Black carbon (BC) is a major short-lived climate pollutant (SLCP) with significant climate and environmentalhealth impacts. This review synthesizes critical advancements in the identification of emerging anthropogenic BC sources, updates to global warming potential (GWP) and global temperature potential (GTP) metrics, technical progress in characterization techniques, improvements in global-regional monitoring networks, emission inventory, and impact assessment methods. Notably, gas flaring, shipping, and urban waste burning have slowly emerged as dominant emission sources, especially in Asia, Eastern Europe, and Arctic regions. The updated GWP over 100 years for BC is estimated at 342 CO2-eq, compared to 658 CO2-eq in IPCC AR5. Recent CMIP6-based Earth System Models (ESMs) have improved attribution of BC's microphysics, identifying a 22 % increase in radiative forcing (RF) over hotspots like East Asia and Sub-Saharan Africa. Despite progress, challenges persist in monitoring network inter-comparability, emission inventory uncertainty, and underrepresentation of BC processes in ESMs. Future efforts could benefit from the integration of satellite data, artificial intelligence (AI)assisted methods, and harmonized protocols to improve BC assessment. Targeted mitigation strategies could avert up to four million premature deaths globally by 2030, albeit at a 17 % additional cost. These findings highlight BC's pivotal roles in near-term climate and sustainability policy.

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.

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.

To address the engineering problems of road subsidence and subgrade instability in aeolian soil under traffic loads, the aeolian soil was improved with rubber particles and cement. Uniaxial compression tests and Digital speckle correlation method (DSCM) were conducted on rubber particles-cement improved soil (RP-CIS) with different mixing ratios using the WDW-100 universal testing machine. The microcrack and force chain evolution in samples were analysed using PFC2D. The results showed that: (1) The incorporation of rubber particles and cement enhanced the strength of the samples. When the rubber particles content was 1% and the cement content was 5%, the uniaxial compressive strength of the RP-CIS reached its maximum. Based on the experimental results, a power function model was established to predict the uniaxial compressive strength of RP-CIS; (2) The deformation of the samples remains stable during the compaction stage, with cracks gradually developing and penetrating, eventually entering the shear failure stage; (3) The crack and failure modes simulated by PFC2D are consistent with the DSCM test. The development of microcracks and the contact force between particles during the loading are described from a microscopic perspective. The research findings provide scientific support for subgrade soil improvement and disaster prevention in subgrade engineering.

Most gravel roads leading to rural areas in Ghana have soft spot sections as a result of weak lateritic subgrade layers. This study presents a laboratory investigation on a typical weak lateritic subgrade soil reinforced with non-woven fibers. The objective was to investigate the strength characteristic of the soil reinforced with non-woven fibers. The California Bearing Ratio and Unconfined Compressive Strength tests were conducted by placing the fibers in single layer and also in multiple layers. The results showed an improved strength of the soil from a CBR value of 7%. The CBR recorded maximum values of 30% and 21% for coconut and palm fibers inclusion at a placement depth of H/5 from the compacted surface. Multiple fiber layer application at depths of H/5 & 2 h/5 yielded CBR values of 38% and 31% for coconut and palm fibers respectively. The Giroud and Noiray design method and the Indian Road Congress design method recorded reduction in the thickness of pavement of 56% to 63% for coconut fiber inclusion and 45% to 55% for palm fiber inclusion. Two-way statistical analysis of variance (ANOVA) showed significant effect of depth of fiber placement and fiber type on the geotechnical characteristics considered. (sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic),(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic). (sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic). (sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic). (sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic). (sic)(sic)(sic)(sic),CBR(sic)(sic)7%(sic),(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic). (sic)(sic)(sic)(sic)(sic)(sic)(sic)H/5(sic)(sic)(sic)(sic)(sic)(sic),CBR(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)30%(sic)21%. (sic)H/5(sic)2H/5(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic),(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)CBR(sic)(sic)(sic)(sic)38%(sic)31%. Giroud&Noiray(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)56%(sic)63%,(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)45%(sic)55%. (sic)(sic)(sic)(sic)(sic)(sic)(ANOVA)(sic)(sic),(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic).

Backfill mining is a lucrative method for extracting coal buried under buildings, and water bodies, which can substantially increase the resource usage efficiency by mitigating the strata movement and surface subsidence. Its effectiveness depends on the mechanical properties of granular backfill materials. A permeability test was performed on gangue and fly ash samples under different stress levels using an original seepage test system. The variation patterns of the broken rock's internal pressure and permeability were determined. The test results indicate the weakening of the seepage effect on granular materials and a gradual reduction of washed away fly ash. The permeability values fall into the range of 3.2 x 10(-15) similar to 3.2 x 10(-13)m(-2), and non-Darcy factor is between 3.2 x 10(10) and 3.2 x 10(12) m(-1). This phenomenon was more pronounced in samples with smaller particle sizes. As the axial stress increased, the backfill material showed a decline in permeability and an increase in the non-Darcy flow coefficient. As the content of fly ash increased, the mass loss grew sharply, which occurred mainly at the early seepage stage. The results are considered instrumental in the characterization of water and sand inrush.

To investigate the effect of interface temperature on the soil-reinforcement interaction mechanism, a series of pullout tests were conducted considering different types of reinforcement (geogrid and non-woven geotextile), backfill (dry sand, wet sand, and clay), and six interface temperatures. The test results indicate that at interface temperatures of 0 degrees C and above, reinforcement failure didn't occur during the pullout tests, whereas it predominantly occurred at subzero temperatures. Besides, the pullout resistance for the same soil-reinforcement interface gradually decreased as the interface temperature rose. At a given positive interface temperature, the pullout resistance between wet sand and reinforcement was significantly higher than that of the clayreinforcement interface but lower than that of the dry sand-reinforcement interface. Compared with geotextile reinforcements, geogrids were more difficult to pull out under the same interface temperature and backfill conditions. In addition, the lag effect in the transfer of tensile forces within the reinforcements was significantly influenced by the type of soil-reinforcement interface and the interface temperature. Finally, the progressive deformation mechanism along the reinforcement length at different interface temperatures was analyzed based on the strain distribution in the reinforcement.

The presence of frozen volatiles (especially H2O ice) has been proposed in the permanently shadowed regions (PSRs) near the poles of the Moon, based on various remote measurements including the visible and near-infrared (VNIR) spectroscopy. Compared with the middle- and low-latitude areas, the VNIR spectral signals in the PSRs are noisy due to poor solar illumination. Coupled with the lunar regolith coverage and mixing effects, the available VNIR spectral characteristics for the identification of H2O ice in the PSRs are limited. Deep learning models, as emerging techniques in lunar exploration, are able to learn spectral features and patterns, and discover complex spectral patterns and nonlinear relationships from large datasets, enabling them applicable on lunar hyperspectral remote sensing data and H2O-ice identification task. Here we present H2O ice identification results by a deep learning-based model named one-dimensional convolutional autoencoder. During the model application, there are intrinsic differences between the remote sensing spectra obtained by the orbital spectrometers and the laboratory spectra acquired by state-of-the-art instruments. To address the challenges of limited training data and the difficulty of matching laboratory and remote sensing spectra, we introduce self-supervised learning method to achieve pixel-level identification and mapping of H2O ice in the lunar south polar region. Our model is applied to the level 2 reflectance data of Moon Mineralogy Mapper. The spectra of the identified H2O ice-bearing pixels were extracted to perform dual validation using spectral angle mapping and peak clustering methods, further confirming the identification of most pixels containing H2O ice. The spectral characteristics of H2O ice in the lunar south polar region related to the crystal structure, grain size, and mixing effect of H2O ice are also discussed. H2O ice in the lunar south polar region tends to exist in the form of smaller particles (similar to 70 mu m in size), while the weak/absent 2-mu m absorption indicate the existence of unusually large particles. Crystalline ice is the main phase responsible for the identified spectra of ice-bearing surface however the possibility of amorphous H2O ice beneath optically sensed depth cannot be ruled out.

Ground subsidence resulting from underground coal mining poses significant challenges to urban safety, infrastructure stability, and environmental protection, particularly in regions extending beneath water bodies. This study investigates subsidence patterns in the Kozlu coal basin by integrating Interferometric Synthetic Aperture Radar (InSAR), numerical modelling, and machine learning techniques. The Kozlu coal basin, located in Zonguldak, Turkey, serves as a critical example, where extensive mining activities have led to complex deformation patterns. InSAR effectively captures terrestrial subsidence but is limited in underwater regions. Numerical modelling provides insights into geological behaviour but requires extensive input data. Machine learning, specifically Gaussian Process Regression (GPR), bridges this gap by predicting subsidence in unobservable underwater zones with high accuracy. The integrated approach reveals consistent deformation trends across terrestrial and marine environments, offering practical tools for risk mitigation and resource management. These findings underscore the importance of interdisciplinary methods in addressing complex geological challenges and pave the way for future advancements in subsidence monitoring and prediction.

Permafrost degradation under climate warming plays a crucial role in hydrological and ecological processes, including the regional water cycle and terrestrial carbon balance. The Tibetan Plateau (TP), which contains the largest expanse of high-altitude permafrost globally, remains understudied in terms of how permafrost degradation affects surface water resources and regional carbon dynamics. Using permafrost simulation models and quantitative analysis, we assess the spatiotemporal impacts of permafrost degradation on surface water resources and carbon dynamics. In the inner endorheic regions of the TP, ground ice meltwater contributed 12.6% of the total lake volume increase from 2000 to 2020, accelerating lake expansion and affecting nearby infrastructure and ecosystems. Cryospheric meltwater accounted for 4.6% of total runoff in the source areas of the Yangtze, Yellow, Lancang, Yarlung Zangbo, and Nujiang Rivers in 2002-2018. This cryospheric meltwater contribution is projected to peak in the 2030s-2040s, followed by a decline, with potentially profound implications for downstream water availability. From 2000 to 2020, carbon sequestration of alpine grassland in permafrost regions is 1.05-1.29 Tg C a-1 in 2000-2020. This estimate is underestimated by approximately 35.5% to 48.1% without considering the impact of permafrost degradation. Top-down thawing of permafrost from 2002 to 2050 is projected to release 129.39 +/- 21.02 Tg C a-1 of thawed soil organic carbon (SOC), with 20.82 +/- 3.06 Tg C a-1 decomposed annually. Additionally, permafrost collapse and thermokarst lake are estimated to reduce ecosystem carbon sinks by 0.41 (0.29-0.52) Tg C a-1 in 2020. (c) 2025 The Authors. Published by Elsevier B.V. and Science China Press. This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).