Our understanding of the sulfur cycle has traditionally come from measurements of the sulfur isotopic composition of marine sulfate (SO42–) and sulfur-bearing materials in marine sediments. Such reconstructions have contributed to our understanding of the interactions between Earth tectonics, climate, and elemental cycles.
88 IV.8 Plot of pyrite sulfur abundance (left axis, red lines) and δ34S (right . axis; blue lines) for buried pyrite emerging from the bottom of the model domain as a function of POC rain rate for the experiments of the model in which the bottom of the water temperature varied. Whiskers (closed dashed lines) are depicted with lengths equal to 2σ(95%) data coverage within each group;.
LIST OF TABLES
Trilobite results obtained from the mQ + NaCl treatment group in scavenging assays were also included.
INTRODUCTION
- Sulfur Isotopes and the Marine Sulfur Cycle
- Geologic Archives of the Ancient Marine Sulfur Cycle
- Methods of S Isotope Analysis
- Strategy and Structure of the Thesis
These models are similar to box models of the geological C cycle (e.g. [190]) and are schematically depicted in Figure I.1. These geological archives of the marine S cycle include S in both oxidized and reduced redox states.
PERMO-CARBONIFEROUS SULFUR CYCLE
Abstract
Geological evidence and mathematical modeling of the Permo-Carboniferous carbon and sulfur cycles suggest that changes in the burial ratio of organic carbon to pyrite (RC:S) are insufficient to explain the observed mid-Carboniferous δ34SCAS record. We found that changes in the 34S depletion of pyrite relative to seawater sulfate (Δδ34S) or in δ34S of input to the ocean (δ34Sin) are also required.
Introduction
Here we present a new δ34SCAS record for the Permo-Carboniferous from individual well-preserved unstained brachiopods. Our results further cement the Permo-Carboniferous as an important transition period in the history of the Earth.
Sample localities
Subsequent brachiopod and conodont δ34S measurements by Wu and colleagues confirmed the trends in the early and latest carbonaceous parts of this record. 2018) have argued for the existence of an additional positive δ34S excursion at the center of Tournai, based on whole-rock CAS δ34S measurements (i.e. δ34SCAS), but previous work suggests that diagenetic changes may prevent measurements of whole rocks reliably record seawater δ34S. The ages of the samples are derived from biostratigraphy; references can be found in the supplementary information for Grossman et al.
Methods
To evaluate δ34SCAS variability within individual samples, triplicate samples were drilled from well-preserved areas of three large brachiopod samples (two Neospirifer sp. from the American Midcontinent and one Choristites sp. from the Russian Platform). In addition, replicate samples from the same sediment horizon were sampled in 39 different cases to evaluate interspecimen and interspecies variability in δ34SCAS.
Results
Maps of three additional thin sections also exhibited variation in CAS abundance near this level, with the most variable sample (TWS43, a Composita subtilita-men species) exhibiting ∼190% variation. Our new record of δ34SCAS variation in the Carboniferous and early Permian (Figure II.4) exhibits significant temporal variability and is largely consistent with previous brachiopod-based δ34SCAS records.
Discussion
The early Carboniferous δ34S decrease represents one of the largest changes in seawater δ34S in the entire Phanerozoic record (Figure II.7). Previous studies of the Cretaceous and Cenozoic seawater δ34S record revealed the potential for rapid (> 0.5hper Myr) changes in the marine sulfur cycle to occur on timescales of several Myr. Special emphasis is placed on simultaneous changes in the pyrite burial flux and Δδ34S, as the interaction of these terms can enable particularly rapid changes in seawater δ34S.
Conclusions
Geological evidence and box modeling suggest that changes in Δδ34S and/or δ34Sin are required in addition to changes in pyrite burial to explain the mid-Carbon δ34SCAS record. We suggest that combined changes in pyrite burial, Δδ34S and δ34Sin should be considered more seriously as drivers of rapid changes in the δ34S of seawater. Changes in shelf area can alter the relative proportions of isotopically distinct depositional environments and force these combined changes viable.
Abstract
Introduction
The combination of biostratigraphy, geochronology, and geochemistry points to the eruption of the large magmatic province of the Siberian Traps as the source of the environmental and climatic disturbance that caused the EPME. Although both CAS data (e.g. and evaporite δ34S data indicate a large increase in seawater δ34S from the Late Permian to Early Triassic, disagreement between the data on the character of the δ34S increase has hindered a better understanding well of the behavior of the marine S cycle across the EPME.Red stars and text indicate the approximate paleolocations of the two EPME sections sampled as part of this study.
Sample Localities
The section is relatively unstudied, although recent work has begun to characterize the biostratigraphy and lithofacies at the site. The exact position of the Permian–Triassic boundary at the site is uncertain; the first appearance datum (FAD) of conodontH. Correlation of the extinction interval at the site with that at Meishan [50] indicates that the absolute sedimentation rate at Yudongzi is at least an order of magnitude higher (> 100 Myrm ) than the lowest sedimentation rates at Meishan.
Methods
Results
3 Figure III.3: Example of XRF screening. (A) Surface optical image of hand specimen YDS32.5, a wakestone with some zones of calcite, veins rich in pyrite and silicastic material, and disseminated pyrite throughout the specimen. The red box indicates the approximate area imaged by µ-XRF microscopy; numbered green stars indicate tears are drilled and sampled for the δ34 measurement of SCAS. (B) XR maps of element counts for sample YDS32.5; the colored line indicates the number of counts. The video image is based on optical brightness and is included because of the link between geochemical and optical properties. the upper left part of the elements map is outside the edge of the pattern. There is a slight positive correlation between Si and Al counts and a strong correlation between Fe and S counts. Also note the secondary trend in the S vs. Fe plot (B) indicating the presence of some S not associated with Fe; all pixels in this trend are located at the edge of the sample and appear to be a topographic artifact.
Discussion
However, existing data suggest that seawater SO42–δ34S was about 10±1 haom 1 Myr before the PTB [17]. These data and the corresponding age model [17] indicate that seawater SO42–δ34S experienced a rapid, ∼20-fold increase over the PTB over about 2 Myr; underwent Alternatively, temporal variation in the concentration and δ34S of seawater SO42 - specifically an increase in [SO42 -] and decrease in SO42 - δ34S - could also explain this trend.
YDS 32.5
- Conclusions
Initial δ34SCASin this case was +10h; all other aspects of the figure are as in Figures III.11 and III.12. Pyrite trace element content (e.g., [28]) may be a viable means of distinguishing whether pyrite formed in the water column constitutes a significant component of the pyrite present in these sediments. Additional work is needed to disentangle the role of marine S-cycle dynamics as a direct driver of the EPME versus a passive follower of other Earth system changes occurring in the late Permian and early Triassic.
A NEW REACTIVE TRANSPORT MODEL OF SULFUR CYCLING IN DEEP MARINE SEDIMENTS
Abstract
Background
In most environments, only a small fraction of organic matter survives passage through the water column into marine sediments [154]. SO42-dominates in abundance over other electron acceptors in modern marine sediments and is responsible for over 50% of organic matter degradation locally [165] and up to 29% globally [43]. This model uses more realistic pyrite formation mechanisms than most previous models and is one of the first to include organic matter sulphidation as a distinct process.
Model Construction
Jørgensen made one of the first attempts to model the S isotopic composition of S species during sedimentary diagenesis. He simply removed a solid fraction of the hydrous sulfide (H2S) generated at each depth as pyrite (FeS2), with no intervening iron monosulfide (FeS) phase. Only recently have modelers begun to incorporate more realistic reaction mechanisms for pyrite formation [127, 217].
CANDI Model Schematic
- Results
- Discussion
- Conclusions
The values used for each of the half-saturation and inhibition constants in I-CANDI are shown in Table IV.7. This Czend+1 value is then substituted into Equation IV.4 to calculate dCdt at the lower limit. Compared to the original set of runs (Figure IV.3), the runs at higher bottom water temperatures show a shift in the transition points between dominant modes of organic matter degradation towards higher RRPOCs.
Are any of the threshold-like transitions in POC degradation reflected in the δ34S of buried pyrite. However, a large increase in δ34S occurs at high rates of organic matter precipitation if the FeCO3 +H2S formation mechanism is activated (Figure IV.13).
SULFUR CYCLING IN DEEP MARINE OXYGENATED SETTINGS: INSIGHTS FROM IODP EXPEDITION 361, IODP
Abstract
Background
Sulfur cycling in deep ocean sediments—and especially deep ocean Δδ34S—remains an understudied component of the global S cycle. This suggests that 34ε is very large in deep ocean sediments and that the deep-sea pyrite burial flux may have a large influence on the global pyrite burial δ34S value. We show that large (> 45 h) S isotopic fractionations are a ubiquitous feature of deep-sea sedimentary sulfur cycles.
Site Locations
Extensive ship- and shore-based chemical analyzes make these sites the best candidates to determine the influence of different sedimentary variables on S-cycling in deep-sea sediments. Onboard sedimentation rate indicates the sedimentation rate estimated for the upper part of the sediments based on the ship-age model. KN223 Sites 02 and 16 were drilled in the North Atlantic near Researcher Ridge and on the Bermuda Rise, respectively.
Methods
Column chromatography and mass spectrometry methods for these samples were identical to those used in Chapter II. Samples were centrifuged and the supernatant was removed immediately after centrifugation to limit the oxidation of the Ag2S by NO3. Many samples were run with different replicates due to the δ34S heterogeneity within the sample powders.
Results
The gradient of δ34S increase is lower at site U1475 than at site U1474, as expected from the lower rate of [SO42−] decrease. Following these minima, [SO42−] increases in a quasi-linear manner with depth to concentrations greater than 22 mM at site U1486 and 24 mM at site U1488. Here the offset gradually decreases with depth until it becomes near zero at 125.9 mbsf at location U1482 and even reverses sign below 60 mbsf at location U1483.
Discussion
Site U1485 has the highest sedimentation rates of all sites studied here, and both RRPOC and nSRR are correspondingly high (Figure V.16). Susceptibility tests (Figure C.5) show similar relationships between RRPOC, RRFe and pyrite δ34S as those at site U1474. The sensitivity of pyrite δ34S to RRPOC and RRFe is comparable to that at site U1474 (Figure C.8). A) Data (filled markers) and best-fit model results (blue lines) for SO42 concentration and δ34S with depth at site KN223-02.
CANDI initial 34 ε
Such cleaning is illustrated by the depth profiles of the S species from the model, which takes place just before the δ34S maximum (Figure V.24). At the maximum, there is a sudden change in the character of the depth profiles (Figure V.25): H2S almost completely consumes Fe and is present only in µM levels. The slope of the contour lines in Figure V.21 suggests that POC addition could facilitate greater SO42 reduction and force the diagenetic regime back to Fe limitation in pyrite burial.
Fe(III) InputBuriedPyriteδ34S
- Conclusions
We can roughly constrain the magnitude of the bias that may be present in current global nSRR estimates based on the exclusion of the sites with an SO42 source at depth. We find high diversity in the character of the [SO42−] and δ34S profiles across the different sites. In addition, a better understanding of the effects of non-S species on the δ34S of pyrite preserved in marine sediments is needed.
GLOBAL TRENDS IN SEDIMENTARY SULFUR CYCLING WITHIN DEEP MARINE SEDIMENTS
- Abstract
- Introduction
- Methods
- Results
- Discussion
After creating the master cluster [SO42−], we used the evalcluster function of MATLAB® to estimate the optimal number of clusters based on the inputs to. The number of sites included in the cluster for these three lower boundary depths are 727, 681, and 506, respectively. In the following, we focus on describing the clustering analysis results for a 100 mbsf lower boundary in detail.
