Sulfur isotopes in rivers: Insights into global weathering budgets, pyrite oxidation, and the modern sulfur cycle

Abstract

Supplementary Information End-member decompositionFollowing the approach of Gaillardet et al. (1999), we use a series of linear equations to solve for the proportions of sodium in the river that are attributed to evaporite, carbonate, and silicate weathering. Table 1 in the main text specifies the end-member molar ratios and their associated uncertainty. In order to propagate this uncertainty in end-member values through the calculation, we solve the linear equations for each river 10,000 times using a random sampling of weathering end-member values assuming a Gaussian distribution. For all of the calculations in the main text, the median and standard deviation of these Monte Carlo simulations were used as the solution and uncertainty for each river. For all rivers, using the median of the Monte Carlo simulations gives proportions attributed to each end-member that sum to 1 (± 0.05).Although many of the rivers have distributions of Monte Carlo solutions that are roughly Gaussian for all three end-members (e.g. Supplementary Figure 1), there are a total of 12 of the 31 rivers whose solution distributions for either the evaporite or silicate (or both) end-members are not Gaussian and they have a long tail (e.g. Supplementary Figure 2). This is likely related to the fact that the end-member values for evaporites and silicates have overlapping ranges. In contrast the carbonate end-member values are more distinct resulting in Monte Carlo solution distributions for the carbonate end-member that are typically roughly Gaussian. These 12 rivers are: Brahmaputra, Fraser, Ganges, Kaoping, Kolyma, Lena, Maipo, Mekong, Orinoco, Red, Yangtze, and Yukon rivers.We have tested the influence that these poorly constrained rivers with long tailed distributions have on the results from this study. If we use the modes instead of the medians for those rivers that do not have near-Gaussian Monte Carlo distributions, the total fluxes reported in the main text change by <0.1 Tmol/y, well within the 0.2 Tmol/y uncertainty. However, it does make a slight difference for the proportions of sulfate attributed to each of the weathering end-members (and excess sulfate) for those 12 rivers. This difference influences where these rivers plot on Figure 6 (main text), and is illustrated in Supplementary Figure 3. Although these 12 rivers plot slightly differently in this figure, the major conclusions remain valid, namely that the rivers plot to the left of the 1:1 line and are farther from the line with increasing excess sulfate values, indicating that the excess sulfate likely has a low δ 34 S value. References Gaillardet, J., Dupré, B., Louvat, P., Allegre, C.J., 1999. Global silicate weathering and CO2 consumption rates deduced from the chemistry of large rivers. Chemical Geology 159, 3-30.

Triple oxygen isotope insight into terrestrial pyrite oxidation

“…The majority of this isotope variability occurs within a single lithologic unit, the TSS, despite all evidence to suggest sulfate is quantitatively derived from pyrite oxidation. This observation implies that riverine sulfate δ 34 S compositions are an insufficient conservative tracer to estimate pyrite vs. evaporite weathering contributions to global fluvial sulfate export (20,56,57). In the TSS alone, MSR appears to increase δ 34 S by ∼ 30‰ within consistently pyrite-dominated lithology; this would traditionally be interpreted as a shift from pyritedominated to evaporite-dominated weathering (57).…”

“…This observation implies that riverine sulfate δ 34 S compositions are an insufficient conservative tracer to estimate pyrite vs. evaporite weathering contributions to global fluvial sulfate export (20,56,57). In the TSS alone, MSR appears to increase δ 34 S by ∼ 30‰ within consistently pyrite-dominated lithology; this would traditionally be interpreted as a shift from pyritedominated to evaporite-dominated weathering (57). Furthermore, downstream Marsyandi River tributary isotope compositions approach median values for global datasets, suggesting that global δ 34 S and δ 18 O distributions may more strongly reflect MSR intensity and secondary sulfur storage in floodplains than weathering lithology.…”

Mineral Weathering and the Permafrost Carbon‐Climate Feedback

“…The presence of sulfides in permafrost may therefore alter the balance between H 2 CO 3 -and H 2 SO 4 -driven weathering, with fundamental implications for climate feedbacks (Burke et al, 2018;Torres et al, 2017). Along with carbonate lithologies, shale-which often contains sulfides (Clarke, 1924)-occurs across the Arctic and within Pleistocene glacial limits (Hartmann & Moosdorf, 2012;Kokelj, Lantz, et al, 2017).…”

Variability in sulfur isotope records of Phanerozoic seawater sulfate

“…Microbial sulfate reduction (MSR), reoxidation of sulfide, and the burial and oxidation of pyrite govern sedimentary inorganic carbon and alkalinity fluxes (Ben-Yaakov, 1973;Froelich et al, 1979). Pyrite in sedimentary rocks may be exposed and oxidized during uplift, erosion, and weathering-impacting Earth's dioxygen and carbon dioxide budgets on tectonic timescales (Burke et al, 2018;Kump & Garrels, 1986;M. A. Torres et al, 2014).…”