Photopaper as a tool for community-level monitoring of industrially produced hydrogen sulfide and corrosion
Bibliographic record
Abstract
Scientific instrumentation driven by academic, military, and industrial applications tends to be high cost, designed for expert use, and “black boxed”. Community-led citizen science (CLCS) is creating different research instruments with different measurement goals and processes. This paper identifies four design attributes for CLCS tools: affordability, accessibility, builds community efficacy and provides actionable data through validating a community method for monitoring the neurotoxic and corrosive gas Hydrogen Sulfide (H2S). For $1 per sample, the semi-quantitative method provides an affordable and easily interpretable data for communities to compare H2S concentrations and silver corrosion in their home environments to those in a major municipal sewage treatment plant. H2S is a leading cause of workplace injury in the U.S. and commonly found in oil and gas production, sewage treatment plants, and concentrated animal feeding operations (CAFOs). Communities neighboring such sources tend to be socio-economically marginalized with little access to scientific or political resources. Consequently, health risks and material degradation from corrosion are well studied in workplaces while community exposures are under-studied. Existing commercial H2S detection methods are prohibitively expensive for low-income communities and often require the support of professional scientists. This paper describes a simple and inexpensive semi-quantitative H2S measurement method that uses photopaper. Photopaper passively measures H2S as its silver halide layer linearly reacts with H2S between concentrations of 30 ppb to 1000 ppb, discoloring the paper from white to brown. We develop a colorimetric scale for this discoloration for visual estimation of H2S concentration and overall corrosion. The scale is based on comparing silver sulfide (Ag2S) measured by Purafil Corrosion Classification Coupons (CCCs) and H2S concentrations measured with the industry standard tool, a Jerome meter, to silver and sulfur bound to the photopaper as measured with X-Ray Fluorescence (XRF). We conduct our validation studies in a major municipal sewage treatment plant to provide real-world occupational benchmarks for comparison to community results. This community science method is affordable, accessible, designed to build collective efficacy and to create actionable data to flag the need for follow-up research.
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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 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".