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Full-Text Articles in Other Earth Sciences
Evaluating Alternative Ebullition Models For Predicting Peatland Methane Emission And Its Pathways Via Data–Model Fusion, Shuang Ma, Lifen Jiang, Rachel M. Wilson, Jeff P. Chanton, Scott Bridgham, Shuli Niu, Colleen M. Iversen, Avni Malhotra, Jiang Jiang, Xingjie Lu, Jason Keller, Xiaofeng Xu, Daniel M. Ricciuto, Paul J. Hanson, Yiqi Luo
Evaluating Alternative Ebullition Models For Predicting Peatland Methane Emission And Its Pathways Via Data–Model Fusion, Shuang Ma, Lifen Jiang, Rachel M. Wilson, Jeff P. Chanton, Scott Bridgham, Shuli Niu, Colleen M. Iversen, Avni Malhotra, Jiang Jiang, Xingjie Lu, Jason Keller, Xiaofeng Xu, Daniel M. Ricciuto, Paul J. Hanson, Yiqi Luo
Biology, Chemistry, and Environmental Sciences Faculty Articles and Research
Understanding the dynamics of peatland methane (CH4) emissions and quantifying sources of uncertainty in estimating peatland CH4 emissions are critical for mitigating climate change. The relative contributions of CH4 emission pathways through ebullition, plant-mediated transport, and diffusion, together with their different transport rates and vulnerability to oxidation, determine the quantity of CH4 to be oxidized before leaving the soil. Notwithstanding their importance, the relative contributions of the emission pathways are highly uncertain. In particular, the ebullition process is more uncertain and can lead to large uncertainties in modeled CH4 emissions. To improve model simulations …
Evaluating Alternative Ebullition Models For Predicting Peatland Methane Emission And Its Pathways Via Data–Model Fusion, Shuang Ma, Lifen Jiang, Rachel M. Wilson, Jeff P. Chanton, Scott Bridgham, Shuli Niu, Colleen M. Iversen, Avni Malhotra, Jiang Jiang, Xingjie Lu, Yuanyuan Huang, Jason Keller, Xiaofeng Xu, Daniel M. Ricciuto, Paul J. Hanson, Yiqi Luo
Evaluating Alternative Ebullition Models For Predicting Peatland Methane Emission And Its Pathways Via Data–Model Fusion, Shuang Ma, Lifen Jiang, Rachel M. Wilson, Jeff P. Chanton, Scott Bridgham, Shuli Niu, Colleen M. Iversen, Avni Malhotra, Jiang Jiang, Xingjie Lu, Yuanyuan Huang, Jason Keller, Xiaofeng Xu, Daniel M. Ricciuto, Paul J. Hanson, Yiqi Luo
Biology, Chemistry, and Environmental Sciences Faculty Articles and Research
Understanding the dynamics of peatland methane (CH4) emissions and quantifying sources of uncertainty in estimating peatland CH4 emissions are critical for mitigating climate change. The relative contributions of CH4 emission pathways through ebullition, plant-mediated transport, and diffusion, together with their different transport rates and vulnerability to oxidation, determine the quantity of CH4 to be oxidized before leaving the soil. Notwithstanding their importance, the relative contributions of the emission pathways are highly uncertain. In particular, the ebullition process is more uncertain and can lead to large uncertainties in modeled CH4 emissions. To improve model simulations of CH4 emission and its pathways, …
Predicting Spatial Patterns In Precipitation Isotope (Δ2h And Δ18o) Seasonality Using Sinusoidal Isoscapes, Scott T. Allen, James W. Kirchner, Gregory R. Goldsmith
Predicting Spatial Patterns In Precipitation Isotope (Δ2h And Δ18o) Seasonality Using Sinusoidal Isoscapes, Scott T. Allen, James W. Kirchner, Gregory R. Goldsmith
Biology, Chemistry, and Environmental Sciences Faculty Articles and Research
Understanding how precipitation isotopes vary spatially and temporally is important for tracer applications. We tested how well month‐to‐month variations in precipitation δ18O and δ2H were captured by sinusoidal cycles, and how well spatial variations in these seasonal cycles could be predicted, across Switzerland. Sine functions representing seasonal cycles in precipitation isotopes explained between 47% and 94% of the variance in monthly δ18O and δ2H values at each monitoring site. A significant sinusoidal cycle was also observed in line‐conditioned excess. We interpolated the amplitudes, phases, and offsets of these sine functions across the landscape, using multiple linear …