Ongoing climate warming and increased human activities have led to significant permafrost degradation on the Qinghai-Tibet Plateau (QTP). Mapping the distribution of active layer thickness (ALT) can provide essential information for understanding this degradation. Over the past decade, InSAR (Interferometric synthetic aperture radar) technology has been utilized to estimate ALT based on remotely-sensed surface deformation information. However, these methods are generally limited by their ability to accurate extract seasonal deformation and model subsurface water content of active layer. In this paper, an ALT inversion method considering both seasonal deformation from InSAR and smoothly multilayer soil moisture from ERA5 is proposed. Firstly, we introduce a ground seasonal deformation extraction model combining RobustSTL and InSAR, and the deformation extraction accuracy by considering the deformation characteristics of permafrost are evaluated, proving the effectiveness of RobustSTL in extracting seasonal deformation of permafrost. Then, using ERA5 soil moisture products, a smoothed multilayer soil moisture model for ALT inversion is established. Finally, integrating the seasonal deformation and multilayer soil moisture, the ALT can be estimated. The proposed model is applied to the Yellow River source region (YRSR) with Sentinel-1A images acquired from 2017 to 2021, and the ALT retrieval accuracy is validated with measured data. Experimental results show that the vertical deformation rate of the study area generally ranges from -30 mm/year to 20 mm/year, with seasonal deformation amplitude ranging from 2 mm to 30 mm. The RobustSTL method has the highest accuracy in extracting seasonal deformation of permafrost, with an RMSE (root mean square error) of 0.69 mm, and is capable of capturing the freeze-thaw characteristics of the active layer. The estimated ALT of the YRSR ranges from 49 cm to 450 cm, with an average value of 145 cm. Compared to the measured data, the proposed method has an average error of 37.5 cm, which represents a 21 % improvement in accuracy over existing methods.

Accurate structural health monitoring (SHM) is crucial for ensuring safety and preventing catastrophic failures. However, conventional parameter identification methods often assume a fixed-base foundation, neglecting the significant influence of soil-structure interaction (SSI) on the dynamic response, leading to inaccurate damage assessments, especially under seismic loading. Therefore, we introduce a novel approach that explicitly incorporates SSI effects into parameter identification for frame structures, utilizing an optimized variational mode decomposition (VMD) technique. The core innovation is the application of the Subtraction Average-Based Optimizer (SABO) algorithm, coupled with permutation entropy as the fitness function, to optimize the critical VMD parameters. This SABO-VMD method was rigorously validated through a shaking table test on a 12-story frame structure on soft soil. Comparative analysis with EMD and conventional VMD demonstrated that SABO-VMD provides a superior time-frequency representation of the structural response, capturing non-stationary characteristics more effectively. A novel energy entropy index, derived from the SABO-VMD output with SSI, was developed for quantitative damage assessment. It revealed 8.1% lower degree of structural damage compared to the fixed-base assumption. The proposed SABO-VMD-based approach, by explicitly accounting for SSI, offers a substantial advancement in SHM of frame structures, leading to more reliable safety evaluations and improved seismic resilience.

The seismic effects of complex, deep, and inhomogeneous sites constitute a significant research topic. Utilizing geological borehole data from the Suzhou urban area, a refined 2D finite element model with nonuniform meshes of a stratigraphic crossing the Suzhou region was established. Within the ABAQUS/explicit framework, the spatial inhomogeneity of soils, including the spatial variation of S-wave velocity structures, was considered in detail. The nonlinear and hysteretic stress-strain relationship of soil was characterized using a non-Masing constitutive model. Ricker wavelets with varying peak times, peak frequencies (fp), and amplitudes were selected as input bedrock motions. The analysis revealed the spatial distribution characteristics of 2D nonlinear seismic effects on the surface of deep and complex sedimentary layers. The surface peak ground acceleration (PGA) amplification coefficients initially increased and then decreased as fp increases. The surface PGA amplification was most pronounced when the fp is close to the site fundamental frequency. Additionally, when fp = 0.1 Hz, the surface PGA amplification was found to depend solely on the level of bedrock seismic shaking, with amplification factors ranging from 1.20 to 1.40. Furthermore, the ensemble empirical mode decomposition components of seismic site responses can intuitively reveal the variations in time-frequency and time-energy characteristics of Ricker wavelets as they propagate upward from bedrock to surface.

Excessive bromine, iodine and dyes can damage soil structure and aquatic ecosystems. Therefore, capturing toxic bromine, iodine and dyes from nuclear fuel waste and organic waste liquid is crucial for protecting the environment and human health. In this study, a tridentate imide acid monomer was synthesized with various functional groups and structures, including carboxyl (-COOH), amide (-CONH), and imide rings, to construct a new type of hyper-crosslinked poly (amide-imide) (PAI1-PAI4). Subsequently, porous carbons (PAI1-900-PAI4900) were prepared, and urea was doped during the secondary carbonization process. The ammonia gas (NH3) and carbon dioxide (CO2) generated from the high-temperature decomposition of urea can be trapped by the porous structure of the carbon-based derivatives, and these gases then react with the carbon in the porous carbon and the N-H/C-H in the amide groups, thus resulting in carbon-based materials (PAI1-U-900-PAI4-U-900) with multiple nitrogen and oxygen Lewis basic sites (C-N/N-O/C--O/-OH) and a moderate porosity. These materials enhanced the interactions between the adsorbent and bromine, iodine, and anionic dyes, and exhibited selective adsorption effects for bromide and Congo red (CR).

Wood plays a vital role in the terrestrial carbon cycle, both sequestering and subsequently releasing carbon to the atmosphere via decomposition. Decomposition has largely been studied in fallen and standing deadwood; much less is known about decomposition occurring inside live trees due to hollowing by wood-feeding termites and microbial heart rot. Internal stem damage is difficult to measure, leaving many unresolved knowledge gaps. Little is known regarding the location and total amount of damage done by termites and microbes, as well as whether these decomposers act in concert or separately. Furthermore, tree species, wood density and stem size can influence fallen deadwood decomposition, but their role in living tree internal damage is largely unknown. We destructively harvested 63 trees, finding internal damage in 32. We intensively sampled the internal stem damage in these 32 to investigate the relative contributions of microbes and termites in a tropical savanna in Queensland, Australia. We tested if damage changed at different heights in the tree, quantified tree-level termite and microbial damage and examined if termite and microbial damage co-occurred. We also tested the influence of tree species, wood specific gravity and size on tree-level internal stem damage across four species. Termite and microbial damage were present in 45% and 33% of all trees, respectively. On average, termite damage reduced total tree biomass by 3.3% (maximum 28%, SD = 4.7%) and microbial damage by 1.8% (maximum 26%, SD = 5.3%). The amount of damage from both decomposers decreased with increasing heights up the tree. Termite and microbial damage co-occurrence was greater within trees than within individual cross samples, suggesting local competitive exclusion or niche partitioning by decomposers. Tree species was a better predictor of damage than either wood specific gravity or tree size. Half of the trees in our study had substantial internal stem damage, highlighting the considerable role that termites and microbes play in decomposing wood within living trees. Our findings unveil the previously concealed wood decomposition dynamics occurring inside trees, with implications for accurate carbon estimation across savanna ecosystems.Read the free Plain Language Summary for this article on the Journal blog.

Straw return is widely acknowledged as a crucial strategy for enhancing soil fertility and increasing crop yields. However, the continuous addition of straw, its slow decomposition, and retention can hinder crop growth. Therefore, it is essential to elucidate the characteristics of the crop straw decomposition. This study aims to explore the alterations in straw decomposition rates, as well as the content and structure of organic components, under the combined application of swine manure and corn straw in the broken skin yellow soil of black soil over time. The findings revealed that the straw decomposition rates in all treatments increased rapidly in the early stage, gradually slowed down and stabilized in the later stage. The decomposition rates of cellulose and hemicellulose were generally consistent with those of straw, while lignin decomposed more rapidly in the middle and later stages. Notably, the decomposition rate of straw and its components was significantly higher under the combined application of swine manure and biochar compared to other treatments, with decomposition rates of straw, cellulose, hemicellulose, and lignin recorded at: 66.16%, 63.38%, 61.16% and 47.96%, respectively, after 360 days. This treatment exhibited the most substantial damage to the apparent structure of corn straw over time, and it resulted in lower C/N ratios and the most pronounced decrease in the intensity of absorption peaks. Among all the treatments, the alkyl carbon/alkoxy carbon ratio was highest in the SCZ treatment, indicating that the addition of swine manure and biochar can significantly enhance straw decomposition. Correlation analysis revealed that the decomposition rates of straw, cellulose, hemicellulose, and lignin were significantly and positively correlated with the rates of alkyl carbon, aromatic carbon, and phenolic carbon in the organic functional groups of straw residues, and significantly negatively correlated with alkoxy carbon. The study suggested that the combined application of straw, swine manure and biochar in the field can effectively promote the decomposition of corn straw. Our findings provided insights into the efficient utilization of various exogenous conditioners, serving as a scientific basis for accelerating straw decomposition and enhancing nutrient utilization.

Viscous compression, the delayed slow compression of soils after loading, has emerged as a challenging process contributing to land subsidence in soft soil areas. Despite previous research on clay soils, there is still limited understanding of the processes and mechanisms of viscous compression of organic soils. As peat is more susceptible to viscous compression than clay, and the subsurface of subsiding deltas can contain substantial bodies of peat, understanding of processes, mechanisms and drivers is needed to predict the potential for and amount of viscous compression to occur and assess the effect of mitigation measures to delta subsidence. This study integrates findings from prior research on viscous compression behaviour of clay for a comprehensive comparison of the structural, geomechanical, chemical, and biological characteristics of clay and peat, to evaluate to what extent compression mechanisms in clay operate in a similar way in peat. The study focuses on mechanisms of viscous clay compression, which are: expulsion of micropore water, changes in the adsorbed water layer, and particle interactions. Our review establishes that these mechanisms also manifest in peat, albeit with varying contributions to the reorientation of peat fibres. Notably, the distinct pore structure and larger average pore diameters of peat result in water expulsion behaviour that is different from clay. Additionally, the negative electrical charge on clay mineral surfaces is stronger than that of peat fibre surfaces, influencing attraction or repulsion forces among particles and the adsorbed water. This study introduces decomposition of organic matter as an additional long-term control of subsidence. Decomposition weakens the peat structure and facilitates particle reorientation, which enhances the susceptibility to compression. On the other hand, when organic material is already decomposed, it shows lower compressibility compared to fibrous organic material.

Global climate change and permafrost degradation have significantly heightened the risk of geological hazards in high-altitude cold regions, resulting in severe casualties and property damage, particularly in the Qinghai-Tibet Plateau of China. To mitigate the risk of geological disasters, it is crucial to identify the primary disaster-inducing factors. Therefore, to address this issue more effectively, this study proposes a spatiotemporal-scale approach for detecting disaster-inducing factors and investigates the disaster-inducing factors of geological hazards in high-altitude cold regions, using the Kanchenjunga Basin as a case study. As the world's third-highest peak, Kanchenjunga is highly sensitive to climate fluctuations. This study first integrates the frost heave model and multitemporal interferometric synthetic aperture radar techniques to monitor ascending and descending track line-of-sight deformation of the frozen active layer in the study area. Subsequently, the surface parallel flow constrained model is employed to decompose the 3-D time-series deformation of geological hazards in the basin, with remote sensing imagery and field surveys used to identify a total of 94 disaster sites. In parallel, a database of potential conditioning factors is constructed by leveraging Google Earth Engine remote sensing inversion technology and relevant data provided by the China Geological Survey. Finally, by integrating monitoring results with a database of potential geological conditioning factors, the spatiotemporal-scale approach for detecting disaster-inducing factors proposed in this study is applied to investigate the disaster-inducing factors in the Kanchenjunga Basin. The research results highlight that surface temperature is the primary driving factor of geological hazards in the Kanchenjunga Basin. This research helps bridge the data gap in the region and offers critical support for local government decision-making in disaster prevention, risk assessment, and related areas.

Rainfall can alter the hydrothermal state of permafrost, subsequently affecting organic carbon decomposition and CO2 transport. However, the mechanisms by which rainfall influences organic carbon decomposition and carbon dioxide transport processes in permafrost remain unclear. In this study, a coupled permafrost water-heatvapor-carbon model, based on the surface energy-water balance theory, is employed to explore the effects of increased precipitation on permafrost moisture, temperature, organic carbon decomposition, and carbon dioxide transport through numerical simulations. The results are as follows: (1) with increased rainfall, surface latent heat flux rises while surface sensible heat flux declines, leading to a reduction in surface heat flux. The annual mean surface heat fluxes for the three precipitation conditions of no change in precipitation (zP = 0 mm), 50 mm increase in precipitation (zP = 50 mm) and 100 mm increase in precipitation (zP = 100 mm) are -0.1 W/m2, -0.2 W/m2 and -0.4 W/m2 respectively; and (2) as rainfall increases, soil moisture content increases significantly, but the impact of rainfall on soil moisture content diminishes with increasing soil depth; and (3) increased rainfall results in a decrease in soil carbon fluxes, soil organic matter decomposition rates, and CO2 concentrations. Compared to the case of constant precipitation, the surface carbon fluxes decreased by 0.04 mu mol center dot m-2s-1 and 0.08 mu mol center dot m-2s-1 under zP = 50 mm and zP = 100 mm, respectively. Additionally, the decomposition rate of soil organic matter at 10 cm depth decreased by 3.2 E-8 mol center dot m-2s-1 and 6.3 E-8 mol center dot m-2s-1, respectively, while the soil carbon concentration decreased by 3 mu mol/mol and 5 mu mol/mol, respectively.

Forest litter decomposition is vital for nutrient cycling and carbon turnover. To investigate their decomposition rate, we conducted a litter bag experiment in plantation forests (PF) and natural forests (NF) in a subtropical ecosystem. Our findings showed significant seasonal variation in litter mass loss (p < 0.0001) between the two sites, indicating seasonality as the main driver of decomposition. The decay rate constant (k) expressed in day(-)(1), reflecting the fraction of litter mass lost per day due to decomposition, reveals that NF has higher k value of 0.007 day(-)(1) than PF at 0.005 day(-)(1) , indicating faster decomposition in NF. This constant is essential for predicting litter breakdown duration, highlighting decomposition dynamics between sites, suggesting that even minimal distances between forest types can affect organic matter breakdown. In both sites, litter mass loss varied significantly from the initial to the final year (p < 0.001), with peak rates during the monsoon, followed by pre-monsoon and dry periods. Mixed litter in NF experienced a 99.94 % loss after 730 days, while PF, saw 97.80 % loss. Carbon, lignin, nitrogen, and potassium concentrations were higher during the monsoon and pre-monsoon seasons at both sites. Except for phosphorus in PF, all soil parameters positively correlated with mass loss, along with litter parameters C, N, P, K, and lignin (p < 0.001). Litter decomposition was higher in NF than PF, with significant seasonal effects (p < 0.0001), highlighting seasonality over litter mixture effects. Understanding climate variability and species diversity is essential for sustainable forest management amid ongoing anthropogenic land-use changes.