Published in

American Geophysical Union, Journal of Geophysical Research, D17(113), 2008

DOI: 10.1029/2007jd009688

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Seasonal variation of nitrogen oxides in the central North Atlantic lower free troposphere

Journal article published in 2008 by M. Val Martin ORCID, R. E. Honrath, R. C. Owen, Q. B. Li
This paper was not found in any repository, but could be made available legally by the author.
This paper was not found in any repository, but could be made available legally by the author.

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Abstract

1] Measurements of NO, NO 2 , and NO y (total reactive nitrogen oxides) made at the Pico Mountain station, 38.47°N, 28.40°W, 2.2 km above sea level, from July 2002 to August 2005 are used to characterize the seasonal and diurnal variations of nitrogen oxides in the background lower free troposphere (FT) over the central North Atlantic Ocean. These observations reveal a well-defined seasonal cycle of nitrogen oxides (NO x = NO + NO 2 and NO y), with higher mixing ratios during the summertime. Observed NO x and NO y levels are consistent with long-range transport of emissions, with significant removal en route to the measurement site. Larger summertime nitrogen oxides levels are attributed to boreal wildfire emissions and more efficient export and transport of NO y from eastern North America during that season. In addition, measurements of NO x and NO y obtained during in-cloud and cloud-free conditions are used to estimate PAN and HNO 3 mixing ratios and examine the partitioning of the reactive nitrogen species. These estimates indicate that reactive nitrogen over the central North Atlantic lower FT largely exists in the form of PAN and HNO 3 ($80–90% of NO y) year-round. The composition of NO y shifts from dominance of PAN in winter-spring to dominance of HNO 3 in summer-fall, as a result of changes in temperature and photochemistry over the region. A further comparison of the nitrogen oxides measurements with results from the global chemical transport model GEOS-Chem finds that simulated nitrogen oxides are significantly larger than the observations.