Dust Model Research Articles

Kpc-scale properties of dust temperature in terms of dust mass and star formation activity

ABSTRACT We investigate how dust temperature is affected by local environmental quantities, especially dust surface density (Σdust), dust-to-gas ratio (D/G), and interstellar radiation field. We compile multiwavelength observations in 46 nearby galaxies, uniformly processed with a common physical resolution of 2 kpc. A physical dust model is used to fit the infrared dust emission spectral energy distribution (SED) observed with WISE and Herschel. The star formation rate (SFR) is traced with GALEX ultraviolet data corrected by WISE infrared. We find that the dust temperature correlates well with the SFR surface density (ΣSFR), which traces the radiation from young stars. The dust temperature decreases with increasing D/G at fixed ΣSFR, as expected from stronger dust shielding at high D/G, when ΣSFR is higher than $\sim 2\times 10^{-3}~\rm M_\odot ~yr^{-1}~kpc^{-2}$. These measurements are in good agreement with the dust temperature predicted by our proposed analytical model. Below this range of ΣSFR, the observed dust temperature is higher than the model prediction and is only weakly dependent on D/G, possibly due to dust heating from an old stellar population or the variation of SFR within the past 1010 yr. Overall, the dust temperature as a function of ΣSFR and Σdust predicted by our analytical model is consistent with observations. We also notice that, at fixed gas surface density, ΣSFR tends to increase with D/G, i.e. we can modify the Kennicutt–Schmidt law empirically with a dependence on D/G to match observations better.

New Mechanical Models to Study the Impact of Contact, Wear, and Adhesion of Lunar Dust on Space Materials

Lunar dust significantly impacts spacecraft and spacesuits during lunar exploration. The mechanical properties of lunar dust, including adhesion, contact, and wear, are investigated using new mechanical models proposed herein. First, the main contribution for mechanics of this paper was implementing the conical Johnson, Kendall, and Roberts (JKR) model using the energy method for investigating the normal and tangential mechanical characteristics of lunar dust. Additionally, the mechanical properties of lunar dust, such as adhesion, contact, and wear are proposed considering the adhesion effect using the mechanical model. The validity and accuracy of the conical JKR model were verified by comparing the results with experimental data and existing spherical and cylindrical JKR models. Furthermore, a new wear mechanical model for typical lunar dust is proposed considering the adhesion effect. The wear width and coefficients based on the wear model fit well with the existing experiment; therefore, the proposed model can be used to calculate the wear coefficient. Additionally, it can be used to estimate the contact force using an atomic force microscope (AFM) probe and analyze the adhesion between rough particles. The mechanical properties of lunar dust based on our models can be valuable for the characteristic research of in situ resource development and manned lunar landings.

Application of a satellite-retrieved sheltering parameterization (v1.0) for dust event simulation with WRF-Chem v4.1

Abstract. Roughness features (e.g., rocks, vegetation, furrows) that shelter or attenuate wind flow over the soil surface can considerably affect the magnitude and spatial distribution of sediment transport in active aeolian environments. Existing dust and sediment transport models often rely on vegetation attributes derived from static land use datasets or remotely sensed greenness indicators to incorporate sheltering effects on simulated particle mobilization. However, these overly simplistic approaches do not represent the three-dimensional nature or spatiotemporal changes of roughness element sheltering. They also ignore the sheltering contribution of non-vegetation roughness features and photosynthetically inactive (i.e., brown) vegetation common to dryland environments. Here, we explore the use of a novel albedo-based sheltering parameterization in a dust transport modeling application of the Weather Research and Forecasting model with Chemistry (WRF-Chem). The albedo method estimates sheltering effects on surface wind friction speeds and dust entrainment from the shadows cast by subgrid-scale roughness elements. For this study, we applied the albedo-derived drag partition to the Air Force Weather Agency (AFWA) dust emission module and conducted a sensitivity study on simulated PM10 concentrations using the Georgia Institute of Technology–Goddard Global Ozone Chemistry Aerosol Radiation and Transport (GOCART) model as implemented in WRF-Chem v4.1. Our analysis focused on a convective dust event case study from 3–4 July 2014 for the southwestern United States desert region discussed by other published works. Previous studies have found that WRF-Chem simulations grossly overestimated the dust transport associated with this event. Our results show that removing the default erodibility map and adding the drag parameterization to the AFWA dust module markedly improved the overall magnitude and spatial pattern of simulated dust conditions for this event. Simulated PM10 values near the leading edge of the storm substantially decreased in magnitude (e.g., maximum PM10 values were reduced from 17 151 to 8539 µg m−3), bringing the simulated results into alignment with the observed PM10 measurements. Furthermore, the addition of the drag partition restricted the erroneous widespread dust emission of the original model configuration. We also show that similar model improvements can be achieved by replacing the wind friction speed parameter in the original dust emission module with globally scaled surface wind speeds, suggesting that a well-tuned constant could be used as a substitute for the albedo-based product for short-duration simulations in which surface roughness is not expected to change and for landscapes wherein roughness is constant over years to months. Though this alternative scaling method requires less processing, knowing how to best tune the model winds a priori could be a considerable challenge. Overall, our results demonstrate how dust transport simulation and forecasting with the AFWA dust module can be improved in vegetated drylands by calculating the dust emission flux with surface wind friction speed from a drag partition treatment.

The Art of Measuring Physical Parameters in Galaxies: A Critical Assessment of Spectral Energy Distribution Fitting Techniques

The study of galaxy evolution hinges on our ability to interpret multiwavelength galaxy observations in terms of their physical properties. To do this, we rely on spectral energy distribution (SED) models, which allow us to infer physical parameters from spectrophotometric data. In recent years, thanks to wide and deep multiwave band galaxy surveys, the volume of high-quality data have significantly increased. Alongside the increased data, algorithms performing SED fitting have improved, including better modeling prescriptions, newer templates, and more extensive sampling in wavelength space. We present a comprehensive analysis of different SED-fitting codes including their methods and output with the aim of measuring the uncertainties caused by the modeling assumptions. We apply 14 of the most commonly used SED-fitting codes on samples from the CANDELS photometric catalogs at z ∼ 1 and z ∼ 3. We find agreement on the stellar mass, while we observe some discrepancies in the star formation rate (SFR) and dust-attenuation results. To explore the differences and biases among the codes, we explore the impact of the various modeling assumptions as they are set in the codes (e.g., star formation histories, nebular, dust and active galactic nucleus models) on the derived stellar masses, SFRs, and A V values. We then assess the difference among the codes on the SFR–stellar mass relation and we measure the contribution to the uncertainties by the modeling choices (i.e., the modeling uncertainties) in stellar mass (∼0.1 dex), SFR (∼0.3 dex), and dust attenuation (∼0.3 mag). Finally, we present some resources summarizing best practices in SED fitting.

Dust polarization spectral dependence from Planck HFI data

The search for the primordial B-modes of the cosmic microwave background (CMB) relies on the separation from the brighter foreground dust signal. In this context, the characterization of the spectral energy distribution (SED) of thermal dust in polarization has become a critical subject of study. We present a power-spectra analysis of Planck data, which improves upon previous studies by using the newly released SRoll2 maps that include corrections on residual data systematics and by extending the analysis to regions near the Galactic plane. Our analysis focuses on the lowest multipoles between ℓ = 4 and 32, as well as three sky areas with sky fractions of fsky = 80%, 90%, and 97%. The mean dust SED for polarization and the 353 GHz Q and U maps are used to compute residual maps at 100, 143, and 217 GHz, highlighting variations of the dust polarization SED on the sky and along the line of sight. Residuals are detected at the three frequencies for the three sky areas. We show that models based on total-intensity data end up underestimating (by a significant factor) the complexity of dust polarized CMB foreground. Our analysis emphasizes the need to include variations of the polarization angles of the dust polarized CMB foreground. The frequency dependence of the EE and BB power spectra of the residual maps yields further insight. We find that the moments expansion to the first order of the modified black-body (MBB) spectrum provides a good fit to the EE power-spectra. This result suggests that the residuals could follow mainly from variations of the dust MBB spectral parameters. However, this conclusion is challenged by cross-spectra showing that the residuals maps at the three frequencies are not fully correlated, as well as the fact that the BB power-spectra do not match the first order moment expansion of a MBB SED. This work sets new requirements for simulations of the dust-polarized foreground and component separation methods, showing that a significant refinement to the dust modeling is necessary to ensure an unbiased detection of the CMB primordial B-modes at the precision required by future CMB experiments. Further works would also be required to theoretically model the impact of polarization-angle variations on the EE and BB power spectra of residual maps.

Modeling Solar Orbiter dust detection rates in the inner heliosphere as a Poisson process

Context.Solar Orbiter provides dust detection capability in the inner heliosphere, but estimating physical properties of detected dust from the collected data is far from straightforward.Aims.First, a physical model for dust collection considering a Poisson process is formulated. Second, it is shown that dust on hyperbolic orbits is responsible for the majority of dust detections with Solar Orbiter’s Radio and Plasma Waves (RPW). Third, the model for dust counts is fitted to Solar Orbiter RPW data and parameters of the dust are inferred, namely radial velocity, hyperbolic meteoroids predominance, and the solar radiation pressure to gravity ratio as well as the uncertainties of these.Methods.Nonparametric model fitting was used to get the difference between the inbound and outbound detection rate and dust radial velocity was thus estimated. A hierarchical Bayesian model was formulated and applied to available Solar Orbiter RPW data. The model uses the methodology of integrated nested Laplace approximation, estimating parameters of dust and their ncertainties.Results.Solar Orbiter RPW dust observations can be modeled as a Poisson process in a Bayesian framework and observations up to this date are consistent with the hyperbolic dust model with an additional background component. Analysis suggests a radial velocity of the hyperbolic component around (63 ± 7) km s−1with the predominance of hyperbolic dust being about (78 ± 4)%. The results are consistent with hyperbolic meteoroids originating between 0.02 AU and 0.1 AU and showing substantial deceleration, which implies effective solar radiation pressure to a gravity ratio ≳ 0.5. The flux of the hyperbolic component at 1 AU is found to be (1.1 ± 0.2) × 10−4m−2s−1and the flux of the background component at 1 AU is found to be (5.4 ± 1.5) × 10−5m−2s−1.

Dark dust

Distance estimates derived from spectroscopy or parallax have been unified by considering extinction by large grains. The addition of such a population of what is called dark dust to models of the diffuse interstellar medium is tested against a contemporary set of observational constraints. By respecting representative solid-phase element abundances, the dark dust model simultaneously explains the typical wavelength-dependent reddening, extinction, and emission of polarised and unpolarised light by interstellar dust particles between far-UV and millimeter wavelengths. The physical properties of dark dust were derived. Dark dust consists of micrometer-sized particles. These particles have recently been detected in situ. Dark dust provides significant wavelength-independent reddening from the far-UV to the near-infrared. Light absorbed by dark dust is re-emitted in the submillimeter region by grains at dust temperatures of 8–12 K. This very cold dust has frequently been observed in external galaxies. Dark dust contributes to the polarisation at ≳1 mm to ~35% and marginally at shorter wavelengths. Optical constants for silicate dust analogous were investigated. By mixing 3% in mass of Mg0.8Fe0.22+ SiO3 to MgO−0.5 SiO2, a good fit to the data was derived that can still accommodate up to 5–10% of mass in dark dust. The additional diming of light by dark dust is unexplored when supernova Ia light curves are discussed and in other research. Previous models that ignored dark dust do not account for the unification of the distance scales.

The thesan project: ionizing escape fractions of reionization-era galaxies

Abstract A fundamental requirement for reionizing the Universe is that a sufficient fraction of the ionizing photons emitted by galaxies successfully escapes into the intergalactic medium. However, due to the scarcity of high-redshift observational data, the sources driving reionization remain uncertain. In this work, we calculate the ionizing escape fractions (fesc) of reionization-era galaxies from the state-of-the-art thesan simulations, which combine an accurate radiation-hydrodynamic solver (arepo-rt) with the well-tested IllustrisTNG galaxy formation model to self-consistently simulate both small-scale galaxy physics and large-scale reionization throughout a large patch of the universe ($L_\text{box} = 95.5\, \text{cMpc}$). This allows the formation of numerous massive haloes ($M_\text{halo} \gtrsim 10^{10}\, {\text{M}_{\odot }}$), which are often statistically underrepresented in previous studies but are believed to be important to achieving rapid reionization. We find that low-mass galaxies ($M_\text{stars} \lesssim 10^7\, {\text{M}_{\odot }}$) are the main drivers of reionization above z ≳ 7, while high-mass galaxies ($M_\text{stars} \gtrsim 10^8\, {\text{M}_{\odot }}$) dominate the escaped ionizing photon budget at lower redshifts. We find a strong dependence of fesc on the effective star formation rate (SFR) surface density defined as the SFR per gas mass per escape area, i.e. $\bar{\Sigma }_\text{SFR} = \text{SFR}/M_\text{gas}/R_{200}^2$. The variation in halo escape fractions decreases for higher mass haloes, which can be understood from the more settled galactic structure, SFR stability, and fraction of sightlines within each halo significantly contributing to the escaped flux. Dust is capable of reducing the escape fractions of massive galaxies, but the impact on the global fesc depends on the dust model. Finally, active galactic nuclei are unimportant for reionization in thesan and their escape fractions are lower than stellar ones due to being located near the centres of galaxy gravitational potential wells.

A foreground model-independent Bayesian CMB temperature and polarization signal reconstruction and cosmological parameter estimation over large angular scales

ABSTRACT Recent CMB observations have resulted in very precise observational data. A robust and reliable CMB reconstruction technique can lead to efficient estimation of the cosmological parameters. We demonstrate the performance of our methodology using simulated temperature and polarization observations using cosmic variance-limited future-generation PRISM satellite mission. We generate samples from the joint distribution by implementing the CMB inverse covariance weighted internal-linear-combination (ILC) with the Gibbs sampling technique. We use the Python Sky Model (PySM), d4f1s1 to generate the realistic foreground templates. The synchrotron emission is parametrized by a spatially varying spectral index, whereas the thermal dust emission is described as a two-component dust model. We estimate the marginalized densities of CMB signal and theoretical angular power spectrum utilizing the samples from the entire posterior distribution. The best-fitting cleaned CMB map and the corresponding angular power spectrum are consistent with the CMB realization and the sky angular power spectrum, implying an efficient foreground-minimized reconstruction. The likelihood function estimated by making use of the Blackwell–Rao estimator is used for the estimation of cosmological parameters. Our methodology can estimate the tensor-to-scalar ratio r ≥ 0.0075 for the chosen foreground models and the instrumental noise levels. Our current work demonstrates an analysis pipeline starting from the reliable estimation of CMB signal and its angular power spectrum to the case of cosmological parameter estimation using the foreground model-independent Gibbs–ILC method.

(Sub)millimetre dust polarization of protoplanetary discs from scattering by large millimetre-sized irregular grains

ABSTRACT The size of dust grains, a, is key to the physical and chemical processes in circumstellar discs, but observational constraints of grain size remain challenging. (Sub)millimetre continuum observations often show a per cent-level polarization parallel to the disc minor axis, which is generally attributed to scattering by ${\sim}100\, \mu{\rm m}$-sized spherical grains (with a size parameter x ≡ 2$\pi$a/λ < 1, where λ is the wavelength). Larger spherical grains (with x greater than unity) would produce opposite polarization direction. However, the inferred size is in tension with the opacity index β that points to larger mm/cm-sized grains. We investigate the scattering-produced polarization by large irregular grains with a range of x greater than unity with optical properties obtained from laboratory experiments. Using the radiation transfer code, RADMC-3D, we find that large irregular grains still produce polarization parallel to the disc minor axis. If the original forsterite refractive index in the optical is adopted, then all samples can produce the typically observed level of polarization. Accounting for the more commonly adopted refractive index using the DSHARP dust model, only grains with x of several (corresponding to ∼mm-sized grains) can reach the same polarization level. Our results suggest that grains in discs can have sizes in the millimetre regime, which may alleviate the tension between the grain sizes inferred from scattering and other means. Additionally, if large irregular grains are not settled to the mid-plane, their strong forward scattering can produce asymmetries between the near and far side of an inclined disc, which can be used to infer their presence.

Impact of dry deposition flux and dust intrusion phenomena on elemental concentrations of air particulate matter

Depositions of trace elements of air particulates in the atmosphere have gained much attention in recent times due to their environmental, climatic and health impacts. In the current study, trace elements of size-segregated rural and urban particulate matter (PM2.5 and PM2.5−10) were characterized using particle-induced X-ray emission method. Effects of dry deposition flux and Saharan dust intrusion on the elemental concentrations were determined. The mean elemental concentration in the rural fine PM ranged between 0.0002 ± 0.0002 μg m−3 (for Se) and 0.6658 ± 0.5816 μg m−3 (for S) whereas in the urban fine PM the concentration ranged between 0.0007 ± 0.0008 μg m−3 (for As) and 0.5869 ± 0.3429 μg m−3 (for Ca). In the coarse PM fraction, concentration ranged between 0.0001 ± 0.0001 μg m−3 (for Se) and 0.5886 ± 0.5343 μg m−3 (for Ca) at the rural site; and between 0.0002 ± 0.0002 μg m−3 (for Se) and 1.9201 ± 1.911 μg m−3 (for Ca) at the urban site. Mainly crustal elements (Al, Ca, Fe) and ‘pollution’ source element (S) recorded high and significant dry deposition fluxes across the two sites in both PM modes. Deposition flux was relatively higher in the coarse than in the fine PM mode. The average dry deposition flux estimated for fine and coarse PM at the rural and urban sites were 33.68 ± 57.19 μg m−2 day−1 and 47.71 ± 92.19 μg m−2 day−1; 36.66 ± 61.95 μg m−2 day−1 and 107.02 ± 237.71 μg m−2 day−1, respectively. Mainly crustal (Al, Ca, Fe) and “pollution” (S) element recorded high and significant dry deposition fluxes across the two sites and in the two PM modes. The impacts of dust on climate, air quality, and the environment in general have increased the need to better understand the dust flow system. In the current study, dust intruding the study area from the Sahara was analyzed using the NMMB/BSC dust model. The model’s output indicated that, the highest daily surface dust concentration was observed in the central and south-west of Turkey which corresponded with the peak period of Saharan dust transport to the Eastern Mediterranean in the month of March.

Predictive modeling of indoor dust lead concentrations: Sources, risks, and benefits of intervention

Lead (Pb) contamination continues to contribute to world-wide morbidity in all countries, particularly low- and middle-income countries. Despite its continued widespread adverse effects on global populations, particularly children, accurate prediction of elevated household dust Pb and the potential implications of simple, low-cost household interventions at national and global scales have been lacking. A global dataset (∼40 countries, n = 1951) of community sourced household dust samples were used to predict whether indoor dust was elevated in Pb, expanding on recent work in the United States (U.S.). Binned housing age category alone was a significant (p < 0.01) predictor of elevated dust Pb, but only generated effective predictive accuracy for England and Australia (sensitivity of ∼80%), similar to previous results in the U.S. This likely reflects comparable Pb pollution legacies between these three countries, particularly with residential Pb paint. The heterogeneity associated with Pb pollution at a global scale complicates the predictive accuracy of our model, which is lower for countries outside England, the U.S., and Australia. This is likely due to differing environmental Pb regulations, sources, and the paucity of dust samples available outside of these three countries. In England, the U.S., and Australia, simple, low-cost household intervention strategies such as vacuuming and wet mopping could conservatively save 70 billion USD within a four-year period based on our model. Globally, up to 1.68 trillion USD could be saved with improved predictive modeling and primary intervention to reduce harmful exposure to Pb dust sources.

Formation of a Stable Co-Amorphous System for a Brick Dust Molecule by Utilizing Sodium Taurocholate with High Glass Transition Temperature.

Brick dust molecules are usually poorly soluble in water and lipoidal components, making it difficult to formulate them in dosage forms that provide efficient pharmacological effects. A co-amorphous system is an effective strategy to resolve these issues. However, their glass transition temperatures (Tg) are relatively lower than those of polymeric amorphous solid dispersions, suggesting the instability of the co-amorphous system. This study aimed to formulate a stable co-amorphous system for brick dust molecules by utilizing sodium taurocholate (NaTC) with a higher Tg. A novel neuropeptide Y5 receptor antagonist (AntiY5R) and NaTC with Tg of 155 °C were used as the brick dust model and coformer, respectively. Ball milling formed a co-amorphous system for AntiY5R and NaTC (AntiY5R-NaTC) at various molar ratios. Deviation from the theoretical Tg value and peak shifts in Fourier-transform infrared spectroscopy indicated intermolecular interactions between AntiY5R and NaTC. AntiY5R-NaTC at equal molar ratios resulting in an 8.5-fold increase in AntiY5R solubility over its crystalline form. The co-amorphous system remained amorphous for 1 month at 25 °C and 40 °C. These results suggest that the co-amorphous system formed by utilizing NaTC as a coformer could stably maintain the amorphous state and enhance the solubility of brick dust molecules.

Concerning colour: The effect of environment on type Ia supernova colour in the dark energy survey

ABSTRACT Recent analyses have found intriguing correlations between the colour (c) of type Ia supernovae (SNe Ia) and the size of their ‘mass-step’, the relationship between SN Ia host galaxy stellar mass (Mstellar) and SN Ia Hubble residual, and suggest that the cause of this relationship is dust. Using 675 photometrically classified SNe Ia from the Dark Energy Survey 5-yr sample, we study the differences in Hubble residual for a variety of global host galaxy and local environmental properties for SN Ia subsamples split by their colour. We find a 3σ difference in the mass-step when comparing blue (c &amp;lt; 0) and red (c &amp;gt; 0) SNe. We observe the lowest r.m.s. scatter (∼0.14 mag) in the Hubble residual for blue SNe in low mass/blue environments, suggesting that this is the most homogeneous sample for cosmological analyses. By fitting for c-dependent relationships between Hubble residuals and Mstellar, approximating existing dust models, we remove the mass-step from the data and find tentative ∼2σ residual steps in rest-frame galaxy U − R colour. This indicates that dust modelling based on Mstellar may not fully explain the remaining dispersion in SN Ia luminosity. Instead, accounting for a c-dependent relationship between Hubble residuals and global U − R, results in ≤1σ residual steps in Mstellar and local U − R, suggesting that U − R provides different information about the environment of SNe Ia compared to Mstellar, and motivating the inclusion of galaxy U − R colour in SN Ia distance bias correction.

Numerical Modeling of Dust Deposition Rate on Ground-Mounted Solar Photovoltaic Panels

Abstract Despite the growth in the global cumulative installed photovoltaic (PV) capacity, the efficiency of PV panels is greatly reduced due to dust accumulation and soiling. To enhance this efficiency, consideration must be given to the factors that affect dust deposition ranging from panel configuration to weather conditions. This research aims to determine which of those factors contribute significantly to dust accumulation and model this behavior. Numerical experiments were performed to study those factors based on a planned Design of Experiments (DOE). Dust particle size, dust amount, wind speed, wind direction, and the solar panel tilt angle are the five factors examined using computational fluid dynamics (CFD) simulations. Statistical and regression analyses were then used to determine the most significant factors and model their effect on the deposition rate. Results revealed that the dust diameter, panel tilt angle, and wind speed influence the deposition rate the most. Dust diameter is positively correlated to the dust deposition rate. Larger dust particles have a lower deposition rate as the wind velocity increases. In addition, smaller dust particles will always give the lowest dust deposition rate irrespective of the tilt angle. It was also seen that the maximum dust deposition rate occurs at a panel’s tilt angle of approximately 50 deg regardless of the wind speed or the dust particle size. The developed mathematical model shows the factors contributing to soiling and panel efficiency reduction over exposure time. This model can be used further to optimize panel cleaning frequency.

The radial profile of dust grain size in the protoplanetary disc of DS Tau

ABSTRACT How do dust grains in protoplanetary discs overcome rapid radial drift and grow from micron size particles to planets is not well understood. The key is to search for evidence of dust accumulation and growth as a function of radius in the disc. We investigate the radial profile of grain size in the DS Tau disc by fitting multiband ALMA observations with self-consistent radiative transfer models. The best-fit grain sizes range from centimeters in the inner disc down to ${\sim }\, 30\, \mu {\rm m}$ in the outer regions. Such an inside-out decreasing tendency is consistent with theories of dust evolution. Based on the best-fit model, we find that dust of ${\sim }\, 2$ Jupiter masses has been depleted within the gap. By taking the gas-to-dust mass ratio into account, the lost mass is enough to form the 3.5 Jupiter mass planet inferred by literature hydrodynamic simulations. Moreover, our modelling also indicates that at the interface region between the gap and the ring, the grain size profile shows a discontinuity, with its amplitude dependent on the dust model adopted in the radiative transfer analysis. Future multiwavelength observations at higher angular resolutions are required to better constrain the grain size and its variation in the vicinity of disc substructures.

Underestimation of the dust mass in protoplanetary disks: Effects of disk structure and dust properties

The total number of dust grains in protoplanetary disks is one of the key properties that characterizes the potential for planet formation. With (sub-)millimeter flux measurements, literature studies usually derive the dust mass using an analytic formula under the assumption of optically thin emission, which may lead to a substantial underestimation. In this work, we conduct a parameter study with the goal of investigating the effects of disk structure and dust properties on the underestimation through self-consistent radiative transfer models. Different dust models, scattering modes, and approaches for dust settling are considered and compared. The influences of disk substructures, such as rings and crescents, on the mass derivation are investigated as well. The results indicate that the traditional analytic method can underestimate the mass by a factor of a few to several hundreds, depending on the optical depth along the line of sight set mainly by the true dust mass, disk size, and inclination. As an application, we performed a detailed radiative transfer modeling of the spectral energy distribution of DoAr 33, one of the disks observed by the Disk Substructures at High Angular Resolution Project (DSHARP). When the DSHARP dust opacities are adopted, the most probable dust mass returned from the Bayesian analysis is roughly seven times higher than the value given by the analytic calculation. Our study demonstrates that estimating disk dust masses from radiative transfer modeling is one solution to alleviate the problem of insufficient mass for planet formation that was raised in the era of the Atacama Large Millimeter/submillimeter Array.

Spitzer/IRS Full Spectral Modeling to Characterize Mineralogical Properties of Silicate Dust in Heavily Obscured AGNs

Mid-infrared silicate dust bands observed in heavily obscured active galactic nuclei (AGNs) include information on the mineralogical properties of silicate dust. We aim to investigate the mineralogical picture of the circumnuclear region of heavily obscured AGNs to reveal obscured AGN activities through the picture. In our previous study, we investigated the properties of silicate dust in heavily obscured AGNs, focusing on the mineralogical composition and the crystallinity with Spitzer/IRS 5.3–12 μm spectra. In this study, we model the full-range Spitzer/IRS 5–30 μm spectra of 98 heavily obscured AGNs using a one-dimensional radiative transfer calculation with four dust species in order to evaluate wider ranges of the properties of silicate dust more reliably. Comparing fitting results between four dust models with different sizes and porosities, 95 out of the 98 galaxies prefer a porous silicate dust model without micron-sized large grains. The pyroxene mass fraction and the crystallinity are overall consistent with—but significantly different from—the previous results for the individual galaxies. The pyroxene-poor composition, small dust size, and high porosity are similar to newly formed dust around mass-loss stars as seen in our Galaxy, which presumably originates from the recent circumnuclear starburst activity. The high crystallinity on average suggests dust processing induced by AGN activities.

Testing the Retrieval of Inner Disk Water Enrichment with Spitzer/IRS and JWST/MIRI

Planet formation by pebble accretion requires an efficient inward flux of icy pebbles to explain the many mini-Neptunes and super-Earths discovered by Kepler within 1 au. Recently, hints of large-scale pebble migration have been found in the anticorrelation between the line ratio of water-to-other volatiles detected in medium-resolution (R ∼ 700) Spitzer/IRS spectra and the dust disk radius measured at millimeter wavelengths with the Atacama Large Millimeter Array. Here, we select three disks in Taurus that span the range of measured line flux ratios (a factor of ∼5) and dust disk radii (1 order of magnitude) and model their Spitzer/IRS spectra assuming gas in local thermodynamic equilibrium to retrieve the water column density in their inner disks. We find that, at the Spitzer/IRS resolution and sensitivity, large uncertainties in the retrieved column densities preclude resolving the expected difference of a factor of ∼5 in water abundance. Next, we simulate higher-resolution (∼3000) JWST/MIRI spectra at the signal-to-noise ratio of ∼100, which will be obtained via the Guaranteed Time and General Observation programs and apply the same retrieval approach used with Spitzer/IRS spectra. We show that the improved resolution and sensitivity of JWST/MIRI significantly reduce the uncertainties in the retrieved water column densities and will enable quantifying the difference in the inner water column of small versus large dust disks.

The simulation of mineral dust in the United Kingdom Earth System Model UKESM1

Abstract. Mineral dust plays an important role in Earth system models and is linked to many components, including atmospheric wind speed, precipitation and radiation, surface vegetation cover and soil properties and oceanic biogeochemical systems. In this paper, the dust scheme in the first configuration of the United Kingdom Earth System Model UKESM1 is described, and simulations of dust and its radiative effects are presented and compared with results from the parallel coupled atmosphere–ocean general circulation model (GCM) HadGEM3-GC3.1. Not only changes in the driving model fields but also changes in the dust size distribution are shown to lead to considerable differences to the present-day dust simulations and to projected future changes. UKESM1 simulations produce a present-day, top-of-the-atmosphere (ToA) dust direct radiative effect (DRE – defined as the change in downward net flux directly due to the presence of dust) of 0.086 W m−2 from a dust load of 19.5 Tg. Under climate change pathways these values decrease considerably. In the 2081–2100 mean of the Shared Socioeconomic Pathway SSP5–8.45 ToA DRE reaches 0.048 W m−2 from a load of 15.1 Tg. In contrast, in HadGEM3-GC3.1 the present-day values of −0.296 W m−2 and 15.0 Tg are almost unchanged at −0.289 W m−2 and 14.5 Tg in the 2081–2100 mean. The primary mechanism causing the differences in future dust projections is shown to be the vegetation response, which dominates over the direct effects of warming in our models. Though there are considerable uncertainties associated with any such estimates, the results presented demonstrate both the importance of the size distribution for dust modelling and also the necessity of including Earth system processes such as interactive vegetation in dust simulations for climate change studies.