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Apparent quantum yield of photochemical dissolved organic carbon mineralization in lakes
Uppsala University, Disciplinary Domain of Science and Technology, Biology, Department of Ecology and Genetics, Limnology.
Linnaeus Univ, Ctr Ecol & Evolut Microbial Model Syst EEMiS, S-39182 Kalmar, Sweden.
Uppsala University, Disciplinary Domain of Science and Technology, Biology, Department of Ecology and Genetics, Limnology.ORCID iD: 0000-0003-3509-8266
2016 (English)In: Limnology and Oceanography, ISSN 0024-3590, E-ISSN 1939-5590, Vol. 61, no 6, 2207-2221 p.Article, review/survey (Refereed) Published
Abstract [en]

Up to one tenth of the carbon dioxide (CO2) emissions from inland waters worldwide are directly induced by the photochemical mineralization of dissolved organic matter (DOM). The photochemical production of dissolved inorganic carbon (DIC) per photon absorbed by chromophoric DOM (CDOM) decreases exponentially with increasing irradiance wavelength, and is commonly described by an “apparent quantum yield” (AQY) spectrum. Although an essential model parameter to simulate photochemical mineralization the AQY remains poorly constrained. Here, the AQY of photochemical DIC production for 25 lakes located in boreal, polar, temperate, and tropical areas, including four saline lagoons, was measured. The wavelength-integrated AQY (300–500 nm; mol DIC mol CDOM-absorbed photons−1) ranged from 0.05 in an Antarctic lake to 0.61 in a humic boreal lake, averaging 0.24 ± 0.03 SE. AQY was positively linearly correlated with the absorption coefficient at 420 nm (a420) as a proxy for CDOM content (R2 of 0.64 at 300 nm and 0.26 at 400 nm), with specific UV absorption coefficients as a proxy for DOM aromaticity (R2 of 0.56 at 300 nm and 0.38 at 400 nm), and with the humification index (R2 of 0.41 at 300 nm and 0.42 at 400 nm). Hence, a considerable fraction of the AQY variability was explained by water optical properties in inland waters. The correlation of AQY with a420 opens up the possibility to improve large-scale model estimates of sunlight-induced CO2 emissions from inland waters based on water color information derived by satellite remote sensing.

Place, publisher, year, edition, pages
2016. Vol. 61, no 6, 2207-2221 p.
National Category
Oceanography, Hydrology, Water Resources
Identifiers
URN: urn:nbn:se:uu:diva-304387DOI: 10.1002/lno.10366ISI: 000387749500018OAI: oai:DiVA.org:uu-304387DiVA: diva2:1032896
Funder
Swedish Research Council Formas, 2009-1350-15339-81Swedish Research Council, 2011-3475-88773-67Knut and Alice Wallenberg Foundation, KAW 2013.009
Available from: 2016-10-05 Created: 2016-10-05 Last updated: 2017-11-30Bibliographically approved

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Koehler, BirgitTranvik, Lars J.

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