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Atmospheric Measurement Techniques An interactive open-access journal of the European Geosciences Union
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Volume 9, issue 6 | Copyright
Atmos. Meas. Tech., 9, 2689-2707, 2016
https://doi.org/10.5194/amt-9-2689-2016
© Author(s) 2016. This work is distributed under
the Creative Commons Attribution 3.0 License.

Research article 28 Jun 2016

Research article | 28 Jun 2016

Increasing the accuracy and temporal resolution of two-filter radon–222 measurements by correcting for the instrument response

Alan D. Griffiths, Scott D. Chambers, Alastair G. Williams, and Sylvester Werczynski Alan D. Griffiths et al.
  • Australian Nuclear Science and Technology Organisation, Locked Bag 2001, Kirrawee DC NSW 2232, Australia

Abstract. Dual-flow-loop two-filter radon detectors have a slow time response, which can affect the interpretation of their output when making continuous observations of near-surface atmospheric radon concentrations. While concentrations are routinely reported hourly, a calibrated model of detector performance shows that ∼40% of the signal arrives more than an hour after a radon pulse is delivered. After investigating several possible ways to correct for the detector's slow time response, we show that a Bayesian approach using a Markov chain Monte Carlo sampler is an effective method. After deconvolution, the detector's output is redistributed into the appropriate counting interval and a 10min temporal resolution can be achieved under test conditions when the radon concentration is controlled. In the case of existing archived observations, collected under less ideal conditions, the data can be retrospectively reprocessed at 30min resolution. In one case study, we demonstrate that a deconvolved radon time series was consistent with the following: measurements from a fast-response carbon dioxide monitor; grab samples from an aircraft; and a simple mixing height model. In another case study, during a period of stable nights and days with well-developed convective boundary layers, a bias of 18% in the mean daily minimum radon concentration was eliminated by correcting for the instrument response.

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Surface-based two-filter radon detectors monitor the ambient concentration of atmospheric radon-222, a natural tracer of mixing and transport. They are sensitive, but respond slowly to ambient changes in radon concentration. In this paper, a deconvolution method is used to successfully correct observations for the instrument response. Case studies demonstrate that it is beneficial, sometimes necessary, to account for the detector response, especially when studying near-surface mixing.
Surface-based two-filter radon detectors monitor the ambient concentration of atmospheric...
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