The aerosol scattering phase function (ASPF), a crucial element of aerosol optical properties, is pivotal for radiative forcing calculations and aerosol remote sensing detection. Current detection methods for the ASPF include multi-sensor detection, single-sensor rotational detection and imaging detection. However, these methods face challenges in achieving high-resolution full-angle measurement, particularly for small forward (i.e., less than 10 degrees) or backward (i.e., more than 170 degrees) scattering angles in open path. In this work, a full-angle ASPF detection system based on the multi-field-of-view Scheimpflug lidar technique has been proposed and demonstrated. A 450 nm continuous-wave semiconductor laser was utilized as the light source and four CMOS image sensors were employed as detectors. To detect the full-angle ASPF, four receiving units capture angular scattering signals across different angle ranges, namely 0 degrees-20 degrees, 10 degrees-96 degrees, 84 degrees-170 degrees, 160 degrees-180 degrees, respectively. The influence of the relative illumination and angular response of the used image sensors have been corrected, and a signal stitching algorithm was developed to obtain a complete 0-180 degrees angular scattering signal. Atmospheric measurements have been conducted by employing the full-angle ASPF detection system in open path. The experimental results of the ASPF have been compared with the AERONET data from the Socheongcho station and simulated ASPF based on the typical aerosol models in mainland China, showing excellent agreement. The promising results demonstrated in this work have shown a great potential for detecting the full-angle ASPF in open path.

In recent years, increasing wildfire activity in the western United States has led to significant emissions of smoke aerosols, impacting the atmospheric energy balance through their absorption and scattering properties. Single scattering albedo (SSA) is a key parameter that governs these radiative effects, but accurately retrieving SSA from satellites remains challenging due to limitations in sensor resolution, low sensitivity of traditional remote sensing methods, and uncertainties in radiative transfer modeling, particularly from surface reflectance and aerosol characterization. Smoke optical properties evolve rapidly after emission, influenced by fuel type, combustion conditions, and chemical aging. Accurate SSA retrieval near the source thus requires high-temporal-resolution satellite observations. Critical Reflectance (CR) method provides this capability by identifying a unique reflectance value at which top-of-atmosphere (TOA) reflectance becomes insensitive to aerosol loading and primarily reflects aerosol absorption. SSA can be retrieved from this critical reflectance. This study presents a geostationary-based CR method using the Advanced Baseline Imager (ABI) on GOES-R satellites. The approach leverages ABI's high temporal (5-10 min) and spatial (3 km) resolution, consistent viewing geometry, and wide coverage. A tailored look-up table, based on an AOD-dependent smoke model for North America, links CR to SSA. Case studies show strong agreement with AERONET measurements, with retrieval differences mostly within 0.01-well below AERONET's +/- 0.03 uncertainty. The method captures temporal and spatial variations in smoke absorption and demonstrates robustness across daylight hours. This GEO-based CR approach offers an effective tool for high-resolution SSA retrieval, contributing to improved aerosol radiative forcing estimates and climate modeling.

Estimating Top-of-Atmosphere (TOA) flux and radiance is essential for understanding Earth's radiation budget and climate dynamics. This study utilized polar nephelometer measurements of aerosol scattering coefficients at 17 angles (9-170 degrees), enabling the experimental determination of aerosol phase functions and the calculation of Legendre moments. These moments were then used to estimate TOA flux and radiance. Conducted at a tropical coastal site in India, the study observed significant seasonal and diurnal variations in angular scattering patterns, with the highest scattering during winter and the lowest during the monsoon. Notably, a prominent secondary scattering mode, with varying magnitude across different seasons, was observed in the 20-30 degrees angular range, highlighting the influence of different air masses and aerosol sources. Chemical analysis of size-segregated aerosols revealed that fine-mode aerosols were dominated by anthropogenic species, such as sulfate, nitrate, and ammonium, throughout all seasons. In contrast, coarse-mode aerosols showed a clear presence of sea-salt aerosols during the monsoon and mineral dust during the pre-monsoon periods. The presence of very large coarse-mode non-spherical aerosols caused increased oscillations in the phase function beyond 60 degrees during the pre-monsoon and monsoon seasons. This also led to a weak association between the phase function derived from angular scattering measurements and those predicted by the Henyey-Greenstein approximation. As a result, TOA fluxes and radiances derived using the Henyey-Greenstein approximation (with the asymmetry parameter as input in the radiative transfer model) showed a significant difference- up to 24% in seasons with substantial coarse-mode aerosol presence- compared to those derived using the Legendre moments of the phase function. Therefore, TOA flux and radiance estimates using Legendre moments are generally more accurate in the presence of complex aerosol scattering characteristics, particularly for non-spherical or coarse-mode aerosols, while the Henyey-Greenstein phase function may yield less accurate results due to its simplified representation of scattering behavior.

In this study, the anisotropic nature of the medium is used to simulate the stratigraphic conditions. Taking the embankment of a high-speed railway as the object of study, the wave function expansion method is used to obtain the level solution for inverse plane shear wave scattering of the anisotropic half-space medium-waisted ladder form of the embankment. Then, by changing the anisotropy parameter of the soil medium, the effects of different incidence angles, dimensionless frequencies, embankment slopes, and anisotropic parameters on the isosceles trapezoidal form of the embankment structure are investigated. The results show that the anisotropy of the medium not only has a significant effect on the surface displacement of the embankment site but also makes other parameters more sensitive to the site effect, as manifested by the larger amplitude of the surface displacement caused by the incident wave along a certain angle at a certain dimensionless frequency compared to that of the isotropic medium. The embankment structure plays an important role in vibration damping and isolation during the propagation of vibration waves in the horizontal direction, and this phenomenon becomes less obvious with larger dimensionless frequency.

In this study, a methodology is proposed to use dual-polarimetric synthetic aperture radar (SAR) to identify the spatial distribution of soil liquefaction. The latter is a phenomenon that occurs in conjunction with seismic events of a magnitude generally higher than 5.5-6.0 and which affects loose sandy soils located below the water table level. The methodology consists of two steps: first the spatial distributions of soil liquefaction is estimated using a constant false alarm rate method applied to the SPAN metric, namely the total power associated with the measured polarimetric channels, which is ingested into a bitemporal approach to sort out dark areas not genuine. Second, the obtained masks are read in terms of the physical scattering mechanisms using a child parameter stemming from the eigendecomposition of the covariance matrix-namely the degree of polarization. The latter is evaluated using the coseismic scenes and contrasted with the preseismic one to have rough information on the time-variability of the scattering mechanisms occurred in the area affected by soil liquefaction. Finally, the obtained maps are qualitatively contrasted against state-of-the-art optical and interferometric SAR methodologies. Experimental results, obtained processing a time-series of ascending and descending Sentinel-1 SAR scenes acquired during the 2023 Turkiye-Syria earthquake, confirm the soundness of the proposed approach.

Simulating synthetic aperture radar (SAR) images of crater terrain is a crucial technique for expanding SAR sample databases and facilitating the development of quantitative information extraction models for craters. However, existing simulation methods often overlook crucial factors, including the explosive depth effect in crater morphology modeling and the double-bounce scattering effect in electromagnetic scattering calculations. To overcome these limitations, this article introduces a novel approach to simulating SAR images of crater terrain. The approach incorporates crater formation theory to describe the relationship between various explosion parameters and craters. Moreover, it employs a hybrid ray-tracing approach that considers both surface and double-bounce scattering effects. Initially, crater morphology models are established for surface, shallow burial, and deep burial explosions. This involves incorporating the explosive depth parameter into crater morphology modeling through crater formation theory and quantitatively assessing soil movement influenced by the explosion. Subsequently, the ray-tracing algorithm and the advanced integral equation model are combined to accurately calculate electromagnetic scattering characteristics. Finally, simulated SAR images of the crater terrain are generated using the SAR echo fast time-frequency domain simulation algorithm and the chirp scaling imaging algorithm. The results obtained by simulating SAR images under different explosion parameters offer valuable insights into the effects of various explosion parameters on crater morphology. This research could contribute to the creation of comprehensive crater terrain datasets and support the application of SAR technology for damage assessment purposes.

This study was conducted to investigate the hydrostatic stability of a steel slag porous asphalt mixture (SSPA) under freeze-thaw cycles in seasonal frozen soil areas and thereafter, compare its (SSPA) characteristic properties and advantages with a traditional porous asphalt pavement. In the study, the freeze-thaw stability of SSPA was tested through multiple freeze-thaw cycle splitting, scattering loss, and trabecular bending tests under various cyclic temperature water immersion conditions including quantitatively analyzing the SSPA volumetric changes. In addition, the scanning electron microscope (SEM) and energy dispersive spectrometer (EDS) tests were used to analyze the microscopic damage mechanism of SSPA after being subjected to various cyclic temperature water immersion conditions. The corresponding test results indicated that: (a) the long-term freeze-thaw cycles had significant adverse effects on the hydrostatic stability, physical/mechanical properties, and volume stability of SSPA; and (b) when the melting temperature was increased, both the hydrostatic stability and mass gain/loss ratio of SSPA decreased whilst the void ratio increased. On the other hand, the SEM and EDS results showed that an increase in the number of freeze-thaw cycles or melting temperature led to a corresponding increase in the width of the steel slag-asphalt transition zone. This resulted in a weakening of the mechanical connection and anchorage between steel slag and asphalt, as well as the destruction of their adhesion bond. However, the short-term freeze-thaw cycles had little effect on the hydrostatic stability of SSPA because the steel slag-asphalt interfacial strength was enhanced by shortterm freeze-thaw cycles.

Over the last few decades, there is increasing worldwide concern over human health risks associated with extensive use of pesticides in agriculture. Developing excellent SERS substrate materials to achieve highly sensitive detection of pesticide residues in the food is very necessary owing to their serious threat to human health through food chains. Self -assembled metallic nanoparticles have been demonstrated to be excellent SERS substrate materials. Hence, alkanethiols-protected gold nanoparticles have been successfully prepared for forming larger -scale two-dimensional monolayer films. These films can be disassembled into a fluid state and reassembled back to crystallized structure by controlling surface pressure. Further investigations reveal that their self -assembled structures are mainly dependent on the diameter of gold nanoparticles and ligand length. These results suggest that the size ratio of nanoparticle diameter/ligand length within the range of 4.45 -2.35 facilitates the formation of highly ordered 2D arrays. Furthermore, these arrays present excellent SurfaceEnhanced Raman Scattering performances in the detection of trace thiram, which can cause environmental toxicity to the soil, water, animals and result in severe damage to human health. Therefore, the current study provides an effective way for preparing monodispersed hydrophobic gold nanoparticles and forming highly ordered 2D close -packed SERS substrate materials via self -assembly to detect pesticide residues in food. We believe that, our research provides not only advanced SERS substrate materials for excellent detection performance of thiram in food, but also novel fundamental understandings of self -assembly, manipulation of nanoparticle interactions, and controllable synthesis.

A comprehensive global investigation on the impact of reduction (changes) in aerosol emissions due to Coronavirus disease-2019 (COVID-19) lockdowns on aerosol single scattering albedo (SSA) utilizing satellite observations and model simulations is conducted for the first time. The absolute change in Ozone Monitoring Instrument (OMI) retrieved, and two highly-spatially resolved models (Modern-Era Retrospective Analysis for Research and Applications-2 (MERRA-2) and Copernicus Atmosphere Monitoring Service (CAMS)) simulated SSA is <4% (<0.04-0.05) globally during COVID (2020) compared to normal (2015-2019) period. Change in SSA during COVID is not significantly different from long-term and year-to-year variability in SSA. A small change in SSA indicates that significant reduction in anthropogenic aerosol emissions during COVID-19 induced lockdowns has a negligible effect in changing the net contribution of aerosol scattering and/or absorption to total aerosol extinction. The changes in species-wise aerosol optical depth (AOD) are examined in detail to explain the observed changes in SSA. Model simulations show that total AOD decreased during COVID-19 lockdowns, consistent with satellite observations. The respective contributions of sulfate and black carbon (BC) to total AOD increased, which resulted in a negligible change in SSA during the spring and summer seasons of COVID over South Asia. Europe and North America experience a small increase in SSA (<2%) during the summer season of COVID due to a decrease in BC contribution. The change in SSA (2%) is the same for a small change in BC AOD contribution (3%), and for a significant change in sulfate AOD contribution (20%) to total AOD. Since, BC SSA is 5-times lower (higher absorption) than that of sulfate SSA, the change in SSA remains the same. For a significant change in SSA to occur, the BC AOD contribution needs to be changed significantly (4-5 times) compared to other aerosol species. A sensitivity analysis reveals that change in aerosol radiative forcing during COVID is primarily dependent on change in AOD rather than SSA. These quantitative findings can be useful to devise more suitable future global and regional mitigation strategies aimed at regulating aerosol emissions to reduce environmental impacts, air pollution, and public health risks.

Objective In coal mining regions, extensive coal dust is generated during mining, transportation, and storage, coupled with substantial black carbon produced resulting from incomplete coal combustion in the industry chain. Over time, these materials form absorbable substances, evolving into core- shell aerosols with inorganic salt shells. These aerosols, including sulfate, nitrate, and water, exert significant climate impacts through direct and indirect radiation effects. The environmental and radiative forcing effects are substantial. Absorbing aerosol demonstrates strong solar radiation absorption across the ultraviolet to infrared spectrum. However, past studies primarily focus on their optical properties in visible and infrared bands, overlooking ultraviolet band absorption. Current research often assumes a lognormal particle size distribution for absorbing aerosols, neglecting variations in distribution and optical properties resulting from diverse emission scenarios. Therefore, a thorough analysis of absorbing aerosol optical properties at local scales is crucial. Quantitative assessments of particle size distribution, mixing state, and spatio-temporal variations are vital for elucidating the intricate interactions with boundary layer development, radiative forcing changes, and air pollution. Methods In our study conducted in the coal mining area of Changzhi City, Shanxi Province, various datasets are collected, including surface black carbon concentration, particle size distribution, and columnar aerosol optical depth (AOD). The investigation commenced with the utilization of the variance maximization method to categorize AOD data into distinct pollution events. Subsequent analysis involved evaluating the particle size distribution corresponding to different pollution degrees through probability density functions. The uncertainty of particle size for the desorption aerosol core and shell is then determined by integrating black carbon mass concentration data and particle size distribution information. These uncertainties are then used as input parameters to run the Mie scattering model based on the core- shell structure. This process results in the inversion of the multi- band optical characteristic parameters of absorbing aerosol in the coal mining area. The computations are carried out under both the assumption of a uniform distribution and a non- uniform distribution, representing different mixing degrees of aerosols. To complete the picture, the uncertainty interval for the single scattering albedo (SSA) of absorbing aerosol was constrained through the application of absorption & Aring;ngstr & ouml;m exponent (AAE) theory. This comprehensive approach provides a nuanced understanding of the complex dynamics of absorbing aerosol in the specific context of coal mining environments. Results and Discussions In the coal mining area, absorbing aerosols are influenced by emission sources, manifesting a particle size distribution divergent from the lognormal model. Under various pollution conditions, robust peaks are discernible in smaller particle size ranges (0.28 -0.3 mu m), with weaker peaks present around 0.58 -0.65 mu m. The relative proportion between the two peaks fluctuates in tandem with the pollution severity (Fig. 3). Using the Mie scattering model, the optical characteristics of absorbing aerosol are inverted based on AOD information, black carbon mass concentration, and particle number concentration. Results indicate that under the assumption of a uniform distribution (Fig. 4), the average size of the core particles at 0.28, 0.58, and 0.7 mu m is relatively low, leading to corresponding patterns in SSA with changes in core particle size. Additionally, the average core particle size shows no significant variation with changes in wavelength in different size ranges. SSA decreases with increasing wavelength, with greater fluctuations in the smaller particle size range (0.25-0.58 mu m) and more stable changes in the larger particle size range (0.58-1.6 mu m). Under this assumption, the AAE theory is found to be inapplicable. In the case of a non- uniform distribution (Fig. 5), SSA values exhibit a slow, followed by a gradual and then rapid increase in the shortwave region, while in the longwave region, SSA first rapidly increases and then gradually levels off. For shorter wavelengths (500 nm and above), AAE theory proves effective for absorbing aerosol with smaller particle sizes. For longer wavelengths (675 nm and above), AAE theory is applicable to absorbing aerosol with moderate particle sizes. However, for larger particles such as coal dust, AAE theory is not suitable. It is noteworthy that, under both assumptions, the inversion results of SSA values in the longwave spectrum (such as 870 and 936 nm) are relatively lower compared to the shortwave spectrum (such as 440 and 500 nm). This discrepancy will lead to an underestimation of emission quantities. Conclusions We conduct on- site observations in the coal mining area of Changzhi City, Shanxi Province, aiming to capture the variation characteristics of AOD, particle concentration, and black carbon mass concentration. Utilizing the Mie scattering model based on the core- shell hypothesis, we simulate the SSA of absorbing aerosol under two different mixing states. Additionally, we calculate the optical variations of absorbing aerosol constrained by the AAE. The research findings reveal the following: 1) The particle size distribution of absorbing aerosol in the coal mining area deviates from the assumptions made in previous studies, which typically assumed single or double- peaked distributions. Influenced by emission sources, the characteristics vary under different pollution conditions. Smaller particles predominantly originate from the incomplete combustion of coal in local power plants and coking factories, producing black carbon. Larger particles stem from the aging processes of black carbon in the atmospheric environment and coal dust generated during coal transportation. 2) Comparison of the SSA variations under different mixing states simulated by the two hypotheses indicates that particle size, mixing state, and spectral range significantly impact the SSA of absorbing. In contrast to previous studies using the infrared spectrum, the present investigation reveals higher SSA values in the ultraviolet and visible light spectrum, suggesting a potential underestimation of black carbon emissions. 3) The AAE theory is applicable only to certain particle size ranges in different spectral bands. For large- sized absorbing aerosol in the coal mining area, using the AAE theory to estimate SSA introduces uncertainty, and applying the AAE assumption across all particle size ranges leads to an underestimation of emissions. These findings underscore that the distribution characteristics of SSA in absorbing aerosol do not strictly adhere to the power- law relationship of the AAE index but are collectively determined by particle size distribution, mixing state, and spectral range.