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.

This study presents the first high-resolution Regional Climate Model 5 (RegCM5) analysis of the unprecedented May-June 2024 heatwave in India, evaluating the role of absorbing aerosols-black carbon (BC) and dust-in amplifying extreme heat. Heatwaves have a severe impact on health, mortality, and agriculture, with absorbing aerosols exacerbating warming. MERRA-2 Aerosol Optical Depth (AOD) anomalies show that BC peaked at +0.027 in May, weakening in June, while dust remained higher (up to +0.36), intensifying over the Indo-Gangetic Plain (IGP) and northwestern India. RegCM5 simulations, validated against India Meteorological Department (IMD) observational data, indicate that these aerosols amplified surface temperature anomalies, with BC-induced warming exceeding +4 degrees C in northern India during May, while dust produced stronger anomalies, surpassing +5 degrees C in the IGP and Rajasthan in June. BC-induced warming was vertically distributed and more pronounced under clear skies, whereas dust-induced warming was surface-concentrated and persisted longer in regions with higher dust concentrations. Both aerosols increased net shortwave radiation (SWR; >300 W m(-2) for BC, similar to 270 W m(-2) for dust) and upward longwave radiation (ULR; >130 W m(-2)), inducing surface energy imbalances. This radiative forcing caused lower-tropospheric warming (up to +3 degrees C at 925 hPa for BC and 850 hPa for dust) and humidity deficits (-0.009 kg/kg), which stabilised the atmosphere, suppressed convection, and delayed monsoon onset. These findings highlight aerosol-radiation interactions as critical drivers of heatwave onset and persistence, emphasizing the need for their integration into regional climate models and early warning systems.

Widespread dieback of natural Mongolian pine (Pinus sylvestris var. mongolica) forests in Hulunbuir sandy land since 2018 has raised concerns about their sustainability in afforestation programs. We hypothesized that this dieback is driven by two interrelated mechanisms: (1) anthropogenic fire suppression disrupting natural fire regime, and (2) climate change-induced winter warming reducing snow cover duration and depth. To test these, we quantified dieback using Green Normalized Difference Vegetation Index (GNDVI) across stands with varying fire histories via UAV-based multispectral imagery, alongside long-term climatic observations (1960-2024) of temperature, precipitation, and snow dynamics from meteorological stations combined with remote sensing datasets. Results showed that an abrupt change point in 2018 for both annual precipitation and mean temperature was identified, coinciding with dieback. Significant negative linear relationship between GNDVI (forest health) and last fire interval indicated prolonged fire exclusion exacerbating dieback, possibly via pathogen/pest accumulation. Winter temperature rose significantly during 1960-2023, with notable acceleration following abrupt change point in 1987. Concurrently, winters during 2018-2023 exhibited pronounced warming, with snow cover duration reduced by 23 days and snow depth diminished by 7.6 cm. These conditions reduced snowmelt -derived soil moisture (critical water source) recharge in early spring, exacerbating drought stress during critical growth periods and predisposing trees to pest and disease infestations. Our results support both hypotheses, demonstrating that dieback is synergistically driven by fire regime alteration and climate-mediated snowpack reductions. Converting pure pine forests into mixed pine-broadleaf forests via differentiated water sources was proposed to restore ecological resilience in sandy ecosystems.

Against the backdrop of global warming, the increasing spatiotemporal variability in precipitation patterns has intensified the frequency and risk of dry-wet abrupt alternation (DWAA) events in semi-arid regions. This study investigates the Hailar River Basin in northern China (1980-2019) and develops the Soil Moisture Concentration Index (SMCI) using daily soil moisture (SM) data simulated by the VIC hydrological model. A high-resolution temporal framework is introduced to detect DWAA events and evaluate the impact of precipitation pattern variations on dry-wet transitions in the basin. The results indicate: (1) Annual precipitation in the basin has significantly increased (0.47 mm y(-1) in the south, P < 0.05), while precipitation intensity follows a gradient pattern, increasing in the upstream (3.65 mm d1 y1) and decreasing in the downstream (-2.34 mm y(-1)). Additionally, the number of dry days and short-duration, high-intensity precipitation events has risen; (2) Soil moisture (SM) data simulated by the VIC model effectively capture DWAA events, showing significantly higher | SMCI| values downstream than upstream (P < 0.05) and indicating more intense dry-wet transitions in the downstream region. Furthermore, 78 % of the area exhibits an increasing trend in |SMCI|(1980-2019), with dry-to-wet transition events occurring more frequently than wet-to-dry events. For instance, in 2013, the maximum coverage area reached 48 % in a single day; (3) The random forest model highlights the spatial heterogeneity of DWAA driving factors: upstream water yield is the dominant factor, whereas downstream variations are closely associated with precipitation intensity (R-2 = 0.76) and the frequency of heavy rainfall days. Permafrost degradation and land use changes further heighten hydrological sensitivity in the downstream region. This study offers a transferable methodological framework for understanding extreme hydrological events and reveals that the driving mechanisms of DWAA are spatially heterogeneous, shifting from being dominated by terrestrial factors in the headwaters to meteorological factors downstream-a finding with significant implications for water resource management in other large, heterogeneous semi-arid basins.

Light-absorbing carbonaceous aerosols, comprising black carbon (BC) and brown carbon (BrC), significantly influence air quality and radiative forcing. Unlike traditional approaches that use a fixed value of absorption & Aring;ngstrom exponent (AAE), this study investigated the absorption and optical properties of carbonaceous aerosols in Beijing for both local emission and regional transport events during a wintertime pollution event by using improved AAE results that employs wavelength-dependent AAE (WDA). By calculating the difference of BC AAE at different wavelengths using Mie theory and comparing the calculated results to actual measurements from an Aethalometer (AE31), a more accurate absorption coefficient of BrC can be derived. Through the analysis of air mass sources, local emission was found dominated the pollution events during this study, accounting for 81 % of all cases, while regional transport played a minor role. Carbonaceous aerosols exhibited a continuous increasing trend during midday, which may be attributed to the re-entrainment of nighttime-accumulated carbonaceous aerosols to the surface during the early planetary boundary layer (PBL) development phase, as the mixed layer rises, combined with the variation of PBL and anthropogenic activity. At night, variations in the PBL height, in addition to anthropogenic activities, effectively contributed to surface aerosol concentrations, leading to peak surface aerosol values during local pollution episodes. The diurnal variation of AAE470/880 exhibited a decreasing trend, with a total decrease of approximately 12 %. Furthermore, the BrC fraction showed a constant diurnal variation, suggesting that the declining AAE470/880 was primarily influenced by BC, possibly due to enhanced traffic contributions.

The long-term trend for aerosol optical properties and climate impact sensitivity in terms of radiative forcing efficiency were analyzed at a suburban station in Athens, Southeast Mediterranean, using an extensive dataset from 2008 to 2022. The study examined scattering (nsc) and absorption (nap) coefficients, scattering & Aring;ngstrom exponent (SAE), absorption & Aring;ngstrom exponent (AAE), single scattering albedo (SSA), asymmetry parameter (g), and radiative forcing efficiency (RFE). Seasonal variability was linked to meteorological conditions and human activities. Single Scattering Albedo (SSA) was lowest (0.86), and Radiative Forcing Efficiency (RFE) was highest (-61 W/m2) in winter, confirming enhanced contributions from traffic and biomass burning. Lower SAE values (1.5) in spring indicate a greater presence of coarse particles due to frequent Saharan dust events (SDEs). Daily patterns of nap and SSA reflect local emissions, with pronounced traffic-related peaks. Aerosol classification revealed that Black Carbon (BC) dominates the suburban aerosol (51 %), with mixed BrC-BC (16 %) peaking in winter and dust-pollution mixtures (13 %) increasing in spring. The presence of large particles mixed with BC (11 %) was more frequent in spring, further highlighting seasonal variability. Trend analysis showed statistically significant (ss) decreases in nsc (-0.611) and SSA (-0.003), alongside increases in nap (+0.027) and RFE (+0.270) at a 95 % confidence level, suggesting a shift toward more absorbing aerosols. The findings provide new insights and reveal a new aerosol regime, where a reduction in anthropogenic emissions is affecting the scattering rather than the absorbing aerosol component, while the impact from forest fires as a climate feedback mechanism has a significant effect in the Eastern Mediterranean. It is important for future studies and climate modelling to account for the regionally observed changes of the state of mixing of ambient aerosol leading to a shift in radiative forcing efficiency through the reduction in SSA. This is evident in the long term for the east Mediterranean region and must be accounted for in radiative forcing estimates and future climate projections.

Tobacco is a significant economic crop cultivated in various regions of China. Arbuscular mycorrhizal fungi (AMF) can establish a symbiotic relationship with tobacco and regulate its growth. However, the influences of indigenous AMF on the growth and development of tobacco and their symbiotic mechanisms remain unclear. In this study, a pot inoculation experiment was conducted, revealing that six inoculants - Acaulospora bireticulata(Ab), Septoglomus viscosum(Sv), Funneliformis mosseae(Fm), Claroideoglomus etunicatum(Ce), Rhizophagus intraradices(Ri), and the mixed inoculant (H) - all formed stable symbiotic relationships with tobacco. These inoculants were found to enhance the activities of SOD, POD, PPO, and PAL in tobacco leaves, increase chlorophyll content, IAA content, CTK content, soluble sugars, and proline levels while reducing malondialdehyde content. Notably, among these inoculants, Fm exhibited significantly higher mycorrhizal infection density, arbuscular abundance, and soil spore density in the root systems of tobacco plants compared to other treatments. Membership function analysis confirmed that Fm had the most pronounced growth-promoting effect on tobacco. The transcriptome analysis results of different treatments of CK and inoculation with Fm revealed that 3,903 genes were upregulated and 4,196 genes were downregulated in the roots and stems of tobacco. Enrichment analysis indicated that the majority of these genes were annotated in related pathways such as biological processes, molecular functions, and metabolism. Furthermore, differentially expressed genes associated with auxin, cytokinin, antioxidant enzymes, and carotenoids were significantly enriched in their respective pathways, potentially indirectly influencing the regulation of tobacco plant growth. This study provides a theoretical foundation for the development and application of AMF inoculants to enhance tobacco growth.

On December 18, 2023, a magnitude MS6.2 earthquake struck Jishishan County, Gansu Province, triggering over 40 seismic subsidence sites within a seismic intensity VI zone, 32 km from the epicenter.The earthquake caused tens of millions in economic losses to mountain photovoltaic power stations. Extensive geological surveys and comparisons with similar landslides (such as soil loosening, widespread cracks, and stepped displacements) triggered by the 1920 Haiyuan MS8.5 earthquake and the 1995 Yongdeng MS5.8 earthquake, this study preliminarily identifies one subsidence sites as a seismic-collapsed loess landslide. To investigate its disaster-causing mechanism: the dynamic triaxial test was conducted to assess the seismic subsidence potential of the loess at the site, and the maximum subsidence amount under different seismic loads were calculated by combining actual data from nearby bedrock stations with site amplification data from the active source; simulation of the destabilization evolution of seismic-collapsed loess landslides by large-scale shaking table tests; and a three-dimensional slope model was developed using finite element method to study the complex seismic conditions responsible for site damage. The research findings provide a theoretical foundation for further investigations into the disaster mechanisms of seismic-collapsed loess landslides.

Bedrock-soil layer slopes (BSLSs) are widely distributed in nature. The existence of the interface between bedrock and soil layer (IBSL) affects the failure modes of the BSLSs, and the seismic action makes the failure modes more complex. In order to accurately evaluate the safety and its corresponding main failure modes of BSLSs under seismic action, a system reliability method combined with the upper bound limit analysis method and Monte Carlo simulation (MCS) is proposed. Four types of failure modes and their corresponding factors of safety (Fs) were calculated by MATLAB program coding and validated with case in existing literature. The results show that overburden layer soil's strength, the IBSL's strength and geometric characteristic, and seismic action have significant effects on BSLSs' system reliability, failure modes and failure ranges. In addition, as the cohesion of the inclination angle of the IBSL and the horizontal seismic action increase, the failure range of the BSLS gradually approaches the IBSL, which means that the damage range becomes larger. However, with the increase of overburden layer soil's friction angle, IBSL's depth and strength, and vertical seismic actions, the failure range gradually approaches the surface of the BSLS, which means that the failure range becomes smaller.

Earthquakes are common geological disasters, and slopes under seismic loading can trigger coseismic landslides, while also becoming unstable due to accumulated damage caused by the seismic activity. Reinforced soil slopes are widely used as seismic-resistant geotechnical systems. However, traditional geosynthetics cannot sense internal damage in reinforced soil systems, and existing in-situ distributed monitoring technologies are not suitable for seismic conditions, thus limiting accurate post-earthquake stability assessments of slopes. This study presents, for the first time, the use of a batch molding process to fabricate self-sensing piezoelectric geogrids (SPGG) for distributed monitoring of soil behavior under seismic conditions. The SPGG's reinforcement and damage sensing abilities were verified through model experiments. Results show that SPGG significantly enhances soil seismic resistance and can detect soil failure locations through voltage distortions. Additionally, the tensile deformation of the reinforcement material can be quantified with sub-centimeter precision by tracking impedance changes, enabling high-precision distributed monitoring of reinforced soil under seismic conditions. Notably, when integrated with wireless transmission technology, the SPGG-based monitoring system offers a promising solution for real-time monitoring and early warning in road infrastructure, where rapid detection and response to seismic hazards are critical for mitigating catastrophic outcomes.