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Volume 17, issue 23
Atmos. Chem. Phys., 17, 14661-14674, 2017
https://doi.org/10.5194/acp-17-14661-2017
© Author(s) 2017. This work is distributed under
the Creative Commons Attribution 3.0 License.
Atmos. Chem. Phys., 17, 14661-14674, 2017
https://doi.org/10.5194/acp-17-14661-2017
© Author(s) 2017. This work is distributed under
the Creative Commons Attribution 3.0 License.

Research article 08 Dec 2017

Research article | 08 Dec 2017

Surface ozone and its precursors at Summit, Greenland: comparison between observations and model simulations

Yaoxian Huang1,a, Shiliang Wu1,2,3, Louisa J. Kramer1,2,b, Detlev Helmig4, and Richard E. Honrath1,2,† Yaoxian Huang et al.
  • 1Department of Geological and Mining Engineering and Sciences, Michigan Technological University, Houghton, Michigan, USA
  • 2Atmospheric Sciences Program, Michigan Technological University, Houghton, Michigan, USA
  • 3College of Environmental Science and Engineering, Ocean University of China, Qingdao, China
  • 4Institute of Arctic and Alpine Research, University of Colorado, Boulder, Colorado, USA
  • anow at: Department of Climate and Space Sciences and Engineering, University of Michigan, Ann Arbor, Michigan, USA
  • bnow at: School of Geography, Earth and Environmental Sciences, University of Birmingham, Birmingham, UK
  • deceased

Abstract. Recent studies have shown significant challenges for atmospheric models to simulate tropospheric ozone (O3) and its precursors in the Arctic. In this study, ground-based data were combined with a global 3-D chemical transport model (GEOS-Chem) to examine the abundance and seasonal variations of O3 and its precursors at Summit, Greenland (72.34°N, 38.29°W; 3212ma.s.l.). Model simulations for atmospheric nitrogen oxides (NOx), peroxyacetyl nitrate (PAN), ethane (C2H6), propane (C3H8), carbon monoxide (CO), and O3 for the period July 2008–June 2010 were compared with observations. The model performed well in simulating certain species (such as CO and C3H8), but some significant discrepancies were identified for other species and further investigated. The model generally underestimated NOx and PAN (by  ∼ 50 and 30%, respectively) for March–June. Likely contributing factors to the low bias include missing NOx and PAN emissions from snowpack chemistry in the model. At the same time, the model overestimated NOx mixing ratios by more than a factor of 2 in wintertime, with episodic NOx mixing ratios up to 15 times higher than the typical NOx levels at Summit. Further investigation showed that these simulated episodic NOx spikes were always associated with transport events from Europe, but the exact cause remained unclear. The model systematically overestimated C2H6 mixing ratios by approximately 20% relative to observations. This discrepancy can be resolved by decreasing anthropogenic C2H6 emissions over Asia and the US by  ∼20%, from 5.4 to 4.4Tgyear−1. GEOS-Chem was able to reproduce the seasonal variability of O3 and its spring maximum. However, compared with observations, it underestimated surface O3 by approximately 13% (6.5ppbv) from April to July. This low bias appeared to be driven by several factors including missing snowpack emissions of NOx and nitrous acid in the model, the weak simulated stratosphere-to-troposphere exchange flux of O3 over the summit, and the coarse model resolution.

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A global chemical transport model (GEOS-Chem) was employed to simulate surface ozone and its precursors at Summit, Greenland in the Arctic and compare them with 2-year in situ surface observations. The model performed well in simulating certain species (such as carbon monoxide and propane), but some significant discrepancies were identified for other species (e.g., nitrogen oxides, ethane, PAN, and ozone). We further investigated the exact causes for model–data biases.
A global chemical transport model (GEOS-Chem) was employed to simulate surface ozone and its...
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