Spatially Resolved Organomineral Interactions across a Permafrost Chronosequence

Abstract

Permafrost contains a large (1700 Pg C) terrestrial pool of organic matter (OM) that is susceptible to degradation as global temperatures increase. Of particular importance is syngenetic Yedoma permafrost containing high OM content. Reactive iron phases promote stabilizing interactions between OM and soil minerals and this stabilization may be of increasing importance in permafrost as the thawed surface region (“active layer”) deepens. However, there is limited understanding of Fe and other soil mineral phase associations with OM carbon (C) moieties in permafrost soils. To elucidate the elemental associations involved in organomineral complexation within permafrost systems, soil cores spanning a Pleistocene permafrost chronosequence (19,000, 27,000, and 36,000 years old) were collected from an underground tunnel near Fairbanks, Alaska. Subsamples were analyzed via scanning transmission X-ray microscopy–near edge X-ray absorption fine structure spectroscopy at the nano- to microscale. Amino acid-rich moieties decreased in abundance across the chronosequence. Strong correlations between C and Fe with discrete Fe­(III) or Fe­(II) regions selectively associated with specific OM moieties were observed. Additionally, Ca coassociated with C through potential cation bridging mechanisms. Results indicate Fe­(III), Fe­(II), and mixed valence phases associated with OM throughout diverse permafrost environments, suggesting that organomineral complexation is crucial to predict C stability as permafrost systems warm.

Molecular Sorption Mechanisms of Cr(III) to Organo-Ferrihydrite Coprecipitates Using Synchrotron-Based EXAFS and STXM Techniques

“…Such a spatial distribution of C, Cr, and Fe was also observed in the Cr­(III)-HA-Fe colloids at the subnanoscale . Although STXM measurements cannot cover the whole sample region, previous studies indicated that a similar approach used for soil or organo-mineral associations investigation was reproducible and reliable, and could capture various colloidal variation. − , Generally, regardless of the C loadings, the C-enriched regions were patched with the Fe-enriched regions in the studied OFC samples, indicating the heterogeneous structures of OFC, which agreed with previous reports. , Since the DOM solution was obtained from the filtration by a 0.22 μm filter, the C-enriched particles in size from 4 to 20 μm were probably due to the self-assembly of the DOM during the formation of OFC. , As labeled by red circles (Figure ), a strong overlapping of Fe and Cr signals in the 1% Ri_Cr­(III) suggested that Cr­(III) was predominantly associated with Fh, which was consistent with our recent study . It was reported that Fh had a great binding ability to Cr­(III) by the formation of inner-sphere complexes .…”

“…Images at 280 and 288.5 eV photon energies with a large area (i.e., 2500 μm 2 ) were first obtained, and a subtraction of the two images was used to select the sample regions of interest (ROIs). Similar approaches used for soil samples investigation have justified that the regions with the sizes of tens of micrometers can capture a wide variety of representative colloidal variations. ,− However, this approach was impossible to obtain the complete information of the OFC samples due to the limited measured area. , The image stack measurements covering C K-edge, Cr L-edge, and Fe L-edge were obtained by image raster scan from 280 to 735 eV with a 1 ms dwell time and 30–40 nm pixel size. Besides, the image stacks for C K-edge and Cr L-edge of the reference sample OM-Cr­(III) were also collected.…”

Sorption Mechanisms of Chemicals in Soils

“…The molecular simulations of Zhang et al [93] predicted that carboxylate functional groups of natural organic matter adsorb onto montmorillonite surfaces through direct bonding of carboxylate to clay mineral edges and through Ca 2+ bridging on basal plane surfaces. The prediction of Ca 2+ bridging agrees with the observations made using spectroscopic analysis of SOM-soil clay interactions by Sowers et al [94]. As computing capability and molecular models advance, predicting soil adsorption behavior from first principles will be possible if the input model is sufficiently constrained.…”

Scanning Transmission X-Ray Microscopy At The Canadian Light Source: Progress And Selected Applications In Geosciences

“…5,70 STXM is a relatively new and emergent technique in the application to soils compared to routine laboratory techniques, and over the years STXM has been adopted to deliver spatially resolved XANES (i.e., spectromicroscopy) to investigate the chemical and electronic heterogeneities of soil microaggregates at multi-element edges, particularly related to OMAs. [71][72][73][74][75][76][77][78][79][80][81][82][83][84][85][86][87][88] In the early studies, carbon Kedge STXM was primarily used to identify the carbon chemical species, functional groups, and morphology within OMA. [71][72][73][74][75][76]80 Their main findings were as follows: (1) typical C 1s features related to soil organic carbon included aromatic (285 eV), phenolic (286.7 eV), aliphatic (287.3 eV), carboxylic (288.6 eV), and O-alkyl (289.3), and their relative intensity varied slightly from soil to soil; (2) soil microaggregates were characterized by pore surfaces, mineral matter, OM, and their mixtures; at the microscopic scale the distribution of carbon OM was patchy rather than uniform, although their composition was stable in each soil type; (3) the surface of phyllosilicate and iron minerals was coated by OM with more aliphatic and carboxylic functional groups; (4) black carbon (BC) in soils was successfully identified by STXM at a spatial resolution of 30-50 nm, and the core of BC was highly aromatic while the surface of BC was oxidized with high amounts of carboxylic and phenolic carbon forms.…”

“…Subsequently, a multi- elemental, combined STXM approach was used to elucidate many more mineral and OM phases and their interactions. 75,77,78,[81][82][83][84][85][86][87][88] Furthermore, STXM analysis is highly quantitative, has excellent sensitivity and a low detection limit, allows for varied environments, and causes a low amount of radiation damage, especially compared to electron microscopy. 12,89 Figs.…”