Potential interferences in photolytic nitrogen dioxide converters for ambient air monitoring: Evaluation of a prototype
Bibliographic record
Abstract
Mixing ratios of the criteria air contaminant nitrogen dioxide (NO2) are commonly quantified by reduction to nitric oxide (NO) using a photolytic converter followed by NO-O3 chemiluminescence (CL). In this work, the performance of a photolytic NO2 converter prototype originally designed for continuous emission monitoring and emitting light at 395 nm was evaluated. Mixing ratios of NO2 and NOx (= NO + NO2) entering and exiting the converter were monitored by blue diode laser cavity ring-down spectroscopy (CRDS). The NO2 photolysis frequency was determined by measuring the rate of conversion to NO as a function of converter residence time and found to be 4.2 s−1. A maximum 96% conversion of NO2 to NO over a large dynamic range was achieved at a residence time of (1.5 ± 0.3) s, independent of relative humidity. Interferences from odd nitrogen (NOy) species such as peroxyacyl nitrates (PAN; RC(O)O2NO2), alkyl nitrates (AN; RONO2), nitrous acid (HONO), and nitric acid (HNO3) were evaluated by operating the prototype converter outside its optimum operating range (i.e., at higher pressure and longer residence time) for easier quantification of interferences. Four mechanisms that generate artifacts and interferences were identified as follows: direct photolysis, foremost of HONO at a rate constant of 6% that of NO2; thermal decomposition, primarily of PAN; surface promoted photochemistry; and secondary chemistry in the connecting tubing. These interferences are likely present to a certain degree in all photolytic converters currently in use but are rarely evaluated or reported. Recommendations for improved performance of photolytic converters include operating at lower cell pressure and higher flow rates, thermal management that ideally results in a match of photolysis cell temperature with ambient conditions, and minimization of connecting tubing length. When properly implemented, these interferences can be made negligibly small when measuring NO2 in ambient air.Implications: A new near-UV photolytic converter for measurement of the criteria pollutant nitrogen dioxide (NO2) in ambient air by CL was characterized. Four mechanisms that generate interferences were identified and investigated experimentally: direct photolysis of HONO which occurred at a rate constant 6% that of NO2, thermal decomposition of PAN and N2O5, surface promoted chemistry involving HNO3, and secondary chemistry involving NO in the tubing connecting the converter and CL analyzer. These interferences are predicted to occur in all NO2 P-CL systems but can be avoided by appropriate thermal management and operating at high flow rates.
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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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.003 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".