Articles | Volume 9, issue 6
https://doi.org/10.5194/amt-9-2689-2016
© Author(s) 2016. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
https://doi.org/10.5194/amt-9-2689-2016
© Author(s) 2016. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
Increasing the accuracy and temporal resolution of two-filter radon–222 measurements by correcting for the instrument response
Alan D. Griffiths
CORRESPONDING AUTHOR
Australian Nuclear Science and Technology Organisation, Locked Bag
2001, Kirrawee DC NSW 2232, Australia
Scott D. Chambers
Australian Nuclear Science and Technology Organisation, Locked Bag
2001, Kirrawee DC NSW 2232, Australia
Alastair G. Williams
Australian Nuclear Science and Technology Organisation, Locked Bag
2001, Kirrawee DC NSW 2232, Australia
Sylvester Werczynski
Australian Nuclear Science and Technology Organisation, Locked Bag
2001, Kirrawee DC NSW 2232, Australia
Related authors
Caleb Mynard, Emily B. Franklin, Joel Alroe, Karen Westwood, Brandon J. McNabb, Robert Strzepek, Philippe D. Tortell, Steven T. Siems, Antonio Patti, Suzie Molloy, Alan Griffiths, Branka Miljevic, Marc D. Mallet, Ruhi Humphries, and Erin Dunne
Atmos. Chem. Phys., 26, 11583–11604, https://doi.org/10.5194/acp-26-11583-2026, https://doi.org/10.5194/acp-26-11583-2026, 2026
Short summary
Short summary
Marine sulfur gases help form climate-cooling particles, but their controls over the Southern Ocean are unclear. During a summer research voyage we measured these gases and linked them to ocean and atmospheric conditions. Near Antarctica, coastal blooms drove sharp rises in dimethyl sulfide while methanethiol remained low. Over the open ocean, both gases varied together, mainly influenced by ocean mixing and temperature, suggesting models should treat coastal and open ocean regions separately.
Scott D. Chambers, Ute Karstens, Alan D. Griffiths, Stefan Röttger, Arnoud Frumau, Christopher T. Roulston, Peter Sperlich, Felix Vogel, Agnieszka Podstawczyńska, Dafina Kikaj, Maksym Gachkivskyi, Michel Ramonet, Blagoj Mitrevski, Janja Vaupotič, Xuemeng Chen, and Annette Röttger
EGUsphere, https://doi.org/10.5194/egusphere-2025-5042, https://doi.org/10.5194/egusphere-2025-5042, 2025
Short summary
Short summary
The Radon Tracer Method (RTM) is a top-down approach to estimate greenhouse gas emissions. While simple in principle, incorrect use can complicate interpretation of results. Based on observations from a range of contrasting sites, this article reviews the underlying assumptions and key considerations for applying the RTM. It also introduces the concept of coupling RTM analyses with nocturnal stability classification, to reduce uncertainty of fetch estimates and improve interpretation of results.
Dafina Kikaj, Edward Chung, Alan D. Griffiths, Scott D. Chambers, Grant Forster, Angelina Wenger, Penelope Pickers, Chris Rennick, Simon O'Doherty, Joseph Pitt, Kieran Stanley, Dickon Young, Leigh S. Fleming, Karina Adcock, Emmal Safi, and Tim Arnold
Atmos. Meas. Tech., 18, 151–175, https://doi.org/10.5194/amt-18-151-2025, https://doi.org/10.5194/amt-18-151-2025, 2025
Short summary
Short summary
We present a protocol to improve confidence in atmospheric radon measurements, enabling site comparisons and integration with greenhouse gas data. As a natural tracer, radon provides an independent check of transport model performance. This standardized method enhances radon’s use as a metric for model evaluation. Beyond UK observatories, it can support broader networks like ICOS and WMO/GAW, advancing global atmospheric research.
Ruhi S. Humphries, Melita D. Keywood, Jason P. Ward, James Harnwell, Simon P. Alexander, Andrew R. Klekociuk, Keiichiro Hara, Ian M. McRobert, Alain Protat, Joel Alroe, Luke T. Cravigan, Branka Miljevic, Zoran D. Ristovski, Robyn Schofield, Stephen R. Wilson, Connor J. Flynn, Gourihar R. Kulkarni, Gerald G. Mace, Greg M. McFarquhar, Scott D. Chambers, Alastair G. Williams, and Alan D. Griffiths
Atmos. Chem. Phys., 23, 3749–3777, https://doi.org/10.5194/acp-23-3749-2023, https://doi.org/10.5194/acp-23-3749-2023, 2023
Short summary
Short summary
Observations of aerosols in pristine regions are rare but are vital to constraining the natural baseline from which climate simulations are calculated. Here we present recent seasonal observations of aerosols from the Southern Ocean and contrast them with measurements from Antarctica, Australia and regionally relevant voyages. Strong seasonal cycles persist, but striking differences occur at different latitudes. This study highlights the need for more long-term observations in remote regions.
Scott D. Chambers, Alan D. Griffiths, Alastair G. Williams, Ot Sisoutham, Viacheslav Morosh, Stefan Röttger, Florian Mertes, and Annette Röttger
Adv. Geosci., 57, 63–80, https://doi.org/10.5194/adgeo-57-63-2022, https://doi.org/10.5194/adgeo-57-63-2022, 2022
Short summary
Short summary
There is a growing need in health and climate research for high-quality radon observations. A variety of radon monitors, with different uncertainties, operate across global networks. Better compatibility between the measurements is required. Here we describe a novel, portable two-filter radon monitor with a calibration traceable to the International System of Units, and demonstrate the transfer of a traceable calibration from this instrument to a separate monitor under field conditions.
Peter Sperlich, Gordon W. Brailsford, Rowena C. Moss, John McGregor, Ross J. Martin, Sylvia Nichol, Sara Mikaloff-Fletcher, Beata Bukosa, Magda Mandic, C. Ian Schipper, Paul Krummel, and Alan D. Griffiths
Atmos. Meas. Tech., 15, 1631–1656, https://doi.org/10.5194/amt-15-1631-2022, https://doi.org/10.5194/amt-15-1631-2022, 2022
Short summary
Short summary
We tested an in situ analyser for carbon and oxygen isotopes in atmospheric CO2 at Baring Head, New Zealand’s observatory for Southern Ocean baseline air. The analyser was able to resolve regional signals of the terrestrial carbon cycle, although the analysis of small events was limited by analytical uncertainty. Further improvement of the instrument performance would be desirable for the robust analysis of distant signals and to resolve the small variability in Southern Ocean baseline air.
Zhenyi Chen, Robyn Schofield, Melita Keywood, Sam Cleland, Alastair G. Williams, Alan Griffiths, Stephen Wilson, Peter Rayner, and Xiaowen Shu
Atmos. Chem. Phys. Discuss., https://doi.org/10.5194/acp-2022-104, https://doi.org/10.5194/acp-2022-104, 2022
Revised manuscript not accepted
Short summary
Short summary
This study studied the marine boundary layer (MBL) process and aerosol properties in the Southern Ocean using miniMPL, ceilometer and sodar. Compared to the gradient method, the Image Edge Detection Algorithm provides more reliable boundary layer height estimations, especially when a convective MBL with stratification existed. The diurnal characteristic of BLH with the veering of the wind vector was also observed. Under the continental sources, the MBL maintained a well-mixed layer of 0.3 km.
Caleb Mynard, Emily B. Franklin, Joel Alroe, Karen Westwood, Brandon J. McNabb, Robert Strzepek, Philippe D. Tortell, Steven T. Siems, Antonio Patti, Suzie Molloy, Alan Griffiths, Branka Miljevic, Marc D. Mallet, Ruhi Humphries, and Erin Dunne
Atmos. Chem. Phys., 26, 11583–11604, https://doi.org/10.5194/acp-26-11583-2026, https://doi.org/10.5194/acp-26-11583-2026, 2026
Short summary
Short summary
Marine sulfur gases help form climate-cooling particles, but their controls over the Southern Ocean are unclear. During a summer research voyage we measured these gases and linked them to ocean and atmospheric conditions. Near Antarctica, coastal blooms drove sharp rises in dimethyl sulfide while methanethiol remained low. Over the open ocean, both gases varied together, mainly influenced by ocean mixing and temperature, suggesting models should treat coastal and open ocean regions separately.
Scott D. Chambers, Ute Karstens, Alan D. Griffiths, Stefan Röttger, Arnoud Frumau, Christopher T. Roulston, Peter Sperlich, Felix Vogel, Agnieszka Podstawczyńska, Dafina Kikaj, Maksym Gachkivskyi, Michel Ramonet, Blagoj Mitrevski, Janja Vaupotič, Xuemeng Chen, and Annette Röttger
EGUsphere, https://doi.org/10.5194/egusphere-2025-5042, https://doi.org/10.5194/egusphere-2025-5042, 2025
Short summary
Short summary
The Radon Tracer Method (RTM) is a top-down approach to estimate greenhouse gas emissions. While simple in principle, incorrect use can complicate interpretation of results. Based on observations from a range of contrasting sites, this article reviews the underlying assumptions and key considerations for applying the RTM. It also introduces the concept of coupling RTM analyses with nocturnal stability classification, to reduce uncertainty of fetch estimates and improve interpretation of results.
Tahereh Alinejadtabrizi, Yi Huang, Francisco Lang, Steven Siems, Michael Manton, Luis Ackermann, Melita Keywood, Ruhi Humphries, Paul Krummel, Alastair Williams, and Greg Ayers
Atmos. Chem. Phys., 25, 2631–2648, https://doi.org/10.5194/acp-25-2631-2025, https://doi.org/10.5194/acp-25-2631-2025, 2025
Short summary
Short summary
Clouds over the Southern Ocean are crucial to Earth's energy balance, but understanding the factors that control them is complex. Our research examines how weather patterns affect tiny particles called cloud condensation nuclei (CCN), which influence cloud properties. Using data from Kennaook / Cape Grim, we found that winter air from Antarctica brings cleaner conditions with lower CCN, while summer patterns from Australia transport more particles. Precipitation also helps reduce CCN in winter.
Dafina Kikaj, Edward Chung, Alan D. Griffiths, Scott D. Chambers, Grant Forster, Angelina Wenger, Penelope Pickers, Chris Rennick, Simon O'Doherty, Joseph Pitt, Kieran Stanley, Dickon Young, Leigh S. Fleming, Karina Adcock, Emmal Safi, and Tim Arnold
Atmos. Meas. Tech., 18, 151–175, https://doi.org/10.5194/amt-18-151-2025, https://doi.org/10.5194/amt-18-151-2025, 2025
Short summary
Short summary
We present a protocol to improve confidence in atmospheric radon measurements, enabling site comparisons and integration with greenhouse gas data. As a natural tracer, radon provides an independent check of transport model performance. This standardized method enhances radon’s use as a metric for model evaluation. Beyond UK observatories, it can support broader networks like ICOS and WMO/GAW, advancing global atmospheric research.
Claudia Grossi, Daniel Rabago, Scott Chambers, Carlos Sáinz, Roger Curcoll, Peter P. S. Otáhal, Eliška Fialová, Luis Quindos, and Arturo Vargas
Atmos. Meas. Tech., 16, 2655–2672, https://doi.org/10.5194/amt-16-2655-2023, https://doi.org/10.5194/amt-16-2655-2023, 2023
Short summary
Short summary
The automatic and low-maintenance radon flux system Autoflux, completed with environmental soil and atmosphere sensors, has been theoretically and experimentally characterized and calibrated under laboratory conditions to be used as transfer standard for in situ measurements. It will offer for the first time long-term measurements to validate radon flux maps used by the climate and the radiation protection communities for assessing the radon gas emissions in the atmosphere.
Ruhi S. Humphries, Melita D. Keywood, Jason P. Ward, James Harnwell, Simon P. Alexander, Andrew R. Klekociuk, Keiichiro Hara, Ian M. McRobert, Alain Protat, Joel Alroe, Luke T. Cravigan, Branka Miljevic, Zoran D. Ristovski, Robyn Schofield, Stephen R. Wilson, Connor J. Flynn, Gourihar R. Kulkarni, Gerald G. Mace, Greg M. McFarquhar, Scott D. Chambers, Alastair G. Williams, and Alan D. Griffiths
Atmos. Chem. Phys., 23, 3749–3777, https://doi.org/10.5194/acp-23-3749-2023, https://doi.org/10.5194/acp-23-3749-2023, 2023
Short summary
Short summary
Observations of aerosols in pristine regions are rare but are vital to constraining the natural baseline from which climate simulations are calculated. Here we present recent seasonal observations of aerosols from the Southern Ocean and contrast them with measurements from Antarctica, Australia and regionally relevant voyages. Strong seasonal cycles persist, but striking differences occur at different latitudes. This study highlights the need for more long-term observations in remote regions.
Scott D. Chambers, Alan D. Griffiths, Alastair G. Williams, Ot Sisoutham, Viacheslav Morosh, Stefan Röttger, Florian Mertes, and Annette Röttger
Adv. Geosci., 57, 63–80, https://doi.org/10.5194/adgeo-57-63-2022, https://doi.org/10.5194/adgeo-57-63-2022, 2022
Short summary
Short summary
There is a growing need in health and climate research for high-quality radon observations. A variety of radon monitors, with different uncertainties, operate across global networks. Better compatibility between the measurements is required. Here we describe a novel, portable two-filter radon monitor with a calibration traceable to the International System of Units, and demonstrate the transfer of a traceable calibration from this instrument to a separate monitor under field conditions.
Peter Sperlich, Gordon W. Brailsford, Rowena C. Moss, John McGregor, Ross J. Martin, Sylvia Nichol, Sara Mikaloff-Fletcher, Beata Bukosa, Magda Mandic, C. Ian Schipper, Paul Krummel, and Alan D. Griffiths
Atmos. Meas. Tech., 15, 1631–1656, https://doi.org/10.5194/amt-15-1631-2022, https://doi.org/10.5194/amt-15-1631-2022, 2022
Short summary
Short summary
We tested an in situ analyser for carbon and oxygen isotopes in atmospheric CO2 at Baring Head, New Zealand’s observatory for Southern Ocean baseline air. The analyser was able to resolve regional signals of the terrestrial carbon cycle, although the analysis of small events was limited by analytical uncertainty. Further improvement of the instrument performance would be desirable for the robust analysis of distant signals and to resolve the small variability in Southern Ocean baseline air.
Zhenyi Chen, Robyn Schofield, Melita Keywood, Sam Cleland, Alastair G. Williams, Alan Griffiths, Stephen Wilson, Peter Rayner, and Xiaowen Shu
Atmos. Chem. Phys. Discuss., https://doi.org/10.5194/acp-2022-104, https://doi.org/10.5194/acp-2022-104, 2022
Revised manuscript not accepted
Short summary
Short summary
This study studied the marine boundary layer (MBL) process and aerosol properties in the Southern Ocean using miniMPL, ceilometer and sodar. Compared to the gradient method, the Image Edge Detection Algorithm provides more reliable boundary layer height estimations, especially when a convective MBL with stratification existed. The diurnal characteristic of BLH with the veering of the wind vector was also observed. Under the continental sources, the MBL maintained a well-mixed layer of 0.3 km.
Sonya L. Fiddes, Matthew T. Woodhouse, Steve Utembe, Robyn Schofield, Simon P. Alexander, Joel Alroe, Scott D. Chambers, Zhenyi Chen, Luke Cravigan, Erin Dunne, Ruhi S. Humphries, Graham Johnson, Melita D. Keywood, Todd P. Lane, Branka Miljevic, Yuko Omori, Alain Protat, Zoran Ristovski, Paul Selleck, Hilton B. Swan, Hiroshi Tanimoto, Jason P. Ward, and Alastair G. Williams
Atmos. Chem. Phys., 22, 2419–2445, https://doi.org/10.5194/acp-22-2419-2022, https://doi.org/10.5194/acp-22-2419-2022, 2022
Short summary
Short summary
Coral reefs have been found to produce the climatically relevant chemical compound dimethyl sulfide (DMS). It has been suggested that corals can modify their environment via the production of DMS. We use an atmospheric chemistry model to test this theory at a regional scale for the first time. We find that it is unlikely that coral-reef-derived DMS has an influence over local climate, in part due to the proximity to terrestrial and anthropogenic aerosol sources.
Cited articles
Adorf, H.-M., Hook, R. N., and Lucy, L. B.: HST image restoration developments at the ST-ECF, Int. J. Imaging Syst. Technol., 6, 339–349, https://doi.org/10.1002/ima.1850060407, 1995.
Ahnert, K. and Mulansky, M.: Odeint – solving ordinary differential equations in C++, in: AIP Conference Proceedings, AIP Publishing, vol. 1389, 1586–1589, https://doi.org/10.1063/1.3637934, 2011.
Allen, D. J., Rood, R. B., Thompson, A. M., and Hudson, R. D.: Three-dimensional radon 222 calculations using assimilated meteorological data and a convective mixing algorithm, J. Geophys. Res., 101, 6871–6881, https://doi.org/10.1029/95JD03408, 1996.
Alonso, M., Kousaka, Y., Hashimoto, T., and Hashimoto, N.: Penetration of nanometer-sized aerosol particles through wire screen and laminar flow tube, Aerosol Sci. Technol., 27, 471–480, https://doi.org/10.1080/02786829708965487, 1997.
Aubinet, M.: Eddy covariance CO2 flux measurements in nocturnal conditions: an analysis of the problem, Ecol. Appl., 18, 1368–1378, https://doi.org/10.1890/06-1336.1, 2008.
Biraud, S., Ciais, P., Ramonet, M., Simmonds, P., Kazan, V., Monfray, P., O'Doherty, S., Spain, T. G., and Jennings, S. G.: European greenhouse gas emissions estimated from continuous atmospheric measurements and radon 222 at Mace Head, Ireland, J. Geophys. Res., 105, 1351–1366, https://doi.org/10.1029/1999JD900821, 2000.
Brunke, E. G., Labuschagne, C., Parker, B., van der Spuy, D., and Whittlestone, S.: Cape Point GAW Station 222Rn detector: factors affecting sensitivity and accuracy, Atmos. Environ., 36, 2257–2262, https://doi.org/10.1016/S1352-2310(02)00196-6, 2002.
Brunke, E.-G., Labuschagne, C., Parker, B., Scheel, H., and Whittlestone, S.: Baseline air mass selection at Cape Point, South Africa: application of 222Rn and other filter criteria to CO2, Atmos. Environ., 38, 5693–5702, https://doi.org/10.1016/j.atmosenv.2004.04.024, 2004.
Chambers, S., Williams, A. G., Zahorowski, W., Griffiths, A., and Crawford, J.: Separating remote fetch and local mixing influences on vertical radon measurements in the lower atmosphere, Tellus B, 63, 843–859, https://doi.org/10.1111/j.1600-0889.2011.00565.x, 2011.
Chambers, S. D., Hong, S.-B., Williams, A. G., Crawford, J., Griffiths, A. D., and Park, S.-J.: Characterising terrestrial influences on Antarctic air masses using Radon-222 measurements at King George Island, Atmos. Chem. Phys., 14, 9903–9916, https://doi.org/10.5194/acp-14-9903-2014, 2014.
Chambers, S. D., Williams, A. G., Conen, F., Griffiths, A. D., Riemann, S., Steinbacher, M., Krummel, P., Steele, L., van der Schoot, M. V., Galbally, I., Molloy, S. B., and Barnes, J.: Towards a universal “baseline” characterisation of air masses for high- and low-altitude observing stations using radon-222, Aerosol Air Qual. Res., https://doi.org/10.4209/aaqr.2015.06.0391, 2015a.
Chambers, S. D., Williams, A. G., Crawford, J., and Griffiths, A. D.: On the use of radon for quantifying the effects of atmospheric stability on urban emissions, Atmos. Chem. Phys., 15, 1175–1190, https://doi.org/10.5194/acp-15-1175-2015, 2015b.
Cheng, Y. S. and Yeh, H. C.: Theory of a screen-type diffusion battery, J. Aerosol Sci., 11, 313–320, https://doi.org/10.1016/0021-8502(80)90105-6, 1980.
Cheng, Y. S., Keating, J. A., and Kanapilly, G. M.: Theory and calibration of a screen-type diffusion battery, J. Aerosol Sci., 11, 549–556, https://doi.org/10.1016/0021-8502(80)90127-5, 1980.
Collaud Coen, M., Praz, C., Haefele, A., Ruffieux, D., Kaufmann, P., and Calpini, B.: Determination and climatology of the planetary boundary layer height above the Swiss plateau by in situ and remote sensing measurements as well as by the COSMO-2 model, Atmos. Chem. Phys., 14, 13205–13221, https://doi.org/10.5194/acp-14-13205-2014, 2014.
Conen, F. and Robertson, L. B.: Latitudinal distribution of radon-222 flux from continents, Tellus B, 54, 127–133, https://doi.org/10.1034/j.1600-0889.2002.00365.x, 2002.
Conen, F., Neftel, A., Schmid, M., and Lehmann, B. E.: N2O/222Rn – soil flux calibration in the stable nocturnal surface layer, Geophys. Res. Lett., 29, 1025, https://doi.org/10.1029/2001GL013429, 2002.
Considine, D. B., Bergmann, D. J., and Liu, H.: Sensitivity of Global Modeling Initiative chemistry and transport model simulations of radon-222 and lead-210 to input meteorological data, Atmos. Chem. Phys., 5, 3389–3406, https://doi.org/10.5194/acp-5-3389-2005, 2005.
Dankelmann, V., Reineking, A., and Postendörfer, J.: Determination of neutralisation rates of 218Po ions in air, Radiat. Prot. Dosim., 94, 353–357, http://rpd.oxfordjournals.org/content/94/4/353, 2001.
Dempster, A. P., Laird, N. M., and Rubin, D. B.: Maximum likelihood from incomplete data via the EM algorithm, J. R. Stat. Soc. Series B Stat. Methodol., 39, 1–38, http://www.jstor.org/stable/2984875, 1977.
Dey, N., Blanc-Feraud, L., Zimmer, C., Roux, P., Kam, Z., Olivo-Marin, J.-C., and Zerubia, J.: Richardson–Lucy algorithm with total variation regularization for 3D confocal microscope deconvolution, Microsc. Res. Tech., 69, 260–266, https://doi.org/10.1002/jemt.20294, 2006.
Dupé, F. X., Fadili, M. J., and Starck, J. L.: Deconvolution under Poisson noise using exact data fidelity and synthesis or analysis sparsity priors, Stat. Methodol., 9, 4–18, https://doi.org/10.1016/j.stamet.2011.04.008, 2012.
Ehrlich, A. and Wendisch, M.: Reconstruction of high-resolution time series from slow-response broadband terrestrial irradiance measurements by deconvolution, Atmos. Meas. Tech., 8, 3671–3684, https://doi.org/10.5194/amt-8-3671-2015, 2015.
Esch, D. N., Connors, A., Karovska, M., and van Dyk, D. A.: An image restoration technique with error estimates, Astrophys. J., 610, 1213–1227, https://doi.org/10.1086/421761, 2004.
Foreman-Mackey, D., Hogg, D. W., Lang, D., and Goodman, J.: emcee: The MCMC Hammer, Publ. Astron. Soc. Pac., 125, 306–312, https://doi.org/10.1086/670067, 2013.
Frank, G., Steinkopff, T., and Salvamoser, J.: Low Level Measurement of 222Rn in the Atmosphere in the Frame of the Global Atmospheric Watch Programme, in: Sources and Measurements of Radon and Radon Progeny Applied to Climate and Air Quality Studies, IAEA Proceedings Series, p. 105, IAEA, Vienna, 2012.
Frey, G., Hopke, P. K., and Stukel, J. J.: Effects of trace gases and water vapor on the diffusion coefficient of polonium-218, Science, 211, 480–481, https://doi.org/10.1126/science.211.4481.480, 1981.
Gäggeler, H., Jost, D., Baltensperger, U., Schwikowski, M., and Seibert, P.: Radon and thoron decay product and 210Pb measurements at Jungfraujoch, Switzerland, Atmos. Environ., 29, 607–616, https://doi.org/10.1016/1352-2310(94)00195-Q, 1995.
Gelman, A., Carlin, J. B., Stern, H. S., Dunson, D. B., Vehtari, A., and Rubin, D. B.: Bayesian data analysis, vol. 2, Chapman and Hall, 2013.
Goodman, J. and Weare, J.: Ensemble samplers with affine invariance, Comm. App. Math. Comp. Sci., 5, 65–80, https://doi.org/10.2140/camcos.2010.5.65, 2010.
Griffiths, A. D., Zahorowski, W., Element, A., and Werczynski, S.: A map of radon flux at the Australian land surface, Atmos. Chem. Phys., 10, 8969–8982, https://doi.org/10.5194/acp-10-8969-2010, 2010.
Griffiths, A. D., Parkes, S. D., Chambers, S. D., McCabe, M. F., and Williams, A. G.: Improved mixing height monitoring through a combination of lidar and radon measurements, Atmos. Meas. Tech., 6, 207–218, https://doi.org/10.5194/amt-6-207-2013, 2013.
Griffiths, A. D., Conen, F., Weingartner, E., Zimmermann, L., Chambers, S. D., Williams, A. G., and Steinbacher, M.: Surface-to-mountaintop transport characterised by radon observations at the Jungfraujoch, Atmos. Chem. Phys., 14, 12763–12779, https://doi.org/10.5194/acp-14-12763-2014, 2014.
Grossi, C., Vargas, A., Camacho, A., López-Coto, I., Bolívar, J., Xia, Y., and Conen, F.: Inter-comparison of different direct and indirect methods to determine radon flux from soil, Radiat. Meas., 46, 112–118, 2011.
Grossi, C., Arnold, D., Adame, J., López-Coto, I., Bolívar, J., de la Morena, B., and Vargas, A.: Atmospheric 222Rn concentration and source term at El Arenosillo 100 m meteorological tower in southwest Spain, Radiat. Meas., 47, 149–162, https://doi.org/10.1016/j.radmeas.2011.11.006, 2012.
Guedalia, D., Lopez, A., Fontan, J., and Birot, A.: Aircraft measurements of Rn-222, Aitken nuclei and small ions up to 6 km, J. Appl. Meteorol., 11, 357–365, https://doi.org/10.1175/1520-0450(1972)011<0357:AMORAN>2.0.CO;2, 1972.
Heim, M., Mullins, B. J., Wild, M., Meyer, J., and Kasper, G.: Filtration Efficiency of Aerosol Particles Below 20 Nanometers, Aerosol Sci. Technol., 39, 782–789, https://doi.org/10.1080/02786820500227373, 2005.
Heim, M., Attoui, M., and Kasper, G.: The efficiency of diffusional particle collection onto wire grids in the mobility equivalent size range of 1.2–8 nm, J. Aerosol Sci., 41, 207–222, https://doi.org/10.1016/j.jaerosci.2009.10.002, 2010.
Hoffman, M. D. and Gelman, A.: The no-U-turn sampler: Adaptively setting path lengths in Hamiltonian Monte Carlo, J. Mach. Learn. Res., 15, 1593–1623, http://jmlr.org/papers/v15/hoffman14a.html, 2014.
Holtslag, A. and Boville, B.: Local versus nonlocal boundary-layer diffusion in a global climate model, J. Clim., 6, 1825–1842, https://doi.org/10.1175/1520-0442(1993)006<1825:LVNBLD>2.0.CO;2, 1993.
Ichitsubo, H., Hashimoto, T., Alonso, M., and Kousaka, Y.: Penetration of ultrafine particles and ion clusters through wire screens, Aerosol Sci. Technol., 24, 119–127, https://doi.org/10.1080/02786829608965357, 1996.
Jacob, D. J. and Prather, M. J.: Radon-222 as a test of convective transport in a general circulation model, Tellus B, 42, 118–134, https://doi.org/10.1034/j.1600-0889.1990.00012.x, 1990.
Jasche, J. and Wandelt, B. D.: Bayesian inference from photometric redshift surveys, Mon. Not. R. Astron. Soc., 425, 1042–1056, https://doi.org/10.1111/j.1365-2966.2012.21423.x, 2012.
Jonassen, N. and McLaughlin, J. P.: On the recoil of RaB from membrane filters, J. Aerosol Sci., 7, 141–149, https://doi.org/10.1016/0021-8502(76)90070-7, 1976.
Karstens, U., Schwingshackl, C., Schmithüsen, D., and Levin, I.: A process-based 222radon flux map for Europe and its comparison to long-term observations, Atmos. Chem. Phys., 15, 12845–12865, https://doi.org/10.5194/acp-15-12845-2015, 2015.
Kempen, V. and Vliet, V.: The influence of the regularization parameter and the first estimate on the performance of Tikhonov regularized non-linear image restoration algorithms, J. Microsc., 198, 63–75, https://doi.org/10.1046/j.1365-2818.2000.00671.x, 2000.
Knutson, E. and George, A.: Measurements of 214Pb loss by recoil from decay of 218Po collected on a wire screen, Abstracts of the 1994 European Aerosol Conference, 25, Supplement 1, 71–72, https://doi.org/10.1016/0021-8502(94)90266-6, 1994.
Kuzyakov, Y. and Gavrichkova, O.: REVIEW: Time lag between photosynthesis and carbon dioxide efflux from soil: a review of mechanisms and controls, Glob. Chang. Biol., 16, 3386–3406, https://doi.org/10.1111/j.1365-2486.2010.02179.x, 2010.
Laasmaa, M., Vendelin, M., and Peterson, P.: Application of regularized Richardson–Lucy algorithm for deconvolution of confocal microscopy images, J. Microsc., 243, 124–140, https://doi.org/10.1111/j.1365-2818.2011.03486.x, 2011.
Levin, I., Born, M., Cuntz, M., Langendörfer, U., Mantsch, S., Naegler, T., Schmidt, M., Varlagin, A., Verclas, S., and Wagenbach, D.: Observations of atmospheric variability and soil exhalation rate of radon-222 at a Russian forest site – Technical approach and deployment for boundary layer studies, Tellus B, 54, 462–475, https://doi.org/10.1034/j.1600-0889.2002.01346.x, 2002.
Lucy, L. B.: An iterative technique for the rectification of observed distributions, Astron. J., 79, 745, https://doi.org/10.1086/111605, 1974.
MacKay, D. J.: Information theory, inference, and learning algorithms, Cambridge University Press, 7th Edn., available at: http://www.inference.phy.cam.ac.uk/mackay/itila/, 2003.
Mahrt, L.: Computing turbulent fluxes near the surface: Needed improvements, Agric. For. Meteorol., 150, 501–509, https://doi.org/10.1016/j.agrformet.2010.01.015, 2010.
Martin, P., Tims, S., Ryan, B., and Bollhöfer, A.: A radon and meteorological measurement network for the Alligator Rivers Region, Australia, J. Environ. Radioact., 76, 35–49, https://doi.org/10.1016/j.jenvrad.2004.03.017, 2004.
Massman, W. J.: A simple method for estimating frequency response corrections for eddy covariance systems, Agric. For. Meteorol., 104, 185–198, https://doi.org/10.1016/S0168-1923(00)00164-7, 2000.
McCarthy, J.: A method for correcting airborne temperature data for sensor response time, J. Appl. Meteorol., 12, 211–214, https://doi.org/10.1175/1520-0450(1973)012<0211:AMFCAT>2.0.CO;2, 1973.
McLaughlin, J. P. and O'Byrne, F. D.: The role of daughter product plateout in passive radon detection, Radiat. Prot. Dosim., 7, 115–119, http://rpd.oxfordjournals.org/content/7/1-4/115, 1984.
Moore, C.: Frequency response corrections for eddy correlation systems, Boundary-Layer Meteorol., 37, 17–35, https://doi.org/10.1007/BF00122754, 1986.
Nazaroff, W. W., Kong, D., and Gadgil, A. J.: Numerical investigations of the deposition of unattached 218Po and 212Pb from natural convection enclosure flow, J. Aerosol Sci., 23, 339–352, https://doi.org/10.1016/0021-8502(92)90003-E, 1992.
Patil, A., Huard, D., and Fonnesbeck, C. J.: PyMC: Bayesian stochastic modelling in Python, J. Stat. Softw., 35, 1–81, https://doi.org/10.18637/jss.v035.i04, 2010.
Porstendörfer, J.: Physical parameters and dose factors of the radon and thoron decay products, Radiat. Prot. Dosim., 94, 365–373, https://doi.org/10.1093/oxfordjournals.rpd.a006512, 2001.
Powell, M. J. D.: An efficient method for finding the minimum of a function of several variables without calculating derivatives, Comput. J., 7, 155–162, https://doi.org/10.1093/comjnl/7.2.155, 1964.
Press, W. H., Teukolsky, S. A., Vetterling, W. T., and Flannery, B. P.: Numerical recipes: The art of scientific computing, Cambridge University Press, 3rd Edn., 2007.
Richardson, W. H.: Bayesian-based iterative method of image restoration, J. Opt. Soc. Am., 62, 55–59, https://doi.org/10.1364/josa.62.000055, 1972.
Rudin, L. I., Osher, S., and Fatemi, E.: Nonlinear total variation based noise removal algorithms, Physica D, 60, 259–268, https://doi.org/10.1016/0167-2789(92)90242-F, 1992.
Scheibel, H. G. and Porstendörfer, J.: Penetration measurements for tube and screen-type diffusion batteries in the ultrafine particle size range, J. Aerosol Sci., 15, 673–682, https://doi.org/10.1016/0021-8502(84)90005-3, 1984.
Schmithüsen, D., Chambers, S., Fischer, B., Gilge, S., Hatakka, J., Kazan, V., Neubert, R., Paatero, J., Ramonet, M., Schlosser, C., Schmid, S., Vermeulen, A., and Levin, I.: A European-wide 222Radon and 222Radon progeny comparison study, Atmos. Meas. Tech. Discuss., submitted, 2016.
Shin, W. G., Mulholland, G. W., Kim, S. C., and Pui, D. Y. H.: Experimental study of filtration efficiency of nanoparticles below 20 nm at elevated temperatures, J. Aerosol Sci., 39, 488–499, https://doi.org/10.1016/j.jaerosci.2008.01.006, 2008.
Slemr, F., Brunke, E.-G., Whittlestone, S., Zahorowski, W., Ebinghaus, R., Kock, H. H., and Labuschagne, C.: 222Rn-calibrated mercury fluxes from terrestrial surface of southern Africa, Atmos. Chem. Phys., 13, 6421–6428, https://doi.org/10.5194/acp-13-6421-2013, 2013.
Solomon, S. B. and Ren, T.: Counting efficiencies for alpha particles emitted from wire screens, Aerosol Sci. Technol., 17, 69–83, https://doi.org/10.1080/02786829208959561, 1992.
Su, Y. F., Newton, G. J., Cheng, Y. S., and Yeh, H. C.: Experimental measurements of the diffusion coefficients and calculated sizes of Pb-212 particles, J. Aerosol Sci., 19, 767–770, https://doi.org/10.1016/0021-8502(88)90011-0, 1988.
Thomas, D., Mouret, G., Cadavid-Rodriguez, M. C., Chazelet, S., and Bémer, D.: An improved model for the penetration of charged and neutral aerosols in the 4 to 80 nm range through stainless steel and dielectric meshes, J. Aerosol Sci., 57, 32–44, https://doi.org/10.1016/j.jaerosci.2012.10.007, 2013.
Thomas, J. W. and Leclare, P. C.: A study of the two-filter method for radon-222, Health Phys., 18, 113–122, https://doi.org/10.1097/00004032-197002000-00002, 1970.
van der Laan, S., van der Laan-Luijkx, I. T., Zimmermann, L., Conen, F., and Leuenberger, M.: Net CO2 surface emissions at Bern, Switzerland inferred from ambient observations of CO2, δ(O2/N2), and 222Rn using a customized radon tracer inversion, J. Geophys. Res.-Atmos., 119, 1580–1591, https://doi.org/10.1002/2013JD020307, 2014.
Vargas, A., Arnold, D., Adame, J. A., Grossi, C., Hernández-Ceballos, M. A., and Bolivar, J. P.: Analysis of the vertical radon structure at the Spanish “El Arenosillo” tower station, J. Environ. Radioact., 139, 1–17, https://doi.org/10.1016/j.jenvrad.2014.09.018, 2015.
Vinuesa, J.-F., Basu, S., and Galmarini, S.: The diurnal evolution of 222Rn and its progeny in the atmospheric boundary layer during the Wangara experiment, Atmos. Chem. Phys., 7, 5003–5019, https://doi.org/10.5194/acp-7-5003-2007, 2007.
Vogel, F. R., Thiruchittampalam, B., Theloke, J., Kretschmer, R., Gerbig, C., Hammer, S., and Levin, I.: Can we evaluate a fine-grained emission model using high-resolution atmospheric transport modelling and regional fossil fuel CO2 observations?, Tellus B, 65, https://doi.org/10.3402/tellusb.v65i0.18681, 2013.
Wada, A., Murayama, S., Kondo, H., Matsueda, H., Sawa, Y., and Tsuboi, K.: Development of a compact and sensitive electrostatic radon-222 measuring system for use in atmospheric observation, J. Meteorol. Soc. Jpn. Ser. II, 88, 123–134, https://doi.org/10.2151/jmsj.2010-202, 2010.
Wada, A., Matsueda, H., Murayama, S., Taguchi, S., Kamada, A., Nosaka, M., Tsuboi, K., and Sawa, Y.: Evaluation of anthropogenic emissions of carbon monoxide in East Asia derived from the observations of atmospheric radon-222 over the western North Pacific, Atmos. Chem. Phys., 12, 12119–12132, https://doi.org/10.5194/acp-12-12119-2012, 2012.
Whittlestone, S. and Zahorowski, W.: Baseline radon detectors for shipboard use: development and deployment in the First Aerosol Characterization Experiment (ACE 1), J. Geophys. Res., 103, 16743–16751, https://doi.org/10.1029/98JD00687, 1998.
Whittlestone, S., Zahorowski, W., and Wasiolek, P.: High sensitivity two filter radon/thoron detectors with a wire or nylon screen as a second filter, ANSTO E Report E718, ANSTO, available at: http://apo.ansto.gov.au/dspace/bitstream/10238/376/1/ANSTO-E-718.pdf, 1994.
Williams, A. G. and Chambers, S. D.: A history of radon measurements at Cape Grim, Baseline Atmospheric Program (Australia) 2011–2013, 16 pp., 2016.
Williams, A. G., Zahorowski, W., Chambers, S., Griffiths, A., Hacker, J. M., Element, A., and Werczynski, S.: The vertical distribution of radon in clear and cloudy daytime terrestrial boundary layers, J. Atmos. Sci., 68, 155–174, https://doi.org/10.1175/2010JAS3576.1, 2011.
Williams, A. G., Chambers, S., and Griffiths, A.: Bulk mixing and decoupling of the nocturnal stable boundary layer characterized using a ubiquitous natural tracer, Boundary-Lay. Meteorol., 149, 381–402, https://doi.org/10.1007/s10546-013-9849-3, 2013.
Winderlich, J., Chen, H., Gerbig, C., Seifert, T., Kolle, O., Lavric, J. V., Kaiser, C., Höfer, A., and Heimann, M.: Continuous low-maintenance CO2/CH4/H2O measurements at the Zotino Tall Tower Observatory (ZOTTO) in Central Siberia, Atmos. Meas. Tech., 3, 1113–1128, https://doi.org/10.5194/amt-3-1113-2010, 2010.
Xia, Y., Sartorius, H., Schlosser, C., Stöhlker, U., Conen, F., and Zahorowski, W.: Comparison of one- and two-filter detectors for atmospheric 222Rn measurements under various meteorological conditions, Atmos. Meas. Tech., 3, 723–731, https://doi.org/10.5194/amt-3-723-2010, 2010.
Xia, Y., Conen, F., and Alewell, C.: Total bacterial number concentration in free tropospheric air above the Alps, Aerobiologia, 29, 153–159, https://doi.org/10.1007/s10453-012-9259-x, 2013.
Zahorowski, W. and Whittlestone, S.: A fast portable emanometer for field measurement of radon and thoron flux, Radiat. Prot. Dosim., 67, 109–120, 1996.
Zahorowski, W., Chambers, S., and Henderson-Sellers, A.: Ground based radon-222 observations and their application to atmospheric studies, J. Environ. Radioact., 76, 3–33, https://doi.org/10.1016/j.jenvrad.2004.03.033, 2004.
Zahorowski, W., Griffiths, A. D., Chambers, S. D., Williams, A. G., Law, R. M., Crawford, J., and Werczynski, S.: Constraining annual and seasonal radon-222 flux density from the Southern Ocean using radon-222 concentrations in the boundary layer at Cape Grim, Tellus B, 65, https://doi.org/10.3402/tellusb.v65i0.19622, 2013.
Zhang, H., Chen, B., Zhuo, W., and Zhao, C.: Measurements of the size distribution of unattached radon progeny by using the imaging plate, Radiat. Meas., 62, 41–44, https://doi.org/10.1016/j.radmeas.2014.01.011, 2014.
Zhang, K., Wan, H., Zhang, M., and Wang, B.: Evaluation of the atmospheric transport in a GCM using radon measurements: sensitivity to cumulus convection parameterization, Atmos. Chem. Phys., 8, 2811–2832, https://doi.org/10.5194/acp-8-2811-2008, 2008.
Zhang, K., Feichter, J., Kazil, J., Wan, H., Zhuo, W., Griffiths, A. D., Sartorius, H., Zahorowski, W., Ramonet, M., Schmidt, M., Yver, C., Neubert, R. E. M., and Brunke, E.-G.: Radon activity in the lower troposphere and its impact on ionization rate: a global estimate using different radon emissions, Atmos. Chem. Phys., 11, 7817–7838, https://doi.org/10.5194/acp-11-7817-2011, 2011.
Short summary
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...