Carbon monoxide (CO) plays an important role in controlling the oxidizing capacity of the atmosphere by reacting with OH radicals that affect atmospheric methane (CH4) dynamics. We develop a process-based biogeochemistry model to quantify the CO exchange between soils and the atmosphere with a 5 min internal time step at the global scale. The model is parameterized using the CO flux data from the field and laboratory experiments for 11 representative ecosystem types. The model is then extrapolated to global terrestrial ecosystems using monthly climate forcing data. Global soil gross consumption, gross production, and net flux of the atmospheric CO are estimated to be from-197 to-180, 34 to 36, and-163 to-145 Tg CO yr-1 (1 Tg Combining double low line 1012 g), respectively, when the model is driven with satellite-based atmospheric CO concentration data during 2000-2013. Tropical evergreen forest, savanna and deciduous forest areas are the largest sinks at 123 Tg CO yr-1. The soil CO gross consumption is sensitive to air temperature and atmospheric CO concentration, while the gross production is sensitive to soil organic carbon (SOC) stock and air temperature. By assuming that the spatially distributed atmospheric CO concentrations (∼ 128 ppbv) are not changing over time, the global mean CO net deposition velocity is estimated to be 0.16-0.19 mm s-1 during the 20th century. Under the future climate scenarios, the CO deposition velocity will increase at a rate of 0.0002-0.0013 mm s-1 yr-1 during 2014-2100, reaching 0.20-0.30 mm s-1 by the end of the 21st century, primarily due to the increasing temperature. Areas near the Equator, the eastern US, Europe and eastern Asia will be the largest sinks due to optimum soil moisture and high temperature. The annual global soil net flux of atmospheric CO is primarily controlled by air temperature, soil temperature, SOC and atmospheric CO concentrations, while its monthly variation is mainly determined by air temperature, precipitation, soil temperature and soil moisture.
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Acknowledgements. This study is supported through projects funded to Qianlai Zhuang by the Department of Energy (DESC0008092 and DE-SC0007007) and the NSF Division of Information and Intelligent Systems (NSF-1028291). The supercomputing resource is provided by the Rosen Center for Advanced Computing at Purdue University. We acknowledge Stephen C. Whalen for making the observational CO flux data available to this study. We are also grateful to the University of Tuscia (dep. DIBAF), Italy, and their affiliated members, for their help and the use of their field data.