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Record W2997443451 · doi:10.5194/amt-13-2241-2020

Intercomparison study of atmospheric <sup>222</sup> Rn and <sup>222</sup> Rn progeny monitors

2020· article· en· W2997443451 on OpenAlex
Claudia Grossi, Scott Chambers, Olivier Llido, Felix Vogel, Victor Kazan, Alessandro Capuana, Sylvester Werczynski, Roger Curcoll, Marc Delmotte, Arturo Vargas, Josep-Antón Morguí, Ingeborg Levin, Michel Ramonet

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueAtmospheric measurement techniques · 2020
Typearticle
Languageen
FieldHealth Professions
TopicRadioactivity and Radon Measurements
Canadian institutionsEnvironment and Climate Change Canada
Fundersnot available
KeywordsRadonEnvironmental scienceTRACERAerosolAtmospheric sciencesChemistryMeteorologyPhysicsNuclear physics

Abstract

fetched live from OpenAlex

Abstract. The use of the noble gas radon (222Rn) as a tracer for different research studies, for example observation-based estimation of greenhouse gas (GHG) fluxes, has led to the need of high-quality 222Rn activity concentration observations with high spatial and temporal resolution. So far a robust metrology chain for these measurements is not yet available. A portable direct atmospheric radon monitor (ARMON), based on electrostatic collection of 218Po, is now running at Spanish stations. This monitor has not yet been compared with other 222Rn and 222Rn progeny monitors commonly used at atmospheric stations. A 3-month intercomparison campaign of atmospheric 222Rn and 222Rn progeny monitors based on different measurement techniques was realized during the fall and winter of 2016–2017 to evaluate (i) calibration and correction factors between monitors necessary to harmonize the atmospheric radon observations and (ii) the dependence of each monitor's response in relation to the sampling height and meteorological and atmospheric aerosol conditions. Results of this study have shown the following. (i) All monitors were able to reproduce the atmospheric radon variability on a daily basis. (ii) Linear regression fits between the monitors exhibited slopes, representing the correction factors, between 0.62 and 1.17 and offsets ranging between −0.85 and −0.23 Bq m−3 when sampling 2 m above ground level (a.g.l.). Corresponding results at 100 m a.g.l. exhibited slopes of 0.94 and 1.03 with offsets of −0.13 and 0.01 Bq m−3, respectively. (iii) No influence of atmospheric temperature and relative humidity on monitor responses was observed for unsaturated conditions at 100 m a.g.l., whereas slight influences (order of 10−2) of ambient temperature were observed at 2 m a.g.l. (iv) Changes in the ratio between 222Rn progeny and 222Rn monitor responses were observed under very low atmospheric aerosol concentrations. Results also show that the new ARMON could be useful at atmospheric radon monitoring stations with space restrictions or as a mobile reference instrument to calibrate in situ 222Rn progeny monitors and fixed radon monitors. In the near future a long-term comparison study between ARMON, HRM, and ANSTO monitors would be useful to better evaluate (i) the uncertainties of radon measurements in the range of a few hundred millibecquerels per cubic meter to a few becquerels per cubic meter and (ii) the response time correction of the ANSTO monitor for representing fast changes in the ambient radon concentrations.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.003
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.592
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.001
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0020.000
Bibliometrics0.0000.001
Science and technology studies0.0010.000
Scholarly communication0.0000.001
Open science0.0010.001
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.103
GPT teacher head0.351
Teacher spread0.248 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it