MD-45 · Towson, Baltimore County · modelled from traffic counts

York Road Air

Nobody measures the air on York Road. The nearest regulatory monitor is miles away, and near-road pollution falls off within a few hundred feet — so the official number for this address is an interpolation from somewhere that does not resemble it. This is the other way at it: take every road around Towson, the traffic on it, what the fleet emits, and where the wind is blowing, and model what actually reaches a given doorstep, hour by hour.

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What the model says

Falling off the road

A transect straight across York Road at the marker's latitude. This steep first 200 metres is the whole reason a monitor miles away cannot describe your block.

Hour by hour

Same wind, every hour of a weekday.

Nine years of counts, and forward

Traffic here is flat. Exhaust falls anyway as the fleet turns over — while brake, tyre and road dust do not, and will not for electric cars either.

How this is calculated

Four steps, each of which you can check:

emissions  = AADT x class split x diurnal share x g/vehicle-mile
plume      = Gaussian line source, Briggs urban coefficients
dilution   = f(wind speed, stability class, distance)
breathed   = regional background + traffic increment

Traffic is every MDOT SHA segment within about 6 km of Towson — segments carrying vehicle-kilometres a day, with nine years of counts each. The class split — cars, light trucks, buses, single-unit and combination trucks — is published for 75 of them; for the rest it is imputed from the median split of segments that do report, grouped by road class. Interstates carry about 2.5× the heavy-vehicle share and roughly 19× the tractor-trailer share of a local road, so road class is the variable that matters.

Why heavy vehicles dominate. Diesel trucks and buses are a couple of percent of the traffic and, on a typical arterial hour, around a fifth of the nitrogen oxides. Overnight their share of the fleet roughly triples while total traffic collapses — which is why the model puts the worst air before dawn rather than at rush hour.

Dispersion discretises each road into point sources every 80 m and sums a Gaussian plume from each, using Briggs urban coefficients plus the initial mixing that traffic's own turbulence creates. Stability class comes from hour and wind speed, blended across dawn and dusk rather than switched on the hour. It is the same family of model as EPA's R-LINE, simplified: no street-canyon effects, no terrain, flat ground.

Background matters. The model predicts the increment the roads add. What you breathe is that plus the regional background the whole city sits in, so both are shown separately — the increment is the part that is about your street rather than your region.

Does it produce sane numbers? Taking the busiest York Road segment alone — 36,780 vehicles a day — with the wind blowing straight across it on a calm, stably layered morning, the model gives roughly 52 µg/m³ of nitrogen oxides at 20 m from the kerb, 18 at 50 m and 5 at 100 m. Published near-road measurements put arterial NOₓ increments in the tens of µg/m³ at that distance, decaying 60–80% within the first 100 m, so the magnitude and the shape both land where the literature says they should. That is a consistency check, not a validation — only a sensor is that.

What would falsify this The model makes specific predictions: worst before dawn, strongly dependent on whether you are upwind or downwind rather than on traffic volume alone, and dominated by the Beltway once you are a few hundred metres off York Road. A pair of calibrated sensors on porches would confirm or break all three — here is exactly how, and what it costs. Until that happens this is a hypothesis with arithmetic behind it, not a measurement — AADT is an annual average rather than today's traffic, emission factors are fleet averages rather than this road's fleet, and the ultrafine row is order-of-magnitude at best. Gaussian models are also unreliable below about 1 m/s, where real near-road concentrations are often worst.
Emission factors, grams per vehicle-mile (2024 fleet)
VehicleNOx PM exh.PM non-exh.UFP /mi
Fleet turnover, change per year
PollutantLight duty Heavy duty

Indexed to 2024. Years after 2024 extend the same rates forward, which folds electrification into the trend rather than modelling it separately — so treat the forward end as extrapolation, not forecast.

York Road Air · a chapter of the Gigawatt Ledger · traffic counts from MDOT SHA (2016–2024), wind from NWS station KBWI, dispersion after Briggs urban coefficients.
Modelled, not measured. The model is deliberately legible so it can be argued with.