Laboratory chalcopyrite oxidation by Acidithiobacillus ferrooxidans: Oxygen and sulfur isotope fractionation

Laboratory experiments were conducted to simulate chalcopyrite oxidation under anaerobic and aerobic conditions in the absence or presence of the bacterium Acidithiobacillus ferrooxidans. Experiments were carried out with 3 different oxygen isotope values of water (δ¹⁸O_H2O) so that approach to equilibrium or steady-state isotope fractionation for different starting conditions could be evaluated. The contribution of dissolved O₂ and water-derived oxygen to dissolved sulfate formed by chalcopyrite oxidation was unambiguously resolved during the aerobic experiments. Aerobic oxidation of chalcopyrite showed 93 ± 1% incorporation of water oxygen into the resulting sulfate during the biological experiments. Anaerobic experiments showed similar percentages of water oxygen incorporation into sulfate, but were more variable. The experiments also allowed determination of sulfate–water oxygen isotope fractionation, ε¹⁸O_SO4–H2O, of ~ 3.8‰ for the anaerobic experiments. Aerobic oxidation produced apparent ε_SO4–H2O values (6.4‰) higher than the anaerobic experiments, possibly due to additional incorporation of dissolved O₂ into sulfate. δ³⁴S_SO4 values are ~ 4‰ lower than the parent sulfide mineral during anaerobic oxidation of chalcopyrite, with no significant difference between abiotic and biological processes. For the aerobic experiments, a small depletion in δ³⁴S_SO4 of ~? 1.5 ± 0.2‰ was observed for the biological experiments. Fewer solids precipitated during oxidation under aerobic conditions than under anaerobic conditions, which may account for the observed differences in sulfur isotope fractionation under these contrasting conditions.     

Iron isotope fractionation during microbially stimulated Fe(II) oxidation and Fe(III) precipitation

Interpretation of the origins of iron-bearing minerals preserved in modern and ancient rocks based on measured iron isotope ratios depends on our ability to distinguish between biological and non-biological iron isotope fractionation processes. In this study, we compared ⁵⁶Fe/⁵⁴Fe ratios of coexisting aqueous iron (Fe(II)_aq, Fe(III)_aq) and iron oxyhydroxide precipitates (Fe(III)_ppt) resulting from the oxidation of ferrous iron under experimental conditions at low pH (<3). Experiments were carried out using both pure cultures of Acidothiobacillus ferrooxidans and sterile controls to assess possible biological overprinting of non-biological fractionation, and both SO₄²⁻ and Cl⁻ salts as Fe(II) sources to determine possible ionic/speciation effects that may be associated with oxidation/precipitation reactions. In addition, a series of ferric iron precipitation experiments were performed at pH ranging from 1.9 to 3.5 to determine if different precipitation rates cause differences in the isotopic composition of the iron oxyhydroxides. During microbially stimulated Fe(II) oxidation in both the sulfate and chloride systems, ⁵⁶Fe/⁵⁴Fe ratios of residual Fe(II)_aq sampled in a time series evolved along an apparent Rayleigh trend characterized by a fractionation factor α_{Fe(III)aq-Fe(II)aq} ∼ 1.0022. This fractionation factor was significantly less than that measured in our sterile control experiments (∼1.0034) and that predicted for isotopic equilibrium between Fe(II)_aq and Fe(III)_aq (∼1.0029), and thus might be interpreted to reflect a biological isotope effect. However, in our biological experiments the measured difference in ⁵⁶Fe/⁵⁴Fe ratios between Fe(III)_aq, isolated as a solid by the addition of NaOH to the final solution at each time point under N₂-atmosphere, and Fe(II)_aq was in most cases and on average close to 2.9‰ (α_{Fe(III)aq-Fe(II)aq} ∼ 1.0029), consistent with isotopic equilibrium between Fe(II)_aq and Fe(III)_aq. The ferric iron precipitation experiments revealed that ⁵⁶Fe/⁵⁴Fe ratios of Fe(III)_aq were generally equal to or greater than those of Fe(III)_ppt, and isotopic fractionation between these phases decreased with increasing precipitation rate and decreasing grain size. Considered together, the data confirm that the iron isotope variations observed in our microbial experiments are primarily controlled by non-biological equilibrium and kinetic factors, a result that aids our ability to interpret present-day iron cycling processes but further complicates our ability to use iron isotopes alone to identify biological processing in the rock record.     

Subseasonal features of the Asian summer monsoon in the NCEP climate forecast system

The operational climate forecast system （CFS） of the US National Centers for Environmental Prediction provides climate predictions over the world, and CFS products are becoming an important source of information for regional climate predictions in many Asian countries where monsoon climate dominates. Recent studies have shown that, on monthly-to-seasonal time-scales, the CFS is highly skillful in simulating and predicting the variability of the Asian monsoon. The higher-frequency variability of the Asian summer monsoon in the CFS is analyzed, using output from a version with a spectral triangular truncation of 126 waves in horizontal and 64 sigma layers in vertical, focusing on synoptic, quasi-biweekly, and intraseasonal time-scales. The onset processes of different regional monsoon components were investigated within Asia. Although the CFS generally overestimates variability of monsoon on these time-scales, it successfully captures many major features of the variance patterns, especially for the synoptic timescale. The CFS also captures the timing of summer monsoon onsets over India and the Indo-China Peninsula. However, it encounters difficulties in simulating the onset of the South China Sea monsoon. The success and failure of the CFS in simulating the onset of monsoon precipitation can also be seen from the associated features of simulated atmospheric circulation processes. Overall, the CFS is capable of simulating the synoptic-to-intraseasonal variability of the Asian summer monsoon with skills. As for seasonal-tointerannual time-scales shown previously, the model is expected to possess a potential for skillful predictions of the high-frequency variability of the Asian monsoon.