Mercury is a toxin that causes neurological impairments in adults, is particularly harmful for fetuses and children, and is deadly in severe cases, making it a worldwide health concern. Methylmercury (MeHg) is the environmentally relevant form of mercury (Hg) because it biomagnifies along the food chain. Methylmercury is mainly produced in aquatic sediments via methylation of inorganic Hg (Hg(II)) and transformed back via demethylation. Because transformation rates determine MeHg concentrations, quantification of methylation and demethylation rates is needed to inform management of MeHg. Published rate constants for Hg(II) methylation ( $k_m$) and MeHg demethylation ( $k_d$) vary greatly, stemming partly from differences in experimental methods. We conducted a comprehensive review of rate laws, evaluated published rate constants, and performed biogeochemical simulations to assess variability in reported $k_m$ and $k_d.$ Based on selected studies employing the same pseudo-first-order rate law and similar experimental methods, we found that $k_m=0.04\pm 0.03\mathrm{ }{\mathrm{d}}^{-1}$ is a reasonable range for wetland sediments. Over a number of environments, maximum $k_d$ was smaller at sites without Hg source ( $k_d=0.5\mathrm{ }{\mathrm{d}}^{-1}$) than at sites with identified Hg source ( $k_d=1.8\mathrm{ }{\mathrm{d}}^{-1}$). Larger variability and higher uncertainty in $k_d$ compared to $k_m$ highlight the need for more research on MeHg demethylation rates. This critical review: (a) aids the design of future experimental studies of $k_m$ and $k_d;$ (b) provides guidance for comparing rate constants from different studies; (c) presents a biogeochemical reaction model to assess rate constants; and (d) informs selection of $k_m$ and $k_d$ values from the literature for use in model simulations. Graphical abstract

Terrestrial nature-based climate solutions (NbCS) for carbon dioxide removal (CDR) are critical for mitigating climate change. However, the arid climates characteristic of drylands (aridity index <0.65) often limit the effectiveness of many NbCS. At the same time, drylands cover approximately 45% of the global land area and are threatened by soil degradation, necessitating the deployment of CDR methods for drylands that also promote soil health. Soil amendments with high CO₂ sorption capacity, such as biochar, could provide CDR potential and soil health benefits in drylands provided they do not negatively impact the large inorganic carbon pools typical of dryland soils. The dynamics of soil CO₂ are therefore critical for assessing the response of dryland systems to sorbing amendments. To assess the soil response to CO₂ sorption, we developed a 1D reactive transport model of unsaturated soils in equilibrium with dissolved inorganic carbon and calcite under varying soil respiration rates and soil amendment application conditions. The simulations highlight how alteration of soil CO₂ due to sorption by biochar affects dissolved inorganic carbon, pH, Ca²⁺, and calcite. The transient conditions that emerge, including delayed emissions of respired CO₂, also emphasize the need to consider response times in monitoring campaigns based on CO₂ measurements. In scenarios where soil respiration is low, as is typical in drylands, sorption becomes increasingly important. Although the CDR potential of CO₂ sorption is variable and was modest relative to the overall CDR for a biochar deployment, the impacts of altered gas dynamics on soil inorganic carbon are important to consider as dryland soil amendments are developed.

Seasonally managed wetlands in the San Joaquin River (SJR) watershed in California provide important benefits to wildlife and humans but are threatened through anthropogenic activity. Wetlands in the SJR are subject to salinity regulation, which poses challenges for wetland management. Salinity management in the SJR basin is supported by a process-based model, the Watershed Analysis Risk Management Framework (WARMF). Wetlands are simulated with a “bathtub” analog where water levels are assumed to be the same over one model compartment and the storage volume depends on depth. The complexity and extent of hydrological features pose challenges for input data acquisition. Two approaches to estimating inflow and pond depth and determining water sources were assessed. Approach 1 used mostly monitored data, while Approach 2 used wetland manager knowledge. Approach 2 predicted outflow and salinity better than Approach 1, and an important benefit was the simulation of water reuse within the wetland complex, which was previously not implemented. Approach 1 is generally suited for estimating pond depth when a model compartment represents one wetland, while Approach 2 is suited for wetlands with large spatial extent, many hydrological features, and managed flows. The improved model will support wetland management.