Glacier shrinkage, a notable consequence of climate change, is expected to intensify, particularly in high-elevation areas. While plant diversity and soil microbial communities have been studied, research on soil organic matter (SOM) and soil protein function dynamics in glacier forefields is limited. This limited understanding, especially regarding the link between microbial protein functions and biogeochemical functions, hampers our knowledge of soil-ecosystem processes along chronosequences. This study aims to elucidate the mechanistic relationships among soil bacterial protein functions, SOM decomposition, and environmental factors such as plant density and soil pH to advance understanding of the processes driving ecosystem succession in glacier forefields over time. Proteomic analysis showed that as ecosystems matured, the dominant protein functions transition from primarily managing cellular and physiological processes (biological controllers) to orchestrating broader ecological processes (ecosystem regulators) and increasingly include proteins involved in the degradation and utilization of OM. This shift was driven by plant density and pH, leading to increased ecosystem complexity and stability. Our confirmatory path analysis findings indicate that plant density is the main driver of soil process evolution, with plant colonization directly affecting pH, which in turn influenced nutrient metabolizing protein abundance, and SOM decomposition rate. Nutrient availability was primarily influenced by plant density, nutrient metabolizing proteins, and SOM decomposition, with SOM decomposition increasing with site age. These results underscore the critical role of plant colonization and pH in guiding soil ecosystem trajectories, revealing complex mechanisms and emphasizing the need for ongoing research to understand long-term ecosystem resilience and carbon sequestration.

Thaw hazards in high-latitude and glaciated regions are becoming increasingly frequent because of global climate warming and human activities, posing significant threats to infrastructure stability and environmental sustainability. However, despite these risks, comprehensive investigations of thaw-hazard susceptibility in permafrost regions remain limited. Here, this gap is addressed by a systematic and long-term investigation of thaw hazards in China's Qinghai Province as a representative permafrost area. A detailed inventory of 534 thawhazard sites was developed based on remote sensing, field verification, and surveys by a UAV, providing critical data for susceptibility analysis. Eleven environmental factors influencing thaw hazards were identified and analyzed using information gain and Shapley additive explanation. By using the random forest model, a susceptibility map was generated, categorizing the study area into five susceptibility classes: very low, low, moderate, high, and very high. The key influencing factors include precipitation, permafrost type, temperature change rate, and human activity. The results reveal that 17.5 % of the permafrost region within the study area is classified as high to very high susceptibility, concentrated primarily near critical infrastructure such as the Qinghai-Tibet Railway, potentially posing significant risks to its structural stability. The random forest model shows robust predictive capability, achieving an accuracy of 0.906 and an area under the receiver operating characteristic curve of 0.965. These findings underscore the critical role of advanced modeling in understanding the spatial distribution and drivers of thaw hazards, offering actionable insights for hazard mitigation and infrastructure protection in permafrost regions under a changing climate.

Objective Absorbing aerosols, particularly black carbon (BC), exerts significant influence on the Earth's radiation budget by modifying both the amount and vertical distribution of solar radiation. Their climatic effects are especially pronounced in regions characterized by concentrated fossil fuel activities, such as large-scale coal mining areas. However, the spatial and temporal variability of their microphysical and optical properties introduces considerable uncertainty into regional radiative forcing assessments. The Zhundong Coalfield, located in eastern Xinjiang, China, is one such region where BC emissions from coal extraction and associated industrial activity are persistent yet under-characterized from a radiative perspective. This study aims to construct a rapid estimation framework for aerosol radiative forcing (ARF) over this region by integrating multi-band satellite observations with physically based scattering and radiative transfer models. The primary goal is to evaluate how aerosol optical depth (AOD), single scattering albedo (SSA), and particle size influence shortwave ARF at the top of the atmosphere (TOA), bottom of the atmosphere (BOA), and within the atmospheric column (ATM), and how ultraviolet-band data enhances the reliability of this estimation. Methods The research adopts a modular approach comprising aerosol property inversion and radiative transfer modeling. The aerosol inversion is based on a Mie scattering model incorporating a core-shell structure assumption, where BC forms the absorbing core and is coated by non-absorbing substances such as sulfate and nitrate. Satellite-derived aerosol products are used to constrain the model: MODIS provides AOD and SSA at visible wavelengths, while OMI contributes ultraviolet (UV) -band SSA and AOD information. Two experimental configurations are established-one based solely on MODIS data, and another integrating both MODIS and OMI-to assess the role of UV spectral information in constraining aerosol characteristics. Following inversion, the retrieved aerosol size and optical parameters are used as input to the SBDART (Santa Barbara DISORT Atmospheric Radiative Transfer) model to simulate instantaneous ARF at TOA, BOA, and ATM under clear-sky conditions. Radiative forcing is calculated as the difference in net shortwave flux with and without aerosols. Multiple linear regression models are then constructed using different combinations of AOD, SSA, and core radius to quantify the relationship between these parameters and simulated ARF. Regression performance is evaluated using R (2) and RMSE statistics across both single-source and combined-source scenarios. Results and Discussions First, the inclusion of OMI UV-band data significantly improves the inversion accuracy of aerosol particle size characteristics. When only MODIS data are used, the retrieved BC core sizes are relatively narrow, mostly centered around 120 nm, and the shell diameters exhibit limited variation. However, when OMI UV observations are incorporated, the core size distribution broadens, capturing particles ranging from 90 to 160 nm, while the shell diameter spans a wider interval of 300?700 nm. This improved resolution stems from the stronger sensitivity of UVs to absorption by fine-mode particles, which enhances the model's ability to distinguish subtle differences in particle morphology. The resulting total particle size distributions-core plus shell-are more consistent with reported field measurements in coal-intensive regions. These results confirm that UV data not only improve inversion detail but also reduce the uncertainty in the wavelength in the representation of aerosol mixing states. Second, the quantitative relationship between optical parameters and ARF demonstrates clear physical consistency across TOA, BOA, and ATM layers. In both MODIS-only and MODIS-OMI configurations, AOD exhibits a strong negative correlation with TOA and BOA radiative forcing (R=-0.77 and -0.78, respectively), indicating a cooling effect due to enhanced scattering and absorption of incoming solar radiation. SSA also shows a strong negative correlation with TOA and BOA forcing (R=-0.78 and -0.62, respectively), suggesting that as the aerosol becomes more scattering-dominant, its net radiative cooling effect intensifies. Conversely, AOD shows weaker but positive correlations with ATM forcing (R=0.43), suggesting an increase in atmospheric heating when aerosol loading or absorption increases. This pattern aligns with physical expectations: absorbing aerosols like BC trap energy in the atmosphere, contributing to vertical energy redistribution. The analysis confirms that SSA has a stronger explanatory power than AOD, emphasizing its role as a key driver of radiative uncertainty forcing. Third, regression model performance improves markedly with the inclusion of SSA and core size as input parameters. Under the MODIS-only scenario, models using AOD alone yield limited explanatory power, withR (2) values of 0.59 (TOA), 0.61 (BOA), and 0.18 (ATM). Adding SSA improves the fits substantially, increasingR (2) to 0.78 (TOA) and 0.67 (BOA), and to 0.21 in the ATM. Incorporating core radius into the model yields additional gains, raisingR (2) in the ATM layer to 0.23 and lowering RMSE values across all layers. In the MODIS-OMI fusion scenario, even though the number of valid observation days decreases significantly (eg, from 2589 to 954 days at the Wucaiwan site), model performance continues to improve. For example,R (2) for ATM forcing increases from 0.18 to 0.29, and RMSE decreases from 2.04 to 1.85. These results suggest that high-spectral-resolution UV data provide greater constraint on aerosol absorption properties, thereby enabling more physically consistent radiative forcing estimates, even with reduced samples. This finding supports the robustness of UV-enhanced satellite inversion strategies in regional ARF modeling. Conclusions This study presents a data-model integration framework for estimating ARF over coal mining regions using multi-source satellite observations and physically based scattering and radiative transfer models. The combination of MODIS visible and OMI ultraviolet aerosol products improves the inversion of absorbing aerosol particle size distributions and enhances the retrieval of SSA, especially under complex mixing conditions. The constructed regression models reveal that SSA exerts a greater influence on radiative forcing than AOD, and that including particle size parameters further strengthens model reliability. Despite a reduction in observational frequency due to OMI's narrower sampling, the incorporation of UV-band information leads to consistently improved model performance across all atmospheric layers, particularly in the atmospheric column. These results highlight the critical role of spectral diversity in satellite remote sensing for accurately characterizing the radiative impacts of absorbing aerosols, and demonstrate the feasibility of applying such approaches to high-emission, data-scarce environments like the Zhundong Coalfield.

In this study, the effect of near-field and far-field ground motions on the seismic response of the soil pile system is investigated. The forward directivity effect, which includes a large velocity pulse at the beginning of the velocity time history of the ground motion is the most damaging phenomenon observed in near-field ground motions. To investigate the effect of near-field and far-field ground motions on the seismic response of a soil-pile system, a three-dimensional model consisting of the two-layer soil, liquefiable sand layer over dense sand, and the pile is utilized. Modeling is conducted in FLAC 3D software. The P2P Sand constitutive model is selected for sandy soil. Three fault-normal near-field and three far-field ground motion records were applied to the model. The numerical results show that near field velocity pulses have a considerable effect on the system behavior and sudden huge displacement demands were observed. Also, during the near-field ground motions, the exceeded pore water pressure coefficient (Ru) increases so that liquefaction occurs in the upper loose sand layer. Due to the pulse-like ground motions, a pulse-like relative displacement is created in response to the pile. Meanwhile the relative displacement response of the pile is entirely different due to the energy distribution during the far-field ground motions.

Ensuring the accuracy of free-field inversion is crucial in determining seismic excitation for soil-structure interaction (SSI) systems. Due to the spherical and cylindrical diffusion properties of body waves and surface waves, the near-fault zone presents distinct free-field responses compared to the far-fault zone. Consequently, existing far-fault free-field inversion techniques are insufficient for providing accurate seismic excitation for SSI systems within the near-fault zone. To address this limitation, a tailored near-fault free-field inversion method based on a multi-objective optimization algorithm is proposed in this study. The proposed method establishes an inversion framework for both spherical body waves and cylindrical surface waves and then transforms the overdetermined problem in inversion process into an optimization problem. Within the multi-objective optimization model, objective functions are formulated by minimizing the three-component waveform differences between the observation point and the delayed reference point. Additionally, constraint conditions are determined based on the attenuation property of propagating seismic waves. The accuracy of the proposed method is then verified through near-fault wave motion characteristics and validated against real downhole recordings. Finally, the application of the proposed method is investigated, with emphasis on examining the impulsive property of underground motions and analyzing the seismic responses of SSI systems. The results show that the proposed method refines the theoretical framework of near-fault inversion and accurately restores the free-field characteristics, particularly the impulsive features of near-fault motions, thereby providing reliable excitation for seismic response assessments of SSI systems.

A utility tunnel is an infrastructure that consolidates multiple municipal pipeline systems into a shared underground passage. As long linear structures inevitably cross different soils, this paper aims to accurately assess the seismic damage to a shallow-buried utility tunnel in a non-homogeneous zone by employing a viscous-spring artificial boundary and deriving the corresponding nodal force equations. The three-dimensional model of the utility tunnel-soil system is established using finite element software, and a plug-in is developed to simulate the three-dimensional oblique incidence of SV waves with a horizontal non-homogeneous field. In this study, the maximum interstory displacement angle of the utility tunnel is used as the damage indicator. Analysis of structural vulnerability based on IDA method using PGA as an indicator of seismic wave intensity, which considers the angle of oblique incidence of SV waves, the type of seismic waves, and the influence of the nonhomogeneous field on the seismic performance of the utility tunnel. The results indicate that the failure probability of the utility tunnel in different soil types increases with the incident angle and PGA. Additionally, the failure probability under the pulse wave is higher than that under the non-pulse wave; Particular attention is given to the states of severe damage (LS) and collapse (CP), particularly when the angle of incidence is 30 degrees and the PGA exceeds 0.6g, conditions under which the probability of failure is higher. Additionally, the failure probability of the non-homogeneous zone is greater than that of sand and clay; the maximum interlayer displacement angle increases with the incident angle, accompanied by greater PGA dispersion, indicating the seismic wave intensity. The maximum inter-layer displacement angle increases with the incident angle, and the dispersion of the seismic wave intensity indicator (PGA) becomes greater. This paper proposes vulnerability curves for different working conditions, which can serve as a reference for the seismic design of underground structures.

Iron pipes connected by bell-spigot joints are utilized in buried pipeline systems for urban water and gas supply networks. The joints are the weak points of buried iron pipelines, which are particularly vulnerable to damage from excessive axial opening during seismic motion. The axial joint opening, resulting from the relative soil displacement surrounding the pipeline, is an important indicator for the seismic response of buried iron pipelines. The spatial variability of soil properties has a significant influence on the seismic response of the site soil, which subsequently affects the seismic response of the buried iron pipeline. In this study, two-dimensional finite element models of a generic site with explicit consideration of random soil properties and random mechanical properties of pipeline joints were established to investigate the seismic response of the site soil and the buried pipeline, respectively. The numerical results show that with consideration of the spatial variability of soil properties, the maximum axial opening of pipeline joints increases by at least 61.7 %, compared to the deterministic case. Moreover, in the case considering the variability of pipeline-soil interactions and joint resistance, the spatial variability of soil properties remains the dominant factor influencing the seismic response of buried iron pipelines.

The entrance of permafrost tunnels in cold regions is particularly vulnerable to frost damage caused by complex thermal-hydro-mechanical (THM) interactions in unsaturated frozen soils. The effects of temperaturedependent volumetric strain variations across different stratum materials on heat and moisture transport are often neglected in existing THM coupling models. In this study, a novel THM coupled model for unsaturated frozen soil integrating volumetric strain correction is proposed, which addresses bidirectional interactions between thermal-hydraulic processes and mechanical responses. The model was validated through laboratory experiments and subsequently applied to the analysis of the Yuximolegai Tunnel. The results indicate that distinct layered ice-water distribution patterns are formed in shallow permafrost under freeze-thaw cycles, driven by bidirectional freezing and water migration. Critical mechanical responses were observed, including a shift in maximum principal stress from the invert (1.40 MPa, frozen state) to the crown (5.76 MPa, thawed state), and periodic lining displacements (crown > invert > sidewalls). Frost damage risks are further quantified by the spatial-temporal zoning of ice-water content-sensitive regions. These findings advance unsaturated frozen soil modeling and provide theoretical guidance for frost-resistant tunnel design in cold regions.

Destructive earthquakes result in significant damage to a wide variety of buildings. The resulting damage data is crucial for evaluating the seismic resilience of buildings in the region and investigating urban resilience. Field damage data from 38 destructive earthquakes in Sichuan Province were collected, classified, and statistically analysed according to the criteria of the latest Chinese seismic intensity scale for evaluating building damage levels. Meanwhile, the construction features and seismic damage characteristics of these buildings were also examined. These results facilitated the development of a damage probability matrix (DPM) for various building typologies, such as raw-soil structures (RSSs), stone-wood structures (SWSs), brick-wood structures (BWSs), masonry structures (MSs), and reinforced concrete frame structures (RCFSs). The damage ratio was employed as the parameter for vulnerability assessment, and a comprehensive analysis was performed on the differences in damage levels among all buildings in various intensity zones and time frames. Furthermore, the DPMs were further refined by simulating additional data from high-intensity zones to more accurately represent the seismic resistance of existing buildings in multiple-intensity zones. Vulnerability prediction models were developed using the biphasic Hill model, which elucidates varying damage trends across different construction typologies. Finally, empirical fragility curves were established based on horizontal peak ground acceleration (PGA) as the damage indicator. This study is based on multiple seismic damage samples from various regions, accounting for the influence of earthquake age. The DPMs, representative of the regional characteristics of Sichuan Province, were developed for different building types. Furthermore, multidimensional vulnerability regression models and empirical fragility curves are established based on these DPMs. These models and curves provide a theoretical foundation for seismic disaster scenario simulations and the seismic capacity analysis of buildings within Sichuan Province.

Rapid urbanization and industrial growth in China have increased brownfield site reclamation, the sustainable remediation for urban transformation and enhancing ecosystem services. However, traditional brownfield safety assessment strategies impose unnecessary costs since excessive remediation. Herein, a comprehensive system integrated by soil self-purification, potential ecological risks and human health risks is developed to investigate the safety of brownfield sites. Indices, including soil environmental loading capacity (SELC), and Nemerow integrated pollution index (NIPI), were introduced to assess heavy metals (HMs) pollution. Results show that 72.05% of the sites are identified as moderate pollution, where Cd, As, and Cr(VI) are at heavy pollution, incorporating soil self-purification. The average values of potential ecological risk (PERI) reached 6615.00, posing a significant damage to the local ecosystem, and Cd was identified as main ecological hazards in the study sites. Furthermore, the health risk assessment shows that children's health risks are higher than that of adults, with non-carcinogenic risk to children (2.60) and adults (0.41), and carcinogenic risk to children (2.30 x 10-3) and adults (1.12 x 10-4). Utilizing a multi-index decision-making approach, it is determined that 19.30% of the site exhibit high-risk values, between concentration screening (11.40%) and risk screening (83.30%) base on single-indices. The study sheds light on the comprehensive assessment of brownfield site safety.