51 Cycling Sustainability Statistics

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These cycling sustainability figures cover the measurement periods and populations identified in the available source material. Estimates, surveys and forecasts retain their reported scope.

Key Cycling Sustainability Statistics

The main findings are:

  • England recorded an estimated 0.9 billion cycling stages in 2023.
  • The average English resident cycled 47 miles in 2023 (England).
  • A 2026 peer-reviewed e-bike LCA estimated 45 g CO2e per kilometer (2025–2050 model period; Chinese urban transport systems).
  • The peer-reviewed e-bike study projected 2.9–5.1% of China’s urban transport emissions could be offset by 2050 under strategic integration (2050 forecast).
  • A China bike-sharing LCA found production contributed an average 81.18% of impacts across nine environmental categories (study model; China bike-sharing system).
  • Great Britain recorded 82 pedal-cyclist fatalities, 3,822 serious injuries and 10,645 slight injuries in 2024.
  • People in England made 15 cycling trips per person in 2023.
  • Average cycling distance in England was 22% higher in 2023 than in 2002 (2002–2023).
  • The same e-bike LCA estimated a life-cycle footprint of 576–890 kg CO2e per e-bike (2025–2050 model period; Chinese urban transport systems).
  • Around 4% of English survey respondents owned or had regular use of an electric cycle in 2021 (England).
  • Pedal-cyclist fatalities in Great Britain fell 6% in 2024 (2023–2024).
  • Cycling accounted for 2% of trips in England in 2023.
  • Average cycling distance in England fell 17% from 57 miles in 2022 to 47 miles in 2023 (2022–2023).
  • The study’s newer e-bike footprint estimates were 48–64% higher than earlier estimates (comparison reported in 2026 paper; Chinese e-bike LCA literature/model).
  • London’s cycling mode share was 4.5% of trips in 2023.

Contents

Cycling sustainability statistics: participation and access

NTS-based estimate; stages are parts of trips and are not equivalent to unique riders.

National Travel Survey household sample and travel diary; small cycling-trip counts can be volatile.

Share is trip-based and covers residents’ travel, not all cycling activity.

NTS distance measure; excludes activity outside its travel definitions.

Ownership and access are combined; this does not measure use frequency.

Ownership and access are combined.

PeopleForBikes participation study; at-least-once participation is not regular riding.

Participation-study estimate; not a measure of trips or distance.

Comparison is between biennial study waves and uses the study’s youth definition.

Self-reported concern, not observed crash risk.

Self-reported familiarity.

NTS estimate; cycling miles include the survey’s defined travel activity.

Long-run comparison of NTS estimates; definitions and survey conditions should be read with the series.

NTS estimate; the release notes small cycling-trip counts and changing trip purposes.

Average trip length, not a median or a distance for every cyclist.

Average across the population, including non-cyclists.

Trip-purpose classification in NTS; not a share of cycling distance.

Trip-purpose classification in NTS.

Road traffic estimate excludes some off-highway cycling such as canal towpaths, byways and bridleways.

Traffic estimate covers specified public highways and adjacent paths.

TfL estimate; stages are not trips or unique people.

TfL series; pandemic-period comparisons and stage definitions matter.

TfL estimate, distinct from cycle stages.

Cycling’s measured climate and air-quality outcomes

Spatially explicit model; result is not a direct measurement of every e-bike trip.

Range reflects model assumptions and provincial grid intensities.

Comparison reflects more complete inventories and grid factors in the study, not an observed time trend.

Sectoral LCA estimate with reported uncertainty; not a national emissions inventory line item.

Counterfactual modal-substitution estimate; depends on assumed replaced modes and travel volumes.

Modelled avoided emissions from modal substitution.

E-bike sustainability statistics and modal substitution

Scenario forecast, not a committed-policy outcome.

Older National Travel Attitudes Study estimate; ownership or regular use is not trip share.

Trip-based mode share, not distance share or lifecycle carbon share.

TfL daily-trip estimate; not a causal estimate of infrastructure effects.

TfL attributes the change primarily to fare-system changes and dockless competition; member hires continued increasing.

LTDS annual participation measure; at least once is not frequent cycling.

LTDS comparison across survey years.

TfL converts the survey percentage-point change to a population estimate.

Bike-sharing life-cycle sustainability statistics

A China bike-sharing LCA found production contributed an average 81.18% of impacts across nine environmental categories (study model; China bike-sharing system). (How can bicycle-sharing have a…)

LCA result for the studied system; category averages can conceal differences between impact categories.

Reported road casualties; under-reporting and reporting coverage can affect non-fatal totals.

Reported fatalities; year-to-year change is not a long-run risk trend by itself.

Uses road-traffic mileage denominator and reported casualties.

Reported fatalities divided by estimated pedal-cycle traffic.

Long-run reported-casualty rate using traffic estimates.

Long-run rate comparison; changes in exposure and reporting matter.

Reported KSI casualties, not population-normalized risk.

The comparison is between fatality location and traffic distribution, not a causal risk estimate.

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