Quantitative Analysis of Volatile Methylsiloxanes in Waste-to-Energy Landfill Biogases Using Direct APCI-MS/MS
Bibliographic record
Abstract
Landfill-biogas utilization is a win-win solution as it creates sources of renewable energy and revenue while diminishing greenhouse gas emissions. However, the combustion of a siloxane-containing biogas produces abrasive microcrystalline silica that causes severe and expensive damages to power generation equipment. Hence, the importance of siloxane analysis of the biogas has increased with the growth of the waste-to-energy market. We have investigated an improved method for the analysis of octamethylcyclotetrasiloxane (D4) and decamethylcyclopentasiloxane (D5) in biogas using deuterated hexamethyldisiloxane (HMDS-d(18)) as an internal standard with direct atmospheric pressure chemical ionization/tandem mass spectrometry (APCI-MS/MS). The use of HMDS-d(18) as a single internal standard provided effective signal compensation for both D4 and D5 in biogas and improved the sensitivity and reliability for the direct APCI-MS/MS quantification of these compounds in biogas. Low detection limits ( approximately 2 microg/m(3)) were achieved. The method was successfully applied for the determination of D4 and D5 contents in various samples of biogas recovered for electrical power generation from a landfill site in Montreal. Concentrations measured for D4 and D5 were in the ranges of 131-1275 and 250-6226 microg/m(3), respectively. Among the various landfill zones sampled, a clear trend of decreasing D4 and D5 concentrations was observed for older landfill materials.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 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 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".