Bibliographic record
Abstract
There are currently over 3,500 USA/Canadian landfills listed by the EPA/EC and like numbers in Europe that are producing methane-rich landfill gas (LFG). This gas is typically made up of 50-percent methane (CH4), 35-percent carbon dioxide (CO2), and 2 to 25% nitrogen and oxygen (N2 & O2), plus dozens of dilute contaminants. LFG is classified as a renewable fuel, because it is generated via biological decay of municipal solid waste, a constant byproduct of human activity. To date, most LFG has been allowed to escape into the atmosphere. On account of its high CH4 content, LFG may contribute to climate change, as CH4 is one of the most harmful greenhouse gases with 21 times the global warming potential of CO2. Of the landfills that collect LFG, most simply flare it. In the past decade, some landfills have begun to use LFG for electricity generation or for direct combustion as low Btu gas. Very few landfills upgrade LFG to high Btu gas. A patented CO2 WashTM process developed by Acrion Technologies Inc., and licensed to Firm Green Inc. shows promise as an economically and environmentally sustainable process to recover energy and prevent pollution from landfills. The CO2 WashTM has already been proven at lab-scale. It upgrades LFG, which consists of 50% methane (CH4) + 35% carbon dioxide (CO2) + 2 to 25% nitrogen + oxygen (N2+O2), 1 to 2% water vapor, and dozens of contaminants (which total a few hundred to a few thousand parts per million). CH4, which by itself has an energy content of 1,012 British thermal units (Btu) per standard cubic foot (SCF), is the only component in LFG that contributes to its energy content, which is therefore about 400-550 Btu/SCF. Accordingly, raw LFG is usually referred to as medium-Btu gas. To be salable, it is necessary to remove essentially all the components besides CH4, while keeping the vast majority of the revenue producing CH4. This is high-Btu gas, yielding 850 to 1,000 Btu/SCF. The CO2 WashTM process upgrades LFG to about 930 Btu/SCF, and reduces the contaminants to levels that make it salable as a vehicle fuel in the form of compressed natural gas (CNG).
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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 teacher head, 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".