Climate change is reshaping the risk landscape for natural gas pipelines, with landslides emerging as a major driver of technological accidents triggered by natural hazards (Natech events). Conventional Natech risk models rarely incorporate climate-sensitive parameters such as groundwater levels and soil moisture, limiting their capacity to capture evolving threats. This study develops a probabilistic model that explicitly links climate-driven landslide susceptibility to pipeline vulnerability, providing a quantitative basis for assessing pipeline failure probability under different emission projection scenarios. Using Monte Carlo simulations across five regions in China, the results show that under high-emission pathways (SSP5-8.5), pipeline failure probability in summer increases dramatically. For example, from 0.320 to 0.943 in Xinjiang, 0.112 to 0.220 in Sichuan, and 0.087 to 0.188 in Hainan. In cold regions, winter failure probability more than doubles, rising from 0.206 to 0.501 in Heilongjiang and from 0.235 to 0.488 in Beijing. These shifts reveal an overall increase in risk, intensification of seasonal contrasts, and, in some areas, a reconfiguration of high-risk periods. Sensitivity analysis highlights groundwater levels and soil moisture as the dominant drivers, with regional differences shaped by precipitation regimes, permafrost thaw, and typhoon impacts. Building on these insights, this study proposes an AI-based condition-monitoring framework that integrates real-time climate and geotechnical data to support adaptive early warning and safety management.

Tidal wetlands provide critical ecosystem functions for coastal communities including flood protection, water filtration, carbon sequestration and aquatic nursery habitat. However, New York City's salt marshes, including our study site at Pelham Bay Park's Turtle Cove, are rapidly disappearing due to accelerating relative sea-level (RSL) rise and coastal development. Field research, mapping and satellite imagery reveal significant loss of this similar to 10 hectare (ha) wetland, as perturbations from human activity prevent marsh landward migration, impede tidal flows and threaten marsh survival. We extracted three sediment cores and conducted 20 m transects across a gradient of disturbed marsh areas. We present the analyses of land-use change, X-ray fluorescence (XRF), loss on ignition (LOI), stable carbon isotopes (delta 13C), foraminifera, and accelerator mass spectrometry (AMS) radiocarbon dating of terrestrial macrofossils to examine the past and to inform future conditions for this rapidly eroding wetland. Moreover, we reconstruct sea level over a millennium to analyze changes in marsh plant communities in response to RSL rise and coastal development. We found that between 1974 and 2018 CE, similar to 65% of marsh disappeared at a rate of 1.5% yr-1 or 800 m2 yr-1. The marsh loss coincided with increasing RSL rates of 3.5 mm yr-1 from 1958-1975 CE to 6.7 mm yr-1 from 1999-2024 CE. Meanwhile, developed areas expanded 568 m2 yr-1 from 1985-2023 CE, replacing wetland areas and disrupting hydrologic processes with hardened shorelines. Marsh loss resulted in the release of soil organic carbon stored over many centuries and a concerning amount of lead (Pb) into Long Island Sound, presenting risks to public health and wildlife. Culvert assessments demonstrated that tidal restriction by built structures contributed to rising tide levels comparable to RSL rise over the past century, which likely exacerbated marsh erosion. Lastly, tidal prism reductions caused enough accumulation of heavy metals to significantly alter peat chemical composition for a century. This study improves our understanding of compounded stressors that prevent the capacity of salt marshes to with stand anthropogenic impacts. Ultimately, our findings inform an adaptive management of these threatened ecosystems in their struggle to keep pace with climate change and urbanization.

The present study performed classification global aerosols based on particle linear depolarization ratio (PLDR) and single scattering albedo (SSA) provided from AErosol RObotic NETwork (AERONET) Version 3.0 and Level 2.0 inversion products of 171 AERONET sites located in six continents. Current methodology could distinguish effectively between dust and non-dust aerosols using PLDR and SSA. These selected sites include dominant aerosol types such as, pure dust (PD), dust dominated mixture (DDM), pollution dominated mixture (PDM), very weakly absorbing (VWA), strongly absorbing (SA), moderately absorbing(MA), and weakly absorbing (WA). Biomass-burning aerosols which are associated with black carbon are assigned as combinations of WA, MA and SA. The key important findings show the sites in the Northern African region are predominantly influenced by PD, while south Asian sites are characterized by DDM as well as mixture of dust and pollution aerosols. Urban and industrialized regions located in Europe and North American sites are characterized by VWA, WA, and MA aerosols. Tropical regions, including South America, South-east-Asia and southern African sites which prone to forest and biomass-burning, are dominated by SA aerosols. The study further examined the impacts by radiative forcing for different aerosol types. Among the aerosol types, SA and VWA contribute with the highest (30.14 +/- 8.04 Wm-2) and lowest (7.83 +/- 4.12 Wm-2) atmospheric forcing, respectively. Consequently, atmospheric heating rates are found to be highest by SA (0.85 K day-1) and lowest by VWA aerosols (0.22 Kday-1). The current study provides a comprehensive report on aerosol optical, micro-physical and radiative properties for different aerosol types across six continents.

Amidst global scarcity, preventing pipeline failures in water distribution systems is crucial for maintaining a clean supply while conserving water resources. Numerous studies have modelled water pipeline deterioration; however, existing literature does not correctly understand the failure time prediction for individual water pipelines. Existing time-to-failure prediction models rely on available data, failing to provide insight into factors affecting a pipeline's remaining age until a break or leak occurs. The study systematically reviews factors influencing time-to-failure, prioritizes them using a magnitude-based fuzzy analytical hierarchy process, and compares results with expert opinion using an in-person Delphi survey. The final pipe-related prioritized failure factors include pipe geometry, material type, operating pressure, pipe age, failure history, pipeline installation, internal pressure, earth and traffic loads. The prioritized environment-related factors include soil properties, water quality, extreme weather events, temperature, and precipitation. Overall, this prioritization can assist practitioners and researchers in selecting features for time-based deterioration modelling. Effective time-to-failure deterioration modelling of water pipelines can create a more sustainable water infrastructure management protocol, enhancing decision-making for repair and rehabilitation. Such a system can significantly reduce non-revenue water and mitigate the socio-environmental impacts of pipeline ageing and damage.

Reclaimed coastal areas are highly susceptible to uneven subsidence caused by the consolidation of soft marine deposits, which can induce differential settlement, structural deterioration, and systemic risks to urban infrastructure. Further, engineering activities, such as construction and loadings, exacerbate subsidence, impacting infrastructure stability. Therefore, monitoring the integrity and vulnerability of linear urban infrastructure after construction on reclaimed land is critical for understanding settlement dynamics, ensuring safe and reliable operation and minimizing cascading hazards. Subsequently, in the present study, to monitor deformation of the linear infrastructure constructed over decades-old reclaimed land in Mokpo city, South Korea (where 70% of urban and port infrastructure is built on reclaimed land), we analyzed 79 Sentinel-1A SLC ascending-orbit datasets (2017-2023) using the Persistent Scatterer Interferometry (PSInSAR) technique to quantify vertical land motion (VLM). Results reveal settlement rates ranging from -12.36 to 4.44 mm/year, with an average of -1.50 mm/year across 1869 persistent scatterers located along major roads and railways. To interpret the underlying causes of this deformation, Casagrande plasticity analysis of subsurface materials revealed that deep marine clays beneath the reclaimed zones have low permeability and high compressibility, leading to slow pore-pressure dissipation and prolonged consolidation under sustained loading. This geotechnical behavior accounts for the persistent and spatially variable subsidence observed through PSInSAR. Spatial pattern analysis using Anselin Local Moran's I further identified statistically significant clusters and outliers of VLM, delineating critical infrastructure segments where concentrated settlement poses heightened risks to transportation stability. A hyperbolic settlement model was also applied to anticipate nonlinear consolidation trends at vulnerable sites, predicting persistent subsidence through 2030. Proxy-based validation, integrating long-term groundwater variations, lithostratigraphy, effective shear-wave velocity (Vs30), and geomorphological conditions, exhibited the reliability of the InSAR-derived deformation fields. The findings highlight that Mokpo's decades-old reclamation fills remain geotechnically unstable, highlighting the urgent need for proactive monitoring, targeted soil improvement, structural reinforcement, and integrated InSAR-GNSS monitoring frameworks to ensure the structural integrity of road and railway infrastructure and to support sustainable urban development in reclaimed coastal cities worldwide.

Buried pipelines are essential for the safe and efficient transportation of energy products such as oil, gas, and various chemical fluids. However, these pipelines are highly vulnerable to ground movements caused by geohazards such as seismic faults, landslide, liquefaction-induced lateral spreading, and soil creep, which can result in potential pipeline failures such as leaks or explosions. Response prediction of buried pipelines under such movements is critical for ensuring structural integrity, mitigating environmental risks, and avoiding costly disruptions. As such, this study adopts a Physics-Informed Neural Networks (PINNs) approach, integrated with a transfer learning technique, to predict structural response (e.g., strain) of both unreinforced and reinforced steel pipes subjected to Permanent Ground Displacement (PGD). The PINN method offers a meshless, simulation-free alternative to traditional numerical methods such as Finite Element Method (FEM) and Finite Difference Method (FDM), while eliminating the need for training data, unlike conventional machine learning approaches. The analyses can provide useful information for in-service pipe integrity assessment and reinforcement, if needed. The accuracy of the predicted results is verified against Finite Element (FE) and Finite Difference (FD) methods, showcasing the capability of PINNs in accurately predicting displacement and strain fields in pipelines under geohazard-induced ground movement.

This study investigates the microhardness and geometric degradation mechanisms of interfacial transition zones (ITZs) in recycled aggregate concrete (RAC) exposed to saline soil attack, focusing on the influence of supplementary cementitious materials (SCMs). Ten RAC mixtures incorporating fly ash (FA), granulated blast furnace slag (GBFS), silica fume (SF), and metakaolin (MK) at 10 %, 15 %, and 20 % replacement ratios were subjected to 180 dry-wet cycles in a 7.5 %MgSO4-7.5 %Na2SO4-5 %NaCl solution. Key results reveal that ITZ's microhardness and geometric degradation decreases with exposure depth but intensifies with prolonged dry-wet cycles. The FAGBFS synergistically enhances ITZ microhardness while minimizing geometric deterioration, with ITZ's width and porosity reduced to 67.6-69.0 mu m and 25.83 %, respectively. In contrast, FA-SF and FA-MK exacerbate microhardness degradation, increasing porosity and amplifying microcrack coalescence. FA-GBFS mitigates the diffusion-leaching of aggressive/original ions and suppresses the formation of corrosion products, thereby inhibiting the initiation and propagation of microcracks. In contrast, FA-SF and FA-MK promote the formation of ettringite/gypsum and crystallization bloedite/glauberite, which facilitates the formation of trunk-limb-twig cracks.

Subsea pipelines in Arctic environments face the risk of damage from ice gouging, where drifting ice keels scour the seabed. To ensure pipeline integrity, burial using methods like ploughs, mechanical trenchers, jetting, or hydraulic dredging is the conventional protection method. Each method has capabilities and limitations, resulting in different trench profiles and backfill characteristics. This study investigates the influence of these trenching methods and their associated trench geometries on pipeline response and seabed failure mechanisms during ice gouging events. Using advanced large deformation finite element (LDFE) analyses with a Coupled Eulerian-Lagrangian (CEL) algorithm, the complex soil behavior, including strain-rate dependency and strainsoftening effects, is modeled. The simulations explicitly incorporate the pipeline, enabling a detailed analysis of its behavior under ice gouging loads. The simulations analyze subgouge soil displacement, pipeline displacement, strains, and ovalization. The findings reveal a direct correlation between increasing trench wall angle and width and the intensification of the backfill removal mechanism. Trench geometry significantly influences the pipeline's horizontal and vertical displacement, while axial displacement and ovalization are less affected. This study emphasizes the crucial role of trenching technique selection and trench shape design in mitigating the risks of ice gouging, highlighting the value of numerical modeling in optimizing pipeline protection strategies in these challenging environments.

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 foundation conditions of piers for multi-span long-distance heavy-haul railway bridges inevitably vary at different locations, which may lead to non-uniform ground motions at each pier position, potentially causing adverse effects on the bridge's seismic response. To investigate the seismic response of bridges and the running safety of heavy-haul trains as they cross the bridge during an earthquake, a three-dimensional heavy-haul railway train-track-bridge (HRTTB) coupled system model was developed using ANSYS/LS-DYNA. This model incorporates the nonlinear behavior of critical components such as bearings, lateral restrainers, piers, and wheel-rail contact interactions, and it has been validated against field-measured data to ensure reliable dynamics parameters for seismic analysis. A multi-span simply supported girder bridge from a heavy-haul railway (HHR) was employed as a case study, in which a spatially correlated non-stationary ground motion field was generated based on spectral representation harmonic theory. Comparative analyses of the seismic responses under spatially varying ground motions (SVGM) and uniform seismic excitation conditions were performed for the coupled system. The results indicate that the presence of heavy-haul trains prolongs the natural period of the HRTTB system, thereby appreciably altering its seismic response. At lower apparent wave velocities, more piers exhibit a low-response state, and some pier bases enter the elastic-plastic stage under local site effects. Compared with the piers, the bearings show higher sensitivity to seismic inputs; fixed bearings experience damage when subjected to traveling wave effects and local site effects, which is subsequently followed by the failure of lateral restrainers. Train running safety is markedly reduced when crossing local soft soil site conditions. The conclusions drawn from this study can be applied in the seismic design and running safety assessment of HHR bridge systems under SVGM.