Multijurisdictional Status Review of Low Carbon Fuel Standards, 2010–2020 Q2: California, Oregon, and British Columbia
Bibliographic record
Abstract
California and British Columbia transportation fuel carbon intensity (CI) standards have been in effect since 2011, and Oregon’s since 2016. Total transport energy consumption under the programs was over 23 billion gasoline gallon equivalents (gge) in 2019.By 2019, the transport energy share from lower-carbon alternative fuels rose under each program to about 11%, 8%, and 7% in California, Oregon, and British Columbia, respectively.Each program met its CI targets and accumulated a bank of credits, which represent greenhouse gas (GHG) emission savings beyond the annual target. Credits cover program deficits assessed for emissions above target levels and can be applied towards future compliance. California and British Columbia drew down their credit banks each year since 2017; Oregon’s credit bank grew since the 2016 program start.Program credit prices in 2020 averaged $200/metric ton (MT), $132/MT, and $192/MT (all $USD) in California, Oregon, and British Columbia, respectively.In California, growth of cost-effective diesel substitutes led to over-compliance with the diesel pool standard (a 25% CI reduction for California in 2020), more than offsetting under-compliance in the gasoline pool (a 3% CI reduction there). The same is true in Oregon and British Columbia to a lesser extent.Renewable diesel (RD) generated a notable share of compliance credits in each jurisdiction, despite zero or near-zero volumes when the programs began. In 2019, RD accounted for more than 16% by volume of the liquid diesel pool in California and approximately 30% of alternative fuel energy and credits in British Columbia. RD was first credited in Oregon in 2019.Biomass-based diesel from used cooking oil grew rapidly; 2019 consumption increased by at least 70% over previous year in all three programs.Low-CI rated electricity (i.e., below the state grid average) accounted for approximately 4% of all credits in California beginning in 2019, after indirect accounting mechanisms that avoid the need for physical traceability became available. Oregon expanded its low-CI value electricity options in 2021 in a similar fashion to California.California’s is the only program to track and penalize increasing CI of petroleum fuels. Additional deficits accrued in 2020, totaling 192,000 – 2.6% of the total – through Q2.All three programs continue to adopt amendments, including extending targets and program durations (20% CI reduction by 2030 for all); opt-in credits for alternative jet fuel (California and Oregon); use of advanced crediting for electric vehicle (EV) charging (California and Oregon); an EV rebate program funded by residential charging credit revenue (California); infrastructure capacity crediting for zero emission vehicle (ZEV) fueling (California); third-party verification (California and Oregon), and carbon capture and sequestration protocol (California).o Washington state passed legislation adopting a Clean Fuel Standard to take effect in 2023.An online visualization tool and data repository, available athttps://asmith.ucdavis.edu/data/LCFS, includes much of the data used in this report.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.006 | 0.015 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.012 | 0.015 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.015 | 0.003 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".