Dust Model Research Articles

The (mis)identification of high-latitude dust events using remote sensing methods in the Yukon, Canada: a sub-daily variability analysis

Abstract. The observation and quantification of mineral dust fluxes from high-latitude sources remains difficult due to a known paucity of year-round in situ observations and known limitations of satellite remote sensing data (e.g. cloud cover and dust detection). Here we explore the chronology of dust emissions at a known and instrumented high-latitude dust source: Lhù'ààn Mân (Kluane Lake) in Yukon, Canada. At this location we use oblique time-lapse (RC) cameras as a baseline for analysis of aerosol retrievals from in situ metrological data, AERONET, and co-incident MODIS MAIAC to (i) investigate the daily to annual chronology of dust emissions recorded by these instrumental and remote sensing methods (at timescales ranging from minutes to years) and (ii) use data intercomparisons to comment on the principal factors that control the detection of dust in each case. Lhù'ààn Mân is a prolific mineral dust source; on 24 May 2018 the RC captured dust in motion throughout the entire day, with the longest dust-free period lasting only 30 min. When compared with time series of RC data, optimized AERONET data only manage an overall 26 % detection rate for events (sub-day) but 100 % detection rate for dust event days (DEDs) when dust was within the field of view. In this instance, RC and remote sensing data were able to suggest that the low event detection rate was attributed to fundamental variations in dust advection trajectory, dust plume height, and inherent restrictions in sun angle at high latitudes. Working with a time series of optimized aerosol optical depth (AOD) data (covering 2018/2019), we were able to investigate the gross impacts of data quality (DQ) choice on DED detection at the month or year scale. Relative to ground observations, AERONET's DQ2.0 cloud-screening algorithm may remove as much as 97 % of known dust events (3 % detection). Finally, when undertaking an AOD comparison for DED and non-DED retrievals, we find that cloud screening of MODIS/AERONET lead to a combined low sample of co-incident dust events and weak correlations between retrievals. Our results quantify and explain the extent of under-representation of dust in both ground and space remote sensing methods; this is a factor that impacts on the effective calibration and validation of global climate and dust models.

A study of the correlation between polarization maximum to minimum ratio and scattering parameters in a spheroid dust model

This paper investigates the correlation between the ratio of polarization maximum to polarization minimum (Pz) and different scattering parameters such as complex refractive indices (m=n+ik), effective radius (reff), effective variance (veff), and axial ratio (E) for spheroidal particles. The simulations are executed using the double-precision T-matrix code for randomly oriented spheroidal particles, considering different sets of scattering parameters. For a specific range of n, k, E, reff, and veff, a strong correlation between Pz and other scattering parameters is observed in all cases, which can be fitted by a second-degree polynomial equation. The simulations are conducted at two wavelengths (λ=0.50 µm and 0.65 µm). Additionally, we compare our results obtained from numerical simulation with the experimental data for a few forsterite samples conducted by Muñoz et al. (2021). A set of conclusions is presented based on our work.

Toward a better understanding of the mid-infrared emission in the Large Magellanic Cloud

Context. The scarcity of spectroscopic data with a high signal-to-noise ratio in the interstellar medium between 20 and 100 μm has led to the development of several dust models with distinct dust properties that are poorly constrained in this broad wavelength range. Some of them require the presence of graphites, whereas others consider small amorphous or small aromatic carbon grains, with various dust sizes. Aims. We aim to constrain the dust emission in the mid- to far-infrared domain in the Large Magellanic Cloud (LMC) for the first time with the use of the Spitzer IRS and MIPS spectral energy distribution (SED) data, combined with Herschel data. We also consider ultraviolet extinction predictions derived from modeling. Methods. We selected ten regions that were observed as part of the SAGE-Spec program (PI: F. Kemper) to probe dust properties in various environments (diffuse, molecular, and ionized regions). All data were smoothed to the 40″ angular resolution before we extracted the dust emission spectra and photometric data. The SEDs were modeled with dust models available in the DustEM package, using the standard Mathis radiation field, as well as three additional radiation fields, with stellar clusters ages ranging from 4 Myr to 600 Myr. Results. Previous analyses of molecular clouds in the LMC have reasonably well reproduced the SEDs of the different phases of the clouds constructed from near- to far-infrared photometric data using the DustEM models. However, only by using spectroscopic data and by changing the dust abundances and size distributions in comparison with our Galaxy we were able to derive new constraints on the small- grain component. Standard dust models (with free dust abundances) that were used to reproduce the Galactic diffuse medium are clearly not able to reproduce the dust emission in the mid-infrared wavelength domain. This analysis shows the need of adjusting the parameters describing the dust size distribution, which shows a clearly distinct behavior depending on the type of environment. In addition, whereas the small-grain emission always seems to be negligible at long wavelengths in our Galaxy, the contribution of this small-dust component might be stronger than expected in the submillimeter to millimeter range in the LMC-averaged SED. Conclusions. The properties of the small-dust component of the LMC are clearly different from those of our Galaxy. Its abundance, which is significantly enhanced, might be the result of the shattering of large grains through strong shocks or turbulence. In addition, this grain component in the LMC systematically shows smaller grain sizes in the ionized regions than in the diffuse medium. Predictions of extinction curves show significantly distinct behaviors depending on the dust models, but they are also different from one region to the next. A comparison of model predictions with the LMC mean extinction curve shows that no model agrees satisfactorily when the Mathis radiation field is used, but a harder radiation field tends to improve the agreement.

Lightning: An X-Ray to Submillimeter Galaxy SED-fitting Code with Physically Motivated Stellar, Dust, and AGN Models

We present an updated version of Lightning, a galaxy spectral energy distribution (SED) fitting code that can model X-ray to submillimeter observations. The models in Lightning include the options to contain contributions from stellar populations, dust attenuation and emission, and active galactic nuclei (AGNs). X-ray emission, when utilized, can be modeled as originating from stellar compact binary populations with the option to include emission from AGNs. We have also included a variety of algorithms to fit the models to observations and sample parameter posteriors; these include adaptive Markov Chain Monte Carlo (MCMC), affine-invariant MCMC, and Levenberg–Marquardt gradient-descent (MPFIT) algorithms. To demonstrate some of the capabilities of Lightning, we present several examples using a variety of observational data. These examples include (1) deriving the spatially resolved stellar properties of the nearby galaxy M81, (2) demonstrating how X-ray emission can provide constraints on the properties of the supermassive black hole of a distant AGN, (3) exploring how to rectify the attenuation effects of inclination on the derived the star formation rate of the edge-on galaxy NGC 4631, (4) comparing the performance of Lightning to similar Bayesian SED-fitting codes when deriving physical properties of the star-forming galaxy NGC 628, and (5) comparing the derived X-ray and UV-to-IR AGN properties from Lightning and CIGALE for a distant AGN. Lightning is an open-source application developed in IDL and is available at https://github.com/rafaeleufrasio/lightning.

Machine learning-assisted dispersion modelling based on genetic algorithm-driven ensembles: An application for road dust in Helsinki

A novel Machine Learning (ML) approach is proposed to assist the dispersion modelling of road dust in an urban area. The aim is to improve ENFUSER model's coarse particle nowcasting estimations, especially during the road dust period in springtime. We assist the dispersion model by combining road condition measurements, regional-scale air quality forecasts, meteorological data, road maintenance information, detailed traffic patterns, as well as GIS-data, for the Helsinki area, via a ML based data fusion procedure. The proposed pipeline consists of feature engineering, a set of feature selection methods, and a Genetic Algorithm search for the optimal stacking ensemble configuration, as well as robust validation in both space and time dimensions. Results suggest that our approach enhances the current ENFUSER capabilities, and thus could be applied to assist its performance under operational conditions, while also offering potential as a versatile tool for addressing a broad range of similar tasks.

Observed dust surface density across cosmic times

ABSTRACT Our ability to interpret observations of galaxies and trace their stellar, gas, and dust content over cosmic time critically relies on our understanding of how the dust abundance and properties vary with environment. Here, we compute the dust surface density across cosmic times to put novel constraints on simulations of the build-up of dust. We provide observational estimates of the dust surface density consistently measured through depletion methods across a wide range of environments, going from the Milky Way up to z = 5.5 galaxies. These conservative measurements provide complementary estimates to extinction-based observations. In addition, we introduce the dust surface density distribution function – in analogy with the cold gas column density distribution functions. We fit a power law of the form log f(ΣDust) = −1.92 × log ΣDust − 3.65, which proves slightly steeper than that for neutral gas and metal absorbers. This observed relation, which can be computed by simulations predicting resolved dust mass functions through 2D projection, provides new constraints on modern dust models.

The Astrodust+PAH Model: A Unified Description of the Extinction, Emission, and Polarization from Dust in the Diffuse Interstellar Medium

We present a new model of interstellar dust in which large grains are a single composite material, “astrodust,” and nanoparticle-sized grains come in distinct varieties including polycyclic aromatic hydrocarbons (PAHs). We argue that a single-composition model for grains larger than ∼0.02 μm most naturally explains the lack of frequency dependence in the far-infrared (FIR) polarization fraction and the characteristic ratio of optical to FIR polarization. We derive a size distribution and alignment function for 1.4:1 oblate astrodust grains that, with PAHs, reproduce the mean wavelength dependence and polarization of Galactic extinction and emission from the diffuse interstellar medium while respecting constraints on solid-phase abundances. All model data and Python-based interfaces are made publicly available.

The Lyα Reference Sample. XIV. Lyα Imaging of 45 Low-redshift Star-forming Galaxies and Inferences on Global Emission

We present Lyα imaging of 45 low-redshift star-forming galaxies observed with the Hubble Space Telescope. The galaxies have been selected to have moderate to high star formation rates (SFRs) using far-ultraviolet (FUV) luminosity and Hα equivalent width criteria, but no constraints on Lyα luminosity. We employ a pixel stellar continuum fitting code to obtain accurate continuum-subtracted Lyα, Hα, and Hβ maps. We find that Lyα is less concentrated than FUV and optical line emission in almost all galaxies with significant Lyα emission. We present global measurements of Lyα and other quantities measured in apertures designed to capture all of the Lyα emission. We then show how the escape fraction of Lyα relates to a number of other measured quantities (mass, metallicity, star formation, ionization parameter, and extinction). We find that the escape fraction is strongly anticorrelated with nebular and stellar extinction, weakly anticorrelated with stellar mass, but no conclusive evidence for correlations with other quantities. We show that Lyα escape fractions are inconsistent with common dust extinction laws, and discuss how a combination of radiative transfer effects and clumpy dust models can help resolve the discrepancies. We present an SFR calibration based on Lyα luminosity, where the equivalent width of Lyα is used to correct for nonunity escape fraction, and show that this relation provides a reasonably accurate SFR estimate. We also show stacked growth curves of Lyα for the galaxies that can be used to find aperture loss fractions at a given physical radius.

Joint Modelling of Dust Scattering and Thermal Emission: The Spider Complex

Observations across the electromagnetic spectrum of radiative processes involving interstellar dust—emission, absorption, and scattering—are used to constrain the parameters of dust models and more directly to aid in foreground removal of dust for extragalactic and cosmological observations. Dust models can benefit from more independent constraints from complementary observations. Here, we quantify the relationship between scattered light and thermal emission from dust in a diffuse (cirrus) intermediate-latitude cloud, Spider, using data from the Dragonfly Telephoto Array and the Herschel Space Observatory. A challenge for optical observations of faint diffuse cirrus is accurate removal of a contaminating, spatially varying sky. We present a technique to analyze two images of the same cirrus field concurrently, correlating pixel values to capture the relationship and simultaneously fitting the sky-related signal as a complex noncorrelating additive component. For the Spider, we measure a color g − r = 0.644 ± 0.024 and ratios of visible-wavelength to 250 μm intensity of γ g,250 = (0.855 ± 0.025) × 10−3 and γ r,250 = (1.55 ± 0.08) × 10−3 for the g and r-bands, respectively. We show how to use any dust model that matches the thermal dust emission to predict an upper limit to the amount of scattered light. The actual brightness of the cirrus will be fainter than this limit because of anisotropic scattering by the dust combined with anisotropy of the incident interstellar radiation field (ISRF). Using models of dust and the ISRF in the literature, we illustrate that the predicted brightness is indeed lower, though not as faint as the observations indicate.

Satellites reveal Earth's seasonally shifting dust emission sources

Establishing mineral dust impacts on Earth's systems requires numerical models of the dust cycle. Differences between dust optical depth (DOD) measurements and modelling the cycle of dust emission, atmospheric transport, and deposition of dust indicate large model uncertainty due partially to unrealistic model assumptions about dust emission frequency. Calibrating dust cycle models to DOD measurements typically in North Africa, are routinely used to reduce dust model magnitude. This calibration forces modelled dust emissions to match atmospheric DOD but may hide the correct magnitude and frequency of dust emission events at source, compensating biases in other modelled processes of the dust cycle. Therefore, it is essential to improve physically based dust emission modules.Here we use a global collation of satellite observations from previous studies of dust emission point source (DPS) dichotomous frequency data. We show that these DPS data have little-to-no relation with MODIS DOD frequency. We calibrate the albedo-based dust emission model using the frequency distribution of those DPS data. The global dust emission uncertainty constrained by DPS data (±3.8 kg m−2 y−1) provides a benchmark for dust emission model development. Our calibrated model results reveal much less global dust emission (29.1 ± 14.9 Tg y−1) than previous estimates, and show seasonally shifting dust emission predominance within and between hemispheres, as opposed to a persistent North African dust emission primacy widely interpreted from DOD measurements.Earth's largest dust emissions, proceed seasonally from East Asian deserts in boreal spring, to Middle Eastern and North African deserts in boreal summer and then Australian shrublands in boreal autumn-winter. This new analysis of dust emissions, from global sources of varying geochemical properties, have far-reaching implications for current and future dust-climate effects. For more reliable coupled representation of dust-climate projections, our findings suggest the need to re-evaluate dust cycle modelling and benefit from the albedo-based parameterisation.

An Improved Pair Method to Probe the Dust Extinction Law

Dust extinction law is crucial to recover the intrinsic energy distribution of celestial objects and infer the characteristics of interstellar dust. Based on the traditional pair method, an improved pair method is proposed to model the dust extinguished spectral energy distribution (SED) of an individual star. Instead of the mathematically parameterizing extinction curves, the extinction curves in this work are directly from the silicate-graphite dust model, so that the dust extinction law can be obtained and the dust properties can be analyzed simultaneously. The ATLAS9 stellar model atmosphere is adopted for the intrinsic SEDs in this work, while the silicate-graphite dust model with a dust size distribution of for each component is adopted for the model extinction curves. One typical extinction tracer in the dense region (V410 Anon9) and one in the diffuse region (Cyg OB2 #12) of the Milky Way are chosen to test the reliability and the practicability of the improved pair method in different stellar environments. The results are consistent with their interstellar environments and are in agreement with the previous observations and studies, which prove that the improved pair method is effective and applicable in different stellar environments. In addition to the reliable extinction results, the derived parameters in the dust model can be used to analyze the dust properties, which cannot be achieved by other methods with the mathematical extinction models. With the improved pair method, the stellar parameters can also be inferred and the extinction law beyond the wavelengths of observed data can be predicted based on the dust model as well.

MmWave Compound Link Budget Model of Dust and Humidity Effect

mmWave Path Loss (PL) Link Budget (LB) modeling considerations are based on many different factors. For instance, the third generation partnership project (3GPP) model is mainly based on the distance from an Access Point (AP) and the frequency of transmission as well as the transmission link budget situation. Furthermore, there are certain interesting models about the effects of dust and humidity on the mmWave propagation. These models had introduced the consequences of the humid and dusty environments without consideration for the additional mmWave transmission LB parameters. First of all, this paper introduces an average dust and humidity model based on statistical Z-test in order to overcome the variation in the results between the three chosen models for dust and humidity effect in the mmWave range. Secondly, it proposes LB compound model, that comprises 3GPP PL LB with an average dust and humidity model. This introduced compound model has been applied on RMa PL LB with and without the presence of dust and humidity. The simulation of the presented model has been applied for distinct distances from the AP and mmWave transmission frequency range from 0.5 to 30 GHz.

Frequency dependence of the thermal dust E/B ratio and EB correlation: Insights from the spin-moment expansion

The change of physical conditions across the turbulent and magnetized interstellar medium induces a 3D spatial variation of the properties of Galactic polarized emission. The observed signal results from the averaging of different spectral energy distributions (SEDs) and polarization angles along and between lines of sight. As a consequence, the total Stokes parameters Q and U will have different frequency dependencies, both departing from the canonical emission law, so that the polarization angle becomes frequency dependent. In the present work, we show how this phenomenon similarly induces a different, distorted SED for the three polarized angular power spectra 𝒟𝓁EE, 𝒟𝓁BB, and 𝒟𝓁EB, implying a variation of the 𝒟𝓁EE/𝒟𝓁BB ratio with frequency. We demonstrate how the previously introduced “spin-moment” formalism provides a natural framework to grasp these effects and enables us to derive analytical predictions for the spectral behaviors of the polarized spectra, focusing here on the example of thermal dust polarized emission. After a quantitative discussion based on a model combining emission from a filament with its background, we further reveal that the spectral complexity implemented in the dust models commonly used by the cosmic microwave background (CMB) community includes different distortions for the three polarized power-spectra. This new understanding is crucial for CMB component separation, in which extreme accuracy is required for the modeling of the dust signal to allow for the search of the primordial imprints of inflation or cosmic birefringence. For the latter, as long as the dust EB signal is not measured accurately, great caution is required regarding the assumptions made to model its spectral behavior, as it may not be inferred from the other dust angular power spectra.

A Comprehensive Model of Morphologically Realistic Cosmic Dust Particles: An Application to Mimic the Unusual Polarization Properties of the Interstellar Comet 2I/Borisov

The cosmic dust particles found in space are mainly porous aggregates of smaller grains. Theoretically, these aggregates are replicated using fractal geometry, assuming a cluster of spheres. Although the light scattering response of cosmic dust aggregates has been thoroughly studied using clusters of spherical grains in the past few decades, the effect of irregularities on the surface of each grain in an entire aggregate has mostly been neglected. We introduce, for the first time, a visually realistic cosmic dust model that incorporates a mixture of rough fractal aggregates (RFA) and agglomerated debris (Solids) to replicate the unusual polarization–phase curve observed in the case of the interstellar comet 2I/Borisov at multiple wavelengths. The authenticity of the RFA structures has been verified by replicating light scattering results of circumstellar dust analogs from the Granada Amsterdam Light Scattering Database. We demonstrate that the light scattering response from the RFA structures has a very close resemblance to the experimental values. Finally, we model the observed polarization–phase curve of the interstellar comet 2I/Borisov using a mixture of RFA and solid particles. The best-fit data indicate the presence of a higher percentage of porous RFA structures (80%) owing to the fact that the comet carries a higher percentage of small and highly porous pristine cosmic dust particles. Further, the model indicates that the unusually steep polarimetric slope and the high dust-to-gas ratio in newer comets are mainly due to a higher porous-to-compact ratio.

Modelling the European wind-blown dust emissions and their impact on particulate matter (PM) concentrations

Abstract. Wind-blown dust (WBD) emitted by the Earth’s surface due to sandblasting can potentially have important effects on both climate and human health via interaction with solar and thermal radiation, reducing air quality. Apart from the main dust “centres” around the world, like deserts, dust can be emitted from partly vegetated mid- and high-latitude areas like Europe if certain conditions are suitable (strong winds, bare soil, reduced soil moisture, etc.). Using a wind-blown dust model (WBDUST) along with a chemical transport model (Comprehensive Air-quality model with Extensions, CAMx) coupled to a regional climate model (Weather Research and Forecasting, WRF), this study is one of the first to provide a model-based estimate of such emissions over Europe as well as the long-term impact of WBD emissions on the total particulate matter (PM) concentrations for the 2007–2016 period. We estimated average WBD emissions of about 0.5 and 1.5 Mgyr-1km-2 in fine and coarse modes. Maximum emissions occur over Germany, where the average seasonal fine- and coarse-mode emission flux can reach 0.5 and 1 gs-1km-2, respectively. Large variability is seen in the averaged daily emissions with values of up to 2 gs-1km-2 for the coarse-mode aerosol on selected days. The WBD emissions increased the modelled winter PM2.5 and PM10 concentrations by up to 10 and 20 µg m−3, respectively, especially over Germany, where the highest emissions occur. The impact on other seasons is lower. Much higher impacts are modelled, however, on selected days when occasionally the urban PM2.5 and PM10 concentrations are increased by more than 50 and 100 µg m−3. The comparison with measurements revealed that if WBD is considered, the summer biases are reduced; however, the winter PM is overestimated even more greatly (so the bias increases). We identified a strong overestimation of the modelled wind speed (the maximum daily wind is almost 2 times higher in WRF than the measured ones) suggesting that WBD emissions are also overestimated – hence the enhanced winter PM biases. Moreover, we investigated the secondary impacts of the crustal composition of fine WBD particles on secondary inorganic aerosol (SIA): sulfates (PSO4), nitrates (PNO3) and ammonium (PNH4). Because the water pH value, and thus the uptake of the gaseous precursors of SIA, is perturbed and because the increased aerosol surface serves as an oxidation site, we modelled seasonal PSO4 and PNO3 concentrations increased by up to 0.1 µg m−3 and PNH4 ones decreased by up to −0.05 µg m−3, especially during winter. In terms of average daily impact, these numbers can, however, reach much larger values of up to 1–2 µg m−3 for sulfates and nitrates, while the decrease in ammonium due to WBD can reach −1 µg m−3 on selected days. The sensitivity test on the choice of the inorganic equilibrium model (ISORROPIA vs. EQuilibrium Simplified Aerosol Model V4, EQSAM) showed that if EQSAM is used, the impact on SIA is slightly stronger (by a few 10 %) due to larger number of cations considered for water pH in EQSAM. Our results have to be regarded as a first estimate of the long-term WBD emissions and the related effects on PM over Europe. Due to the strong positive wind bias and hence strong WBD emissions, we should consider these results as an upper bound. More sensitivity studies involving the impact of the driving meteorological fields, WBD model choice and the input data used to describe the land surface need to be carried out in future to better constrain these emissions.

Thez≲ 1 drop of cosmic dust abundance in a semi-analytic framework

ABSTRACTObservations suggest that the amount of galactic dust in the Universe decreased by a factor of ∼2–3 during the last ∼8 Gyr. However, cosmological models of galaxy evolution usually struggle to explain this decrease. Here, we use the semi-analytic model (SAM) L-Galaxies2020 to show that this drop may be reproduced assuming standard prescriptions for dust production and evolution. We extend the SAM with (i) a state-of-the-art dust model that adopts the two-size approximation and (ii) a new disc instability criterion that triggers bulge and central black hole growth. The model reproduces some fundamental properties of the local galaxy population, such as the fraction of spheroid-dominated galaxies and some scaling relations involving dust. Moreover, the model predicts a galactic dust drop from z ∼ 1 → 0, which becomes closer to the observed one when adopting the new treatment of disc instabilities. This result is related to the newly implemented supermassive black hole growth during disc instabilities, which enhances the quenching of massive galaxies. Consequently, these objects feature a lower gas and dust content. We provide a census of the contribution of all the processes affecting the galactic dust content. Accretion is the dominant dust mass growth process. Destruction by supernovae, astration and ejection by winds have all a non-negligible role in decreasing the overall dust content in galaxies below z ∼ 1. We also discuss predictions concerning extra-galactic dust, confirming that a sputtering efficiency lower than the canonical one is required to match the few available observations.

Deep multi-task learning for early warnings of dust events implemented for the Middle East

Events of high dust loading are extreme meteorological phenomena with important climate and health implications. Therefore, early forecasting is critical for mitigating their adverse effects. Dust modeling is a long-standing challenge due to the multiscale nature of the governing meteorological dynamics and the complex coupling between atmospheric particles and the underlying atmospheric flow patterns. While physics-based numerical modeling is commonly being used, we propose a meteorological-based deep multi-task learning approach for forecasting dust events. Our approach consists of forecasting the local PM10 (primary task) measured in situ, and simultaneously to predict the satellite-based regional PM10 (auxiliary task); thus, leveraging valuable information from a correlated task. We use 18 years of regional meteorological data to train a neural forecast model for dust events in Israel. Twenty-four hours before the dust event, the model can detect 76% of the events with even higher predictability of winter and spring events. Further analysis shows that local dynamics drive most misclassified events, meaning that the coherent driving meteorology in the region holds a predictive skill. Further, we use machine-learning interpretability methods to reveal the meteorological patterns the model has learned, thus highlighting the important features that govern dust events in the Middle East, being primarily lower-tropospheric winds, and Aerosol Optical Depth.

On the Association between Fine Dust Concentrations from Sand Dunes and Environmental Factors in the Taklimakan Desert

Dust in sand dunes is an effective and important source of dust emission. The Taklimakan Desert (TD) is one of the main sources of global dust: the sand dunes account for approximately 85% of the total area of the TD. However, the dust concentration, emission characteristics, and physical factors of different parts of the sand dunes in the TD during the day and night, as well as dust and non-dust days, remain unclear. In this study, dust observations were collected over a 3 month period in the TD to investigate the physical processes by which dust moves across a surface and generates PM10 and PM2.5 from the top and bottom of sand dunes. The results showed that the daily average maximum concentrations of particulate matter with diameters below 2.5 and 10 µm (PM2.5 and PM10) in the dune during the observation period reach ~90 and ~190 µg·m−3, respectively. Dust emission generated in the saltation process (maximum emission of PM10 was 3–5 mg·m−2·s−1) in the TD dunes was larger than that in other areas and had a good correlation with u* (friction velocity), where u* = 0.4 m·s−1 was the threshold of sand dune dust emission. The wind speed at the top of dunes was larger than that at the bottom, which was conducive to the accumulation of PM10 at the top of the dune. Furthermore, the MLH (mixed layer height) decreased after sunset and the turbulence weakens, which was conducive to the retention of dust in the air. Moreover, the dust made the solar radiation at the top of the dune −15 W·m−2 (average) lower than at the bottom. These results provided a new understanding of dune emissions in the TD and could be used for dust modeling in regional and global models.

Filaments in the OMC-3 cloud and uncertainties in estimates of filament profiles

Context.Filamentary structures are an important part of star-forming interstellar clouds. The properties of filaments hold clues to their formation mechanisms and their role in the star-formation process.Aims.We compare the properties of filaments in the Orion Molecular Cloud 3 (OMC-3), as seen in mid-infrared (MIR) absorption and far-infrared (FIR) dust emission. We also wish to characterise some potential sources of systematic errors in filament studies.Methods.We calculated optical depth maps of the OMC-3 filaments based on the MIR absorption seen inSpitzerdata and FIR dust emission observed withBerscheland the ArTéMiS instrument. We then compared the filament properties extracted from the data. Potential sources of error were investigated more generally with the help of radiative transfer models.Results.The widths of the selected OMC-3 filament segments are in the range 0.03–0.1 pc, with similar average values seen in both MIR and FIR analyses. Compared to the widths, the individual parameters of the fitted Plummer functions are much more uncertain. The asymptotic power-law index has typically valuesp ~3 but with a large scatter. Modelling shows that the FIR observations can systematically overestimate the filament widths. The effect is potentially tens of per cent at column densities aboveN(H2) ~ 1022cm–2but is reduced in more intense radiation fields, such as the Orion region. Spatial variations in dust properties could cause errors of similar magnitude. In the MIR analysis, dust scattering should generally not be a significant factor, unless there are high-mass stars nearby or the dust MIR scattering efficiency is higher than in the tested dust models. Thermal MIR dust emission can be a more significant source of error, especially close to embedded sources.Conclusions.The analysis of interstellar filaments can be affected by several sources of systematic error, but mainly at high column densities and, in the case of FIR observations, in weak radiation fields. The widths of the OMC-3 filaments were consistent between the MIR and FIR analyses and did not reveal any systematic dependence on the angular resolution of the observations.

Numerical Simulation of Airflow and Dust Migration in Vacuum Vessel During Loss of Vacuum Accident for Updated CFETR

A loss of vacuum accident (LOVA) occurs during in-vessel component failure and air ingress. The airflow characteristics of a LOVA are determined by many factors like initial pressure, location of a break, and size of a break and have a great impact on dust migration, which could cause a serious explosion with incoming air and H2. In this paper, a computational fluid dynamics method is adopted, and the k-ε Shear Stress Transport model for airflow and the Discrete Phase Model for dust are used to simulate a LOVA with the updated Chinese Fusion Engineering Test Reactor (CFETR) tokamak device. The effects of initial pressure, break size, and break location on airflow during the LOVA are discussed, and the effects of dust size, break size, and break location on dust migration during the LOVA are investigated as well. The results indicate that the initial pressure and size of a break have a greater impact on airflow of a LOVA than the location of the break and that both the dust size and the characteristics of the airflow have a greater impact on the distribution of the dust. A break located in the upper port has even more dust chaos. This research is the basis for the safety analysis of the CFETR device, and it provides a reference for subsequent studies on dust removal, mitigation of dust explosions, and radioactive substances.