Formaldehyde and Total VOC (TVOC) Commercial Low-Cost Monitoring Devices: From an Evaluation in Controlled Conditions to a Use Case Application in a Real Building
Bibliographic record
Abstract
Formaldehyde and volatile organic compounds (VOCs) are major indoor pollutants with multiple origins. Standard methods exist to measure them that require analytical expertise and provide, at best, an average value of their concentrations. There is a need to monitor them continuously during periods of several days, weeks, or even months. Recently, portable devices have become available. Two categories of portable devices are considered in this research paper: connected objects for the general public (price <500 €) and monitoring portable devices for professional users (price in the range >500 to 5000 €). The ISO method (ISO 16000-29) describes the standard for VOC detector qualification. It is quite complex and is not well adapted for a first qualitative evaluation of these low-cost devices. In this paper, we present an experimental methodology used to evaluate commercial devices that monitor formaldehyde and/or total volatile organic compounds (TVOC) under controlled conditions (23 °C, 50–65% relative humidity (RH)). We conclude that none of the connected objects dedicated to the general public can provide reliable data in the conditions tested, not even for a qualitative evaluation. For formaldehyde monitoring, we obtained some promising results with a portable device dedicated to professional users. In this paper, we illustrate, with a real test case in an office building, how this device was used for a comparative analysis.
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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 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| 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 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".