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Title: Modeling CO2 emissions from Arctic lakes: Model development and site-level study

Journal Article · · Journal of Advances in Modeling Earth Systems
ORCiD logo [1]; ORCiD logo [2]; ORCiD logo [3];  [3]; ORCiD logo [3]; ORCiD logo [4];  [5]
  1. Purdue Univ., West Lafayette, IN (United States). Department of Earth, Atmospheric, and Planetary Sciences; Pacific Northwest National Lab. (PNNL), Richland, WA (United States)
  2. Purdue Univ., West Lafayette, IN (United States). Department of Earth, Atmospheric, and Planetary Sciences and Department of Agronomy
  3. University of Eastern Finland, Kuopio (Finland). Department of Environmental and Biological Science
  4. ETH Zurich, Zurich (Switzerland). Department of Environmental Systems Science
  5. University of Alaska Fairbanks, Fairbanks, AK (United States). Water and Environmental Research Center
+ Show Author Affiliations

Recent studies indicated that Arctic lakes play an important role in receiving, processing, and storing organic carbon exported from terrestrial ecosystems. To quantify the contribution of Arctic lakes to the global carbon cycle, we developed a one-dimensional process-based Arctic Lake Biogeochemistry Model (ALBM) that explicitly simulates the dynamics of organic and inorganic carbon in Arctic lakes. By realistically modeling water mixing, carbon biogeochemistry, and permafrost carbon loading, the model can reproduce the seasonal variability of CO2 fluxes from the study Arctic lakes. The simulated area-weighted CO2 fluxes from yedoma thermokarst lakes, nonyedoma thermokarst lakes, and glacial lakes are 29.5, 13.0, and 21.4 g C m-2 yr-1, respectively, close to the observed values (31.2, 17.2, and 16.5 ± 7.7 g C m-2 yr-1, respectively). The simulations show that the high CO2 fluxes from yedoma thermokarst lakes are stimulated by the biomineralization of mobilized labile organic carbon from thawing yedoma permafrost. The simulations also imply that the relative contribution of glacial lakes to the global carbon cycle could be the largest because of their much larger surface area and high biomineralization and carbon loading. According to the model, sunlight-induced organic carbon degradation is more important for shallow nonyedoma thermokarst lakes but its overall contribution to the global carbon cycle could be limited. Overall, the ALBM can simulate the whole-lake carbon balance of Arctic lakes, a difficult task for field and laboratory experiments and other biogeochemistry models.

Research Organization:
Pacific Northwest National Laboratory (PNNL), Richland, WA (United States)
Sponsoring Organization:
USDOE Office of Science (SC), Biological and Environmental Research (BER)
Grant/Contract Number:
AC05-076RL01830; FG02-08ER64599; AC02-05CH11231; DE‐FG02‐08ER64599
OSTI ID:
1390343
Alternate ID(s):
OSTI ID: 1390344; OSTI ID: 1413514
Report Number(s):
PNNL-SA-129018; TRN: US1800444
Journal Information:
Journal of Advances in Modeling Earth Systems, Vol. 9, Issue 5; ISSN 1942-2466
Publisher:
American Geophysical Union (AGU)Copyright Statement
Country of Publication:
United States
Language:
English
Citation Metrics:
Cited by: 33 works
Citation information provided by
Web of Science

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Multidecadal climate‐induced changes in Arctic tundra lake geochemistry and geomorphology journal September 2018
Tundra landscape heterogeneity, not interannual variability, controls the decadal regional carbon balance in the Western Russian Arctic journal September 2018
Applicability and consequences of the integration of alternative models for CO2 transfer velocity into a process-based lake model journal January 2019
Minor contribution of small thaw ponds to the pools of carbon and methane in the inland waters of the permafrost-affected part of the Western Siberian Lowland journal March 2018
Applicability and consequences of the integration of alternative models for CO2 transfer velocity into a process-based lake model posted_content April 2019
ISIMIP2a Simulation Data from the Global Lakes Sector dataset January 2022
ISIMIP2b Simulation Data from the Global Lakes Sector dataset January 2022
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