Abstract

Abstract. 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 (~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.

Highlights

  • Since its inception in 1989, the United States National Science Foundation research station at the highest point of the Greenland Ice Sheet (72◦ N, 38◦ W, elevation 3200 m, website address: www.geosummit.org), “Summit Camp”, has been an extremely valuable research site

  • As K+ is a known tracer for biomass burning, these results suggest that a long-distance source was controlling the elemental carbon (EC) levels in the snow pit

  • In all remote and pristine sampling environments, the impact of research site activities on the local environment needs to be taken into consideration to ensure the accuracy of field measurements

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Summary

Introduction

Since its inception in 1989, the United States National Science Foundation research station at the highest point of the Greenland Ice Sheet (72◦ N, 38◦ W, elevation 3200 m, website address: www.geosummit.org), “Summit Camp”, has been an extremely valuable research site. The focus of our research team’s effort at Summit Camp was to measure carbonaceous particulate matter (organic and elemental carbon) in the air and snow These species are of interest as markers of natural and anthropogenic emissions reaching the Greenland Ice Sheet (e.g. fossil fuel combustion and biomass burning), both in ambient sampling and as a paleorecord of previous source activity. The camp generators are in continuous use and intermittent (every 2–3 weeks during the spring to summer and every 2–3 months during late-summer to early-spring) supply aircraft arrivals occur regardless of wind direction As these emitting sources could potentially contaminate our atmospheric sampling for organic and elemental carbon, protective measures were integrated into our atmospheric sampling protocol during the field season (cessation of integrated filter sampling during air traffic and ongoing sector control at all other times). While this study is focused primarily on carbonaceous species, this research is expected to be applicable to other atmospheric species of interest that may be impacted by camp emissions at Summit, Greenland

Methods
Snow pits
26 June 2006 25 June 2006 20 June 2006 22 June 2006 29 June 2006 3 July 2006
Gaussian plume modeling
Findings
Conclusions
Full Text
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