Updating the U.S. Life Cycle GHG Petroleum Baseline to 2014 with Projections to 2040 Using Open-Source Engineering-Based Models
Bibliographic record
Abstract
Abstract The National Energy Technology Laboratory produced a well-to-wheels (WTW) life cycle greenhouse gas analysis of petroleum-based fuels consumed in the U.S. in 2005, known as the NETL 2005 Petroleum Baseline. This study uses a set of engineering-based, open-source models combined with publicly available data to calculate baseline results for 2014. An increase between the 2005 baseline and the 2014 results presented here (e.g., 92.4 vs 96.2 g CO2e/MJ gasoline, + 4.1%) are due to changes both in modeling platform and in the U.S. petroleum sector. An updated result for 2005 was calculated to minimize the effect of the change in modeling platform, and emissions for gasoline in 2014 were about 2% lower than in 2005 (98.1 vs 96.2 g CO2e/MJ gasoline). The same methods were utilized to forecast emissions from fuels out to 2040, indicating maximum changes from the 2014 gasoline result between +2.1% and −1.4%. The changing baseline values lead to potential compliance challenges with frameworks such as the Energy Independence and Security Act (EISA) Section 526, which states that Federal agencies should not purchase alternative fuels unless their life cycle GHG emissions are less than those of conventionally produced, petroleum-derived fuels.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.002 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".