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Anthropogenic emissions of vanadium (V) into terrestrial and aquatic surface systems now match those of geogenic processes, and yet, the geochemistry of vanadium is poorly described in comparison to other comparable contaminants like arsenic. In oxic systems, V is present as an oxyanion with a +5 formal charge on the V center, typically described as H x VO4 (3-x)-, but also here as V(V). Iron (Fe) and manganese (Mn) (oxy)hydroxides represent key mineral phases in the cycling of V(V) at the solid-solution interface, and yet, fundamental descriptions of these surface-processes are not available. Here, we utilize extended X-ray absorption fine structure (EXAFS) and thermodynamic calculations to compare the surface complexation of V(V) by the common Fe and Mn mineral phases ferrihydrite, hematite, goethite, birnessite, and pyrolusite at pH 7. Inner-sphere V(V) complexes were detected on all phases, with mononuclear V(V) species dominating the adsorbed species distribution. Our results demonstrate that V(V) adsorption is exergonic for a variety of surfaces with differing amounts of terminal -OH groups and metal-O bond saturations, implicating the conjunctive role of varied mineral surfaces in controlling the mobility and fate of V(V) in terrestrial and aquatic systems.

In an effort to optimize soil management practices that can help mitigate terrestrial carbon emissions, biochar has been applied to a wide range of soil environments to examine its effect on soil greenhouse gas emissions. Such studies have shown that the soil methane (CH4) flux response can vary widely leading to both increase and decrease in CH4 flux upon biochar amendment. To address this discrepancy, multiple meta-analysis studies have been performed in recent years to determine the key factors that may control the direction of CH4 flux upon biochar treatment. However, even comparing across conclusions from meta-analyses reveals disagreement upon which factors ultimately determine the change in direction and magnitude of CH4 flux due to biochar addition. Furthermore, using multiple observations from a single study can lead to misinterpretation of the influence of a factor within a meta-analysis due to non-independence. In this study, we use a multivariate meta-regression approach that allows factor interactions to investigate which biochar, soil, and management practice factors in combination or individually best explain the CH4 flux response in past biochar amendment studies. Our results show that the interaction of multiple soil factors (i.e., water saturation, soil texture, and soil organic carbon content) best explains the soil CH4 flux response to biochar addition (minimum deviance information criterion (DIC) value along with lowest heterogeneity) as compared to all models utilizing individual factors alone. These findings provide insight into the specific soil factors that should be taken into account simultaneously when optimizing the CH4 flux response to biochar amendments and building empirical models to quantitatively predict soil CH4 flux.

In an effort to optimize soil management practices that can help mitigate terrestrial carbon emissions, biochar has been applied to a wide range of soil environments to examine its effect on soil greenhouse gas emissions. Such studies have shown that the soil methane (CH4) flux response can vary widely leading to both increase and decrease in CH4 flux upon biochar amendment. To address this discrepancy, multiple meta-analysis studies have been performed in recent years to determine the key factors that may control the direction of CH4 flux upon biochar treatment. However, even comparing across conclusions from meta-analyses reveals disagreement upon which factors ultimately determine the change in direction and magnitude of CH4 flux due to biochar addition. Furthermore, using multiple observations from a single study can lead to misinterpretation of the influence of a factor within a meta-analysis due to non-independence. In this study, we use a multivariate meta-regression approach that allows factor interactions to investigate which biochar, soil, and management practice factors in combination or individually best explain the CH4 flux response in past biochar amendment studies. Our results show that the interaction of multiple soil factors (i.e., water saturation, soil texture, and soil organic carbon content) best explains the soil CH4 flux response to biochar addition (minimum deviance information criterion (DIC) value along with lowest heterogeneity) as compared to all models utilizing individual factors alone. These findings provide insight into the specific soil factors that should be taken into account simultaneously when optimizing the CH4 flux response to biochar amendments and building empirical models to quantitatively predict soil CH4 flux.