Influences of pH and substrate supply on the ratio of iron to sulfate reduction

Abstract

Iron reduction and sulfate reduction often occur simultaneously in anoxic systems, and where that is the case, the molar ratio between the reactions (i.e., Fe/SO 4 2− reduced) influences their impact on water quality and carbon storage. Previous research has shown that pH and the supply of electron donors and acceptors affect that ratio, but it is unclear how their influences compare and affect one another. This study examines impacts of pH and the supply of acetate, sulfate, and goethite on the ratio of iron to sulfate reduction in semi-continuous sediment bioreactors. We examined which parameter had the greatest impact on that ratio and whether the parameter influences depended on the state of each other. Results show that pH had a greater influence than acetate supply on the ratio of iron to sulfate reduction, and that the impact of acetate supply on the ratio depended on pH. In acidic reactors (pH 6.0 media), the ratio of iron to sulfate reduction decreased from 3:1 to 2:1 as acetate supply increased (0-1 mM). In alkaline reactors (pH 7.5 media), iron and sulfate were reduced in equal proportions, regardless of acetate supply. Secondly, a comparison of experiments with and without sulfate shows that the extent of iron reduction was greater if sulfate reduction was occurring and that the effect was larger in alkaline reactors than acidic reactors. Thus, the influence of sulfate supply on iron reduction extent also depended on pH and suggests that iron reduction grows more dependent on sulfate reduction as pH increases. Our results compare well to trends in groundwater geochemistry and provide further evidence that pH is a major control on iron and sulfate reduction in systems with crystalline (oxyhydr)oxides. pH not only affects the ratio between the reactions but also the influences of other parameters on that ratio.

An emulation-based approach for interrogating reactive transport models

“…This dependence emerged somewhat unexpectedly from the emulator as one would not inherently expect a relationship between injectate pCO 2 and SO 2− 4 reduction rates, yet it agrees with results previously reported by Kirk (2016, 2018), as well as by Paper et al (2021). These studies related the influence of pCO 2 and pH to the rate of microbial reactions in vitro, in situ, and in silico.…”

“…Emulation makes sensitivity analysis for RTMs simple and allows us to identify correlations and interactions among parameters that would otherwise be difficult to anticipate by allowing an investigator to quickly test a wide variety of hypotheses. We demonstrate this in the case of Old Rifle by identifying the CO 2 dependency of microbially mediated reactions (Bethke et al, 2011;Kirk, 2016, 2018;Paper et al, 2021). This ability to elucidate unexpected but key model dependencies and sensitivities could prove to be invaluable in helping direct RTM development.…”

An emulation-based approach for interrogating reactive transport models

“…This dependence emerged somewhat unexpectedly from the emulator, as one would not inherently expect a relationship between injectate pCO2 and SO 4 2reduction rates, yet it agrees with results previously reported by Kirk (2016, 2018) as well as Paper et al (2021). These studies related the influence of pCO2 and pH to the rate of microbial reactions, both in vitro, in situ, and in silico.…”

“…Further to this, the ability to evaluate the state of a system after a fixed period of time makes the emulator approach ideally suited for modelling more complex time-series models with time varying boundary conditions: instead of having to run the RTM forward each time the system changes boundary conditions, the emulator can be interrogated for the expected result given the systems current state from the previous regime. Emulation makes sensitivity analysis for RTMs simple and allows us to identify correlations and interactions among parameters that would otherwise be difficult to anticipate, for example the CO2 dependency of microbially mediated reactions (Bethke et al, 2011;Kirk, 2016, 2018;Paper et al, 2021). This ability to elucidate unexpected but key model dependencies and sensitivities could prove invaluable in helping direct RTM development.…”

Biostimulation of Jarosite and Iron Oxide-Bearing Mine Waste Enhances Subsequent Metal Recovery

“…2b). The increase was coeval with the rapid increase in iron concentrations, indicating the onset of iron and/or sulphate reduction as these are both protons consuming/alkalinity producing reactions (Paper et al, 2021). The variability in releases between replicate columns may be attributed to the variations in flow path/residence time.…”