Development of a Sub-ppb Resolution Methane Sensor Using a GaSb-Based DFB Diode Laser near 3270 nm for Fugitive Emission Measurement
Bibliographic record
Abstract
A challenge for mobile measurement of fugitive methane emissions is the availability of portable sensors that feature high sensitivity and fast response times, simultaneously. A methane gas sensor to measure fugitive emissions was developed using a continuous-wave, thermoelectrically cooled, GaSb-based distributed feedback diode laser emitting at a wavelength of 3.27 μm to probe methane in its strong ν 3 vibrational band. Direct absorption spectra (DAS) as well as wavelength-modulated spectra (WMS) of pressure-broadened R(3) manifold lines of methane were recorded through a custom-developed open-path multipass cell with an effective optical path length of 6.8 m. A novel metrological approach was taken to characterize the sensor response in terms of the linearity of different WMS metrics, namely, the peak-to-peak amplitude of the X 2 f component and the peak and/or the integrated area of the background-subtracted quadrature signal (i.e., Q (2 f – 2 f 0 )) and the background-subtracted 1 f -normalized quadrature signal (i.e., Q (2 f /1 f – 2 f 0 /1 f 0 )). Comparison with calibration gas concentrations spanning 1.5 to 40 ppm v indicated that the latter WMS metric showed the most linear response, while fitting DAS provides a traceable reference. In the WMS mode, a sensitivity better than 1 ppb v was achieved at a 1 s integration time. The sensitivity and response time are well-suited to measure enhancements in ambient methane levels caused by fugitive emissions.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".