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Soil organic carbon (SOC) is pivotal for both agricultural activities and climate change mitigation, and biochar stands as a promising tool for bolstering SOC and curtailing soil carbon dioxide (CO 2 ) emissions. However, the involvement of biochar in SOC dynamics and the underlying interactions among biochar, soil microbes, iron minerals, and fresh organic matter (FOM, such as plant debris) remain largely unknown, especially in agricultural soils after long-term biochar amendment. We therefore introduced FOM to soils with and without a decade-long history of biochar amendment, performed soil microcosm incubations, and evaluated carbon and iron dynamics as well as microbial properties. Biochar amendment resulted in 2-fold SOC accrual over a decade and attenuated FOM-induced CO 2 emissions by approximately 11% during a 56-day incubation through diverse pathways. Notably, biochar facilitated microbially driven iron reduction and subsequent Fenton-like reactions, potentially having enhanced microbial extracellular electron transfer and the carbon use efficiency in the long run. Throughout iron cycling processes, physical protection by minerals could contribute to both microbial carbon accumulation and plant debris preservation, alongside direct adsorption and occlusion of SOC by biochar particles. Furthermore, soil slurry experiments, with sterilization and ferrous iron stimulation controls, confirmed the role of microbes in hydroxyl radical generation and biotic carbon sequestration in biochar-amended soils. Overall, our study sheds light on the intricate biotic and abiotic mechanisms governing carbon dynamics in long-term biochar-amended upland soils.

Soil aggregates are crucial for soil organic carbon (OC) accumulation. This study, utilizing a 32-year fertilization experiment, investigates whether the core microbiome can elucidate variations in carbon content and decomposition across different aggregate sizes more effectively than broader bacterial and fungal community analyses. Employing ensemble learning algorithms that integrate machine learning with network inference, we found that the core microbiome accounts for an average increase of 26 % and 20 % in the explained variance of PCoA and Adonis analyses, respectively, in response to fertilization. Compared to the control, inorganic and organic fertilizers decreased the decomposition index (DDI) by 31 % and 38 %, respectively. The fungal core microbiome predominantly influenced OC content and DDI in larger macroaggregates (>2000 μm), explaining over 35 % of the variance, while the bacterial core microbiome had a lesser impact, explaining <30 %. Conversely, in smaller aggregates (<2000 μm), the bacterial core microbiome significantly influenced DDI (R 2  > 0.2), and the fungal core microbiome more strongly affected OC content (R 2  > 0.3). Mantel tests showed that pH is the most significant environmental factor affecting core microbiome composition across all aggregate sizes (Mantel's r > 0.8, P < 0.01). Linear correlation analysis further confirmed that the core microbiome's community structure could accurately predict OC content and DDI in aggregates (R 2  > 0.8, P < 0.05). Overall, our findings suggested that the core microbiome provides deeper insights into the variability of aggregate organic carbon content and decomposition, with the bacterial core microbiome playing a particularly pivotal role within the soil aggregates., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 Elsevier B.V. All rights reserved.)

The association of poorly crystalline iron (hydr)oxides with organic matter (OM), such as extracellular polymeric substances (EPS), exerts a profound effect on Fe and C cycles in soils and sediments, and their behaviors under sulfate-reducing conditions involve complicated mineralogical transformations. However, how different loadings and types of EPS and water chemistry conditions affect the sulfidation still lacks quantitative and systematic investigation. We here synthesized a set of ferrihydrite-organic matter (Fh-OM) coprecipitates with various model compounds for plant and microbial exopolysaccharides (polygalacturonic acids, alginic acid, and xanthan gum) and bacteriogenic EPS (extracted from Bacillus subtilis ). Combining wet chemical analysis, X-ray diffraction, and X-ray absorption spectroscopic techniques, we systematically studied the impacts of C and S loadings by tracing the temporal evolution of Fe mineralogy and speciation in aqueous and solid phases. Our results showed that the effect of added OM on sulfidation of Fh-OM coprecipitates is interrelated with the amount of loaded sulfide. Under low sulfide loadings (S(-II)/Fe < 0.5), transformation to goethite and lepidocrocite was the main pathway of ferrihydrite sulfidation, which occurs more strongly at pH 6 compared to that at pH 7.5, and it was promoted and inhibited at low and high C/Fe ratios, respectively. While under high sulfide loadings (S(-II)/Fe > 0.5), the formation of secondary Fe-S minerals such as mackinawite and pyrite dominated ferrihydrite sulfidation, and it was inhibited with increasing C/Fe ratios. Furthermore, all three synthetic EPS proxies unanimously inhibited mineral transformation, while the microbiogenic EPS has a more potent inhibitory effect than synthetic EPS proxies compared at equivalent C/Fe loadings. Collectively, our results suggest that the quantity and chemical characteristics of the associated OM have a strong and nonlinear influence on the extent and pathways of mineralogical transformations of Fh-OM sulfidation.

The formation of carcinogenic N-nitrosamines from reactions between solvent amines and flue gas NO x is an important concern for the application of amine-based processes to capture CO 2 post-combustion. Using an advanced test rig with interconnected absorber and desorber units, we evaluated the importance for N-nitrosamine formation of the desorber relative to the absorber, and any synergism between the two units. Variations in desorber temperature and in flue gas composition indicated that N-nitrosamine formation from fresh monoethanolamine (MEA) occurred predominantly in the absorber. N-nitrosamine formation was driven by high NO 2 and O 2 flue gas concentrations, although NO also contributed. In contrast, N-nitrosamine formation from piperazine (PZ) was driven by reactions with nitrite in the heated desorber, and accelerated concurrent with nitrite accumulation. A complementary experiment simulating aged MEA solvent (high nitrite, 1.5% sarcosine as a proxy of secondary amine degradation products) suggested the desorber becomes an order of magnitude more important than the absorber for N-nitrosamine formation. For fresh MEA solvent, increasing the desorber temperature from 110 °C to 130 °C promoted thermal decomposition of N-nitrosamines, reducing N-nitrosamine accumulation rates two-fold. Compared to the test rig, the prevailing practice of using separate absorber columns and autoclave-like treatments to mimic desorber units predicted the direction, but underestimated the magnitude of N-nitrosamine formation. Because N-nitrosamine accumulation rates are the net result of competing formation and thermal decomposition processes, use of continuously cycling test rigs may be necessary to understand the impacts of different operating conditions., (Copyright © 2019 Elsevier Ltd. All rights reserved.)

A recent study published in the journal Nature used a data-driven machine-learning approach to examine the relationship between microbial carbon use efficiency (CUE) and soil organic carbon (SOC) storage. The study concluded that CUE promotes global SOC storage based on a positive correlation between CUE and SOC content. However, the study has been criticized for excluding important data sets and lacking mechanistic consideration of the complexities of SOC formation. The critics argue that the stabilization process, rather than CUE, matters more for SOC formation. They also caution against inferring causality from large data sets and emphasize the need for more sophisticated empirical measurements before establishing a globally causal link between CUE and SOC. [Extracted from the article]

Geological carbon storage is considered as a promising strategy to reduce greenhouse gas emissions. For those subsurface systems with uranium-bearing minerals in rock formations, there is an uncharacterized possibility for injected CO 2 to cause uranium mobilization due to the coupled chemical and physical interactions at mineral--water interfaces. We developed a TOUGHREACT model to assess the uranium mobilization potential from uraninite (UO 2) dissolution induced by CO 2 injection into a hypothetical CO 2 storage reservoir in a time scale of 30 years of CO 2 injection and 100 years after. Numerical simulation results show that the concentration of HCO 3 − increased after CO 2 injection, and CO 2 was able to migrate toward the shallow aquifer through existing leakage pathways. HCO 3 −-assisted UO 2 oxidative dissolution was the dominant mechanism that led to the increase of dissolved uranium concentration in a form of uranyl carbonate complex and the mechanism of H+-assisted UO 2 dissolution could be ignored. Sensitivity tests suggested that the increase of UO 2 content and O 2 level in the CO 2 storage reservoir resulted in the most significant increase of dissolved uranium concentration, but no sign of uranium intrusion was predicted up to the shallow aquifer. In summary, uranium release induced by CO 2 injection is possible if the target CO 2 storage reservoir contains U-bearing minerals and is exposed to oxidizing environment, but our simulation assured that significant upward migration of uranium from deep CO 2 storage reservoir driven by CO 2 injection is unlikely even at the worst scenario. Image 1 • A TOUGHREACT model was developed to simulate uranium mobilization potential from deep aquifer under GCS condition. • HCO 3 −-assisted UO 2 oxidative dissolution was the dominant mechanism that led to the increase of dissolved U concentration. • The uranium migration potential is most sensitive to the increase of UO 2 content and O 2 level in the storage reservoir. • Under the most aggressive scenario, upward migration of U from CO 2 storage reservoir to shallow groundwater is unlikely. [ABSTRACT FROM AUTHOR]