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Dual-flow-loop two-filter radon detectors have a slow time response, whichcan affect the interpretation of their output when making continuousobservations of near-surface atmospheric radon concentrations. Whileconcentrations are routinely reported hourly, a calibrated model of detectorperformance shows that ∼ 40 % of the signal arrives more than anhour after a radon pulse is delivered. After investigating several possibleways to correct for the detector's slow time response, we show that aBayesian approach using a Markov chain Monte Carlo sampler is an effectivemethod. After deconvolution, the detector's output is redistributed into theappropriate counting interval and a 10 min temporal resolution can beachieved under test conditions when the radon concentration is controlled. Inthe case of existing archived observations, collected under less idealconditions, the data can be retrospectively reprocessed at 30 minresolution. In one case study, we demonstrate that a deconvolved radon timeseries was consistent with the following: measurements from a fast-responsecarbon dioxide monitor; grab samples from an aircraft; and a simple mixingheight model. In another case study, during a period of stable nights anddays with well-developed convective boundary layers, a bias of 18 % inthe mean daily minimum radon concentration was eliminated by correcting forthe instrument response

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