Sustainability

Replacing conventional chemical binders with natural polymers in geotechnically treated soil allows for the creation of more sustainable materials with both valuable ecological and mechanical properties. Xanthan gum and sodium alginate are natural polymers with excellent binding properties and water retention, which can help reduce carbon emissions. However, there is a lack of research on how to achieve optimal performance through the rational formulation of different biopolymers. This study investigates the use of these two natural biopolymers as binders (xanthan gum and sodium alginate) in slope-protection habitats treated with soil optimised using response surface methodology (RSM) within Design-Expert analysis software. The effects of xanthan gum concentration, sodium alginate concentration, and time, as well as their interactions on the properties of treated soil, ryegrass growth, and soil greenhouse gas emissions were evaluated, resulting in an optimized substrate formulation that balances good geotechnical properties with low environmental impact. Pot cultivation trials indicated that cohesion (c) and internal friction angle (φ) increased linearly with rising xanthan gum and sodium alginate concentrations, while the number of ryegrass plants (N_p) and root area ratio (RAR) decreased linearly with increasing binder concentration. Both CO₂ and CH₄ fluxes increased with rising binder concentrations. An analysis of variance (ANOVA) revealed that xanthan gum concentration had a stronger promoting effect on c and φ and a stronger inhibiting effect on N_p and RAR than sodium alginate. In contrast, sodium alginate concentration exhibited a stronger inhibitory effect on CO₂ and CH₄ fluxes. Through comprehensive optimization of geotechnical properties, vegetation growth, and greenhouse gas emissions, the optimal formulation was determined to be 0.885% for xanthan gum and 0.791% for alginate. The optimized composition resulted in increases of 38.6% and 19.1% for c and φ, respectively, while N_p and RAR increased by 7.7% and 15.0%, respectively. CO₂ and CH₄ fluxes decreased by 61.6% and 65.2%, respectively. This study contributes to advancing the sustainability of geotechnical treatments to favour vegetation regrowth. However, these materials will need to be further tested under field conditions to verify their effectiveness and duration.

In recent years, there has been a significant negative impact on the sustainability of supply chains for the delivery of small batch cargo, caused by crisis situations. Therefore, it is important to develop a modern methodology to reduce uncertainty in the delivery of small batch cargo, especially when considering a flexible inventory management system. This study proposes an integrated approach to inventory management, consisting of three elements: an updated ABC-XYZ structure of inventory formation analysis with criteria that determine stability; an additive mathematical model for calculating inventory management costs; and the development of a regression model for operational forecasting of inventory management costs, based on the number of end customers, unit cost and batch size. A comparison of regressions showed the advantage of the power model over the linear one. The main advantage of the study is the proposed mathematical and regression models for the operational calculation of inventory management costs, considering the uncertainty factors that determine the sustainability of the supply chain. This approach will be of interest to trading enterprises, allowing them to make flexible decisions in inventory management in the event of various disruptions in small batch cargo supply chains.

With increasing worldwide attention to green and sustainable energy, thermal infrared remote sensing technology has gained significant popularity for detecting geothermal anomalies, as it can overcome the limitations of traditional ground surveys. This study explores the potential application of thermal infrared images in geothermal exploration within the Datong Basin. We mainly utilized Landsat-8 images to obtain the actual land surface temperature (LST), hydrothermal alteration, and linear structures of the Datong Basin. Radiative transfer equation algorithm (RTE), principal component analysis (PCA), and interactive interpretation method were applied in this study. The results show that LST retrieval through the RTE method accurately reveals geothermal anomalies in the Datong Basin. Five areas with distinct high-LST values were identified as geothermal anomaly zones based on field investigation, including Xiejiatun, Gushancun, Taipingpu, Shuitongsi, and Wenjiayao–Yuanjialiang. Effective estimation of hydrothermal alteration zones (dominated by clays, OH⁻/H₂O, and carbonates) in the basin was achieved using the PCA method and band combinations. In total, 394 linear structures were obtained through interactive interpretation, including 45 concealed structures. All of these linear structures were associated with deep-seated faults. The basin’s primary controlling structures are the Yunmen Mountain piedmont fault (F1-1) and the northern margin of Xiong’er Mountain faults (F1-2 and F1-3), with F1-1 and F1-3 playing a key role in regional thermal regulation. The high-LST premium geothermal target zones of Shuitongsi and Gushancun were identified based on remote sensing interpretations and geothermal geological conditions. Furthermore, strong consistency was verified between the remote sensing predictions and four deep drilling temperature field measurements. This study confirms that remote sensing is an effective approach for geothermal potential identification, providing a scientific basis for future sustainable resource exploration in other regions.