalence between a bus and cars
The equivalence between a bus and cars depends on the bus’s capacity, its actual occupancy and the average number of people per car. A standard bus can carry 50 to 60 passengers: at full load, it therefore replaces 10 to 12 fully occupied five-seat cars. In reality, vehicles rarely run full. ADEME uses two reference values:
- 1.43 people per car for short-distance trips (under 100 km), the average occupancy of a five-seat car in 2022;
- 10 passengers per urban bus, the average occupancy rate used in the Base Carbone.
10 passengers per bus ÷ 1.43 people per car ≈ 7. At average occupancy rates, one bus in service replaces seven cars. Every additional passenger improves this ratio further.
3CO₂ comparison between buses and cars
To compare the CO₂ emissions of different types of buses and cars, we use the well-to-wheel emission factors from ADEME’s Base Carbone, taking the “short-distance” values representative of urban trips. A bus emits more than a car per kilometre; it is the number of people carried that makes all the difference.
| Vehicle type | Per vehicle (kg/10 km) | Per vehicle (kg/100 km) | Per person (kg/100 km) | For 10 people (kg) |
|---|---|---|---|---|
| Buses (10 passengers) | ||||
| Electric bus | 2.17 | 21.7 | 2.2 | 21.7 |
| Combustion bus (diesel) | 9.20 | 92.0 | 9.2 | 92.0 |
| CNG bus (natural gas) | 10.40 | 104.0 | 10.4 | 104.0 |
| Cars (1.43 people) | ||||
| Diesel car | 1.95 | 19.5 | 13.6 | 136.4 |
| Petrol car | 2.07 | 20.7 | 14.5 | 144.8 |
| CNG car | 2.01 | 20.1 | 14.1 | 140.6 |
| LPG car | 2.01 | 20.1 | 14.1 | 140.6 |
| E85 car | 1.26 | 12.6 | 8.8 | 88.1 |
Source: ADEME, Base Carbone Documentation 23.3.0 (11 July 2024), p. 184 (cars) and p. 191 (buses); impactco2.fr.
CO₂ emissions per person per 100 km
Buses at 10 passengers, cars at 1.43 people. Kilograms of CO₂ per person.
To carry 10 people over 100 km, a combustion bus emits 92 kg of CO₂, whereas the 7 cars it replaces emit around 145 kg (petrol car), more than a third less. An electric bus emits only 21.7 kg, 85% less than the cars. Per person, the bus remains markedly more frugal than a combustion-engine car, even at the average occupancy of 10 passengers; and every additional passenger lowers the footprint of all the others.
Source tables
| Vehicle | France mixed | Long distance | Short distance | Assumptions |
|---|---|---|---|---|
| Bus, diesel | – | – | 92 | Occupancy rate: 10 people |
| Bus, CNG | – | – | 104 | Occupancy rate: 10 people |
| Bus, electric | – | – | 21.7 | Occupancy rate: 10 people |
| Coach | 29.5 | 25 | 34 | Occupancy rate: 30 people (62%), source ARAFER 2019 |
Source: ADEME, Base Carbone Documentation 23.3.0, p. 191; electric bus: impactco2.fr (ADEME).
| Fuel | France mixed | Long distance | Short distance | Assumptions |
|---|---|---|---|---|
| Diesel | 186 | 174 | 195 | Consumption adjusted to the 2019 Transport Accounts |
| Petrol | 197 | 184 | 207 | Consumption adjusted to the 2019 Transport Accounts |
| CNG | 196 | 180 | 201 | |
| LPG | 192 | 180 | 201 | |
| E85 | 121 | 112 | 126 | |
| Fleet average | 190 | 171 | 209 | 59% diesel, 39% petrol, 2% other (SDES). Long distance: −10%; short distance: +10% relative to the average |
Source: ADEME, Base Carbone Documentation 23.3.0, p. 184.
4NOₓ, fine particles and CO₂ comparison
The same comparison can be made for local pollutants. Exact values depend on the age of the vehicles and their Euro standard; we use the averages published by ADEME to obtain a consistent estimate.
A key air quality pollutant, particularly harmful to the respiratory tract and a cause of acid rain.
Microscopic components that penetrate deep into the lungs and bloodstream and cause health problems.
The main human-generated greenhouse gas, responsible for global warming.
| Bus type | Vehicle NOₓ (g/km) | Vehicle PM (g/km) | Vehicle CO₂ (kg/100 km) | NOₓ per person (g/km) | PM per person (g/km) | CO₂ per person (kg/100 km) |
|---|---|---|---|---|---|---|
| Electric bus | 0 | 0 | 21.7 | 0 | 0 | 2.2 |
| Combustion bus (diesel) | 3.25 | 0.052 | 92.0 | 0.3250 | 0.00520 | 9.2 |
| CNG bus (natural gas) | 1.15 | 0.013 | 104.0 | 0.1150 | 0.00130 | 10.4 |
Source: ADEME, study “Facteurs d’émissions des différents modes de transport routier” (Emission factors of the various road transport modes) (Excel file) and Base Carbone 23.3.0.
| Car type | Vehicle NOₓ (g/km) | Vehicle PM (g/km) | Vehicle CO₂ (kg/100 km) | NOₓ per person (g/km) | PM per person (g/km) | CO₂ per person (kg/100 km) |
|---|---|---|---|---|---|---|
| Diesel car | 0.7000 | 0.0052 | 19.5 | 0.4895 | 0.00364 | 13.6 |
| Petrol car | 0.1408 | 0.0010 | 20.7 | 0.0985 | 0.00070 | 14.5 |
| CNG car | 0.1718 | 0.0004 | 20.1 | 0.1201 | 0.00027 | 14.1 |
| LPG car | 0.1769 | 0 | 20.1 | 0.1237 | 0 | 14.1 |
Source: ADEME, study “Facteurs d’émissions des différents modes de transport routier” (Emission factors of the various road transport modes) and Base Carbone 23.3.0. Per-person values divide vehicle values by 1.43.
Key takeaways
- Electric bus: no direct NOₓ or particle emissions, and the lowest CO₂ per person of all road modes (2.2 kg per 100 km, i.e. 0.022 kg per kilometre).
- CNG bus: nearly three times less NOₓ and four times fewer particles than a diesel bus, for slightly higher CO₂ per person (10.4 versus 9.2 kg per 100 km).
- Combustion bus: 9.2 kg of CO₂ per person per 100 km, a third less than a diesel car (13.6 kg). At the average occupancy of 10 passengers, however, its NOₓ per person remain higher than those of a petrol car: hence the importance of occupancy and fleet renewal.
- Cars: petrol, CNG and LPG emit comparable CO₂ per person (14 to 14.5 kg per 100 km); the diesel car emits slightly less CO₂ (13.6 kg) but four to five times more NOₓ; LPG shows the lowest NOₓ of all cars and no particles.
These data clearly show the effect of vehicle type on emissions: electric buses and, to a lesser extent, CNG buses are the most effective at reducing pollutants per person carried. In every case, the fuller a bus is, the clearer its advantage over the car.
5Case study method
The four case studies that follow apply one and the same deliberately cautious method to ridership measured by 2FLOW. It answers two questions: what did the additional passengers avoid by leaving their cars behind, and how do fleet emissions per passenger change?
- Measured ridership
Boardings and alightings counted at every door by 2FLOW, year after year, not estimates. The increase in ridership between two periods gives the number of additional passengers.
- A typical 5.3 km trip
The median home-to-work distance in urban areas in France (INSEE, 2019). Each additional trip is treated as a 5.3 km journey.
- Modal shift based on national modal shares
Without the solution, the additional passengers would have travelled like the average French person: 62.8% by car, 23.7% on foot, 9.1% by public transport, 2.7% by bicycle. The public transport share is limited to the modes actually present on the network, with the remainder allocated pro rata.
- Official emission factors
CO₂, NOₓ and fine particle factors from ADEME (Base Carbone 23.3, July 2024, and road transport study), applied per person and per trip.
- Conservative assumptions
10 passengers per bus, 1.43 people per car, and each additional passenger bears a full share of the emissions of the bus they ride. In reality, buses and trams are often far fuller.
- A contribution, not an attribution
Ridership growth also stems from the networks’ own choices: service levels, fares, new vehicles. 2FLOW provides the data that inform these choices and measures their effect.
In 2024, most everyday trips are made by private car or motorised two-wheeler (62.8%), followed by walking (23.7%). Public transport accounts for 9.1% of trips and cycling for 2.7%. It is this high modal share of the car that gives modal shift to public transport its full weight.
Source: ADEME, guide “Bouger autrement au quotidien” (Getting around differently every day), pp. 4–5 (Enquête mobilité des personnes, national personal mobility survey).
Trips avoided per mode = additional passengers × modal share of the modeEmissions avoided = Σmodes (trips avoided × emissions per person per trip) − emissions of the same trips on the network| Mode | NOₓ (g) | PM (g) | CO₂ (g) |
|---|---|---|---|
| Tram | 0 | 0 | 22.7 |
| Electric bus | 0 | 0 | 115.0 |
| Combustion bus (diesel) | 1.723 | 0.028 | 487.6 |
| CNG bus | 0.610 | 0.007 | 551.2 |
| Cars (fleet average) | 1.812 | 0.013 | 774.6 |
| Diesel | 2.594 | 0.019 | 722.7 |
| Petrol | 0.522 | 0.004 | 767.2 |
| CNG | 0.637 | 0.001 | 745.0 |
| LPG | 0.656 | 0 | 745.0 |
| E85 | – | – | 467.0 |
| Walking | 0 | 0 | 0 |
| Cycling | 0 | 0 | 0 |
Sources: ADEME, Base Carbone 23.3.0 and study “Facteurs d’émissions des différents modes de transport routier” (Emission factors of the various road transport modes); impactco2.fr. Vehicle factors × 5.3 km ÷ occupancy rate.
The same 5.3 km trip, five carbon footprints
Grams of CO₂ per person, at ADEME average occupancy rates.
Modal shift compares the emissions of the additional passengers on the network with those of the modes they would have used without it. As a precaution, each additional passenger is counted with a full share of the emissions of a bus at average occupancy: on a combustion fleet, this choice greatly understates the real gain and may even show an increase in NOₓ or particles.
Dilution divides the fleet’s annual emissions by the number of passengers carried. With a constant fleet and distance travelled, every passenger gained reduces the footprint of all the others: it is the most direct measure of what 2FLOW changes.
6Case study A: a BRT line with electric buses
Sixteen electric buses fitted with 2FLOW counting cells on a bus rapid transit line. We compare ridership in 2021, before the equipment was installed, with that of 2022 and 2023.
- Equipped fleet
- 16 electric buses
- Average distance per bus
- 35,318 km in 2022 · 31,393 km in 2023
- Vehicles at key times
- 10 in 2021 → 16 in 2022
- Emissions per 5.3 km trip
- 0 g NOₓ · 0 g PM · 115 g CO₂ per passenger
Ridership rose by +25.6% in 2022 (+1,021,307 trips) and then by +3.8% in 2023 (+190,512 trips), making 1,211,819 additional trips in two years. The crowding data justified increasing the number of vehicles in service at key times from 10 to 16, which made this growth possible.
Less CO₂ per passenger
| Emissions per passenger | 2021 | 2022 | 2023 | Change |
|---|---|---|---|---|
| CO₂ (kg per passenger) | 0.0308 | 0.0245 | 0.0210 | −32% |
Annual emissions of the 16 electric buses at 0.217 kgCO₂/km: 2022 = 16 × 35,318 km = 122.6 t; 2023 = 16 × 31,393.47 km = 109.0 t. As 2FLOW holds no 2021 distance data (line equipped in 2022), the 2022 distance is used for 2021.
Between 2021 and 2023, each bus trip generated 32% less CO₂ per passenger: fleet emissions were spread over more passengers, and the distance per bus was reduced in 2023 thanks to a better match between supply and demand, with no loss of ridership.
Modal shift: emissions avoided
| Mode | Share without | Share with | Without · 2022 | Without · 2023 | Without · total | With · 2022 | With · 2023 | With · total |
|---|---|---|---|---|---|---|---|---|
| Combustion bus | 1.66% | 0% | 16,954 | 3,162 | 20,116 | 0 | 0 | 0 |
| Electric bus | 1.66% | 100% | 16,954 | 3,162 | 20,116 | 1,021,307 | 190,512 | 1,211,819 |
| Car | 68.06% | 0% | 695,102 | 129,662 | 824,764 | 0 | 0 | 0 |
| Walking | 25.69% | 0% | 262,374 | 48,943 | 311,316 | 0 | 0 | 0 |
| Cycling | 2.93% | 0% | 29,924 | 5,582 | 35,506 | 0 | 0 | 0 |
| Total | 100% | 100% | 1,021,307 | 190,512 | 1,211,819 | 1,021,307 | 190,512 | 1,211,819 |
| Pollutant | Without the solution | With the solution | Avoided |
|---|---|---|---|
| CO₂ | 651.0 t | 139.4 t | 511.6 t |
| NOₓ | 1.5 t | 0 g | 1.5 t |
| Fine particles | 11.3 kg | 0 g | 11.3 kg |
Without the solution, 824,764 of these trips would have been made by car, equivalent to around 576,758 vehicle trips avoided (at 1.43 people per car). On this line, the use of electric buses and the optimisation of service using 2FLOW data thus avoided the production of 1.5 t of NOₓ, 11.3 kg of fine particles and 511.6 t of CO₂ in two years. These results illustrate the effect of investing in clean public transport sized to actual ridership.
7Case study B: an 18-bus urban network
In 2021, we fitted 12 combustion buses with counting cells and supplied the data to the operator via 2FLOW. The network was then strengthened step by step, with 6 additional buses between November 2021 and January 2023.
- Equipped fleet
- 18 buses: 14 diesel and 4 CNG
- Annual distance per bus
- 20,916 km
- Period
- 2021 to end of 2023
- Emissions per 5.3 km trip
- Diesel bus: 1.72 g NOₓ · 0.028 g PM · 488 g CO₂
CNG bus: 0.61 g NOₓ · 0.007 g PM · 551 g CO₂
Ridership more than tripled in two years: +407,057 trips in 2022 and +66,597 in 2023, making 473,654 additional trips.
Three times lower emissions per passenger
| Emissions per passenger | 2021 | 2022 | 2023 | Change |
|---|---|---|---|---|
| CO₂ (kg per passenger) | 1.765 | 0.585 | 0.528 | −70.1% |
| NOₓ (g per passenger) | 5.19 | 1.72 | 1.55 | −70.1% |
| Fine particles (g per passenger) | 0.081 | 0.027 | 0.024 | −70.1% |
Annual fleet emissions, taken as constant at 18 buses (14 diesel + 4 CNG) each covering 20,916 km: NOₓ 1.0 t; PM 16.3 kg; CO₂ 356.4 t. High-end assumption for 2021, when the fleet numbered 12 buses.
Between 2021 and 2023, emissions per passenger fell by 70.1%, thanks to ridership growth made possible by continuous optimisation of the network based on counting data and by the addition of CNG buses, which emit less NOₓ and fewer particles. Each trip emits three times less than in 2021.
Modal shift: emissions avoided
| Mode | Share without | Share with | Without · 2022 | Without · 2023 | Without · total | With · 2022 | With · 2023 | With · total |
|---|---|---|---|---|---|---|---|---|
| Combustion bus | 1.63% | 77.78% | 6,635 | 1,086 | 7,721 | 316,600 | 51,798 | 368,398 |
| Electric bus | 1.63% | 0% | 6,635 | 1,086 | 7,721 | 0 | 0 | 0 |
| CNG bus | 1.63% | 22.22% | 6,635 | 1,086 | 7,721 | 90,457 | 14,799 | 105,256 |
| Car | 66.95% | 0% | 272,525 | 44,587 | 317,111 | 0 | 0 | 0 |
| Walking | 25.27% | 0% | 102,863 | 16,829 | 119,692 | 0 | 0 | 0 |
| Cycling | 2.88% | 0% | 11,723 | 1,918 | 13,641 | 0 | 0 | 0 |
| Total | 100% | 100% | 407,057 | 66,597 | 473,654 | 407,057 | 66,597 | 473,654 |
| Pollutant | Without the solution | With the solution | Avoided |
|---|---|---|---|
| CO₂ | 254.5 t | 237.6 t | 16.9 t |
| NOₓ | 592.6 kg | 698.7 kg | + 106.1 kg (increase) |
| Fine particles | 4.4 kg | 10.9 kg | + 6.5 kg (increase) |
Without the solution, 317,111 of these trips would have been made by car, equivalent to around 221,756 vehicle trips avoided. Under the cautious assumption, the network avoided 16.9 t of CO₂.
Counted with a full share of the emissions of a combustion bus carrying 10 passengers, the additional passengers show a slight increase in NOₓ (+106.1 kg) and particles (+6.5 kg) compared with the mix of modes avoided, a quarter of which is walking and cycling. This increase is an artefact of the cautious assumption: if the additional passengers are absorbed by buses already in service, as confirmed by the 70% drop in emissions per passenger, all the emissions of the car trips avoided are saved, i.e. up to 245.6 t of CO₂, 574.6 kg of NOₓ and 4.1 kg of particles. Switching to CNG and electric eliminates this gap.
On Network B, the efforts to make the network more efficient and more environmentally friendly avoided hundreds of thousands of car trips, with a marked reduction in emissions per passenger. These tangible results illustrate the effect of investing in cleaner, more efficient and more sustainable public transport.
8Case study C: a 46-bus conurbation network
Forty-six combustion buses fitted with counting cells, whose data are made available via 2FLOW. With a constant fleet and distance travelled, ridership increased 2.3-fold in one year.
- Equipped fleet
- 46 combustion buses
- Annual distance per bus
- 55,322 km
- Period
- 2022 to 2023
- Emissions per 5.3 km trip
- 1.72 g NOₓ · 0.028 g PM · 488 g CO₂ per passenger
Ridership rose by +2,573,411 trips in 2023, i.e. +130%, with no increase in the number of buses or the distances covered.
The same buses, twice as many passengers
| Emissions per passenger | 2022 | 2023 | Change |
|---|---|---|---|
| CO₂ (kg per passenger) | 1.183 | 0.514 | −56.5% |
| NOₓ (g per passenger) | 4.18 | 1.82 | −56.5% |
| Fine particles (g per passenger) | 0.0668 | 0.0291 | −56.5% |
Annual emissions of the 46 combustion buses, identical in 2022 and 2023 (fleet and distance unchanged), 55,322 km each: NOₓ 8.3 t; PM 132.3 kg; CO₂ 2,341 t.
Between 2022 and 2023, NOₓ, fine particle and CO₂ emissions per passenger fell by 57%. The number of passengers rose sharply while total bus emissions remained constant: the environmental impact of each trip is diluted accordingly.
Modal shift: emissions avoided
| Mode | Share without | Share with | Without · 2023 | Without · total | With · 2023 | With · total |
|---|---|---|---|---|---|---|
| Combustion bus | 1.69% | 100% | 43,491 | 43,491 | 2,573,411 | 2,573,411 |
| Car | 69.21% | 0% | 1,781,058 | 1,781,058 | 0 | 0 |
| Walking | 26.12% | 0% | 672,175 | 672,175 | 0 | 0 |
| Cycling | 2.98% | 0% | 76,688 | 76,688 | 0 | 0 |
| Total | 100% | 100% | 2,573,411 | 2,573,411 | 2,573,411 | 2,573,411 |
| Pollutant | Without the solution | With the solution | Avoided |
|---|---|---|---|
| CO₂ | 1,400.8 t | 1,254.8 t | 146.0 t |
| NOₓ | 3.3 t | 4.4 t | + 1.1 t (increase) |
| Fine particles | 24.4 kg | 70.9 kg | + 46.6 kg (increase) |
With more than 2.5 million additional trips in 2023, 1,781,058 of which would have been made by car, the network avoided around 1,245,495 vehicle trips and, under the cautious assumption, 146.0 t of CO₂.
As on Network B, the cautious assumption assigns each additional passenger one tenth of the emissions of a diesel bus, which produces an apparent increase in NOₓ and particles. Here, the fleet and distance travelled did not change: the buses’ actual emissions did not rise by a single gram. On a “constant fleet” reading, the car trips avoided represent savings of up to 1,379.6 t of CO₂, 3.2 t of NOₓ and 23.2 kg of particles. Renewing the fleet with CNG or electric vehicles would transform this result for good.
This project shows that public transport service better matched to demand can have a positive environmental effect by reducing pollution from individual travel, even before any investment in new vehicles.
9Case study D: a metropolis, bus and tram
Two hundred and twenty-seven vehicles fitted with counting cells, 137 CNG buses and 86 electric trams, on a network that has become free for its residents. We compare the measured 2023/2024 season with the projection for the 2024/2025 season.
- Equipped fleet
- 137 CNG buses · 86 electric trams
- Annual distance
- 39,368 km per bus · 40,095 km per tram
- 2023/2024 season
- 107,072,956 passengers counted (September 2023 to August 2024)
- 2024/2025 season
- 129,005,632 passengers projected, based on trends observed after fares were abolished
- Emissions per 5.3 km trip
- Tram: 0 g NOₓ · 0 g PM · 22.7 g CO₂
CNG bus: 0.61 g NOₓ · 0.007 g PM · 551 g CO₂
The projection assumes +21,932,676 passengers (+20.5%) over the 2024/2025 season, split between the tram (92.7%) and buses (7.3%) according to observed ridership. The network’s trams have 263 places and an average occupancy rate of 77%, i.e. 202 people per tram.
* Projection made in September 2024; to be updated with the season’s actual counts.
Modal shift: emissions avoided
| Mode | Share without | Share with | Without · 2024/25 | Without · total | With · 2024/25 | With · total |
|---|---|---|---|---|---|---|
| Tram | 4.82% | 92.70% | 1,057,155 | 1,057,155 | 20,331,591 | 20,331,591 |
| CNG bus | 1.61% | 7.30% | 353,116 | 353,116 | 1,601,085 | 1,601,085 |
| Car | 65.87% | 0% | 14,447,054 | 14,447,054 | 0 | 0 |
| Walking | 24.86% | 0% | 5,452,463 | 5,452,463 | 0 | 0 |
| Cycling | 2.83% | 0% | 620,695 | 620,695 | 0 | 0 |
| Total | 100% | 100% | 21,932,676 | 21,932,676 | 21,932,676 | 21,932,676 |
| Pollutant | Without the solution | With the solution | Avoided |
|---|---|---|---|
| CO₂ | 11,409.5 t | 1,343.7 t | 10,065.8 t |
| NOₓ | 26.4 t | 975.9 kg | 25.4 t |
| Fine particles | 190.2 kg | 11.0 kg | 179.2 kg |
The expected rise in ridership, partly due to the network becoming free, represents 14,447,054 trips that would have been made by car, equivalent to around 10,102,835 vehicle trips avoided over one season. With 93% carried by tram, these trips would avoid 10,065.8 t of CO₂, 25.4 t of NOₓ and 179.2 kg of fine particles.
Lower emissions per bus passenger
| Emissions per passenger | 2023/24 | 2024/25 | Change |
|---|---|---|---|
| CO₂ (kg per bus passenger) | 0.718 | 0.596 | −17% |
| NOₓ (g per bus passenger) | 0.794 | 0.659 | −17% |
| Fine particles (g per bus passenger) | 0.0090 | 0.0074 | −17% |
Annual emissions of the 137 CNG buses, 39,368 km each: NOₓ 6.2 t; PM 70.1 kg; CO₂ 5,609 t. Fleet and distance taken as constant over both seasons.
With a constant fleet, the expected rise in CNG bus ridership would cut emissions per passenger by 17%. This project shows that improving public transport service, here by making it free, can have a major effect on pollution from individual travel, and that counting data make it possible to measure it.
10Conclusion
2FLOW stands out as a key tool for greener, better-optimised mobility. By enabling smart management of passenger flows, the solution reduces unnecessary trips, optimises network resources and makes public transport more attractive.
| Network | Additional passengers | Car trips avoided | CO₂ avoided | NOₓ avoided | PM avoided | Per passenger |
|---|---|---|---|---|---|---|
| A · BRT line 2022–2023 | 1,211,819 | 576,758 | 511.6 t | 1.5 t | 11.3 kg | −32% |
| B · Urban network 2022–2023 | 473,654 | 221,756 | 16.9 t | + 106.1 kg* | + 6.5 kg* | −70% |
| C · Conurbation 2023 | 2,573,411 | 1,245,495 | 146.0 t | + 1.1 t* | + 46.6 kg* | −57% |
| D · Metropolis (projection) 2024/2025 | 21,932,676 | 10,102,835 | 10,065.8 t | 25.4 t | 179.2 kg | −17% |
| Total | 26,191,560 | 12,146,844 | 10,740.4 t |
The results observed on these four networks demonstrate the ability of counting data to support reductions in CO₂, NOₓ and fine particle emissions, while increasing ridership and avoiding millions of car trips. Across these four networks, the additional passengers represent, under our cautious assumptions, more than 10,740 tonnes of CO₂ avoided.
Applying the same method to all equipped networks, we estimate that we helped our customers avoid more than 15,000 tonnes of CO₂ in 2023, compared with 13,900 tonnes in 2022: a positive, ongoing trend that illustrates the growing effectiveness of our initiatives for air quality and against global warming.
Adopting solutions such as 2FLOW is essential to support sustainable mobility and improve air quality in cities: every passenger who leaves their car behind means more clean air for everyone.
We deliberately relied on conservative assumptions, 10 passengers per bus and 1.43 people per car, to reflect reality as closely as possible. In practice, buses are often far fuller, and trams in large metropolitan areas are regularly packed: the real gains are probably greater than those presented here.
11Sources and references
- ADEME, Documentation Base Carbone 23.3.0, 11 July 2024 — emission factors for cars (p. 184), buses and coaches (p. 191), and trams (p. 196).
- ADEME, Étude des facteurs d’émissions des différents modes de transport routier (Study of emission factors for the various road transport modes) — list and fact sheets, Excel file (NOₓ and particles by powertrain). data.ademe.fr
- ADEME, Impact CO₂ — outil transport (transport tool). impactco2.fr/outils/transport
- ADEME, guide Bouger autrement au quotidien (Getting around differently every day), pp. 4–5 — modal shares of trips (Enquête mobilité des personnes, national personal mobility survey).
- INSEE — median home-to-work distance in urban areas (5.3 km, 2019).
- ARAFER, 2019 — coach occupancy rates.
- World Health Organization — ambient air pollution and health.
- WEBREATHE — ridership and distances measured by 2FLOW on the networks studied, 2021 to 2024.
- Document
- WEBREATHE environmental report — revised and corrected web edition, October 2026 (based on version 0 of 25 September 2024).
- Publisher
- WEBREATHE (Wenius SAS), 225 rue des Templiers, 59000 Lille — products designed and assembled in France on our premises.
- Approval
- WEBREATHE General Management.
- Reproduction
- This document is the property of WEBREATHE. Any reproduction, even partial, is subject to the written authorisation of management.