Assessing Attenuation Effects in X-ray Fluorescence Analysis of Light Elements in Mineral Dust

Experimental study on the influence of three typical surfactants on the explosion characteristics of coal dust clouds

CFD simulation and experimental study on the effect of dust concentration, oxygen content and airflow temperature on the explosion characteristics of RDX dust clouds

Abstract. Deposition of mineral dust aerosol into open oceans impacts marine biogeochemistry, and the deposition flux can be constrained using dissolved aluminum (Al) in surface seawater as a tracer. However, aerosol Al solubility, a critical parameter used in this method, remains highly uncertain. We investigated seasonal variations of Al solubility for supermicron and submicron particles at two locations in Northern China. Aerosol Al solubility was very low at Xi'an (0.11 %–9.1 %), showed no apparent variation with seasons or relative humidity, and was not correlated with sulfate or nitrate; in contrast, it was much higher at Qingdao (0.06 %–23.4 %), exhibited distinct seasonal variability, and increased with relative humidity and the abundance of sulfate and nitrate. All these features observed can be explained by the effects of atmospheric chemical processing. Mineral dust transported to Xi'an, an inland city in Northwest China, was still not obviously aged and thus chemical processing had little effect on Al solubility; after arriving at Qingdao, a coastal city in the Northwest Pacific, mineral dust was substantially aged by chemical processing, leading to significant enhancement in Al solubility. Our work further reveals that aerosol liquid water and acidity play vital roles in the dissolution of aerosol Al by chemical processing. We suggest that chemical aging can lead to spatiotemporal variation of aerosol Al solubility, and this should be considered when using dissolved Al in surface seawater to constrain oceanic dust deposition.

Abstract Observations have shown that the optical colors of Galactic cirrus clouds differ significantly from those of extragalactic sources; thus, they can be used to distinguish Galactic cirrus from extragalactic low surface brightness (LSB) features. To understand these properties, we calculate radiative transfer models in dust clouds, where photons are incident from the ambient interstellar medium (ISM). Dust clouds are modeled to mimic a turbulent medium using a fractional Brownian motion algorithm, resulting in a lognormal density distribution and a power-law power spectral density that are appropriate for the ISM. The results are compared with optical observations of cirrus clouds in the Stripe 82 region. The observed color–color ( g − r , r − i , and i − z ) diagrams of the cirrus clouds can be reproduced by scattered light if the interstellar radiation field (ISRF) of Mathis et al. (as updated by Draine) is modified, either by reducing the intensities in the i and z bands or by enhancing those in the g and r bands. Similar results can also be obtained by adjusting the scattering albedos at the corresponding wavelengths. This demonstrates that the color–color diagrams are effective not only for identifying extragalactic LSB features but also for studying the ISRF and the properties of interstellar dust.

Mineral dust aerosols play an important role in the Earth’s radiation budget and climate system, and their optical properties strongly influence the accuracy of polarization lidar retrievals. Developing realistic optical models is therefore essential for representing dust scattering and polarization behaviors. This study compares three shape models—spheroid, super-ellipsoid, and irregular-hexagonal—in reproducing the optical characteristics of mineral dust at wavelengths of 355, 532, and 1064 nanometers. By combining theoretical simulations with multi-wavelength field and laboratory observations, the suitability of each model is evaluated. Optimal combinations of particle shape and refractive index are obtained using the sum of squared errors criterion. The results show that both the irregular-hexagonal and super-ellipsoid models reproduce the observed relationships between the particle linear depolarization ratio and the lidar ratio, whereas the spheroid model fails to capture high depolarization values. Shape mixing analyses indicate that the irregular-hexagonal model is relatively insensitive to morphological variation, while the super-ellipsoid model exhibits higher adaptability. When measurement uncertainties are considered, the super-ellipsoid model performs best under low error conditions, whereas the irregular-hexagonal model remains more robust under high error conditions. These findings highlight the importance of realistic shape distributions in dust optical modeling and support more reliable polarization lidar retrievals.

Abstract. Cirrus clouds play a crucial role in the Earth's radiation budget. However, direct observations and model simulations of cirrus at high-latitudes are still sparse. In this study, we present the occurrence rate (OR) and geometrical thickness as well as extinction and particle linear depolarization ratio (PLDR) of cirrus at midlatitudes (35–60° N; 30° W–30° E) and high-latitudes (60–80° N; 30° W–30° E) at temperatures below −38 °C using lidar measurements of CALIPSO in the years 2014 and 2018–2021. The results indicate a distinct seasonal cycle in the cirrus occurrence and optical properties. The seasonality in ORs and geometrical thicknesses generally becomes more pronounced with increasing latitude, while the altitude ranges of cirrus decrease with increasing latitude. The extinction coefficients decrease with increasing altitude at both high- and midlatitudes and are, in addition, larger at midlatitudes than at high-latitudes in all seasons. The calculated cirrus optical depths also show larger values at midlatitudes than at high-latitudes, while the differences across latitudes in winter are negligible. The distributions of PLDR in each 5° latitude bin show a general decrease with increasing latitude, leading to a remarkable latitudinal difference with larger values at midlatitudes than at high-latitudes. This indicates larger and more irregular ice crystals forming at midlatitudes than at high-latitudes. Finally, we compare the aerosol concentrations at different latitudes acting as ice-nucleating particles (INPs) to trigger heterogeneous freezing, as reported in previous studies. It turns out that aerosols such as mineral dust and soot (including aviation-induced soot) indicate much larger concentrations at midlatitudes than at high-latitudes.

Abstract The direct radiative effect (DRE) of dust aerosols in Earth system models (ESMs) remains highly uncertain, largely due to inadequate representations of particle size distribution (PSD) and mineral composition. Using NASA's Earth Surface Mineral Dust Source Investigation (EMIT) soil mineralogy data and observed PSD in an ESM that resolves dust mineral composition and emitted diameters from 0.1 to 70 μm, we find a near‐neutral global dust net DRE (−0.057 W m −2 ), weaker than most previous estimates. Large dust (diameter >10 μm) contributes 30% of the global longwave dust optical depth, providing observational constraints on large‐particle abundance, and offsets 20% of the dust shortwave cooling over major source regions. Incorporation of EMIT mineralogy reduces shortwave uncertainty by more than 50%. The remaining uncertainty mainly exists in processes controlling dust abundance, particularly the poorly understood transport of large dust, and longwave optical properties, which require additional observational constraints to more accurately quantify the dust DRE.

We present a novel technique for the decomposition of line-of-sight (LOS) stellar polarization as a function of distance, aimed at reconstructing 3D plane-of-sky magnetic structures in the interstellar medium. The method is based on the assumption that the observed polarization arises from discrete, thin dust layers located at varying distances along the LOS. Using a simple and intuitive frequentist framework, our method identifies structural changes in the distance-sorted cumulative Mahalanobis distance between Stokes parameters (q and u) to detect the locations of dust layers and estimates their associated physical properties (parallax and Stokes parameters) necessary for constructing 3D maps. We benchmarked the method using mock datasets representative of high-Galactic-latitude regions, incorporating realistic parallax uncertainties from Gaia and expected polarization measurements from the upcoming Pasiphae survey. Our tests show that the method reliably recovers the distances and polarization properties of dust clouds when the polarization signal exceeds 0.1%, and the effective fraction of background stars is greater than 10% in our tested samples with ∼ 345 stars. The effect of background star fraction on the performance becomes less critical with increasing amplitude of the polarization source field from the dust cloud. We applied our method to existing polarization data from two illustrative sight lines -- one at intermediate-high Galactic latitude and one near the Galactic plane -- with known tomographic solutions, finding excellent agreement with the literature and demonstrating its accuracy across both regions. We compare the performance of our method with that of the Bayesian method BISP-1. While both methods effectively recover dust cloud properties, our approach is prior-free and computationally more efficient in determining the optimal number of clouds along the LOS. These advantages make our method more flexible and broadly applicable for multilayer dust cloud reconstruction for the upcoming era of large-scale stellar polarization surveys.

Abstract Secondary aerosols are a major component of atmospheric particulate matter, but their formation pathways under different conditions in high mountains remain incompletely understood, impeding accurate assessment of their environmental and climatic impacts. In this study, the physicochemical properties and formation mechanisms of secondary aerosols in cloud‐free, cloud interstitial, and cloud residual particles are investigated at a mountain site in southeastern China. The results show that elevated concentrations of NO 3 − and more‐oxidized oxygenated organic aerosol (MO‐OOA) in cloud‐free particles primarily result from aqueous‐phase reactions along the dust transport. Aqueous‐phase processes during cloud events promoted the formation of NO 3 − , SO 4 2− , NH 4 + and MO‐OOA, with cloud residual particles exhibited 1.2–1.6 times higher growth rates than cloud interstitial particles. Lower fractions of C 4 H 7 + , C 4 H 9 + , C 5 H 6 O + , and C 3 H 7 O 3 + were found in cloud residual particles, suggesting that cloud droplets could facilitate the aging of these organics. Additionally, higher liquid water content increases the O/C ratio in secondary organic aerosols (SOA) by 0.1–0.15, and higher O 3 concentrations facilitate oxidation in cloud droplets via hydroxyl radicals (•OH) production in the acidic cloud water. SOA in cloud residual particles was enriched with carbonyl functional groups (>C=O), suggesting the presence of oxidized acids or esters, which contrasted with less‐oxidized aldehydes/ketones in cloud‐free and cloud interstitial particles. These findings highlight the combined influence of long‐range transport and cloud processing on secondary aerosol chemistry in high mountain region in southeastern China and provide critical insights for improving aerosol‐climate models in topographically complex regions.

Abstract. Light-absorbing organic carbon, collectively known as brown carbon (BrC), significantly influences climate and air quality, particularly in urban environments like Dhaka, Bangladesh. Despite their significance, the contributions and transformation pathways of phenolic compounds – major precursors of brown carbon (BrC) – are still insufficiently understood in the South Asian megacities. This study addresses this gap by investigating the surface morphology of PM2.5, quantifying seven phenolic BrC precursors, and exploring the aqueous-phase formation pathway of nitrophenols at two urban sites (Dhaka South and Dhaka North) from July 2023 to January 2024. Phenolic compounds, including phenol, methylphenols, methoxyphenol, hydroxyphenol, and nitrophenol were identified and quantified using gas chromatography–flame ionization detector (GC-FID). PM2.5 surface morphology and elemental composition were analyzed via Field Emission Scanning Electron Microscopy – Energy Dispersive X-ray Spectroscopy (FESEM-EDX), and functional groups were characterized using Attenuated Total Reflectance – Fourier Transform Infrared Spectroscopy (ATR-FTIR). Results revealed that PM2.5 particles were predominantly spherical or chain-like with carbonaceous elements (C, O, N, S), mineral dust, and trace metals. The dominant functional groups included aromatic conjugate double bond, carbonyl, and nitro group. Aqueous-phase nitration of 2-hydroxyphenol under acidic conditions, analyzed via UV-Vis spectroscopy, demonstrated an alternative nitrophenol formation pathway. Among the detected compounds, 2-hydroxyphenol and 4-nitrophenol showed the highest average concentrations (2.31 ± 1.39 and 2.20 ± 1.21 µg m−3, respectively). Seasonal variations showed elevated nitrophenol levels during winter, especially in Dhaka South (4.54 ± 2.94 µg m−3). These findings highlight the quantification of phenolic precursors and the role of aqueous-phase reactions in BrC formation, providing valuable insights for future atmospheric modeling and air quality management strategies in South Asia.

Trends in Fine Particulate Matter and Source Contributions over the Last Decade in Central Los Angeles (2014-2024): Policy-Driven Declines, COVID-19 Disruptions, and Wildfires.

Spatial-temporal characteristics of microparticles in glacier and waters of the Mt. Yulong region, southeastern Tibetan Plateau.

Environmental radioactivity in atmospheric dust deposition samples from Northern Algeria.

Revealing nitrate photolysis on atmospheric particulate matter (PM), which generates secondary NOx and contributes to haze, acid rain, and daytime HONO formation, offers crucial insights into regulating regional air quality. While in situ spectroscopic techniques are useful to reveal photolysis mechanisms on single-component PM surfaces, it remains challenging to infer the photolysis behavior of mixed PM in real environments and quantify the influencing factors. To mitigate this challenge, we herein utilized artificial intelligence (AI) to capture time-dependent spectral variations, enabling the prediction and analysis of nitrate photolysis in complex atmospheric systems. Specifically, the deterministic learning approach, a novel machine learning (ML) algorithm specialized in modeling and analyzing the nonlinear systems, was innovatively applied to extract critical dynamic characteristic curves from time-series infrared spectra. Taking NH4NO3 photolysis on mineral dust as an example, we developed a spectroscopy-based ML approach that relies on single-component PM data sets and demonstrates its broad applicability by enabling direct prediction of nitrate photolysis trends across diverse mixed-source PMs without experimental measurements. In addition to the predominant contribution of photoactive TiO2 and Fe3O4 to nitrate photolysis by dynamic characteristic curve analysis, we also uncovered and experimentally validated a significant but overlooked inhibitory mechanism exerted by carbonates on these components. This work advances the integration of AI with atmospheric research, offering new perspectives for predicting and analyzing multisystem interactions in atmospheric environments while reducing the reliance on extensive experiments.

We present two case studies of tropospheric aerosol transport observed over the high-altitude Helmos observatory (1800–2300 m a.s.l.) in Greece during September 2021. Two cases were linked to Saharan dust intrusions, of which one was additionally linked to a mixture of biomass-burning and continental aerosols. Aerosol vertical profiles from the AIAS mobile backscatter/depolarization lidar (532 nm, NTUA) revealed distinct aerosol layers between 2 and 6 km a.s.l., with particle linear depolarization ratio values of up to 0.30–0.40, indicative of mineral dust. The elevated location of Helmos allows lidar measurements in the free troposphere, minimizing planetary boundary layer influence and improving the attribution of long-range transported aerosols. Radiative impacts were quantified using the LibRadtran model. For the 27 September dust outbreak, simulations showed strong shortwave absorption within 3–7 km, peaking at 5–6 km, with surface forcing reaching −25 W m−2 and TOA forcing around −12 W m−2, thus, implying a net cooling by 13 W m−2 on the Earth’s atmosphere system. In contrast, the 30 September mixed aerosol case produced substantial solar attenuation, a surface heating rate of 2.57 K day−1, and a small positive forcing aloft (~0.05 K day−1). These results emphasize the contrasting radiative roles of dust and smoke over the Mediterranean and the importance of high-altitude observatories for constraining aerosol–radiation interactions.

Abstract. Saharan dust deposits frequently turn alpine glaciers orange and darken their surface. Together with other light-absorbing particles, mineral dust reduces snow albedo, increases snow melt rate, and lowers the surface mass balance of glaciers. Since the surface mass balance drives the evolution of alpine glaciers, assessing the impact of impurities helps to understand their current and future evolution. The location of impurities within the snowpack and their effect on snow albedo can be estimated through physical modelling. In this study, we quantified the impact of dust, taking into account mineral dust and black carbon in snow, on the Argentière Glacier over the period 2019–2022. Our results show that during the three years preceding 2022, the contribution of mineral dust to the annual decrease in surface mass balance was between 0.31–0.45 m w.e., while it reached the double in 2022 with 0.63 m w.e. [0.54, 0.69] (median, [Q10–Q90]), and up to 1.2 m w.e. [0.9, 1.4] at specific locations. The impact of dust in snow was unevenly distributed over the glacier, especially in 2022. The highest simulated impacts occurred where firn layers from previous years were exposed after the total melt of the snowpack of the previous winter. The gravitational redistribution of the snow from avalanches was not taken into account, which can reduce the impact of dust at specific locations. Increasing the modelled scavenging efficiency of black carbon can double the impact of dust alone at the glacier scale. In general, the contribution of mineral dust to the melt represents between 8 % and 16 % of Argentière Glacier summer melt depending on the year. Hence, we recommend accounting for impurities to simulate the distributed surface mass balance of glaciers.

Abstract. In situ observations are currently used to classify synoptic cirrus as formed by homogeneous or heterogeneous ice nucleation based on ice residual analysis. We use UCLALES-SALSA to show the limitations of this method by demonstrating that prior heterogeneous freezing events can shape the thermodynamic conditions for homogeneous freezing to occur more likely in subsequent nucleation events. In a single-cloud case study of synoptic cirrus from NASA’s Midlatitude Airborne Cirrus Properties Experiment (MACPEX), observations suggest homogeneous freezing as the dominant nucleation mechanism, despite the other mission days with synoptic cirrus showing generally heterogeneous freezing characteristics. Model simulations reveal that ice residual analysis cannot capture influence of earlier heterogeneous freezing events, where mineral dust acted as ice-nucleating particles (INPs). These earlier events depleted INPs at cloud-forming altitudes, enabling homogeneous freezing at the time of observations. Cirrus cloud properties were simulated using measured meteorological and aerosol conditions and compared with observed cloud structures. Results show that modeling the impact of prior nucleation events on the vertical distribution of mineral dust and humidity in the model is necessary to reproduce the observed cloud characteristics. Heterogeneous freezing played a role in the removal of active mineral dust from cloud-forming altitudes well before arriving at the measurement location, while having limited role in forming ice crystals shortly before the time of measurements. Simulations also show that small-scale wave activity significantly influenced ice nucleation efficiency and cloud properties. Although large-scale atmospheric dynamics typically dominate synoptic cirrus formation, they alone were insufficient to replicate the observed cloud characteristics.

Chronic multilobar segmental bronchial stenosis (CMBS) is a chronic inflammatory airway disease characterized by stenosis across multiple lobar and segmental bronchi, primarily diagnosed via bronchoscopy. Epidemiologically, its prevalence exhibits significant regional variation, ranging from 0.1% to 22.5%, with higher rates observed in developing countries, rural populations, women, and individuals with a history of tuberculosis. Clinically, CMBS manifests as progressive dyspnea, chronic cough, recurrent pulmonary infections, and obstructive ventilatory dysfunction that is typically poorly responsive to bronchodilators. Radiologically, high-resolution computed tomography (HRCT) reveals characteristic bronchial wall thickening, luminal narrowing, and often associated mediastinal or peribronchial calcified lymph nodes. Long-term exposure to biomass fuel smoke (e.g., from wood or coal combustion), is established as a major etiological factor. Other significant risk factors include prior tuberculosis infection, and occupational exposures to inhalable irritants like silica dust in mining or textile workers. Despite its considerable global disease burden, the precise pathogenesis remains elusive. Research has identified transforming growth factor-β1 (TGF-β1) as a pivotal regulator of airway remodeling in various chronic respiratory diseases, such as asthma and chronic obstructive pulmonary disease (COPD). Notably, animal models of chronic biomass smoke exposure demonstrate a significant correlation between upregulated TGF-β1 expression and a distinct airway remodeling phenotype, suggesting its potential involvement in the pathological progression of CMBS. Accumulating evidence indicates that TGF-β1 mediates airway remodeling through multiple intricate mechanisms, including immune dysregulation, fibroblast activation and proliferation, aberrant extracellular matrix (ECM) deposition, epithelial-mesenchymal transition (EMT), and pathological vascular remodeling. In recent years, groundbreaking progress has been made in research on therapeutics targeting the TGF-β1 signaling pathway, including monoclonal antibodies (e.g., Fresolimumab), small molecule kinase inhibitors (e.g., Galunisertib, TEW-7197), and novel targeted delivery systems. This review systematically summarizes the molecular mechanisms of TGF-β1 in CMBS airway remodeling and the advances in the development of targeted drugs. Furthermore, it proposes future research directions focused on CMBS-specific applications, such as validating these therapeutics in preclinical CMBS models, developing inhaled formulations for localized delivery, establishing biomarker-driven patient stratification, and exploring combination therapies with anti-fibrotic agents. This aims to provide a comprehensive theoretical foundation for elucidating the disease’s pathology and developing novel, precise diagnostic and therapeutic strategies for CMBS.

Abstract Planets and their host stars form from the same cloud of gas and dust, so we assume that their chemical compositions are linked. However, a clear correlation between rocky planet interior properties and host star chemistry remains elusive for planets around FGK dwarfs, and nonexistent for planets around M dwarfs because cool stars frequently lack detailed chemical information. Here, we investigate the relationship between small ( R P ≤ 1.8 R ⊕ ) planet densities and host star elemental abundances. We use the Sloan Digital Sky Survey-V/Milky Way Mapper and an accompanying data-driven framework to obtain abundances for FGK and M dwarf hosts of 22 rocky planets. We find that planet densities exhibit a strong, inverse relationship to [Mg/Fe] abundances of FGK hosts ( p = 0.001). This correlation becomes more significant with the addition of M dwarf hosts ( p = 0.0005). If we assume that rocky planets have terrestrial-like compositions, this suggests that low [Mg/Fe] environments form planets with larger Fe-rich cores and thus higher densities. The thick disk planets in our sample help anchor this trend, illustrating the importance of sampling exoplanet properties across a range of host star populations. This finding highlights the connection between Galactic chemical evolution and rocky planet formation, and indicates that Earth-like planet compositions may vary significantly across different regions of the Galaxy.