Global fjords as transitory reservoirs of labile organic carbon modulated by organo-mineral interactions.

The global carbon cycle is strongly modulated by organic carbon (OC) sequestration and decomposition. Whereas OC sequestration is relatively well constrained, there are few quantitative estimates of its susceptibility to decomposition. Fjords are hot spots of sedimentation and OC sequestration in marine sediments. Here, we adopt fjords as model systems to investigate the reactivity of sedimentary OC by assessing the distribution of the activation energy required to break OC bonds. Our results reveal that OC in fjord sediments is more thermally labile than that in global sediments, which is governed by its unique provenance and organo-mineral interactions. We estimate that 61 ± 16% of the sedimentary OC in fjords is degradable. Once this OC is remobilized and remineralized during glacial maxima, the resulting metabolic CO2 could counterbalance up to 50 ppm of the atmospheric CO2 decrease during glacial times, making fjords critical actors in dampening glacial-interglacial climate fluctuations through negative carbon cycling loops.

Quantification of geogenic carbon in anthropogenic alluvial coal soils of the Susquehanna River.

Alluvial riparian soils act as a filtration system, improving the environmental quality of downstream soils and waters. In areas affected by coal mining, alluvial soils also serve as a modern "sink" of fossil carbon (C). To date, little research has been done on ecosystem services provided by alluvial landscapes (i.e., river islands and tributary deltas) in the retention of coal in coal-mining regions. The objective of this study was to distinguish between and quantify geogenic and neogenetic C in alluvial soils of the North Branch of the Susquehanna River (NBSR). To investigate this, we compared five thermal analysis methods to quantify geogenic (coal) C in soils. Our results indicate that multivariate curve resolution of ramped thermal combustion data provided the most accurate estimate of coal content in soils. Our analysis found that NBSR alluvial soils have accumulated ∼375 Gg of anthropogenic, geogenic C (upper 1 m). In these soils, an average of ∼11% of soil mass is attributable to coal, yet ∼73% of the total soil C is attributable to geogenic C. These soil organic C stocks are substantially greater than locally mapped riparian soils unaffected by coal mining and are greater than regional organic soils (Histosols). Quantification of microbial decomposition of coal in alluvial soils and vulnerability to extreme flood events (potential remobilization) requires further investigation and will be important in determining the fate of this C sink.

Assessment of artificial neural network to identify compositional differences in ultrahigh-resolution mass spectra acquired from coal mine affected soils.

This study assessed the applicability of artificial neural networks (ANNs) as a tool to identify compounds contributing to compositional differences in coal-contaminated soils. An artificial neural network model was constructed from laser desorption ionization ultrahigh-resolution mass spectra obtained from coal contaminated soils. A good correlation (R2 = 1.00 for model and R2 = 0.99 for test) was observed between the measured and predicted values, thus validating the constructed model. To identify chemicals contributing to the coal contents of the soils, the weight values of the constructed model were evaluated. Condensed hydrocarbon and low oxygen containing compounds were found to have larger weight values and hence they were the main contributors to the coal contents of soils. In contrast, compounds identified as lignin did not contribute to the coal contents of soils. These findings were consistent with the conventional knowledge on coal and results from the conventional partial least square method. Therefore, we concluded that the weight interpretation following ANN analysis presented herein can be used to identify compounds that contribute to the compositional differences of natural organic matter (NOM) samples.

Blank corrections for ramped pyrolysis radiocarbon dating of sedimentary and soil organic carbon.

Ramped pyrolysis (RP) targets distinct components of soil and sedimentary organic carbon based on their thermochemical stabilities and allows the determination of the full spectrum of radiocarbon ((14)C) ages present in a soil or sediment sample. Extending the method into realms where more precise ages are needed or where smaller samples need to be measured involves better understanding of the blank contamination associated with the method. Here, we use a compiled data set of RP measurements of samples of known age to evaluate the mass of the carbon blank and its associated (14)C signature, and to assess the performance of the RP system. We estimate blank contamination during RP using two methods, the modern-dead and the isotope dilution method. Our results indicate that during one complete RP run samples are contaminated by 8.8 ± 4.4 µg (time-dependent) of modern carbon (MC, fM ∼ 1) and 4.1 ± 5.5 µg (time-independent) of dead carbon (DC, fM ∼ 0). We find that the modern-dead method provides more accurate estimates of uncertainties in blank contamination; therefore, the isotope dilution method should be used with caution when the variability of the blank is high. Additionally, we show that RP can routinely produce accurate (14)C dates with precisions ∼100 (14)C years for materials deposited in the last 10,000 years and ∼300 (14)C years for carbon with (14)C ages of up to 20,000 years.