Oregon Fleet Turnover and Technology Projections

A fuel standard is enforced on fuel, but it is decided by vehicles. The carbon intensity of what Oregon sells at the pump and the plug depends on how much gasoline, diesel, renewable liquid, gas and electricity the state consumes, and that follows from what is registered and being driven — a stock that changes slowly and mostly by attrition.

So the first question is not what Oregon will buy, but what it will still own. This report answers that: how many vehicles of what technology are on Oregon roads in each year to 2050, how far each is driven, and how efficiently. The fuel-demand model that assesses Clean Fuels Program compliance runs on top of it.

The fleet is treated as a set of overlapping age cohorts. In every simulated year survival curves retire part of the existing stock and new sales enter on top, so the full age distribution is carried forward rather than averaged away — a fifteen-year-old passenger car is driven about half as far as a new one, and burns fuel at an older vintage's rate while doing it. Energy use is then computed on an Activity–Stock–Intensity–Fuel backbone across ten vehicle categories, rebuilt from an earlier California spreadsheet into Python, which is what makes four scenarios to 2050 tractable and reproducible.

The base year is anchored rather than assumed: stock and age structure from Oregon DMV registrations, survival curves from CARB's EMFAC re-fitted to observed Oregon retirements, travel from EMFAC and the EPA MOVES Oregon database, and modeled energy demand validated against the Clean Fuels Program's own 2024 reported consumption before any projection runs. Two defects in the registration data were repaired first — plug-in hybrids miscoded in the DMV's motive-power field, corrected vehicle by vehicle against NHTSA's VIN database, and a pickup segment carrying more old vehicles than the EMFAC curves predicted. Neither is a result; both would have propagated silently through every scenario.

Zero-emission share of new sales in 2050 under each scenario, developed with DEQ to bound the range relevant to the state's rulemaking. Fuel economy and travel-per-vehicle assumptions are common to all four — the scenarios differ only in the technology mix of new sales, so any divergence downstream is attributable to that alone. Transit buses are the exception to the heavy-duty column, reaching 40% BEV even under Business as Usual on existing procurement trends.

Source: Jamhar, Fulton & Murphy (2026), Scenario Definitions.

1. 01

   Turnover sets the timetable, not the sales mandate

   Under ACC2 Delayed every new light-duty vehicle is zero-emission from 2040 and every heavy-duty one from 2045, and ZEVs still reach only 65% of light-duty and 61% of medium- and heavy-duty stock by 2050. Because the fleet also grows, conventional vehicle counts fall more slowly than those shares suggest.

2. 02

   For a decade the scenarios are indistinguishable

   Near-term fleet composition is nearly identical across all four cases despite sharply different sales assumptions, and separates only as turnover works through the 2030s and 2040s. Early compliance data will not tell Oregon which trajectory it is on.

3. 03

   The light-duty fleet is becoming a light-truck fleet

   Light trucks are 54% of light-duty stock in 2025 and pass 70% by 2050 in every scenario. New light trucks average 36 mpg against 49 for cars, so the mix shift pushes against the carbon-intensity target independently of what powers them.

4. 04

   Heavy-duty is mostly a pickup problem

   Heavy-duty pickups are 70% of the medium- and heavy-duty fleet; long-haul combination trucks are 9%. Under ACC2 Delayed the pickup segment alone sheds about 89,000 diesel vehicles by 2050, and diesel falls from 79% to 36% of that fleet.

5. 05

   Hydrogen appears only where batteries struggle

   Fuel cells reach 17% of long-haul ZEV sales by 2050 under ACC2, 18% in heavy-duty pickup and 14% in heavy-duty vocational. Medium-duty delivery and transit buses stay almost entirely battery-electric — the hydrogen case is an energy-density case, not a general one.

These projections are an input, not a conclusion. The next stage applies the Fuel Portfolio Scenario Model — the framework behind the analyses of California's Low Carbon Fuel Standard, the policy the Clean Fuels Program was modeled on — to Oregon, converting the fleet and travel projected here into demand for each fuel, then testing programme compliance, credit-market behaviour and greenhouse gas outcomes scenario by scenario.

Part one was built to be scenario-agnostic so that part two can be read cleanly. Efficiency and travel assumptions are shared across all four cases; only the technology composition of new sales moves. Anything that diverges in the fuel results therefore traces to sales mix and turnover rather than to an assumption quietly changing underneath.