Abstract
Soil bacteria known as methanotrophs are the sole biological sink for atmospheric methane (CH4/, a potent greenhouse gas that is responsible for ∼20% of the humandriven increase in radiative forcing since pre-industrial times. Soil methanotrophy is controlled by a plethora of factors, including temperature, soil texture, moisture and nitrogen content, resulting in spatially and temporally heterogeneous rates of soil methanotrophy. As a consequence, the exact magnitude of the global soil sink, as well as its temporal and spatial variability, remains poorly constrained.We developed a process-based model (Methanotrophy Model; MeMo v1.0) to simulate and quantify the uptake of atmospheric CH4 by soils at the global scale. MeMo builds on previous models by Ridgwell et al. (1999) and Curry (2007) by introducing several advances, including (1) a general analytical solution of the one-dimensional diffusion-reaction equation in porous media, (2) a refined representation of nitrogen inhibition on soil methanotrophy, (3) updated factors governing the influence of soil moisture and temperature on CH4 oxidation rates and (4) the ability to evaluate the impact of autochthonous soil CH4 sources on uptake of atmospheric CH4. We show that the improved structural and parametric representation of key drivers of soil methanotrophy in MeMo results in a better fit to observational data. A global simulation of soil methanotrophy for the period 1990-2009 using MeMo yielded an average annual sink of 33.5±0.6 TgCH4 yr-1. Warm and semi-arid regions (tropical deciduous forest and open shrubland) had the highest CH4 uptake rates of 602 and 518 mgCH4 m-2 yr-1, respectively. In these regions, favourable annual soil moisture content (∼20% saturation) and low seasonal temperature variations (variations
Cite
CITATION STYLE
Murguia-Flores, F., Arndt, S., Ganesan, A. L., Murray-Tortarolo, G., & Hornibrook, E. R. C. (2018). Soil Methanotrophy Model (MeMo v1.0): A process-based model to quantify global uptake of atmospheric methane by soil. Geoscientific Model Development, 11(6), 2009–2032. https://doi.org/10.5194/gmd-11-2009-2018
Register to see more suggestions
Mendeley helps you to discover research relevant for your work.