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Atmospheric Chemistry and Physics An interactive open-access journal of the European Geosciences Union
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https://doi.org/10.5194/acp-2020-804
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/acp-2020-804
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.

  24 Aug 2020

24 Aug 2020

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This preprint is currently under review for the journal ACP.

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

Bo Zhang1, Hongyu Liu1, James H. Crawford2, Gao Chen2, T. Duncan Fairlie2, Scott Chambers3, Chang-Hee Kang4, Alastair G. Williams3, Kai Zhang5, David B. Considine6, Melissa P. Sulprizio7, and Robert M. Yantosca7 Bo Zhang et al.
  • 1National Institute of Aerospace, Hampton, Virginia, USA
  • 2NASA Langley Research Center, Hampton, Virginia, USA
  • 3Australian Nuclear Science and Technology Organization, Kirrawee, New South Wales, Australia
  • 4Jeju National University, Jeju, Republic of Korea
  • 5Pacific Northwest National Laboratory, Richland, Washington, USA
  • 6NASA Headquarters, Washington, D.C., USA
  • 7Harvard University, Cambridge, Massachusetts, USA

Abstract. Radon-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, MERRA and 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 (< 70 % data within a factor of 2) and a large underestimate of winter surface 222Rn concentrations at Northern Hemisphere mid- 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 up-scaling 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 % 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 U.S., 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 mid-latitude 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 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.

Bo Zhang et al.

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Short summary
We simulate atmospheric Rn-222 using the GEOS-Chem model to improve understanding of Rn-222 emissions and characterize convective transport in the model. We demonstrate the potential of a customized global Rn-222 emission scenario to improve simulated surface Rn-222 concentrations and seasonality. We assess convective transport using observed Rn-222 vertical profiles. Results have important implications for using chemical transport models to interpret the transport of trace gases and aerosols.
We simulate atmospheric Rn-222 using the GEOS-Chem model to improve understanding of Rn-222...
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