What decision are we actually trying to support?
A clean-transport project may replace vehicles, redesign a street, shift trips to public transport, change delivery operations, or reduce traffic volume. Each intervention changes a different part of the system. The evidence plan should begin with that operating change, not with a broad claim that transport became clean.
Total PM2.5 concentration is an essential health and air-quality measure. It tells a project team how much fine particulate matter is present at a monitoring location over a defined period. It does not, by itself, identify how much came from traffic, which traffic process produced it, where people were exposed, or whether another source changed at the same time.
The practical question is therefore narrower: what evidence would allow an operator, city, funder, or reviewer to connect a transport intervention to a measured change in traffic-related exposure without hiding uncertainty?
What the 2026 multi-country study reports
A 2026 Nature Sustainability study analysed daily cancer mortality records from 2000 to 2019 across Australia, Brazil, Canada, Chile, South Korea, Mexico, New Zealand, and Thailand. The authors used a time-stratified case-crossover design and included 9,223,612 cancer deaths.
For each 10 ug/m3 increase in the two-day moving average, the study reported an association with a 0.77% increase in all-cancer mortality risk for all-source PM2.5 and a 3.87% increase for traffic-sourced PM2.5. The reported 95% confidence intervals were 0.64% to 0.89% and 3.28% to 4.47%, respectively.
Within the study model, traffic-sourced PM2.5 represented 14.72% of total PM2.5 concentration but 73.55% of PM2.5-attributable cancer deaths during the study period. The authors concluded that reducing traffic-sourced exposure may help lower acute pollution-related mortality risks among people with cancer.
Those figures need a strict boundary. They are results from an observational, multi-country epidemiological analysis that combined mortality records with modelled source-specific exposure. They do not prove that every traffic particle caused a death, predict the effect of one local project, or replace local monitoring and source assessment.
Why total PM2.5 is necessary but not sufficient for a transport claim
The World Health Organization uses PM2.5 as a central indicator because its health effects are well documented and because consistent concentration measures support public-health decisions. WHO also notes that outdoor particle sources vary by location and can include transport, industry, power generation, construction, waste burning, fires, and other activities.
A roadside monitor can therefore show a real concentration change without proving that the transport intervention caused all of it. Weather, seasonal burning, construction, industry, regional background pollution, and monitoring placement can move the result. A project needs a comparison strategy that can separate the intervention signal from those concurrent changes.
Transport itself is also not one source. Tailpipe combustion, brake wear, tyre wear, road abrasion, resuspended dust, and upstream electricity or fuel systems have different evidence needs. As exhaust controls and electrification reduce some emissions, non-exhaust particles can become a larger share of what remains.
The European Environment Agency reported that non-exhaust sources accounted for 60% of road-transport PM2.5 emissions in the EU-27 in 2023. That is a European inventory result, not a universal ratio. Its operational lesson travels more widely: a vehicle transition should not treat the disappearance of a tailpipe as the disappearance of particulate pollution.
Build the measurement plan in five layers
A useful evidence plan connects five layers. The first two establish what changed in the environment. The next two establish whether the change is plausibly connected to the intervention and meaningful for people. The final layer keeps remaining impacts visible.
- Total concentration: define PM2.5, PM10, nitrogen dioxide, black carbon, ultrafine-particle, or particle-number metrics that match the decision. Record averaging period, instrument, calibration, completeness, and quality-control rules.
- Source contribution: use a defensible source-apportionment method, traffic counts, fleet composition, fuel or powertrain data, and operating patterns to distinguish traffic-related change from background and concurrent sources.
- Place and time: combine roadside and background locations, before-and-after periods, comparable seasons, meteorology, construction activity, exceptional events, and enough monitoring duration to avoid reading one unusual day as a trend.
- Exposure: identify where people live, work, walk, cycle, wait, study, or receive care. Do not assume that an area-wide average represents a kerbside worker, school entrance, transit stop, or neighbourhood beside a freight route.
- Residual impacts: track brake, tyre, road-wear and resuspension evidence, vehicle mass, traffic volume, congestion, noise, safety, land use, energy source, and displaced activity when those factors are material to the intervention.
Before and after: from a technology claim to a decision record
Before: a fleet replaces combustion vehicles with electric vehicles. The project reports the number purchased, estimates avoided tailpipe emissions, and labels the programme an air-quality success. One city monitor shows a lower annual PM2.5 value after deployment.
That record may support an equipment and tailpipe claim. It does not yet show whether traffic-sourced exposure changed at relevant locations, whether the monitoring periods were comparable, or whether tyre, brake, road, freight, and background sources altered the outcome.
After: the team records the intervention date, routes, kilometres, vehicle mass, traffic volume, charging or fuel boundary, and operating conditions. It defines roadside and background monitors, source indicators, weather and activity controls, and exposure locations before reviewing the result. Tailpipe and non-exhaust findings remain separate. Exceptions and missing data stay visible.
The improved record does not guarantee a positive result. It makes the decision auditable. A project can then show which burden changed, where confidence is strong, where the outcome is mixed, and which next action is justified.
A practical clean-transport evidence checklist
Use this checklist before approving a claim, procurement decision, funding milestone, or public report. It is an evidence-design aid, not medical, legal, or engineering advice.
- Name the exact transport intervention, operating area, start date, and decision owner.
- State whether the claim concerns emissions, ambient concentration, exposure, health risk, climate impact, or several separate outcomes.
- Record a pre-intervention baseline with location, season, traffic, weather, and data-quality context.
- Use both roadside and suitable background evidence where source attribution matters.
- Document traffic volume, speed, congestion, fleet composition, routes, and vehicle activity before and after the change.
- Keep exhaust, brake, tyre, road abrasion, and resuspended-dust evidence separate where material.
- Record the source-apportionment or modelling method, inputs, resolution, validation, and uncertainty.
- Identify sensitive or highly exposed locations without treating one population average as universal.
- Check for construction, fires, industry, weather, seasonal activity, or policy changes that could confound the comparison.
- Separate measured results from modelled estimates and projected future benefits.
- Report adverse, neutral, and uncertain findings alongside improvements.
- Define when the evidence will be refreshed as routes, traffic, vehicles, streets, or background pollution change.
What this evidence cannot prove
The Nature study reports associations at population level. Its case-crossover design helps compare exposure shortly before an event with control periods for the same person, but exposure modelling, outcome coding, spatial resolution, source estimates, and unmeasured factors still limit interpretation.
The study does not provide a universal traffic-to-health conversion factor for a city or project. Its eight-country result should not be copied into a local business case without local baseline, exposure, source, population, and uncertainty evidence.
A lower traffic-sourced PM2.5 estimate also does not prove that every other transition outcome improved. Climate emissions, congestion, road safety, noise, material use, battery impacts, accessibility, and affordability are separate questions with separate boundaries.
The correct conclusion is modest but useful: source-specific evidence can materially change how a total concentration is interpreted. A serious clean-transport claim should make that layer visible.
The circular-systems lesson is to measure what remains
Circular and green-transition projects often focus on the component being replaced. The operating system is wider. When one source declines, another source, constraint, or exposure pathway can become more important.
A source-specific air-quality record keeps that wider system in view. It links the intervention to measured environmental conditions, separates tailpipe and non-exhaust particles, checks where people are exposed, and returns remaining impacts to the next design decision.
That is not an argument against electrification or clean mobility. It is an argument for evidence that is specific enough to improve the next decision instead of merely confirming the previous one.