Simulation of radon-222 with the GEOS-Chem global model: emissions, seasonality, and convective transport

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dc.contributor.authorZhang, Ben_AU
dc.contributor.authorLiu, HYen_AU
dc.contributor.authorCrawford, JHen_AU
dc.contributor.authorChen, Gen_AU
dc.contributor.authorFairlie, TDen_AU
dc.contributor.authorChambers, SDen_AU
dc.contributor.authorKang, CHen_AU
dc.contributor.authorWilliams, AGen_AU
dc.contributor.authorZhang, Ken_AU
dc.contributor.authorConsidine, DBen_AU
dc.contributor.authorSulprizio, MPen_AU
dc.contributor.authorYantosca, RMen_AU
dc.date.accessioned2022-06-02T20:14:42Zen_AU
dc.date.available2022-06-02T20:14:42Zen_AU
dc.date.issued2021-02-10en_AU
dc.date.statistics2022-05-12en_AU
dc.descriptionPublished by Copernicus Publications on behalf of the European Geosciences Union. This work is distributed under the Creative Commons Attribution 4.0 License.en_AU
dc.description.abstractRadon-222 (222Rn) is a short-lived radioactive gas naturally emitted from land surfaces and has long been used to assess convective transport in atmospheric models. In this study, we simulate 222Rn using the GEOS-Chem chemical transport model to improve our understanding of 222Rn emissions and surface concentration seasonality and characterize convective transport associated with two Goddard Earth Observing System (GEOS) meteorological products, the Modern-Era Retrospective analysis for Research and Applications (MERRA) and GEOS Forward Processing (GEOS-FP). We evaluate four global 222Rn emission scenarios by comparing model results with observations at 51 surface sites. The default emission scenario in GEOS-Chem yields a moderate agreement with surface observations globally (68.9 % of data within a factor of 2) and a large underestimate of winter surface 222Rn concentrations at Northern Hemisphere midlatitudes and high latitudes due to an oversimplified formulation of 222Rn emission fluxes (1 atom cm−2 s−1 over land with a reduction by a factor of 3 under freezing conditions). We compose a new global 222Rn emission scenario based on Zhang et al. (2011) and demonstrate its potential to improve simulated surface 222Rn concentrations and seasonality. The regional components of this scenario include spatially and temporally varying emission fluxes derived from previous measurements of soil radium content and soil exhalation models, which are key factors in determining 222Rn emission flux rates. However, large model underestimates of surface 222Rn concentrations still exist in Asia, suggesting unusually high regional 222Rn emissions. We therefore propose a conservative upscaling factor of 1.2 for 222Rn emission fluxes in China, which was also constrained by observed deposition fluxes of 210Pb (a progeny of 222Rn). With this modification, the model shows better agreement with observations in Europe and North America (> 80 % of data within a factor of 2) and reasonable agreement in Asia (close to 70 %). Further constraints on 222Rn emissions would require additional concentration and emission flux observations in the central United States, Canada, Africa, and Asia. We also compare and assess convective transport in model simulations driven by MERRA and GEOS-FP using observed 222Rn vertical profiles in northern midlatitude summer and from three short-term airborne campaigns. While simulations with both GEOS products are able to capture the observed vertical gradient of 222Rn concentrations in the lower troposphere (0–4 km), neither correctly represents the level of convective detrainment, resulting in biases in the middle and upper troposphere. Compared with GEOS-FP, MERRA leads to stronger convective transport of 222Rn, which is partially compensated for by its weaker large-scale vertical advection, resulting in similar global vertical distributions of 222Rn concentrations between the two simulations. This has important implications for using chemical transport models to interpret the transport of other trace species when these GEOS products are used as driving meteorology. © Author(s) 2021.en_AU
dc.description.sponsorshipThis research has been supported by the NASA Atmospheric Composition Campaign Data Analysis and Modeling program (ACCDAM) managed by Hal Maring (grant no. NNX14AR07G).en_AU
dc.identifier.citationZhang, B., Liu, H., Crawford, J. H., Chen, G., Fairlie, T. D., Chambers, S., Kang, C.-H., Williams, A. G., Zhang, K., Considine, D. B., Sulprizio, M. P., & Yantosca, R. M. (2021). Simulation of radon-222 with the GEOS-Chem global model: emissions, seasonality, and convective transport. Atmospheric Chemistry and Physics, 21(3), 1861-1887. doi:10.5194/acp-21-1861-2021en_AU
dc.identifier.issn1680-7324en_AU
dc.identifier.issue3en_AU
dc.identifier.journaltitleAtmospheric Chemistry and Physicsen_AU
dc.identifier.pagination1861-1887en_AU
dc.identifier.urihttps://doi.org/10.5194/acp-21-1861-2021en_AU
dc.identifier.urihttps://apo.ansto.gov.au/dspace/handle/10238/13257en_AU
dc.identifier.volume21en_AU
dc.language.isoenen_AU
dc.publisherCopernicus Publicationsen_AU
dc.subjectRadon 222en_AU
dc.subjectGasesen_AU
dc.subjectSeasonsen_AU
dc.subjectAtmospheric chemistryen_AU
dc.subjectSimulationen_AU
dc.subjectEmissionen_AU
dc.subjectConvectionen_AU
dc.titleSimulation of radon-222 with the GEOS-Chem global model: emissions, seasonality, and convective transporten_AU
dc.typeJournal Articleen_AU
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