Microbial Impacts to the Near-Field Environment Geochemistry: a model for estimating microbial communities in repository drifts at Yucca Mountain

Geochemical and microbiological modeling was performed to evaluate the potential quantities and impact of microorganisms on the geochemistry of the area adjacent to and within nuclear waste packages in the proposed repository drifts at Yucca Mountain, Nevada. The microbial growth results from the introduction of water, ground support, and waste package materials into the deep unsaturated rock. The simulations, which spanned 1 million years, were accomplished using a newly developed computer code, Microbial Impacts to the Near-Field Environment Geochemistry (MING). MING uses environmental thresholds for limiting microbial growth to temperatures below 120 °C and above relative humidities of 90% in repository drifts. Once these thresholds are met, MING expands upon a mass balance and thermodynamic approach proposed by McKinley et al. [FEMS Microbiol. Rev. 20 (1997) 545] by using kinetic rates to supply constituents from design materials and constituent fluxes including solubilized rock components into the drift to perform two separate mass balance calculations as a function of time. The first (nutrient limit) assesses the available nutrients (C, N, P and S) and calculates how many microorganisms can be produced based on a microorganism stoichiometry of C160(H280O80)N30P2S. The second (energy limit) calculates the energy available from optimally combined redox couples for the temperature and pH at that time. This optimization maximizes those reactions that produce >15 kJ/mol (limit on useable energy) using an iterative linear optimization technique. The final available energy value is converted to microbial mass at a rate of 1 kg of biomass (dry weight) for every 64 MJ of energy. These two values (nutrient limit and energy limit) are then compared and the smaller value represents the number of microorganisms that can be produced over a specified time. MING can also be adapted to investigate other problems of interest as the model can be used in saturated and unsaturated environments and in laboratory situations to establish microbial growth limitations. Other projected uses include investigations of contaminated locations where monitored natural attenuation or engineered bioremediation could be employed.