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Kikaj, Dafina, Chung, Edward, Griffiths, Alan D., Chambers, Scott D., Forster, Grant, Wenger, Angelina, Pickers, Penelope, Rennick, Chris, O'Doherty, Simon, Pitt, Joseph, Stanley, Kieran, Young, Dickon, Fleming, Leigh S. 
ORCID: https://orcid.org/0000-0002-3114-8740, Adcock, Karina ORCID: https://orcid.org/0000-0002-8224-5399, Safi, Emmal and Arnold, Tim
(2025)
Direct high-precision radon quantification for interpreting high frequency greenhouse gas measurements.
Atmospheric Measurement Techniques Discussions, 18 (1).
151–175.
ISSN 1867-8610
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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.
| Item Type: | Article |
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| Additional Information: | Code and data availability: The graphical radon data processing software described in Sect. 5.3 is available upon request. The runtime script for the Python-based research package used for this study is available upon request. Software for logging radon detector output (https://doi.org/10.5281/zenodo.14504311, Griffiths, 2024b), for implementing the deconvolution algorithm (https://doi.org/10.5281/zenodo.14503937, Griffiths, 2024c), and for simulating the detector response during calibration cycles (https://doi.org/10.5281/zenodo.14504261, Griffiths, 2024a) is released under open-source licenses and is freely available. The fitting algorithm described in Sect. 3.3 is available in the Supplement. Radon and GHG data from the UK DECC network sites, Heathfield and Tacolneston, are accessible through the Centre for Environmental Data Analysis (CEDA) at https://doi.org/10.5285/bd7164851bcc491b912f9d650fcf7981 (O'Doherty et al., 2024). Radon and GHG data from the Weybourne Atmospheric Observatory are available through CEDA at https://data.ceda.ac.uk/badc/ncas-wao/data/uea-radon-1/20180321_longterm/v1.0 (Forster et al., 2024) and https://data.ceda.ac.uk/badc/ncas-wao/data/ncas-ftir-1/20170801_longterm/v3.0 (Forster, 2024), respectively. Funding information: This research has been supported by the NPL Directors' Fund, National Measurement System Funding, and the NERC – Building a Green Future: GEMMA Greenhouse Gas Emissions Measurement and Modelling Advancement project (grant no. NE/Y001788/1). The ANSTO radon detectors for this work and the Picarro G5310 at HFD were purchased with the UKRI NERC grant “Advanced UK Observing Network For Air Quality, Public Heath and Greenhouse Gas Research” (grant no. NE/R011532/1) in 2018, awarded to the University of Edinburgh, University of Bristol, and University of East Anglia. |
| Faculty \ School: | University of East Anglia Research Groups/Centres > Theme - ClimateUEA Faculty of Science > School of Environmental Sciences Faculty of Science |
| UEA Research Groups: | Faculty of Science > Research Groups > Centre for Ocean and Atmospheric Sciences |
| Depositing User: | LivePure Connector |
| Date Deposited: | 03 Sep 2024 16:33 |
| Last Modified: | 19 Jan 2025 00:59 |
| URI: | https://ueaeprints.uea.ac.uk/id/eprint/96494 |
| DOI: | 10.5194/amt-2024-54 |
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