Dust Emission Model Research Articles

Filamentary Molecular Cloud Formation via Collision-induced Magnetic Reconnection in a Cold Neutral Medium

We have investigated the possibility of molecular cloud formation via the collision-induced magnetic reconnection (CMR) mechanism of the cold neutral medium (CNM). Two atomic gas clouds with conditions typical of the CNM were set to collide at the interface of reverse magnetic fields. The cloud–cloud collision triggered magnetic reconnection and produced a giant 20 pc filamentary structure that was not seen in the control models without CMR. The cloud, with rich fiber-like substructures, developed a fully molecular spine at 5 Myr. Radiative transfer modeling of dust emission at far-infrared wavelengths showed that the middle part of the filament contained dense cores over a span of 5 pc. Some of the cores were actively forming stars and typically exhibited both connecting fibers in dust emission and high-velocity gas in CO line emission, indicative of active accretion through streamers. Supersonic turbulence was present in and around the CMR filament due to inflowing gas moving at supersonic velocities in the collision midplane. The shocked gas was condensed and transported to the main filament piece by piece by reconnected fields, making the filament and star formation a bottom-up process. Instead of forming a gravitationally bounded cloud that then fragments hierarchically (top-down) and forms stars, the CMR process creates dense gas pieces and magnetically transports them to the central axis to constitute the filament. Since no turbulence is manually driven, our results suggest that CMR is capable of self-generating turbulence. Finally, the resulting helical field should show field reversal on both sides of the filament from most viewing angles.

Spatial Source Contribution and Interannual Variation in Deposition of Dust Aerosols Over the Chinese Loess Plateau

AbstractThe Chinese Loess Plateau (CLP) in northern China is home to one of the most prominent loess records in the world, reflecting past eolian dust activity in East Asia. However, their interpretation is hampered by ambiguity in the origin of loess‐forming dust and an incomplete understanding of the circulation forcing dust accumulation. In this study, we used a novel modeling approach combining a dust emission model FLEXDUST with simulated back trajectories from FLEXPART to trace the dust back to where it was emitted. Over 21 years (1999–2019), we modeled back trajectories for fine (∼2 μm) and super‐coarse (∼20 μm) dust particles at six CLP sites during the peak dust storm season from March to May. FLEXPART source‐receptor relationships are combined with the dust emission inventory from FLEXDUST to create site‐dependent high‐resolution maps of the source contribution of deposited dust. The nearby dust emission areas were found to be the main source of dust to the CLP. Dust deposition across the CLP was found to predominantly occur via wet removal, with also some super‐coarse dust from distant emission regions being wet deposited following high‐level tropospheric transport. The high topography located on the downwind side of the emission area plays an essential role in forcing the emitted super‐coarse dust upward. On an interannual scale, the phase of the Arctic Oscillation in the preceding winter was found to have a strong association with the spring deposition rate on the CLP, while the strength of the East Asian Winter Monsoon was less influential.

Assessing the Cosmic Infrared Background Monopole from Far-infrared to Millimeter Wavelengths

We measured the cosmic infrared background (CIB) monopole for the COBE Diffuse Infrared Background Experiment (DIRBE) and Planck High-Frequency Instrument (HFI) bands with an updated model for the Galactic dust emission. This model includes a dust excess recently observed in 25% of the sky mainly at high latitude compared to the prediction from N H I. We correlated observations from COBE/DIRBE and Planck-HFI with this model to extract the zero levels of the sky maps. We corrected for the isotropic interplanetary dust (IPD) emission and calibration gains and obtained CIB values of 1.4 ± 8.0, 24.5 ± 3.9, 15.4 ± 4.9, 6.8 ± 2.0, 3.2 ± 0.3, 1.5 ± 0.1, 0.40 ± 0.05, 0.11 ± 0.04, 0.014 ± 0.027, and 0.008 ± 0.012 nW m−2 sr−1 at 60, 100, 140, and 240 μm, and 857, 545, 353, 217, 143, and 100 GHz. We compared those numbers with previous direct CIB measurements and extragalactic source counts. We obtain CIB values lower than previous measurements for wavelengths above 140 μm. Below this value, the large uncertainty related to the IPD emission prevents a clear interpretation.

The ALMA-QUARKS Survey. II. The ACA 1.3 mm Continuum Source Catalog and the Assembly of Dense Gas in Massive Star-Forming Clumps

Leveraging the high resolution, sensitivity, and wide frequency coverage of the Atacama Large Millimeter/submillimeter Array (ALMA), the QUARKS survey, standing for “Querying Underlying mechanisms of massive star formation with ALMA-Resolved gas Kinematics and Structures”, is observing 139 massive star-forming clumps at ALMA Band 6 (λ ∼ 1.3 mm). This paper introduces the Atacama Compact Array (ACA) 7 m data of the QUARKS survey, describing the ACA observations and data reduction. Combining multi-wavelength data, we provide the first edition of QUARKS atlas, offering insights into the multiscale and multiphase interstellar medium in high-mass star formation. The ACA 1.3 mm catalog includes 207 continuum sources that are called ACA sources. Their gas kinetic temperatures are estimated using three formaldehyde transitions with a non-LTE radiation transfer model, and the mass and density are derived from a dust emission model. The ACA sources are massive (16–84 percentile values of 6–160 M ⊙), gravity-dominated (M ∝ R 1.1) fragments within massive clumps, with supersonic turbulence ( M>1 ) and embedded star-forming protoclusters. We find a linear correlation between the masses of the fragments and the massive clumps, with a ratio of 6% between the two. When considering fragments as representative of dense gas, the ratio indicates a dense gas fraction (DGF) of 6%, although with a wide scatter ranging from 1% to 10%. If we consider the QUARKS massive clumps to be what is observed at various scales, then the size-independent DGF indicates a self-similar fragmentation or collapsing mode in protocluster formation. With the ACA data over four orders of magnitude of luminosity-to-mass ratio (L/M), we find that the DGF increases significantly with L/M, which indicates clump evolutionary stage. We observed a limited fragmentation at the subclump scale, which can be explained by a dynamic global collapse process.

THEMIS 2.0: A self-consistent model for dust extinction, emission, and polarisation

Context. Recent observational constraints in emission, extinction, and polarisation have at least partially invalidated most of the astronomical standard grain models for the diffuse interstellar medium. Moreover, laboratory measurements on interstellar silicate analogues have shown quite significant differences with the optical properties used in these standard models. Aims. To address these issues, our objective is twofold: (i) to update the optical properties of silicates and (ii) to develop The Heterogeneous dust Evolution Model for Interstellar Solids (THEMIS) to allow the calculation of polarised extinction and emission. Methods. Based on optical constants measured in the laboratory from 5 µm to 1 mm for amorphous silicates and on observational constraints in mid-IR extinction and X-ray scattering, we defined new optical constants for the THEMIS silicates. Absorption and scattering efficiencies for spheroidal grains using these properties were subsequently derived with the discrete dipole approximation. Results. These new optical properties make it possible to explain the dust emission and extinction, both total and polarised. It is noteworthy that the model is not yet pushed to its limits since it does not require the perfect alignment of all grains to explain the observations and it therefore has the potential to accommodate the highest polarisation levels inferred from extinction measurements. Moreover, the dispersion of the optical properties of the different silicates measured in the laboratory naturally explain the variations in both the total and polarised emission and extinction observed in the diffuse interstellar medium. Conclusions. A single, invariant model calibrated on one single set of observations is obsolete for explaining contemporary observations. We are proposing a completely flexible dust model based entirely on laboratory measurements that has the potential to make major advances in understanding the exact nature of interstellar grains and how they evolve as a function of their radiative and dynamic environment. Even if challenging, this is also relevant for future cosmic microwave background (CMB) missions that will aim to perform precise measurements of the CMB spectral distortions and polarisation.

Reducing Resolution Dependency of Dust Emission Modeling Using Albedo‐Based Wind Friction

AbstractNumerical simulations of dust emission processes are essential for dust cycle modeling and dust‐atmosphere interactions. Models have coarse spatial resolutions which, without tackling sub‐grid scale heterogeneity, bias finely resolved dust emission. Soil surface wind friction velocity (us*) drives dust emission non‐linearly with increasing model resolution, due mainly to thresholds of sediment entrainment. Albedo is area‐integrated, scales linearly with resolution, is related to us* and hence represents its sub‐grid scale heterogeneity. Calibrated albedo‐based global dust emission estimates decreased by only 2 Tg y−1 (10.5%) upscaled from 0.5 to 111 km, largely independent of resolution. Without adjusting wind fields, this scaling uncertainty is within recent estimates of global dust emission model uncertainty (±14.9 Tg y−1). This intrinsic scaling capability of the albedo‐based approach offers considerable potential to reduce resolution dependency of dust cycle modeling and improve the representation of local dust emission in Earth system models and operational air quality forecasting.

Impact of discontinuous grain size distributions on the spectral energy distribution of debris disks

Context. The collisional evolution of debris disks is expected to cause the characteristic wavy pattern, that is, an under- or overabundance of particles of specific sizes, of grain size distributions. This perturbed grain size distribution potentially leaves characteristic patterns in the spectral energy distribution (SED) of the disk system. Aims. We aim to quantify and understand the specific influence of discontinuous particle size distributions on the appearance of debris disks. For this purpose, we considered dust emission models based on two different grain size distributions, namely, one with a single power law and one with a broken power law. In particular, our study is focused on the impact of an overabundance of small grains and an underabundance of medium-sized grains on the far-IR and (sub-)millimeter regime on the dust reemission radiation and the potential to constrain discontinuities in the grain size distribution from (sub-)millimeter photometric measurements of debris disks. Methods. We compared the spectral index α (Fν ∝ να) in the case of a continuous grain size distribution with that of a discontinuous grain size distribution. We performed this comparison for central stars with different spectral types and two different disk structures (e.g., slim and broad debris dust rings). Results. Within the considered parameter space, we found a characteristic difference between the spectral slopes of the SED in the different scenarios. In particular, the overabundance of small grains resulting from collisional events and thus parameters defining the outcome of disk events in debris disks is potentially observable by comparison with the SED corresponding to a grain size distribution resulting from an ideal collisional cascade. More specifically, the overabundance of small grains leads to a steeper slope in the far-IR and sub-millimeter regime, while the spectral index in the millimeter regime is hardly affected. On the other hand, the underabundance of medium-sized grains results in a slight steepening of the far-IR slope of the SED, but its primary effect is on the millimeter slope of the SED, causing it to become shallower. We also found that the impact of an overabundance of small dust particles is more pronounced than that of an underabundance of medium-sized dust particles. We also found that the difference between the spectral indices for the two different grain size distributions is largest for debris disks around brighter central stars and broader disks. However, the impact of the considered spatial distributions described by the fractional width of the disk system is weak. Our results also show that the dust composition is not the sole physical mechanism responsible for the spectral inversion observed in the far-IR to millimeter part of the SED of debris disk systems. Furthermore, the location of the spectral break is placed at different wavelength regimes if the grain size distribution is considered as a function of blowout size and stellar type.

A new framework for evaluating dust emission model development using dichotomous satellite observations of dust emission

Dust models are essential for understanding the impact of mineral dust on Earth's systems, human health, and global economies, but dust emission modelling has large uncertainties. Satellite observations of dust emission point sources (DPS) provide a valuable dichotomous inventory of regional dust emissions. We develop a framework for evaluating dust emission model performance using existing DPS data before routine calibration of dust models. To illustrate this framework's utility and arising insights, we evaluated the albedo-based dust emission model (AEM) with its areal (MODIS 500 m) estimates of soil surface wind friction velocity (us∗) and common, poorly constrained grain-scale entrainment threshold (u∗ts) adjusted by a function of soil moisture (H). The AEM simulations are reduced to its frequency of occurrence, P(us∗>u∗tsH). The spatio-temporal variability in observed dust emission frequency is described by the collation of nine existing DPS datasets. Observed dust emission occurs rarely, even in North Africa and the Middle East, where DPS frequency averages 1.8 %, (~7 days y−1), indicating extreme, large wind speed events. The AEM coincided with observed dust emission ~71.4 %, but simulated dust emission ~27.4 % when no dust emission was observed, while dust emission occurrence was over-estimated by up to 2 orders of magnitude. For estimates to match observations, results showed that grain-scale u∗ts needed restricted sediment supply and compatibility with areal us∗. Failure to predict dust emission during observed events, was due to us∗ being too small because reanalysis winds (ERA5-Land) were averaged across 11 km pixels, and inconsistent with us∗ across 0.5 km pixels representing local maxima. Assumed infinite sediment supply caused the AEM to simulate dust emission whenever P(us∗>u∗tsH), producing false positives when wind speeds were large. The dust emission model scales of existing parameterisations need harmonising and a new parameterisation for u∗ts is required to restrict sediment supply over space and time.

Assessment and optimization of co-firing power plant in Thailand: Seasonal effects and dust emission concerns

In this work, the industrial-scale co-fired power plant in Thailand was analyzed and the optimization model was proposed to provide a proper fuel selection for the feedstock seasonal planning to minimize the cost of electricity generation. Also, the dust emission model was introduced in this work to investigate the environmental concern of the proposed fuel formula. The seasonal effects including feed price, properties, and availability were also included in the optimization model. The optimum solution reported a set of fuel formulas for each season that is capable of maintaining power production stability and minimizing fuel costs. Although, the global demand for coal was at its peak in the winter season, using biomass (wood chip, wood bark, and fiber) could increase the production to achieve its minimum requirement. The optimization could reduce the cost of electricity (COE) production by up to 14% (in the winter season). Also, the emission model indicated that to increase the steam production rate to meet the requirement in the summer season, a larger amount of mixed fuel consumption rate was needed. This led to an increase in dust emissions in the summer season. However, in the winter season, the result from optimization could decrease dust emissions by up to 50%. In conclusion, increasing biomass utilization is a favorable option in both economic and environmental aspects.

Elucidating Hidden and Enduring Weaknesses in Dust Emission Modeling

AbstractLarge‐scale classical dust cycle models, developed more than two decades ago, assume for simplicity that the Earth's land surface is devoid of vegetation, reduce dust emission estimates using a vegetation cover complement, and calibrate estimates to observed atmospheric dust optical depth (DOD). Consequently, these models are expected to be valid for use with dust‐climate projections in Earth System Models. We reveal little spatial relation between DOD frequency and satellite observed dust emission from point sources (DPS) and a difference of up to 2 orders of magnitude. We compared DPS data to an exemplar traditional dust emission model (TEM) and the albedo‐based dust emission model (AEM) which represents aerodynamic roughness over space and time. Both models overestimated dust emission probability but showed strong spatial relations to DPS, suitable for calibration. Relative to the AEM calibrated to the DPS, the TEM overestimated large dust emission over vast vegetated areas and produced considerable false change in dust emission. It is difficult to avoid the conclusion that calibrating dust cycle models to DOD has hidden for more than two decades, these TEM modeling weaknesses. The AEM overcomes these weaknesses without using masks or vegetation cover data. Considerable potential therefore exists for ESMs driven by prognostic albedo, to reveal new insights of aerosol effects on, and responses to, contemporary and environmental change projections.

Wind tunnel simulation of wind erosion and dust emission processes, and the influences of soil texture

Dust emission caused by wind erosion of soil is an important surface process in arid and semi-arid regions. However, existing dust emission models pay insufficient attention to the impacts of aerodynamic entrainment of particles. In addition, studies of wind erosion processes do not adequately account for the dynamics of wind erosion rates and dust emission fluxes, or for the impact of soil texture on dust emission. Our wind tunnel simulations of wind erosion and dust emission showed that the soil texture, wind erosion duration, and shear velocity are major factors that affect the dynamics of wind erosion and dust emission. Because of the limited supply of surface sand and the change in surface erosion resistance caused by surface coarsening during erosion, the wind erosion rate and the flux of particles smaller than 10 μm (PM10) caused by aerodynamic entrainment decreased rapidly with increasing erosion duration, which suggests that surface wind erosion and dust emission occur primarily during the initial stage of wind erosion. The PM10 emission efficiency decreased with increasing shear velocity following a power function, and finer textured sandy loam soils had greater PM10 emission efficiency than loamy sand soils.

Variability and combination as an ensemble of mineral dust forecasts during the 2021 CADDIWA experiment using the WRF 3.7.1 and CHIMERE v2020r3 models

Abstract. As operational support to define the Clouds–Atmospheric Dynamics–Dust Interactions in West Africa (CADDIWA) field campaign which took place in the Cape Verde area, the coupled regional model WRF–CHIMERE is deployed in forecast mode during the summer 2021. The simulation domain covers West Africa and the eastern Atlantic and allows the modeling of dust emissions and their transport to the Atlantic. On this route, we find Cape Verde, which was used as a base for measurements during the CADDIWA campaign. Meteorological variables and mineral dust concentrations are forecasted on a horizontal grid with a 30 km resolution and from the surface to 200 hPa. For a given day D, simulations are initialized from D−1 analyses and run for 4 d until D+4, yielding up to six available simulations on a given day. For each day, we thus have six different calculations, with better precision expected the closer we get to the analysis (lead D−1). In this study, a quantification of the forecast variability of wind, temperature, precipitation and mineral dust concentrations according to the modeled lead is presented. It is shown that the forecast quality does not decrease with time, and the high variability observed on some days for some variables (wind, temperature) does not explain the behavior of other dependent and downwind variables (mineral dust concentrations). A new method is also tested to create an ensemble without perturbing input data, but considering six forecast leads available for each date as members of an ensemble forecast. It has been shown that this new forecast based on this ensemble is able to give better results for two AErosol RObotic NETwork (AERONET) stations than the four available for aerosol optical depth observations. This could open the door to further testing with more complex operational systems.

Elemental ratios as tracers of the sources of mineral dust in north-eastern Sahara

The objective of this study is to confirm the possibility of tracing sources of airborne mineral dust using elemental ratios. The region of study is the north-eastern part of the Sahara where dust compositional data were lacking; 272 mineral dust samples collected at 3 experimental stations of Egypt were analyzed by X-ray fluorescence. Based on the mineral dust concentration, 65% of the samples correspond to moderate (3–10 μg m−3), 22% to medium (10–25 μg m−3), and 13% to intense (> 25 μg m−3) dust events. The Ca/Al and (Mg + Ca)/Fe ratios were found to be strongly correlated and their ranges of variation to cover are more than one order of magnitude, which confirms their interest for the tracing of the dust sources. Using a combination of MODIS satellite observations, HYSPLIT back-trajectory analysis, and simulations with dust emission models, the large (> 6) and intermediate (2–6) Ca/Al ratios were shown to correspond to dust originating from saline playas (chotts) and calcareous surfaces, respectively. Conversely, the lowest (< 2) ratios correspond to dust emitted by siliceous sand seas (ergs). Therefore, a classification of the dust in 3 categories (erg-like, calcareous, and chott-like) based on Ca/Al is proposed. The events of moderate to medium intensity are dominated by chott-like and calcareous dust, which suggests that these sources are activated during erosion events of limited (local) extension. Conversely, the fact that the dust composition is more likely to be of the erg-like type during intense events underlines the dominant role played by sand dune fields during major erosion events.

BEYONDPLANCK

We constrained the level of polarized anomalous microwave emission (AME) on large angular scales usingPlanckLow-Frequency Instrument (LFI) and WMAP polarization data within a Bayesian cosmic microwave background (CMB) analysis framework. We modeled synchrotron emission with a power-law spectral energy distribution, as well as the sum of AME and thermal dust emission through linear regression with thePlanckHigh-Frequency Instrument (HFI) 353 GHz data. This template-based dust emission model allowed us to constrain the level of polarized AME while making minimal assumptions on its frequency dependence. We neglected CMB fluctuations, but show through simulations that these fluctuations have a minor impact on the results. We find that the resulting AME polarization fraction confidence limit is sensitive to the polarized synchrotron spectral index prior. In addition, for prior meansβs &lt; −3.1 we find an upper limit ofpAMEmax ≲ 0.6% (95% confidence). In contrast, for meansβs = −3.0, we find a nominal detection ofpAME = 2.5 ± 1.0% (95% confidence). These data are thus not strong enough to simultaneously and robustly constrain both polarized synchrotron emission and AME, and our main result is therefore a constraint on the AME polarization fraction explicitly as a function ofβs. Combining the currentPlanckand WMAP observations with measurements from high-sensitivity low-frequency experiments such as C-BASS and QUIJOTE will be critical to improve these limits further.

SN 2018gk Revisited: the Photosphere, the Central Engine, and the Putative Dust

We perform a comprehensive study of the physical properties of SN 2018gk, which is a luminous Type IIb supernova (SN). We find that the early-time photospheric velocity varies from a larger value to a smaller one before the photosphere reaches a temperature floor. We generalize the photosphere modulus and fit the multiband light curves (LCs) of SN 2018gk. We find that the 56Ni mass model requires ∼0.90 M ⊙ of 56Ni, which is larger than the derived ejecta mass (∼0.10 M ⊙). Alternatively, we use the magnetar plus 56Ni and the fallback plus 56Ni models to fit the LCs of SN 2018gk, finding that the two models can fit the LCs. We favor the magnetar plus 56Ni model since the parameters are rather reasonable (M ej = 1.65 M ⊙, M Ni = 0.05 M ⊙, which is smaller than the upper limit of the 56Ni mass that can by synthesized by neutrino-powered core-collapse SNe, B = 6.52 × 1014 G, which is comparable to magnetic fields in luminous and superluminous SNe studied in the literature, and P 0 = 10.42 ms, which is comparable to initial periods for luminous SNe), while the validity of the fallback plus 56Ni model depends on the accretion efficiency (η). Therefore, we suggest that SN 2018gk might be an SN IIb powered mainly by a central engine. Finally, we confirm the near-IR excesses of the spectral energy distributions of SN 2018gk at some epochs and constrain the physical properties of the putative dust using the blackbody plus dust emission model.

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.

Shadow is related to roughness but MODIS BRDF should not be used to estimate lateral cover

A simple geometric-optical model is used to show that shadow in optical remote sensing imagery contains information about surface roughness. The use of MODIS albedo products for the purpose of estimating surface roughness so that these products may aid in dust emission modeling has been proposed in previous studies (Chappell et al. 2010; Chappell and Webb 2016; Chappell et al. 2018). This approach is evaluated through geometric-optical modeling and by analysis of existing MODIS data. Little support is found for the utility of this approach for dust emission modeling. However, because there is clearly information about surface roughness in optical satellite imagery, some suggestions for the proper use of optical data to estimate surface roughness are made.Chappell, A., Van Pelt, S., Zobeck, T., & Dong, Z. (2010). Estimating aerodynamic resistance of rough surfaces using angular reflectance. Remote Sensing of Environment, 114, 1462–1470.Chappell, A., & Webb, N.P. (2016). Using albedo to reform wind erosion modeling, mapping and monitoring. Aeolian Research, 23, 63–78.Chappell, A., Webb, N.P., Guerschman, J.P., Thomas, D.T., Mata, G., Handcock, R.N., Leys, J.F., & Butler, H.J. (2018). Improving ground cover monitoring for wind erosion assessment using MODIS BRDF parameters. Remote Sensing of Environment, 204, 756–768.

Probing the Nature of the First Galaxies with JWST and ALMA

By implementing a model of primordial dust emission, we predict dust-continuum fluxes for massive galaxy sources similar to those recently detected by James Webb Space Telescope (JWST) at z ≳ 7. Current upper flux limits, obtained with Atacama Large Millimeter/submillimeter Array (ALMA) for some of these sources, can constrain the gas metallicity and dust fraction of the first galaxies. Encouragingly, if assuming expected properties for typical first galaxies (i.e., dust-to-metal mass ratio: D/M = 5 × 10−3, gas metallicity: Z g = 5 × 10−3 Z ☉, star formation efficiency: η = 0.01), model far-infrared (FIR) fluxes are consistent with current upper flux limits inferred from ALMA bands 6 and 7 (≲104 nJy). Such low D/M values and metallicities are in agreement with some scenarios proposed in the literature to explain the nondetection of the FIR dust continuum for high-z JWST galaxy candidates. On the other hand, higher values of model parameters D/M (≳0.06) and Z g (≳5 × 10−2 Z ☉) are ruled out by observational data, unless a higher η is assumed. According to our findings, ALMA multiband observations could constrain the dust chemistry and dust grain size distribution in the early universe. In this context, future observational challenges would involve not only reaching higher FIR sensitivities, but also increasing the wavelength coverage by exploring distinct ALMA bands.

Modelling the 2021 East Asia super dust storm using FLEXPART and FLEXDUST and its comparison with reanalyses and observations

The 2021 East Asia sandstorm began from the Eastern Gobi desert steppe in Mongolia on March 14, and later spread to northern China and the Korean Peninsula. It was the biggest sandstorm to hit China in a decade, causing severe air pollution and a significant threat to human health. Capturing and predicting such extreme events is critical for society. The Lagrangian particle dispersion model FLEXPART and the associated dust emission model FLEXDUST have been recently developed and applied to simulate global dust cycles. However, how well the model captures Asian dust storm events remains to be explored. In this study, we applied FLEXPART to simulate the recent 2021 East Asia sandstorm, and evaluated its performance comparing with observation and observation-constrained reanalysis datasets, such as the Modern-Era Retrospective analysis for Research and Applications, Version 2 (MERRA-2) and CAMS global atmospheric composition forecasts (CAMS-F). We found that the default setting of FLEXDUST substantially underestimates the strength of dust emission and FLEXPART modelled dust concentration in this storm compared to that in MERRA-2 and CAMS-F. An improvement of the parametrization of bare soil fraction, topographical scaling, threshold friction velocity and vertical dust flux scheme based on Kok et al. (Atmospheric Chemistry and Physics, 2014, 14, 13023–13041) in FLEXDUST can reproduce the strength and spatio-temporal pattern of the dust storm comparable to MERRA-2 and CAMS-F. However, it still underestimates the observed spike of dust concentration during the dust storm event over northern China, and requires further improvement in the future. The improved FLEXDUST and FLEXPART perform better than MERRA-2 and CAMS-F in capturing the observed particle size distribution of dust aerosols, highlighting the importance of using more dust size bins and size-dependent parameterization for dust emission, and dry and wet deposition schemes for modelling the Asian dust cycle and its climatic feedbacks.

Plant phenology drives seasonal changes in shear stress partitioning in a semi-arid rangeland

Accurate representation of surface roughness in predictive models of aeolian sediment transport and dust emission is required for model accuracy and for models to inform wind erosion management. While past wind tunnel and field studies have examined roughness effects on drag partitioning, the spatial and temporal variability of surface shear velocity and the shear stress ratio remain poorly described. Here, we use a four-month dataset of total shear velocity (u*) and soil surface shear velocity (us*) measurements to examine the spatiotemporal variability of the shear stress ratio (R) before, during, and after vegetation green-up at a honey mesquite (Prosopis glandulosa Torr.) shrub-invaded grassland in the Chihuahuan Desert, New Mexico, USA. Results show that vegetation green-up, the emergence of leaves, led to increased drag and surface aerodynamic sheltering and a reduction in us* and R magnitude and variability. We found that us* decreased from 20% to 5% of u* as the vegetation form drag and its sheltering effect increased. Similarly, the spatiotemporal variability of R was found to be linked directly to plant phenological phases. We conclude that drag partition schemes should incorporate seasonal vegetation change, via dynamic drag coefficients and/or R, to accurately predict the timing and magnitude of seasonal aeolian sediment fluxes. The drag partition response to mesquite phenological phases also provided insight to potential mesquite herbicide treatment effects which, if successful, could increase wind erosivity and the onsite and downwind impacts of wind erosion unless protection by herbaceous plants is maintained.