Biogeochemical modeling of CO 2 and CH 4 production in anoxic Arctic soil microcosms

Tang, Guoping; Zheng, Jianqiu; Xu, Xiaofeng; Yang, Ziming; Graham, David E.; Gu, Baohua; Painter, Scott L.; Thornton, Peter E.

doi:10.5194/bg-13-5021-2016

Title: Biogeochemical modeling of CO ₂ and CH ₄ production in anoxic Arctic soil microcosms

Journal Article · Mon Sep 12 00:00:00 EDT 2016 · Biogeosciences (Online)

DOI:https://doi.org/10.5194/bg-13-5021-2016· OSTI ID:1323989

Tang, Guoping; Zheng, Jianqiu;

; Yang, Ziming;

; Gu, Baohua; Painter, Scott L.; Thornton, Peter E.

Soil organic carbon turnover to CO₂ and CH₄ is sensitive to soil redox potential and pH conditions. But, land surface models do not consider redox and pH in the aqueous phase explicitly, thereby limiting their use for making predictions in anoxic environments. Using recent data from incubations of Arctic soils, we extend the Community Land Model with coupled carbon and nitrogen (CLM-CN) decomposition cascade to include simple organic substrate turnover, fermentation, Fe(III) reduction, and methanogenesis reactions, and assess the efficacy of various temperature and pH response functions. Incorporating the Windermere Humic Aqueous Model (WHAM) enables us to approximately describe the observed pH evolution without additional parameterization. Though Fe(III) reduction is normally assumed to compete with methanogenesis, the model predicts that Fe(III) reduction raises the pH from acidic to neutral, thereby reducing environmental stress to methanogens and accelerating methane production when substrates are not limiting. Furthermore, the equilibrium speciation predicts a substantial increase in CO₂ solubility as pH increases, and taking into account CO₂ adsorption to surface sites of metal oxides further decreases the predicted headspace gas-phase fraction at low pH. Without adequate representation of these speciation reactions, as well as the impacts of pH, temperature, and pressure, the CO₂ production from closed microcosms can be substantially underestimated based on headspace CO₂ measurements only. Our results demonstrate the efficacy of geochemical models for simulating soil biogeochemistry and provide predictive understanding and mechanistic representations that can be incorporated into land surface models to improve climate predictions.

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Research Organization:: Oak Ridge National Laboratory (ORNL), Oak Ridge, TN (United States)

Sponsoring Organization:: USDOE Office of Science (SC), Biological and Environmental Research (BER)

Grant/Contract Number:: AC05-00OR22725

OSTI ID:: 1323989

Alternate ID(s):: OSTI ID: 1327608

Journal Information:: Biogeosciences (Online), Journal Name: Biogeosciences (Online) Vol. 13 Journal Issue: 17; ISSN 1726-4189

Publisher:: Copernicus Publications, EGUCopyright Statement

Country of Publication:: Germany

Language:: English

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Cited by: 19 works

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