Variability of ozone in the marine boundary layer of the equatorial Pacific Ocean View Full Text


Ontology type: schema:ScholarlyArticle     


Article Info

DATE

2010-07

AUTHORS

Xiao-Ming Hu, Jeffrey M. Sigler, Jose D. Fuentes

ABSTRACT

This study examines the processes controlling the diurnal variability of ozone (O3) in the marine boundary layer of the Kwajalein Atoll, Republic of the Marshall Islands (latitude 8° 43′ N, longitude 167° 44′ E), during July to September 1999. At the study site, situated in the equatorial Pacific Ocean, O3 mixing ratios remained low, with an overall average of 9–10 parts per billion on a volume basis (ppbv) and a standard deviation of 2.5 ppbv. In the absence of convective storms, daily O3 mixing ratios decreased after sunrise and reached minimum during the afternoon in response to photochemical reactions. The peak-to-peak amplitude of O3 diurnal variation was approximately 1–3 ppbv. During the daytime, O3 photolysis, hydroperoxyl radicals, hydroxyl radicals, and bromine atoms contributed to the destruction of O3, which explained the observed minimum O3 levels observed in the afternoon. The entrainment of O3-richer air from the free troposphere to the local marine boundary layer provided a recovery mechanism of surface O3 mixing ratio with a transport rate of 0.04 to 0.2 ppbv per hour during nighttime. In the presence of convection, downward transport of O3-richer tropospheric air increased surface O3 mixing ratios by 3–12 ppbv. The magnitude of O3 increase due to moist convection was lower than that observed over the continent (as high as 20–30 ppbv). Differences were ascribed to the higher O3 levels in the continental troposphere and weaker convection over the ocean. Present results suggest that moist convection plays a role in surface-level O3 dynamics in the tropical marine boundary layer. More... »

PAGES

117

Identifiers

URI

http://scigraph.springernature.com/pub.10.1007/s10874-011-9196-z

DOI

http://dx.doi.org/10.1007/s10874-011-9196-z

DIMENSIONS

https://app.dimensions.ai/details/publication/pub.1012875995


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