Black carbon (BC) is a major short-lived climate pollutant (SLCP) with significant climate and environmentalhealth impacts. This review synthesizes critical advancements in the identification of emerging anthropogenic BC sources, updates to global warming potential (GWP) and global temperature potential (GTP) metrics, technical progress in characterization techniques, improvements in global-regional monitoring networks, emission inventory, and impact assessment methods. Notably, gas flaring, shipping, and urban waste burning have slowly emerged as dominant emission sources, especially in Asia, Eastern Europe, and Arctic regions. The updated GWP over 100 years for BC is estimated at 342 CO2-eq, compared to 658 CO2-eq in IPCC AR5. Recent CMIP6-based Earth System Models (ESMs) have improved attribution of BC's microphysics, identifying a 22 % increase in radiative forcing (RF) over hotspots like East Asia and Sub-Saharan Africa. Despite progress, challenges persist in monitoring network inter-comparability, emission inventory uncertainty, and underrepresentation of BC processes in ESMs. Future efforts could benefit from the integration of satellite data, artificial intelligence (AI)assisted methods, and harmonized protocols to improve BC assessment. Targeted mitigation strategies could avert up to four million premature deaths globally by 2030, albeit at a 17 % additional cost. These findings highlight BC's pivotal roles in near-term climate and sustainability policy.

The development of biodegradable and recyclable food packaging materials derived from biomass is a promising solution to mitigate resource depletion and minimize ecological contamination. In this study, lignin nanoparticles (LNPs) were effectively produced from bamboo powder using an eco-friendly recyclable acid hydrotrope (RAH) strategy. A sustainable CA/LNPs nanocomposite film was then designed by incorporating these LNPs into a casein (CA) matrix. The LNPs served as nucleation templates, inducing ordered hydrogen bonding and close packing of the CA chains. The addition of 5 wt% LNPs significantly enhanced the mechanical properties of the film, with tensile strength enhanced to 21.42 MPa (219.7 % improvement) and elastic modulus rising to 354.88 MPa (220.3 % enhancement) compared to pure CA film. Notably, the resultant CA/LNPs nanocomposite film exhibited recyclable recasting characteristics, maintaining a reasonable mechanical strength even after three recasting cycles. The incorporation of LNPs also decreased the water solubility of the pure CA film from 31.65 % to 24.81 % indicating some interactions are taking place, while endowing the film with superior UV-blocking ability, achieving nearly complete absorption in the 200-400 nm range. Moreover, the inherent properties of LNPs imparted improved antibacterial and antioxidant activities to the CA/LNPs nanocomposite film. Owing to its comprehensive properties, the CA/LNPs nanocomposite film effectively extended the storage life of strawberries. A soil burial degradation test confirmed over 100 % mass loss within 45 days, highlighting excellent degradability of the films. Therefore, the simple extraction of LNPs and the easily recovery of p-TsOH provide significant promise and feasibility for extending the developed methodologies in this work to rapidly promote the produced films in fields such as degradable and packaging materials.

Cadmium (Cd) contamination in soil threatens global food production and human health. This study investigated zinc (Zn) addition as a potential strategy to mitigate Cd stress using two barley genotypes, Dong-17 (Cd-sensitive) and WSBZ (Cd-tolerant). Hydroponically grown seedlings were treated with different Cd (0, 1.0, 10 mu M) and Zn (0, 5, 50 mu M) levels. Results showed that Zn addition effectively alleviated Cd induced growth inhibition, improving SPAD values, photosynthetic parameters, fluorescence efficiency (Fv/Fm), and biomass. Zn reduced Cd contents in roots and shoots, inhibited Cd translocation, and ameliorated Cd induced ultrastructural damage to organelles. Transcriptomic analysis revealed distinct gene expression patterns between genotypes, with WSBZ showing enhanced expression of metal transporters, antioxidant defense, and stress signaling genes. Significantly, cell wall related pathways were upregulated in WSBZ, particularly lignin biosynthesis genes (PAL, C4H, 4CL, COMT, CAD/SAD), suggesting cell wall reinforcement as a key Cd tolerance mechanism. Zn induced upregulation of ZIP family transporters and downregulation of Cd transporters (HvHMA) aligned with reduced Cd accumulation. These findings provide comprehensive insights into molecular mechanisms of Zn mediated alleviation of Cd toxicity in barley, supporting improved agronomic practices for Cd contaminated soils.

Mastering the mechanical properties of frozen soil under complex stress states in cold regions and establishing accurate constitutive models to predict the nonlinear stress-strain relationship of the soil under multi-factor coupling are key to ensuring the stability and safety of engineering projects. In this study, true triaxial tests were conducted on roadbed peat soil in seasonally frozen regions under different temperatures, confining pressures, and b-values. Based on analysis of the deviatoric stress-major principal strain curve, the variation patterns of the intermediate principal stress, volumetric strain and minor principal strain deformation characteristics, and anisotropy of deformation, as well as verification of the failure point strength criterion, an intelligent constitutive model that describes the soil's stress-strain behavior was established using the Transformer network, integrated with prior information, and the robustness and generalization ability of the model were evaluated. The results indicate that the deviatoric stress is positively correlated with the confining pressure and the b-value, and it is negatively correlated with the freezing temperature. The variation in the intermediate principal stress exhibits a significant nonlinear growth characteristic. The soil exhibits expansion deformation in the direction of the minor principal stress, and the volumetric strain exhibits shear shrinkage. The anisotropy of the specimen induced by stress is negatively correlated with temperature and positively correlated with the bvalue. Three strength criteria were used to validate the failure point of the sample, and it was found that the spatially mobilized plane strength criterion is the most suitable for describing the failure behavior of frozen peat soil. A path-dependent physics-informed Transformer model that considers the physical constraints and stress paths was established. This model can effectively predict the stress-strain characteristics of soil under different working conditions. The prediction correlation of the model under the Markov chain Monte Carlo strategy was used as an evaluation metric for the original model's robustness, and the analysis results demonstrate that the improved model has good robustness. The validation dataset was input to the trained model, and it was found that the model still exhibits a good prediction accuracy, demonstrating its strong generalization ability. The research results provide a deeper understanding of the mechanical properties of frozen peat soil under true triaxial stress states, and the established intelligent constitutive model provides theoretical support for preventing engineering disasters and for early disaster warning.

Gas station sites pose potential risks of soil and groundwater contamination, which not only threatens public health and property but may also damage the assets and reputation of businesses and government entities. Given the complex nature of soil and groundwater contamination at gas station sites, this study utilizes field data from basic and environmental information, maintenance information for tank and pipeline monitoring, and environmental monitoring to develop machine learning models for predicting potential contamination risks and evaluating high-impact risk factors. The research employs three machine learning models: XGBoost, LightGBM, and Random Forest (RF). To compare the performance of these models in predicting soil and groundwater contamination, multiple performance metrics were utilized, including Receiver Operating Characteristic (ROC) curves, Precision-Recall graphs, and Confusion Matrix (CM). The Confusion Matrix analysis revealed the following results: accuracy of 85.1-87.4 %, precision of 86.6-88.3 %, recall of 83.0-87.2 %, and F1 score of 84.8-87.8 %. Performance ranking across all metrics consistently showed: XGBoost > LightGBM > RF. The area under the ROC curve and precision-recall curve for the three models were 0.95 (XGBoost), 0.94 (LightGBM), and 0.93 (RF), respectively. While all three machine learning approaches demonstrated satisfactory predictive capabilities, the XGBoost model exhibited optimal performance across all evaluation metrics. This research demonstrates that properly trained machine learning models can serve as effective tools for environmental risk assessment and management. These findings have significant implications for decision-makers in environmental protection, enabling more accurate prediction and control of contamination risks, thereby enhancing the preservation of ecological systems, public health, and property security.

The rapid depletion of natural aggregate resources has led to the exploration of recycled aggregates as sustainable alternatives. The steel industry annually generates 28 million tons of magnesia-based waste refractories (WMRs), making their incorporation into construction materials a potential strategy for resource conservation. However, WMR recycling poses a challenge because of its susceptibility to volume expansion during hydration. This study evaluated the feasibility of an environmentally friendly additive, lignosulfonate (LS), for stabilizing crushed waste magnesia refractory bricks (CWMR) to explore the potential application of WMR as construction aggregates. The swelling properties, including the free swell index (FSI) and the swell pressure (Ps), and mechanical properties including unconfined/uniaxial compressive strength (qU), shear wave velocity (VS), and thermal conductivity (lambda) of LS stabilized CWMR (CWMLS) were evaluated over different curing periods at varying LS contents (LSc). Hydration transformed CWMR from sandlike to highly plastic silt-like, resulting in a significant FSI of 250 % and Ps of 5.2 MPa. LS effectively stabilized CWMR, as indicated by decreased FSI and Ps, and enhanced qU and VS. Microscopic observation and mineralogy analyzes confirmed that LS stabilizes CWMR by adsorbing onto its surface. Stabilization of thermal conductivity at higher LSc over curing periods further supports these interactions. Macroscopic behavioral analyzes give stabilized effect of 94.3 % at LSc = 5 % with minimal improvement at higher LSc. These findings highlight LS as a promising stabilizer for mitigating hydration-induced expansion and improving the mechanical properties of CWMR, supporting its application as a recycled aggregate in construction.

Lignin fiber is a type of green reinforcing material that can effectively enhance the physical and mechanical properties of sandy soil when mixed into it. In this study, the changes in the dynamic elastic modulus and damping ratio of lignin-fiber-reinforced sandy soil were investigated through vibratory triaxial tests at different lignin fiber content (FC), perimeter pressures and consolidation ratios. The research results showed that FC has a stronger effect on the dynamic elastic modulus and damping ratio at the same cyclic dynamic stress ratio (CSR); with the increase in FC, the dynamic elastic modulus and damping ratio increase and then decrease, showing a pattern of change of the law. Moreover, perimeter pressure has a positive effect on the dynamic elastic modulus, which can be increased by 81.22-130.60 %, while the effect on the damping ratio is slight. The increase in consolidation ratio increases the dynamic elastic modulus by 10.89-30.86 % and the damping ratio by 38.24-100.44 %. Based on the Shen Zhujiang dynamic model, a modified model considering the effect of lignin fiber content FC was established, and the modified model was experimentally verified to have a broader application scope with a maximum error of 5.36 %. This study provides a theoretical basis for the dynamic analysis and engineering applications of lignin-fiber-reinforced sandy soil.

The exploration of the Moon necessitates sustainable habitat construction. Establishing a permanent base on the Moon requires solutions for challenges such as transportation costs and logistics, driving the emphasis on In-Situ Resource Utilization (ISRU) techniques including Additive Manufacturing. Given the limited availability of regolith on Earth, researchers utilize simulants in laboratory studies to advance technologies essential for future Moon missions. Despite advancements, a comprehensive understanding of the fundamental properties and processing parameters of sintered lunar regolith still needs to be studied, demonstrating the need for further research. Here, we investigated the fundamental properties of lunar regolith simulant material with respect to the stereolithography-based AM process needed for the engineering design of complex items for lunar applications. Material and mechanical characterization of milled and sintered LHS-1 lunar regolith was done. Test specimens, based on ASTM standards, were fabricated from a 70 wt% (48.4 vol %) LHS-1 regolith simulant suspension and sintered up to 1150 degrees C. The compressive, tensile, and flexural strengths were (510.7 +/- 133.8) MPa, (8.0 +/- 0.9) MPa, and (200.3 +/- 49.3) MPa respectively, surpassing values reported in previous studies. These improved mechanical properties are attributed to suspension's powder loading, layer thickness, exposure time, and sintering temperature. A set of regolith physical and mechanical fundamental material properties was built based on laboratory evaluation and prepared for utilization, with the manufacturing of complex-shaped objects demonstrating the technology's capability for engineering design problems.

Foamed lightweight soil with red mud (FLS-RM), a new type of subgrade material commonly used in projects such as bridge backfill. In engineering applications, FLS-RM tends to crack after pouring to weaken its properties, which limits its further application, and this situation can be improved by adding fiber into FLS-RM. Thus, this study developed a new type of FLS-RM reinforced by polypropylene fibers, polyester fibers, and kenaf fibers to investigate the changes in the mechanical properties of FLS-RM and its deterioration mechanism. The experimental results showed that the mechanical properties of FLS-RM could be enhanced by the fibers, and the compressive and flexural strengths of FLS-RM specimens reinforced by polypropylene fiber reached 0.87 MPa and 0.85 MPa, respectively, when the fiber length was 12 mm and the content was 0.75 wt% and 1.00 wt%. Design Expert was used to analyze the experimental data to obtain the pattern of the effect of different fiber conditions on the strength of FLS-RM and optimal fiber conditions, and to establish the strength equation. The EDS results revealed that the red mud can be excited to generate an aluminosilicate gel filling in the skeleton under alkaline conditions. The results of the microscopic analysis indicated that the close bonding between the fibers and the matrix increased the friction and mechanical bite between the independent blocks and enhanced the strength of the specimens.

As an emerging environmentally friendly solid waste-based composite foam lightweight soil, saponified slag fly ash (SS-FA) foam lightweight soil has a wide range of application prospects in road engineering. In this paper, the dynamic characteristics of SS-FA foam light soil material were investigated. Dynamic triaxial tests under different cyclic loading conditions were designed to analyze the variation rules of dynamic elastic modulus and damping ratio. The results showed that the stress-strain curve of SS-FA foam lightweight soil can be divided into three stages: elastic stage, plateau stage, and stress yielding stage. Under cyclic dynamic load, with the increase of dynamic stress amplitude, the dynamic elastic modulus of 400-700 kg/m3 samples gradually increased to the maximum, reaching 235.24 MPa, 324.54 MPa, 356.45 MPa, 379.67 MPa, respectively. The damping ratio, on the other hand, shows a tendency to first decrease and then slowly increase to stabilize. The dynamic elastic modulus is positively correlated with density grade, confining pressure and loading frequency. The damping ratio decreases with the increase of density grade and loading frequency, and increases with the increase of confining pressure. The electron microscope test was designed and image processing and data statistics were carried out. Through the grey correlation analysis, the correlation degree between the microstructure parameters of SS-FA foamed lightweight soil and the macroscopic mechanical properties is basically above 0.6, indicating that the two have a significant correlation. A normalized prediction formula model between the dynamic elastic modulus of materials and the conditional parameters was established. The R2 of the linear fitting of the predicted value is 0.964, indicating that the prediction model has a high degree of fitting and a good prediction effect. The research results revealed the dynamic mechanical properties of foamed lightweight soil, and provided a reference for the application of SS-FA foamed lightweight soil in subgrade engineering.