Large CO2 effluxes at night and during synoptic weather events significantly contribute to CO2 emissions from a reservoir

CO2 emissions from inland waters are commonly determined by indirect methods that are based on the product of a gas transfer coefficient and the concentration gradient at the air water interface (e.g., wind-based gas transfer models). The measurements of concentration gradient are typically collecte...

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Vydáno v:Environmental research letters Ročník 11; číslo 6; s. 064001 - 64008
Hlavní autoři: Liu, Heping, Zhang, Qianyu, Katul, Gabriel G, Cole, Jonathan J, Chapin, F Stuart, MacIntyre, Sally
Médium: Journal Article
Jazyk:angličtina
Vydáno: Bristol IOP Publishing 24.05.2016
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ISSN:1748-9326, 1748-9326
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Shrnutí:CO2 emissions from inland waters are commonly determined by indirect methods that are based on the product of a gas transfer coefficient and the concentration gradient at the air water interface (e.g., wind-based gas transfer models). The measurements of concentration gradient are typically collected during the day in fair weather throughout the course of a year. Direct measurements of eddy covariance CO2 fluxes from a large inland water body (Ross Barnett reservoir, Mississippi, USA) show that CO2 effluxes at night are approximately 70% greater than those during the day. At longer time scales, frequent synoptic weather events associated with extratropical cyclones induce CO2 flux pulses, resulting in further increase in annual CO2 effluxes by 16%. Therefore, CO2 emission rates from this reservoir, if these diel and synoptic processes are under-sampled, are likely to be underestimated by approximately 40%. Our results also indicate that the CO2 emission rates from global inland waters reported in the literature, when based on indirect methods, are likely underestimated. Field samplings and indirect modeling frameworks that estimate CO2 emissions should account for both daytime-nighttime efflux difference and enhanced emissions during synoptic weather events. The analysis here can guide carbon emission sampling to improve regional carbon estimates.
Bibliografie:ERL-102128.R1
ObjectType-Article-1
SourceType-Scholarly Journals-1
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content type line 14
SC0006967; SC0011461
USDOE Office of Science (SC), Biological and Environmental Research (BER)
ISSN:1748-9326
1748-9326
DOI:10.1088/1748-9326/11/6/064001