Local anthropogenic impact on particulate elemental carbon concentrations at Summit, Greenland

  • Hagler G
  • Bergin M
  • Smith E
 et al. 
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Summit, Greenland is a remote Arctic research station allowing for field
measurements at the highest point of the Greenland Ice Sheet. Due to the
current reliance on diesel generators for electricity at Summit,
unavoidable local emissions are a potential contamination threat to the
measurement of combustion-related species in the air and snow. The
effect of fossil-fuel combustion on particulate elemental carbon (EC) is
assessed by a combination of ambient measurements (similar to 1 km from
the main camp), a series of snow pits, and Gaussian plume modeling.
Ambient measurements indicate that the air directly downwind of the
research station generators experiences particulate absorption
coefficient (closely related to EC) values that are up to a factor of
200 higher than the summer 2006 non-camp-impacted ambient average. Local
anthropogenic influence on snow EC content is also evident. The average
EC concentration in 1-m snow pits in the `clean air' sector of Summit
Camp are a factor of 1.8-2.4 higher than in snow pits located 10 km and
20 km to the north ('downwind') and south ('upwind') of the research
site. Gaussian plume modeling performed using meteorological data from
years 2003-2006 suggests a strong angular dependence of anthropogenic
impact, with highest risk to the northwest of Summit Camp and lowest to
the southeast. Along a transect to the southeast (5 degree angle bin),
the modeled frequency of significant camp contribution to atmospheric EC
(i.e. camp-produced EC>summer 2006 average EC) at a distance of 0.5 km,
10 km, and 20 km is 1%, 0.2%, and 0.05%, respectively. According to
both the snow pit and model results, a distance exceeding 10 km towards
the southeast is expected to minimize risk of contamination. These
results also suggest that other remote Arctic monitoring stations
powered by local fuel combustion may need to account for local air and
snow contamination in field sampling design and data interpretation.

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  • G. S. W. Hagler

  • M. H. Bergin

  • E. a. Smith

  • M. Town

  • J. E. Dibb

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