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Upscaling carbon dioxide emissions from lakes
Author(s) -
Seekell David A.,
Carr Joel A.,
Gudasz Cristian,
Karlsson Jan
Publication year - 2014
Publication title -
geophysical research letters
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 2.007
H-Index - 273
eISSN - 1944-8007
pISSN - 0094-8276
DOI - 10.1002/2014gl061824
Subject(s) - environmental science , atmosphere (unit) , flux (metallurgy) , atmospheric sciences , carbon dioxide , aggregate (composite) , covariance , carbon cycle , climatology , meteorology , geology , statistics , ecology , mathematics , geography , ecosystem , chemistry , composite material , biology , materials science , organic chemistry
Quantifying CO 2 fluxes from lakes to the atmosphere is important for balancing regional and global‐scale carbon budgets. CO 2 emissions are estimated through statistical upscaling procedures that aggregate data from a large number of lakes. However, aggregation can bias flux estimates if the physical and chemical factors determining CO 2 exchange between water and the atmosphere are not independent. We evaluated the magnitude of aggregation biases with moment expansions and pCO 2 data from 5140 Swedish lakes. The direction of the aggregation bias depends on lake size; mean flux was overestimated by 4% for small lakes (0.01–0.1 km 2 ) but underestimated by 13% for large lakes (100–1000 km 2 ). Simple covariance‐based correction factors were generated to adjust for upscaling biases. These correction factors represent an easily interpretable and implemented approach to improving the accuracy of regional and global estimates of lake CO 2 emissions.