Direct High-Precision Radon Quantification for Interpreting High Frequency Greenhouse Gas Measurements

Abstract. We present a protocol to improve confidence in reported radon activity concentrations, facilitating direct site-to-site comparisons and integration with co-located greenhouse gas (GHG) measurements within a network of three independently managed observatories in the UK. Translating spot measurements of atmospheric GHG amount fractions into regional flux estimates (‘top-down’ analysis) is usually performed with atmospheric transport models (ATM), which calculate the sensitivity of regional emissions to changes in observed GHGs at a finite number of locations. However, the uncertainty of regional emissions is closely linked to ATM uncertainties. Radon, emitted naturally from the land surface, can be used as a tracer of atmospheric transport and mixing to independently evaluate the performance of such models. To accomplish this, the radon measurements need to have a comparable precision to the GHGs at the modelled temporal resolution. ANSTO dual-flow-loop two-filter radon detectors provide output every 30 minutes. The measurement precision at this temporal resolution depends on the characterisation and removal of instrumental background, the calibration procedure, and response time correction. Consequently, unless these steps are standardised, measurement precision may differ between sites. Here we describe standardised approaches regarding 1) instrument maintenance, 2) quality control of the raw data stream, 3) determination and removal of the instrumental background, 4) calibration methods and 5) response time correction (by deconvolution). Furthermore, we assign uncertainties for each reported 30-minute radon estimate (assuming these steps have been followed), and validate the final result through comparison of diurnal and sub-diurnal radon characteristics with co-located GHG measurements. While derived for a network of UK observatories, the proposed standardised protocol could be equally applied to two-filter dual-flow-loop radon observations across larger networks, such as the Integrated Carbon Observation System (ICOS) or the Global Atmosphere Watch (GAW) baseline network.