Buried water pipelines, as crucial urban infrastructure, play an essential role. However, the damage to the pipeline structure has emerged as a severe public safety hazard. Monitoring the state of the pipeline structure holds great significance for the normal operation of water pipelines. In this paper, a damage monitoring method for buried pipelines based on distributed acoustic sensing technology is proposed. Through a series of field experiments conducted on a pipeline, the feasibility of utilizing the attached fiber-optic cable to acquire vibration information has been demonstrated. The recorded vibration signals can indicate various damage statuses during the pipeline damage process, including rock/soil fall, pipeline seepage, and pipe wall failure. The results suggest that the fiber-optic cable accompanying the pipelines can be exploited as sensing resources to monitor damage risks to the pipelines, which presents advantages in the damage identification and location of buried pipelines. This research provides a valuable reference for the application of distributed acoustic sensing technology in the damage monitoring of urban buried water pipelines.

Soil moisture is a key parameter in the exchange of energy and water between the land surface and the atmosphere. This parameter plays an important role in the dynamics of permafrost on the Qinghai-Xizang Plateau, China, as well as in the related ecological and hydrological processes. However, the region's complex terrain and extreme climatic conditions result in low-accuracy soil moisture estimations using traditional remote sensing techniques. Thus, this study considered parameters of the backscatter coefficient of Sentinel-1A ground range detected (GRD) data, the polarization decomposition parameters of Sentinel-1A single-look complex (SLC) data, the normalized difference vegetation index (NDVI) based on Sentinel-2B data, and the topographic factors based on digital elevation model (DEM) data. By combining these parameters with a machine learning model, we established a feature selection rule. A cumulative importance threshold was derived for feature variables, and those variables that failed to meet the threshold were eliminated based on variations in the coefficient of determination (R2) and the unbiased root mean square error (ubRMSE). The eight most influential variables were selected and combined with the CatBoost model for soil moisture inversion, and the SHapley Additive exPlanations (SHAP) method was used to analyze the importance of these variables. The results demonstrated that the optimized model significantly improved the accuracy of soil moisture inversion. Compared to the unfiltered model, the optimal feature combination led to a 0.09 increase in R2 and a 0.7% reduction in ubRMSE. Ultimately, the optimized model achieved a R2 of 0.87 and an ubRMSE of 5.6%. Analysis revealed that soil particle size had significant impact on soil water retention capacity. The impact of vegetation on the estimated soil moisture on the Qinghai-Xizang Plateau was considerable, demonstrating a significant positive correlation. Moreover, the microtopographical features of hummocks interfered with soil moisture estimation, indicating that such terrain effects warrant increased attention in future studies within the permafrost regions. The developed method not only enhances the accuracy of soil moisture retrieval in the complex terrain of the Qinghai-Xizang Plateau, but also exhibits high computational efficiency (with a relative time reduction of 18.5%), striking an excellent balance between accuracy and efficiency. This approach provides a robust framework for efficient soil moisture monitoring in remote areas with limited ground data, offering critical insights for ecological conservation, water resource management, and climate change adaptation on the Qinghai-Xizang Plateau.

The unique optical properties of microplastic particles have a significant impact on atmospheric radiative forcing. Based on the generalized multi-particle Mie theory, this paper presents a comparative study of the extinction properties and absorption properties of single-component and mixed aerosol clusters composed of microplastics, dust, and black carbon in different structural forms and particle sizes. The results show that the structure, particle size, mixing arrangement, and orientation of aerosol particles containing microplastics will directly affect their optical properties. As the incident wavelength increases, significant differences are observed in the extinction and absorption cross-sections of microplastic and dust particle chains with different structures, although they exhibit similar trends. However, black carbon particle chains show a distinct variation pattern. In the mixed particle chains with different particle sizes, as the incident wavelength increases, the extinction and absorption cross-sections are significantly larger than those of the particle chains with the same particle size, indicating that the particle size has a remarkable influence on their optical properties. The different mixing forms and orientations of aerosol clusters also significantly affect their extinction and absorption cross-sections. These findings provide a new theoretical perspective for environmental optics and remote sensing monitoring of aerosols.

The solidification and molding of lunar regolith are essential for constructing lunar habitats. This study introduces an innovative lunar regolith molding technique that synergistically combines solar concentration, flexible optical fiber bundle energy transfer, and powder bed fusion. A functional prototype is developed to validate the proposed scheme. Systematic experiments including fixed beam spot melting, line melting, surface melting, and body melting are conducted using simulated basalt lunar regolith. Through in-situ observation of the melt pool's formation, evolution, and expansion dynamics, we identify a sequential transformation mechanism on the powder bed's surface: initial curling evolves into detachment from the bed, subsequent incorporation into a molten droplet, and ultimate solidification. A comprehensive evaluation of density and mechanical properties across multiple parameter combinations reveals that energy flux density of 3.33 MW/m2 with a scan speed of 30 mm/min, inter-track spacing of 3 mm, and layer thickness of 2 mm enables the production of structurally integral samples with continuous morphology. The resulting specimens demonstrate a maximum compressive strength of 4.25 MPa and a density of 2.31 g/cm3. This solar-powered additive manufacturing approach establishes a viable reference framework for large-scale on-site construction of lunar research stations.

Aerosol optical properties and radiative forcing critically influence Earth's climate, particularly in semi-arid regions. This study investigates these properties in Yinchuan, Northwest China, focusing on aerosol optical depth (AOD), single-scattering albedo (SSA), & Aring;ngstr & ouml;m Index, and direct radiative forcing (DRF) using 2023 CE-318 sun photometer data, HYSPLIT trajectory analysis, and the SBDART model. Spring AOD peaks at 0.58 +/- 0.15 (500 nm) due to desert dust, with coarse-mode particles dominating, while summer SSA reaches 0.94, driven by fine-mode aerosols. Internal mixing of dust and anthropogenic aerosols significantly alters DRF through enhanced absorption, with spring surface DRF at -101 +/- 22W m-2 indicating strong cooling and internal mixing increasing atmospheric DRF to 52.25W m-2. These findings elucidate dust-anthropogenic interactions' impact on optical properties and radiative forcing, offering critical observations for semi-arid climate research.

The real-time monitoring of fracture propagation during hydraulic fracturing is crucial for obtaining a deeper understanding of fracture morphology and optimizing hydraulic fracture designs. Accurate measurements of key fracture parameters, such as the fracture height and width, are particularly important to ensure efficient oilfield development and precise fracture diagnosis. This study utilized the optical frequency domain reflectometer (OFDR) technique in physical simulation experiments to monitor fractures during indoor true triaxial hydraulic fracturing experiments. The results indicate that the distributed fiber optic strain monitoring technology can efficiently capture the initiation and expansion of fractures. In horizontal well monitoring, the fiber strain waterfall plot can be used to interpret the fracture width, initiation location, and expansion speed. The fiber response can be divided into three stages: strain contraction convergence, strain band formation, and postshutdown strain rate reversal. When the fracture does not contact the fiber, a dual peak strain phenomenon occurs in the fiber and gradually converges as the fracture approaches. During vertical well monitoring in adjacent wells, within the effective monitoring range of the fiber, the axial strain produced by the fiber can represent the fracture height with an accuracy of 95.6% relative to the actual fracture height. This study provides a new perspective on real-time fracture monitoring. The response patterns of fiber-induced strain due to fractures can help us better understand and assess the dynamic fracture behavior, offering significant value for the optimization of oilfield development and fracture diagnostic techniques. (c) 2025 Institute of Rock and Soil Mechanics, Chinese Academy of Sciences. Published by Elsevier B.V. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/ 4.0/).

Smoky haze which occurs during large-scale wildfires essentially transforms the radiative regime of the atmosphere over large territories. The variability of shortwave radiation fluxes in a smoke-laden atmosphere is driven by variations in the optical and microphysical properties of smoke aerosols, including the spectral dependences of the imaginary part of the refractive index. These dependences are determined by the presence of black carbon, brown carbon, and radiation-selective absorbing organic compounds in aerosol particles. This study analyzes the aforementioned spectral dependences based on AERONET data during large-scale wildfires in Alaska in 2019 and Canada in 2023. The analysis includes the cases of extreme radiation absorption by black and brown carbon, where the imaginary part of the refractive index at a wavelength of 440 nm attained 0.50 and 0.27, respectively. Variations in the spectral dependence of the imaginary part of the refractive index under moderate manifestations of selective absorption of smoke aerosol during massive fires in Alaska and Canada are analyzed. Approximations for the spectral dependence of the imaginary part of the refractive index are suggested. The aerosol radiative forcing at the top of the atmosphere is estimated for the cases of extreme radiation absorption by black carbon and brown carbon in the visible and near-infrared spectral regions and of anomalous selective absorption. The results can be useful in monitoring of the radiative regime of the atmosphere and for the development of atmospheric remote sounding techniques.

This study investigates aerosol characteristics using ground-based measurements at two distinct regions, MohalKullu (31.9 degrees N, 77.12 degrees E; 1154 m amsl) and Kosi-Katarmal (29.64 degrees N, 79.62 degrees E; 1225 m amsl), from July 2019 to June 2022. The average Black Carbon (BC) concentrations were 1.5 f 1.0 mu g m- 3 at Mohal and 1.1 f 1.4 mu g m-3 at Katarmal. BC showed strong seasonal variability, with maxima during post-monsoon (2.6 f 1.0 mu g m- 3) and pre-monsoon (1.8 f 0.5 mu g m-3) seasons. The diurnal variation displayed distinct morning and evening peaks in all the seasons. High pre-monsoon AOD500 (0.30 f 0.06 to 0.54 f 0.08) and low values of & Aring;ngstrom exponent (0.67 f 0.10 to 0.95 f 0.30) indicated dominance of large particles, whereas lower AOD500 (0.21 f 0.07 to 0.25 f 0.03) in post-monsoon and winter, along with larger & Aring;ngstrom exponent (1.05 f 0.74 to 1.13 f 0.11), indicated smaller particles. Satellite-derived (OMI and MAIAC) AOD500 showed weak to moderate correlation with ground-based measurements at Mohal (R = 0.4639 for MAIAC, R = 0.1402 for OMI) and Katarmal (R = 0.3976 for MAIAC, R = 0.2980 for OMI). Using optical properties of aerosols and clouds (OPAC) and Santa Barbara discrete ordinate radiative transfer (SBDART) models, the short-wave aerosol radiative forcing (SWARF) was found negative at the surface and top of the atmosphere but positive in the atmosphere, suggesting significant surface cooling and atmospheric warming leading to high heating rates, respectively. Annual mean atmospheric radiative forcing was 27.36 f 6.00 Wm- 2 at Mohal and 21.87 f 7.26 Wm- 2 at Katarmal. These findings may have consequences for planning air pollution strategies and understanding the effects of regional climate change.

Aerosols are an important factor leading to reduced visibility. In order to better comprehend the connection between visibility and aerosols, aerosol optical depth (AOD) and Angstrom exponent (AE) data from the Himawari-8 Advanced Himawari Imager (AHI) are used for validation in comparison with the data from the Aerosol Robotic Network (AERONET) observations in this paper, which amounted to 69,026 sets of data. The results indicate that the AOD of AHI is in good agreement with AERONET observations, but AE performs poorly. The correlation coefficients between the AOD of AHI and AERONET data increase with decreasing visibility and the root mean square error increase. The AE of AHI performs poorly in different visibility conditions. The conclusion drawn from further analysis of the correlation between aerosol products and meteorological factors is that the factor with the highest correlation with visibility. Mixed aerosols dominate at higher visibility and biomass burning/urban-industrial aerosols dominate at lower visibility. The visibility in a typical city (Beijing) has a strong negative correlation with AOD, a weak negative correlation with AE, and a strong correlation with aerosol radiative forcing. The reduction in visibility may be caused by the scattering and adsorption effects of aerosols. The results are important for the improvement and application of AHI aerosol products in regional pollution studies.

Particulate matter (PM) is a vital pollutant that severely impacts human health, ecosystem well-being, and climate systems. In this review, the importance of vertical profiling is considered for understanding PM behavior between different layers of the atmosphere, and it includes modern techniques used such as meteorological towers and building methods, unmanned aerial vehicles (UAVs), aircraft, and satellite-based aerosol optical depth measurements. A systematic review was conducted, sourcing 150 articles published between 2000 and 2023, using relevant keywords such as Particulate Matter, Vertical Profiling, Environmental Impacts, and Climate Change from databases like Web of Science, Scopus, and Google Scholar. Key findings illustrate the vertical variations in PM levels associated with interactions among urban environments, meteorology, and specific atmospheric processes such as cloud formation, radiative forcing, and long-distance transport of pollutants. PM's effects on biodiversity, nutrient cycles, and ecosystem stability are also discussed. The environmental impacts of PM deposition, including biodiversity loss, nutrient cycling disruption, and ecosystem destabilization, elucidate widespread chronic anthropogenic particulate causes of long-term ecological damage around the globe. The study also examines relevant regulatory frameworks, specifically air quality standards, and policies, underpinning mitigation strategies. This review discusses how PM pollution is an increasingly alarming health risk. It reiterates the importance of demanding effective regulations on the local and global levels to counteract detrimental environmental and climatic consequences. This review clearly shows the immediate threats of PM. It should form a wake-up call to develop more effective monitoring tools and stringent regulatory measures against this omnipresent pollutant.