Biochar最新文献

Abstract

Hydrothermal carbonization (HTC) is a thermochemical conversion technology to produce hydrochar from wet biomass without drying, but it is time-consuming and expensive to experimentally determine the optimal HTC operational conditions of specific biomass to produce desired hydrochar. Therefore, a machine learning (ML) approach was used to predict and optimize hydrochar properties. Specifically, biochemical components (proteins, lipids, and carbohydrates) of biomass were predicted and analyzed first via elementary composition. Then, accurate single-biomass (no mixture) based ML multi-target models (average R² = 0.93 and RMSE = 2.36) were built to predict and optimize the hydrochar properties (yield, elemental composition, elemental atomic ratio, and higher heating value). Biomass composition (elemental and biochemical), proximate analyses, and HTC conditions were inputs herein. Interpretation of the model results showed that ash, temperature, and the N and C content of biomass were the most critical factors affecting the hydrochar properties, and that the relative importance of biochemical composition (25%) for the hydrochar was higher than that of operating conditions (19%). Finally, an intelligent system was constructed based on a multi-target model, verified by applying it to predict the atomic ratios (N/C, O/C, and H/C). It could also be extended to optimize hydrochar production from the HTC of single-biomass samples with experimental validation and to predict hydrochar from the co-HTC of mixed biomass samples reported in the literature. This study advances the field by integrating predictive modeling, intelligent systems, and mechanistic insights, offering a holistic approach to the precise control and optimization of hydrochar production through HTC.

Combined straw and straw-derived biochar input is commonly applied by farmland management in low-fertility soils. Although straw return increases soil organic matter (SOM) contents, it also primes SOM mineralization. The mechanisms by which active microorganisms mineralize SOM and the underlying factors remain unclear for such soils. To address these issues, paddy soil was amended with ¹³C-labeled straw, with and without biochar (BC) or ferrihydrite (Fh), and incubated for 70 days under flooded conditions. Compound-specific ¹³C analysis of phospholipid fatty acids (¹³C-PLFAs) allowed us to identify active microbial communities utilizing the ¹³C-labeled straw and specific groups involved in SOM mineralization. Cumulative SOM mineralization increased by 61% and 27% in soils amended with Straw + BC and Straw + Fh + BC, respectively, compared to that with straw only. The total PLFA content was independent of the straw and biochar input. However, ¹³C-PLFAs contents increased by 35–82% after biochar addition, reflecting accelerated microbial turnover. Compared to that in soils without biochar addition, those with biochar had an altered microbial community composition-increased amounts of ¹³C-labeled gram-positive bacteria (¹³C-Gram +) and fungi, which were the main active microorganisms mineralizing SOM. Microbial reproduction and growth were susceptible to nutrient availability. ¹³C-Gram + and ¹³C-fungi increased with Olsen P but decreased with dissolved organic carbon and ({text{NO}}_{3}^{ - }) contents. In conclusion, biochar acts as an electron shuttle, stimulates iron reduction, and releases organic carbon from soil minerals, which in turn increases SOM mineralization. Gram + and fungi were involved in straw decomposition in response to biochar application and responsible for SOM mineralization.

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Emergent plants have been remarkably effective in reducing phosphorus (P) discharge from ecological ditches; however, the treatment and recycling of these residues is a great challenge. In this study, magnetic biochars (MB_s, i.e., MB-A, MB-C, and MB-T) were fabricated from three emergent plant residues (Acorus calamus L., Canna indica L., and Thalia dealbata Fraser, respectively) and modified with Fe(II)/Fe(III). Scanning electron microscopy-energy dispersive spectroscopy and X-ray diffraction spectra confirmed the successful loading of Fe₃O₄ and FeO(OH) onto the surfaces of the MB_s. Batch adsorption experiments showed that MB_s exhibited a higher P adsorption capacity than that of the raw biochars. Within the range of 0.8–43.0 mg L⁻¹ in solution, the adsorption capacities of P by MB-A, MB-C, and MB-T were 304.6–5658.8, 314.9–6845.6, and 292.8–5590.0 mg kg⁻¹, with adsorption efficiencies of 95.2–32.9%, 98.4–39.8%, and 91.5–32.5%, respectively. The primary mechanisms that caused P to adsorb onto the MB_s were inner-sphere complexation and electrostatic attraction. Low pH conditions were more beneficial for the P adsorption of the MB_s, while co-existing anions had a negative impact with the following order: HCO₃⁻ > SO₄²⁻ > Cl⁻≈NO₃⁻. The P-31 nuclear magnetic resonance results further demonstrated that the main adsorbed P species on the MB_s was orthophosphate, followed by orthophosphate monoesters and DNA. Overall, MB_s offer a resource utilization strategy for emergent plant residues and P-laden MB_s are promising alternative P fertilizers.

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Biochar incorporation into soil has shown potential, in enhancing nitrogen fertilizer (N-fertilizer) efficacy and soil organic carbon content (SOC). This study addresses a critical gap in the literature by investigating the effects of biochar addition over a seven-year period (2014–2020) on inorganic N, SOC, and pH in Haplic Luvisol. The research involved a rain-fed field experiment, with a crop rotation comprising spring barley, maize, spring wheat, and pea. Biochar, applied at the rates of 0, 10, and 20 t ha⁻¹ in 2014, was reapplied to specific plots in 2018. Biochar was also combined with N-fertilizer at three level (N0, N1, and N2). Results showed a significant interactive influence of biochar and N-fertilizer combination on NO₃⁻ and NH₄⁺ contents. Intriguingly, the addition of 10 t biochar ha⁻¹ consistently decreased soil inorganic N levels across most of the examined months. Increasing biochar application rates led to a significant rise in pH, establishing a clear, negative correlation between soil pH and inorganic N content. Biochar significantly increased SOC compared to the control, particularly after the reapplication in 2018. However, this effect showed a diminishing trend over time. The study suggests that incorporating biochar treatments may enhance N-fertilizer effectiveness. However, the long-term implications of biochar application with N-fertilizer on N mineralization are specific to individual soil and biochar combinations. Except the application of 20 t ha⁻¹ biochar at N2 in 2019, biochar did not affect the crop yields. Studied soil properties, including those influenced by biochar had nuanced impact on different aspects of crop yield.

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In addition to the adsorption and immobilization capacities of iron-modified biochars, these materials produce persistent free radicals (PFRs) that can carry out metal [i.e., Cr(VI)] redox transformations, but the primary forms and active species of PFRs involved are not well understood. Here, we investigated the key species of PFRs of α-Fe₂O₃-modified biochar (MBC) and their influence on Cr(VI) reduction under anaerobic conditions simulating paddy soil environments. MBC produced bulk phenoxyl PFRs that promoted Cr(VI) reduction due to the catalytic effect of the transition metal Fe. In addition, MBC was more efficient in reducing Cr(VI) under anaerobic conditions than under aerobic conditions due to the more active and accessible dissolved PFRs present in the dissolved organic matter (DOM). The electron transfer capacity of DOM was demonstrated by excitation-emission matrix (EEM) spectrophotometry combined with parallel factor analysis, which showed that the protein-like and humic-like components of DOM were involved in Cr(VI) reduction. Furthermore, Fourier transform ion cyclotron resonance mass spectrometry (FTICR-MS) analysis indicated that reduced-S compounds (O/S < 4) and carboxylic acid (–COO) groups in the unsaturated aliphatic and lignin-like compounds are potentially the main active species accelerating Cr(VI) reduction under anaerobic conditions. Our results provide new insights into the role of dissolved PFRs from iron-modified biochar in promoting Cr(VI) reduction under anaerobic conditions such as flooded soils.

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Modification serves as an excellent approach to enhancing the adsorption performance of biochar for tetracycline. Selective modification further allows the attainment of biochar materials that are not only more efficient but also cost-effective. However, the key structural factors influencing the adsorption of tetracycline by biochar remain unclear at present, hindering the effective guidance for modification strategies. This study established the relationship between carbonization degree and adsorption capacity, constructed a standardized microscopic model for biochar adsorption of tetracycline, and explored potential reaction mechanisms. The results indicated that with increases in the degree of carbonization, the tetracycline adsorption capacity of biochar increased from 16.08 mg L⁻¹ to 98.35 mg L⁻¹. The adsorption energy exhibited a strong correlation with the aromatic condensation of biochar at p ≤ 0.01, with a linear relationship (r² ≥ 0.94). For low carbonization degrees, the adsorption of tetracycline by biochar was primarily driven by chemical bonds (69.21%) and complemented with electrostatic interactions, weak van der Waals forces or π-π interactions. For high carbonization degrees, the synergistic effects of hydrogen bonding, van der Waals forces, and π-π interactions determined the adsorption of tetracycline on biochar (91.1%). Additionally, larger carbon clusters resulted in stronger and more stable adsorption interactions. Furthermore, carboxyl-functionalized highly carbonized biochar displayed the highest reaction energy of − 1.8370 eV for adsorption of tetracycline through electrostatic interactions. This study suggests that a high degree of aromatic condensation in the carbon structure of biochar is crucial for the efficient adsorption of tetracycline.

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In order to treat dyes in the wastewater of the printing industry and to reutilize walnut shell (WS) waste generate economic benefits, supercritical carbon dioxide (SC-CO₂) pretreatment technology was developed to prepare porous biochar as a precursor for adsorption material. Orthogonal experiments were conducted at the temperatures of 200, 300, and 400 ℃ with durations of 20, 40, and 60 min, and a control group was set up using N₂ pretreatment. Then, KOH activation was employed to prepare biochar adsorption material. The biochars were analyzed and characterized using TGA, BET, SEM, FT-IR, and XRD, and the liquid and gas phase products of the pretreatment process were analyzed semi-quantitatively and quantitatively using GC–MS and gas chromatography. Methylene blue (MB) dye was selected as an indicator to measure the adsorption capacity of biochar, and adsorption kinetics were analyzed based on the data. The results indicate that pretreatment with SC-CO₂ effectively enhanced the performance and yield of the activated carbon. The highest specific surface area increased by 18%, and the maximum adsorption of MB increased by 23% compared to the N₂ control group. The yield increased by 8–262% and the specific surface area increased by 50–192% compared to the direct activation of walnut shell (WS). During the pretreatment processes for the preparation of biochar adsorption material with the best specific surface area, phenol-enriched bio-oil was produced as a by-product which has economic value.

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Abstract

The use of machine learning (ML) in the field of predicting heavy metals interaction with biochar is a promising field of research, mainly because of the growing understanding of how removal efficiency is affected by characteristic variables, reaction conditions and biochar properties. The practical application in biochar still faces large challenges, such as difficulties in data collection, inadequate algorithm development, and insufficient information. However, the quantity, quality, and representation of data have a large impact on the accuracy, efficiency, and generalizability of machine learning tasks. From this perspective, the present data descriptors, the efficiency of machine learning-aided property and performance prediction, the interpretation of underlying mechanisms and complicated relationships, and some potential ways to augment the data are discussed regarding the interactions of heavy metals with biochar. Finally, future perspectives and challenges are discussed, and an enhanced model performance is proposed to reinforce the feasibility of a particular perspective.

Noble metal materials have been identified as high efficiency catalysts for electrocatalytic reduction of nitrate, and the synthesis and manufacture of high catalytic activity and environmentally friendly catalysts of activating hydrogen for water purification applications is extremely attractive. In this work, the Pd–Cu single-atom catalysts (Pd–Cu-N-BC) were first prepared by direct growth of Pd–Cu single-atom on bamboo biochar by regulating the concentration of precursors and doping method, and then enhanced electrocatalytic reduction nitrate performance and N₂ generation. The results showed that Pd–Cu-N-BC displayed excellent catalytic activity and reusability in electrocatalytic reduction nitrate with a low potential of 0.47 V vs. RHE (@10 mA cm⁻²). The maximum nitrate removal efficiency and N₂ generation could reach about 100% and 72.32% within 180 min, respectively. The density functional theory (DFT) calculations confirmed that Cu atoms could catalyze the electrochemical reduction of nitrate to nitrite, and Pd atoms anchored in the nitrogen-doped biochar (N-BC) lattice could catalyze electrochemical reduction of nitrite to N₂ involving the formation of hydrogen radical (H*). The characterization results of XANES showed that electronic synergistic effect between Pd and Cu single atoms significantly promotes the N₂ production through hydrogenation while inhibiting the generation of byproducts, leading to significantly enhanced electrocatalytic reduction of nitrate to N₂. Finally, Pd–Cu-N-BC was designed as a 3D particle electrode for enhanced electrocatalytic reduction of nitrate, exhibiting excellent stability and reusability, which could be considered as a suitable candidate for applications in the remediation of nitrate contamination.

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Biochar has been widely recognized for its potential to increase carbon (C) sequestration and mitigate climate change. This potential is affected by how biochar interacts with native soil organic carbon (SOC) and fresh organic substrates added to soil. However, only a few studies have been conducted to understand this interaction. To fill this knowledge gap, we conducted a ¹³C-glucose labelling soil incubation for 6 months using fine-textured agricultural soil (Stagnosol) with two different biochar amounts. Biochar addition reduced the mineralization of SOC and ¹³C-glucose and increased soil microbial biomass carbon (MBC) and microbial carbon use efficiency (CUE). The effects were found to be additive i.e., higher biochar application rate resulted in lower mineralization of SOC and ¹³C-glucose. Additionally, soil density fractionation after 6 months revealed that most of the added biochar particles were recovered in free particulate organic matter (POM) fraction. Biochar also increased the retention of ¹³C in free POM fraction, indicating that added ¹³C-glucose was preserved within the biochar particles. The measurement of ¹³C from the total amino sugar fraction extracted from the biochar particles suggested that biochar increased the microbial uptake of added ¹³C-glucose and after they died, the dead microbial residues (necromass) accumulated inside biochar pores. Biochar also increased the proportion of occluded POM, demonstrating that increased soil occlusion following biochar addition reduced SOC mineralization. Overall, the study demonstrates the additional C sequestering potential of biochar by inducing negative priming of native SOC as well as increasing CUE, resulting in the formation and stabilization of microbial necromass.

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